Ain Shams University, Faculty of Computer and Information ScienceInternational Journal of Intelligent Computing and Information Sciences1687-109X17420171001A SYSTEM FOR MANAGING ATTENDANCE OF ACADEMIC STAFF MEMBERS IN UNIVERSITY DEVELOPMENT PROGRAMS USING FACE RECOGNITION117770610.21608/ijicis.2018.7706ENWessamElSaidDepartment of Computer Teacher Prepration, Faculty of Specific Education, Mansoura University,
Mansoura, EgyptJournal Article20180603great development in all aspects of the life imposes new changes on various organizations. Since the academic institutions are not isolated from the real world events, they have sought to build an integrated strategy for developing their activities and services to keep pace with the new reality. One of the major development areas in the university sector is the improvement of the academic staff members’ skills on both the leadership and academic levels through a series of certified development programs. Until now, recording the members’ attendance in these programs depends on traditional manual methods which have many drawbacks. Therefore, the current study presents an automatic system based on face recognition technology to address these drawbacks.The proposed system includes five main steps: capturing member image, detecting member face, extracting facial features, comparing facial features and creating target reports. The system usefulness can be viewed form two major aspects.Aspect-1; is the accuracy rate in which proposed system achieved significant performance under ideal imaging conditions and achieved acceptable performance under un-ideal imaging conditions compared with some other systems in the same field. Aspect-2; is the cost rate in which the proposed system does not require an expensive settings, making it an appropriate choice for various educational institutions.Ain Shams University, Faculty of Computer and Information ScienceInternational Journal of Intelligent Computing and Information Sciences1687-109X17420171001Perfromance Analysis of aTree Routing Protocol for Cognitive Radio Network Under Impact of Different Primary User Activity Patterns.1930791210.21608/ijicis.2018.7912ENMHashemDepartment of information Systems,
Faculty of Computers and Information Sciences,
Ain Shams University,
Cairo, EgyptSBarakatDepartment of information Systems,
Faculty of Computers and Information Sciences,
Mansoura University,
Mansoura ,EgyptMAttaAllaDepartment of information Systems,
Faculty of Computers and Information Sciences,
Mansoura University,
Mansoura ,EgyptJournal Article20180607The mistakes in the spectrum management have drive to a problem of the scarcity of spectrum,<br />which can be solved through the use of Cognitive Radio (CR) technology. The main concept of CR<br />technology allows unauthorized users (secondary users (SUs))for using the spectrum resources for<br />communication without harm authorized users (primary users (PUs)).The traditional wireless networks,<br />the nodes are connected based on a centralized infrastructure. But in Cognitive Radio Ad Hoc Network<br />(CRAHN) Networks, mobile SUs nodes are connected to each other without a central infrastructure.<br />Routing in CRAHNs is an important and necessary process in CRAHNs. It faces many and various<br />challenges. These challenges include PUs intervention, frequently dynamic topology, energy<br />consumption problems, unavailable channels, and fragile connections between nodes. The our probased<br />routing protocol called A tree routing protocol for cognitive radio network (C-TRP) has utilized the tree<br />routing algorithm with a spectrum management module in one routing decision module. In this paper,<br />weevalute a performance of the tree routing protocol (C-TRP) under the influence of the different PUs<br />activity patterns with help of three performance metrics :hop count, the number of CR nodes and number<br />of available channels. The performance evaluation is evaluted using NS-2 simulator. Simulation results<br />confirm that C-TRP outperforms “spectrum-tree based on demand routing protocol for multi-hop<br />cognitive radio networks”(STOD-RP), and Cognitive Tree-based Routing(CTBR) in terms of packet<br />delivery ratio and causes less harmful interference to PR nodes, and also less end-to-end delay in all<br />primary radio nodes activity patterns.Ain Shams University, Faculty of Computer and Information ScienceInternational Journal of Intelligent Computing and Information Sciences1687-109X17420171001COMPARATIVE STUDY OF ROUTING PROTOCOLS FOR MOBILE AD HOC NETWORKS3143791310.21608/ijicis.2018.7913ENAdelEl-KabbanyHigher Technology Institute,HanafyAliComputers and Systems
Engineering Depart.,-Faculty of
Engineering, Minia University, El
Minia, EgyptAzizaHusseinComputers and Systems Eng. Dept.
Minia University, Minia, Egypt
2Electrical and Computer Eng. Dept.
Effat University, Jeddah, Saudi ArabiaBenTawfeekComputers and Systems
Engineering Depart.,-Faculty
of Engineering, Suze Canal
University, Suze Canal, EgyptJournal Article20180607Mobile Ad-hoc Network (MANET) is an infrastructure less and decentralized network<br />which need a robust dynamic routing protocol. Many routing protocols for such networks have been<br />proposed so far to find optimized routes from source to the destination and prominent among them are<br />Dynamic Source Routing (DSR), Ad-hoc On-Demand Distance Vector (AODV), and Destination-<br />Sequenced Distance Vector (DSDV) routing protocols. The performance comparison of these protocols<br />should be considered as the primary step towards the invention of a new routing protocol. This paper<br />presents a performance comparison of proactive and reactive routing protocols DSDV, AODV and DSR<br />based on QoS metrics (packet delivery ratio, average end-to-end delay, throughput, and jitter),<br />normalized routing overhead and normalized MAC overhead by using the NS-2 simulator. In this work,<br />the performance comparison is conducted by varying mobility speed, a number of nodes and data rate.<br />The comparison results show that AODV performs optimally well not the best among all the studied<br />protocols.Ain Shams University, Faculty of Computer and Information ScienceInternational Journal of Intelligent Computing and Information Sciences1687-109X17420171001INTELLIGENTPERSONALIZATION APPROACHESFORCOMPLEX CUSTOMER BEHAVIOUR: AN OVERVIEW4557792710.21608/ijicis.2018.7927ENMohamedGalalCommercial International Bank0000-0003-2314-7219GhadaHassanComputer Science department Ain Shams University
and British University in EgyptMostafaArefComputer Science department
Ain Shams University0000-0002-1278-0070Journal Article20180607Intelligent techniques have been used in the marketing and sales sectors of business to<br />improve analysis, increase revenues and save time. In customer-centric institutions, one of the areas in<br />which intelligent techniques and data mining algorithms have been used is the personalization for<br />enhanced CRM (customer relationship management) performance. However, with a growing number of<br />customers, the diversity of products on offer, the complex behavior of customer groups and the<br />continuous change of personalization parameters, the production of a tailored personalized<br />recommendation and the prediction of future needs are a challenging task. Within these institutions,<br />personalization that is more true to the customer needs leads to better targeted marketing campaigns<br />and enhances customer satisfaction with the ultimate aim of increasing the rates of customer retention,<br />and improving competitive advantage. Intelligent techniques and data mining algorithms have been<br />used to produce a more accurately tailored action or service to individual customers or segments of<br />customers. However, many limitations still exist in the CRM personalization lifecycle that undermine<br />the scope of personalized actions that follow; especially in evaluating of effectiveness of targeting,<br />ensuring the coverage of a large segment customers and the control on the decision making process.Ain Shams University, Faculty of Computer and Information ScienceInternational Journal of Intelligent Computing and Information Sciences1687-109X17420171001FRAMEWORK FOR GAMIFICATION BASED E-LEARNING SYSTEMS FOR HIGHER EDUCATION IN EGYPT5971793210.21608/ijicis.2018.7932ENMElabnodyCollege of Computing & Information Technology (CCIT)
Arab Academy for Science, Technology, and Maritime Transport (AASTMT)Journal Article20180607With gamification, design elements known from games can be used in several<br />ways;Businesses have begun to use gamification to enhance profitability, staffhave turned work into a<br />game in order to reduce the monotony, serious applications like work and education are being started<br />using mechanisms borrowed from game design, by adding elements from games into non-game elearning<br />applications. This study aims to identify how the elements of gamification affect user<br />experienceand increase their engagementwith registered subjects. Through a dynamic question<br />selection approach based on the gamification tactics, the real exams of a number of students showed the<br />improvement of their knowledge acquisition by 55% over the traditional examination approaches.