Search results for: environmental mining

Authors: Mir Md. Abdus Salam, Muhammad Mohsin, Pertti Pulkkinen, Paavo Pelkonen, Ari Pappinen

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Soil and water pollution caused by extensive mining practices can adversely affect environmental components, such as humans, animals, and plants. Despite a generally positive contribution to society, mining practices have become a serious threat to biological systems. As metals do not degrade completely, they require immobilization, toxicity reduction, or removal. A greenhouse experiment was conducted to evaluate the effects of lime and N100 (11-amino-1-hydroxyundecylidene) chelate amendment on the growth and phytoextraction potential of the willow variety Klara (S. viminalis × S. schwerinii × S. dasyclados) grown in soils heavily contaminated with copper (Cu). The plants were irrigated with tap or processed water (mine wastewater). The sequential extraction technique and inductively coupled plasma-mass spectrometry (ICP-MS) tool were used to determine the extractable metals and evaluate the fraction of metals in the soil that could be potentially available for plant uptake. The results suggest that the combined effects of the contaminated soil and processed water inhibited growth parameter values. In contrast, the accumulation of Cu in the plant tissues was increased compared to the control. When the soil was supplemented with lime and N100; growth parameter and resistance capacity were significantly higher compared to unamended soil treatments, especially in the contaminated soil treatments. The combined lime- and N100-amended soil treatment produced higher growth rate of biomass, resistance capacity and phytoextraction efficiency levels relative to either the lime-amended or the N100-amended soil treatments. This study provides practical evidence of the efficient chelate-assisted phytoextraction capability of Klara and highlights its potential as a viable and inexpensive novel approach for in-situ remediation of Cu-contaminated soils and mine wastewaters. Abandoned agricultural, industrial and mining sites can also be utilized by a Salix afforestation program without conflict with the production of food crops. This kind of program may create opportunities for bioenergy production and economic development, but contamination levels should be examined before bioenergy products are used.

Keywords: copper, Klara, lime, N100, phytoextraction

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Authors: Chong Zhang, Guoming Tang, Bin Ge, Jiuyang Tang

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With the fast growing road traffic and increasingly severe traffic congestion, more and more citizens choose to use the public transportation for daily travelling. Meanwhile, the shared bike provides a convenient option for the first and last mile to the public transit. As of 2016, over one thousand cities around the world have deployed the bike-sharing system. The combination of these two transportations have stimulated the development of each other and made significant contribution to the reduction of carbon footprint. A lot of work has been done on mining the riding behaviors in various bike-sharing systems. Most of them, however, treated the bike-sharing system as an isolated system and thus their results provide little reference for the public transit construction and optimization. In this work, we treat the bike-sharing and public transit as a whole and investigate the customers’ bike-and-ride behaviors. Specifically, we develop a spatio-temporal traffic delivery model to study the riding patterns between the two transportation systems and explore the traffic characteristics (e.g., distributions of customer arrival/departure and traffic peak hours) from the time and space dimensions. During the model construction and evaluation, we make use of large open datasets from real-world bike-sharing systems (the CitiBike in New York, GoBike in San Francisco and BIXI in Montreal) along with corresponding public transit information. The developed two-dimension traffic model, as well as the mined bike-and-ride behaviors, can provide great help to the deployment of next-generation intelligent transportation systems.

Keywords: riding pattern mining, bike-sharing system, public transportation, bike-and-ride behavior

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Authors: Reiner-Ace P. Mateo, Vince Paolo F. Obille

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The traditional method of classifying the potential mineral resources requires a significant amount of time and money. In this paper, an alternative way to classify potential mineral resources with GIS application in Surigao del Sur. The three (3) analog map data inputs integrated to GIS are geologic map, topographic map, and land cover/vegetation map. The indicators used in the classification of potential nickel laterite integrated from the analog map data inputs are a geologic indicator, which is the presence of ultramafic rock from the geologic map; slope indicator and the presence of plateau edges from the topographic map; areas of forest land, grassland, and shrublands from the land cover/vegetation map. The potential mineral of the area was classified from low up to very high potential. The produced mineral potential classification map of Surigao del Sur has an estimated 4.63% low nickel laterite potential, 42.15% medium nickel laterite potential, 43.34% high nickel laterite potential, and 9.88% very high nickel laterite from its ultramafic terrains. For the validation of the produced map, it was compared with known occurrences of nickel laterite in the area using a nickel mining tenement map from the area with the application of remote sensing. Three (3) prominent nickel mining companies were delineated in the study area. The generated potential classification map of nickel-laterite in Surigao Del Sur may be of aid to the mining companies which are currently in the exploration phase in the study area. Also, the currently operating nickel mines in the study area can help to validate the reliability of the mineral classification map produced.

Keywords: mineral potential classification, nickel laterites, GIS, remote sensing, Surigao del Sur

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Authors: Elaheh Talebi, Fariba Yavari, Lucy Philip, Lesley Town

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The mining industry generates vast amounts of data, necessitating robust data management systems and advanced analytics tools to achieve better decision-making processes in the development of mining production and maintaining safety. This paper highlights the advantages of Power BI, a powerful intelligence tool, over traditional Excel-based approaches for effectively managing and harnessing mining data. Power BI enables professionals to connect and integrate multiple data sources, ensuring real-time access to up-to-date information. Its interactive visualizations and dashboards offer an intuitive interface for exploring and analyzing geotechnical data. Advanced analytics is a collection of data analysis techniques to improve decision-making. Leveraging some of the most complex techniques in data science, advanced analytics is used to do everything from detecting data errors and ensuring data accuracy to directing the development of future project phases. However, while Power BI is a robust tool, specific visualizations required by geotechnical engineers may have limitations. This paper studies the capability to use Python or R programming within the Power BI dashboard to enable advanced analytics, additional functionalities, and customized visualizations. This dashboard provides comprehensive tools for analyzing and visualizing key geotechnical data metrics, including spatial representation on maps, field and lab test results, and subsurface rock and soil characteristics. Advanced visualizations like borehole logs and Stereonet were implemented using Python programming within the Power BI dashboard, enhancing the understanding and communication of geotechnical information. Moreover, the dashboard's flexibility allows for the incorporation of additional data and visualizations based on the project scope and available data, such as pit design, rock fall analyses, rock mass characterization, and drone data. This further enhances the dashboard's usefulness in future projects, including operation, development, closure, and rehabilitation phases. Additionally, this helps in minimizing the necessity of utilizing multiple software programs in projects. This geotechnical dashboard in Power BI serves as a user-friendly solution for analyzing, visualizing, and communicating both new and historical geotechnical data, aiding in informed decision-making and efficient project management throughout various project stages. Its ability to generate dynamic reports and share them with clients in a collaborative manner further enhances decision-making processes and facilitates effective communication within geotechnical projects in the mining industry.

Keywords: geotechnical data analysis, power BI, visualization, decision-making, mining industry

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Authors: Dasom Kim, William Xiu Shun Wong, Yoonjin Hyun, Donghoon Lee, Minji Paek, Sungho Byun, Namgyu Kim

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There have been many researches on document classification for classifying voluminous documents automatically. Through document classification, we can assign a specific category to each unlabeled document on the basis of various machine learning algorithms. However, providing labeled documents manually requires considerable time and effort. To overcome the limitations, the semi-supervised learning which uses unlabeled document as well as labeled documents has been invented. However, traditional document classifiers, regardless of supervised or semi-supervised ones, cannot sufficiently explain the reason or the process of the classification. Thus, in this paper, we proposed a methodology to visualize major topics and class components of each document. We believe that our methodology for visualizing topics and classes of each document can enhance the reliability and explanatory power of document classifiers.

Keywords: data mining, document classifier, text mining, topic modeling

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Authors: Faiza Hussain, Usman Qamar

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Synonym-based searching is recognized to be a complicated problem as text mining from unstructured data of web is challenging. Finding useful information which matches user need from bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration to realize the technique. Parts-of-Speech tagging is applied for pattern generation of the query and a thesaurus for this experiment was formed and used. Comparison with Non-Context Based Searching, Context Based searching proved to be a more efficient approach while dealing with linguistic semantics. This approach is very beneficial in doing intent based searching. Finally, results and future dimensions are presented.

Keywords: natural language processing, text mining, information retrieval, parts-of-speech tagging, grammar, semantics

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Authors: Sarah Niklas, Lynne Chester, Mark Diesendorf

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Geopolitical tensions, climate change and recent movements favouring a transformative shift in institutional power structures have influenced the economics of conventional energy supply for decades. This study takes a multi-dimensional approach to illustrate the potential of renewable energy (RE) technology to provide a pathway to a low-carbon economy driven by ecologically sustainable, independent and socially just energy. This comparative analysis identifies economic, political and social drivers that shaped the adoption of RE policy in two significantly different economies, Germany and Australia, with strong and weak commitments to RE respectively. Two complementary political-economy theories frame the document-based analysis. Régulation Theory, inspired by Marxist ideas and strongly influenced by contemporary economic problems, provides the background to explore the social relationships contributing the adoption of RE within the macro-economy. Varieties of Capitalism theory, a more recently developed micro-economic approach, examines the nature of state-firm relationships. Together these approaches provide a comprehensive lens of analysis. Germany’s energy policy transformed substantially over the second half of the last century. The development is characterised by the coordination of societal, environmental and industrial demands throughout the advancement of capitalist regimes. In the Fordist regime, mass production based on coal drove Germany’s astounding economic recovery during the post-war period. Economic depression and the instability of institutional arrangements necessitated the impulsive seeking of national security and energy independence. During the postwar Flexi-Fordist period, quality-based production, innovation and technology-based competition schemes, particularly with regard to political power structures in and across Europe, favoured the adoption of RE. Innovation, knowledge and education were institutionalized, leading to the legislation of environmental concerns. Lastly the establishment of government-industry-based coordinative programs supported the phase out of nuclear power and the increased adoption of RE during the last decade. Australia’s energy policy is shaped by the country’s richness in mineral resources. Energy policy largely served coal mining, historically and currently one of the most capital-intense industry. Assisted by the macro-economic dimensions of institutional arrangements, social and financial capital is orientated towards the export-led and strongly demand-oriented economy. Here energy policy serves the maintenance of capital accumulation in the mining sector and the emerging Asian economies. The adoption of supportive renewable energy policy would challenge the distinct role of the mining industry within the (neo)-liberal market economy. The state’s protective role of the mining sector has resulted in weak commitment to RE policy and investment uncertainty in the energy sector. Recent developments, driven by strong public support for RE, emphasize the sense of community in urban and rural areas and the emergence of a bottom-up approach to adopt renewables. Thus, political economy frameworks on both the macro-economic (Regulation Theory) and micro-economic (Varieties of Capitalism theory) scales can together explain the strong commitment to RE in Germany vis-à-vis the weak commitment in Australia.

Keywords: political economy, regulation theory, renewable energy, social relationships, energy transitions

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Authors: Sanaz Moayer, Fang Huang, Scott Gardner

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In the highly leveraged business world of today, an organisation’s success depends on how it can manage and organize its traditional and intangible assets. In the knowledge-based economy, knowledge as a valuable asset gives enduring capability to firms competing in rapidly shifting global markets. It can be argued that ability to create unique knowledge assets by configuring ICT and human capabilities, will be a defining factor for international competitive advantage in the mid-21st century. The concept of KM is recognized in the strategy literature, and increasingly by senior decision-makers (particularly in large firms which can achieve scalable benefits), as an important vehicle for stimulating innovation and organisational performance in the knowledge economy. This thinking has been evident in professional services and other knowledge intensive industries for over a decade. It highlights the importance of social capital and the value of the intellectual capital embedded in social and professional networks, complementing the traditional focus on creation of intellectual property assets. Despite the growing interest in KM within professional services there has been limited discussion in relation to multinational resource based industries such as mining and petroleum where the focus has been principally on global portfolio optimization with economies of scale, process efficiencies and cost reduction. The Australian minerals and metals mining industry, although traditionally viewed as capital intensive, employs a significant number of knowledge workers notably- engineers, geologists, highly skilled technicians, legal, finance, accounting, ICT and contracts specialists working in projects or functions, representing potential knowledge silos within the organisation. This silo effect arguably inhibits knowledge sharing and retention by disaggregating corporate memory, with increased operational and project continuity risk. It also may limit the potential for process, product, and service innovation. In this paper the strategic application of knowledge management incorporating contemporary ICT platforms and data mining practices is explored as an important enabler for knowledge discovery, reduction of risk, and retention of corporate knowledge in resource based industries. With reference to the relevant strategy, management, and information systems literature, this paper highlights possible connections (currently undergoing empirical testing), between an Strategic Knowledge Management (SKM) framework incorporating supportive Data Mining (DM) practices and competitive advantage for multinational firms operating within the Australian resource sector. We also propose based on a review of the relevant literature that more effective management of soft and hard systems knowledge is crucial for major Australian firms in all sectors seeking to improve organisational performance through the human and technological capability captured in organisational networks.

Keywords: competitive advantage, data mining, mining organisation, strategic knowledge management

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: Runlang Zhu, Weijun Gao, Yinqi Zhang, Gangwei Cai

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In order to deal with issues such as the environmental problems and aging of the population, the Japanese government wanted to achieve goals like 'a city where everyone wants to live' and 'a city full of energy for everyone' by creating environmental, social, and economic values in the process of urban development. They began to promote the concept of 'Environmental Future City' in 2010, aiming to create cities and regions with excellent environments, sustainable economic development, and social systems. After taking a look at the history, concept, and development of environmental future cities, the paper will discuss the evaluation system of them, introduce representative cases, and point out what other cities can learn from their development process.

Keywords: environmental future city, city concept, CASBEE, environmental performance assessment

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Authors: K. Y. Chen, H. Chua, C. W. Kan

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In this study, we will analyze Germany’s environmental situation such as water and air quality and review its environmental policy. In addition, we will collect the yearly environmental data as well as information concerning public environmental investment. Based on the data collect, we try to find out the relationship between public environmental investment and sustainable development in Germany. In addition, after comparing the trend of environmental quality and situation of environmental policy and investment, we may have some conclusions and learnable aspects to refer to. Based upon the data collected, it was revealed that Germany has established a well-developed institutionalization of environmental education. And the ecological culture at school is dynamic and continuous renewal. The booming of green markets in Germany is a very successful experience for learning. The green market not only creates a number of job opportunities, but also helps the government to improve and protect the environment. Acknowledgement: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: Germany, public environmental investment, environment quality, sustainable development

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Authors: Volker Mittendorf, Andre Schmale

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In this case study, we want to explore the Twitter-use of candidates during the state parliamentary elections-year 2018 in Bavaria, Germany. This paper focusses on the seven parties that probably entered the parliament. Against this background, the paper classifies the use of language as populism which itself is considered as a political communication style. First, we determine the election campaigns which started in the years 2017 on Twitter, after that we categorize the posting times of the different direct candidates in order to derive ideal types from our empirical data. Second, we have done the exploration based on the dictionary of concerned citizens which contains German political language of the right and the far right. According to that, we are analyzing the corpus with methods of text mining and social network analysis, and afterwards we display the results in a network of words of concerned citizen communication style (CCCS).

Keywords: populism, communication style, election, text mining, social media

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Authors: Vishwas Chakranarayan, Mariyam Al Salman

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Despite the global environmental threats, previous approaches used to overcome these problems have failed to prevent environmental degradation. Scholars believe that entrepreneurs can help conserve habitats, combat climate change, increase freshwater availability, sustain biodiversity, and reduce environmental degradation and deforestation. The pandemic is creating a different ecosystem for fostering the eco-entrepreneurship opportunities. However, attending a course physically is a challenge for many willing learners. Therefore, it is an opportune time to contemplate on developing a social entrepreneurship curriculum which can be offered online.

Keywords: ecopreneurship, environmental problems, environmental degradation, entrepreneurship education

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Authors: Cristina Schreiner, Romeo Ciobanu, Marius Pislaru

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This paper aims to build a system based on fuzzy models that can be implemented in the assessment of ecological systems, to determine appropriate methods of action for reducing adverse effects on environmental and implicit the population. The model proposed provides new perspective for environmental assessment, and it can be used as a practical instrument for decision-making.

Keywords: ecosystem model, environmental security, fuzzy logic, sustainability of habitable regions

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Authors: Koutsopoulou Ioanna, Gkintoni Evgenia, Halkiopoulos Constantinos, Antonopoulou Hera

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Recent advances in Internet Computer Technology (ICT) and the ever-increasing use of technological equipment amongst adolescents and young adults along with unattended access to the internet and social media and uncontrolled use of smart phones and PCs have caused social problems like sexting to emerge. The main purpose of the present article is first to present an analytic theoretical framework of sexting as a recent social phenomenon based on studies that have been conducted the last decade or so; and second to investigate Greek students’ and also social network users, sexting perceptions and to record how often social media users exchange sexual messages and to retrace demographic variables predictors. Data from 1,000 students were collected and analyzed and all statistical analysis was done by the software package WEKA. The results indicate among others, that the use of data mining methods is an important tool to draw conclusions that could affect decision and policy making especially in the field and related social topics of educational psychology. To sum up, sexting lurks many risks for adolescents and young adults students in Greece and needs to be better addressed in relevance to the stakeholders as well as society in general. Furthermore, policy makers, legislation makers and authorities will have to take action to protect minors. Prevention strategies based on Greek cultural specificities are being proposed. This social problem has raised concerns in recent years and will most likely escalate concerns in global communities in the future.

Keywords: educational ethics, sexting, Greek sexters, sex education, data mining

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Authors: Muhammad Saqlain, Nazar Abbas Saqib, Muazzam A. Khan

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Heart Failure (HF) has become the major health problem in our society. The prevalence of HF has increased as the patient’s ages and it is the major cause of the high mortality rate in adults. A successful identification and progression of HF can be helpful to reduce the individual and social burden from this syndrome. In this study, we use a real data set of cardiac patients to propose a classification model for the identification and progression of HF. The data set has divided into three age groups, namely young, adult, and old and then each age group have further classified into four classes according to patient’s current physical condition. Contemporary Data Mining classification algorithms have been applied to each individual class of every age group to identify the HF. Decision Tree (DT) gives the highest accuracy of 90% and outperform all other algorithms. Our model accurately diagnoses different stages of HF for each age group and it can be very useful for the early prediction of HF.

Keywords: decision tree, heart failure, data mining, classification model

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Authors: Zahra Bakhtiari

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This article explores the development and evolution of the concept of environmental justice, which has shifted from being dominated by white and middle-class individuals to a civil struggle by marginalized communities against environmental injustices. Environmental justice aims to achieve equity in decision-making and policy-making related to the environment. The concept of justice in this context includes four fundamental aspects: distribution, procedure, recognition, and capabilities. Recent scholars have attempted to broaden the concept of justice to include dimensions of participation, recognition, and capabilities. Focusing on all four dimensions of environmental justice is crucial for effective planning and policy-making to address environmental issues. Ignoring any of these aspects can lead to the failure of efforts and the waste of resources.

Keywords: environmental justice, distribution, procedure, recognition, capabilities

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Authors: Ami Fadhillah Amir Abdul Nasir, Amanda C. Niehaus, Skye F. Cameron, Frank A. Von Hippel, John Postlethwait​, Robbie S. Wilson

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For suicidal breeders, the physiological stresses and energetic costs of breeding are fatal. Environmental stressors such as pollution should compound these costs, yet suicidal breeding is so rare among mammals that this is unknown. Here, we explored the consequences of metal contamination to the health, aging and performance of endangered, suicidally-breeding northern quolls (Dasyurus hallucatus) living near an active manganese mine on Groote Eylandt, Northern Territory, Australia. We found respirable manganese dust at levels exceeding international recommendations even 20km from mining sites and substantial accumulation of manganese within quolls’ hair, testes, and in two brain regions—the neocortex and cerebellum, responsible for sensory perception and motor function, respectively. Though quolls did not differ in sprint speeds, motor skill, or manoeuvrability, those with higher accumulation of manganese crashed at lower speeds during manoeuvrability tests, indicating a potential effect on sight or cognition. Immune function and telomere length declined over the breeding season, as expected with ageing, but manganese contamination exacerbated immune declines and suppressed cortisol. Unexpectedly, male quolls with higher levels of manganese had longer telomeres, supporting evidence of unusual telomere dynamics among Dasyurids—though whether this affects their lifespan is unknown. We posit that sublethal contamination via pollution, mining, or urbanisation imposes physiological costs on wildlife that may diminish reproductive success or survival.

Keywords: ecotoxicology, heavy metal, manganese, telomere length, cortisol, locomotor

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Authors: K. R. Balabiyev, A. O. Kaipbayeva

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The article discusses the legal framework of the government’s environmental function and analyzes the role of the national policy in protection of wetlands. The problem is of interest for it deals with the most important branch of economy–utilization of Kazakhstan’s natural resources, protection of health and environmental well being of the population. Development of a long-term environmental program addressing the protection of wetlands represents the final stage of the government’s environmental policy, and is a relatively new function for the public administration system. It appeared due to the environmental measures that require immediate decisions to be taken. It is an integral part of the effort in the field of management of state-owned natural resource, as well as of the measures aimed at efficient management of natural resources to avoid their early depletion or contamination.

Keywords: environmental focus, government’s environmental function, protection of wetlands, Kazakhstan

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Authors: Huilei Wang, Yuanfeng Wang

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In the early period of China, economy developed rapidly at the cost of environment. Recently, it is generally recognized that the heavily polluted environment not only puts a brake on economic development but also paces negative impact on people’ health as well as probably next decades of generations. Accordingly, the latest Environmental Protection Law revised in 2014 makes a clear-cut division of environmental responsibility and regulates stricter penalties of breaching law. As the new environmental law is enforced gradually, environmental forensic is increasingly required in the process of ascertaining facts in judicial proceedings of environmental cases. Based on the outcomes of documentary analysis for all environmental cases judged on the basis of new environmental law, it is concluded that there still exists problems in present system of environmental forensic. Thus, this paper is aimed to make proposition on improving Chinese environmental forensic system, which involves: (i) promoting capability of environmental forensic system (EFS) to handle professional questions; (ii) develop price mechanism; (iii) multi-departments cooperate to establish unifying and complete EFS system;(iv) enhance the probative value of results of EFS. Such protocol for amending present regulation on environmental forensic is of significant importance because a quality report of environmental forensic will contributes to providing strong probative evidence of culprits’ activity of releasing contaminant into environment, degree of damages for victims and above all, causality between the behavior of public nuisance and damages.

Keywords: China, environmental cases, environmental forensic system, proposition

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Authors: Yael Teff-Seker

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More often than not, ecosystems do not follow anthropogenic political borders. Thus, transboundary environmental protection or rehabilitation initiatives can be beneficial and at times even vital for supporting healthy ecosystems. Marine areas demand unique considerations and challenges for such initiatives, as maritime borders tend to be less defined, less fortified and less visible. In areas of recent conflict, cross-border environmental initiatives can also improve relations between states and promote peace-building efforts, in addition to their environmental benefits. The current study reviews the current literature on transboundary marine environmental protection initiatives that take place in these areas and focuses on joint initiatives in Israel-Jordan and Croatia-Slovenia. In addition to factors described in the literature such as funding and third-party involvement, findings suggest that the peripheral location of marine environmental initiatives can be beneficial for the success of such initiatives, as well as facilitating border crossing and the extent to which such initiatives advance other governmental goals. A sense of urgency, environmental or other, has also been found to be highly relevant to project success.

Keywords: environmental cooperation, environmental peacebuilding, marine environment, environmental conflict, environmental management

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Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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Authors: Ahmad. A. Kardan, Amir Narimani, Foozhan Ataiefard

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Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC forums by applying social network analysis and association rule mining techniques. Initial results indicate that the proposed recommender system performs comparatively well with regard to limited available data from users' previous posts in the forum.

Keywords: association rule mining, hybrid recommender system, massive open online courses, MOOCs, social network analysis

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Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

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Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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Authors: David L. Knott, Robert Kingsland, Alistair Hitchon

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The proposed Newcastle Light Rail is a key part of the revitalisation of Newcastle, NSW and will provide a frequent and reliable travel option throughout the city centre, running from Newcastle Interchange at Wickham to Pacific Park in Newcastle East, a total of 2.7 kilometers in length. Approximately one-third of the route, along Hunter and Scott Streets, is subject to potential shallow underground mine workings. The extent of mining and seams mined is unclear. Convicts mined the Yard Seam and overlying Dudley (Dirty) Seam in Newcastle sometime between 1800 and 1830. The Australian Agricultural Company mined the Yard Seam from about 1831 to the 1860s in the alignment area. The Yard Seam was about 3 feet (0.9m) thick, and therefore, known as the Yard Seam. Mine maps do not exist for the workings in the area of interest and it was unclear if both or just one seam was mined. Information from 1830s geological mapping and other data showing shaft locations were used along Scott Street and information from the 1908 Royal Commission was used along Hunter Street to develop an investigation program. In addition, mining was encountered for several sites to the south of the alignment at depths of about 7 m to 25 m. Based on the anticipated depths of mining, it was considered prudent to assess the potential for sinkhole development on the proposed alignment and realigned underground utilities and to obtain approval for the work from Subsidence Advisory NSW (SA NSW). The assessment consisted of a desktop study, followed by a subsurface investigation. Four boreholes were drilled along Scott Street and three boreholes were drilled along Hunter Street using HQ coring techniques in the rock. The placement of boreholes was complicated by the presence of utilities in the roadway and traffic constraints. All the boreholes encountered the Yard Seam, with conditions varying from unmined coal to an open void, indicating the presence of mining. The geotechnical information obtained from the boreholes was expanded by using various downhole techniques including; borehole camera, borehole sonar, and downhole geophysical logging. The camera provided views of the rock and helped to explain zones of no recovery. In addition, timber props within the void were observed. Borehole sonar was performed in the void and provided an indication of room size as well as the presence of timber props within the room. Downhole geophysical logging was performed in the boreholes to measure density, natural gamma, and borehole deviation. The data helped confirm that all the mining was in the Yard Seam and that the overlying Dudley Seam had been eroded in the past over much of the alignment. In summary, the assessment allowed the potential for sinkhole subsidence to be assessed and a mitigation approach developed to allow conditional approval by SA NSW. It also confirmed the presence of mining in the Yard Seam, the depth to the seam and mining conditions, and indicated that subsidence did not appear to have occurred in the past.

Keywords: downhole investigation techniques, drilling, mine subsidence, yard seam

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Authors: Daria Karasalihovic Sedlar, Lucija Jukic, Ivan Smajla, Marija Macenic

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This paper analyses possible geothermal energy production from a mature oil reservoir based on exploitation of underlying aquifer thermal energy for the purpose of heating public buildings. Research was conducted based on the case study of the City of Ivanic-Grad public buildings energy demand and Ivanic oil filed that is situated in the same area. Since the City of Ivanic is one of the few cities in the EU where hydrocarbon exploitation has been taking place for decades almost entirely in urban area, decommissioning of oil wells is inevitable; therefore, the research goal was to investigate how to extend the life-time of the reservoir by exploiting geothermal brine beneath the oil reservoir in an environmental friendly manner. This kind of a project is extremely complex in all segments, from documentation preparation, implementation of technological solutions, and providing ecological measures for environmentally acceptable geothermal energy production and utilization. New mining activities that will be needed for the development of geothermal project at the observed Hydrocarbon Exploitation Field Ivanic will be carried out in order to prepare wells for increasing geothermal brine production. These operations involve the conversion of existing wells (well completion for conversion of the observation wells to production ones) along with workover activities, installation of new heat exchangers, and pipelines. Since the wells are in the urban area of the City of Ivanic-Grad in high density populated area, the inhabitants will be exposed to the different environmental impacts during preparation phase of the project. For the purpose of performing workovers, it will be necessary to secure access to wellheads of existing wells. This paper gives guidelines for describing potential impacts on environment components that could occur during geothermal production preparation on existing mature oil filed, recommends possible protection measures to mitigate these impacts, and gives recommendations for environmental monitoring.

Keywords: geothermal energy production, mature oil filed, environmental impact assessment, underlying aquifer thermal energy

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Authors: Tigabu Dagne Akal

Abstract:

While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Sukran Acikel, Mehmet Ekmekci, Otgonbayar Namkhai

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Lignite coal fields in western Turkey generally occurs in tensional Neogene basins bordered by major faults. Karacahisar coal field in Mugla province of western Turkey is a large Neogene basin filled with alternation of silisic and calcerous layers. The basement of the basin is composed of mainly karstified carbonate rocks of Mesozoic and schists of Paleozoic age. The basement rocks are exposed at highlands surrounding the basin. The basin fill deposits forms shallow, low yield and local aquifers whereas karstic carbonate rock masses forms the major aquifer in the region. The karstic aquifer discharges through a spring zone issuing at intersection of two major faults. Municipal water demand in Bodrum city, a touristic attraction area is almost totally supplied by boreholes tapping the karstic aquifer. A well field has been constructed on the eastern edge of the coal basin, which forms a ridge separating two Neogene basins. A major concern was raised about the plausible impact of mining activities on groundwater system in general and on water supply well field in particular. The hydrogeological studies carried out in the area revealed that the coal seam is located below the groundwater level. Mining operations will be affected by groundwater inflow to the pits, which will require dewatering measures. Dewatering activities in mine sites have two-sided effects: a) lowers the groundwater level at and around the pit for a safe and effective mining operation, b) continuous dewatering causes expansion of cone of depression to reach a spring, stream and/or well being utilized by local people, capturing their water. Plausible effect of mining operations on the flow of the spring zone was another issue of concern. Therefore, a detailed representative hydrogeological conceptual model of the site was developed on the basis of available data and field work. According to the hydrogeological conceptual model, dewatering of Neogene layers will not hydraulically affect the water supply wells, however, the ultimate perimeter of the open pit will expand to intersect the well field. According to the conceptual model, the coal seam is separated from the bottom by a thick impervious clay layer sitting on the carbonate basement. Therefore, the hydrostratigraphy does not allow a hydraulic interaction between the mine pit and the karstic carbonate rock aquifer. However, the structural setting in the basin suggests that deep faults intersecting the basement and the Neogene sequence will most probably carry the deep groundwater up to a level above the bottom of the pit. This will require taking necessary measure to lower the piezometric level of the carbonate rock aquifer along the faults. Dewatering the carbonate rock aquifer will reduce the flow to the spring zone. All findings were put together to recommend a strategy for safe and effective mining operation.

Keywords: conceptual model, dewatering, groundwater, mining operation

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Authors: Mingming Guo, Xiaozan Wang

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Introduction: The purpose of this study is to examine the correlation between the physical fitness of Chinese college students and their daily running habits (RH). Methods: A total of 718 college students from East China Normal University participated in this study (385 boys and 333 girls). Each participant participated in the Chinese Students’ Physical Fitness Test during the 2018-2019 school year. In addition, each student is also required to use the app to record all their running results during each run during the 2018-2019 school year. Researchers can query and export all running records through the app's management platform. Results: (1) The total number of kilometers run by the students showed a significant negative correlation with their vital capacity (VC), sitting body flexion (SBF), and long jump (LJ) (rᵥ

Keywords: college students, physical fitness, running habits, data mining

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Authors: A. Clementking, C. Jothi Venkateswaran

Abstract:

Mathematical and computational functionalities such as descriptive mining, optimization, and predictions are espoused to resolve natural resource planning. The water quality prediction and its attributes influence determinations are adopted optimization techniques. The water properties are tainted while merging water resource one with another. This work aimed to predict influencing water resource distribution connectivity in accordance to water quality and sediment using an innovative proposed master-slave neural network back-propagation model. The experiment results are arrived through collecting water quality attributes, computation of water quality index, design and development of neural network model to determine water quality and sediment, master–slave back propagation neural network back-propagation model to determine variations on water quality and sediment attributes between the water resources and the recommendation for connectivity. The homogeneous and parallel biochemical reactions are influences water quality and sediment while distributing water from one location to another. Therefore, an innovative master-slave neural network model [M (9:9:2)::S(9:9:2)] designed and developed to predict the attribute variations. The result of training dataset given as an input to master model and its maximum weights are assigned as an input to the slave model to predict the water quality. The developed master-slave model is predicted physicochemical attributes weight variations for 85 % to 90% of water quality as a target values.The sediment level variations also predicated from 0.01 to 0.05% of each water quality percentage. The model produced the significant variations on physiochemical attribute weights. According to the predicated experimental weight variation on training data set, effective recommendations are made to connect different resources.

Keywords: master-slave back propagation neural network model(MSBPNNM), water quality analysis, multivariate analysis, environmental mining

Procedia PDF Downloads 463