Pub Date : 2022-08-01DOI: 10.1109/CCPQT56151.2022.00059
Yaoqun Huang, Qijing Zhang
Image enhancement is an important part of image information processing, image manipulation enhanced algorithm plays an important role in improving image quality, it involves all aspects of human life and social production. Because of the conditions of the scene, the visual effects and quality of images are often unable to meet the requirements, their quality is poor, this requires image enhancement technology to improve human visual effect, improve image quality. Compared with the deep learning method of big data, the traditional image manipulation enhanced algorithm does not need a larger number of learning samples, and has a small amount of calculation and fast processing speed, and is still the main way of image manipulation enhanced algorithm at present. This essay takes optical processing as a breakthrough point, the image manipulation enhanced algorithm is improved based on the principle of Abbe's image, and the High frequency image signal is enhanced by Unsharp Masking, the low frequency images are enhanced by Contrast Limited Adaptive Histogram Equalization. Finally, the high frequency and low frequency images are fused by weighted wavelet to achieve multi-dimensional enhancement of the image, obtain more detailed information of the image, and improve the image quality significantly.
{"title":"The Improved Algorithm Of Image Enhancement Based on Optical Fourier Transformation","authors":"Yaoqun Huang, Qijing Zhang","doi":"10.1109/CCPQT56151.2022.00059","DOIUrl":"https://doi.org/10.1109/CCPQT56151.2022.00059","url":null,"abstract":"Image enhancement is an important part of image information processing, image manipulation enhanced algorithm plays an important role in improving image quality, it involves all aspects of human life and social production. Because of the conditions of the scene, the visual effects and quality of images are often unable to meet the requirements, their quality is poor, this requires image enhancement technology to improve human visual effect, improve image quality. Compared with the deep learning method of big data, the traditional image manipulation enhanced algorithm does not need a larger number of learning samples, and has a small amount of calculation and fast processing speed, and is still the main way of image manipulation enhanced algorithm at present. This essay takes optical processing as a breakthrough point, the image manipulation enhanced algorithm is improved based on the principle of Abbe's image, and the High frequency image signal is enhanced by Unsharp Masking, the low frequency images are enhanced by Contrast Limited Adaptive Histogram Equalization. Finally, the high frequency and low frequency images are fused by weighted wavelet to achieve multi-dimensional enhancement of the image, obtain more detailed information of the image, and improve the image quality significantly.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","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":"127883201","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}
Pub Date : 2022-08-01DOI: 10.1109/CCPQT56151.2022.00069
He Wang, Haijun Li
Since the outbreak of the new crown epidemic, in order to curb the spread of the epidemic, the World Health Organization and others have carried out a series of work studies. At present, wearing a mask correctly when traveling in any public place is one of the effective means of protection. However, for example, in places with high traffic such as high-speed railway stations and airports, the efficiency of manual detection and supervision of mask wearing is low. Therefore, it is very necessary to use the automatic detection mask device to supervise the wearing of masks in real time. With the deepening of research on deep learning network models, in the real-time detection of masks Deep Learning-based network models, it is difficult to achieve satisfactory results in terms of precise and real-time in all performance. In order to improve the detection accuracy and other issues, based on the YOLOv5 object detecting algorithm, we first created a dataset MaskData for mask recognition by using the open source dataset downloaded from the Internet and adding various types of face mask datasets. Secondly, in the detection network, the DIOU_nms method is designed to be a replacement for the IOU in the NMS, and under the same parameters, the detection accuracy of occluded and overlapping targets is improved. Finally, replacing the GIOU loss function with the a-CIoU loss function can obtain higher-quality localized image regions faster and more accurately, generate bounding boxes and predict categories. The results of the experiment have demonstrated that the refined network can more accurately identify whether the face is wearing a mask, and to some extent, the detection accuracy was greatly improved. And using the designed GUI interface, the trained and improved YOLOv5 model can be directly called to perform real-time mask-wearing detection for videos and pictures.
{"title":"Mask Recognition Based on Improved YOLOv5 Target Detection Algorithm","authors":"He Wang, Haijun Li","doi":"10.1109/CCPQT56151.2022.00069","DOIUrl":"https://doi.org/10.1109/CCPQT56151.2022.00069","url":null,"abstract":"Since the outbreak of the new crown epidemic, in order to curb the spread of the epidemic, the World Health Organization and others have carried out a series of work studies. At present, wearing a mask correctly when traveling in any public place is one of the effective means of protection. However, for example, in places with high traffic such as high-speed railway stations and airports, the efficiency of manual detection and supervision of mask wearing is low. Therefore, it is very necessary to use the automatic detection mask device to supervise the wearing of masks in real time. With the deepening of research on deep learning network models, in the real-time detection of masks Deep Learning-based network models, it is difficult to achieve satisfactory results in terms of precise and real-time in all performance. In order to improve the detection accuracy and other issues, based on the YOLOv5 object detecting algorithm, we first created a dataset MaskData for mask recognition by using the open source dataset downloaded from the Internet and adding various types of face mask datasets. Secondly, in the detection network, the DIOU_nms method is designed to be a replacement for the IOU in the NMS, and under the same parameters, the detection accuracy of occluded and overlapping targets is improved. Finally, replacing the GIOU loss function with the a-CIoU loss function can obtain higher-quality localized image regions faster and more accurately, generate bounding boxes and predict categories. The results of the experiment have demonstrated that the refined network can more accurately identify whether the face is wearing a mask, and to some extent, the detection accuracy was greatly improved. And using the designed GUI interface, the trained and improved YOLOv5 model can be directly called to perform real-time mask-wearing detection for videos and pictures.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","volume":"137 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":"133171486","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}
In order to shorten the staining process of pathological slides and provide reference for the optimized design of Slide-Stainer. A scheduling algorithm for Slide-Stainer is proposed, which can optimize staining process of slides perform various staining method. First, the scheduling problem of Slide-Stainer is described, constants and variables used in this paper are defined. Second, a mathematical model containing four formula sets was constructed to constrain variables. Third, a hybrid two-stage scheduling algorithm was constructed to get the feasible solution to the problem. The solution contains the execution sequence of pathological slides and the workflow of each slide. The algorithm was coded based on Python language, and Queue insertion operation was used in the first stage to obtain the optimal execution sequence of pathological slides. The second stage consists of time-basic program and time-tune program, which calculates the workflow of each slide based on the execution sequence obtained in the first stage and performs calibration. Fourth, the effectiveness of the proposed algorithm is verified by simulation of actual staining method data, and the results obtained meet the requirements. Finally, the shortcomings of the mathematical model and algorithm are summarized, and the future work direction is described.
{"title":"A Hybrid Two-stage Scheduling Algorithm for Slide-Stainer","authors":"Debin Yang, Bingxian Liu, Kehui Wang, Xingshang Wang, Kewei Chen, F. Dong","doi":"10.1109/CCPQT56151.2022.00057","DOIUrl":"https://doi.org/10.1109/CCPQT56151.2022.00057","url":null,"abstract":"In order to shorten the staining process of pathological slides and provide reference for the optimized design of Slide-Stainer. A scheduling algorithm for Slide-Stainer is proposed, which can optimize staining process of slides perform various staining method. First, the scheduling problem of Slide-Stainer is described, constants and variables used in this paper are defined. Second, a mathematical model containing four formula sets was constructed to constrain variables. Third, a hybrid two-stage scheduling algorithm was constructed to get the feasible solution to the problem. The solution contains the execution sequence of pathological slides and the workflow of each slide. The algorithm was coded based on Python language, and Queue insertion operation was used in the first stage to obtain the optimal execution sequence of pathological slides. The second stage consists of time-basic program and time-tune program, which calculates the workflow of each slide based on the execution sequence obtained in the first stage and performs calibration. Fourth, the effectiveness of the proposed algorithm is verified by simulation of actual staining method data, and the results obtained meet the requirements. Finally, the shortcomings of the mathematical model and algorithm are summarized, and the future work direction is described.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","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":"117288876","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}
Pub Date : 2022-08-01DOI: 10.1109/CCPQT56151.2022.00046
Juan Fang, Zhenzhen Liu, Shuopeng Li, Siqi Chen, Huijing Yang
To solve the problem of communication delay and resource shortage when multiple users offload tasks at the same time in mobile edge computing (MEC), the deep reinforcement learning algorithm based on non-orthogonal multiple access (NOMA) technology was proposed to optimize users' communication resource allocation. Firstly, the taboo tag deep Q-network algorithm was used to train the relationship between users and subchannels at the users grouping stage, then the deep deterministic policy gradient algorithm was used to allocate users transmission power who sharing subchannel. The simulation results display that the proposed algorithm perform more stable than other reinforcement learning and traditional algorithm, moreover, the system sum rate have been significantly improved when multiple edge users offload tasks.
{"title":"MEC Communication Resource Allocation Optimization Algorithm Based on NOMA","authors":"Juan Fang, Zhenzhen Liu, Shuopeng Li, Siqi Chen, Huijing Yang","doi":"10.1109/CCPQT56151.2022.00046","DOIUrl":"https://doi.org/10.1109/CCPQT56151.2022.00046","url":null,"abstract":"To solve the problem of communication delay and resource shortage when multiple users offload tasks at the same time in mobile edge computing (MEC), the deep reinforcement learning algorithm based on non-orthogonal multiple access (NOMA) technology was proposed to optimize users' communication resource allocation. Firstly, the taboo tag deep Q-network algorithm was used to train the relationship between users and subchannels at the users grouping stage, then the deep deterministic policy gradient algorithm was used to allocate users transmission power who sharing subchannel. The simulation results display that the proposed algorithm perform more stable than other reinforcement learning and traditional algorithm, moreover, the system sum rate have been significantly improved when multiple edge users offload tasks.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","volume":"13 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":"125629798","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}
Pub Date : 2022-08-01DOI: 10.1109/CCPQT56151.2022.00020
Zhihao Li, Xinying Chen, Biao Zhang, Jiatao Meng, Yang Shen, Hang Su, Chuanlong Xu
Background oriented schlieren tomography (BOST) is an effective reconstruction technique of unsteady 3D refractive index field. In this paper, the equivalent optical system model of lens is used to replace the pinhole model and simulate the imaging process of background oriented schlieren accurately. Based on the optical flow equation reconstruction model, the reconstruction process of turbulent flame are simulated. The effects of different reconstruction methods on the reconstruction results are discussed. Finally, the feasibility of the reconstruction method is verified by experiments.
{"title":"3D Flow Visualization via Background Oriented Schlieren Tomography","authors":"Zhihao Li, Xinying Chen, Biao Zhang, Jiatao Meng, Yang Shen, Hang Su, Chuanlong Xu","doi":"10.1109/CCPQT56151.2022.00020","DOIUrl":"https://doi.org/10.1109/CCPQT56151.2022.00020","url":null,"abstract":"Background oriented schlieren tomography (BOST) is an effective reconstruction technique of unsteady 3D refractive index field. In this paper, the equivalent optical system model of lens is used to replace the pinhole model and simulate the imaging process of background oriented schlieren accurately. Based on the optical flow equation reconstruction model, the reconstruction process of turbulent flame are simulated. The effects of different reconstruction methods on the reconstruction results are discussed. Finally, the feasibility of the reconstruction method is verified by experiments.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","volume":"100 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":"126073598","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}
Pub Date : 2022-08-01DOI: 10.1109/CCPQT56151.2022.00037
Yanxu Zhu, Hong Wen, Peng Zhang, Wen Han, Fan Sun, Jia Jia
Recent trends in the convergence of edge computing and artificial intelligence (AI) have led to a new paradigm of “edge intelligence”, which are more vulnerable to attack such as data and model poisoning and evasion of attacks. This paper proposes a white-box poisoning attack against online regression model for edge intelligence environment, which aim to prepare the protection methods in the future. Firstly, the new method selects data points from original stream with maximum loss by two selection strategies; Secondly, it pollutes these points with gradient ascent strategy. At last, it injects polluted points into original stream being sent to target model to complete the attack process. We extensively evaluate our proposed attack on open dataset, the results of which demonstrate the effectiveness of the novel attack method and the real implications of poisoning attack in a case study electric energy prediction application.
{"title":"Poisoning Attack against Online Regression Learning with Maximum Loss for Edge Intelligence","authors":"Yanxu Zhu, Hong Wen, Peng Zhang, Wen Han, Fan Sun, Jia Jia","doi":"10.1109/CCPQT56151.2022.00037","DOIUrl":"https://doi.org/10.1109/CCPQT56151.2022.00037","url":null,"abstract":"Recent trends in the convergence of edge computing and artificial intelligence (AI) have led to a new paradigm of “edge intelligence”, which are more vulnerable to attack such as data and model poisoning and evasion of attacks. This paper proposes a white-box poisoning attack against online regression model for edge intelligence environment, which aim to prepare the protection methods in the future. Firstly, the new method selects data points from original stream with maximum loss by two selection strategies; Secondly, it pollutes these points with gradient ascent strategy. At last, it injects polluted points into original stream being sent to target model to complete the attack process. We extensively evaluate our proposed attack on open dataset, the results of which demonstrate the effectiveness of the novel attack method and the real implications of poisoning attack in a case study electric energy prediction application.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","volume":"58 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":"126545512","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}
Pub Date : 2022-08-01DOI: 10.1109/CCPQT56151.2022.00023
Changquan Qiu, Yanrong Yuan, Jinghua Sun, Zhichao Xue, Jinghui Lan
The standard Telemetry Network System(TmNS) has been officially incorporated into the IRIG 106–17 standard developed by the Range Instrument Group IRIG, a subsidiary of the RCC, in 2017 and has been gradually improved. TmNS brings new capabilities to the traditional telemetry system and represents the development direction of the next generation telemetry system. Time synchronization is the key technology of TmNS, which is the basis of wireless network connection between multiple test objects and multiple ground stations. In order to adapt to the situation of high packet loss rate of wireless link and high requirement of time synchronization accuracy, an improved time synchronization protocol algorithm is proposed and evaluated by simulation.
遥测网络系统(TmNS)标准已于2017年正式纳入RCC下属的Range Instrument Group IRIG制定的IRIG 106-17标准，并逐步完善。TmNS为传统遥测系统带来了新的功能，代表了下一代遥测系统的发展方向。时间同步是TmNS的关键技术，是实现多个测试对象与多个地面站之间无线网络连接的基础。为了适应无线链路丢包率高、对时间同步精度要求高的情况，提出了一种改进的时间同步协议算法，并进行了仿真评估。
{"title":"Research on Improvement of Time Synchronization Protocol in Telemetry Network System (TmNS)","authors":"Changquan Qiu, Yanrong Yuan, Jinghua Sun, Zhichao Xue, Jinghui Lan","doi":"10.1109/CCPQT56151.2022.00023","DOIUrl":"https://doi.org/10.1109/CCPQT56151.2022.00023","url":null,"abstract":"The standard Telemetry Network System(TmNS) has been officially incorporated into the IRIG 106–17 standard developed by the Range Instrument Group IRIG, a subsidiary of the RCC, in 2017 and has been gradually improved. TmNS brings new capabilities to the traditional telemetry system and represents the development direction of the next generation telemetry system. Time synchronization is the key technology of TmNS, which is the basis of wireless network connection between multiple test objects and multiple ground stations. In order to adapt to the situation of high packet loss rate of wireless link and high requirement of time synchronization accuracy, an improved time synchronization protocol algorithm is proposed and evaluated by simulation.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","volume":"42 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":"128307241","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}
Pub Date : 2022-08-01DOI: 10.1109/CCPQT56151.2022.00033
Wen Han, Hong Wen, Peiyao Wang, Yanxu Zhu
False data injection attacks (FDIAs) pose a great threat to the data security of microgrid. The day-ahead scheduling strategy of microgrid is in turn mainly based on microgrid operation data. Under FDIAs, it is important for the efficiency and economic cost of microgrid scheduling to properly repair the attacked data and optimize the scheduling using predictive data from deep learning. In this work, we model the economic cost of microgrid scheduling, use deep learning prediction algorithm to predict data based on historical values of microgrid operation, and repair the attacked data by the predicted data, and combine the optimization algorithm to optimize microgrid day-ahead power scheduling to make scheduling more economical and efficient. By this way, the malicious action was corrected and system recover as normal performance to avoid the economical lost that FDIAs aimed to attrite.
{"title":"Microgrid Scheduling Optimization under False Data Injection Attack","authors":"Wen Han, Hong Wen, Peiyao Wang, Yanxu Zhu","doi":"10.1109/CCPQT56151.2022.00033","DOIUrl":"https://doi.org/10.1109/CCPQT56151.2022.00033","url":null,"abstract":"False data injection attacks (FDIAs) pose a great threat to the data security of microgrid. The day-ahead scheduling strategy of microgrid is in turn mainly based on microgrid operation data. Under FDIAs, it is important for the efficiency and economic cost of microgrid scheduling to properly repair the attacked data and optimize the scheduling using predictive data from deep learning. In this work, we model the economic cost of microgrid scheduling, use deep learning prediction algorithm to predict data based on historical values of microgrid operation, and repair the attacked data by the predicted data, and combine the optimization algorithm to optimize microgrid day-ahead power scheduling to make scheduling more economical and efficient. By this way, the malicious action was corrected and system recover as normal performance to avoid the economical lost that FDIAs aimed to attrite.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","volume":"27 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":"133955847","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}
Pub Date : 2022-08-01DOI: 10.1109/CCPQT56151.2022.00060
Haitao Wang, Lina Tan, Yang Zhang, Qiwen Gong, Shan Zhang, Yanan Ren, Tao He
With the rapid advancement of the informatization process of the coal industry, applications based on the Internet of Things and intelligent processing technologies for smart mines have sprung up. The sharing and aggregation of various colliery automation system data is the core foundation for the realization of intelligent mine applications. The resolution of integrity and real-time issues in data sharing determines the availability of upper-level intelligent applications. This paper proposes a set of smart mine specifications. It regulates coal mine data sharing behavior from three perspectives: data collection, data transmission, and data storage. The data source specification specifies the protocol for data collection and transmission. The evaluation indicators and governance methods are described in the data quality specification. It sets data reliability sharing standards based on the characteristics of each business system. The labels defined in the data storage specification model realize the efficient management of data indexing which can be used by professional and non-professional users in the coal industry. We constructed an experimental system based on real measured data from a certain colliery. The system can collect, manage and store the data from various automation systems following the specifications.
{"title":"A Management Specification for Big Data Sharing in Smart Mine","authors":"Haitao Wang, Lina Tan, Yang Zhang, Qiwen Gong, Shan Zhang, Yanan Ren, Tao He","doi":"10.1109/CCPQT56151.2022.00060","DOIUrl":"https://doi.org/10.1109/CCPQT56151.2022.00060","url":null,"abstract":"With the rapid advancement of the informatization process of the coal industry, applications based on the Internet of Things and intelligent processing technologies for smart mines have sprung up. The sharing and aggregation of various colliery automation system data is the core foundation for the realization of intelligent mine applications. The resolution of integrity and real-time issues in data sharing determines the availability of upper-level intelligent applications. This paper proposes a set of smart mine specifications. It regulates coal mine data sharing behavior from three perspectives: data collection, data transmission, and data storage. The data source specification specifies the protocol for data collection and transmission. The evaluation indicators and governance methods are described in the data quality specification. It sets data reliability sharing standards based on the characteristics of each business system. The labels defined in the data storage specification model realize the efficient management of data indexing which can be used by professional and non-professional users in the coal industry. We constructed an experimental system based on real measured data from a certain colliery. The system can collect, manage and store the data from various automation systems following the specifications.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","volume":"47 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":"128564025","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}
Pub Date : 2022-08-01DOI: 10.1109/CCPQT56151.2022.00063
Yuxia Yang, C. Meng, Chunsheng Zhang, Tu Ya
Odor detection plays an irreplaceable role in food safety, environmental monitoring, medical treatment and disease diagnosis. The traditional artificial electronic nose can be used to some extent, but its performance is far inferior to the biological olfactory field in many aspects, for instance, detection range, response rate, specificity, etc. Three kinds of waves propagate on surface acoustic wave (SAW) device. They are longitudinal wave, Rayleigh waves and leaky Rayleigh wave. We also pay attention the SAW in a SAW device in with ethanol, Cp-Lip1 odorant binding protein and 5 odorant molecules are used as liquid media. Then, we compare between the theoretical and experimental velocities to verify the effectiveness of the SAW device. The results of surface acoustic wave propagation velocity of odorant binding proteins and odorant molecules show that some odorant molecules can be recognized by surface acoustic wave devices using odorant binding proteins.
{"title":"Research on Detection Technology of Bio-electronic Nose Based on SAW Devices","authors":"Yuxia Yang, C. Meng, Chunsheng Zhang, Tu Ya","doi":"10.1109/CCPQT56151.2022.00063","DOIUrl":"https://doi.org/10.1109/CCPQT56151.2022.00063","url":null,"abstract":"Odor detection plays an irreplaceable role in food safety, environmental monitoring, medical treatment and disease diagnosis. The traditional artificial electronic nose can be used to some extent, but its performance is far inferior to the biological olfactory field in many aspects, for instance, detection range, response rate, specificity, etc. Three kinds of waves propagate on surface acoustic wave (SAW) device. They are longitudinal wave, Rayleigh waves and leaky Rayleigh wave. We also pay attention the SAW in a SAW device in with ethanol, Cp-Lip1 odorant binding protein and 5 odorant molecules are used as liquid media. Then, we compare between the theoretical and experimental velocities to verify the effectiveness of the SAW device. The results of surface acoustic wave propagation velocity of odorant binding proteins and odorant molecules show that some odorant molecules can be recognized by surface acoustic wave devices using odorant binding proteins.","PeriodicalId":235893,"journal":{"name":"2022 International Conference on Computing, Communication, Perception and Quantum Technology (CCPQT)","volume":"21 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":"132836092","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}
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