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Circuit area optimization of multi-output MPRM based on ERWOA algorithm

Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics 2023年第5期49卷 1193-1200页

作者： He, Juncai He, Zhenxue Wang, Fushun Huo, Zhisheng Xiao, Limin Intelligent Agricultural Equipment Research Institute Hebei Agricultural University Baoding071001 China Key Laboratory of Agricultural Big Data of Hebei Province Hebei Agricultural University Baoding071001 China High Performance Computing Platform Beihang University Beijing100191 China School of Software Beihang University Beijing100191 China School of Computer Science and Engineering Beihang University Beijing100191 China

Mixed polarity Reed-Muller (MPRM) circuit area optimization has become a research hotspot in the field of integrated circuit design. It is a combinatorial optimization, aiming at finding the MPRM expression with the least number of terms among many MPRM expressions. A explosion strategy and restart strategy based whale optimization algorithm (ERWOA) is proposed. In addition, a multi-output MPRM circuit area optimization method is proposed, which uses the improved whale algorithm and the improved polarity conversion algorithm to search for the MPRM circuit with the least number of AND terms. Results on the MCNC Benchmark circuits show that the proposed algorithm increases the conversion efficiency by 99.93% and 99.96% at most, compared with the mixed polarity and inter-polarity conversion algorithms based on the list technology, respectively. Compared with the genetic algorithm and the artificial bee colony algorithm, the improved whale optimization algorithm saves the circuit area up to 18.32% with an average of 5.54%, and 14.41% with an average of 5.00%, respectively. © 2023 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.

关键词： Genetic algorithms

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DrugProtKGE: Weakly Supervised Knowledge Graph Embedding for highly-Effective Drug-Protein Interaction Representation

DrugProtKGE: Weakly Supervised Knowledge Graph Embedding for...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yanlong Qiu Siqi Wang Xi Yang Xinyuan Qiu Chengkun Wu Yingbo Cui Canqun Yang Institute for Quantum Information & State Key Laboratory of High-Performance Computing College of Computer Science National University of Defense Technology Changsha P. R. China National Supercomputer Center in Tianjin Tianjin P. R. China National Key Laboratory of Parallel and Distributed Computing College of Computer Science National University of Defense Technology Changsha P. R. China Department of Biology and Chemistry College of Science National University of Defense Technology Changsha P. R. China

With the exponential growth of biomedical knowledge in unstructured text repositories such as PubMed, it is imminent to establish a knowledge graph-style, efficient searchable and targeted database that can support the need of information retrieval from researchers and clinicians. To mine knowledge from graph databases, most previous methods view a triple in a graph (see Fig. 1) as the basic processing unit and embed the triplet element (i.e. drugs/chemicals, proteins/genes and their interaction) as separated embedding matrices, which cannot capture the semantic correlation among triple elements. To remedy the loss of semantic correlation caused by disjoint embeddings, we propose a novel approach to learn triple embeddings by combining entities and interactions into a unified representation. Furthermore, traditional methods usually learn triple embeddings from scratch, which cannot take advantage of the rich domain knowledge embedded in pre-trained models, and is also another significant reason for the fact that they cannot distinguish the differences implied by the same entity in the multi-interaction triples. In this paper, we propose a novel fine-tuning based approach to learn better triple embeddings by creating weakly supervised signals from pre-trained knowledge graph embeddings. The method automatically samples triples from knowledge graphs and estimates their pairwise similarity from pre-trained embedding models. The triples are then fed pairwise into a Siamese-like neural architecture, where the triple representation is fine-tuned in the manner bootstrapped by triple similarity scores. Finally, we demonstrate that triple embeddings learned with our method can be readily applied to several downstream applications (e.g. triple classification and triple clustering). We evaluated the proposed method on two open-source drug-protein knowledge graphs constructed from PubMed abstracts, as provided by BioCreative. Our method achieves consistent improvement in both t

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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...

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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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Ability of strong-pulse illumination to hack self-differencing avalanche photodiode detectors in a high-speed quantum-key-distribution system

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Physical Review A 2022年第3期106卷 033713-033713页

作者： Binwu Gao Zhihao Wu Weixu Shi Yingwen Liu Dongyang Wang Chunlin Yu Anqi Huang Junjie Wu Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha 410073 China China Greatwall Research Institute China Greatwall Technology Group Co. Ltd. Shenzhen 518057 China

Implementation of high-speed quantum key distribution (QKD) has become one of the major focuses in the field, which produces a high key-generation rate for applications. To achieve high-speed QKD, tailored techniques are developed and employed to quickly generate and detect quantum states. However, these techniques may introduce unique loopholes to compromise the security of QKD systems. In this paper, we investigate the loopholes of the self-differencing (SD) avalanche photodiode (APD) detector, typically used for high-speed detection in a QKD system, and demonstrate experimental testing of the SD APD detector under strong-pulse-illumination attack. This attack presents blinding stability and helps an eavesdropper to learn the secret key without introducing extra quantum bit rate error. Based on this testing, we propose a set of criteria for protecting SD APD detectors from the strong-pulse-illumination attack.

关键词： Quantum communication Quantum cryptography

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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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Integrated framework for assessment and spatial prediction of humus layer properties of forest soils

Discover Soil

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Discover Soil 2025年第1期2卷 1-21页

作者： Thomas, Felix Becker, Carina Petzold, Rainer Schmidt, Karsten Scholten, Thomas Werban, Ulrike Department Monitoring and Exploration Technologies Helmholtz Centre for Environmental Research Leipzig Germany Soil Science and Geomorphology Institute of Geography University of Tübingen Tübingen Germany Center for Information Services and High Performance Computing (ZIH) TU Dresden Dresden Germany Unit Site Survey Soil Monitoring and Laboratory Public Enterprise Sachsenforst Pirna Germany Swiss Competence Center for Soils (KOBO) Data Science BFH-HAFL Zollikofen Switzerland

Data about the availability of nutrients in the humus layer of forest soils is vital information for sustainable forest management. For well-informed decision making, changes in humus layer conditions have to be monitored. The currently used schemes based on indicator plants are more and more overprinted by element input and forest management measures. Large and repeated field campaigns and laboratory analysis can provide the required information, but are expensive and time consuming. Techniques of Digital Soil Mapping (DSM) offer an alternative to gain the necessary information by spatially predicting selected soil properties, but their usage for mapping humus layer properties of forest soils is rare. Further, vis-NIR spectroscopy is a non-destructive approach that can provide physical and chemical soil properties via regression models. In this study, we present the application of an integrated framework as measuring system using DSM with the aim of providing spatial information about properties of the humus layer of forest soils. In order to reduce the amount of laboratory work, we applied the use of vis-NIR spectroscopy to determine the humus layer properties values within the framework. As input variables, we used available information based on soil forming factors and already existing information on mineral soils (soil form class, climate data, satellite data as proxy for vegetation, relief data and parent material and geographic location). Therefore, generally available data like satellite imagery and climate data can be used in combination with information that is already available in forest site mapping, e.g. on parent material, soil texture and pedogenetic soil type as well as hydromorphic features. Conditioned Latin Hypercube sampling was used to determine the locations of the field sampling points to collect the soil material, ensuring a valid representation of the humus layer properties in the test area. Probed layers were the Oh horizon and 0–5 cm

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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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dugMatting: Decomposed-Uncertainty-Guided Matting

arXiv

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arXiv 2023年

作者： Wu, Jiawei Zhang, Changqing Li, Zuoyong Fu, Huazhu Peng, Xi Zhou, Joey Tianyi College of Mechanical and Electrical Engineering Fujian Agriculture and Forestry University Fuzhou China College of Intelligence and Computing Tianjin University Tianjin China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China Institute of High Performance Computing Agency for Science Technology and Research Singapore College of Computer Science Sichuan University Chengdu China Singapore

Cutting out an object and estimating its opacity mask, known as image matting, is a key task in image and video editing. Due to the highly ill-posed issue, additional inputs, typically user-defined trimaps or scribbles, are usually needed to reduce the uncertainty. Although effective, it is either time consuming or only suitable for experienced users who know where to place the strokes. In this work, we propose a decomposed-uncertainty-guided matting (dugMatting) algorithm, which explores the explicitly decomposed uncertainties to efficiently and effectively improve the results. Basing on the characteristic of these uncertainties, the epistemic uncertainty is reduced in the process of guiding interaction (which introduces prior knowledge), while the aleatoric uncertainty is reduced in modeling data distribution (which introduces statistics for both data and possible noise). The proposed matting framework relieves the requirement for users to determine the interaction areas by using simple and efficient labeling. Extensively quantitative and qualitative results validate that the proposed method significantly improves the original matting algorithms in terms of both efficiency and efficacy. Copyright © 2023, The Authors. All rights reserved.

关键词： Uncertainty analysis

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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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