Search results for: Arabic data mining

Authors: Walid Moudani, Ahmad Shahin

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This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

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Authors: Nabilah Filzah Mohd Radzuan, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Uncertain data is believed to be an important issue in building up a prediction model. The main objective in the time series uncertainty analysis is to formulate uncertain data in order to gain knowledge and fit low dimensional model prior to a prediction task. This paper discusses the performance of a number of techniques in dealing with uncertain data specifically those which solve uncertain data condition by minimizing the loss of compression properties.

Keywords: compression properties, uncertainty, uncertain time series, mining technique, weather prediction

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Authors: Ezra Yehuwalashet, Alireza Malehmir

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Blötberget mining area in central Sweden, part of the Bergslagen mineral district, is well known for its various type of mineralization particularly iron-oxide deposits since the 1600. To shed lights on the knowledge of the host rock structures, depth extent and tonnage of the mineral deposits and support deep mineral exploration potential in the study area, new ground gravity and existing aeromagnetic data (from the Geological Survey of Sweden) were used for interpretations and modelling. A major boundary separating a gravity low from a gravity high in the southern part of the study area is noticeable and likely representing a fault boundary separating two different lithological units. Gravity data and modeling offers a possible new target area in the southeast of the known mineralization while suggesting an excess high-density region down to 800 m depth.

Keywords: gravity, magnetics, ore deposit, geophysics

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Authors: Jeries Khoury

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The use of legendary, folkloric and religious symbols is one of the most important phenomena in modern Arabic poetry. Interestingly enough, most of the modern Arabic poetry’s pioneers were so fascinated by the biblical symbols and they managed to use many modern techniques to make these symbols adequate for their personal life from one side and fit to their Islamic beliefs from the other. One of the most famous poets to do so was al-Sayya:b. The way he employed one of these symbols ‘job’, the new features he adds to this character and the link between this character and his personal life will be discussed in this study. Besides, the study will examine the influence of al-Sayya:b on another modern poet Saadi Yusuf, who, following al-Sayya:b, used the character of Job in a special way, by mixing its features with al-Sayya:b’s personal features and in this way creating a new mixed character. A semantic, cultural and comparative analysis of the poems written by al-Sayya:b himself and the other poets who evoked the mixed image of al-Sayya:b-Job, can reveal the changes Arab poets made to the original biblical figure of Job to bring it closer to Islamic culture. The paper will make an intensive use of intertextuality idioms in order to shed light on the network of relations between three kinds of texts (indeed three ‘palimpsests’: 1- biblical- the primary text; 2- poetic- al-Syya:b’s secondary version; 3- re-poetic- Sa’di Yusuf’s tertiary version). The bottom line in this paper is that that al-Sayya:b was directly influenced by the dramatic biblical story of Job more than the brief Quranic version of the story. In fact, the ‘new’ character of Job designed by al-Sayya:b himself differs from the original one in many aspects that we can safely say it is the Sayyabian-Job that cannot be found in the poems of any other poets, unless they are evoking the own tragedy of al-Sayya:b himself, like what Saadi Yusuf did.

Keywords: Arabic poetry, intertextuality, job, meter, modernism, symbolism

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

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Authors: Tagreed Alzahrani

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The syntax of quantifiers has received much attention by linguists, philosophers and logicians within different frameworks and in various languages. However, the syntax of Arabic quantifiers has received limited attention in the literature, especially in relation to floating quantifiers. There have been a few discussions of floating quantifiers in Modern Standard Arabic (henceforth, MSA), although the analysis and the properties of their counterparts in other Saudi dialects are rare. Therefore, the aim of the paper is to provide a clear description of floating quantifiers (FQs) in Hijazi dialect (henceforth, HA) by utilising the following approaches: the adverbial approach, and the derivational (stranding) analysis. For a long time, Linguists have tried to explain the floating quantifiers’ phenomenon, as exemplified in the following sentences: 1. All the friends have watched the movie. 2. The friends have all watched the movie. The adverbial approach assumes that the floating quantifier is a type of adverb, because it occupies the adverbial position next to the verb. Thus, the subject in the first example is all the friends and the subject in the second example is the friends with all becoming an adverb, as it is located in an adverbial position. However, in stranding analysis, it is argued that the floating quantifier becomes stranded when its complement has moved to a higher position in the sentence [SPEC, TP]. Therefore, both sentences have the same subject all the friends, although in second example the friends has moved to a higher position and has stranded the quantifier all. The paper will investigate the floating quantifiers in HA using both approaches. The analysis will show that neither view is entirely successful in providing a unified account for FQs in HA.

Keywords: floating quantifier, adverbial analysis, stranding approach, universal quantifier

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Authors: Riham Debian

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This paper deals with the translational mystic in Arabic aesthetics and their linguistic and narrative revelation and mediation across textual spaces. The paper particularly engages with the nature of the Egyptian Sufi Madad, its relation to spaces/places, its intergenerational and intertextual manifestations, and its intersection with questions of identity—the historical spaces and geographical places one inhabits and embodies. Opening a repertoire between contextualized stylistics and poetics semiology (Boise-Bier2011; Jackobson 1960), the paper reads in al-Ghitany’s Kitab al-Tagiliat (The Book of Revelation1983), Bassiouny’s Sabil Al-Ghareq (2018) and its translation (Fountain of the Drowning2022). The paper examines the stylistic and poetical encoding and recoding of the Sufi Madads from Ghitany to Bassiouny and their entanglement in the question of Egyptian identity-politics through the embodiment of historical places and geographical spaces. The paper argues for the intergenerational intertextuality of Arabic aesthetics that stylistically and poetically enacts the mysticism of Sufi Madad through historical and geographical semioticization of the Egyptian character continuity across time and space. Both Ghitany and Bassiouny engage with the historical novel as a form of delivery of their Egyptian mystical relation with time and place. Both novelist-historians are involved with the question of place and the life-worlds that spaces generate across time and gender.

Keywords: intertextuality, interdiscusivity, madad, egyptian identity

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Authors: Loay Badran

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This article on synonymy came into existence to meet the academic needs of students who specialize in this field. The article has two parts: the first part discusses the forms that authors of textbooks and dictionaries assumed when explaining a word as well as explaining the precision or lack of it thereof in delivering an understandable and clear meaning of using such forms. Meanwhile, the second part of this research article focuses on the application of synonymy and at taking into consideration the point of view of others who dismissed synonymy in its minute details, especially Alaskari in his book “Linguistic Differences” “Al Forouq Alloqhawiyyah”. The author determined that collecting the most commonly-used synonymous notions scattered in Alaskari’s book and compiling them in tables would be of great importance in easing lessons according to the Arabic Alphabet System meanwhile citing all that pertains to the corresponding scattered pages in “Linguistic Differences”.

Keywords: synonymy, semantics, camel, teaching, non-native

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Authors: Eman AbuKhousa, Marwan Z. Bataineh

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The 21^st century higher education and globalization challenge new faculty members to build effective professional networks and partnership with industry in order to accelerate their growth and success. This creates the need for community of practice (CoP)-oriented development approaches that focus on cognitive apprenticeship while considering individual predisposition and future career needs. This work adopts data mining, clustering analysis, and social networking technologies to present the CoP-Network as a virtual space that connects together similar career-aspiration individuals who are socially influenced to join and engage in a process for domain-related knowledge and practice acquisitions. The CoP-Network model can be integrated into higher education to extend traditional graduate and professional development programs.

Keywords: clustering analysis, community of practice, data mining, higher education, new faculty challenges, social network, social influence, professional development

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Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

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In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: text mining, topic extraction, independent, incremental, independent component analysis

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

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

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

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Authors: Agnieszka A. Malinowska, R. Hejmanowski

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A number of European cities are strongly affected by ground movements caused by anthropogenic activities or post-anthropogenic metamorphosis. Those are mainly water pumping, current mining operation, the collapse of post-mining underground voids or mining-induced earthquakes. These activities lead to large and small-scale ground displacements and a ground ruptures. The ground movements occurring in urban areas could considerably affect stability and safety of structures and infrastructures. The complexity of the ground deformation phenomenon in relation to the structures and infrastructures vulnerability leads to considerable constraints in assessing the threat of those objects. However, the increase of access to the free software and satellite data could pave the way for developing new methods and strategies for environmental risk mitigation and management. Open source geographical information systems (OS GIS), may support data integration, management, and risk analysis. Lately, developed methods based on fuzzy logic and experts methods for buildings and infrastructure damage risk assessment could be integrated into OS GIS. Those methods were verified base on back analysis proving their accuracy. Moreover, those methods could be supported by ground displacement observation. Based on freely available data from European Space Agency and free software, ground deformation could be estimated. The main innovation presented in the paper is the application of open source software (OS GIS) for integration developed models and assessment of the threat of urban areas. Those approaches will be reinforced by analysis of ground movement based on free satellite data. Those data would support the verification of ground movement prediction models. Moreover, satellite data will enable our mapping of ground deformation in urbanized areas. Developed models and methods have been implemented in one of the urban areas hazarded by underground mining activity. Vulnerability maps supported by satellite ground movement observation would mitigate the hazards of land displacements in urban areas close to mines.

Keywords: fuzzy logic, open source geographic information science (OS GIS), risk assessment on urbanized areas, satellite interferometry (InSAR)

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Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

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Authors: Fatima Saab

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This paper attempts to study colloquialism in audio-visual translation, with particular emphasis given to investigating the difficulties and challenges encountered by subtitlers in translating Lebanese colloquial into English. To achieve the main objectives of this study, ample and thorough cultural and translational analysis of examples drawn from the subtitled movie Capernaum are presented in order to identify the strategies used to overcome cultural barriers and differences and to show the process of decision-making by the translator. Also, special attention is given to explain the technicalities in translating subtitles and how they affect the translation process. The research is a descriptive analytical study whereby the writer sets out empirical observations, consisting of descriptive and analytical examination of the difficulties and problems associated with translating Arabic colloquialisms, specifically Lebanese, into English in the subtitled film, Capernaum. The research methodology utilizes a qualitative approach to group the selected data into the subtitling strategies presented by Gottlieb under the domesticating or foreignizing strategies according to Venuti's Model. It is shown that producing the same meanings to a foreign audience is not an easy task. The background of cultural elements and the stories that make up the history and mindset of the Lebanese and Arabic peoples leads to the use of the transfer and paraphrase methodologies most of the time (81% of the sample used for analysis). The research shows that translating and subtitling colloquialism needs special skills by the translators to overcome the challenges imposed by the limited presentation space as well as cultural differences. Translation of colloquial Arabic/Lebanese can be achieved to a certain extent and delivering the meaning and effect of the source language culture is accomplished in as much as the translator investigates and relates to the target culture.

Keywords: Lebanese colloquial, audio-visual translation, subtitling, Capernaum

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Authors: Kateryna Zharan, Jan C. Bongaerts

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In recent years, economic attractiveness of renewable energy (RE) for the mining industry, especially for off-grid mines, and a negative environmental impact of fossil energy are stimulating to use RE for mining needs. Being that remote area mines have higher energy expenses than mines connected to a grid, integration of RE may give a mine economic benefits. Regarding the literature review, there is a lack of business models for adopting of RE at mine. The main aim of this paper is to develop an optimized model of RE integration into the German mining industry (GMI). Hereby, the GMI with amount of around 800 mill. t. annually extracted resources is included in the list of the 15 major mining country in the world. Accordingly, the mining potential of Germany is evaluated in this paper as a perspective market for RE implementation. The GMI has been classified in order to find out the location of resources, quantity and types of the mines, amount of extracted resources, and access of the mines to the energy resources. Additionally, weather conditions have been analyzed in order to figure out where wind and solar generation technologies can be integrated into a mine with the highest efficiency. Despite the fact that the electricity demand of the GMI is almost completely covered by a grid connection, the hybrid energy system (HES) based on a mix of RE and fossil energy is developed due to show environmental and economic benefits. The HES for the GMI consolidates a combination of wind turbine, solar PV, battery and diesel generation. The model has been calculated using the HOMER software. Furthermore, the demonstrated HES contains a forecasting model that predicts solar and wind generation in advance. The main result from the HES such as CO2 emission reduction is estimated in order to make the mining processing more environmental friendly.

Keywords: diesel generation, German mining industry, hybrid energy system, hybrid optimization model for electric renewables, optimized model, renewable energy

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Authors: Nakache Radouane, M. Boukelloul, M. Fredj

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Method room and pillar sizes are key factors for safe mining and their recovery in open-stop mining. This method is advantageous due to its simplicity and requirement of little information to be used. It is probably the most representative method among the total load approach methods although it also remains a safe design method. Using a finite element software (PLAXIS 3D), analyses were carried out with an elasto-plastic model and comparisons were made with methods based on the total load approach. The results were presented as the optimization for improving the ore recovery rate while maintaining a safe working environment.

Keywords: room and pillar, mining, total load approach, elasto-plastic

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Authors: Seyed Mohsen Samaei, Shirley Gato-Trinidad

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A pre-treatment stage prior to reverse osmosis (RO) is very important to ensure the long-term performance of the RO membranes in any wastewater treatment using RO. This study aims to evaluate the application of the Actiflo^® clarifier as part of a pre-treatment unit in mining operations. It involves performing analytical testing on RO feed water before and after installation of Actiflo^® unit. Water samples prior to RO plant stage were obtained on different dates from Costerfield mining operations in Victoria, Australia. Tests were conducted in an independent laboratory to determine the concentration of various compounds in RO feed water before and after installation of Actiflo^® unit during the entire evaluated period from December 2015 to June 2018. Water quality analysis shows that the quality of RO feed water has remarkably improved since installation of Actiflo^® clarifier. Suspended solids (SS) and turbidity removal efficiencies has been improved by 91 and 85 percent respectively in pre-treatment system since the installation of Actiflo^®. The Actiflo^® clarifier proved to be a valuable part of pre-treatment system prior to RO. It has the potential to conveniently condition the mining wastewater prior to RO unit, and reduce the risk of RO physical failure and irreversible fouling. Consequently, reliable and durable operation of RO unit with minimum requirement for RO membrane replacement is expected with Actiflo^® in use.

Keywords: ACTIFLO ® clarifier, mining wastewater, reverse osmosis, water treatment

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Authors: Srushti Patil, Preethi Baligar, Gopalkrishna Joshi, Gururaj N. Bhadri

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In designing learning environments, the instructional strategies can be tailored to suit the learning style of an individual to ensure effective learning. In this study, the information shared on social media like Facebook is being used to predict learning style of a learner. Previous research studies have shown that Facebook data can be used to predict user personality. Users with a particular personality exhibit an inherent pattern in their digital footprint on Facebook. The proposed work aims to correlate the user's’ personality, predicted from Facebook data to the learning styles, predicted through questionnaires. For Millennial learners, Facebook has become a primary means for information sharing and interaction with peers. Thus, it can serve as a rich bed for research and direct the design of learning environments. The authors have conducted this study in an undergraduate freshman engineering course. Data from 320 freshmen Facebook users was collected. The same users also participated in the learning style and personality prediction survey. The Kolb’s Learning style questionnaires and Big 5 personality Inventory were adopted for the survey. The users have agreed to participate in this research and have signed individual consent forms. A specific page was created on Facebook to collect user data like personal details, status updates, comments, demographic characteristics and egocentric network parameters. This data was captured by an application created using Python program. The data captured from Facebook was subjected to text analysis process using the Linguistic Inquiry and Word Count dictionary. An analysis of the data collected from the questionnaires performed reveals individual student personality and learning style. The results obtained from analysis of Facebook, learning style and personality data were then fed into an automatic classifier that was trained by using the data mining techniques like Rule-based classifiers and Decision trees. This helps to predict the user personality and learning styles by analysing the common patterns. Rule-based classifiers applied for text analysis helps to categorize Facebook data into positive, negative and neutral. There were totally two models trained, one to predict the personality from Facebook data; another one to predict the learning styles from the personalities. The results show that the classifier model has high accuracy which makes the proposed method to be a reliable one for predicting the user personality and learning styles.

Keywords: educational data mining, Facebook, learning styles, personality traits

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Authors: Oleg Redkin, Olga Bernikova

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Globalization and migrations have made cross-cultural contacts more frequent and intensive. Sometimes, these contacts may lead to misunderstanding between partners of communication and misinterpretations of the verbal messages that some researchers tend to consider as the 'clash of civilizations'. In most cases, reasons for that may be found in cultural and linguistic differences and hence misinterpretations of intentions and behavior. The current research examines factors of verbal and non-verbal communication that should be taken into consideration in verbal and non-verbal contacts. Language is one of the most important manifestations of the cultural code, and it is often considered as one of the special features of a civilization. The Arabic language, in particular, is commonly associated with Islam and the language and the Arab-Muslim civilization. It is one of the most important markers of self-identification for more than 200 million of native speakers. Arabic is the language of the Quran and hence the symbol of religious affiliation for more than one billion Muslims around the globe. Adequate interpretation of Arabic texts requires profound knowledge of its grammar, semantics of its vocabulary. Communicating sides who belong to different cultural groups are guided by different models of behavior and hierarchy of values, besides that the vocabulary each of them uses in the dialogue may convey different semantic realities and vary in connotations. In this context direct, literal translation in most cases cannot adequately convey the original meaning of the original message. Besides that peculiarities and diversities of the extralinguistic information, such as the body language, communicative etiquette, cultural background and religious affiliations may make the dialogue even more difficult. It is very likely that the so called 'clash of civilizations' in most cases is due to misinterpretation of counterpart's means of discourse such as language, cultural codes, and models of behavior rather than lies in basic contradictions between partners of communication. In the process of communication, one has to rely on universal values rather than focus on cultural or religious peculiarities, to take into account current linguistic and extralinguistic context.

Keywords: Arabic, civilization, discourse, language, linguistic

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

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Authors: Heeyeul Kwon, Yongtae Park

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Despite the highly touted benefits, emerging technologies have unleashed pervasive concerns regarding unintended and unforeseen social impacts. Thus, those wishing to create safe and socially acceptable products need to identify such side effects and mitigate them prior to the market proliferation. Various methodologies in the field of technology assessment (TA), namely Delphi, impact assessment, and scenario planning, have been widely incorporated in such a circumstance. However, literatures face a major limitation in terms of sole reliance on participatory workshop activities. They unfortunately missed out the availability of a massive untapped data source of futuristic information flooding through the Internet. This research thus seeks to gain insights into utilization of futuristic data, future-oriented documents from the Internet, as a supplementary method to generate social impact scenarios whilst capturing perspectives of experts from a wide variety of disciplines. To this end, network analysis is conducted based on the social keywords extracted from the futuristic documents by text mining, which is then used as a guide to produce a comprehensive set of detailed scenarios. Our proposed approach facilitates harmonized depictions of possible hazardous consequences of emerging technologies and thereby makes decision makers more aware of, and responsive to, broad qualitative uncertainties.

Keywords: emerging technologies, futuristic data, scenario, text mining

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Montaha Al Yaari, Ayman Al Yaari, Aayah Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Introduction: It is well established that lengthening (longer duration) is considered one of the correlates of lexical and phrasal prominence. However, it is unexplored whether the scope of vowel lengthening in the Arabic dialect of Yemen (ADY) is differently affected by educated and/or uneducated speakers from different dialectal backgrounds. Specifically, the research aims to examine whether or not linguistic background acquired through different educational channels makes a difference in the speech of the speaker and how that is reflected in related psychoneurolinguistic impairments. Methods: For the above mentioned purpose, we conducted an articulatory experiment wherein a set of words from ADY were examined in the dialectal speech of thousand and seven hundred Yemeni educated and uneducated speakers aged 19-61 years growing up in five regions of the country: Northern, southern, eastern, western and central and were, accordingly, assigned into five dialectal groups. A seven-minute video clip was shown to the participants, who have been asked to spontaneously describe the scene they had just watched before the researchers linguistically and statistically analyzed recordings to weigh vowel lengthening in the speech of the participants. Results: The results show that vowels (monophthongs and diphthongs) are lengthened by all participants. Unexpectedly, educated and uneducated speakers from northern and central dialects lengthen vowels. Compared with uneducated speakers from the same dialect, educated speakers lengthen fewer vowels in their dialectal speech. Conclusions: These findings support the notion that extensive exposure to dialects on account of standard language can cause changes to the patterns of dialects themselves, and this can be seen in the speech of educated and uneducated speakers of these dialects. Further research is needed to clarify the phonemic distinctive features and frequency of lengthening in other open class systems (i.e., nouns, adjectives, and adverbs). Phonetic and phonological report measures are needed as well as validation of existing measures for assessing phonemic vowel length in the Arabic population in general and Arabic individuals with voice, speech, and language impairments in particular.

Keywords: vowel lengthening, Arabic dialect of Yemen, phonetics, phonology, impairment, distinctive features

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Authors: Slah Alsaleh

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In the recent years and with popularity of internet and technology, e-learning became a major part of majority of education systems. One of the advantages the e-learning systems provide is the large amount of information available about the students' behavior while communicating with the e-learning system. Such information is very rich and it can be used to improve the capability and efficiency of e-learning systems. This paper discusses how e-learning can benefit from implicit data in different ways including; creating homogeneous groups of student, evaluating students' learning, creating behavior profiles for students and identifying the students through their behaviors.

Keywords: e-learning, implicit data, user behavior, data mining

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Authors: Messaouda Annab

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The rapid development of technology has led to an important context in which different languages and structures are used in the same conversations. This paper investigates the practice of language borrowing within social media platform, namely, Facebook among Algerian Vernacular Arabic (AVA) students. In other words, this study will explore how Algerian students have incorporated lexical English borrowing in their online conversations. This paper will examine the relationships between language, culture and identity among a multilingual group. The main objective is to determine the cultural and linguistic functions that borrowing fulfills in social media and to explain the possible factors underlying English borrowing. The nature of the study entails the use of an online research method that includes ten online Facebook conversations in the form of private messages collected from Bachelor and Masters Algerian students recruited from the English department at the University of Oum El-Bouaghi. The analysis of data revealed that social media platform provided the users with opportunities to shift from one language to another. This practice was noticed in students’ online conversations. English borrowing was the most relevant language performance in accordance with Arabic which is the mother tongue of the chosen sample. The analysis has assumed that participants are skilled in more than one language.

Keywords: borrowing, language performance, linguistic background, social media

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Authors: Samuel Munaf, Kevin Swingler, Franz Brülisauer, Anthony O’Hare, George Gunn, Aaron Reeves

Abstract:

Background: Avian influenza, more commonly known as Bird flu, is a viral zoonotic respiratory disease stemming from various species of poultry, including pets and migratory birds. Researchers have purported that the accessibility of health information online, in addition to the low-cost data collection methods the internet provides, has revolutionized the methods in which epidemiological and disease surveillance data is utilized. This paper examines the feasibility of using internet data sources, such as Twitter and livestock forums, for the early detection of the avian flu outbreak, through the use of text mining algorithms and social network analysis. Methods: Social media mining was conducted on Twitter between the period of 01/01/2021 to 31/12/2021 via the Twitter API in Python. The results were filtered firstly by hashtags (#avianflu, #birdflu), word occurrences (avian flu, bird flu, H5N1), and then refined further by location to include only those results from within the UK. Analysis was conducted on this text in a time-series manner to determine keyword frequencies and topic modeling to uncover insights in the text prior to a confirmed outbreak. Further analysis was performed by examining clinical signs (e.g., swollen head, blue comb, dullness) within the time series prior to the confirmed avian flu outbreak by the Animal and Plant Health Agency (APHA). Results: The increased search results in Google and avian flu-related tweets showed a correlation in time with the confirmed cases. Topic modeling uncovered clusters of word occurrences relating to livestock biosecurity, disposal of dead birds, and prevention measures. Conclusions: Text mining social media data can prove to be useful in relation to analysing discussed topics for epidemiological surveillance purposes, especially given the lack of applied research in the veterinary domain. The small sample size of tweets for certain weekly time periods makes it difficult to provide statistically plausible results, in addition to a great amount of textual noise in the data.

Keywords: veterinary epidemiology, disease surveillance, infodemiology, infoveillance, avian influenza, social media

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Authors: Bilal Orfali

Abstract:

It is common practice in modern times to read mystical poetry and apply it to our mundane lives and loves. Sufis in the early period did the opposite. Their mystical hymns often spun out of the courtly poetic ghazal, panegyric, and wine songs. This paper highlights the relation of the Arabic courtly poetic canon to early Sufism. Sufi akhbār and poetry evoke past poets and their poetic heritage. They tend to quote or refer to eminent poets whose poetry must have been widely circulated and memorized. However, Sufism places this readily recognizable poetry in a new context that deliberately changes the past. It is a process of a metaphorization in which the reality of the pre-Islamic, Umayyad, and Abbasid models now acts as a device or metaphor for the Sufi poetics.

Keywords: Sufism, Arabic poetry, literature, Islamic literature, Abbasid

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Authors: Shahin Shabani, Pouya Pourmadadi

Abstract:

Tunnel boring machines (TBMs) have been used for the construction of various tunnels for mining projects for the purpose of access, conveyance of ore and waste, drainage, exploration, water supply and water diversion. Several mining projects have seen the successful and economic beneficial use of TBMs, and there is an increasing awareness of the benefits of TBMs for mining projects. Key technical considerations for the use of TBMs for the construction of tunnels for mining projects include geological issues (rock type, rock alteration, rock strength, rock abrasivity, durability, ground water inflows), depth of cover and the potential for overstressing/rockbursts, site access and terrain, portal locations, TBM constraints, minimum tunnel size, tunnel support requirements, contractor and labor experience, and project schedule demands. This study focuses on tunnelling mining, with the goal to develop methods and tools to be used to gain understanding of these processes, and to analyze metro of Tehran. The Metro Line 7 of Tehran is one of the Longest (26 Km) and deepest (27m) of projects that’s under implementation. Because of major differences like passing under all geotechnical layers of the town and encountering part of it with underground water table and also using mechanized excavation system, is one of special metro projects.

Keywords: TBM, tunnel boring machines economic, metro, line 7

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Authors: Teklu Urgessa, Joong Seek Lee

Abstract:

Social media is becoming the primary choice of activists to make their voices heard. This fact is coupled by two main reasons. The first reason is the emergence web 2.0, which gave the users opportunity to become content creators than passive recipients. Secondly the control of the mainstream mass media outlets by the governments and individuals with their political and economic interests. This paper aimed at exploring twitter data of network actors talking about the marathon silver medalists on Rio2016, who showed solidarity with the Oromo protesters in Ethiopia on the marathon race finish line when he won silver. The aim is to discover important insight using social network analysis and mining. The hashtag #FeyisaLelisa was used for Twitter network search. The actors’ network was visualized and analyzed. It showed the central influencers during first 10 days in August, were international media outlets while it was changed to individual activist in September. The degree distribution of the network is scale free where the frequency of degrees decay by power low. Text mining was also used to arrive at meaningful themes from tweet corpus about the event selected for analysis. The semantic network indicated important clusters of concepts (15) that provided different insight regarding the why, who, where, how of the situation related to the event. The sentiments of the words in the tweets were also analyzed and indicated that 95% of the opinions in the tweets were either positive or neutral. Overall, the finding showed that Olympic stage protest of the marathoner brought the issue of Oromo protest to the global stage. The new research framework is proposed based for event-based social network analysis and mining based on the practical procedures followed in this research for event-based social media sense making.

Keywords: human rights, Olympics, social media, network analysis, social network ming

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Authors: Raja Al-Ghamdi

Abstract:

This paper aims to systematically assess the translation of key cultural texts. The paper, therefore, proposes a modification of the discourse analysis model for translation quality assessment introduced by the linguist Juliane House (1977, 1997, 2015). The data for analysis has been chosen from a religious text that has never been investigated before. It is an overt translation of the biography of Prophet Mohammad. The book is written originally in Arabic and translated into English. A soft copy of the translation, entitled The Sealed Nectar, is posted on numerous websites including the Internet Archive library which offers a free access to everyone. The text abounds with linguistic and cultural phenomena relevant to Islamic and Arab lingua-cultural context which make its translation a challenge, as well as its assessment. Interesting findings show that (1) culturemes are rich points and both the translator’s subjectivity and intervention are apparent in mediating them, (2) given the nature of historical narration, the source text reflects the author’s positive shading, whereas the target text reflects the translator’s axiological orientation as neutrally shaded, and, (3) linguistic gaps, metaphorical expressions and intertextuality are major stimuli to compensation strategies.

Keywords: Arabic-English discourse analysis, key cultural texts, overt translation, quality assessment

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Authors: Mohammad Al-Dawoody

Abstract:

This study aims at exploring if priming is affected by gender in Modern Standard Arabic and if it is restricted solely to subjects with no specific language impairment (SLI). The sample in this study consists of 74 subjects, between the ages of 11;1 and 11;10, distributed into (a) 2 SLI experimental groups of 38 subjects divided into two gender groups of 18 females and 20 males and (b) 2 non-SLI control groups of 36 subjects divided into two gender groups of 17 females and 19 males. Employing a mixed research design, the researcher conducted this study within the framework of the relevance theory (RT) whose main assumption is that human beings are endowed with a biological ability to magnify the relevance of the incoming stimuli. Each of the four groups was given two different priming stimuli: audio-visual priming (T1) and syntactic priming (T2). The results showed that the priming effect was sheer distinct among SLI participants especially when retrieving typical responses (TR) in T1 and T2 with slight superiority of males over females. The results also revealed that non-SLI females showed stronger original response (OR) priming in T1 than males and that non-SLI males in T2 excelled in OR priming than females. Furthermore, the results suggested that the audio-visual priming has a stronger effect on SLI females than non-SLI females and that syntactic priming seems to have the same effect on the two groups (non-SLI and SLI females). The conclusion is that the priming effect varies according to gender and is not confined merely to non-SLI subjects.

Keywords: specific language impairment, relevance theory, audio-visual priming, syntactic priming, modern standard Arabic

Procedia PDF Downloads 152