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Path Planning of Randomly Scattering Waypoints for Wafer Probing Based on Deep Attention Mechanism

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2023年第1期53卷 529-541页

作者： Shi, Haobin Li, Jingchen Liang, Meng Hwang, Maxwell Hwang, Kao-Shing Hsu, Yun-Yu Northwestern Polytech Univ Sch Comp Sci Xian 710072 Peoples R China Zhejiang Univ Sch Med Hangzhou 310000 Peoples R China Natl Sun Yat Sen Univ Dept Elect Engn Kaohsiung 80424 Taiwan

Wafer probing is a critical process employed to measure the yield of wafer fabrication. The primary object of wafer probing is to find the defect grain on the wafer. After a full coverage check, there are always some suspected grains existing for further inspection. However, this second probing result could be affected by the shape of the probe card and the setting actions (path planning) of operators for grains randomly scattering on the wafer. Good grains can be damaged by reprobe actions, which decrease production performance and customer trust. In general, it also requires manpower to perform reprobing, which dramatically deteriorates the throughput of production. This article has studied this problem, and an adaptive coverage path planning (CPP) method for randomly scattering grains using an attention interface is proposed. The proposed randomly scattering waypoints method uses deep reinforcement learning (DRL) for automatic real-time path planning of the second detection. A soft attention interface accelerates the process with a less overlapped check. The experimental results demonstrate the efficiency of the proposed method in terms of less overlapping and steps, and this method learns a better CPP strategy for wafer probing than programmed paths and other RL-based methods.

关键词： Path planning Artificial neural networks Testing Semiconductor device modeling Probes approximation algorithms Task analysis Attention mechanism (AM) coverage path planning (CPP) deep reinforcement learning (DRL) wafer probing

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A Multi-Market Trading Framework for Low-Latency Service Provision at the Edge of Networks

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IEEE TRANSACTIONS ON SERVICES COMPUTING 2023年第1期16卷 27-39页

作者： Shih, Yuan-Yao Pang, Ai-Chun He, Tian Chiu, Te-Chuan Natl Chung Cheng Univ Dept Commun Engn Chiayi 62102 Taiwan Natl Taiwan Univ Grad Inst Networking & Multimedia Taipei 10617 Taiwan Natl Taiwan Univ Dept Comp Sci & Informat Engn Taipei 10617 Taiwan Univ Minnesota Dept Comp Sci & Engn Minneapolis MN 55455 USA Acad Sin Res Ctr Informat Technol Innovat CITI Taipei 115024 Taiwan

Along with the Ultra-Reliable and Low-Latency Communications (URLLC) of 5G, edge computing enables many potential low-latency IoT applications and has recently gained widespread attention. Addressing edge computing's economic issues is critical as we need to motivate edge devices as resource providers to devote their computing resources to the service. There are multiple users and resource providers in most edge computing service scenarios. The communication delays between users and providers are not the same since their physical distances are different. However, most existing works on edge computing regarding network economics adopt single market models that do not consider the influence of communication delay. Some researchers advocate using multi-market models to overcome this issue by grouping users who connect to the same access point or base station and letting each host its auction for resource trading. However, due to the high cost of deploying 5G ultra-dense small cells, barely a network operator can reach full network coverage. Users cannot rely on a single network, but these models do not allow resource trading between different groups. Thus, this article proposes a novel multi-market trading (MMT) framework to address these shortcomings. The framework combines the double auction at each group and a market selection game to enable the resource providers to participate in multiple auctions and analyze their choice of markets. We present the framework's detailed design and propose a theory-based learning algorithm to approximate each provider's optimal strategies. Through extensive simulations using real-world datasets of vehicular networks, we show that the proposed framework can improve the social welfare by $14.45\%$14.45% and $36.74\%$36.74%, respectively, compared with classic multi-market and single market models.

关键词： Performance evaluation 5G mobile communication Computational modeling Biological system modeling Games Ultra reliable low latency communication approximation algorithms Double auction edge computing multi-market fictitious play

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The High-frequency Phenomenon of Copper Clad Aluminum Wires which are Lower the Alternating Current Resistance than Copper Solid Wires, and the Application of Copper Clad Aluminum Wires to the Electrical Equipment

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IEEJ Transactions on Power and Energy 2023年第3期143卷 194-206页

作者： Ueda, Katsuhiko Hung, Chefen UEDA Lb 4-27 Minami Hongo-cho Numazu410-0815 Japan TAYA Electric Wire & Cable No249 Sec.2. Chung Shan Rd. Kuan Miao Hsiang Tainan71847 Taiwan

The paper is proposed approximate formulas of the ac resistance of lead wires and coils which made by using copper clad aluminum (CCA) wires. There are the frequency range that the ac resistance of CCA wires is lower than it of cupper solid wires for lead wires and coils of an electrical equipment. It is shown that the application of CCA wires is economical as comparing with copper solid wires, if the design is due to successful calculation in the electrical equipment. The measured resistance is compared with the formula. CCA wires is an example of multiple conductors which shall be expected to apply in future. © 2023 The Institute of Electrical Engineers of Japan.

关键词： approximation algorithms

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Inserting Multiple Edges into a Planar Graph

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Journal of Graph algorithms and Applications 2023年第6期27卷 489-522页

作者： Chimani, Markus Hliněný, Petr Theoretical Computer Science University Osnabrück Germany Faculty of Informatics Masaryk University Brno Czech Republic

Let G be a connected planar (but not yet embedded) graph and F a set of edges with ends in V (G) and not belonging to E(G). The multiple edge insertion problem (MEI) asks for a drawing of G + F with the minimum number of pairwise edge crossings, such that the subdrawing of G is plane. A solution to this problem is known to approximate the crossing number of the graph G + F, but unfortunately, finding an exact solution to MEI is NP-hard for general F . The MEI problem is linear-time solvable for the special case of |F | = 1 (SODA 01 and Algorithmica), and there is a polynomial-time solvable extension in which all edges of F are incident to a common vertex which is newly introduced into G (SODA 09). The complexity for general F but with constant k = |F | was open, but algorithms both with relative and absolute approximation guarantees have been presented (SODA 11, ICALP 11 and JoCO). We present a fixed-parameter algorithm for the MEI problem in the case that G is biconnected, which is extended to also cover the case of connected G with cut vertices of bounded degree. These are the first exact algorithms for the general MEI problem, and they run in time O(|V (G)|) for any constant k. © 2023, Brown University. All rights reserved.

关键词： approximation algorithms

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Brief Announcement: Towards Proportionate Fair Assignment 26th

Brief Announcement: Towards Proportionate Fair Assignment

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26th International Symposium on Stabilization, Safety, and Security of Distributed Systems

作者： Schieber, Baruch New Jersey Inst Technol Newark NJ 07102 USA

ISBN: (纸本)9783031744976;9783031744983

The well known assignment problem finds an optimal assignment of tasks to agents. Optimal assignment is applicable to the placement of virtual machines in cloud systems to optimize resource allocation and ensure efficient operation. It is also applicable to fault-tolerant computation to ensure continued operation in case of component failures. In some instances the assignment needs to satisfy extraneous fairness constraints. For example, in a multi-tenant cloud environment the assignment has to guarantee equitable treatment of customers. We initiate the study of proportionate fair assignment. In the multi-tenant setting such an assignment ensures proportionate representation of the customers over all servers. We show that even the simple case of computing an assignment that ensures equal representation of two customers is hard. On the positive side, we present a 1/2-approximation algorithm for computing an assignment that ensures equal representation of two customers.

关键词： Assignment Perfect matching Proportionate fairness Cloud system approximation algorithms

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Mixed-integer simulation optimization for multi-echelon inventory problems with lost sales

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Journal of the Operational Research Society 2023年第11期74卷 2312-2326页

作者： Tsai, Shing Chih Wang, Honggang Hung, Li Hsuan National Cheng Kung University Tainan City Taiwan California State Polytechnic University-Pomona PomonaCA United States

We propose a mixed-integer simulation optimization framework for solving multi-echelon inventory problems with lost sales. We want to seek optimal settings of the order-up-to levels and the review intervals for warehouse and retailers. The aim is to minimize the total expected costs including the inventory holding cost, the ordering cost and the penalty cost. The proposed optimization method represents a complementary combination of ranking-and-selection procedures and stochastic-approximation algorithms for both integer-valued and real-valued variables. We provide a proof for the finite-time statistical validity of the developed algorithm. We also discuss the convergence conditions for the asymptotic optimality of our algorithm. The algorithmic performance is examined with experiments under different parameter settings and stopping conditions. During the experiments, our algorithm performs favorably in comparison to the popular Arena optimization tool, OptQuest. © Operational Research Society 2022.

关键词： approximation algorithms

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LPN-based Attacks in the White-box Setting

IACR Transactions on Cryptographic Hardware and Embedded Sys...

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IACR Transactions on Cryptographic Hardware and Embedded Systems 2023年第4期2023卷 318-343页

作者： Charlès, Alex Udovenko, Aleksei University of Luxembourg Esch-sur-Alzette Luxembourg

In white-box cryptography, early protection techniques have fallen to the automated Differential Computation Analysis attack (DCA), leading to new countermeasures and attacks. A standard side-channel countermeasure, Ishai-SahaiWagner’s masking scheme (ISW, CRYPTO 2003) prevents Differential Computation Analysis but was shown to be vulnerable in the white-box context to the Linear Decoding Analysis attack (LDA). However, recent quadratic and cubic masking schemes by Biryukov-Udovenko (ASIACRYPT 2018) and Seker-Eisenbarth-Liskiewicz (CHES 2021) prevent LDA and force to use its higher-degree generalizations with much higher complexity. In this work, we study the relationship between the security of these and related schemes to the Learning Parity with Noise (LPN) problem and propose a new automated attack by applying an LPN-solving algorithm to white-box implementations. The attack effectively exploits strong linear approximations of the masking scheme and thus can be seen as a combination of the DCA and LDA techniques. Different from previous attacks, the complexity of this algorithm depends on the approximation error, henceforth allowing new practical attacks on masking schemes which previously resisted automated analysis. We demonstrate it theoretically and experimentally, exposing multiple cases where the LPN-based method significantly outperforms LDA and DCA methods, including their higher-order variants. This work applies the LPN problem beyond its usual post-quantum cryptography boundary, strengthening its interest for the cryptographic community, while expanding the range of automated attacks by presenting a new direction for breaking masking schemes in the white-box model. © 2023, Ruhr-University of Bochum. All rights reserved.

关键词： approximation algorithms

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ENAP: An Efficient Number-Aware Pruning Framework for Design Space Exploration of Approximate Configurations

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2023年第5期70卷 2062-2073页

作者： Dou, Yuqin Wang, Chenghua Woods, Roger Liu, Weiqiang Nanjing Univ Aeronaut & Astronaut NUAA Coll Elect & Informat Engn Nanjing 211106 Peoples R China Queens Univ Belfast Sch Elect Elect Engn & Comp Sci Belfast BT7 1NN North Ireland

Approximate computing has emerged as a new computing architecture paradigm that trades off necessary numerical accuracy for performance. Various approximation operation units such as adders and multipliers have been created and provide the basis for improving system efficiency, but it is clear, that a design space exploration (DSE) is needed if improved performance is to be systematically achieved. The challenge is to determine a suitable configuration among approximation units with different error characteristics to ensure a minimization of resources while not exceeding user-defined error constraints. In this paper, we propose the efficient number-aware pruning (ENAP) technique that can compress the search space size. Using common fault-tolerant applications, we demonstrate a compression rate up to 0.0008%, meaning that 99.9992% of invalid designs can remain unsearched. An improved genetic algorithm (GA) is subsequently proposed to improve ENAP, allowing the creation of the optimal configuration in only 2 to 3 iterations, thereby greatly improving search efficiency compared to the initial 9 iterations. We integrate these two approaches into the proposed framework, demonstrating how we can achieve better exploration results compared to state-of-the-artwork.

关键词： Space exploration Genetic algorithms Adders Approximate computing Energy consumption approximation algorithms Libraries design space exploration number-aware pruning genetic algorithms

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Evaluation of Neural Network Verification Methods for Air-to-Air Collision Avoidance

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Journal of Air Transportation 2023年第1期31卷 1-17页

作者： Lopez, Diego Manzanas Johnson, Taylor T. Bak, Stanley Tran, Hoang-Dung Hobbs, Kerianne L. Vanderbilt University Electrical Engineering and Computer Science 1025 16th Avenue South Suite 102 NashvilleTN37235 United States Stony Brook University 100 Nicolls Road Stony Brook NY11794 United States University of Nebraska at Lincoln LincolnNE68588 United States U.S. Air Force Research Laboratory 2210 8th Street Wright-Patterson Air Force Base OH45433 United States

Neural network approximations have become attractive to compress data for automation and autonomy algorithms for use on storage-limited and processing-limited aerospace hardware. However, unless these neural network approximations can be exhaustively verified to be safe, they cannot be certified for use on aircraft. An example of such systems is the unmanned Airborne Collision Avoidance System (ACAS) Xu, which is a very popular benchmark for open-loop neural network control system verification tools. This paper proposes a new closed-loop extension of this benchmark, which consists of a set of 10 closed-loop properties selected to evaluate the safety of an ownship aircraft in the presence of a co-altitude intruder aircraft. These closed-loop safety properties are used to evaluate five of the 45 neural networks that comprise the ACAS Xu benchmark (corresponding to co-altitude cases) as well as the switching logic between the five neural networks. The combination of nonlinear dynamics and switching between five neural networks is a challenging verification task accomplished with star-set reachability methods in two verification tools. The safety of the ownship aircraft under initial position uncertainty is guaranteed in every scenario proposed. © 2022 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： approximation algorithms

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Approximating Small Sparse Cuts 2024

Approximating Small Sparse Cuts

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56th Annual ACM Symposium on Theory of Computing (STOC)

作者： Anand, Aditya Lee, Euiwoong Li, Jason Saranurak, Thatchaphol Univ Michigan Ann Arbor MI 48109 USA Carnegie Mellon Univ Pittsburgh PA USA

ISBN: (纸本)9798400703836

We study polynomial-time approximation algorithms for edge and vertex Sparsest Cut and Small Set Expansion in terms of k, the number of edges or vertices cut in the optimal solution. Our main results are O( polylog k)-approximation algorithms for various versions in this setting. Our techniques involve an extension of the notion of sample sets (Feige and Mahdian STOC'06), originally developed for small balanced cuts, to sparse cuts in general. We then show how to combine this notion of sample sets with two algorithms, one based on an existing framework of LP rounding and another new algorithm based on the cut-matching game, to get such approximation algorithms. Our cut-matching game algorithm can be viewed as a local version of the cut-matching game by Khandekar, Khot, Orecchia and Vishnoi and certifies an expansion of every vertex set of size.. in O(log s) rounds. These techniques may be of independent interest. As corollaries of our results, we also obtain an O(log opt) approximation for min-max graph partitioning, where opt is the min-max value of the optimal cut, and improve the bound on the size of multicut mimicking networks computable in polynomial time.

关键词： approximation algorithms Sparsest Cut Small Set Expansion Cutmatching game Sample sets

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