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A Secure Framework for Blockchain Transactions Protection

computer Systems science & engineering 2023年第5期45卷 1095-1111页

作者： Wafaa N.Al-Sharu Majdi K.Qabalin Muawya Naser Omar A.Saraerh Department of Electrical Engineering Faculty of EngineeringThe Hashemite UniversityZarqa13133Jordan Department of Computer Science King Hussein School of Computing SciencesPrincess Sumaya University for TechnologyAmman11941Jordan

One of the most extensively used technologies for improving the security of IoT devices is blockchain *** is a new technology that can be utilized to boost the *** is a decentralized peer-to-peer network with no central *** nodes on the network mine or verify the data recorded on the *** is a distributed ledger that may be used to keep track of transactions between several *** one can tamper with the data on the blockchain since it is *** the blocks are connected by hashes,the transaction data is *** is managed by a system that is based on the consensus of network users rather than a central *** immutability and tamper-proof nature of blockchain security is based on asymmetric cryptography and ***,Blockchain has an immutable and tamper-proof smart contract,which is a logic that enforces the Blockchain’s *** is a conflict between the privacy protection needs of cyber-security threat intelligent(CTI)sharing and the necessity to establish a comprehensive attack chain during blockchain *** paper presents a blockchain-based data sharing paradigm that protects the privacy of CTI sharing parties while also preventing unlawful sharing and ensuring the benefit of legitimate sharing *** builds a full attack chain using encrypted threat intelligence and exploits the blockchain’s backtracking capacity to finish the decryption of the threat source in the attack *** contracts are also used to send automatic early warning replies to possible attack *** tests are used to verify the feasibility and efficacy of the suggested model.

关键词： Manuscript preparation typeset format

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IoT-Enabled Solar-Powered Water Trash Collector with Conveyor Belt 8th

IoT-Enabled Solar-Powered Water Trash Collector with Conveyo...

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8th International Conference on Information and Communication Technology for Competitive Strategies, ICTCS 2023

作者： Devapriya, S. Krishna, M. K. Nandana Gondi, Bhavika Vinuha, Chinta Pandi, V. Ravikumar Sathyan, Soumya Valsan, Vipina Suresh, Kavya Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9789819994854

This study presents a novel solution in the form of a solar-powered water trash collector, designed specifically for deployment in backwaters and smaller water bodies, to address the critical issues of water pollution and waste management. Focusing on the challenges faced by national rivers, including hazardous polymers, plastic waste, and decaying organic matter, the collector operates under IoT-enabled Bluetooth control using mobile application, incorporating a conveyor belt mechanism for efficient waste collection, particularly targeting prevalent plastic debris in freshwater environments. A notable feature of this solution is its integration of solar power, ensuring self-sustained operation and reduced environmental impact, aligning with the imperative for eco-friendly waste management technologies. Bluetooth control enhances adaptability for smaller water bodies, crucial for precise navigation. The core objective is to provide an effective solar-powered water trash collector tailored for backwaters, addressing the escalating waste production due to population growth. Additionally, a comprehensive waste management approach is proposed, facilitated by an Android application for seamless navigation of integrated trash bins. In conclusion, this study offers an innovative approach to tackle water pollution and waste management, introducing a solar-powered collector uniquely equipped to address backwater ecosystems’ specific challenges while promoting sustainability and environmental well-being. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Bluetooth

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Comparison of CNN-based deep learning architectures for rice diseases classification

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Artificial Intelligence in Agriculture 2023年第3期9卷 22-35页

作者： Md Taimur Ahad Yan Li Bo Song Touhid Bhuiyan Department of Computer Science and Engineering Daffodil International UniversitySavarBangladesh School of Mathematics Physics and Computing University of Southern QueenslandToowoombaAustralia School of Engineering University of Southern Queensland ToowoombaAustralia Department of Computer Science and Engineering Faculty of Science and Information TechnologyDaffodil International UniversityBangladesh

Although convolutional neural network(CNN)paradigms have expanded to transfer learning and ensemble models from original individual CNN architectures,few studies have focused on the performance comparison of the applicability of these techniques in detecting and localizing rice ***,most CNN-based rice disease detection studies only considered a small number of diseases in their *** these shortcomings were addressed in this *** this study,a rice disease classification comparison of six CNN-based deep-learning architectures(DenseNet121,Inceptionv3,MobileNetV2,resNext101,Resnet152V,and Seresnext101)was conducted using a database of nine of the most epidemic rice diseases in *** addition,we applied a transfer learning approach to DenseNet121,MobileNetV2,Resnet152V,Seresnext101,and an ensemble model called DEX(Densenet121,EfficientNetB7,and Xception)to compare the six individual CNN networks,transfer learning,and ensemble *** results suggest that the ensemble framework provides the best accuracy of 98%,and transfer learning can increase the accuracy by 17%from the results obtained by Seresnext101 in detecting and localizing rice leaf *** high accuracy in detecting and categorisation rice leaf diseases using CNN suggests that the deep CNN model is promising in the plant disease detection domain and can significantly impact the detection of diseases in real-time agricultural *** research is significant for farmers in rice-growing countries,as like many other plant diseases,rice diseases require timely and early identification of infected diseases and this research develops a rice leaf detection system based on CNN that is expected to help farmers to make fast decisions to protect their agricultural yields and quality.

关键词： Deep learning Convolutional neural networks(CNNs) Transfer learning Plant leaf disease detection

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Eye-Tracking Based Autism Spectrum Disorder Diagnosis Using Chaotic Butterfly Optimization with Deep Learning Model

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computers, Materials & Continua 2023年第8期76卷 1995-2013页

作者： Tamilvizhi Thanarajan Youseef Alotaibi Surendran Rajendran Krishnaraj Nagappan Department of Computer Science and Engineering Panimalar Engineering CollegeChennai600123India Department of Computer Science University College of Al JamoumUmm Al-Qura UniversityMakkah21421Saudi Arabia Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India School of Computing SRM Institute of Science and TechnologyKattankulathur603203India

Autism spectrum disorder(ASD)can be defined as a neurodevelopmental condition or illness that can disturb kids who have heterogeneous characteristics,like changes in behavior,social disabilities,and difficulty communicating with *** tracking(ET)has become a useful method to detect *** vital aspect of moral erudition is the aptitude to have common visual *** eye-tracking approach offers valuable data regarding the visual behavior of children for accurate and early ***-tracking data can offer insightful information about the behavior and thought processes of people with ASD,but it is important to be aware of its limitations and to combine it with other types of data and assessment techniques to increase the precision of ASD *** operates by scanning the paths of eyes for extracting a series of eye projection points on images for examining the behavior of children with *** purpose of this research is to use deep learning to identify autistic disorders based on eye *** Chaotic Butterfly Optimization technique is used to identify this specific ***,this study develops an ET-based Autism Spectrum Disorder Diagnosis using Chaotic Butterfly Optimization with Deep Learning(ETASD-CBODL)*** presented ETASDCBODL technique mainly focuses on the recognition of ASD via the ET and DL *** accomplish this,the ETASD-CBODL technique exploits the U-Net segmentation technique to recognize interested *** addition,the ETASD-CBODL technique employs Inception v3 feature extraction with CBO algorithm-based hyperparameter ***,the long-shorttermmemory(LSTM)model is exploited for the recognition and classification of *** assess the performance of the ETASD-CBODL technique,a series of simulations were performed on datasets from the figure-shared data *** experimental values of accuracy(99.29%),precision(98.78%),sensitivity(99.29%)and specificity(99.29%)showed a better perfo

关键词： Eye tracking ASD diagnosis deep learning butterfly optimization algorithm behavior analysis

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Blockchain-Based Communicator with Multicast Transmission 8

Blockchain-Based Communicator with Multicast Transmission

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8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Nair, Praanesh Balakrishnan Varun Adhitya, G.B. Vineetha, K.V. Ullas, S. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331505462

This paper examines the conceptualization and implementation of an instant messaging application, which is decentralized. The proposed work utilizes a blockchain with end-to-end encryption and digital signatures. The need for nodes dedicated to mining has been done away with, by introducing a new consensus mechanism called Proof of Message (PoM). The implementation demonstrates improved security over traditional centralized messaging systems while maintaining usability for small to medium-sized groups (50-100 users). When compared to conventional instant messaging applications which are centralized, the increase in latency has been found to be minimal, according to performance analysis. © 2024 IEEE.

关键词： Instant messaging

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Industrial Worker Safety Device with Proactive Gas Leak and Fire Protection System 8th

Industrial Worker Safety Device with Proactive Gas Leak and ...

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8th International Conference on Information and Communication Technology for Competitive Strategies, ICTCS 2023

作者： Kesanapalli, Sri Kaushik Yarramallu, V. S. N. Lokesh Abbaraju, Sree Tharun Raju Gangireddy, Rahul Jogi Suresh, Kavya Valsan, Vipina Pandi, V. Ravikumar Sathyan, Soumya Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9789819994854

Gas leaks and fires present dangers that require detection and decisive action to protect lives and property. This paper specifically proposes cutting-edge sensor technologies with intelligent threshold algorithms and real-time communication capabilities to enhance the safety and well-being of industrial workers by reducing the risk of accidents and injuries, which addresses Sustainable Development Goal (SDG) 3 (good health and well-being). It includes MQ5 and MQ135 gas sensors, a DHT11 temperature sensor, and an IR flame sensor to provide monitoring. The real-time data from the gas sensors is carefully analyzed to trigger alerts at two threshold levels directly linked to gas concentrations, ensuring warnings in case of any risks. If the second threshold is exceeded, indicating the presence of gas, the device activates a safety protocol. An exhaust fan swiftly dissipates any accumulated gas, while a servo motor promptly shuts off the gas supply, effectively preventing any escalation of the situation. An integrated Wi-Fi module will enable communication and notifications through a dedicated smartphone app or web interface to enhance functionality, which enables remote device control and real-time access to sensor data for users. This combination of sensor technologies, intelligent algorithms, and remote accessibility showcases how technology-driven solutions can significantly enhance safety measures. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Gases

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Optimizing Federated Semantic Learning in Distributed AIGC-Enabled Human Digital Twins: A Multi-Criteria and Multi-Shard User Selection Framework

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IEEE Transactions on Mobile computing 2025年第07期24卷 5916-5933页

作者： Okegbile, Samuel D. Gao, Haoran Talabi, Oluwasegun Cai, Jun Niyato, Dusit Shen, Xuemin Concordia University Department of Electrical and Computer Engineering MontrealQCH3G 1M8 Canada University of the Fraser Valley School of Computing AbbotsfordBCV2S 7M8 Canada Nanyang Technological University College of Computing and Data Science Singapore University of Waterloo Department of Electrical and Computer Engineering Canada

Artificial intelligence-generated content (AIGC) has been proposed as a solution to meet the requirements of ultra-reliable, secure, and privacy-preserving connectivity in human digital twin (HDT) networks. In such an AIGC-enhanced HDT, contents representing the true statuses of physical twins are generated in the virtual environment for the immediate update and evolution of the corresponding virtual twins (VTs). However, adopting a distributed AIGC in HDT presents several challenges, including the need for personalized VTs, data privacy concerns, and insufficient contextual understanding. This paper introduces a multi-layer federated semantic learning framework to address these challenges, incorporating batch learning to meet the training requirements for semantic-channel encoders and decoders. Furthermore, we introduce a novel user association framework to maximize the overall system performance under shard formation constraints. We then formulate a long-term joint optimization problem for user selection over finite learning periods. A novel Lyapunov-based online optimization strategy was proposed to mitigate the impact of time-varying and unpredictable training conditions. Additionally, we introduce a multi-arm bandit-based method and a context-centric user selection approach to solve the optimization problem. The results demonstrate that the proposed user association framework addresses the limitations of existing approaches, thereby improving the overall performance of the multi-shard AIGC-enhanced HDT. © 2025 IEEE.

关键词： Federated learning

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An improved swarm intelligence for power system economic operations based on optimal power generation to control congestion in transmission channels

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Neural computing and Applications 2025年 1-28页

作者： Kumari, Pooja Paul, Kaushik Kumar, Niranjan Sinha, Pampa Agarwal, Krishna Kant Vidyarthi, Ankit Alkhayyat, Ahmed Department of Electrical Engineering NIT Jamshedpur Jamshedpur India Department of Electrical Engineering BIT Sindri Dhanbad828123 India School of Electrical Engineering KIIT University Bhubaneswar751024 India School of Computing Science and Engineering Galgotias University Greater Noida India Department of CSE & IT Jaypee Institute of Information Technology Uttar Pradesh Noida201309 India College of Technical Engineering The Islamic University Najaf Iraq

Power system congestion is a key challenge in the deregulated era. Finding ways to transmit power without congestion is crucial. Achieving optimal generator power output with the application of evolutionary algorithms is a primary method to manage this issue. This paper proposes a novel modified whale optimization algorithm (MWOA) for the optimal power generation to address the power system economic operations for the nonlinear transmission congestion management cost problem. The MWOA has been developed by introducing two correction factors in the exploration and exploitation phases that enhances its performance and coordination in these two phases. The MWOA strikes a good balance between exploring and exploiting WOA phases. Its capabilities are validated using benchmark functions and compared to other heuristic algorithms. The MWOA has been applied to accomplish minimum congestion cost by optimal adjustment in the generator power output while alleviating congestion in the lines. Generator sensitivity factors are computed to identify the most sensitive generators that are participating in the power rescheduling process. The results show that MWOA lowered congestion costs by 6.00%, 4.45%, 3.14%, and 2.30% for the 39-bus system, 7.91%, 4.29%, 2.57%,1.69% for the 30-bus system, and 10.44%, 8.48%, 7.36%, 5.17%, 2.00% for 118-bus system when compared to FEP, GA, DE, and original WOA. Statistical and comparative analysis has shown that with MWOA there has been a considerable reduction in the congestion cost, system losses, amount of power rescheduled, and improved in the system bus voltages when contrasted with other referred optimization algorithms. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Swarm intelligence

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Comparing the Pre-Trained Models with LSTM Combination to Improve Image Captioning Technology 3

Comparing the Pre-Trained Models with LSTM Combination to Im...

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3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Mukil, L.D. Singh, Tripty Sharma, Mansi Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India Graphic Era University Department of Computer Science and Engineering India

ISBN: (纸本)9798331508456

Image captioning, integrating computer vision and natural language processing, has become one of the critical areas of work for better accessibility and advancing technology. In this study, the performance of pre-trained convolutional neural networks-DenseNet, VGG-16, ResNet, and Xception-has been evaluated when coupled with LSTM units for generating captions on Flickr8k. These models have been evaluated on the basis of BLEU and ROUGE scores. The best scores were produced by ResNet-LSTM, which indicates the model's stronger ability to produce captions that are accurate and contextual. VGG-16 with LSTM ranked second;it was almost on par. Xception with LSTM gave results that were moderate. DenseNet with LSTM had the worst score, indicating that the feature extraction mechanism of this model is weak. The following results provide evidence for the practical use of ResNet-LSTM to facilitate access: from assistive technology for visually impaired users to automatically generated content. The comparative study would further indicate which one has more merits or drawbacks compared with others and thereby enable a more informed selection of the models suitable for each particular application. © 2025 IEEE.

关键词： Convolutional neural networks

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Programmable directional color dynamics using plasmonics

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Microsystems & Nanoengineering 2024年第1期10卷 325-334页

作者： Gyurin Kim Doeun Kim Soeun Ko Jang-Hwan Han Juhwan Kim Joo Hwan Ko Young Min Song Hyeon-Ho Jeong School of Electrical Engineering and Computer Science Gwangju Institute of Science and TechnologyGwangju 61005Republic of Korea Department of Semiconductor Engineering Gwangju Institute of Science and TechnologyGwangju 61005Republic of Korea Artificial Intelligence(AI)Graduate School Gwangju Institute of Science and TechnologyGwangju 61005Republic of Korea

Adaptive multicolor filters have emerged as key components for ensuring color accuracy and resolution in outdoor visual ***,the current state of this technology is still in its infancy and largely reliant on liquid crystal devices that require high voltage and bulky structural ***,we present a multicolor nanofilter consisting of multilayered‘active’plasmonic nanocomposites,wherein metallic nanoparticles are embedded within a conductive polymer *** nanocomposites are fabricated with a total thickness below 100 nm using a‘lithography-free’method at the wafer level,and they inherently exhibit three prominent optical modes,accompanying scattering phenomena that produce distinct dichroic reflection and transmission ***,a pivotal achievement is that all these colors are electrically manipulated with an applied external voltage of less than 1 V with 3.5 s of switching speed,encompassing the entire visible ***,this electrically programmable multicolor function enables the effective and dynamic modulation of the color temperature of white light across the warm-to-cool spectrum(3250 K-6250 K).This transformative capability is exceptionally valuable for enhancing the performance of outdoor optical devices that are independent of factors such as the sun’s elevation and prevailing weather conditions.

关键词： directional prevailing exceptional

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