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作者： Zhang, Mingyue Zhou, Junlong Cong, Peijin Zhang, Gongxuan Zhuo, Cheng Hu, Shiyan Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China Institute of Computing Technology Chinese Academy of Sciences State Key Laboratory of Computer Architecture Beijing100190 China Zhejiang University Department of Information Science and Electronic Engineering Hangzhou310027 China University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom

Internet of Vehicles (IoV) has become an indispensable data sensing and processing platform in Internet of Things (IoT) for intelligent transportation. The mounted cameras on the vehicles along with the fixed roadside cameras are utilized to provide pictorial services for IoV users and law enforcement agencies. For such forensic services, ensuring the security and privacy of vehicles while guaranteeing the efficiency of data transmission among vehicles is important. In this paper, we propose a lightweight incentive authentication scheme (LIAS) for forensic services in IoV. LIAS is developed on a three-tier architecture containing cloud layer, fog layer, and user layer. LIAS uses pairing-free certificateless signcryption, pseudonym update mechanism, and incentive mechanism to realize a secure anonymous authentication efficiently. We conduct correctness and security analysis, as well as performance analysis and evaluation to validate the high security and efficiency of LIAS. Experimental results reveal that, the communication and computation overheads as well as the message delay and packet loss of LIAS are much lower than those of state-of-the-art techniques. Note to Practitioners - This paper is motivated by the security and privacy issues of forensic services in IoV for intelligent transportation. Our goal is to improve the security and privacy of vehicles while guaranteeing the lightweight and incentive of data transmission among the vehicles. Fog-assisted IoV is introduced to fully utilize the capacities of near-user edge devices as well as the connections between fog nodes and devices. However, it still faces the difficulties in ensuring vehicles' security and privacy. Moreover, vehicles' information dissemination could be easily monitored because of the unavoidable defect of wireless communication. Thereby, it is essential to guarantee the security and privacy of vehicles while enhancing the efficiency of vehicles' data transmission during the forensic service.

关键词： Authentication

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NDANN: Efficient SSD-Based Approximate Nearest Neighbor Search through Navigation

NDANN: Efficient SSD-Based Approximate Nearest Neighbor Sear...

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2022 International Conference on Mechanisms and Robotics, ICMAR 2022

作者： Yang, Kaixiang Wang, Hongya Tan, Zongyuan Zhang, Jie College of Computer Science and Technology Donghua University Shanghai China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Institute of Artificial Intelligence Donghua University Shanghai China

ISBN: (纸本)9781510657328

Graph-based Approximate Nearest Neighbor Search (ANNS) algorithms have attracted more attention due to their better performance. Numerous ANNS optimization methods have been proposed by researchers. However, Current graph-based ANNS algorithms still cannot index billion-scale datasets on a single server with 256GB RAM. Although several researchers have investigated on this problem, we believe there is still an improvement in reducing disk accesses. In this paper, we provide a fast navigation layer to decrease the number of disk accesses by assisting query points in swiftly reaching the range of strongly connected components. Compared with the state-of-the-art ANNS algorithms, NDANN reduces the mean latency by about 20% under the same recall. © 2022 SPIE.

关键词： Graphic methods

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GraphTensor: Comprehensive GNN-Acceleration Framework for Efficient Parallel Processing of Massive Datasets

GraphTensor: Comprehensive GNN-Acceleration Framework for Ef...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Junhyeok Jang Miryeong Kwon Donghyun Gouk Hanyeoreum Bae Myoungsoo Jung Computer Architecture and Memory Systems Laboratory Korea Advanced Institute of Science and Technology (KAIST)

We present GraphTensor, a comprehensive open-source framework that supports efficient parallel neural network processing on large graphs. GraphTensor offers a set of easy-to-use programming primitives that appreciate both graph and neural network execution behaviors from the beginning (graph sampling) to the end (dense data processing). Our framework runs diverse graph neural network (GNN) models in a destination-centric, feature-wise manner, which can significantly shorten training execution times in a GPU. In addition, GraphTensor rearranges multiple GNN kernels based on their system hyperparameters in a self-governing manner, thereby reducing the processing dimensionality and the latencies further. From the end-to-end execution viewpoint, GraphTensor significantly shortens the service-level GNN latency by applying pipeline parallelism for efficient graph dataset preprocessing. Our evaluation shows that GraphTensor exhibits 1.4× better training performance than emerging GNN frameworks under the execution of large-scale, real-world graph workloads. For the end-to-end services, GraphTensor reduces training latencies of an advanced version of the GNN frameworks (optimized for multi-threaded graph sampling) by 2.4×, on average.

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Smartphone-based colorimetric detection of formaldehyde in the air

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Building Simulation 2024年第11期17卷 2007-2015页

作者： Meng Yang Jin Ye Tao Yu Ying Song Hua Qian Tianyi Liu Yang Chen Junqi Wang Shi-jie Cao Cong Liu School of Energy and Environment Southeast UniversityNanjing210096China School of Energy and Power Jiangsu University of Science and TechnologyZhenjiangJiangsu212100China Wuhan Second Ship Design and Research Institute Wuhan430205China Hubei Provincial Engineering and Technology Research Center for Food Quality and Safety Test Hubei Provincial Institute for Food Supervision and TestWuhan430075China Laboratory of Image Science and Technology the School of Computer Science and EngineeringSoutheast UniversityNanjingChina Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Southeast UniversityNanjingChina School of Cyber Science and Engineering Southeast UniversityNanjingChina Key Laboratory of Computer Network and Information Integration Southeast UniversityMinistry of EducationNanjingChina School of Architecture Southeast UniversityNanjingChina Jiangsu Province Engineering Research Center of Urban Heat and Pollution Control Southeast UniversityNanjingChina Global Centre for Clean Air Research(GCARE) University of SurreyGuildfordUK

Adverse impacts of exposure to formaldehyde on human health significantly increases attention in monitoring formaldehyde concentrations in the *** formaldehyde detection methods typically rely on large and costly instruments and requires high skills of expertise,preventing it from being widely accessible to *** study introduced a novel approach utilizing smartphone-based colorimetric *** of green channel signals of digital images by a smartphone successfully capture variation of purple color of 4-amino-3-hydrazino-5-mercapto-1,2,4-triazol solution,which is proportional to formaldehyde *** is because that green and purple are complimentary color pairs.A calibration curve was established between green channel signals and formaldehyde concentrations,with a correlation coefficient of *** limit of the smartphone-based method is 0.008 mg/m^(3).Measurement errors decrease as formaldehyde concentrations increase,with median relative errors of 34%,17%,and 6%for concentration ranges of 0–0.06 mg/m^(3),0.06–0.12 mg/m^(3),and 0.12–0.35 mg/m^(3),*** method replaced scientific instrumentation with ordinary items,greatly reducing cost and operation *** would provide an opportunity to realize onsite measurements for formaldehyde by occupants themselves and increase awareness of air quality for better health protection.

关键词： indoor air quality VOC RGB color identification machine vision

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Makespan and Security-Aware Workflow Scheduling for Cloud Service Cost Minimization Using Firefly Optimizer 22nd

Makespan and Security-Aware Workflow Scheduling for Cloud ...

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22nd International Conference on Algorithms and architectures for Parallel Processing, ICA3PP 2022

作者： Zhou, Chengliang Wang, Tian Li, Liying Sun, Jin Zhou, Junlong School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China National Trusted Embedded Software Engineering Technology Research Center East China Normal University Shanghai200062 China

ISBN: (纸本)9783031226762

As efficient commercial information technology, cloud computing has attracted more and more users to submit their requests to the cloud platform and pay for them based on the amount and quality of services. One of the most important concerns of cloud service providers is to minimize the monetary cost for completing users’ requests while meeting constraints on the quality of services such as makespan and security. To solve this concern, this paper proposes a makespan and security-aware workflow scheduling method based on an improved firefly optimizer that consists of a new solution initialization scheme, a firefly position updating scheme, a firefly-to-solution mapping operator, and two task-to-virtual machine assignment schemes. We carry out extensive simulation experiments on real-world workflows to validate our proposed workflow scheduling method. The results reveal that the monetary cost reduction achieved by our method can be up to 54.0% compared to a baseline and two state-of-the-art approaches. © 2023, Springer Nature Switzerland AG.

关键词： Cloud computing

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Data Availability Optimization for Cyber-Physical Systems 15

Data Availability Optimization for Cyber-Physical Systems

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2022 IEEE Congress on Cybermatics: 15th IEEE International Conferences on Internet of Things, iThings 2022, 18th IEEE International Conferences on Green Computing and Communications, GreenCom 2022, 2022 IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2022 and 8th IEEE International Conference on Smart Data, SmartData 2022

作者： Li, Liying Cong, Peijin Zhou, Junlong Gu, Zonghua Li, Keqin School of Computer Science and Engineering Nanjing University of Science and Technology China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Department of Applied Physics and Electronics Ume˚a University Sweden Department of Computer Science State University of New York United States

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

As the backbone of Industry 4.0, Cyber-Physical Systems (CPSs) have attracted extensive attention from industry, academia, and government. Missing data is a common problem in CPS data processing and may cause incorrect results and eventually serious malfunction. Existing data availability optimization methods either rely on a large amount of complete training data or suffer from poor performance. To solve these problems, this paper proposes an iterative data availability optimization method for CPSs. Specifically, the proposed method first pre-processes the raw dataset by using a Singular Value Decomposition-based feature selection approach to identify crucial features and reduce computation overheads. It then makes an initial guess for missing values via a designed K-Means-based imputation approach. The appropriate initial estimation decreases the probability of the proposed method falling into the local optimum. Finally, the proposed method iteratively estimates missing data based on the Orthogonal Matching Pursuit algorithm. The proposed method optimizes data availability by accurately imputing missing values. Simulation results on two datasets demonstrate that compared to multiple state-of-the-art approaches, the proposed data availability optimization method can reduce imputation error by up to 99.65%. © 2022 IEEE.

关键词： Iterative methods

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Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding

Modeling Layout Reading Order as Ordering Relations for Visu...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Zhang, Chong Tu, Yi Zhao, Yixi Yuan, Chenshu Chen, Huan Zhang, Yue Chai, Mingxu Guo, Ya Zhu, Huijia Zhang, Qi Gui, Tao School of Computer Science Fudan University Shanghai China Shanghai Key Laboratory of Intelligent Information Processing Shanghai China Ant Tiansuan Security Lab Ant Group Hangzhou China School of Statistics and Data Science Nankai University Tianjin China Institute of Modern Languages and Linguistics Fudan University Shanghai China

ISBN: (纸本)9798891761643

Modeling and leveraging layout reading order in visually-rich documents (VrDs) is critical in document intelligence as it captures the rich structure semantics within documents. Previous works typically formulated layout reading order as a permutation of layout elements, i.e. a sequence containing all the layout elements. However, we argue that this formulation does not adequately convey the complete reading order information in the layout, which may potentially lead to performance decline in downstream VrD tasks. To address this issue, we propose to model the layout reading order as ordering relations over the set of layout elements, which have sufficient expressive capability for the complete reading order information. To enable empirical evaluation on methods towards the improved form of reading order prediction (ROP), we establish a comprehensive benchmark dataset including the reading order annotation as relations over layout elements, together with a relation-extraction-based method that outperforms previous methods. Moreover, to highlight the practical benefits of introducing the improved form of layout reading order, we propose a reading-order-relation-enhancing pipeline to improve model performance on any arbitrary VrD task by introducing additional reading order relation inputs. Comprehensive results demonstrate that the pipeline generally benefits downstream VrD tasks: (1) with utilizing the reading order relation information, the enhanced downstream models achieve SOTA results on both two task settings of the targeted dataset;(2) with utilizing the pseudo reading order information generated by the proposed ROP model, the performance of the enhanced models has improved across all three models and eight cross-domain VrD-IE/QA task settings without targeted optimization. © 2024 Association for Computational Linguistics.

关键词： Semantics

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Unveiling and Consulting Core Experts in Retrieval-Augmented MoE-based LLMs

Unveiling and Consulting Core Experts in Retrieval-Augmented...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Zhou, Xin Nie, Ping Guo, Yiwen Wei, Haojie Zhang, Zhanqiu Minervini, Pasquale Ma, Ruotian Gui, Tao Zhang, Qi Huang, Xuanjing School of Computer Science Fudan University Shanghai China LightSpeed Studios Tencent China Institute of Modern Languages and Linguistics Fudan University Shanghai China Key Laboratory of Intelligent Information Processing Fudan University Shanghai China School of Informatics and ELLIS University of Edinburgh United Kingdom

ISBN: (纸本)9798891761643

Retrieval-Augmented Generation (RAG) significantly improved the ability of Large Language Models (LLMs) to solve knowledge-intensive tasks. While existing research seeks to enhance RAG performance by retrieving higher-quality documents or designing RAG-specific LLMs, the internal mechanisms within LLMs that contribute to the effectiveness of RAG systems remain underexplored. In this paper, we aim to investigate these internal mechanisms within the popular Mixture-of-Expert (MoE)based LLMs and demonstrate how to improve RAG by examining expert activations in these LLMs. Our controlled experiments reveal that several core groups of experts are primarily responsible for RAG-related behaviors. The activation of these core experts can signify the model's inclination towards external/internal knowledge and adjust its behavior. For instance, we identify core experts that can (1) indicate the sufficiency of the model's internal knowledge, (2) assess the quality of retrieved documents, and (3) enhance the model's ability to utilize context. Based on these findings, we propose several strategies to enhance RAG's efficiency and effectiveness through expert activation. Experimental results across various datasets and MoE-based LLMs show the effectiveness of our method. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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WIP: An Engaging Undergraduate Intro to Model Checking in Software Engineering Using TLA+

WIP: An Engaging Undergraduate Intro to Model Checking in So...

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Frontiers in Education (FIE) Conference

作者： Konstantin Läufer Gunda Mertin George K. Thiruvathukal Department of Computer Science Software and Systems Laboratory Loyola University Chicago Institute for Software Engineering and Programming Languages University of Lübeck

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions $(\text{TLA}^{+})$ , into computer science education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts. Aims: We aim to (1) qualitatively assess the state of formal methods in computer science programs, (2) construct level-appropriate examples that could be included midway into one's undergraduate studies, (3) demonstrate how to address successive “failuresy” through progressively stringent safety and liveness requirements, and (4) establish an ongoing framework for assessing interest and relevance among students. Methods: We detail our pedagogical strategy for embedding $\text { TLA }^{+}$ into an intermediate course on formal methods at our institution. After starting with a refresher on mathematical logic, students specify the rules of simple puzzles in $\text { TLA }^{+}$ and use its included model checker (known as TLC) to find a solution. We gradually escalate to more complex, dynamic, event-driven systems, such as the control logic of a microwave oven, where students will study safety and liveness requirements. We subsequently discuss explicit concurrency, along with thread safety and deadlock avoidance, by modeling bounded counters and buffers. Results: Our initial findings suggest that through careful curricular design and choice of examples and tools, it is possible to inspire and cultivate a new generation of software engineers proficient in formal methods. Conclusions: Our initial efforts suggest that 84% of our students had a positive experience in our formal methods course. Our future plans include a longitudi

关键词： computer science Open Access Model checking System recovery Software Safety Logic Reliability Proposals Software engineering

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BuildEnVR: An Immersive Analysis System for Environmental Field 30

BuildEnVR: An Immersive Analysis System for Environmental Fi...

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30th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2024

作者： Zhou, Zhenghan Liu, Kebin Xie, Yantong Jin, Hangxu Liu, Shi Wang, Ruiqing Zhao, Haitian Lin, Borong Mu, Xiaofang Qi, Hui Tsinghua University Global Innovation Exchange China Fuzhou Fuyao Institute for Advanced Study China Carnegie Mellon University School of Architecture United States Tsinghua University School of Architecture China Taiyuan Normal University College of Computer Science and Technology China Shanxi Key Laboratory of Intelligent Optimization Computing and Blockchain Technology China

ISBN: (纸本)9798331515966

Amidst global warming and escalating extreme weather events, indoor environmental quality's impact on human health and public hygiene gains prominence. Environmental parameters exist essentially as fields, which are characterized by high dimensionality, density and complexity, and contain massive amounts of information in space. To facilitate visualization and analysis of indoor environmental field, we design and implement BuildEnVR, an immersive analysis system by virtual reality, enabling remote analysis of real-time and historical environmental field data. Grounded in user needs and cognitive psychology, three visualization modes emerge: the Virtual Sensor mode enables users to access perceptual data in real-time at any 3D coordinates in ambient space, the 4D Heatmap mode visualizes spatial variations and trends over time in environmental field data, and the Synaesthesia mode realizes the fusion display of multi-dimensional environmental field data, allowing users to quickly understand the overall condition of the indoor environment with a low cognitive load. Extensive user surveys validate BuildEnVR's intuitiveness and precision, and it is suitable for both experts and general users. © 2024 IEEE.

关键词： Indoor air pollution

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