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International Conference on Science in Information Technology (ICSITech)

作者： Rodziah binti Atan Department of Software Engineering and Information Systems Faculty of Computer Science and Information Technology Universiti Putra Malaysia 43400 Serdang Selangor MALAYSIA

ISBN: (纸本)9781509017225

Various SLA monitoring systems are proposed by different features and abilities to evaluate the agreed SLA. The current SLA monitoring systems in cloud computing for its structural, behavioral characteristics and situation are also in place. The systematic reviews of a well-known methods and approaches shows a significant numbers of researches been done in this area. Based on the number of effort and researches, the quality of services should proportionately increase alongside them. We look this matter from the perspectives of enforcement, that evident the stand of quality of services. Service Level Agreement (SLA) enforcement impact measures is a potential research area to be explored. Assumptions that this study is making are, SLA management will become better by a firm enforcement, where every customers are responsible to launch report of bugs or mischief of services such as unsatisfactory quality or service unavailability to a collection pool, and the provider will react immediately to the complaints so that the total downtime not exceeding the SLA value, with efficient enforcement. This study establishes fundamental theory to measure enforcement impact to SLA monitoring and management. We proposed eight activity phases from formulating until analyzing and decision formation. Descriptive statistics is utilized to analyze the extracted data. The SLA validation detection is the most frequent purpose of SLA monitoring systems in cloud by 58% and throughput is checked as an attribute target by 28%. The self-monitoring SLA, self-healing system, hierarchical structure are recognized points of SLA monitoring systems which need improvement before the enforcement could be based upon.

关键词： quality of service Service Level Agreement enforcement monitoring cloud computing

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A compact patch antenna for ultrawideband application

A compact patch antenna for ultrawideband application

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International Conference on Innovations in Science, engineering and Technology (ICISET)

作者： M. Tarikul Islam M. Samsuzzaman M. M. Islam M.Z. Mahmmud M.T. Islam Dept. of Computer and Communication Engineering Faculty of Computer Science and Engineering Dept. of Software Engineering Daffodil International University Dept. of Electrical Electronic and Systems Engineering Universiti Kebangsaan Malaysia Malaysia

ISBN: (纸本)9781509061235

A compact microstrip line fed tapered-shaped slotted ultra-wideband(UWB) antenna is presented. The new design is composed of a rectangular slotted patch with a compact size of 21.44 × 23.53 mm 2 and fed by microstrip transmission line of 50 Ω. The proposed antenna is simulated onto a less expensive FR4 substrate which has a height of 1.6 mm. There achieved a wider bandwidth of 8.51 GHz (3.49-12 GHz) with good impedance matching, constant gain, 5.76 dBi of maximum gain and stable radiation pattern results in the proposed antenna more appropriate for using UWB communication applications compared to existing antennas. The proposed antenna is designed and simulated in HFSS and CST Microwave Studio software to see the antenna performance.

关键词： Ultra wideband antennas Microstrip antennas Bandwidth Slot antennas Antenna radiation patterns Microstrip Gain

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Tensor Canonical Correlation Analysis for Multi-view Dimension Reduction

Tensor Canonical Correlation Analysis for Multi-view Dimensi...

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IEEE International Conference on Data engineering

作者： Yong Luo Dacheng Tao Kotagiri Ramamohanarao Chao Xu Yonggang Wen School of Computer Engineering Nanyang Technological University Centre for Quantum Computation & Intelligent Systems Faculty of Engineering and Information Technology University of Technology Department of Computer Science and Software Engineering The University of Melbourne School of Electronics Engineering and Computer Science Peking University

ISBN: (纸本)9781509020218

Canonical correlation analysis (CCA) has proven an effective tool for two-view dimension reduction due to its profound theoretical foundation and success in practical applications. In respect of multi-view learning, however, it is limited by its capability of only handling data represented by two-view features, while in many real-world applications, the number of views is frequently many more. Although the ad hoc way of simultaneously exploring all possible pairs of features can numerically deal with multi-view data, it ignores the high order statistics (correlation information) which can only be discovered by simultaneously exploring all features. Therefore, in this work, we develop tensor CCA (TCCA) which straightforwardly yet naturally generalizes CCA to handle the data of an arbitrary number of views by analyzing the covariance tensor of the different views. TCCA aims to directly maximize the canonical correlation of multiple (more than two) views. Crucially, we prove that the main problem of multi-view canonical correlation maximization is equivalent to finding the best rank-1 approximation of the data covariance tensor, which can be solved efficiently using the well-known alternating least squares (ALS) algorithm. As a consequence, the high order correlation information contained in the different views is explored and thus a more reliable common subspace shared by all features can be obtained.

关键词： Correlation Tensile stress Electronic mail Feature extraction Approximation algorithms computers Australia

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Investigation of security awareness on e-learning system among lecturers and students in Higher Education Institution 2

Investigation of security awareness on e-learning system amo...

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2nd International Conference on computer, Communications, and Control Technology, I4CT 2015

作者： Abdul Majid, Hasmanizam Abdul Majid, Mazlina Ibrahim, Mohd Izham Wan Manan, Wan Nurul Safawati Ramli, Muhammed Ramiza Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Malaysia

ISBN: (纸本)9781479979523

The advancement of computer and Internet technologies have brought teaching and learning activities to a new dimension. Learners were virtually moved out from their classrooms to a new learning environment where learning contents and materials were delivered electronically. This new environment, which is called e-learning environment uses the web and other Internet technologies to enhance teaching and learning experience. The success and failure of any e-learning system fall on how secure the system is. Security of an e-learning system is very important so that the information contained in the system is not compromised. However no matter how secure an e-learning system is the security threats always fall on human factor. Human is identified as the weakest link in information security and lack of security awareness such as password sharing will compromise the security of e-learning system. This paper studies the awareness level in information security among e-learning users, particularly students at Higher Education Institution. The study focuses on evaluating awareness level, perception and behavior of e-learning users from International Islamic University Malaysia. Results of this study helps the university authority in preparing effective and specific awareness program in e-learning security for their students. © 2015 IEEE.

关键词： Students

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Knowledge of extraction from trained neural network by using decision tree

Knowledge of extraction from trained neural network by using...

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International Conference on Science in Information Technology (ICSITech)

作者： Soleh Ardiansyah Mazlina Abdul Majid Jasni Mohamad Zain Department of Information Systems Kalimantan Institute of Technology Balikpapan Indonesia Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Gambang-Kuantan Malaysia

ISBN: (纸本)9781509017225

Inside the sets of data, hidden knowledge can be acquired by using neural network. These knowledge are described within topology, using activation function and connection weight at hidden neurons and output neurons. Is hardly to be understanding since neural networks act as a black box. The black box problem can be solved by extracting knowledge (rule) from trained neural network. Thus, the aim of this paper is to extract valuable information from trained neural networks using decision. Further, the Levenberg Marquardt algorithm was applied to training 30 networks for each datasets, using learning parameters and basis weights differences. As the number of hidden neurons increase, mean squared error and mean absolute percentage error decrease, and more time they need to deal with the dataset, that is result of investigation from neural network architectures. Decision tree induction generally performs better in knowledge extraction result with accuracy and precision level from 84.07 to 93.17 percent. The extracted rule can be used to explaining the process of the neural network systems and also can be applied in other systems like expert systems.

关键词： Biological neural networks Neurons Training Forecasting Predictive models Data mining Decision trees

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A static approach towards mobile botnet detection

A static approach towards mobile botnet detection

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International Conference on Electronic Design (ICED)

作者： Shahid Anwar Jasni Mohamad Zain Zakira Inayat Riaz Ul Haq Ahmad Karim Aws Naser Jabir Faculty of Computer Systems and Software Engineering Universiti Malaysia Gambang Pahang Malaysia Computer Science and Information Technology Malaysia University of Engineering & Technology Peshawar Pakistan Computer Science and Information Technology University Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9781509021611

The use of mobile devices, including smartphones, tablets, smart watches and notebooks are increasing day by day in our societies. They are usually connected to the Internet and offer nearly the same functionality, same memory and same speed like a PC. To get more benefits from these mobile devices, applications should be installed in advance. These applications are available from third party websites, such as google play store etc. In existing mobile devices operating systems, Android is very easy to attack because of its open source environment. Android OS use of open source facilty attracts malware developers to target mobile devices with their new malicious applications having botnet capabilities. Mobile botnet is one of the crucial threat to mobile devices. In this study we propose a static approach towards mobile botnet detection. This technique combines MD5, permissions, broadcast receivers as well as background services and uses machine learning algorithm to detect those applications that have capabilities for mobile botnets. In this technique, the given features are extracted from android applications in order to build a machine learning classifier for detection of mobile botnet attacks. Initial experiments conducted on a known and recently updated dataset: UNB ISCX Android botnet dataset, having the combination of 14 different malware families, shows the efficiency of our approach. The given research is in progress.

关键词： Mobile communication Smart phones Malware Receivers Androids Humanoid robots

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A variable combinatorial test suite strategy based on modified greedy algorithm 4

A variable combinatorial test suite strategy based on modifi...

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4th International Conference on software engineering and computer systems, ICSECS 2015

作者： Ba Homaid, Ameen A. Alsewari, Abdulrahman A. Faculty of Computer Systems and Software Engineering University Malaysia Pahang Gambang Malaysia

ISBN: (纸本)9781467367226

A software should be tested before released to the market to be sure that a software has been achieved the quality assurance measurement objectives. Therefore, one of the testing sorts is the combinatorial interaction testing (CIT) which is intended to discover the faults that are happened by interacting between the software features. Test case generation is the most active area of CIT research. As the problem of generating the most minimum test suite of CIT is NP-hard (i.e. NP where NP terms Non-deterministic Polynomial). Several researchers have been addressed the combinatorial interaction testing issues by developing the various strategies based on a search-based approach or a pure-computational approach, although, these are useful, but most of them have a lack to support the variable strength interaction which is one of CIT techniques. A variable strength interaction is the interaction between some of software features which have higher priority than the interaction between the others software features. This proposed will suggest a new CIT strategy based on a modified greedy algorithm (MGA) with addressing the supporting of variable strength interaction to generate a satisfactory test suite size. © 2015 IEEE.

关键词： software testing

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V for variety: Lessons learned from complex smart cities data harmonization and integration

V for variety: Lessons learned from complex smart cities dat...

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IEEE Annual Conference on Pervasive Computing and Communications Workshops (PerCom)

作者： Iman Avazpour John Grundy Liming Zhu Faculty of Science University of Technology Hawthorn VIC Australia School of Computer Science and Engineering University of New South Wales Sydney Australia Software and Computational Systems CSIRO

With emerging trends for Internet of Things (IoT) and Smart Cities, complex data transformation, aggregation and visualization problems are becoming increasingly common. These tasks support improved business intelligence, analytics and enduser access to data. However, in most cases developers of these tasks are presented with challenging problems including noisy data, diverse data formats, data modeling and increasing demand for sophisticated visualization support. This paper describes our experiences with just such problems in the context of Household Travel Surveys data integration and harmonization. We describe a common approach for addressing these harmonizations. We then discuss a set of lessons that we have learned from our experience that we hope will be useful for others embarking on similar problems. We also identify several key directions and needs for future research and practical support in this area.

关键词： Data models Data integration High-temperature superconductors Smart cities Data visualization Australia Business

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Estimating the efficiency of Information Technology for Domain-Specific Mathematical Modelling 2

Estimating the efficiency of Information Technology for Doma...

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2nd International Conference on computer, Communications, and Control Technology, I4CT 2015

作者： Mezhuyev, Vitaliy Abdul Majid, Mazlina Samikannu, Ravi Faculty of Computer Systems and Software Engineering University Malaysia Pahang Gambang Malaysia Faculty of Electrical Engineering Selvam College of Technology India

ISBN: (纸本)9781479979523

The paper analyses the efficiency of the Information Technology (IT) for Domain-Specific Mathematical Modelling (DSMM). IT DSMM was developed to meet the shortcomings of the IT for Domain-Specific Modelling (DSM). IT DSMM allows us to develop metamodels in the different mathematical semantics and thus to increase the level of adequateness of models to the modelled domains. It also reduces an amount of operations needed for the development of metamodels and models of software systems. The optimization problem of choosing the most effective IT by selection and comparison of the multiple features inherent to DSM, DSMM and GPM (General Purpose Modelling) is solved. © 2015 IEEE.

关键词： Semantics

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Restoring the missing features of the corrupted speech using linear interpolation methods

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AIP Conference Proceedings 2017年第1期1891卷

作者： Taha H. Rassem Nasrin M. Makbol Ali Muttaleb Hasan Siti Syazni Mohd Zaki P. N. Girija 1Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Kuantan Malaysia 2School of Electrical and Electronic Engineering Universiti Sains Malaysia Penang Malaysia 3School of Computer and Information Sciences UoH Hyderabad T.S India

One of the main challenges in the Automatic Speech Recognition (ASR) is the noise. The performance of the ASR system reduces significantly if the speech is corrupted by noise. In spectrogram representation of a speech signal, after deleting low Signal to Noise Ratio (SNR) elements, the incomplete spectrogram is obtained. In this case, the speech recognizer should make modifications to the spectrogram in order to restore the missing elements, which is one direction. In another direction, speech recognizer should be able to restore the missing elements due to deleting low SNR elements before performing the recognition. This is can be done using different spectrogram reconstruction methods. In this paper, the geometrical spectrogram reconstruction methods suggested by some researchers are implemented as a toolbox. In these geometrical reconstruction methods, the linear interpolation along time or frequency methods are used to predict the missing elements between adjacent observed elements in the spectrogram. Moreover, a new linear interpolation method using time and frequency together is presented. The CMU Sphinx III software is used in the experiments to test the performance of the linear interpolation reconstruction method. The experiments are done under different conditions such as different lengths of the window and different lengths of utterances. Speech corpus consists of 20 males and 20 females; each one has two different utterances are used in the experiments. As a result, 80% recognition accuracy is achieved with 25% SNR ratio.

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