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IEEE International Conference on computer Research and Development

作者： Bhuiyan, Moshiur Rana, Sohel Krishna, Aneesh Decision Systems Laboratory School of Computer Science and Software Engineering University of Wollongong NSW 2522 Australia OptInfra Systems Sydney NSW Australia Department of Computing Faculty of Science and Engineering Curtin University of Technology Perth WA 6102 Australia

ISBN: (纸本)9781612848372

In this paper firstly we discuss an approach for supporting risk identification with the use of higher-level organizational models. We provide some intuitive metrics for extracting measures of actor criticality and vulnerability from organizational models. This helps direct risk management to areas of critical importance within organization models. Secondly, we provide details of an experiment that we conducted to evaluate our methodology. We believe our novel approach, will provide added benefits when used with other approaches to risk management during business process management, that do not reference the greater organizational context during risk assessment. © 2011 IEEE.

关键词： Risk management

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Integration of cultural dimensions into software localisation testing of assistive technology for deaf children

Integration of cultural dimensions into software localisatio...

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2011 5th Malaysian Conference in software engineering, MySEC 2011

作者： Ping, Tan Ping Chan, Chiu Po Sharbini, Hamizan Julaihi, Azlina Ahmadi Department of Computing and Software Engineering Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Malaysia Department of Information Systems Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Malaysia Department of Computer System and Comm. Technologies Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Malaysia

ISBN: (纸本)9781457715310

Lack of hearing ability hinders deaf children from mastering grammar in language studies. Unfortunately, such software targeting Malay language is limited. This paper attempts to generate new approach in handling such software. These include detection of defects when switching into local languages, date format and accommodating the local laws. The acceptance of international software for local use goes beyond just these aspects. For this purpose, software that supports the multi-languages is evaluated. The main research question of this paper: The lack of cultural dimensions in localisation testing of assistive technology decreases the effectiveness of localisation testing of the localised software. On the account of cultural dimensions, Hofstede's Cultural Dimensions will be experimented to study which cultural dimensions are most suited for such software. From our empirical results, the failure rate of the testing is higher compared to incorporating culture dimensions. © 2011 IEEE.

关键词： Audition

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Coordinated PI-based frequency deviation control of isolated hybrid microgrid: An online multi-agent tuning approach via reinforcement learning

Coordinated PI-based frequency deviation control of isolated...

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2022 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2022

作者： Nosrati, K. Tepljakov, A. Petlenkov, E. Levron, Y. Skiparev, V. Belikov, J. Tallinn University of Technology Department of Computer Systems Tallinn Estonia Technion Faculty of Electrical Engineering Haifa Israel Tallinn University of Technology Department of Software Science Tallinn Estonia

ISBN: (数字)9781665480321

ISBN: (纸本)9781665480321

Numerous remote area applications welcome standalone renewable energy power generation systems or isolated microgrids (MGs). Due to the nature of solar and wind energy, the frequency deviation control (FDC) in hybrid MGs has become more complicated and critical than the conventional grid for power quality purposes. By using a coordination control strategy between a double-layered capacitor and a fuel cell, our mission here is to design a FDC system based on the PI controller which is tuned by an artificial neural network (ANN) in a multi-agent structure. To achieve this aim, a reinforcement learning technique is applied to train the ANN-based tuners. The performance of the proposed FDC system has been verified under different conditions by using real data to demonstrate the stability and robustness of the proposed controller. © 2022 IEEE.

关键词： Reinforcement learning

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A formulation of rod based nonlinear model predictive control of nuclear reaction with temperature effects and Xenon poisoning 23

A formulation of rod based nonlinear model predictive contro...

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23rd International Conference on Nuclear engineering: Nuclear Power - Reliable Global Energy, ICONE 2015

作者： Teatro, Timothy A.V. McNelles, Phillip Eklund, J. Mikael Department of Electrical Computer and Software Engineering University of Ontario Institute of Technology OshawaON Canada Faculty of Energy Systems and Nuclear Science University of Ontario Institute of Technology OshawaON Canada

ISBN: (纸本)9784888982566

This paper presents a formulation of a nonlinear model predictive controller for steering of a nuclear reaction in a pressurized water reactor via control rod displacement. The predictive model, based on point kinetic equations, includes an averaged delayed neutron group, thermal dependence on reactivity, heat exchange between temperature and moderator and Xenon poisoning. From the model, a finite horizon optimal control problem is cast in the form of a control Hamiltonian minimization. A basic gradient descent scheme is derived to solve the optimal control problem. The predictive model and gradient descent are used to form the basis from which the model predictive controller is formulated. Copyright © 2015 by JSME.

关键词： Model predictive control

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A static approach towards mobile botnet detection 3

A static approach towards mobile botnet detection

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3rd International Conference on Electronic Design, ICED 2016

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

ISBN: (纸本)9781509021604

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. © 2016 IEEE.

关键词： Android (operating system)

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On Understanding Sports-HAR: Hierarchical, Mobile, Multi-Sensor based Classification of Table-Tennis Strokes 1

On Understanding Sports-HAR: Hierarchical, Mobile, Multi-Sen...

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1st International Conference of Intelligent Methods, systems and Applications, IMSA 2023

作者： Ezzeldin, Mustafa Ghoneim, Amr S. Abdelhamid, Laila Atia, Ayman Helwan University Faculty of Computers AI Software Engineering Cairo Egypt Helwan University Faculty of Computers and AI Computer Science Cairo Egypt Helwan University Faculty of Computers and AI Information Systems Cairo Egypt Helwan Univeristy HCI-LAB Faculty of Computers and AI Computer Science Cairo Egypt Faculty of Computer Science Giza Egypt

ISBN: (纸本)9798350335569

Table Tennis is a renowned competitive and recreational sport. An Olympic sport since 1988, table tennis in-cludes several movements, shots (i.e., strokes), and positions. Consequently, many factors can affect the strokes' accuracy and strength. This paper aims twofold: to classify the type of shot and to enhance the performance of the classification by improving the recognition accuracy and reducing the computational time. To track the movement of the body parts and extract table tennis stroke information, sensors (both Accelerometers and Gyroscopes) were utilized. The extracted data are processed and passed to a P-Dollar classifier to recognize six different table tennis strokes. This work utilizes two classification approaches to evaluate the performance, both linear and hierarchical. The presented results demonstrate that the hierarchical classification yields a better accuracy of 88%, achieved in 4 seconds, while traditional linear classification achieved 83% within 6 seconds. © 2023 IEEE.

关键词： Gyroscopes

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Node verification to join the cloud environment using third party verification server

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2017年第4期11卷 55-65页

作者： Aljammal, Ashraf H. Bani-Salameh, Hani Alsarhan, Ayoub Kharabsheh, Mohammad Obiedat, Mamoon Department of Computer Science and its Applications Faculty of Prince Al-Hussein Bin Abdullah II for Information Technology The Hashemite University Zarqa Jordan Department of Software Engineering Faculty of Prince Al-Hussein Bin Abdullah II for Information Technology The Hashemite University Zarqa Jordan Department of Computer Information Systems Faculty of Prince Al-Hussein Bin Abdullah II for Information Technology The Hashemite University Zarqa Jordan

Currently, cloud computing is facing different types of threats whether from inside or outside its environment. This may cause cloud to be crashed or at least unable to provide services to the requests made by clients. In this paper, a new technique is proposed to make sure that the new node which asks to join the cloud is not composing a threat on the cloud environment. Our new technique checks the node before it will be guaranteed to join the cloud whether it runs malwares or software that could be used to launch an attack. In this way the cloud will allow only the clean node to join it, eliminating the risk of some types of threats that could be caused by infected nodes.

关键词： Network security

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Scalable rekeying algorithm in IEEE 802.16e

Scalable rekeying algorithm in IEEE 802.16e

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17th Asia Pacific Conference on Communications, APCC 2011

作者： Sadeghi, Mohammad Mehdi Gilanian Ali, Borhanuddin Mohd Ma, Maode Manan, Jamalul-Lail Ab Noordin, Nor Kamariah Khatun, Sabira Department of Computer and Communication Systems Engineering Universiti Putra Malaysia Malaysia School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Cluster MIMOS Berhad Malaysia Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Malaysia Institute of Advanced Technology Universiti Putra Malaysia Malaysia

ISBN: (纸本)9781457703881

IEEE 802.16e standard provides wide coverage and high bandwidth for subscribers in a metropolitan area network. It introduces Multicast and Broadcast Rekeying Algorithm (MBRA) which is a multicasting scheme to communicate with many users concurrently. Although ELAPSE (for Efficient sub-Linear rekeying Algorithm with Perfect SEcrecy) improves on the deficiencies of MBRA, the algorithm poorly responds to scalability issue. This paper proposes a Scalable Rekeying Algorithm (SRA) based on a complete binary tree structure. SRA is introduced with linear linked list structure in order to make the system more scalable. Evaluation analysis shows that SRA manages to improve the scalability issue in MBRA for Mobile WiMAX. © 2011 IEEE.

关键词： Scalability

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High-Accuracy Hand Segmentation for Palmprint Biometric systems Improving Auto-Encoder Techniques 8

High-Accuracy Hand Segmentation for Palmprint Biometric Syst...

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8th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2024

作者： Yalcin, Kadir Dogan, Ramazan Ozgur Dogan, Hulya Bingol, Ozkan Graduate Education Institute Gumushane University Department of Artificial Intelligence and Intelligent Systems Gumushane Turkey Trabzon University Faculty of Computer and Information Sciences Department of Artificial Intelligence Engineering Trabzon Turkey Karadeniz Technical University Faculty of Engineering Department of Software Engineering Trabzon Turkey Gumushane University Faculty of Eng. and Natural Sciences Department of Software Engineering Gumushane Turkey

ISBN: (纸本)9798331540104

Biometric technologies have been widely adopted in various commercial products, ranging from security systems to personal devices, due to their exceptional reliability and user-friendliness. Among these, palmprint biometrics has gained increasing attention for its advantages, such as ease of use, a larger surface area, and the ability to capture more features compared to other biometric methods. A typical palmprint biometric system involves five key stages: (a) Image Acquisition, (b) Hand Segmentation, (c) Pattern Generation, (d) Feature Extraction, and (e) Verification/Identification. The overall success of the system depends on the effectiveness of each stage, with hand segmentation being crucial for identifying the most relevant features for accurate verification. This study aims to achieve high-accuracy biometric recognition by segmenting hands from images captured in uncontrolled environments with complex backgrounds. Accuracy (ACC), Intersection over Union (IoU), F1-Score, and Dice Coefficient are the four critical metrics used to assess the performance of segmentation techniques. The findings demonstrate that the U-Net + ViT and MA-Net + ResNet34 techniques outperform traditional auto-encoder methods in both quantitative performance metrics and visual analysis, leading to significantly improved hand segmentation for biometric systems. © 2024 IEEE.

关键词： Image acquisition

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Towards Eco-Sustainability and Green Analytics Model to Measure the Performance of Big Data systems 9

Towards Eco-Sustainability and Green Analytics Model to Meas...

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9th International Conference on Information Management, ICIM 2023

作者： Jusoh, Yusmadi Yah Abdullah, Rusli Nor, Rozi Nor Haizan Yahaya, Jamaiah Hj. Muhammad, Shireen Arunachalam, Aishwharya Raani Universiti Putra Malaysia Faculty of Computer Science and Information Technology Dept. of Software Engineering and Information Systems Serdang Malaysia Universiti Kebangsaan Malaysia Faculty of Information Science and Technology Bangi Malaysia Faculty of Communication Selangor Malaysia

ISBN: (纸本)9798350336382

Many BDS is doomed to failure because of the missing knowledge on measuring the performance of BDS. The failure to identify the performance measurement and correct will make the problems worsen. This will complicate the efforts of fixing such problems and more importantly, will affect the quality of knowledge, insights, and results expected by the users in the future. In achieving durable performance, the organization needsto understand the factors that contribute to the performance of the eco-sustainability and green analytics metrics for BDS. Although the existence of its importance and awareness was largely neglected. Therefore, the eco-sustainability and green analytic measurement of the BDS is examined in this research. Measuring the BDS performance has the benefit of identifying problems and launching corrective actions before these problems happen and become worsen. The research will investigate the eco-sustainability and green analytic measures which will be proposed and used to capture performance for each process of BDS. Then, based on such measures and metrics, as well as existing performance concepts, frameworks, and models, a measurement model for BDS will be created. The model will be validated through expert evaluations and confirmatory studies with users and practitioners of BDS users. The research has a greater significance in leveraging existing performance concepts in BDS settings and the research proposes users' participation in the sustainability and continuous performance evaluation of theirBDS. © 2023 IEEE.

关键词： Big data

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