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9th IEEE International Conference on Computational Intelligence and Applications, ICCIA 2024

作者： Thongpiem, Jirawat Punkong, Narong Ratanavilisagul, Chiabwoot Kosolsombat, Somkiat Faculty of Applied Science Department of Computer and Information Sciences Bangkok Thailand Digital Technology for Business Faculty of Management Science Kanchanaburi Thailand Data Science and Innovation College of Interdisciplinary Studies Thammasat University Pathum Thani Thailand

ISBN: (纸本)9798350352214

The traveling salesman problem (TSP) is a combinatorial optimization problem and a NP-complete problem. It is a well-known problem for comparison of algorithm performance. Many researchers try to solve the TSP by the meta-heuristic algorithms. Ant Colony Optimization (ACO) algorithm is a popular method to solve the TSP. To enhance performance of ACO for solving TSP, the recently proposed improving the ACO algorithm by the results from searching for 2-OPT algorithms that are applied with pheromones of ants. Moreover, when the population of ACO occurs trapping in local optimum, the pheromone of ants is re-initialized to solve trapping in local optimum problem. This algorithm is called Modified Ant Colony Optimization with updating Pheromone by Leader and Re-initialization Pheromone (MACO-LR). However, performance searching of MACO-LR can be improved. In this research, we propose to solve TSP using Hybrid Genetic Algorithm and Ant Colony Algorithm (HGAACO) to optimize the total travelled distance. The proposed technique is tested on twenty-three maps from the Traveling Salesman Problem Library (TSPLIB) and it is composed with MACO-LR. The results from the experiment show the proposed technique can enhance performance searching of MACO-LR. © 2024 IEEE.

关键词： Ant colony optimization

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'Do Not Disturb': An Implication Design To Be Alerted But Less Stress

'Do Not Disturb': An Implication Design To Be Alerted But Le...

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2023 International Seminar on Application for technology of Information and Communication, iSemantic 2023

作者： Jarupreechachan, Weerachaya Kitchat, Kotcharat Surasak, Thattapon Kasetsart University Faculty of Engineering at Kamphaeng Saen Dept. of Computer Engineering Nakhon Pathom Thailand National Central University Dept. of Computer Science and Information Engineering Taoyuan Taiwan King Mongkut's University of Technology North Bangkok Faculty of Applied Science Dept. of Computer and Information Science Bangkok Thailand

ISBN: (纸本)9798350339215

The pervasive utilization of smartphones, while augmenting personal and professional communications, also elicits mental stress and disrupts the work-life balance. Users necessitate staying connected to critical updates without undue disruption, necessitating an optimized, user-friendly smartphone interface. However, current "Do Not Disturb (DND)"features fall short of providing the desired customization options, thereby contributing to heightened anxiety and diminished productivity. Consequently, this study proposes a design modification to the DND mode by incorporating an "Exceptional Apps Notification", feature thereby aiding in alleviating stress and enhancing focus by permitting essential alerts from selected apps or contacts. In other words, the users only need to turn off notifications for specific applications, not every application. This approach addresses the problem of users fearing they will miss some important notifications. Therefore, the design process employed principles of selective attention and color theory, and user experience was assessed through questionnaires and psycho-physiological feedback. Early findings suggest the potential for stress reduction, albeit with opportunities for further optimization, such as including a memory feature for user preferences and allowing selective access for specific contacts. © 2023 IEEE.

关键词： User interfaces

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SimV: A Self-extension Similarity Viterbi Algorithm for Service Function Chain Deployment for Multi-access Edge Computing

SimV: A Self-extension Similarity Viterbi Algorithm for Serv...

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International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Wenqiang Deng School of Computer Science Guangzhou College of Applied Science and Technology Zhaoqing China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Advancements in Multi-access Edge Computing (MEC) and Network Function Virtualization (NFV) offer a lot of potential for providing flexible and low-latency network services at the edge. In NFV, traditional middleboxes are transformed into Virtual Network Functions (VNFs), which are then combined into Service Function Chains (SFCs) to deliver complex network services. However, the features of MEC hosts and VNFs, along with the heterogeneity of their resources, make it challenging to develop low-latency deployment solutions. In this paper, we formulate the problem of Service Function Chain Deployments in Edge networks to minimize Latency under Heterogeneous conditions (SDELH). To address this problem, we designed a self-extension Similarity Viterbi algorithm (SimV), which contains three sub-algorithms. Firstly, a basic Viterbi algorithm is employed to find the delay-optimized SFC deployment path. Secondly, a similarity algorithm is designed to assess suitable hosts for each VNF to streamline the matching process and reduce the time complexity of the Viterbi algorithm. Lastly, a self-extension method is devised to broaden the solution space for enhancing the SFC acceptance rate. Extensive simulations are conducted. Based on the comparison simulation results, SimV significantly reduces decision time for deployment, and outperforms the compared algorithms in terms of latency, number of accepted requests, and scalability, with average improvements of 20.37%, 6.04%, and 14.49%, respectively.

关键词： Distributed processing Multi-access edge computing Viterbi algorithm Service function chaining Scalability Simulation Middleboxes Network function virtualization Low latency communication Time complexity

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Fog Computing – Desktop Review

Fog Computing – Desktop Review

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International Multidisciplinary Information technology and Engineering Conference (IMITEC)

作者： Sicelo Prince Sithole Naume Sonhera Tranos Zuva Department of Computer Science Faculty of Applied and Computer Sciences Vaal University of Technology Vanderbjilpark South Africa

ISBN: (数字)9798350387988

ISBN: (纸本)9798350387995

Fog computing is an innovative approach that brings cloud computing capabilities to the edge of the network, and it has great potential for enterprises looking to improve real-time data processing and lower latency. However, the adoption of fog computing in organizations remains relatively unexplored. This review paper aims to investigate the factors influencing fog computing adoption in organizations. Through a systematic review of existing literature, case studies, and expert opinions, this paper identifies and analyses the unique adoption factors. The review examines challenges, characteristics, benefits, and Open Fog Computing Issues with the Internet of Things (IoT), shaping fog computing adoption decisions in organizations across various industries. This analysis highlights fog computing advantages over traditional cloud computing approaches, such as low latency, improved data privacy, and enhanced scalability. Furthermore, this review investigates the challenges hindering the adoption of fog computing, including security concerns, implementation complexity, connectivity, and lack of awareness, as well as open fog computing issues with IoT. Key findings indicate that while fog computing can offer low-latency solutions, organizations face considerable challenges, including security risks, implementation complexity, and a lack of skilled personnel. By synthesizing and analysing the findings, this paper provides valuable insights for decision-makers, researchers, and policymakers seeking to promote and facilitate fog computing adoption.

关键词： Industries Cloud computing Standards organizations Organizations Medical services Real-time systems Complexity theory Security Internet of Things Edge computing

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A local meshless method for solving multi-dimensional Galilei invariant fractional advection–diffusion equation

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Engineering Analysis with Boundary Elements 2022年 143卷 283-292页

作者： Eslami, Samira Ilati, Mohammad Dehghan, Mehdi Department of Applied Mathematics Faculty of Basic Sciences Sahand University of Technology Tabriz Iran Department of Applied Mathematics Faculty of Mathematics and Computer Science Amirkabir University of Technology Hafez Ave. TehranNo. 424 Iran

In this article, a local meshless technique is applied for numerical simulation of multi-dimensional Galilei invariant fractional advection–diffusion model on regular and irregular computational domains. In the suggested method, a second-order Crank–Nicolson scheme along with the second-order weighted and shifted Grünwald difference (WSGD) formula, is used to discretize the time derivatives of the model. This time-discretization scheme is unconditionally stable and convergent with order O(τ2). To approximate the spatial derivatives of this model, a local radial point interpolation technique is employed. Finally, to prove and demonstrate the validity of the proposed algorithm, various one, two and three-dimensional problems are investigated on regular and irregular computational domains. © 2022 Elsevier Ltd

关键词： Diffusion

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Classifying Psychiatric Patients Using Machine Learning 25

Classifying Psychiatric Patients Using Machine Learning

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25th International Arab Conference on Information technology, ACIT 2024

作者： Alrjoob, Hmmam M. Alazaidah, Raed Batyha, Radwan Khafajeh, Hayel Elsoud, Esraa Abu Saeb Al-Sherideh, Ala'a Elrashidi, Ali Alqaraleh, Muhyeeddin Amer, Waleed Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan Zarqa University Faculty of Information Technology Department of Data Science and Ai Zarqa Jordan Applied Science Private University Faculty of Information Technology Department of Computer Science Amman Jordan Zarqa University Faculty of Information Technology Department Computer Science Zarqa Jordan Zarqa University Faculty of Information Technology Department of Cyper Security Zarqa Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia Zarqa University Faculty of Information Technology Department of Software Engineering Zarqa Jordan Zarqa University Faculty on Information Technology Department of Cyber Security Zarqa Jordan

ISBN: (纸本)9798331540012

Psychological disorders are considered chronic illnesses that affect a wide range of populations. Some studies in the United States indicate that one in every eight individuals is affected by a psychological disorder. Additionally, individuals with a psychological disorder often have an impact on the nature of the lives of those around them. It is beneficial to detect the illness in its early stages to increase the likelihood of recovery. In this research, thirteen classification algorithms are used. Each algorithm has an interesting approach. It can be used to analyze several datasets where three datasets specific to Psychiatric patients were selected. The datasets have been chosen from UCI Machine Learning Repository. The datasets were re-analyzed after only 50% of the characteristics were approved after being evaluated by the several feature selection techniques. The main objective of this research is to find the best classifier and feature selection strategy in analyzing datasets of Psychiatric patients. After conducting numerous comparisons, it became evident that, the best classifier for the Autism-Adult-Data dataset are Bagging and Random Forest. As for the best learning strategy, it was found to be Functions and Trees, the best feature selection was obtained using Symmetrical Uncourt Attribute Evaluation. Both IBK and KStar classifier proved to be the best classifier for the Parkinson's dataset, Lazy demonstrated to be the most effective learning strategy, Correlation Attribute Evaluation technique yielded the best feature selection. Logistic emerged as the best classifier for planning-relax dataset, the best learning strategy was Bayes, the best feature selection was found to be Symmetrical Uncert Feature Selection. © 2024 IEEE.

关键词： Contrastive Learning

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Automated Road Toll Collection and Vehicle Tracking (ARTCVT) Using Advanced RFID and GSM technology

Automated Road Toll Collection and Vehicle Tracking (ARTCVT)...

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2022 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2022

作者： Khder, Moaiad Ahmad Dawood, Kareem Abbas Abdal, Rozin Badeel Alqaisy, Sarah Abdulrahman Applied Science University Bahrain Komar University of Science and Technology Computer Science Department Kurdistan Region Iraq Malaysia

ISBN: (数字)9781665469197

ISBN: (纸本)9781665469197

Toll plazas in Malaysia now utilize two passing techniques for toll collection: touch n' go and smart tag. These methods are not fast which is time-consuming the car pausing to pay the toll, or passing slowly if utilizing smart tags, cause heavy traffic, and makes the queues appear prior to the tollbooths, furthermore, none of these technologies has been using a tracking system to detect the number of the vehicles that are contrary to traffic law. In this paper, we propose using advanced Radio Frequency Identification (RFID) and Global System for Mobile (GSM) technology (ARTCVT) to automate road toll collection and vehicle tracking to eliminate delays on toll roads by collecting tolls electronically, as well as to automatically track vehicles that violate rules, Automatic process of toll collection will save time, effort, and manpower. Moreover, can be very effective to support social distancing during pandemics. An RFID tag will be fixed in the vehicle's front glass;this tag will hold a unique identification number issued by the traffic authority;all the basic information of the vehicle and driver in addition to the amount of money for the toll collection will store and identify with the identification number. The toll amount will be deducted automatically whenever the vehicle passes through the toll gate and the balance will be updated, the deducted amount and new balance will send to the driver as an SMS message. SMS as a reminder to top up the account will be sent in case of insufficient balance. The advantages of our proposed system are reduced traffic jams and save fuel consumption, time, effort, and manpower. © 2022 IEEE.

关键词： Traffic congestion

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Text Post-processing on Optical Character Recognition output using Natural Language Processing Methods 3

Text Post-processing on Optical Character Recognition output...

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3rd IEEE Mysore Sub Section International Conference, MysuruCon 2023

作者： Thangam Kumaran, U. Biswas, Dipshikha Sneha, B. Nadipalli, Suneel Raja, Saleem Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India University of Technology and Applied Sciences Shinas Oman

ISBN: (纸本)9798350340358

The technique of turning images of printed or written text from scanned documents, images of documents, or simple photos into machine-encoded text is known as optical character recognition (OCR). OCR has proven to be very useful in terms of digitizing documents and making them easier to analyze. Despite the advancement in the technology since it was introduced, there are still areas OCR falls short. If either the written text is illegible, or the OCR software isn't powerful enough, it results in inaccurate translations. This research work aims at addressing this shortcoming by performing post-processing on OCR outputs primarily using Transformers such as BERT in a two-step pipeline to correct these mistakes and improve the quality of the document. © 2023 IEEE.

关键词： Optical character recognition

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A Blockchain Framework for Investment Authorities to Manage Assets and Funds 5th

A Blockchain Framework for Investment Authorities to Manage ...

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5th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing, BDCC 2022

作者： Sherimon, P.C. Sherimon, Vinu Thomas, Jeff Jaimon, Kevin Faculty of Computer Studies Arab Open University Muscat Oman Department of IT University of Technology and Applied Sciences Muscat Oman Department of Computer Science and Engineering Saintgits College of Engineering Kerala Pathamuttam Kottayam India

ISBN: (纸本)9783031283239

Investment authorities are broad financial institutions that carefully manage investments on behalf of the national government using a long-term value development approach. To provide a stronger structure or framework for Investment Authorities to govern the distribution of funds to public and private markets, we have started research to create a blockchain-based prototype for managing and tracking numerous finances of such authorities. We have taken the case study of Oman Investment Authority (OIA) of Sultanate of Oman. Oman’s wealth is held in OIA. It is the organization that oversees and utilizes the additional capital generated by oil and gas profits in public and private markets. Unlike other Omani funds, this one focuses primarily on assets outside the Sultanate. The operation of the OIA entails a large number of transactions, necessitating a high level of transparency and administration among the parties involved. Currently, OIA relies on various manuals to achieve its goals, such as the Authorities and Responsibilities manual, the Investment Manual, and the Code of Business Conduct, among others. In this paper, we propose a blockchain-based framework to manage the operations of OIA. Blockchain is a part of the Fourth Industrial Revolution, and it is reshaping every industry. The main components of every blockchain are assets and participants. The funds are the major assets in the proposed study, and the participants are the various fund shareholders/recipients. The blockchain’s transactions are all safe, secure, and immutable, and it is part of a trust less network. The transactions are simple to follow and verify. By replacing intermediary firms with smart contracts, blockchain-based solutions eliminate any middlemen in the fund allocation process. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Blockchain

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Statistical Investigation of Scientific Journals Impact Factors in Relation to Benford's Law 6

Statistical Investigation of Scientific Journals Impact Fact...

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6th IEEE Novel Intelligent and Leading Emerging sciences Conference, NILES 2024

作者： Sorour, Marwa A. Marey, Yassmine A. Halim, Islam Tharwat Abdel Kasem, Mohamed Mahran School of Information Technology and Computer Science Nile University Giza Egypt Nile University Giza Egypt Alexandria University Faculty of Engineering Egypt School of Engineering and Applied Science Nile University Giza Egypt

ISBN: (纸本)9798350378511

Benford's law (BL) has been used as a tool for the detection of possible data manipulation in datasets. The statistics of the first digit(s) of the observed values are compared to a set of expected values given by BL, and violations signal possible data anomalies. Though this method is first used for economical purposes, it has been recently used in bibliometric statistical analyses. The method provides alert that records may have certain unusual trends. In the present work, we investigate the impact factor statistics for 24 years starting from 1997 up to 2021, for open access and subscribed journals. We study conformity to BL using the basic first digit(s) violation test and the mantissa arc test, besides using the relative size factor test. Results show that open access journals adhere to Benford's Law more closely than subscribed journals. © 2024 IEEE.

关键词： Open access

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