{"title":"Intelligent Diagnosis Model Based on Optimized Probabilistic Neural Networks","authors":"Xiaohan Wei, Bin Xu, Yunqing Gong, Qing Zhang","doi":"10.1109/IAEAC47372.2019.8997801","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997801","url":null,"abstract":"Existing intelligent fault diagnosis models for equipment are insufficient in time-consuming and complication, making it hard to apply to practice. A novel intelligent diagnosis model has been carried out in this paper to improve this issue. Firstly, the process that experts realize the reasoning diagnosis by experience is analyzed to design an intelligent analysis flow. Based on the probabilistic neural network, the fault knowledge learning and reasoning from a large number of samples are carried out. Then the fault knowledge is mapped into a high-dimensional spatial distribution to realize the optimization of the probabilistic neural network. Finally, the fault bearing data is used to verify model performance.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134191314","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}
{"title":"Job Information Crawling, Visualization and Clustering of Job Search Websites","authors":"Zhen Yang, Sanxing Cao","doi":"10.1109/IAEAC47372.2019.8997713","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997713","url":null,"abstract":"With so much information available on job-hunting websites, the partial information provided by job-hunting websites is of little reference value to fresh graduates or cross-industry job seekers. This paper is a machine learning algorithm based on Python language. It makes a comprehensive analysis of job information and realizes the visualization and text clustering of job information. It has good applicability and is convenient to be extended to other fields.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133886699","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}
{"title":"Malicious nodes detection algorithm based on triangle module fusion operator in wireless sensor networks","authors":"Li Min, Gao Ranxin","doi":"10.1109/IAEAC47372.2019.8997710","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997710","url":null,"abstract":"The characteristics of wireless sensor networks and its deployment environment determine that wireless sensor networks is vulnerable to intrusion. In this paper, a malicious nodes detection algorithm based on triangle module fusion operator (MDTMO) is proposed for selective forwarding attack. The algorithm establishes the membership functions according to data packets that received and forwarded by the node, it uses the fusion method of triangle module operator to determine the suspected malicious node. Subsequently, the base station node detects the buffer occupancy and channel occupancy of the suspected malicious node to judge whether the network is in congestion. If the network quality is good, it is considered that the packets loss is due to the selective forwarding attack instead of congestion, so the node is judged to be a malicious node. The experimental results show that compared with the algorithm in [6], MDTMO has improved performance in both the malicious nodes detection rate and false positive rate.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133989262","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}
{"title":"Luminescent Polymer Thims in Microelectronic Sensors","authors":"Zhaoye Li, Zhaojun Xue, X. Ni","doi":"10.1109/IAEAC47372.2019.8997582","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997582","url":null,"abstract":"many electronic sensors need different colors when used in detections, indications and other different applications. These colors can come from europium ions taken polymer matrixes as basis materials. Colored sensors can be used in different integrated circuits. Though many integrated circuits are composed of semiconductors, they are easily cracked. Weak film-formation property hinders their markets and profits. In order to improve film formation, polymer matrixes are mixed in semiconductors and integrated circuits. Good film-formation property enhances furious competition and development of colored widescreen. In this paper, colored thin films were prepared, which could be used in ions sensors and widescreen.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134165667","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}
{"title":"Influence of Different Gas Parameters on Sensitivity of Thermal Expansion Gyroscope","authors":"Anrun Ren, L. Piao, Yuxing Wang","doi":"10.1109/IAEAC47372.2019.8997679","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997679","url":null,"abstract":"In this paper, the effects of gas heat capacity, thermal conductivity, viscosity coefficient and pressure on the sensitivity of thermal expansion fluid gyro were studied. The temperature field and flow field of sensing component were calculated by using COMSOL software. The flow velocity decreases with the increase of specific heat capacity, thermal conductivity of the working gas. But the flow velocity increases with the increase of pressure in the cavity. there is no significant change in flow velocity under different viscosity coefficients. The sensitivity of thermal expansion flow gyro increases with the increase of specific heat capacity of working gas and pressure in the cavity. But the sensitivity decreases with the increase of thermal conductivity and viscosity coefficient of the working gas.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131632676","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}
{"title":"Research on Time Concealed Channel Technology of Cloud Computing Platform Based on Shared Memory","authors":"Shenmin Zhang, Chencheng Wang, Qi-Shan Wang","doi":"10.1109/IAEAC47372.2019.8997733","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997733","url":null,"abstract":"Security issues severely restrict the development and popularization of cloud computing. As a way of data leakage, covert channel greatly threatens the security of cloud platform. This paper introduces the types and research status of covert channels, and discusses the classical detection and interference methods of time-covert channels on cloud platforms for shared memory time covert channels.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"14 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131840378","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}
{"title":"A Bi-Directional LSTM Model with Attention for Malicious URL Detection","authors":"Fangli Ren, Zhengwei Jiang, Jian Liu","doi":"10.1109/IAEAC47372.2019.8997947","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997947","url":null,"abstract":"Malicious URLs have become an important attack vector used by attackers to perpetrate cybercrimes, how to effectively detect malicious URLs is an important and urgent problem to be solved. Due to current feature based malicious URLs detection models need manual feature engineering, and deep learning based models have their limit on processing long sequences, which reduces the detection performance. We proposed an attentional based BiLSTM model AB-BiLSTM for the Malicious URLs detection in this paper. Firstly, the URLs were preprocessed and converted into word vectors by using pre-trained Word2Vec, then BiLSTM combined with an attention mechanism was trained to extract URL sequences features and classify them. The model was tested on collected dataset, the experimental results show that our proposed model can achieve the accuracy of 98.06%, the precision rate of 96.05, the recall rate of 95.79% and the F1 Score of 95.92%, which achieved better performance than other comparison traditional machine learning based and deep learning based models.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128940762","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}
{"title":"Revisiting the Reed-Muller Locally Correctable Codes","authors":"Feng Cheng","doi":"10.1109/IAEAC47372.2019.8997905","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997905","url":null,"abstract":"Local codes are a special kind of error-correcting codes. Locally correctable codes (LCCs) are one type of local codes. LCCs can efficiently recover any coordinate of its corrupted encoding by probing only a few but not all fraction of the corrupted word. A q-ary LCC which encodes length k messages to length N codewords with relative distance Δ has three parameters: r, δ and ϵ. r is called query complexity recording the number of queries. δ is called tolerance fraction measuring the relative distance between encoding codewords and its corrupted codes which can be locally decoded. ϵ is called error probability showing the coordinate of its corrupted encoding fail to be recovered with probability at most ϵ. One fundamental problem in LCCs is to determine the trade-off among rate, distance and query complexity. But for a specific LCC, focus is on query complexity, tolerance fraction and error probability. Reed-Muller codes (RM codes) are the most presentative LCCs. In order to understand the \"local\" more clearly, we revisit local correctors for RM codes and analyze them in detail: 1)The decoding procedures; 2)The role of Reed-Solomon codes (RS codes) in decoding RM LCCs; 3)Other local correctors for RM codes. How parameters including r, δ and ϵ change in RM LCCs have been analyzed in different correctors. We believe this paper can help us understand local codes better and grasp the main soul of this research direction.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131198803","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}
{"title":"A batch data based PSO identification method for Hammerstein systems","authors":"Zhixin Wang, Dongqing Wang","doi":"10.1109/IAEAC47372.2019.8997869","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997869","url":null,"abstract":"For a single input-output Hammerstein model with a polynomial nonlinear part, the standard particle swarm optimization (PSO) method loses some accuracy, due to computing fitness only based on a set of input-output data in each iteration. Therefore, to promote the identification accuracy, this paper investigates a batch data based particle swarm optimization (BD-PSO) method to identify parameters of the system. The simulation results prove that the BDPSO method has a fast convergence speed and has a good estimation accuracy.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133068843","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}
{"title":"The Maximum Generation Capacity Replaced by Wind Power Considering Voltage and Transient Stability","authors":"Anjia Mao, Jing Ma, Shengyu Kuai, Cong Chen, Qinyong Zhou, Shanshan Zhao","doi":"10.1109/IAEAC47372.2019.8997817","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997817","url":null,"abstract":"Under the circumstance that the global energy security and environmental issues becoming increasingly critical, developing new energy sources has become an important demand for sustainable development of energy and economies in China and even the world. As an important renewable energy source, wind power has been developed and applied in many places around the world. Since the output characteristics of wind power are greatly different from the conventional generation unit, when a large number of conventional generators in the system are replaced by wind power, the system voltage and power angle stability characteristics will change, which may even destroy the stability of the whole system. Therefore, Determine the maximum generating capacity that replaced by wind power is significant for the security of the power system. Based on the mathematical model of power system stability, by utilizing network equations and the simplified wind power model, this paper obtained the maximum generating capacity that can be replaced by wind power under the precondition of satisfying the power angle and voltage stability. Finally, the WSCC 3-machine 9-bus system is used to simulate and testify the method with the DigSILENT PowerFactory software. The outcome shows that the model and conclusions in the report are verified.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133389878","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}