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Mining Engineering Graduate Theses and Dissertations

Theses/dissertations from 2023 2023.

Development of A Hydrometallurgical Process for the Extraction of Cobalt, Manganese, and Nickel from Acid Mine Drainage Treatment Byproduct , Alejandro Agudelo Mira

Selective Recovery of Rare Earth Elements from Acid Mine Drainage Treatment Byproduct , Zeynep Cicek

Identification of Rockmass Deformation and Lithological Changes in Underground Mines by Using Slam-Based Lidar Technology , Francisco Eduardo Gil Hurtado

Analysis of the Brittle Failure Mechanism of Underground Stone Mine Pillars by Implementing Numerical Modeling in FLAC3D , Rosbel Jimenez

Analysis of the root causes of fatal injuries in the United States surface mines between 2008 and 2021. , Maria Fernanda Quintero

AUGMENTED REALITY AND MOBILE SYSTEMS FOR HEAVY EQUIPMENT OPERATORS IN SURFACE MINING , Juan David Valencia Quiceno

Theses/Dissertations from 2022 2022

Integrated Large Discontinuity Factor, Lamodel and Stability Mapping Approach for Stone Mine Pillar Stability , Mustafa Baris Ates

Noise Exposure Trends Among Violating Coal Mines, 2000 to 2021 , Hanna Grace Davis

Calcite depression in bastnaesite-calcite flotation system using organic acids , Emmy Muhoza

Investigation of Geomechanical Behavior of Laminated Rock Mass Through Experimental and Numerical Approach , Qingwen Shi

Static Liquefaction in Tailing Dams , Jose Raul Zela Concha

Experimental and Theoretical Investigation on the Initiation Mechanism of Low-Rank Coal's Self-Heating Process , Yinan Zhang

Development of an Entry-Scale Modeling Methodology to Provide Ground Reaction Curves for Longwall Gateroad Support Evaluation , Haochen Zhao

Size effect and anisotropy on the strength of shale under compressive stress conditions , Yun Zhao

Theses/Dissertations from 2021 2021

Evaluation of LIDAR systems for rock mass discontinuity identification in underground stone mines from 3D point cloud data , Mario Alejandro Bendezu de la Cruz

Implementing the Empirical Stone Mine Pillar Strength Equation into the Boundary Element Method Software LaModel , Samuel Escobar

Recovery of Phosphorus from Florida Phosphatic Waste Clay , Amir Eskanlou

Optimization of Operating Conditions and Design Parameters on Coal Ultra-Fine Grinding Through Kinetic Stirred Mill Tests and Numerical Modeling , Francisco Patino

The Effect of Natural Fractures on the Mechanical Behavior of Limestone Pillars: A Synthetic Rock Mass Approach Application , Mustafa Can Süner

Evaluation of Various Separation Techniques for the Removal of Actinides from A Rare Earth-Containing Solution Generated from Coarse Coal Refuse , Deniz Talan

Geology Oriented Loading Approach for Underground Coal Mines , Deniz Tuncay

Various Operational Aspects of the Extraction of Critical Minerals from Acid Mine Drainage and Its Treatment By-product , Zhongqing Xiao

Theses/Dissertations from 2020 2020

Adaptation of Coal Mine Floor Rating (CMFR) to Eastern U.S. Coal Mines , Sena Cicek

Upstream Tailings Dam - Liquefaction , Mladen Dragic

Development, Analysis and Case Studies of Impact Resistant Steel Sets for Underground Roof Fall Rehabilitation , Dakota D. Faulkner

The influence of spatial variance on rock strength and mechanism of failure , Danqing Gao

Fundamental Studies on the Recovery of Rare Earth Elements from Acid Mine Drainage , Xue Huang

Rational drilling control parameters to reduce respirable dust during roof bolting operations , Hua Jiang

Solutions to Some Mine Subsidence Research Challenges , Jian Yang

An Interactive Mobile Equipment Task-Training with Virtual Reality , Lazar Zujovic

Theses/Dissertations from 2019 2019

Fundamental Mechanism of Time Dependent Failure in Shale , Neel Gupta

A Critical Assessment on the Resources and Extraction of Rare Earth Elements from Acid Mine Drainage , Christopher R. Vass

Time-dependent deformation and associated failure of roof in underground mines , Yuting Xue

Theses/Dissertations from 2018 2018

Parametric Study of Coal Liberation Behavior Using Silica Grinding Media , Adewale Wasiu Adeniji

Three-dimensional Numerical Modeling Encompassing the Stability of a Vertical Gas Well Subjected to Longwall Mining Operation - A Case Study , Bonaventura Alves Mangu Bali

Shale Characterization and Size-effect study using Scanning Electron Microscopy and X-Ray Diffraction , Debashis Das

Behaviour Of Laminated Roof Under High Horizontal Stress , Prasoon Garg

Theses/Dissertations from 2017 2017

Optimization of Mineral Processing Circuit Design under Uncertainty , Seyed Hassan Amini

Evaluation of Ultrasonic Velocity Tests to Characterize Extraterrestrial Rock Masses , Thomas W. Edge II

A Photogrammetry Program for Physical Modeling of Subsurface Subsidence Process , Yujia Lian

An Area-Based Calculation of the Analysis of Roof Bolt Systems (ARBS) , Aanand Nandula

Developing and implementing new algorithms into the LaModel program for numerical analysis of multiple seam interactions , Mehdi Rajaeebaygi

Adapting Roof Support Methods for Anchoring Satellites on Asteroids , Grant B. Speer

Simulation of Venturi Tube Design for Column Flotation Using Computational Fluid Dynamics , Wan Wang

Theses/Dissertations from 2016 2016

Critical Analysis of Longwall Ventilation Systems and Removal of Methane , Robert B. Krog

Implementing the Local Mine Stiffness Calculation in LaModel , Kaifang Li

Development of Emission Factors (EFs) Model for Coal Train Loading Operations , Bisleshana Brahma Prakash

Nondestructive Methods to Characterize Rock Mechanical Properties at Low-Temperature: Applications for Asteroid Capture Technologies , Kara A. Savage

Mineral Asset Valuation Under Economic Uncertainty: A Complex System for Operational Flexibility , Marcell B. B. Silveira

A Feasibility Study for the Automated Monitoring and Control of Mine Water Discharges , Christopher R. Vass

Spontaneous Combustion of South American Coal , Brunno C. C. Vieira

Calibrating LaModel for Subsidence , Jian Yang

Theses/Dissertations from 2015 2015

Coal Quality Management Model for a Dome Storage (DS-CQMM) , Manuel Alejandro Badani Prado

Design Programs for Highwall Mining Operations , Ming Fan

Development of Drilling Control Technology to Reduce Drilling Noise during Roof Bolting Operations , Mingming Li

The Online LaModel User's & Training Manual Development & Testing , Christopher R. Newman

How to mitigate coal mine bumps through understanding the violent failure of coal specimens , Gamal Rashed

Theses/Dissertations from 2014 2014

Effect of biaxial and triaxial stresses on coal mine shale rocks , Shrey Arora

Stability Analysis of Bleeder Entries in Underground Coal Mines Using the Displacement-Discontinuity and Finite-Difference Programs , Xu Tang

Experimental and Theoretical Studies of Kinetics and Quality Parameters to Determine Spontaneous Combustion Propensity of U.S. Coals , Xinyang Wang

Bubble Size Effects in Coal Flotation and Phosphate Reverse Flotation using a Pico-nano Bubble Generator , Yu Xiong

Integrating the LaModel and ARMPS Programs (ARMPS-LAM) , Peng Zhang

Theses/Dissertations from 2013 2013

Column Flotation of Subbituminous Coal Using the Blend of Trimethyl Pentanediol Derivatives and Pico-Nano Bubbles , Jinxiang Chen

Applications of Surface and Subsurface Subsidence Theories to Solve Ground Control Problems , Biao Qiu

Calibrating the LaModel Program for Shallow Cover Multiple-Seam Mines , Morgan M. Sears

The Integration of a Coal Mine Emergency Communication Network into Pre-Mine Planning and Development , Mark F. Sindelar

Factors considered for increasing longwall panel width , Jack D. Trackemas

An experimental investigation of the creep behavior of an underground coalmine roof with shale formation , Priyesh Verma

Evaluation of Rope Shovel Operators in Surface Coal Mining Using a Multi-Attribute Decision-Making Model , Ivana M. Vukotic

Theses/Dissertations from 2012 2012

Calculating the Surface Seismic Signal from a Trapped Miner , Adeniyi A. Adebisi

Comprehensive and Integrated Model for Atmospheric Status in Sealed Underground Mine Areas , Jianwei Cheng

Production and Cost Assessment of a Potential Application of Surface Miners in Coal Mining in West Virginia , Timothy A. Nolan

The Integration of Geomorphic Design into West Virginia Surface Mine Reclamation , Alison E. Sears

Truck Cycle and Delay Automated Data Collection System (TCD-ADCS) for Surface Coal Mining , Patricio G. Terrazas Prado

New Abutment Angle Concept for Underground Coal Mining , Ihsan Berk Tulu

Theses/Dissertations from 2011 2011

Experimental analysis of the post-failure behavior of coal and rock under laboratory compression tests , Dachao Neil Nie

The influence of interface friction and w/h ratio on the violence of coal specimen failure , Simon H. Prassetyo

Theses/Dissertations from 2010 2010

A risk management approach to pillar extraction in the Central Appalachian coalfields , Patrick R. Bucks

The Impacts of Longwall Mining on Groundwater Systems -- A Case of Cumberland Mine Panels B5 and B6 , Xinzhi Du

Evaluation of ultrafine spiral concentrators for coal cleaning , Meng Yang

Theses/Dissertations from 2009 2009

Development of a coal reserve GIS model and estimation of the recoverability and extraction costs , Chandrakanth Reddy Apala

Application and evaluation of spiral separators for fine coal cleaning , Zhuping Che

Weak floor stability in the Illinois Basin underground coal mines , Murali M. Gadde

Design of reinforced concrete seals for underground coal mines , Rajagopala Reddy Kallu

Employing laboratory physical modeling to study the radio imaging method (RIM) , Jun Lu

Influence of cutting sequence and time effects on cutters and roof falls in underground coal mine -- numerical approach , Anil Kumar Ray

Implementing energy release rate calculations into the LaModel program , Morgan M. Sears

Modeling PDC cutter rock interaction , Ihsan Berk Tulu

Analytical determination of strain energy for the studies of coal mine bumps , Qiang Xu

Improvement of the mine fire simulation program MFIRE , Lihong Zhou

Theses/Dissertations from 2008 2008

Program-assisted analysis of the transverse pressure capacity of block stoppings for mine ventilation control , Timothy J. Batchler

Analysis of factors affecting wireless communication systems in underground coal mines , David P. McGraw

Analysis of underground coal mine refuge shelters , Mickey D. Mitchell

Theses/Dissertations from 2007 2007

Dolomite flotation of high magnesium phosphate ores using fatty acid soap collectors , Zhengxing Gu

Evaluation of longwall face support hydraulic supply systems , Ted M. Klemetti II

Experimental studies of electromagnetic signals to enhance radio imaging method (RIM) , William D. Monaghan

Analysis of water monitoring data for longwall panels , Joseph R. Zirkle

Theses/Dissertations from 2006 2006

Measurements of the electrical properties of coal measure rocks , Nikolay D. Boykov

Geomechanical and weathering properties of weak roof shales in coal mines , Hakan Gurgenli

Assessment and evaluation of noise controls on roof bolting equipment and a method for predicting sound pressure levels in underground coal mining , Rudy J. Matetic

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UKnowledge > College of Engineering > Mining Engineering > Theses & Dissertations

Theses and Dissertations--Mining Engineering

Theses/dissertations from 2024 2024.

THE METHODOLOGY FOR INTEGRATING ROBOTIC SYSTEMS IN UNDEGROUND MINING MACHINES , Peter Kolapo

DISCRETE ELEMENT MODELING TO PREDICT MUCKPILE PROFILES FROM CAST BLASTING , Russell Lamont

Theses/Dissertations from 2023 2023

ASSESSMENT OF AIR OVERPRESSURE FROM BLASTING USING COMPUTATIONAL FLUID DYNAMICS , Cecilia Estefania Aramayo

RECOVERY OF VALUABLE METALS FROM ELECTRONIC WASTE USING A NOVEL AMMONIA-BASED HYDROMETALLURGICAL PROCESS , Peijia Lin

AN ACID BAKING APPROACH TO ENHANCE RARE EARTH ELEMENT RECOVERY FROM BITUMINOUS COAL SOURCES , Ahmad Nawab

PREDICTION OF DYNAMIC SUBSIDENCE IN THE PROXIMITY OF LONGWALL PANEL BOUNDARIES , JESUS DAVID ROMERO BENITEZ

Prediction of Blast-Induced Ground Vibrations: A Comparison Between Empirical and Artificial-Neural-Network Approaches , Luis F. Velasquez

A LABORATORY AND NUMERICAL INVESTIGATION OF THE STRENGTH OF IRREGULARLY SHAPED PILLARS , Zachary Wedding

Theses/Dissertations from 2022 2022

DEVELOPMENT OF UNIVARIATE AND MULTIVARIATE FORECASTING MODELS FOR METHANE GAS EMISSIONS IN UNDERGROUND COAL MINES , Juan Diaz

PARAMETRIC NUMERICAL ANALYSIS OF INCLINED COAL PILLARS , Robin Flattery

Strain Energy Analysis Related To Strata Failure During Caving Operations , Caroline Gerwig

LAPTOP RECYCLING CASE STUDY: ESTIMATING THE CONTAINED VALUE AND VALUE RECOVERY PROCESS FEASIBILITY OF END-OF-LIFE CONSUMER ELECTRONICS , Zebulon Hart

INVESTIGATION INTO, & ANALYSIS OF TEMPERATURE & STRAIN DATA FOR COAL MINE SEAL MATERIAL DURING CURING , Stephanus Jaco van den Berg

Theses/Dissertations from 2021 2021

DEVELOPMENT OF AN AUTONOMOUS NAVIGATION SYSTEM FOR THE SHUTTLE CAR IN UNDERGROUND ROOM & PILLAR COAL MINES , Vasileios Androulakis

Investigation of Coal Burst Potential Using Numerical Modeling and Rock Burst Indices , Cristian David Cardenas Triana

Capture of Respirable Dust using Maintenance Free Impingement Screen , Neeraj Kumar Gupta

OXIDATION PRETREATMENT FOR ENHANCED LEACHABILITY OF RARE EARTH ELEMENTS FROM BITUMINOUS COAL SOURCES , Tushar Gupta

AN APPROACH FOR PREDICTING FLOW CHARACTERISTICS AT THE CONTINUOUS MINER FACE , Kayla Henderson

CONCEPTS FOR DEVELOPMENT OF SHUTTLE CAR AUTONOMOUS DOCKING WITH CONTINUOUS MINER USING 3-D DEPTH CAMERA , Sibley Miller

MODELING OF RARE EARTH SOLVENT EXTRACTION PROCESS FOR FLOWSHEET DESIGN AND OPTIMIZATION , Vaibhav Kumar Srivastava

Application of a Novel Ventilation Simplification Algorithm , Caitlin V. Strong

A METHODOLOGY FOR AUTONOMOUS ROOF BOLT INSTALLATION USING INDUSTRIAL ROBOTICS , Anastasia Xenaki

Theses/Dissertations from 2020 2020

NUMERICAL APPROXIMATION OF THE GROUND REACTION AND SUPPORT REACTION CURVES FOR UNDERGROUND LIMESTONE MINES , Jesus Castillo Gomez

Proof of Concept for the Development of a Ground Vibration Sensor System for Future Research in Blasting , John Meuth

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Home > College of Engineering > Dept. of Geological and Mining Engineering and Sciences > Dissertations, Master's Theses and Master's Reports

Department of Geological and Mining Engineering and Sciences

Dept. of Geological and Mining Engineering and Sciences Dissertations, Master's Theses and Master's Reports

Explore our collection of dissertations, master's theses and master's reports from the Department of Geological and Mining Engineering and Sciences below.

Theses/Dissertations/Reports from 2023 2023

AGE AND CHEMISTRY OF BELL CREEK BATHOLITH , Elana G. Barth

AN ENTROPY-BASED RISK INDEX (ERI) OF MINING HEALTH AND SAFETY USING CLUSTERING AND STATISTICAL METHODS , Dharmasai Eshwar Reddy Sirigiri

AN INVESTIGATION OF MICROSEISMICITY DURING THE 2018 KILAUEA CALDERA COLLAPSE , Isabella S. Metts

CLIMATE CHANGES IN EL SALVADOR: IMPACTS OF ‘LA CANÍCULA’ (MIDSUMMER DROUGHT) ON AGRICULTURAL PRACTICES AND DECISION-MAKING IN RURAL COMMUNITIES , Paola M. Rivera González

COMPREHENSIVE ANALYSIS OF SEISMIC SIGNALS FROM PACAYA VOLCANO USING DEEP LEARNING EVENT DETECTION , Jessica L. DeVlieg

Developing a regional scale landslide early warning system in a data-sparse region using remote sensing, geostatistics, and Google Earth Engine , Vishnu Chakrapani Lekha

EVALUATING GEOMECHANICAL UNCERTAINTY IN OPEN PIT MINE PLANNING , Evan Ricchio-Hitchcock

EXPLORING GROUND-PENETRATING RADAR RESPONSES TO BASALTIC TERRAIN FOR UPCOMING LUNAR EXPEDITIONS , Caleb J. Kaminski

Information use and decision-making for evacuation at Fuego volcano, Guatemala , Beth A. Bartel

INTEGRATING LIDAR, AEROMAGNETIC, AND GEOLOGICAL FIELD DATA TO IDENTIFY STRUCTURAL-LITHOLOGIC ELEMENTS WITHIN THE ARCHEAN CARNEY LAKE GNEISS COMPLEX , Ian M. Gannon

RAIN-INDUCED HAZARDS IN REMOTE, LOW-RESOURCE COMMUNITIES: A CASE STUDY OF FLASH FLOODING IN THE USULUTÁN DEPARTMENT, EL SALVADOR , Natalea Cohen

REMOTE SENSING APPROACH FOR TERRAMECHANICS APPLICATIONS UTILIZING MACHINE AND DEEP LEARNING , Jordan J. Ewing

STRUCTURAL ANALYSIS AND INTERPRETATION OF DEFORMATION ALONG THE KEWEENAW FAULT SYSTEM FROM LAKE LINDEN TO MOHAWK, MICHIGAN , Nolan G. Gamet

STRUCTURAL ANALYSIS AND SLIP KINEMATICS OF THE KEWEENAW FAULT SYSTEM BETWEEN BÊTE GRISE BAY AND GRATIOT LAKE, KEWEENAW COUNTY, MICHIGAN , Daniel J. Lizzadro-McPherson

Theses/Dissertations/Reports from 2022 2022

A GLOBAL SURVEY OF VOLCANIC SO2 EMISSIONS AND HEAT FLUX MEASURED FROM SPACE , Nelmary Rodríguez-Sepúlveda

BUILDING INTEREST AND KNOWLEDGE IN GEOSCIENCES THROUGH PLACE- & FIELD-BASED TEACHER PROFESSIONAL LEARNING PROGRAMS: A COMPARATIVE MULTI-CASE STUDY , Emily Gochis

DEFINING THE ENDMEMBER SYSTEM OF US SOILS AND QUANTIFYING RELATIONSHIPS, AND A HYPERSPECTRAL APPROACH TO THE ALTERATION STRENGTH INDEX , Rachel Rulison

EVALUATION OF PRODUCTION-WELL PERFORMANCE IN RESPONSE TO FORMATION CLOGGING AND REHABILITATION FOR THE KEWEENAW BAY TRIBAL FISH HATCHERY , Brock O. Howell

INJURY SEVERITY MODELING IN MINING INDUSTRY USING WORKERS' COMPENSATION DATA AND DATA ANALYTICS , Poorva Kadrolli

SIMULATING GROUNDWATER POLLUTANT TRANSPORT FOR REMEDIATION DESIGN, ANTRIM COUNTY, MICHIGAN , Abilynn Raetz

THERMOMECHANICAL EVOLUTION OF A MAGMATIC SYSTEM DURING A CALDERA CYCLE: OKATAINA VOLCANIC CENTER, NEW ZEALAND , Jacob Bonessi

USING SENTINEL-1 SYNTHETIC APERTURE RADAR TO DETECT BURN AREA AND BURN SEVERITY IN COASTAL AREAS, CALIFORNIA , Kassidy O'Connor

Theses/Dissertations/Reports from 2021 2021

Advancement of full-vector variable-temperature magnetometry for rock-magnetic and paleointensity applications , Leonid Surovitskii

A METHODOLOGY FOR THE CREATION OF VOLCANIC GAS HAZARD MAPS USING SATELLITE-DERIVED SULFUR DIOXIDE , Sanna J. Mairet

APPLICATION OF REMOTE SENSING FOR PERMAFROST MONITORING IN ALASKA , Iuliia V. Tcibulnikova

COMPARING SCOOP3D AND GIS-TISSA MODELS FOR SLOPE STABILITY ANALYSIS IN IDUKKI, KERALA, INDIA , Stepan Pikul

DYNAMICS OF THE TOBA MAGMATIC SYSTEM AS RECORDED BY CRYSTALS , Olivia Barbee

GAS AND HEAT FLUXES DURING MULTIPLE EFFUSIVE ERUPTIONS OF PITON DE LA FOURNAISE (RÉUNION) AND THEIR IMPLICATIONS FOR MAGMATIC PROCESSES , Pauline Verdurme

HYDROLOGIC INVESTIGATION OF THE CHIWAUKEE PRAIRIE (WISCONSIN) RESTORATION , Nick Potter

ORIGIN AND DISTRIBUTION OF DIFFUSE SOIL CO2 GAS EMISSIONS ACROSS TURRIALBA AND IRAZÚ VOLCANOES, COSTA RICA , Katie Nelson

PRE-FAILURE PERSISTENT SCATTERER INTERFEROMETRY (PSI) AND SOIL MOISTURE INDEX (SMI) ANALYSIS OF THE EDENVILLE DAM IN MIDLAND, MICHIGAN , Ryan Klida

SEISMOTECTONIC INTERPRETATION OF AN EXPANSIVE SET OF EARTHQUAKE FOCAL MECHANISMS FROM FIRST MOTIONS AND AMPLITUDE RATIOS ON THE YELLOWSTONE PLATEAU , Cristhian Salas Pazmiño

SOIL CO2 DIFFUSE DEGASSING AT CHACHIMBIRO VOLCANO, ECUADOR , Domenicca Mileth Guillen Pachacama

Structural Analysis and Interpretation of Deformation Along the Keweenaw Fault System West of Lake Gratiot, Keweenaw County, Michigan , Sophie A. Mueller

UTILIZATION OF PAENIBACILLUS POLYMYXA IN THE RECOVERY OF LITHIUM BEARING MINERALS , Diana Bullen

Volcan de Fuego: A Machine Learning Approach in Understanding the Eruptive Cycles Using Precursory Tilt Signals , Kay Sivaraj

Theses/Dissertations/Reports from 2020 2020

AMBIENT NOISE SEISMIC INTERFEROMETRY THROUGH SURFACE SEISMIC DATA ACQUISITION VS ZERO-OFFSET VERTICAL SEISMIC PROFILING (VSP) , Erdi Apatay

A MULTI-YEAR ANALYSIS FROM 2014 TO 2017 OF SNOWFALL TYPES IN MARQUETTE, MICHIGAN: A DIFFERENTIATION BETWEEN SYNOPTIC SNOW EVENTS AND LAKE EFFECT SNOW EVENTS IMPACTED BY THE PRESENCE OF LAKE SUPERIOR , Roberto Piemontese

A Novel Pixel-based Multiple-Point Geostatistical Simulation Method for Stochastic Modeling of Earth Resources , Adel Asadi

Assessing the Accuracy of a UAV Snow Depth Survey: Utqiagvik (Barrow), Alaska CALM Grid , Ian Nichols

DEVELOPING INNOVATIVE SPECTRAL AND MACHINE LEARNING METHODS FOR MINERAL AND LITHOLOGICAL CLASSIFICATION USING MULTI-SENSOR DATASETS , Chandan Kumar

Exploring the Need for Improved Precipitation Measurements for Rainfall-Induced Landslides , Katelyn E. Kring

FLUID INCLUSION STUDY OF SELECTED CALCITE ASSOCIATED WITH NATIVE COPPER, QUINCY MINE, KEWEENAW PENINSULA, MICHIGAN , David Kelly

GEOCHEMICAL AND PETROLOGICAL EVIDENCE OF THE GEODYNAMIC EVOLUTION OF THE BELL CREEK BATHOLITH, REPUBLIC QUADRANGLE, MARQUETTE , Anna Dalle Fratte

GLOBAL OPTIMIZATION OF THE OPEN PIT MINING COMPLEX WITH INTEGRATED CUT-OFF GRADE OPTIMIZATION UNDER UNCERTAINTY , Amol Paithankar

JOINT SIMULATION OF CONTINUOUS AND CATEGORICAL VARIABLES FOR MINERAL RESOURCE MODELING AND RECOVERABLE RESERVES CALCULATION , Sentle Augustinus Hlajoane

PHYSICAL MODELING OF THE KRAUKLIS WAVES: INSIGHTS FROM TWO EXPERIMENTAL APPARATUSES , Haitao Cao

QUANTIFYING WATER RECHARGE AND WATER USE IN HAND DUG WELLS: A CASE STUDY OF THIAWOR, SENEGAL, WEST AFRICA , Celine Carus

RAIN GENERATED LAHARS PRIOR TO THE 2018 CATASTROPHIC ERUPTION OF FUEGO VOLCANO, GUATEMALA , Claudia Buondonno

Reconstruction of the 2018 Anak Krakatau collapse using PlanetScope imaging and numerical modeling , Davide Saviano

ROCK MAGNETIC PROPERTIES OF THE L5 ORDINARY CHONDRITE DAULE , Katie E. Bristol

STOCHASTIC INVERSION INTEGRATING SEISMIC DATA, LITHO-FACIES PHYSICAL PROPERTIES, AND MULTIPLE-POINT GEOSTATISTICS FOR RESERVOIR CHARACTERIZATION , Mohamed Mohamed

THE EFFECT OF SPACING OF VETIVER GRASS (CHRYSOPOGON ZIZANIOIDES) HEDGEROWS ON HILLSLOPE EROSION IN EASTERN REGION, GHANA , Evan R. Lanese

The impacts of accessibility on vulnerability of place in Comfort Castle, Jamaica , Heather Thole

THE OVEREXPLOITATION OF THE VALLE DE QUERÉTARO AQUIFER AND ITS IMPACT IN SMALL PERI-URBAN COMMUNITIES, QUERÉTARO, MÉXICO , Kelsey Kirkland

Theses/Dissertations/Reports from 2019 2019

APPLICATION OF A DISTRIBUTED HYDROLOGIC MODEL FOR THE ANALYSIS OF LAND USE CHANGE IN KEDOUGOU, SENEGAL , Francisco Perez

Assessing the spatial and temporal variability of the Detroit River and harmful algal blooms in western Lake Erie , Angela W. Yu

CHARACTERIZING FRESHWATER PHYTOPLANKTON DYNAMICS WITH ELECTRO-OPTICAL REMOTE SENSING , Michael Sayers

Determination of Reduced Salt Dome Hydrocarbon Accumulation Using Full-Azimuth 3D Seismic Data: A Case Study , Ben Pletcher

KEWEENAW FAULT GEOMETRY AND SLIP KINEMATICS - BÊTE GRISE BAY, KEWEENAW PENINSULA, MICHIGAN , Colin Tyrrell

LINKING HISTORICAL, FIELD, AND SATELLITE DATA TO DETERMINE THE RELATIONSHIP BETWEEN GAS EMISSIONS AND VEGETATION CHANGE IN THE PUHIMAU GEOTHERMAL AREA EAST RIFT ZONE KILAUEA, HAWAII , Christie Torres Rosa

Magnetic Characterization of Iron Formations from drill cores near Iron Mountain, Michigan , Adren Rigdon

PALEOMAGNETIC INVESTIGATION OF IGNEOUS ROCKS DEFORMED BY THE KEWEENAW FAULT IN THE NORTHWESTERN KEWEENAW PENINSULA. , Daniel Trekas

SEISMIC SIGNALS AND SOURCES AT FUEGO VOLCANO, GUATEMALA DURING JANUARY 2012 , Kyle Brill

SPATIAL AND TEMPORAL DISTRIBUTION OF HYDROTHERMAL MINERALS AND SOURCES OF HYDROTHERMAL FLUIDS INFERRED FROM LIGHT STABLE ISOTOPES, KEWEENAW PENINSULA NATIVE COPPER DISTRICT, MICHIGAN , Thomas Bodden

SPECTRAL DECOMPOSITION OF SEISMIC DATA USING SPARSE S-TRANSFORM COMPARED TO CONVENTIONAL METHODS , Kara Donahue

TESTING THE USE OF VEGETATION INDICES AS INDICATORS OF PRE-ERUPTIVE VOLCANIC UNREST AT KILAUEA VOLCANO, HAWAII , Quelyn Bekkering

THE ORIGIN OF AN ARCHEAN BATHOLITH IN MICHIGAN’S UPPER PENINSULA , Brandi Petryk

VOLCANO MONITORING FROM SPACE USING HIGH-CADENCE PLANET CUBESATS: APPLICATION TO FUEGO VOLCANO, GUATEMALA , Anna Aldeghi

Theses/Dissertations/Reports from 2018 2018

ANALYZING THE LIFE-CYCLE OF UNSTABLE SLOPES USING APPLIED REMOTE SENSING WITHIN AN ASSET MANAGEMENT FRAMEWORK , El Hachemi Y. Bouali

Application of remote sensing and machine learning modeling to post-wildfire debris flow risks , Priscilla Addison

APPLICATION OF SEISMIC RADIAL ANISOTROPY FOR NEAR-SURFACE FRACTURES IDENTIFICATION , Jer-Yu Jeng

CHARACTERIZING CDOM SPECTRAL VARIABILITY FROM SEAS TO SPACE , Brice Grunert

COMPARISON OF KARSTIFICATION METHODS AND ISOSTATIC REBOUND IN THE SUWANNEE RIVER BASIN, FLORIDA , Toni Larche

DISASTER RISK IN THE LAKE NYOS AREA, CAMEROON: EFFECTS OF THE GAS HAZARD AND SOCIALLY PRODUCED VULNERABILITY , Mary Witucki

GROUND DEFORMATION STUDIES AND EVACUATION BEHAVIOR DURING ERUPTIONS AT GUATEMALAN VOLCANOES , Hans Lechner

Long-term Changes in Extreme Air Pollution Meteorology and Implications for Air Quality , Pei Hou

PROBABILISTIC REGIONAL LANDSLIDE HAZARD ASSESSMENT FOR THE ENGURI DAM (JIVARI, GEORGIA) , MARIA DILETTA ACCIARO

PROBING THE PRECAMBRIAN GEODYNAMO: ANALYSIS OF THE GEOMAGNETIC FIELD BEHAVIOR AND CALIBRATION OF PSEUDO-THELLIER PALEOINTENSITY METHOD FOR MESOPROTEROZOIC ROCKS , Marine Foucher

RISK QUANTIFICATION IN PRODUCTION PHASE-DESIGN BY CONSIDERING PRICE, VOLUME, AND CALORIFIC VALUE: AN APPLICATION FROM INDONESIAN COAL MINE , Fanteri Aji Dharma Suparno

THE EFFECTS OF EUCALYPTUS PLANTATIONS ON SLOPE STABILITY IN ABAJALE, ETHIOPIA , Levi Rhody

WILDFIRE EMISSIONS IN THE CONTEXT OF GLOBAL CHANGE AND THE IMPLICATIONS FOR MERCURY POLLUTION , Aditya Kumar

Theses/Dissertations/Reports from 2017 2017

COMPARISON OF AMBIENT NOISE METHODS TO FIND SURFACE - WAVE DISPERSION CURVES AT PACAYA VOLCANO, GUATEMALA , Simone Puel

COMPARISON OF STACKING RESULTS USING CONVENTIONAL AND WEIGHTED TECHNIQUES, AND THEIR AFFECT ON COHERENCE ATTRIBUTE FOR PENOBSCOT SEISMIC DATA OF NOVA SCOTIA, CANADA , Erdem Cetin

Detecting Overpressure Zones by Using Model Based Inversion in Kupe Field, New Zealand , Timucin Cakir

DEVELOPING A GIS TOOL FOR INFINITE SLOPE STABILITY ANALYSIS (GIS-TISSA) , Jonathon Sanders

FORENSIC ANALYSIS OF SHALLOW PRECIPITATION TRIGGERED LAHARS IN 2016 ON CONCEPCIÓN AND MADERAS VOLCANOES, OMETEPE ISLAND, NICARAGUA , Lindsay Ellingson

Magnetic Petrophysics of the Vulcan Iron Formation (Michigan, USA) , Matthew Laird

Multiple Suppression from 2-D Shallow Marine Seismic Reflection Data Using Filtering and Deconvolution Approaches: A Case Study from Southwest Taiwan , Fatma Sinem Boyaci

NOVEL METHODS FOR QUANTIFYING SPATIO-TEMPORAL CHANGE IN GLACIATED AND SUBAQUEOUS ENVIRONMENTS , Jordan Mertes

Patterns in eruptions at Fuego from statistical analysis of video surveillance , Monica Castro-Escobar

RISK CONTROL IN PRODUCTION SCHEDULING BY CONSIDERING VOLUME AND GRADE UNCERTAINTIES IN RESOURCE ESTIMATION , Amol Paithankar

Rock Magnetic Investigation of the Michigan Basin Soils and Sediments Overlying the Oil-Bearing Silurian Pinnacle Reefs , Jake Tresnak

USING LiDAR TO MAP THE GEOLOGY AND MORPHOLOGY OF ALLUVIAL FANS: SALTON SEA AREA, CALIFORNIA , Eric Alexander Macleod

Theses/Dissertations/Reports from 2016 2016

A PETROPHYSICAL EVALUATION FOR PERMEABILITY OF A GAS RESERVOIR IN THE TARANAKI BASIN, NEW ZEALAND , Musa Cetin

A SIGNAL ANALYSIS OF CROSSWELL SEISMIC INTERFEROMETRY USING 2D FINITE DIFFERENCE MODELING OF AMBIENT NOISE , Garvie Crane

A SMALL-SCALE WATER BUDGET APPROACH AND WATER QUALITY ASSESSMENT: A CASE STUDY FOR CALDERAS LAKE, GUATEMALA , Edrick Ramos

Assessment of the Geological Hazards Pertaining to Arch Rock, Mackinac Island, USA , Cassandra M. Javor

CAN SEISMIC VELOCITY STACKING ERRORS RESULT IN THE LOW-FREQUENCY SHADOW? , Umit Serhan Inan

CAVE DETECTION USING SEISMIC METHODS AT MADISON BLUE SPRING STATE PARK, MADISON COUNTY, FLORIDA , Charles Breithaupt

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Data Mining

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Student theses

1 - 50 out of 258 results
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3d face reconstruction using deep learning.

Supervisor: Medeiros de Carvalho, R. (Supervisor 1), Gallucci, A. (Supervisor 2) & Vanschoren, J. (Supervisor 2)

Student thesis : Master

Achieving Long Term Fairness through Curiosity Driven Reinforcement Learning: How intrinsic motivation influences fairness in algorithmic decision making

Supervisor: Pechenizkiy, M. (Supervisor 1), Gajane, P. (Supervisor 2) & Kapodistria, S. (Supervisor 2)

Activity Recognition Using Deep Learning in Videos under Clinical Setting

Supervisor: Duivesteijn, W. (Supervisor 1), Papapetrou, O. (Supervisor 2), Zhang, L. (External person) (External coach) & Vasu, J. D. (External coach)

A Data Cleaning Assistant

Supervisor: Vanschoren, J. (Supervisor 1)

Student thesis : Bachelor

A Data Cleaning Assistant for Machine Learning

A deep learning approach for clustering a multi-class dataset.

Supervisor: Pei, Y. (Supervisor 1), Marczak, M. (External person) (External coach) & Groen, J. (External person) (External coach)

Aerial Imagery Pixel-level Segmentation

A framework for understanding business process remaining time predictions.

Supervisor: Pechenizkiy, M. (Supervisor 1) & Scheepens, R. J. (Supervisor 2)

A Hybrid Model for Pedestrian Motion Prediction

Supervisor: Pechenizkiy, M. (Supervisor 1), Muñoz Sánchez, M. (Supervisor 2), Silvas, E. (External coach) & Smit, R. M. B. (External coach)

Algorithms for center-based trajectory clustering

Supervisor: Buchin, K. (Supervisor 1) & Driemel, A. (Supervisor 2)

Allocation Decision-Making in Service Supply Chain with Deep Reinforcement Learning

Supervisor: Zhang, Y. (Supervisor 1), van Jaarsveld, W. L. (Supervisor 2), Menkovski, V. (Supervisor 2) & Lamghari-Idrissi, D. (Supervisor 2)

Analyzing Policy Gradient approaches towards Rapid Policy Transfer

An empirical study on dynamic curriculum learning in information retrieval.

Supervisor: Fang, M. (Supervisor 1)

An Explainable Approach to Multi-contextual Fake News Detection

Supervisor: Pechenizkiy, M. (Supervisor 1), Pei, Y. (Supervisor 2) & Das, B. (External person) (External coach)

An exploration and evaluation of concept based interpretability methods as a measure of representation quality in neural networks

Supervisor: Menkovski, V. (Supervisor 1) & Stolikj, M. (External coach)

Anomaly detection in image data sets using disentangled representations

Supervisor: Menkovski, V. (Supervisor 1) & Tonnaer, L. M. A. (Supervisor 2)

Anomaly Detection in Polysomnography signals using AI

Supervisor: Pechenizkiy, M. (Supervisor 1), Schwanz Dias, S. (Supervisor 2) & Belur Nagaraj, S. (External person) (External coach)

Anomaly detection in text data using deep generative models

Supervisor: Menkovski, V. (Supervisor 1) & van Ipenburg, W. (External person) (External coach)

Anomaly Detection on Dynamic Graph

Supervisor: Pei, Y. (Supervisor 1), Fang, M. (Supervisor 2) & Monemizadeh, M. (Supervisor 2)

Anomaly Detection on Finite Multivariate Time Series from Semi-Automated Screwing Applications

Supervisor: Pechenizkiy, M. (Supervisor 1) & Schwanz Dias, S. (Supervisor 2)

Anomaly Detection on Multivariate Time Series Using GANs

Supervisor: Pei, Y. (Supervisor 1) & Kruizinga, P. (External person) (External coach)

Anomaly detection on vibration data

Supervisor: Hess, S. (Supervisor 1), Pechenizkiy, M. (Supervisor 2), Yakovets, N. (Supervisor 2) & Uusitalo, J. (External person) (External coach)

Application of P&ID symbol detection and classification for generation of material take-off documents (MTOs)

Supervisor: Pechenizkiy, M. (Supervisor 1), Banotra, R. (External person) (External coach) & Ya-alimadad, M. (External person) (External coach)

Applications of deep generative models to Tokamak Nuclear Fusion

Supervisor: Koelman, J. M. V. A. (Supervisor 1), Menkovski, V. (Supervisor 2), Citrin, J. (Supervisor 2) & van de Plassche, K. L. (External coach)

A Similarity Based Meta-Learning Approach to Building Pipeline Portfolios for Automated Machine Learning

Aspect-based few-shot learning.

Supervisor: Menkovski, V. (Supervisor 1)

Assessing Bias and Fairness in Machine Learning through a Causal Lens

Supervisor: Pechenizkiy, M. (Supervisor 1)

Assessing fairness in anomaly detection: A framework for developing a context-aware fairness tool to assess rule-based models

Supervisor: Pechenizkiy, M. (Supervisor 1), Weerts, H. J. P. (Supervisor 2), van Ipenburg, W. (External person) (External coach) & Veldsink, J. W. (External person) (External coach)

A Study of an Open-Ended Strategy for Learning Complex Locomotion Skills

A systematic determination of metrics for classification tasks in openml, a universally applicable emm framework.

Supervisor: Duivesteijn, W. (Supervisor 1), van Dongen, B. F. (Supervisor 2) & Yakovets, N. (Supervisor 2)

Automated machine learning with gradient boosting and meta-learning

Automated object recognition of solar panels in aerial photographs: a case study in the liander service area.

Supervisor: Pechenizkiy, M. (Supervisor 1), Medeiros de Carvalho, R. (Supervisor 2) & Weelinck, T. (External person) (External coach)

Automatic data cleaning

Automatic scoring of short open-ended questions.

Supervisor: Pechenizkiy, M. (Supervisor 1) & van Gils, S. (External coach)

Automatic Synthesis of Machine Learning Pipelines consisting of Pre-Trained Models for Multimodal Data

Automating string encoding in automl, autoregressive neural networks to model electroencephalograpy signals.

Supervisor: Vanschoren, J. (Supervisor 1), Pfundtner, S. (External person) (External coach) & Radha, M. (External coach)

Balancing Efficiency and Fairness on Ride-Hailing Platforms via Reinforcement Learning

Supervisor: Tavakol, M. (Supervisor 1), Pechenizkiy, M. (Supervisor 2) & Boon, M. A. A. (Supervisor 2)

Benchmarking Audio DeepFake Detection

Better clustering evaluation for the openml evaluation engine.

Supervisor: Vanschoren, J. (Supervisor 1), Gijsbers, P. (Supervisor 2) & Singh, P. (Supervisor 2)

Bi-level pipeline optimization for scalable AutoML

Supervisor: Nobile, M. (Supervisor 1), Vanschoren, J. (Supervisor 1), Medeiros de Carvalho, R. (Supervisor 2) & Bliek, L. (Supervisor 2)

Block-sparse evolutionary training using weight momentum evolution: training methods for hardware efficient sparse neural networks

Supervisor: Mocanu, D. (Supervisor 1), Zhang, Y. (Supervisor 2) & Lowet, D. J. C. (External coach)

Boolean Matrix Factorization and Completion

Supervisor: Peharz, R. (Supervisor 1) & Hess, S. (Supervisor 2)

Bootstrap Hypothesis Tests for Evaluating Subgroup Descriptions in Exceptional Model Mining

Supervisor: Duivesteijn, W. (Supervisor 1) & Schouten, R. M. (Supervisor 2)

Bottom-Up Search: A Distance-Based Search Strategy for Supervised Local Pattern Mining on Multi-Dimensional Target Spaces

Supervisor: Duivesteijn, W. (Supervisor 1), Serebrenik, A. (Supervisor 2) & Kromwijk, T. J. (Supervisor 2)

Bridging the Domain-Gap in Computer Vision Tasks

Supervisor: Mocanu, D. C. (Supervisor 1) & Lowet, D. J. C. (External coach)

CCESO: Auditing AI Fairness By Comparing Counterfactual Explanations of Similar Objects

Supervisor: Pechenizkiy, M. (Supervisor 1) & Hoogland, K. (External person) (External coach)

Clean-Label Poison Attacks on Machine Learning

Supervisor: Michiels, W. P. A. J. (Supervisor 1), Schalij, F. D. (External coach) & Hess, S. (Supervisor 2)

Associate Professor Simit Raval

Fields of Research (FoR)

Associate Professor Simit Raval is Director of Undergraduate Studies in Mining Engineer and Co-Director of the Laboratory for Imaging of the Mine Environment (LIME), at the University of New South Wales (UNSW) in Sydney, Australia. He is specialised in the integration of sensing technologies to drive applied innovation in mining, environmental and civil engineering sectors. He leads a group of researchers focused on utilising data from sensors mounted on various platforms, from satellite through to UAVs, to visualise, identify and monitor operational environments. He has received several competitive research grants, including SIX nationally competitive ACARP grants as the project leader. He has supervised PhD research projects involving drone-based smart sensing (multispectral, hyperspectral and LiDAR), underground mobile laser scanning, image-based automated material characterisation, mine rehabilitation/closure, climate change and asteroid mining. He has received SIX teaching awards including UNSW Vice Chancellor’s Awards for Outstanding Contributions to Student Learning (2020) and the International Tim Show Award for Innovation in Teaching and Learning (2018).

I have received a total of more than $3 million competitive research funding that includes:

Category 1 (Federal government competitive grants)

Raval S (2024). Methane Matters: Updates on Relevant Advances for Coal Mine Emissions. Australian Coal Industry’s Research Program (ACARP).

Raval S (Project Leader) , Banerjee B and Roddis D (2024). Assessment of sensors and airflow modelling for their suitability to quantify methane emissions in open cut mines. Australian Coal Industry’s Research Program (ACARP).

Raval S (Project Leader) and Banerjee B (2024). “SCANDY” - A handheld Imaging System for Real Time Spoil Categorisation. Australian Coal Industry’s Research Program (ACARP).

Raval S (2022) . Image-based automated characterisation of wast e materials - Extension. Australian Coal Industry’s Research Program (ACARP).
Khalili-Naghadeh N., … Raval S . (total 16 CIs) (2022). ARC Industry Transformation Research Hub for Resilient and Intelligent Infrastructure Systems (RIIS) in Urban, Resources and Energy Sectors.
Raval S (2020) . Automated structural mapping in underground mines using mobile laser scanning technology (Extension). Australian Coal Industry’s Research Program (ACARP).
Raval S (2019) . Image-based automated characterisation of waste materials. Australian Coal Industry’s Research Program (ACARP).
Fityus S, Simmons J, Thoeni K, Burton G and Raval S (2019). Baseline data for the development of automated characterisation of waste materials. Australian Coal Industry’s Research Program (ACARP).
Raval S (Project Leader) and Canbulat I (2017). Automated structural mapping in underground mines using mobile laser scanning technology. Australian Coal Industry’s Research Program (ACARP).
Raval S (Project Leader) , Shen X, Masoumi H and Tannant D (2016). Improved structural mapping of pit walls using UAV-based mobile laser scanning. Australian Coal Industry’s Research Program (ACARP).

Category 2, 3 (State, Industry, University and School level competitive grants and other grants)

Raval S. (2023). Advanced underground laser scanning for safety and automation. Azure Mining Technology funded industry research project.
Raval S (Project Leader) , Tabelin C and Saydam S (2022). On-Belt Lithium Ore Characterisation: Choosing the right technology. Australian Remote Operations for Space and Earth (AROSE) facilitated industry research.
Raval S (Project Leader) , Le-Hussain F, Zhang C, Li B (2022). Thermal infrared (TIR) and multi-spectral remote sensing.
Kara S... Raval S . (total 21 CIs) (2021). BHP Tailings Challenge Proof of Concept Stage.
Raval S. (2019). Automated volumetric calculation of grain storage. Industry (ANZ bank) funding through Innovation Central Sydney.
Raval S (Project Leader) and Rasekh (2019). Development of virtual reality based interactive sustainable mining practice module. MERE School Teaching Initiative Grant.
Hussain F, Clark S and Raval S (2019). Impact of CO2 sequestration on groundwater resources and vegetation. UNSW MERE Collaborative Research Grant.
Raval S (2017). Precision data integration tool for a friction free agronomic workflow. Tech Voucher Grant funded by Agronomeye Pty Ltd and NSW Department of Industries.
Raval S (Project Leader) and Canbulat I (2016). Underground mobile laser scanner. UNSW School of Mining Research Grant.
Raval S (Project Leader) , Sharifzadeh M and Kizil M (2017). Evaluation of mobile laser scanning for rapid rock mass characterisation in underground mining environment. MEA Collaborative Research grant.
Cullen PJ, Raval S , Prescott S, Spicer P, Boyer C, S aydam S and Triantafilis J (2017). High Resolution Laser-induced Breakdown Spectroscopy (LIBS) Imaging. UNSW Research Infrastructure Scheme.
Raval S (Project Leader) , Chanda E, Unger C and Winchester S (2016). Review of the Socio Environmental Aspect of Mining Course. Mining Education Australia (MEA) .
Cullen PJ, Raval S and other 9 co-investigators (2015). Provision of non-thermal plasma technology and hyperspectral imaging. UNSW Research Infrastructure Scheme.
Raval S , Timms W and Taplin R (2014). A novel approach to monitor peat swamp conditions in the vicinity of underground mines using a combination of LiDAR, radar, and time-series optical satellite data. UNSW School of Mining Research Grant .
Taplin R and Raval S ( 2014). Operationalising best practice in biodiversity offsets for coal mining in the Upper Hunter/Bowen Basin: A toolkit for industry. UNSW School of Mining Research Grant .
Raval S and Taplin R ( 2013). Investigating the capabilities of hyperspectral remote sensing in detecting fugitive metals around the Yerranderie Silver Mine in the Blue Mountains National Park. UNSW Faculty of Engineering Early Career Researcher Grant .
Raval S ( 2013). Development of satellite imagery based most suitable vegetation index to monitor mine site rehabilitation. UNSW School of Mining Research Grant .
Taplin R and Raval S ( 2013). Assessing the effectiveness of biodiversity offsetting efforts to balance conservation and mining industry impacts. UNSW School of Mining Research Grant .
Raval S ( 2012). Investigating capabilities of an advanced Interferometry in detecting horizontal displacement at the Metropolitan Mine. UNSW School of Mining Research Grant .
Raval S ( 2011). Provision for spectroradiometer and image processing software. UNSW School of Mining Laboratory Equipment Grant .

My Qualifications

PhD Mining Engineering ( 2008 – 2011) from the University of New South Wales, Sydney, Australia
Bachelor of Mining Engineering (1991-1994) from the Guru Ghasidas University, Bilaspur, India
"Environment Champion" – the title bestowed by the student society (MERESOC) (2022).
UNSW Vice Chancellor’s Awards for Outstanding Contributions to Student Learning (2020).
Postgraduate Coursework Teaching Excellence Award (2020) by UNSW Engineering,
The International Tim Show Award for Innovation in Teaching and Learning (2018) presented by the Society of Mining Professors (SOMP).
Best Lecturer Award 2017 judged by the Mining Society (MINSOC) - A student-run society for Mining Engineering Undergraduates and Postgraduates at UNSW.
School of Mining Engineering Teaching Award (2015) judged by the peers.
The Best Teacher Award (2013) judged by the IEEE conference committee for MOOC, Innovation and Technology in Education (MITE).
The Endeavour Postgraduate Award funded by the Australian Government (2008).
The inaugural Australian Centre for Sustainable Mining Practices (ACSMP) scholarship award (2010).
Finalist for the Dean’s Award for Excellence in Postgraduate Research , a poster competition at UNSW (2010).

My Research Activities

I have developed an interdisciplinary research approach that is capable of addressing wider issues of sustainable mining practices and innovation in mining.

I am currently engaged in the following TWO core research domains:

Industrial Automation
Optimising LiDAR for specific application, both at hardware and software levels.
Applying AI on point cloud for automated data analytics.
Sensor fusion (multispectral, hyperspectral, LiDAR)
Rapid characterisation of critical minerals (LIBS, PGNAA)
Environmental Monitoring
Quantification of Methane Emissions from Coal Mines and Landfills.
Quantification of environmental impact plus rehabilitation success through remote sensing
Assessment of mining impacts on surrounding ecosystem (water, soil, air, flora, and fauna) through satellite, drone, handheld, ground-based sensors (multispectral, hyperspectral, thermal, radar)
Mine closure (completion criteria, GIS based data analytics)
Environmental considerations of space resource extraction

My Research Supervision

Supervision keywords, areas of supervision.

Low-cost, long-lifespan sensors for underground mines and tunnels as well as infrastructures
IoT sensing platforms
Robotics and Autonomous Systems for Data Collection
AI assisted automation in geotechnical analysis
Visualisation and digital twin (Mixed Reality)
Remote sensing-based monitoring of mine environmental impacts
Quantitative and qualitative GIS based data analytics for mine rehabilitation

Currently supervising

Charles Baylis (Topic: Optimising geotechnical data collection for underground metalliferous mines, Other supervisor: Ismet Canbulat)
Dibyayan Patra (Topic: Mine Internet of Things, Other supervisors: Ismet Canbulat & Bikram Banerjee).
Sureka Thiruchittampalam (Topic: Development of Advance Remote Sensing based Monitoring Protocols for Mining, Other supervisors: Nancy Glenn & Bikram Banerjee).
Jiachao Ge (Topic: CO2 storage in saline aquifers, Other supervisors: Furqan Le-Hussain & Stuart Clark)
Zain Rasheed (Topic: Effect of CO2 injectivity on CO2 sequestration and enhanced oil recovery, Other supervisors: Furqan Le-Hussain & Peter Nea l)

Graduated PhDs:

Timothy Pelech (Topic: Off-Earth Mining, Other supervisors: Serkan Saydam, Lina Yao & Andrew Dempster). My role: Secondary Supervisor.
Sarvesh Kumar Singh (Jan 2022 - Recipient of the Dean’s Award). Thesis Title: Optimising mobile laser scanning for underground mines. My role: Primary Supervisor.
Jessica Dallas (Aug 2021 - Recipient of the Dean’s Award). Thesis Title: Environmental considerations of space resource extraction. My role: Joint Supervisor.
Michael Dello-Iacovo (Nov 2020). Thesis Title: Off-Earth seismic: Viability and examination of use for measuring geophysical, geomechanical and structural properties of off-Earth bodies. My role: Secondary Supervisor.
Bikram Pratap Banerjee (2018). Thesis Title: Development of UAV-based hyperspectral and LiDAR systems for environmental monitoring. My role: Primary Supervisor.

My Teaching

I am currently coordinating following 4 courses besides delivering specialised guest lectures to other 5 UG&PG courses.

Socio-Environmental Aspects of Mining (MINE3910): 3rd year undergraduate core course.
Environmental Management for the Mining Industry (MINE8780): Fully distance based postgraduate course.
Surface Mining Systems (MINE3440): Project based 3rd year undergraduate elective course
Mining Systems (MINE3430): 3rd year undergraduate core course.

Publications

Journal articles 43
Conference Papers 27
Conference Posters 3
Conference Presentations 24
Conference Abstracts 3
Theses / Dissertations 1
Preprints 8

ORCID as entered in ROS

Computer Science > Computer Vision and Pattern Recognition

Title: mining supervision for dynamic regions in self-supervised monocular depth estimation.

Abstract: This paper focuses on self-supervised monocular depth estimation in dynamic scenes trained on monocular videos. Existing methods jointly estimate pixel-wise depth and motion, relying mainly on an image reconstruction loss. Dynamic regions1 remain a critical challenge for these methods due to the inherent ambiguity in depth and motion estimation, resulting in inaccurate depth estimation. This paper proposes a self-supervised training framework exploiting pseudo depth labels for dynamic regions from training data. The key contribution of our framework is to decouple depth estimation for static and dynamic regions of images in the training data. We start with an unsupervised depth estimation approach, which provides reliable depth estimates for static regions and motion cues for dynamic regions and allows us to extract moving object information at the instance level. In the next stage, we use an object network to estimate the depth of those moving objects assuming rigid motions. Then, we propose a new scale alignment module to address the scale ambiguity between estimated depths for static and dynamic regions. We can then use the depth labels generated to train an end-to-end depth estimation network and improve its performance. Extensive experiments on the Cityscapes and KITTI datasets show that our self-training strategy consistently outperforms existing self/unsupervised depth estimation methods.

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82 Data Mining Essay Topic Ideas & Examples

🏆 best data mining topic ideas & essay examples, 💡 good essay topics on data mining, ✅ most interesting data mining topics to write about.

Disadvantages of Using Web 2.0 for Data Mining Applications This data can be confusing to the readers and may not be reliable. Lastly, with the use of Web 2.
Data Mining Classifiers: The Advantages and Disadvantages One of the major disadvantages of this algorithm is the fact that it has to generate distance measures for all the recorded attributes. We will write a custom essay specifically for you by our professional experts 808 writers online Learn More
Data Warehouse and Data Mining in Business The circumstances leading to the establishment and development of the concept of data warehousing was attributed to the fact that failure to have a data warehouse led to the need of putting in place large […]
Summary of C4.5 Algorithm: Data Mining 5 algorism: Each record from set of data should be associated with one of the offered classes, it means that one of the attributes of the class should be considered as a class mark.
The Data Mining Method in Healthcare and Education Thus, I would use data mining in both cases; however, before that, I would discover a way to improve the algorithms used for it.
Data Mining Tools and Data Mining Myths The first problem is correlated with keeping the identity of the person evolved in data mining secret. One of the major myths regarding data mining is that it can replace domain knowledge.
Hybrid Data Mining Approach in Healthcare One of the healthcare projects that will call for the use of data mining is treatment evaluation. In this case, it is essential to realize that the main aim of health data mining is to […]
Terrorism and Data Mining Algorithms However, this is a necessary evil as the nation’s security has to be prioritized since these attacks lead to harm to a larger population compared to the infringements.
Data Mining and Its Major Advantages Thus, it is possible to conclude that data mining is a convenient and effective way of processing information, which has many advantages.
Transforming Coded and Text Data Before Data Mining However, to complete data mining, it is necessary to transform the data according to the techniques that are to be used in the process.
Data Mining and Machine Learning Algorithms The shortest distance of string between two instances defines the distance of measure. However, this is also not very clear as to which transformations are summed, and thus it aims to a probability with the […]
Data Mining in Social Networks: Linkedin.com One of the ways to achieve the aim is to understand how users view data mining of their data on LinkedIn.
Ethnography and Data Mining in Anthropology The study of cultures is of great importance under normal circumstances to enhance the understanding of the same. Data mining is the success secret of ethnography.
Issues With Data Mining It is necessary to note that the usage of data mining helps FBI to have access to the necessary information for terrorism and crime tracking.
Large Volume Data Handling: An Efficient Data Mining Solution Data mining is the process of sorting huge amount of data and finding out the relevant data. Data mining is widely used for the maintenance of data which helps a lot to an organization in […]
Data Mining and Analytical Developments In this era where there is a lot of information to be handled at ago and actually with little available time, it is necessarily useful and wise to analyze data from different viewpoints and summarize […]
Levi’s Company’s Data Mining & Customer Analytics Levi, the renowned name in jeans is feeling the heat of competition from a number of other brands, which have come upon the scene well after Levi’s but today appear to be approaching Levi’s market […]
Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence This paper aims to review the application of A.I.in the context of blockchain finance by examining scholarly articles to determine whether the A.I.algorithm can be used to analyze this financial market.
Data Mining in Healthcare: Applications and Big Data Analyze Big data analysis is among the most influential modern trends in informatics and it has applications in virtually every sphere of human life.
“Data Mining and Customer Relationship Marketing in the Banking Industry“ by Chye & Gerry First of all, the article generally elaborates on the notion of customer relationship management, which is defined as “the process of predicting customer behavior and selecting actions to influence that behavior to benefit the company”.
Data Mining Techniques and Applications The use of data mining to detect disturbances in the ecosystem can help to avert problems that are destructive to the environment and to society.
Ethical Data Mining in the UAE Traffic Department The research question identified in the assignment two is considered to be the following, namely whether the implementation of the business intelligence into the working process will beneficially influence the work of the Traffic Department […]
Canadian University Dubai and Data Mining The aim of mining data in the education environment is to enhance the quality of education for the mass through proactive and knowledge-based decision-making approaches.
Data Mining and Customer Relationship Management As such, CRM not only entails the integration of marketing, sales, customer service, and supply chain capabilities of the firm to attain elevated efficiencies and effectiveness in conveying customer value, but it obliges the organization […]
E-Commerce: Mining Data for Better Business Intelligence The method allowed the use of Intel and an example to build the study and the literature on data mining for business intelligence to analyze the findings.
Ethical Implications of Data Mining by Government Institutions Critics of personal data mining insist that it infringes on the rights of an individual and result to the loss of sensitive information.
Data Mining Role in Companies The increasing adoption of data mining in various sectors illustrates the potential of the technology regarding the analysis of data by entities that seek information crucial to their operations.
Data Mining: Concepts and Methods Speed of data mining process is important as it has a role to play in the relevance of the data mined. The accuracy of data is also another factor that can be used to measure […]
Data Mining Technologies According to Han & Kamber, data mining is the process of discovering correlations, patterns, trends or relationships by searching through a large amount of data that in most circumstances is stored in repositories, business databases […]
Data Mining: A Critical Discussion In recent times, the relatively new discipline of data mining has been a subject of widely published debate in mainstream forums and academic discourses, not only due to the fact that it forms a critical […]
Commercial Uses of Data Mining Data mining process entails the use of large relational database to identify the correlation that exists in a given data. The principal role of the applications is to sift the data to identify correlations.
A Discussion on the Acceptability of Data Mining Today, more than ever before, individuals, organizations and governments have access to seemingly endless amounts of data that has been stored electronically on the World Wide Web and the Internet, and thus it makes much […]
Applying Data Mining Technology for Insurance Rate Making: Automobile Insurance Example
Applebee’s, Travelocity and Others: Data Mining for Business Decisions
Applying Data Mining Procedures to a Customer Relationship
Business Intelligence as Competitive Tool of Data Mining
Overview of Accounting Information System Data Mining
Applying Data Mining Technique to Disassembly Sequence Planning
Approach for Image Data Mining Cultural Studies
Apriori Algorithm for the Data Mining of Global Cyberspace Security Issues
Database Data Mining: The Silent Invasion of Privacy
Data Management: Data Warehousing and Data Mining
Constructive Data Mining: Modeling Consumers’ Expenditure in Venezuela
Data Mining and Its Impact on Healthcare
Innovations and Perspectives in Data Mining and Knowledge Discovery
Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Linking Data Mining and Anomaly Detection Techniques
Data Mining and Pattern Recognition Models for Identifying Inherited Diseases
Credit Card Fraud Detection Through Data Mining
Data Mining Approach for Direct Marketing of Banking Products
Constructive Data Mining: Modeling Argentine Broad Money Demand
Data Mining-Based Dispatching System for Solving the Pickup and Delivery Problem
Commercially Available Data Mining Tools Used in the Economic Environment
Data Mining Climate Variability as an Indicator of U.S. Natural Gas
Analysis of Data Mining in the Pharmaceutical Industry
Data Mining-Driven Analysis and Decomposition in Agent Supply Chain Management Networks
Credit Evaluation Model for Banks Using Data Mining
Data Mining for Business Intelligence: Multiple Linear Regression
Cluster Analysis for Diabetic Retinopathy Prediction Using Data Mining Techniques
Data Mining for Fraud Detection Using Invoicing Data
Jaeger Uses Data Mining to Reduce Losses From Crime and Waste
Data Mining for Industrial Engineering and Management
Business Intelligence and Data Mining – Decision Trees
Data Mining for Traffic Prediction and Intelligent Traffic Management System
Building Data Mining Applications for CRM
Data Mining Optimization Algorithms Based on the Swarm Intelligence
Big Data Mining: Challenges, Technologies, Tools, and Applications
Data Mining Solutions for the Business Environment
Overview of Big Data Mining and Business Intelligence Trends
Data Mining Techniques for Customer Relationship Management
Classification-Based Data Mining Approach for Quality Control in Wine Production
Data Mining With Local Model Specification Uncertainty
Employing Data Mining Techniques in Testing the Effectiveness of Modernization Theory
Enhancing Information Management Through Data Mining Analytics
Evaluating Feature Selection Methods for Learning in Data Mining Applications
Extracting Formations From Long Financial Time Series Using Data Mining
Financial and Banking Markets and Data Mining Techniques
Fraudulent Financial Statements and Detection Through Techniques of Data Mining
Harmful Impact Internet and Data Mining Have on Society
Informatics, Data Mining, Econometrics, and Financial Economics: A Connection
Integrating Data Mining Techniques Into Telemedicine Systems
Investigating Tobacco Usage Habits Using Data Mining Approach
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How does data mining work?

A standard data mining design begins with the appropriate business statement in the questionnaire, the appropriate data is collected to tackle it, and the data is prepared for the examination.
What happens in the earlier stages determines how successful the later versions are.
Data miners should assure the data quality they utilize as input for research because bad data quality results in poor outcomes.
Establishing a detailed understanding of the design factors, such as the present business scenario, the project’s main business goal, and the performance objectives.
Identifying the data required to address the problem as well as collecting this from all sorts of sources.
Addressing any errors and bugs, like incomplete or duplicate data, and processing the data in a suitable format to solve the research questions.
Algorithms are used to find patterns from data.
Identifying if or how another model’s output will contribute to the achievement of a business objective.
In order to acquire the optimum outcome, an iterative process is frequently used to identify the best method.
Getting the project’s findings suitable for making decisions in real-time

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Data Mining Tasks

Data mining finds application in many ways including description, Analysis, summarization of data, and clarifying the conceptual understanding by data description
And also prediction, classification, dependency analysis, segmentation, and case-based reasoning are some of the important data mining tasks
Regression – numerical data prediction (stock prices, temperatures, and total sales)
Data warehousing – business decision making and large-scale data mining
Classification – accurate prediction of target classes and their categorization
Association rule learning – market-based analytical tools that were involved in establishing variable data set relationship
Machine learning – statistical probability-based decision making method without complicated programming
Data analytics – digital data evaluation for business purposes
Clustering – dataset partitioning into clusters and subclasses for analyzing natural data structure and format
Artificial intelligence – human-based Data analytics for reasoning, solving problems, learning, and planning
Data preparation and cleansing – conversion of raw data into a processed form for identification and removal of errors

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How to work on a data mining thesis topic?

The following are the important stages or phases in developing data mining thesis topics.

First of all, you need to identify the present demand and address the question
The next step is defining or specifying the problem
Collection of data is the third step
Alternative solutions and designs have to be analyzed in the next step
The proposed methodology has to be designed
The system is then to be implemented

Usually, our experts help in writing codes and implementing them successfully without hassles . By consistently following the above steps you can develop one of the best data mining thesis topics of recent days. Furthermore, technically it is important for you to have a better idea of all the tasks and techniques involved in data mining about which we have discussed below

Data visualization
Neural networks
Statistical modeling
Genetic algorithms and neural networks
Decision trees and induction
Discriminant analysis
Induction techniques
Association rules and data visualization
Bayesian networks
Correlation
Regression analysis
Regression analysis and regression trees

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Furthermore, data mining strategies must be picked before instruments in order to prevent using strategies that do not align with the article’s true purposes.
The typical data mining strategy has always been to evaluate a variety of methodologies in order to select one which best fits the situation.
As previously said, there are some principles that may be used to choose effective strategies for data mining projects.
Since they are easy to handle and comprehend
They could indeed collaborate with definitional and parametric data
Tare unaffected by critical values, they could perhaps function with incomplete information
They could also expose various interrelationships and an absence of linear combinations
They could indeed handle noise in records
They can process huge amounts of data.
Decision trees, on the other hand, have significant drawbacks.
Many rules are frequently necessary for dependent variables or numerous regressions, and tiny changes in the data can result in very different tree architectures.

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Current methods in Data Mining

Prediction of data (time series data mining)
Discriminant and cluster analysis
Logistic regression and segmentation

Our technical specialists and technicians usually give adequate accurate data, a thorough and detailed explanation, and technical notes for all of these processes and algorithms. As a result, you can get all of your questions answered in one spot. Our technical team is also well-versed in current trends, allowing us to provide realistic explanations for all new developments. We will now talk about the latest data mining trends

Latest Trending Data Mining Thesis Topics

Visual data mining and data mining software engineering
Interaction and scalability in data mining
Exploring applications of data mining
Biological and visual data mining
Cloud computing and big data integration
Data security and protecting privacy in data mining
Novel methodologies in complex data mining
Data mining in multiple databases and rationalities
Query language standardization in data mining
Integration of MapReduce, Amazon EC2, S3, Apache Spark, and Hadoop into data mining

These are the recent trends in data mining. We insist that you choose one of the topics that interest you the most. Having an appropriate content structure or template is essential while writing a thesis . We design the plan in a chronological order relevant to the study assessment with this in mind. The incorporation of citations is one of the most important aspects of the thesis. We focus not only on authoring but also on citing essential sources in the text. Students frequently struggle to deal with appropriate proposals when commencing their thesis. We have years of experience in providing the greatest study and data mining thesis writing services to the scientific community, which are promptly and widely acknowledged. We will now talk about future research directions of research in various data mining thesis topics

Future Research Directions of Data Mining

The potential of data mining and data science seems promising, as the volume of data continues to grow.
It is expected that the total amount of data in our digital cosmos will have grown from 4.4 zettabytes to 44 zettabytes.
We’ll also generate 1.7 gigabytes of new data for every human being on this planet each second.
Mining algorithms have completely transformed as technology has advanced, and thus have tools for obtaining useful insights from data.
Only corporations like NASA could utilize their powerful computers to examine data once upon a time because the cost of producing and processing data was simply too high.
Organizations are now using cloud-based data warehouses to accomplish any kinds of great activities with machine learning, artificial intelligence, and deep learning.

The Internet of Things as well as wearable electronics, for instance, has transformed devices to be connected into data-generating engines which provide limitless perspectives into people and organizations if firms can gather, store, and analyze the data quickly enough. What are the aspects to be remembered for choosing the best data mining thesis topics?

An excellent thesis topic is a broad concept that has to be developed, verified, or refuted.
Your thesis topic must capture your curiosity, as well as the involvement of both the supervisor and the academicians.
Your thesis topic must be relevant to your studies and should be able to withstand examination.

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Trending Data Mining Research Thesis Topics

Research Topics in Data Mining

Handling cost-effective, unbalanced non-static data
Issues related to data mining and their solutions
Network settings in data mining and ensuring privacy, security, and integrity of data
Environmental and biological issues in data mining
Complex data mining and sequential data mining (time series data)
Data mining at higher dimensions
Multi-agent data mining and distributed data mining
High-speed data mining
Development of unified data mining theory

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Dissertations / Theses on the topic 'Data mining – Research'

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Consult the top 50 dissertations / theses for your research on the topic 'Data mining – Research.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.

Shioda, Romy 1977. "Integer optimization in data mining." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/17579.

Zhang, Ya Klein Cerry M. "Association rule mining in cooperative research." Diss., Columbia, Mo. : University of Missouri--Columbia, 2009. http://hdl.handle.net/10355/6540.

Kardell, Oliver [Verfasser]. "DIA data mining in colorectal cancer research / Oliver Kardell." Hamburg : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2020. http://d-nb.info/1223621022/34.

Fang, Yao-chuen. "Scientific research impact and data mining applications in hydrogeology." Connect to this title online, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1092774125.

Shao, Huijuan. "Temporal Mining Approaches for Smart Buildings Research." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/84349.

Geltz, Rebecca L. "Using Data Mining to Model Student Success." Youngstown State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1264697709.

Flietstra, Bryan C. "A data mining approach for acoustic diagnosis of cardiopulmonary disease." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45400.

Lavelle, Stephen J. "Fabricating synthetic data in support of training for domestic terrorist activity data mining research." Thesis, Monterey, California. Naval Postgraduate School, 2010. http://hdl.handle.net/10945/5196.

Snyder, Ashley M. (Ashley Marie). "Data mining and visualization : real time predictions and pattern discovery in hospital emergency rooms and immigration data." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61199.

Knoetze, Ronald Morgan. "The mining and visualisation of application services data." Thesis, Nelson Mandela Metropolitan University, 2005. http://hdl.handle.net/10948/451.

Houston, Andrea L., Hsinchun Chen, Susan M. Hubbard, Bruce R. Schatz, Tobun Dorbin Ng, Robin R. Sewell, and Kristin M. Tolle. "Medical Data Mining on the Internet: Research on a Cancer Information System." Kluwer, 1999. http://hdl.handle.net/10150/106388.

Wu, Qionglin 1964. "Data mining and knowledge discovery in financial research : empirical investigations into currency." Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=31560.

Burley, Keith Martin. "Data mining techniques in higher education research : the example of student retention." Thesis, Sheffield Hallam University, 2006. http://shura.shu.ac.uk/19412/.

Yuan, Fan. "Modeling and computational strategies for medical decision making." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54857.

Liu, Yang. "Data mining methods for single nucleotide polymorphisms analysis in computational biology." HKBU Institutional Repository, 2011. http://repository.hkbu.edu.hk/etd_ra/1287.

Gadaleta, Emanuela. "A multidisciplinary computational approach to model cancer-omics data : organising, integrating and mining multiple sources of data." Thesis, Queen Mary, University of London, 2015. http://qmro.qmul.ac.uk/xmlui/handle/123456789/8141.

Domm, Maryanne. "Mathematical programming in data mining: Models for binary classification with application to collusion detection in online gambling." Diss., The University of Arizona, 2003. http://hdl.handle.net/10150/280270.

Pafilis, Evangelos. "Web-based named entity recognition and data integration to accelerate molecular biology research." [S.l. : s.n.], 2008. http://nbn-resolving.de/urn:nbn:de:bsz:16-opus-89706.

Kamenieva, Iryna. "Research Ontology Data Models for Data and Metadata Exchange Repository." Thesis, Växjö University, School of Mathematics and Systems Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-6351.

For researches in the field of the data mining and machine learning the necessary condition is an availability of various input data set. Now researchers create the databases of such sets. Examples of the following systems are: The UCI Machine Learning Repository, Data Envelopment Analysis Dataset Repository, XMLData Repository, Frequent Itemset Mining Dataset Repository. Along with above specified statistical repositories, the whole pleiad from simple filestores to specialized repositories can be used by researchers during solution of applied tasks, researches of own algorithms and scientific problems. It would seem, a single complexity for the user will be search and direct understanding of structure of so separated storages of the information. However detailed research of such repositories leads us to comprehension of deeper problems existing in usage of data. In particular a complete mismatch and rigidity of data files structure with SDMX - Statistical Data and Metadata Exchange - standard and structure used by many European organizations, impossibility of preliminary data origination to the concrete applied task, lack of data usage history for those or other scientific and applied tasks.

Now there are lots of methods of data miming, as well as quantities of data stored in various repositories. In repositories there are no methods of DM (data miming) and moreover, methods are not linked to application areas. An essential problem is subject domain link (problem domain), methods of DM and datasets for an appropriate method. Therefore in this work we consider the building problem of ontological models of DM methods, interaction description of methods of data corresponding to them from repositories and intelligent agents allowing the statistical repository user to choose the appropriate method and data corresponding to the solved task. In this work the system structure is offered, the intelligent search agent on ontological model of DM methods considering the personal inquiries of the user is realized.

For implementation of an intelligent data and metadata exchange repository the agent oriented approach has been selected. The model uses the service oriented architecture. Here is used the cross platform programming language Java, multi-agent platform Jadex, database server Oracle Spatial 10g, and also the development environment for ontological models - Protégé Version 3.4.

Chiang, H.-Y., and 蔣筱雲. "A Research of Compensating Missing Data by Data Mining." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/42484926395418255313.

Chou-ChengChen and 陳疇丞. "Application of text mining and data mining in cancer research." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/5m9x87.

Cahng, Feng-Hao, and 張峰豪. "Research on machine utilization using data mining." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/9w95bv.

Waranashiwar, Shruti Dilip. "Interactive pattern mining of neuroscience data." Thesis, 2014. http://hdl.handle.net/1805/3878.

Liu, Ying-Ching, and 劉應慶. "The Initial Research of Using Data Mining Techniques for Data Classification Optimization." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/07565943030329965805.

Wen, Hao Liao, and 廖文豪. "The Research of Value Analysis Applying Data Mining Technique." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/10327866038049761206.

Tai, Chuntien, and 戴俊典. "A Research of Data Mining in Warfarin Dosage Decisions." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/12554411984456215497.

Wang, Dung-Chi, and 王東祈. "A Research on Mining Frequent Itemsets in Data Stream." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/4vne38.

LEE, YUN-FANG, and 李雲芳. "Research on Functional Clothing Recommendations by Using Data Mining." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/ymwg3a.

Song, Zi-kong, and 宋子康. "A research on mining association rules in data stream." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/sx7u24.

Tsai, Yi-Ting, and 蔡依庭. "Application of Data Mining Techniques to Film Market Research." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/16605744340914078907.

Lin, Shih-Hau, and 林施豪. "Data Mining in Bioinformatic Contents Research - with Biological Genetic Database." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/50107356145725150045.

Lin, De-Fong, and 林德豐. "Applying Data Mining Technology in Network Behavior Anomaly Performance Research." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/22513426476489517747.

ISUN, WU YI, and 吳毅尊. "Research of Agent Technology on Data Mining of Enterprise's Knowledge." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/15491769030768636621.

Wu, Tzu-Cheng, and 吳自晟. "The Research of Data Mining Techniques applied to Insurance CRM." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/3362mt.

Chiu, Jheng-Ci, and 邱政琦. "Research on the Predictions of Fire Incidents with Data Mining." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/23dkp7.

Wu, Yen-Lin, and 吳彥霖. "A Research of Using Data Mining Techniques in Retrieving Researchers." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/why3sw.

Hung, Pin-Kai, and 洪斌凱. "Using data mining methodology to research C company accessory market." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/25149984457867750574.

SU, YUNG-HSIANG, and 蘇詠翔. "Data Mining Methods for the Research of E-stock Transaction." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/68222088478818233241.

YU, LI-HSUAN, and 余立宣. "Research on the Repairing Information Technology Devices Using Data Mining." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/76957267545832294507.

Hsieh, Ju-Cheng, and 謝儒誠. "Research of using data mining technique for automatic documents clustering." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/u47m93.

Chang, Yu-Jen, and 張于仁. "Apply Data Mining Integrated with Hierarchical Learning Architecture in the Research of Data Classification." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/34876736036020662364.

Wu, Tai-Long, and 吳台隆. "A Research of Taiwan’s Vessel Smuggling Analysis-Applied Data-Mining Technique." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/92259244989853093179.

Chang, Yung-Ku, and 張永固. "Data Mining on Target Marketing Research: An Example of Telecommunication Users." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/97687487797728422391.

Huang, Ya-Fang, and 黃雅芳. "Using Data Mining to Assess the Research of Coronary Artery Disease." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/99992822280891583455.

WANG, CHEN YUNG, and 陳永旺. "Apply data mining technology in the index fund investment strategy research." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/66307548507508554222.

Liao, Ko-Hsuan, and 廖克軒. "Campus Electricity Meter Data Mining and Application of Visualisation Initial Research." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/v9scpf.

Wang, Hsi-Chin, and 王璽欽. "The Research of Using Data Mining Technology in The Patent Analysis." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/dz4g92.

Madsen, Jacob Hastrup. "Outlier detection for improved clustering : empirical research for unsupervised data mining." Master's thesis, 2018. http://hdl.handle.net/10362/34464.

Bonates, Tiberius. "Optimization in logical analysis of data." 2007. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.15788.

Lin, Tinghao, and 林鼎浩. "Research on Constructing a Data Mining Framework for Semiconductor Manufacturing Data and the Empirical Study." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/00819160195077260729.

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Distance Based Pattern Driven Mining for Outlier Detection in High Dimensional Big Dataset

Detection of outliers or anomalies is one of the vital issues in pattern-driven data mining. Outlier detection detects the inconsistent behavior of individual objects. It is an important sector in the data mining field with several different applications such as detecting credit card fraud, hacking discovery and discovering criminal activities. It is necessary to develop tools used to uncover the critical information established in the extensive data. This paper investigated a novel method for detecting cluster outliers in a multidimensional dataset, capable of identifying the clusters and outliers for datasets containing noise. The proposed method can detect the groups and outliers left by the clustering process, like instant irregular sets of clusters (C) and outliers (O), to boost the results. The results obtained after applying the algorithm to the dataset improved in terms of several parameters. For the comparative analysis, the accurate average value and the recall value parameters are computed. The accurate average value is 74.05% of the existing COID algorithm, and our proposed algorithm has 77.21%. The average recall value is 81.19% and 89.51% of the existing and proposed algorithm, which shows that the proposed work efficiency is better than the existing COID algorithm.

Implementation of Data Mining Technology in Bonded Warehouse Inbound and Outbound Goods Trade

For the taxed goods, the actual freight is generally determined by multiplying the allocated freight for each KG and actual outgoing weight based on the outgoing order number on the outgoing bill. Considering the conventional logistics is insufficient to cope with the rapid response of e-commerce orders to logistics requirements, this work discussed the implementation of data mining technology in bonded warehouse inbound and outbound goods trade. Specifically, a bonded warehouse decision-making system with data warehouse, conceptual model, online analytical processing system, human-computer interaction module and WEB data sharing platform was developed. The statistical query module can be used to perform statistics and queries on warehousing operations. After the optimization of the whole warehousing business process, it only takes 19.1 hours to get the actual freight, which is nearly one third less than the time before optimization. This study could create a better environment for the development of China's processing trade.

Multi-objective economic load dispatch method based on data mining technology for large coal-fired power plants

User activity classification and domain-wise ranking through social interactions.

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A data mining analysis of COVID-19 cases in states of United States of America

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Capturing Dynamics of Information Diffusion in SNS: A Survey of Methodology and Techniques

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The Influence of E-book Teaching on the Motivation and Effectiveness of Learning Law by Using Data Mining Analysis

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DRESDEN, Germany � In the gray villa at No. 4 Angelikastrasse here, perched on a hill overlooking the Elbe River, a young major in the Soviet secret police spent the last half of the 1980s recruiting people to spy on the West.

Vladimir Putin looked for East Germans who had a plausible reason to travel abroad, such as professors, journalists, scientists and technicians, for whom there were acceptable "legends," or cover stories.

The legend was often a business trip, during which the agents could covertly link up with other spies permanently stationed in the West. According to German intelligence specialists who described Putin's task, the goal was stealing Western technology or NATO secrets. A newly revealed document shows Putin was trying to recruit agents to be trained in "wireless communications." But for what purpose is not clear.

Putin defends the Soviet-era intelligence service to this day. In recent comments to a writers' group in Moscow, he even seemed to excuse its role in dictator Joseph Stalin's brutal purges, saying it would be "insincere" for him to assail the agency where he worked for so many years. Fiercely patriotic, Putin once said he could not read a book by a Soviet defector because "I don't read books by people who have betrayed the Motherland."

Such is the professional background of the man who emerged unexpectedly last month as Russia's new leader. Today, Putin is acting president and the clear favorite to win the March 26 election and a four-year presidential term. Yet a review of his career shows that Putin previously has thrived in closed worlds, first as an intelligence agent and later in city government.

Until he was handpicked in August by then-President Boris Yeltsin to become prime minister, Putin had never been a public figure. He spent 17 years as a mid-level agent in the Soviet KGB's foreign intelligence wing, rising only to the rank of lieutenant colonel. Later, as an aide to a prickly, controversial mayor of St. Petersburg, Russia's second-largest city and Putin's home town, he made a point of staying in the background.

Yet Putin's career also suggests that he witnessed firsthand the momentous finale of the Cold War. From the front line in East Germany, Putin saw how the centrally planned economies of the East staggered to disintegration. In St. Petersburg, he had a taste of the ragged path of Russia's early transition to a free-market, democratic system.

What Putin has taken from these experiences is not entirely clear. He has embraced the conviction that "there is no alternative" to market democracy, and soberly acknowledged Russia's economic weaknesses. But he also has expressed enthusiasm for reasserting the role of a strong state. He has said the Russian economy has become "criminalized," but so far only hinted that he would tackle the powerful tycoons who lord over it. Putin has vowed Russia will not revert to totalitarianism, but he has not demonstrated much skill working with Russia's fledgling, competitive political system.

Putin has never campaigned for office, and he told an interviewer two years ago he found campaigns distasteful. "One has to be insincere and promise something which you cannot fulfill," he said. "So you either have to be a fool who does not understand what you are promising, or deliberately be lying."

Putin, an only son, was born in Leningrad, now St. Petersburg, to a factory foreman and his wife in 1952, shortly before Stalin's death. He entered Leningrad State University's law department in 1970, but the Soviet Union was not a state governed by the rule of law. Valery Musin, then a university lecturer, said the law department was a training ground for the KGB, the police and the bureaucracy.

Putin later recalled that the KGB targeted him for recruitment even before he graduated in 1975. "You know, I even wanted it," he said of joining the KGB. "I was driven by high motives. I thought I would be able to use my skills to the best for society."

After a few years spying on foreigners in Leningrad, Putin was summoned to Moscow in the early 1980s to attend the elite foreign intelligence training institute, and then was assigned to East Germany. He arrived in Dresden at age 32 when East Germany was a major focus of Moscow's attention. The German Democratic Republic was home to 380,000 Soviet troops and Soviet intermediate-range missiles. Berlin was a constant source of Cold War tensions and intrigue.

At the time, several thousand KGB officers reported to a headquarters at Karlshorst, outside Berlin; Soviet military intelligence also was stationed in East Germany. But the biggest intelligence operation was the East German secret police, the Stasi, who monitored hundreds of thousands of citizens and kept millions of documents on file.

The broad Stasi network was used often by the KGB, and the raw intelligence sent directly to Moscow. The East German dictatorship, headed in those years by Erich Honecker, remained steadfastly rigid even as Soviet leader Mikhail Gorbachev was beginning to experiment with political and economic reforms at home.

In Dresden, the KGB outpost at No. 4 Angelikastrasse was located directly across the street from the city's main Stasi headquarters. The Stasi poked into every aspect of life; in Dresden alone, the documents they preserved on citizens now stretch nearly seven miles in the archives here, according to Konrad Felber, a spokesman for the commission that maintains the documents.

There is little information about Putin's specific tasks in Dresden, but specialists and documents point to several assignments, including recruiting and preparing agents. The work likely involved Robotron, a Dresden-based electronics conglomerate, which was the Eastern Bloc's largest mainframe computer maker and a microchip research center.

At the time, a major KGB effort was underway to steal Western technology. The Soviet Bloc was so far behind, according to a German specialist, that agents at Stasi headquarters often preferred to work on a Western-made Commodore personal computer rather than on their office mainframe.

The presence of Robotron may have provided Putin with legends for sending technicians to the West, or for recruiting Westerners who came to East Germany from such large electronics companies as Siemans or IBM. Putin may also have been interested in military electronics and intelligence about NATO from informers in the West.

The KGB was known to the Stasi as "the friends," and it relied on the Stasi for support. For years, the Stasi prepared fake passports and driver's licenses for "the friends" to create cover stories for agents. Tens of thousands of people in East Germany were "registered," or marked in the secret files of the Stasi, as being "of interest" to the KGB. According to the German specialist, some were marked because the KGB was searching for people with plausible cover stories for trips abroad.

"You needed a guy with a background that looked good, a professor who had to go to an international conference or had to do business in the West," he said. "You needed such a legend."

Later, Erich Mielke, the East German state security minister, tried to rein in the Stasi's assistance to the KGB, which led to one case in which Putin is known to have been involved. On March 29, 1989, Maj. Gen. Horst Bohm, then the head of the Dresden branch of the Stasi, wrote a memo to Putin's boss, Gen. Vladimir Shirokov. While some names in the letter are blacked out, sources said the case involved Putin.

Bohm complained the KGB was recruiting reservists from the East German military who had gone into civilian life. They were being recruited "frequently" for temporary, special missions, Bohm said.

One reservist was called in, he said, to the Dresden "recruitment center" and was sent to talk with two Soviet civilians. "These talks included the issue of special training for wireless communications and also a short mission once each quarter of the year," the letter says. But Bohm complained that the agent was already working for the Stasi and urged the KGB to keep its hands off. "It is not possible" to recruit the East German army reservists for wireless communications training, he insisted.

Bohm later committed suicide, but one of his aides, Horst Jemlich, said in a brief telephone interview that the KGB was interested in procuring Western technology.

A puzzling and unexplained aspect of the Bohm letter is a reference to Soviet "military intelligence," which was a different agency from the KGB, to which Putin belonged. It is possible Putin was targeting Western military operations.

Putin also turned to the Stasi for help with routine logistics, such as obtaining a telephone � they were strictly controlled � and apartments. Putin was formally assigned to run a Soviet-German "friendship house" in Leipzig and carried out the duties, but this apparently was his own cover story. Intelligence specialists and political scientists said Putin may have had a political assignment to make contact with East Germans who were sympathetic to Gorbachev, such as the Dresden party leader Hans Modrow, in case the Honecker regime collapsed.

Putin's work with the Stasi won him a bronze medal in November 1987 from the East German security service, but the reasons for the award are unknown. It was described by one source as the next level up from the lowest, basic award for service.

Clearly, Putin was on the seam of East-West confrontation at the end of the Cold War, and the lessons were self-evident. In East Germany, Putin "must have noticed the system did not work anymore," said the German specialist. "If he was not stupid he would have noticed the East Germans were the losers of economic history."

The Soviet economy was also in trouble. Yuri Andropov, the KGB boss and later Soviet leader, had responded in the early 1980s by trying to impose more discipline on the ailing system, and many in the KGB shared his hope it could be saved from within. Others thought this to be unrealistic and believed the system itself would have to be junked. Putin, in a newspaper interview last year, hinted that he believed the system could have been salvaged. He said that "few people understand the magnitude of the catastrophe that happened late in the 1980s when the Communist Party had failed to modernize the Soviet Union."

When Putin returned to St. Petersburg, he took a job for a year and a half as assistant to the rector of the university, dealing with "international relations." However, that was partly a cover story. He was still working for the KGB, recruiting or spying on students. Putin acknowledged recently that he was "a KGB officer under the roof, as we say," noting that the rector knew about it.

Putin told a journalist, Natalya Nikiforova, that he did not move up higher in the KGB ranks because he did not want to move his family to Moscow. "I have two small children and old parents," he said. "They are over 80, and we all live together. They survived the blockade during the war. How could I take them from the place they were born in? I could not abandon them."

Putin also said then that he wanted to write a dissertation "on a subject I always knew and understood, I mean international private law." Musin said Putin came to him to make preparations for the dissertation but then dropped it when he got reacquainted with one of his old law professors, Anatoly Sobchak.

Sobchak, a leader in the first wave of democratic reformers in the Gorbachev years, was elected chairman of the Soviet-era Leningrad council. Putin quit the KGB, at the rank of lieutenant colonel, to work as Sobchak's aide. In 1991, the city governance system was changed, and Sobchak became St. Petersburg's first post-Soviet elected mayor.

Sobchak, like many of the early democrats, "was not prepared to govern," recalled journalist Sergei Shelin of New Times magazine. Sobchak constantly collided with members of the newly renamed legislature, the city Duma. Putin often was dispatched to repair relations. "Sobchak often asked Putin to go to the deputies," recalled Mikhail Amosov, a member of the Yabloko party. "Sobchak had bad relations with the lawmakers. There were always frictions. Sobchak always wanted to put them in their place; he treated them like an enemy force."

Putin quietly played a key role for Sobchak at the moment of the 1991 Soviet coup attempt. Sobchak, in Moscow at that moment, vowed to defend Yeltsin and fight the coup, and took the risky step of flying back to his city to oppose the putsch. Putin, with good ties in the local security services, showed up at the airport with armed guards to protect Sobchak, who was potentially vulnerable as a leading democrat.

In the early days of the new Russia, Putin headed a committee to woo overseas companies to St. Petersburg. But the city primarily needed humanitarian aid. "There was no food in the city at all," recalled Marina Salye, who was then a member of the legislature's food committee. "There was no money. Barter was the only way � say, metals for potatoes and meat."

St. Petersburg was a port and military city, and the state-owned shipbuilding and defense factories were stocked with precious metals. Salye said contracts were signed to trade metals for food, but she discovered the metals had been sold at discount prices, the food prices were inflated, and the food never arrived. Then it turned out that front companies had taken the profits and disappeared. Salye said she thinks Putin "was manipulating these contracts and was directly involved. But it hasn't been proved."

Salye confronted Putin, she recalled, but he brushed off her inquiries. "Everything is correct," she said he told her. "You are just making up things." Salye demanded an investigation, which was referred to a Moscow auditing commission and then dropped without explanation.

Putin, who speaks German, brought some companies to St. Petersburg, including German banks. A currency exchange was opened, and hotels were privatized. "All the work we did on privatization was supported by Putin, and not everyone was for it," recalled Sergei Belyaev, a former deputy mayor and later a member of the Russian parliament. But St. Petersburg never lived up to Sobchak's dream of becoming an international financial center. Moscow attracted far more foreign investment, while St. Petersburg lagged.

Putin's influence grew under Sobchak, but he remained in the shadows. "In the Petersburg days, it was always other people in front of the television cameras," said Igor Artemyev, leader of the Yabloko party. "Almost all the other vice mayors lined up next to the boss. Putin was always in the farthest corner."

After Sobchak was defeated in 1996, Putin left for Moscow. There, for reasons which remain largely unexplained, he suddenly moved onto a remarkably fast career track. After first serving on the Kremlin staff, he became director of the Federal Security Service, the domestic successor to the KGB, in 1998, and later added duties as head of the Kremlin Security Council. He was picked for prime minister last August because he appears to have impressed Yeltsin's inner circle and friendly tycoons, who were scrambling to find a premier and a potential Yeltsin successor.

During the same period, Putin apparently somehow found time to complete a postgraduate dissertation, which usually takes three years of study. He got a prestigious "candidate of science" degree, the equivalent of a PhD, from the Mining Institute in St. Petersburg in June 1997, a time when he was also working in the Kremlin.

Earlier, Putin had said he wanted to research international private law, but his 218-page dissertation was completely different. The title is "Strategic Planning of the Renewal of the Minerals-Raw Materials Base of the Region in Conditions of the Formation of Market Relations." Much of the document is a discussion about the cost-effectiveness of building a port and roads in St. Petersburg, and offers little insight into Putin's views of the market economy. The Mining Institute recently refused to show Putin's thesis to a reporter. When a copy of a summary was found by the reporter in the institute's library, officials snatched it away, saying it was private.

Mikhail Mednikov, a professor at the St. Petersburg Technical University, who was one of the "opponents" or reviewers at Putin's oral defense of his dissertation, said, "The defense was brilliant. It's a paper written by a market-oriented person."

But while Putin has promised to keep Russia on a market path, his critics worry about his commitment to Russia's young democracy. The institutions of a broad civil society � the press, political parties, free associations and others � are not yet well developed. The rule of law has not been well entrenched. And these weaknesses are, in part, a legacy of the Soviet police state of Putin's early career, when the Communist Party had a monopoly on power.

In a long, private talk recently with the Moscow PEN writers group, Putin tried to evade the question of the KGB's role in the Soviet system's legacy of terror. Referring to the Stalin-era purges, in which millions were sent to prison camps and death, Putin said, according to a transcript, "Of course, one must not forget about the year 1937, but one must not keep alluding to only this experience, pretending that we do not need state security bodies [such as the KGB]. All the 17 years of my work are connected with this organization. It would be insincere for me to say that I don't want to defend it."

Putin then went on to offer a strangely oblique explanation for the Great Terror, which seemed to avoid blaming the KGB.

"The state security bodies should not be seen as an institution that works against society and the state; one needs to understand what makes them work against their own people. If one recollects those hard years connected with the activities of the security bodies, and the damage they brought to society, one must keep in mind what sort of society it was. But that was an entirely different country. That country produced such security bodies."

He added, however, that if Russia will "treasure elements of civil society that we have got, our only gain over these years, then gradually we will be creating conditions under which those horrifying bodies of security will never be able to revive."

Putin's role in the blatantly misleading information issued by the government about the Chechnya offensive also has been criticized. His talent for creating legends has been evident in his explanations about the war. For example, Putin told the writers group that the military had been open with the news media, when the military has in fact hidden information about casualties, combat events, attacks on civilians and its goals and methods.

Felix Svetov, a writer who spent time in Stalin's prison camps as a child and who lost his father in the purges, was present at the writers meeting. He said Putin's comment "does not correspond with reality." Putin is a typical KGB type, he added. "If the snow is falling, they will calmly tell you, the sun is shining."

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Subject of Bachelor's thesis Entry in Moscow, Russia market for Mad Pro-fessor Amplification Oy. ABSTRACT The commissioner of the thesis is a Finnish company Mad Professor Amplification Oy and it was founded in 2002. In 14 years it has be-come one of the most respected producers of its products in the world
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Nigeria revokes 924 dormant mining titles, seeks new investors
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Putin's Career Rooted in Russia's KGB
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Russia-related Designations and Designations Updates; Issuance of
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The Second Congress Of The Communist International
Endnotes. Lenin is quoting from Marx's work "Zur Kritik der Hegelschen Rechtsphilosophie" (see Marx/Engels, Werke, Bd. 1, S. 385). The American Socialist Party was formed in July 1901 at a congress held in Indianapolis, as the result of a merger of groups that had broken away from the Socialist Workers' Party and the Social-Democratic Party of the U.S.A.