The paper describes the design of an intelligent tutoring system for teaching Introduction to Computer Science-a compulsory curriculum in Al-Azhar University of Gaza to students who attend the university. The basic idea of this system is a systematic introduction into computer science. The system presents topics with examples. The system is dynamically checks student's individual progress. An initial evaluation study was done to investigate the effect of using the intelligent tutoring system on the performance of students enrolled in computer science (...) curriculum at Al-Azhar University, Gaza. The results showed a positive impact on the evaluators. (shrink)

The study aimed to identify the knowledge management processes and their role in achieving competitive advantage at Al-Quds Open University. The study was based on the descriptive analytical method, and the study population consists of academic and administrative staff in each of the branches of Al-Quds Open University in (Tulkarm, Nablus and Jenin). The researchers selected a sample of the study population by the intentional non-probability method, the size of (70) employees. A questionnaire was prepared and supervised by a number (...) of specialists in order to obtain the results of the study. The study concluded that there is a positive direct relationship, that is, the higher the degree of application of knowledge management processes, the greater the degree of competitive advantage. Knowledge Technology came first with a score of 80.02% on all items. Competitive advantage came second with 81.74%. In the third place came "knowledge generation" where the total score on all paragraphs in this area (78.24%). In the fourth place, "knowledge transfer" (77.21%). "Developing and storing knowledge" came in fifth place (77.13%). "Acquisition of knowledge" came in sixth place (76.45%). Knowledge Organization ranked seventh (74.26%). The study recommended that the university should enable the employees to benefit from the experiences and expertise available to help generate knowledge. The University encourages the creation of knowledge through the system of incentives and open the way for creators to apply their creations and spread and invest in excellence and creativity. The university should design work performance levels based on the integration of knowledge and organize it according to policies that support freedom of research. The need for Palestinian universities to adopt a knowledge management approach. The need to adopt a system of incentives that rewards cognitive efforts, and give workers enough freedom to enable them to apply their knowledge. (shrink)

Al-Makhtoobah (The fiancé), a social-realistic drama that can be claimed as the first drama to make a mark in Indian Arabic literature published in 2009 by Syed Ehtisham Ahmad Nadvi, depicts generally a vivid picture of Indian Muslim society and some unwelcomed marital issues especially, in the form of dialogue. Al-Makhtoobah, is a tragedy in manners turning round the pertinacious attempts of a young girl to pass her life with her drunkard irresponsible husband. Before marriage, her rich parents were (...) in a promise to marry her with a meritorious madrassa student, while a fraudulent became successful to make their promise fail showing fallaciously superiority of a boy who becomes her husband later. Henceforth, the fraudulent occupies wealth of the girl and her father and finally this incident makes her father mysterious, mad and he dies. The writer Syed Ehtisham Ahmad Nadvi is a famous Indian Arabic literary critic, litterateur; an alumnus of Aligarh Muslim University, Jamia Millia Islamia and the great Islamic learning center namely Darul Uloom Nadwatul Ulama, Lucknow. He is also one of the shining figures in the history of Indian Arabic literature who wrote a good number of books and articles in Arabic as well as Urdu and retired as a professor of Arabic in the University of Calicut, Kerala in the year 2000 A.D. The present paper aims to study the themes of Al-Makhtoobah and styles that have followed the writer in making of the drama an artistic one. Further, it attempts to present writer’s academic, administrative and artistic excellence. (shrink)

BĪRŪNĪ, ABŪ RAYḤĀN MOḤAMMAD b. Aḥmad (362/973- after 442/1050), scholar and polymath of the period of the late Samanids and early Ghaznavids and one of the two greatest intellectual figures of his time in the eastern lands of the Muslim world, the other being Ebn Sīnā.

The weaponizing of scientific expertise to oppose regulation has been extensively studied. However, the relevant studies, belonging to the emerging discipline of agnotology, remain focused on the analysis of empirical corruption: of misinformation, doubt mongering, and other practices that cynically deploy expertise to render audiences ignorant of empirical facts. This paper explores the wrongful deployment of expertise beyond empirical corruption. To do so, I develop a broader framework of morally subversive expertise, building on recent work in political philosophy (Howard, 2016). (...) Expertise is subversive if it sets up its audience to fail morally, either intentionally or negligently. I distinguish three modes of subversive expertise: empirical subversion (the focus of agnotology), normative subversion and motivational subversion. Drawing on these distinctions, I offer a revisionary account of the Trump Administration’s regulatory science as a case study. I show that the Trump Administration’s use of expertise to dismantle climate regulation, contra the standard charge, cannot be explained using the resources of agnotology alone: the Administration produced highly reliable climate assessments, detailing the risks of climate change, candidly admitting the harms of its proposed policies, and still successfully deployed these findings to justify massive climate deregulation. The lesson of the analysis is that dismissing the expertise that underpins climate deregulation as empirically corrupt ‘anti-science’ both obscures its actual role in the politics of climate change and understates its wrongfulness: it misses the breadth of the assault on moral agency that sustains climate injustice. (shrink)

It is crucial to actively detect the risks of transactions in a financial company to improve customer experience and minimize financial loss. In this study, we compare different machine learning algorithms to effectively and efficiently predict the legitimacy of financial transactions. The algorithms used in this study were: MLP Repressor, Random Forest Classifier, Complement NB, MLP Classifier, Gaussian NB, Bernoulli NB, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Bagging Classifier, Decision Tree Classifier and Deep Learning. The dataset (...) was collected from Kaggle depository. It consists of 6362620 rows and 10 columns. The best classifier with unbalanced dataset was the Random Forest Classifier. The Accuracy 99.97%, precession 99.96%, Recall 99.97% and the F1-score 99.96%. However, the best classifier with balanced dataset was the Bagging Classifier. The Accuracy 99.96%, precession 99.95%, Recall 99.98% and the F1-score 99.96%. (shrink)

The setting of evidential standards is a core practice of scientific assessment for policy. Persuaded by considerations of inductive risk, philosophers generally agree that the justification of evidential standards must appeal to non-epistemic values but debate whether the balance of non-epistemic reasons favours varying evidential standards versus maintaining fixed high evidential standards in assessment, as both sets of standards promote different and important political virtues of advisory institutions. In this paper, I adjudicate the evidential standards debate by developing a novel (...) argument from justice, drawing on the IPCC’s assessment of climate impacts as a case study. I argue that in assessments marked by background evidential inequality, maintaining fixed high evidential standards results in an unequal distribution of ‘epistemic power’ among stakeholders, producing a ‘powerful assessment’ for the data-rich (a high rate of findings) and a ‘weak assessment’ for the data-poor (a low rate of findings). Where such inequalities of epistemic power disadvantage those in data-poor regions with respect to fundamental interests, such as basic human rights, we have decisive reasons of justice to vary evidential standards. (shrink)

الملخص قاعدة "الأصل" و "استصحاب الحال" قراءة في منهج النحاة من الاستعمال إلى التعليل إلى القاعدة ملخص تعدّ فكرة "الأصل" (=علة الأصل) منهجـًا اتّبعه النّحاة لتقديم تفسيرات منطقية في بعض مسائل الكلم في العربية، إذ أخذ النحاة إجراء منهج تحليليّ يعتمد افتراض أو استحضار مكوّن بنيوي على أنّه "أصل الاستعمال" غاية إيجاد مقاربات منطقية تربط الاستعمال المنجز بالقاعدة، فـ"الأصل"–وفق النحاة- إمّا "نمطٌ لغويٌّ مهجورٌ غير أنّه اُستعمل في طور من أطوار العربية"، أو "نمط لغوي افتراضي" يجريه النحاة على معيارية الاستعمال (...) بحيث يصحّ عدّه منجزًا لغويًا تقابليًّا لاستعمالات تجري والقاعدة؛ وقد أجرى سيبيويه منهج قياسٍ افتراضي وَفْقَ عبارته:"وهذا تمثيلٌ ولم يُتكلّم به" ليجعل "المكوّن" الافتراضي شاهدًا نحويًّا يمثّل "أصل الاستعمال" ويصحّ الرجوع إليه في اشتقاق القاعدة والوصول إلى التعليل. يدرس البحث علاقة الوظيفة التعليلية بين "الأصل" و"استصحاب الحال" أجْل الوقوف على منهج النحاة في إطلاق الأحكام القواعدية في المسائل التي اعتمدوا فيها فكرة التعليل بـ"الأصل"، وهل كانت أحكامهم في تلك المسائل مقنعة أو غير مقنعة؟ ويسعى البحث إلى بيان العلاقة بين فكرة "الأصل" و"أدلة النحو" (الأصول) من وجهة تسعى إلى بيان منطق التعليل بـ"علة الأصل". The original rule of the historical usage of the primary sentence and the semi-original rules of the grammatical thinking A reading in the grammarian's approach, from usage to the reasoning to the rules Abstract The original rule of the historical usage of the primary sentence is considered one of the methods that followed by the grammarians to provide a logical explanation sequence for some of the language issues. Most of the grammarians assume that there is a new sentence style that referred to an old usage in some of the sentence’s structure. According to the grammarians that these old structures are being the reference rules and evidences to explain the structure of the new structure style. Also based on the grammarian approach the old structure is divided into two parts: the first, sentence structure that have been actually used in the language history. The second is an imagination assumption where such kind of structures have not been used before and therefore can be considered as a hypothetical lingual style only, Sebaweeh has conducted a standard approach according to his phrase "This is a an example only, it has not been spoken". It is important to know that the grammarians have followed an analytical approach to make a center point between the original rule and the semi-original rule so as to provide a logical explanation of these structure styles. This research seeks to study the relation between the original rule and semi-original rules of the grammatical thinking. In addition, this search seeks to study the relation between the original rule and the Grammatical evidence (=OSOL) Key Words: The original rule - the semi-original rules -/- الكلمات المفتاحية أصول النحو، قاعدة الأصل، استصحاب الحال. (shrink)

Abstract: Background: In spite of the fact that computers continue to improve in speed and functions operation, they remain complex to use. Problems frequently happen, and it is hard to resolve or find solutions for them. This paper outlines the significance and feasibility of building a desktop PC problems diagnosis system. The system gathers problem symptoms from users’ desktops, rather than the user describes his/her problems to primary search engines. It automatically searches global databases of problem symptoms and solutions, and (...) also allows ordinary users to contribute exact problem reports in a structured manner. Objectives: The main goal of this Knowledge Based System is to get the suitable problem desktop PC symptoms and the correct way to solve the errors. Methods: In this paper the design of the proposed Knowledge Based System which was produced to help users of desktop PC in knowing many of the problems and error such as : Power supply problems, CPU errors, RAM dumping error, hard disk errors and bad sectors and suddenly restarting PC. The proposed Knowledge Based System presents an overview about desktop PC hardware errors are given, the cause of fault are outlined and the solution to the problems whenever possible is given out. CLIPS Knowledge Based System language was used for designing and implementing the proposed expert system. Results: The proposed PC desktop troubleshooting Knowledge Based System was evaluated by IT students and they were satisfied with its performance. (shrink)

ملخـــص -/- بشارات، أحمد محمد. التفسير الدلالي في إعراب المضارع-الجزم أنموذجًا. رسالة ماجستير في جامعة اليرموك. 2007م. (المشرف: أ.د. فيصل صفا). هدف البحث إلى إعطاء تفسيرات دلالية لظهور إعراب الجزم في تركيبات الجملة الفعلية، وحاول تعليل ارتباط الجزم بفكرة التعليق الشرطي، وتعليل عدم الجزم في بعض التركيبات الشرطية، وحاول أن يقدم تفسيرًا دلاليًا لاختلاف آخر المضارع، وتعليلاً لاختلاف آخر المضارع المنفي (لا/ لن/ لم/ يفعل) مختلف الصورة الإعرابية بالرفع مرة والنصب أخرى والجزم ثالثة. وسعى البحث في ظاهرة الجزم إلى الكشف (...) عن حالة الإعراب في المضارع أهي بالمشابهة للأسماء أم بالأصالة، والكشف عن فكرة الإعراب في المضارع أيقدم إعراب المضارع معنىً نحويًا أم أنه حالة من الإعراب تخرج عن فكرة النحاة القائلة بأن الإعراب فرع المعنى. وقد جاء البحث في مقدمة وتمهيد وبابين وخاتمة، عرضت في المقدمة أهمية البحث في ظاهرة الجزم، وذكرت الدراسات السابقة لهذا البحث، مبينًا أهم نتائجها، ووضحت في المقدمة خطة البحث ومنهجيته. أما الباب الأول فقد جاء في فصلين: الأول عنوانه" الجزم في الدرس النحوي القديم" عرضت فيه لمصطلح الجزم لغةً واصطلاحًا غاية ربط مفهوم المصطلح بفكرة الدلالة في الإنجاز اللغوي، وبحثت في مصطلحات الإعراب الأخرى لغةً واصطلاحًا، وعرضت لفكرة إعراب المضارع علةً ودلالةً، والفصل الثاني وعنوانه" علة إعراب المضارع ودلالته في الدرس النحوي الحديث" بحثت فيه علة تشكل علامة الإعراب أهي بالمعنى أو بالعامل؟ وعرضت فيه لفكرة المحدثين في بحثهم معنى الإعراب في المضارع. أما الباب الثاني، فقد جاء في فصلين: الأول عنوانه" التفسير الدلالي لظاهرة الجزم، وعرضت فيه علة اختلاف آخر المضارع محاولاً ربط الشكل الإعرابي بالدلالة النحوية، وعرضت فيه لمعاني الفعل(الإسناد والزمن والحدث) محاولا ربط علامة آخر المضارع بدلالة الإسناد فيه. والفصل الثاني عنوانه" معنى الجزم في السياقات اللغوية، عرضت فيه لمعنى الجزم في التركيبات اللغوية، وعرضت فيه لفكرة الجزم في صيغ الأمر معللاً حالة الاخر في صيغ الأمر على نحو يربطها بمسألة الإعراب. وقد خضعت الدراسة لمنهج تحليليّ. وخرج البحث ببعض النتائج، نذكر منها: - إن إطلاق المصطلحات الإعرابية يرجع إلى ملحظ صوتيّ حسب، فلا يتوافق معنى المصطلح الإعرابي مع واقع الإنجاز اللغوي. - المضارع معرب بالأصالة لا بالمشابهة؛ ذلك أن المضارع المنصوب والمجزوم لا يقع موقع الأسماء، والموقعية علة في إعراب الفعل. - معاني النحو هي المعاني الوظيفية للسياق، وقول النحاة إنّ المعاني النحوية هي الفاعلية والمفعولية والإضافة قول غير دقيق؛ لأن النعت والحال والوصف والإسناد وغيرها معانٍ نحوية تعتور على السياق. - يرتبط إعراب المضارع بفكرة الإسناد في الفعل، فالرفع للإسناد الواقع، والنصب للإسناد الغائي، والجزم يدل على عدم وقوع الإسناد. -/- الكلمات المفتاحية: الجزم، دلالة الجزم، إعراب الجزم، إعراب المضارع، الإسناد، التعليق الشرطي، الجزم والتعليق الشرطي، الأدوات الجازمة. دلالة الإعراب في المضارع. (shrink)

Interfaith dialogue is a vital tool for promoting understanding and cooperation between different religious communities. This article presents a comparative study of the Islamic and Buddhist perspectives on interfaith dialogue. Drawing on primary sources from both religions, this study explores the theological foundations of interfaith dialogue and the practical strategies employed by Muslims and Buddhists in promoting interfaith understanding. The similarities and differences between the two religions’ approaches to interfaith dialogue are analysed, examining how their respective beliefs, practices, and histories (...) shape their attitudes towards religious diversity. The research design is qualitative using library research by emphasizing content analysis on Islam and Buddhism scripture. The results show that Islamic paradigms of interreligious dialogue is da’wah (propagation, invitation or introducing Islam) that rooted from Tawḥīd, in contrast Buddhism, promotes on liberation from human suffering which rooted Bhavana and mindfulness. The study contributes to the principle of interfaith dialogue and provides insights into the potential of interfaith relation for sustaining harmony, peace, and mutual respect in diverse societies. Studies suggest the understanding of each fundamental to encourage Muslim and Buddhists scholars to produce comprehensive interreligious dialogue, theologically and philosophically. (shrink)

This paper offers preliminary notes on Buddhism in modern Muslim exegesis with an emphasis on Tafsir al-Qasimi by Muhammad Jamal al-Din al-Qasimi (1866–1914) and al-Mizan fi Tafsir al-Qurʾan by Muhammad Husayn Tabatabaʾi (1892-1981). The research adopts a qualitative design using content analysis to collect the data. In this paper two main questions regarding both exegetes will be explored. The first question concerns the sources of both scholars for their information about Buddhism by including the discussion in their exegesis. The second (...) question concerns the methodology they used to discuss Buddhism in the Qurʾan since this has not been done by any classical exegetes nor among the most modern exegetes. Studies have found that the approach of the two exegetes is different from both the classical and modern exegetes because their work also contains resources from the fields of comparative religion and the history of religion to make their work relevant in the current context and reliable to be referred to by any parties. The author concludes that both al-Qasimi and Tabatabaʾi used analysis (taḥlil) in discussing verses related to the position of the Buddha. (shrink)

Throughout this research, imposing the training of an Artificial Neural Network (ANN) to play tic-tac-toe bored game, by training the ANN to play the tic-tac-toe logic using the set of mathematical combination of the sequences that could be played by the system and using both the Gradient Descent Algorithm explicitly and the Elimination theory rules implicitly. And so on the system should be able to produce imunate amalgamations to solve every state within the game course to make better of results (...) of winnings or getting draw. (shrink)

We focus on a sui generis grounding move in Hindi-Urdu dialogue, namely 'voh hi na'. 'Voh' is third person pronoun and can function as a propositional anaphor in dialogue. 'Hi' and 'na' are two discourse particles in Hindi-Urdu. A dataset consisting of minimal pairs of dialogues is presented to get a better sense of the move. Using dynamic models of discourse structure, we propose a semantics for 'voh hi na' in terms of its update effects.

Automatic detection of diseases and anatomical landmarks in medical images by the use of computers is important and considered a challenging process that could help medical diagnosis and reduce the cost and time of investigational procedures and refine health care systems all over the world. Recently, gastrointestinal (GI) tract disease diagnosis through endoscopic image classification is an active research area in the biomedical field. Several GI tract disease classification methods based on image processing and machine learning techniques have been proposed (...) by diverse research groups in the recent past. However, yet effective and comprehensive deep ensemble neural network-based classification model with high accuracy classification results is not available in the literature. In this thesis, we review ways and mechanisms to use deep learning techniques to research on multi-disease computer-aided detection about gastrointestinal and identify these images. We re-trained five state-of-the-art neural network architectures, VGG16, ResNet, MobileNet, Inception-v3, and Xception on the Kvasir dataset to classify eight categories that include an anatomical landmark (pylorus, z-line, cecum), a diseased state (esophagitis, ulcerative colitis, polyps), or a medical procedure (dyed lifted polyps, dyed resection margins) in the Gastrointestinal Tract. Our models have showed results with a promising accuracy which is a remarkable performance with respect to the state-of-the-art approaches. The resulting accuracies achieved using VGG, ResNet, MobileNet, Inception-v3, and Xception were 98.3%, 92.3%, 97.6%, 90% and 98.2%, respectively. As it appears, the most accurate result has been achieved when retraining VGG16 and Xception neural networks with accuracy reache to 98% due to its high performance on training on ImageNet dataset and internal structure that support classification problems. (shrink)

Relationship-oriented questions have always been at the crossroads of ethnoreligious identity, religious freedom, religious conversion, religious prejudice, and religious pluralism throughout Muslim-Buddhist co-existence in the sixth century within the Malay Archipelago. Other faiths could be freely practised except for propagation towards Muslim communities with Islam being the religion of the federation. This study aimed to explore Muslim-Buddhist relation types and the issues underpinning the following themes: history, identity, and concerns. Content and thematic analysis as well discourse analysis were utilised as (...) the study method for data collection and evaluation. Resultantly, the Muslim-Buddhist interaction pattern in Malaysia has occurred (culturally and religiously) from the early establishment of both religious communities. This relation, which has shifted in ethnoreligious orientation at every interaction level, opens more avenues and complexities requiring holistic management. (shrink)

Since the emergence of the global challenges of COVID-19 pandemic, its impact could be widely viewed in various human society aspects, such as education, business trading and also social interaction limit. Apart from many discussions on the pandemic from a wide range of such perspectives, scholarly attention is still rarely mainly in trying to elaborate the critical overview from an Islamic perspective following theological, historical, and sociological points of view. In this paper, the critical elaboration of the pandemic has been (...) widely discussed by analysing the contents of sacred scriptures and responses from an Islamic point of view. The literature was critically conducted from religious sources such as the Qur’an and Hadith, and also related contemporary works. The finding reveals that the pandemic has been given full attention as stated in the Qur’an and narrated in Hadith by taking a lesson from pandemics and strategically battling the pandemic. The following attentions were addressed in order to strengthen the Muslim community and society in order to support the health protocols arranged by the local and international health organizations. The value is that religion’s clear comprehension could give continued support to encourage the Muslim community especially and general society at large in the attempts to battle the spreading pandemic. -/- . (shrink)

Artificial intelligence (AI), deep learning, machine learning and neural networks represent extremely exciting and powerful machine learning-based techniques used to solve many real-world problems. Artificial intelligence is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, recognition, problem-solving, learning, visual perception, decision-making and planning. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Deep learning (...) is a technique used to generate face detection and recognize it for real or fake by using profile images and determine the differences between them. In this study, we used deep learning techniques to generate models for Real and Fake face detection. The goal is determining a suitable way to detect real and fake faces. The model was designed and implemented, including both Dataset of images: Real and Fake faces detection through the use of Deep learning algorithms based on neural networks. We have trained dataset which consists of 9,000 images for total in 150 epochs, and got the ResNet50 model to be the best model of network architectures used with 100% training accuracy, 99.18% validation accuracy, training loss 0.0003, validation loss 0.0265, and testing accuracy 99%. (shrink)

To counter a general belief that all the paradoxes stem from a kind of circularity (or involve some self--reference, or use a diagonal argument) Stephen Yablo designed a paradox in 1993 that seemingly avoided self--reference. We turn Yablo's paradox, the most challenging paradox in the recent years, into a genuine mathematical theorem in Linear Temporal Logic (LTL). Indeed, Yablo's paradox comes in several varieties; and he showed in 2004 that there are other versions that are equally paradoxical. Formalizing these versions (...) of Yablo's paradox, we prove some theorems in LTL. This is the first time that Yablo's paradox(es) become new(ly discovered) theorems in mathematics and logic. (shrink)

This article (in a PowerPoint format) outlines some of the essential aspects of a Muslim's belief and practice.

In many areas, technology has facilitated many things, diagnosing diseases, regulating traffic and teaching students in schools rely on Intelligent systems to name a few. At present, traditional classroom-based education is no longer the most appropriate in schools. From here, the idea of intelligent e-learning for students to increase their culture and keep them updated in life began. E-learning has become an ideal solution, relying on artificial intelligence, which has a footprint in this through the development of systems based on (...) education without a teacher taking into account the individual differences of students. This study describes intelligent tutoring system for teaching the Data Manipulation Language (DML) Commands Using SQLite to non IT students to overcome the difficulties they face. The System was built as education system by using the researcher own authoring tool that based on mobile and web App. The basic idea of this system is a systematic introduction into the concept of Database and its DML query. The system presents the topic of DML Commands, help student to execute what they are learn from the system content using the practical part of the system and administers automatically adapted at run time to the student’s individual growth. The system was assessed by a group of teachers and students and the outcome showed as 91% from the database specialists, 94% from Diploma students group and 89% from the secondary school students group. (shrink)

The aim of this paper is to evaluate the critical success factors and investigate the benefits that might be gained once implementing Electronic Customer Relationship Management at HEI from employee perspective. The study conducted at Al Quds Open University in Palestine and data collected from (300) employee through a questionnaire which consist of four variables. A number of statistical tools were intended for hypotheses testing and data analysis, including Spearman correlation coefficient for Validity, reliability correlation using Cronbach’s alpha, and Frequency (...) and Descriptive analysis. The overall findings of the current study show that all the features were important for staff and it was critical success factors, at the same time, websites were providing all the features discussed by the theory whereas staff showed their willingness to use those features if provided. It is also discovered that implementing Electronic Customer Relationship Management can cause staff retention, were provided efficiently and needed to be improved. Research limitations: The survey findings were based on QOU employee in Palestine, UAE and KSA branches not included in the study. (shrink)

Abstract. Intelligent Tutoring System Builder (ITSB) is an authoring tool designed and developed to aid teachers in constructing intelligent tutoring systems in a multidisciplinary fields. The teacher is needed to create a set of pedagogical fundamentals, which, in line, are inured to automatically build up a broad tutor framework and construct an intelligent tutoring system. In this paper an explanation of the theory and the architecture of the tool is outlined. A presentation of several system components, the requirements of the (...) different components, integration of these components in ITSB tool are shown. Furthermore, implanting of requirements, cognitive principle, and common design fundamentals in the tool to ease the use of teachers. A variety of design matters, an example of building an intelligent tutoring system for teaching Java language using ITSB tool and an evaluation are presented. (shrink)

Background: The castor bean is a large grassy or semi-wooden shrub or small tree. Any part of the castor plant parts can suffering from a disease that weakens the ability to grow and eliminates its production. Therefore, in this paper will identify the pests and diseases present in castor culture and detect the symptoms in each disease. Also images is showing the symptom form in this disease. Objectives: The main objective of this expert system is to obtain appropriate diagnosis of (...) the disease. Methods: In this paper, the expert system is designed for the ability of agricultural engineers to detect and diagnose disease of castor like as: seeding blight, alternaria blight, cercospora leaf spot, powdery mildew and wilt. This system presents the disease symptoms, survival and spread, favorable conditions and image for each disease. Clips and Delphi expert system languages are used for designing and implementing the proposed expert system. Results: The expert system in the diagnosis of castor diseases was assessed by farmers and agricultural engineers and they were satisfied and accepted with its quality of performance. Conclusions: The expert system is easy for farmers and people have experience in the plant of castor to detect and diagnosis the symptoms that may face this plant from several disease. (shrink)

Infants and children are suffering from a lots of nausea and vomiting problems. Doctors, usually face various difficulties dealing with these problems because of their similarities. In this paper, we present an expert system to help users in getting the correct diagnosis of problems of nausea and vomiting in infants and children (Gastro-esophageal reflux, Gastroenteritis, Systemic Infection, Bowel obstruction, Tumors, A bleeding disease, tonsillitis, and Hepatitis pharynx). Furthermore, this expert system provide information about the disease and how to deal with (...) it. SL5 Object expert system language was used to design and implement this expert system. (shrink)

This paper presents a study into the Hindi-Urdu 'na' as a sentence-final particle. Although also used as a topic marker and negation, 'na' occurs sentence-finally across clause-types. In light of the data, we think the following hypothesis offers the best fit: 'na' signals the speaker’s belief that the content of na’s containing clause is a reasonable inference, given what’s common ground. Notably, in addition to other clause-types, we explore na's distribution in exclamations and exclamatives. We link our work to recent (...) research on the polar question particle 'kya' in Hindi-Urdu. (shrink)

In the last decade, online learning has grown rapidly. However, the outbreak of coronavirus (COVID-19) has caused learning institutions to embrace online learning due to the lockdown and campus closure. This paper presents an analysis of students’ feedback (n=354) from the Centre of Pre-University Studies (PPPU), Universiti Malaysia Sarawak (UNIMAS), Malaysia, during the transition to fully online learning. Three phases of online surveys were conducted to measure the learners’ acceptance of the migration and to identify related problems. The result shows (...) that there is an increased positivity among the students on the vie of teaching and learning in STEM during the pandemic. It is found that online learning would not be a hindrance, but blessing towards academic excellence in the face of calamity like the COVID-19 pandemic. The suggested future research direction will be of interest to educators, academics, and researchers’ community. (shrink)

Chest pain is the pain felt in the chest by infants, children and adolescents. In most cases the pain is not associated with the heart. It is mainly recognized by the observance or report of pain by the infant, child or adolescent by reports of distress by parents or care givers. Chest pain is not unusual in children. Lots of children are seen in ambulatory clinics, emergency rooms and hospitals and cardiology clinics. Usually there is a benign cause for the (...) pain for utmost children. Certain patients have conditions that are serious and perhaps life-threatening. Chest pain in pediatric patients needs careful physical examination and a detailed history that would point to the possibility of a serious cause. Researches of pediatric chest pain are scarce. It has been difficult to create evidence-based guidelines for evaluation. In this paper we propose an expert system to help doctors and parents, and care giver in diagnosing chest pain in infants and children. This expert System is design and implemented in SL5 Object language. (shrink)

Recent scoreboard models of conversation, in addition to modeling update effects of assertions and questions, also make sense of how one may react to such discourse moves. An account of acceptance and rejection is captured by Farkas & Bruce (2010), while Bledin & Rawlins (2020) have recently made sense of how one may resist an assertion too. For rejection and resistance of assertions, truth comes out to be a crucial notion. Between X and Y, if Y doesn't believe p to (...) be true, then Y might resist or reject X's assertion of p. For questions however, truth cannot serve this purpose. A complete model of discourse would seek to offer explanation of resisting questions. Much like Bledin & Rawlins, one can non-exhaustively enumerate a class of resistance moves. In many ways, one can resist a request to make a particular question QUD. In this paper, we raise following question: which notion can serve to explain question uptake in discourse? In our paper, we show how the expected utility value (EUV) of questions can serve this role for questions. EUV is used by van Rooij (2003) to give an account of interpretation of questions; we think it can serve our intended purposes too. To demonstrate plausibility, we build a workable formalism. (shrink)

Kidney stones pose a significant health concern, and early detection can lead to timely intervention and improved patient outcomes. This research endeavours to predict the presence of kidney stones based on urine analysis, utilizing a neural network model. A dataset of 552 urine specimens, comprising six essential physical characteristics (specific gravity, pH, osmolarity, conductivity, urea concentration, and calcium concentration), was collected and prepared. Our proposed neural network architecture, featuring three layers (input, hidden, output), was trained and validated, achieving an impressive (...) accuracy of 98.67% and an average error of 0.012. In addition to model performance, feature importance analysis was conducted to determine the most influential factors in predicting kidney stone presence. The findings underscore the significance of urea concentration, specific gravity, calcium concentration, conductivity, osmolarity, and pH as key indicators. This research contributes to the early diagnosis of kidney stones and demonstrates the potential of neural networks in medical diagnostics. The clinical implications of these findings are discussed, emphasizing the importance of timely intervention in managing kidney stone-related health issues. (shrink)

Malaria is a life-threatening disease spread to humans by some types of mosquitoes. It is mostly found in tropical countries. It is preventable and curable. The infection is caused by a parasite and does not spread from person to person. Symptoms can be mild or life-threatening. Mild symptoms are fever, chills and headache. Severe symptoms include fatigue, confusion, seizures, and difficulty breathing. Infants, children under 5 years, pregnant women, travelers and people with HIV or AIDS are at higher risk of (...) severe infection. Discovering this disease is a good step for proper and correct treatment. Determining the treatment with high accuracy depends on the method used in the diagnosis. Correctly, expert systems can greatly help to avoid spreading this disease. The expert system diagnoses malaria disease correctly to facilitate doctors to find the correct treatment based on the appropriate diagnosis. Objectives: An expert system has been established based on CLIPS to diagnose malaria disease. (shrink)

Recently, Intelligent Tutoring Systems (ITS) got much attention from researchers even though ITS educational technology began in the late 1960s and ITS is just embryonic from laboratories into the field. In this paper we outline an intelligent tutoring system for teaching basics of the databases system called (MDB). The MDB was built as education system by using the authoring tool (ITSB). MDB contains learning materials as a group of lessons for beginner level which include relational database system and lessons in (...) the process to install and set up a database. MDB system has exams for each level of the Lessons. An evaluation was done to see the effectiveness the MDB among learners and instructors. The outcome of the evaluation was promising. (shrink)

Publication date: 29 September 2016 Source: Author: Samy S. Abu Naser, Mazen J. Al Shobaki, Youssef M. Abu Amuna This paper aims to measure knowledge management maturity in higher education institutions to determine the impact of knowledge management on high performance. Also the study aims to compare knowledge management maturity between universities and intermediate colleges. This study was applied on five higher education institutions in Gaza strip, Palestine. Asian productivity organization model was applied to measure Knowledge Management Maturity. Second dimension (...) which assess high performance was developed by the authors. The controlled sample was. Several statistical tools were used for data analysis and hypotheses testing, including reliability correlation using Cronbach’s alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression. The overall findings of the current study shows that maturity level is in the second level. Findings also support the main hypothesis and it is sub- hypotheses. The most important factors effecting high performance are: Processes, knowledge management leadership, People, knowledge management Outcomes. Furthermore the current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first comparative study between universities and intermediate colleges in Gaza Strip that explores the status of knowledge management maturity using the Asian productivity Model. (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

We all know that problems of transportation and allocation appear frequently in practical life. We need to transfer materials from production centers to consumption centers to secure the areas’ need for the transported material or allocate machines or people to do a specific job at the lowest cost, or in the shortest time. We know that the cost factors Time is one of the most important factors that decision-makers care about because it plays an “important” role in many of the (...) practical and scientific issues that we face in our daily lives, and we need careful study to enable us to avoid losses. For this, the linear programming method was used, which is one of the research methods. Processes, where the problem data is converted into a linear mathematical model for which the optimal solution achieves the desired goal. Since these models are linear models, we can solve them using the direct simplex method and its modifications, but the specificity that these models enjoy has enabled scholars and researchers to find special methods that help us in obtaining the optimal solution. Whatever the method used, the goal is to determine the number of units transferred from any material from production centers to consumption centers, or to allocate a machine or person to do a job so that the cost or time is as short as possible. These issues were addressed according to classical logic, but the ideal solution was a specific value appropriate to the conditions in which the data was collected and does not take into account the changes that may occur in the work environment. In order to obtain results that are more accurate and enjoy a margin of freedom, we present in this book a study of transport issues and neutrosophic allocation issues and some methods for solving them. By neutrosophic issues we mean These are the problems in which the data are neutrosophic values, i.e. the required quantities and the available quantities. (shrink)

We propose a framework that makes space for both non-indexical contextualism and assessment-sensitivity. Such pluralism is motivated by considering possible variance in judgments about retraction. We conclude that the proposed pluralism, instead of problematizing, vindicates defining truth of a proposition w.r.t. a context of utterance and a context of assessment. To implement this formally, we formalize initialization of parameters by contexts. Then, a given parameter, depending on a speaker's judgment, can get initialized by either the context of utterance or the (...) context of assessment. An upshot of the proposal is that one need not exclusively espouse one of non-indexical contextualism or assessment-sensitivity about a particular class of expressions, for instance predicates of personal taste, in language; one can be pluralist in this sense. (This manuscript is part of an ongoing research project). (shrink)

Abstract Alzheimer's disease has spread insanely throughout the world. Early detection and intervention are essential to improve the chances of a positive outcome. This study presents a new method to predict a person's likelihood of developing Alzheimer's using a neural network model. The dataset includes 373 samples with 10 features, such as Group,M/F,Age,EDUC, SES,MMSE,CDR ,eTIV,nWBV,Oldpeak,ASF.. A four-layer neural network model (1 input, 2 hidden, 1 output) was trained on the dataset and achieved an accuracy of 98.10% and an average error (...) of 0.01. This study provides a valuable tool for early detection and intervention of Alzheimer's, thus contributing to the field of health and medicine. (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

Life expectancy prediction, a pivotal facet of public health and policy formulation, has witnessed remarkable advancements owing to the integration of neural network models and comprehensive datasets. In this research, we present an innovative approach to forecasting life expectancy in diverse countries. Leveraging a neural network architecture, our model was trained on a dataset comprising 22 distinct features, acquired from Kaggle, and encompassing key health indicators, socioeconomic metrics, and cultural attributes. The model demonstrated exceptional predictive accuracy, attaining an impressive 99.27% (...) and an average error of 0.0034, underscoring the potency of deep learning in tackling complex, real-world challenges. Furthermore, our study delved into feature importance analysis, identifying critical determinants such as HIV/AIDS prevalence, income composition of resources, and socioeconomic status that significantly influence life expectancy. These findings provide actionable insights for healthcare policymakers and practitioners, emphasizing the importance of addressing health disparities, promoting economic development, and implementing targeted interventions. This research bridges the gap between data-driven methodologies and global health, offering a robust predictive tool and enriching our understanding of the multifaceted dynamics that shape life expectancy across nations. (shrink)

This paper aims to assess knowledge management maturity at HEI to determine the most effecting variables on knowledge management that enhance the total performance of the organization. This study was applied on Al-Azhar University in Gaza strip, Palestine. This paper depends on Asian productivity organization model that used to assess KM maturity. Second dimension assess high performance was developed by the authors. The controlled sample was (364). Several statistical tools were used for data analysis and hypotheses testing, including reliability Correlation (...) using Cronbach’s alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression. The overall findings of the current study suggest that KMM is suitable for measuring and lead to enhance high performance. KMM assessment shows that the university maturity level is in level three. Findings also support the main hypothesis and it is subhypotheses. The most important factors effecting high performance are: Processes, KM leadership, People, KM Outcomes, Knowledge Process. Furthermore the current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first study at HEI in Palestine explores the status of KMM using the Asian productivity model. (shrink)

Modern technology plays an important role in our daily lives. Many people use technology for their works, interactions, and special interests such as art. Art as a discipline, which expresses human emotion and creative side, takes a new form for its contextualization with the help of information technology. A neologism for this discipline is “digital art.” Some experts who employ a traditional value in their aesthetical perspective consider this new approach unlikely. Walter Benjamin, an eminent figure from this group, stated (...) that art must have an aura in its production as is the case in paintings. With this aura, the work of art and not artwork has uniqueness of value. However, the problem arises when information technology becomes a predominant tool for the work of art. Digital art does not consider the aura as the core value in defining something as a work of art. Furthermore, digital artists think that art can exist within a digital object and maintain its uniqueness. Parallel with the latter, this article will describe the dispute and make a clear statement that a work of art in the digital age does not require aura. (shrink)

Background: Dengue Disease is a mosquito-borne tropical disease caused by the dengue virus, symptoms typically begin three to fourteen days after infection. This may include a high fever, headache, vomiting, muscle and joint pains, and a characteristic skin rash. Dengue serology is applied in different settings, such as for surveillance, in health care facilities in endemic areas and in travel clinics in non-endemic areas. The applicability and quality of serological tests in dengue endemic regions has to be judged against a (...) background of potential cross reactivity with other flavi-viruses, difficulties in distinguishing primary from secondary infections and technological problems related to the fact that most dengue endemic regions are relatively poor of resources .Objectives: to help doctors and patients in diagnosing Dengue Disease and give them the information of how to prevent Dengue Disease and to be able to understand the signs and symptoms of Dengue Disease. Methods: We collected all relevant material for Dengue Disease. Then we designed and implemented a knowledge based system for diagnosing Dengue Disease using SL5 Object Language. Results: The knowledge based system was evaluated by a group of Patients and specialized doctors and they found it very friendly and easy to use. (shrink)

In computer science, Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Deep Learning is a new field of research. One of the branches of Artificial Intelligence Science deals with the creation of theories and algorithms that (...) allow the machine to learn by simulating neurons in the human body. Most in-depth learning research focuses on finding high-level methods. The strippers analyze a large data set using linear and nonlinear transformations. The method of deep learning is used in the detection of several diseases including blood cell diseases and their classification using the radiography of blood cells to help decision makers to know the type of blood cell and its associated diseases and the results will be presented in detail and discussed. This thesis is using python language and deep learning to detect blood cell diseases and their classifications. The proposed deep learning model was trained, validated and the tested. The accuracy of proposed model was 98.00%. (shrink)

Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural networks to (...) predict whether a person is diabetic or not. The criterion was to minimize the error function in neural network training using a neural network model. After training the ANN model, the average error function of the neural network was equal to 0.01 and the accuracy of the prediction of whether a person is diabetics or not was 87.3%. (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and react like humans. Some of the activities computers with artificial intelligence are designed for include, Speech, recognition, Learning, Planning and Problem solving. Deep learning is a collection of algorithms used in machine learning, It is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is a technique used (...) to produce Pneumonia detection and classification models using x-ray imaging for rapid and easy detection and identification of pneumonia. In this thesis, we review ways and mechanisms to use deep learning techniques to produce a model for Pneumonia detection. The goal is find a good and effective way to detect pneumonia based on X-rays to help the chest doctor in decision-making easily and accuracy and speed. The model will be designed and implemented, including both Dataset of image and Pneumonia detection through the use of Deep learning algorithms based on neural networks. The test and evaluation will be applied to a range of chest x-ray images and the results will be presented in detail and discussed. This thesis uses deep learning to detect pneumonia and its classification. (shrink)

There is an increase in the use of in-door wireless networking solutions via Wi-Fi and this increase infiltrated and utilized Wi-Fi enable devices, as well as smart mobiles, games consoles, security systems, tablet PCs and smart TVs. Thus the demand on Wi-Fi connections increased rapidly. Rule Based System is an essential method in helping using the human expertise in many challenging fields. In this paper, a Rule Based System was designed and developed for diagnosing the wireless connection problems and attain (...) a precise decision about the cause of the problem. SL5 Object expert system language was used in developing the rule based system. An Evaluation of the rule based system was carried out to test its accuracy and the results were promising. (shrink)

Abstract: Sign language recognition is one of the most rapidly expanding fields of study today. Many new technologies have been developed in recent years in the fields of artificial intelligence the sign language-based communication is valuable to not only deaf and dumb community, but also beneficial for individuals suffering from Autism, downs Syndrome, Apraxia of Speech for correspondence. The biggest problem faced by people with hearing disabilities is the people's lack of understanding of their requirements. In this paper we try (...) to fill this gap. By trying to translate sign language using artificial intelligence algorithms, we focused in this paper using transfer learning technique based on deep learning by utilizing a MobileNet algorithm and compared it with the previous paper results[10a], where we get in the Mobilenet algorithm on the degree of Accuracy 93,48% but the VGG16 the accuracy was 100% For the same number of images (43500 in the dataset in size 64*64 pixel ) and the same data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch . (shrink)

Abstract: This research paper presents a novel approach to predict audit risks using a neural network model. The dataset used for this study was obtained from Kaggle and comprises 774 samples with 18 features, including Sector_score, PARA_A, SCORE_A, PARA_B, SCORE_B, TOTAL, numbers, marks, Money_Value, District, Loss, Loss_SCORE, History, History_score, score, and Risk. The proposed neural network architecture consists of three layers, including one input layer, one hidden layer, and one output layer. The neural network model was trained and validated, achieving (...) an impressive accuracy of 100% and an average error of 0.000015, indicating its robust predictive capability. Moreover, we conducted feature importance analysis to identify the most influential features for predicting audit risk. The key features found to be critical for classifying fraudulent activities in audit risk prediction are Sector_score, PARA_A, SCORE_A, PARA_B, SCORE_B, TOTAL, numbers, marks, Money_Value, District, Loss, Loss_SCORE, History, and History_score. This research contributes to the field of audit risk prediction by demonstrating the effectiveness of a neural network-based approach and highlighting the importance of specific features in detecting fraudulent activities. The findings have significant implications for auditors and organizations seeking to enhance their audit risk assessment processes, ultimately leading to improved financial transparency and fraud detection. (shrink)

As a type of evidence glass can be very useful contact trace material in a wide range of offences including burglaries and robberies, hit-and-run accidents, murders, assaults, ram-raids, criminal damage and thefts of and from motor vehicles. All of that offer the potential for glass fragments to be transferred from anything made of glass which breaks, to whoever or whatever was responsible. Variation in manufacture of glass allows considerable discrimination even with tiny fragments. In this study, we worked glass classification (...) and testing of artificial neural network model created by the JustNN. The aim of the study is help investigator in identifying the type of glass found in arena of the crime. The Neural Network model was trained and validated using the type of glass dataset. The accuracy of model in predicting the type of glass reached 96.7%. Thus neural network is suitable for predicating type of glasses. (shrink)