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2012 International Conference on information Retrieval and Knowledge Management, CAMP'12

作者： Jabar, Marzanah A. Cheah, Chee-Yeong Sidi, Fatimah Department of Information System Faculty of Computer Science and Information Technology University Putra Malaysia 43400 Serdang Malaysia

ISBN: (纸本)9781467310901

Knowledge hoarding in Requirements Elicitation (RE) phase could lead to information systems Development (ISD) project failure. Many researchers have discussed important factors in knowledge sharing. Nevertheless, the success rate for ISD projects is low and there are other major factors for consideration. Review was conducted to identify potential gaps in existing literature and to explore new factors that impact ISD knowledge sharing in RE. Based on systematic review of literature, two new factors are identified namely Organizational Justice and Social Interdependence. The success of ISD projects are impacted by organizational justice and social interdependence. The proposed theoretical model provides project managers a new platform to further understand ISD knowledge sharing between business users and external IT professionals in RE. © 2012 IEEE.

关键词： information use

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XMCCTree: An algorithm for producing Mcctree in incompact structure

XMCCTree: An algorithm for producing Mcctree in incompact st...

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2011 5th Malaysian Conference in Software Engineering, MySEC 2011

作者： Sazaly, Ummu Sulaim Selamat, Mohd Hasan Baharom, Salmi Jabar, Marzanah Ab. Department of Information System Faculty of Computer Science and Information Technology Universiti Putra Malaysia 43400 Serdang Malaysia

ISBN: (纸本)9781457715310

Different notions and techniques have been proposed to support query in XML. This led to the generation of algorithms to provide more efficient and accurate query processing. This research proposes an efficient algorithm to support keyword query in XML document. The propose algorithm, namely XMCCTree, employs MCLCA notion with some modifications in order to provide more efficient algorithm. © 2011 IEEE.

关键词： XML

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Real-time Privacy Preserving Framework for Covid-19 Contact Tracing

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computers, Materials & Continua 2022年第1期70卷 1017-1032页

作者： Akashdeep Bhardwaj Ahmed A.Mohamed Manoj Kumar Mohammed Alshehri Ahed Abugabah School of Computer Science University of Petroleum&Energy Studies(UPES)Dehradun248007India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Department of Information Technology Faculty of Computer and InformationAssiut UniversityAssiut71515Egypt Department of Information Technology College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Department of Information System College of Technological InnovationZayed UniversityAbu DhabiUnited Arab Emirates

The recent unprecedented threat from COVID-19 and past epidemics,such as SARS,AIDS,and Ebola,has affected millions of people in multiple *** have shut their borders,and their nationals have been advised to *** variety of responses to the pandemic has given rise to data privacy *** prevention and control strategies as well as disease control measures,especially real-time contact tracing for COVID-19,require the identification of people exposed to *** tracing frameworks use mobile apps and geolocations to trace ***,while the motive may be well intended,the limitations and security issues associated with using such a technology are a serious cause of *** are growing concerns regarding the privacy of an individual’s location and personal identifiable information(PII)being shared with governments and/or health *** study presents a real-time,trust-based contact-tracing framework that operateswithout the use of an individual’sPII,location sensing,or gathering GPS *** focus of the proposed contact tracing framework is to ensure real-time privacy using the Bluetooth range of individuals to determine others within the *** research validates the trust-based framework using Bluetooth as practical and *** our proposed methodology,personal information,health logs,and location data will be secure and not *** research analyzes 100,000 tracing dataset records from 150 mobile devices to identify infected users and active users.

关键词： Privacy contact tracing mobile apps Bluetooth Covid epidemic

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What affect true information findings from rural children survey? 8

What affect true information findings from rural children su...

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8th International Conference on information technology, ICIT 2017

作者： Kamarudin, Abrar Noor Akramin Ranaivo-Malancon, Bali Musa, Nadianatra Department of Information System Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Kota Samarahan Malaysia

ISBN: (纸本)9781509063321

Recently, the Internet is accessible by the children in the rural area. The purpose of this paper is to understand what affects their true information findings based on the analysis of the survey. Data collection is obtained from the secondary school students (N=237) in Serian, a rural area of Sarawak. A self-administered questionnaire was conducted in three public secondary schools to obtain a socio-demographic profile, language usage, medium of assistance required, Internet access platforms and Internet content exposure. Logistic regression model tested the parent's educational level, Internet availability at home, English usage when online and mobile device easiness for learning in explaining the respondent's ability to find true information from the Internet. The focus group is able to obtain true information from the Internet if they are able to use English as their main Internet language as well as other factors. Based on the findings, an initial system framework is designed to personalize the children's Internet access. © 2017 IEEE.

关键词： Surveys

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R3 - Rescale, Rotate, and Randomize: A Novel Image Cryptosystem Utilizing Chaotic and Hyper-Chaotic systems

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IEEE Access 2023年 11卷 119284-119312页

作者： Gabr, Mohamed Korayem, Yousef Chen, Yen-Lin Yee, Por Lip Ku, Chin Soon Alexan, Wassim Faculty of Media Engineering and Technology Computer Science Department Cairo11835 Egypt National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia Faculty of Information Engineering and Technology Communications Department Cairo11835 Egypt New Administrative Capital Mathematics Department Cairo13507 Egypt

This work proposes a novel image encryption algorithm that integrates unique image transformation techniques with the principles of chaotic and hyper-chaotic systems. By harnessing the unpredictable behavior of the Chua system and the hyper-chaotic nature of the Chen system, the algorithm carries out rescaling, rotation, and randomization on the target image. The intrinsic unpredictability and sensitivity to initial conditions of these chaotic systems endow the encryption algorithm with an expansive key space of 25208. This feature not only bolsters its resilience against brute-force attacks but also magnifies its overall security profile. The algorithm's efficiency is evident in its rapid computational speed and lean resource consumption, making it suitable for real-time applications. To gauge its robustness, a battery of rigorous tests and analyses, spanning differential attacks, statistical attacks, and brute-force assaults, were employed. The results validate its ability to resist a diverse spectrum of threats. With its expansive key space, exceptional efficiency, and sturdy defenses, the proposed algorithm emerges as a potential cornerstone for safeguarding digital images in arenas like secure communication, data storage, and multimedia transmission. In sum, this research pushes the boundaries of high-security image encryption methodologies, catering to the burgeoning demands of the digital age. © 2013 IEEE.

关键词： Cryptography

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Classification of unknown Internet traffic applications using Multiple Neural Network algorithm 2

Classification of unknown Internet traffic applications usin...

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2nd International Conference on computer and information Sciences, ICCIS 2020

作者： Mohamed, Abdelbasst Abbas Osman, Ahmed Hamza Motwakel, Abdelwahed Faculty of Computer Science and Information Technology Omdurman Islamic University Department of Computer Science Khartoum Sudan Faculty of Computing and Information Technology King Abdulaziz University Department of Information System Saudi Arabia

ISBN: (纸本)9781728154671

Traffic classification software is an important tool in complex environments like a cloud-based environment for network and device safety. The new methods of traffic classification attempt to benefit from numerical flow characteristics and computer teaching techniques, but minimal supervised knowledge and uncertain applications seriously affect classification efficiency. We propose a new way of dealing with an unknown application issue in the critical situation of a limited supervised training set to achieve an efficient network classification. The proposed model applied the multiple neural network algorithms to predict the unknown application that run through organization internet network. The advantage of the suggested approach is to filter and exclude the unknown internet applications that can be affecting into internet network performance. By Appling proposed method, the internet performance can be improved and the internet traffic and delay of transferred data can be reduced. The proposed method compared with other based line method in term of predication precision accuracy measure. © 2020 IEEE.

关键词： Classification (of information)

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Flood alerts system with android application 6

Flood alerts system with android application

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6th ICT International Student Project Conference, ICT-ISPC 2017

作者： Napiah, Mohamad Nazrin Idris, Mohd Yamani Idna Ahmedy, Ismail Asri Ngadi, Md. Department of Computer System & Technology Faculty of Computer Science & Information Technology University of Malaya Malaysia Department of Computer Science Faculty of Computing Universiti Teknologi Malaysia Malaysia

ISBN: (纸本)9781538629963

Internet of things (IoT) is technology that connected anything and everything to the Internet. IoT is the newest technology rapidly widen in its usage. This technology brings new products such as disaster monitoring. Flood disaster is the main concern in Malaysia because every year there are flood occurred. We can use this technology to do monitoring activity that people are not able to do it in 24 hours and inform to the user in real time. In this paper, we propose IoT approach that known as flood alerts system with Android application. This system will monitor the potential drainage usually occur flooding and share the info in real time to people nearby. © 2017 IEEE.

关键词： Internet of things

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Colored satellites image enhancement using wavelet and threshold decomposition

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International Journal of computer Science Issues 2011年第5 5-3期8卷 33-41页

作者： Al-Samaraie, Muna F. Al Saiyd, Nedhal Abdul Majied Management Information System Department Faculty of Economics and Administrative Sciences Al-Zaytoonah University Amman Jordan Computer Science Department Faculty of Information Technology Applied Science University Amman Jordan

For decades, several image enhancement techniques have been proposed. Although most techniques require profuse amount of advance and critical steps, the result for the perceive image are not as satisfied. In this study, we proposed a new method to enhance the satellite image which using intelligent aspect of filtering and describe multi-threshold technique with an additional step in order to obtain the perceived image. In this way, several simple filters can be combined to form a more efficient and more flexible context dependent filter. This paper proposes a new idea for edge enhancement using smoothing techniques. Various smoothing technologies are explored and implemented for comparing their performance with various threshold values. Comparison is done by qualitative and quantitative approaches. From the results, specific filtering is only applied to the region for which it is suitable. We also evaluate the image quality. The proposed method shows dramatically increase in pixel distribution throughout the range of RGB. The result of this research is also beneficial in terms of geographical views due to the process which determined the difference appeared on each area.

关键词： Image enhancement

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Creating granular learning object towards reusability of Learning Object in e-learning context

Creating granular learning object towards reusability of Lea...

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2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011

作者： Noor, Siti Fadzilah Mat Yusof, Norazah Hashim, Siti Zaiton Mohd School of Information Technology Faculty of Technology and Information Science National University of Malaysia Malaysia Software Engineering Department Faculty of Computer Science and Information System University Technology of Malaysia Malaysia

ISBN: (纸本)9781457707520

Learning Object (LO) is one of the main research topics in the e-learning community in the recent years, and most researchers pay attention to the issue of Learning Object Reusability. The most obvious motivation is the economic interest of reusing learning material instead of repeatedly authoring it. In this paper we present the process of creating granular learning object for enabling the reusing of LO in e-Learning context. Reusability requires the LO to be in a fine-grain form because raw media elements are often much easier to reuse then aggregate assemblies. In other words, as the LO size decreases (lower granularity), its potential for reuse increases. A prototype of learning objects repository that contain granular LO has been developed to show the process of granularizing LO. Each of existing LO will be extracted into granular element with the metadata and the system generated unique id for each LO based on its identifier (URL of LO) and save automatically the metadata contain in the LO. These metadata will be used for searching and retrieval process of the granule LO. © 2011 IEEE.

关键词： Metadata

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N-gram and Word2Vec Feature Engineering Approaches for Spam Recognition on Some Influential Twitter Topics in Saudi Arabia 22

N-gram and Word2Vec Feature Engineering Approaches for Spam ...

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6th International Conference on information system and Data Mining, ICISDM 2022

作者： Balfagih, Ahmed Keselj, Vlado Taylor, Stacey Faculty of Computer Science Dalhousie University Canada Information System Faculty of Computing and Information Technology King Abdulaziz University Saudi Arabia

ISBN: (纸本)9781450396257

Social media platforms, such as Twitter, have become powerful sources of information on people's perception of major events. Many people use Twitter to express their views on various issues and events and use it to develop their opinion on the diverse economic, political, technical, and social occurrences related to their daily lives. Spam and non-relevant tweets are a major challenge for Twitter trend detection. Saudi Arabia is a top ranked country in Twitter usage worldwide, and in recent years has experienced difficulties due to the use and rise of hashtags based on misleading tweets and spam. The goal of this paper is to apply machine learning techniques to identify spam on the Saudi tweets collected to the end of 2020. To date, spam detection on Twitter data has been mostly done in English, leaving other major languages, such as Arabic, insufficiently covered. Additionally, publicly accessible Arabic Twitter datasets are hard to find. For our research, we use eight Twitter datasets on some significant topics in politics, health, national affairs, economy, and sport, to train and evaluate different machine learning algorithms, with a focus on two feature generation techniques based on N-grams and Word2Vec embeddings. One contribution of this paper is providing these new labelled datasets with embeddings. The experimental results show improvement from using embeddings over N-grams in more balanced datasets vs. more unbalanced ones. We also find a superior performance of the Random Forest algorithm over other algorithms in most experiments. © 2022 ACM.

关键词： Embeddings

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