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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Jyothi, M. Nandini, B.M. Computer Network Engineering The National Institute of Engineering Mysuru India Department of Information Science & Engineering The National Institute of Engineering Mysuru India

The images which are taken in foggy weather/bad weather are not expressed clearly therefore they are not very comprehensible. The images that are taken in that environment will be reduced in quality to a great degree, the reason is that because of the scattering of light in the atmosphere will reduce the clarity and visibility of a single image. Because of fog, the images are in low contrast whereas in case the haze in the atmosphere will affect the clearness and precision of the image. The pictures taken in this condition will not only affect the visibility but also complicate the post-processing of the image required for the implementation of numerous computer vision algorithms. Hence it is important to eliminate fog from the image So, firstly density of fog is estimated and based on that, image defogging can be done. © Grenze Scientific Society, 2023.

关键词： Image reconstruction

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Multi-class Bitcoin mixing service identification based on graph classification

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Digital Communications and networks 2024年第6期10卷 1881-1893页

作者： Xiaoyan Hu Meiqun Gui Guang Cheng Ruidong Li Hua Wu School of Cyber Science&Engineering Southeast UniversityNanjing 211189China Purple Mountain Laboratories for Network and Communication Security Nanjing 211111China Jiangsu Provincial Engineering Research Center of Security for Ubiquitous Network Nanjing 211189China Key Laboratory of Computer Network and Information Integration Southeast UniversityMinistry of EducationChina Research Base of International Cyberspace Governance Southeast UniversityNanjing 211189China Institute of Science and Engineering Kanazawa UniversityKakumaKanazawa920-1192Japan

Due to its anonymity and decentralization,Bitcoin has long been a haven for various illegal *** generally legalize illicit funds by Bitcoin mixing ***,it is critical to investigate the mixing services in cryptocurrency anti-money *** studies treat different mixing services as a class of suspicious Bitcoin ***,they are limited by relying on expert experience or needing to deal with large-scale *** far,multi-class mixing service identification has not been explored *** is challenging since mixing services share a similar procedure,presenting no sharp ***,mixing service identification facilitates the healthy development of Bitcoin,supports financial forensics for cryptocurrency regulation and legislation,and provides technical means for fine-grained blockchain *** paper aims to achieve multi-class Bitcoin Mixing Service Identification with a Graph Classification(BMSI-GC)***,BMSI-GC constructs 2-hop ego networks(2-egonets)of mixing services based on their historical ***,it applies graph2vec,a graph classification model mainly used to calculate the similarity between graphs,to automatically extract address features from the constructed ***,it trains a multilayer perceptron classifier to perform classification based on the extracted ***-GC is flexible without handling the full-size network and handcrafting address ***,the differences in transaction patterns of mixing services reflected in the 2-egonets provide adequate information for *** experimental study demonstrates that BMSI-GC performs excellently in multi-class Bitcoin mixing service identification,achieving an average identification F1-score of 95.08%.

关键词： Bitcoin Anti-money laundering Mixing service Ego network Graph classification

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Analysis on Technique for Code Obfuscation 23

Analysis on Technique for Code Obfuscation

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2nd International Conference on networks, Communications and Information Technology, CNCIT 2023

作者： Zhang, Ni Dong, Wei Xia, Zehong Feng, Zhi Li, Zhicheng National Computer System Engineering Research Institute of China Network Security Programme China

ISBN: (纸本)9798400700620

Code obfuscation is used to reduce legibility of the code, and protect the critical code information from being stolen by reverse engineering. For the characteristic that obfuscation can be used for assembly and source code, the main method and principle of obfuscation including identifier obfuscation, control obfuscation and data obfuscation are expounded from the aspects of assembly and source level. Measuring the effectiveness of obfuscation is urgently needed. Existing evaluation methods are mostly based on software complexity measurement, and this leads to a single dimension. The VirusTotal, a website that integrates antivirus software is used to evaluate the killing rates of detecting malicious code in which different obfuscating methods are used. The killing rates are inversely proportional to the code obfuscating effects. Through the comparative experiment, the effects obfuscating factors including encoding times, encoding multiplicities, file formats, obfuscating levels, and obfuscating methods have on killing rates are compared and analyzed, and the ability of different code obfuscating technologies for assembly and source code are measured. The results show that the code obfuscating technologies whose characteristic codes are new and that can change program logic have good effects, which helps developers to use code obfuscating technologies effectively to prevent man-at-the-end attack. © 2023 ACM.

关键词： Encoding (symbols)

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Resource Allocation in 6G network for High-Speed Train Using D2D Outband Communication 3rd

Resource Allocation in 6G Network for High-Speed Train Using...

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3rd International Conference on Machine Vision and Augmented Intelligence, MAI 2023

作者： Garg, Aakansha Arya, Rajeev Singh, Maheshwari Prasad Wireless Sensor Network Lab Department of Electronics and Communication Engineering Patna India Department of Computer Science and Engineering National Institute of Technology Patna India

ISBN: (纸本)9789819743582

The growth of 6G results in rising data transmission rate in static scenario. To achieve fast communication and computation with quality service in high-speed train is a challenge. This is due to fast handover and Doppler shift. To effectively communicate in high-speed train, the placement of a mobile relay (MR) with small server at the rooftop of train coach is proposed. The base station sends channel state information to mobile relay which stores it in the stack. The resource assignment has been conducted by an improved grey wolf optimization algorithm. The focus is at improving throughput with reduction in latency and energy consumption. The simulation outcomes manifests that the presented algorithm carry-out finer in comparison of the Hungarian algorithm. The accomplished results are refined almost three times in respect of energy consumption, latency, and throughput. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Resource allocation

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Benchmarking the Performance of Mobile Mid-haul networks with Multi-flow Optical Transponders

Benchmarking the Performance of Mobile Mid-haul Networks wit...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Brasileiro, Ítalo B. Zacarias, Iulisloi Drummond, André C. Napoli, Antonio Jukan, Admela Technische Universität Braunschweig Institute of Computer and Network Engineering Germany University of Brasília Department of Computer Science Brazil Infinera Munich Germany

ISBN: (纸本)9798350351255

The next-generation mobile networks follow the 3GPP disaggregated Radio Access network (RAN) model, composed of three separate functional units: Centralized Unit (CU), Distributed Unit (DU), and Radio Unit (RU), and its interconnection network infrastructures, front-haul, between RU and DU and mid-haul, between DU and CU. The current focus has been extensively on the front-haul, proposing a myriad of networking technologies and resource allocation solutions. Mid-haul transport infrastructure has received comparably less attention. This paper explores the implementation and performance of optical multi-flow transponders in mobile mid-haul networks. It evaluates the performance of mid-haul mesh topologies with different DU placement methods. Numerical results show the achievable throughput and blocking performance. We also derive the number of Multi-flow optical transponders (MOTP) units deployed, as well as the related trade-offs. © 2024 IEEE.

关键词： Radio access networks

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A Random Fusion of Mix 3D and Polar Mix to Improve Semantic Segmentation Performance in 3D Lidar Point Cloud

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computer Modeling in engineering & Sciences 2024年第7期140卷 845-862页

作者： Bo Liu Li Feng Yufeng Chen School of Computer Science and Engineering Macao University of Science and TechnologyMacao999078China School of Computer Science and Artificial Intelligence Chaohu UniversityChaohu238000China Institute of Vehicle Information Control and Network Technology Hubei University of Automotive TechnologyShiyan442002China

This paper focuses on the effective utilization of data augmentation techniques for 3Dlidar point clouds to enhance the performance of neural network *** point clouds,which represent spatial information through a collection of 3D coordinates,have found wide-ranging *** augmentation has emerged as a potent solution to the challenges posed by limited labeled data and the need to enhance model generalization *** of the existing research is devoted to crafting novel data augmentation methods specifically for 3D lidar point ***,there has been a lack of focus on making the most of the numerous existing augmentation *** this deficiency,this research investigates the possibility of combining two fundamental data augmentation *** paper introduces PolarMix andMix3D,two commonly employed augmentation techniques,and presents a new approach,named *** of using a fixed or predetermined combination of augmentation methods,RandomFusion randomly chooses one method from a pool of options for each instance or *** innovative data augmentation technique randomly augments each point in the point cloud with either PolarMix or *** crux of this strategy is the random choice between PolarMix and Mix3Dfor the augmentation of each point within the point cloud data *** results of the experiments conducted validate the efficacy of the RandomFusion strategy in enhancing the performance of neural network models for 3D lidar point cloud semantic segmentation *** is achieved without compromising computational *** examining the potential of merging different augmentation techniques,the research contributes significantly to a more comprehensive understanding of how to utilize existing augmentation methods for 3D lidar point *** data augmentation technique offers a simple yet effective method to leverage the diversity of augmentation techniques and boost the ro

关键词： 3D lidar point cloud data augmentation RandomFusion semantic segmentation

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Research on Security Data of Federated Learning Privacy LSTM Model Based on Generative Adversarial network

Research on Security Data of Federated Learning Privacy LSTM...

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2023 International Conference on Machine Learning and Cybernetics, ICMLC 2023

作者： Xu, Wang Zhuoming, Liang School of Computer Neusoft Institute Guangdong Department of Network Engineering China South China Nomal University Network Center China

ISBN: (纸本)9798350303780

As a new wireless transmission architecture technology, cSO can effectively reduce the influence of fading channels and provide cSO links for low channel quality. Secondly, in the ultra-large traffic cSO, The fitting of data and the constraint on the model must be considered at the same time. Generally speaking, regularization is the most common method, because in the process of inversion, it is far from enough to only use data fitting terms as constraints. In order to make the inversion results stable, model constraint terms should be added to the objective function on the basis of data fitting terms, and there are usually different model constraint methods for different practical problems. When the physical properties of anomalous body are different from those of surrounding rock, the minimum model constraint can be used. When inversion of the moderocess of EMM-connected state was consistent with the determination of the coverage enhancement level. © 2023 IEEE.

关键词： Fading channels

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Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games 63

Conjectural Online Learning with First-order Beliefs in Asym...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Li, Tao Hammar, Kim Stadler, Rolf Zhu, Quanyan New York University Department of Electrical and Computer Engineering United States Kth Royal Institute of Technology Division of Network and Systems Engineering Sweden

ISBN: (纸本)9798350316339

Asymmetric information stochastic games (AISGs) arise in many complex socio-technical systems, such as cyberphysical systems and IT infrastructures. Existing computational methods for AISGs are primarily offline and can not adapt to equilibrium deviations. Further, current methods are limited to particular information structures to avoid belief hierarchies. Considering these limitations, we propose conjectural online learning (COL), an online learning method under generic information structures in AISGs. COL uses a forecaster-actorcritic (FAC) architecture, where subjective forecasts are used to conjecture the opponents' strategies within a lookahead horizon, and Bayesian learning is used to calibrate the conjectures. To adapt strategies to nonstationary environments based on information feedback, COL uses online rollout with cost function approximation (actor-critic). We prove that the conjectures produced by COL are asymptotically consistent with the information feedback in the sense of a relaxed Bayesian consistency. We also prove that the empirical strategy profile induced by COL converges to the Berk-Nash equilibrium, a solution concept characterizing rationality under subjectivity. Experimental results from an intrusion response use case demonstrate COL's faster convergence over state-of-the-art reinforcement learning methods against nonstationary attacks. © 2024 IEEE.

关键词： Cost functions

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Learning group interaction for sports video understanding from a perspective of athlete

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Frontiers of computer Science 2024年第4期18卷 175-188页

作者： Rui HE Zehua FU Qingjie LIU Yunhong WANG Xunxun CHEN Intelligent Recognition and Image Processing(IRIP)Lab School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Hangzhou Innovation Institute Behang UniversityHangzhou 310051China National Computer Network Emergency Response Technical Team/Coordination Center of China(CNCERT or CNCERT/CC) Beijing 100029China

Learning activities interactions between small groups is a key step in understanding team sports *** research focusing on team sports videos can be strictly regarded from the perspective of the audience rather than the *** team sports videos such as volleyball and basketball videos,there are plenty of intra-team and inter-team *** this paper,a new task named Group Scene Graph Generation is introduced to better understand intra-team relations and inter-team relations in sports *** tackle this problem,a novel Hierarchical Relation network is *** all players in a video are finely divided into two teams,the feature of the two teams’activities and interactions will be enhanced by Graph Convolutional networks,which are finally recognized to generate Group Scene *** evaluation,built on Volleyball dataset with additional 9660 team activity labels,a Volleyball+dataset is proposed.A baseline is set for better comparison and our experimental results demonstrate the effectiveness of our ***,the idea of our method can be directly utilized in another video-based task,Group Activity *** show the priority of our method and display the link between the two ***,from the athlete’s view,we elaborately present an interpretation that shows how to utilize Group Scene Graph to analyze teams’activities and provide professional gaming suggestions.

关键词： group scene graph group activity recognition scene graph generation graph convolutional network sports video understanding

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Smart Geometry Learning in Authentic Contexts with Personalization, Contextualization, and Socialization

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IEEE Transactions on Learning Technologies 2023年 1-18页

作者： Hwang, Wu-Yuin Lin, Yi Jing Utami, Ika Qutsiati Nurtantyana, Rio Department of Computer Science and Information Engineering National Dong Hwa University Hualien Taiwan Graduate Institute of Network Learning Technology National Central University Taiwan

This study aimed to investigate the effectiveness of smart mechanisms (i.e., personalization, contextualization, and socialization) on geometry learning supported by Smart-UG, a mobile application with the integration of augmented reality (AR) to facilitate authentic learning and provide learners with some features in measuring and applying geometric concepts in a real-world environment. To investigate the impact of the technology with smart mechanisms on student learning achievements (i.e., geometry ability (GA) and problem-solving skill (PSS), we conducted a quasi-experiment with the participation of fifth-grade students (n = 52). They were divided into two groups (i.e., experimental and control group) and carried out two stages of learning activity with an independent experiment which is underpinned by a set of problem-solving activities. Stage 1 aimed to investigate the impact of personalization and contextualization mechanisms, while stage 2 focuses on assessing socialization's impact on geometry learning. The results showed that the experimental group students achieve good performance in geometry measurement and problem-solving compared to those in the control group. It implied that our proposed application with smart mechanisms can benefit learners to improve their geometry understanding and skill. A positive attitude and high intention by the students toward Smart-UG also signify system utilization in the future. Therefore, this study has the potential to be applied in more complex geometry learning with enhanced smart mechanisms. IEEE

关键词： Geometry

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