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Deciphering urban traffic impacts on air quality by deep learning and emission inventory

Journal of Environmental Sciences 2023年第2期124卷 745-757页

作者： Wenjie Du Lianliang Chen Haoran Wang Ziyang Shan Zhengyang Zhou Wenwei Li Yang Wang School of Software Engineering University of Science and Technology of ChinaHefei 230026China Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhou 215123China Alibaba Inc. Hangzhou 310052China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230026China CAS Key Laboratory of Urban Pollutant Conversion Department of environmental science and EngineeringUniversity of Science and Technology of ChinaHefei 230026China USTC-CityU Joint Advanced Research Center Suzhou 215123China

Air pollution is a major obstacle to future sustainability,and traffic pollution has become a large drag on the sustainable developments of future ***,combined with the large volume of real-time monitoring data,we propose a deep learning model,iDeepAir,to predict surface-level PM2.5 concentration in Shanghai megacity and link with MEIC emission inventory creatively to decipher urban traffic impacts on air *** model exhibits high-fidelity in reproducing pollutant concentrations and reduces the MAE from 25.355μg/m^(3) to 12.283μg/m^(3) compared with other *** identifies the ranking of major factors,local meteorological conditions have become a nonnegligible ***-wise relevance propagation(LRP)is used here to enhance the interpretability of the model and we visualize and analyze the reasons for the different correlation between traffic density and PM_(2.5) concentration in various regions of ***,As the strict and effective industrial emission reduction measurements implementing in China,the contribution of urban traffic to PM_(2.5) formation calculated by combining MEIC emission inventory and LRP is gradually increasing from 18.03%in 2011 to 24.37% in 2017 in Shanghai,and the impact of traffic emissions would be ever-prominent in 2030 according to our *** also infer that the promotion of vehicular electrification would achieve further alleviation of PM_(2.5) about 8.45% by 2030 *** insights are of great significance to provide the decision-making basis for accurate and high-efficient traffic management and urban pollution control,and eventually benefit people’s lives and high-quality sustainable developments of cities.

关键词： PM_(2.5)concentration forecast Traffic emissions Deep learning Attention mechanism New energy vehicles

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CAC 2.0: A Corrupt and Correct Logic Locking Technique Resilient to Structural Analysis Attacks 25

CAC 2.0: A Corrupt and Correct Logic Locking Technique Resil...

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25th IEEE Latin American Test Symposium, LATS 2024

作者： Aksoy, Levent Yasin, Muhammad Pagliarini, Samuel National University Of Sciences And Technology Department Of Computer And Software Engineering Islamabad Pakistan Tallinn University Of Technology Department Of Computer Systems Tallinn Estonia Carnegie Mellon University Department Of Electrical And Computer Engineering Pittsburgh United States

ISBN: (纸本)9798350365559

Logic locking proposed to protect integrated circuits from serious hardware threats has been studied extensively over a decade. In these years, many logic locking techniques have been proven to be broken. The state-of-the-art logic locking techniques, including the prominent corrupt and correct (CAC) technique, are resilient to satisfiability (SAT)-based and removal attacks, but vulnerable to structural analysis attacks. To overcome this drawback, this paper introduces an improved version of CAC, called CAC 2.0, which increases the search space of structural analysis attacks using obfuscation. To do so, CAC 2.0 locks the original circuit twice, one after another, on different nodes with different number of protected primary inputs using CAC, while hiding original protected primary inputs among decoy primary inputs. This paper also introduces an open source logic locking tool, called HIID, equipped with well-known techniques including CAC 2.0. Our experiments show that CAC 2.0 is resilient to existing SAT-based, removal, and structural analysis attacks. To achieve this, it increases the number of key inputs at most 4× and the gate-level area between 30.2% and 0.8% on circuits with low and high complexity with respect to CAC. © 2024 IEEE.

关键词： Structural analysis

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GuidedNet: Semi-Supervised Multi-Organ Segmentation via Labeled Data Guide Unlabeled Data 24

GuidedNet: Semi-Supervised Multi-Organ Segmentation via Labe...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Zhao, Haochen Meng, Hui Yang, Deqian Xie, Xiaozheng Wu, Xiaoze Li, Qingfeng Niu, Jianwei School of Computer Science and Engineering Beihang University Beijing China School of Intelligent Science and Technology Hangzhou Institute for Advanced Study University of the Chinese Academy of Sciences Hangzhou China Institute of Software Hangzhou Institute for Advanced Study University of the Chinese Academy of Sciences Hangzhou China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China School of Software Beihang University Beijing China

ISBN: (纸本)9798400706868

Semi-supervised multi-organ medical image segmentation aids physicians in improving disease diagnosis and treatment planning and reduces the time and effort required for organ *** state-of-the-art methods train the labeled data with ground truths and train the unlabeled data with pseudo-labels. However, the two training flows are separate, which does not reflect the interrelationship between labeled and unlabeled *** address this issue, we propose a semi-supervised multi-organ segmentation method called GuidedNet, which leverages the knowledge from labeled data to guide the training of unlabeled data. The primary goals of this study are to improve the quality of pseudo-labels for unlabeled data and to enhance the network's learning capability for both small and complex organs.A key concept is that voxel features from labeled and unlabeled data that are close to each other in the feature space are more likely to belong to the same *** this basis, a 3D Consistent Gaussian Mixture Model (3D-CGMM) is designed to leverage the feature distributions from labeled data to rectify the generated ***, we introduce a Knowledge Transfer Cross Pseudo Supervision (KT-CPS) strategy, which leverages the prior knowledge obtained from the labeled data to guide the training of the unlabeled data, thereby improving the segmentation accuracy for both small and complex organs. Extensive experiments on two public datasets, FLARE22 and AMOS, demonstrated that GuidedNet is capable of achieving state-of-the-art performance. © 2024 ACM.

关键词： Self-supervised learning

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Rustcheck: Safety Enhancement of Unsafe Rust via Dynamic Program Analysis 23

Rustcheck: Safety Enhancement of Unsafe Rust via Dynamic Pro...

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23rd IEEE International Conference on software Quality, Reliability, and Security Companion, QRS-C 2023

作者： Xia, Lei Wu, Yufei Hua, Baojian School of Software Engineering University of Science and Technology of China Hefei230026 China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China

ISBN: (纸本)9798350359398

Rust is a modern system-level programming language providing strong security guarantees, which has been widely applied in building software infrastructures. However, unsafe Rust, a language feature introduced for programming flexibility and efficiency, can be prone to memory vulnerabilities due to the lack of compile-Time and run-Time checks. Worse yet, it is challenging to diagnose such memory vulnerabilities in Rust programs, due to the subtle interactions between the safe and unsafe code. This paper presents Rustcheck, the first memory safety enhancement framework for dynamic program analysis of Rust programs. The key idea of Rustcheck is to dynamically detect memory safety issues caused by the improper use of unsafe Rust through static instrumentations. We have implemented a software prototype for Rustcheck and conducted experiments to evaluate the effectiveness and performance of it by applying Rustcheck to 56 CVES from real-world Rust projects. And experimental results showed that Rustcheck can successfully detect all of 65 memory vulnerabilities in CVEs, with low runtime overhead (3.30% on average) to the Rust projects being checked. © 2023 IEEE.

关键词： software prototyping

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Swelling and erosion assisted sustained release of tea polyphenol from antibacterial ultrahigh molecular weight polyethylene for joint replacement

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Chinese Chemical Letters 2025年第2期36卷 316-320页

作者： Yue Ren Kang Li Yi-Zi Wang Shao-Peng Zhao Shu-Min Pan Haojie Fu Mengfan Jing Yaming Wang Fengyuan Yang Chuntai Liu State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450002China Tianjian Laboratory of Advanced Biomedical Sciences Academy of Medical SciencesZhengzhou UniversityZhengzhou 450000China Department of Stomatology The First Affiliated Hospital of Zhengzhou UniversityZhengzhou 450000China

The considerable hazard posed by periprosthetic joint infections underlines the urgent need for the rapid advancement of in-situ drug delivery systems within joint ***,the pursuit of sustained antibacterial efficacy remains a formidable *** this context,we proposed a novel strategy that leverages swelling and erosion mechanisms to facilitate drug release of drug-loaded ultrahigh molecular weight polyethylene(UHMWPE),thereby ensuring its long-lasting antibacterial *** oxide(PEO),a hydrophilic polymer with fast hydrating ability and high swelling capacity,was incorporated in UHMWPE alongside the antibacterial tea polyphenol(epigallocatechin gallate,EGCG as representative).The swelling of PEO enhanced water infiltration into the matrix,while the erosion of PEO balanced the release of the encapsulated EGCG,resulting in a steady *** behavior was supported by the EGCG release profiles and the corresponding fitted release kinetic *** demonstrated by segmented antibacterial assessments,the antibacterial efficiency was enhanced 2to 3 times in the PEO/EGCG/UHMWPE composite compared to that of EGCG/***,the PEO/EGCG/UHMWPE composite exhibited favorable biocompatibility and mechanical performance,making it a potential candidate for the development of drug-releasing joint implants to combat prosthetic bacterial infections.

关键词： Tea polyphenol Antibacterial PEO UHMWPE Joint replacement

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Archer: Adaptive Memory Compression with Page-Association-Rule Awareness for High-Speed Response of Mobile Devices 23

Archer: Adaptive Memory Compression with Page-Association-Ru...

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23rd USENIX Conference on File and Storage Technologies, FAST 2025

作者： Li, Changlong Zhu, Zongwei Wang, Chao Liu, Fangming Xu, Fei Sha, Edwin H.-M. Zhou, Xuehai School of Computer Science and Technology East China Normal University China Jianghuai Advance Technology Center Hefei230026 China MoE Engineering Research Center of Hardware/Software Co-Design Technology and Application China School of Software Engineering University of Science and Technology of China Hefei230026 China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China Huazhong University of Science and Technology China Peng Cheng Laboratory China

ISBN: (纸本)9781939133458

In mobile systems, memory can be compressed page-by-page to save space. This approach is widely adopted because memory data is accessed by page. However, this paper shows that the system response speed is significantly limited by page-grained compression. In this paper, we observe that approximately a quarter of anonymous memory pages are highly correlated, even though the association is implicit. Inspired by this, we propose Archer, an association-rule-aware memory compression framework in mobile systems. Archer demonstrates that memory in mobile devices should be compressed using flexible granularity, rather than relying solely on traditional page compression. To further integrate association-rule mining techniques into system design, we redesign the LRU mechanism and propose an adaptive memory compression region. Experimental results show that the average app launching speed is 1.55x faster when enabling Archer, and the average photographic speed and frame rate increase by 1.42x and 1.31x, respectively, compared to the state-of-the-art. © 2025 FAST. All Rights Reserved.

关键词： Portable equipment

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On Configuration Sequences in Feature Models 24

On Configuration Sequences in Feature Models

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18th International Working Conference on Variability Modelling of software-Intensive systems, VaMoS 2024

作者： Meixner, Kristof Feichtinger, Kevin Greiner, Sandra Rabiser, Rick Cdl Sqi Ise Tu Wien Austria Crc 1608 Kastel Dependability of Software-intensive Systems Karlsruhe Institute of Technology Germany Software Engineering Group Institute of Computer Science University of Bern Switzerland Cdl VaSiCS Lit Cps Lab Jku Linz Austria

ISBN: (纸本)9798400708770

Feature models are the de-facto standard in product line engineering to capture the commonalities and variability of systems. However, feature models provide little user guidance during configuration and are unable to represent configuration sequences. A configuration sequence refers to the specific order and combination of features that can be selected when configuring a product line. While mechanisms, such as staged configuration and configuration workflows, exist, we argue that the effort to implement these mechanisms does not pay off for small feature models. This paper motivates the use of configuration sequences for feature models to support better user guidance even for a single feature model. We highlight the need for such user guidance and configuration sequences with a real-world use case. © 2024 ACM.

关键词： Configuration Sequence Feature Models User Guidance.

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On-demand imidazolidinyl urea-based tissue-like,self-healable,and antibacterial hydrogels for infectious wound care

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Bioactive Materials 2025年第2期44卷 116-130页

作者： Qi Wu Krishanu Ghosal Nadine Kana’an Shounak Roy Nagham Rashed Ranabir Majumder Mahitosh Mandal Liang Gao Shady Farah The Laboratory for Advanced Functional/Medicinal Polymers&Smart Drug Delivery Technologies The Wolfson Faculty of Chemical EngineeringTechnion-Israel Institute of TechnologyHaifa3200003Israel School of Medical Science and Technology Indian Institute of Technology KharagpurWest Bengal721302India Jinan Key Laboratory of High Performance Industrial Software Jinan Institute of Supercomputing TechnologyJinan250000China The Russell Berrie Nanotechnology Institute Technion-Israel Institute of TechnologyHaifa3200003Israel

Bacterial wound infections are a growing challenge in healthcare,posing severe risks like systemic infection,organ failure,and sepsis,with projections predicting over 10 million deaths annually by *** hydrogels,with adaptable extracellular matrix-like features,are emerging as promising solutions for treating infectious ***,the antibacterial properties of most of these hydrogels are largely attributed to extrinsic agents,and their mechanisms of action remain poorly *** we introduce for the first time,modified imidazolidinyl urea(IU)as the polymeric backbone for developing tissue-like antibacterial ***-designed hydrogels behave tissue-like mechanical features,outstanding antifreeze behavior,and rapid self-healing *** dynamics(MD)simulation and density functional theory(DFT)calculation were employed to well-understand the extent of H-bonding and metal-ligand coordination to finetune hydrogels’*** vitro studies suggest good biocompatibility of hydrogels against mouse fibroblasts&human skin,lung,and red blood cells,with potential wound healing ***,the hydrogels exhibit good 3D printability and remarkable antibacterial activity,attributed to concentration dependent ROS genera-tion,oxidative stress induction,and subsequent disruption of bacterial *** top of that,in vitro biofilm studies confirmed that developed hydrogels are effective in preventing biofilm ***,these tissue-mimetic hydrogels present a promising and effective platform for accelerating wound healing while simulta-neously controlling bacterial infections,offering hope for the future of wound care.

关键词： Imidazolidinyl urea Self-healing Antibacterial hydrogel Antibiofilm hydrogel Wound care

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Towards optimized tensor code generation for deep learning on sunway many-core processor

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Frontiers of Computer Science 2024年第2期18卷 1-15页

作者： Mingzhen LI Changxi LIU Jianjin LIAO Xuegui ZHENG Hailong YANG Rujun SUN Jun XU Lin GAN Guangwen YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China National University of Singapore Singapore 119077Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214000China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing 100854China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware *** the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning *** paper combines the trends in these two ***,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as *** addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on *** experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative *** work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in *** believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.

关键词： sunway processor deep learning compiler code generation performance optimization

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Intrusion Detection Mechanism Using Deep Learning 5

Intrusion Detection Mechanism Using Deep Learning

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5th International Conference on IoT Based Control Networks and Intelligent systems, ICICNIS 2024

作者： Ananthi, P. Nirmaladevi, K. Naveen Kumar, S. Kongu Engineering College Department of Computer Technology-PG Tamilnadu Erode638060 India Madanapalle Institute of Technology & Science Department of Computer Applications India M.Sc Software Systems Kongu Engineering College Erode India

ISBN: (纸本)9798331518097

In today's connected and data-driven world, networks and digital systems need to be protected from malicious attacks. The effectiveness of conventional Intrusion Detection systems (IDS) in recognizing and impeding novel threats and intricate methodologies has its limits. This study introduces a new method for improving network security by using deep learning techniques in the design and development of an intrusion detection system (IDS). The suggested Intrusion Detection System uses deep learning techniques, specifically Long Short Term Memory (LSTM) and Convolutional Neural Networks (CNNs), to identify and react to known and new security threats. Data can be taught to be encoded into a lower-dimensional representation and then decoded back into its original form using autoencoders (AEs). Autoencoders are a cutting-edge intrusion detection system that can lower false positives and raise overall detection accuracy because of their capacity to automatically learn from and adjust to the ever-changing threat landscape. They enhance computer networks capacity to spot irregularities and possible security threats. With the deep learning model obtaining a high accuracy of 99% in real-world threat detection, the results show that deep learning is effective in developing intrusion detection systems. © 2024 IEEE.

关键词： Network intrusion

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