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Digital Learning Ecosystem: Online Concept for engineering Education 65

Digital Learning Ecosystem: Online Concept for Engineering E...

引用

65th IEEE Annual International Scientific Conference on Power and Electrical engineering of Riga Technical University, RTUCON 2024

作者： Zabasta, Anatolijs Kazymyr, Volodymyr Kunicina, Nadezhda Velihorskyi, Oleksandr Riga Technical University Faculty of Computer Science Information Technology and Energy Riga Latvia Chernihiv Polytechnic National University Information and Computer Systems Department Chernihiv Ukraine Chernihiv Polytechnic National University Radio Engineering and Embedded Systems Department Chernihiv Ukraine

ISBN: (纸本)9798350365771

This article examines the development of a Digital Learning Ecosystem (DLE) for engineering education, supported by online learning, within the framework of Erasmus+ international educational projects. We hypothesize that a DLE can address the challenges posed by rapid technological changes associated with Industry 4.0 and digital transformation, thus transforming engineering education to meet modern industry needs. Building on the earlier Erasmus+ CybPhys project, which established a Sharing Modelling and Simulation Environment (SMSE) for digitalizing online technical courses, the DIGITRANS project aims to enhance this architecture to include remote laboratories through the Sharing Remote Experiment Environment (SREE) platform. The project involves acquiring hardware and open-source software for SREE and establishing two physical remote laboratories. A study conducted in spring 2023, using the technology Acceptance Model framework, indicated positive student perceptions of SMSE, with students believing it would enhance learning outcomes and expressing intentions to use the platform frequently. The efficacy of the DLE in addressing technological advancement challenges will be further evaluated through post-ante assessments and feedback from prospective employers and stakeholders, focusing on the implementation of industry recommendations and the correlation between pre- and post-implementation survey responses from industry and academic experts. © 2024 IEEE.

关键词： Open source software

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Pursuit-Evasion Game of Multiple Unmannd Surface Vessels in Partially Observable Environments

Pursuit-Evasion Game of Multiple Unmannd Surface Vessels in ...

引用

2023 China Automation Congress, CAC 2023

作者： Zhuang, Yufei Qu, Delin Yao, Yiyi Huang, Haibin Wang, Runan Duan, Lianqi School of Information Science and Engineering Harbin Institute of Technology Weihai China Key Laboratory of Cross-Domain Synergy and Comprehensive Support for Unmanned Marine Systems Ministry of Industry and Information Technology Weihai China School of Astronautics Harbin Institute of Technology Harbin China School of Information Science and Engineering Harbin Institute of Technology Weihai Weihai China

ISBN: (纸本)9798350303759

The pursuit-evasion game for unmanned surface vessels (USVs) is a topic of great interest in the field of ocean engineering. Most of the previous studies only focused on ideal scenarios with fully observable environments, which are beyond the practical applications. In this paper, we present a reinforcement learning (RL) model for the real marine environment including signal shielding regions, depots, and obstacles. Suppose in the signal shielding regions, the vessels' position information is unknown to each other except for the leader pursuer, and the new environment model is partially observable to ordinary USVs. Then, a distributed multi-agent RL algorithm is proposed and a leader-follower implicit communication mechanism to train the pursuer's strategy is introduced. Weighting the distance, number of captures, and other relevant parameters, a new reward function of the pursuit-evasion game is designed to optimize the pursuit strategy continuously. As shown in the simulation results, the ordinary pursuers can predict the movement direction and capture points of the evader with high accuracy, even when it is in the signal shielding area. This is due to the implicit communication with the leader pursuer in the partially observable environment, which can also effectively optimize the pursuit strategy in the new environment. © 2023 IEEE.

关键词： Reinforcement learning

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Successful Integration of IoT and Blockchain Technologies Using Several Machine Learning Algorithms 5

Successful Integration of IoT and Blockchain Technologies Us...

引用

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

作者： Calarany, C. Indumathy, M. Senthilraja, P. Suganya, D. Gopi Vardhan, V. Rahul, Yelisetty Shanmukh Tagore Government Arts and Science College Department of Computer Science Puducherry India Rajiv Gandhi College of Engineering & Technology Department of Information Technology Kirumampakkam India K.S.Rangasamy College of Technology Department of Computer Science Tamil Nadu India Rajiv Gandhi College of Engineering & Technology Department of Computer Science Kirumampakkam India Data Science and Business Systems Srm Institute of Science and Technology Kattankulathur India

ISBN: (纸本)9798350383522

Internet of Things (IoT) produces massive amounts of data that need to be processed and saved securely. The strong features of Blockchain makes it as a best candidate for storing the data received from IoT sensors. However, there is a need of concern to take care of the challenges associated with both IoT and blockchain paradigms. Firstly, the enormous amount of data should be effortlessly handled by Blockchain network, without adding much complexity. Secondly, the heterogeneous nature of data that are received from various IoT Sensors should be stored within the blockchain. In this paper, a conceptual framework based on Multimodal Machine Learning (MML) algorithm is proposed as an interface between the IoT sensors and Blockchain networks. The MML algorithm is used to understand the different modalities of the data and provides a way to manage the heterogeneity in that data. The MML algorithms provides an intelligent data processing that allows for real-time data storage in the blockchain networks. The conceptual frame assumes that audio, video, and text are the three types of data as received from IoT. These inputs are processed in simplistic Recurrent neural network RNN that acts as MML and then passed to Blockchain networks for secure storage. Simulation of the above said conceptual framework is performed assuming all other relevant requirements of IoT, MML and Blockchain are taken into account with default parameters and values. The results obtained provide a promising note for future scope in this direction. © 2024 IEEE.

关键词： IoT MML RNN

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An Efficient Detection and Classification of Plant Diseases using Deep Learning Approach

An Efficient Detection and Classification of Plant Diseases ...

引用

2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Jagadeesan, S. Deepakraj, E. Ramalingam, Venkadeshan Venkatachalam, Ilayaraja Vivekanandan, Manojkumar Manjula, R. Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India University of Technology and Applied Sciences - Shinas Branch Information Technology Department Oman Vellore Institute of Technology School of Computer Science and Engineeing Vellore India School of Engineering and Applied Sciences Srm University-AP Department of Computer Science & Engineering Andhra Pradesh Amaravati India Srm Institute of Science and Technology College of Engineering and Technology Department of Computing Technology Kattankulathur India

ISBN: (纸本)9798350313413

Crop failure caused by disease-causing pests is an important problem. Farmers struggle with disease management and detection due to inadequate interventions. The goal is to create an automatic system to efficiently identify plant diseases from photos while reducing crop losses and increasing productivity. Machine learning algorithms offer a faster and cheaper alternative to visual inspection by experts. The main goal is to perform image analysis for early diagnosis and effective disease control. The use of CNN architecture for plant disease classification and detection offers a promising solution for plant health monitoring and risk mitigation. Given the threats to crop productivity and global food security, reliable methods for early detection and accurate classification are essential. CNNs enable efficient analysis of vast plant image databases, enabling accurate plant disease identification with speed and accuracy. The multi-layer CNN approach extracts feature and refines the representation, facilitating accurate prediction and accurate diagnosis. Transfer learning methods accelerate system development and allow adaptation to plant disease-specific databases. Combining computer vision algorithms with CNN architecture enables real-time monitoring, early disease detection and targeted intervention, reducing yield losses and improving crop management. This approach uses AI, image analysis, and plant pathology to solve the challenges of sustainable agriculture and plant diseases. System performance is measured by various performance metrics. © 2023 IEEE.

关键词： CNN-Based Approach Error Rate Plant disease Precision ROC

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A Simplified Method for Optimising Geometrically Shaped Constellations of Higher Dimensionality 49

A Simplified Method for Optimising Geometrically Shaped Cons...

引用

49th European Conference on Optical Communications, ECOC 2023

作者： Gumus, Kadir Chen, Bin Bradley, Thomas Okonkwo, Chigo High-Capacity Optical Lab Eindhoven University of Technology Netherlands School of Computer Science and Information Engineering Hefei University of Technology China

We introduce a simplified method for calculating the loss function for use in geometric shaping, allowing for the optimisation of high dimensional constellations. We design constellations up to 12D with 4096 points, w... 详细信息

ISBN: (纸本)9781839539954

关键词： Geometry

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Seastar: A Cache-Efficient and Load-Balanced Key-Value Store on Disaggregated Memory

Seastar: A Cache-Efficient and Load-Balanced Key-Value Store...

引用

2024 IEEE International Conference on Cluster Computing, CLUSTER 2024

作者： Du, Jingwen Wang, Fang Feng, Dan Zeng, Dexin Yi, Sheng Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System China School of Computer Science and Technology Huazhong University of Science and Technology China Shenzhen Huazhong University of Science and Technology Research Institute China

ISBN: (纸本)9798350358711

In modern datacenters, memory disaggregation un-packs monolithic servers to build independent network-connected compute and memory pools, greatly improving resource uti-lization. Existing memory-disaggregated key-value stores adopt ownership sharing or ownership partitioning for request scheduling and they all show poor performance and scalability. The former generates multiple cache misses and multiple network round trips due to poor cache locality, while the latter fails to fully use resources on all Compute Nodes (CNs) due to load imbalance. In this paper, we propose Seastar, a fast and scalable key-value store that achieves high cache locality as well as load balancing. To enable high concurrency and ensure linearizability, Seastar exploits a self-verification version chain to provide out-of-place atomic updates and ensure consistent reads. To improve cache locality, Seastar leverages a pair-based ownership assigning scheme to assign the processing permission of requests corre-sponding to each key to a CN pair through two independent hash functions. To ensure load balancing among CNs, Seastar proposes a decentralized power-of-two-choices routing scheme to route the requests to the less-loaded CNs in CN pairs for handling. Experimental results demonstrate that Seastar improves the throughput by up to 6.7x and significantly reduces the latency compared with state-of-the-art memory-disaggregated key-value stores. © 2024 IEEE.

关键词： Scalability

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COI Oriented Evaluation Method of Multi-domain Operation Demand Satisfaction of Equipment System of systems 10th

COI Oriented Evaluation Method of Multi-domain Operation Dem...

引用

10th China Conference on Command and Control, C2 2022

作者： Wu, Saisai Hu, Tao Liu, Junjie Liu, Junxian Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789811960512

The current battlefield environment is no longer a single key operational area. In order to evaluate the requirement satisfaction of the existing equipment system of systems (SoS) in complex multi-domain operations (MDO), starting with the critical operational issues and considering the actual operational requirements, the operational task model related to the equipment SoS is established, the complex multi domain operational tasks are decomposed into multiple indexes that can be analyzed quantitatively, and a measurement SoS including basic measurement and derived measurement is established by using the measurement information model for reference, The specific flow of the evaluation method of operational demand satisfaction is given, and the evaluation level of equipment SoS is determined. Finally, taking the joint air defense and anti missile (JADAM) operational test as an example, the equipment SoS is analyzed and evaluated to verify the rationality and effectiveness of this method. © 2022, Chinese Institute of Command and Control.

关键词： System of systems

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MIMO Radar Waveform Design for Transmit Beamforming via an Mainifold Optimization Idea 6

MIMO Radar Waveform Design for Transmit Beamforming via an M...

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6th International Conference on information Communication and Signal Processing, ICICSP 2023

作者： Zhao, Zhongqing Tong, Fangqiu Sun, Ping Feng, Xiang Liu, Shuai Zhao, Zhanfeng Zhang, Tingting School of Information Science and Engineering Harbin Institute of Technology Weihai China Shanghai Aerospace Systems Engineering Institute Project Number One Department Shanghai China

ISBN: (纸本)9798350339994

In this paper, we try to design constant modulus waveform for ideal transmit beamforming in MIMO radar. By taking advantage of the novel manifold frame, we first transform the problem into an unconstrained optimization problem within Riemannian space. Furthermore, to effectively solve this problem, we formulate an iterative closed-form ADMM algorithm combined with an accelerated Manifold-ADMM to enhance efficiency. Therein, compared with traditional Nonlinear-ADMM algorithm, the accelerated Manifold-ADMM algorithm could achieve better beampattern performance. Finally, simulations and experiments show that our method can effectively optimize the transmit pattern under the constant modulus constraint, which would provide a new way for waveform design. © 2023 IEEE.

关键词： ADMM algorithm Constant modulus constraint Riemannian manifold Waveform design

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Construction Method of Resilience Killing Chain Based on Two-Layer Optimization Model 1

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10th China Conference on Command and Control, C2 2022

作者： Zhang, Lu Zhu, Xianqiang Xiao, Kaiming Zhang, Weiming Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha410073 China

ISBN: (数字)9789811960529

ISBN: (纸本)9789811960512

Killing-chain is the core mode of energy accumulation and release of the system. Under the concept of multi domain cooperative operation, the structure mode of killing-chain has been converted from one-way superposition and series chain structure to complex and multi-dimensional network structure. In order to efficiently plan the killing-chain, it is necessary to optimize the combination mode of killing chain based on two-layer optimization. Firstly, a networked description method of combat network is introduced based on heterogeneous network model. Secondly, the optimization model is established based on the two-layer optimization method, and two novel evaluation metrics: effectiveness index and robustness index, are proposed. Finally, we compare the proposed optimization model with the stochastic optimization method through a simulation case study and verify the superiority of the two-layer optimization model. © 2022, Chinese Institute of Command and Control.

关键词： Optimization

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Evaluation Method of Multi-domain System information Sharing Capability 10th

Evaluation Method of Multi-domain System Information Sharing...

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10th China Conference on Command and Control, C2 2022

作者： Liu, Junjie Wu, Saisai Hu, Tao Liu, Junxian Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789811960512

In order to solve the problem of information sharing capability assessment of multi-domain battle command system, this paper studies the relevant theories of information quality, and proposes a multi-domain command system information sharing capability assessment method based on information exchange model. The method fully combines the command and control characteristics of multi-domain operations and evaluates the information sharing capability of the multi-domain command system from between and within the battle domain, so as to analyze the information sharing status of the multi-domain command system, which is of high value for assessing the overall effectiveness of the multi-domain battle command system. © 2022, Chinese Institute of Command and Control.

关键词： information analysis

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