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India has a distinction of extensive mining for development pursuits and undermining environmental and social imperatives. The legal policy for sustainable mining is governed by Mines Act, 1952, The Mines and Minerals (Development...
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India has a distinction of extensive mining for development pursuits and undermining environmental and social imperatives. The legal policy for sustainable mining is governed by Mines Act, 1952, The Mines and Minerals (Development and Regulation) Act,1957, Mineral Concession Rule, 1960, Mineral Conservation and Development Rules, 1988. The techno-legal dimension of mining under National Mineral Policy, 1993 and, National Mineral Policy of 2008 chart out a sustainable mining framework. The legislative history of mining is centripetal to the developer for extracting minerals and neglecting towards ecological sustainability. On the other hand, the workers face the appalling state of health and safety. The innocent population living in mining areas often suffers from adverse environmental impacts and polluted atmosphere. The paper takes a legal stance on precept and practices for developing sustainable mining in the Meghalaya State of India.
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Advances in multimedia data acquisition and storage technology have led to the growth of very large multimedia databases. Analyzing this huge amount of multimedia data to discover useful knowledge is a challenging problem. This ch...
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Advances in multimedia data acquisition and storage technology have led to the growth of very large multimedia databases. Analyzing this huge amount of multimedia data to discover useful knowledge is a challenging problem. This challenge has opened the opportunity for research in Multimedia Data Mining (MDM). Multimedia data mining can be defined as the process of finding interesting patterns from media data such as audio, video, image and text that are not ordinarily accessible by basic queries and associated results. The motivation for doing MDM is to use the discovered patterns to improve decision making. MDM has therefore attracted significant research efforts in developing methods and tools to organize, manage, search and perform domain specific tasks for data from domains such as surveillance, meetings, broadcast news, sports, archives, movies, medical data, as well as personal and online media collections. This paper presents a survey on the prob-lems and solutions in Multimedia Data Mining, approached from the following angles: feature extraction, transformation and representation techniques, data min-ing techniques, and current multimedia data mining systems in various application domains. We discuss main aspects of feature extraction, transformation and repre-sentation techniques. These aspects are: level of feature extraction, feature fusion, features synchronization, feature correlation discovery and accurate representa-tion of multimedia data. Comparison of MDM techniques with state of the art video processing, audio processing and image processing techniques is also provided. Similarly, we compare MDM techniques with the state of the art data mining tech-niques involving clustering, classification, sequence pattern mining, association rule mining and visualization. We review current multimedia data mining systems in detail, grouping them according to problem formulations and approaches. The re-view includes supervised and unsupervised discovery of events and actions from one or more continuous sequences. We also do a detailed analysis to understand what has been achieved and what are the remaining gaps where future research efforts could be focussed. We then conclude this survey with a look at open research directions.
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The advancement of electronic technology enables us to collect logs from various devices. Such logs require detailed analysis in order to be broadly useful. Data mining is a technique that has been widely used to extract hidden in...
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The advancement of electronic technology enables us to collect logs from various devices. Such logs require detailed analysis in order to be broadly useful. Data mining is a technique that has been widely used to extract hidden information from such data. Data mining is mainly composed of association rules mining, sequent pattern mining, classification and clustering. Association rules mining has attracted significant attention and been successfully applied to various fields. Although the past studies can effectively discover frequent patterns to deduce association rules, execution efficiency is still a critical problem. To speed up execution, many methods using parallel and distributed computing technology have been proposed in recent years. Most of the past studies focused on parallelizing the workload in a high end machine or in distributed computing environments like grid or cloud computing systems; however, very few of them discuss how to efficiently determine the appropriate number of computing nodes, considering execution efficiency and load balancing. An intuition is that execution speed is proportional to the number of computing nodes-that is, more the number of computing nodes, faster is the execution speed. However, this is incorrect for such algorithms because of the inherently algorithmic design. Allocating too many computing nodes can lead to high execution time. In addition to the execution inefficiency, inappropriate resource allocation is a waste of computing power and network bandwidth. At the same time, load cannot be effectively distributed if there are too few nodes allocated. In this paper, we propose a fast, load balancing and resource efficient algorithm named FLR-Mining for discovering frequent patterns in distributed computing systems. FLR-Mining is capable of determining the appropriate number of computing nodes automatically and achieving better load balancing as compared with existing methods. Through empirical evaluation, FLR-Mining is shown to deliver excellent performance in terms of execution efficiency and load balancing.
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Kwasne wody kopalniane (Acid Mine Drainage) sa uwazane za jedno z najwiekszych zagrozen srodowiska powstalych w wyniku dzialalnosci gornictwa wegla kamiennego i rud metali na swiecie. Wyplywaja przede wszystkim z opuszczonych i za...
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Kwasne wody kopalniane (Acid Mine Drainage) sa uwazane za jedno z najwiekszych zagrozen srodowiska powstalych w wyniku dzialalnosci gornictwa wegla kamiennego i rud metali na swiecie. Wyplywaja przede wszystkim z opuszczonych i zatopionych wyrobisk kopalnianych i sa glowna przyczyna zanieczyszczenia wod powierzchniowych i podziemnych w wielu regionach na swiecie. Na swiecie znanych jest wiele tysiecy zlikwidowanych wyrobisk kopaln wegla kamiennego i metali, z ktorych wyplywaja, kwasne wody. Wyplywy z calkowicie zatopionych kopaln moga sie pojawic po kilku, a nawet kilkunastu latach od ich zatopienia. Oznacza to, ze zatapianie wyrobisk kopalnianych jest to tzw. "bomba ekologiczna" z opo?nionym zaplonem. Najwiekszym problemem jest to, ze zanieczyszczenia te moga trwac od kilku do kilkuset lat az do wyczerpania sie ?rodla lugowanych mineralow i zwiazkow chemicznych. Na przyklad w Wielkiej Brytanii znane sa wyplywy kwasnych wod kopalnianych z wyrobisk, ktore byly eksploatowane przez Rzymian okolo 2000 lat temu. W niniejszej publikacji przestawione saprzyklady wystepowania kwasnych wod kopalnianych w wybranych zaglebiach na swiecie.
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Data mining has become increasingly important in the Internet era. The problem of mining inter-sequence pattern is a sub-task in data mining with several algorithms in the recent years. However, these algorithms only focus on the ...
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Data mining has become increasingly important in the Internet era. The problem of mining inter-sequence pattern is a sub-task in data mining with several algorithms in the recent years. However, these algorithms only focus on the transitional problem of mining frequent inter-sequence patterns and most frequent inter-sequence patterns are either redundant or insignificant. As such, it can confuse end users during decision-making and can require too much system resources. This led to the problem of mining inter-sequence patterns with item constraints, which addressed the problem when end-users only concerned the patterns contained a number of specific items. In this paper, we propose two novel algorithms for it. First is the ISP-IC (Inter-Sequence Pattern with Item Constraint mining) algorithm based on a theorem that quickly determines whether an inter-sequence pattern satisfies the constraints. Then, we propose a way to improve the strategy of ISP-IC, which is then applied to the i $i$ ISP-IC algorithm to enhance the performance of the process. Finally, pi ISP-IC, a parallel version of i $i$ ISP-IC, will be presented. Experimental results show that pi ISP-IC algorithm outperforms the post-processing of the-state-of-the-art method for mining inter-sequence patterns (EISP-Miner), ISP-IC, and i $i$ ISP-IC algorithms in most of the cases.
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There can be an inclination amongst some governments and non-governmental organisations (NGOs) to view the resource sector with some cynicism. Junior mining companies sometimes engage with local communities (or not), leave without...
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There can be an inclination amongst some governments and non-governmental organisations (NGOs) to view the resource sector with some cynicism. Junior mining companies sometimes engage with local communities (or not), leave without a trace (or perhaps with tracks, trails and trenches) and offer only a brief hope for betterment (or long-standing court battles over environmental or community issues) causing strong emotive reactions. None of the major miners have managed to avoid controversy in their own corporate histories either; of course, none ever could. The art of crafting reform to mineral regulation throughout the world has become a balancing act for the international resource lawyer. The mining company requires certainty when investing in exploration, development or expansion projects in a foreign country to offset the substantial uncertainty inherent in the exploration and mining processes themselves. One needs clear rules which are consistently applied that assure the developer that it may explore, develop and produce any discovery without interference of government or any other person and can measure with some accuracy the expected investment and the anticipated reward. This paper examines several mining codes in the Middle East and offers a critical assessment of their relative opportunity and risk to the developer. It examines each risk in comparative detail, including in comparison to a set of principles found in an exemplary mining code adopted by Madagascar in 2005. The principles of a model mining code (MMC) have been determined after examining more than 50 mining codes from around the world and benefit from the work of MineHutte and the Fraser Institute, which offer ratings for mining regulatory regimes based on different criteria.
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Recently, high utility pattern (HUP) mining is one of the most important research issues in data mining due to its ability to consider the nonbinary frequency values of items in transactions and different profit values for every i...
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Recently, high utility pattern (HUP) mining is one of the most important research issues in data mining due to its ability to consider the nonbinary frequency values of items in transactions and different profit values for every item. On the other hand, incremental and interactive data mining provide the ability to use previous data structures and mining results in order to reduce unnecessary calculations when a database is updated, or when the minimum threshold is changed. In this paper, we propose three novel tree structures to efficiently perform incremental and interactive HUP mining. The first tree structure, Incremental HUP Lexicographic Tree ({rm IHUP}_{{rm {L}}}-Tree), is arranged according to an item's lexicographic order. It can capture the incremental data without any restructuring operation. The second tree structure is the IHUP Transaction Frequency Tree ({rm IHUP}_{{rm {TF}}}-Tree), which obtains a compact size by arranging items according to their transaction frequency (descending order). To reduce the mining time, the third tree, IHUP-Transaction-Weighted Utilization Tree ({rm IHUP}_{{rm {TWU}}}-Tree) is designed based on the TWU value of items in descending order. Extensive performance analyses show that our tree structures are very efficient and scalable for incremental and interactive HUP mining.
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This paper is a practical overview of ways to reduce cost in the design and operation of an Arctic mine. The economically important issues of the Arctic mine that will be addressed include: permafrost ad the active zone in general...
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This paper is a practical overview of ways to reduce cost in the design and operation of an Arctic mine. The economically important issues of the Arctic mine that will be addressed include: permafrost ad the active zone in general terms; road building in and over permafrost; Arctic geotechnical mine design considerations; pit dewatering techniques in subzero temperatures; and blasting frozen materials with techniques to obtain optimal results. A final section on a few special topics conclude this paper.Although this paper primarily refers to near surface conditions more closely associated to an Arctic surface mine, many of the ideas and techniques contained in the paper also apply to the surface construction of an Arctic underground mine.
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Frequent pattern mining (FPM) is an important data mining paradigm to extract informative patterns like itemsets, sequences, trees, and graphs. However, no practical framework for integrating the FPM tasks has been attempted. In t...
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Frequent pattern mining (FPM) is an important data mining paradigm to extract informative patterns like itemsets, sequences, trees, and graphs. However, no practical framework for integrating the FPM tasks has been attempted. In this paper, we describe the design and implementation of the Data Mining Template Library (DMTL) for FPM. DMTL utilizes a generic data mining approach, where all aspects of mining are controlled via a set of properties. It uses a novel pattern property hierarchy to define and mine different pattern types. This property hierarchy can be thought of as a systematic characterization of the pattern space, i.e., a meta-pattern specification that allows the analyst to specify new pattern types, by extending this hierarchy. Furthermore, in DMTL all aspects of mining are controlled by a set of different mining properties. For example, the kind of mining approach to use, the kind of data types and formats to mine over, the kind of back-end storage manager to use, are all specified as a list of properties. This provides tremendous flexibility to customize the toolkit for various applications. Flexibility of the toolkit is exemplified by the ease with which support for a new pattern can be added. Experiments on synthetic and public dataset are conducted to demonstrate the scalability provided by the persistent back-end in the library. DMTL been publicly released as open-source software (http://dmtl.sourceforge.net/), and has been downloaded by numerous researchers from all over the world.
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The purpose of this paper is to provide a more current evaluation and update of web mining research and techniques available. Current advances in each of the three different types of web mining are reviewed in the categories of we...
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The purpose of this paper is to provide a more current evaluation and update of web mining research and techniques available. Current advances in each of the three different types of web mining are reviewed in the categories of web content mining, web usage mining, and web structure mining. For each tabulated research work, we examine such key issues as web mining process, methods/techniques, applications, data sources, and software used. Unlike previous investigators, we divide web mining processes into the following five subtasks: (1) resource finding and retrieving, (2) information selection and preprocessing, (3) patterns analysis and recognition, (4) validation and interpretation, and (5) visualization. This paper also reports the comparisons and summaries of selected software for web mining. The web mining software selected for discussion and comparison in this paper are SPSS Clementine, Megaputer PolyAnalyst, ClickTracks by web analytics, and QL2 by QL2 Software Inc. Applications of these selected web mining software to available data sets are discussed together with abundant presentations of screen shots, as well as conclusions and future directions of the research.
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