Samy S. Abu-Naser

The paper depicts the blueprint of an electronic wise indicating system for demonstrating learning French to understudies to overcome the inconveniences they go up against. The fundamental idea of this structure is a proficient introduction into learning French. The system shows the purpose of learning French and coordinates thusly made issues for the understudies to clarify. The system is logically balanced at run time to the understudy’s individual progress. The system gives unequivocal help to adaptable presentation to learners.

Background: Arthritis is very common but is not well understood. Actually, “arthritis” is not a single disease; it is an informal way of referring to joint pain or joint disease. There are more than 100 different types of arthritis and related conditions. People of all ages, sexes and races can and do have arthritis, and it is the leading cause of disability in America. More than 50 million adults and 300,000 children have some type of arthritis. It is most common among women and occurs more frequently as people get older. Common arthritis joint symptoms include swelling, pain, stiffness and decreased range of motion. Symptoms may come and go. They can be mild, moderate or severe. They may stay about the same for years, but may progress or get worse over time. Severe arthritis can result in chronic pain, inability to do daily activities and make it difficult to walk or climb stairs. Arthritis can cause permanent joint changes. These changes may be visible, such as knobby finger joints, but often the damage can only be seen on X-ray. Some types of arthritis also affect the heart, eyes, lungs, kidneys and skin as well as the joints. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment and give the appropriate method of treatment through several tips that concern the disease and how to treat it and we will see it through the application on the expert system. Methods: in this paper the design of the proposed Expert System which was produced to help Orthopedist in diagnosing Arthritis disease through its symptoms such as: pain on pressure in a joint , Inflammation indicated by joint swelling, Stiffness especially in the morning , Loss of flexibility of joint, Limited, joint movement, Deformity of the joints , Weight loss and fatigue , Non-specific fever and Crepitus. The proposed expert system presents an overview about Arthritis disease is given, the cause of diseases is outlined and the treatment of disease whenever possible is given out. SL5 Object Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Arthritis disease diagnosis expert system was evaluated by Orthopedics students and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for Orthopedist, patients with arthritis and newly graduated Orthopedics students.

The aim of this study was to identify the obstacles facing the application of knowledge management and its impact on performance at Palestine Technical University-Kadoorei from the point of view of employees and to detect the differences between the average views of the study sample on the subject of the study according to some variables such as (gender, nature of work, Education Level, specialization, years of experience). The study followed the descriptive analytical method and the questionnaire as a tool for study. It was distributed to 74 employees. After the questionnaire was distributed, the data was collected and coded and entered into the computer and processed statistically using the SPSS program. The study found that the percentage of approval of the obstacles to the application of knowledge management at Palestine Technical University-Kadoorei differed between few and large, and the relative weight of the axis was complete (68.2). The degree of awareness of the workers of the reality of performance excellence at the University of Palestine Technical-Kadoorei was between medium and very large. There is an impact of the constraints of the application of knowledge management on performance excellence at Palestine Technical University-Kadoorei. In light of the results of the previous study, the researchers recommended that the importance of knowledge management should be taken into account in order to raise the university's reputation and reputation at home and abroad and improve its services to students and the local community. And to promote the exchange of experiences and knowledge with local, regional and international universities in order to enhance the knowledge and preserve it and provide modern and sophisticated scientific techniques and use them in administrative and academic work at the university.

Abstract— This study aimed to identify the degree of use of the capabilities of decision-support systems in Palestinian institutions higher education, Aqsa University in Gaza - a case study. The study used a analytical descriptive approach, and the researchers used the of questionnaire tool to collect the data, the researchers using stratified random sample distributed (150) questioners to the study population and (126) was obtained back with rate of 84%. The study showed that the most important results are: that senior management supports the existence of decision support systems and that there is approval by the respondents on the paragraphs of the use of the capabilities of decision support systems in general. And that there are no significant differences between the averages of the answers of respondents differences about the degree of use of decision support systems capabilities attributed to personal data. The study also concluded a series of recommendations including: increasing the adoption of the senior management decision support in their decision-making systems. And increased regulatory attention to the potential available to decision support systems directly to the senior management in the Palestinian universities in the Gaza Strip. There is an increased interest in the physical and technical possibilities available for the use of decision support systems. There is an increased interest in human potential available for the use of decision support systems. Investment of information available to universities in building the capacities of integration techniques and other information technology capabilities. The empowerment of human resources in universities and participating in making decisions concerning the construction of the capabilities of information technology.

The study aimed to identify Design Thinking and its use in NGOs in Gaza Strip. In order to achieve the objectives of the study and to test its hypotheses, the analytical descriptive method was used, relying on the questionnaire as a main tool for data collection. The study society was one of the decision makers in the local NGOs in the Gaza Strip. The study population reached 78 local NGOs in Gaza Strip. The overall inventory of the possible study community was based mainly on the use of the SPSS in processing and analyzing the data obtained through the survey tool. Smart-PLS was also used to construct the structural equation model (SEM) Analyzing the relationship between study variables. The study found that Design Thinking mediates the relationship between the management of process design and decision making with a holistic effect. The study showed the interest of local NGOs in creating a good mental image in the local community. And the ownership of local NGOs to the expertise and technical skills required to implement the projects, and showed the adoption of local NGOs in their activities to meet the needs of the beneficiaries and their wishes, and local NGOs analyze the problem, and causes, through data relevant to the decision, based on reference data for decision-making. The main recommendations of the study are: The need for senior management in the local NGOs in Gaza Strip to adopt the methodology of design thinking because of its impact on the sustainability of the projects, design the technical feasibility study and meet the wishes of the beneficiaries.

Abstract cantaloupe and honeydew melons are part of the muskmelon family, which originated in the Middle East. When picking either cantaloupe or honeydew melons to eat, you should choose a firm fruit that is heavy for its size, with no obvious signs of bruising. They can be stored at room temperature until you cut them, after which they should be kept in the refrigerator in an airtight container for up to five days. You should always wash and scrub the rind of your melon before you cut it to remove any dirt or bacteria on the outside. In this paper, cantaloupe classification approach is presented with a dataset that contains approximately 1,312 of Cantaloupes and honeydews. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used, for this task. The results found that CNN-driven classification applications when used in farming automation have the latent to enhance crop harvest and improve output and productivity when designed properly. The trained model achieved an accuracy of 99.74% on a held-out test set, demonstrating the feasibility of this approach.

Abstract: The study aimed to identify the creative behavior in the Palestinian civil organizations between reality and expectations, and the study used the descriptive analytical approach and the questionnaire as a main tool for collecting data from employees of associations operating in the governorates of Gaza Strip, and the cluster sample method was used and the sample size was (343) individuals and has been recovered (298) Resolution. The following results were reached: The relative weight of the measure of creative behavior was 78.99 (%), and there were no statistically significant differences in creative behavior according to the gender variable, age group, educational qualification, specialization, while the results indicated that there were differences according to the number of years of service. The study presented a set of recommendations, the most important of which are: the necessity of working to follow up the strategic plan for NGOs using electronic messages as it paves the way for achieving excellence and creativity in the field of work, the need to hold meetings and workshops with the local community and this helps them determine the needs of the community.

This study aimed to identify the reality of marketing services in Palestine Cellular Communications Company (Jawwal) from the viewpoint of the workers, where the researchers used the descriptive analytical method, through a questionnaire randomly distributed to the sample of workers in Palestine Cellular Communications Company (Jawwal) in Gaza Strip reached (60) employees. The study reached a number of results, the most important of which are: The results showed that there is a high level of efficiency of marketing services in Palestine Cellular Communications Company (Jawwal) with a relative weight (91.63%). The results showed that there were no statistically significant differences in the efficiency of marketing services according to the gender variable in favor of males. The study made a number of recommendations, the most important of which are: Attention to the use of electronic publishing means to motivate beneficiaries to receive the company's services. Increase the confidence of the beneficiaries in the company's services by offering competitive campaigns that meet the needs of the beneficiaries.

The research aims to identify the status of the application of electronic document management system in governmental institutions – the study was applied on the Palestinian Pension Agency. The population of this study is composed of all employees in the Palestinian Pension Agency. In order to achieve the objectives of the study, the researchers used the descriptive and analytical approach, through which try to describe the phenomenon of the subject of the study, analyze the data and the relationship between the components and the views put around it. Census method was used due to the small size of the study population and ease of access to the target group. (108) questionnaires were distributed to all members of the study population, were (65) employees in the Gaza Strip and (43) employees in the West Bank. All questionnaires were recovered. The study found the following results: There were no statistically significant differences in the members of the population in response to differences in the study about the reality of the application of electronic document management system in governmental institutions - case study on the Palestinian Pension Authority due to the age. There are no statistically significant differences in population members in response to the reality of the application of electronic document management system in governmental institutions - case Study on the Palestinian Pension Authority due to the variable nature of the job. As well as there are no statistically significant differences in the members of the population in response to the study about the reality of the application of electronic document management system in governmental institutions - case study on the Palestinian Pension Authority due to the variable of specialization. There are statistically significant differences in the study about the reality of the application of electronic document management system in governmental institutions - case study on the Palestinian Pension Authority due to Qualification variable for the benefit of members of the population study who are holding a Bachelor degree. There are statistically significant differences in the study about the reality of the application of electronic document management system in governmental institutions – case study on the Palestinian Pension Authority due to the variable number of years of experience for the benefit of members of the study population who have experience between 11-15 years. The study found a group of recommendations, including: the need to focus on the establishment of a general management of electronic documents in the organization structure that takes care of all the technical processes in it an contains scientifically qualified persons in the field of electronic document management. The need is for the attention in developing strategic plans, policies and mechanisms of action commensurate with the electronic document management system.

Abstract— Anatomy of the anterior compartment includes the tibia and the fibula. It also includes the tibialis anterior tendon, the extensor hallucis longus tendon and the extensor digitorum longus tendons. The anterior tibial artery and the deep peroneal nerve and finally the superior and inferior extensor retinaculum. In this paper an expert system was designed to help users to correctly diagnose ankle problems. There are many structures present at the anterior aspect of the ankle; these structures are often susceptible to injury common injuries and conditions around the anterior ankle. Clips expert system language was used to design and implement this expert system.

Cardiovascular diseases, including heart disease, pose a significant global health challenge, contributing to a substantial burden on healthcare systems and individuals. Early detection and accurate prediction of heart disease are crucial for timely intervention and improved patient outcomes. This research explores the potential of neural networks in predicting heart disease using a dataset collected from Kaggle, consisting of 1025 samples with 14 distinct features. The study's primary objective is to develop an effective neural network model for binary classification, identifying the presence or absence of heart disease. The neural network architecture includes an input layer, a hidden layer, and an output layer, designed to capture intricate relationships within the dataset. Rigorous training and validation processes, accompanied by data preprocessing steps, ensure the model's robustness and generalization capabilities. The results demonstrate promising performance, with an accuracy of 92% and an average error of 0.062. Moreover, an analysis of feature importance highlights key predictors, including "oldpeak," "thalach," "trestbps," "ca," "thal," "cp," "chol," "sex," "restecg," "age," "slope," "fbs," and "exang." This research contributes to the field of predictive healthcare by leveraging neural networks to enhance heart disease prediction. The developed model offers the potential for early identification of individuals at risk, facilitating timely medical interventions and ultimately improving public health. Further exploration of machine learning techniques in healthcare promises to reshape disease prediction and prevention strategies.

Background: A bean is the seed of one of several genera of the flowering plant family Fabaceae, which are used as vegetables for human or animal food. They can be cooked in many different ways, including boiling, frying, and baking, and are used in many traditional dishes throughout the world. Beans are one of the longest-cultivated plants. Broad beans, also called fava beans, in their wild state the size of a small fingernail, were gathered in Afghanistan and the Himalayan foothills. In a form improved from naturally occurring types, Beans were an important source of protein throughout old and new world history, and still are today. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper, the design of the proposed Expert System was produced to help farmers and those interested in agriculture in diagnosing many of the Bean diseases such as Fusarium wilt, Charcoal rot or ashy stem blight, Bacterial leaf spot and blight, Mung bean yellow mosaic virus, Cercospora leaf spot. The proposed expert system presents an overview of Bean diseases are given, the cause of diseases outlined and the treatment of disease whenever possible is given out. CLIPS Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Bean diseases diagnosis expert system was evaluated by Agricultural experts and some friends interested in agriculture and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for Farmers and those interested in agriculture.

Background: Obstetrics and gynaecology are many and common, where a woman suffers from problems related to pregnancy or her reproductive organs. Any part of her body may be affected due to some symptoms that are completely related to the reproductive organs when she is in a critical period for her, whether in her menstrual cycle, pregnancy, or disease conditions. The bulk of cases of diseases related to women and childbirth are dealt with great care and special care, as all diseases related to women are considered very sensitive diseases due to the presence of the disease in sensitive and not simple places. A gynaecologist is a specialist in all diseases and problems related to the female sexual organs. They perform regular preventive medical exams, such as cervical smear tests and breast exams. It also provides consultations for women of all ages about the problems of contraception, infertility and menopause. Objectives: The objective of this expert system is to help and facilitate women in diagnosing diseases related to their obstetrics and gynaecology, a simple expert system has been designed consisting of ten various common diseases that affect women whether During or without pregnancy, Methods: In this system, the system consists of a list of some common symptoms, the correct diagnosis adopted for these diseases, and how to treat diseases in the correct way with the help of a consultant obstetrician and gynaecologist, Dr. Fathi Muhammad Al-Habibi, and these diseases are: uterine cancer, cervical cancer, Infertility, double uterus, ectopic pregnancy, endometrial cancer, female sexual dysfunction, endometriosis, faecal incontinence, female infertility, CLIPS Expert System language was used to design and implement the proposed expert system. Results: The proposed ten obstetrics and gynaecology diagnostic expert system was evaluated by medical students and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for obstetricians and gynaecologists, patients with reproductive system problems, and recent graduates.

Diabetes is a major public health issue that affects the nations of our time to a large extent and is described as a non-communicable epidemic. Diabetes mellitus is a common disease where there is too much sugar (glucose) floating around in your blood. This occurs because either the pancreas can’t produce enough insulin or the cells in body have become resistant to insulin. The concentration in this paper is on diagnosis diabetes by designing a proposed expert system. The main goal of this expert system is to get the appropriate diagnosing of the illness, dealing with it quickly, and tips for permanent treatment whenever possible is given out. SL5 object expert system language was used for designing and implementing the proposed expert system

The study aimed to identify the reality of total quality management in university colleges in Gaza Strip, through its dimensions, which are (commitment of senior management; organizational building; employee empowerment; continuous improvement; focus on beneficiaries; management by facts), and to detect differences in the responses of sample members according to For personal variables (type; educational qualification; college; nature of work; years of service). The researchers used the descriptive analytical method, and used a main tool to collect information: the questionnaire consisted of (42) phrases, and the study population reached (596) academic and administrative employees distributed to (5) university colleges in Gaza Strip, and it was chosen A stratified random sample of them consisted of (240) employees, approximately (40.3%) of the study population. (SPSS) was used to analyze the data. The study concluded a set of results, the most important of which are: (1) The application of the requirements of total quality management in university colleges in Gaza Strip is generally appropriate in terms of: (the commitment of senior management to total quality management, organizational building, facts management, focus on beneficiaries, employee empowerment, continuous improvement), where the response of the sample members was about the dimensions Total quality management with relative weight (69.93%). (2) There are differences at the level of significance (α =.05) between the averages of the respondents' responses to total quality management in university colleges in Gaza Strip due to gender and differences in favor of the male category. And differences attributed to the college and in favor of the University College of Professional Sciences. (3) There are no differences between the averages of the respondents' responses to total quality management in university colleges in Gaza Strip due to (Educational Qualification, Nature of Work, and Years of Service). Among the most important recommendations of the study: The need for university colleges to ensure: (achieving job satisfaction, employee participation when setting regulations and policies and making important decisions, adhering to the requirements of scientific research and encouraging scientific achievements and job creativity among employees, while providing material and moral facilities for scientific research and development, developing Mechanisms and patterns of electronic work). And that university colleges give attention to handling complaints and grievances through: (assigning a competent and competent committee to handle complaints and grievances in all fairness and transparency, adopting and following up on the results of implementing complaints and grievances, protecting the complainants from any arbitrary procedure against them).

In this research, an Artificial Neural Network (ANN) model was developed and tested to predict Birth Weight. A number of factors were identified that may affect birth weight. Factors such as smoke, race, age, weight (lbs) at last menstrual period, hypertension, uterine irritability, number of physician visits in 1st trimester, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some birth cases in hospitals. The evaluation of testing the dataset shows that the ANN model is capable of correctly predicting the birth weight with 100% accuracy.

هدفت هذه الدراسة إلى التعرف على العلاقة بين نظم دعم القرار وإعادة الهندسة في الجامعات الفلسطينية بقطاع غزة، واستخدمت الدراسة المنهج الوصفي التحليلي، واستخدم الباحث أسلوب الاستبانة لجمع البيانات، وقام الباحث باستخدام طريقة العينة الطبقية العشوائية، وتم توزيع ( 500 ) إستبانة على .(% عينة الدراسة، حيث تم استرداد ( 449 ) إستبانة بنسبة استرداد ( 89.8 α ≤ وقد أظهرت الدراسة نتائج أهمها ما يلي: وجود علاقة ذات دلالة إحصائية عند مستوى دلالة 0.04 ) بين نظم دع م القرا ر وإعادة الهندسة في الجامعات الفلسطينية في قطاع غز ة، كذلك وضحت ) النتائج وجود فروق ذات دلالة إحصائية بين متوسطات تقديرا ت عينة الدراسة حول العلاقة بين نظم دعم القرا ر وإعادة الهندسة في الجامعات الفلسطينية بقطاع غز ة تعزى لمتغي ر الجنس لصالح الذكور، ووجود فروق بالنسبة لمتغير العمر بالنسبة إلى مجال " دعم الإدارة العليا لاستخدام نظم دعم القرا ر" 55 ) سن ة و( 55 ) سنة فأكثر، ووجود فروق بالنسبة - لدى المبحوثين الذين تتراوح أعمارهم من ( 45 لمتغير المستوى التعليمي بالنسبة إلى مجال " دعم الإدارة العليا لاستخدام نظم دع م الق رار " لد ى المبحوثين الذين يحملون درجة الماجستير، ووجود فروق لمتغير اسم الجامعة وذلك لكل مجال من مجالات الدراس ة لصالح الجامعة الإسلامية ثم جامعة الأزهر ثم جامعة الأقصى، ووجود فروق بالنسبة لمتغير سنوات الخدمة بالنسبة إلى مجال "دعم الإدارة العليا لاستخدام نظم دعم القرار" لدى المبحوثي ن 20 ) سنة و( 21 ) سنة فأكثر. - الذين تتراوح سنوات خدمتهم من ( 15 كما خلصت الدراسة إلى مجموعة من التوصيات أهمه ا: لكي تتمكن الجامعات الفلسطينية بقطاع غزة من معايشة عصر العولمة والتعامل مع مفرداتة التقنية التي فرضت نفسها على مختلف قطاعات الحياة المعاصرة، فان هذا يستلزم إعادة هندسة الجامعات الفلسطينية بقطاع غز ة، وتوضيح أهمية عملية إعادة الهندسة للإدارة العلي ا للجامعات الفلسطيني ة التي لا يوجد لديها توجه لإعادة الهندس ة، وتشجي ع الجامعات التي تخطط لإعادة الهندسة للبدء بتنفيذ برامجها في التغيير الجذري بالسرعة الممكن ة، وانه من الضروري للجامعات الفلسطينية بقطاع غزة عند أعادة هندسة عملياتها أن تقوم بتطوير البنية التحتية لتكنولوجيا المعلومات بصورة عامة، ونظم دعم القرار بصورة خاصة، وتعزيز دعم واهتمام الإدارة العليا في الجامعات الفلسطينية بقطاع غزة بنظ م دعم القرار، زيادة اعتماد الإدارة العليا على نظم دعم القرار في اتخاذ قراراتها، وقيامها بتشخيص المشاكل وتشجيع العاملين من خلال توفير الكادر اللازم لتنفيذ عملية نظم دعم القرار وتشجيع العاملين على استخدام نظم دعم القرار وتشخيص المشاكل والتغلب على المعيقات التي تعترض تطوير نظم دعم القرار.

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.

Climate change temperature prediction plays a crucial role in effective environmental planning. This study introduces an innovative approach that harnesses the power of Artificial Neural Networks (ANNs) within the Just Neural Network (JustNN) framework to enhance temperature forecasting in the context of climate change. By leveraging historical climate data, our model achieves exceptional accuracy, redefining the landscape of temperature prediction without intricate preprocessing. This model sets a new standard for precise temperature forecasting in the context of climate change. Moreover, our research provides valuable insights into the pivotal factors influencing temperature variations, making significant contributions to environmental science and climate mitigation strategies.

Artificial intelligence is one of the most rapidly evolving fields today. It is used in the majority of computer science applications nowadays. Expert systems are one of the most valuable types of AI; they are used to deliver predictions and decisions in order to make scientific, medical, and even architectural challenges easier to address; they will eventually take the place of a human expert. Without having to meet with a genuine human specialist, the user will be able to get a precise solution or diagnose to his problem. This study provides an illustration of how computer systems can be used in agriculture. In order to construct an expert system that can forecast a disease based on its symptoms, we chose a Coriander plant and five of its recognized ailments. CLIPS was used to develop the system. This article contains a full summary of the work that has been done.

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.

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.

Abstract: As the integration of Artificial Intelligence (AI) continues to permeate various sectors, the legal domain stands on the cusp of a transformative era. This research paper delves into the multifaceted relationship between AI and the law, scrutinizing the profound implications and innovative applications that emerge at the intersection of these two realms. The study commences with an examination of the current landscape, assessing the challenges and opportunities that AI presents within legal frameworks. With an emphasis on efficiency, accuracy, and accessibility, AI technologies are reshaping traditional legal processes, ranging from document analysis and contract review to predictive legal analytics. Furthermore, the paper scrutinizes the ethical considerations and potential biases inherent in AI algorithms, exploring the delicate balance between technological advancements and the preservation of legal principles such as fairness, accountability, and transparency. The research also delves into the evolving role of legal professionals in navigating and overseeing AI applications, emphasizing the importance of responsible AI deployment. Drawing on case studies and real-world examples, this paper showcases instances where AI has already demonstrated its efficacy in legal contexts, highlighting successful implementations and identifying areas for improvement. The discussion extends to the evolving regulatory landscape, as legal systems grapple with the need to adapt and establish frameworks that ensure the responsible and ethical use of AI technologies. In conclusion, this research contributes to the growing discourse on the dynamic interplay between AI and the legal domain. By illuminating the potential benefits, ethical considerations, and regulatory challenges, it provides a comprehensive overview for legal practitioners, policymakers, and technologists alike, fostering a nuanced understanding of the evolving landscape where artificial intelligence intersects with the law.

Background: There is no doubt that strawberry diseases are one of the most important reasons that led to the destruction of strawberry plants and their crops. This leads to obvious damage to these plants and they become inedible. Discovering these diseases after a good step for proper and correct treatment. Determining the treatment with high accuracy depends on the method used in the diagnosis. Correctly, expert systems can greatly help in avoiding damage to these plants. The expert system correctly diagnoses strawberry disease to make it easier for farmers to find the right treatment based on the appropriate diagnosis. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper the design of the proposed Expert System which was produced to help Farmers and students interested in agriculture strawberry in diagnosing many of the strawberry diseases such as: Leaf Spots, Grey Mold, Red Stele/Red Core, Wilt, Powdery Mildew, Alternaria Spot, Black Root Rot, Anthracnose (black spot), and Angular Leaf Spot. The proposed expert system presents an overview about strawberry diseases are given, the cause of diseases are outlined and the treatment of disease whenever possible is given out. CLIPS language was used for designing and implementing the proposed expert system. Results: The proposed strawberry diseases diagnosis expert system was evaluated by Farmers and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for Farmers with strawberry problem and students interested in agriculture strawberry.

This study aims to identify the strengthening of the global entrepreneurial orientation practice for employees at the University of Palestine, where the researchers used the descriptive and analytical approach, through a questionnaire distributed to a sample of employees at the University of Palestine, where the size of the study population is (234) employees and the sample size is (117) Employees, of whom (90) employees responded. The study found a set of results, the most important of which are: that there is a good degree of global entrepreneurial orientation for employees, as the percentage reached (70.25%), and the results also showed that there are no statistically significant differences in the smart university transformation and their impact on the global entrepreneurial trend according to personal and organizational data. The study presented a set of recommendations, the most important of which are: The need to work to enhance the global entrepreneurial orientation of the university's employees.

The study aimed to investigate the reality of spreading the culture of entrepreneurship at Al-Azhar University from the point of view of students of the Faculty of Engineering and Information Technology and diagnose the most important obstacles that limit its activation. The researchers used the descriptive approach (survey) to achieve the objectives of the study, and relied on the questionnaire as a tool for applied study. The study concluded that: The reality of spreading the culture of entrepreneurship at Al-Azhar University from the point of view of the students participating in the study came with an average degree of approval, while the most important obstacles and possible proposals for activating it came with a high degree of approval, which indicates the existence of strengths of Al-Azhar University in spreading the culture of entrepreneurship among students. Deficiencies must be corrected through proposals. In light of the results of the study, it was possible to develop a number of recommendations that can contribute to activating the culture of entrepreneurship at Al-Azhar University. Including the establishment of a specialized center for entrepreneurship within the university, develop a declared strategic plan to spread and develop the culture of entrepreneurship, allocate a sufficient budget to sponsor and support entrepreneurial ideas and projects for students and provide specialized cadres and certified trainers in the field of entrepreneurship.

According to the literature review, there is much room for improvement of college student retention. The aim of this research is to evaluate the possibility of using deep and machine learning algorithms to predict whether students continue to attend college or will stop attending college. In this research a feature assessment is done on the dataset available from Kaggle depository. The performance of 20 learning supervised machine learning algorithms and one deep learning algorithm is evaluated. The algorithms are trained using 11 features from 1000 records of previous student registrations that have been enrolled in college. The best performing classifier after tuning the parameters was NuSVC. It achieved Accuracy (91.00%), Precision (91.00%), Recall (91.00%), F1-score (91.00%), and time required for training and testing (0.04 second). Additionally, the proposed DL algorithm scored: Accuracy (93.00%), Precision (93.00%), Recall (93.00%), F1-score (93.00%), time required for training and testing (0.66 second) for predicting whether student will continue to attend college or not.

The Knowledge Based System for Diagnosing Breast Cancer is used to assist medical students to improve their education on diagnosis and counseling the process of analyzing the biopsy image of the microscope, determining the type of tumor and the treatment method for each case and identifying the disease related questions. According to the Ministry of Health in its annual report in Gaza, between 2009 and 2014 there are 7069 cases of breast cancer, and in 2014 there are 1502 cases of breast cancer . We are now in the age of visual information where 65% of the populations are visual learners; the Knowledge Based System is the easiest way to ensure students remember the information in the long term, using visual and textual information. The Knowledge Based System has an easy-to-use interface to help students diagnose the disease and enhance their information about the disease; the system can be used on smart phones. This Knowledge Based System can be divided into three main parts: The first part is specific questions for the patient, to help student to know questions type. The second part is the process of analyzing the biopsy sample image, to see if the biopsy image is intact or infected. The last part is the video shows ways to treat breast cancer in the form of animation.

Breast cancer remains a significant health concern worldwide, necessitating the development of effective diagnostic tools. In this study, we employ a neural network-based approach to analyze the Wisconsin Breast Cancer dataset, sourced from Kaggle, comprising 570 samples and 30 features. Our proposed model features six layers (1 input, 1 hidden, 1 output), and through rigorous training and validation, we achieve a remarkable accuracy rate of 99.57% and an average error of 0.000170 as shown in the image below. Furthermore, our investigation identifies the most influential features in breast cancer diagnosis, shedding light on the key determinants of malignancy. Notably, we find that factors such as fractal dimension_se, symmetry worst, compactness_worst, symmetry_se, and smoothness_se play pivotal roles in distinguishing between benign and malignant cases. This research contributes to the ongoing efforts to enhance breast cancer diagnosis, providing valuable insights into feature importance and showcasing the potential of neural networks in medical applications. Our findings have implications for improving early detection and treatment strategies, ultimately contributing to improved patient outcomes.