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Software Defect Prediction via Deep Belief Network

Chinese Journal of Electronics 2019年第5期28卷 925-932页

作者： WEI Hua SHAN Chun HU Changzhen ZHANG Yu YU Xiao School of Computer Science and Technology Beijing Institute of Technology China Information Technology Security Evaluation Center Beijing Key Laboratory of Software Security Engineering Technology Beijing Institute of Technology School of Electrical and Information Engineering and Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture State Key Laboratory in China for Geomechanics and Deep Underground Engineering (Beijing) China University of Mining and Technology School of Computer Science and Technology Shandong University of Technology

Defect distribution prediction is a meaningful topic because software defects are the fundamental cause of many attacks and data loss. Building accurate prediction models can help developers find bugs and prioritize their testing efforts. Previous researches focus on exploring different machine learning algorithms based on the features that encode the characteristics of *** problem of data redundancy exists in software defect data set, which has great influence on prediction *** propose a defect distribution prediction model(Deep belief network prediction model, DBNPM), a system for detecting whether a program module contains defects. The key insight of DBNPM is Deep belief network(DBN)technology, which is an effective deep learning technique in image processing and natural language processing,whose features are similar to defects in source *** results show that DBNPM can efficiently extract and process the data characteristics of source program and the performance is better than Support vector machine(SVM), Locally linear embedding SVM(LLE-SVM), and Neighborhood preserving embedding SVM(NPE-SVM).

关键词： Defect prediction Software security Deep belief network(DBN)

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A Survey of Common IOT Communication Protocols and IOT Smart-X Applications of 5G Cellular 1

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16th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of Information Technology, Applications and Tools, FITAT 2020

作者： Chu, Kai-Chun Turatsinze, Elias Chang, Kuo-Chi Zhou, Yu-Wen Chang, Fu-Hsiang Wang, Ming-Tsung Department of Business Management Fujian University of Technology Fuzhou China School of Information and Engineering Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Department of Tourism Shih-Hsin University Taipei Taiwan Institute of Communications Engineering National Yunlin University of Science and Technology Yunlin Taiwan College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (数字)9789813364202

ISBN: (纸本)9789813364196

New technologies and the potential development of Internet-connected devices have made the IoT one of the main concerns in the areas of computing. In this review paper, Bluetooth, Zigbee, Z-Wave, Wi-Fi, 5G cellular, NFC, and LoRaWAN were described. Furthermore, IOT applications like smart city, smart energy and grids, smart transport, smart buildings, smart home, smart industrial manufacturing, smart Health, and smart farming were also described. However, every communication technology has its own merits and demerits when we consider scalability, cost, and network requirements. The survey provided sufficient knowledge to select the best communication protocol suitable for the application based on network reliability, roaming capabilities, recovery mechanisms, and costs. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Zigbee

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Rockburst prediction using artificial intelligence techniques:A review

岩石力学通报（英文）

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岩石力学通报（英文） 2024年第3期3卷 1-13页

作者： Yu Zhang Kongyi Fang Manchao He Dongqiao Liu Junchao Wang Zhengjia Guo School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and ArchitectureBeijing100044China State Key Laboratory for Geomechanics and Deep Underground Engineering China University of Mining and TechnologyBeijing100083China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and ArchitectureBeijing100044China State Key Laboratory for Geomechanics and Deep Underground Engineering China University of Mining and TechnologyBeijing100083China Thomas Lord Department of Computer Science University of Southern CaliforniaLos Angeles90007CAUSA

Rockburst is a phenomenon where sudden,catastrophic failure of the rock mass occurs in underground deep regions or areas with high tectonic stress during the excavation *** disasters endanger the safety of people's lives and property,national energy security,and social interests,so it is very important to accurately predict *** rockburst prediction has not been able to find an effective prediction method,and the study of the rockburst mechanism is facing a *** the development of artificial intelligence(AI)techniques in recent years,more and more experts and scholars have begun to introduce AI techniques into the study of the rockburst *** previous research,several scholars have attempted to summarize the application of AI techniques in rockburst ***,these studies either are not specifically focused on reviews of the application of AI techniques in rockburst prediction,or they do not provide a comprehensive *** on the advantages of extensive interdisciplinary research and a deep understanding of AI techniques,this paper conducts a comprehensive review of rockburst prediction methods leveraging AI ***,pertinent definitions of rockburst and its associated hazards are ***,the applications of both traditional prediction methods and those rooted in AI techniques for rockburst prediction are summarized,with emphasis placed on the respective advantages and disadvantages of each ***,the strengths and weaknesses of prediction methods leveraging AI are summarized,alongside forecasting future research trends to address existing challenges,while simultaneously proposing directions for improvement to advance the field and meet emerging demands effectively.

关键词： Rockburst Rockburst prediction Artificial intelligence techniques

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Study of Assessing the Stability of Rwanda’s Power System from Big data Based on Power Generation 1

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作者： Shyirambere, Gilbert Chang, Kuo-Chi Chu, Kai-Chun Wang, Hsiao-Chuan Omer, AbdalazizAltayeb Ibrahim Amesimenu, Governor David Kwabena Chang, Fu-Hsiang Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China School of Information Science and Engineering Fujian University of Technology Fuzhou China Department of Business Management Fujian University of Technology Fuzhou China Institute of Environmental Engineering National Taiwan University Taipei Taiwan College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia Department of Tourism Shih-Hsin University Taipei Taiwan

ISBN: (数字)9789813364202

ISBN: (纸本)9789813364196

Rwanda has insufficient of electricity in which the electricity access among its citizens is at 53% equals to 224 MW of power generation. However, even among 53% of electrification, there are still some blackouts and erratic outages in cities during the night when many devices are connected on the system. This blackout and sudden shutdown could make the power system stability of Rwanda to be questionable and it can be so-called unstable. Meanwhile, the Rwanda Government is very ambitious targeting to achieve universal access by 2023/24 in which 52% will be on-grid connected and 48% off-grid. In this study, the current and proposed Rwanda power generation sector, transmission sector, and distribution sector are discussed;general Rwanda energy sources like, hydro, solar, diesel thermal, methane gas, peat are also discussed based on big data. In the end, conclusion and some recommendations have been proposed to be done in order to make stable the power system. For instance, Kalman-filtered solar forecasting approach could be used to predict weather condition every hour so that blackout coming from bad atmosphere could be prevented. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Outages

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Two Tasks, One Goal: Uniting Motion and Planning for Excellent End To End Autonomous Driving Performance

arXiv

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arXiv 2025年

作者： Liu, Lin Song, Ziying Pan, Hongyu Yang, Lei Jia, Caiyan Luo, Y. Beijing Key Laboratory of Traffic Data Mining and Embodied Intelligence Beijing Jiaotong University China Horizon Robotics China School of Information Technology and Electrical Engineering The University of Queensland Australia School of Vehicle and Mobility Tsinghua University China

End-to-end autonomous driving has made impressive progress in recent years. Former end-to-end autonomous driving approaches often decouple planning and motion tasks, treating them as separate modules. This separation overlooks the potential benefits that planning can gain from learning out-of-distribution data encountered in motion tasks. However, unifying these tasks poses significant challenges, such as constructing shared contextual representations and handling the unobservability of other vehicles’ states. To address these challenges, we propose TTOG, a novel two-stage trajectory generation framework. In the first stage, a diverse set of trajectory candidates is generated, while the second stage focuses on refining these candidates through vehicle state information. To mitigate the issue of unavailable surrounding vehicle states, TTOG employs a self-vehicle data-trained state estimator, subsequently extended to other vehicles. Furthermore, we introduce ECSA (equivariant context-sharing scene adapter) to enhance the generalization of scene representations across different agents. Experimental results demonstrate that TTOG achieves state-of-the-art performance across both planning and motion tasks. Notably, on the challenging open-loop nuScenes dataset, TTOG reduces the L2 distance by 36.06%. Furthermore, on the closed-loop Bench2Drive dataset, our approach achieves a 22% improvement in the driving score (DS), significantly outperforming existing baselines. Copyright © 2025, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Study of Smart Decorating Machine on Cake Patten 1

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作者： Jiang, Shi-Jie Chang, Kuo-Chi Wang, Hong-Jiang Chu, Kai-Chun Wang, Hsiao-Chuan Chang, Fu-Hsiang School of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Department of Business Management Fujian University of Technology Fuzhou China Institute of Environmental Engineering National Taiwan University Taipei Taiwan Department of Tourism Shih-Hsin University Taipei Taiwan College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (数字)9789813364202

ISBN: (纸本)9789813364196

Adding some shapes to food in the production process can greatly increase the added value of food and make the same food. The market is more competitive. At present, cake decorating is mainly done manually, which requires high operating skills of personnel, and there are fewer optional decorating styles. Aiming at these shortcomings, a design concept of a smart cake spotting machine is proposed. This design uses a three-axis linkage device to cooperate with the cream delivery mechanism;the main control system used STM32F103ZET6 chip. It stores the G-code files of the flower pattern through the SD card and externally stores the SD card in the SD card data, external stepper motor drive circuit to control the operation of the mechanical structure. Finally, the stepper motor controls the displacement of the mechanism and conveys the cream. The movement of the mechanism makes it possible to finish the work of decorating the cake. In this article, the specific design and implementation of the cake automatic flowering machine are introduced in detail. This study has undergone experimental testing and the results show that the cake embossing machine designed by this study institute can automatically complete embossing according to the set embossing pattern. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Stepping motors

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Matching Ontologies Through Evolutionary Algorithm with Context-Based Reasoning 6th

Matching Ontologies Through Evolutionary Algorithm with Cont...

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6th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2021

作者： Yang, Chaofan Xue, Xingsi Yue, Cai Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou Fujian350118 China Intelligent Information Processing Research Center Fujian University of Technology Fuzhou Fujian350118 China College of Information Science and Engineering Fujian University of Technology Fuzhou Fujian350118 China Fujian Key Lab for Automotive Electronics and Electric Drive Fujian University of Technology Fuzhou Fujian350118 China Guangxi Key Laboratory of Automatic Detecting Technology and Instruments Guilin University of Electronic Technology Guilin Guangxi541004 China School of Information and Communication Guilin University of Electronic Technology Guilin Guangxi541004 China

ISBN: (纸本)9783030697167

Ontology matching can solve the heterogeneity problem between two ontologies, and EA represents a state-of-the-art technique for matching ontologies. However, there are two defects concerning the EA-based ontology matching technique: (1) a reference alignment between two ontologies to be matched is required in advance;(2) the confidence of entity similarity measure is low computational complexity of measuring the similarity value is high. To overcome these drawbacks, in this paper, an Evolutionary Algorithm with Context-based Reasoning method (EA-CR) is proposed, where: (1) an approximate metric without the reference alignment is utilized for evaluating the alignment’s quality;(2) a Context-based Reasoning method is presented to distinguish the heterogeneous entities. The experimental results show that the proposed approach is effective. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Ontology

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Robust and Fast Measure of Information via Low-rank Representation

arXiv

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arXiv 2022年

作者： Dong, Yuxin Gong, Tieliang Yu, Shujian Chen, Hong Li, Chen School of Computer Science and Technology Xi’an Jiaotong University Xi’an710049 China Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering Ministry of Education Xi’an710049 China Machine Learning Group UiT - The Arctic University of Norway Norway College of Science Huazhong Agriculture University Wuhan430070 China Engineering Research Center of Intelligent Technology for Agriculture Ministry of Education Wuhan430070 China

The matrix-based Rényi’s entropy allows us to directly quantify information measures from given data, without explicit estimation of the underlying probability distribution. This intriguing property makes it widely applied in statistical inference and machine learning tasks. However, this information theoretical quantity is not robust against noise in the data, and is computationally prohibitive in large-scale applications. To address these issues, we propose a novel measure of information, termed low-rank matrix-based Rényi’s entropy, based on low-rank representations of infinitely divisible kernel matrices. The proposed entropy functional inherits the specialty of of the original definition to directly quantify information from data, but enjoys additional advantages including robustness and effective calculation. Specifically, our low-rank variant is more sensitive to informative perturbations induced by changes in underlying distributions, while being insensitive to uninformative ones caused by noises. Moreover, low-rank Rényi’s entropy can be efficiently approximated by random projection and Lanczos iteration techniques, reducing the overall complexity from O(n3) to O(n2s) or even O(ns2), where n is the number of data samples and s n. We conduct large-scale experiments to evaluate the effectiveness of this new information measure, demonstrating superior results compared to matrix-based Rényi’s entropy in terms of both performance and computational efficiency. Copyright © 2022, The Authors. All rights reserved.

关键词： Entropy

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Visual Feedback in Eye-Controlled Interaction: A Study on the Applicability for Pointing and Selection Tasks Across Different Vibration Environments

SSRN

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SSRN 2025年

作者： Ai, Mingyu Wei, Wanni Yang, Xiaonan Hao, Jia Niu, Hongwei Wang, Shuai Industrial and Systems Engineering Laboratory School of Mechanical Engineering Beijing Institute of Technology Beijing100081 China Yangtze Delta Region Academy Beijing Institute of Technology Jiaxing314019 China Key Laboratory of Industry Knowledge & Data Fusion Technology and Application Ministry of Industry and Information Technology Beijing Institute of Technology Beijing100081 China

Because of the advantages of short learning time and strong collaborative ability, eye-control interaction is considered to be a promising human-computer interaction method. In the process of eye-controlled interaction, the operator needs to choose more effective visual feedback to accurately understand the operation process, so as to reduce the wrong operation and the interaction burden. Meanwhile, vibration, as an unavoidable interaction environment in life, affects the performance of different visual feedback modalities to a great extent. Based on the above reasons, we want to explore the performance of different visual feedback in different vibration environments. First, we have investigated the performance of cross cursor and circle cursor in static, low vibration and high vibration environments to accomplish the pointing task. Second, we have investigated the performance of the time-delayed selection confirmation mechanism and selection sub-selection reconfirmation mechanism in the selection task under three vibration states. We found that in the pointing task, the circular cursor has a lower perceived workload and a longer onset of visual fatigue in the static environment. It turns out that the circular cursor is more suitable for the pointing task. In the selection task, the time-delayed selection mechanism had higher selection accuracy, lower perceptual workload, and higher subjective preference compared to the selection sub-selection reconfirmation mechanism, although there was no significant difference in the time to fatigue onset. The time-delayed selection mechanism was the better selection mechanism. © 2025, The Authors. All rights reserved.

关键词： Machine vibrations

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Face SSD: A Real-time Face Detector based on SSD

Face SSD: A Real-time Face Detector based on SSD

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第31届中国过程控制会议（CPCC 2020）

作者： Yunlin Shi Huijun Li Bin Ye School of Information and Control Engineering China University of Mining and Technology Xuzhou Key Laboratory of Artificial Intelligence and Big Data

Face detection has gotten some great breakthroughs in recent years. In many application scenarios, face detectors run on mobile and other embedded devices. However, it is difficult to achieve real-time and accurate processing when running on such mobile devices due to the limited computing resources. In this circumstance, most detectors cannot detect small face accurately or its detection speed would slow down. To address this challenge, we propose a novel face detector, named Face SSD whose basic framework is single shot multibox detector(SSD). In order to accelerate the detection speed and improve the detection accuracy, we make contributions in the following three aspects: We improve structure of ShuffleNet V2, and use it as backbone network;Then we propose modified prediction module(MPM) to improve recall of small face;Finally we introduce a scale-equitable face detection framework to match face better. Experimental results show that Face SSD runs 40 frames per second(FPS) on CPU and 110 FPS on GPU. We train Face SSD on WIDER FACE, a face detection benchmark. And achieve the excellent performance on FDDB, a benchmark for face detection in unconstrained settings.

关键词： SSD Face Detector ShuffleNet V2

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