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Cryptography And Information Security (VCRIS), International Conference On

作者： Phuc-Phan Duong Ba-Anh Dao Thai-Ha Tran Trong-Hung Nguyen Trong-Thuc Hoang Cong-Kha Pham University of Electro-Communications (UEC) Tokyo Japan Academy of Cryptography Techniques Hanoi Vietnam

ISBN: (数字)9798331529949

ISBN: (纸本)9798331529956

The Internet of Things (IoT) relies on resourcelimited devices that require efficient cryptographic solutions for security. In block ciphers, S-Boxes play the most crucial role as they are the only nonlinear component. Designing efficient S-Boxes for IoT devices is essential. In this paper, chaotic maps have been applied to create 4x4 S-Boxes that are optimized for resource efficiency, requiring very few logic gates for implementation. Additionally, the cryptanalysis results demonstrate that these S-Boxes meet other main criteria such as nonlinearity (NL), Differential approximation Probability (DP), Linear approximation Probability (LP), Strict Avalanche Criterion (SAC), and Bit Independence Criterion (BIC) when compared to alternative S-Boxes. The proposed S-Boxes can be used as replacements in existing algorithms that use 4x4 S-Boxes or in the development of new algorithms.

关键词： Ciphers Linear approximation Information security Logic gates approximation algorithms Hardware Internet of Things Optimization S Box

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Research on Motion Control Model of Siemens PMC System for Industrial Automation

Research on Motion Control Model of Siemens PMC System for I...

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Electrical, Automation and Computer Engineering (ICEACE), International Conference on

作者： Xianjun Song Zhiqiang Zhang Jin Liu Xincai Chang CGN Digital Technology Co. Ltd. Beijing China

ISBN: (数字)9798350368208

ISBN: (纸本)9798350368215

The application of the Siemens PMC system in industrial automation is explored, with a focus on the design and enhancement of a motion control model utilizing the sliding mode control algorithm. The Siemens PMC system, a crucial automation solution, comprises multiple layers, including hardware modules, software control systems, and communication networks. The hardware components primarily handle data acquisition and the execution of control commands, while the software control system processes and analyzes the acquired data through sophisticated algorithms to achieve precise motion control. A motion control model based on the sliding mode control algorithm is subsequently developed, and its efficacy and performance improvements are validated through simulation. Experimental findings demonstrate that, compared to conventional control methods, the sliding mode control algorithm offers notable advantages in terms of system stability and precision. Specifically, motion control errors are reduced by approximately 11.8%, the system’s response time is decreased by 13.7%, and the system’s resistance to external disturbances is significantly enhanced, leading to improved overall stability. Detailed data analysis reveals that the sliding mode control algorithm not only enhances the dynamic performance of the system but also contributes to reductions in energy consumption and operational costs.

关键词： Motion planning Automation Heuristic algorithms Software algorithms Dynamics approximation algorithms Stability analysis Software Hardware Sliding mode control

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PrompTCC: Transactional Causally Consistent Reads Can Be Fast and Fresh

PrompTCC: Transactional Causally Consistent Reads Can Be Fas...

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Pacific Rim International Symposium on Dependable Computing

作者： Taras Lykhenko Rafael Soares Luís Rodrigues INESC-ID Instituto Superior Técnico Universidade de Lisboa Portugal

ISBN: (数字)9798331540746

ISBN: (纸本)9798331540753

Transactional Causal Consistency (TCC) is the strongest consistency model compatible with availability and, therefore, it avoids the pitfalls of the CAP theorem while simplifying the programming of cloud applications. Unfortunately, with previous implementations, TCC came at the cost of expensive reads. TCC has been implemented either using conservative approaches, that always require two communication rounds, or using optimistic approaches that, in good cases, require just one round, but in face of skewed workloads, that are common in real applications, can require three communication rounds. In this paper we propose a novel algorithm, named PrompTCC, that in most cases offers reads in just one round and that, even in face of skewed workloads, never takes more than two rounds. As a result, PrompTCC is able to closely approximate the performance of an eventually consistent system while providing stronger guarantees, achieving only 12% throughput and 20% latency penalty in realistic scenarios, outperforming state-of-the-art systems which present up to 37% and 60% throughput and latency degradation respectively.

关键词： Degradation Protocols Costs Programming Throughput approximation algorithms Vectors Faces Clocks

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Approximate state estimation with large-scale sensor networks under event-based sensor scheduling strategy

Approximate state estimation with large-scale sensor network...

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IEEE Conference on Decision and Control

作者： Xinhui Liu Meiqi Cheng Dawei Shi Ling Shi MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we investigate the issues of real-time sensor scheduling and state estimator design within large-scale sensor network systems. Specifically, data redundancy sometimes occurs in large-scale sensor arrays due to the excessive proximity of sensing units in the spatial domain, leading to high similarity in their measurement data. Currently, it is difficult to account for such redundancy in sensor scheduling algorithms found in existing literature, where the optimal subset of sensors is generally selected by optimizing objective functions formulated from certain performance criteria. To tackle this problem, we introduce an event-based sensor scheduling strategy, the triggering condition of which is designed founded on the similarity of sensor data, so as to identify the most informative subset of sensors for state estimation. To evaluate the impact of the sensor scheduling protocol on system observability, we propose a new notion of $\mathscr{E}(\varepsilon)$-observability, based on which an observability criterion is derived. In addition, we have designed a set-valued state estimation algorithm, which takes into account the intricate measurement information structure inherent within the sensor selection mechanism. The performance enhancement of the proposed estimator is also investigated. Finally, numerical experiments are conducted to validate the effectiveness of the proposed estimation algorithm and to verify the performance improvement.

关键词： Protocols Event detection Scheduling algorithms Redundancy approximation algorithms Real-time systems Sensors State estimation Observability Sensor arrays

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Personalized Course Selection Optimization Using QAOA

Personalized Course Selection Optimization Using QAOA

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Takeru Ota Keisuke Fukada Tatsuhiko Shirai Nozomu Togawa Dept. of Computer Science and Communications Engineering Waseda Univ. Waseda Institute for Adcanced Study Quanmatic Inc.

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Quantum approximate optimization algorithm (QAOA) is an algorithm for solving combinatorial optimization problems (COP), which can be implemented on gate based quantum computers. However, many practical COPs such as a personalized course selection problem (PCSP) have not been solved by QAOA yet. In this paper, we solve a PCSP using QAOA by transforming the problem into a quadratic unconstrained binary optimization (QUBO), and investigate the solution properties when the weight of the problem's constraint is changed. Experimental evaluations demonstrate that tuning the weight value improves the probability of obtaining optimal solutions and reduces the energy expectation value averaged over the obtained feasible solutions.

关键词： Computers Quantum computing Logic gates approximation algorithms Optimization Tuning Consumer electronics

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GarmentFolding:Learning Efficient Garment Folding Based on Lift&Drag Dynamic Action

GarmentFolding:Learning Efficient Garment Folding Based on L...

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IEEE Symposium on Product Compliance Engineering - Asia (ISPCE-CN)

作者： Ruhan He Jie Lu Lianqing Yu School of Computer Science and Artificial Intelligence Wuhan Textile University WuHan China School of Mechanical Engineering and Automation Wuhan Textile University WuHan China

ISBN: (数字)9798331523008

ISBN: (纸本)9798331523015

In robotic arm manipulation, folding clothes is highly challenging due to the garments' inherent infinite degrees of freedom. Our designed system can unfold garments from any configuration and automatically center them in the workspace during folding, thereby minimizing constraints on the robotic arm's motion range. High-quality garment unfolding significantly enhances folding efficiency. Therefore, this study introduces a novel action strategy, “Lift&Drag,” which involves high-speed dynamic actions to adjust garments from any state to a prede-fined configuration, ensuring superior unfolding. To bridge the simulation-reality gap and improve fabric keypoint detection ac-curacy, we collected extensive real-world fabric images, creating a dataset of approximately 2,000 images. This dataset notably enhances the performance of fabric folding keypoint detection. Experimental results show that the method reliably performs in real-world settings, achieving 91.3 % unfolding coverage and a 92.8 % folding success rate, particularly with heavily wrinkled t-shirts.

关键词： Bridges Accuracy Clothing Dynamics Asia Manipulators approximation algorithms Fabrics Reliability

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A Note On Deterministic Submodular Maximization With Bounded Curvature

arXiv

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arXiv 2024年

作者： Li, Wenxin The Ohio State University United States

We show that the recent breakthrough result of Buchbinder and Feldman [1] could further lead to a deterministic (1 − κf/e − Ε)-approximate algorithm for maximizing a submodular function with curvature κf under matroid constraint. A set function f: 2E → R+ defined on ground E of size n is submodular, if inequality f(S)+f(T) ≥ f(S ∪ T) + f(S ∩ T) holds for any two subsets S,T ⊆ E. One of the important concepts that influences the performance and analysis of algorithms for monotone submodular maximization is curvature [4]. The curvature of a submodular function measures how far the function deviates from being modular (i.e., linear), and it plays a crucial role in determining the approximation guarantees of various algorithms. Sviridenko et al. [7] presented two optimal algorithms achieving an approximation ratio of (1 − κf/e − Ε), by optimizing the sum of a submodular and a linear function. Several studies [2, 3, 6] have focused on the development and analysis of deterministic algorithms for submodular maximization, offering provable guarantees and practical effectiveness. Recently, Buchbinder and Feldman [1] achieved a significant breakthrough by introducing the first deterministic algorithm with an optimal approximation ratio for submodular function maximization under matroid constraint. We demonstrate that if (approximate) local maxima are used as solutions in the non-oblivious local search, the algorithm also achieve an optimal approximation ratio for submodular functions with bounded curvature. The main result is stated in the following theorem. It is important to emphasize that this result is attributed to [1], and is also inspired by the work presented in [7]. Most of our notations are aligned with that of [1], our goal here is to point out this fact. Copyright © 2024, The Authors. All rights reserved.

关键词： approximation algorithms

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Learning-Enabled Optimization for Security-Constrained Unit Commitment with Energy Storage

Learning-Enabled Optimization for Security-Constrained Unit ...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Weimao Xu Junru Lin Xuebing Sheng Ou Zhang Xue Jiang Xiao Wang Economic Research Institute State Grid Liaoning Electric Power Company Limited Shenyang China School of Automation Wuhan University of Technology Wuhan China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

Fast and intelligent scheduling is essential for the safe and stable operation of modern renewable energy power systems. To address the complex Security-Constrained Unit Commitment (SCUC) problem, this paper introduces a rapid solution algorithm based on the learning-enabled optimization. Using the SCUC model that incorporates energy storage, we integrate machine learning techniques within a mixed-integer programming framework, proposing a "prediction + decision" approach. Turing statistics are employed to build a confidence-based training set, and a multi-layer neural network classifier is used to predict logical strategies in real time, enabling fast online decisions. Simulation results on the IEEE 9-bus system demonstrate that this method outperforms traditional solvers and other data-driven algorithms in terms of speed, success rate, and optimal value. The learning-enabled decision-making algorithm provides high-quality approximate solutions, improving decision-making speed by more than an order of magnitude.

关键词： Training Machine learning algorithms Simulation Decision making Machine learning Prediction algorithms approximation algorithms Classification algorithms Optimization Energy storage

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Steel Surface Defect Detection Based on Improved YOLOv7

Steel Surface Defect Detection Based on Improved YOLOv7

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Computer, Control and Robotics (ICCCR), International Conference on

作者： Ming Li Lisheng Wei Bowen Zheng School of Electrical Engineering Anhui Polytechnic University Wuhu China Anhui Key Laboratory of Electric Drive and Control Wuhu China

ISBN: (数字)9798350373141

ISBN: (纸本)9798350373158

Aiming at the current problem of steel surface defect detection with low accuracy and slow speed, which can easily lead to misdetection and omission, an algorithm for steel surface defect detection based on improved YOLOv7 is proposed. Firstly, the GAM (Global Attention Mechanism) attention mechanism is introduced, while CNeB and C3C2 are added to improve the feature extraction ability of the model by reducing the information approximation and amplifying the global interaction representation. Secondly, the WIoU (Wise-IoU) loss function is used to improve the convergence speed at the late stage of model training. Finally, the improved YOLOv7 is compared with other models. The experimental results show that the algorithm of this paper has an average detection accuracy (mAP) of 72.9% on the NEU-DET dataset, which is 4.1% higher compared with the original YOLOv7 algorithm, and the detection time is reduced by 63.6% under the same conditions, which verifies the effectiveness and feasibility of this paper's algorithm, and it has a certain value of application in industrial applications.

关键词： Training Accuracy Attention mechanisms Optimization methods Feature extraction approximation algorithms Steel

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Toward UAV-Enabled Stereoscopic UL Heavy NOMA: Joint Resource Allocation and 3D Trajectory Design

Toward UAV-Enabled Stereoscopic UL Heavy NOMA: Joint Resourc...

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IEEE International Conference on Communications (ICC)

作者： Haiyong Zeng Rui Zhang Xu Zhu Yufei Jiang Zhongxiang Wei Fu-Chun Zheng Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips School of Electronic and Information Engineering Guangxi Normal University China School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen China College of Electronic and Information Engineering Tongji University Shanghai China

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

We study an unmanned aerial vehicle (UAV)-enabled uplink heavy non-orthogonal multiple access (NOMA) system in this paper, where the UL communication becomes extremely important in some hot spot areas such as live concerts or soccer stadiums, and investigate the joint optimization of bandwidth assignment (BA) and power allocation (PA) with UAV three-dimensional (3D) trajectory design to maximize the minimum average rate among all ground users, while meeting their heterogeneous rate requirements. More specifically, we propose a joint BA and PA algorithm by revealing that the inter-user interference in each NOMA group can be eliminated naturally while deriving the sum rate of users. The algorithm is proposed to get the optimal BA and PA solutions with the help of closed-form results and ellipsoid method. After that, in order to solve the UAV 3D trajectory design problem we introduce the elevation angle as a supplementary variable, and the successive convex approximation method is adopted to obtain the UAV 3D trajectory. The joint BA and PA algorithm and the UAV 3D trajectory design can be optimized alternatively, which leads to fast convergence and demonstrates a superior minimum average rate among users and user fairness performance over the previous methods.

关键词： NOMA Three-dimensional displays Stereo image processing Autonomous aerial vehicles approximation algorithms Trajectory Resource management

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