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ASIS Edge Computing Model to Determine the Communication Protocols for IoT Based Irrigation

Journal of Mobile Multimedia 2022年第3期18卷 885-916页

作者： Premkumar, S. Sigappi, A.N. Department of Computer Science & Engineering Faculty of Engineering & Technology Annamalai University Tamilnadu India

Internet of Things (IoT) provide a promising Smart irrigation facilitator for continual monitoring and control of environmental parameters, thereby leading to a huge volume of data to be efficiently collected, transferred, processed and stored. The deployment of cloud-based infrastructure with on-field connectedness, allowing information exchange among IoT nodes, and the usage of energy scavenging (e.g., solar power) in feeding them, become necessary, since agricultural fields are in lack of wired energy supply and, often, a reliable (Internet) network coverage. Therefore, these issues can be addressed through the integration of Edge computing in IoT scenarios. An efficient strategy is required to select the best communication technology with a motive of increasing the network performance between the IoT devices, Edge device and cloud. Application Specific Infrastructure Selection (ASIS) is an edge computing model developed to select the appropriate communication protocols according to the infrastructure requirements of three different real time scenarios namely: Assembly line automation, Smart parking system and Automatic irrigation system are deployed to get the most suitable application specific protocol from ZigBee, LoRa (Long Range) and LoWPAN (Low-Power Wireless Personal Area Network) to implement in real-time basis. ASIS model is proposed as a network resource manager that is capable of sensing, acting, signal processing, and/or communication abilities to perform a protocol selection according to their physical and technological limitations. Further Edge based ASIS model is developed to enhance the network performance even better when compared with cloud-based model. Automatic irrigation system is extended in the Edge based ASIS model. The overall ASIS system is evaluated by means of network parameters such as network usage, network delay and power consumption. The ASIS model and Edge based ASIS model is deployed in iFogSim simulator that compares each protoc

关键词： Cloud infrastructure Edge computing IFogSim Internet of things Irrigation system LoRa LoWPAN Network protocols Zigbee

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Smart ports: Sustainable smart business port operation schemes based on the Artificial Intelligence of Things and blockchain technologies

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IEEE Potentials 2022年第6期41卷 32-37页

作者： Kuo, Szu-Yu Huang, Xiang-Rui Chen, Liang-Bi National Kaohsiung University of Science and Technology Department of Shipping and Transportation Management Kaohsiung811213 Taiwan National Penghu University of Science and Technology Computer Science and Information Engineering Penghu Magong880011 Taiwan

In recent years, the application and development of the Internet of Things (IoT) has increased significantly. In general, the IoT requires many technologies. Usually, a large amount of IoT sensor information is collected through IoT devices, and devices are connected to each other through IoT communication technology. The Internet exchanges and transmits information, issues instructions and commands to the device, and then conducts prediction and decision making by artificial intelligence (AI) after big data analysis, which is called the AI of Things (AIoT) system. © 1988-2012 IEEE.

关键词： Internet of things

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The Study of User Experience Interview Using Semantic Analysis and Short-Term Memory Chatbot 8

The Study of User Experience Interview Using Semantic Analys...

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8th International Conference on information technology, InCIT 2024

作者： Krutta, Manassanun Phongpaibul, Monvorath Thammasat University Faculty of Science and Technology Department of Computer Science Pathumthani Thailand

ISBN: (纸本)9798350366303

There are many ways to study user experience, each with its own strengths and weaknesses. One popular method is questionnaires. However, questionnaires may not provide deep insights. Phanupong's research proposed a chatbot using semantic analysis and short-term memory called SEBASS. This chatbot uses a customized semantic short-term memory with RDF as a knowledge representative for the chatbot's memory. We applied SEBASS, a semantic short-term memory service chatbot, to query the user experience of the MICROSOFT® TEAMS application. Comparison with traditional chatbot and online interview, results show that both BASELINE chatbot and traditional chatbot can effectively interact with the participants in querying the user experience of the MICROSOFT® TEAMS application. Compared to online interviews conducted by humans, the SEBASS chatbot is equally effective in extracting insight user interface information as evidenced by high average scores in specificity, clarity, average number of nodes, and percentage of depth in UI knowledge RDF. © 2024 IEEE.

关键词： chatbot interview shortterm memory user experience user interface

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WALGES: Weighted Probability Based Scoring Approach for Solving Algebraic Word Problems using Semantic Parsing 2

WALGES: Weighted Probability Based Scoring Approach for Solv...

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2nd International Conference on Electrical, computer and Communication Engineering, ECCE 2019

作者： Rahman, Habibur Rahman, Julia Husna, Asmaul Department of Computer Science and Engineering University of Information Technology and Sciences Dhaka Bangladesh Department of Computer Science and Engineering Rajshahi University of Engineering and Technology Rajshahi Bangladesh

ISBN: (纸本)9781538691113

Virtual assistants like Google Assistant, Siri, Cortana, and many others, are now the major feature of smart-phones and tablets. Natural language understanding is the most promising part of those. Besides question and answering, sometimes those smart assistants face verbally stated mathematical problems. Algebraic word problems are one of the fundamental mathematical problems where financial news, election results, sports results, and many other services are also related. In this paper, we have generated solutions of the algebraic word problems. Semantic parsing is used to ground the problem text into containers, quantities, and entities to generate equation trees. From the equation trees, features are extracted to train a local and a global classifier model. After that, to find the candidate equation from the generated equation, probabilistic scores from the local and the global classifier models have used. Backpropagation neural network algorithm is used to incorporate the probabilistic scores of the local and the global classifier models with weights. Our proposed weighted probability based scoring approach increases the accuracy to predict the solution of the algebraic word problems about 9% surpassing the existing system. Our result showed that our proposed technique is useful. © 2019 IEEE.

关键词： Forestry

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Wrist joint synovial hypertrophy and effusion detection in musculoskeletal ultrasound images using self-attention U-Net

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Multimedia Tools and Applications 2024年第41期83卷 89317-89334页

作者： Chang, Chuan-Wang Chang, Chuan-Yu Zhu, Yu-Xian Wang, Sz-Tsan Department of Computer Science and Information Engineering National Chin-Yi University of Technology Taichung Taiwan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Douliu Taiwan Division of Allergy Immunology and Rheumatology Dalin Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Dalin Chiayi Taiwan

Skeletal muscle ultrasound has emerged as a pivotal imaging modality in rheumatology clinics, offering unparalleled advantages such as radiation-free imaging, safety, and dynamic examination capabilities. However, its reliance on operator expertise often leads to inconsistent interpretations and diagnostic variability. In this study, we present a novel diagnostic system aimed at detecting rheumatoid arthritis (RA) in the wrist joint, with a focus on identifying synovial hypertrophy and effusion using musculoskeletal ultrasound images. Leveraging deep learning techniques, specifically semantic segmentation models, we introduce SEAT-UNet, which combines the U-Net architecture with a self-attention mechanism to enhance the accuracy of lesion classification and localization. SEAT-UNet addresses the challenge of discontinuous dispersion encountered in conventional segmentation models, particularly when delineating lesion areas. Our experimental results demonstrate exceptional performance, achieving a sensitivity and Dice coefficient of 100% and 84%, respectively, in synovial hypertrophy detection, and 86% sensitivity with an 84% Dice coefficient in effusion detection. These findings underscore the potential of SEAT-UNet as a valuable tool for early RA diagnosis, offering improved patient outcomes and facilitating more effective disease management strategies. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Diagnosis

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Improving the Efficiency of Smart Grid Scheduling: A Linear Regression Model with Meta Job information 2

Improving the Efficiency of Smart Grid Scheduling: A Linear ...

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： Al-Najjar, Hazem Al-Rousan, Nadia College Of Information Technology University Of Petra Department Of Computer Science Amman Jordan German Jordianian University Faculty Of Electrical Engineering And Information Systems Department Of Computer Engineering Jordan

ISBN: (纸本)9798350394962

In order to forecast the run time of the jobs that were submitted, this research provides two linear regression prediction models that include continuous and categorical factors. A continuous predictor is built using the number of CPUs, average CPU speed, and memory size, whereas a categorical predictor is built using the user ID, group ID, and executable ID. According to the findings, the prediction rates for categorical and continuous predictors are 61% and 1%, respectively. sixty times better than the earlier models, which used continuous variables as a foundational model to determine task complexity and weight. The effectiveness of the categorical predictor in enhancing a job scheduling problem is then evaluated by combining it with three suggested job scheduling strategies. The suggested algorithms incorporated metrics - predicted run time, waiting time, and resource requirement - to select the smallest jobs. According to the results, Algorithm 3 performs better than earlier models in both performance metrics. The variation in total execution time and average waiting time is 1.14 to 1.76 and 4.5, respectively compared to previous models, Additionally, Algorithms 1 and 2 demonstrating superior performance in every scenario. © 2024 IEEE.

关键词： Grid computing

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IoMT-Based Smart Monitoring Hierarchical Fuzzy Inference system for Diagnosis of COVID-19

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computers, Materials & Continua 2020年第12期65卷 2591-2605页

作者： Tahir Abbas Khan Sagheer Abbas Allah Ditta Muhammad Adnan Khan Hani Alquhayz Areej Fatima Muhammad Farhan Khan Department of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Information Sciences Division of Science&TechnologyUniversity of EducationLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science and Information College of Science in ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Forensic Sciences University of Health SciencesLahore54000Pakistan

The prediction of human diseases,particularly COVID-19,is an extremely challenging task not only for medical experts but also for the technologists supporting them in diagnosis and *** deal with the prediction and diagnosis of COVID-19,we propose an Internet of Medical Things-based Smart Monitoring Hierarchical Mamdani Fuzzy Inference system(IoMTSM-HMFIS).The proposed system determines the various factors like fever,cough,complete blood count,respiratory rate,Ct-chest,Erythrocyte sedimentation rate and C-reactive protein,family history,and antibody detection(lgG)that are directly involved in *** expert system has two input variables in layer 1,and seven input variables in layer *** layer 1,the initial identification for COVID-19 is considered,whereas in layer 2,the different factors involved are ***,advanced lab tests are conducted to identify the actual current status of the *** major focus of this study is to build an IoMT-based smart monitoring system that can be used by anyone exposed to COVID-19;the system would evaluate the user’s health condition and inform them if they need consultation with a specialist for ***-2019a tool is used to conduct the *** COVID-19 IoMTSM-HMFIS system has an overall accuracy of approximately 83%.Finally,to achieve improved performance,the analysis results of the system were shared with experts of the Lahore General Hospital,Lahore,Pakistan.

关键词： IoMT MERS-COV Ct-chest ESR/CRP ABD(lgG) Fuzzy logic HMFIS WHO

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A computational framework for Carreau nanomaterial induced by stretchy regime considering Brownian diffusion, viscous dissipation, ferromagnetism and thermophoresis

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Partial Differential Equations in Applied Mathematics 2025年 13卷

作者： Hussain, Iftikhar Khan, Waqar Azeem Tabrez, Muhammad Waqas, M. Ibrahim, Talib K. Saidani, Taoufik Kausar, M.S. Zamri, Nurnadiah Abdullaeva, Barno Garalleh, Hakim AL Department of Mathematics Mohi-ud-Din Islamic University Nerian Sharif Jammu and Kashmir Azad 12010 Pakistan School of Mathematics and Statistics Beijing Institute of Technology Beijing 100081 China NUTECH School of Applied Sciences and Humanities National University of Technology Islamabad 44000 Pakistan Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Besut Campus Terengganu Besut 22200 Malaysia Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Department of Petroleum Engineering College of Engineering Knowledge University Erbil 44001 Iraq Department of Petroleum Engineering Al-Kitab University Altun Kupri Iraq Center for Scientific Research and Entrepreneurship Northern Border University Arar 73213 Saudi Arabia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin (Kampus Gong Badak) Terengganu Kuala Terengganu 21300 Malaysia Department of Mathematics and Information Technologies Vice-Rector for Scientific Affairs Tashkent State Pedagogical University Tashkent Uzbekistan Department of Mathematical Science College of Engineering University of Business and Technology Jeddah 21361 Saudi Arabia

In recent decade, the research in nanotechnology brought the idea of nanofluids which are highly conducting materials. Some important applications of nanofluids are justified in pharmaceutical industry, coolants in vehicles engine, preparation process of various medicines for treatment of fatal diseases like cancer, aircraft industry, latest heat exchangers etc. The ferro particles are special class of nanomaterial which attract variety of interest from the researchers. The objective of current research is to perform the investigation for heat and mass transfer subject to Carreau nanofluid to observe the enhancement of heat transmission phenomena. The induction of magnetic dipole has been observed for thermal transport phenomenon. The flow is causing by stretched surface. A simplified system is obtained by utilizing the dimensionless variables. Physical interpretation of results have been presented. Result showed that temperature profile in presence of ferrofluid fluid boosts up with escalation in thermophoresis parameter, while opposite behavior is noted for power law index. The concentration of ferrofluid showing declining behavior for Schmidt numbers and rises for thermophoresis parameter. © 2024

关键词： Carreau ferrofluid Heat and mass transfer Magnetic dipole Numerical solution

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Implications of Onshore Development on Global Software Engineering

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computers, Materials & Continua 2023年第2期74卷 3029-3044页

作者： Abdulrahman M.Qahtani Ahmed S.Ghiduk College of Computers and Information Technology Taif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Mathematics and Computer Science Faculty of ScienceBeni-Suef UniversityBeni-Suef62521Egypt

Recently software industry has paid significant attention to customizing software products across distributed *** the requirements of multiple clients across distributed borders is a crucial challenge for the software customization *** decision-making and local development at the client site are considered methods for reducing difficulties in communicating the requirements of multiple clients across distributed *** paper introduces a new model called the onshore development model(ODM)for accomplishing the customization requests in the distributed development process of *** model presents a scenario for enhancing the onsite development of specific requirements to reduce delays andmisunderstandings between the clients and the team *** model depends on moving the development process to the client’s *** empirical studies were conducted to evaluate the proposed model to measure its productivity,time performance,and cost *** proposed model has been compared with two other models:the basic model(BM),which allocates the decision-making process and the development process for teams at the vendor’s location,and the local decision-making model(LDec),which assigns the decision-making process for team at the client’s *** results of the empirical studies showed significant outperforming of the proposed model over the basic model and local decision-making model in productivity,time performance,and cost *** productivity of the proposed model improved by 39%and 10%more than the basic model and the local decision-making model,*** addition,the time performance of the proposed model became faster by 49%and 20.8%than the basic model and the local decision-making model,***,it reduced the total cost of the development process by 31%in terms of the salaries of all persons involved in requirements collecting,decision-making,and development.

关键词： Distributed development local development software customization

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information technology knowledge management in Malaysian Armed Forces

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Journal of Convergence information technology 2012年第6期7卷 178-184页

作者： Nohuddin, Puteri N.E. Isa, Mohd Rizal Mohd Shukran, Mohd Afizi Mohd Department of Computer Science Faculty of Science and Technology Defense National Defense University of Malaysia Sungai Besi Camp 57000 Kuala Lumpur Malaysia

information technology Knowledge Management (ITKM) is a process that helps organization to create, identify, manage and distribute important information including the expertise owned for activities like making decision, strategic planning, dynamic learning and problem solving. In the business of waging wars, the military has always maintained that knowledge is critical to victory. For the military, a learning organization allows its units to gain an advantage over the enemy by adapting quickly to changing situations and tactics while never remaining in a predictable pattern. The objective of this paper is to review the management of knowledge in the military and propose the typology of knowledge that should be codified and shared by the workforce within the context of empowering the Malaysians Armed Forces with knowledge-based systems. Communities of Practices (CoP) also will be discussed as to be truly a learning organization the knowledge must be share from individual to communities.

关键词： Knowledge based systems

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