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)

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

Abstract: In worldwide, there are several hundred cultivars of mango. Depending on the cultivar, mango fruit varies in size, shape, sweetness, skin color, and flesh color which may be pale yellow, gold, or orange. Where there are more than 15 types of manga. In this paper, two types Mango classification approach is presented with a dataset that contains approximately 1200 images. 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 Mango classification applications when used in classification automation it enables people to know the type of mango properly. The trained model achieved an accuracy of 100% on test set, demonstrating the feasibility of this approach. (shrink)

Abstract: Nuts are nutrient-dense foods with complex matrices rich in unsaturated fatty and other bioactive compounds. By virtue of their unique composition, all types of nuts are likely to beneficially impact health outcomes. In this paper, we classified five types of Nuts with a dataset that contains 2868 images. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used for this task. The trained model achieved an accuracy of 98% on a held-out test set, (...) demonstrating the feasibility of this approach. (shrink)

Fruit has been recognized as a good source of vitamins and minerals, and for their role in preventing vitamin C and vitamin A deficiencies. People who eat fruit as part of an overall healthy diet generally have a reduced risk of chronic diseases. Fruit are important sources of many nutrients, including potassium, fiber, vitamin C and folate (folic acid). One of important types of fruit is Grapefruit . Grapefruit is a tropical citrus fruit known its sweet and somewhat sour taste. (...) It's rich in nutrients, antioxidants and fiber, making it one of the healthiest citrus fruits you can eat. Research shows that it may have some powerful health benefits, including weight loss and a reduced risk of heart disease. In this paper we presented a system that recognize the two types of Grapefruit Pink and white based on deep learning using python on colab editor . This system may help people to automate their factories , restaurants or anything else need to classify these two types for different use . (shrink)

The study aimed to examine the Information Technology used and its effect on the nature of the work of the administrators at Al-Azhar University in Gaza. The researchers used the analytical descriptive method through a questionnaire randomly distributed among the employees of Al-Azhar University in Gaza. The study was conducted on a sample of 77 employees the response rate was 92.20%. The study reached a number of results, the most important of which is that there is a high degree of (...) Information Technology Used at Al-Azhar University- Gaza from the point of view of the administrative staff, where the percentage (74.14%). And that there is a high level of the prevailing the Nature of Administrators Work from the point of view of administrative staff, where the percentage (72.14%), there is a direct correlation between the Information Technology Used and the Nature of Administrators Work, there is a statistically significant effect of the Information Technology Used on the Nature of Administrators Work at the university, the absence of differences between the sample according to the variable (gender and variable age) in their perception of the Information Technology Used and the Nature of Administrators Work, there are differences of statistical Sig. in the perception depending on the variable of scientific qualification in Field of the Nature of Administrators Work, while there were no differences in Field: technology used, the differences in the Nature of Administrators Work according to the scientific qualification were in favor of those who obtained the diploma degree compared to postgraduate studies, the absence of differences in the perception of employees of the Information Technology Used and the Nature of Administrators Work according to the variable years of service, and the variable level of employment (manager, head of department, administrative officer), and the change of the workplace. The study reached a number of recommendations, the most important of which is the necessity of giving universities the opportunity to participate in decision-making, the continued administration of universities interest and continuous improvement of the performance of its employees, the need to strengthen the periodic evaluation of job performance and to inform the employees and to express their opinion, the importance of solving the problems of Employees and giving them the opportunity to contribute to solving their own problems, the need to use the method of rotation of employees and periodically, and the importance of strengthening the democratic leadership style and empowering university staff. (shrink)

Background: Depression (major depressive disorder) is a common and serious medical illness that negatively affects how you feel, the way you think and how you act. Fortunately, it is also treatable. Depression causes feelings of sadness and/or a loss of interest in activities once enjoyed. It can lead to a variety of emotional and physical problems and can decrease a person’s ability to function at work and at home. Depression affects an estimated one in 15 adults (6.7%) in any given (...) year. And one in six people (16.6%) will experience depression at some time in their life. Depression can strike at any time, but on average, first appears during the late teens to mid-20s. Women are more likely than men to experience depression. Some studies show that one-third of women will experience a major depressive episode in their lifetime. 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 Psychologist in diagnosing depression disease through its symptoms such as: a loss of energy, a change in appetite, sleeping more or less, anxiety, reduced concentration, indecisiveness, restlessness, feelings of worthlessness, guilt or hopelessness and thoughts of self-harm or suicide. The proposed expert system presents an overview about depression 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 depression disease diagnosis expert system was evaluated by psychologist students and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for psychologist, patients with depression and newly graduated psychologist. (shrink)

The study aimed to study The Organizational Structure and its role in applying the Information Technology Used the Palestinian universities as a comparative study between Al-Azhar and Islamic universities. The researchers used the analytical descriptive method through a questionnaire that randomly distributed among Palestinian university workers in Gaza Strip. A sample of (182) administrative staff from the two universities, the response rate was (81.35%). The study reached a number of results, the most important of which is that there is a (...) high level of the Information Technology Used from the perspective of administrative staff, there is a direct correlation between The Organizational Structure and the Information Technology Used, the role and impact of The Organizational Structure in the nature of the Information Technology Used, the absence of differences between the sample according to the variable (gender and age), there are statistically significant differences in the perception of The Organizational Structure and the Information Technology Used according to the variable of scientific qualification in The Organizational Structure, while there were no differences in Field of the Information Technology Used, the differences in The Organizational Structure according to the scientific qualification were in favor of those who obtained the diploma degree compared to other practical qualifications, the absence of differences in the perception of employees The Organizational Structure and the Information Technology Used depending on the variable years of service, the differences in The Organizational Structure and technology perception depending on the job level variable (Director, Head of Section, and Administrative Officer) for the benefit of the Administrative Officer, the absence of differences in the perception of employees The Organizational Structure and the Information Technology Used depending on the workplace variable, the differences in the perception of employees The Organizational Structure and the Information Technology Used by the University working for the Islamic University. The study reached a number of recommendations, the most important of which is that the managements of the Palestinian universities in Gaza Strip should be given more attention to the existing The Organizational Structure and modified to suit the need of work, the need for universities to continue to pay attention to the continuous improvement of the Information Technology Used and strengthening the democratic leadership style and empowering university staff. (shrink)

Abstract: In recent years email has become one of the fastest and most economical means of communication. However increase of email users has resulted in the dramatic increase of spam emails during the past few years. Data mining -classification algorithms are used to categorize the email as spam or non-spam. Numerous email spam messages are marketable in nature but might similarly encompass camouflaged links that seem to be for acquainted websites but actually lead to phishing web sites or sites that (...) are holding malware. Spam email might likewise comprise malware as scripts or other executable file attachments. Spammers use spam bots to generate email distribution lists. A spammer naturally sends an email to millions of email addresses. The address and identity of the sender are concealed Mass Mailing with the expectation that only a small number will respond or interact with the message and Spam mails might be the cause of phishing attack, hacking of banking accounts, attacks on confidential data. Spamming is rising at a quick speed as sending a deluge of mails is simple and for free. Spam mails interrupt the one calmness, spending much time and put away various resources like memory and networks bandwidth. In this study, we present a method for spam filtering using Artificial Neural Network to predict whether an email is spam or not. (shrink)

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. (shrink)

Abstract: Banana, fruit of the genus Musa, of the family Musaceae, one of the most important fruit crops of the world. The banana is grown in the tropics, and, though it is most widely consumed in those regions, it is valued worldwide for its flavour, nutritional value, and availability throughout the year. Cavendish, or dessert, bananas are most commonly eaten fresh, though they may be fried or mashed and chilled in pies or puddings. They may also be used to flavour (...) muffins, cakes, or breads. Cooking varieties, or plantains, are starchy rather than sweet and are grown extensively as a staple food source in tropical regions; they are cooked when ripe or immature. A ripe fruit contains as much as 22 percent of carbohydrate and is high in dietary fibre, potassium, manganese, and vitamins B6 and C.. In this paper, machine learning based approach is presented for identifying type Apple with a dataset that contains 8,554 images use 4,488 images for training, 1,928 images for validation and 2,138 images for testing. A deep learning technique that extensively applied to image recognition was used. use 70% from image for training and 30% from image for validation. Our trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

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

Background: The occurrence of any disturbance in the seventh facial nerve in the nerves of the brain called inflammation of the seventh nerve or paralysis in the face of half (Bell's paralysis), where paralysis affects one side of the face, and occurs when the seventh nerve, which controls the muscles of the face loses the patient control of the facial muscles on The side of inflammation is the seventh nerve because it controls the muscles on both sides of the face (...) that enable us to express the smile, laughter, crying and other facial expressions to any injury that affects the facial expressions of the motor. Objectives: This paper will solve the problems of treatment of seventh nerve inflammation through correct diagnosis and treatment. Methods: In this research, we provide an expert system for the diagnosis of seven nerve inflammation which will help doctors to explore everything related to the problems of seventh nerve inflammation. We look forward to providing simplified answers to seven nerve inflammation. (shrink)

Associations can grow, succeed, and sustain if their employees are committed. The main assets of an association are those employees who are giving it a required number of hours per month, in other words, those employees who are punctual towards their attendance. Absenteeism from work is a multibillion-dollar problem, and it costs money and decreases revenue. At the time of hiring an employee, Associations do not have an objective mechanism to predict whether an employee will be punctual towards attendance or (...) will be habitually absent. For some Associations, it can be very difficult to deal with those employees who are not punctual, as firing may be either not possible or it may have a huge cost to the association. In this paper, we propose An Artificial Neural Networks algorithm that can predict the behavior of employees towards punctuality at workplace. The efficacy of the proposed method is tested with traditional machine learning techniques, and the results indicate 99.00% accuracy. The proposed model will provide a useful mechanism to associations that are interested to know the behavior of employees at the time of hiring and can reduce the cost of paying to inefficient or habitually absent employees. (shrink)

Background: Your liver is your body’s largest solid organ. This organ is vital to the body’s metabolic functions and immune system. Without a functioning liver, a person cannot survive. The liver’s position is mostly in the right upper portion of the stomach, just below the diaphragm. A portion of the liver goes into the left upper abdomen as well. There are many types of diseases that can affect the liver and its functions. Objectives: The main objective of this expert system (...) is to assist doctors in detecting Hepatitis diseases. Methods: In this paper we will implement an expert system using SL5 Object programming language so that it diagnoses the patient's condition and provides the appropriate solution. Results: This program was evaluated and tested by a group of doctors and patients with liver problems and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for doctors; to diagnosing liver diseases and treatment it whenever possible is given. (shrink)

The article studies the impact of Fintech on entrepreneurship in Arabic region by using Crowdfunding platforms as the field of study. The article focuses on Arabic Crowdfunding platforms. The population of (12) platforms consist of: individuals, entrepreneurs, investors, employees at Crowdfunding platforms. Descriptive and quantitative approach used in this article, and a questionnaire used as a tool to collect primary data. The results indicate an impact for Fintech on entrepreneurship in general and obvious obstacles to use it widely in Arabic (...) region cause of legislations or e-payments. The article recommended more awareness for innovative products and services such as Fintech, Crowdfunding and adopting the culture of e-business models. Also the article promoting the process of developing regulations that organize e-business models, especially Fintech and Crowdfunding, the use of modern communication technology to serve the development of society, more interest to innovation and creativity as a key factor for entrepreneurial success. (shrink)

Agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Preceding instrument vision methods established for selective weeding have confronted with major challenges for trustworthy and precise weed recognition. In this paper, (...) plant seedlings classification approach is presented with a dataset that contains approximately 5,000 images with 960 unique plants that belong to 12 species at a few developing phases. 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 seedling 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 99.48% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

A cherry is the fruit of many plants of the genus Prunus, and is a fleshy drupe (stone fruit), Michigan's Northwest Lower Peninsula is the largest producer of tart cherries in the United States. In fact, grow 75% of the country's variety of mighty Montmorency cherries. We use these Ruby Red Morsels of Joy in over 200 cherry products like Salsas, Chocolate Covered Cherries, Cherry Nut Mixes, and much more. Cherry fruits are rich in vitamins and minerals, and it is (...) one of the natural sources that can supply the body with abundant amounts of potassium and energy. There are two types of sour cherries, sour or tart, with a little acidity, and the red cherries have a blackish color. Cherry blossoms are very beautiful and in Japan cherry trees are celebrated in bloom. In this paper, machine learning based approach is presented for identifying type Cherry with a dataset that contains 7,002 images use 3,444 images for training, 2,410 images for validation and 1,148 images for testing. A deep learning technique that extensively applied to image recognition was used. 70% from image for training and 30% from image for validation. Our trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

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. (shrink)

The aim of the research is to identify the relationship between the performance criteria and the achievement of the objectives of supervision which is represented in the performance of the job at the Islamic University in Gaza Strip. To achieve the objectives of the research, the researchers used the descriptive analytical approach to collect information. The questionnaire consisted of (22) paragraphs 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, 276 responses were retrieved with a return rate of 88.1%. The SPSS program was used to enter, process, and analyze the data. The results of the study showed a positive relationship between the performance criteria and the achievement of the control objectives represented by the job performance in the Islamic University from the point of view of the members (senior management, faculty and their assistants and the administrative board). The researchers also recommended a number of recommendations, including the provision of an appropriate level of control system components today through the continuous updating and development of performance standards and the need to provide the necessary physical and financial resources to continue the development and achievement within the university. Expand the development of technology in the various activities of the university through the construction of a complete and integrated system to support the control systems in the university to suit its size. The researchers also recommended the follow-up, review of the performance standards and work to modify them in line with the mission of the university and the goals that the university seeks to reach. (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: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.62 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method is (...) suitable for the evaluation of car acceptability forecasting, can also be extended to all other areas. (shrink)

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

Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...) potatoes, which can be classified into a number of categories based on the cooked texture and ingredient functionality. Using a public dataset of 2400 images of potatoes, we trained a deep convolutional neural network to identify 4 types (Red, Red Washed, Sweet, and White).The trained model achieved an accuracy of 99.5% of test set, demonstrating the feasibility of this approach. (shrink)

Abstract: Small Blue Round Cell Tumors (SBRCTs) are a heterogeneous group of tumors that are difficult to diagnose because of overlapping morphologic, immunehistochemical, and clinical features. About two-thirds of EWSR1-negative SBRCTs are associated with CIC-DUX4-related fusions, whereas another small subset shows BCOR-CCNB3 X-chromosomal par acentric inversion. In this paper, we propose an ANN model to Classify and Predict SBRCTs Cancers. The accuracy of the classification reached 100%.

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)

Forest fires are a major environmental issue, creating economical and ecological damage while endangering human lives. Fast detection is a key element for controlling such phenomenon. To achieve this, one alternative is to use automatic tools based on local sensors, such as provided by meteorological stations. In effect, meteorological conditions (e.g. temperature, wind) are known to influence forest fires and several fire indexes, such as the forest Fire Weather Index (FWI), use such data. In this work, we explore a Just (...) Neural Network (JNN) approach to predict the burned area of forest fires were tested on recent real-world data collected from the northeast region of Portugal. The best accuracy we achieved was 98.75 percent. Such knowledge is particularly useful for improving firefighting resource management (e.g. prioritizing targets for air tankers and ground crews). (shrink)

In this paper we describe a Artificial Neural Network model of children's development on the balance scale task. In balance scale experiments, the child is asked to predict the outcome of placing certain numbers of equal weights at various distances to the left or right of a fulcrum. Both stage progressions and information salience effects have been found with children on this task. Artificial Neural Network provided better fits to these human data than did previous models, whether rule-based or connectionist. (...) The ANN network model was used to generate a variety of novel predictions for psychological research. The dataset was collected from UCI Machine learning repository. The model was trained and validated using Just Neural Network Tool. The accuracy rate was 93%. (shrink)

Abstract: Predication is an application of Artificial Neural Network (ANN). It is a supervised learning due to predefined input and output attributes. Multi-Layer ANN model is used for training, validating, and testing of the data. In this paper, Multi-Layer ANN model was used to train and test the mushroom dataset to predict whether it is edible or poisonous. The Mushrooms dataset was prepared for training, 8124 instances were used for the training. JustNN software was used to training and validating the (...) data. The most important attributes of the data set were identified, and the accuracy of the predication of whether Mushroom is edible or Poisonous was 99.25%. (shrink)

ASP.net is one of the most widely used languages in web developing of its many advantages, so there are many lessons that explain its basics, so it should be an intelligent tutoring system that offers lessons and exercises for this language.why tutoring system? Simply because it is one-one teacher, adapts with all the individual differences of students, begins gradually with students from easier to harder level, save time for teacher and student, the student is not ashamed to make mistakes, and (...) more. Therefore, in this paper, we describe the design of an Intelligent Tutoring System for teaching ASP.net to help students learn ASP.net easily and smoothly. Tutor provides beginner level in ASP.net. Finally, we evaluated our tutor and the results were excellent by students and teacher. (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: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method is (...) suitable for the evaluation of car acceptability forecasting, can also be extended to all other areas. (shrink)

Avocado is the fruit of the avocado tree, scientifically known as Persia Americana. This fruit is prized for its high nutrient value and is added to various dishes due to its good flavor and rich texture. It is the main ingredient in guacamole. These days, the avocado has become an incredibly popular food among health-conscious individuals. It’s often referred to as a superfood, which is not surprising given its health properties. Using a public dataset of 1,234 images of Avocado collected (...) under controlled conditions, we trained a deep convolutional neural network to identify tow type of avocado. The trained model achieved an accuracy of 99.84% on a held-out test set, demonstrating the feasibility of this approach. Overall, the approach of training deep learning models on increasingly large and publicly available image datasets present a clear path toward types of avocado. (shrink)

Abstract: A grape is a fruit, botanically a berry, of the deciduous woody vines of the flowering plant genus Vitis. it can be eaten fresh or they can be used for making jam, grape juice, jelly, grape seed extract, raisins, and grape seed oil. Grapes are a nonclimacteric type of fruit, generally occurring in clusters. Grapes are a type of fruit that grow in clusters of 15 to 300, and can be crimson, black, dark blue, yellow, green, orange, and pink. (...) "White" grapes are actually green in color, and are evolutionarily derived from the purple grape. Mutations in two regulatory genes of white grapes turn off production of anthocyanins, which are responsible for the color of purple grapes. Grapes are typically an ellipsoid shape resembling a prolate spheroid. In this paper, machine learning based approach is presented for identifying type Grapes with a dataset that contains 4,565 images use 2,393 images for training, 1,026 images for validation and 1,146 images for testing. A deep learning technique that extensively applied to image recognition was used. use 70% from image for training and 30% from image for validation. Our trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

Abstract: In this paper an Artificial Neural Network (ANN) model, was developed and tested for predicting the category of an animal. There is a number of factors that influence the classification of animals. Such as the existence of hair/ feather, if the animal gives birth or spawns, it is airborne, aquatic, predator, toothed, backboned, venomous, has –fins, has-tail, cat-sized, and domestic. They were then used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was (...) developed and trained, using data set, which its title is “Zoo Data Set” and was obtained from Machine Learning Repository, and its created by Richard Forsyth. Test data evaluation shows that the ANN model is able to correctly predict the animal category with 100% accuracy. (shrink)

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

In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was developed and tested. Taking patients’ tests, a number of information gained that influence the classification of the tumor. Such information as age, sex, histologic-type, degree-of-diffe, status of bone, bone-marrow, lung, pleura, peritoneum, liver, brain, skin, neck, supraclavicular, axillar, mediastinum, and abdominal. They were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was established and trained using (...) data set which its title is “primary tumor” and was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia Test data evaluation shows that the ANN model is able to correctly predict the tumor category with 76.67 % accuracy. (shrink)

Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a (...) dataset for building energy performance. The main factors for input variables are: relative compactness, roof area, overall height, surface area, glazing are a, wall area, glazing area distribution of a building, orientation, and the output variables: heating and cooling loads of the building. The dataset used for training are the data published in the literature for various 768 residential buildings. The model was trained and validated, most important factors affecting heating load and cooling load are identified, and the accuracy for the validation was 99.60%. (shrink)

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

This paper aims at helping trainees to overcome the difficulties they face when dealing with Arduino platform by describing the design of a desktop based intelligent tutoring system. The main idea of this system is a systematic introduction into the concept of Arduino platform. The system shows the circuit boards of Arduino that can be purchased at low cost or assembled from freely-available plans; and an open-source development environment and library for writing code to control the board topic of Arduino (...) platform. The system is adaptive with the trainee’s individual progress. The system functions as a special tutor who deals with trainees according to their levels and skills. Evaluation of the system has been applied on professional and unprofessional trainees in this field and the results were good. (shrink)

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

: Crop diseases are a key danger for food security, but their speedy identification still difficult in many portions of the world because of the lack of the essential infrastructure. The mixture of increasing worldwide smartphone dispersion and current advances in computer vision made conceivable by deep learning has cemented the way for smartphone-assisted disease identification. Using a public dataset of 9000 images of infected and healthy Tomato leaves collected under controlled conditions, we trained a deep convolutional neural network to (...) identify 5 diseases. The trained model achieved an accuracy of 99.84% on a held-out test set, demonstrating the feasibility of this approach. Overall, the approach of training deep learning models on increasingly large and publicly available image dataset presents a clear path toward smartphone-assisted crop disease diagnosis on a massive global scale. (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)

To automate examination of massive amounts of sequence data for biological function, it is important to computerize interpretation based on empirical knowledge of sequence-function relationships. For this purpose, we have been constructing an Artificial Neural Network (ANN) by organizing various experimental and computational observations as a collection ANN models. Here we propose an ANN model which utilizes the Dataset for UCI Machine Learning Repository, for predicting localization sites of proteins. We collected data for 336 proteins with known localization sites and (...) divided them into training data and validating data. It was found that the accuracy rate for predicting Protein Localization Sites in Cells is 92.11%. This Indicates that Artificial Neural Network approach is powerful and flexible enough to be used in Protein Localization Sites prediction. (shrink)

Abstract: Apple is a plant species that follows the apple genus, which is a fruit because it contains seeds of the pink family. It is one of the most fruit trees in terms of agriculture. The apple tree is small in length from 3 to 12 meters. Several recent studies have shown many health benefits of apples. It helps with the strengthening of the brain, heart, and stomach. It is used in the treatment of joint pain and limberness. It is (...) opposite. It stops vomiting. It goes to dyspnea. It corrects the liver, purifies the blood of toxins, strengthens the heart muscle, and kills the abdominal dentures. Which are richer in cell nutrition and development, bone strengthening and neuronal regeneration is an important source of detoxification, viruses, bacteria, and microbes in the body. In this paper, machine learning based approach is presented for identifying type of Apple with a dataset that contains 8,554 images. We used 4,488 images for training, 1,928 images for validation and 2,138 images for testing. A deep learning technique that extensively applied to image recognition was used. 70% from images were used for training and 30% from image for validation. Our trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

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. (shrink)

Abstract: Peach, (Prunus persica), fruit tree of the rose family (Rosaceae), grown throughout the warmer temperate regions of both the Northern and Southern hemispheres. Peaches are widely eaten fresh and are also baked in pies and cobblers; canned peaches are a staple commodity in many regions. Yellow-fleshed varieties are especially rich in vitamin A. Peach trees are relatively short-lived as compared with some other fruit trees. In some regions orchards are replanted after 8 to 10 years, while in others trees (...) may produce satisfactorily for 20 to 25 years or more, depending upon their resistance to diseases, pests, and winter damage. in the body.[1] In this paper, machine learning based approach is presented for identifying type peach with a dataset that contains 2,306 images use 1,212 images for training, 520 images for validation and 574 images for testing. A deep learning technique that extensively applied to image recognition was used. use 70% from image for training and 30% from image for validation. Our trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

A neural network exploits the non-linearity of a problem to define a set of desired inputs. Neural networks are important in realizing a better way for classification in machine learning and finds application in various fields such as data mining, pattern recognition, forensics etc. In this paper, our focus is to classify of patient records obtained from clinical data. Feature selection is a supervised method that attempts to select a subset of the predictor features based on the information gain. The (...) Lymphography dataset comprises of 18 attributes and 148 instances with the class label having four distinct values. This paper highlights the accuracy of EasyNN backbrapagation calssification algorithm in classifying predictor attributes and highlights its performance on Lymphography dataset. The accuracy we have reached is 97.78 percent in classification accuracy with the predictor feature. (shrink)

The objective of the study was to identify the reality of the lean management in Jawwal from the point of view of its employees, and to indicate the availability of lean management tools (organization of the work site, continuous improvement, standard work, multi-function workers, Six Sigma) The study used the analytical descriptive method. The study was applied to Jawwal Company in Gaza Governorate - North Branch. The number of employees was (85) employees. The questionnaire was used as a tool for (...) study. Comprehensive method and (75) questionnaire were recovery at a rate (96%). The study concluded with a number of results, the most important of which were the application of lean management dimensions at Jawwal, and the dimensions that received the least attention from the perspective of the employees of Jawwal (Six Sigma and Multifunctional Workers). There are also no differences between the opinions of employees on the availability of lean management dimensions in terms of (type, qualification, and years of service). The most important recommendations were to increase interest and expand the use of lean management tools because they have a clear impact on innovation, by focusing on tools that have the greatest impact on the achievement of the elements of creativity (continuous improvement, standard work, six Sigma). (shrink)

We proposed an Artificial Neural Network (ANN) in this paper for predicting the rate category of movies. A dataset used obtained from UCI repository created for research purposes. Our ANN prediction model was developed and validated; validation results showed that the ANN model is able to 92.19% accurately predict the category of movies’ rate.

Background: With the coming of the Industrial Revolution, the levels of pollution grow significantly. This Technological development contributed to the worsening of shortness breath problems in great shape. especially in infants and children. There are many shortness breath diseases that infants and children face in their lives. Shortness of breath is one of a very serious symptom in children and infants and should never be ignored. Objectives: Along these lines, the main goal of this expert system is to help physician (...) in diagnosing and describe some common causes of shortness of breath in infants and children by diagnosing their cases through our expert system. Moreover, this system which we are presenting will give patient the appropriate diagnosis of disease and the treatment required. Methods: In this paper the strategy of the expert system for diagnosing a number of the existed shortness of breath in infants and children diseases such as (Asthma , Bronchiolitis, Viral Pneumonia, cough, Shortness of breath' dyspnea ', Epiglottitis, Croup, ABSCESS in the tonsil 'peritonsillar abscess', Bronchitis, Viral Bronchitis, Wheezing, sudden infant death syndrome 'SIDS' ) is introduced, an overview about the shortness of breath in children and infants diseases are delineated, the cause of diseases are sketched and the treatment of disease whenever conceivable is given . SL5 Object Expert System language was utilized for designing and implementing the proposed expert system. Results: The proposed shortness of breath in children and infants diseases diagnosis expert system was estimated by Medical students and they were satisfied with its result. Conclusions: The Proposed expert system is very useful for Respiratory physician, pediatrician, recently graduated physician, and for children's parents with shortness of breath problem. (shrink)

The aim of the study was to identify the lean management and its impact on the achievement of creativity among the employees of Jawwal, and to indicate the availability of flexible management tools (organization of the work site, continuous improvement, standard work, multi-function workers, Six Sigma), and to determine their ability to achieve creativity in its different dimensions (problem solving and decision making, changeability, accept risk, encourage creativity). The researchers used the analytical descriptive method. The study was applied to the (...) Jawwal Company in Gaza Governorate - the North Branch (85 employees). The questionnaire was used as a tool for study, and the comprehensive inventory method was used. (75) Questionnaires were recovered with a recovery rate of (96%). The study concluded with a number of results, the most important of which is the impact of the flexible management tools and the achievement of the elements of creativity through: (standard work, multi-function workers, and six sigma). There are also no statistical differences between the opinions of the sample of the study due to the graceful management and creativity in Jawwal Company in terms of (Gender, qualification and years of service). The researchers recommend a number of recommendations, the most important of which are: Increase interest and expansion in the use of lean management tools because they have a clear impact on the achievement of elements of creativity, focusing on tools that have the greatest impact in achieving the elements of creativity (continuous improvement, standard work, Six Sigma). (shrink)