Search results for: text mining analysis

Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Dewi Juliah Ratnaningsih, Imas Sukaesih Sitanggang

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Classification is one of data mining techniques that aims to discover a model from training data that distinguishes records into the appropriate category or class. Data mining classification methods can be applied in education, for example, to determine the classification of non-active students in Indonesia Open University. This paper presents a comparison of three methods of classification: Naïve Bayes, Bagging, and C.45. The criteria used to evaluate the performance of three methods of classification are stratified cross-validation, confusion matrix, the value of the area under the ROC Curve (AUC), Recall, Precision, and F-measure. The data used for this paper are from the non-active Indonesia Open University students in registration period of 2004.1 to 2012.2. Target analysis requires that non-active students were divided into 3 groups: C1, C2, and C3. Data analyzed are as many as 4173 students. Results of the study show: (1) Bagging method gave a high degree of classification accuracy than Naïve Bayes and C.45, (2) the Bagging classification accuracy rate is 82.99 %, while the Naïve Bayes and C.45 are 80.04 % and 82.74 % respectively, (3) the result of Bagging classification tree method has a large number of nodes, so it is quite difficult in decision making, (4) classification of non-active Indonesia Open University student characteristics uses algorithms C.45, (5) based on the algorithm C.45, there are 5 interesting rules which can describe the characteristics of non-active Indonesia Open University students.

Keywords: comparative analysis, data mining, clasiffication, Bagging, Naïve Bayes, C.45, non-active students, Indonesia Open University

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Authors: Hamza A. Al-Sewadi, Akram N. A. Aldakari

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Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods, and hence, it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted in embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods), and a fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.

Keywords: steganography, watermarking, time complexity measurements, private keys

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Authors: Iis Diatin, Yani Hadiroseyani, Muhammad Mujahid, Ahmad Teduh, Juang R. Matangaran

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One of silica quarry managed by a mining company is located at Sukabumi District of West Java Province Indonesia with an area of approximately 70 hectares. Since 2013 this company stopped the mining activities. The company tries to restore the ecosystem post-mining with rehabilitation activities such as reclamation and revegetation of their ex-mining area. After three years planting the area the trees grown well. Not only planting some tree species but also some cover crop has covered the soil surface. There are two settling ponds located in the middle of the ex-mining area. Those settling pond were built in order to prevent the effect of acid mine drainage. Acid mine drainage (AMD) or the acidic water is created when sulphide minerals are exposed to air and water and through a natural chemical reaction produce sulphuric acid. AMD is the main pollutant at the open pit mining. The objective of the research was to analyze the effect of revegetation on water quality change at the settling pond. The physical and chemical of water quality parameter were measured and analysed at site and at the laboratory. Physical parameter such as temperature, turbidity and total organic matter were analyse. Also heavy metal and some other chemical parameter such as dissolved oxygen, alkalinity, pH, total ammonia nitrogen, nitrate and nitrite were analysed. The result showed that the acidity of first settling pond was higher than that of the second settling pond. Both settling pond water’s contained heavy metal. The turbidity and total organic matter were the parameter of water quality which become better after revegetation.

Keywords: acid mine drainage, ex-mining area, revegetation, settling pond, water quality

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Authors: Abrar Ajmal

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The language used in literature reveals the culture and social gestalt of any society in which it has been constructed and consumed. This paper carries the same rationale, which aims to track certain socio-religious and cultural-economic disparities and discrepancies towards minorities, particularly Christians, in an Islamic re(public) where there is a clear majority of Muslims with the help of analysis of instances of language used in the narratives “Our Lady of Alice Bhatt” by Mohammad Hanif. It would highlight social inequalities practiced deeply in sociocultural discourse. Moreover, this research would also touch upon the question of gender discrimination and gender construction as a female entity in a male-chauvinistic scenic turnout using language since the novel revolves around communicative forfeits of Alice Bhatti’s life where she is fraying in fisticuffs to befit herself in a miss-fitted society. It would employ using Fairclough's framework for analysis to conduct a critical discourse analysis of the text at three axiom levels namely textual analysis, discursive practices, and socio-cultural analysis. Thus, the results would reveal textual findings in linguistic analysis, a range of embedded discourses in discursive practices, and consumption of the text into socio-cultural explications with the use of language and lexicalization employed in the selected excerpts.

Keywords: gendered discourse, socio-economic disparities minorities, Islamization, analytical framework

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Authors: Abdul Rahman M. Chamseddine, Mahmoud El-ashiri

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In the field of language teaching, communication skills are essential for the learner to achieve, however, these skills, in general, might not support the comprehension of some texts of literary or artistic nature like poetry. Understanding sentences and expressions is not enough to understand a poem; other skills are needed in order to understand the special structure of a text which literary meaning is inapprehensible even when the lingual meaning is well comprehended. And then there is the need for many other components that surpass one text to other similar texts that can be understood through solid traditions, which do not form an obstacle in the face of change and progress. This is not exclusive to texts that are classified as a literary but it is also the same with some daily short phrases and indicatively charged expressions that can be classified as literary or bear a taste of literary nature.. it can be found in Newpapers’ titles, TV news reports, and maybe football commentaries… the need to understand this special lingual use – described as literary – is highly important to understand this discourse that can be generally classified as very far from literature. This work will try to explore the role of the literary text in the language class and the way it is being covered or dealt with throughout all levels of acquiring proficiency. It will also attempt to survery the position of the literary text in some of the most important books for teaching Arabic around the world. The same way grammar is needed to understand the language, another (literary) grammar is also needed for understanding literature.

Keywords: language teaching, Arabic, literature, pedagogy, language proficiency

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Authors: Mohammed Al-Shalabi, Alaa Obeidat

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In any food stores, some items will be expired or destroyed because the demand on these items is infrequent, so we need a system that can help the decision maker to make an offer on such items to improve the demand on the items by putting them with some other frequent item and decrease the price to avoid losses. The system generates hundreds or thousands of patterns (offers) for each low demand item, then it uses the association rules (support, confidence) to find the interesting patterns (the best offer to achieve the lowest losses). In this paper, we propose a data mining method for determining the best offer by merging the data mining techniques with the e-commerce strategy. The task is to build a model to predict the best offer. The goal is to maximize the profits of a store and avoid the loss of products. The idea in this paper is the using of the association rules in marketing with a combination with e-commerce.

Keywords: data mining, association rules, confidence, online stores

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Authors: Sven Gehrke, Johannes Ruhland

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Data is the oil of our time, without them progress would come to a hold [1]. On the other hand, the mistrust of data mining is increasing [2]. The paper at hand shows different aspects of the concept of trust and describes the information asymmetry of the typical stakeholders of a data mining project using the CRISP-DM phase model. Based on the identified influencing factors in relation to trust, problematic aspects of the current approach are verified using various interviews with the stakeholders. The results of the interviews confirm the theoretically identified weak points of the phase model with regard to trust and show potential research areas.

Keywords: trust, data mining, CRISP DM, stakeholder management

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Authors: Trayan Kushev, E. Shaunn Mattingly, Andrew S. Manikas

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This study utilizes computer-aided text analysis (CATA) on the descriptions of 248,614 Kickstarter crowdfunding campaigns to reveal that backers are more likely to provide funding to projects that contain a higher percentage of creativity-speak words. Further, this relationship is observed to be stronger for product-based campaigns (e.g., games, technology, design) and weaker for content-based campaigns (e.g., film, music, publishing). In addition, both positive linguistic tone and the use of words expressing gratitude in the text of the campaign strengthen the positive effect of creativity-speak on campaign success.

Keywords: creativity-speak, crowdfunding, entrepreneurship, gratitude, tone

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Authors: Tengku Sepora Tengku Mahadi

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Where the speed of book writing lags behind the high need for such material for tertiary studies, translation offers a way to enhance the equilibrium in this demand-supply equation. Nevertheless, translation is confronted by obstacles that threaten its effectiveness. The primary challenge to the production of efficient translations may well be related to the text-type and in terms of its complexity. A text that is intricately written with unique rhetorical devices, subject-matter foundation and cultural references will undoubtedly challenge the translator. Longer time and greater effort would be the consequence. To understand these text-related challenges, the present paper set out to analyze a lawbook entitled Learning the Law by David Melinkoff. The book is chosen because it has often been used as a textbook or for reference in many law courses in the United Kingdom and has seen over thirteen editions; therefore, it can be said to be a worthy book for studies in law. Another reason is the existence of a ready translation in Malay. Reference to this translation enables confirmation to some extent of the potential problems that might occur in its translation. Understanding the organization and the language of the book will help translators to prepare themselves better for the task. They can anticipate the research and time that may be needed to produce an effective translation. Another premise here is that this text-type implies certain ways of writing and organization. Accordingly, it seems practicable to adopt the functional theory of language as suggested by Michael Halliday as its theoretical framework. Concepts of the context of culture, the context of situation and measures of the field, tenor and mode form the instruments for analysis. Additional examples from similar materials can also be used to validate the findings. Some interesting findings include the presence of several other text-types or sub-text-types in the book and the dependence on literary discourse and devices to capture the meanings better or add color to the dry field of law. In addition, many elements of culture can be seen, for example, the use of familiar alternatives, allusions, and even terminology and references that date back to various periods of time and languages. Also found are parts which discuss origins of words and terms that may be relevant to readers within the United Kingdom but make little sense to readers of the book in other languages. In conclusion, the textual analysis in terms of its functions and the linguistic and textual devices used to achieve them can then be applied as a guide to determine the effectiveness of the translation that is produced.

Keywords: functional theory of language, lawbook text-type, rhetorical devices, culture

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Authors: L. Hamsaveni, Navya Prakash, Suresha

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Document Image Analysis recognizes text and graphics in documents acquired as images. An approach without Optical Character Recognition (OCR) for degraded document image analysis has been adopted in this paper. The technique involves document imaging methods such as Image Fusing and Speeded Up Robust Features (SURF) Detection to identify and extract the degraded regions from a set of document images to obtain an original document with complete information. In case, degraded document image captured is skewed, it has to be straightened (deskew) to perform further process. A special format of image storing known as YCbCr is used as a tool to convert the Grayscale image to RGB image format. The presented algorithm is tested on various types of degraded documents such as printed documents, handwritten documents, old script documents and handwritten image sketches in documents. The purpose of this research is to obtain an original document for a given set of degraded documents of the same source.

Keywords: grayscale image format, image fusing, RGB image format, SURF detection, YCbCr image format

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Authors: D. Nam Kim, D. Jin Kim, Jeonghwan Jeon

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Defense Defensive Modeling and Simulation (M&S) is a system which enables impracticable training for reducing constraints of time, space and financial resources. The necessity of defensive M&S has been increasing not only for education and training but also virtual fight. Soldiers who are using defensive M&S for education and training will obtain empirical knowledge and know-how. However, the obtained knowledge of individual soldiers have not been managed and utilized yet since the nature of military organizations: confidentiality and frequent change of members. Therefore, this study aims to develop a management system for the experience of defensive M&S based on data mining approach. Since individual empirical knowledge gained through using the defensive M&S is both quantitative and qualitative data, data mining approach is appropriate for dealing with individual empirical knowledge. This research is expected to be helpful for soldiers and military policy makers.

Keywords: data mining, defensive m&s, management system, knowledge management

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Authors: Aji Budi Rinekso

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There are some common problems that are often faced by students in writing. The problems are related to macro and micro skills of writing, such as incorrect spellings, inappropriate diction, grammatical errors, random ideas, and irrelevant supporting sentences. Therefore, it is needed a teaching technique that can solve those problems. Dictogloss technique is a teaching technique that involves listening practices. So, it is a suitable teaching technique for students with auditory learning style. Dictogloss technique comprises of four basic steps; (1) warm up, (2) dictation, (3) reconstruction and (4) analysis and correction. Warm up is when students find out about topics and do some preparatory vocabulary works. Then, dictation is when the students listen to texts read at normal speed by a teacher. The text is read by the teacher twice where at the first reading the students only listen to the teacher and at the second reading the students listen to the teacher again and take notes. Next, reconstruction is when the students discuss the information from the text read by the teacher and start to write a text. Lastly, analysis and correction are when the students check their writings and revise them. Dictogloss offers some advantages in relation to the efforts of improving writing skills. Through the use of dictogloss technique, students can solve their problems both on macro skills and micro skills. Easier to generate ideas and better writing mechanics are the benefits of dictogloss.

Keywords: auditory learners, writing skills, dictogloss technique, second language learning

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Authors: Hina Kausher, Sangita Srivastava

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In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which covers the variety of figure proportions in both height and girth. 3,000 data has been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from some states of India to produce the sizing system suitable for clothing manufacture and retailing. This data is used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from a large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: anthropometric data, data mining, decision tree, garments manufacturing, sizing systems, ready-made garments

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

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Authors: Livhuwani Muthelo, Tebogo Maria Mothiba, Rambelani Nancy Malema

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Background: Despite occupational legislation/standards being in place in the industry, there are many reported health and safety incidents, including both occupational injuries and illnesses in the South African mining industry. Purpose: This systematic literature review aimed to describe and identify the existing gaps in health and safety compliance within the South African mining industry and propose future research areas. Methodology: A systematic literature review was conducted using the key concepts of health and safety, compliance, standards, and mining. A total of 102 papers issued from 1994 to April 2020 were extracted from an online database search, which included a combination of South African and international government OHS legislation documents, policies, standards, reports from the mineral departments and international labour office, qualitative and quantitative journal articles, dissertations, seminars and conference proceedings. Results: The literature review revealed that, though there are laws, regulations, standards to guide the industry on health and safety issues in South Africa, the main challenge is with the compliance with the existing health and safety systems, wherein systems are not being implemented. Conclusion: Gaps between research, policy, and implementation in occupational health practice in the South African mining industry were also identified.

Keywords: circumstances, non-compliance, health and safety, standards, mining industry

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Authors: Sujata Upgupta, Prasoon Kumar Singh

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The expansion of large scale coal mining into forest areas is a potential hazard for the local biodiversity and wildlife. The objective of this study is to provide a picture of the threat that coal mining poses to the forests of the East Bokaro landscape. The vulnerable forest areas at risk have been assessed and the priority areas for conservation have been presented. The forested areas at risk in the current scenario have been assessed and compared with the past conditions using classification and buffer based overlay approach. Forest vulnerability has been assessed using an analytical framework based on systematic indicators and composite vulnerability index values. The results indicate that more than 4 km² of forests have been lost from 1973 to 2016. Large patches of forests have been diverted for coal mining projects. Forests in the northern part of the coal field within 1-3 km radius around the coal mines are at immediate risk. The original contiguous forests have been converted into fragmented and degraded forest patches. Most of the collieries are located within or very close to the forests thus threatening the biodiversity and hydrology of the surrounding regions. Based on the vulnerability values estimated, it was concluded that more than 90% of the forested grids in East Bokaro are highly vulnerable to mining. The forests in the sub-districts of Bermo and Chandrapura have been identified as the most vulnerable to coal mining activities. This case study would add to the capacity of the forest managers and mine managers to address the risk and vulnerability of forests at a small landscape level in order to achieve sustainable development.

Keywords: forest, coal mining, indicators, vulnerability

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Authors: Amir Taghizadeh Vahed, Adithya Thaduri

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Shovels are the main components in the mining transportation system. The productivity of the mines depends on the availability of shovels due to its high capital and operating costs. The unplanned failure/shutdowns of a shovel results in higher repair costs, increase in downtime, as well as increasing indirect cost (i.e. loss of production and company’s reputation). In order to mitigate these failures, predictive maintenance can be useful approach using failure prediction. The modern mining machinery or shovels collect huge datasets automatically; it consists of reliability and maintenance data. However, the gathered datasets are useless until the information and knowledge of data are extracted. Machine learning as well as data mining, which has a major role in recent studies, has been used for the knowledge discovery process. In this study, data mining and machine learning approaches are implemented to detect not only anomalies but also patterns from a dataset and further detection of failures.

Keywords: maintenance, machine learning, shovel, conditional based monitoring

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Authors: Mariam Matiashvili

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Argumentation is an integral part of our daily communications - formal or informal. Argumentative reasoning, techniques, and language tools are used both in personal conversations and in the business environment. Verbalization of the opinions requires the use of extraordinary syntactic-pragmatic structural quantities - arguments that add credibility to the statement. The study of argumentative structures allows us to identify the linguistic features that make the text argumentative. Knowing what elements make up an argumentative text in a particular language helps the users of that language improve their skills. Also, natural language processing (NLP) has become especially relevant recently. In this context, one of the main emphases is on the computational processing of argumentative texts, which will enable the automatic recognition and analysis of large volumes of textual data. The research deals with the linguistic analysis of the argumentative structures of Georgian political speeches - particularly the linguistic structure, characteristics, and functions of the parts of the argumentative text - claims, support, and attack statements. The research aims to describe the linguistic cues that give the sentence a judgmental/controversial character and helps to identify reasoning parts of the argumentative text. The empirical data comes from the Georgian Political Corpus, particularly TV debates. Consequently, the texts are of a dialogical nature, representing a discussion between two or more people (most often between a journalist and a politician). The research uses the following approaches to identify and analyze the argumentative structures Lexical Classification & Analysis - Identify lexical items that are relevant in argumentative texts creating process - Creating the lexicon of argumentation (presents groups of words gathered from a semantic point of view); Grammatical Analysis and Classification - means grammatical analysis of the words and phrases identified based on the arguing lexicon. Argumentation Schemas - Describe and identify the Argumentation Schemes that are most likely used in Georgian Political Speeches. As a final step, we analyzed the relations between the above mentioned components. For example, If an identified argument scheme is “Argument from Analogy”, identified lexical items semantically express analogy too, and they are most likely adverbs in Georgian. As a result, we created the lexicon with the words that play a significant role in creating Georgian argumentative structures. Linguistic analysis has shown that verbs play a crucial role in creating argumentative structures.

Keywords: georgian, argumentation schemas, argumentation structures, argumentation lexicon

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Authors: Pascal Rey, Anaïs Weber

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Many mining projects are being developed in Africa the last decades. Due to the economic opportunities they offer, these projects result in a massive and rapid influx of migrants to the surrounding area. In areas where central government representation is low and local administration lack financial resources, urban development is often anarchical, beyond all public control. It leads to socio-spatial segregation, insecurity and the risk of social conflicts rising. Aware that their economic development is very correlated with local situation, mining companies get more and more involved in regional planning in setting up tools and Strategic Directions document. One of the commonly used tools in this regard is the “Influx Management Plan”. It consists in looking at the region’s absorption capacities in order to ensure its coherent development and by developing several urban centers than one macrocephalic city. It includes many other measures such as urban governance support, skills transfer, creation of strategic guidelines, financial support (local taxes, mining taxes, development funds etc.) local development projects. Through various examples of mining projects in Guinea, A country that is host to many large mining projects, we will look at the implications of regional and urban planning of which mining companies are key playor as well as public authorities. While their investment capacity offers advantages and accelerates development, their actions raise questions of the unilaterality of interests and local governance. By interfering in public affairs are mining companies not increasing the risk of central and local government shirking their responsibilities in terms of regional development, or even calling their legitimacy into question? Is such public-private collaboration really sustainable for the region as a whole and for all stakeholders?

Keywords: Africa, guinea, mine, urban planning

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: Javad Someehneshin, Weizhou Quan, Abdelsalam Abugharara, Stephen Butt

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Narrow vein mining (NVM) is exploiting very thin but valuable ore bodies that are uneconomical to extract by conventional mining methods. NVM applies the technique of Sustainable Mining by Drilling (SMD). The SMD method is used to mine stranded, steeply dipping ore veins, which are too small or isolated to mine economically using conventional methods since the dilution is minimized. This novel mining technique uses drilling rigs to extract the ore through directional drilling surgically. This paper is focusing on utilizing the run of the mine tailings and Portland cement as backfill material to support the hanging wall for providing safe mine operation. Cemented paste backfill (CPB) is designed by mixing waste tailings, water, and cement of the precise percentage for optimal outcomes. It is a non-homogenous material that contains 70-85% solids. Usually, a hydraulic binder is added to the mixture to increase the strength of the CPB. The binder fraction mostly accounts for 2–10% of the total weight. In the mining industry, CPB has been improved and expanded gradually because it provides safety and support for the mines. Furthermore, CPB helps manage the waste tailings in an economical method and plays a significant role in environmental protection.

Keywords: backfilling, cement backfill, tailings, Portland cement

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Sergio Perez Rodriguez

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Coltan Artisanal and Small-Scale Mining (ASM) production from Africa's Great Lakes region has previously been addressed at large scales, notably from regional to country levels. The current findings address the unresolved issue of a production model of ASM of coltan ore by an average Democratic Republic of Congo (DRC) mineworker, which can be used as a reference for a similar characterization of the daily labor of counterparts from other countries in the region. To that end, the Fundamental Equation of Mineral Production has been applied, considering a miner's average daily output of coltan, estimated in the base of gross statistical data gathered from reputable sources. Results indicate daily yields of individual miners in the order of 300 g of coltan ore, with hourly peaks of production in the range of 30 to 40 g of the mineral. Yields are expected to be in the order of 5 g or less during the least productive hours. These outputs are expected to be achieved during the halves of the eight to ten hours of daily working sessions that these artisanal laborers can attend during the mining season.

Keywords: coltan, mineral production, production to reserve ratio, artisanal mining, small-scale mining, ASM, human work, Great Lakes region, Democratic Republic of Congo

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Authors: Othmane Touri, Sanaa El Filali, El Habib Benlahmar

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Natural Language Processing (NLP) has gained significant attention lately. It has proved its ability to analyze and extract insights from unstructured text data in various languages. It is found that one of the most popular NLP applications is sentiment analysis which aims to identify the sentiment expressed in a piece of text, such as positive, negative, or neutral, in multiple languages. While there are several multilingual NLP models available for sentiment analysis, there is a need to investigate their effectiveness in different contexts and applications. In this study, we aim to investigate the effectiveness of different multilingual NLP models for sentiment analysis on a dataset of online product reviews in multiple languages. The performance of several NLP models, including Google Cloud Natural Language API, Microsoft Azure Cognitive Services, Amazon Comprehend, Stanford CoreNLP, spaCy, and Hugging Face Transformers are being compared. The models based on several metrics, including accuracy, precision, recall, and F1 score, are being evaluated and compared to their performance across different categories of product reviews. In order to run the study, preprocessing of the dataset has been performed by cleaning and tokenizing the text data in multiple languages. Then training and testing each model has been applied using a cross-validation approach where randomly dividing the dataset into training and testing sets and repeating the process multiple times has been used. A grid search approach to optimize the hyperparameters of each model and select the best-performing model for each category of product reviews and language has been applied. The findings of this study provide insights into the effectiveness of different multilingual NLP models for Multilingual Sentiment Analysis and their suitability for different languages and applications. The strengths and limitations of each model were identified, and recommendations for selecting the most performant model based on the specific requirements of a project were provided. This study contributes to the advancement of research methods in multilingual NLP and provides a practical guide for researchers and practitioners in the field.

Keywords: NLP, multilingual, sentiment analysis, texts

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Authors: Khaled M. Alhawiti

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This paper aims to analyze the role of natural language processing (NLP). The paper will discuss the role in the context of automated data retrieval, automated question answer, and text structuring. NLP techniques are gaining wider acceptance in real life applications and industrial concerns. There are various complexities involved in processing the text of natural language that could satisfy the need of decision makers. This paper begins with the description of the qualities of NLP practices. The paper then focuses on the challenges in natural language processing. The paper also discusses major techniques of NLP. The last section describes opportunities and challenges for future research.

Keywords: data retrieval, information retrieval, natural language processing, text structuring

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Authors: Saleem Abu Jaber, Khaled Igbaria

Abstract:

For readers, space/place is one of the most significant references to reveal deep significances and indications in modern Arabic poetic texts. Generally, when poets evoke places and/or spaces, they do not mean to refer readers to detailed geographic or physical spaces, but to the symbolic significances and dimensions that those spaces have and through which poets encourage spacial awareness in their readers. Recently, as a result, there has been a great deal of interest in research addressing spacial poetic texts and dimensions in modern Arabic poetry in general and in Palestinian poetry in particular. Samih al-Qasim is one of the most recent prominent Palestinian revolutionary poets. Al-Qasim has published six series of poems that are well known in the Arab world. Although several researchers have studied al-Qasim's poetry, to our knowledge, yet no one has studied the aspect of spacial poetic text in his poetry. Therefore, this paper seeks to fill a gap in the scholarship that has not been addressed up to now. This article aims, not only to demonstrate the presence of spacial poetic text and dimensions throughout al-Qasim's poetry, but also to investigate the purpose for which the poet uses spacial poetic text. Our theory is that the poet, consciously and significantly, uses spacial poetic texts to magnify the Palestinian identity of the Palestinian readers.  Methodologically, we applied a descriptive analytic method, referencing al-Qasim's poetry, addressing spacial poetic texts practically but not theoretically or statistically.

Keywords: spatial poetic text, Samih al-Qasim, space and identity, Palestinian poetry

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Authors: Thuy Hanh Nguyen Thi

Abstract:

By the method of deep reading and text analysis, this article will analyze the use and creation of dialects as a way of demonstrating Yan Lianke's creative stance. This article indicates that this is the writer’s narrative strategy in a fight against aphasia, a language disorder of Chinese people and culture, demonstrating a sense of return to folklore and marks his own linguistic style. In terms of verbal text, the dialect in the Yan Lianke’s novels manifested through the use of words, sentences and dialects. There are two types of dialects that exist in Yan Lianke’s novels: the current dialect system and the particular dialect system of Pa Lau world created by the writer himself in order to enrich the vocabulary of Han Chinese.

Keywords: Yan Lianke , aphasia, dialect, Pa Lou world

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Authors: Ju-Young Kim, Tae-Heon Moon, Jung-Hun Cho

Abstract:

Urban regeneration projects have been actively promoted in Korea. In particular, Jeonju Hanok Village is evaluated as one of representative cases in terms of utilizing local cultural heritage sits in the urban regeneration project. However, recently, there has been a growing concern in this area, due to the ‘gentrification’, caused by the excessive commercialization and surging tourists. This trend was changing land and building use and resulted in the loss of identity of the region. In this regard, this study analyzed the land use transformation between 2010 and 2016 to identify the commercialization trend in Jeonju Hanok Village. In addition, it conducted SNS big data analysis on Jeonju Hanok Village from February 14th, 2016 to March 31st, 2016 to identify visitors’ awareness of the village. The study results demonstrate that rapid commercialization was underway, unlikely the initial intention, so that planners and officials in city government should reconsider the project direction and rebuild deliberate management strategies. This study is meaningful in that it analyzed the land use transformation and SNS big data to identify the current situation in urban regeneration area. Furthermore, it is expected that the study results will contribute to the vitalization of regeneration area.

Keywords: land use, SNS, text mining, urban regeneration

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Authors: Manoj Gujar

Abstract:

The present paper is an attempt to interpret two Marathi translations of Khushwant Singh’s (1915-2014) novel Train to Pakistan (1956). The 20th century was branded as an era of Liberalization, Privatization and Globalization. Different countries and cultures have enunciated interaction with one another in an unprecedented manner. The world is becoming multilingual and multicultural. The democratic countries such as the U.S.A., the U.K., and India have become pivotal centers of interlingual and cross-cultural exchange. People belonging to different nationalities showed keen interest in knowing the characteristic features of different languages and of their cultures. Here, ‘Translation’ plays an important role in such multilingual and multicultural contexts. Translation is not only translation of a language but a translation of a culture. However, in the act of translation a translator makes use of such procedures as borrowing, definition, literal translation, substitution, lexical creation, omission, addition as well as their various combinations. To him, a text produced in one linguistic and cultural context can reach other linguistic and cultural contexts through these processes of translation. A worthy work of art appeals many readers. India, being a multilingual country we find that there goes multiple translations of the same text in different Indian languages. But sometimes, if can be found that a same text appeals to different ages and the same text gets translated into the same language by the two or more authors. In this reference, the present paper is an attempt to study how different translations of the same text differ in terms of procedures and strategies during the process of the translation of culture. The source text is Khushwant Singh’s historical novel Train to Pakistan (1956). The novel was widely appreciated and so translated into different regional languages in India. The novel has two Marathi translations: Agniratha (1972) by Hidayatkhan and Train to Pakistan (1980) by Anil Kinikar. This paper is an attempt to evaluate the strategies and procedures in translation to analyze these two Marathi translations. Hidayat Khan made a lot of omissions of the significant details and distorted the original text to a large extent, whereas, Anil Kinikar has done justice to the Source Text by rendering it in Marathi as faithfully as possible.

Keywords: culture, multilingual, procedures and strategies, translation

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