Search results for: Arabic data mining

Authors: Haq Nawaz, Muhammad Amjad Iqbal, Kamran Malik

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"Altasreef" is an automated system available for Web and Android users which provide facility to the users to learn the Quran verbs. It provides the facility to the users to practice the learned material and also provide facility of exams of Arabic verbs variation focusing on Quran text. Arabic is a highly inflectional language. Almost all of its words connect to roots of three, four or five letters which approach the meaning of all their inflectional forms. In Arabic, a verb is formed by inserting the consonants into one of a set of verb patterns. Suffixes and prefixes are then added to generate the meaning of number, person, and gender. The active/passive voice and perfective aspect and other patterns are than generated. This application is designed for learners of Quranic Arabic who already have learn basics of Arabic conjugation. Application also provides the facility of translation of generated patterns. These translations are generated with the help of rule-based approach to give 100% results to the learners.

Keywords: NLP, Quran, Computational Linguistics, E Learning

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Authors: Fairouz Beggas

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Due to the large number of exchanges in the networks, the security of communications is essential. Most ways of keeping communication secure rely on encryption. In this work, a symmetric encryption technique is offered to encrypt and decrypt simple Arabic scripts based on a multi-level security. A proposed technique uses an idea of Playfair encryption with a larger table size and an additional layer of encryption to ensure more security. The idea of the proposed algorithm aims to generate a dynamic table that depends on a secret key. The same secret key is also used to create other secret keys to over-encrypt the plaintext in three steps. The obtained results show that the proposed algorithm is faster in terms of encryption/decryption speed and can resist to many types of attacks.

Keywords: arabic data, encryption, playfair, symmetric algorithm

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Authors: Z. Abdullah, A. R. Hamdan

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Clustering is a process of grouping objects and data into groups of clusters to ensure that data objects from the same cluster are identical to each other. Clustering algorithms in one of the areas in data mining and it can be classified into partition, hierarchical, density based, and grid-based. Therefore, in this paper, we do a survey and review for four major hierarchical clustering algorithms called CURE, ROCK, CHAMELEON, and BIRCH. The obtained state of the art of these algorithms will help in eliminating the current problems, as well as deriving more robust and scalable algorithms for clustering.

Keywords: clustering, unsupervised learning, algorithms, hierarchical

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Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

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This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

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Authors: Gameel Abdelmageed

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Arabs have a rhetorical heritage which has greatly contributed to the monitoring and analyzing of the rhetoric of the Holy Quran, Hadith, and Arabic texts on poetry and oratory. But Arab scholars - as far as the researcher knows – have not contributed to monitoring and analyzing the rhetoric of digital Arabic discourse although it has prominence, particularly in social media and has strong effectiveness in the political and social life of Arab society. This discourse has made its impact by using very new rhetorical techniques in language, voice, image, painting and video clips which are known as “Multimedia” and belong to “Digital Rhetoric”. This study suggests that it is time to draw the attention of Arab scholars and invite them to monitor and analyze the rhetoric of digital Arabic discourse.

Keywords: digital discourse, digital rhetoric, Facebook, social media

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Authors: Abdel Rahman Altakhaineh

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This paper has analysed the conceptual relations between the elements of NN compounds in Arabic and compared them to those found in English based on the framework of Conceptual Semantics and a modified version of Parallel Architecture referred to as Relational Morphology. The analysis revealed that the repertoire of possible semantic relations between the two nouns in Arabic NN compounds reproduces that in English NN compounds and that, therefore, the main difference is in headedness (right-headed in English, left-headed in Arabic). Adopting RM allows productive and idiosyncratic elements to interweave with each other naturally. Semantically transparent compounds can be stored in memory or produced and understood online, while compounds with different degrees of semantic idiosyncrasy are stored in memory. Furthermore, the predictable parts of idiosyncratic compounds are captured by general schemas. In compounds, such schemas pick out the range of possible semantic relations between the two nouns. Finally, conducting a cross-linguistic study of the systematic patterns of possible conceptual relationships between compound elements is an area worthy of further exploration. In addition, comparing and contrasting compounding in Arabic and Hebrew, especially as they are both Semitic languages, is another area that needs to be investigated thoroughly. It will help morphologists understand the extent to which Jackendoff’s repertoire of semantic relations in compounds is universal. That is, if a language as distant from English as Arabic displays a similar range of cases, this is evidence for a (relatively) universal set of relations from which individual languages may pick and choose.

Keywords: conceptual semantics, morphology, compounds, arabic, english

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Authors: Nidhin Dani Abraham, T. K. Sri Shilpa

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Asset liability management is an important aspect in banking business. Moreover, the today’s banking is based on BASEL III which strictly regulates on the counterparty default. This paper focuses on prediction and analysis of counter party default risk, which is a type of risk occurs when the customers fail to repay the amount back to the lender (bank or any financial institutions). This paper proposes an approach to reduce the counterparty risk occurring in the financial institutions using an appropriate data mining technique and thus predicts the occurrence of NPA. It also helps in asset building and restructuring quality. Liability management is very important to carry out banking business. To know and analyze the depth of liability of bank, a suitable technique is required. For that a data mining technique is being used to predict the dormant behaviour of various deposit bank customers. Various models are implemented and the results are analyzed of saving bank deposit customers. All these data are cleaned using data cleansing approach from the bank data warehouse.

Keywords: data mining, asset liability management, BASEL III, banking

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Authors: Chandan Pramanik, Bikramjit Chanda

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Large metal mines operated with open-cast mining methods must transition to underground mining at the conclusion of the operation; however, this requires a period of a difficult time when production convergence due to interference between the two mining methods. A transition model with collaborative mining operations is presented and established in this work, based on the case of the South Kaliapani Underground Project, to address these technical issues of inadequate production security and other mining challenges during the transition phase and beyond. By integrating the technology of the small-scale Drift and Fill method and Highly productive Sub Level Open Stoping at deep section, this hybrid mining concept tries to eliminate major bottlenecks and offers an optimized production profile with the safe and sustainable operation. Considering every geo-mining aspect, this study offers a genuine and precise technical deliberation for the transition from open pit to underground mining.

Keywords: drift and fill, geo-mining aspect, sublevel open stoping, underground mining method

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Authors: Jamal Gaber Abdalla

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In business promotion and advertising, language is used intentionally to create a powerful influence over people and their behavior. In commercial and marketing activities, the choice of language to convey specific messages with the intention of influencing people is pragmatically important. Design and visual content in promotional and advertising texts also have a great persuasive impact on consumers. It is the functional combination of design, language and visual content that helps people to identify a product or service and remember it. Translating promotional and advertising texts between structurally and culturally different languages, such as English and Arabic, usually involves pragmatic/functional shifts that decide the quality of translation. This study explores some of these shifts in translating promotional and advertising texts between English and Arabic and their implications for translation quality. The study is based on a contrastive analysis of data collected from real samples of English-Arabic translations of promotional and advertising texts. The samples cover different promotional and advertising text types and different business domains. The aim is to identify the most recurrent translation shifts and most used translation approaches/strategies that achieve quality in view of the functional nature of promotional and advertising texts and target language culture conventions. The study shows that linguistic shifts and visual shifts are recurrent in English-Arabic translations of promotional and advertising texts. The study also shows that the most commonly used translation approaches/strategies are functional translation, domestication, communicative translation.

Keywords: advertising, Arabic, English, functional translation, promotion

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Authors: Fongang Robert Tichuck

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This paper reports the findings of a study undertaken to assess the socio-economic and environmental impacts of mining in Bertoua Eastern Region of Cameroon. In addition to sampling community perceptions of mining activities, the study prescribes interventions that can assist in mitigating the negative impacts of mining. Marked environmental and interrelated socio-economic improvements can be achieved within regional artisanal gold mines if the government provides technical support to local operators, regulations are improved, and illegal mining activity is reduced.

Keywords: gold mining, socio-economic, mining activities, local people

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Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

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Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

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Authors: Grace Omowunmi Soyebi

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Data Mining is the extraction of information from a large database which helps in predicting a trend or behavior, thereby helping management make knowledge-driven decisions. One principal problem of most hospitals in rural areas is making use of the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved; this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method, which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to easily retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: data mining, medical record system, systems programming, computing

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Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Redouane Tlemsani, Abdelkader Benyettou

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Work is in on line Arabic character recognition and the principal motivation is to study the Arab manuscript with on line technology. This system is a Markovian system, which one can see as like a Dynamic Bayesian Network (DBN). One of the major interests of these systems resides in the complete models training (topology and parameters) starting from training data. Our approach is based on the dynamic Bayesian Networks formalism. The DBNs theory is a Bayesians networks generalization to the dynamic processes. Among our objective, amounts finding better parameters, which represent the links (dependences) between dynamic network variables. In applications in pattern recognition, one will carry out the fixing of the structure, which obliges us to admit some strong assumptions (for example independence between some variables). Our application will relate to the Arabic isolated characters on line recognition using our laboratory database: NOUN. A neural tester proposed for DBN external optimization. The DBN scores and DBN mixed are respectively 70.24% and 62.50%, which lets predict their further development; other approaches taking account time were considered and implemented until obtaining a significant recognition rate 94.79%.

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, computer vision

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Authors: Yousef Barahmeh

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This paper is a linguistic and pragmatic analysis of the use of the diminutive in Colloquial Jordanian Arabic (CJA). It demonstrates a peculiar form of the diminutive in CJA inflected by means of feminine plural ends with -aat suffix. The analysis shows that the pragmatic function(s) of the diminutive in CJA refers primarily to ‘littleness’ while the morphological inflection conveys the message of ‘the plethora’. Examples of this linguistic phenomenon are intelligible and often include a large number of words that are culture-specific to the rural dialect in the north of Jordan. In both cases, the diminutive in CJA is an adaptive strategy relative to its pragmatic and social contexts.

Keywords: Colloquial Jordanian Arabic, diminutive, morphology, pragmatics

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Authors: Mohamed Lotfy, Ghada Soliman

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Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

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Authors: Ashwag O. Maghraby, Nida N. Khan, Hosnia A. Ahmed, Ghufran N. Brohi, Hind F. Assouli, Jawaher S. Melibari

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The Arabic language is one of the most important languages. Learning it is so important for many people around the world because of its religious and economic importance and the real challenge lies in practicing it without grammatical or syntactical mistakes. This research focused on detecting and correcting the syntactic mistakes of Arabic syntax according to their position in the sentence and focused on two of the main syntactical rules in Arabic: Dual and Plural. It analyzes each sentence in the text, using Stanford CoreNLP morphological analyzer and machine-learning approach in order to detect the syntactical mistakes and then correct it. A prototype of the proposed system was implemented and evaluated. It uses support vector machine (SVM) algorithm to detect Arabic grammatical errors and correct them using the rule-based approach. The prototype system has a far accuracy 81%. In general, it shows a set of useful grammatical suggestions that the user may forget about while writing due to lack of familiarity with grammar or as a result of the speed of writing such as alerting the user when using a plural term to indicate one person.

Keywords: Arabic language acquisition and learning, natural language processing, morphological analyzer, part-of-speech

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Authors: Erin Lynne Plettenberg, Jeremy Vickery

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In an access-control situation, the role of a user determines whether a data request is appropriate. This paper combines vetted web mining and logic modeling to build a lightweight system for determining the role of a health care provider based only on their prior authorized requests. The model identifies provider roles with 100% recall from very little data. This shows the value of vetted web mining in AI systems, and suggests the impact of the ICD classification on medical practice.

Keywords: electronic medical records, information extraction, logic modeling, ontology, vetted web mining

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Authors: Olga Bernikova, Oleg Redkin

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Globalization is a process of worldwide economic, political and cultural integration. Obviously, this phenomenon has both positive and negative issues. This article analyzes the impact of the modern process of globalization on the national traditions of language teaching and research. In this context, the problem of the ratio of local to global can be viewed from several sides. Firstly, since English is the language of over 80 percent of scientific and technical research worldwide, what should be the language of science in certain region? Secondly, language 'globality' is not always associated with English, because intercultural communications may have their regional peculiarities. For example, in the Arab world, Modern Standard Arabic can also be regarded as 'global' phenomenon, since the mother-tongue languages of the population are local Arabic dialects. In addition, the correlation 'local' versus 'global' is manifested not only in the linguistic sphere but also in the methodology used in language acquisition and research. Thus, the major principles of the Arabic philological tradition, which goes back to the 7th century, are still spread in the modern Arab world. At the same time, the terminology and methods of language research that are peculiar to this tradition are quite far from the issues of general linguistics that underlies the description of all the languages of the world. The present research relies on a comparative analysis of sources in Arabic linguistics, including original works in Arabic dating back to the 12th-13th centuries. As a case study, interaction of local and global is also considered on the example of the Arabic teaching and research in Russia. Speaking about the correlation between local and global it is possible to forecast development of two parallel tendencies: the spread of the phenomena of globalization on one hand, and local implementation of a language policy aimed at preserving native languages, including Arabic, on the other.

Keywords: Arabic, global, language, local, tradition

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Authors: Shivam Dwivedi, Sumit Prakash Gupta, Durga Toshniwal

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It is a challenging task in today’s date to keep defence forces in the highest state of combat readiness with budgetary constraints. A huge amount of time and money is squandered in the unnecessary and expensive traditional maintenance activities. To overcome this limitation Defence Intelligent Mission Readiness and Maintenance Scheduling System has been proposed, which ameliorates the maintenance system by diagnosing the condition and predicting the maintenance requirements. Based on new data mining algorithms, this system intelligently optimises mission readiness for imminent operations and maintenance scheduling in repair echelons. With modified data mining algorithms such as Weighted Feature Ranking Genetic Algorithm and SVM-Random Forest Linear ensemble, it improves the reliability, availability and safety, alongside reducing maintenance cost and Equipment Out of Action (EOA) time. The results clearly conclude that the introduced algorithms have an edge over the conventional data mining algorithms. The system utilizing the intelligent condition-based maintenance approach improves the operational and maintenance decision strategy of the defence force.

Keywords: condition based maintenance, data mining, defence maintenance, ensemble, genetic algorithms, maintenance scheduling, mission capability

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Authors: Archana Singh, Jyoti Agarwal, Ajay Rana

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Data Mining is an efficient technology to discover patterns in large databases. Association Rule Mining techniques are used to find the correlation between the various item sets in a database, and this co-relation between various item sets are used in decision making and pattern analysis. In recent years, the problem of finding association rules from large datasets has been proposed by many researchers. Various research papers on association rule mining (ARM) are studied and analyzed first to understand the existing algorithms. Apriori algorithm is the basic ARM algorithm, but it requires so many database scans. In DIC algorithm, less amount of database scan is needed but complex data structure lattice is used. The main focus of this paper is to propose a new optimized algorithm (Friendly Algorithm) and compare its performance with the existing algorithms A data set is used to find out frequent itemsets and association rules with the help of existing and proposed (Friendly Algorithm) and it has been observed that the proposed algorithm also finds all the frequent itemsets and essential association rules from databases as compared to existing algorithms in less amount of database scan. In the proposed algorithm, an optimized data structure is used i.e. Graph and Adjacency Matrix.

Keywords: association rules, data mining, dynamic item set counting, FP-growth, friendly algorithm, graph

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Authors: Ahmed Al-Awthan

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This study addresses the prevalence of English terminology in published Arabic documentation on social media. Although the problem of using English terms in translation instead of existing native ones has been addressed in general by researchers around the world, to the best of the author’s knowledge the attitude of the translators as professionals to this phenomenon in Qatar and Yemen has not received a detailed study. This study examines the impact of the use of English, social media terms in the Arab world on aspiring and professional translators; it explores the benefits and drawbacks of linguistic borrowing as identified by the translators and investigates whether translators consider any means of resisting linguistic borrowing and prioritizing Arabic. It also aims to answer the following questions: i. Is there any prevalence of English, social media terms in Arabic translation? Why or why not? ii. Do Arabic translators prefer using English, social media terms to their equivalents in Arabic? If so, why? iii. Which measures could be adopted to help reduce the frequently observed borrowing of English terms? In particular, how do translators see the role of the Arabic Language Academies in preserving Arabic? iv. This research is descriptive, comparative and analytical in nature. It is both qualitative and quantitative. To validate the problem, the researcher will analyze articles published by Al-Jazeera in 2016-2018 that refer to the use of social media in diplomacy. It will be examined whether the increased international discussion of political events in social media increased the amount of transliterated English terminology referring to this mode of communication.To investigate whether the translators recognize the phenomenon of borrowing, the researcher proposes to use a survey. This survey will use multiple choice questions. It will target 20 aspiring translators from Yemen and 20 participants from Qatar. It will offer 15 English, social media terms used in discourse in 15 sentences. For each sentence, the researcher will provide three different translations and will ask the translators to rate them and offer their rendition. After collecting all the answers online, the researcher will analyze the data. The results are expected to confirm whether there is a prevalence of English terms in translating into Arabic. It is also expected to show what measures the translators used to render the English, social media terms, and it raises awareness of borrowing English terms. It will guide the translator toward using Arabicization methods in order to contribute to preserving Arabic.

Keywords: Arabicization, trans lingual borrowing, social media terms, terminology

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Authors: Sharafat Karimi, Jamil Jafari

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The impact of Western Literature on other nations' pieces of literature (including Arabic) has caused critics to ignore the importance of Arabic cultural & literary heritage in the formation of contemporary Arabic fiction; but on the contrary, an important part of literary genres in any society, especially fiction has been formed in the past and depends on ancient literary events. The current paper, utilizing the descriptive-analytical method and by means of library studies, tries to challenge those critics who regard Western Literature as the only effective factor on the appearance of Arabic fiction. Furthermore, this research tries to find out effective Islamic-Arabic elements on the development of Arabic novel by the investigation of some fictional works. The results show that in addition to regarding Western literature as an important factor, Arab novelists have applied their heritage, culture, and ancient history, either written or orally transmitted to the current generation, in their innovations. Among great historical works containing moral stories, allegorical legends, myths, tales of heroes, and folklore, we can refer to Arabian Nights, Kalila & Dimna, romantic stories, historical puzzles, history of Islam, history of ancient Egypt, Maqama, and Quranic stories. Famous novels like 'Hadith Isa ibn-Hisham', 'Layali Alif Layla', 'Abas al-Aqdar', 'Radoubis', 'Ahlam Shahrzad, and 'Alam Bela Kharaet' were compiled on the basis of ancient literary heritage not only in the theme but also in the structure; so one can conclude that the ancient literary-cultural heritage and Islamic-Arabian history have been influential on Arabic novel appearance and development.

Keywords: Arabic fictional literature, culture, heritage, history, language, novel

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Authors: Rizka Aisha Rahmi Hariadi, Chao Ou-Yang, Han-Cheng Wang, Rajesri Govindaraju

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As the increasing of medical check-up popularity, there are a huge number of medical check-up data stored in database and have not been useful. These data actually can be very useful for future strategic planning if we mine it correctly. In other side, a lot of patients come with unpredictable coming and also limited available facilities make medical check-up service offered by hospital not maximal. To solve that problem, this study used those medical check-up data to predict patient re-coming. Sequential pattern mining (SPM) and association rules method were chosen because these methods are suitable for predicting patient re-coming using sequential data. First, based on patient personal information the data was grouped into … groups then discriminant analysis was done to check significant of the grouping. Second, for each group some frequent patterns were generated using SPM method. Third, based on frequent patterns of each group, pairs of variable can be extracted using association rules to get general pattern of re-coming patient. Last, discussion and conclusion was done to give some implications of the results.

Keywords: patient re-coming, medical check-up, health examination, data mining, sequential pattern mining, association rules, discriminant analysis

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Authors: Khenfer Koummich Fatma, Hendel Fatiha, Mesbahi Larbi

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This paper presents an approach based on Hidden Markov Models (HMM: Hidden Markov Model) using HTK tools. The goal is to create a human-machine interface with a voice recognition system that allows the operator to teleoperate a mentor robot to execute specific tasks as rotate, raise, close, etc. This system should take into account different levels of environmental noise. This approach has been applied to isolated words representing the robot commands pronounced in two languages: French and Arabic. The obtained recognition rate is the same in both speeches, Arabic and French in the neutral words. However, there is a slight difference in favor of the Arabic speech when Gaussian white noise is added with a Signal to Noise Ratio (SNR) equals 30 dB, in this case; the Arabic speech recognition rate is 69%, and the French speech recognition rate is 80%. This can be explained by the ability of phonetic context of each speech when the noise is added.

Keywords: Arabic speech recognition, Hidden Markov Model (HMM), HTK, noise, TIMIT, voice command

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Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

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This paper aims to create the model for student in choosing an emphasized track of student majoring in computer science at Suan Sunandha Rajabhat University. The objective of this research is to develop the suggested system using data mining technique to analyze knowledge and conduct decision rules. Such relationships can be used to demonstrate the reasonableness of student choosing a track as well as to support his/her decision and the system is verified by experts in the field. The sampling is from student of computer science based on the system and the questionnaire to see the satisfaction. The system result is found to be satisfactory by both experts and student as well.

Keywords: data mining technique, the decision support system, knowledge and decision rules, education

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Authors: Mai Alharthy, Agnes Shiel, Hynes Sinead

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Objectives: The objectives of the study are to translate and culturally adapt the RBMT-3 to be appropriate for use within an Arabic-speaking population and to achieve maximum equivalency between the translated and original versions and to evaluate the psychometric properties of the Arabic version of the RBMT-3. Participants' numbers are 16 (10 females and 6 males). All participants are bilingual speakers of Arabic and English, above 18 years old and with no current nor past memory impairment. Methods: The study was conducted in two stages: Translation and cultural adaptation stage: Forward and backward translations were completed by professional translators. Five out of the 14 RBMT-3 subtests required cultural adaptations. Half of the faces in the face recognition subtests were replaced with Arabic faces by a professional photographer. Pictures that are irrelevant to the Arabic culture in the picture recognition subtests were replaced. Names, story and orientations subtests were also adapted to suit the Arabic culture. An expert committee was formed to compare the translated and original versions and to advise on further changes required for test materials. Validation of the Arabic RBMT-3- pilot: 16 Participants were tested on version 1 of the English version and the two versions of the Arabic RBMT-3 ( counterbalanced ). The assessment period was 6 weeks long, with two weeks gap between tests. All assessments took place in a quiet room in the National University of Ireland Galway. Two qualified occupational therapists completed the assessments. Results: Wilcox signed-rank test was used to compare between subtest scores. Significant differences were found in the story, orientation and names subtests between the English and Arabic versions. No significant differences were found in subtests from both Arabic versions except for the story subtest. Conclusion: The story and orientation subtests should be revised by the expert committee members to make further adaptations. The rest of the Arabic RBMT-3 subtests are equivalent to the subtests of the English version. The psychometric properties of the Arabic RBMT-3 will be investigated in a larger Arabic-speaking sample in Saudi Arabia. The outcome of this research is to provide clinicians and researchers with a reliable tool to assess memory problems in Arabic speaking population.

Keywords: memory impairment, neuropsychological assessment, cultural adaptation, cognitive assessment

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Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung

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In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.

Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining

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Authors: Mohammad Anwarul Kabir, Fayezul Islam

Abstract:

Language invariably is learned / taught to be used primarily as means of communications. Teaching a language for its native audience differs from teaching it to non-native audience. Moreover, teaching a language for communication only is different from teaching it for specific purposes. Arabic language is primarily regarded as the language of the Quran and the Sunnah (Prophetic tradition). Arabic is, therefore, learnt and spread all over the globe. However, Arabic is also a cultural heritage shared by all Islamic nations which has used Arabic for a long period to record the contributions of Muslim thinkers made in the field of wide spectrum of knowledge and scholarship. That is why the phenomenon of teaching Arabic by different educational institutes became quite rife, and the idea of teaching Arabic for specific purposes is heavily discussed in the academic sphere. Although the number of learners of Arabic is increasing consistently, yet their purposes vary. These include religious purpose, international trade, diplomatic purpose, better livelihood in the Arab world extra. By virtue of this high demand for learning Arabic, numerous institutes have been established all over the world including Bangladesh. This paper aims at focusing on the current status of the language institutes which has been established for learning Arabic for specific purposes in Bangladesh including teaching methodology, curriculum, and teachers’ quality. Such curricula and using its materials resulted in a lot of problems. The least, it confused teachers and students as well. Islamic educationalists have been working hard to professionally meet the need. They are following a systematic approach of stating clear and achievable goals, building suitable content, and applying new technology to present these learning experiences and evaluate them. It also suggests a model for designing instructional systems that responds to the need of non-Arabic speaking Islamic communities and provide the knowledge needed in both linguistic and cultural aspects. It also puts forward a number of suggestions for the improvement of the teaching / learning Arabic for specific purposes in Bangladesh after a detailed investigation in the following areas: curriculum, teachers’ skills, method of teaching and assessment policy.

Keywords: communication, Quran, sunnah, educational institutes, specific purposes, curriculum, method of teaching

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Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

Abstract:

Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

Procedia PDF Downloads 556