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41st International Conference on Machine Learning, ICML 2024

作者： Lian, Junrong Dong, Ziyue Wei, Pengxu Ke, Wei Liu, Chang Ye, Qixiang Ji, Xiangyang Lin, Liang School of Computer Science and Engineering Sun Yat-sen University Guangzhou China School of Software Engineering Xi'an Jiaotong University Xi'an China Department of Automation Tsinghua University Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China Peng Cheng Laboratory Shenzhen China

A codebook designed for learning discrete distributions in latent space has demonstrated state-of-the-art results on generation tasks. This inspires us to explore what distribution of codebook is better. Following the spirit of Kepler's Conjecture, we cast the codebook training as solving the sphere packing problem and derive a Kepler codebook with a compact and structured distribution to obtain a codebook for image representations. Furthermore, we implement the Kepler codebook training by simply employing this derived distribution as regularization and using the codebook partition method. We conduct extensive experiments to evaluate our trained codebook for image reconstruction and generation on natural and human face datasets, respectively, achieving significant performance improvement. Besides, our Kepler codebook has demonstrated superior performance when evaluated across datasets and even for reconstructing images with different resolutions. Codes and pre-trained weights are available at https://***/banianrong/KeplerCodebook. Copyright 2024 by the author(s)

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SCSegamba: Lightweight Structure-Aware vision Mamba for Crack Segmentation in Structures

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arXiv 2025年

作者： Liu, Hui Jia, Chen Shi, Fan Cheng, Xu Chen, Shengyong School of Computer Science and Engineering Tianjin University of Technology China Engineering Research Center of Learning-Based Intelligent System Ministry of Education Key Laboratory of Computer Vision and System Ministry of Education

Pixel-level segmentation of structural cracks across various scenarios remains a considerable challenge. Current methods encounter challenges in effectively modeling crack morphology and texture, facing challenges in balancing segmentation quality with low computational resource usage. To overcome these limitations, we propose a lightweight Structure-Aware vision Mamba Network (SCSegamba), capable of generating high-quality pixel-level segmentation maps by leveraging both the morphological information and texture cues of crack pixels with minimal computational cost. Specifically, we developed a Structure-Aware Visual State Space module (SAVSS), which incorporates a lightweight Gated Bottleneck Convolution (GBC) and a Structure-Aware Scanning Strategy (SASS). The key insight of GBC lies in its effectiveness in modeling the morphological information of cracks, while the SASS enhances the perception of crack topology and texture by strengthening the continuity of semantic information between crack pixels. Experiments on crack benchmark datasets demonstrate that our method outperforms other state-of-the-art (SOTA) methods, achieving the highest performance with only 2.8M parameters. On the multi-scenario dataset, our method reached 0.8390 in F1 score and 0.8479 in mIoU. The code is available at https://***/Karl1109/SCSegamba. © 2025, CC BY.

关键词： State space methods

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Study on the Effectiveness of New Development Methods in Software engineering Based on Experiments with AB Testing 24

Study on the Effectiveness of New Development Methods in Sof...

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9th International Conference on Cyber Security and Information engineering, ICCSIE 2024

作者： Chen, Lei Zhang, Difeng Li, Simu School of Computer Science and Engineering Wuhan Institute of Technology China Hubei Key Laboratory of Intelligent Robot Wuhan Institution of Technology China School of Electrical and Information Engineering Wuhan Institute of Technology China Economic and Business Department College of Post and Telecommunication of Wuhan Institute of Technology China

ISBN: (纸本)9798400718137

This study aims to evaluate the effectiveness of an emerging software engineering development method through AB testing experiments. As a commonly used online experimental method, AB testing is used to compare the performance of two or more solutions. It has been widely used in the software development process to optimize user experience and function implementation. This study proposes a new development framework that combines AB testing and software testing, which quantifies the impact of different development strategies on software quality by constructing a correlation matrix. In order to verify the effectiveness of this method, this paper designed a series of experiments and implemented AB testing in multiple software projects. Experimental results show that by accurately adjusting the variable combinations in AB testing, software stability and user satisfaction can be significantly improved. In addition, this paper also develops a set of computer algorithm models to simulate different development scenarios and predict the potential benefits of new development methods through simulation technology. Through the analysis of simulation results, this article found that projects using new development methods have improved in key performance indicators, especially in shortening development cycles and reducing defect rates. The development method that combines AB testing and software testing not only improves the quality of software products, but also enhances the flexibility and response speed of the development process. © 2024 Copyright held by the owner/author(s).

关键词： Software quality

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Harnessing the power of functionalized biochar:progress,challenges,and future perspectives in energy,water treatment,and environmental sustainability

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Biochar 2024年第1期6卷 407-486页

作者： Muhammad Zubair Yameen Salman Raza Naqvi Dagmar Juchelková Muhammad Nouman Aslam Khan Laboratory of Alternative Fuels and Sustainability School of Chemical and Materials Engineering(SCME)National University of Sciences and Technology(NUST)Sector H-12Islamabad 44000Pakistan. Department of Electronics Faculty of Electrical Engineering and Computer ScienceVŠB-Technical University of Ostrava17.Listopadu 2172/1570800 OstravaPorubaCzech Republic. Department of Engineering and Chemical Sciences Karlstad UniversityKarlstadSweden.

The swift advancement of sustainable energy technologies,coupled with the urgent need to address environmental challenges,has generated considerable interest in the multifaceted applications of biochar materials to promote energy,water,and environmental *** comprehensive review examines recent advancements in the production and applications of functionalized biochar materials,emphasizing their pivotal roles in energy conversion and storage,wastewater treatment,CO_(2)reduction,soil amelioration,and the promotion of carbon neutrality within a circular economy *** functionalization of biochar materials involves surface chemistry and porosity modifications,achieved through techniques like templating,chemical activation,metal impregnation,or heteroatom *** modifications substantially enhance the catalytic activity,energy storage capacity,and cycling stability of biochar materials,making them particularly effective in diverse energy applications such as water splitting,fuel cells,and ***,functionalized biochar materials demonstrate remarkable efficacy as catalysts and adsorbents in wastewater treatment,proficiently removing pollutants like heavy metals,organic contaminants,and nutrients,thereby facilitating resource recovery from *** review also underscores the potential of functionalized biochar materials in CO_(2)capture and conversion,exploring innovative strategies to augment their CO_(2)adsorption capacity and state-of-the-art catalytic processes for transforming captured CO_(2)into valuable fuels and *** summary,this review offers valuable insights into the recent advancements in biochar research,underscoring its substantial commercial potential as a versatile material contributing to a cleaner and more sustainable future.

关键词： Engineered biochar Sustainable energy technologies Wastewater treatment Carbon reduction Circular economy

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A Multi-Armed Bandits Learning-Based Approach to Service Caching in Edge Computing Environment 30th

A Multi-Armed Bandits Learning-Based Approach to Service Ca...

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30th International Conference on Web Services, ICWS 2023

作者： Li, Jinpeng Zhao, Jiale Chen, Peng Xia, Yunni Li, Fan Li, Yin Zeng, Feng Liu, Hui School of Computer Chongqing University Chongqing400030 China School of Computer and Software Engineering Xihua University Chengdu610039 China Key Laboratory of Fundamental Synthetic Vision Graphics and Image Science for National Defense Sichuan University Chengdu610065 China Guangzhou Institute of Software Application Technology Guangzhou510990 China Limited Shenzhen518129 China School of Computer Science and Technology Beijing Institute of Technology Beijing100083 China

ISBN: (纸本)9783031448355

Mobile edge computing (MEC) is a newly emerging concept that provides significant local computing power and reduces end-to-end latency. In MEC environments, caching frequently accessed services on edge servers effectively reduces latency and improves system responsiveness. An ongoing research topic in such a cachable MEC context is to design novel algorithms for yielding high-quality caching decision that guarantee high user-perceived quality-of-service (QoS) and high system responsiveness of delivery of cached content with the difference of caching capacities of edge servers and diversified content popularity appropriately addressed. In this article, we propose a multi-armed bandits learning-based method busing a Thompson sampling for generating caching decisions. We introduce a genetic multi-armed bandits algorithm (GMAB), which synthesizes the genetic algorithm (GA) and multi-armed bandits (MAB), for optimizing caching effectiveness with timing and space constraints. The experiment results show that GMAB outperforms traditional methods in terms of multiple aspects. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Genetic algorithms

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GCFuzz: An Intelligent Method for Generating IoT Protocols Test Cases Using GAN with CVAE 7th

GCFuzz: An Intelligent Method for Generating IoT Protocols ...

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7th International Conference on Attacks and Defenses for Internet-of-Things, ADIoT 2024

作者： Zhong, Ming Zeng, Zisheng Guo, Yijia Zhao, Dandan Zhang, Bo Li, Shenghong Peng, Hao Ding, Zhiguo School of Computer Science and Technology Zhejiang Normal University Zhejiang Jinhua China Key Laboratory of Intelligent Educational Technology and Application in Zhejiang Normal University Jinhua321004 China School of Cyber Science and Engineering Shanghai Jiao Tong University Shanghai China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9783031855924

The importance of Internet of Things (IoT) systems security cannot be ignored, particularly in the realm of communication. IoT protocols serve as standards for communication and interaction among devices in IoT environments. This paper enhances IoT security by identifying and exposing protocol vulnerabilities through fuzzing, a crucial method for discovering security flaws. Traditional generation-based fuzzers require reverse engineering to understand protocol grammar and generate test cases. In this paper, we propose an intelligent method called GCFuzz, which generates high-quality test cases without prior knowledge of the protocol. To understand different classes of protocol grammar, GCFuzz applies Generative Adversarial Networks (GAN) with Conditional Variational Autoencoders (CVAE) to train a generative model on various classes of protocol messages. After training, the model generates fake but credible messages. Additionally, to accurately cluster real protocol messages, we devise a novel clustering method based on a keyword. Results show that, compared to GANFuzz, Peach, BooFuzz, and Sulley, the test cases generated by GCFuzz have stronger targeting and less redundancy, while GCFuzz has higher accurate testing efficiency. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Generative adversarial networks

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CryptoPyt: Unraveling Python Cryptographic APIs Misuse with Precise Static Taint Analysis 40

CryptoPyt: Unraveling Python Cryptographic APIs Misuse with ...

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40th Annual computer Security Applications Conference, ACSAC 2024

作者： Guo, Xiangxin Jia, Shijie Lin, Jingqiang Ma, Yuan Zheng, Fangyu Li, Guangzheng Xu, Bowen Cheng, Yueqiang Ji, Kailiang School of Cyber Security University of Science and Technology of China Hefei China Key Laboratory of Cyberspace Security Defense Institute of Information Engineering CAS Beijing China School of Cryptology University of Chinese Academy of Sciences Beijing China Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China NIO China

ISBN: (纸本)9798331520885

Cryptographic APIs are essential for ensuring the security of software systems. However, many research studies have revealed that the misuse of cryptographic APIs is commonly widespread. Detecting such misuse in Python poses challenges due to its intricate features, including dynamic features and pass-by-object-reference. Existing tools lack the precision and accuracy to tackle these challenges, leading to both high false positives and false negatives. In this work, we propose a specific Python Cryptographic Abstract Syntax Tree (PCAST) to represent the structure of source code, which rewrites AST nodes to handle complex Python features. Based on PCAST, we design and implement CryptoPyt, a static code analysis tool that leverages precise taint analysis and 17 cryptographic misuse rules to automatically identify potential cryptographic APIs misuse in Python projects. We conduct an in-depth analysis of all the APIs within the popular 21 Python cryptographic libraries and design five kinds of taint detectors to perform intra-procedural and inter-function analysis on the APIs and arguments. To demonstrate the effectiveness of CryptoPyt, we conduct experiments with six state-of-the-art tools (i.e., Cryptolation, LICMA, Bandit, Dlint, Semgrep and CodeQL) on both the labeled benchmark PyCryptoBench and the real-world Python cryptographic projects datasets PCAMD. Our evaluations show that CryptoPyt achieves an F1 score of 0.80 on PyCryptoBench and a recall rate of 99.08% on PCAMD. Furthermore, we disclose the discovered critical issues to the developers and seven high-level CVE IDs have been assigned to these findings. Our tool contributes to enhancing the security of Python cryptographic software. © 2024 IEEE.

关键词： Python

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A metasurface-based light-to-microwave transmitter for hybrid wireless communications

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Light(science & Applications) 2022年第6期11卷 1139-1148页

作者： Xin Ge Zhang Ya Lun Sun Bingcheng Zhu Wei Xiang Jiang Qian Yu Han Wei Tian Cheng-Wei Qiu Zaichen Zhang Tie Jun Cui State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast University210096 NanjingChina National Mobile Communications Research Laboratory School of Information Science and EngineeringSoutheast University210096 NanjingChina Frontiers Science Center for Mobile Information Communication and Security Southeast University210096 NanjingChina Purple Mountain Laboratories 211111 NanjingChina Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

Signal conversion plays an important role in many applications such as communication,sensing,and *** signal conversion between optical and microwave frequencies is a crucial step to construct hybrid communication systems that combine both optical and microwave wireless technologies to achieve better features,which are highly desirable in the future wireless ***,such a signal conversion process typically requires a complicated relay to perform multiple operations,which will consume additional hardware/time/energy ***,we report a light-to-microwave transmitter based on the time-varying and programmable metasurface integrated with a high-speed photoelectric detection circuit into a *** a transmitter can convert a light intensity signal to two microwave binary frequency shift keying signals by using the dispersion characteristics of the metasurface to implement the frequency division *** illustrate the metasurface-based transmitter,a hybrid wireless communication system that allows dual-channel data transmissions in a light-to-microwave link is demonstrated,and the experimental results show that two different videos can be transmitted and received simultaneously and *** metasurface-enabled signal conversion solution may enrich the functionalities of metasurfaces,and could also stimulate new information-oriented applications.

关键词： microwave surface light

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An AoI-Guaranteed Sensor Data Collection Strategy for RIS-assisted UAV Communication System

An AoI-Guaranteed Sensor Data Collection Strategy for RIS-as...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Yang, Bowen Yu, Yao Li, Jianqi Xu, Tongze Deng, Der-Jiunn Chin, Hui-Hsin Li, Yonghui Northeastern University School of Computer Science and Engineering Shenyang China National Changhua University of Education Department of Computer Science and Information Engineering China Overseas Chinese University Department of Information Technology China University of Sydney School of Electrical and Information Engineering Sydney Australia Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang China

ISBN: (纸本)9798350345384

The recently proposed concept of Age of Information (AoI) measures the freshness of the sensor data sampled by remote Internet of Things (IoT) devices, which is an important indicator for the smart city. Unmanned Aerial Vehicles (UAV) communication can significantly reduce the sensor data's AoI due to its high maneuverability. However, the UAV's high energy consumption remains a challenging issue. In this paper, we propose a Reconfigurable Intelligent Surface (RIS) assisted UAV data collection framework to minimize UAV energy consumption. By adjusting the phase of the RIS, the UAV can collect more sensor data simultaneously. A RIS phase alignment method is introduced to reduce the complexity of RIS phase solving. The IoT devices are clustered to discretize UAV trajectory. The optimal clustering scheme to maximize the AoI suppression efficiency is found by adjusting the RIS phase alignment points continuously. Therefore, the AoI requirement can be achieved with a shorter UAV flight distance. Finally, the UAV trajectory is solved by the Deep Q network (DQN) algorithm to guarantee the long-term AoI requirement. Simulation results validate the effectiveness of the proposed method. © 2023 IEEE.

关键词： Maneuverability

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SIVD: Dataset of Iranian Vehicles for Real-Time Multi-Camera Video Tracking and Recognition 8

SIVD: Dataset of Iranian Vehicles for Real-Time Multi-Camera...

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8th International Iranian Conference on Signal Processing and Intelligent Systems, ICSPIS 2022

作者： Siahkali, Farbod Alavi, Seyed Amirmahdi Masouleh, Mehdi Tale University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran Islamic Azad University Human and Robot Interaction Laboratory School of Computer Science Central Tehran Branch Tehran Iran

ISBN: (纸本)9781665476232

In this paper, a new publicly available 1 web-Scraped Iranian Vehicle Dataset (SIVD) for simultaneous real-time vehicle tracking and recognition is proposed. The datasets provided for Iranian cars in the literature have two fundamental problems. First, the lack of images from different angles, and second, the small number of classes compared to the dispersion of car models in the real world. Therefore, for the purposes of this paper, Iranian vehicle images from car sales websites are collected, and the SIVD dataset is proposed which contains 29 classes and 36,705 images. This paper aims at developing a classification network for Iranian vehicle recognition and implement a real-time tracking system using the YOLOv5 network to perform real-time vehicle model recognition and tracking tasks simultaneously. The ResNet50 achieved an accuracy of 99.29%, the highest among the investigated classification networks.1https://***/Farbod-Siahkali/Iranian-Vehicle-Tracking-and-Recognition © 2022 IEEE.

关键词： Model automobiles

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