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2nd International Conference on Smart Computing and Electronic Enterprise, ICSCEE 2021

作者： Bamansoor, Samer Pande, Bishwajeet Al Moaiad, Yazeed Pathmanathan, P. Ravindran El-Ebiary, Yousef A. Baker Latiff, Nurul Adilah Abdul Aseh, Khairi Aledinat, Lowai Saleh Yusoff, Fakhrul Hazman MEDIU Faculty of Computer and Information Technology Malaysia Faculty of Informatics and Computing UniSZA Malaysia Gyancity Research Consultancy Pvt Ltd Motihari India MEDIU Faculty of Computer and Information Technology Malaysia International Institute of Applied Science Swiss School of Management Netherlands UniSZA Faculty of Informatics and Computing Malaysia Universiti Malaysia Terengganu Faculty of Ocean Engineering Technology and Informatics Malaysia UniSZA Faculty of Informatics and Computing Malaysia Universiti Teknologi MARA Malaysia

ISBN: (纸本)9781665432221

With the emergence of current developments and their devices that allow correspondence between organizations with each other, just as it is between organizations and service providers, just as with their customers, for some reasons, including advertising and a return to what is acceptable to them with the organization. Items, deals, etc., therefore, this examination provides an internal and external investigation of the current web-based business phase with a focus on promising conditions, risks, qualities, and shortcomings of FashionValet's electronic stage, whose administrations offer more than the Internet. Also, FashionValet is a stage organizer for online shopping and style in Southeast Asia other than Poplook, Zalora, and others, and the bulk of them are important competitors to FashionValet and they implement their own systems. The FashionValet experience, for example, is the history of the creator just as the other company's foundation has been pointed out to characterize how organizations, especially FashionValet, have moved from their primary stage to where they are today as the most aggressive design project. In addition, the technologies and innovations used by FashionValet are shown to provide a comprehensive detailed blueprint. To understand the improvement in style organizations in Malaysia, it was examined further. The paper outlines the critical elements to FashionValet's thriving as an end. © 2021 IEEE.

关键词： Online systems

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Exploring the Benefits of AI for Content Retrieval

Exploring the Benefits of AI for Content Retrieval

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Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Ahmadi Begum Kavitha Karthikeyan Dattatray G. Takale Pawan Bhambu Dhananjay Yadav Sidhant Das Department of Basic Science Faculty of Engineering and Technology JAIN (Deemed-to-be University) Ramnagar Karnataka India Department of Civil Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India

The latest emergence of synthetic Intelligence (AI) and its packages in content retrieval have made it an increasing hobby for educational and technical networks. AI has made the information and utilization of content material retrieval gear less complicated and less complicated, offering a more advantageous consumer revel. This newsletter explores the advantages of AI for content retrieval and affords examples of standard AI-based content material retrieval packages. First, AI algorithms help improve the accuracy of content retrieval, allowing more excellent relevant content material to be retrieved from the web. Furthermore, AI can be used to perceive and advocate content that can be of hobby to the person primarily based on the consumer's possibilities and behaviors. AI can examine textual content files, organizing them into topics and sub-topics to facilitate green content material retrieval. Moreover, online entities such as engines like Google or content recommendation systems can leverage AI-primarily based predictive analytics to tailor content material hints to character users, allowing more powerful content retrieval. In conclusion, AI can help streamline and enhance content retrieval by enhancing the accuracy of seeking outcomes, offering more excellent applicable content pointers, and imparting better organization of documents and topics.

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Facilitating Data Use: Achieving Maximum Efficiency with AI-Enhanced information Capture and Retrieval

Facilitating Data Use: Achieving Maximum Efficiency with AI-...

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Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Dharmesh Dhabliya Nitish Vashisht Swati Singh Mahesh TR Ravindra Kumar V. Mahalakshmi Department of Information Technology Vishwakarma Institute of Information Technology Pune Maharashtra India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science and Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Department of Civil Engineering Vivekananda Global University Jaipur India Department of Electrical and Electronics Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai

The extraordinary boom of data keeps to undertaking the conventional methods to information usage. the use of synthetic intelligence (AI) and gadget studying (ML) is reworking how information is captured and used, as businesses increasingly more undertake a zero-believe approach to garage and retrieval of records. this article explores the ability of AI-enhanced data capture and retrieval to assist groups unleashes the price of their facts with the intention to maximize performance. It covers the basics of AIbased facts capture and retrieval, inclusive of photo popularity, speech reputation, optical character recognition, and herbal language processing (NLP). It additionally examines the effective implications of AI-improved statistics use, in addition to capacity troubles which can prevent or put off its adoption. sooner or later, the thing affords insights into how organizations can equip themselves with the essential AI-based skills to optimize their facts use and selection-making processes.

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Exploring the RFID mutual authentication domain

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International Journal of computers and Applications 2021年第2期43卷 127-141页

作者： Mohsin, Syed Muhammad Khan, Imran Ali Abrar Akber, Syed Muhammad Shamshirband, Shahaboddin Chronopoulos, Anthony T. Department of Computer Science Virtual University of Pakistan Lahore Pakistan Department of Computer Science COMSATS Institute of Information Technology Islamabad Pakistan Wuhan China Department for Management of Science and Technology Development Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Science University of Texas at San Antonio San AntonioTX United States Department of Computer Engineering & Informatics University of Patras Rio Greece

Mutual Authentication is the initial and the most significant line of defense in any open and trusted network system. Weaknesses in mutual authentication protocol may lead to eavesdropping, unauthorized access to the tag or reader data, Denial of Service attack, counterfeiting attack, de-synchronization attack, location tracking, cloning attack, timing attack, man-in-the-middle attack, spoofing attack, and many more. As a result of continuous focus on research of mutual authentication protocols for Radio Frequency Identification (RFID) systems, numerous solutions to address the security issues of RFID system have been proposed. A Comprehensive survey of existing state-of-the-art RFID mutual authentication protocols is presented in this paper. The ultimate objective of this survey paper is to categorize the existing RFID mutual authentication protocols on the basis of their working principle along with their strengths and weaknesses. This categorization of RFID mutual authentication protocols will be beneficial for new researchers to have a quick overview and understanding of the domain and will serve as an input to devise more effective and efficient algorithms for RFID mutual authentication. © 2018 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Surveys

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Uncovering the Link Between Deep Learning and Data Science Practices

Uncovering the Link Between Deep Learning and Data Science P...

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Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Rajarajeswari S Vikas K. Kolekar Manpreet Singh Preeti Naval Savitha R Jyoti Seth Department of Science and Humanities Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Electrical and Electronics Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Ramnagar Karnataka India Department of Computer Science & Engineering Vivekananda Global University Jaipur India

Facts technological know-how has emerge as a vital device for agencies around the sector to understand their customers, optimize their operations, and stay aggressive. But, groups often lack an understanding of the technical factors of records technology, and the way new and rising deep gaining knowledge of strategies can be implemented to resolve their business demanding situations. This paper examines the relationship between deep mastering and records science, in addition to the ways wherein companies can use each to their full potential. It covers the basics of ways deep mastering works, and the way corporations can take benefit of it. Additionally, it discusses how information science satisfactory practices should be integrated right into a deep getting to know software, and the way businesses can make sure they may be leveraging these strategies within the maximum efficient manner. Ultimately, this paper highlights the significance of statistics tradition and the way it can force the adoption of the cutting-edge facts technological know-how and deep getting to know techniques.

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End-to-End Mobility Management in Underwater High Speed Communication Networks

End-to-End Mobility Management in Underwater High Speed Comm...

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Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Geetha Pranali S Ojasvee Kaneria Abhishek Singla Koushik V Prasad Neeraj Das Department of Science and Humanities Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Computer Engineering Vishwakarma Institute of Information Technology Pune INDIA Department of Computer Science & Engineering Vivekananda Global University Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Department of Mechanical Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Ramnagar Karnataka India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

Underwater high pace communique networks have emerge as increasingly critical for an expansion of packages which includes underwater exploration, oil and gas industry, protection, and environmental monitoring. Those networks require reliable and green mobility control strategies to guide the motion of underwater cars and sensors in harsh aquatic environments. The give up-to-end Mobility control in underwater excessive pace verbal exchange Networks targets to provide a comprehensive solution for managing the mobility of nodes in those networks. This answer entails the coordination of diverse layers in the community architecture which includes the bodily, records link, and network layers. at the physical layer, the solution utilizes advanced acoustic conversation techniques which includes beamforming and channel equalization to mitigate the outcomes of multipath fading, Doppler shifts, and sign attenuation. This allows the nodes to keep a dependable communication link even when moving at high speeds. at the records hyperlink layer, the answer carries strategies for seamless handover between extraordinary forms of underwater communique hyperlinks, inclusive of acoustic, optical, and hybrid links. This permits the nodes to exchange among links primarily based on their vicinity and communication requirements, with none disruption to the continuing communication session.

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Robustness Aware SFC Placement in NFV-Enabled Multi-Domain Networks Under Resource Demand Uncertainty

Robustness Aware SFC Placement in NFV-Enabled Multi-Domain N...

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International Conference on Dependable Systems and Their Applications (DSA)

作者： Chuangchuang Zhang Shou-Yu Lee Pan Liu Hongyong Yang William Cheng-Chung Chu School of Information and Electrical Engineering Ludong University Yantai China Department of Computer Science Tunghai University Taiwan Faculty of Business Information Shanghai Business School Shanghai China School of Computing and Artificial Intelligence Fuyao University of Science and Technology China

ISBN: (数字)9798331532390

ISBN: (纸本)9798331532406

The increasing service demands in 5G networks have led to the emergence of Network Function Virtualization (NFV) technology. Through the virtualization technique, NFV enables on-demand and flexible service provisioning and deployment by implementing networks functions in forms of software instances, called Virtual Network Functions (VNFs). With the rapid development and implementation of 5G, the Service Function Chain (SFC) placement problem in multi-domain network scenarios is gaining significant attentions due to the sudden and dynamic patterns of resource demands from a diversity of service requests. Most existing proposals attempt to optimize the SFC placement in multi-domain networks, under the assumption that resource demand required each service request is given in prior and keeps unchanged during the SFC execution period. However, it is impractical in real network scenarios due to the evolving dynamic changes of service requests. The uncertainty of service demands has an important effect on service reliability, service quality and network performance. To this end, in this paper, we study the problem of robust SFC placement in multi-domain networks under the assumption that resource demands of SFC requests are uncertain. We first formulated the problem of robust SFC placement in multi-domain networks as an integer programming model with the aim to minimize the SFC placement cost while considering the Quality of Service (QoS) guarantee. Then, we develop a three-stage heuristic placement algorithm to solve the problem. The extensive simulation results demonstrate that our proposed heuristic algorithm is efficient and can save more placement cost than comparison mechanisms.

关键词： Integer programming Costs Uncertainty 5G mobile communication Heuristic algorithms Simulation Quality of service Software Network function virtualization Virtualization

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GRAPH THEORETICAL MODELS AND ALGORITHMS OF PORTFOLIO COMPRESSION

arXiv

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arXiv 2022年

作者： Hanics, Mihály Péter Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Computer Science and Information Theory Hungary

Matching problems under preferences gained significant attention not just in mathematical sciences, but in other fields too since the paper published by Gale and Shapley in 1962-ben on the college admission being modelled as a matching problem with preferences, and Al Roth's work on matching problems in practice, such as modelling kidney exchanges as matching markets. For their work on matching markets, Roth and Shapley received the 2012 Nobel Memorial Prize in Economics. Today, this interdisciplinary field extended to other parts of mathematics, for example, stability of flows is examined, and focuses on the real-life application of this field. One such application is financial clearing, or portfolio compression. Market participants (banks, organizations, companies, financial agents) sign contracts, creating liabilities between each other, which increases the systemic risk. Large, dense markets commonly can be compressed by reducing obligations without lowering the net notional of each participant (an example is if liabilities make a cycle between agents, then it is possible to reduce each of them altogether without any net notional changing), and our target is to eliminate as much excess notional as possible in practice (excess is defined as the difference between gross and net notional). A limiting factor which may reduce the effectiveness of the compression can be the preferences and priorities of compression participants, who may individually define conditions for the compression, which must be considered when designing the clearing process, otherwise a participant may bail out, resulting in the designed clearing process to be impossible to execute. These markets can be well-represented with edge-weighted graphs. In this paper, I examine cases when preferences and conditions of participants on behalf of clearing are given, e.g., in what order would they pay back their liabilities (a key factor can be rate of interest) and I show a clearing algorithm for these p

关键词： Graph theory

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PSO-based procedure to find number of clusters and better initial centroids for K-means algorithm: Image segmentation as case study

PSO-based procedure to find number of clusters and better in...

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International Conference on Pattern Recognition and Image Analysis (IPRIA)

作者： M. Alizadeh Zarei A. M. Nickfarjam Department of Computer Engineering Faculty of Electrical and Computer Engineering Islamic Azad University of Kashan Kashan Iran Department of Health Information Management and Technology Kashan University of Medical Sciences Kashan Iran Research Centre for Health Information Management Kashan University of Medical Sciences Kashan Iran

In this paper, we propose a combination of K-means algorithm and Particle Swarm Optimization (PSO) method. The K-means algorithm is utilized for data clustering. On one hand, the number of clusters (K) should be determined by expert or found by try-and-error procedure in the K-means algorithm. On the other hand, initial centroids and number of clusters (K) are influenced on the quality of resulted grouping. Therefore, the aim of the proposed procedure is using PSO and the Structural Similarity Index (SSIM) criterion as a fitness function in order to find the best value for K parameter and better initial clusters' center. Due to different value of K parameter, the number of initial centroids which should be produced is variant. Thus, length of particles in PSO method may be different in each iteration. Experimental results show the superiority of this approach in comparison with standard K-means algorithm and both of them are evaluated on image segmentation problem.

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Contract-Based Incentive Mechanism for Blockchain-Enabled Federated Learning in Vehicle Edge Computing

Contract-Based Incentive Mechanism for Blockchain-Enabled Fe...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Runchen Xu Zheng Chang Zhiwei Zhao Geyong Min School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Information Technology University of Jyväskylä Jyväskylä Finland Department of Computer Science University of Exeter Exeter U.K.

Vehicular edge computing (VEC) has been introduced to bring powerful in-proximity computing solutions to vehicles. VEC is able to boost the development of vehicular networks by handling computing tasks and accommodating artificial intelligence (AI). To fulfill the requirements of low latency and security in realizing AI for vehicular networks, and fully utilize the vehicles' capabilities on sensing and computing, federated learning (FL) in VEC emerges as a potential solution. However, privacy protection, data security and information asymmetry issues pose challenges on efficiently and securely motivating more vehicles to participate in FL. Thus, this paper proposes a contract-based incentive mechanism for blockchain-enabled FL, which employs contract theory to establish an optimal contract design between VEC servers and vehicles. We present the necessary and sufficient conditions to obtain an optimal contract and analyze the simplification of the constraints. The simulation results show that our proposed method is effective in providing incentives and outperforms other benchmark schemes.

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