@article { author = {FaDl, Dalia and abas, Safiaa and Aref, Mostafa}, title = {AN APPROACH FOR AUTOMATIC ARABIC ONTOLOGY GENERATION}, journal = {International Journal of Intelligent Computing and Information Sciences}, volume = {17}, number = {3}, pages = {1-10}, year = {2017}, publisher = {Ain Shams University, Faculty of Computer and Information Science}, issn = {1687-109X}, eissn = {2535-1710}, doi = {10.21608/ijicis.2017.8205}, abstract = {Abstract. The increasing interest in Ontologies for many natural language applications in the recent years has led to the creation of ontologies for different purposes and with different feature systems.Manual ontology building is a time consuming activity that requires a lot of effort. In order to overcome these problems many methods have been developed to generate ontologies. There are various studies conducted on Arabic language in Semantic Web. This paper purposes an approach for the generation of an Arabic ontology from semi-structured data (xml document). This approach takes xml document and generates Arabic Ontology. First the system generates xml schema for the xml document. Using this schema it develops the xml schema graph XSG, translate this graph into Arabic and then start the generation of the ontology and the relations using the graph and the xml document. Finally, the system is going to evaluate the generated Arabic ontology using data driven ontology measures.   generates xml schema for the xml document. Using thisschema it develops the xml schema graph XSG, translate this graph into Arabic and then start thegeneration of the ontology and the relations using the graph and the xml document. Finally, the systemis going to evaluate the generated Arabic ontology using data driven ontology measures.}, keywords = {ontology learning,Arabic ontology,Natural language applications}, url = {https://ijicis.journals.ekb.eg/article_8205.html}, eprint = {https://ijicis.journals.ekb.eg/article_8205_0131c0de6b3577ae65ba889f3b75ae6f.pdf} } @article { author = {elbedwehy, Samar and Alrahmawy, M and Hamza, Taher}, title = {REAL TIME FIRST STORY DETECTION IN TWITTER USING A MODIFIED TF-IDF ALGORITHM}, journal = {International Journal of Intelligent Computing and Information Sciences}, volume = {17}, number = {3}, pages = {11-31}, year = {2017}, publisher = {Ain Shams University, Faculty of Computer and Information Science}, issn = {1687-109X}, eissn = {2535-1710}, doi = {10.21608/ijicis.2017.8245}, abstract = {Twitter is a social micro blogging, it has its own feature that it enables to tweet only a maximum of 140 characters per tweet. Even with this small number of characters per tweet, analyzing the tweets for billions of users faces the challenges of real-time data processing. One of the important aspects of social behavior is that we can detect the significance of the events and the way the people reacted to them. In this paper, we focus on First Story Detection (FSD) that means we can detect bursts of tweets that refer to a particular topic. First story is defined as the first document from a given series of documents to discuss a specific event, which occurred at a particular time and place. TF-IDF denotes to term frequency–inverse document frequency is an algorithm traditionally used in most of Text similarity applications like FSD. In this paper, we embedded a modified version of TF-IDF algorithm to enhance the accuracy of a pre-implemented open source for FSD that uses Storm platform to benefit from its scalability, efficiency and robustness in analyzing the tweets in real time. The empirical results show significant enhancements in the accuracy of the detection without noticeable effect on performance}, keywords = {Real Time,Similarity Algorithms,social media,Information Retrieval,Big Data}, url = {https://ijicis.journals.ekb.eg/article_8245.html}, eprint = {https://ijicis.journals.ekb.eg/article_8245_38fb8ee9b7969fe8770c2f31fd545a61.pdf} } @article { author = {Ali, Khaled and mazen, S and Hassanein, E}, title = {A PROPOSED FRAMEWORK FOR THE ORGANIZATION READINESS ASSESSMENT OF IT INNOVATION ADOPTION IN E-GOVERNMENT ENVIRONMENT}, journal = {International Journal of Intelligent Computing and Information Sciences}, volume = {17}, number = {3}, pages = {33-50}, year = {2017}, publisher = {Ain Shams University, Faculty of Computer and Information Science}, issn = {1687-109X}, eissn = {2535-1710}, doi = {10.21608/ijicis.2017.8248}, abstract = { Most of developing countries are now experiencing revolution in e-government to deliver fluent and simple services for their citizens. But, the organization will face three main problems if it decided to modernize its IT infrastructure; firstly, there are many solutions of new technologies, how to choose between them. Secondly, what is the impact of the factors affect on those solutions? Thirdly,what is the degree of readiness each of these factors to comply this new changing? Therefore, a systematic approach to measure organization readiness for adopting this new solution is needed, this paper proposes a practical framework helps in answering these questions and assists decision makers in estimating organization readiness for adopting all IT suggested solutions and to compare between these solutions. Whereas, it will use Multi-Criteria Decision Making method to rank the alternatives, taking into account all the attributes and factors affect the result, finally, it assess the degree of readiness of these factors to accept the preferred solution.}, keywords = {Multi Criteria Decision Making (MCDM),Analytic network process (ANP),Fuzzy analytic network process (FANP),E-government}, url = {https://ijicis.journals.ekb.eg/article_8248.html}, eprint = {https://ijicis.journals.ekb.eg/article_8248_c30cb29a3fe1be1850f2d26481275d41.pdf} } @article { author = {yehia, lobna and Darwish, ashraf and elngar, Ahmed and khedr, Ayman}, title = {ARTIFICIAL NEURAL NETWORK AND C4.5 ALGORITHMS FOR TAMPER DETECTION MODEL OF HEALTHCARE APPLICATIONS IN INTERNET OF THINGS}, journal = {International Journal of Intelligent Computing and Information Sciences}, volume = {17}, number = {3}, pages = {51-63}, year = {2017}, publisher = {Ain Shams University, Faculty of Computer and Information Science}, issn = {1687-109X}, eissn = {2535-1710}, doi = {10.21608/ijicis.2017.9148}, abstract = {Abstract: Security of a network is the most important challenges of the Internet of Things (IOT) that needs smarter security mechanism. Tamper detection is an effective technique used to deal with security violations. In this paper, a new IoT-Tamper Detection Model (TDM) based IoT for real data of healthcare applications has been proposed. In this model, artificial neural network (ANN) algorithm with RC4-EA encryption method and IOT-C4.5 algorithm are applied for TDM. The experimental results showed that the detection performance of ANN is 98.51% and 76.66 % for the C4.5 algorithm. In addition, the proposed model showed that the ANN algorithm enhances the timing speed than C4.5 algorithm which is important for real time IOT - TDM healthcare application.}, keywords = {Keywords: Internet of Things (IoT),Tamper detection,security,Healthcare applications,artificial neural network,C4.5 algorithm}, url = {https://ijicis.journals.ekb.eg/article_9148.html}, eprint = {} } @article { author = {Elsayed, E.K and Ibrahim, A}, title = {A METHODOLOGY FOR DESIGNING HIGH CONFIDENCE PATTERN VIA EVENT B}, journal = {International Journal of Intelligent Computing and Information Sciences}, volume = {17}, number = {3}, pages = {65-84}, year = {2017}, publisher = {Ain Shams University, Faculty of Computer and Information Science}, issn = {1687-109X}, eissn = {2535-1710}, doi = {10.21608/ijicis.2017.9149}, abstract = {The correct formal design is an achievement in software engineering, but we faced withchallenges to satisfy that. The informal problems types are general or special. The special informalproblems depend on the case study and the general informal problems come from an inexperienceddesigner called anti-patterns". In this paper we discuss these two types on Insulin Infusion Pump (IIP)and sample of UML class diagrams. The proposed approach to formalize IIP is based on using event B.Finally, we could verify that the code generated from the proposed approach is correct and formal touse as a pattern. The accuracy of the proposed verification steps are suitable for using to any systemsor medical device. We applied the proposed approach on the sample of eight famous UML classdiagrams used as templates. The method ameliorates the proofpercentage}, keywords = {Event-B,Insulin Infusion Pump (IIP),Patterns,anti-patterns}, url = {https://ijicis.journals.ekb.eg/article_9149.html}, eprint = {https://ijicis.journals.ekb.eg/article_9149_d9e8e38d21e1e89d36cd48507b71a478.pdf} } @article { author = {Elabnody, M. and Fouad, M. and Maghraby, F. and Hegazy, A.}, title = {FRAMEWORK FOR GAMIFICATION BASED E-LEARNING SYSTEMS FOR HIGHER EDUCATION IN EGYPT}, journal = {International Journal of Intelligent Computing and Information Sciences}, volume = {17}, number = {3}, pages = {85-97}, year = {2017}, publisher = {Ain Shams University, Faculty of Computer and Information Science}, issn = {1687-109X}, eissn = {2535-1710}, doi = {10.21608/ijicis.2017.19816}, abstract = {With gamification, design elements known from games can be used in several ways; Businesses have begun to use gamification to enhance profitability, staff have turned work into a game in order to reduce the monotony, serious applications like work and education are being started using mechanisms borrowed from game design, by adding elements from games into non-game e-learning applications. This study aims to identi how the elements of gamification affect user experience and increase their engagement with registered subjects. Through a dynamic question selection approach based on'the gamification tactics, the real exams of a number of students showed the improvement of their knowledge acquisition by 55% over the traditional examination approaches.}, keywords = {E-learning,games-based learning,Gamification,gamified e-learning course,Higher Education}, url = {https://ijicis.journals.ekb.eg/article_19816.html}, eprint = {https://ijicis.journals.ekb.eg/article_19816_0c9ce42a7587b347d428aaf6f47188fb.pdf} } @article { author = {Alkhalidi, M. and Abu-Elnasr, Osama and Elarif, T.}, title = {A ROBUST STEGANALYSIS METHOD FOR DETECTING THE STEGANOGRAPHY IN IMAGES}, journal = {International Journal of Intelligent Computing and Information Sciences}, volume = {17}, number = {3}, pages = {99-106}, year = {2017}, publisher = {Ain Shams University, Faculty of Computer and Information Science}, issn = {1687-109X}, eissn = {2535-1710}, doi = {10.21608/ijicis.2017.19819}, abstract = {Recently, steganography and steganalysis have been received an increasing attention due the nature of our modern societies which depends on exchanging information on a large scale. Steganography is the art of communication through sharing secret messages by embedding them into useless cover messages. The cover message can be an image, audio, or video file. On the other side, the steganalysis techniques are concerned with discovering the existence of steganography. This paper presents a specific image steganalysis technique with main objective is to detect the existence of steganography made by the least significant bit (LSB) technique in a certain image. The proposed approach extracts the gray level co-occurrence matrix (GLCM) as salient features which capable to distinguish a stego image from a non-stego one using a Back-Propagation (BP) classifier at the classification phase. Experimental results on standard datasets that consists of 297 images are encouraging. The proposed method is robust and high accuracy level has been achieved.}, keywords = {Steganography,Steganalysis,LSB,GLCM,BP}, url = {https://ijicis.journals.ekb.eg/article_19819.html}, eprint = {https://ijicis.journals.ekb.eg/article_19819_07bbf89879d33c1aec6e3402473eff30.pdf} } @article { author = {Rezk, Amira and Barakat, Sherif and Saleh, Hossam}, title = {THE IMPACT OF CYBER CRIME ON E-COMMERCE}, journal = {International Journal of Intelligent Computing and Information Sciences}, volume = {17}, number = {3}, pages = {85-96}, year = {2017}, publisher = {Ain Shams University, Faculty of Computer and Information Science}, issn = {1687-109X}, eissn = {2535-1710}, doi = {10.21608/ijicis.2017.30055}, abstract = {}, keywords = {}, url = {https://ijicis.journals.ekb.eg/article_30055.html}, eprint = {https://ijicis.journals.ekb.eg/article_30055_4ae34bb8657b022ec28e3c593902663d.pdf} }