Computer Science علم الحاسوب

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3D Environment Based on Desktop Metaphor A Usability Study
(AL-Quds University, 2004-12-30) سوزان جميل حلمي سلطان.; Suzanne Jamil Hilmi Sultan; غسان القيمري; Rashid Jayousi; Yousef Asad Hassouneh
3D Environment Based on Desktop Metaphor: A Usability Study
(AL-Quds University, 2004-12-30) سوزان جميل سلطان; suzanne jamil sultan; غسان القيمري; Rashid Jayousi; Yousef Asad Hassouneh
A smart Framework for identifying the training needs of Palestinian Teachers using Data Mining Techniques
(Al-Quds University, 2020-12-17) Nidaa “Mohammad Ghazi” Hasan Farhaneh; نداء "محمد غازي" حسن فرحانه
This study aims to establish a Smart Framework that works as a system based on searching for data related to teachers of the Arabic Language, Science, Mathematics and English Language studies within specific criteria and variables, to determine the training needs by predictions through framework using data mining AI algorithm, which is necessary to enhance teacher’s performance in the classroom environment. The researcher took a sample of public school teachers in the academic year 2014/2015 AD and determined the following variables: academic qualification, specialization, stages that he teaches, an annual calendar, training courses, and their number of hours in content areas and teaching methods. The search was conducted using Angular as a JavaScript tool for the client-side (FE) in the framework and the spring boot as a server-side (BE) connected to a database MySQL and Flask Python server which is responsible for machine learning of deep neural network (DNN) as (AI) algorithm, all servers connected via (API) in Jhipster environment. Results of applying the prototype showed high effectiveness in identifying training needs to improve teachers' performance in an organized and interactive way. The researcher recommends the Ministry of Education to use this intelligent technology tool for its effectiveness in predicting needed training courses for a teacher to enhance his performance, and also to organize teacher’s data in an oriented w
An Aggregate Scalable Scheme for Expanding the Crossbar Switch Network; Design and Performance Analysis
(AL-Quds University, 2004-09-05) أحلام محمد درويش قريع; Ahlam Mohammed Darwish Qrie; عبدالكريم عياد; Rashid JAYOUSI; Luai MALHIS
New computer network topology, called Penta-S, is simulated. This network is built of cross bar switch modules. Each module connects 32 computer nodes. Each node has two ports, one connects the node to the crossbar switch module and the other connects the node to a correspondent client node in another module through a shuffle link. The performance of this network is simulated under various network sizes, packet lengths and loads. The results are compared with those obtained from Macramé project for Clos multistage interconnection network and 2D-Grid network. The throughput of Penta-S falls between the throughput of Clos and the throughput of 2D-Grid networks. The maximum throughput of Penta-S was obtained at packet length of 128 bytes. Also the throughput grows linearly with the network size. On the opposite of Clos and 2D-Grid networks, the per-node throughput of Penta-S improves as the network size grows. The per-packet latency proved to be better than that of Clos network for large packet lengths and high loads. Also the packet latency proved to be nearly constant against various loads. The cost-efficiency of Penta-S proved to be better than those of 2D-Grid and Clos networks for large number of nodes (>200 nodes in the case of 2D-Grid and >350 nodes in the case of Clos).On the opposite of other networks, the cost-efficiency of Penta-S grows as its size grows. So this topology suits large networks and high traffic loads.
Analysis Study of Classification Techniques for Web Services
(AL-Quds University, 2017-10-07) دعاء وليد عطا فرعون; Duaa Waleed Ata Faroun; رشيد الجيوسي; Nidal Kafri; Derar Eleyan
Analytical study of E-Learning Platforms
(AL-Quds University, 2007-04-03) ماجد احمد عبد الله أبو ريان; Majed Ahmed Abdallah Abu Rayyan; رشيد جيوسي; نضال; يوسف ابو زر
Anomaly-Based Network Intrusion Detection System Using Deep Neural Networks (ANIDS-DNN)
(Al-Quds University, 2023-01-08) Sharif Mohammed Ahmad Yasin; شريف محمد احمد ياسين
تقوم أنظمة الكشف عن اختراق الشبكات (NIDS) بمراقبة وتحليل حركة مرور الشبكة الواردة والصادرة وإصدار الإنذارات عند اكتشاف عمليات اقتحام أو أنشطة ضارة حيث تعتبر هذه الأنظمة خط الدفاع الثاني بعد جدار الحماية. في السنوات الأخيرة، حفز العدد المتزايد من الهجمات السيبرانية الحاجة إلى تطوير أنظمة آلية وذكية للكشف عن اختراق الشبكة والتي تتعلم السلوك الطبيعي لحركة مرور الشبكة (ANIDS)، وبالتالي فإن حركة المرور التي تنحرف عن المعتاد تعتبر شاذة أو ضارة. على الرغم من أن أنظمة كشف التسلل المستندة إلى حركة المرور غير المعتادة أفضل من أنظمة كشف التسلل القائمة على التوقيع في اكتشاف هجمات اليوم الصفري أو غير المعروفة، إلا أنها تولد معدل إنذار خاطئ مرتفعًا إذا تم تغيير السلوك الطبيعي للشبكة. لحل المشكلات المذكورة أعلاه، تقترح هذه الأطروحة نموذج ANIDS لاكتشاف الهجمات غير المعروفة او هجمات اليوم الصفري في تدفقات الشبكة باستخدام تغذية الشبكات العصبية العميقة الى الامام كخوارزمية تصنيف. يأخذ النموذج ميزات NetFlow المجمعة كمدخلات وبعد إعداد البيانات، تصنف خوارزمية التعلم العميق كل اتصال بالشبكة على أنه عادي أو شاذ. من أجل تحسين دقة الكشف عن أنماط الهجوم التي لها ترددات تعتمد على الوقت مثل هجوم nerisbotnet، تم تصميم ثلاث ميزات إدخال جديدة وهي sa_nsessions_T و da_nsessions_T و sa_da_nsessions_T عن طريق تجميع التدفقات بناءً على عنوان المصدر وعنوان الوجهة وسمات الطابع الزمني باستخدام نافذة زمنية مدتها دقيقة واحدة. وبعد المعالجة المسبقة لميزات المدخلات، يتم تحديد أهم 45 ميزة إدخال. علاوة على ذلك، يتم تعلم معلمات النموذج باستخدام عدد كبير من التدفقات ذات التصنيف متعدد الفئات من مجموعة بيانات UGR’16 العامة [32]. تم تحسين المعلمات الفائقة للنموذج للحصول على أفضل أداء من حيث الدقة ومعدل الاكتشاف والوقت اللازم لتدريب النموذج المقترح. أكدت النتائج التجريبية الأداء العالي للنموذج المقترح عند اختباره على تدفقات الشبكة غير المرئية من مجموعة بيانات UGR’16. تتكون بنية الشبكة المثلى من طبقة إدخال واحدة وثلاث طبقات مخفية وطبقة إخراج واحدة. حقق النموذج دقة 99.773٪، ومعدل موجب خاطئ أقل من 1٪، ومساحة تحت منحنى خاصية تشغيل المستقبل (ROC-AUC) تبلغ 0.999915. أيضًا، تبلغ دقة الكشف للمصنف متعدد الفئات 99.58٪ ومعدل الكشف لجميع الفئات الفردية أعلى من 99٪ باستثناء هجوم NerisBotNet حيث يبلغ معدل الكشف 94.70٪. عند مقارنة النموذج المقترح بالنماذج الحديثة الأخرى في الأدبيات [33]، [52]، والتي تم تقييمها على نفس مجموعة بيانات UGR’16، تظهر النتائج التجريبية أن النموذج المقترح يتفوق على النماذج الأخرى من حيث معدل الاكتشاف والدقة.
Application–Based Statistical Approach for Identifying Appropriate Queuing Model
(AL-Quds University, 2015-05-14) نعيمه 'محمد سالم' صالح حرباوي; Naimeh Mohammad Salem Saleh Hirbawi; بديع سرطاوي; رائد الزغل; اسامه سلامه
Queuing theory is a mathematical study of queues or waiting lines. It is used to model many systems in different fields in our life, whether simple or complex systems. The key idea in queuing theory of a mathematical model is to improve performance and productivity of the applications. Queuing models are constructed in order to compute the performance measures for the applications and to predict the waiting times and queue lengths. This thesis is depended on previous papers of queuing theory for varies application which analyze the behavior of these applications and shows how to calculate the entire queuing statistic determined by measures of variability (mean, variance and coefficient of variance) for variety of queuing systems in order to define the appropriate queuing model. Computer simulation is an easy powerful tool to estimate approximately the proper queuing model and evaluate the performance measures for the applications. This thesis presents a new simulation model for defining the appropriate models for the applications and identifying the variables parameters that affect their performance measures. It depends on values of mean, variance and coefficient of the real applications, comparing them to the values for characteristics of the queuing model, then according to the comparison the appropriate queuing model is approximately identified.The simulation model will measure the effectiveness performance of queuing models A/B/1 where A is inter arrival distribution, B is the service time distributions of the type Exponential, Erlang, Deterministic and Hyper-exponential. The effectiveness performance of queuing model are: *L : The expected number of arrivals in the system. *Lq : The expected number of arrivals in the queue. *W : The expected time required a customer to spend in the system. *Wq : The expected time required a customer to spend in Queue. *U : the server utilization.
Arabic Alphabet Deaf Sign Gestures Recognition Based on Deep Machine Learning Methods
(AL-Quds University, 2019-07-13) عهود عادل سلامة الدرابيع; Ohood Adel Salameh Darabee; عبد الله كمال; بديع سرطاوي; احمد حساسنة
Automatic Matching Engine: Towards Enhanced Finding of Jobs & Learning Opportunities
(AL-Quds University, 2016-10-20) يوسف مشهور ابراهيم صباح; Yousef Mashhour Ibrahim Sabbah; جاد النجار; Dr. Badie Sartawi; Dr. Ahmed Ewais
Benchmark for Tuning Metaheuristic Optimization Technique to Optimize Traffic Light Signals Timing
(AL-Quds University, 2015-12-10) رامي كمال عزت ابوشهاب; Rami Kamal Izzat Abu Shehab; بديع سرطاوي; Baker Abdalhaq; رشيد جيوسي; Emad Barhoumi
Traffic congestion at intersections is an international problem in the cities. This problem causes more waiting time, air pollution, petrol consumption, stress of people and healthy problems. Against this background, this research presents a benchmark iterative approach for optimal use of the metaheuristic optimization techniques to optimize the traffic light signals timing problem. A good control of the traffic light signals timing on road networks may help in solving the traffic congestion problems. The aim of this research is to identify the most suitable metaheuristic optimization technique to optimize the traffic light signals timing problem, thus reducing average travel time (ATT) for each vehicle, waiting time, petrol consumption by vehicles and air pollution to the lowest possible level/degree. The central part of Nablus road network has a huge traffic congestion at the traffic light signals. It was selected as a research case study and was represented by the SUMO simulator. The researcher used a random algorithm and three different metaheuristic optimization techniques: three types of Genetic Algorithm (GA), Particle Swarm Algorithm (PS) and five types of Tabu Search Algorithm (TS). Parameters in each metaheuristic algorithm affect the efficiency of the algorithm in finding the optimal solutions. The best values of these parameters are difficult to be determined; their values were assumed in the previous traffic light signals timing optimization research. The efficiency of the metaheuristic algorithm cannot be ascertained of being good or bad. Therefore, the values of these parameters need a tuning process but this cannot be done by using SUMO simulator because of its heavy computation. The researcher used a benchmark iterative approach to tune the values of them etaheuristic algorithm parameters by using a benchmark function. The chosen function has similar characteristics to the traffic light signals timing problem. Then, through the use of this approach, the researcher arrived at the optimal use of the metaheuristic optimization algorithms to optimize traffic light signals timing problem. The efficiency of each metaheuristic optimization algorithm, tested in this research, is in finding the optimal or near optimal solution after using the benchmark iterative approach. The results of metaheuristic optimization algorithm improved at some values of the tuned parameters. The researcher validated the research results by comparing average results of the metaheuristic algorithms, used in solving the traffic light signals optimization problem after using benchmark iterative approach, with the average results of the same metaheuristic algorithms used before using the benchmark iterative approach; they were also compared with the results of Webster, HCM methods and SYNCHRO simulator. In the light of these study findings, the researcher recommends trying the benchmark iterative approach to get ore efficient solutions which are very close to the optimal solution for the traffic light signals timing optimization problem and many complex practical optimization problems that we face in real life.
Comparative study on feature selection and ensemble methods for sentiment analysis classification
(AL-quds University, 2020-06-10) Zahir Mohammad Adnan Younis; زاهر "محمد عدنان" يونس
People use the Web and social media to express their opinions and comments on various topics and posts generating huge amounts of data. Hence, comes the necessity to analyze this large amount of text regarding a certain subject and figuring out what people think of it. The interest and necessity of this analysis is continuously rising in many fields, such as politics, marketing, entertainment, sports, etc., to figure out people opinions, thinking, interests, preferences, and trends. Consequently, analysis, classification and clustering of this huge amount of text data regarding certain subjects became an interest of a vast number of researchers and beneficiaries. This analysis of text data content is known as sentiment analysis. Sentiment Analysis (SA) is a text-mining field that computationally treats and analyses these sentiments (opinions, thinks, subjectivity, interests, preferences, etc.,.) of available text. SA aims to classify expressions in a text as positive, negative or neutral opinion towards the subject of interest. The main objective of this research is to carry out a comparative study on the accuracy and performance of feature selection and ensemble methods for SA classification. The comparison was carried out using different combinations of classification algorithms for classifying text to being either positive or negative. During the comparison of the algorithms and methods, the results showed that better accuracy can be achieved based on the used feature selection method (i.e., statistical, wrapper, or embedded). Additionally, it showed which feature selection method outperforms and is more suitable than other methods for the type of data and classification algorithms. Furthermore, when using combined ensemble methods (Bagging, Boosting, Stacking and Vote) performed better than using a single classifier by means of accuracy. Moreover, merging feature subsets selected by embedded method improved classification accuracy. Finally, tuning the parameters of feature selection methods improved the classification accuracy and reduced the time needed to select feature subsets. Particularly, the results showed that accuracy depends on the feature selection method, ensemble methods, number of selected features, type of classifier, and tuning parameters of the algorithms used. A high accuracy of up to 99.85% was achieved by merging features of two embedded methods when using stacking ensemble method. Also, a high accuracy of 99.5% was achieved by tuning parameters in stacking method, and it reached 99.95% and iv 100% by tuning parameters in SVMAttributeEval method using statistical and machine learning approaches, respectively. Furthermore, tuning algorithms' parameters reduced the time needed to select feature subsets.
Comparison of Data Mining and Statistical Techniques for Prediction Model
(AL-Quds University, 2012-05-10) امجد عبد المنعم محمود حرب; AMJAD A. M. HARB; رشيد الجيوسي; Nidal Kafri; Yousef Abuzir
The aim of this research is to perform a comparison study between statistical and data mining modeling techniques. These techniques are statistical Logistic Regression, data mining Decision Tree and data mining Neural Network. The performance of these prediction techniques were measured and compared in terms of measuring the overall prediction accuracy percentage agreement for each technique and the models were trained using eight different training datasets samples drawn using two different sampling techniques. The effect of the dependent variable values distribution in the training dataset on the overall prediction percent and on the prediction accuracy of individual “0” and “1” values of the dependent variable values was also experimented. For a given data set, the results shows that the performance of the three techniques were comparable in general with small outperformance for the Neural Network. An affecting factor that makes the percent prediction accuracy varied is the dependent variable values distribution in the training dataset, distribution of “0” and “1”. The results showed that, for all the three techniques, the overall prediction accuracy percentage agreement was high when the dependent variable values distribution ratio in the training data was greater than 1:1 but at the same time they, the techniques, fails to predict the individual dependent variable values successfully or in acceptable prediction percent. If the individual dependent variable values needed to be predicted comparably, then the dependent variable values distribution ratio in the training data should be exactly 1:1.
A Comparison Study on the Performance of Different Applications using MANET Routing Protocols under Various Circumstances
(AL-Quds University, 2015-03-15) شذى داود حسين نجم; Shatha Dawod Husien Nijim; د. نضال الكفري; Dr. Raed Al-Zagal; د. أحمد سعدة
Mobile adhoc network is a collection of mobile devices that communicate amongst each other using message passing to collaborate in a wireless medium, without any centralized management; each device acts as a router, sends and receive packets. Nodes can move freely and can set itself in any adhoc network. Adhoc networks are widely use in the absence of the wired network infrastructure. Quality of service of routing in ad hoc networks is an important and complicated issue with a changing topology. In this work we carried out a comparison study in a simulation scenarios on the performance of different routing protocols i.e., proactive and reactive, with different standard applications such as FTP, HTTP and database under various circumstances by means of network size, load, and speed of nodes. As a conclusion of this study, results show when measuring performance of delay and throughput of FTP, HTTP and Database traffic, delay and throughput metrics, using AODV, DSR, OLSR routing protocols, under 10, 50 and 100 nodes with spee of 10, 30 m/s. When using DSR routing protocol it showed the worst results under various network size and speed between other protocols, while when using AODV routing protocol it performed in a better way in which it showed a good performance in small and medium network size. OLSR routing protocol performed the best to be used in all network size especially in large network size.
Consolidated Ranking and Recommendation Framework for Learning Objects Based on Usage Data
(AL-Quds University, 2013-05-10) بهاء حمزة محمد هرشه; Baha Hamzah Mohammad Harasheh; جاد النجار; Raid Zaghal; Derar Eleyan
Customize Social Network Analysis for Telecommunications Companies
(AL-Quds University, 2017-07-05) اكثم فهيم عقل صوان; aktham faheem aqel sawan; رشيد الجيوسي; Dr. Nidal Kafri; Dr.Yousef Abu Zir
Social Network Analysis (SNA) is created to analyze social network data. Therefore, the main companies in the data mining filed (such as IBM, SAS, R and python) have created their own SNA algorithms. The aim of this research is to create customized SNA algorithm for telecom companies because the current algorithms were not designed just for the telecom networks, in addition when current algorithms were used for telecom many high value customer not include in final result plus results coverage just 55% from input customers, so in the new algorithm relation strength and extenders were used to enhance final results 300 million records that belong to around 4 million customers in the last three were collected from (Jawwal Telecommunications Company) as case study. The current algorithms and the new algorithm were used the same data. In this research six experiments were applied based on call duration, call count and ratio between call duration and call count, in addition two groups size were used (15 and 20), Oracle Sql-PL/SQL was used to implement algorithm. The results that approved by Jawwal were based on parameters that used in experiment number six (ratio between calls count and call duration with group size till 20 customer), it has increased the coverage of NW to be 75.9% instead of around 55% for current algorithms, in addition all high valued customers has included in results for the new algorithm, moreover algorithm have applied in Mobily in Saudi Arabia and the same positive results have been found same as Jawwal. New novelty ideas have created in this research such as, extenders this type of customers used for customer who is influencer in one group and follower in the other group. Also relation strength used to create groups and assign followers to their most related influencer; furthermore, Super Group used as new layer to connect related groups in one group and find super influencer.
Data Injection in ICMP Protocol Vulnerability and Exploitation
(Al-quds University, 2021-01-05) Eyad Fatih Ali Refai; اياد فتيح علي الرفاعي
This thesis and scientific research aim to prove and review the possibility of injecting the ICMP protocol packets with encrypted or unencrypted data and passing it to another network, external or internal receiver. We will also see the potential and ability of modern generations in the network structure to follow up, monitor, or block such incorrect behavior due to this protocol’s inefficient use. As ICMP is one of the critical protocols at work, this protocol’s exploitation began to threaten networks and their components and enable their work and privacy. Cyber-attacks or electronic attacks in various forms are an old/new phenomenon that the world is experiencing. Still, it started to increase due to the considerable expansion of networks’ usage and their applications and systems, which poses a threat to these network administrators and employees. Different technologies have emerged to exploit the structure of building these networks to use their software components to carry out cyber-attacks. It affects systems such as blocking the service, disabling access, or electronic spying on packets and other forms. Our study problem has emerged after research and audit and through the work of the author at the Center for Combating Cyber Crime in Palestine. The need to combat this phenomenon is an essential part of understanding networks' general structure and how they and their components work. Thus, our study emerged in relation to leaking data and injecting data within a legal packet. We will perform several real experiments to prove our concept and then draw recommendations and conclusions. We will work on technical experiments to prove the validity of scientific research. It has already appeared to us that data can be injected into the packages, which may cause data to leak, and modification in the header of the packet. Also, this type of change shows the emergence of a new kind of cyber-attacks that may be caused by the ICMP package as many from cyber-attacks using these packages. تهدف هذه الرسالة والبحث العلمي الى اثبات واستعراض امكانية حقن حزمة البروتوكول ICMP ببيانات مشفره او غير مشفرة وتمريرها الى شبكة اخرى او مستقبل خارجي او داخلي، بالإضافة الى ذلك سنرى امكانية وقدرة الاجيال الحديثة في هيكلية الشبكات لمتابعة او رصد او حجب مثل هذا النوع من السلوك الغير صحيح للاستخدام الغير أمثل لهذا البروتوكول. حيث يعتبر بروتوكول ICMP من البروتوكولات ذات الاهمية في العمل وقد بدأ استغلال هذا البروتوكول في تشكيل تهديد وخطر على الشبكات ومكوناتها واتاحة عملها وخصوصيتها ايضا. تعتبر ظاهرة الهجمات السيبرانية او الهجمات الالكترونية بأشكالها المختلفة ظاهرة جديدة قديمة يعيشها العالم ولكن بدأت بالازدياد نتيجة التوسع الكبير في استخدام الشبكات وتطبيقاتها وانظمتها، مما يشكل خطراً على مديري هذه الشبكات والعاملين فيها. وقد ظهرت تقنيات مختلفة لاستغلال هيكلية بناء هذه الشبكات من حيث استغلال مكوناتها البرمجية في ارتكاب هجمات سيبرانية تؤثر على عمل الشبكات مثل حجب الخدمة، أو تعطيل الوصول، أو التجسس الالكتروني على الحزم، وغيرها من أشكال الخروقات الأمنية. إن تطور ادوات التقنية بشكلها الحالي قد يساهم ايضا في الوصول الى هجمات واستغلالها بشكل غير اخلاقي وسيؤثر ذلك على الصلاحيات الفنية الممنوحة للفنين في داخل اقسام العمل في مراكز البيانات المختلفة او الذين يعملون داخل اقسام ذات حساسية عالية ومعلومات حساسة. وسوف نجيب في هذه الدراسة عن العديد من التساؤلات والتي بطبيعتها ستخلق منهجية أمن المعلومات، بحيث أنها يمكن أن تضاف على لوائح وسياسات أمن المعلومات كقضايا جديدة ويكون لها وظائف جديده. لقد ظهرت المشكلة التي تعالجها هذه الدراسة بعد البحث والتدقيق، ومن خلال عملي في مركز مكافحة الجرائم السيبرانية في فلسطين، حيث تعتبر ضرورة مكافحة هذه الظواهر جزء مهم من فهم الهيكلية العامة للشبكات وطريقه عملها ومكوناتها، ومن هنا ظهرت مشكلة الدراسة الخاصة بنا التي تتعلق بتسريب بيانات وحقن بيانات داخل حزمة مهمة في العمل اليومي لمهندسي الشبكات والفنيين.ايضا ستطرح هذه الدراسة العديد من الاسئلة والمواضيع للبحث العلمي بحيث تطرح مسالة تطوير وانتاج برمجيات ومعدات تساهم في الحد او تتبع او حفظ السجلات والتقاط الحزم او مساعدة البحث الجنائي الالكتروني في حال تم الاستغلال او اجراءات التدقيق الدوري للأنظمة وسلامة مركز البيانات وسرية وخصوصية البيانات. ففي "الطب الشرعي" الالكتروني يمكن الاستفادة من الحزمة التي يتم التقاطها في تحليل سلوك الشبكة او البرمجيات ذات السلوك الضار، أو تمرير بيانات الى أطراف غير مخول لها للوصول الى المعلومات، أو الاتصالات العكسية، ومن ثم إيجاد حلول للمشاكل التي من الممكن أن تقع فيها الشبكات من خلال إحصاء كمية البيانات التي تمر عبر الشبكة مما يساعد في اكتشاف عمليات الدخول الغير مرخصة، واكتشاف الهجمات من نوع ) DoS ( و ) DDoS (، وتحليل بروتوكولات الشبكة وتنقيحها. سنعمل في هذا البحث على تجارب فنية لإثبات صحة البحث العلمي وقد ظهر لدينا بالفعل انه يمكن حقن بيانات داخل الحزم مما قد يسبب في تسريب البيانات ، والتعديل في ترويسة الحزمة ، وايضا يظهر هذا النوع من التعديل ظهور نوع جديد من الهجمات السيبرانية التي قد تتسبب بها حزمة ICMP كما العديد من الهجمات السيبرانية بإستخدام هذه الحزم .
Data Mining in E-Government: Design of Palestinian E-Government and Identifying Suitable Mining Model
(AL-Quds University, 2011-03-29) خلود عبدالحليم محمد طويل; KHOLOUD ABED HALIM NMOHAMMED TAWIL; بديع السرطاوي; رائد الزغل; رضوان طهبوب
Design Principles of Learning Management Systems
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DIHA : data integrity algorithm using hashing authentication
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