Search results for: frequent item sets mining

Authors: I. Inthanongsone, C. Drebenstedt, J. C. Bongaerts, P. Sontamino

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The major concern in evaluating the value of mining projects related to the deficiency of the traditional discounted cash flow (DCF) method. This method does not take uncertainties into account and, hence it does not allow for an economic assessment of managerial flexibility and operational adaptability, which are increasingly determining long-term corporate success. Such an assessment can be performed with the real options valuation (ROV) approach, since it allows for a comparative evaluation of unforeseen uncertainties in a project life cycle. This paper presents an economic evaluation model for open pit mining projects based on real options valuation approach. Uncertainties in the model are caused by metal prices and cost uncertainties and the system dynamics (SD) modeling method is used to structure and solve the real options model. The model is applied to a case study. It can be shown that that managerial flexibility reacting to uncertainties may create additional value to a mining project in comparison to the outcomes of a DCF method. One important insight for management dealing with uncertainty is seen in choosing the optimal time to exercise strategic options.

Keywords: DCF methods, ROV approach, system dynamics modeling methods, uncertainty

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Authors: Ermias A. Tegegn, Million Meshesha

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Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome (HIV/AIDS) is a major cause of death for most African countries. Ethiopia is one of the seriously affected countries in sub Saharan Africa. Previously in Ethiopia, having HIV/AIDS was almost equivalent to a death sentence. With the introduction of Antiretroviral Therapy (ART), HIV/AIDS has become chronic, but manageable disease. The study focused on a data mining technique to predict future living status of HIV/AIDS patients at the time of drug regimen change when the patients become toxic to the currently taking ART drug combination. The data is taken from University of Gondar Hospital ART program database. Hybrid methodology is followed to explore the application of data mining on ART program dataset. Data cleaning, handling missing values and data transformation were used for preprocessing the data. WEKA 3.7.9 data mining tools, classification algorithms, and expertise are utilized as means to address the research problem. By using four different classification algorithms, (i.e., J48 Classifier, PART rule induction, Naïve Bayes and Neural network) and by adjusting their parameters thirty-two models were built on the pre-processed University of Gondar ART program dataset. The performances of the models were evaluated using the standard metrics of accuracy, precision, recall, and F-measure. The most effective model to predict the status of HIV patients with drug regimen substitution is pruned J48 decision tree with a classification accuracy of 98.01%. This study extracts interesting attributes such as Ever taking Cotrim, Ever taking TbRx, CD4 count, Age, Weight, and Gender so as to predict the status of drug regimen substitution. The outcome of this study can be used as an assistant tool for the clinician to help them make more appropriate drug regimen substitution. Future research directions are forwarded to come up with an applicable system in the area of the study.

Keywords: HIV drug regimen, data mining, hybrid methodology, predictive model

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Authors: Vera G. Dianova, Lori P. Montross, Charles M. Burke

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In the digital age, the widespread and frequently excessive use of mobile phones amongst university students is recognized as a significant distractor which interferes with their ability to enter a deep state of concentration during studies and diminishes their prospects of experiencing the enjoyable and instrumental state of flow, as defined and described by psychologist M. Csikszentmihalyi. This study has targeted 50 university students with the aim of teaching them to cultivate their ability to engage in deep work and to attain the state of flow, fostering more effective and enjoyable learning experiences. Prior to the start of the intervention, all participating students completed a comprehensive survey based on a variety of validated scales assessing their inclination toward lifelong learning, frequency of flow experiences during study, frustration tolerance, sense of agency, as well as their love of learning and daily time devoted to non-academic mobile phone activities. Several days after this initial assessment, students received a 90-minute lecture on the principles of flow and deep work, accompanied by a critical discourse on the detrimental effects of excessive mobile phone usage. They were encouraged to practice deep work and strive for frequent flow states throughout the semester. Subsequently, students submitted weekly surveys, including the 10-item CORE Dispositional Flow Scale, a 3-item agency scale and furthermore disclosed their average daily hours spent on non-academic mobile phone usage. As a final step, at the end of the semester students engaged in reflective report writing, sharing their experiences and evaluating the intervention's effectiveness. They considered alterations in their love of learning, reflected on the implications of their mobile phone usage, contemplated improvements in their tolerance for boredom and perseverance in complex tasks, and pondered the concept of lifelong learning. Additionally, students assessed whether they actively took steps towards managing their recreational phone usage and towards improving their commitment to becoming lifelong learners. Employing a mixed-methods approach our study offers insights into the dynamics of concentration, flow, mobile phone usage and attitudes towards learning among undergraduate and graduate university students. The findings of this study aim to promote profound contemplation, on the part of both students and instructors, on the rapidly evolving digital-age higher education environment. In an era defined by digital and AI advancements, the ability to concentrate, to experience the state of flow, and to love learning has never been more crucial. This study underscores the significance of addressing mobile phone distractions and providing strategies for cultivating deep concentration. The insights gained can guide educators in shaping effective learning strategies for the digital age. By nurturing a love for learning and encouraging lifelong learning, educational institutions can better prepare students for a rapidly changing labor market, where adaptability and continuous learning are paramount for success in a dynamic career landscape.

Keywords: deep work, flow, higher education, lifelong learning, love of learning

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Authors: E Tambo, O. O. Olalubi, E. C. Ugwu, J. Y. Ngogang

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Despite the World Health Organization (WHO) declaration of international health emergency concern, the status quo of responses and efforts to stem the worst-recorded Ebola epidemic Ebola outbreak is still precariously inadequate in most of the affected in West. Mining natural resources have been shown to play a key role in both motivating and fuelling ethnic, civil and armed conflicts that have plagued a number of African countries over the last decade. Revenues from the exploitation of natural resources are not only used in sustaining the national economy but also armies, personal enrichment and building political support. Little is documented on the mining and ecological impact on the emergence and geographical distribution of Ebola in Africa over time and space. We aimed to provide a better understanding of the interconnectedness among issues of mining natural, resource management, mining conflict and post-conflict on Ebola outbreak and how wealth generated from abundant natural resources could be better managed in promoting research and development towards strengthening environmental, socioeconomic and health systems sustainability on Ebola outbreak and other emerging diseases surveillance and responses systems prevention and control, early warning alert, durable peace and sustainable development rather than to fuel conflicts, resurgence and emerging diseases epidemics in the perspective of community and national/regional approach. Our results showed the first assessment of systematic impact of all major minerals conflict events diffusion over space and time and mining activities on nine Ebola genesis and geo-distribution in affected countries across Africa. We demonstrate how, where and when mining activities in Africa increase ecological degradation, conflicts at the local level and then spreads violence across territory and time by enhancing the financial capacities of fighting groups/ethnics and diseases onset. In addition, led process of developing minimum standards for natural resource governance; improving governmental and civil society capacity for natural resource management, including the strengthening of monitoring and enforcement mechanisms; understanding the post-mining and conflicts community or national reconstruction and rehabilitation programmes in strengthening or developing community health systems and regulatory mechanisms. In addition the quest for the control over these resources and illegal mining across the landscape forest incursion provided increase environmental and ecological instability and displacement and disequilibrium, therefore affecting the intensity and duration of mining and conflict/wars and episode of Ebola outbreaks over time and space. We highlight the key findings and lessons learnt in promoting country or community-led process in transforming natural resource wealth from a peace liability to a peace asset. The imperative necessity for advocacy and through facilitating intergovernmental deliberations on critical issues and challenges affecting Africa community transforming exploitation of natural resources from a peace liability to outbreak prevention and control. The vital role of mining in increasing government revenues and expenditures, equitable distribution of wealth and health to all stakeholders, in particular local communities requires coordination, cooperative leadership and partnership in fostering sustainable developmental initiatives from mining context to outbreak and other infectious diseases surveillance responses systems in prevention and control, and judicious resource management.

Keywords: mining, mining conflicts, mines, ecological, Ebola, outbreak, mining companies, miners, impact

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Authors: Saeidreza Radpour, Md. Ahiduzzaman, Amit Kumar

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Alberta’s mining sector consumed 871.3 PJ in 2012, which is 67.1% of the energy consumed in the industry sector and about 40% of all the energy consumed in the province of Alberta. Natural gas, petroleum products, and electricity supplied 55.9%, 20.8%, and 7.7%, respectively, of the total energy use in this sector. Oil sands mining and upgrading to crude oil make up most of the mining energy sector activities in Alberta. Crude oil is produced from the oil sands either by in situ methods or by the mining and extraction of bitumen from oil sands ore. In this research, the factors affecting oil sands production have been assessed and a framework has been developed for market penetration of new efficient technologies in this sector. Oil sands production amount is a complex function of many different factors, broadly categorized into technical, economic, political, and global clusters. The results of developed and implemented statistical analysis in this research show that the importance of key factors affecting on oil sands production in Alberta is ranked as: Global energy consumption (94% consistency), Global crude oil price (86% consistency), and Crude oil export (80% consistency). A framework for modeling oil sands energy technologies’ market penetration (OSETMP) has been developed to cover related technical, economic and environmental factors in this sector. It has been assumed that the impact of political and social constraints is reflected in the model by changes of global oil price or crude oil price in Canada. The market share of novel in situ mining technologies with low energy and water use are assessed and calculated in the market penetration framework include: 1) Partial upgrading, 2) Liquid addition to steam to enhance recovery (LASER), 3) Solvent-assisted process (SAP), also called solvent-cyclic steam-assisted gravity drainage (SC-SAGD), 4) Cyclic solvent, 5) Heated solvent, 6) Wedge well, 7) Enhanced modified steam and Gas push (emsagp), 8) Electro-thermal dynamic stripping process (ET-DSP), 9) Harris electro-magnetic heating applications (EMHA), 10) Paraffin froth separation. The results of the study will show the penetration profile of these technologies over a long term planning horizon.

Keywords: appliances efficiency improvement, diffusion models, market penetration, residential sector

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Authors: Stellina Jolly

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July 18th to August 19th 2013 has gone down in the history of India for undertaking the country’s first environment referendum. The Supreme Court had ruled that the Vedanta Group's bauxite mining project in the Niyamgiri Hills of Orissa will have to get clearance from the gram sabha, which will consider the cultural and religious rights of the tribals and forest dwellers living in Rayagada and Kalahandi districts. In the Niyamgiri hills, people of small tribal hamlets were asked to voice their opinion on bauxite mining in their habitat. The ministry has reiterated its stand that mining cannot be allowed on the Niyamgiri hills because it will affect the rights of the Dongria Kondhs. The tribal person who occupies the Niyamgiri Hills in Eastern India accomplished their first success in 2010 in their struggle to protect and preserve their existence, culture and land against Vedanta a London-based mining giant. In August, 2010 Government of India revoked permission for Vedanta Resources to mine bauxite from hills in Orissa State where the Dongria Kondh live as forest dwellers. This came after various protests and reports including amnesty report wherein it highlighted that an alumina refinery in eastern India operated by a subsidiary of mining company. Vedanta was accused of causing air and water pollution that threatens the health of local people and their access to water. The abuse of human rights by corporate is not a new issue it has occurred in Africa, Asia and other parts of the world. Paper focuses on the instances and extent of human right especially in terms of environment violations by corporations. Further Paper details on corporations and sustainable development. Paper finally comes up with certain recommendation including call for a declaration by United Nations on Corporate environment Human Rights Liability.

Keywords: environment, corporate, human rights, sustainable development

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Authors: Serge B. Provost, Yishan Zhang

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A moment-based adjustment to the saddlepoint approximation is introduced in the context of density estimation. First applied to univariate distributions, this methodology is extended to the bivariate case. It then entails estimating the density function associated with each marginal distribution by means of the saddlepoint approximation and applying a bivariate adjustment to the product of the resulting density estimates. The connection to the distribution of empirical copulas will be pointed out. As well, a novel approach is proposed for estimating the support of distribution. As these results solely rely on sample moments and empirical cumulant-generating functions, they are particularly well suited for modeling massive data sets. Several illustrative applications will be presented.

Keywords: empirical cumulant-generating function, endpoints identification, saddlepoint approximation, sample moments, density estimation

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Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

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Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

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Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

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Authors: Diana Codat

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Tweets' analysis is part of text mining. Each document is a written text. It's possible to apply the usual text search techniques, in particular by switching to the bag-of-words representation. But the tweets induce peculiarities. Some may enrich the analysis. Thus, their length is calibrated (at least as far as public messages are concerned), special characters make it possible to identify authors (@) and themes (#), the tweet and retweet mechanisms make it possible to follow the diffusion of the information. Conversely, other characteristics may disrupt the analyzes. Because space is limited, authors often use abbreviations, emoticons to express feelings, and they do not pay much attention to spelling. All this creates noise that can complicate the task. The tweets carry a lot of potentially interesting information. Their exploitation is one of the main axes of the analysis of the social networks. We show how to access Twitter-related messages. We will initiate a study of the properties of the tweets, and we will follow up on the exploitation of the content of the messages. We will work under R with the package 'twitteR'. The study of tweets is a strong focus of analysis of social networks because Twitter has become an important vector of communication. This example shows that it is easy to initiate an analysis from data extracted directly online. The data preparation phase is of great importance.

Keywords: data mining, language R, social networks, Twitter

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Authors: Khaled Benyounes

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Determination of the rock mechanical properties such as unconfined compressive strength UCS, Young’s modulus E, and tensile strength by the Brazilian test Rtb is considered to be the most important component in drilling and mining engineering project. Research related to establishing correlation between strength and physical parameters of rocks has always been of interest to mining and reservoir engineering. For this, many rock blocks of limestone were collected from the quarry located in Meftah (Algeria), the cores were crafted in the laboratory using a core drill. This work examines the relationships between mechanical properties and some physical properties of limestone. Many empirical equations are established between UCS and physical properties of limestone (such as dry bulk density, velocity of P-waves, dynamic Young’s modulus, alteration index, and total porosity). Other correlations, UCS - tensile strength, dynamic Young’s modulus - static Young’s modulus have been find. Based on the Mohr-Coulomb failure criterion, we were able to establish mathematical relationships that will allow estimating the cohesion and internal friction angle from UCS and indirect tensile strength. Results from this study can be useful for mining industry for resolve range of geomechanical problems such as slope stability.

Keywords: limestone, mechanical strength, Young’s modulus, porosity

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Authors: Diana Katherine Gonzalez Galindo, David Rolando Suarez Mora

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With this study, we used data mining as a new alternative of the solution to evaluate the comments of the customers in order to find a pattern that helps us to determine some behaviors to reduce the deactivation of the partners of the LEVEL app. In one of the greatest business created in the last times, the partners are being affected due to an internal process that compensates the customer for a bad experience, but these comments could be false towards the driver, that’s why we made an investigation to collect information to restructure this process, many partners have been disassociated due to this internal process and many of them refuse the comments given by the customer. The main methodology used in this case study is the observation, we recollect information in real time what gave us the opportunity to see the most common issues to get the most accurate solution. With this new process helped by data mining, we could get a prediction based on the behaviors of the customer and some basic data recollected such as the age, the gender, and others; this could help us in future to improve another process. This investigation gives more opportunities to the partner to keep his account active even if the customer writes a message through the app. The term is trying to avoid a recession of drivers in the future offering improving in the processes, at the same time we are in search of stablishing a strategy which benefits both the app’s managers and the associated driver.

Keywords: agent, driver, deactivation, rider

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Authors: Cisil Gulumser, Francesc Medina, Sevil Veli

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In this study, the synthesis of photocatalytic Bi₂WO₆ was practiced with simple heating processes and the effects of these treatments on the production of the desired compound were investigated. For this purpose, experiments with Bi(NO₃)₃.5H₂O and H₂WO₄ precursors were carried out to synthesize Bi₂WO₆ by four different combinations. These four combinations were grouped in two main sets as ‘treated in microwave reactor’ and ‘directly filtrated’; additionally these main sets were grouped into two subsets as ‘calcined’ and ‘not calcined’. Calcination processes were conducted at temperatures of 400ᵒC, 600ᵒC, and 800ᵒC. X-ray diffraction (XRD) and environmental scanning electron microscopy (ESEM) analyses were performed in order to investigate the crystal structure of powdered product synthesized with each combination. The highest crystallization of produced compounds was observed for calcination at 600ᵒC from each main group.

Keywords: bismuth tungstate, crystallization, microwave, photocatalysts

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Authors: Rojin Bana Derakhshan, Abbas Toloie

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For the purpose of optimizing and developing energy efficiency in building, it is required to recognize key elements of success in optimization of energy consumption before performing any actions. Surveying Principal Components is one of the most valuable result of Linear Algebra because the simple and non-parametric methods are become confusing. So that energy management system implemented according to energy management system international standard ISO50001:2011 and all energy parameters in building to be measured through performing energy auditing. In this essay by simulating used of data mining, the key impressive elements on energy saving in buildings to be determined. This approach is based on data mining statistical techniques using feature selection method and fuzzy logic and convert data from massive to compressed type and used to increase the selected feature. On the other side, influence portion and amount of each energy consumption elements in energy dissipation in percent are recognized as separated norm while using obtained results from energy auditing and after measurement of all energy consuming parameters and identified variables. Accordingly, energy saving solution divided into 3 categories, low, medium and high expense solutions.

Keywords: energy saving, key elements of success, optimization of energy consumption, data mining

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: K. Jahani, J. Razavi

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Nowadays, to decrease the number of downtimes in the industries such as metal mining, petroleum and chemical industries, predictive maintenance is crucial. In order to have efficient predictive maintenance, knowing the performance of critical equipment of production line such as pumps and hydro-cyclones under variable operating parameters, selecting best indicators of this equipment health situations, best locations for instrumentation, and also measuring of these indicators are very important. In this paper, computer aided engineering (CAE) tools are implemented to study some important elements of copper process line, namely slurry pumps and cyclone to predict the performance of these components under different working conditions. These modeling and simulations can be used in predicting, for example, the damage tolerance of the main shaft of the slurry pump or wear rate and location of cyclone wall or pump case and impeller. Also, the simulations can suggest best-measuring parameters, measuring intervals, and their locations.

Keywords: computer aided engineering, predictive maintenance, fault detection, mining process line, slurry pump, hydrocyclone

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Authors: Mohan Kotamrazu

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Tall buildings block and divert strong upper level winds to the ground. These high velocity winds many a time create adverse wind effects at ground level which can be uncomfortable and even compromise the safety of pedestrians and people who frequent the spaces in the vicinity of tall buildings. Discomfort can be experienced around the entrances and corners of tall buildings. Activities such as strolling or sitting in a park, waiting for a bus near a tall building can become highly unpleasant. For the elderly unpleasant conditions can also become dangerous leading to accidents and injuries. Today there is a growing concern among architects, planners and urban designers about the wind environment in the vicinity of tall building. Regulating authorities insist on wind tunnel testing of tall buildings in cities such as Wellington, Auckland, Boston, San Francisco, etc. prior to granting permission for their construction The present paper examines the different ways that tall buildings can induce strong winds at pedestrian level and their impact on people who frequent the spaces around tall buildings.

Keywords: tall buildings, wind effects, wind comfort, wind safety

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Authors: Mohit Kumar, Mayur Betharia

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Healthcare domain, with the emergence of Electronic Medical Record (EMR), collects a lot of data which have been attracting Data Mining expert’s interest. In the past, doctors have relied on their intuition while making critical clinical decisions. This paper presents the means to analyze the Medical workflows to get business insights out of huge dumped medical databases. Market Basket Analysis (MBA) which is a special data mining technique, has been widely used in marketing and e-commerce field to discover the association between products bought together by customers. It helps businesses in increasing their sales by analyzing the purchasing behavior of customers and pitching the right customer with the right product. This paper is an attempt to demonstrate Market Basket Analysis applications in healthcare. In particular, it discusses the Market Basket Analysis Algorithm ‘Apriori’ applications within healthcare in major areas such as analyzing the workflow of diagnostic procedures, Up-selling and Cross-selling of Healthcare Systems, designing healthcare systems more user-friendly. In the paper, we have demonstrated the MBA applications using Angiography Systems, but can be extrapolated to other modalities as well.

Keywords: data mining, market basket analysis, healthcare applications, knowledge discovery in healthcare databases, customer relationship management, healthcare systems

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Authors: Issa Qabaja, Fadi Thabtah

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Email phishing classification is one of the vital problems in the online security research domain that have attracted several scholars due to its impact on the users payments performed daily online. One aspect to reach a good performance by the detection algorithms in the email phishing problem is to identify the minimal set of features that significantly have an impact on raising the phishing detection rate. This paper investigate three known feature selection methods named Information Gain (IG), Chi-square and Correlation Features Set (CFS) on the email phishing problem to separate high influential features from low influential ones in phishing detection. We measure the degree of influentially by applying four data mining algorithms on a large set of features. We compare the accuracy of these algorithms on the complete features set before feature selection has been applied and after feature selection has been applied. After conducting experiments, the results show 12 common significant features have been chosen among the considered features by the feature selection methods. Further, the average detection accuracy derived by the data mining algorithms on the reduced 12-features set was very slight affected when compared with the one derived from the 47-features set.

Keywords: data mining, email classification, phishing, online security

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Authors: K. H. Oyuntungalag, Scott Kenner, O. Erdenetuya

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The life cycle phases of mining projects are described in this guidance document, and includes initial phases (exploration, feasibility and planning), mine development (construction and operations), closure and reclamation. Initial phases relate to field programs and desktop studies intended to build the data and knowledge base, including the design of water management infrastructure and development during these initial phases. Such a model is essential to demonstrate that the water management plan (WMP) will provide adequate water for the mine operations and sufficient capacity for anticipated flows and volumes, and minimize environmental impacts on the receiving environment. The water and mass balance model must cover the whole mine life cycle, from the start of mine development to a date sufficiently far in the future where the reclaimed landscape is considered self- sustaining following complete closure of the mine (i.e., post- closure). The model simulates the movement of water within the components of the water management infrastructure and project operating areas, and calculates chemical loadings to each mine component. At Erdenet Mining company an initial water balance model reflecting the tailings dam, groundwater seepage and mine process water was developed in collaboration with Dr. Scott Kenner (visiting Fulbright scholar). From this preliminary study the following recommendations were made: 1. Develop a detailed groundwater model to simulate seepage from the tailings dam, 2. Establish an evaporation pan for improving evapotranspiration estimates, and 3. Measure changes in storage of water within the tailings dam and other water storage components within the mine processing.

Keywords: evapotranspiration , monitoring program, Erdenet mining, tailings dam

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Authors: Emin Gundogar, Burak Erkayman, Nusret Sazak

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Providing effective management performance through the whole supply chain is critical issue and hard to applicate. The proper evaluation of integrated data may conclude with accurate information. Analysing the supply chain data through OLAP (On-Line Analytical Processing) technologies may provide multi-angle view of the work and consolidation. In this study, association rules and classification techniques are applied to measure the supply chain performance metrics of an automotive manufacturer in Turkey. Main criteria and important rules are determined. The comparison of the results of the algorithms is presented.

Keywords: supply chain performance, performance measurement, data mining, automotive

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Authors: A. J. Julius, E. Imoagene, O. A. Ganiyu

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The purpose of this study is to estimate the economic value of the services and functions rendered by the forest landscape using a conditional logit model. For this study, attributes and levels of forest landscape were chosen; specifically, attributes include topographical forest type, forest type, forest density, recreational factor (side trip, accessibility of valley), and willingness to participate (WTP). Based on these factors, 48 choices sets with balanced and orthogonal form using statistical analysis system (SAS) 9.1 was adopted. The efficiency of the questionnaire was 6.02 (D-Error. 0.1), and choice set and socio-economic variables were analyzed. To reduce the cognitive load of respondents, the 48 choice sets were divided into 4 types in the questionnaire, so that respondents could respond to 12 choice sets, respectively. The study populations were citizens from seven metropolitan cities including Ibadan, Ilorin, Osogbo, etc. and annual WTP per household was asked by using the interview questionnaire, a total of 267 copies were recovered. As a result, Oshogbo had 0.45, and the statistical similarities could not be found except for urban forests, forest density, recreational factor, and level of WTP. Average annual WTP per household for forest landscape was 104,758 Naira (Nigerian currency) based on the outcome from this model, total economic value of the services and functions enjoyed from Nigerian forest landscape has reached approximately 1.6 trillion Naira.

Keywords: economic valuation, urban cities, services, forest landscape, logit model, nigeria

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Authors: Aloysius Hardoko, Susilo

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The root cause of environmental damage post coal mining activities as determined by the province of East Kalimantan as a corridor of economic activity masterplan acceleration of economic development expansion (MP3EI) is the behavior of adults. Adult behavior can be changed through knowledge management and attitude. Based on the root of the problem, the objective of the research is to apply knowledge management and attitude based on holistic approach in learning andragogy as an effort to solve environmental problems after coal mining activities. Research methods to achieve the objective of using quantitative research with pretest posttest group design. Knowledge management and attitudes based on a holistic approach in adult learning are applied through initial learning activities, core and case-based cover of environmental damage. The research instrument is a description of the case of environmental damage. The data analysis uses t-test to see the effect of knowledge management attitude based on holistic approach before and after adult learning. Location and sample of representative research of adults as many as 20 people in Kutai Kertanegara District, one of the districts in East Kalimantan province, which suffered the worst environmental damage. The conclusion of the research result is the application of knowledge management and attitude in adult learning influence to adult knowledge and attitude to overcome environmental problem post coal mining activity.

Keywords: knowledge management and attitude, holistic approach, andragogy learning, environmental damage

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Authors: Abha Gupta, Deepak K. Mishra

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Food security issue in India has surrounded over availability and accessibility of cereal which is regarded as the only food group to check hunger and improve nutrition. Significance of fruits, vegetables, meat and other food products have totally been neglected given the fact that they provide essential nutrients to the body. There is a need to shift the emphasis from cereal-based approach to a more diverse diet so that aim of achieving food security may change from just reducing hunger to an overall health. This paper attempts to analyse how far dietary diversity level has been achieved across different socio-economic groups in India. For this purpose, present paper sets objectives to determine (a) percentage share of different food groups to total food expenditure and consumption by background characteristics (b) source of and preference for all food items and, (c) diversity of diet across socio-economic groups. A cross sectional survey covering 304 households selected through proportional stratified random sampling was conducted in six villages of Aligarh district of Uttar Pradesh, India. Information on amount of food consumed, source of consumption and expenditure on food (74 food items grouped into 10 major food groups) was collected with a recall period of seven days. Per capita per day food consumption/expenditure was calculated through dividing consumption/expenditure by household size and number seven. Food variety score was estimated by giving 0 values to those food groups/items which had not been eaten and 1 to those which had been taken by households in last seven days. Addition of all food group/item score gave result of food variety score. Diversity of diet was computed using Herfindahl-Hirschman index. Findings of the paper show that cereal, milk, roots and tuber food groups contribute a major share in total consumption/expenditure. Consumption of these food groups vary across socio-economic groups whereas fruit, vegetables, meat and other food consumption remain low and same. Estimation of dietary diversity show higher concentration of diet due to higher consumption of cereals, milk, root and tuber products and dietary diversity slightly varies across background groups. Muslims, Scheduled caste, small farmers, lower income class, food insecure, below poverty line and labour families show higher concentration of diet as compared to their counterpart groups. These groups also evince lower mean intake of number of food item in a week due to poor economic constraints and resultant lower accessibility to number of expensive food items. Results advocate to make a shift from cereal based diet to dietary diversity which not only includes cereal and milk products but also nutrition rich food items such as fruits, vegetables, meat and other products. Integrating a dietary diversity approach in food security programmes of the country would help to achieve nutrition security as hidden hunger is widespread among the Indian population.

Keywords: dietary diversity, food Security, India, socio-economic groups

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Authors: Rajkumar Ghosh

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The industrialization of coal mining and related activities has a significant impact on groundwater in the surrounding areas of the Damodar River. The Damodar River basin, located in eastern India, is known as the "Ruhr of India" due to its abundant coal reserves and extensive coal mining and industrial operations. One of the major consequences of collieries on groundwater is the contamination of water sources. Coal mining activities often involve the excavation and extraction of coal through underground or open-pit mining methods. These processes can release various pollutants and chemicals into the groundwater, including heavy metals, acid mine drainage, and other toxic substances. As a result, the quality of groundwater in the Damodar River region has deteriorated, making it unsuitable for drinking, irrigation, and other purposes. The high concentration of heavy metals, such as arsenic, lead, and mercury, in the groundwater has posed severe health risks to the local population. Prolonged exposure to contaminated water can lead to various health problems, including skin diseases, respiratory issues, and even long-term ailments like cancer. The contamination has also affected the aquatic ecosystem, harming fish populations and other organisms dependent on the river's water. Moreover, the excessive extraction of groundwater for industrial processes, including coal washing and cooling systems, has resulted in a decline in the water table and depletion of aquifers. This has led to water scarcity and reduced availability of water for agricultural activities, impacting the livelihoods of farmers in the region. Efforts have been made to mitigate these issues through the implementation of regulations and improved industrial practices. However, the historical legacy of coal industrialization continues to impact the groundwater in the Damodar River area. Remediation measures, such as the installation of water treatment plants and the promotion of sustainable mining practices, are essential to restore the quality of groundwater and ensure the well-being of the affected communities. In conclusion, the coal industrialization in the Damodar River surrounding has had a detrimental impact on groundwater. This research focuses on soil subsidence induced by the over-exploitation of ground water for dewatering open pit coal mines. Soil degradation happens in arid and semi-arid regions as a result of land subsidence in coal mining region, which reduces soil fertility. Depletion of aquifers, contamination, and water scarcity are some of the key challenges resulting from these activities. It is crucial to prioritize sustainable mining practices, environmental conservation, and the provision of clean drinking water to mitigate the long-lasting effects of collieries on the groundwater resources in the region.

Keywords: coal mining, groundwater, soil subsidence, water table, damodar river

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Authors: Hans Frenk, Sonya Javadi, Semih Onur Sezer

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We consider the so-called end of life inventory problem for the supplier of a product in its final phase of the service life cycle. This phase starts when the production of the items stops and continues until the warranty of the last sold item expires. At the beginning of this phase, the supplier places a final order for spare parts to serve customers coming with defective items. At any time during the final phase, the supplier may also decide to switch to an alternative and more cost-effective policy. This alternative policy may be in the form of replacing a defective item with a substitutable product or offering discounts / rebates on new generation products. In this setup, the objective is to find a final order quantity and also a switching time which will minimize the total expected discounted cost. We study this problem under a general cost structure in a continuous-time framework where arrivals of defective items are given by a non-homogeneous Poisson process. We consider four formulations which differ by the nature of the switching time. These formulations are studied in detail and properties of the objective function are derived in each case. Using these properties, we provide exact algorithms for efficient numerical implementations. Numerical examples are provided illustrating the application of these algorithms. In these examples, we also compare the costs associated with these different formulations.

Keywords: End-of-life inventory control, martingales, optimization, service parts

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Authors: Steven W. Carruthers

Abstract:

The purpose of the present research is to equate two test forms as part of a study to evaluate the educational effectiveness of the ARTé: Mecenas art history learning game. The researcher applied Item Response Theory (IRT) procedures to calculate item, test, and mean-sigma equating parameters. With the sample size n=134, test parameters indicated “good” model fit but low Test Information Functions and more acute than expected equating parameters. Therefore, the researcher applied equipercentile equating and linear equating to raw scores and compared the equated form parameters and effect sizes from each method. Item scaling in IRT enables the researcher to select a subset of well-discriminating items. The mean-sigma step produces a mean-slope adjustment from the anchor items, which was used to scale the score on the new form (Form R) to the reference form (Form Q) scale. In equipercentile equating, scores are adjusted to align the proportion of scores in each quintile segment. Linear equating produces a mean-slope adjustment, which was applied to all core items on the new form. The study followed a quasi-experimental design with purposeful sampling of students enrolled in a college level art history course (n=134) and counterbalancing design to distribute both forms on the pre- and posttests. The Experimental Group (n=82) was asked to play ARTé: Mecenas online and complete Level 4 of the game within a two-week period; 37 participants completed Level 4. Over the same period, the Control Group (n=52) did not play the game. The researcher examined between group differences from post-test scores on test Form Q and Form R by full-factorial Two-Way ANOVA. The raw score analysis indicated a 1.29% direct effect of form, which was statistically non-significant but may be practically significant. The researcher repeated the between group differences analysis with all three equating methods. For the IRT mean-sigma adjusted scores, form had a direct effect of 8.39%. Mean-sigma equating with a small sample may have resulted in inaccurate equating parameters. Equipercentile equating aligned test means and standard deviations, but resultant skewness and kurtosis worsened compared to raw score parameters. Form had a 3.18% direct effect. Linear equating produced the lowest Form effect, approaching 0%. Using linearly equated scores, the researcher conducted an ANCOVA to examine the effect size in terms of prior knowledge. The between group effect size for the Control Group versus Experimental Group participants who completed the game was 14.39% with a 4.77% effect size attributed to pre-test score. Playing and completing the game increased art history knowledge, and individuals with low prior knowledge tended to gain more from pre- to post test. Ultimately, researchers should approach test equating based on their theoretical stance on Classical Test Theory and IRT and the respective  assumptions. Regardless of the approach or method, test equating requires a representative sample of sufficient size. With small sample sizes, the application of a range of equating approaches can expose item and test features for review, inform interpretation, and identify paths for improving instruments for future study.

Keywords: effectiveness, equipercentile equating, IRT, learning games, linear equating, mean-sigma equating

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Authors: M. Lloret-Climent, J. Nescolarde-Selva

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The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Keywords: attractor, invariant set, tourist flows, orbits, social responsibility, tourism, tourist variables

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Authors: Jose Daniel Braga Alves, Joaquim Gois, Alexandre Leite

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This abstract presents the responsible and sustainable mining case study of a Portuguese mine operation, highlighting how mine exploitation can sustainably exist in balance with the environment, aligned with all stakeholders. The mining operation is remotely located in a United Nations (UN) biodiversity reserve, away from major industrial centers or logistical ports, and presents an interesting investigation to assess the balanced mine operation in alignment with all key stakeholders, which presents unique opportunities as well as challenges. Based on the sustainable mining framework, it is intended to detail examples of best practices from Sociedade Mineira de Neves-Corvo (SOMINCOR), demonstrating social acceptance by the local community, health, and safety at work, reduction of environmental impacts and management of mining waste, which directly influence the acceptance and recognition of a sustainable operation. The case study aims to present the SOMINCOR approach to sustainable mining, focusing on social responsibility, considering materials provided by Lundin Mining Corporation (LMC) and SOMINCOR and the socially responsible approach of the mining operations., referencing related international guidelines, UN Sustainable Development Goals. The researchers reviewed LMC's annual Sustainability Reports (2019, 2020 and 2021) and updated information regarding material topics of the most significant interest to internal and external stakeholders. These material topics formed the basis of the corporation-wide sustainability strategy. LMC's Responsible Mining Policy (RMP) was reviewed, focusing on the commitment that guides the approach to responsible operation and management of the Company's business. Social performance, compliance, environmental management, governance, human rights, and economic contribution are principles of the RMP. The Human Rights Risk Impact Assessment (HRRIA), based on frameworks including UN Guiding Principles (UNGP), Voluntary Principles on Security and Human Rights, and a community engagement program implemented (SLO index), was part of this research. The program consists of ongoing surveys and perceptions studies using behavioural science insights, data from which was not available within the timeframe of completing this research. LMC stakeholder engagement standards and grievance mechanisms were also reviewed. Stakeholder engagement and the community's perception are key to this operation to ensure social license to operate (SLO). Preliminary surveys with local communities provided input data for the local development strategy. After the implementation of several initiatives, subsequent surveys were performed to assess acceptance and trust from the local communities and changes to the SLO index. SOMINCOR's operation contributes to 12 out of 17 sustainable development goals. From the assessed and available data, local communities and social engagement are priorities to SOMINCOR. Experience to date shows that the continual engagement with local communities and the grievance mechanisms in place are respected and followed for all concerns presented by any stakeholder. It can be concluded that this underground mine in Portugal complies with applicable regulations and goes beyond them with regard to sustainable development and engagement with key stakeholders.

Keywords: sustainable mining, development goals, portuguese mining, zinc copper

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Authors: Philip T. Broughton, Mark P. Bettney, Isla L. Smail

Abstract:

Effective treatment of ground instability is essential when managing the impacts associated with historic mining. A field trial was undertaken by the Coal Authority to investigate the geotechnical performance and potential use of composite materials comprising resin and fill or stone to safely treat surface collapses, such as crown-holes, associated with shallow mining. Test pits were loosely filled with various granular fill materials. The fill material was injected with commercially available silicate and polyurethane resin foam products. In situ and laboratory testing was undertaken to assess the geotechnical properties of the resultant composite materials. The test pits were subsequently excavated to assess resin permeation. Drilling and resin injection was easiest through clean limestone fill materials. Recycled building waste fill material proved difficult to inject with resin; this material is thus considered unsuitable for use in resin composites. Incomplete resin permeation in several of the test pits created irregular ‘blocks’ of composite. Injected resin foams significantly improve the stiffness and resistance (strength) of the un-compacted fill material. The stiffness of the treated fill material appears to be a function of the stone particle size, its associated compaction characteristics (under loose tipping) and the proportion of resin foam matrix. The type of fill material is more critical than the type of resin to the geotechnical properties of the composite materials. Resin composites can effectively support typical design imposed loads. Compared to other traditional treatment options, such as cement grouting, the use of resin composites is potentially less disruptive, particularly for sites with limited access, and thus likely to achieve significant reinstatement cost savings. The use of resin composites is considered a suitable option for the future treatment of shallow mining collapses.

Keywords: composite material, ground improvement, mining legacy, resin

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