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2022 9th International Conference on Dependable Systems and Their Applications (DSA)最新文献

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Bearing Fault Diagnosis based on Fixed Threshold Wavelet Transform and ELM 基于固定阈值小波变换和ELM的轴承故障诊断
2022 9th International Conference on Dependable Systems and Their Applications (DSA) Pub Date : 2022-08-01 DOI: 10.1109/DSA56465.2022.00068
Zhen Zhao, Jingchao Li, Bo Deng, Yulong Ying
{"title":"Bearing Fault Diagnosis based on Fixed Threshold Wavelet Transform and ELM","authors":"Zhen Zhao, Jingchao Li, Bo Deng, Yulong Ying","doi":"10.1109/DSA56465.2022.00068","DOIUrl":"https://doi.org/10.1109/DSA56465.2022.00068","url":null,"abstract":"In order to improve the efficiency and accuracy of bearing fault diagnosis, fixed threshold wavelet transform and extreme learning machine (ELM) are used to diagnose the fault data set. Firstly, the original signal underwent wavelet noise reduction by fixed threshold and heuristic threshold method, comparing SNR and mean square error, the processed signal was extracted, select cliff, margin factor, waveform factor, pulse factor, variance, mean, maximum and minimum 8 features, and the values were input into ELM for training and testing, and adjust the number of ELM neurons to check the fault identification accuracy, and compared with other diagnostic methods. The simulation results show that the proposed method provides a new idea for solving the bearing fault diagnosis problems.","PeriodicalId":208148,"journal":{"name":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129935185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Correlation between Training Set Perturbations and Robustness for CNN Models CNN模型训练集扰动与鲁棒性的关系
2022 9th International Conference on Dependable Systems and Their Applications (DSA) Pub Date : 2022-08-01 DOI: 10.1109/DSA56465.2022.00077
Zili Wu, Jun Ai, Minyan Lu, Jie Wang, Liang Yan
{"title":"The Correlation between Training Set Perturbations and Robustness for CNN Models","authors":"Zili Wu, Jun Ai, Minyan Lu, Jie Wang, Liang Yan","doi":"10.1109/DSA56465.2022.00077","DOIUrl":"https://doi.org/10.1109/DSA56465.2022.00077","url":null,"abstract":"Convolutional Neural Network (CNN) models perform well in image processing and are increasingly used in face recognition, self-driving cars, etc. However, CNN models are susceptible to perturbation and thus fail. Adding perturbation samples to the training sets is a method to improve the perturbation resistance of CNN models. In this paper, we give the methods including dataset construction, model retraining, and robustness metrics. The empirical study on the correlation between Project Gradient Descent (PGD) adversarial training and CNN model robustness is carried out in perturbation degree, proportion, and sample feature in training sets. The results show that the trend of CNN model robustness is related to the network architecture and it changes with the perturbation degree and proportion, and that perturbing images with one feature in the training set can improve the ability of CNN models to recognize images with that feature, and training for the scenario to which the CNN model is applied can improve the robustness of the model.","PeriodicalId":208148,"journal":{"name":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130707181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Automatic Localization of Potential Faults for Java Runtime Exceptions Java运行时异常潜在故障的自动定位
2022 9th International Conference on Dependable Systems and Their Applications (DSA) Pub Date : 2022-08-01 DOI: 10.1109/DSA56465.2022.00050
Hongning Miao, Shaoying Liu
{"title":"Automatic Localization of Potential Faults for Java Runtime Exceptions","authors":"Hongning Miao, Shaoying Liu","doi":"10.1109/DSA56465.2022.00050","DOIUrl":"https://doi.org/10.1109/DSA56465.2022.00050","url":null,"abstract":"Exceptions are unintended or undesired events that occur during program execution and have a negative effect on the robustness of the program. In the Java language, exceptions are divided into two types: checked exceptions and unchecked exceptions. A checked exception is required to be handled at compile time whereas an unchecked exception occurs at run time, so it is also called a runtime exception. Runtime exceptions can cause serious consequences like system crashes. Today's programs are still likely to contain a large number of runtime exceptions, such as null pointer exceptions and arithmetic exceptions in real-world bugs, indicating that the error-checking strategy is insufficient to clear the occurrence of runtime exceptions. In this paper, we propose a potential fault localization approach for Java runtime exceptions. It mainly uses regular expressions to support the detection of code fragments containing such exceptions and checklists to help the developer examine whether the exception may occur to cause errors.","PeriodicalId":208148,"journal":{"name":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125466928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Software Quality Evaluation Model based on Multiple Linear Regression and Fuzzy Comprehensive Evaluation Method 基于多元线性回归和模糊综合评价方法的软件质量评价模型
2022 9th International Conference on Dependable Systems and Their Applications (DSA) Pub Date : 2022-08-01 DOI: 10.1109/DSA56465.2022.00058
Chiyang Gao, Wenbing Luo, Jian Wang, Yingying Zhang
{"title":"Software Quality Evaluation Model based on Multiple Linear Regression and Fuzzy Comprehensive Evaluation Method","authors":"Chiyang Gao, Wenbing Luo, Jian Wang, Yingying Zhang","doi":"10.1109/DSA56465.2022.00058","DOIUrl":"https://doi.org/10.1109/DSA56465.2022.00058","url":null,"abstract":"At present the scale and complexity of software is increasing exponentially. It is very essential to establish software quality measurement model and method in order to measure software quality. By analyzing software quality characteristics, this paper put forward a software quality model. Then combine with multiple linear regression and fuzzy comprehensive evaluation method to build a quality evaluation algorithm. Finally we select some software projects to perform research verification on the software quality evaluation model and algorithm. And result shows the feasibility and effectiveness of the model and method.","PeriodicalId":208148,"journal":{"name":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121187699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Speech Instruction Recognition Method based on Stacking Ensemble Learning 基于叠加集成学习的语音指令识别方法
2022 9th International Conference on Dependable Systems and Their Applications (DSA) Pub Date : 2022-08-01 DOI: 10.1109/DSA56465.2022.00079
Jun Zhao, Qingguo Yan, Qinwei Dong, Xianguang Zha, Jun Wu, Zejiang He, Xindong Zhao, Xiaowen Zhang
{"title":"Speech Instruction Recognition Method based on Stacking Ensemble Learning","authors":"Jun Zhao, Qingguo Yan, Qinwei Dong, Xianguang Zha, Jun Wu, Zejiang He, Xindong Zhao, Xiaowen Zhang","doi":"10.1109/DSA56465.2022.00079","DOIUrl":"https://doi.org/10.1109/DSA56465.2022.00079","url":null,"abstract":"In the field of speech instruction recognition, deep learning technology can significantly improve recognition performance, which has become a new research hotspot. However, due to the increasing scale of data, it is difficult to achieve the ideal classification effect using a single model. Aiming at this problem, a speech instruction recognition method based on Stacking ensemble learning is proposed. This method combines deep learning with ensemble learning and applies it to the task of speech instruction recognition. Perform preprocessing and feature extraction on speech data to extract different audio features; build multiple deep models as primary classifiers, and input different audio features into different primary classifiers for training. A secondary classifier is constructed based on the SoftMax regression model, the output of the primary classifier is used as the input of the secondary classifier, and the stacking ensemble algorithm is used for learning to obtain the final recognition result of the speech instruction. The effectiveness of the method is demonstrated through speech instruction recognition experiments on large-scale datasets.","PeriodicalId":208148,"journal":{"name":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114801992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
UGDA: Data Augmentation Methods for Uyghur Language Named Entity Recognition 维吾尔语命名实体识别的数据增强方法
2022 9th International Conference on Dependable Systems and Their Applications (DSA) Pub Date : 2022-08-01 DOI: 10.1109/DSA56465.2022.00130
Yifei Ge, Azragul Yusup, Degang Chen, Hongliang Mao, Yingjie Cao
{"title":"UGDA: Data Augmentation Methods for Uyghur Language Named Entity Recognition","authors":"Yifei Ge, Azragul Yusup, Degang Chen, Hongliang Mao, Yingjie Cao","doi":"10.1109/DSA56465.2022.00130","DOIUrl":"https://doi.org/10.1109/DSA56465.2022.00130","url":null,"abstract":"Data augmentation methods can effectively improve model generalization performance and have been widely used to alleviate the overfitting problem in the case of low resources or class imbalance; however, the data noise generated by traditional data augmentation methods can make named entity recognition models sensitive and fragile. To address the above problems, this paper proposes an applicable Uyghur language named entity recognition data augmentation method (UGDA), which improves the traditional data augmentation methods to improve the quality of data augmentation sample generation. It is shown experimentally that using the data augmentation method on a self-constructed Uyghur language dataset improves F1 values by 2.97% compared to the baseline model ($text{BIGRU}+text{CRF}$) and by 1.81% compared to the baseline model ($text{CINO}+text{CRF}$), and the generated augmented samples are also applicable to the pre-trained model, fully demonstrating that the data augmentation method proposed in this paper can generate diverse and information-rich enhanced data, effectively improving the performance of the Uyghur language named entity recognition task.","PeriodicalId":208148,"journal":{"name":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115517297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Privacy-preserving Approach to Distributed Set-membership Estimation over Wireless Sensor Networks 无线传感器网络分布式集隶属度估计的隐私保护方法
2022 9th International Conference on Dependable Systems and Their Applications (DSA) Pub Date : 2022-08-01 DOI: 10.1109/DSA56465.2022.00137
Xuefeng Yang, Li Liu, Yinggang Zhang, Yihao Li, Pan Liu, Shili Ai
{"title":"A Privacy-preserving Approach to Distributed Set-membership Estimation over Wireless Sensor Networks","authors":"Xuefeng Yang, Li Liu, Yinggang Zhang, Yihao Li, Pan Liu, Shili Ai","doi":"10.1109/DSA56465.2022.00137","DOIUrl":"https://doi.org/10.1109/DSA56465.2022.00137","url":null,"abstract":"This paper focuses on the system on wireless sensor networks. The system is linear and the time of the system is discrete as well as variable, which named discrete-time linear time-varying systems (DLTVS). DLTVS are vulnerable to network attacks when exchanging information between sensors in the network, as well as putting their security at risk. A DLTVS with privacy-preserving is designed for this purpose. A set-membership estimator is designed by adding privacy noise obeying the Laplace distribution to state at the initial moment. Simultaneously, the differential privacy of the system is analyzed. On this basis, the real state of the system and the existence form of the estimator for the desired distribution are analyzed. Finally, simulation examples are given, which prove that the model after adding differential privacy can obtain accurate estimates and ensure the security of the system state.","PeriodicalId":208148,"journal":{"name":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123251569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Application of Software Cost Measurement in the Construction of Ship Information Management System 软件成本计量在船舶信息管理系统建设中的应用
2022 9th International Conference on Dependable Systems and Their Applications (DSA) Pub Date : 2022-08-01 DOI: 10.1109/DSA56465.2022.00071
Hanting Zhao, Jing Zhang, Xueqing Li, Zhen An, Lanmin Chen, Xiqiao Pang
{"title":"Application of Software Cost Measurement in the Construction of Ship Information Management System","authors":"Hanting Zhao, Jing Zhang, Xueqing Li, Zhen An, Lanmin Chen, Xiqiao Pang","doi":"10.1109/DSA56465.2022.00071","DOIUrl":"https://doi.org/10.1109/DSA56465.2022.00071","url":null,"abstract":"This paper studies the method and implementation steps of software cost measurement. Based on function point analysis, a ship task management system is taked as an example to explore the application of software cost measurement in the construction of ship information management system, which provides engineering practical experience for the implementation of software cost measurement and scientific quantification of software intellectual cost in ship field.","PeriodicalId":208148,"journal":{"name":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125875324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Development of an Octocopter Drone for Accompanying and Carrying Objects 伴随和携带物体的八旋翼无人机的研制
2022 9th International Conference on Dependable Systems and Their Applications (DSA) Pub Date : 2022-08-01 DOI: 10.1109/DSA56465.2022.00147
Shunsuke Wakamatsu, Bin Zhang, Hun-ok Lim
{"title":"Development of an Octocopter Drone for Accompanying and Carrying Objects","authors":"Shunsuke Wakamatsu, Bin Zhang, Hun-ok Lim","doi":"10.1109/DSA56465.2022.00147","DOIUrl":"https://doi.org/10.1109/DSA56465.2022.00147","url":null,"abstract":"In this paper, an octocopter drone for accompanying and carry the user's personal belongings is developed, which can be used during daily life, such as walking or jogging. This drone is designed with a four-layer structure and can carry objects up to 300[g]. Its size is reduced by dividing the eight brushless motors on the planes in two layers. It is equipped with two ESCs to drive eight brushless motors and one six-axis attitude sensor to control its posture. The effectiveness of the drone was confirmed through flight experiments.","PeriodicalId":208148,"journal":{"name":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126033095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Quantitative Measurement Method of Code Quality Evaluation Indicators based on Data Mining 基于数据挖掘的代码质量评价指标定量度量方法
2022 9th International Conference on Dependable Systems and Their Applications (DSA) Pub Date : 2022-08-01 DOI: 10.1109/DSA56465.2022.00094
Yikang Shao, Wu Liu, J. Ai, Chunhui Yang
{"title":"A Quantitative Measurement Method of Code Quality Evaluation Indicators based on Data Mining","authors":"Yikang Shao, Wu Liu, J. Ai, Chunhui Yang","doi":"10.1109/DSA56465.2022.00094","DOIUrl":"https://doi.org/10.1109/DSA56465.2022.00094","url":null,"abstract":"Software Code Quality Measurement is a systematic subject with a long history and rich theory. Since the 1960s, a large number of academic research on software code quality measurement methods have been generated. Many scholars have proposed software code quality measurement indicators and measurement methods, and given the measurement trend of evaluation indicators, and proposed a model to measure software quality. However, there are still some blanks in the quantitative evaluation of software code quality evaluation index. The software code quality measurement system is not complete enough to cover all aspects of software code quality from multiple perspectives. In addition, most studies have measured software code quality based on code inspection or code review, which has some limitations. This paper puts forward a software code quality evaluation system based on software network. On this basis, this paper proposes a quantitative measurement method of code quality evaluation indicators based on data mining. It provides a new idea for software quality evaluation or code quality evaluation.","PeriodicalId":208148,"journal":{"name":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127277684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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