Search results for: specific language impairment.

Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: Subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing.

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Authors: Eleni Galiotou, Angela Ralli

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In this paper we propose a computational model for the representation and processing of morpho-phonological phenomena in a natural language, like Modern Greek. We aim at a unified treatment of inflection, compounding, and word-internal phonological changes, in a model that is used for both analysis and generation. After discussing certain difficulties cuase by well-known finitestate approaches, such as Koskenniemi-s two-level model [7] when applied to a computational treatment of compounding, we argue that a morphology-based model provides a more adequate account of word-internal phenomena. Contrary to the finite state approaches that cannot handle hierarchical word constituency in a satisfactory way, we propose a unification-based word grammar, as the nucleus of our strategy, which takes into consideration word representations that are based on affixation and [stem stem] or [stem word] compounds. In our formalism, feature-passing operations are formulated with the use of the unification device, and phonological rules modeling the correspondence between lexical and surface forms apply at morpheme boundaries. In the paper, examples from Modern Greek illustrate our approach. Morpheme structures, stress, and morphologically conditioned phoneme changes are analyzed and generated in a principled way.

Keywords: Morpho-Phonology, Natural Language Processing.

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Authors: László Lengyel, Tihamér Levendovszky, Hassan Charaf

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This paper presents the visual control flow support of Visual Modeling and Transformation System (VMTS), which facilitates composing complex model transformations out of simple transformation steps and executing them. The VMTS Visual Control Flow Language (VCFL) uses stereotyped activity diagrams to specify control flow structures and OCL constraints to choose between different control flow branches. This work discusses the termination properties of VCFL and provides an algorithm to support the termination analysis of VCFL transformations.

Keywords: Control Flow, Metamodel-Based Visual Model Transformation, OCL, Termination Properties, UML.

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Authors: Viet-Hoang Vu, Nhan Le-Thanh

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Recently the usefulness of Concept Abduction, a novel non-monotonic inference service for Description Logics (DLs), has been argued in the context of ontology-based applications such as semantic matchmaking and resource retrieval. Based on tableau calculus, a method has been proposed to realize this reasoning task in ALN, a description logic that supports simple cardinality restrictions as well as other basic constructors. However, in many ontology-based systems, the representation of ontology would require expressive formalisms for capturing domain-specific constraints, this language is not sufficient. In order to increase the applicability of the abductive reasoning method in such contexts, we would like to present in the scope of this paper an extension of the tableaux-based algorithm for dealing with concepts represented inALCQ, the description logic that extends ALN with full concept negation and quantified number restrictions.

Keywords: Abductive reasoning, description logics, semantic matchmaking, non-monotonic inference, tableaux-based method.

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Authors: S. H. J. Liu

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This paper aims to explore the role of peer Corrective Feedback (CF) in improving written productions by English-as-a- foreign-language (EFL) learners who work together via Wikispaces. It attempted to determine the effect of peer CF on form accuracy in English, such as grammar and lexis. Thirty-four EFL learners at the tertiary level were randomly assigned into the experimental (with peer feedback) or the control (without peer feedback) group; each group was subdivided into small groups of two or three. This resulted in six and seven small groups in the experimental and control groups, respectively. In the experimental group, each learner played a role as an assessor (providing feedback to others), as well as an assessee (receiving feedback from others). Each participant was asked to compose his/her written work and revise it based on the feedback. In the control group, on the other hand, learners neither provided nor received feedback but composed and revised their written work on their own. Data collected from learners’ compositions and post-task interviews were analyzed and reported in this study. Following the completeness of three writing tasks, 10 participants were selected and interviewed individually regarding their perception of collaborative learning in the Computer-Mediated Communication (CMC) environment. Language aspects to be analyzed included lexis (e.g., appropriate use of words), verb tenses (e.g., present and past simple), prepositions (e.g., in, on, and between), nouns, and articles (e.g., a/an). Feedback types consisted of CF, affective, suggestive, and didactic. Frequencies of feedback types and the accuracy of the language aspects were calculated. The results first suggested that accurate items were found more in the experimental group than in the control group. Such results entail that those who worked collaboratively outperformed those who worked non-collaboratively on the accuracy of linguistic aspects. Furthermore, the first type of CF (e.g., corrections directly related to linguistic errors) was found to be the most frequently employed type, whereas affective and didactic were the least used by the experimental group. The results further indicated that most participants perceived that peer CF was helpful in improving the language accuracy, and they demonstrated a favorable attitude toward working with others in the CMC environment. Moreover, some participants stated that when they provided feedback to their peers, they tended to pay attention to linguistic errors in their peers’ work but overlook their own errors (e.g., past simple tense) when writing. Finally, L2 or FL teachers or practitioners are encouraged to employ CMC technologies to train their students to give each other feedback in writing to improve the accuracy of the language and to motivate them to attend to the language system.

Keywords: Peer corrective feedback, computer-mediated communication, second or foreign language learning, Wikispaces.

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Authors: Theologos Athanaselis, Stelios Bakamidis, Ioannis Dologlou

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Emotion in speech is an issue that has been attracting the interest of the speech community for many years, both in the context of speech synthesis as well as in automatic speech recognition (ASR). In spite of the remarkable recent progress in Large Vocabulary Recognition (LVR), it is still far behind the ultimate goal of recognising free conversational speech uttered by any speaker in any environment. Current experimental tests prove that using state of the art large vocabulary recognition systems the error rate increases substantially when applied to spontaneous/emotional speech. This paper shows that recognition rate for emotionally coloured speech can be improved by using a language model based on increased representation of emotional utterances.

Keywords: Statistical language model, N-grams, emotionallycoloured speech

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Authors: Amic G. Ho

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Language usage and typography in Hong Kong are unique, as can be seen clearly on the streets of the city. In contrast to many other parts of the world, where there is only one language, in Hong Kong many signs and billboards display two languages: Chinese and English. The language usage on signage, fonts and types used, and the designs in magazines and advertisements all demonstrate the unique features of Hong Kong typographic design, which reflect the multicultural nature of Hong Kong society. This study is the first step in investigating the nature and development of Hong Kong typography. The preliminary research explored how the historical development of Hong Kong is reflected in its unique typography. Following a review of historical development, a quantitative study was designed: Local Hong Kong participants were invited to provide input on what makes the Hong Kong typographic style unique. Their input was collected and analyzed. This provided us with information about the characteristic criteria and features of Hong Kong typography, as recognized by the local people. The most significant typographic designs in Hong Kong were then investigated and the influence of Chinese and other cultures on Hong Kong typography was assessed. The research results provide an indication to local designers on how they can strengthen local design outcomes and promote the values and culture of their mother town.

Keywords: Typography, Hong Kong, historical developments, multiple cultures.

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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: Sheetal R. Jadhwani, Daisy Sang, Chang-Shyh Peng

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Web applications are an integral part of modem life. They are mostly based upon the HyperText Markup Language (HTML). While HTML meets the basic needs, there are some shortcomings. For example, applications can cease to work once user goes offline, real-time updates may be lagging, and user interface can freeze on computationally intensive tasks. The latest language specification HTML5 attempts to rectify the situation with new tools and protocols. This paper studies the new Web Storage, Geolocation, Web Worker, Canvas, and Web Socket APIs, and presents applications to test their features and efficiencies.

Keywords: HTML5, Web Worker, Canvas, Web Socket.

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Authors: Huda Al Shuaily, Karen Renaud

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Databases comprise the foundation of most software systems. System developers inevitably write code to query these databases. The de facto language for querying is SQL and this, consequently, is the default language taught by higher education institutions. There is evidence that learners find it hard to master SQL, harder than mastering other programming languages such as Java. Educators do not agree about explanations for this seeming anomaly. Further investigation may well reveal the reasons. In this paper, we report on our investigations into how novices learn SQL, the actual problems they experience when writing SQL, as well as the differences between expert and novice SQL query writers. We conclude by presenting a model of SQL learning that should inform the instructional material design process better to support the SQL learning process.

Keywords: Pattern, SQL, learning, model.

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Authors: M. Debyeche, J.P Haton, A. Houacine

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The paper presents a complete discrete statistical framework, based on a novel vector quantization (VQ) front-end process. This new VQ approach performs an optimal distribution of VQ codebook components on HMM states. This technique that we named the distributed vector quantization (DVQ) of hidden Markov models, succeeds in unifying acoustic micro-structure and phonetic macro-structure, when the estimation of HMM parameters is performed. The DVQ technique is implemented through two variants. The first variant uses the K-means algorithm (K-means- DVQ) to optimize the VQ, while the second variant exploits the benefits of the classification behavior of neural networks (NN-DVQ) for the same purpose. The proposed variants are compared with the HMM-based baseline system by experiments of specific Arabic consonants recognition. The results show that the distributed vector quantization technique increase the performance of the discrete HMM system.

Keywords: Hidden Markov Model, Vector Quantization, Neural Network, Speech Recognition, Arabic Language

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Authors: Mohammad J. Rezai, Fereshteh Davarpanah

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Producing a text in a language which is not one’s mother tongue can be a demanding task for language learners. Examining lexical errors committed by EFL learners is a challenging area of investigation which can shed light on the process of second language acquisition. Despite the considerable number of investigations into grammatical errors, few studies have tackled formal and semantic errors of lexis committed by EFL learners. The current study aimed at examining Persian learners’ formal and semantic errors of lexis in English. To this end, 60 students at three different proficiency levels were asked to write on 10 different topics in 10 separate sessions. Finally, 600 essays written by Persian EFL learners were collected, acting as the corpus of the study. An error taxonomy comprising formal and semantic errors was selected to analyze the corpus. The formal category covered misselection and misformation errors, while the semantic errors were classified into lexical, collocational and lexicogrammatical categories. Each category was further classified into subcategories depending on the identified errors. The results showed that there were 2583 errors in the corpus of 9600 words, among which, 2030 formal errors and 553 semantic errors were identified. The most frequent errors in the corpus included formal error commitment (78.6%), which were more prevalent at the advanced level (42.4%). The semantic errors (21.4%) were more frequent at the low intermediate level (40.5%). Among formal errors of lexis, the highest number of errors was devoted to misformation errors (98%), while misselection errors constituted 2% of the errors. Additionally, no significant differences were observed among the three semantic error subcategories, namely collocational, lexical choice and lexicogrammatical. The results of the study can shed light on the challenges faced by EFL learners in the second language acquisition process.

Keywords: Collocational errors, lexical errors, Persian EFL learners, semantic errors.

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Authors: Suwaree Yordchim, Toby J. Gibbs

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The objective is to study the satisfaction on English with an online learning. Online learning system mainly consists of English lessons, exercises, tests, web boards, and supplementary lessons for language practice. The sample groups are 80 Thai students studying English for Business Communication, majoring in Hotel and Lodging Management. The data are analyzed by mean, standard deviation (S.D.) value from the questionnaires. The results were found that the most average of satisfaction on academic aspects are technological searching tool through E-learning system that support the students’ learning (4.51), knowledge evaluation on pre-post learning and teaching (4.45), and change for project selections according to their interest, subject contents including practice in the real situations (4.45), respectively.

Keywords: English Learning, Online System, Satisfaction.

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Authors: A. Kowcika, E. Umamaheswari, T.V. Geetha

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In this paper we focus on event extraction from Tamil news article. This system utilizes a scoring scheme for extracting and grouping event-specific sentences. Using this scoring scheme eventspecific clustering is performed for multiple documents. Events are extracted from each document using a scoring scheme based on feature score and condition score. Similarly event specific sentences are clustered from multiple documents using this scoring scheme. The proposed system builds the Event Template based on user specified query. The templates are filled with event specific details like person, location and timeline extracted from the formed clusters. The proposed system applies these methodologies for Tamil news articles that have been enconverted into UNL graphs using a Tamil to UNL-enconverter. The main intention of this work is to generate an event based template.

Keywords: Event Extraction, Score based Clustering, Segmentation, Template Generation.

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Authors: S. Ait Ali Yahia

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One of the main features of the Maghreb is its linguistic richness. The multilingualism is a fact which always marked the Maghreb since the beginning of the history up to know. Since the arrival of the Phoenicians, followed by the Carthaginians, Romans, and Arabs, etc, there was a social group in the Maghreb which controlled two kinds of idioms. The libyc one remained, despite everything, the local language used by the major part of the population. This language had a support of written transmission attested by many inscriptions. Among all the forms of the Maghreb writing, this alphabet, however, continues to cause a certain number of questions about the origin and the date of its appearance. The archaeological, linguistic and historical data remain insufficient to answer these questions. This did not prevent the researchers from giving an opinion. In order to answer these questions we will expose here the various assumptions adopted by various authors who are founded on more or less explicit arguments. We will also speak about the various forms taken by the libyc writing during antiquity.

Keywords: The alphabet libyc, Eastern libyc, Western libyc.

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Authors: Helmi Adly Mohd Noor, Faaizah Shahbodin, Naim Che Pee

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Autism Spectrum Disorder (ASD) is a pervasive developmental disorder which affects individuals with varying degrees of impairment. Currently, there has been ample research done in serious game for autism children. Although serious games are traditionally associated with software developments, developing them in the autism field involves studying the associated technology and paying attention to aspects related to interaction with the game. Serious Games for autism cover matters related to education, therapy for communication, psychomotor treatment and social behavior enhancement. In this paper, a systematic review sets out the lines of development and research currently being conducted into serious games which pursue some form of benefit in the field of autism. This paper includes a literature review of relevant serious game developments since in year 2007 and examines new trends.

Keywords: Serious Game, Autism, Education, Therapy

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Authors: Shilpy Sharma

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As the web continues to grow exponentially, the idea of crawling the entire web on a regular basis becomes less and less feasible, so the need to include information on specific domain, domain-specific search engines was proposed. As more information becomes available on the World Wide Web, it becomes more difficult to provide effective search tools for information access. Today, people access web information through two main kinds of search interfaces: Browsers (clicking and following hyperlinks) and Query Engines (queries in the form of a set of keywords showing the topic of interest) [2]. Better support is needed for expressing one's information need and returning high quality search results by web search tools. There appears to be a need for systems that do reasoning under uncertainty and are flexible enough to recover from the contradictions, inconsistencies, and irregularities that such reasoning involves. In a multi-view problem, the features of the domain can be partitioned into disjoint subsets (views) that are sufficient to learn the target concept. Semi-supervised, multi-view algorithms, which reduce the amount of labeled data required for learning, rely on the assumptions that the views are compatible and uncorrelated. This paper describes the use of semi-structured machine learning approach with Active learning for the “Domain Specific Search Engines". A domain-specific search engine is “An information access system that allows access to all the information on the web that is relevant to a particular domain. The proposed work shows that with the help of this approach relevant data can be extracted with the minimum queries fired by the user. It requires small number of labeled data and pool of unlabelled data on which the learning algorithm is applied to extract the required data.

Keywords: Search engines; machine learning, Informationretrieval, Active logic.

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Authors: Ratanaporn Leesing, Ratanaporn Baojungharn

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Microbial oil was produced by soil isolated oleaginous yeast YU5/2 in flask-batch fermentation. The yeast was identified by molecular genetics technique based on sequence analysis of the variable D1/D2 domain of the large subunit (26S) ribosomal DNA and it was identified as Torulaspora globosa. T. globosa YU5/2 supported maximum values of 0.520 g/L/d, 0.472 g lipid/g cells, 4.16 g/L, and 0.156 g/L/d for volumetric lipid production rate, and specific yield of lipid, lipid concentration, and specific rate of lipid production respectively, when culture was performed in nitrogen-limiting medium supplemented with 80g/L glucose. Among the carbon sources tested, maximum cell yield coefficient (YX/S, g/L), maximum specific yield of lipid (YP/X, g lipid/g cells) and volumetric lipid production rate (QP, g/L/d) were found of 0.728, 0.237, and 0.619, respectively, using sweet potato tubers hydrolysates as carbon source.

Keywords: Microbial oil, oleaginous yeast, Torulasporaglobosa YU5/2, sweet potato tubers, kinetic parameters.

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Authors: Negar Khezri, Golnaz Yaghoubnezhadzanganeh, Amirreza Attarzadeh

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Type 2 Diabetes (T2DM) and Alzheimer's disease (AD) are two main health problems influencing millions of people in the world. Neuron loss and synaptic impairment that interfere with cognition and memory cause for the behavioral indications of AD. While it is now accepted that insulin has central neuromodulatory purpose, it was contemplated for many years that brain is insusceptible to insulin, involving its function in memory and learning, which are impaired in AD. The common characteristics of both AD and T2D are impaired insulin signaling, oxidative stress, the excitation of inflammatory pathways and unqualified glucose metabolism. This review summarizes how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches. Here we summarize how the recognition of these mechanisms may lead to the development of alternative therapeutic approaches.

Keywords: Alzheimer’s disease, diabetes, insulin resistance, neurodegenerative.

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Authors: W. Astiata, N. Elmesrati, N. Elmesrati, A. Abo Reyana

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The aim of this study is to survey the incidence, prevalence, types and associated impairments of CP in children at the Tripoli children hospital (T.C.H). The study covered all the cases the hospital had diagnosed in the period between (1.1.2009) and (31.12.2010), during which 38 cases of ages between 2 months to 3 years were diagnosed in the mentioned period. The incidence of CP was (17.42 per one thousand) out of (2143) of different neurological cases and came with a result of 23 cases of spastic CP which represented about (60.53%) out of the total number of cases, and the most associated impairment is convulsion. Medical information was collected from the patients’ files at the registration department from the neurology department. The data has been collected by a questionnaire, which had been set to finely organize the patient’s files.

Keywords: Physiotherapy, Rehabilitation, Libya, Cerebral Palsy, hospital, survey.

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Authors: Ashly Joseph, Jithu Paulose

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Large language models (LLMs) have revolutionized natural language processing capabilities, enabling applications such as chatbots, dialogue agents, image, and video generators. Nevertheless, their trainings on extensive datasets comprising personal information poses notable privacy and safety hazards. This study examines methods for addressing these challenges, specifically focusing on approaches to enhance the security of LLM outputs, safeguard user privacy, and adhere to data protection rules. We explore several methods including post-processing detection algorithms, content filtering, reinforcement learning from human and AI inputs, and the difficulties in maintaining a balance between model safety and performance. The study also emphasizes the dangers of unintentional data leakage, privacy issues related to user prompts, and the possibility of data breaches. We highlight the significance of corporate data governance rules and optimal methods for engaging with chatbots. In addition, we analyze the development of data protection frameworks, evaluate the adherence of LLMs to General Data Protection Regulation (GDPR), and examine privacy legislation in academic and business policies. We demonstrate the difficulties and remedies involved in preserving data privacy and security in the age of sophisticated artificial intelligence by employing case studies and real-life instances. This article seeks to educate stakeholders on practical strategies for improving the security and privacy of LLMs, while also assuring their responsible and ethical implementation.

Keywords: Data privacy, large language models, artificial intelligence, machine learning, cybersecurity, general data protection regulation, data safety.

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Authors: Bruno Škrinjarić

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Rapid technological developments and increase in organizations’ interdependence on international scale are changing the traditional workplace paradigm. A key feature of knowledge based economy is that employers are looking for individuals that possess both specific academic skills and knowledge, and also capability to be proactive and respond to problems creatively and autonomously. The focus of this paper is workers with Economics and Business background and its goals are threefold: (1) to explore wide range of competences and identify which are the most important to employers; (2) to investigate the existence and magnitude of gap between required and possessed level of a certain competency; and (3) to inquire how this gap is connected with performance of a company. A study was conducted on a representative sample of Croatian enterprises during the spring of 2016. Results show that generic, rather than specific, competences are more important to employers and the gap between the relative importance of certain competence and its current representation in existing workforce is greater for generic competences than for specific. Finally, results do not support the hypothesis that this gap is correlated with firms’ performance.

Keywords: Competency gap, competency matching, key competences, firm performance.

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Authors: Azlin S Azmi, Mus’ab Zainal, Sarina Sulaiman, Azura Amid, Zaki Zainudin

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Microalgae lipid is a promising feedstock for biodiesel production. The objective of this work was to study growth factors affecting marine mutant Synechococcus sp. (PCC 7002) for high lipid production. Four growth factors were investigated; nitrogen-phosporus-potassium (NPK) concentration, light intensity, temperature and NaNO₃ concentration on mutant strain growth and lipid production were studied. Design Expert v8.0 was used to design the experimental and analyze the data. The experimental design selected was Min-Run Res IV which consists of 12 runs and the response surfaces measured were specific growth rate and lipid concentration. The extraction of lipid was conducted by chloroform/methanol solvents system. Based on the study, mutant Synechococcus sp. PCC 7002 gave the highest specific growth rate of 0.0014 h^-1 at 0% NPK, 2500 lux, 40^oC and 0% NaNO₃. On the other hand, the highest lipid concentration was obtained at 0% NPK, 3500 lux, 30^oC and 1% NaNO₃.

Keywords: Cyanobacteria, lipid, mutant, marine Synechococcus sp. PCC 7002, specific growth rate.

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Authors: Azza Taha Zaki

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Technology-enhanced teaching has been in the limelight since the 90s when educators started investigating and experimenting with using computers in the classroom as a means of building 21^st. century skills and motivating students. The concept of technology-enhanced strategies in education is kaleidoscopic! It has meant different things to different educators. For the purpose of this paper, however, it will be used to refer to the diverse technology-based strategies used to support and enrich the flipped learning process, in the classroom and outside. The paper will investigate how technology is put in the service of teaching and learning to improve the students’ learning experience as manifested in students’ attendance and engagement, achievement rates and finally, students’ projects at the end of the semester. The results will be supported by a student survey about relevant specific aspects of their learning experience in the modules in the study.

Keywords: Attendance, British University, Egypt, flipped, student achievement, student-centred, student engagement, students’ projects.

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Authors: M. Omer, D. Wilson

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Creating a database scheme is essentially a manual process. From a requirement specification the information contained within has to be analyzed and reduced into a set of tables, attributes and relationships. This is a time consuming process that has to go through several stages before an acceptable database schema is achieved. The purpose of this paper is to implement a Natural Language Processing (NLP) based tool to produce a relational database from a requirement specification. The Stanford CoreNLP version 3.3.1 and the Java programming were used to implement the proposed model. The outcome of this study indicates that a first draft of a relational database schema can be extracted from a requirement specification by using NLP tools and techniques with minimum user intervention. Therefore this method is a step forward in finding a solution that requires little or no user intervention.

Keywords: Information Extraction, Natural Language Processing, Relation Extraction.

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Authors: Samal Abzhanova, Saule Mussabekova

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Today, a new system of education is being created in Kazakhstan in order to develop the system of education and to satisfy the world class standards. For this purpose, there have been established new requirements and responsibilities to the instructors. Students should not be limited with providing only theoretical knowledge. Also, they should be encouraged to be competitive, to think creatively and critically. Moreover, students should be able to implement these skills into practice. These issues could be resolved through the permanent improvement of teaching methods. Therefore, a specialist who teaches the languages should use up-to-date methods and introduce new technologies. The result of the investigation suggests that an interactive teaching method is one of the new technologies in this field. This paper aims to provide information about implementing new technologies in the process of teaching language. The paper will discuss about necessity of introducing innovative technologies and the techniques of organizing interactive lessons. At the same time, the structure of the interactive lesson, conditions, principles, discussions, small group works and role-playing games will be considered. Interactive methods are carried out with the help of several types of activities, such as working in a team (with two or more group of people), playing situational or role-playing games, working with different sources of information, discussions, presentations, creative works and learning through solving situational tasks and etc.

Keywords: Games, interactive learning, Kazakh language, teaching methods.

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Authors: Ewa Wywial, Shaneen M. Singh

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The PRAF family of proteins is a plant specific family of proteins with distinct domain architecture and various unique sequence/structure traits. We have carried out an extensive search of the Arabidopsis genome using an automated pipeline and manual methods to verify previously known and identify unknown instances of PRAF proteins, characterize their sequence and build 3D structures of their individual domains. Integrating the sequence, structure and whatever little known experimental details for each of these proteins and their domains, we present a comprehensive characterization of the different domains in these proteins and their variant properties.

Keywords: PRAF proteins, homology modeling, Arabidopsisthaliana

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Authors: Tlili-Guiassa Yamina

Abstract:

Many natural language expressions are ambiguous, and need to draw on other sources of information to be interpreted. Interpretation of the e word تعاون to be considered as a noun or a verb depends on the presence of contextual cues. To interpret words we need to be able to discriminate between different usages. This paper proposes a hybrid of based- rules and a machine learning method for tagging Arabic words. The particularity of Arabic word that may be composed of stem, plus affixes and clitics, a small number of rules dominate the performance (affixes include inflexional markers for tense, gender and number/ clitics include some prepositions, conjunctions and others). Tagging is closely related to the notion of word class used in syntax. This method is based firstly on rules (that considered the post-position, ending of a word, and patterns), and then the anomaly are corrected by adopting a memory-based learning method (MBL). The memory_based learning is an efficient method to integrate various sources of information, and handling exceptional data in natural language processing tasks. Secondly checking the exceptional cases of rules and more information is made available to the learner for treating those exceptional cases. To evaluate the proposed method a number of experiments has been run, and in order, to improve the importance of the various information in learning.

Keywords: Arabic language, Based-rules, exceptions, Memorybased learning, Tagging.

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Authors: Ahsan Bin Tufail, Ali Abidi, Adil Masood Siddiqui, Muhammad Shahzad Younis

Abstract:

An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.

Keywords: Biomedical image processing, classification algorithms, feature extraction, statistical learning.

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Authors: O. Onal, O. Turan

Abstract:

In this paper, some performance parameters of a selected turbofan engine (JT9D) are analyzed. The engine is a high bypass turbofan engine which powers a wide-body aircraft and it produces 206 kN thrust force (thrust/weight ratio is 5.4). The objective parameters for the engine include calculation of power, specific fuel consumption, specific thrust, engine propulsive, thermal and overall efficiencies according to the various definitions given in the literature. Furthermore, in the case study, wasted energy from the exhaust is calculated at the maximum power setting (i.e. take off phase) for the engine.

Keywords: Turbofan, power, efficiency, trust.

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