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Ultra-Dense LEO Satellite-Aircraft Access and Service Management in Civil Aviation

China Communications 2025年第1期22卷 277-292页

作者： Wang Yilei Ma Ting Liu Xiaoyu Gao Zhuxuan Zhou Haibo Shen Xuemin School of Electronic Science and Engineering Nanjing UniversityNanjing 210046China School of Electronic and Optical Engineering Nanjing University of Science and TechnologyNanjing 210094China The Department of Electrical and Computer Engineering University of WaterlooWaterloo N2L 3G1Canada

With the deployment of ultra-dense low earth orbit(LEO)satellite constellations,LEO satellite access network(LEO-SAN)is envisioned to achieve global Internet ***,the civil aviation communications have increased dramatically,especially for providing airborne Internet ***,due to dynamic service demands and onboard LEO resources over time and space,it poses huge challenges in satellite-aircraft access and service management in ultra-dense LEO satellite networks(UDLSN).In this paper,we propose a deep reinforcement learning-based approach for ultra-dense LEO satellite-aircraft access and service ***,we develop an airborne Internet architecture based on UDLSN and design a management mechanism including medium earth orbit satellites to guarantee lightweight ***,considering latency-sensitive and latency-tolerant services,we formulate the problem of satellite-aircraft access and service management for civil aviation to ensure service ***,we propose a proximal policy optimization-based access and service management algorithm to solve the formulated *** results demonstrate the convergence and effectiveness of the proposed algorithm with satisfying the service continuity when applying to the UDLSN.

关键词： civil aviation deep reinforcement learning satellite-aircraft access service management ultra-dense LEO satellite network

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MQTT and blockchain sharding:An approach to user-controlled data access with improved security and efficiency

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Blockchain(Research and Applications) 2023年第4期4卷 86-98页

作者： P.S.Akshatha S.M.Dilip Kumar Department of Computer Science and Engineering University of Visvesvaraya College of EngineeringBangalore UniversityBengaluruKarnataka 560056India

The rapid growth of the Internet of Things(IoT)has raised security concerns,including MQTT protocol-based applications that lack built-in security features and rely on resource-intensive Transport Layer Security(TLS)*** paper presents an approach that utilizes blockchain technology to enhance the security of MQTT communication while maintaining *** approach involves using blockchain sharding,which enables higher scalability,improved performance,and reduced computational overhead compared to traditional blockchain approaches,making it well-suited for resource-constrained IoT *** approach leverages Ethereum blockchain’s smart contract mechanism to ensure trust,accountability,and user ***,we introduce a shard-based consensus mechanism that enables improved security while minimizing computational *** also provide a user-controlled and secured algorithm using Proof-of-Access implementation to decentralize user access control to data stored in the blockchain *** proposed approach is analyzed for usability,including metrics such as bandwidth consumption,CPU usage,memory usage,delay,access time,storage time,and jitter,which are essential for IoT application *** analysis demonstrated that the approach reduces resource consumption,and the proposed system outperforms TLS and existing blockchain approaches in these metrics,regardless of the choice of the MQTT ***,thoroughly addressing future research directions,including issues and challenges,ensures careful consideration of potential advancements in this domain.

关键词： Blockchain Internet of Things MQTT Publish/Subscribe MQTT brokers HiveMQ Mosquitto EMQx Eclipse Sharding

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A new design of parity-preserving reversible multipliers based on multiple-control toffoli synthesis targeting emerging quantum circuits

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Frontiers of computer science 2024年第6期18卷 229-244页

作者： Mojtaba NOORALLAHZADEH Mohammad MOSLEH Kamalika DATTA Department of Computer Engineering Dezful BranchIslamic Azad UniversityDezfulIran German Research Centre for Artificial Intelligence(DFKI) Bremen 28359Germany Institute of Computer Science University of BremenBremen 28359Germany

With the recent demonstration of quantum computers,interests in the field of reversible logic synthesis and optimization have taken a different *** every quantum operation is inherently reversible,there is an immense motivation for exploring reversible circuit design and *** it comes to faults in circuits,the parity-preserving feature donates to the detection of permanent and temporary *** the context of reversible circuits,the parity-preserving property ensures that the input and output parities are *** this paper we suggest six parity-preserving reversible blocks(ZFATSL)with improved quantum *** reversible blocks are synthesized using an existing synthesis method that generates a netlist of multiple-control Toffoli(MCT)*** optimization rules are applied at the reversible circuit level,followed by transformation into a netlist of elementary quantum gates from the NCV *** designs of full-adder and unsigned and signed multipliers are proposed using the functional blocks that possess parity-preserving *** proposed designs are compared with state-of-the-art methods and found to be better in terms of cost of *** savings of 25.04%,20.89%,21.17%,and 51.03%,and 18.59%,13.82%,13.82%,and 27.65% respectively,are observed for 4-bit unsigned and 5-bit signed multipliers in terms of quantum cost,garbage output,constant input,and gate count as compared to recent works.

关键词： reversible circuits parity-preserving NCV library multiple-control Toffoli gates quantum circuits quantum cost

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An Energy Efficient IoT Based Smart Street Lighting Using Low Cost SOC 1

An Energy Efficient IoT Based Smart Street Lighting Using Lo...

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1st IEEE International Conference on Electronics, Computing, Communication and Control Technology, ICECCC 2024

作者： Velu, Anitha Ramamoorthy, Raghu Manasa, S.M. Navulkumar, Devakirubai Sri Sairam College of Engineering Department of Electronics and Communication Engineering Bengaluru India The Oxford College of Engineering Department of Computer Science and Engineering Bengaluru India Jayam College of Engineering and Technology Department of Computer Science and Engineering Dharmapuri India

ISBN: (纸本)9798350371802

Internet of Things (IoT) has radically improved and modernized in every aspect of human existence. The term IoT is a recent trend that states the development a self-configurable network by connecting a variety of hardware objects, to internet without requiring human input to improve service delivery and automate processes by means of data transmission to the cloud. Streetlights are an essential component of any city, although they provide safer roadways, improved night vision, and increased visibility of public spaces it uses a significant amount of electricity and operates at maximum intensity from dusk till dawn. The wastage of electricity can be secured by having lights turn OFF on their own if it is not in use. This work presents an energy efficient IoT-based smart street lighting by using low-cost System On Chip (SOC) circuit. This work deploys an LDR sensor which acts as a decision device, to choose whether to switch ON or OFF the street light based on the level of ambient light. This simple switch has a relay at its output and is activated by either light or dark. This switching may be done using a cost-effective Wi-Fi module namely, ESP8266 for which the LDR sensed value is given as input. Any user can check the status of a street light whether it is ON/OFF from anywhere using internet in real time. It promises great dependability and remarkable stability for long-term. The proposed work is implemented using a NodeMCU board that is designed to supply the required light intensity at different times. © 2024 IEEE.

关键词： Internet of things

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Debugging approach for IEC 61499 control applications in FBME 32

Debugging approach for IEC 61499 control applications in FBM...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Akifev, Daniil Liakh, Tatiana Ovsiannikova, Polina Sorokin, Radimir Vyatkin, Valeriy Lulea Tekniska Universitet Department of Computer Science Computer and Space Engineering Sweden Aalto University Department of Electrical Engineering and Automation Espoo Finland

ISBN: (纸本)9798350399714

With the increase in the use of distributed control systems in industrial automation, it is becoming more challenging to analyze the behavior of the system to evaluate its quality. The lack of data coming from the system during operation also complicates debugging and error finding in the system software. The paper presents a quality control method of IEC 61499 industrial control software. The proposed method is based on a combination of several techniques: monitoring of the system behavior, recovering missing data with a simulator, and explanation of the recovered traces by highlighting a sequence of events that led to the explored state of the system. The paper integrates the method into modular IDE for IEC 61499 applications FBME. We also demonstrate the method on a simple example. © 2023 IEEE.

关键词： Quality control

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Invoice Processing Automation Using UI Path Studio 5

Invoice Processing Automation Using UI Path Studio

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5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Ramyadevi, R. Anbuselvan, A. Julian, Anitha Selvi, S. Murali Dhar, M.S. Saveetha Engineering College Department of Computer Science and Engineering Chennai India R.M.K Engineering College Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350383522

Invoices are the fundamental document that play a vital role in encapsulating the details of the products and the business transactions between the seller and the buyer. We cannot check our invoices at any time for emergencies. Substituting the case, by storing the basic details of multiple invoices in an excel sheet might be used for future purposes. This paper provides the advancement of data extraction through automation technologies. We begin this research by the technique Optical Character Recognition (OCR) in automation of data extraction from invoices. This reduces the manual errors during extraction as the entire process works with the automation and provides an accuracy of 95%. The paper discusses the design of the automation that has to be processed for the data extraction including the invoice details, line items and relevant metadata and stored in a structured and accessible format. This storage allows the customer to get through all their product details in a document. Furthermore, the study investigates the integration of extracted data from the invoice to the customer. This integration acts as the strategic role in transforming invoice data into a dynamic asset, enabling customers to glean insights. The paper incorporates real-world examples and case studies to illustrate implementations of scrapping techniques using automation. By addressing challenges such as technological limitations, integration complexities, and data security concerns, the paper provides practical understanding for customers in processing the automation. © 2024 IEEE.

关键词： Accuracy Automation Technologies Data Extractions Data Storage Invoice Processing Optical Character Recognition (OCR)

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Design of a High-Efficiency Temporal Engine for Real-Time Spatial Satellite Image Classification Using Augmented Incremental Transfer Learning for Crop Analysis

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SN computer science 2024年第5期5卷 1-12页

作者： Dhande, Akshay Pramodrao Malik, Rahul Saini, Dipen Garg, Rachit Jha, Sudan Nazeer, Jabeen Ahmad, Sultan Department of Electronics and Telecommunication Engineering Lovely Professional University Punjab Phagwara India School of Computer Science and Engineering Lovely Professional University Punjab Phagwara India Department of Computer Science and Engineering Kathmandu University Dhulikhel Nepal Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Alkharj 11942 Saudi Arabia University Center for Research and Development (UCRD) Department of Computer Science and Engineering Chandigarh University Gharuan Punjab Mohali 140413 India

Satellite image processing is a multidomain task which involves design of image capturing, denoising, segmentation, feature extraction, feature reduction, classification, and post-processing tasks. A wide variety of satellite image processing models are proposed by researchers, and each of them has different data and process requirements. For instance, the image capturing module might obtain images in layered form, while feature extraction module might require data in 2D or 3D forms. Moreover, performance of these models also varies due to changes in internal process parameters and dataset parameters, which limits their accuracy and scalability when applied to real-time scenarios. To reduce the probability of these limitations, a novel high-efficiency temporal engine for real-time satellite image classification using augmented incremental transfer learning is proposed and discussed in this text. The model initially captures real-time satellite data using Google’s Earth Engine and processes it using a transfer learning-based convolutional neural network (CNN) via backscatter coefficient analysis. These coefficients indicate average intensity value of Precision Image (PRI) when evaluated over a distributed target. Due to extraction of backscattering coefficients, the model is capable of representing crop images in VV (vertical transmit, vertical receive), and HV (horizontal transmit vertical receive) modes. Thereby assisting the CNN model to extract a wide variety of features from input satellite image, which classifies these datasets (original, VV, and VH) into different crop categories. The classified images are further processed via an incremental learning layer, which assists in visual identification of affected regions. Due to use of incremental learning and CNN for classification, the proposed TRSAITL model is capable of achieving an average accuracy of 97.8% for crop type and severity of damage detection, with an average PSNR (Peak Signal-to-Noise Ratio) of 29.

关键词： Accuracy Classification Crop Damage Deep learning Earth Incremental Precision Recall Satellite Transfer Type

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Designing a Heuristic Based Hybrid CNN with Attention Mechanism for the Effective Classification of Fish Species 5

Designing a Heuristic Based Hybrid CNN with Attention Mechan...

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5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Bhanumathi, M. Arthi, B. Srm Institute of Science and Technology Department of Computer Science and Engineering India Department of Computer Science and Engineering India College of Engineering and Technology Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computer Science and Engineering India

ISBN: (纸本)9798350321425

In recent days, the population of fish species is enormously increased. The measurement of the total population of the fish species is also a complex task. The population of fishes can be easily identified by its classification of variants. But, the categorization of fishes is an annoying task for marine ecologists and biologists. The fishery activities can be easily managed by calculating the total population and size. Several methods are developed for classifying the fish species, but they take more computational time and manpower. These limitations are overthrown by automatic methods. The automatic method monitors the activities of fish and their path. The major advantages of this automatic System are to reduce labor requirement and time. This research study suggests a new fish species categorization model with the help of a Hybrid Convolution Neural Network(CNN) with an Attention Mechanism (HCNN-AM). In the initial phase, the images are aggregated from the standard benchmark dataset. Then, the images are forwarded to the hybrid CNN with an attention mechanism for effectively classifying the fish species, in which the attributes are optimized with the aid of a hybrid Fitness-based Hybrid Rat Swarm with Billiards-inspired Optimization (FH-RSBO). Therefore, the planned method is an efficient substitute for strenuous and time-consuming methods of physical recognition by marine experts. Thus, it becomes the most advantageous task to monitor the fish biodiversity in their natural habitats. © 2023 IEEE.

关键词： Optimization

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Traffic Sign Categorization Using YOLO Algorithm: Leveraging Real-Time Object Detection for Improved Road Safety 9

Traffic Sign Categorization Using YOLO Algorithm: Leveraging...

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Santha Sheela, K. Jason Kingsly, R. Bhalaji, C.K. Selvalakshmi, C.B. Radhika, A. Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India Velammal college of engineering and Technology Dept of Electrical and Electronics Engineering Madurai India

ISBN: (纸本)9798350377972

Traffic signs, and navigation provide drivers with crucial information about speed limits, hazards and are essential for maintaining road safety. Detecting these signs and classifying in real-time plays a vital for autonomous driving systems, as timely information can prevent accidents and ensure compliance with traffic regulations. This paper presents a traffic sign detection system based on the YOLOv8 algorithm, known for its high-speed object detection capabilities, addressing challenges such as occlusion, small object detection, and adverse lighting conditions. The system is trained using a dataset of traffic signs sourced from Roboflow, capturing various types of traffic signs under different environmental conditions, such as lighting, weather, and occlusion scenarios. By using advanced feature extraction techniques, we have visualize the critical features that proposed for the model's classification decisions. The results confirm the efficacy and real-time applications in autonomous vehicles and smart traffic management systems of YOLOv8, indicating the intelligence potential for widespread adoption in the field of vehicles transportation systems. © 2024 IEEE.

关键词： Advanced traffic management systems

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A survey of artificial intelligence models for wireless capsule endoscopy videos for superior automatic diagnosis: problems and solutions

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Multimedia Tools and Applications 2025年 1-35页

作者： El-Gammal, Eman M. El-Shafai, Walid Taha, Taha E. El-Fishawy, Adel S. Abd El-Samie, Fathi E. Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Center of Advanced Software and Biomedical Clinical Engineering Consultations Faculty of Engineering Cairo University Giza Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University 84428 Riyadh11671 Saudi Arabia

Wireless Capsule Endoscopy (WCE) emerged as an innovative and patient-centric approach for non-invasive and painless examination of the gastrointestinal (GI) tract. It serves as a pivotal tool in helping medical practitioners in the early detection of anomalies within the intricate domain of the human GI tract. The automated identification of aberrations assumes paramount significance, contributing not only to temporal efficiency but also to timely diagnosis. Within the realm of academic literature, a plethora of Artificial Intelligence (AI) methodologies have been proposed to effectuate the automatic classification, segmentation, and synthesis of anomalies inherent in WCE images. This scholarly endeavor undertakes a comprehensive and meticulous survey, elucidating the spectrum of anomaly classification, summarization, and detection techniques harnessed for computer-Aided Diagnosis (CAD) in the context of WCE images. The survey begins by delineating the methodologies underpinning WCE image classification and video processing. Subsequently, an exhaustive evaluation of techniques for analyzing WCE images is furnished, accompanied by an in-depth exploration of pertinent surveys, in addition to a judicious assessment of their merits and demerits. Furthermore, this study undertakes a rigorous evaluation of prevailing datasets utilized to benchmark the efficacy of various WCE techniques. In summary, this survey serves as a vanguard, delineating promising avenues for future investigations in the realm of WCE image analysis models. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Endoscopy

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