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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Ioannis Katsidimas Alexandros–Ioannis Manolopoulos Sotiris Nikoletseas Department of Computer Engineering and Informatics University of Patras Patras Greece Department of Physics National and Kapodistrian University of Athens Athens Greece Department of Computer Engineering and Informatics University of Patras and Computer Technology Institute and Press “Diophantus” Patras Greece

IoT applications often rely on battery-powered nodes that may be challenging to recharge, making energy efficiency a crucial concern. In this context, routing protocols play a vital role as they dictate the paths data packets take between nodes, directly influencing the energy consumption of IoT networks. Energy-aware routing protocols have been proposed to address this issue, with the aim of optimizing energy consumption by selecting paths that minimize the energy required for data transmission and reception. These protocols employ various strategies, such as distance-based, traffic-based, and hybrid schemes, to achieve energy efficiency in IoT networks. LoRaWAnprotocol has been adopted for various IoT applications with requirements in low-power and extended coverage. Over the recent years attempts have been made to replace the typical star topology employed by LoRa with multihop solutions, in an effort to further increase its capabilities. In this paper, we present a multihop algorithm that is based on an energy-balanced routing scheme adopted by LoRa nodes to increase energy efficiency and network lifetime. Multiple one-hop routes are configured for critical nodes and a different route is selected in each transmission. Additionally, critical nodes adjust their Spreading Factor and Transmission Power according to the distance of intermediate nodes. Simulation testing results verify the improved performance of our algorithm over the direct link approach.

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EfficientNetB0-based Automated Diabetic Retinopathy Classification in Fundus Images

EfficientNetB0-based Automated Diabetic Retinopathy Classifi...

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Automation, Computing and Renewable Systems (ICACRS), International Conference on

作者： Ezekiel Alaric Majaw G. Naveen Sundar D. Narmadha Senthil Kumar Thangavel Venkatesan Adeyemi Abel Ajibesin Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Computer Science and Engineering Amrita School of Computing Coimbatore India Department of Information Technology Faculty of Informatics and Design Cape Peninsula University of Technology South Africa

ISBN: (数字)9798331532420

ISBN: (纸本)9798331532437

The most common cause of blindness among diabetics is diabetic retinopathy. This disease must be detected in its early stages as delaying treatment can result in permanent blindness. In today’s modern world with the development of technologies, automated techniques have improved the accuracy and efficiency of detecting and classifying this disease. This study suggests a deep learning model utilizing EfficientNetB0 that focuses on designing a neural network structure that requires fewer parameters and computations compared to traditional architectures. Further to help in increasing the accuracy, the image is being processed with methods like CLAHE which is an image processing algorithm that helps in enhancing the contrast while keeping the noise of the images as low as possible. Also, augmentation is being done on the images and SMOTE is applied to handle class imbalance. We collected the APTOS Blindness Detection dataset consisting of retinal fundus images. The accuracy that is being obtained from the proposed methodology is 98.78% indicating the model's effectiveness in detection and classifying between the various stages of diabetic retinopathy.

关键词： Diabetic retinopathy Renewable energy sources Accuracy Computational modeling Blindness computer architecture Transformers Retina Real-time systems Diseases

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Mitigation Methods of Reducing DDOS Attack Frequency on Blockchain 3

Mitigation Methods of Reducing DDOS Attack Frequency on Bloc...

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3rd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Sathees Kumar, R. Chintamaneni, Phanikanth Kumar, Madarapu Naresh Joshi, Ankita Swathi, Bajila Dhanraj, Joshuva Arockia Jntuk University Narasaraopeta Institute of Technology Department of Cse Andhra Pradesh Narasaraopet India Department of Cse New Delhi India National Informatics Centre New Delhi India Uttaranchal University Uttaranchal Institute of Technology India Sr University School of Computer Science and Artificial Intelligence Telangana Warangal India Department of Mechatronics Engineering Padur Chennai603103 India

ISBN: (纸本)9798350399264

A serious risk to genuine organization demands is a distributed denial of service (DDoS) attack. The main DDoS attack was archived in 1996, however, from that point forward, their intricacy and refinement have consistently expanded. A 2 TBps attack on a crucial foundation, including the monetary area, was accounted for in August 2020 during the Coronavirus pandemic. In the accompanying two years, it is anticipated that the number of attacks would twofold, stretching around 15 million. Since its beginning, many relief plans have been made, however, the intricacy is rising, requiring modern arrangements in view of new innovation. A potential and common-sense method for DDoS relief is blockchain. The point of the review is to give an exhaustive examination of the fundamental and intrinsic properties of blockchain, including their decentralization, inside and outer trust lessness, unchanging nature, honesty, obscurity, and evidence, which have demonstrated to be a fantastic contender for battling this destructive cyber threat. © 2023 IEEE.

关键词： Blockchain

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CentIER:Accurate centromere identification for plant genomes

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Plant Communications 2024年第10期5卷 12-15页

作者： Dong Xu Jinbao Yang Huaming Wen Wenle Feng Xiaohui Zhang Xingqi Hui Junyang Yue Yun Xu Fei Chen Weihua Pan Shenzhen Branch Guangdong Laboratory of Lingnan Modern AgricultureGenome Analysis Laboratory of the Ministry of Agriculture and Rural AffairsAgricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhen 518120China Rubber Research Institute Chinese Academy of Tropical Agricultural ScienceHaikouHainan 571101China School of Computer Science and Technology University of Science and Technology of ChinaHefeiAnhui 230026China College of Informatics Huazhong Agricultural UniversityWuhanHubei 430070China School of Horticulture Anhui Agricultural UniversityHefeiAnhui 230026China Nan Fan College Hainan UniversitySanyaHainan 572000China

Dear Editor,Centromeres,the basis for cell division,offer essential insights into cell dynamics,genome stability,and evolutionary processes(McKinley and Cheeseman,2016).Because of ultra-high complexity,high-quality sequences of centromeric regions have long been difficult to obtain,hindering studies of centromere function,evolution,and variation.

关键词： hinder insight stability

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HealthChain: A Blockchain-aided Federated Healthcare Management System

HealthChain: A Blockchain-aided Federated Healthcare Managem...

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IEEE International Conference on Blockchain and Cryptocurrency (ICBC)

作者： Arnab Mukherjee Raju Halder Joydeep Chandra Shailesh Shrivastava Department of Computer Science and Engineering Indian Institute of Technology Patna Bihta India National Informatics Center Patna India

Privacy and integrity of medical records while preserving and sharing them within any healthcare system is of high importance. Recently, India's Ayushman Bharat Digital Mission (ABDM) aims to address various issues of the existing healthcare systems and proposes a federated healthcare system to bring all the players under a common umbrella. However, it falls short on various aspects, including transparency, auditability, and traceability of activities and information within the system. In this proposal, we aim to bridge these existing gaps and propose an extension of the ABDM proposal by incorporating a blockchain layer instrumented with additional features such as traceable consent management, auditable access logs, etc., while keeping in mind its performance and scalability. We present a proof of concept of our proposal based on Hyperledger Fabric and related backend technologies and manifest experimental results to reinforce the practicality of our proposal.

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Analysis for optimizer based on spiking-neural oscillator networks with a simple network topology

Analysis for optimizer based on spiking-neural oscillator ne...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Tomoyuki Sasaki Hidehiro Nakano Department of Informatics Shonan Institute of Technology Fujisawa-shi Kanagawa Japan Department of Computer Science Tokyo City University Setagaya-ku Tokyo Japan

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Optimizer based on Spiking Neural-oscillator Networks (OSNNs) are one of the deterministic PSO methods, which are based on dynamics of spiking neural-oscillator networks. In OSNNs, each particle consists of plural spiking oscillators which are coupled with other spiking oscillators by the Ring 1-way network. The Ring 1-way network affects search performances of OSNNs. However, an effectiveness of the Ring 1-way network has not been clarified. In this study, we theoretically analyze the Ring 1-way OSNNs in more detail. In addition, in order to demonstrate analytical results, we conduct numerical simulations and discuss the simulation results.

关键词： Network topology Simulation Numerical simulation Particle swarm optimization Oscillators

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TIGHT BOUND ON TREEDEPTH IN TERMS OF PATHWIDTH AND LONGEST PATH

arXiv

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arXiv 2023年

作者： Hatzel, Meike Joret, Gwenaël Micek, Piotr Pilipczuk, Marcin Ueckerdt, Torsten Walczak, Bartosz National Institute of Informatics Tokyo Japan Computer Science Department Université libre de Bruxelles Brussels Belgium Department of Theoretical Computer Science Faculty of Mathematics and Computer Science Jagiellonian University Kraków Poland Institute of Informatics University of Warsaw Warsaw Poland Computer Science Department Karlsruhe Institute of Technology Karlsruhe Germany

We show that every graph with pathwidth strictly less than a that contains no path on 2b vertices as a subgraph has treedepth at most 10ab. The bound is best possible up to a constant factor. Copyright © 2023, Th...

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Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots

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Internet of Things and Cyber-Physical Systems 2024年第1期4卷 19-23页

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Faculty of Computing and Data Science FLAME University Maharashtra Pune India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, offers coherent and useful replies based on analysis of large volumes of data. In this article, leading academics, scientists, distinguish researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research discusses ChatGPT capabilities and its use in the education sector, identifies potential concerns and challenges. Our preliminary evaluation shows that ChatGPT perform differently in different subject areas including finance, coding, maths, and general public queries. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions, transforming education through smartphones and IoT gadgets, and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within GenerativeAI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023 The Authors

关键词： Machine learning

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User-Guided Anime Line Art Colorization with Spatially-adaptive Normalization

User-Guided Anime Line Art Colorization with Spatially-adapt...

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Smart World Congress (SWC), IEEE

作者： Yulu Fu Haowei Zhong Jinrong Cui Hailong Liu Cheng Huang Jinghua Wang College of Mathematics and Informatics South China Agricultural University Guangzhou China School of Computer Science and Technology Harbin Institute of Technology Shenzhen China

Line art plays an essential role in the process of anime creation. Colorization of the line art images is a tough task for the reason that neither grayscale values nor coloring semantic information exists in grayscale line art images. In this paper, we propose a novel line art colorization architecture with spatially-adaptive normalization for user-guide colorization. Our method can obtain high-quality colorized anime images by reserving more semantic information of inputs. Specifically, we integrate spatially-adaptive normalization block as well as spectral normalization, and the hybrid normalization enables us to train the network robustly while preserving the semantic information as much as possible. Our model is based on U-net architecture, which is regarded as a successful feature extraction architecture and is widely applied in the field of image segmentation and image generation. Also, We propose an anime data processing paradigm, combining the colored picture and the synthetic line art to generate simulated strokes in line with human intuition, which is conducive to making the generated images more realistic and perform on in-the-wild data better. With the proposed model, we evaluate a collected anime dataset and compare it with the existing method. The experimental results demonstrate the excellent and stable coloring effect of our proposed model.

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Deep Learning Based License Plate Number Recognition for Smart Cities

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computers, Materials & Continua 2022年第1期70卷 2049-2064页

作者： T.Vetriselvi E.Laxmi Lydia Sachi Nandan Mohanty Eatedal Alabdulkreem Shaha Al-Otaibi Amal Al-Rasheed Romany F.Mansour Department of Computer Science and Engineering K.Ramakrishnan College of TechnologyTrichy620002India Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science&Engineering Vardhaman College of Engineering(Autonomous)Hyderabad501218India Department of Informatics and Computing Singidunum UniversitySerbia Computer Science Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Information Systems Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

Smart city-aspiring urban areas should have a number of necessary elements in place to achieve the intended *** controlling and management of traffic conditions,increased safety and surveillance,and enhanced incident avoidance and management should be top priorities in smart city *** the same time,Vehicle License Plate Number Recognition(VLPNR)has become a hot research topic,owing to several real-time applications like automated toll fee processing,traffic law enforcement,private space access control,and road traffic *** VLPNR is a computer vision-based technique which is employed in the recognition of automobiles based on vehicle number *** current research paper presents an effective Deep Learning(DL)-based VLPNR called DLVLPNR model to identify and recognize the alphanumeric characters present in license *** proposed model involves two main stages namely,license plate detection and Tesseract-based character *** detection of alphanumeric characters present in license plate takes place with the help of fast RCNN with Inception V2 ***,the characters in the detected number plate are extracted using Tesseract Optical Character Recognition(OCR)*** performance of DL-VLPNR model was tested in this paper using two benchmark databases,and the experimental outcome established the superior performance of the model compared to other methods.

关键词： Deep learning smart city tesseract computer vision vehicle license plate recognition

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