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computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA), International Conference on

作者： Domagoj Tuličić Marko Horvat Sandra Lovrenčić Department of Computer System and Networks University of Applied Science in Information Technology Zagreb Croatia Department of Applied Computing University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia Department of Theoretical and Applied Foundations of Information Sciences University of Zagreb Faculty of Organization and Informatics Varaždin Croatia

Swarm intelligence is a class of nature-inspired metaheuristic algorithms, that is specifically derived from biological systems in nature with an emphasis on their social interactions. These algorithms have been primarily developed to solve complex combinatorial optimization problems and are extremely popular among researchers in metaheuristic algorithms. This is evident from the numerous published scientific papers describing algorithms inspired by biological systems, ranging from insects such as ants and bees to the largest animals on the planet like whales. All these algorithms share some common concepts and relationships that can be explicitly identified, named, and formalized. These shared concepts and relationships can be organized and represented through the construction of an ontology. The goal of this paper is to present a formal ontology that standardizes vocabulary, as well as a set of rules enabling precise communication and reasoning about these algorithms. Ultimately, this will improve our understanding, analysis, research processes, and utilization of these computational approaches.

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Analysis of Robotics, Artificial intelligence and Machine learning in the field of healthcare sector

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Materials Today: Proceedings 2022年 56卷 2323-2327页

作者： Sarath Kumar Boddu, Raja Ahamad, Shahanawaj Pradeep Kumar, K.V. Ramalingam, Mritha Kirana Pallathadka, Laxmi Peniero Tupas, Fernan Department of CSE Lenora College of Engineering Andhra Pradesh Rampachodavaram India College of Computer Science and Engineering University of Hail Saudi Arabia Department of Mechanical Engineering Ramaiah Institute of Technology Bengaluru India Faculty of Computing College of Computing and Applied Sciences University Malaysia Pahang Malaysia Manipur International University Manipur Imphal India Department of Biology Northern Iloilo Polytechnic State College India

Technological innovation or AI is enabled to determine the human's cognitive activities. ML, AI and automation processes made rapid changes in the pharma industry. The use of different analytic techniques helped to decrease the mortality rate worldwide. Uses of the AI tools help to determine the critical disease. Identification of genetic disputes is important for diagnosis and treatment. The growing technology helps to identify the dose errors in pharma companies. Currency analysis, frequent spectral analysis and the feature attraction process are necessary for Machine Learning (ML). Industry 4.0, ML considers the effectiveness of ML. Development of the intelligence computer programme is important for machine simulation. Moreover, it increases problem-solving skills in the pharma industry. The introduction sheds light on the entire project. The literature review has discussed the role of technological advantages in the medical industry. The impact of AI, ML and automation processes enhance profitability. The advantages and disadvantages of AI, ML and automation processes have been discussed in the literature review. In the methodology section, the secondary methodology has been chosen. Some inclusion and exclusion criteria have been concerned for the collection of effective information on the research topic. Cloud computing, cognitive systems and big data analysis, R&D process make huge changes in the pharma company. Increasing the use of the automation process provides safety and consistency to develop interconnectivity between the market demands, production rate of medicines. Recommendation and conclusion will be provided to maintain accuracy throughout the research paper. © 2021

关键词： Automation

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Cat Swarm with Fuzzy Cognitive Maps for Automated Soil Classification

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Computer Systems Science & Engineering 2023年第2期44卷 1419-1432页

作者： Ashit Kumar Dutta Yasser Albagory Manal Al Faraj Majed Alsanea Abdul Rahaman Wahab Sait Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Kingdom of Saudi Arabia Department of Computing Arabeast CollegesRiyadh11583Kingdom of Saudi Arabia Department of Archives and Communication King Faisal UniversityAl AhsaHofuf31982Kingdom of Saudi Arabia

Accurate soil prediction is a vital parameter involved to decide appro-priate crop,which is commonly carried out by the *** an auto-mated soil prediction tool helps to considerably improve the efﬁcacy of the *** the same time,fuzzy logic(FL)approaches can be used for the design of predictive models,particularly,Fuzzy Cognitive Maps(FCMs)have involved the concept of uncertainty representation and cognitive *** other words,the FCM is an integration of the recurrent neural network(RNN)and FL involved in the knowledge engineering *** this aspect,this paper introduces effective fuzzy cognitive maps with cat swarm optimization for automated soil classiﬁca-tion(FCMCSO-ASC)*** goal of the FCMCSO-ASC technique is to identify and categorize seven different types of *** accomplish this,the FCMCSO-ASC technique incorporates local diagonal extrema pattern(LDEP)as a feature extractor for producing a collection of feature *** addition,the FCMCSO model is applied for soil classiﬁcation and the weight values of the FCM model are optimally adjusted by the use of CSO *** exam-ining the enhanced soil classiﬁcation outcomes of the FCMCSO-ASC technique,a series of simulations were carried out on benchmark dataset and the experimen-tal outcomes reported the enhanced performance of the FCMCSO-ASC technique over the recent techniques with maximum accuracy of 96.84%.

关键词： Soil classiﬁcation intelligent models fuzzy cognitive maps cat swarm optimization fuzzy logic

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Metric Basis of Four-Dimensional Klein Bottle

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Computer Modeling in Engineering & Sciences 2023年第9期136卷 3011-3024页

作者： Ali N.A.Koam Ali Ahmad Maryam Salem Alatawi Muhammad Azeem Muhammad Faisal Nadeem Department of Mathematics College of SciencesNew CampusJazan UniversityJazanSaudi Arabia College of Computer Science&Information Technology Jazan UniversityJazanSaudi Arabia Department of Mathematics Faculty of SciencesUniversity of TabukTabukSaudi Arabia Department of Mathematics Riphah Institute of Computing and Applied SciencesRiphah International UniversityLahorePakistan Department of Mathematics COMSATS University IslamabadLahore CampusLahorePakistan

The Metric of a graph plays an essential role in the arrangement of different dimensional structures and finding their basis in various *** metric dimension of a graph is the selection of the minimum possible number of vertices so that each vertex of the graph is distinctively defined by its vector of distances to the set of selected *** set of selected vertices is known as the metric basis of a *** applied mathematics or computer science,the topic of metric basis is considered as locating number or locating set,and it has applications in robot navigation and finding a beacon set of a computer *** to the vast applications of this concept in computer science,optimization problems,and also in chemistry enormous research has been *** extend this research to a four-dimensional structure,we studied the metric basis of the Klein bottle and proved that the Klein bottle has a constant metric dimension for the variation of all its *** the metric basis is variying in 3 and 4 values when the values of its parameter change,it remains constant and unchanged concerning its order or number of *** methodology of determining the metric basis or locating set is based on the distances of a ***,we proved the main theorems in distance forms.

关键词： Klein bottle metric basis resolving set metric dimension

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Fair Selection of Edge Nodes to Participate in Clustered Federated Multitask Learning

arXiv

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arXiv 2023年

作者： Albaseer, Abdullatif Abdallah, Mohamed Al-Fuqaha, Ala Mohammed, Abegaz Erbad, Aiman Dobre, Octavia A. The Division of Information and Computing Technology College of Science and Engineering Doha Qatar The Faculty of Engineering and Applied Science Memorial University Canada

Clustered federated Multitask learning is introduced as an efficient technique when data is unbalanced and distributed amongst clients in a non-independent and identically distributed manner. While a similarity metric can provide client groups with specialized models according to their data distribution, this process can be time-consuming because the server needs to capture all data distribution first from all clients to perform the correct clustering. Due to resource and time constraints at the network edge, only a fraction of devices is selected every round, necessitating the need for an efficient scheduling technique to address these issues. Thus, this paper introduces a two-phased client selection and scheduling approach to improve the convergence speed while capturing all data distributions. This approach ensures correct clustering and fairness between clients by leveraging bandwidth reuse for participants spent a longer time training their models and exploiting the heterogeneity in the devices to schedule the participants according to their delay. The server then performs the clustering depending on predetermined thresholds and stopping criteria. When a specified cluster approximates a stopping point, the server employs a greedy selection for that cluster by picking the devices with lower delay and better resources. The convergence analysis is provided, showing the relationship between the proposed scheduling approach and the convergence rate of the specialized models to obtain convergence bounds under non-i.i.d. data distribution. We carry out extensive simulations, and the results demonstrate that the proposed algorithms reduce training time and improve the convergence speed by up to 50% while equipping every user with a customized model tailored to its data distribution. © 2023, CC BY.

关键词： Learning systems

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Effect of thickness variations of lithium niobate on insulator waveguide on the frequency spectrum of spontaneous parametric down-conversion

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Chinese Physics B 2021年第11期30卷 268-273页

作者： Guang-Tai Xue Xiao-Hui Tian Chi Zhang Zhenda Xie Ping Xu Yan-Xiao Gong Shi-Ning Zhu National Laboratory of Solid State Microstructures School of PhysicsSchool of Electronic Science and EngineeringCollege of Engineering and Applied Sciencesand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093China Institute for Quantum Information and State Key Laboratory of High Performance Computing College of ComputingNational University of Defense TechnologyChangsha 410073China

We study the effect of waveguide thickness variations on the frequency spectrum of spontaneous parametric downconversion in the periodically-poled lithium niobate on insulator(LNOI)*** analyze several variation models and our simulation results show that thickness variations in several nanometers can induce distinct effects on the central peak of the spectrum,such as narrowing,broadening,and *** also prove that the effects of positive and negative variations can be canceled and thus lead to a variation-robust feature and an ultra-broad *** study may promote the development of on-chip photon sources in the LNOI platform,as well as opens up a way to engineer photon frequency state.

关键词： lithium niobate on insulator spontaneous parametric down-conversion waveguide thickness variation frequency spectrum

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Entropies of the Y-Junction Type Nanostructures

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Computer Modeling in Engineering & Sciences 2023年第6期135卷 2665-2679页

作者： Ricai Luo Aisha Javed Muhammad Azeem Muhammad Kamran Jamil Hassan Raza Muhammad Yasir Ilyas School of Mathematics and Physics Hechi UniversityYizhou456300China Abdus Salam School of Mathematical Sciences Government College UniversityLahore54000Pakistan Department of Mathematics Riphah Institute of Computing and Applied SciencesRiphah International UniversityLahore54000Pakistan School of Mathematical Sciences College of Science and TechnologyWenzhou-Kean UniversityWenzhou325060China Department of Physics COMSATS University IslamabadLahore54000Pakistan

Recent research on nanostructures has demonstrated their importance and application in a variety of *** are used directly or indirectly in drug delivery systems,medicine and pharmaceuticals,biological sensors,photodetectors,transistors,optical and electronic devices,and so *** discovery of carbon nanotubes with Y-shaped junctions is motivated by the development of future advanced electronic *** of their interactionwithY-junctions,electronic switches,amplifiers,and three-terminal transistors are of particular *** is a concept that determines the uncertainty of a system or *** concepts are also used in biology,chemistry,and applied *** on the requirements,entropy in the form of a graph can be classified into several *** 1955,graph-based entropy was *** of the types of entropy is edgeweighted *** examined the abstract form of Y-shaped junctions in this *** edge-weight-based entropy formulas for the generic view of Y-shaped junctions were created,and some edge-weighted and topological index-based concepts for Y-shaped junctions were discussed in the present paper.

关键词： Y-shaped junctions three-terminal junctions nanostuctures entropy carbon nanotube

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AI Modeling and Water Quality Sensing Technique Proffers Water Security: An Open Review

AI Modeling and Water Quality Sensing Technique Proffers Wat...

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Electronics and Renewable Systems (ICEARS), International Conference on

作者： Wilfred Blessing N.R Suresh Palarimath Hemalatha Gunasekaran Sk Wasim Haidar Sutherlin Subitha G Sarmila J College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Sultanate of Oman College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Sultanate of Oman Department of Computer Science and Engineering Stella Mary’s College of Engineering Kanyakumari District India Department of Computer Science and Engineering St. Xavier’s Catholic College of Engineering Chunkankadai Tamil Nadu India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

Water Quality Sensors (WQSs) are becoming a promised tool in water quality data assessment and scientific value of aquatic structure. Such sensors are broadly used to produce live results by evaluating major water quality parameters and components. Artificial intelligence (AI) based WQSs and machine learning (ML) algorithms primarily enable long term operations for real time detention of water quality information at different time periods. Messaging services, alarms, alerts and other proper warnings are given to water quality managers or assessing communities while the quality deterioration occurs at the particular water quality checking sites. A good number of impressive challenges are identified in hosting the variety of sensors to manage, warehouse and analyze incessant water quality information that they generate periodically. This paper places interests in highlighting lack of suitable assessment standards and determine logistical deliberations for fruitful implementations together with transportation, storage services and appropriate trustworthy communication. The main objective is to identify the designs targeting water security that support to monitor, reassure and protect the water resources all the way through uninterrupted quality supervision in addition to AI features. This open review also discusses a variety of applications in water quality sensors, AI modeling, electronic tongues and indices, hence results the knowledge of improvement required for upgrading the quality in water resources through computer technologies and models.

关键词： Wireless sensor networks Reviews Computational modeling Transportation Water quality Predictive models Artificial intelligence Water resources Intelligent sensors Monitoring

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A Collaborative Consumption Digital Platform for Government Organizations using Design Science

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Digital Government: Research and Practice 2022年第1期3卷 1–14页

作者： Gebeyehu, Seffi Twinomurinzi, Hossana Faculty of Computing Bahirdar Technology Institute Bahirdar University P.O.Box 26 Bahirdar Ethiopia Applied Information Systems Department School of Consumer Intelligence and Information Systems College of Business and Economics Office 17 Auckland Park Bunting Road Campus Johannesburg South Africa

The growth of digital technologies that enable the sharing of resources, underutilized assets, and services, is bringing new ways of shared consumption commonly called the "sharing economy"or "collaborative consumption". This study used a design science paradigm and the elaborated action design method (eADR) to design and develop a "collaborative consumption"(CC) digital artifact under the government to government (G2G) domain towards improving resource limitations in developing country contexts. The Ethiopian WoredaNet government project was used as a case study. The new artifact was evaluated using the post-study system usability framework (n = 35) to reveal its practical usefulness in improving resource limitations. A new design principle was also elicited: intentionally elicit user responses for unfamiliar digital innovations. The study recommends for policymakers of low-income countries (LICs) to create new sharing-capable policies in the G2G domain, and consider extending it towards non-government organizations and citizens. Overall, the findings contribute to Information Systems discourse and digital government practice by identifying the importance of novel CC digital platforms to optimize government resources in LICs. The study also contributes to the eADR method by identifying that the action research cycle is not a strict requirement but helpful as an entry point into design science efforts. © 2022 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Developing countries

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Preliminary Tensile Investigation of FDM Printed PLA/Coconut Wood Composite 6th

Preliminary Tensile Investigation of FDM Printed PLA/Coconut...

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6th International Conference on Mechanical Engineering Research, ICMER 2021

作者： Kananathan, J. Rajan, K. Samykano, M. Kadirgama, K. Moorthy, K. Rahman, M.M. Green Kingdom Solutions Sdn. Bhd. Taman Salak Selatan Kuala Lumpur57100 Malaysia College of Engineering Universiti Malaysia Pahang Pahang Gambang26300 Malaysia Faculty of Mechanical and Automotive Engineering Technology Universiti Malaysia Pahang Pahang Pekan26600 Malaysia College of Computing and Applied Sciences Faculty of Computing Universiti Malaysia Pahang Pahang Pekan26600 Malaysia

ISBN: (纸本)9789811915765

Fused deposition modeling (FDM) is a technique in additive manufacturing that has been used to produce various components using a variety of materials for a broad range of applications adapting layer-by-layer deposition process. Thermoplastic polymers are commonly used raw material that comes in the form of a filament. Coconut wood is highly recognized for its naturally affable ecological components, thermal resilience, and corrosion resistance. However, PLA's qualities embedded in coconut wood remain inadequate. The objective of this analysis is to investigate and analyze the tensile properties of the 3D printed specimens with varying infill percentages (25, 50, and 75%) and the infill patterns (grid, rectilinear, concentric, honeycomb, and triangle) on coconut wood reinforced PLA using the FDM technique. The specimen is printed in accordance with the ASTM standard for tensile testing, which is ASTM D638 type 1. Following that, the tensile properties of the PLA and PLA/Coconut wood were analyzed. The results demonstrate that the concentric infill pattern with a 75% infill percentage provides the strongest structure in PLA and PLA/Coconut wood composites. The PLA has a maximum tensile strength of 37.55 MPa, whereas the PLA/Coconut wood has 19.35 MPa. PLA has a maximum elastic modulus of 1.148 GPa, while the PLA/Coconut wood composite has a maximum elastic modulus of 1.121 GPa. PLA has a yield strength of 23.33 MPa, while the PLA/Coconut wood composite has a yield strength of 15.33 MPa in tensile testing. Meanwhile, the grid pattern has the weakest properties for both materials. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Composite materials

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