Job motivation remains an area of concern among researchers due to the rising issues of poor or lack of motivation among workers. This refers to one’s personal will or drives to perform a task at work. Meanwhile, job satisfaction refers to an employee’s sense of fulfillment with his or her work experience. Therefore, the current study utilized the descriptive- correlational research design to investigate the impact of job motivation on the job satisfaction of accountants. To gather essential data and achieve (...) the objectives of the study, Multidimensional Work Motivational Scale (MWMS) and Minnesota Satisfaction Questionnaire (MSQ) were administered to the target respondents. The collected data were then analyzed using a Multiple Regression Analysis; findings revealed that job motivation has a significant impact on the job satisfaction of accountants. Additionally, the results of this study were carefully evaluated and discussed, and recommendations were made to benefit the stakeholders of the study and contribute to the existing body of knowledge. (shrink)

Throughout the 20th century, market capitalism was defended on parallel grounds. First, it promotes freedom by enabling individuals to exploit their own property and labor-power; second, it facilitates an efficient allocation and use of resources. Recently, however, both defenses have begun to unravel—as capitalism has moved into its “platform” phase. Today, the pursuit of allocative efficiency, bolstered by pervasive data surveillance, often undermines individual freedom rather than promoting it. And more fundamentally, the very idea that markets are necessary to achieve (...) allocative efficiency has come under strain. Even supposing, for argument’s sake, that the claim was true in the early 20th century when von Mises and Hayek pioneered it, advances in computing have rekindled the old “socialist calculation” debate. And this time around, markets—as information technology—are unlikely to have the upper hand. -/- All of this, we argue, raises an important set of governance questions regarding the political economy of the future. We focus on two: How much should our economic system prioritize freedom, and to what extent should it rely on markets? The arc of platform capitalism bends, increasingly, toward a system that neither prioritizes freedom nor relies on markets. And the dominant critical response, exemplified by Shoshana Zuboff’s work, has been to call for a restoration of market capitalism. Longer term, however, we believe it would be more productive to think about how “postmarket” economic arrangements might promote freedom—or better yet, autonomy—even more effectively than markets, and to determine the practical steps necessary to realize that possibility. (shrink)

Discussions about singular cognition, and its linguistic counterpart, are by no means exclusive to contemporary philosophy. In fact, a strikingly similar discussion, to which several medieval texts bear witness, took place in the late Middle Ages. The aim of this article is to partly reconstruct this medieval discussion, as it took place in Parisian question-commentaries on Aristotle’s De anima, so as to show the progression from the rejection of singular intellection in Siger of Brabant to the descriptivist positions of John (...) Duns Scotus and John of Jandun, and finally to the singularism of John Buridan. All these authors accept some kind of intellectual access to individuals. Therefore, the conundrum is not whether we have some kind of intellectual knowledge of individuals, but rather whether we can know them singularly. This article begins by presenting the crucial obstacle to singular intellection in Siger. Thereafter, the author shows that Jandun and Scotus depart in fundamental ways from Siger’s account, but that for them the intellection of individuals is of a general character. Finally, she proposes that Buridan is a genuine singularist. (shrink)

In this critical notice we review Bozickovic's recent attempt to settle two interrelated issues: (i) the issue of the cognitive significance of indexical thoughts expressed at a time in the face of difficulties posed by cases in which the subject either mistakes two objects for one or one for two different objects; (ii) that of the cognitive dynamics of temporal indexical thoughts in the face of difficulties posed by cases in which the belief seems to be retained while the proper (...) adjustments fail to be made (that is, in cases such as Rip Van Winkle's). We argue that, despite its elegance and merits, the proposal falls short of accounting for the problematic cases in their full complexity. For one thing, the intended non-modal construal of Frege's Criterion of Difference promoted by Bozickovic does not block, in our view, the "proliferation" of senses brought about by the occasion-sensitivity of the individuation of demonstrative thoughts. For another, the proposal fails to appreciate the need for the subject to have an adequate conception of the object of her thought when it comes to orienting herself in space and time. That being so, we conclude that neither (i) nor (ii) is settled. (shrink)

Starting from Brentano’s classical characterization of intentionality, we review the radical enactivist proposal about basic cognition and show that the underlying assumption that stripping teleosemantics of its representationalist commitments results in no explanatory loss is unwarranted. Significant features of basic cognition are lost, or so we argue, with the RECtification of teleosemantics that are retrieved by means of an alternative dubbed metaphysically non-committal content-ascriptivism.

LEITE (Fábio Rodrigo) – STOFFEL (Jean-François), Introduction (pp. 3-6). BARRA (Eduardo Salles de O.) – SANTOS (Ricardo Batista dos), Duhem’s analysis of Newtonian method and the logical priority of physics over metaphysics (pp. 7-19). BORDONI (Stefano), The French roots of Duhem’s early historiography and epistemology (pp. 20-35). CHIAPPIN (José R. N.) – LARANJEIRAS (Cássio Costa), Duhem’s critical analysis of mecha­ni­cism and his defense of a formal conception of theoretical phy­sics (pp. 36-53). GUEGUEN (Marie) – PSILLOS (Stathis), Anti-­scepticism and epistemic humility (...) in Pierre Duhem’s philosophy of science (pp. 54-72). LISTON (Michael), Duhem : images of science, historical continuity, and the first crisis in physics (pp. 73-84). MAIOCCHI (Roberto), Duhem in pre-war Italian philos­ophy : the reasons of an absence (pp. 85-92). HERNÁNDEZ MÁRQUEZ (Víctor Manuel), Was Pierre Duhem an «esprit de finesse» ? (pp. 93-107). NEEDHAM (Paul), Was Duhem justified in not distinguishing between physical and chemical atomism ? (pp. 108-111). OLGUIN (Roberto Estrada), «Bon sens» and «noûs» (pp. 112-126). OLIVEIRA (Amelia J.), Duhem’s legacy for the change in the historiography of science : An analysis based on Kuhn’s writings (pp. 127-139). PRÍNCIPE (João), Poincaré and Duhem : Resonances in their first epistemological reflec­tions (pp. 140-156). MONDRAGON (Damián Islas), Book review of «Pierre Duhem : entre física y metafísica» (pp. 157-159). STOFFEL (Jean-François), Book review of P. Duhem : «La théorie physique : son objet, sa structure» / edit. by S. Roux (pp. 160-162). STOFFEL (Jean-François), Book review of St. Bordoni : «When historiography met epistemology» (pp. 163-165). (shrink)

The book covers scientific and philosophical topics by bringing them closer to literature. Some topics are scientific explanation, the concept of cause, rational argumentation, pseudoscience, language, ethics, philosophy of mind, posthumanism, and democracy. Summary Prefazione di Severino Saccardi. Introduzione. Capitolo 1: Le scrivanie di Eddington. 1.1. Il vecchio Qfwfq (I. Calvino. Le cosmicomiche). 1.2. L’assassino invisibile (L.F. Celine, Il dottor Semmelweis). 1.3. Gli gnommeri di Ingravallo (C.E. Gadda, Quer pasticciaccio brutto de via Merulana). 1.4. I sergenti di Napoleone (L. Tolstoj, (...) Guerra e pace). 1.5. Tex e il Coyote nero (G. Bonelli, Il Coyote nero). 1.6. “Elementare Watson!” (A.C. Doyle, Il segno dei quattro). Capitolo 2. Non saranno mai delusi. 2.1. L’albero di Natale. (V. Perrin, Cambiare l’acqua ai fiori). 2.2. Il dagherrotipo di Buendia. (G.G. Marquez, Cent’anni di solitudine). 2.3. Don Ferrante e la peste. (A. Manzoni, I promessi sposi). Capitolo 3. Capitolo puffo. 3.1. L’Accademia di Lagado. (J. Swift, I viaggi di Gulliver). 3.2. Bruto è uomo d’onore. (W. Shakespeare, Giulio Cesare). 3.3. Le oche mute. (G. Orwell, 1984). Capitolo 4. “Quarantadue!” 4.1. Lo zio N’Ba N’Ga. (I. Calvino, Le cosmicomiche). 4.2. La mosca cocchiera. (J. de La Fontaine, Favole). 4.3. Il fiore del dr. Dek. (E. Salgari, Le meraviglie del Duemila). Capitolo 5. L’ultimo uomo. 5.1. La pernice accusatrice. (Cyrano de Bergerac, Gli stati e gli imperi del Sole). 5.2. Pallino in via Mjasnickaja. (M.A. Bulgakov, Cuore di cane). Capitolo 6. Scenari perturbanti. 6.1. Dissipatio. (G. Morselli, Dissipatio H.G.). 6.2. Un mammifero meccanizzato. (S. Butler, Erewhon). 6.3. Mlle Olimpia. (E.T.A. Hoffmann, Racconti notturni). Capitolo 7. La gente perbene. 7.1. La balena bianca. (H. Melville, Moby Dick). 7.2. Betsabea Everdeene. (T. Hardy, Via dalla pazza folla). 7.3. Un’idea francese. (C. McCarthy, Cavalli selvaggi). 7.4. Le montagne del Montana. (D. Delillo, Rumore bianco). (shrink)

The era of AI-based decision-making fast approaches, and anxiety is mounting about when, and why, we should keep “humans in the loop” (“HITL”). Thus far, commentary has focused primarily on two questions: whether, and when, keeping humans involved will improve the results of decision-making (making them safer or more accurate), and whether, and when, non-accuracy-related values—legitimacy, dignity, and so forth—are vindicated by the inclusion of humans in decision-making. Here, we take up a related but distinct question, which has eluded the (...) scholarship thus far: does it matter if humans appear to be in the loop of decision-making, independent from whether they actually are? In other words, what is stake in the disjunction between whether humans in fact have ultimate authority over decision-making versus whether humans merely seem, from the outside, to have such authority? Our argument proceeds in four parts. First, we build our formal model, enriching the HITL question to include not only whether humans are actually in the loop of decision-making, but also whether they appear to be so. Second, we describe situations in which the actuality and appearance of HITL align: those that seem to involve human judgment and actually do, and those that seem automated and actually are. Third, we explore instances of misalignment: situations in which systems that seem to involve human judgment actually do not, and situations in which systems that hold themselves out as automated actually rely on humans operating “behind the curtain.” Fourth, we examine the normative issues that result from HITL misalignment, arguing that it challenges individual decision-making about automated systems and complicates collective governance of automation. (shrink)

In this paper we show how a student can learn the basics of the system databases using (W3school CSS) which was built as intelligent tutoring educational system by using the authoring tool called (ITSB). The learning material contains CSS and HTML. We divided the material in a group of lessons for novice learner which combines relational system and lessons in the process of learning. The student can learn using example of CSS, and types of CSS color. Furthermore, the intelligent tutoring (...) system supports not only lessons; but exercises of different difficult levels for each lesson. When a student finish successfully the first difficulty level in a lesson, the student is allowed to move to the next difficulty level of the exercises of the lesson. (shrink)

Amidst the challenges that teachers are facing nowadays, teachers resiliency in this new tough learning environment seemed to be an unexplored area. Thus, it is crucial to conduct studies that would explore factors that increase teachers resiliency particularly amidst teachers work-related stress and emotional exhaustion. This study explores the moderating effect of social support to self- efficacy and stress management strategies toward teachers resiliency employing descriptive-correlational with moderation design. teachers resiliency. The respondents were one hundred one (101) public elementary school (...) teachers who are currently associated with the four (4) public elementary schools in San Francisco District for the school year 2022-2023 using online survey questionnaire as the main instrument in gathering the data. The findings revealed that both teachers self-efficacy and stress management strategies have a significant relationship in teachers resiliency. This suggests that teachers must also be persistent in strengthening their self-efficacy and developing their stress management strategies to sustain their resiliency. Results also showed that social support effectively moderates the relationship between self-efficacy and teachers resilience. At the same time, it indicated that the higher self-efficacy of teachers was associated with a lower level of social support. Likewise, social support effectively moderates the relationship between stress management strategies and teachers resilience. Results also indicated that the higher level of stress management strategies was associated with lower level of social support. Individuals in the workplace especially supervisors and co-workers must consider providing their colleagues especially those with lower level of self- efficacy and stress management strategies with the necessary social support that they need to be resilient. (shrink)

Medieval Integration Challenge for Intellection (MICI) in Albert the Great, Siger of Brabant, and Radulphus Brito.

La fuerza del movimiento español se debe bastante a su constitución como tecnopolítica. La capacidad demostrada de construir dispositivos que transitan entre la calle y la red torna el movimiento potente en ambos los espacios y tiene ayudado en la movilización de la sociedad española. Ese uso táctico de las nuevas tecnologías de comunicación y de la internet permiten que el #15M forme una especie de consciencia de red, o mejor, la subjetividad de red hace parte de la actuación dentro (...) de él. De cierta forma, la visualización del #25S en Twitter nos revela éso. A pesar de ser solo una parte de toda la red del movimiento, que es constituida también por blogs, sites, perfiles individuales y colectivos en el Facebook, etc., la configuración de esa red presenta un poco como es la actuación colectiva de los sujetos. La narrativa colaborativa construida por medio de hashtags es también un de los mecanismos del movimiento usado para aprovechar una parte de su inteligencia colectiva. (shrink)

How did the Franciscan friars translate Scotism to the New Spain? And Which controversies did it created? In this work we pretend to build the Scotistic Tradition in the New Spain by searching the bibliographical works used to teach and spread the ideas of John Duns Scotus since 1531 to 1780.

There is no doubt that custard apple diseases are among the important reasons that destroy the Custard Apple plant and its agricultural crops. This leads to obvious damage to these plants and they become inedible. Discovering these diseases is a good step to provide the appropriate and correct treatment. Determining the treatment with high accuracy depends on the method used to correctly diagnose the disease, expert systems can greatly help in avoiding damage to these plants. The expert system correctly diagnoses (...) Custard Apple disease to make it easier for farmers to find the right treatment based on the appropriate diagnosis. Objectives: A specialized syllable language system was established for the diagnosis of Custard Apple plant disease. (shrink)

Identification of factors that predict recurrent antisocial behavior is integral to the social sciences, criminal justice procedures, and the effective treatment of high-risk individuals. Here we show that error-related brain activity elicited during performance of an in- hibitory task prospectively predicted subsequent rearrest among adult offenders within 4 y of release (N =96). The odds that an offender with relatively low anterior cingulate activity would be rearrested were approximately double that of an offender with high activity in this region, holding (...) constant other observed risk factors. These results suggest a potential neurocognitive biomarker for persistent antisocial behavior. (shrink)

The study aimed to identify the relationship between correcting the deviations in the measurement of performance and achieving the objectives of control and the performance of the job at the Islamic University in the Gaza Strip. To achieve the objectives of the research, the researchers used the descriptive analytical approach to collect information. The questionnaire consisted of (20) statements distributed to three categories of employees of the Islamic University (senior management, faculty members, their assistants and members of the administrative board). (...) A random sample of 314 employees was selected and 276 responses were retrieved with a recovery rate of 88.1%. The Statistical Analysis Program (SPSS) was used to enter, process, and analyze the data. The results of the study showed a positive relationship between correcting deviations in performance measurement and achieving the control objectives represented by the functional performance in the Islamic University from the point of view of the members (senior management, faculty and their assistants, and the administrative board), where the relative weight of all the paragraphs was (74.25%). The study recommended the need to ensure that the actual performance of the planned performance is matched and decisions are taken to correct the serious deviations and take the necessary measures in terms of retraining and change in regulations, wages and bonuses and punishment of the culprit, neglect and negligence by mistake. (shrink)

The evolution of Intelligent Tutoring System (ITS) is the result of the amount of research in the field of education and artificial intelligence in recent years. English is the third most common languages in the world and also is the internationally dominant in the telecommunications, science and trade, aviation, entertainment, radio and diplomatic language as most of the areas of work now taught in English. Therefore, the demand for learning English has increased. In this paper, we describe the design of (...) an Intelligent Tutoring System for teaching English language grammar to help students learn English grammar easily and smoothly. The system provides all topics of English grammar and generates a series of questions automatically for each topic for the students to solve. The system adapts with all the individual differences of students and begins gradually with students from easier to harder level. The intelligent tutoring system was given to a group of students of all age groups to try it and to see the impact of the system on students. The results showed a good satisfaction of the students toward the system. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with 97.50 (...) % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

An Intelligent Tutoring System (ITS) is a computer system that offers an instant, adapted instruction and customized feedback to students without human teacher interference. Reciting "Tajweed" the Holy Quran in the appropriate way is very important for all Muslims and is obligatory in Islamic devotions such as prayers. In this paper, the researchers introduce an intelligent tutoring system for teaching Reciting "Tajweed". Our "Tajweed" tutoring system is limited to "Tafkhim and Tarqiq in TAJWEED" the Holy Quran, Rewaya: Hafs from ‘Aasem. (...) The system was evaluated by reciting teachers and students, and the results were auspicious. (shrink)

The truth of every human being is the end his life with death, and this leads to leaving assets and funds for those after him and can lead to hate between the heirs, it has made a point of Islamic law on all aspects of life, including the subject of the inheritance of the deceased. The main problem is how to get the knowledge of the basics of inheritance. This paper reviews work done in the use of expert system software (...) to calculate inheritance in Islam. A proposed expert system was designed and developed using CLIPS language to calculate the inheritance in Islam. (shrink)

: Natural Language Processing (NLP), a subset of Artificial Intelligence (AI), has emerged as a powerful tool in analyzing human language to detect underlying mental health issues such as depression and suicidal tendencies. By leveraging techniques in machine learning and deep learning, NLP systems can process and interpret textual data from diverse sources like social media, forums, and online journals to identify patterns and linguistic markers associated with mental health conditions. These markers include the use of emotionally charged words, changes (...) in writing style, expressions of hopelessness, isolation, or distress, which are critical indicators of a person's psychological state. The process typically involves data preprocessing, feature extraction using models such as TF-IDF or word embeddings (e.g., Word2Vec, GloVe), and classification using supervised learning techniques or deep learning models like BERT or LSTM. Understanding human emotions is a critical aspect of human-computer interaction, mental health diagnostics, and customer service applications. This project focuses on leveraging Natural Language Processing (NLP) techniques to analyze and interpret emotions expressed in textual data. By utilizing state-of-the-art machine learning models, including deep learning architectures such as recurrent neural networks (RNNs) and transformers, the project aims to develop models capable of detecting and classifying emotional states such as joy, sadness, anger, fear, and surprise from written content. The research investigates various aspects of emotion detection, including sentiment analysis, contextual understanding, and the role of linguistic features in emotion recognition. Additionally, it explores challenges like sarcasm, ambiguity, and cultural differences in emotional expression. The goal is to create an emotionaware system that can improve applications in fields such as automated customer support, mental health monitoring, and social media analysis, enabling more empathetic and responsive interactions between humans and machines. Through this work, we seek to enhance the understanding of emotions in textual communication, providing valuable insights into emotional dynamics and improving human-computer interactions. (shrink)

Lately in the past couple of years, there are an increasing in the normal rate of playing computer games or video games compared to the E-learning content that are introduced for the safety of our children, and the impact of the video game addictiveness that ranges from (Musculoskeletal issues, Vision problems and Obesity). Furthermore, this paper introduce an intelligent tutoring system for both parent and their children for enhancement the experience of gaming and tell us about the health problems and (...) how we can solve them, with an easy user interface that way can our children be happy and excited about the information and their health. (shrink)

Abstract: Tomatoes are part of the major crops in food security. Tomatoes are plants grown in temperate and hot regions of South American origin from Peru, and then spread to most countries of the world. Tomatoes contain a lot of vitamin C and mineral salts, and are recommended for people with constipation, diabetes and patients with heart and body diseases. Studies and scientific studies have proven the importance of eating tomato juice in reducing the activity of platelets in diabetics, which (...) helps in protecting them from developing deadly blood clots. A tomato classification approach is presented with a data set containing approximately 5,266 images with 7 species belonging to tomatoes. The Neural Network Algorithms (CNN), a deep learning technique applied widely in image recognition, is used for this task. (shrink)

Natural Language Processing (NLP), a subset of Artificial Intelligence (AI), has emerged as a powerful tool in analyzing human language to detect underlying mental health issues such as depression and suicidal tendencies. By leveraging techniques in machine learning and deep learning, NLP systems can process and interpret textual data from diverse sources like social media, forums, and online journals to identify patterns and linguistic markers associated with mental health conditions. These markers include the use of emotionally charged words, changes in (...) writing style, expressions of hopelessness, isolation, or distress, which are critical indicators of a person's psychological state. The process typically involves data preprocessing, feature extraction using models such as TF-IDF or word embeddings (e.g., Word2Vec, GloVe), and classification using supervised learning techniques or deep learning models like BERT or LSTM. The application of NLP for mental health detection is particularly impactful in healthcare and public safety. It enables early identification and intervention for at-risk individuals by providing clinicians and support organizations with actionable insights from large volumes of textual content. On social media platforms, it facilitates automated monitoring to detect crisis situations and initiate timely support. Additionally, in educational institutions and workplaces, such systems can promote mental well-being by identifying signs of distress and enabling appropriate counseling or outreach efforts. However, this field faces notable challenges, including data privacy concerns, ethical considerations, the risk of false positives or misdiagnosis, and ensuring the cultural and linguistic diversity of datasets to avoid bias. Ongoing research aims to improve model accuracy and interpretability while integrating multimodal data for more robust detection. The goal is to develop responsible and sensitive AI systems that assist in understanding and supporting mental health, ultimately contributing to a safer, more empathetic digital environment. (shrink)

Undeniably, the greatest way for a Moslem to be closer to Allah, is recitation of Holy-Quran approves with the method conveyed from Messenger of Allah Mohammed from the feature of speech points of letters and the intrinsic and fleeting characteristics of the letters, So, there is a persistent need to teach all Moslems the science of Tajweed Al-Quran. ITS (Intelligent Tutoring System) is computer software that supplies direct and tailored training or response to students without human teacher interfering. The main (...) target of ITS is smoothing the learning process using the wide-ranging facilities of computer. The proposed system will be implemented using the ITSB Authoring tool. In this thesis, the researcher presents an intelligent tutoring system for teaching Reciting Al-Quran "Tajweed" with Rewaya: Hafs from ‘Aasem by the way of Shatebiyyah. It was a novel idea that the researcher combined the science of Tajweed Al-Quran and the science of artificial intelligence in his thesis. The researcher arranged the material into chapters, lessons, examples then, added all these to the proposed system. He also added questions, right answers and the level of difficulty for each lesson. He prepared an exam for each chapter and a final exam to test the knowledge of the learner in the whole material. The system was evaluated by teachers and students in reciting science and the outcome of the assessment was encouraging and promising. (shrink)

Como parte del trabajo del taller interno permanente del Cuerpo Académico de Estética y Arte de la Benemérita Universidad Autónoma de Puebla, el 12 de noviembre de 2013 se realizó una Mesa Redonda sobre el tema “Universalidad e identidad cultural”. En esta Mesa participaron los doctores José Ramón Fabelo Corzo, José Antonio Pérez Diestre y Ramón Patiño Espino, como ponentes principales; además, se contó con la asistencia del doctor Jesús Márquez Carrillo, quien se integró al debate. Diferentes disciplinas —la filosofía, (...) la antropología, la historia del pensamiento y del arte, incluso la biología— pueden, cada una, ofrecer sus aportes al tan socorrido tema de la relación entre lo universal y lo propio en la cultura latinoamericana. El debate suscitado puso de manifiesto esa diversidad de aportaciones. En este trabajo presentamos las intervenciones realizadas por cada uno de los integrantes de la mesa, en el orden en que se produjeron. (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)

In fact, people get neck problems due to something such as sports or woke and Wrong sleep habits. In this paper an expert system was designed to help users to correctly diagnose neck problems world (muscle spasm, Muscle aches, Meningitis, herniated cervical disc, Fibromyalgia, Cervical spondylosis, Trigger points) with some information about the disease and self-care. Java language was used to design and implement this expert system.

Abstract: Lotteries have long been a source of fascination and intrigue, offering the tantalizing prospect of unexpected fortunes. In this research paper, we delve into the world of lottery predictions, employing cutting-edge AI techniques to unlock the secrets of lottery outcomes. Our dataset, obtained from Kaggle, comprises historical lottery draws, and our goal is to develop predictive models that can anticipate future winning numbers. This study explores the use of deep learning and time series analysis to achieve this elusive feat. (...) Through rigorous experimentation and data-driven approaches, we seek to determine the viability of AI in the realm of lottery predictions. Our findings reveal both the promise and limitations of AI in this context, shedding light on the complexities of lottery data and the potential need for quantum computing as a last resort. (shrink)

Abstract.This article examines an orientation for thinking theologically and ethically about the cultural pattern of technology and a vision for living responsibly within it. Building upon and joining select insights of philosophers Hans Jonas and Albert Borgmann, I recommend the analytic and evaluative leverage to be gained through development of an integrative biocultural theological anthropology.

Abstract: The sinking of the RMS Titanic in 1912 remains a poignant historical event that continues to captivate our collective imagination. In this research paper, we delve into the realm of data-driven analysis by applying Artificial Neural Networks (ANNs) to predict the chances of survival for passengers aboard the Titanic. Our study leverages a comprehensive dataset encompassing passenger information, demographics, and cabin class, providing a unique opportunity to explore the complex interplay of factors influencing survival outcomes. Our ANN-based predictive model (...) achieved an accuracy rate of 78%, shedding light on the underlying patterns within the data. However, this paper underscores the multifaceted nature of survival prediction and acknowledges several challenges. These include missing data imputation, feature engineering, and the inherent noise within historical datasets. We further discuss the importance of model evaluation metrics, showcasing not only accuracy but also precision, recall, and F1-score as essential indicators of predictive performance. The research paper meticulously outlines the architecture of the ANN model, emphasizing the key hyperparameters, activation functions, and regularization techniques employed in model development. Additionally, we address ethical considerations related to data handling and potential biases within the dataset. While our achieved accuracy is a notable achievement, this study emphasizes the importance of interpreting the results with due caution. It underscores the need for a holistic perspective that considers the practical implications of false positives and false negatives, especially in the context of a disaster scenario. In conclusion, this research contributes to our understanding of survival prediction in historical events like the Titanic disaster using modern machine learning techniques. It calls for further exploration and refinement of predictive models, with a focus on enhancing the interpretability and generalizability of such models to real-world applications. (shrink)

Abstract: This research focuses on utilizing Artificial Neural Networks (ANNs) to predict Audit Risk accurately, a critical aspect of ensuring financial system integrity and preventing fraud. Our dataset, gathered from Kaggle, comprises 18 diverse features, including financial and historical parameters, offering a comprehensive view of audit-related factors. These features encompass '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,' with a total of 774 samples. Our proposed neural network architecture, consisting of three (...) layers (1 input, 1 hidden, and 1 output), forms the core of this study. While it may seem simple, the power of ANNs lies not in complexity but in their ability to uncover intricate data patterns. The model underwent rigorous training and validation, resulting in remarkable outcomes—an accuracy of 100% and an average error rate of 0.000015. In addition to performance metrics, our research investigates feature importance, revealing the key contributors to Audit Risk prediction. Notably, 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' and 'History_score' emerged as the most influential factors, shedding light on the elements crucial for precise risk assessment. This study advances Audit Risk prediction models and highlights the potential of ANNs in strengthening financial system integrity and fraud prevention. The insights gained from our findings offer practical guidance for stakeholders in the audit and financial sectors. (shrink)

Abstract: Fruits are a rich source of energy, minerals and vitamins. They also contain fiber. There are many fruits types such as: Apple and pears, Citrus, Stone fruit, Tropical and exotic, Berries, Melons, Tomatoes and avocado. Classification of fruits can be used in many applications, whether industrial or in agriculture or services, for example, it can help the cashier in the hyper mall to determine the price and type of fruit and also may help some people to determining whether a (...) certain type of fruit meets their nutritional requirement. In this paper, machine learning based approach is presented for classifying and identifying 10 different fruit with a dataset that contains 6847 images use 4793 images for training, 1027 images for validation and 1027 images for testing. A deep learning technique that extensively applied to image recognition was used. We used 70% from image for training and 15% from image for validation 15% for testing. Our trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. (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)

Abstract: The aim behind analyzing Google Stock Prices dataset is to get a fair idea about the relationships between the multiple attributes a day might have, such as: the opening price for each day, the volume of trading for each day. With over a hundred thousand days of trading data, there are some patterns that can help in predicting the future prices. We proposed an Artificial Neural Network (ANN) model for predicting the closing prices for future days. The prediction is (...) based on these features (date, opening price, highest price, lowest price, volume), which were used as input variables and (closing price) as output variable for our ANN model. Our model was created, trained, and validated using data set in JNN environment, which its title is “Google-Stock-Prices”. The model evaluation showed that the ANN model is able to predict correctly 99.48% of the validation samples. (shrink)

This study employs machine learning to predict diabetes using a Kaggle dataset with 13 features. Our three-layer model achieves an accuracy of 98.73% and an average error of 0.01%. Feature analysis identifies Age, Gender, Polyuria, Polydipsia, Visual blurring, sudden weight loss, partial paresis, delayed healing, irritability, Muscle stiffness, Alopecia, Genital thrush, Weakness, and Obesity as influential predictors. These findings have clinical significance for early diabetes risk assessment. While our research addresses gaps in the field, further work is needed to enhance (...) model generalizability. (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)

Accurate assessment and comprehension of smoking behavior are pivotal for elucidating associated health risks and formulating effective public health strategies. In this study, we introduce an innovative approach to predict and analyze smoking prevalence using an artificial neural network (ANN) model. Leveraging a comprehensive dataset spanning multiple years and geographic regions, our model incorporates various features, including demographic data, economic indicators, and tobacco control policies. This research investigates smoking trends with a specific focus on gender-based analyses. These findings are pivotal (...) for enhancing public health initiatives aimed at mitigating tobacco use, assessing associated health risks, and mitigating smoking-related diseases. (shrink)

As sustainable tourism gains increasing attention, understanding the factors that influence travelers' motivation to engage with sustainable travel agents becomes crucial. This study investigates the moderating effect of social media usage on the relationship between the perceived value of websites and motivational factors for sustainable travel agents. The study proposes that social media usage acts as a moderator in shaping the relationship between the perceived value of websites and motivational factors. This study has utilized smart tourism. Therefore, independent variable motivation (...) in terms of informativeness gratification and gratification acted as moderating variables. This study has utilized an online questionnaire adapted from a standardized questionnaire based on the literature review. Moreover, a total of 146 managers were surveyed in which they were required to respond to 55 items that elicited the 7 variables social media use, Propensity, perceived website value, motivating factors, entertainment gratification, informativeness gratification, sustainable smart tourism. The data were analyzed by SPSS and PLS-SEM. The findings indicated that relevance and importance of social media use and sustainable smart tourism. The result revealed that 7 hypotheses had a significant relationship. 3 hypotheses did not show a moderating effect. Overall, this study extends the understanding of sustainable smart tourism. These findings will benefit travel agents’ managers in Malaysia to better understand the role of social media use and utilize it towards developing sustainable sustainable smart tourism. (shrink)

Abstract: In this study, we explore the possibility of classifying the plant species. We collected the plant species from Kaggle website. This dataset encompasses 544 samples, encompassing 136 distinct plant species. Recent advancements in machine learning, particularly Artificial Neural Networks (ANNs), offer promise in enhancing plant Species classification accuracy and efficiency. This research explores plant Species classification, harnessing neural networks' power. Utilizing a rich dataset from Kaggle, containing 544 entries, we develop and evaluate a neural network model. Our neural network, (...) featuring a single hidden layer, achieves remarkable results—a staggering 100% accuracy and a minute average error rate of 0.002. Beyond performance metrics, we delve into the intricacies of plant Species classification through feature importance analysis. The most influential features— Vegsout, durflow, semiros, pdias, begflow, wind, leafy, autopoll and insects— uncover the physiological traits underpinning accurate rice classification. This research contributes to advancing rice classification methods and highlights the potential of ANNs in optimizing agricultural practices, ensuring plant safety, and bolstering global trade. (shrink)

there is a communication gap between hearing-impaired people and those with normal hearing, sign language is the main means of communication in the hearing-impaired population. Continuous sign language recognition, which can close the communication gap, is a difficult task since the ordered annotations are weakly supervised and there is no frame-level label. To solve this issue, we compare the accuracy of each model using two deep learning models, Inception and Xception . To that end, the purpose of this paper is (...) By attempting to translate sign language using deep learning models, we focused in this paper a comparing between Inception and Xception ¬¬¬¬¬ algorithm and compared it to previous papers in which we used VGG19[1], mobileNet [2], where we get in the Inception and Xception algorithm on the degree of Accuracy 99.32%, 99,43% respectively. number of images (29000 in the dataset in size 75*75 pixel ) and the data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch. (shrink)

Every person has his/her own unique signature that is used mainly for the purposes of personal identification and verification of important documents or legal transactions. There are two kinds of signature verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her signature on a digital tablet or a similar device. Offline signature verification is not efficient and slow for a (...) large number of documents. To overcome the drawbacks of offline signature verification, we have seen a growth in online biometric personal verification such as fingerprints, eye scan etc. In this paper we created CNN model using python for offline signature and after training and validating, the accuracy of testing was 99.70%. (shrink)

American Sign Language, or ASL as its acronym is commonly known, is a fascinating language, and many people outside of the Deaf community have begun to recognize its value and purpose. It is a visual language consisting of coordinated hand gestures, body movements, and facial expressions. Sign language is not a universal language; it varies by country and is heavily influenced by the native language and culture. The American Sign Language alphabet and the British Sign Language alphabet are completely contrary. (...) Fingerspelling is one-handed in ASL and two-handed in BSL, with the exception of the letter C. AI technologies, particularly deep learning, can play an important role in breaking down communication barriers between deaf or hearing-impaired people and other communities, significantly contributing to their social inclusion. Recent advances in sensing technologies and AI algorithms have paved the way for the development of a wide range of applications aimed at meeting the needs of the deaf and hearing-impaired communities. To that end, the purpose of this paper is By attempting to translate sign language using artificial intelligence algorithms, we focused in this paper on a transfer learning technique based on deep learning using a ResNet algorithm and compared it to previous papers in which we used VGG19[1]and mobileNet [2], where we get in the ResNet algorithm on the degree of Accuracy 93,48% e number of images (43500 in the dataset in size 64*64 pixel ) and the data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch. (shrink)

Abstract: Purpose - This study aimed to analyze the relationship between the determinants of organizational justice and their relationship to conscientious behavior from the point of view of officers working in the Palestinian police in Gaza Strip. Methodology - The study relied on the descriptive and analytical approach, using the questionnaire, targeting a stratified random sample of (400) officers, who hold the rank of captain and above, from the study population of 1550 officers. The study tool was distributed among the (...) sample members in all departments and governorates. Police in Gaza Strip. (353) questionnaires were retrieved, with a recovery rate of (88.3%). Findings - The existence of a positive correlation between the determinants of organizational justice and the behavior of conscience, and the existence of organizational justice in general in a medium degree and the order of its determinants is as follows: fairness of dealings and to a large degree, followed by fairness of procedures and a medium degree, and finally distribution fairness was to a small degree, while the behavior of conscience awareness came to a large extent. Significance - The existence of statistically significant differences between the respondents' averages of responding to the searched relationship due to the variables (type of administration, age group, job title, military rank, years of service). Recommendations - Work to take into account the fairness of distribution by providing adequate and fair salaries, granting bonuses for the additional efforts exerted, and budgeting in the distribution of duties and job burdens, as well as recommending attention to the interests of employees when making decisions and involving them in formulating them, explaining their justifications, and creating an organizational climate dominated by a sense of justice. (shrink)

Abstract: The study aimed to determine the strategic flexibility and its relationship to the level of quality of services provided, from the viewpoint of the internal beneficiary in non-governmental hospitals in Gaza Strip. The study relied on the descriptive and analytical approach, and the questionnaire was designed as a tool to collect data and consisted of (39) items, and the researchers used the comprehensive survey method, and the number of the study population was (536) individuals, where (434) questionnaires were retrieved, (...) and the recovery rate was (80.97%). The study revealed many results, the most important of which were: the existence of a moderate degree of approval by the study sample individuals on strategic flexibility, as it was evident through the area of strategic flexibility as a whole having a relative weight (60.44%). The study is on the quality of services, as it became clear through the field of service quality obtaining a relative weight (79.90%). The results of the study revealed a statistically significant relationship between strategic flexibility and the quality of services in non-governmental hospitals in Gaza Strip, with a correlation coefficient of 0.490. The study reached many recommendations, the most important of which were: the need to work on appointing young people and those with potentials, because jobs are vacant in the hospitals under study, and the need to seek the help of an administrative staff with scientific and practical qualifications, and to work on updating information systems, archiving and networks through which data and information are transferred between departments And the creation of mechanisms by which stored information can be used to enhance the decision-making process, and an effective system to receive patients' complaints in a manner that ensures rapid response and treatment, to achieve continuous communication between patients and the hospital management, and to notify patients of dealing with the complaints they submit, and work to provide all Medical and health specialties in the hospitals under study, by making use of the medical delegations that visit Gaza Strip, involving them in the treatment processes, bringing in doctors and specialists from abroad, updating the standards related to measuring the services provided to patients on an ongoing basis, based on the suggestions and complaints of patients, and developing facilities in hospitals As well as updating the medical devices and equipment used in hospitals periodically. (shrink)

Critics have recently argued that reliabilists face trade-off problems, forcing them to condone intuitively unjustified beliefs when they generate lots of true belief further downstream. What these critics overlook is that reliabilism entails that there areside-constraintson belief-formation, on account of which there are some things you should not believe, even if doing so would have very good epistemic consequences. However, we argue that by embracing side-constraints the reliabilist faces a dilemma: she can either hold on to reliabilism, and with it (...) aforementioned side-constraints, but then needs to explain why we should allow the pursuit of justification to get in the way of the acquisition of true belief; or she can deny that there are side-constraints – and in effect give up on reliabilism. We'll suggest that anyone moved by the considerations that likely attract people to reliabilism in the first place – the idea the true belief is good, and as such should be promoted – should go for the second horn, and instead pursue a form ofepistemic utilitarianism. (shrink)

This thesis focuses on the use of intelligent tutoring system for education and training of students specialized in electricity in the field of technical and vocational education. The use of modern systems in training and education will have a great positive impact in improving the level of students receiving training and education; this will improve the level of the local economy by producing students of professionals who are able to engage in society efficiently, especially for those who have specialized in (...) electricity. It is known that students in electrical specialties face many problems because of time and cost. Learning and training is not as easy as you imagine, so intelligence is how to overcome these limitations effectively. Motivating the Intelligent Tutorial System (ITS) for this type of training. This system consists of a student model, which in turn will contain lessons, exercises and examples that will be used by the student in addition to the user interface model which makes the teacher to be able to manage lessons, examples, and questions and make changes to the system. Expert System (ES) model representing the Artificial Intelligence (AI) here has been used to determine the level of the student and gives him the results, directions and levels. The program was implemented and was used by trainees to show the extent of its impact. The students expressed their surprise and admiration in this way of education as the system used focuses on individual education which can be used at any time and without restrictions. After this experience, the dedicated (ITS) system needs to be developed in several ways such as to be used on mobile systems and web systems in addition to linking some of the specialized programs in the field of electricity. (shrink)