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Attacks, Detection, and Prevention on Commercial Drones: A Review 3

Attacks, Detection, and Prevention on Commercial Drones: A R...

引用

3rd international conference on Image Processing and Robotics, ICIPRoB 2024

作者： Warnakulasooriya, Kolitha Segev, Aviv University of South Alabama School of Computing Mobile United States

ISBN: (纸本)9798350374766

In recent years, the rising popularity of commercial drones across various industries and applications has been notable. These modern drone systems boast an array of advanced features such as Autopiloting, Video Streaming, and Swarming. However, the pressing need to address the cybersecurity vulnerabilities inherent in commercially available drones cannot be overstated. The prevalence of open technologies, coupled with constraints on costs for robust security implementations, and the overshadowing focus on other functionalities underscores the urgency of this discussion. This paper aims to engage in a comprehensive discussion of current threats and propose easily implementable prevention mechanisms for manufacturers to enhance the cybersecurity of commercial drones at a broad level. © 2024 ieee.

关键词： Drones

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Research on the current Situation and Future Trend of Microservice Technology Development 6

Research on the Current Situation and Future Trend of Micros...

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6th ieee advanced Information Technology, Electronic and Automation Control conference (ieee IAEAC)

作者： Wang, Fuxue Zhang, Jie Acad Mil Sci Inst Syst Engn Beijing Peoples R China

ISBN: (数字)9781665458641

ISBN: (纸本)9781665458641

For many years, we have been looking for a better approach to software architecture, and microservices is one of the latest trends in cloud computing and Internet of Things (IoT) research. It is also one of the most popular trends in software architecture research today. Microservices Architecture (MSA) revolutionizes software systems and cloud-native architecture. New microservices technologies are constantly being born, covering existing technology vulnerabilities and going beyond state-of-the-art frameworks. In recent years,many significant achievements have been made worldwide in this area. Because microservices architectures are evolving rapidly, it is difficult to keep up with their progress, especially for researchers new to the field. In this article, we will briefly discuss the latest developments in microservices architecture in recent years.

关键词： software architecture IoT microservices architecture cloud native

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A Review of Battery Energy Storage System Optimization: current State-Of- The-Art and Future trends

A Review of Battery Energy Storage System Optimization: Curr...

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2024 international conference on Green Energy, computing and Sustainable Technology, GECOST 2024

作者： Talebi, Shiva Aly, Hamed H. Dalhousie University Department of Electrical and Computer Engineering HalifaxNS Canada

ISBN: (纸本)9798350357905

The transition away from fossil fuels due to their environmental impact has prompted the integration of renewable energy sources, particularly wind and solar, into the main grid. However, the intermittent nature of these renewables and the potential for overgeneration pose significant challenges. Battery energy storage systems (BESS) emerge as a solution to balance supply and demand by storing surplus energy for later use and optimizing various aspects such as capacity, cost, and power quality. Battery energy storage systems are a key component, and determining optimal sizing and scheduling is a critical aspect of the design of the system. The degradation of batteries may not seem important in some optimization studies, but it has a significant impact on objectives like system reliability and cost. Addressing degradation either as a constraint or an objective in optimization models is a crucial point. This paper provides a comprehensive overview of BESS, covering various battery technologies, degradation, optimization strategies, objectives, and constraints. It categorizes optimization goals and methods, offering insights into the current research landscape and identifying research gaps. The paper's recommendations aim to guide researchers in designing efficient battery-based energy storage systems, promoting a sustainable future with green energy solutions. © 2024 ieee.

关键词： Renewable energy

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Portability of Fortran's 'do concurrent' on GPUs

Portability of Fortran's 'do concurrent' on GPUs

引用

2024 Workshops of the international conference for High Performance computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Caplan, Ronald M. Stulajter, Miko M. Linker, Jon A. Larkin, Jeff Gabb, Henry A. Su, Shiquan Rodriguez, Ivan Tschirhart, Zachary Malaya, Nicholas Predictive Science Inc. San DiegoCA United States NVIDIA Corporation Santa ClaraCA United States Intel Corporation AustinTX United States Intel Corporation BoulderCO United States Hewlett Packard Enterprise AustinTX United States Advanced Micro Devices Inc AustinTX United States

ISBN: (纸本)9798350355543

There is a continuing interest in using standard language constructs for accelerated computing in order to avoid (sometimes vendor-specific) external APIs. For Fortran codes, the do concurrent (DC) loop has been successfully demonstrated on the NVIDIA platform. However, support for DC on other platforms has taken longer to implement. Recently, Intel has added DC GPU offload support to its compiler, as has HPE for AMD GPUs. In this paper, we explore the current portability of using DC across GPU vendors using the in-production solar surface flux evolution code, HipFT. We discuss implementation and compilation details, including when/where using directive APIs for data movement is needed/desired compared to using a unified memory system. The performance achieved on both data center and consumer platforms is shown. © 2024 ieee.

关键词： accelerated computing do concurrent Fortran OpenACC OpenMP standard language parallelism

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A Comprehensive Review of Knee Abnormalities Detection current Procedures, Outcomes and Prospects 1

A Comprehensive Review of Knee Abnormalities Detection Curre...

引用

1st international conference on Technological Innovations and Advance computing, TIACOMP 2024

作者： Parekh, Maulik Arvindbhai Meva, Divyakant Marwadi University Faculty of Computer Applications Gujarat Rajkot India

ISBN: (纸本)9798350392111

Knee joints are made up of cartilage, bone, fluid and ligaments in which muscles and tendons are there for helping knee joints movement. Knee pains caused due to injury, repeated stress on knee or aging. Knee abnormalities or injury can be diagnosed using different methodologies like X-RAY, CT scan, Arthroscopy or MRI. In our survey, we thoroughly analyzed several recent research to investigate the landscape of predictive modeling, a comprehensive analysis of current literature, evaluating trends, and methodologies. We identified that deep-learning models showcased average accuracy for predicting that knee is normal or abnormal is ranged from 63.4% to 98%. In this review paper, we also highlight several limitations like challenges for generalization of models in different centers, biasness in verification, lack of multi-classification studies, unavailability of data and subjectivity of ground-truth. We also proposed An Explainable Attention Based Deep Learning Knee Anomalies Prediction Model with Ensemble Learning Algorithms framework. Here, multi-modal deep learning model architecture is designed to handle and learn from multiple types of data inputs. We achieved 84.54% accuracy with Kaggle knee dataset. © 2024 ieee.

关键词： Joints (anatomy)

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Message from the General Chair

Proceedings - 2024 International Conference on Current Trend...

引用

Proceedings - 2024 international conference on current trends in advanced computing, ICCTAC 2024 2024年

作者： Kumar, R. India

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Big Data-Driven Strategies for Growth in 3PL with advanced IT Solutions 1

Big Data-Driven Strategies for Growth in 3PL with Advanced I...

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1st international conference on advanced computing and Emerging Technologies, ACET 2024

作者： Yogi, Kottala Sri Suganthi, N. Dankan Gowda, V. Hanumantharao, Attru Srinivas, Ved Kavitha, R. Hyderabad Symbiosis International University Symbiosis Institute of Business Management Department of Operations Pune India Dayananda Sagar College of Engineering Department of Electrical and Electronics Engineering Karnataka Bangalore India Bms Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India Aditya College of Engineering and Technology Department of Computer Science & Engineering Andhra Pradesh Surampalem India Thiagarajar School of Management Department of Human Resources Tamil Nadu Madurai India Velammal College of Engineering and Technology Department of Information Technology Madurai India

ISBN: (纸本)9798350367720

The focus of this paper is to examine how different big data initiatives support the development and operations of third party logistics providers. Focusing on the use of advanced technologies like IoT, AI, and ML in the context of 3PL, the research has the objective to show how these innovations enhance efficiency, operating cost, and customer satisfaction. Information gathered from live monitoring, use of algorithms or predictive techniques, and integration of logistics optimization techniques are used to highlight performance enhancement. According to the proposed model, the processes related to the utilisation of big data and IT solutions are divided into several categories: big data acquisition, cloud computing, and subsequent constant evaluation. This study reveals insights that 3PL providers can create a sustainable competitive advantage to the clientele firms by adopting accurate demand forecasting, improvement of routes, and optimization of supply chain visibility. Thus, the findings of this study add to the current literature and practice by enumerating effective big data technologies to apply in logistics management and showcasing how these advancements can catalyze sustainable development. © 2024 ieee.

关键词： 3PL Artificial Intelligence Big Data Data Analytics Internet of Things IT Solutions Supply Chain Management Third-Party Logistics

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A Dynamic Monitoring and Early Warning System for Industrial Markets Based on Computer Algorithms 3

A Dynamic Monitoring and Early Warning System for Industrial...

引用

3rd international conference on Data Analytics, computing and Artificial Intelligence, ICDACAI 2024

作者： Jin, Li China Electrical Equipment International Company Limited Shanghai China

ISBN: (纸本)9798331519032

With the deepening development of global economic integration, industrial market fluctuations are becoming increasingly frequent and complex, which puts higher demands on enterprises and policy makers to timely and accurately grasp market dynamics, accurately predict potential risks, and formulate effective response strategies based on this. Market risk is not only related to the success or failure of enterprise operations, but also an important factor affecting national economic stability. Therefore, establishing a comprehensive industrial market dynamic monitoring and early warning system to achieve real-time monitoring and early warning of various internal and external risk factors has become a key issue that enterprises and governments urgently need to solve. This article delves into the dynamic monitoring and early warning system of industrial markets based on computer algorithms. The system integrates multi-source data using big data processing technology, and uses advanced machine learning (ML) algorithms to explore hidden patterns behind the data, constructing accurate prediction models. The experimental results show that the system proposed in this article performs well in terms of prediction accuracy, real-time performance, and stability. This system can accurately capture market trends, provide early warning of potential risks, and provide strong support for enterprise decision-making. © 2024 ieee.

关键词： Commerce

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Proceedings - 2023 ieee international conference on Cloud computing Technology and Science, CloudCom 2023

Proceedings - 2023 IEEE International Conference on Cloud Co...

引用

14th ieee international conference on Cloud computing Technology and Science, CloudCom 2023

ISBN: (纸本)9798350339826

The proceedings contain 48 papers. The topics discussed include: 5G SUCI Catcher: attack and detection;enabling 5G QoS configuration capabilities for IoT applications on container orchestration platform;decentralized authentication in microservice architectures with SSI and DID in blockchain;performance analysis of the raft consensus algorithm on Hyperledger fabric and Ethereum on cloud;cost-optimized scheduling for microservices in Kubernetes;surveying cyber threat intelligence and collaboration: a concise analysis of current landscape and trends;semi-automatic PenTest methodology based on threat-model: the IoT brick case study;a flexible trust manager for remote attestation in heterogeneous critical infrastructures;and enabling trusted TEE-as-a-Service models with privacy preserving automatons.

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Transmission Line Fault Detection and Classification Using Feature Extraction Based Self-Attention Convolutional Neural Network with Time Series Image 3

Transmission Line Fault Detection and Classification Using F...

引用

3rd ieee international conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Almusawi, Muntather Babu, D. Raja Mazumder, Debarshi Bala Dhandayuthapani, V. Saranya, N. Naga College Of Technical Engineering The Islamic University Department Of Computers Techniques Engineering Najaf Iraq Sr University Department Of Electrical And Electronics Engineering Warangal India Nitte Meenakshi Institute Of Technology Department Of Ai & Ds Bengaluru India College Of Computing And Information Sciences University Of Technology And Applied Sciences Department Of It Shinas campus Oman Saveetha College Of Liberal Arts & Science Simats Department Of Computer Applications Chennai India

ISBN: (纸本)9798350318609

The transmission lines continuously experience the number of shunt faults and its effective in practical system increases the instability, load damages and line restoration cost. This work implements an advanced self-attention convolutional neural network (SAT-CNN) method for fault detection and classification (FDC) of high voltage transmission lines experiencing a constant number of shunt faults. Faults cause load damage in real-time applications, increase instability, and increase the cost of line restoration. Therefore, a precise model is needs to identify and categorize the flaws to quickly restore he problematic phases. In this research, implemented SAT-CNN feature extraction model with imaging-based on time series that can accurately detect and classify faults. By employing a number of input signals, including, current, voltage, and combined current and voltage signals, at different sampling frequencies, the efficacy of implemented SAT-CNN model is evaluated. Implemented SAT-CNN method obtains high performance when compared to existing methods including weight-sharing network (WSCN), Truncated singular value decomposition and Human urbanization algorithm based Recurrent Perceptron Neural Network (TSVD-HUARPNN), and Graph convolutional neural network (GCN), and result achieved 99.90% accuracy value. © 2024 ieee.

关键词： Convolutional neural networks

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