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15th International Conference on Spatial Information Theory, COSIT 2022

作者： Wang, Yadi Pan, Yicheng Ma, Meng Wang, Ping School of Software and Microelectronics Peking University Beijing China School of Electronics Engineering and Computer Science Peking University Beijing China National Engineering Research Center for Software Engineering Peking University Beijing China

ISBN: (纸本)9783959772570

Various participants in urban traffic systems intertwine a highly complicated coupling network. An interpretable analysis of underlying correlations is one of the keys to understanding traffic anomalies. Unfortunately, abnormal situation analysis in real scenarios faces severe limitations in negative sample deficiency, data integrity, and verifiability. In view of this, we developed a simulation tool - the Traffic Anomaly Situation Simulator (TASS). Through configurable scripts, TASS simulates real traffic networks by road editing, data collection, and fault injection. Given the generated cases, we designed a dynamic causal discovery algorithm, Dycause-Traffic, to demonstrate the features of causality in traffic anomalies. © 2022 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

关键词： Traffic congestion

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Face Detection and Recognition in Near Infra-Red Image 6

Face Detection and Recognition in Near Infra-Red Image

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6th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2022

作者： Shet, Athreya V Bs, Chinmay Shetty, Anvithkumar A Shankar, T. Hemavathy, R. Ramakanth, P. R v College of Engineering Computer Science and Engineering Department Bengaluru India R v College of Engineering Research and Projects Center for Cctv Research Bengaluru India

ISBN: (纸本)9781665456982

Face detection and recognition is an extensively researched topic in Artificial Intelligence. The use of AI in detection and mapping of faces or any objects can reduce the time spent in video auditing. A face recognition system maps facial traits from a picture or video using biometrics. To identify a match, it compares the data with a database of recognized faces. In any situation, facial recognition technology can intelligently assist in confirming a person's identification. Infra-Red camera or night vision in security cameras uses infrared light to capture near-infrared images in the dark and also through fog, dust and smoke, such that camera works in all conditions. Cameras operating in visual spectrum will work well only when the image capturing works well, but IR camera images can capture quality images at all times. The paper presents our work in creating a facial recognition system in near-infrared images from a surveillance camera, in which database was created in live Close Circuit Television footage for different individuals and the same was tested with different face detection techniques, classify images using the facial embeddings from VGG-face model to determine the faces. © 2022 IEEE.

关键词： Face recognition

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Pose Estimation of Spacecraft Using Dual Transformers and Efficient Bayesian Hyperparameter Optimization

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International Journal of Advanced computer science and Applications 2025年第4期16卷 629-644页

作者： Raja, N. Kannaiya Ramesh, Janjhyam Venkata Naga El-Ebiary, Yousef A. Baker Muniyandy, Elangovan Reddy, N. Konda Kumar, Vanipenta Ravi Devarasetty, Prasad School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh Bhopal466114 India Department of CSE Graphic Era Hill University Dehradun248002 India Department of CSE Graphic Era Deemed To Be University Uttarakhand Dehradun248002 India Faculty of Informatics and Computing UniSZA University Malaysia Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602 105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of Engineering Mathematics K L University Greenfields Guntur Dist Andhra Pradesh Vaddeswaram522302 India Department of Mathematics Annamacharya University New Boyanapalli Rajampet India Department of Computer Science and Engineering DVR & Dr HS MIC College of Technology Andhra Pradesh Kanchikacherla India

Spacecraft pose estimation is an essential contribution to facilitating central space mission activities like autonomous navigation, rendezvous, docking, and on-orbit servicing. Nonetheless, methods like Convolutional Neural Networks (CNNs), Simultaneous Localization and Mapping (SLAM), and Particle Filtering suffer significant drawbacks when implemented in space. Such techniques tend to have high computational complexity, low domain generalization capacity for varied or unknown conditions (domain generalization problem), and accuracy loss with noise from the space environment causes such as fluctuating lighting, sensor limitations, and background interference. In order to overcome these challenges, this study suggests a new solution through the combination of a Dual-Channel Transformer Network with Bayesian Optimization methods. The innovation is at the center with the utilization of EfficientNet, augmented with squeeze-and-excitation attention modules, to extract feature-rich representations without sacrificing computational efficiency. The dual-channel architecture dissects satellite pose estimation into two dedicated streams—translational data prediction and orientation estimation via quaternion-based activation functions for rotational precision. Activation maps are transformed into transformer-compatible sequences via 1×1 convolutions, allowing successful learning in the transformer's encoder-decoder system. To maximize model performance, Bayesian Optimization with Gaussian Process Regression and the Upper Confidence Bound (UCB) acquisition function makes the optimal hyperparameter selection with fewer queries, conserving time and resources. This entire framework, used here in Python and verified with the SLAB Satellite Pose Estimation Challenge dataset, had an outstanding Mean IOU of 0.9610, reflecting higher accuracy compared to standard models. In total, this research sets a new standard for spacecraft pose estimation, by marrying the versatility of deep le

关键词： Convolutional neural networks

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An Effective Automated Speaking Assessment Approach to Mitigating Data Scarcity and Imbalanced Distribution

An Effective Automated Speaking Assessment Approach to Mitig...

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2024 Findings of the Association for Computational Linguistics: NAACL 2024

作者： Lo, Tien-Hong Chao, Fu-An Wu, Tzu-I Sung, Yao-Ting Chen, Berlin Department of Computer Science and Information Engineering National Taiwan Normal University Taiwan Research Center for Psychological and Educational Testing National Taiwan Normal University Taiwan Department of Educational Psychology and Counseling National Taiwan Normal University Taiwan

ISBN: (纸本)9798891761193

Automated speaking assessment (ASA) typically involves automatic speech recognition (ASR) and hand-crafted feature extraction from the ASR transcript of a learner's speech. Recently, self-supervised learning (SSL) has shown stellar performance compared to traditional methods. However, SSL-based ASA systems are faced with at least three data-related challenges: limited annotated data, uneven distribution of learner proficiency levels and non-uniform score intervals between different CEFR proficiency levels. To address these challenges, we explore the use of two novel modeling strategies: metric-based classification and loss re-weighting, leveraging distinct SSL-based embedding features. Extensive experimental results on the ICNALE benchmark dataset suggest that our approach can outperform existing strong baselines by a sizable margin, achieving a significant improvement of more than 10% in CEFR prediction accuracy. © 2024 Association for Computational Linguistics.

关键词： Speech recognition

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Fuzzing JavaScript Engines with Diversified Mutation Strategies 1

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25th International Conference on Information Security Applications, WISA 2024

作者： Shie, Cheng-Han Fang, Pin-Huang Fan, Chun-I Department of Computer Science and Engineering National Sun Yat-sen University Kaohsiung804201 Taiwan Information Security Research Center National Sun Yat-sen University Kaohsiung804201 Taiwan Intelligent Electronic Commerce Research Center National Sun Yat-sen University Kaohsiung804201 Taiwan

ISBN: (数字)9789819616244

ISBN: (纸本)9789819616237

Current fuzzers for JavaScript (JS) engines often produce test cases that are syntactically correct but semantically incorrect, hindering efficient crash discovery. To address this issue, we propose three mutation methods: simple mutation, state mutation, and Just-In-Time (JIT) compilation optimization triggering. The combination of these methods significantly increases the variety of seed mutations, distinguishing our approach from other fuzzers. Additionally, we analyze each JS engine to identify conditions that trigger JIT optimization, incorporating these conditions into the mutation methods to enhance path coverage. This approach achieves over 20% branch coverage, at least 5% higher than other fuzzers, with a semantic correctness rate above 80%, reducing time wasted on semantic errors. Finally, our method nearly doubles the crash discovery rate compared to other fuzzers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Semantics

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LOPO: An Out-of-order Layer Pulling Orchestration Strategy for Fast Microservice Startup 42

LOPO: An Out-of-order Layer Pulling Orchestration Strategy f...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Gu, Lin Huang, Junhao Huang, Shaoxing Zeng, Deze Li, Bo Jin, Hai Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Wuhan China China University of Geosciences School of Computer Science Wuhan China Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9798350334142

Container based microservices have been widely applied to promote the cloud elasticity. The mainstream Docker containers are structured in layers, which are organized in stack with bottom-up dependency. To start a microservice, the required layers are pulled from a remote registry and stored on its host server, following the layer dependency order. This incurs long microservice startup time and hinders the performance efficiency. In this paper, we discover that, for the first time, the layer pulling order can be adjusted to accelerate the microservice startup. Specifically, we address the problem on microservice layer pulling orchestration for startup time minimization and prove it as NP-hard. We propose a Longest-chain based Out-of-order layer Pulling Orchestration (LOPO) strategy with low computational complexity and guaranteed approximation ratio. Through extensive real-world trace driven experiments, we verify the efficiency of our LOPO and demonstrate that it reduces the microservice startup time by 22.71% on average in comparison with state-of-the-art solutions. © 2023 IEEE.

关键词： Containers

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Slotted ALOHA with Code Combining for IoT Networks 3

Slotted ALOHA with Code Combining for IoT Networks

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3rd IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2023

作者： Tyrovolas, Dimitrios Chrysologou, Athanasios Chondrogiannis, Georgios Tegos, Sotiris Mekikis, Prodromos-Vasileios Diamantoulakis, Panagiotis Ioannidis, Sotiris Liaskos, Christos Chatzidiamantis, Nestor Karagiannidis, George Aristotle University of Thessaloniki Dept. of Electrical and Computer Engineering Thessaloniki Greece Technical University of Chania Dept. of Electrical and Computer Engineering Chania Greece University of Ioannina Computer Science Engineering Department Ioannina Greece Cyber Security Systems and Applied Ai Research Center Lebanon

ISBN: (纸本)9798350333732

Internet of Things (IoT) networks are expected to be a key enabler technology for smart cities, due to their ability to offer real-time monitoring. In this work, we propose a novel medium access control (MAC) protocol, inspired by the synergy of slotted ALOHA and hybrid automatic repeat request with code combining (HARQ-CC), termed as code combining slotted ALOHA (CCSA), to improve the performance of IoT networks with multiple randomly deployed sensors. Specifically, we provide analytical closed-form expressions for the network's outage probability as well as for its average throughput when CCSA is applied. Finally, we provide simulation results that reveal the authenticity of the derived expressions and reveal the capabilities of HARQ-CC to significantly improve the network's performance when the sensors' access is based on a random access scheme. © 2023 IEEE.

关键词： Wireless sensor networks

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A disposable tartrazine sensor fabricated with a synchronously activated nanocomposite comprising gadolinium molybdate nanoflowers anchored on functionalized carbon nanofibers

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New Journal of Chemistry 2023年第6期48卷 2660-2672页

作者： Jayapaul, Abishek Sakthivel, Rajalakshmi Lin, Yu-Chien Dhawan, Udesh Liu, Xinke Wen, Hsiao-Wei Chung, Ren-Jei No. 1 Section 3 Zhongxiao E. Rd. Taipei10608 Taiwan Centre for the Cellular Microenvironment Division of Biomedical Engineering James Watt School of Engineering Mazumdar-Shaw Advanced Research Centre University of Glasgow GlasgowG116EW United Kingdom College of Materials Science and Engineering Chinese Engineering and Research Institute of Microelectronics Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Department of Food Science and Biotechnology National Chung Hsing University Taichung402202 Taiwan Food and Animal Product Safety Inspection Center National Chung Hsing University Taichung402202 Taiwan Taipei10608 Taiwan

Tartrazine (TRZ) is a synthetic food dye considered noxious to human health and a toxic environmental contaminant owing to the presence of a harmful azo group (-N 00000000 00000000 00000000 00000000 11111111 00000000 11111111 00000000 00000000 00000000 N-) in its chemical structure. The global necessity to prevent food contamination has led scientific researchers to develop disposable sensing platforms. This study aims to integrate nanotechnology with electrochemistry to fabricate a disposable screen-printed carbon electrode (SPCE) with a nanocomposite composed of gadolinium molybdate (Gd2MoO6) nanoflowers decorated on an enmeshed matrix of acid-functionalized carbon nanofibers (f-CNF). The hierarchal arrangement of distinct components in the nanocomposite is promoted by synergism through the formation of a hybrid heterojunction. This heterojunction in the electrode modifier activates the electrode to sense TRZ with a remarkable limit of detection (0.8 nmol L−1) and quantification (2 nmol L−1) over a broad linear range of 0.025 μM to 216.45 μM. Furthermore, the functional sensing ability of the proposed sensor was analyzed in various commercial food products. © 2024 The Royal Society of Chemistry.

关键词： Nanocomposites

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Contact optimisation strategy for wafer-scale field-effect transistors based on two-dimensional semiconductors

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Journal of Materials science & Technology 2023年第2期133卷 230-237页

作者： Ling Tong Xiaojiao Guo Zhangfeng Shen Lihui Zhou Jingyi Ma Xinyu Chen Honglei Chen Yin Xia Chuming Sheng Saifei Gou Die Wang Xinyu Wang Xiangqi Dong Yuxuan Zhu Xinzhi Zhang David Wei Zhang Sheng Dai Xi Li Peng Zhou Yangang Wang Wenzhong Bao State Key Laboratory of ASIC and System School of MicroelectronicsFudan UniversityShanghai 200433China College of Biological Chemical Science and EngineeringJiaxing UniversityJiaxing 314001China Key Laboratory for Advanced Materials and Feringa Nobel Prize Scientist Joint Research Center Institute of Fine ChemicalsSchool of Chemistry&Molecular EngineeringEast China University of Science and TechnologyShanghai 200237China State Key Laboratory of Surface Physics and Department of Physics Fudan UniversityShanghai 200433China

Two-dimensional(2D)semiconductors can be utilized to continually miniaturize nanoscale electronic ***,achieving a practical solution for satisfying electrical contact with 2D semiconductors remains *** this study,we developed a novel contact structure with transferred multilayer(t-ML)MoS 2 by integrating both edge and top *** in-situ plasma treatment for the edge of the MoS 2 channel and successive metal deposition,we achieved 16 times lower contact resistivity(22.8 kΩμm)than that of the top contacted *** thickness-dependent electrical measurement indicates that edge contact is highly effective with thick MoS 2 due to the alleviated current-crowding effect re-sulting from the small contact *** temperature-dependent transport measurement further confirms the effective minimization of the influence from the Schottky barrier and tunnelling ***,the simplified resistor network model and energy-band diagram were proposed to understand the carrier transport *** work provides a practical strategy for achieving excellent electrical contact between bulk metals and 2D semiconductors,paving the way for future large-scale 2D electronic devices.

关键词： Edge contact 2D materials Field-effect transistors Schottky barrier Contact resistance

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Blockchain-Based Secure and Efficient Secret Image Sharing With Outsourcing Computation in Wireless Networks

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IEEE Transactions on Wireless Communications 2024年第1期23卷 423-435页

作者： Zhou, Zhili Wan, Yao Cui, Qi Yu, Keping Mumtaz, Shahid Yang, Ching-Nung Guizani, Mohsen Institute of Artificial Intelligence and Blockchain Guangzhou University Guangzhou510006 China Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology Nanjing210044 China Graduate School of Science and Engineering Hosei University Tokyo184-8584 Japan RIKEN Center for Advanced Intelligence Project RIKEN Tokyo103-0027 Japan Department of Applied Informatics Silesian University of Technology Gliwice44-100 Poland Department of Engineering Nottingham Trent University NottinghamNG1 4FQ United Kingdom Department of Computer Science and Information Engineering National Dong Hwa University Hualien97401 Taiwan Abu Dhabi United Arab Emirates

Secret Image Sharing (SIS) is the technology that shares any given secret image by generating and distributing n shadow images in the way that any subset of k shadow images can restore the secret image. However, in the existing SIS schemes, the shadow images will be easily tampered and corrupted during the communication, which will pose serious security issues. Recently, blockchain has emerged as a promising paradigm in the field of data communication and information security. To securely communicate and effectively protect the secret image data in wireless networks, we propose a Blockchain-based Secure and Efficient Secret Image Sharing (BC-SESIS) scheme with outsourcing computation in wireless networks. In the proposed BC-SESIS scheme, the shadow images are encrypted and stored in the blockchain to prevent them from being tampered and corrupted. The identity authentication-enabled smart contract is deployed to achieve the (k,n) threshold for secret image restoring. Furthermore, to reduce the computational burden of smart contract and users, an efficient outsourcing computation method is designed to outsource the restoring task, which is securely implemented by agent miners in the encryption domain. Theoretical analysis and extensive experiments demonstrate that the BC-SESIS scheme can achieve desirable communication security and high computational efficiency in the wireless networks. © 2023 IEEE.

关键词： Smart contract

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