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Amalgamation of Classical and Large Language Models for Duplicate Bug Detection:A Comparative Study

computers, Materials & Continua 2025年第4期83卷 435-453页

作者： Sai Venkata Akhil Ammu Sukhjit Singh Sehra Sumeet Kaur Sehra Jaiteg Singh Department of Physics and Computer Science Wilfrid Laurier UniversityWaterlooN2L 3C5Canada Appilied Computer Science and Information Technology Conestoga CollegeWaterlooN2J 2W2Canada Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjab140401India

Duplicate bug reporting is a critical problem in the software repositories’mining *** bug reports can lead to redundant efforts,wasted resources,and delayed software ***,their accurate identification is essential for streamlining the bug triage process mining *** researchers have explored classical information retrieval,natural language processing,text and data mining,and machine learning *** emergence of large language models(LLMs)(ChatGPT and Huggingface)has presented a new line of models for semantic textual similarity(STS).Although LLMs have shown remarkable advancements,there remains a need for longitudinal studies to determine whether performance improvements are due to the scale of the models or the unique embeddings they produce compared to classical encoding *** study systematically investigates this issue by comparing classical word embedding techniques against LLM-based embeddings for duplicate bug *** this study,we have proposed an amalgamation of models to detect duplicate bug reports using textual and non-textual information about bug *** empirical evaluation has been performed on the open-source datasets and evaluated based on established metrics using the mean reciprocal rank(MRR),mean average precision(MAP),and recall *** experimental results have shown that combined LLMs can outperform(recall-rate@k 68%–74%)other individual=models for duplicate bug *** findings highlight the effectiveness of amalgamating multiple techniques in improving the duplicate bug report detection accuracy.

关键词： Duplicate bug detection large language models information retrieval

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Fuzzy clustering for electric field characterization and its application to thunderstorm interpretability

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Digital Communications and Networks 2025年第2期11卷 299-307页

作者： Xu Yang Hongyan Xing Xinyuan Ji Wei Xu Witold Pedrycz School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 2R3Canada Systems Research Institute Polish Academy of Sciences00-901 WarsawPoland Department of Computer Engineering Faculty of Engineering and Natural SciencesIstinye University34010 IstanbulTurkey

Changes in the Atmospheric Electric Field Signal(AEFS)are highly correlated with weather changes,especially with thunderstorm ***,little attention has been paid to the ambiguous weather information implicit in AEFS *** this paper,a Fuzzy C-Means(FCM)clustering method is used for the first time to develop an innovative approach to characterize the weather attributes carried by ***,a time series dataset is created in the time domain using AEFS *** AEFS-based weather is evaluated according to the time-series Membership Degree(MD)changes obtained by inputting this dataset into the ***,thunderstorm intensities are reflected by the change in distance from a thunderstorm cloud point charge to an AEF ***,a matching relationship is established between the normalized distance and the thunderstorm dominant MD in the space ***,the rationality and reliability of the proposed method are verified by combining radar charts and expert *** results confirm that this method accurately characterizes the weather attributes and changes in the AEFS,and a negative distance-MD correlation is obtained for the first *** detection of thunderstorm activity by AEF from the perspective of fuzzy set technology provides a meaningful guidance for interpretable thunderstorms.

关键词： Atmospheric electric field(AEF) Thunderstorm Fuzzy C-means(FCM) Attribute

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Binary Program Vulnerability Mining Based on Neural Network

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computers, Materials & Continua 2024年第2期78卷 1861-1879页

作者： Zhenhui Li Shuangping Xing Lin Yu Huiping Li Fan Zhou Guangqiang Yin Xikai Tang Zhiguo Wang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu611731China School of Electrical and Computer Engineering University ofWaterlooWaterlooN2L 3G1Canada

Software security analysts typically only have access to the executable program and cannot directly access the source code of the *** poses significant challenges to security *** it is crucial to identify vulnerabilities in such non-source code programs,there exists a limited set of generalized tools due to the low versatility of current vulnerability mining ***,these tools suffer from some *** terms of targeted fuzzing,the path searching for target points is not streamlined enough,and the completely random testing leads to an excessively large search ***,when it comes to code similarity analysis,there are issues with incomplete code feature extraction,which may result in information *** this paper,we propose a cross-platform and cross-architecture approach to exploit vulnerabilities using neural network obfuscation *** leveraging the Angr framework,a deobfuscation technique is introduced,along with the adoption of a VEX-IR-based intermediate language conversion *** combination allows for the unified handling of binary programs across various architectures,compilers,and compilation ***,binary programs are processed to extract multi-level spatial features using a combination of a skip-gram model with self-attention mechanism and a bidirectional Long Short-Term Memory(LSTM)***,the graph embedding network is utilized to evaluate the similarity of program *** on these similarity scores,a target function is determined,and symbolic execution is applied to solve the target *** solved content serves as the initial seed for targeted *** binary program is processed by using the de-obfuscation technique and intermediate language transformation method,and then the similarity of program functions is evaluated by using a graph embedding network,and symbolic execution is performed based on these similarity *** approach facilitates

关键词： Vulnerability mining de-obfuscation neural network graph embedding network symbolic execution

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Joint AP Clustering and Beamforming Design for RIS-Aided Cell-Free Networks

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IEEE Transactions on Vehicular technology 2025年第5期74卷 8315-8320页

作者： Xu, Chunmei Jia, Yuanqi Chen, Youjia Huang, Wei GuildfordGU2 7XH United Kingdom Southeast University School of Information Science and Engineering Nanjing210096 China Fuzhou University Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering Fuzhou350108 China Hefei University of Technology School of Computer Science and Information Engineering Hefei230601 China

Cell-free networks and reconfigurable intelligent surfaces (RIS) are two promising techniques for future wireless communications. The integration of RIS into cell-free networks, termed RIS-aided cell-free networks, offers the potential to significantly enhance network performance. However, the realization of this potential is constrained by the limited capacities of the fronthaul links. To address this challenge, we investigate the joint design of access point (AP) clustering, transmit and passive beamforming in RIS-aided cell-free networks. The objective is to maximize the weighted sum-rate performance while minimizing the number of clustered APs to alleviate the fronthaul overhead. The problem is formulated in a group sparse manner, employing a mixed zero-norm/two-norm term to represent the number of the clustered APs. To solve this problem, we first approximate the mixed zero-norm/two-norm term by the mixed one-norm/two-norm term and provide its equivalent formulation by introducing receive beamforming vectors and weight parameters. Then, an iterative method is proposed based on the block coordinate descent (BCD) technique, which is guaranteed to converge to a stationary point. Simulation results demonstrate the effectiveness of the proposed method. © 1967-2012 IEEE.

关键词： Iterative methods

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Feature Selection for Malicious Detection on Industrial IoT Using Machine Learning

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Sensors and Materials 2024年第3期36卷 1035-1046页

作者： Chuang, Hong-Yu Chen, Ruey-Maw Computer Science and Information Engineering National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd. Taiping Dist. Taichung411030 Taiwan

The rapid deployment of IoT devices for enhanced convenience and increased production efficiency has resulted in a significant rise in the potential for cyberattacks. Consequently, the detection of malicious attacks has become a crucial concern in industrial IoT (IIoT) applications. Furthermore, IoT usage is continuously expanding, with new functional IoT devices connecting to the network daily, leading to a substantial increase in network traffic. To address the need for an intrusion detection system (IDS) to identify malicious attacks under a high-traffic condition, a highly efficient IDS is essential. In this study, an IDS based on machine learning (ML) with a reduced set of features on the TON_IoT dataset is employed. The TON_IoT includes telemetry data, operating systems data, and network data for an IoT network. A Pearson correlation coefficient (PCC) was applied to assess the correlations among packet features, and a filtering rule based on the Jamovi software's frequency table was used to identify the most essential features within the TON_IoT dataset. Finally, the 45 original features were narrowed down to 10 core features for the IDS to effectively detect intrusion activities. To evaluate the detection performance of malicious intrusion activities using the yielded set of 10 core features, we utilized evaluation metrics including accuracy, precision, recall, and F1-score. Four ML techniques, namely, K-Nearest Neighbors, Random Forest, Naïve Bayes, and eXtreme Gradient Boosting, were tested. The experimental results demonstrated that the four ML techniques could detect multiple types of attack with an accuracy exceeding 96% and with a recall rate over 97%, underscoring the effectiveness and efficiency of utilizing the reduced 10 core features for malicious attack detection while maintaining a high level of accuracy. © 2024 M Y U Scientific Publishing Division. All rights reserved.

关键词： Network security

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Deployment of Polar Codes for Mission-Critical Machine-Type Communication Over Wireless Networks

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computers, Materials & Continua 2022年第4期71卷 573-592页

作者： Najib Ahmed Mohammed Ali Mohammed Mansoor Rodina Binti Ahmad Saaidal Razalli Bin Azzuhri Department of Software Engineering Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala Lumpur Malaysia 2Department of Computer System&TechnologyFaculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia

Mission critical Machine-type Communication(mcMTC),also referred to as Ultra-reliable Low Latency Communication(URLLC),has become a research *** is primarily characterized by communication that provides ultra-high reliability and very low latency to concurrently transmit short commands to a massive number of connected *** the reduction in physical(PHY)layer overhead and improvement in channel coding techniques are pivotal in reducing latency and improving reliability,the current wireless standards dedicated to support mcMTC rely heavily on adopting the bottom layers of general-purpose wireless standards and customizing only the upper *** mcMTC has a significant technical impact on the design of all layers of the communication protocol *** this paper,an innovative bottom-up approach has been proposed for mcMTC applications through PHY layer targeted at improving the transmission reliability by implementing ultra-reliable channel coding scheme in the PHY layer of IEEE 802.11a standard bearing in mind short packet transmission *** achieve this aim,we analyzed and compared the channel coding performance of convolutional codes(CCs),low-density parity-check(LDPC)codes,and polar codes in wireless network on the condition of short data packet *** Viterbi decoding algorithm(VA),logarithmic belief propagation(Log-BP)algorithm,and cyclic redundancy check(CRC)successive cancellation list(SCL)(CRC-SCL)decoding algorithm were adopted to CC,LDPC codes,and polar codes,***,a new PHY layer for mcMTC has been *** reliability of the proposed approach has been validated by simulation in terms of Bit error rate(BER)and packet error rate(PER)***-to-noise ratio(SNR).The simulation results demonstrate that the reliability of IEEE 802.11a standard has been significantly improved to be at PER=10−5 or even better with the implementation of polar *** results also show that the general-purpose wireless net

关键词： Machine-type communication mission-critical applications MTC URLLC M2M wireless networks polar codes

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Factors affecting forensic electric network frequency matching-A comprehensive study

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Digital Communications and Networks 2024年第4期10卷 1121-1130页

作者： Guang Hua Qingyi Wang Dengpan Ye Haijian Zhang Guoyin Wang Shuyin Xia School of Electronic Information Wuhan UniversityWuhan430072China Institute for Infocomm Research(I2R) Agency for ScienceTechnology and Research(A*STAR)Singapore138632Singapore School of Cyber Science and Engineering Wuhan UniversityWuhan430072China School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China

The power system frequency fluctuations could be captured by digital recordings and extracted to compare with a reference database for forensic timestamp *** is known as the Electric Network Frequency(ENF)criterion,enabled by the properties of random fluctuations and intra-grid *** essence,this is a task of matching a short random sequence within a long reference,whose accuracy is mainly concerned with whether this match could be uniquely *** this paper,we comprehensively analyze the factors affecting the reliability of ENF matching,including the length of test recording,length of reference,temporal resolution,and Signal-to-Noise Ratio(SNR).For synthetic analysis,we incorporate the first-order AutoRegressive(AR)ENF model and propose an efficient Time-Frequency Domain noisy ENF synthesis ***,the reliability analysis schemes for both synthetic and real-world data are respectively *** a comprehensive study,we quantitatively reveal that while the SNR is an important external factor to determine whether timestamp verification is viable,the length of test recording is the most important inherent factor,followed by the length of ***,the temporal resolution has little impact on ***,a practical workflow of the ENF-based audio timestamp verification system is proposed,incorporating the discovered results.

关键词： Digital forensics Audio forensics Data authentication Timestamp verification Electric network frequency criterion

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An integrated strategy of AEF attribute evaluation for reliable thunderstorm detection

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Digital Communications and Networks 2025年第1期11卷 234-245页

作者： Xu Yang Hongyan Xing Xinyuan Ji Xin Su Witold Pedrycz School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 2R3Canada College of Internet of Things Engineering Hohai UniversityChangzhou 213022China Systems Research Institute Polish Academy of Sciences00-901 WarsawPoland Department of Computer Engineering Faculty of Engineering and Natural SciencesIstinye UniversitySariyer/IstanbulTurkey

Thunderstorm detection based on the Atmospheric Electric Field(AEF)has evolved from time-domain models to space-domain *** is especially important to evaluate and determine the particularly Weather Attribute(WA),which is directly related to the detection reliability and *** this paper,a strategy is proposed to integrate three currently competitive WA's evaluation ***,a conventional evaluation method based on AEF statistical indicators is *** evaluation approaches include competing AEF-based predicted value intervals,and AEF classification based on fuzzy *** AEF attributes contribute to a more accurate AEF classification to different *** resulting dynamic weighting applied to these attributes improves the classification *** evaluation method is applied to evaluate the WA of a particular AEF,to obtain the corresponding evaluation *** integration in the proposed strategy takes the form of a score *** cumulative score levels correspond to different final WA *** imaging is performed to visualize thunderstorm activities using those AEFs already evaluated to exhibit thunderstorm *** results confirm that the proposed strategy effectively and reliably images thunderstorms,with a 100%accuracy of WA *** is the first study to design an integrated thunderstorm detection strategy from a new perspective of WA evaluation,which provides promising solutions for a more reliable and flexible thunderstorm detection.

关键词： Atmospheric electric field(AEF) Thunderstorm Attribute Fuzzy c-means Imaging

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RC structural system control subjected to earthquakes and TMD

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Structural engineering and Mechanics 2024年第2期89卷 213-223页

作者： Shao, Jenchung Noor, M. Nasir Ken, P. Chang, Chuho Wang, R. College of Electrical Engineering and Computer Science National Kaohsiung University of Science and Technology Taiwan College of Maritime National Kaohsiung University of Science and Technology Taiwan Information and Research Center of China 1/9 Road: 2 Block: D Section: 15 Dhaka1216 Bangladesh

This paper proposes a composite design of fuzzy adaptive control scheme based on TMD RC structural system and the gain of two-dimensional fuzzy control is controlled by parameters. Monitoring and learning in LMI then produces performance indicators with a weighting matrix as a function of cost. It allows to control the trade-off between the two efficiencies by adjusting the appropriate weighting matrix. The two-dimensional Boost control model is equivalent to the LMI-constrained multi-objective optimization problem under dual performance criteria. By using the proposed intelligent control model, the fuzzy nonlinear criterion is satisfied. Therefore, the data connection can be further extended. Evaluation of controller performance the proposed controller is compared with other control techniques. This ensures good performance of the control routines used for position and trajectory control in the presence of model uncertainties and external influences. Quantitative verification of the effectiveness of monitoring and control. The purpose of this article is to ensure access to adequate, safe and affordable housing and basic services. Therefore, it is assumed that this goal will be achieved in the near future through the continuous development of artificial intelligence and control theory. Copyright © 2024 Techno-Press, Ltd.

关键词： Fuzzy control

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The Impact of Electric Car Charging on the Power Grid 32nd

The Impact of Electric Car Charging on the Power Grid

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32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Klaić, Zvonimir Đaković, Filip Primorac, Mario Fekete, Krešimir Faculty of Electrical Engineering Computer Science and Information Technology Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (纸本)9783031514937

In recent years, the number of electric vehicles has been growing rapidly in the European Union, and in the world in general. Electric cars are more efficient than fossil fuel cars, they have better driving characteristics, and most importantly: they do not emit gas while driving. There are still some challenges related to electric cars. Energy storage - batteries - are still under development to increase the range of cars. An even bigger challenge is the car charging infrastructure - charging stations of increasing capacity are being installed to shorten charging times. The growing number of charging stations brings new challenges, and an important question is what impact car charging stations have on the power quality. The paper presents a detailed analysis of the impact of electric car charging stations on the power quality in the distribution power grid. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Power quality

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