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A Novel Enhanced EfficientNet Model for Identification of Floating Debris on Marine Surface

A Novel Enhanced EfficientNet Model for Identification of Fl...

引用

2023 international conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering, ICECONF 2023

作者： Joseph, Sneha Suresh, G. Jyothi, P. Ashok, S. Venkatesan, D. Shifani, S. Agnes Department of Electronics and Communication Engineering R.M.K. Engineering College Chennai India Department of Electrical and Electronics Engineering Sona College of Technology Salem India Department of Management Studies Saveetha Engineering College Chennai India Department of Electronics and Communication Engineering Vel Tech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College Chennai India Department of Chemical Engineering Sathyabama Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering Jp College of Engineering Tenkasi India

ISBN: (纸本)9798350334357

Two methods of encoding time series, the Gramian Angular Summation Field (GASF) and the Gramian Angular Difference Field (GADF), are investigated in this research to provide a novel framework for encoding radar echo Doppler spectral patterns into pictures. The purpose of this study is to use the advantages offered by CNN models in order to better identify submerged objects. In order to improve the model's convergence, this study implements the coordinate attention (CA) method into EfficientNet's mobile inverted bottleneck convolution (MBConv) structure. The goal is to draw attention to the crucial role played by the coordinates in which the GAF map stores texture data. At last, the updated EfficientNet model is put through its paces by being tested and trained on the newly built GADF and GASF datasets, respectively. The findings from the experiments provide evidence that the suggested algorithm is successful. The upgraded EfficientNet model achieves a recognition accuracy of 96.13% on the GADF dataset and 96.28% on the GASF dataset, respectively. This is an increase of 1.74% and 2.06% when compared to the recognition accuracy of the pre-enhanced network model. The suggested approach achieves a greater level of accuracy than the traditional method of picture categorization while maintaining a smaller burden of computing. © 2023 IEEE.

关键词： Deep learning

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Advancing Textual Semantic Understanding with Quantum LSTM Networks

Advancing Textual Semantic Understanding with Quantum LSTM N...

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international conference on Information and Communication technology convergence (ICTC)

作者： Muhammad Mustafa Umar Gondel Kyung Min Byun Hyundong Shin Department of Electronics and Information Convergence Engineering Kyung Hee University Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Long Short-Term Memory (LSTM) networks are adept at managing long-term dependencies in sequential data, making them particularly effective for understanding semantics in context. However, challenges such as language complexity and data limitations persist in natural language processing (NLP). Quantum computing utilizes quantum mechanics to tackle complex language structures with limited data. By integrating quantum computing with LSTM, we can address the issues of linguistic complexity and data scarcity. In this paper, we present a Quantum Long Short-Term Memory (QLSTM) network that comprehends the semantics of textual data. Our simulations demonstrate superior capability of QLSTM in capturing textual semantics.

关键词： Computational modeling Semantics Speech recognition Linguistics Natural language processing Data models Complexity theory Integrated circuit modeling Quantum circuit Long short term memory

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Intelligent SDN Routing: A Threshold-Based and LSTM-Enhanced Deep Q-Network Routing Algorithm

Intelligent SDN Routing: A Threshold-Based and LSTM-Enhanced...

引用

2023 international conference on Electronics, Computers and Communication technology, CECCT 2023

作者： Liu, Bo Yang, Bo Sun, Runyuan Liang, Zhifeng Sun, Zhenxiang Li, Zhenyu School of Information Science and Engineering University of Jinan 250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan 250022 China Quancheng Laboratory China and School of Information Science and Engineering University of Jinan 250022 China

ISBN: (纸本)9798400707629

With the rapid development of Internet technology and the diversification of new network applications and services, traditional routing protocols make decisions based on limited information, which leads to untimely responses to changing network demands and limitations in meeting the quality of service requirements of applications. As a new type of network architecture, a Software-Defined Network (SDN) can obtain a global view of the network, realize more granular network monitoring, and flexible deployment of network functions. With the rise of artificial intelligence, SDN routing algorithms based on machine learning gradually show potential for development, however, such algorithms usually can only deal with discrete low-dimensional action spaces and rely on in-network data for training, which is ineffective for dynamic network environments. Therefore, this paper proposes a framework of Intelligent SDN Routing (ISR) based on SDN and designs a threshold-based LSTM-enhanced Deep Q-Network Routing Algorithm (TL- DQN-RA ) applied in SDN, TL-DQN-RA adds Long Short-Term Memory (LSTM) to Deep Q-Network (DQN) and sets the experience playback pool threshold to accelerate the convergence of the algorithm, so that the network can learn in real-time and automatically adjust the routing strategy to cope with the changing network demands. Experiments show that TL-DQN-RA significantly outperforms existing routing solutions in terms of key performance, and the ISR framework provides strong support for network performance improvement. © 2023 ACM.

关键词： Reinforcement learning

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New trends in high speed networking

New trends in high speed networking

引用

international conference on computing for Sustainable Global Development (INDIACom)

作者： S. C. Gupta Raj Kumar Goel Institute of Technology Ghaziabad

convergence of information and communication technology (ICT) has met the large demand of voice, data, video and internet. The necessity of high speed network between computer to computer, computer to business houses and industrial users is the current requirement. The high speed network in advanced countries has increased from 40 Gbps to 40 Tbps. Such signals can not be processed electronically due to low signal to noise ratio. Hence, new technology based on optical-optical multiplexing using lasers as transmitters and photo diode as receiver via optical fiber medium has been successfully developed now a days.

关键词： Optical fiber amplifiers Optical amplifiers Optical fiber networks Wavelength division multiplexing Optical fiber dispersion

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Research on Computer Cloud Intelligent System Based on Intelligent Virtualization technology

Research on Computer Cloud Intelligent System Based on Intel...

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Electrical Engineering, Big Data and Algorithms (EEBDA), IEEE international conference on

作者： Qingfeng Shi Fei Zhao College of Physical Education Taishan University Tai'an China Zibo High-sports Industry Development Zone Education and Sports Center Zibo City China

This paper is mainly the smart home system and some other intelligent devices and robot technology organic integration together, so that it can be more comprehensive for the robot service. At the same time, computer cloud computing technology is also integrated with the API of other third-party cloud computing platforms, so that it has more business capabilities. The goal of computer cloud computing architecture is to improve the computing and storage performance of robots with the help of massive data. The integration of third-party cloud computing services with intelligent hardware technology expands the resources and business functions of robots. By using cloud computing simulation technology, the inconsistency between observer and predictor is corrected, and a new cloud computing predictive control algorithm is designed to effectively suppress complex network attacks. Secondly, the D cloud computing system with predictive control mechanism is modeled, and the state convergence criterion in D cloud computing is established by using Lyapunov stability theory and LMI theory. Through remote operation of mobile terminals, the collaboration between mobile terminals based on cloud computing and third-party clouds is realized.

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PLCD: Policy Learning for Capped Service Mobility Downtime 32

PLCD: Policy Learning for Capped Service Mobility Downtime

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32nd international conference on Computer Communications and Networks, ICCCN 2023

作者： Mwasinga, Lusungu J. Raza, Syed M. Le, Duc-Tai Kim, Moonseong Choo, Hyunseung Sungkyunkwan University Dept. of Computer Science and Engineering Suwon Korea Republic of Sungkyunkwan University Dept. of Electrical and Computer Engineering Suwon Korea Republic of Seoul Theological University Dept. of It Convergence Software Bucheon Korea Republic of

ISBN: (纸本)9798350336184

Service mobility in Multi-access Edge computing (MEC) paradigm is necessary to provide ultra-Reliable Low Latency Communications for the erratically roaming MEC users. It involves relocation of containerized application services to a strategically selected optimal edge host. During relocation, service containers are unavailable (downtime), resulting in the interruption of ongoing user sessions and increased operational expenses for the network operator. Prolonged service downtime degrades perceived quality of experience for users, and this study handles this problem by proposing a downtime-aware Policy Learning based Capped Downtime (PLCD) service mobility strategy. It exploits Deep Actor-Critic prowess for effectively deciding when and where to relocate a containerized application service while taking user mobility and MEC server resource fluctuations into account. Efficacy of the proposed PLCD strategy is confirmed through simulation experiments, and results indicate over 90% average reduction in service downtime comparing to a baseline scheme. © 2023 IEEE.

关键词： Reinforcement learning

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Linking manufacturing acquisition strategies with firm success: evidence from the semiconductor silicon industry

Linking manufacturing acquisition strategies with firm succe...

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international conference on Engineering and technology Management (IEMC)

作者： S.T. Walsh C. McDermott R. Boylan School of Industrial Management New Jersey Institute of Technology Newark NJ USA Lally School of Management Rensselaer Polytechnic Institute RPI Troy NY USA

The purpose of this paper is to describe the different manufacturing acquisition strategies adopted by firms in the semiconductor silicon industry and to highlight potential strengths and weaknesses of these strategies. The industry leaders have followed different approaches for the development of their manufacturing capabilities. Some firms developed new production technology internally, others added "living" technology by acquiring existing firms, or through joint ventures. Other firms improved technological capabilities by adding "static" technology through the purchase of licensees, processes, or equipment. Preliminary evidence suggests that successful firms increased technological capabilities through all three avenues mentioned above. The evidence also suggests a link between the core capabilities perspective on strategy and the technological acquisition strategy utilized by the successful firms.

关键词： Joining processes Semiconductor device manufacture Silicon Manufacturing industries Pulp manufacturing technology management Production international collaboration Personnel Manufacturing processes

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A Kind of Composite Genetic Algorithm Based on Extreme Pre-Judgement

A Kind of Composite Genetic Algorithm Based on Extreme Pre-J...

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international conference on Computer Supported Cooperative Work in Design

作者： Fachao Li Limin Liu Chenxia Jin College of Economics and Management Hebei University of Science and Technology Shijiazhuang China College of Science Hebei University of Science and Technology Shijiazhuang China

ISBN: (纸本)1424409624

In view of the slowness and the locality of convergence for Simple Genetic Algorithm (SGA for short), Composite Genetic Algorithm, as an improved genetic algorithm, is proposed based on extreme pre-judgement. The implementation is also given. The convergence and computing efficiency are analyzed from different aspects by the methods of Markov chain and simulation. All the results indicate that the new type of algorithm possess better convergence with the strategy of reserving the optimal individuals and could avoid efficiently the premature phenomenon. So it will be applied to the optimization problems with large-scale and high-accuracy.

关键词： Genetic algorithms Genetic mutations Large-scale systems Algorithm design and analysis Computational modeling Analytical models convergence Optimization methods Collaborative work Educational institutions

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Computation Offloading with Bus-Mounted Edge Servers Based on Dung Beetle Optimization in Internet of Vehicles 12

Computation Offloading with Bus-Mounted Edge Servers Based o...

引用

12th international conference on Advanced Cloud and Big Data, CBD 2024

作者： Deng, Xia Bao, Yubin Chen, Shuhong Chang, Le School of Computer Science and Cyber Engineering Guangzhou University Guangzhou510006 China School of Automation Guangdong University of Technology Guangzhou510006 China

ISBN: (纸本)9798331511074

In Internet of Vehicles (IoV), edge computing alleviates congestion in the backbone network and significantly reduces the delay by deploying servers close to users. However, the existing fixed-site and fixed-capacity edge server deployment cannot effectively cope with the spatiotemporal dynamics of IoV end users, i.e., vehicles on road. Therefore, this paper proposes leveraging the inherent mobility of public buses to carry edge servers, and cooperate with fixed-site edge servers to provision elastic joint task offloading service for 1oV end users. We first build a multi-objective optimization model with fixed-site and bus-mounted servers to minimize the user delay, energy consumption, and payment cost. Then, a computation offloading strategy based on the Dung Beetle optimization algorithm is proposed. Taking into account the varying tolerance for delay among different tasks, a preprocessing method is adopted to set the offloading ratio for each task, thereby reducing the search space and accelerating the convergence speed. Furthermore, the maximum acceptable delay constraint is transformed into an unconstrained problem through the penalty function method. Experimental results verify that the proposed computation offloading algorithm outperforms various classical intelligent optimization algorithms in terms of the overall cost. © 2024 IEEE.

关键词： Computation offloading

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Performance of a multi-frontal parallel direct solver for hp-finite element method

Performance of a multi-frontal parallel direct solver for hp...

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IASTED international conference on Advances in Computer Science and Engineering, ACSE 2009

作者： Paszyński, Maciej Pardo, David Torres-Verdín, Carlos Department of Computer Science AGH University of Science and Technology Kraków Poland Basque Center for Applied Mathematics Bilbao Spain Department of Petroleum and Geosystems Engineering University of Texas Austin TX United States

ISBN: (纸本)9780889867901

In this paper we present the performance of our parallel multi-frontal direct solver when applied to solve linear systems of equations resulting from discretizations of a hp Finite Element Method (hp-FEM). The hp-FEM generates a sequence of computational meshes delivering exponential convergence of the numerical error with respect to the mesh size (number of degrees of freedom). A sequence of meshes is obtained by performing several hp refinements starting from an arbitrary initial mesh. The solver constructs initial elimination tree for an arbitrary initial mesh, and expands the elimination tree each time the mesh is refined. The solver has been tested on 3D Direct Current (DC) borehole resistivity measurement simulations problems. We compare the solver with two versions of the MUMPS parallel solver: with (1) distributed entries executed over the entire problem, and (2) the direct sub-structuring method with parallel MUMPS solver utilized to solve the interface problem. We show that by providing to the solver the knowledge about the structure of the hp-FEM, the order of elimination is obtained straightforward, and leads to a better performance than by submitting the entire matrix to the solver and executing a connectivity graph based ordering algorithm.

关键词： Finite element method

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