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5th International Conference on Sustainable Technologies for Industry 5.0, STI 2023

作者： Uddin, Nazim Mia, Md Sajib Uddin, Mohammed Nasir Mahmud, Prince Chandpur Science and Technology University Dept. of Information and Communication Technology Bangladesh Sylhet Engineering College Dept. of Computer Science and Engineering Bangladesh Jagannath University Dept. of Computer Science and Engineering Bangladesh Chandpur Science and Technology University Dept. of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350394290

As the world advances in technology, the classification of eye diseases is thought to have clinical applications since it evaluates and analyzes the results. Optometrists research and diagnose age-related eye problems such as Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), and Drusen using optical coherence tomography (OCT) of the human eye. Because their symptoms are similar, identifying these diseases is challenging and requires hours of expert analysis. The requirements for eye illness classification should be straightforward in nature, structure, and evaluation. Deep Learning Convolutional Neural Network Classification can create a hierarchical representation of images to differentiate between normal and diseased eye patterns for diagnostic purposes. Therefore, this paper aims to implement and define deep learning to classify and identify eye diseases. Using a four-class classification problem, this work investigates the automatic detection of Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), Drusen, and Normal in Optical Coherence Tomography (OCT) pictures. Multi-transfer learning architecture was used in the suggested deep learning Ensemble classification model. The most incredible accuracy of our proposed Ensemble model for multi- class classification was 83%. © 2023 IEEE.

关键词： Optical tomography

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Feedback Attention-Augmented Bilateral Network for Amodal Instance Segmentation 1st

Feedback Attention-Augmented Bilateral Network for Amodal I...

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1st International Conference on Cognitive Computation and Systems, ICCCS 2022

作者： Dong, Junjie Liu, Huaping Xie, Jun Xu, XinYing Lan, Zijun College of Information and Computer Taiyuan University of Technology Taiyuan China Department of Computer Science and Technology Tsinghua University Beijing China College of electrical and power engineering Taiyuan University of Technology Taiyuan China

ISBN: (纸本)9789819927883

Amodal instance segmentation is a recently novel research in the field of computer vision, which includes the prediction of the visible and occluded parts of each object instance. Many modern computer vision methods demonstrate excellent performance by using the mechanism of looking and thinking twice and the attention mechanism. In this paper, we propose a feedback attention-augmented bilateral network. Specifically, after the convolutional network extracts the first round features of the input image, a feedback connection for relearning is introduced to extract the second round features. Meanwhile, a spatial detail preservation network with multi-scale attention feature module is designed to preserve and capture the rich spatial details information. Finally, a simple but practical feature fusion module is used to effectively combine both shallow and deep features from the backbone branch and the spatial branch. We achieve better results on COCOA dataset and D2SA dataset. For COCOA dataset, our method outperforms different state-of-the-art models by 1.2% and 1.6% mAP under "All regions" and "Things only", and brings 9.4% improvement on D2SA dataset. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： computer vision

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Natural Language Processing Studies in Humancomputer Interaction: A Bibliometric Analysis and Future Research Framework 22

Natural Language Processing Studies in HumanComputer Interac...

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22nd IEEE Student Conference on Research and Development, SCOReD 2024

作者： Rashid, Farah Syazwani Binti Mohd Kamsin, Amirrudin Bin Noor, Nurul Fazmidar Binti Mohd Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System Technology Kuala Lumpur50603 Malaysia Universiti Teknologi MARA College of Computing Informatics and Mathematics Selangor Shah Alam40450 Malaysia

ISBN: (纸本)9798331510077

This study conducts a bibliometric analysis of Natural Language Processing (NLP) within Human-computer Interaction (HCI) to identify trends, challenges, and future directions. Analyzing 1,710 SCOPUS-indexed documents (1983-2024) using a PRISMA flowchart, the results show that the United States and China are leading contributors. Key developments include emotion recognition, chatbot interfaces, and speech processing, highlighting NLP's role in user-centered technologies. Despite growing applications, challenges such as reliability and ethical concerns persist. This analysis emphasizes the need for ethical frameworks and technological advancements to address deployment issues and align NLP innovations with the United Nations Sustainable Development Goals (SDGs). By mapping global research trends, this study provides insights into the transformative potential of NLP in HCI for developing inclusive and responsive systems. © 2024 IEEE.

关键词： Emotion Recognition

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IntegraSec: Securing IoT with an Integrated Lightweight Privacy-Aware Publish-Subscribe Framework 2

IntegraSec: Securing IoT with an Integrated Lightweight Priv...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Chamarajappa, Rashmi H. Dyamanna, Guruprakash C. Sri Siddhartha Institute of Technology Ssahe Department of Information Science & Engineering Tumkur India Sri Siddhartha Institute of Technology Ssahe Department of Computer Science and Engineering Tumkur India

ISBN: (纸本)9798350306415

Publish/subscribe(pub/sub) communication in IoT healthcare systems enables efficient and real-time dissemination of patient data, facilitating timely medical interventions and remote monitoring. Moreover, the pub/sub model has characteristics of loose coupling which could lead to security and privacy;this paper introduces a comprehensive security framework IntegraSec which integrates the lightweight design, LAA (Lightweight Authentication based on anonymity), LAC(lightweight access control), principle based on the AE(Asymmetric Encryption) based model integrated with different model such as anonymous authentication through, user registration and so on to enhance the access control and data privacy. Moreover, the proposed model secures the pub/sub model by safeguarding the content, securing the subscriber identity and publication authenticity for lightweight secure communication. Considering the lightweight approach IntegraSec improvises the overhead in terms of storage and communication. © 2024 IEEE.

关键词： IntegraSec IoT lightweight pub/sub model security

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Enhancing Literary Exploration: A Machine Learning Approach to Book Recommendations 7

Enhancing Literary Exploration: A Machine Learning Approach ...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Singh, Kritika Gupta, Sumita Dhir, Saru Gambhir, Sapna Amity University Amity School of Engineering & Technology Department of Computer Science & Engineering Uttar Pradesh Noida India Amity University Amity School of Engineering & Technology Department of Information Technology Uttar Pradesh Noida India George Mason University College of Engineering and Computing Department of Computer Science United States

ISBN: (纸本)9798350350067

In today's era of rapid internet expansion, the need for efficient information retrieval tools is paramount. Recommendation systems serve as indispensable instruments, aiding users in navigating vast datasets swiftly and accessing relevant information. This paper presents a novel approach to book recommendation systems, offering readers a quick and intuitive method to discover their next read. Implementations encompass three algorithms: Popularity-based, Contentbased, and Collaborative-based recommendation systems. The primary focus lies in proposing a swift book idea system, facilitating users in promptly discovering fitting reading materials. By harnessing the power of these algorithms, readers can explore a diverse range of book options tailored to their preferences, enhancing their overall reading experience and satisfaction. Through this study, we aim to contribute to the advancement of recommendation systems, providing valuable insights and practical solutions for optimizing the book discovery process in the digital age. © 2024 IEEE.

关键词： Collaborative filtering

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A Novel Approach Based on Hybrid Algorithm for Energy Efficient Cluster Head Identification in Wireless Sensor Networks

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computer Systems science & Engineering 2022年第10期43卷 259-273页

作者： C.Ram Kumar K.Murali Krishna Mohammad Shabbir Alam K.Vigneshwaran Sridharan Kannan C.Bharatiraja Department of Electronics and Communication Engineering Dr.N.G.P.Institute of TechnologyCoimbatore641048India Department of Electronics and Communication Engineering Vignan’s Institute of Information TechnologyDuvvadaVisakhapatnam530049India Department of Computer Science College of Computer Science and Information TechnologyJazan UniversityJizan45142Kingdom of Saudi Arabia Department of Electronics and Communication Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and Engineering JKK Munirajah College of TechnologyErode638506India Department of Electrical and Electronics Engineering SRM Institute of Science and TechnologyChennai603203India

The Wireless Sensor Networks(WSN)is a self-organizing network with random deployment of wireless nodes that connects each other for effective monitoring and data *** clustering technique employed to group the collection of nodes for data transmission and each node is assigned with a cluster *** major concern with the identification of the cluster head is the consideration of energy consumption and hence this paper proposes an hybrid model which forms an energy efficient cluster head in the Wireless Sensor *** proposed model is a hybridization of Glowworm Swarm Optimization(GSO)and Artificial Bee Colony(ABC)algorithm for the better identification of cluster *** performance of the proposed model is compared with the existing techniques and an energy analysis is performed and is proved to be more efficient than the existing model with normalized energy of 5.35%better value and reduction of time complexity upto 1.46%.Above all,the proposed model is 16%ahead of alive node count when compared with the existing methodologies.

关键词： Wireless sensor network cluster cluster head hybrid model glowworm swarm optimization artificial bee colony algorithm energy consumption

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Hybrid Computational Modeling for Web Application Security Assessment

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computers, Materials & Continua 2022年第1期70卷 469-489页

作者： Adil Hussain Seh Jehad F.Al-Amri Ahmad F.Subahi Md Tarique Jamal Ansari Rajeev Kumar Mohammad Ubaidullah Bokhari Raees Ahmad Khan Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al Qura UniversityMakkah21421Saudi Arabia Department of Computer Applications Shri Ramswaroop Memorial UniversityBarabanki225003Uttar PradeshIndia Department of Computer Science Aligarh Muslim UniversityAligarh202002Uttar PradeshIndia

Transformation from conventional business management systems to smart digital systems is a recurrent trend in the current *** has led to digital revolution,and in this context,the hardwired technologies in the software industry play a significant role However,from the beginning,software security remains a serious issue for all levels of *** vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data,compromising the organizations’reputation that translates into,financial losses as *** of the data breaches are financially motivated,especially in the healthcare *** cyber invaders continuously penetrate the E-Health data because of the high cost of the data on the dark ***,security assessment of healthcare web-based applications demands immediate intervention mechanisms to weed out the threats of *** aim of this work is to provide efficient and effective healthcare web application security *** study has worked with the hybrid computational model of Multi-Criteria Decision Making(MCDM)based on Analytical Hierarchy Process(AHP)and Technique for Order of Preference by Similarity to Ideal-Solutions(TOPSIS)under the Hesitant Fuzzy(HF)*** fuzzy sets provide effective solutions to address decision making problems where experts counter hesitation to make a *** proposed research endeavor will support designers and developers in identifying,selecting and prioritizing the best security attributes for web applications’*** empirical analysis concludes that Robustness got highest priority amongst the assessed security attributes set followed by Encryption,Authentication,Limit Access,Revoke Access,Data Validation,and Maintain Audit *** results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the web application *** study also establishes g

关键词： Healthcare web application security assessment hesitant fuzzy sets AHP-TOPSIS

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NearBySell : A Novel Approach to Localized E-Commerce with Focus on Seller-Customer Interaction and Enhanced Local Retail Network 11

NearBySell : A Novel Approach to Localized E-Commerce with F...

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11th IEEE International Conference on Advances in Computing and Communications, ICACC 2024

作者： Chavan, Vishal Subhash Hake, Ashok Shrimant Rao, Bhukya Nageswar Kotkar, Suyash Sanjay Kolhapur Institute of Technology's College of Engineering Department of Computer Science and Business Systems Kolhapur India

ISBN: (纸本)9798350379136

This paper examines a novel online retail application optimized for local commerce via a location-based matching system. The application supports the sale of new and secondhand items, home goods, and vegetables, requiring users to register and input their locations. Transactions occur only when the buyer's and seller's locations align, reducing logistical challenges. The system features a review mechanism allowing customers to rate sellers, influencing future buyer decisions and seller reputation. Security is ensured through hand-to-hand payments and direct seller delivery, mitigating risks associated with digital payments and third-party delivery. Additionally, the application supports long-term relationships by maintaining permanent connections between customers and sellers. Technical aspects include the development of location-based matching algorithms, review systems, and security measures. Notably, the application incorporates advanced security features such as fake reviews detection and duplicate listings detection to protect both buyers and sellers from fraudulent activities. This study highlights how these components enhance local market efficiency and e-commerce reliability. © 2024 IEEE.

关键词： Location

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Locomotion of Bioinspired Underwater Snake Robots Using Metaheuristic Algorithm

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computers, Materials & Continua 2022年第7期72卷 1293-1308页

作者： Souad Larabi-Marie-Sainte Taiseer Abdalla Elfadil Eisa Fahd N.Al-Wesabi Amani Abdulrahman Albraikan Manar Ahmed Hamza Abdelwahed Motwakel Ishfaq Yaseen Mesfer Al Duhayyim Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid University62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’a1247Yemen Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman University11564Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz University16278Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz University16278Saudi Arabia

Snake Robots(SR)have been successfully deployed and proved to attain bio-inspired solutions owing to its capability to move in harsh environments,a characteristic not found in other kinds of robots(like wheeled or legged robots).Underwater Snake Robots(USR)establish a bioinspired solution in the domain of underwater *** is a key challenge to increase the motion efficiency in underwater robots,with respect to forwarding speed,by enhancing the locomotion *** the same time,energy efficiency is also considered as a crucial issue for long-term automation of the *** this aspect,the current research paper concentrates on the design of effectual Locomotion of Bioinspired Underwater Snake Robots using Metaheuristic Algorithm(LBIUSR-MA).The proposed LBIUSR-MA technique derives a bi-objective optimization problem to maximize the ForwardVelocity(FV)and minimize the Average Power Consumption(APC).LBIUSR-MA technique involves the design ofManta Ray Foraging Optimization(MRFO)technique and derives two objective functions to resolve the optimization *** addition to these,effective weighted sum technique is also used for the integration of two objective ***,the objective functions are required to be assessed for varying gait variables so as to inspect the performance of locomotion.A detailed set of simulation analyses was conducted and the experimental results demonstrate that the developed LBIUSR-MA method achieved a low Average Power Consumption(APC)value of 80.52W underδvalue of *** proposed model accomplished the minimum PAC and maximum FV of USR in an effective manner.

关键词： Bio-inspired robots underwater snake robots locomotion efficiency forwarding velocity average power consumption objective function

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MOCBOA:Multi-Objective Chef-Based Optimization Algorithm Using Hybrid Dominance Relations for Solving Engineering Design Problems

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computer Modeling in Engineering & sciences 2025年第4期143卷 967-1008页

作者： Nour Elhouda Chalabi Abdelouahab Attia Abdulaziz S.Almazyad Ali Wagdy Mohamed Frank Werner Pradeep Jangir Mohammad Shokouhifar Computer Science Department University of M’silaIchebiliaM’sila28000Algeria Computer ScienceDepartment Mohamed El Bachir El IbrahimiUniversity of Bordj BouArreridjBordj BouArreridj34000Algeria Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan Faculty of Mathematics Otto-von-Guericke UniversityMagdeburg39016Germany University Centre for Research and Development Chandigarh UniversityMohali140413India Department of Electrical and Computer Engineering Shahid Beheshti UniversityTehran14399Iran DTU AI and Data Science Hub(DAIDASH) Duy Tan UniversityDa Nang550000Vietnam

Multi-objective optimization is critical for problem-solving in engineering,economics,and *** study introduces the Multi-Objective Chef-Based Optimization Algorithm(MOCBOA),an upgraded version of the Chef-Based Optimization Algorithm(CBOA)that addresses distinct *** approach is unique in systematically examining four dominance relations—Pareto,Epsilon,Cone-epsilon,and Strengthened dominance—to evaluate their influence on sustaining solution variety and driving convergence toward the Pareto *** comparison investigation,which was conducted on fifty test problems from the CEC 2021 benchmark and applied to areas such as chemical engineering,mechanical design,and power systems,reveals that the dominance approach used has a considerable impact on the key optimization measures such as the hypervolume *** paper provides a solid foundation for determining themost effective dominance approach and significant insights for both theoretical research and practical applications in multi-objective optimization.

关键词： Multi-objective optimization chef-based optimization algorithm(CBOA) pareto dominance epsilon dominance cone-epsilon dominance strengthened dominance

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