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P3DC:Reducing DRAM Cache Hit Latency by Hybrid Mappings

Journal of computer science & Technology 2024年第6期39卷 1341-1360页

作者： Ye Chi Ren-Tong Guo Xiao-Fei Liao Hai-Kun Liu Jianhui Yue National Engineering Research Center for Big Data Technology and System Wuhan 430074China Services Computing Technology and System Laboratory Wuhan 430074China Cluster and Grid Computing Laboratory Wuhan 430074China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China School of Big Data and Internet Shenzhen Technology UniversityShenzhen 518118China Department of Computer Science Michigan Technological UniversityHoughton 49931-1295U.S.A.

Die-stacked dynamic random access memory(DRAM)caches are increasingly advocated to bridge the performance gap between the on-chip cache and the main *** fully realize their potential,it is essential to improve DRAM cache hit rate and lower its cache hit *** order to take advantage of the high hit-rate of set-association and the low hit latency of direct-mapping at the same time,we propose a partial direct-mapped die-stacked DRAM cache called *** design is motivated by a key observation,i.e.,applying a unified mapping policy to different types of blocks cannot achieve a high cache hit rate and low hit latency *** address this problem,P3DC classifies data blocks into leading blocks and following blocks,and places them at static positions and dynamic positions,respectively,in a unified set-associative *** also propose a replacement policy to balance the miss penalty and the temporal locality of different *** addition,P3DC provides a policy to mitigate cache thrashing due to block type *** results demonstrate that P3DC can reduce the cache hit latency by 20.5%while achieving a similar cache hit rate compared with typical set-associative caches.P3DC improves the instructions per cycle(IPC)by up to 66%(12%on average)compared with the state-of-the-art direct-mapped cache—BEAR,and by up to 19%(6%on average)compared with the tag-data decoupled set-associative cache—DEC-A8.

关键词： die-stacked dynamic random access memory(DRAM) cache set-associative direct-mapped hit latency

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Security and privacy issues in blockchain and its applications

IET Blockchain

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IET Blockchain 2023年第4期3卷 169-171页

作者： Wang, Liangmin Sheng, Victor S. Düdder, Boris Wu, Haiqin Zhu, Huijuan School of Cyber Science and Engineering Southeast University Nanjing China Department of Computer Science Texas Tech University LubbockTX United States Department of Computer Science University of Copenhagen Copenhagen Denmark Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China

The papers in the first category focus on analyzing and providing insights into the security of blockchain applications. [...]significant research efforts have been dedicated to security analysis and detection in typical blockchain applications. The framework incorporates pre-training and fine-tuning, enabling the pre-trained model (teacher) to effectively adapt to the new data distribution and improve prediction performance. [...]to enhance the practicality of the system, they implement a copyright blockchain framework called ICP-Chain and conduct evaluations to assess its security and reliability. [...]the authors would like to express their utmost appreciation to the editors-in-chief and the editorial office for their unwavering support and guidance throughout this venture.

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Online Self-distillation and Self-modeling for 3D Brain Tumor Segmentation

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IEEE Journal of Biomedical and Health Informatics 2025年第6期29卷 4290-4302页

作者： Pang, Yan Li, Yunhao Huang, Teng Liang, Jiaming Wang, Zhen Dong, Changyu Kuang, Dongyang Hu, Ying Chen, Hao Lei, Tim Wang, Qiong The Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China The School of Artificial Intelligence Guangzhou University China The Zhejiang Lab Hangzhou China Sun Yat-sen University China The Department of Computer Science and Engineering The Department of Chemical and Biological Engineering Hong Kong University of Science and Technology China The Department of Electrical Engineering University of Colorado Denver United States

In the specialized domain of brain tumor segmentation, supervised segmentation approaches are hindered by the limited availability of high-quality labeled data, a condition arising from data privacy concerns, significant costs, and ethical issues. In response to this challenge, this paper presents a training framework that adeptly integrates a plug-and-play component, MOD, into current supervised learning models, boosting their efficacy in scenarios with limited data. The MOD consists of an Online Tokenizer and a Dense Predictor, which employs self-distillation and self-modeling on masked patches, promoting swift convergence and efficient representation learning. During the inference phase, the plug-and-play MOD component is excluded, preserving the computational efficiency of the original model without incurring extra processing costs. We substantiated the value of our approach through experiments on leading 3D brain tumor segmentation baselines. Remarkably, models augmented with the MOD consistently showcased superior results, achieving elevated Dice coefficients and HD95 scores on two datasets: BraTS 2021 and MSD 2019 Task-01 Brain Tumor. Code: https://***/aigzhusmart/MOD © 2013 IEEE.

关键词： Self-supervised learning

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Counterfactual discriminative micro-expression recognition

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Visual Intelligence 2024年第1期2卷 350-359页

作者： Yong Li Menglin Liu Lingjie Lao Yuanzhi Wang Zhen Cui Department of Computer Science City University of Hong KongHong Kong999077China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing210094China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of EducationSchool of Computer Science and EngineeringNanjing University of Science and TechnologyNanjing210094China

Micro-expressions are spontaneous,rapid and subtle facial movements that can hardly be suppressed or ***-expression recognition(MER)is one of the most challenging topics in affective *** aims to recognize subtle facial movements which are quite difficult for humans to perceive in a fleeting ***,many deep learning-based MER methods have been ***,how to effectively capture subtle temporal variations for robust MER still perplexes *** propose a counterfactual discriminative micro-expression recognition(CoDER)method to effectively learn the slight temporal variations for video-based *** explicitly capture the causality from temporal dynamics hidden in the micro-expression(ME)sequence,we propose ME counterfactual reasoning by comparing the effects of the facts *** ME sequences and the counterfactuals ***-revised ME sequences,and then perform causality-aware prediction to encourage the model to learn those latent ME temporal *** experiments on four widely-used ME databases demonstrate the effectiveness of CoDER,which results in comparable and superior MER performance compared with that of the state-of-the-art *** visualization results show that CoDER successfully perceives the meaningful temporal variations in sequential faces.

关键词： Affective computing Micro-expression recognition Temporal variation Counterfactual reasoning Causal graph

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Dynamics-incorporated Modeling Framework for Stability Constrained Scheduling under High-penetration of Renewable Energy

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IEEE Transactions on Sustainable Energy 2025年第3期16卷 1673-1685页

作者： Wang, Jinning Li, Fangxing Fang, Xin Cui, Hantao She, Buxin Shuai, Hang Zhang, Qiwei Tomsovic, Kevin University of Tennessee Department of Electrical Engineering and Computer Science KnoxvilleTN37996 United States Mississippi State University Department of Electrical and Computer Engineering StarkvilleMS39762 United States NC State University Department of Electrical and Computer Engineering RaleighNC27606 United States Pacific Northwest National Laboratory RichlandWA99352 United States Johns Hopkins University Department of Environmental Health and Eng. BaltimoreMD21205 United States

In this paper, a modularized modeling framework is designed to enable a dynamics-incorporated power system scheduling under high-penetration of renewable energy. This unique framework incorporates an adapted hybrid symbolic-numeric approach to scheduling models, effectively bridging the gap between device- and system-level optimization models and streamlining the scheduling modeling effort. The adaptability of the proposed framework stems from four key aspects: extensible scheduling formulations through modeling blocks, scalable performance via effective vectorization and sparsity-aware techniques, compatible data structure aligned with dynamic simulators by common power flow data, and interoperable dynamic interface for bi-direction data exchange between steady-state generation scheduling and time-domain dynamic simulation. Through extensive benchmarks with various usage scenarios, the framework's accuracy and scalability are validated. The case studies also demonstrate the efficient interoperation of generation scheduling and dynamics, significantly reducing the modeling conversion work in stability-constrained grid operation towards high-penetration of renewable energy. © 2025 IEEE.

关键词： Adaptation models Dynamic scheduling Numerical models Power system stability Power system dynamics Stability analysis Aerodynamics Transient analysis Computational modeling Renewable energy sources

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A Secured and Optimized Clustering Approch in Vehicular Ad-hoc Network 4

A Secured and Optimized Clustering Approch in Vehicular Ad-h...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Khan, Imran Khan, Fazlullah Ali, Asad Alshawi, Bandar Alturki, Ryan Wedyan, Mohammad Abdul Wali Khan University Computer Science Department KPK Mardan Pakistan School of Computer Science University of Nottingham Ningbo China Faculty of Science and Engineering Zhejiang315104 China University of Engineering and Technology Department of Computer Science KPK Peshawar Pakistan College of Computing Umm Al-Qura University Department of Computer and Network Engineering Makkah Saudi Arabia College of Computing Umm Al-Qura University Department of Software Engineering Makkah Saudi Arabia Faculty of Information Technology and Computer Sciences Department of Computer Sciences Irbid21163 Jordan

ISBN: (纸本)9798350395914

Vehicular ad hoc networks (VANETs) take vital role in intelligent transportation systems, but they face challenges due to dynamic network topology, impacting communication efficiency, especially with increasing active nodes. Security and privacy concerns are paramount, necessitating authentication to ensure only legitimate vehicles access the network. Secure vehicular clustering offers a solution, yet the number of clusters affects network dependability and efficiency. To tackle this, we present a secure clustering mechanism using Bat optimization algorithm, mimicking echolocation behavior to optimize clusters. We introduce an authentication technique for cluster heads to admit approved members, enhancing vehicular authentication. Simulations using MATLAB evaluate our approach, showing improved performance in end-to-end delay, overhead, and cluster head count compared to similar methods. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Student Perceptions of Authentic Learning to Learn White-box Testing 2024

Student Perceptions of Authentic Learning to Learn White-box...

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55th ACM Technical Symposium on computer science Education, SIGCSE 2024

作者： Rahman, Akond Zhang, Yue Wu, Fan Shahriar, Hossain Department of Computer Science and Software Engineering Auburn University AuburnAL United States Department of Computer Science Tuskegee University TuskegeeAL United States Center for Cybersecurity University of West Florida PensacolaFL United States

ISBN: (纸本)9798400704246

The pivotal role of white-box testing with respect to software quality assurance, necessitates dissemination of education materials related to white-box testing in the course curriculum. In this poster, we describe our experiences in conducting an authentic learning-based exercise related to white-box testing. From a conducted survey with 124 students, we observe the authentic learning-based exercise to be helpful for students to learn about white-box testing. © 2024 Owner/Author.

关键词： Students

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Computational Approaches for Traditional Chinese Painting: From the “Six Principles of Painting” Perspective

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Journal of computer science & Technology 2024年第2期39卷 269-285页

作者：张玮张建伟黄锦畦王懿芳封颖超杰王璐玮陈为 State Key Laboratory of CAD&CG Zhejiang UniversityHangzhou 310058China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong 999077China Kellogg School of Management Northwestern UniversityEvanston 60208U.S.A Laboratory of Art and Archaeology Image Zhejiang UniversityHangzhou 310058China

Traditional Chinese painting(TCP)is an invaluable cultural heritage resource and a unique visual art *** recent years,there has been a growing emphasis on the digitalization of TCP for cultural preservation and *** resulting digital copies have enabled the advancement of computational methods for a structured and systematic understanding of *** explore this topic,we conduct an in-depth analysis of 94 pieces of *** examine the current use of computer technologies on TCP from three perspectives,based on numerous conversations with ***,in light of the“Six Principles of Painting”theory,we categorize the articles according to their research focus on artistic ***,we create a four-stage framework to illustrate the purposes of TCP ***,we summarize the popular computational techniques applied to *** work also provides insights into potential applications and prospects,with professional opinion.

关键词： traditional Chinese painting(TCP) digital humanities cultural heritage computer vision deep learning

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Energy Efficient Transmitter Creation by Consuming Free Energy in Molecular Communication

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IEEE Transactions on Molecular, Biological, and Multi-Scale Communications 2025年第2期11卷 292-303页

作者： Jing, Dongliang Li, Linjuan Cheng, Zhen Lin, Lin Eckford, Andrew W. Northwest A and F University College of Mechanical and Electronic Engineering Yangling China Ministry of Agriculture and Rural Affairs Key Laboratory of Agricultural Internet of Things Yangling China Zhejiang University of Technology School of Computer Science and Technology Hangzhou310023 China Tongji University College of Electronics and Information Engineering Shanghai China York University Department of Electrical Engineering and Computer Science TorontoON Canada

Information molecules play a crucial role in molecular communication (MC), acting as carriers for information transfer. A common approach to get information molecules in MC involves harvesting them from the environment;however, the harvested molecules are often a mixture of various environmental molecules, and the initial concentration ratios in the reservoirs are identical, which hampers high-fidelity transmission techniques such as molecular shift keying (MoSK). This paper presents a transmitter design that harvests molecules from the surrounding environment and stores them in two reservoirs. To separate the mixed molecules, energy is consumed to transfer them between reservoirs. Given limited energy resources, this work explores energy-efficient strategies to optimize transmitter performance. Through theoretical analysis and simulations, we investigate different methods for moving molecules between reservoirs. The results demonstrate that transferring higher initial concentration molecules enhances transmitter performance, while using fewer molecules per transfer further improves efficiency. These findings provide valuable insights for optimizing MC systems through energy-efficient molecule transfer techniques. © 2015 IEEE.

关键词： Transmitters

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Adaptive Cost Aggregation in Iterative Depth Estimation for Efficient Multi-view Stereo 12th

Adaptive Cost Aggregation in Iterative Depth Estimation for...

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12th International Conference on Image and Graphics, ICIG 2023

作者： Wang, Xiang Bai, Xiao Wang, Chen School of Computer Science and Engineering State Key Laboratory of Software Development Environment Jiangxi Research Institute Beihang University Beijing China

ISBN: (纸本)9783031463075

The deep multi-view stereo (MVS) approaches generally construct 3D cost volumes to regularize and regress the depth map. These methods are limited with high-resolution outputs since the memory and time costs grow cubically as the volume resolution increases. In this paper, we presented an multi-stage iterative depth map estimation method for MVS. In our network, the cost volume is iteratively processed by lightweight 2D convolution based GRU modules, and the multi-stage coarse-to-fine structure is adopted to speed up the depth estimation process. To further improve the 3D reconstruction quality, we make improvements from two different perspectives of adaptive cost aggregation: a view-adaptive weighting module is proposed to account for the occlusion problem in cost volume fusion, and a spatial-adaptive deformable geometric feature encoding module is introduced to the cost volume feature encoding before feeding into GRUs for stronger modeling capability. Experiments on the DTU dataset demonstrated the effectiveness of the proposed network in accuracy with remarkable efficiency performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Iterative methods

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