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2020 IEEE Conference on Application, information and Network Security, AINS 2020

作者： Onwuegbuzie, Innocent Uzougbo Razak, Shukor Abd Isnin, Ismail Fauzi Anuar, Nor Badrul School of Computing Faculty of Engineering Johor Malaysia Faculty of Computer Science and Information Technology University of Malaya Department of Computer System and Technology Kuala Lumpur Malaysia

ISBN: (纸本)9781728192406

Wireless Sensor Networks (WSN) is the network of embedded and resource-constrained nodes, that forms the foundation of the Internet of Things (IoT). These networks are designed to sense, aggregate and transport sensed data to locations that may be local or remote to the sensory field, for immediate or stored for later use. In most cases, WSN generates heterogeneous data that conveys information of varying priorities which may be real-time (RT) or non-real-time (NRT). However, the de facto routing protocol;Routing Protocol for Low-power and Lossy Networks (RPL) is not optimized for heterogeneous data routing. Likewise, routing schemes proposed in the literature have not proffered a lasting solution. In this paper, we proposed the Shortest Path Priority-based RPL (SPPB-RPL). The SPPB-RPL scheme not only routes data with varying priorities but also does so with optimal network performances. Its application in a smart campus is used as a case study. The scheme uses the mechanism of class of service (CS) to classify and prioritized data into various priority classes. Subsequently, the standard RPL DIO base object was improved upon to accommodate the prioritized data classes, and finally, the Dijkstra Algorithm (DA) was adopted to generate the optimal shortest routing path leading to the destination node which is guided by the priority of the data. Benchmarked with related schemes, SPPB-RPL performed optimally with a 99.98% packet delivery ratio with the least latency. This enhanced the network performance for a prolonged operational lifetime. © 2020 IEEE.

关键词： Routing protocols

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Smart Agriculture Prediction system for Vegetables Grown in Sri Lanka 12

Smart Agriculture Prediction System for Vegetables Grown in ...

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12th IEEE Annual information technology, Electronics and Mobile Communication Conference, IEMCON 2021

作者： Gamage, Rashmika Rajapaksa, Hasitha Sangeeth, Abhiman Hemachandra, Gimhani Wijekoon, Janaka Nawinna, Dasuni Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe 10115 Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe 10115 Sri Lanka Sri Lanka Institute of Information Technology Department of Computer System Engineering Malabe 10115 Sri Lanka

ISBN: (纸本)9781665400664

Agriculture planning plays a dominant role in the economic growth and food security of agriculture-based countries such as Sri Lanka. Even though agriculture plays a vital role, there are still several major complications to be addressed. Some of the major complications are lack of knowledge about yield and price resulting in the farmers selecting crops based on experience. Machine learning has a great potential to solve these complications. To this end, this paper proposes a novel system comprises of a mobile application, SMS (Short Message Service), and API (Application Programming Interface) with yield prediction, price prediction, and crop optimization. Several machine learning algorithms were used for yield and price predictions while a generic algorithm was used to optimize crops. The yield was predicted considering the environmental factors while the price was predicted considering supply and demand, import and export, and seasonal effect. To select the best suitable crops to cultivate, the output of yield and price prediction have been used. Yield prediction has been implemented using elastic net, ridge, and multilinear regression. R2 of yield prediction is varied from 0.74 to 0.89 while RMSE value is between 15.69 and 35.05. Price prediction has been implemented using the algorithms of Gradient Boosting Tree, Random Forest, Facebook Prophet, and R2 is varied from 0.72 to 0.92 while RMSE value is between 26.81 and 140.72. Crop optimization has been implemented using the genetic algorithm. © 2021 IEEE.

关键词： Crops

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Relational reinforcement rule induction and the effect of pruning

Relational reinforcement rule induction and the effect of pr...

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2016 International Conference on Artificial Intelligence, ICAI 2016 - WORLDCOMP 2016

作者： ElGibreen, Hebah Aksoy, Mehmet Sabih Information Technology Department College of Computer and Information Sciences King Saud University Riyadh11415 Saudi Arabia Information System Department College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia

ISBN: (纸本)1601324383

Covering Algorithm (CA) is a Machine Learning field that produces a powerful repository represented as simple if-then rules. Although this field is well established with discrete data but it has its deficiency when dealing with numeric data. This paper introduces a new algorithm called RULES-CONT, which deal with continuous attributes using Relational Reinforcement Learning (RRL). This algorithm is a non-discretization algorithm that directly deal with all kind of data and transfer past experience to improve and generalize its learning. Different pruning levels will also be tested with RULES-CONT, in order to study the possibility of using pruning with RRL to reduce the time and solve the speed problem. The main contribution is to propose a novel solution for rule induction and analyse the most effective pruning level that should be integrated with RRL. Several experiments will be presented to compare RULES-CONT with other algorithms. These experiments are validated using 10-cross-fold validation and Friedman test to measure the significance between the algorithms and decide on the most suitable pruning level with RRL. CSREA Press ©.

关键词： Reinforcement learning

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Towards accountable authority attribute-based encryption

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High technology Letters 2013年第1期19卷 82-87页

作者：王永涛 Chen Kefei Long Yu Department of Computer Science and Engineering Shanghai Jiao Tong University China Information Technology Security Evaluation Center Shanghai Key Laboratory of Scalable Computing and System Shanghai JiaoTong University

An accountable authority attribute-based encryption （A-ABE） scheme is presented in this paper. The notion of accountable authority identity-based encryption （A-IBE） was first introduced by Goyal at Crypto＇07. It is a novel approach to mitigate the （inherent） key escrow problem in identity-based cryptosystems. In this work, the concept of accountable authority to attribute-based encryption （ABE） setting is generalized for the first time, and then a construction is given. The scheme non-trivially integrates an A-IBE scheme proposed by Libert et al. with an ABE scheme. In our construction, a user will be identified by a pair （ id, o~）, where id denotes the user＇ s identity and ω denotes the set of attributes associated to the user. In addition, our construction is shown to be secure under some reasonable assumptions.

关键词： cryptography attribute-based encryption accountable authority key escrow traceability

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Metaheuristics Enabled Clustering with Routing Scheme for Wireless Sensor Networks

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computers, Materials & Continua 2022年第12期73卷 5491-5507页

作者： Mashael M.Asiri Saud S.Alotaibi Dalia H.Elkamchouchi Amira Sayed A.Aziz Manar Ahmed Hamza Abdelwahed Motwakel Abu Sarwar Zamani Ishfaq Yaseen Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Wireless Sensor Network(WSN)is a vital element in Internet of Things(IoT)as the former enables the collection of huge quantities of data in energy-constrained *** offers independent access to the target region and performs data collection in an effective *** energy constraints remain a challenging issue in WSN since it operates on in-built *** studies conducted earlier recommended that the energy spent on communication processmust be considerably reduced to improve the efficiency of *** organization and optimal selection of the routes are considered as NP hard optimization problems which can be resolved with the help of metaheuristic *** and routing are considered as effective approaches in enhancing the energy effectiveness and lifespan of *** this background,the current study develops an Improved Duck and Traveller Optimization(IDTO)-enabled cluster-based Multi-Hop Routing(IDTOMHR)technique for ***,IDTO algorithm is exploited for the selection of Cluster Head(CH)and construction of ***,Artificial Gorilla Troops Optimization(ATGO)technique is also used to derive an optimal set of routes to the *** clustering and routing approaches derive a fitness function with the inclusion of multiple input *** proposed IDTOMHR model was experimentally validated for its performance under different *** extensive experimental results confirmed the better performance of IDTOMHR model over other recent approaches.

关键词： Wireless sensor network clustering routing metaheuristics energy efficiency lifetime

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A Clustering based Hybrid Mobility in WPAN 3

A Clustering based Hybrid Mobility in WPAN

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3rd International Conference on Innovative Computing, ICIC 2019

作者： Rizwan, Muhammad Shabbir, Aysha Shabbir, Maryam Ahmad, Fahad Sattar, Mian Usman Kinnaird College for Women Department of Computer Science Lahore Pakistan University of Management and Technology Department of Information System Lahore Pakistan

ISBN: (纸本)9781728146829

IEEE 802.15.4 is a standard for low rate wireless personal area network (i.e. LR-WPANs) and ZigBee based wireless sensor networks (WSNs). This research presents an analysis of clustering based hybrid mobility in IEEE 802.15.4 PAN. This paper unfolds: (1) performance analysis of IEEE 802.15.4 from little to expansive scale PAN;(2) utilization of clustering mobility on remote node prompts to loss of packets. The hybrid mobility designs (directed and undirected mobility) on a remote node has been researched and claimed to contrast in a variable size network. The simulation results expound the relationship of the arbitrary mobility on remote sensor node with influences over the performance metrics of the network, for example, the end-to-end delay, packet loss, and throughput. © 2019 IEEE.

关键词： Zigbee

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Exploring the Intention to Adopt Mining-Stages VR Application Using Modified UTAUT Model: A Perspective of the Philippine Mining Sector 8

Exploring the Intention to Adopt Mining-Stages VR Applicatio...

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8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024

作者： Moyon, Elbert S. Jayoma, Jaymer M. Morales, Edsel Matt O. Information System Department Caraga Butuan City Philippines Information Technology Department Caraga Butuan City Philippines Computer Science Department Caraga Butuan City Philippines

ISBN: (纸本)9798331531492

Virtual Reality (VR) technology has gained attention in education, architecture, gaming, and healthcare industries with proven potential to enhance training and simulation experiences. In the mining sector, VR offers great potential to improve training, effectiveness, and safety;however, understanding the adaptation factors is imperative for a smooth implementation. To understand the factors driving technological acceptance and offer suggestions for effective integration in the industry, this study uses the UTAUT model to examine the adoption of VR applications in the Philippine mining sector. The findings show that adopting the Mining-Stages VR Application is primarily driven by perceived benefits and hedonic motivation, with less influence from social influence and simplicity of use. Furthermore, the behavioral intention of users turns out to be a crucial component in the actual adoption, providing crucial direction for institutions and legislators seeking to encourage the adoption of VR technology in the Philippine mining industry. © 2024 IEEE.

关键词： Mining industry

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Thermal-aware relocation of servers in green data centers

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Frontiers of information technology & Electronic Engineering 2015年第2期16卷 119-134页

作者： Muhammad Tayyab CHAUDHRY T. C. LING S. A. HUSSAIN Xin-zhu LU Department of Computer System & Technology Faculty of Computer Science & Information Technology University of Malaya Kuala Lumpur 50603 Malaysia Department of Computer Science COMSATS Institute of lnformation Technology Lahore 54000 Pakistan

Rise in inlet air temperature increases the corresponding outlet air temperature from the server. As an added effect of rise in inlet air temperature, some active servers may start exhaling intensely hot air to form a hotspot. Increase in hot air tem- perature and occasional hotspots are an added burden on the cooling mechanism and result in energy wastage in data centers. The increase in inlet air temperature may also result in failure of server hardware. Identifying and comparing the thermal sensi- tivity to inlet air temperature for various servers helps in the thermal-aware arrangement and location switching of servers to minimize the cooling energy wastage. The peak outlet temperature among the relocated servers can be lowered and even be homogenized to reduce the cooling load and chances of hotspots. Based upon mutual comparison of inlet temperature sensitivity of heterogeneous servers, this paper presents a proactive approach for thermal-aware relocation of data center servers. The experimental results show that each relocation operation has a cooling energy saving of as much as 2.1 kW·h and lowers the chances of hotspots by over 77%. Thus, the thermal-aware relocation of servers helps in the establishment of green data centers.

关键词： Servers Green data center Thermal-aware Relocation

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Unified resilience model using deep learning for assessing power system performance

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Heliyon 2025年第4期11卷 e42802页

作者： Artemchuk, Volodymyr Garbuz, Iurii Jamil Alsayaydeh, Jamil Abedalrahim Shkarupylo, Vadym Oliinyk, Andrii Bin Yusof, Mohd Faizal Herawan, Safarudin Gazali Department of Mathematical and Econometric Modelling G.E. Pukhov Institute for Modelling in Energy Engineering of the NAS of Ukraine Kyiv Ukraine Department of Environmental Protection Technologies and Radiation Safety Center for Information-analytical and Technical Support of Nuclear Power Facilities Monitoring of the NAS of Ukraine Kyiv Ukraine Department of Іnformation Systems in Economics Kyiv National Economic University Named After Vadym Hetman Kyiv Ukraine Department of Computerized Control System National Aviation University Kyiv Ukraine Department of Engineering Technology Fakulti Teknologi Dan Kejuruteraan Elektronik Dan Komputer (FTKEK) Universiti Teknikal Malaysia Melaka (UTeM) Melaka 76100 Malaysia Department of Computer Systems Networks and Cybersecurity of the National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Department of Software Tools Faculty of Computer Science and Technology Zaporizhzhia Polytechnic National University Zaporizhzhia Ukraine Research Section Faculty of Resilience Rabdan Academy Abu Dhabi United Arab Emirates Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta 11480 Indonesia

Energy resilience in renewable energy sources dissemination components such as batteries and inverters is crucial for achieving high operational fidelity. Resilience factors play a vital role in determining the performance of power systems, regardless of their operating environment and interruptions. This article introduces a Unified Resilience Model (URM) using Deep Learning (DL) to enhance power system performance. The proposed model analyzes environmental factors impacting the resilience of batteries and energy storage devices. This deep learning approach trains performance-impacting factors using previously known low resilience drain data. The learning output is utilized to augment various strengthening factors, thereby improving resilience. Drain mitigation and performance improvements are combined for direct impact verification. This process validates the model's fidelity in enhancing power system performance, with a specific focus on the impact of weather factors. © 2025 The Authors

关键词： Deep learning Energy resilience Fidelity Weather impact

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Design Framework on Tertiary Education system in Indonesia Using Blockchain technology 7

Design Framework on Tertiary Education System in Indonesia U...

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7th International Conference on Cyber and IT Service Management, CITSM 2019

作者： Rahardja, Untung Hidayanto, Achmad Nizar Hariguna, Taqwa Aini, Qurotul Universitas Raharja Tangerang Master of Information System Department Indonesia Universitas Indonesia Depok Master of Computer Science Department Indonesia Universitas Amikom Purwokerto Information System Department Indonesia Universitas Raharja Tangerang Master of Information Technology Department Indonesia

ISBN: (纸本)9781728129099

The objective of the research is to study the blockchain technology impact on the higher education system in Indonesia. Blockchain technology is widely used in other industrial aspects, as well as global utilization and acceptance in education sectors. Few, however, have been found in Indonesia private and public schools, as well as tertiary institutions. Indonesian community and governments struggle to improve the quality of education nationwide and also to face challenging disruption wave of industrial revolution 4.0. In line with RIRN (Rencana Induk Riset Nasional), the government is concentrating on investing in human capital and social capital. Finding an education solution using blockchain technology could be a highly probable solution to national education challenges. Further will be to develop a blockchain technology framework using an artificial intelligence platform that is best suited for Indonesia tertiary education. © 2019 IEEE.

关键词： Blockchain

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