Search results for: Erdenet Mining Corporation

Authors: Anurag Savarnya

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The reliability of the various parts of electric mining shovel has been assessed through the application of Weibull Model. The study was initiated to find reliability of components of electric mining shovel. The paper aims to optimize the reliability of components and increase the life cycle of component. A multilevel decomposition of the electric mining shovel was done and maintenance records were used to evaluate the failure data and appropriate system characterization was done to model the system in terms of reasonable number of components. The approach used develops a mathematical model to assess the reliability of the electric mining shovel components. The model can be used to predict reliability of components of the hydraulic mining shovel and system performance. Reliability is an inherent attribute to a system. When the life-cycle costs of a system are being analyzed, reliability plays an important role as a major driver of these costs and has considerable influence on system performance. It is an iterative process that begins with specification of reliability goals consistent with cost and performance objectives. The data were collected from an Indian open cast coal mine and the reliability of various components of the electric mining shovel has been assessed by following a Weibull Model.

Keywords: reliability, Weibull model, electric mining shovel

Procedia PDF Downloads 472

Authors: Adewale O. Ogunde, Olusegun Folorunso, Adesina S. Sodiya

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Most existing Distributed Association Rule Mining (DARM) systems are still facing several challenges. One of such challenges that have not received the attention of many researchers is the inability of existing systems to adapt to constantly changing databases and mining environments. In this work, an Adaptive Incremental Mining Algorithm (AIMA) is therefore proposed to address these problems. AIMA employed multiple mobile agents for the entire mining process. AIMA was designed to adapt to changes in the distributed databases by mining only the incremental database updates and using this to update the existing rules in order to improve the overall response time of the DARM system. In AIMA, global association rules were integrated incrementally from one data site to another through Results Integration Coordinating Agents. The mining agents in AIMA were made adaptive by defining mining goals with reasoning and behavioral capabilities and protocols that enabled them to either maintain or change their goals. AIMA employed Java Agent Development Environment Extension for designing the internal agents’ architecture. Results from experiments conducted on real datasets showed that the adaptive system, AIMA performed better than the non-adaptive systems with lower communication costs and higher task completion rates.

Keywords: adaptivity, data mining, distributed association rule mining, incremental mining, mobile agents

Procedia PDF Downloads 367

Authors: Andri Ottesen, Sam Toglaw, Mirna Safa

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Entrepreneurial companies on their developing path from an idea to a corporation go through a similar six-step process. Each of these six development steps is supported by a distinctive financing path. This paper explores the Kuwait model for Entrepreneurial Finance and Development through in-depth interviews with ten successful Kuwaiti entrepreneurs. This paper offers insight into the development and financing of entrepreneurial companies in this oil-rich, predominantly Islamic country that are in many ways different from the steps. Western entrepreneurial companies go through. This model could be used to understand the commonalities and the difference between entrepreneurial development and financing and could be used to bridge the gap.

Keywords: entrepreneurial-financing, entrepreneurial-developing, Kuwait, Vancouver school

Procedia PDF Downloads 183

Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

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There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

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Authors: Maram Saleh

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Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

Procedia PDF Downloads 180

Authors: Adarsh Shroff

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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

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Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

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Nowadays considering human involved in increasing data development some methods such as data mining to extract science are unavoidable. One of the discussions of data mining is inherent distribution of the data usually the bases creating or receiving such data belong to corporate or non-corporate persons and do not give their information freely to others. Yet there is no guarantee to enable someone to mine special data without entering in the owner’s privacy. Sending data and then gathering them by each vertical or horizontal software depends on the type of their preserving type and also executed to improve data privacy. In this study it was attempted to compare comprehensively preserving data methods; also general methods such as random data, coding and strong and weak points of each one are examined.

Keywords: data mining, distributed data mining, privacy protection, privacy preserving

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Authors: Suzan Wedyan

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Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

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Authors: M. Sai Veerendra

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Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most of the financial institutions internationally have been implementing anti-money laundering solutions (AML) to fight investment fraud activities. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project on developing a new data mining solution for AML Units in an international investment bank in Ireland, we survey recent data mining approaches for AML. In this paper, we present not only these approaches but also give an overview on the important factors in building data mining solutions for AML activities.

Keywords: data mining, clustering, money laundering, anti-money laundering solutions

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Authors: Ali Mortazavi

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The main objective of this research project is to delve into a multitude of geomechanical risks associated with various mining methods employed within the underground mining industry. Controlling geotechnical design parameters and operational factors affecting the selection of suitable mining techniques for a given underground mining condition will be considered from a risk assessment point of view. Important geomechanical challenges will be investigated as appropriate and relevant to the commonly used underground mining methods. Given the complicated nature of rock mass in-situ and complicated boundary conditions and operational complexities associated with various underground mining methods, the selection of a safe and economic mining operation is of paramount significance. Rock failure at varying scales within the underground mining openings is always a threat to mining operations and causes human and capital losses worldwide. Geotechnical design is a major design component of all underground mines and basically dominates the safety of an underground mine. With regard to uncertainties that exist in rock characterization prior to mine development, there are always risks associated with inappropriate design as a function of mining conditions and the selected mining method. Uncertainty often results from the inherent variability of rock masse, which in turn is a function of both geological materials and rock mass in-situ conditions. The focus of this research is on developing a methodology which enables a geomechanical risk assessment of given underground mining conditions. The outcome of this research is a geotechnical risk analysis algorithm, which can be used as an aid in selecting the appropriate mining method as a function of mine design parameters (e.g., rock in-situ properties, design method, governing boundary conditions such as in-situ stress and groundwater, etc.).

Keywords: geomechanical risk assessment, rock mechanics, underground mining, rock engineering

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Authors: Linus O. Asuquo

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Mining in Nigeria and development effort of metallurgical technologies at National Metallurgical Development Centre Jos has been addressed in this paper. The paper has looked at the history of mining in Nigeria, the impact of mining on social and industrial development, and the contribution of the mining sector to Nigeria’s Gross Domestic Product (GDP). The paper clearly stated that Nigeria’s mining sector only contributes 0.5% to the nation’s GDP unlike Botswana that the mining sector contributes 38% to the nation’s GDP. Nigeria Bureau of Statistics has it on record that Nigeria has about 44 solid minerals awaiting to be exploited. Clearly highlighted by this paper is the abundant potentials that exist in the mining sector for investment. The paper made an exposition on the extensive efforts made at National Metallurgical Development Center (NMDC) to develop metallurgical technologies in various areas of the metals sector; like mineral processing, foundry development, nonferrous metals extraction, materials testing, lime calcination, ANO (Trade name for powder lubricant) wire drawing lubricant, refractories and many others. The paper went ahead to draw a conclusion that there is a need to develop the mining sector in Nigeria and to give a sustainable support to the efforts currently made at NMDC to develop metallurgical technologies which are capable of transforming the metals sector in Nigeria, which will lead to industrialization. Finally the paper made some recommendations which traverse the topic for the best expectation.

Keywords: mining, minerals, technologies, value addition

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Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

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Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, Data Mining, Hadoop, MapReduce, MongoDB, NoSQL

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Authors: Awatef Hicheur Cairns, Billel Gueni, Hind Hafdi, Christian Joubert, Nasser Khelifa

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Given the ever changing needs of the job markets, education and training centers are increasingly held accountable for student success. Therefore, education and training centers have to focus on ways to streamline their offers and educational processes in order to achieve the highest level of quality in curriculum contents and managerial decisions. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to discover, analyze and provide a visual representation of complete educational processes. In this paper, we present our distributed computation platform which allows different education centers and institutions to load their data and access to advanced data mining and process mining services. To achieve this, we present also a comparative study of the different clustering techniques developed in the context of process mining to partition efficiently educational traces. Our goal is to find the best strategy for distributing heavy analysis computations on many processing nodes of our platform.

Keywords: educational process mining, distributed process mining, clustering, distributed platform, educational data mining, ProM

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Authors: Seema Vaidya

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Mining association rule is a key issue in data mining. In any case, the standard models ignore the distinction among the exchanges, and the weighted association rule mining does not transform on databases with just binary attributes. This paper proposes a novel continuous example and executes a tree (FP-tree) structure, which is an increased prefix-tree structure for securing compacted, discriminating data about examples, and makes a fit FP-tree-based mining system, FP enhanced capacity algorithm is used, for mining the complete game plan of examples by illustration incessant development. Here, this paper handles the motivation behind making remarkable and weighted item sets, i.e. rare weighted item set mining issue. The two novel brightness measures are proposed for figuring the infrequent weighted item set mining issue. Also, the algorithm are handled which perform IWI which is more insignificant IWI mining. Moreover we utilized the rare item set for choice based structure. The general issue of the start of reliable definite rules is troublesome for the grounds that hypothetically no inciting technique with no other person can promise the rightness of influenced theories. In this way, this framework expects the disorder with the uncommon signs. Usage study demonstrates that proposed algorithm upgrades the structure which is successful and versatile for mining both long and short diagnostics rules. Structure upgrades aftereffects of foreseeing rare diseases of patient.

Keywords: association rule, data mining, IWI mining, infrequent item set, frequent pattern growth

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Authors: Hitham Yami

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This study will focus primarily on assessing the availability requirements of the electronic management of oil companies in Libya, and the mean objectives of the research applying electronic management and make recommendations and steps to approach electronic management. There are limited research and statistical analysis to support electronic management in Libyan companies. The groundwork for the proposed approach is to develop independent variables and the dependent variables to be restructured after it Alntra side of the field and the side to get the data to achieve the desired results and solving the problem faced by the Libyan Oil Corporation. All these strategies are proposed to achieve the goal, and solving Libyan oil installations.

Keywords: oil company’s revenue, independent variables, electronic management, Libyan oil corporation

Procedia PDF Downloads 238

Authors: Kateryna Zharan, Jan C. Bongaerts

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Mining operations are energy intensive, and the share of energy costs in total costs is often quoted in the range of 40 %. Saving on energy costs is, therefore, a key element of any mine operator. With the improving reliability and security of renewable energy (RE) sources, and requirements to reduce carbon dioxide emissions, perspectives for using RE in mining operations emerge. These aspects are stimulating the mining companies to search for ways to substitute fossil energy with RE. Hereby, the main purpose of this study is to present the survey research assessment in matter of finding out the key issues related to the integration of RE into mining activities, based on the mining and renewable energy experts’ opinion. The purpose of the paper is to present the outcomes of a survey conducted among mining and renewable energy experts about the feasibility of RE in mining operations. The survey research has been developed taking into consideration the following categories: first of all, the mining and renewable energy experts were chosen based on the specific criteria. Secondly, they were offered a questionnaire to gather their knowledge and opinions on incentives for mining operators to turn to RE, barriers and challenges to be expected, environmental effects, appropriate business models and the overall impact of RE on mining operations. The outcomes of the survey allow for the identification of factors which favor and disfavor decision-making on the use of RE in mining operations. It concludes with a set of recommendations for further study. One of them relates to a deeper analysis of benefits for mining operators when using RE, and another one suggests that appropriate business models considering economic and environmental issues need to be studied and developed. The results of the paper will be used for developing a hybrid optimized model which might be adopted at mines according to their operation processes as well as economic and environmental perspectives.

Keywords: carbon dioxide emissions, mining industry, photovoltaic, renewable energy, survey research, wind generation

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Authors: Sri Suryaningsum

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The achievement ‘Best Practice Model’ holds by the government on behalf of the success implementation corporate social responsibility program that held on PT. Kaltim Prima Coal which had operation located in the isolated district in Sanggata, it could be the reference for the other companies to improve the social welfare in surrounding area, especially for the companies that have operated in the isolated area in Indonesia. The rule of Kaltim Prima Coal as the catalyst in the development progress to push up the independence of district especially for the district which has located in surrounding mining operation from village level to the regency level, those programs had written in the 7 field program in Corporate Social Responsibility, it was doing by stakeholders. The stakeholders are village government, sub-district government, Regency and citizen. One of the best programs that implement at PT. Kaltim Prima Coal is Regarding Resettlement that was completed based on Asian Development Bank Resettlement Best Practice and International Financial Corporation Resettlement Action Plan. This program contributed on the resettlement residences to develop the isolated and the neglected district.

Keywords: CSR, isolated, neglected, poverty, mining industry

Procedia PDF Downloads 218

Authors: Mohammad Aljuhani, Yasamina Aljuhani

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The Mining Engineering Department at College of Engineering in NBU is under establishment. It is essential to establish such department in NBU. This is because, it is the only university in the region. Moreover, the mining industry is very active in the northern borders region. However, there is no mining engineering department in KSA except one in King Abdulziz University, which is 1400 km from the mining industry in the northern borders. As a result, department graduates from KAU find difficulties to get suitable jobs in their specialization in spite of their few numbers graduated per year and the presence of many jobs vacancies at the local mining sector. Therefore, the objectives of this research are to identify, measure and analyze the above mentioned problem from educational point of view. One more objective is to add a contribution towards solving such vital, society affecting problem. For achieving the first task of the research, that is problem size identification and analyses, a questionnaire was designed. The questionnaire was directed towards experienced engineers, in the mining and related industries, including the ministry of petroleum and minerals, Saudi Geological Survey, and Ma’aden Company as being prospective employers for the mining sector. The questionnaire target was to evaluate the Saudi mining engineers from an industrial point of view and to detect the main reasons behind their failure to find jobs. In addition, the study focuses in the demand of mining engineers in the northern borders region. Moreover, the study plan of the suggested department is designed based on the requirements of the mining industry. The feedback received from the industry reflected major educational shortcomings. In order to overcome the revealed defects, the second objective of the research was achieved where a suggested study plan “curriculum” has been prepared to take into consideration all the points of weakness so as to improve the graduates’ quality to fit the local mining work market.

Keywords: mining engineering, labor market, qualifications, curriculum, mining industry, mining engineers

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Authors: Davidson E. Egirani, Nanfe R. Poyi, Napoleon Wessey

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This paper would report the environmental challenges faced by stakeholders in the development and management of mineral resources in Mindanao mining region of the Philippines. The paper would proffer solutions via the development and management of integrated mineral resource framework. This is by interfacing the views of government, operating mining companies and the mining host communities. The project methods involved the desktop review of existing local, regional, national environmental and mining legislation. This was followed up with visits to mining sites and discussions were held with stakeholders in the mineral sector. The findings from a 2-year investigation would reveal lack of information, education, and communication campaign by stakeholders on environmental, health, political, and social issues in the mining industry. Small-scale miners lack the professional muscles for a balance shift of emphasis to sustainable and responsible mining to avoid environmental degradation and human health effect. Therefore, there is a need to balance ecological requirements, sustainability of the environment and development of mineral resources. This paper would provide an environmentally friendly mineral resource development framework.

Keywords: ecological requirements, environmental degradation, human health, mining legislation, responsible mining

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Authors: Bagam Venkateswarlu

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NMDC Limited, Indian multinational mining company operates under administrative control of Ministry of Steel, Government of India. This study is undertaken to evaluate how sustainable mining practiced by the company fulfils the provisions of Indian Constitution to secure to its citizen – justice, equality of status and opportunity, promoting social, economic, political, and religious wellbeing. The Constitution of India lays down a road map as to how the goal of being a “Welfare State” shall be achieved. The vision of sustainable mining being practiced is oriented along the constitutional responsibilities on Indian Citizens and the Corporate World. This qualitative study shall be backed by quantitative studies of National Mineral Development Corporation performances in various domains of sustainable mining and ESG, that is, environment, social and governance parameters. For example, Five Star Rating of mine is a comprehensive evaluation system introduced by Ministry of Mines, Govt. of India is one of the methodologies. Corporate Social Responsibilities is one of the thrust areas for securing social well-being. Green energy initiatives in and around the mines has given the title of “Eco-Friendly Miner” to NMDC Limited. While operating fully mechanized large scale iron ore mine (18.8 million tonne per annum capacity) in Bacheli, Chhattisgarh, M/s NMDC Limited caters to the needs of mineral security of State of Chhattisgarh and Indian Union. It preserves forest, wild-life, and environment heritage of richly endowed State of Chhattisgarh. In the remote and far-flung interiors of Chhattisgarh, NMDC empowers the local population by providing world class educational & medical facilities, transportation network, drinking water facilities, irrigational agricultural supports, employment opportunities, establishing religious harmony. All this ultimately results in empowered, educated, and improved awareness in population. Thus, the basic tenets of constitution of India- secularism, democracy, welfare for all, socialism, humanism, decentralization, liberalism, mixed economy, and non-violence is fulfilled. Constitution declares India as a welfare state – for the people, of the people and by the people. The sustainable mining practices by NMDC are in line with the objective. Thus, the purpose of study is fully met with. The potential benefit of the study includes replicating this model in existing or new establishments in various parts of country – especially in the under-privileged interiors and far-flung areas which are yet to see the lights of development.

Keywords: ESG values, Indian constitution, NMDC limited, sustainable mining, CSR, green energy

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Authors: J. Suneetha, Vijayalaxmi

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Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

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This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: data mining, textile production, decision trees, classification

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Authors: Tanvi P. Patel, Warish D. Patel

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Association rule mining forms the core of data mining and it is termed as one of the well-known methodologies of data mining. Objectives of mining is to find interesting correlations, frequent patterns, associations or casual structures among sets of items in the transaction databases or other data repositories. Hence, association rule mining is imperative to mine patterns and then generate rules from these obtained patterns. For efficient targeted query processing, finding frequent patterns and itemset mining, there is an efficient way to generate an itemset tree structure named Memory Efficient Itemset Tree. Memory efficient IT is efficient for storing itemsets, but takes more time as compare to traditional IT. The proposed strategy generates maximal frequent itemsets from memory efficient itemset tree by using levelwise pruning. For that firstly pre-pruning of items based on minimum support count is carried out followed by itemset tree reconstruction. By having maximal frequent itemsets, less number of patterns are generated as well as tree size is also reduced as compared to MEIT. Therefore, an enhanced approach of memory efficient IT proposed here, helps to optimize main memory overhead as well as reduce processing time.

Keywords: association rule mining, itemset mining, itemset tree, meit, maximal frequent pattern

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Authors: Fahad Hanash Alzahrani

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This paper describes some recent advances in a quickly developing area of data storing and processing based on Data Warehouses and Data Mining techniques, which are associated with software, hardware, data mining algorithms and visualisation techniques having common features for any specific problems and tasks of their implementation.

Keywords: data warehouse, data mining, knowledge discovery in databases, on-line analytical processing

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Authors: Najiba Ouled Omar, Azza Harbaoui, Henda Ben Ghezala

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Current research practices sentiment analysis with a focus on social networks, DEfi Fouille de Texte (DEFT) (Text Mining Challenge) evaluation campaign focuses on opinion mining and sentiment analysis on social networks, especially social network Twitter. It aims to confront the systems produced by several teams from public and private research laboratories. DEFT offers participants the opportunity to work on regularly renewed themes and proposes to work on opinion mining in several editions. The purpose of this article is to scrutinize and analyze the works relating to opinions mining and sentiment analysis in the Twitter social network realized by DEFT. It examines the tasks proposed by the organizers of the challenge and the methods used by the participants.

Keywords: opinion mining, sentiment analysis, emotion, polarity, annotation, OSEE, figurative language, DEFT, Twitter, Tweet

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Authors: Justine Ugochukwu Osuagwu, Sazali Abd Wahab

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The performance and operation of NNPC have faced series of attacks by all stakeholders as many have observed lots of inefficiency not only on the part of the management but the staff. This has raised questions of whether their operations and performance are being seriously affected by lack of transformational leadership, and the political competition prevalent in the country. The author has applied the administrative leadership theory and institutional theory as a guide to this study and empirically relates such theories to the study. The study also has utilized the quantitative approach where questionnaires were distributed to 370 participants, and the correctly filled and returned questionnaires were used for the analysis using structural equation modeling. The path coefficient of transformational leadership to performance is strong and positive with β = 0.672; t-value = 14.245; p-value = 0.000. Also, the result found that political competition does not mediate the relationship between transformational leadership and performance of NNPC. (β = -0.008; t-value = -0.600; p- value > 0.05). However, the indirect path is all insignificant, meaning that transformational leadership has relationship with corporate performance.The study found that,while political competition does not serve as a mediator in the relationship between transformational leadership and corporate performance, these styles of leadership have a direct and positive impact on corporate performance. The direct relationship between transformational leadership and political competition was not discovered, despite the fact that political competition has a direct and significant impact, both positive and negative, on corporate performance. As a result, both political competition and transformational leadership have the potential to significantly alter corporate performance.

Keywords: performance, transformational leadership, political competition, corporation performance, Nigeria national petroleum corporation

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: Harpreet Singh

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Finding relevant information on the World Wide Web is becoming highly challenging day by day. Web usage mining is used for the extraction of relevant and useful knowledge, such as user behaviour patterns, from web access log records. Web access log records all the requests for individual files that the users have requested from the website. Web usage mining is important for Customer Relationship Management (CRM), as it can ensure customer satisfaction as far as the interaction between the customer and the organization is concerned. Web usage mining is helpful in improving website structure or design as per the user’s requirement by analyzing the access log file of a website through a log analyzer tool. The focus of this paper is to enhance the accessibility and usability of a guitar selling web site by analyzing their access log through Deep Log Analyzer tool. The results show that the maximum number of users is from the United States and that they use Opera 9.8 web browser and the Windows XP operating system.

Keywords: web usage mining, web mining, log file, data mining, deep log analyzer

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Authors: Vithya Veeramani, Karunanidhi Subbaiah

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Emotional problems were found to be the predominant cause of suicide and second leading cause of death among adolescents in India. Emotional problems seem to be the underlying cause for various other severe psycho-social problems experienced in adolescence and also in later years of life. The Corporation schools in Chennai city are named as Chennai High School or Chennai Higher Secondary School run by the Corporation of Chennai. These schools fulfill the educational needs of students who hail from lower socio-economic status living in slums of the Chennai city. Adolescent students of Chennai schools tend to lack basic needs like food, clothes, shelter, etc. Some of the other significant problems faced by them are broken family, lack of parental support, frequent quarrel between parents, alcoholic parents, drug abuse and substance abuse among parents and neighbors, extended family, illiterate parents, deprivation of love and care, and lack of sense of belongingness. This prevailing condition may affect them emotionally and could lead to maladaptive behaviour, aggressiveness, poor interpersonal relationship with others, school refusal behaviour, school drop-out, suicide, etc. Therefore, it is very important to investigate the emotional problems faced by the adolescent students studying in Chennai schools, Chennai. A cross-sectional survey design was used to find the prevalence of emotional problems among adolescent students. Cluster sampling technique was used to select the schools for the present study considering the school as a cluster. In total, there are 15 zones, under the control of Chennai Corporation, of which only 7 zones have Corporation Schools in Chennai city, comprising of 32 Chennai Higher Secondary Schools and 38 Chennai High Schools. Out of these 70 schools, 29 schools comprising of 17 high schools and 12 higher secondary schools were selected randomly using lottery method. A sample of 2594 adolescent students from 9th standard and 11th standard was chosen for the study. Percentage analysis was done to find out the prevalence rate of emotional problems among adolescents students studying in Chennai Schools. Results of the study revealed that, out of 2594 students surveyed, 21.04% adolescent students were found to have academic problems (n = 546), 15.99% adolescent students had social problems (n = 415), behaviour problems was found to be prevalent among 12.87% adolescent students (n = 334), depression was prevalent among 15.88% adolescent students (n = 412) and anxiety was prevalent among 14.42% adolescent students (n = 374). Prevalence of emotional problems among male and female revealed that academic problems were more prevalent compared to other problems. Behaviour problems were least prevalent among boys and anxiety was least prevalent among girls than other problems. The overall prevalence rate of emotional problems was found to be on an increasing trend among adolescent students of low socio-economic status in Chennai city. The findings indicated the need for intervention to prevent and rehabilitate these adolescent students.

Keywords: adolescents, corporation schools, emotional problems, prevalence

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Authors: Taşkın Deniz Yıldız, Mustafa Topaloğlu, Orhan Kural

Abstract:

The right to operate a fairly long periods of prior periods and after the 3213 Mining Law has been observed to be shortened in Turkey. Permit the realization of business activities (or concession) requested the purchase of the mine operated "found mine" position, as well as the financial and technical capability to have the owner of the right to operate the mines as well as the principle of equality is important in terms of assessing the best way be. In particular, in this context, license fields "negligence" (downsizing) have noted that the current arrangement for all periods. However, in the period after 3213 Mining Act and a permit to operate more effectively within the framework of implementation of negligence is laid down.

Keywords: mining legislation, operation, permit, Turkey

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