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IOT based prediction of rainfall forecast in coastal regions using deep reinforcement model

Measurement: Sensors 2023年 29卷

作者： Nithyashri, J. Poluru, Ravi Kumar Balakrishnan, S. Ashok Kumar, M. Prabu, P. Nandhini, S. Department of Computing Technologies School of Computing SRM Institute of Science and Technology Chengalpet District Kattankulathur603203 India Department of Information Technology Institute of Aeronautical Engineering Hyderabad India Department of Computer Science and Business Systems Sri Krishna College of Engineering and Technology Coimbatore India Faculty of Computer Science Department of Computer Science and Software Engineering Skyline University Nigeria Kano Nigeria Bengaluru560029 India Department of Computer Science and Engineering Karpagam Academy of Higher Education Tamilnadu Coimbatore India

This research proposes an IoT based technique for predicting rainfall forecast in coastal regions using a deep reinforcement learning model. The proposed technique utilizes Long Short-Term Memory (LSTM) networks to capture the temporal dependencies between the rainfall data collected from the coastal regions and the prediction model parameters. The proposed technique is evaluated on a dataset of rainfall data collected from the coastal regions of India and compared to traditional methods of rainfall forecasting. The accuracy and reliability of these models are evaluated by comparing them to prior models. Precipitation in coastal locations may be predicted with an average accuracy of 89% using the suggested model, as shown by the results. The suggested framework is computationally efficient and can be trained with little input. The results of this research give strong evidence that the proposed model is an effective tool for coastal precipitation forecasting. © 2023 The Authors

关键词： Internet of things

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Formal semantics for component assembly pattern of software architecture

Formal semantics for component assembly pattern of software ...

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IEEE International Conference on Industrial engineering and engineering Management

作者： Wei Guo Sheng Xu Ren Zuo Xu College of Computer Science Wuhan University Wuhan China International Software School Wuhan University Wuhan China State Key Lab. of Software Engineering Wuhan University Wuhan China

The performance and reliability of component-based software architectures rely fundamentally on the quality of the components and the configuration that the system is composed. This paper analysis the assembly patterns and interaction behaviors of components at first, then an ontology of the component¿s operation is proposed, which the interactions of components are formalized and abstracted. Based on the in-depth analysis of the component assembly patterns, this paper try to define the assembly patterns in architecture on process algebra theory, which can establish a practical means of describing and analyzing the component assembly pattern in the software architectures. Furthermore, the architecture algebra model has been built, which can set a theoretical foundation for the further research on analysis and validation of architecture.

关键词： software architecture computer architecture Pattern analysis Assembly systems software quality Algebra software systems Application software Educational institutions computer science

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An n-MOSFET Layout with Multi-Finger Z Gate for Radiation Tolerance 5

An n-MOSFET Layout with Multi-Finger Z Gate for Radiation To...

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5th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2022

作者： Shan, Chan Liu, Ying Chen, Huan Huo, Dong-Yang Xu, Tian-Rong Jimei University College of Ocean Information Engineering Xiamen China Xiamen Institute of Software Technology Department of Software Technology Xiamen China Minjiang University School of Journalism and Communication Fuzhou China Universiti Malaya Faculty of Computer Science and Information Technology Department of Information Systems Kuala Lumpur Malaysia Universiti Malaya Planning Faculty of Built Environment Department of Urban and Regional Kuala Lumpur Malaysia

ISBN: (数字)9781665479295

ISBN: (纸本)9781665479295

In this paper, a new n-MOSFET layout with multi-finger Z gate is proposed to reduce the total ionizing dose (TID) effect. In addition to the proposed layout, multi-finger single gate layout is also simulated using Sentaurus TCAD in 3D. Firstly, drain current - gate voltage curves of both layouts are compared in order to verify the radiation hardening ability of the proposed layout. Secondly, we compare TID responses by extracting threshold voltages and leakage currents from both layouts. Thirdly, the finger number is investigated for both layouts because it is an important factor for multi-finger layout. The results have indicated that the finger number significantly affects the multi-finger single gate layout, whereas the proposed multi-finger Z gate layout is relatively little affected by the finger number in radiation environment. © 2022 IEEE.

关键词： Drain current

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A hardware intellectual property protection scheme based digital compression coding technology

A hardware intellectual property protection scheme based dig...

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IEEE International Conference on Smart Cloud (SmartCloud)

作者： Lijun Xiao Weihong Huang Han Deng Weidong Xiao the Department of Accounting Guangzhou college of Technology and Business Guangzhou China the College of Computer Science and Electronic Engineering Hunan University Changsha China the School of Software Engineering Xiamen university of technology Xiamen China

ISBN: (数字)9781728155067

ISBN: (纸本)9781728155074

This paper presents a scheme of intellectual property protection of hardware circuit based on digital compression coding technology. The aim is to solve the problem of high embedding cost and low resource utilization of IP watermarking. In this scheme, the watermark information is preprocessed by dynamic compression coding around the idle circuit of FPGA, and the free resources of the surrounding circuit are optimized that the IP watermark can get the best compression coding model while the extraction and detection of IP core watermark by activating the decoding function. The experimental results show that this method not only expands the capacity of watermark information, but also reduces the cost of watermark and improves the security and robustness of watermark algorithm.

关键词： Watermarking Encoding IP networks Hardware Cryptography Field programmable gate arrays Table lookup

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A new dynamic probabilistic Particle Swarm Optimization with dynamic random population topology

A new dynamic probabilistic Particle Swarm Optimization with...

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Congress on Evolutionary Computation

作者： Qingjian Ni Cen Cao Xushan Yin College of Software Engineering Southeast University Nanjing China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou China School of Computer Science and Engineering Southeast University Nanjing China

ISBN: (纸本)9781479914869

Population topologies of Particle Swarm Optimization algorithm (PSO) have direct impacts on the information sharing amony particles during the evolution, and will influence the PSO algorithms' performance obviously. The canonical PSO algorithms usually use static population topologies, and the majority are the classic population topologies (such as fully connected topology and ring topology). In this paper, we present the strategies of dynamic random topology based on the random generation of population topologies. The basic idea is as follows: various random topologies are used at different stages of evolution in the population, and the solving performance of PSO algorithms is enhanced by improving the information exchange of population in different evolutionary stages. This provides a new way of thinking for the improvement of the PSO algorithm. Experimental results on a relatively new variant of dynamic probabilistic particle swarm optimization show that our strategies can achieve better performance compared with traditional static population topologies. Experimental data are analyzed and discussed in the paper, and the useful conclusions will provide a basis for further research.

关键词： Topology Sociology Statistics Heuristic algorithms Equations Mathematical model Particle swarm optimization

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One-stage Multi-task Detector for 3D Cardiac MR Imaging

One-stage Multi-task Detector for 3D Cardiac MR Imaging

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International Conference on Pattern Recognition

作者： Weizeng Lu Xi Jia Wei Chen Nicolò Savioli Antonio de Marvao Linlin Shen Declan O'Regan Jinming Duan Computer Vision Institute School of Computer Science and Software Engineering Shenzhen University Shenzhen China School of Computer Science University of Birmingham United Kingdom MRC London Institute of Medical Sciences Imperial College London United Kingdom

Fast and accurate landmark location and bounding box detection are important steps in 3D medical imaging. In this paper, we propose a novel multi-task learning framework, for real-time, simultaneous landmark location and bounding box detection in 3D space. Our method extends the famous single-shot multibox detector (SSD) from single-task learning to multitask learning and from 2D to 3D. Furthermore, we propose a post-processing approach to refine the network landmark output, by averaging the candidate landmarks. Owing to these settings, the proposed framework is fast and accurate. For 3D cardiac magnetic resonance (MR) images with size 224×224×64, our framework runs ~128 volumes per second (VPS) on GPU and achieves 6.75mm average point-to-point distance error for landmark location, which outperforms both state-of-the-art and baseline methods. We also show that segmenting the 3D image cropped with the bounding box results in both improved performance and efficiency.

关键词： Heart Image segmentation Three-dimensional displays Magnetic resonance Graphics processing units Detectors Real-time systems

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Applying Hybrid Clustering in Pulsar Candidate Sifting with Multi-modality for FAST Survey

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Research in Astronomy and Astrophysics 2024年第3期24卷 283-296页

作者： Zi-Yi You Yun-Rong Pan Zhi Ma Li Zhang Shuo Xiao Dan-Dan Zhang Shi-Jun Dang Ru-Shuang Zhao Pei Wang Ai-Jun Dong Jia-Tao Jiang Ji-Bing Leng Wei-An Li Si-Yao Li School of Physics and Electronic Science Guizhou Normal UniversityGuiyang 550025China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal UniversityGuiyang 550025China College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China CAS Key Laboratory of FAST National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China Key Laboratory of Information and Computing Guizhou Province Guizhou Normal UniversityGuiyang 550001China School of Big data and Computer Science Guizhou Normal UniversityGuiyang 550025China Guizhou Software Engineering Research Center Guiyang 550000China

Pulsar search is always the basis of pulsar navigation,gravitational wave detection and other research ***,the volume of pulsar candidates collected by the Five-hundred-meter Aperture Spherical radio Telescope(FAST)shows an explosive growth rate that has brought challenges for its pulsar candidate filtering ***,the multi-view heterogeneous data and class imbalance between true pulsars and non-pulsar candidates have negative effects on traditional single-modal supervised classification *** this study,a multi-modal and semi-supervised learning based on a pulsar candidate sifting algorithm is presented,which adopts a hybrid ensemble clustering scheme of density-based and partition-based methods combined with a feature-level fusion strategy for input data and a data partition strategy for *** on both High Time Resolution Universe SurveyⅡ(HTRU2)and actual FAST observation data demonstrate that the proposed algorithm could excellently identify pulsars:On HTRU2,the precision and recall rates of its parallel mode reach0.981 and 0.988 *** FAST data,those of its parallel mode reach 0.891 and 0.961,meanwhile,the running time also significantly decreases with the increment of parallel nodes within ***,we can conclude that our algorithm could be a feasible idea for large scale pulsar candidate sifting for FAST drift scan observation.

关键词： methods data analysis-surveys-methods numerical

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Research on Improved Quick Sort Algorithm with Duplicate Value Handling

Research on Improved Quick Sort Algorithm with Duplicate Val...

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International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Hemin Amit Yadav Asif Khan Abhishek Pratap Sah College of Computer and Software Chengdu Neusoft University Chengdu China College of Engineering IT and Environment Charles Darwin University NT Australia Department of Computer Application Integral University Lucknow India School of Management Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

An improved algorithm based on Quick Sort algorithm research method is proposed to deal with prevailing duplicate values in the sorting of data. The duplicate values are specially processed, which effectively reduces the number of division and greatly reduces the number of recursions. The experimental results show that the time efficiency is improved by more than 50% when dealing with large data than the traditional Quick Sort algorithm without reducing the space efficiency.

关键词： Distributed processing Multicore processing Big Data Stability analysis Hardware Distributed computing Optimization Sorting

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Enhancing the Robustness of QMIX against State-adversarial Attacks

arXiv

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arXiv 2023年

作者： Guo, Weiran Liu, Guanjun Zhou, Ziyuan Wang, Ling Wang, Jiacun Department of Computer Sciences Tongji University Shanghai China College of Transportation Engineering Tongji University Shanghai China Department of Computer Science and Software Engineering Monmouth University West Long Branch United States

Deep reinforcement learning (DRL) performance is generally impacted by state-adversarial attacks, a perturbation applied to an agent’s observation. Most recent research has concentrated on robust single-agent reinforcement learning (SARL) algorithms against state-adversarial attacks. Still, there has yet to be much work on robust multi-agent reinforcement learning. Using QMIX, one of the popular cooperative multi-agent reinforcement algorithms, as an example, we discuss four techniques to improve the robustness of SARL algorithms and extend them to multi-agent scenarios. To increase the robustness of multi-agent reinforcement learning (MARL) algorithms, we train models using a variety of attacks in this research. We then test the models taught using the other attacks by subjecting them to the corresponding attacks throughout the training phase. In this way, we organize and summarize techniques for enhancing robustness when used with MARL. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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SCS: A Secure Cloud Storage Framework with Enhanced Integrity and Auditability Using Consortium Blockchain System

SCS: A Secure Cloud Storage Framework with Enhanced Integrit...

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IEEE International Conference on Smart Internet of Things (SmartIoT)

作者： Aguru Aswani Devi Erukala Suresh Babu Mekala Srinivasa Rao Rajesh Kaluri Thippa Reddy Gadekallu Department of Computer Science & Engineering SRM University AP Amaravati Andhra Pradesh India Department of Computer Science & Engineering National Institute of Technology Warangal India Department of Computer Science & Engineering Lakireddy Bali Reddy College of Engineering India Department of Software and Systems Engineering Vellore Institute of Technology Vellore India The College of Mathematics and Computer Science Zhejiang A&F University Hangzhou China Division of Research and Development Lovely Professional University Phagwara India

ISBN: (数字)9798350366440

ISBN: (纸本)9798350366457

The widespread adoption of cloud storage enables users to remotely access resources through a self-service model. Utilizing pay-per-use storage services provided by cloud service providers (CSPs) requires users to commit financially to their resources. This paper introduces a Secure Cloud Storage (SCS) framework, offering a secure architecture for cloud storage using a consortium blockchain network to address trust issues. This framework substitutes the third-party auditor with peers of a consortium blockchain network, which handles the role of data storage and verification. Storage space is divided into uncommitted and committed segments. Uncommitted storage is used for storing unverified documents, while committed storage is reserved for documents that have been validated through a consensus mechanism. In contrast, committed storage is des-ignated for the storage of committed documents. Documents validated by a consensus threshold of peer nodes are moved from uncommitted to committed storage. The implementation of the SCS framework is conducted using Hyperledger Fabric, a modular blockchain platform optimized for permissioned networks. The security analysis demonstrates that SCS effectively protects cloud storage against attacks, including unauthorized access attacks, data integrity attacks, and malicious server attacks, while maintaining data integrity and auditability. The performance evaluation shows that document upload and retrieval times, block acceptance, execution times, and latency are all improved compared to state-of-the-art cloud storage techniques.

关键词： Performance evaluation Cloud computing Data integrity Memory Peer-to-peer computing Servers Security Internet of Things Secure storage Self-service

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