If business requires ethical solutions that are viable in the liminal landscape between concepts and corporate office, then business ethics and corporate social responsibility should offer tools that can survive the trek, that flourish in this well-traveled, but often unarticulated, environment. Indeed, feminist ethics produces, accesses, and engages such tools. However, work in BE and CSR consistently conflates feminist ethics and feminine ethics and care ethics. I offer clarification and invoke the analytic power of three feminist ethicists 'in action' whose (...) investigations into the "grey zones" of harms; identity and representational conventions; and "asymmetrical reciprocity" harmonize with business ethics' requirements. (shrink)

The study aimed to identify the effect of applying detection and prevention tools for career fraud in combating and preventing fraud and reducing its risks through an applied study on Palestinian Ministry of Health in Gaza Strip, Palestine. To achieve the objectives of the study, the researchers used the questionnaire as a main tool to collect data, and the descriptive and analytical approach to conducting the study. The study population consisted of (501) supervisory employees working at MOH in Gaza Strip, (...) Palestine. The researchers used the stratified random sample method and the multiple regression method to measure the effect. The study concluded a set of results, the most important of which is a positive evaluation among respondents about the levels of application of tools to detect and prevent job fraud within MOH, and the presence of a high interest in tools to prevent job fraud during the implementation of its various work. The study recommended the necessity for the Palestinian National Authority to develop and approve laws regulating health sector, so that those laws guarantee the prevention of conflicts of interest, especially for the category of doctors, by preventing job duplication of doctors working in the government sector. Also study recommended the need for MOH to adopt principles of health sector governance and begin immediately to implement them. This process to ensure transparency, disclosure and accountability in the business framework in a manner that realizes the effective protection of stakeholders and does not compromise or discriminate in the application of these principles, which ensures that all forms of job fraud are organized in an organized manner and within fixed legal frameworks. (shrink)

Although the issue of Imāmate was not initially seen as being one of the central subjects of Kalām, by the time it has gained importance especially after the Shīʿa started debating the matter in terms of credential aspects and as a result, it came to be covered as a specific chapter in Kalām books. The Muʿtazilite scholars on the other hand, did not lag from the relevant debates and included the matters that were related to Imāmate, in their works. Abū (...) l-Ḥusayn al-Baṣrī who was portrayed among one of the most influential figures of late Muʿtazila and was also recognized as the founder of Ḥusayniyya branch within the school, wrote extensively on the subject at stake. From among his works, Imāmate chapter of Sharḥ al-Uṣūl al-Khamsa has managed to survive. Abū l-Ḥusayn al-Baṣrī’s work is crucial not only because it included Imāmate discussions prior to him, but also it determined the directions in which the relevant debates took place since many refutations were written against it. Considering that Baṣrī’s work reflects the issues of his time in terms of both content and classification, it plays a significant role in the development of Islamic political thought and Imāmate discussions. Including the debates on Imāmate, this work extensively discusses the rational defenses of 10th century Shite Imāmate theory. The only extant copy of al-Baṣrī’s work is preserved at Glaser collection from VI/XIII. century under the heading number 114 at the Austrian National Library in Vienna. This study provides an examination regarding the authorship of Imāmate fragment of Sharḥ al-Uṣūl al-Khamsa, analyses the main characteristics of the manuscript, its contents and its approach to the Imāmate discussions; and finally provides the critical edition of al-Baṣrī’s mentioned work to the attention of researchers. (shrink)

Since the spread of Islam in Transoxiana (Mā-warāʾ al-Nahr), religious understandings based on the opinions of Abū Ḥanīfa (d. 150/767) have always been dominant in the region. Therefore, it was not possible for other understandings, which may seem to be opposite to Abū Ḥanīfa’s opinions, to be influential in the region. That Najjāriyya and Karrāmiyya could not be perennial in the region may be an example of this case. Similarly, Māturīdiyya, which benefited from Abū Ḥanīfa’s treatises of creed and his (...) rational method, could not adequately get the support of people at the time of Abū Manṣūr al-Māturīdī (d. 333/944) and Abū l-Muʿīn al-Nasafī (d. 508/1114) because the school was seen as an opposite approach to the prevailing imaginations about Abū Ḥanīfa. Moreover, the Ḥanafī jurists (Ḥanafī fuqahāʾ), who were influential in not only people but also bureaucracy, and the Ḥanafī theologians (Ḥanafī mutakallimūn), who followed al-Māturīdī’s theological method , did not come to terms on their interpretations of Abū Ḥanīfa. The Ḥanafī jurists who benefited mostly from juridical sources and manāqibworks were thinking different from the Ḥanafī theologians who relied on the treatises of Abū Ḥanīfa on such issues as the legitimacy of Kalām as a scholarly discipline, the responsibility of people of fatra(ahl al-fatra: people having no access to the message of Islam), and the creation of faith (īmān). The Ḥanafī jurists took different stance on various issues and argued that faith is not created; the informative (khabarī) attributes of God (ṣifāt Allāh) mentioned in the Qurʾān cannot be interpreted (taʾwīl); no one can be held accountable for faith only based on the intellect unless the message of the Prophet reaches to her or him; the people of fatracannot be responsible for faith. They also stated that Abū Ḥanīfa broke his relationship with the theological (kalāmī) issues in the last years of his life. Although these jurists accepted Abū Ḥanīfa’s distinction between faith and deeds and his view of the stability of one’s faith without increasing or decreasing they condemned theological discussions on these issues by going beyond the limits of the treatise of creed. While the Ḥanafī theologians known as the Ḥanafī scholars of Samarqand who adopted the religious views of Imām al-Māturīdī of Samarqand acknowledged the intellect and considered it as an independent source in religion, the Ḥanafī jurists known as the Ḥanafī scholars of Bukhārāauthorized the intellect only in understanding the transmission (naql) and its interpretation. The different opinions of the two groups can be seen clearly on the question of the religious responsibility of the people of fatra. When we look at the debates regarding Kalām and the Islamic law, we can see that the difference between these two cities (Samarqand and Bukhārā) stems from their methodological views on the epistemological values of the reason (ʿaql) and the transmission (tradition). Māturīdiyya is a school of theology established by the Ḥanafī theologians who upheld the necessity and significance of Kalām. It is possible to say that the Ḥanafī jurists did not contribute to the establishment and systematisation of this school; rather, they tried to prevent it. Our findings show that the Ḥanafī jurists who lived in Transoxiana differ from each other because of their different understandings of Abū Ḥanīfa. In the historical process extending today it is evident that the religious views of the Ḥanafī jurists and their interpretation of Abū Ḥanīfa have been prominent and effective, not that of Māturīdiyya, which is the understanding of the Ḥanafī theologians. (shrink)

Abū Ishāq al-Ṣaffār was one of scholars of the Western Qarakhānids’ period who followed the Kalām thought of al-Māturīdī (d. 333/944). His theological works Talkhīs al-adilla and Risāla fī al-kalām, his method in kalām, and frequent reference to his works by Ottoman and Arab scholars indicate that al-Ṣaffār is a respected and authorative Māturīdī theologian. The article focuses on his defense of the kalām. By adding a long introduction to Talkhīs about the naming, importance, and religious legitimacy of the science (...) of kalām, Saffār asserted that the kalām should be learned. When systematical vindication of the science of kalām is examined, it is understood that al-Ṣaffār is the first theologian who reserved a private and voluminous part for defensing the kalām among Ḥanafī-Māturīdīs. Even though he does not state its systematic, it can be understood that vindication of kalām in al-Ṣaffār divides into three parts as of explanation, demonstration and refutation. Al-Ṣaffār’s defending the science of kalām shows that there were opposite thoughts against kalām in the 4th/10th and 5th/11th centuries throughout in Transoxania. In this period Aṣḥāb al-Ḥadīth and Ikhwān al-Ṣafāʾ were the opposite fronts of kalām. In addition, he was trying to go beyond the oppositions of Ḥanafī jurists. His vindication is consistent and has scholarly depth because it is able to be against a strong opposition. -/- SUMMARY: Abū Ishāq Ibrahīm b. Ismāil Zāhid al-Ṣaffār al-Bukhārī is a scholar belonging to the Ḥanafī theological tradition which was improved by the contribution of Ḥanafī theologians who used thinking system of Abū Ḥanīfa (d. 150/767) as base and adopted Abū Manṣūr al-Māturīdī (d. 333/944) and his thoughts in historical process. The contents of his theological works Talkhīs al-adilla li-qawāʿid al-tawḥīd and Risāla fī al-Kalām, the method that he used, and references to his works made by Ottoman and Arab scholars indicate that he is an important Māturīdī theologian. The article focuses on his defense of the science of Kalām. -/- In Talkhīs al-adilla, there are two sections including the subject of naming, and importance and necessity of Kalām discipline. Here, the necessity of learning Kalām and its value are defended in detail. -/- Besides, rumors “Abū Ḥanīfa turned away from the science of Kalām in his doomsdays” and that “He prohibited to make occupation with Kalām completely” are evaluated. -/- When systematical vindication of the science of Kalām is examined, it is understood that al-Ṣaffār is the first theologian who reserved a private and voluminous part for defensing the Kalām among Ḥanafī Māturīdīs. Even if Abū Manṣūr al-Māturīdī, Abū al-Yusr al-Bazdawī (d. 493/1100) and Abū Muʿīn al-Nasafī (d. 508/1115) defend that the science of Kalām is not wrong for religion; yet, the vindication of Kalām does not take a place under a separate title and in a detailed manner in any of Māturīdī theologians works. -/- The method that al-Ṣaffār used when he is defending the science of Kalām, differs from strategy of Abū Ḥanīfa. While Abū Ḥanīfa has mentioned that there is a need for the science of Kalām under these new circumstances, al-Ṣaffār has defended theologians who were charged with being Ahl al-Bidaʿ, by trying to prove that the prophets especially the Prophet Ibrāhīm, even the Companions of the Prophet Muḥammad (Ṣaḥāba) and the Successors of the Companions (Tābiʿūn) scholars use their minds and make arguments in religious matters. In this respect, he emphasizes that the Qurʾān orders to think and discuss gently, not to be stay in silence: “And dispute with them, using what is best” (16.125-126). Therefore, he states that this discipline which took a mission to explain and defend the creed of Islam (ʿaqīda), cannot be characterized as an innovation (bidʿah) or illicit. -/- His vindication method can be defined as a more developed type of method that Abu’l-Ḥasan al-Ash’arī’s (d. 324/935) used in Risāla fī istiḥsān al-khawḍ fī ʿilm al-kalām. Even though he does not state its systematic, it can be understood that vindication of Kalām in al-Ṣaffār divides into three parts as of explanation, demonstration and refutation: -/- a) Explanation: Explaining the necessity and importance of the science of Kalām by giving information about its definition, names, value and place among other principles. -/- b) Demonstration: Revealing the religious basics of the science of Kalām from the Qurʾān, the Sunna of the Prophet Muḥammad, the Companions of the Prophet, and the Successors of the Companions thus specifying that it is legitimate for religion. -/- c) Refutation: Replying the claims having aim to weaken the value of Kalām principle and its religious legality. -/- Al-Ṣaffār describes ‘the science of Kalām’ as ‘Knowing the Real with the evidences which help to reach the absolute information’. By allocating the concept of 'Ḥaqq', he repeats the definition of Kalām as “it is to know God with certain evidences” in a part of his work, and “it is to know the principles of religion (uṣūl al-dīn) with certain evidences” in another part. He describes Kalām as “Knowing ḥaqq / God / uṣūl al-dīn by depending on evidence”, and tries to prove that it is wrong to consider a science which performs the stated duty, as illicit and abominable and thus turn away from it. -/- Al-Ṣaffār thinks that it is right to call this principle as ‘Kalām’ because of the certain evidences leading to the truth that this science has used. This thought was defended by other theologians as well. -/- For example, according to Saʿd al-Dīn Masʿūd al-Taftazānī (d. 792/1310) it seems like to say “This is the word (kalām), not the other knowings” by the way of the power of evidences used in Kalām.Thus, it is appropriate to give name Kalām for this science which based on certain evidences. -/- Al-Ṣaffār’s explanations revealed in scope of vindication of the Kalām are adopted by some of following scholars. Ḥusām al-Dīn al-Sighnāqī (d. 714/1314) in his book called al-Tasdīd sharḥ al-Tamhīd fī qawāʿid al-tawḥīd quotes Saffâr’s explanations as the same. -/- Al-Ṣaffār indicates that the method told in the Qurʾān is to reply questions about religion, beliefs and rejection instead of remaining in silence. The duty taken on by Kalām is this vindication activity performed by the prophets whose examples are described in the Qurʾān and which is legal and demanded. His way of thinking and vindication of the Kalām resembles that of Abū Manṣūr al-Māturīdī. Al-Māturīdī says, “Prophets and we were ordered to invite infidels to Islam. When this invitation happens, the respondents will ask for evidence and explanation, and discussion will be inevitable. Therefore, discussing and talking about subjects of Kalām is not objectionable”. -/- Thoughts of al-Māturīdī and al-Ṣaffār regarding the vindication of the Kalām were repeated by Nūr al-Dīn al-Ṣābūnī (d. 580/1184), and Fakhr al-Dīn al-Rāzī (d. 606/1210) later. According to al-Ṣābūnī, the evidences put against deniers and especially the discussion made by the Prophet Ibrāhīm to defend his own belief, prove the legality of Kalām discipline. Likewise, according to al-Rāzī, the duty of Kalām is just an activity performed already in the Qurʾān and ordered to the prophets. At this point of view, since the prophets were leading to Kalām, banning this activity is nonsense. -/- According to al-Ṣaffār, the reason for why Abu Hanifa avoids his son Hammād from these discussions is that Abu Hanifa does not like discussions based on obstinate. Otherwise, it cannot be that Abū Ḥanīfa prohibits to learn Kalām and make discussion about Kalām. According to him, this behavior of Abū Ḥanīfa results from that people discussing with him are ignorant about the subject of Kalām, discussion turns to an obstinate, and coming to an end of discussion seems impossible. This comment of al-Ṣaffār is quoted in Miftāḥ al-saʿāda wa-miṣbāḥ al-siyāda by ʿIṣām al-Dīn Aḥmed b. Muṣṭafā Tashköprüzāde (d. 968/1561) and in Minaḥ al-rawḍ al-azhar fī sharḥ al-Fiqh al-akbar by ʿAlī b. Sulṭān Muḥammad al-Qārī (d. 1014/1606) as same as his words. -/- Al-Ṣaffār’s defending the science of Kalām shows that there were opposite thoughts against Kalām in the 4th/10th and 5th/11th centuries throughout in Transoxania.In this period Aṣḥāb al-Ḥadīth and Ikhwān al-Ṣafāʾ were the opposite fronts of Kalām. In addition, he was trying to go beyond the oppositions of Ḥanafī jurists (fuqahāʾ). Because some of the Ḥanafī jurists thought that Abū Ḥanīfa forsook occupation with the science of Kalām and even he prohibited his son to have interest in this discipline. But some of Ḥanafī theologians such as al-Māturīdī, al-Nasafī and al-Ṣaffār protested this thought which describes Abū Ḥanīfa as a banner for Kalām. -/- His vindication is consistent and has scholarly depth because it is able to be against a strong opposition. -/- His book Talkhīs al-adilla li-qawāʿid al-tawḥīd is a unique source in terms of containing vindication of the Kalām in detail and also influencing the approaches of the next period scholars. (shrink)

Bu kitapta, Ebû İshâk es-Saffâr’ın (öl. 534/1139) kelâmî görüşleri, Telḫîṣü’l-edille li-ḳavâʿidi’t-tevḥîd adlı eserinde Allah’ın isimlerinin anlamlarını açıklarken yaptığı yorumlar çerçevesinde ele alınmaktadır. Ebû İshâk es-Saffâr, 6./12. yüzyıl Hanefî-Mâtürîdî âlimlerinden biridir. Kelâma dair Telḫîṣü’l-edille eserinde esmâ-i hüsnâ konusuna ayrıntılı olarak yer vermektedir. İki cilt hâlinde yayımlanan bu eserin yaklaşık üçte birlik bir kısmını esmâ-i hüsnâ konusu oluşturmaktadır. Bu kısım incelendiğinde, Saffâr’ın Allah’ın varlığı, birliği ve sıfatları ile ilgili konular başta olmak üzere pek çok konuyu 175 esmâ-i hüsnâya dayanarak izah ettiği görülmektedir. (...) O, esmâ-i hüsnâ bölümünde yer vermediği bazı isimlere ise müstakil başlıklar altında değinmektedir. Örneğin el-Mütekkelim ismi kelâm sıfatını bağlamında ve halku’l-Kur’ân ile icâz’ul-Kur’ân gibi konularla ilişkili bir şekilde ele almaktadır. Bu isimler de listeye dahil edildiğinde sayı 178’e ulaşmaktadır. Bu durumda eserin yarısını esmâ-i hüsnâ konusu teşkil etmektedir. -/- Saffâr, esmâ-i hüsnâ bölümünde alfabetik bir sıra içerisinde ele aldığı ilâhî isimleri öncelikle lugavî (semantik) yönden izah etmektedir. Sonrasında ise değerlendirdiği ilahî ismi, bir kelâm konusu ile bağlantı kurarak kelâmî perspektifle açıklamaktadır Esmâ-i hüsnâ temelinde ele alınan konuların hilâfet meselesi hariç diğer kelâm bahislerini kapsadığı görülmektedir. Saffâr öncesi Hanefî-Mâtürîdî kelâm literatürü içinde esmâ-i hüsnânın bu kadar kapsamlı ele alındığı başka bir eser bilinmemektedir. -/- Bu kitap; üç ana bölümden oluşmaktadır. “Metodolojik Çerçeve” başlıklı giriş bölümünde çalışmanın konusu, önemi, amacı, yöntemi ve kaynakları hakkında bilgi verilmiştir. Birinci bölümde Saffâr’ın yaşadığı sosyokültürel çevre olan Mâverâünnehir bölgesi ile Buhara ve Merv şehirlerinin siyasî, sosyal ve dinî durumu ortaya konulmaya çalışılmıştır. İkinci bölümde esmâ-i hüsna konusunun anlaşılmasına temel oluşturan isim, tesmiye, müsemmâ, sıfat ve vasf gibi kavramlar ile esmâ-i hüsnânın sayısı ve ihsâsı gibi kelâmî tartışmalara değinilmiştir. Sonrasında Saffâr öncesi dönemde kaleme alınan esmâ-i hüsnâ litaratürü hakkında bilgi verilmiştir. Bölüm sonuna Saffâr’ın rivayet ettiği 178 ilahî isme dair ayrıntılı bir tablo eklenmiştir. Üçüncü bölümde öncelikle, Saffâr’ın esmâ-i hüsnâyı izah ederken dikkate aldığı kelâmî ilkeler tespit edilmeye çalışılmıştır. Sonrasında ise Saffâr’ın Telḫîṣü’l-edille’de ilâhî isimleri açıklarken ortaya koyduğu kelâmî görüş ve değerlendirmeler belirlenerek sistematik bir şekilde kategorize edilmiştir. Bu kapsamda ele alınan her konunun sonuna ilgili ilâhî isimleri ve bağlantılı olduğu tartışmaları içeren tablolar eklenmiştir. Sonuç bölümünde ise Saffâr’ın esmâ-i hüsnâ anlayışına dayanan kelâm yöntemine dair ulaştığımız sonuçlara yer verilmiştir. Bu kitapta onun, esmâ-i hüsnânın %75’inde kelâmî yorumlarda bulunduğu ve bilgi-varlık bahsinden âhiret hayatına kadar bütün kelâm konularını esmâ-i hüsnâ ile bağlantılı yorumladığı tespit edilmiştir. Ulaşılan bu sonuçlar, Saffâr’ın kelâm anlayışının ilâhî isimlerin yorumuna dayandığını ortaya koymaktadır. [his book discusses the theological views of Abū Isḥāq al-Ṣaffār d. 534/1139), within the framework of his comments on the meanings of Allah’s names, provided in his work titled Talkhīṣ al-adilla. Abū Isḥāq al-Ṣaffār is one of the Ḥanafite-Māturīdite scholars in the 6th/12th century. In his work titled Talkhīṣ al-adilla li-qawāʿid al-tawḥīd on kalām, he spared extensive space for al-asmāʾ al-husnā. Approximately one third of this work, published in two volumes, is devoted to al-asmāʾ al-husnā. An examination of the related section reveals that al-Ṣaffār explains many issues, particularly those related to the existence, unity and attributes of Allah, based on 175 al-asmāʾ al-husnā. He mentions some of the names that he does not include in the al-asmāʾ al-husnā section under separate headings. For example, the name al-Mutakallim is addressed within the context of the attribute of kalām and in relation to subjects, such as the khalq al-Qurʾān and i‘jaz al-Qurʾān. Upon the addition of these names to the list, the number names reaches 178. This means that half of the work deals with the subject of al-asmāʾ al-husnā. -/- al-Ṣaffār lists the divine names in alphabetical order and explains them semantically in the chapter of al-asmāʾ al-husnā. Then he goes on to clarify each divine name through a theological lens with a specific reference to the subject of kalām. In the pre-Saffar Ḥanafite-Māturīdite theological literature, there is no other work that addresses al-asmāʾ al-husnā in such an extensive way. -/- This book consists of three main sections. The first section titled “Methodological Framework”, elaborates on the focus, significance, purpose and method of the study, along with the sources used. The first part describes the political, social and religious status of Transoxiana (Mā-warāʾ al-Nahr) region and the cities of Bukhara and Marw, the sociocultural environment in which Saffar lived. The second chapter addresses various concepts, which promote the understanding of al-asmāʾ al-husnā, such as name, tasmiya, musammā, attribute and qualification in addition to the theological debates such as the number and iḥṣāʾ of al-asmāʾ al-husnā. Then, it provides information about the al-asmāʾ al-husnā literature produced in the pre- Ṣaffār period. The end of each chapter comes with a detailed table with the 178 divine names mentioned by al-Ṣaffār. In the third chapter, the author initially discusses the theological principles that al-Ṣaffār considered while explaining the essence of al-asmāʾ al-husnā. This section also determines and systematically categorizes the theological views and evaluations put forward by al-Ṣaffār while explaining the divine names in Talkhīṣ al-adilla. The tables with the divine names and the related discussions can be seen at the end of the discussion for each subject. The last section presents the conclusions reached, regarding the kalām method based on al-Ṣaffār’s understanding of the essence of al-asmāʾ al-husnā. The present study revealed that he made theological interpretations in 75% of the al-asmāʾ al-husnā and interpreted all theological issues ranging from the subjects of knowledge and existence to the Afterlife in connection with the al-asmāʾ al-husnā. These results indicate that al-Ṣaffār's understanding of kalām is based on the interpretation of the divine names.]. (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)

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)

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)

This paper examines visual representation from a distinctive, interdisciplinary perspective that draws on ethics, visual studies and critical race theory. Suggests ways to clarify complex issues of representational ethics in marketing communications and marketing representations, suggesting an analysis that makes identity creation central to societal marketing concerns. Analyzes representations of the exotic Other in disparate marketing campaigns, drawing upon tourist promotions, advertisements, and mundane objects in material culture. Moreover, music is an important force in marketing communication: visual representations in music (...) promotions are also explored as data for inquiry. Offers an alternative to phenomenologically based approaches in marketing and consumer research scholarship that use consumer responses to generate data. Contributes additional insight into societal marketing and places global marketing processes within the intersection of ethics, aesthetics and representation. (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)

Families play an essential role in deceased organ procurement. As the person cannot directly communicate his or her wishes regarding donation, the family is often the only source of information regarding consent or refusal. We provide a systematic description and analysis of the different roles the family can play, and actions the family can take, in the organ procurement process across different jurisdictions and consent systems. First, families can inform or update healthcare professionals about a person’s donation wishes. Second, families (...) can authorize organ procurement in the absence of deceased’s preferences and the default is not to remove organs, and oppose donation where there is no evidence of preference but the default is to presume consent; in both cases, the decision could be based on their own wishes or what they think the deceased would have wanted. Finally, families can overrule the known wishes of the deceased, which can mean preventing donation, or permitting donation when the deceased refused it. We propose a schema of 4 levels on which to map these possible family roles: no role, witness, surrogate, and full decisional authority. We conclude by mapping different jurisdictions onto this schema to provide a more comprehensive understanding of the consent system for organ donation and some important nuances about the role of families. This classificatory model aims to account for the majority of the world’s consent systems. It provides conceptual and methodological guidance that can be useful to researchers, professionals, and policymakers involved in organ procurement. (shrink)

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)

This article draws in particular on existential-phenomenological notions of “witnessing.” Witnessing, often conceived in the context of testimony, obviously involves epistemological concerns, such as how we come to know through the experiences and reports of others. I shall argue, however, that witnessing as a mode of intersubjectivity offers understandings that involve questions about how people come to be. More specifically, I want to consider the positive potential of “witnessing” to disrupt intersubjective completeness or closure, particularly as this relates to work (...) on organizing subjectivities, as well as, in the field of organization studies. (shrink)

The context of international health research involving human subjects, and this should appear obvious, is the human community. As such, basic questions of how human beings should be treated by other human beings, particularly in situations of unequal power – e.g., in the form of control, choice, or opportunity – lay at the foundations of related ethical discourse when ethics are discussed at all. I trace a narrative that follows upon a recent revision process of international guidelines for biomedical research (...) involving human subjects. I focus in particular upon the issue of a standard of care. In the second section, I draw upon philosophers John Rawls, Claudia Card, and Allen Buchanan to discuss concerns regarding the 'least advantaged members of society' in the context of global inequality. The paper includes reflections upon pedagogy in courses focused upon international health research involving human subjects. (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)

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)

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)

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)

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)

When Mill published The Subjection of Women in 1869 he wanted to replace the domination of one sex by the other laws based on ‘a principle of perfect equality’. It is widely complained, however, that even advanced countries have still failed to achieve equality between the sexes. Power and wealth and influence are still overwhelmingly in the hands of men. But equalities of these kinds are not the ones required by the principle of equality that Mill had in mind; and, (...) furthermore, a principle that demanded them would actually be incompatible with Mill’s. The conclusion is not, however, that social policies dealing with men and women are all they should be. It is just that although the fundamental problems of feminism could be – and to a considerable extent still can be – expressed in terms of requirements for justice and equality, we have now reached a stage where concentrating on these ideas can distort the real problems, and may actually impede the kind of progress that is needed. (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)

Our reluctance to demystify grief is a sign of the distinctive obligation and discomfort that people feel towards those who have died. These feelings, however, are instructive about the nature of grief. As a vehicle of a living person’s relation to the dead, grief is mysterious—and we are rightly reluctant to take that mystery away. But grief is not to be avoided by philosophy on that account. I defend a less Romantic view of grief, in which a grieving person’s experience (...) of “normal” grief: 1) is felt to require an objectively recognized loss; 2) is felt to be dedicated to that lost object; 3) seems to most people to be something that she ought to feel; and 4) probably ought not to be medicalized, nor consequently medicated. This view of grief affords an understanding and appreciation of this rather special and important emotion without reducing its mystery. (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)

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)

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)

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)

Abstract: The Spotify Status Dataset is a valuable resource that provides real-time insights into the operational status and performance of Spotify, a popular music streaming platform. This dataset contains a wide array of information related to server uptime, user activity, service disruptions, and more, serving as a critical tool for both Spotify's internal monitoring and the broader data analysis community. As digital services like Spotify continue to play a central role in music consumption, understanding the platform's status becomes crucial for (...) ensuring a seamless user experience. This dataset offers numerous research and analysis opportunities, whether you're interested in exploring service availability trends or investigating user behavior patterns during service disruptions. This study highlights the significance of the Spotify Status Dataset, its potential applications, and the valuable insights it can offer to various stakeholders, from Spotify engineers working to enhance service reliability to researchers studying the effects of downtime on user engagement. It invites readers on a journey through this dataset to uncover the secrets of Spotify's operational status and its impact on music enthusiasts worldwide. (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)

Abstract: This research paper presents the development and evaluation of a neural network-based model for predicting fire alarms in smoke detection systems. Using a dataset from Kaggle containing 15 features and 3487 samples, we trained and validated a neural network with a three-layer architecture. The model achieved an accuracy of 100% and an average error of 0.0000003. Additionally, we identified the most influential features in predicting fire alarms.

Understanding science requires appreciating the values it presupposes and its social context. Both the values that scientists hold and their social context can affect scientific communication. Philosophers of science have recently begun studying scientific communication, especially as it relates to public policy. Some have proposed “guiding principles for communicating scientific findings” to promote trust and objectivity. This paper contributes to this line of research in a novel way using behavioural experimentation. We report results from three experiments testing judgments about the (...) trustworthiness, competence and objectivity of scientists. More specifically, we tested whether such judgments are affected by three factors: consulting or not consulting nonscientists, conducting research under a restrictive or non-restrictive governmental communication policy, and the source of a lab’s funding (i.e., government funding, private funding, or a combination of the two). We found that each of these factors affects ordinary judgments of trustworthiness, competence and objectivity. These findings support several recommendations that could help improve scientific communication and communication policies. (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)

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)

Abstract: In, this research embodies the spirit of interdisciplinary collaboration, bringing together data science, healthcare, and public health to address one of the most significant global health challenges in recent history. The achievements of this study underscore the potential of advanced machine learning techniques to enhance our understanding of the pandemic and guide effective decision-making. As we navigate the ongoing battle against COVID-19 and prepare for future health emergencies, the lessons learned from this research serve as a testament to the (...) power of data-driven insights and the unwavering commitment of the global scientific community in the face of adversity. (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: This study has effectively tackled the critical challenge of accurate calorie prediction in dishes by employing a robust neural network-based model. With an outstanding accuracy rate of 99.32% and a remarkably low average error of 0.009, our model has showcased its proficiency in delivering precise calorie estimations. This achievement equips individuals, healthcare practitioners, and the food industry with a powerful tool to promote healthier dietary choices and elevate awareness of nutrition. Furthermore, our in-depth feature importance analysis has shed light (...) on the indispensable role played by specific nutritional attributes in calorie estimation. This unveiling of crucial factors provides valuable insights for further research endeavors and practical applications. Notably, this research extends its impact beyond the immediate context by making substantial contributions to the domains of nutrition science and dietary planning. It underscores the transformative potential of artificial intelligence, demonstrating how it can revolutionize our approach to food, nutrition, and health. As the world grapples with the challenges of diet-related health issues and environmental concerns, the accuracy and precision achieved in calorie prediction through neural networks represent a significant stride towards more informed and conscientious dietary practices. In this era of data-driven decision-making, our research paves the way for healthier lifestyles, heightened nutritional awareness, and a more health-conscious society. (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)

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)

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)

Sign Language Recognition (SLR) aims to translate sign language into text or speech in order to improve communication between deaf-mute people and the general public. This task has a large social impact, but it is still difficult due to the complexity and wide range of hand actions. We present a novel 3D convolutional neural network (CNN) that extracts discriminative spatial-temporal features from photo datasets. This article is about classification of sign languages are not universal and are usually not mutually intelligible (...) although there are also similarities among different sign languages. They are the foundation of local Deaf cultures and have evolved into effective means of communication. Although signing is primarily used by the deaf and hard of hearing, hearing people also use it when they are unable to speak, when they have difficulty speaking due to a health condition or disability (augmentative and alternative communication), or when they have deaf family members, such as children of deaf adults. In this article we use the 43500 image in the dataset in size 64*64 pixel by use CNN Architecture and achieved 100% accuracy. (shrink)

Intelligent tutoring system (ITS) is a computer system which aims to provide immediate and customized or reactions to learners, usually without the intervention of human teacher's instructions. Secretariats professional to have the common goal of learning a meaningful and effective manner through the use of a variety of computing technologies enabled. There are many examples of professional Secretariats used in both formal education and in professional settings that have proven their capabilities. There is a close relationship between private lessons intelligent, (...) cognitive learning and design theories; and there are ongoing to improve the effectiveness of ITS research. And it aims to find a solution to the problem of over-reliance on students' teachers for quality education. The program aims to provide access to high-quality education to every student, and therefore the reform of the education system as a whole. In this paper, we will use Intelligent Tutoring System Builder (ITSB) to build an education system on cloud computing in terms of the concept of cloud computing and components and how to take advantage of cloud computing in the field. (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)

The research aims to identify the trends of Palestinian higher educational institutions in Gaza Strip as learning organizations from the perspective of senior management in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) employees from (...) the Palestinian universities was selected and the recovery rate was (69.2%). Statistical analysis (SPSS) program was used for analysis and processing the data. The study found the following results: There is an agreement about: the importance of the focus of "organizational structure" with an average approval, the importance of "technological infrastructure" axis with high approval, and the importance of "strategic" with an average approval. The results concluded that the study sample agree on the importance of "organizational dimension" highly. The results showed that the sample believe that the "strategic leadership" level in the universities got medium-approval. There is a fair level agreement about the axis of interest "teams / committees". There is an agreement about the importance of the "human dimension" moderately. The results showed that the sample is highly agreed about the importance of focus of the "knowledge management", and the focus of the "continuing education". They agreed weakly to somewhat about the importance of the focus of "scientific research", moderately agree about the importance of the center of "institutional culture", agree moderately on the importance of "cognitive dimension". The results showed that the sample largely agree on the importance of the focus of "strategic partnerships and alliances". They agree highly on the axis "keep up with the labor market" and on the focus of the importance of "technology incubators". The results showed that the sample moderately agree about the importance of the theme on "consulting and training", the importance of the focus of "social responsibility", and the focus of the "Community dimension". The study found a group of recommendations including: there is a need to provide suitable environment that achieve learning organizations. There is a need to develop the technological infrastructure (hardware, software, networks, databases, and human skills) because of the great advantages that they offer. The universities need to adopt knowledge management in the academic and administrative departments because knowledge is the core of the work of these departments. The establishment of technology incubators in universities to adopt outstanding university research projects, to protect, to supports, and to market them; furthermore, to develop the capabilities and skills of employees in the field of information technology. (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)

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)