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SSRN 2024年

作者： Cong, HaiLong Zhang, Zhen Cheng, ZeFan Li, HaiChao Wang, Pei Sun, WanTing School of Materials Engineering Shanghai University of Engineering Science Shanghai201620 China Henan Key Laboratory of High Performance Carbon Fiber Reinforced Composites Institute of Carbon Matrix Composites Henan Academy of Sciences Zhengzhou450046 China Department of Electrical and Computer Engineering University of Nebraska LincolnNE68588 United States

In this study, hot pressing was applied to fabricate high alloying Al-Zn-Mg-Cu composites with excellent properties reinforced with two types of nanoceramic particles, including SiC and Al2O3. With the combination of hot extrusion and T6 heat treatment, the influences of nanoceramic particle addition on the microstructural evolution and mechanical properties of the high alloying Al-Zn-Mg-Cu alloy were systematically investigated. The experimental results demonstrated that the Mg atoms in theα-Al matrix were consumed by the addition of SiC/Al2O3 nano-ceramic particles, and thereby the grain size primary η' (MgZn2) strengthening phase was refined, leading to an enhanced overall mechanical performance of the Al-Zn-Mg-Cu composite. In particular, the Mg2Si phase was generated by the addition of SiC nanoceramic particles, through the interfacial reactions, and thus with the synergistic effects of precipitation strengthening and Orowan strengthening, the ultimate compression strength and compressibility of Al-Zn-Mg-Cu composite can be increased to 844 MPa and 27.5%, respectively. On the other hand, the addition of Al2O3 nanoceramic particles can bring about the formation of an oxygen-rich phase and refined precipitates at grain boundaries. Accordingly, the elongation is increased to 43.5% while a high ultimate compressive strength in the composites can be maintained. It is anticipated that nanoceramic particle-reinforced Al-based metal composites have significant potential for achieving both high strength and exceptional ductility for the application in the industry field. © 2024, The Authors. All rights reserved.

关键词： Binary alloys

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Salient Object Detection From Arbitrary Modalities

arXiv

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arXiv 2024年

作者： Huang, Nianchang Yang, Yang Xi, Ruida Zhang, Qiang Han, Jungong Huang, Jin The Center for Complex Systems School of Mechano-Electronic Engineering Xidian University Shaanxi Xi’an710071 China The Department of Computer Science University of Sheffield United Kingdom The State Key Laboratory of Electromechanical Integrated Manufacturing of High-Performance Electronic Equipment Shaanxi Xi’an710071 China

Toward desirable saliency prediction, the types and numbers of inputs for a salient object detection (SOD) algorithm may dynamically change in many real-life applications. However, existing SOD algorithms are mainly designed or trained for one particular type of inputs, failing to be generalized to other types of inputs. Consequentially, more types of SOD algorithms need to be prepared in advance for handling different types of inputs, raising huge hardware and research costs. Differently, in this paper, we propose a new type of SOD task, termed Arbitrary Modality SOD (AM SOD). The most prominent characteristics of AM SOD are that the modality types and modality numbers will be arbitrary or dynamically changed. The former means that the inputs to the AM SOD algorithm may be arbitrary modalities such as RGB, depths, or even any combination of them. While, the latter indicates that the inputs may have arbitrary modality numbers as the input type is changed, e.g. single-modality RGB image, dual-modality RGB-Depth (RGB-D) images or triple-modality RGB-Depth-Thermal (RGB-D-T) images. Accordingly, a preliminary solution to the above challenges, i.e. a modality switch network (MSN), is proposed in this paper. In particular, a modality switch feature extractor (MSFE) is first designed to extract discriminative features from each modality effectively by introducing some modality indicators, which will generate some weights for modality switching. Subsequently, a dynamic fusion module (DFM) is proposed to adaptively fuse features from a variable number of modalities based on a novel Transformer structure. Finally, a new dataset, named AM-XD, is constructed to facilitate research on AM SOD. Extensive experiments demonstrate that our AM SOD method can effectively cope with changes in the type and number of input modalities for robust salient object detection. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Modeling Neural Networks Training Process with Markov Decision Process 2

Modeling Neural Networks Training Process with Markov Decisi...

引用

2nd International Conference on Artificial Intelligence and computer engineering, ICAICE 2021

作者： Bai, Yantao Liu, Wanwei Mao, Xinjun Liang, Zhen National University of Defense Technology Key Laboratory of Software Engineering for Complex Systems Changsha China College of Computer Science National University of Defense Technology Changsha China Institute for Quantum Information National University of Defense Technology State Key Laboratory of High Performance Computing Changsha China

ISBN: (纸本)9781665421867

With the development of computer technology, statistics-based machine learning method has made great break-throughs, and also improved the development of artificial intelligence. Nevertheless, as a very influential model, neural networks are still treated as 'black boxes'. The results of neural networks are extremely sensitive to the training samples, which lead to great challenges to the controllability of the algorithm. With the wide application of machine learning, demand for interpretability and controllability of neural networks algorithms is increasing. As a result, various scholars have tried to explain and verify neural networks algorithms based on formal methods in recent years. In this paper, a method (called MNNTP) is presented to model the training process of neural networks by using a Markov decision process (MDP). Through MNNTP, the neural networks are abstracted into the form of MDP, which makes notable contributions for verifying some mathematical properties of the neural networks. © 2021 IEEE.

关键词： Markov processes

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Nanoceramic Particle Reinforced high Alloying Al-Zn-Mg-Cu Composites

SSRN

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SSRN 2024年

In this study, hot pressing was applied to fabricate high alloying Al-Zn-Mg-Cu composites with excellent properties reinforced with two types of nanoceramic particles, including SiC and Al2O3. With the combination of hot extrusion and T6 heat treatment, the influences of nanoceramic particle addition on the microstructural evolution and mechanical properties of the high alloying Al-Zn-Mg-Cu alloy were systematically investigated. The experimental results demonstrated that the Mg atoms in theα-Al matrix were consumed by the addition of SiC/Al2O3 nano-ceramic particles, and thereby the grain size primary η' (MgZn2) strengthening phase was refined, leading to an enhanced overall mechanical performance of the Al-Zn-Mg-Cu composite. In particular, the Mg2Si phase was generated by the addition of SiC nanoceramic particles, through the interfacial reactions, and thus with the synergistic effects of precipitation strengthening and Orowan strengthening, the ultimate compression strength and elongation of Al-Zn-Mg-Cu composite can be increased to 844 MPa and 27.5%, respectively. On the other hand, the addition of Al2O3 nanoceramic particles can bring about the formation of an oxygen-rich phase and refined precipitates at grain boundaries. Accordingly, the elongation is increased to 43.5% while a high ultimate compressive strength in the composites can be maintained. It is anticipated that nanoceramic particle-reinforced Al-based metal composites have significant potential for achieving both high strength and exceptional ductility for the application in the industry field. © 2024, The Authors. All rights reserved.

关键词： Binary alloys

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Health Care and Management based on Block chain and Machine Learning

Health Care and Management based on Block chain and Machine ...

引用

Artificial Intelligence and Knowledge Discovery in Concurrent engineering (ICECONF), International Conference on

作者： Ruhi Bakh VeenaNair Sarkar Jerlin Priya Lovelin Auguskani Galiveeti Poornima Monali N. Shetty Meerjumla Govind Raj Dr. Ambedkar Institute of Management Studies and Research IIHMR UNIVERSITY. Department of Nursing College Aldrab Jazan University Kingdom of Saudi Arabia. High Performance Computing Lab School of Computer Science and Information Science Presidency University Bengaluru Computer Science Engineering Fr. CRCE St. Martin's Engineering College Secunderabad Telangana

With the coming of technology, we currently have an immense measure of information accessible in each field, making it conceivable to offer responses to many issues. We will utilize machine learning and block chain technology to resolve issues with healthcare information the executives in this review. With the guide of machine learning, separating just the relevant information from the data is plausible. Using prepared calculations, this is finished. The reliability of information trade turns into a test after this information has been put away. This is where block chain technology is valuable. Block chain technology's agreement guarantees that information is credible and exchanges are secure. By putting the patient at the focal point of the healthcare framework and upgrading the security and interoperability of health information, block chain technology can possibly further develop health care organization. This article fundamentally centres around settling issues with healthcare information the board using Block chain technology and including a few urgent highlights utilizing Machine Learning. The freshest technology, block chain, offers a strong and secure groundwork. With these offices, block chain has gotten some momentum in an assortment of use areas, including the food business, store network the board, energy, government support offices, and healthcare.

关键词： Telemedicine Government Medical treatment Machine learning Medical services Knowledge discovery Blockchains

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A method of generating random bits by using electronic bipolar memristor

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Chinese Physics B 2020年第4期29卷 535-540页

作者： Bin-Bin Yang Nuo Xu Er-Rui Zhou Zhi-Wei Li Cheng Li Pin-Yun Yi Liang Fang Institute for Quantum Information&State Key Laboratory of High Performance Computing College of ComputerNational University of Defense TechnologyChangsha 410073China College of Computer National University of Defense TechnologyChangsha 410073China College of Electronic Science and Engineering National University of Defense TechnologyChangsha 410073China

The intrinsic stochasticity of resistance switching process is one of the holdblocks for using memristor as a fundamental element in the next-generation nonvolatile ***,such a weakness can be used as an asset for generating the random bits,which is valuable in a hardware security *** this work,a forming-free electronic bipolar Pt/Ti/Ta2O5/Pt memristor is successfully fabricated to investigate the merits of generating random bits in such a *** resistance switching mechanism of the fabricated device is ascribed to the electric field conducted electrons trapping/de-trapping in the deep-energy-level traps produced by the"oxygen grabbing"*** stochasticity of the electrons trapping/detrapping governs the random distribution of the set/reset switching voltages of the device,making a single memristor act as a random bit in which the resistance of the device represents information and the applied voltage pulse serves as the triggering *** physical implementation of such a random process provides a method of generating the random bits based on memristors in hardware security applications.

关键词： memristor resistance switching electrons trapping/de-trapping random bits

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Synergizing Symbolic Execution and Fuzzing By Function-level Selective Symbolization

Synergizing Symbolic Execution and Fuzzing By Function-level...

引用

Asia-Pacific Conference on Software engineering

作者： Guofeng Zhang Zhenbang Chen Ziqi Shuai Yufeng Zhang Ji Wang College of Computer National University of Defense Technology ChangSha China State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (纸本)9781665455381

Constraint solving and environment modeling are two challenging problems for symbolic execution. When a program contains non-linear expressions, it is difficult for symbolic execution to explore the program’s whole path space due to the high complexity of the constraint solving for the nonlinear constraints. Besides, when the program uses a third-party library and the source code of the library is not available, the symbolic execution of the program often under-approximates the analysis by concrete execution or over-approximates by introducing new symbolic variables, which may fail to explore the whole path space or introduce false alarms, respectively. This paper proposes FUSE, a framework of synergizing symbolic execution and fuzzing by function-level selective symbolization to tackle these problems. First, FUSE collects the path constraints of each function selectively and introduces symbolic function invocation expressions for the complex or third-party functions. Then, FUSE combines SMT solving and fuzzing to solve the path constraints. We have implemented FUSE on the start-of-theart symbolic execution engine KLEE. The experimental results demonstrate that FUSE effectively and efficiently improves the code coverage. Compared with the state-of-the-art, FUSE achieves 6. 6x speedups for achieving the same code coverage.

关键词： Codes Fuses Source coding Semantics Fuzzing Benchmark testing Libraries

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Verifying ReLU Neural Networks from a Model Checking Perspective

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Journal of computer science & Technology 2020年第6期35卷 1365-1381页

作者： Wan-Wei Liu Fu Song Tang-Hao-Ran Zhang Ji Wang College of Computer Science National University of Defense TechnologyChangsha 410073China School of Information Science and Technology ShanghaiTech UniversityShanghai 201210China Shanghai Engineering Research Center of Intelligent Vision and Imaging Shanghai 201210China State Key Laboratory for High Performance Computing Changsha 410073China

Neural networks, as an important computing model, have a wide application in artificial intelligence (AI) domain. From the perspective of computer science, such a computing model requires a formal description of its behaviors, particularly the relation between input and output. In addition, such specifications ought to be verified automatically. ReLU (rectified linear unit) neural networks are intensively used in practice. In this paper, we present ReLU Temporal Logic (ReTL), whose semantics is defined with respect to ReLU neural networks, which could specify value-related properties about the network. We show that the model checking algorithm for theΣ2∪Π2 fragment of ReTL, which can express properties such as output reachability, is decidable in EXPSPACE. We have also implemented our algorithm with a prototype tool, and experimental results demonstrate the feasibility of the presented model checking approach.

关键词： model checking rectified linear unit neural(ReLU)network temporal logic

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Complex Permeability Determination for EE Core Based on Flexible PCB Fixture and Magnetic Flux Path Length Analysis

Complex Permeability Determination for EE Core Based on Flex...

引用

China Power Supply Society Electromagnetic Compatibility Conference (CPEMC)

作者： Huamin Jie Zhenyu Zhao Yongqi Chang Changdong Wang Shiqi Jiang Richard Xian-Ke Gao Kye Yak See School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering National Univeristy of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China A*STAR Institute of High Performance Computing Singapore Singapore

ISBN: (数字)9798331509552

ISBN: (纸本)9798331509569

The complex permeability of magnetic cores acts as a vital factor in electromagnetic interference (EMI) filtering choke design and optimization. Many efforts have been reported for toroid cores, but fewer target those with other shapes, such as EE, EI, UU, and UI cores. Owing to their commonly used in planar EMI filters, determining the complex permeability of them is of significance. Targeting EE cores, this paper presents a flexible printed circuit board (PCB)-based fixture adapter tailored designed for performing the measurement, while the corresponding core permeability can be calculated through magnetic flux path length analysis. The experiments validate the effectiveness and accuracy of the proposed methods, spanning a wide frequency range up to 120 MHz.

关键词： Magnetic flux Accuracy Flexible printed circuits Magnetic cores Fixtures Electromagnetic interference Permeability measurement Length measurement Permeability Inductors

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Towards Faster Matrix Diagonalization with Graph Isomorphism Networks and the AlphaZero Framework

arXiv

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arXiv 2024年

作者： Zollicoffer, Geigh Bhattarai, Manish Negre, Christian F.A. Bhatta, Kshitij Romero, Phil Niklasson, Anders M.N. Adedoyin, Adetokunbo Georgia Institute of Technology AtlantaGA United States Theoretical division Los Alamos National Laboratory NM United States Department of Mechanical Engineering University of Virginia CharlottesvilleVA United States High Performance Computing division Los Alamos National Laboratory NM United States Computer Computational and Statistical Sciences Division Los Alamos National Laboratory NM United States

In this paper, we introduce innovative approaches for accelerating the Jacobi method for matrix diagonalization, specifically through the formulation of large matrix diagonalization as a Semi-Markov Decision Process and small matrix diagonalization as a Markov Decision Process. Furthermore, we examine the potential of utilizing scalable architecture between different-sized matrices. During a short training period, our method discovered a significant reduction in the number of steps required for diagonalization and exhibited efficient inference capabilities. Importantly, this approach demonstrated possible scalability to large-sized matrices, indicating its potential for wide-ranging applicability. Upon training completion, we obtain action-state probabilities and transition graphs, which depict transitions between different states. These outputs not only provide insights into the diagonalization process but also pave the way for cost savings pertinent to large-scale matrices. The advancements made in this research enhance the efficacy and scalability of matrix diagonalization, pushing for new possibilities for deployment in practical applications in scientific and engineering domains. Copyright © 2024, The Authors. All rights reserved.

关键词： Scalability

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