Recently, the positioning technology has advanced rapidly, however, the outdoor positioning technology with high positioning accuracy can't be applied effectively indoors. Therefore applied to indoor positioning methods such as inertial positioning system has always been a research hot spot. This paper presents an indoor location method integrating inertial data, map information and pedestrian motion state. This method involves collecting the inertial data of pedestrian motion in real-time, calculating the current coordinates of the pedestrian, detecting pedestrian movement state in real-time, and correcting positioning coordinates. Based on the characteristics of indoor key landmarks and the motion state characteristics of pedestrians at key landmarks. Firstly, collecting the motion data of pedestrians by inertial sensors placed on the pedestrian's waist, then extract the features from the data and use the classifier to establish the pedestrian movement state model. Last, utilizing this model to identify the pedestrian motion state, and then infer the key landmark type where the pedestrian is located. Through the simulation demonstrate that this method can make the positioning error always be in a narrower range, fulfill the indoor scenario of low precision inertial sensor positioning requirements, and has the value of application and promotion.
{"title":"An indoor positioning method integrating inertial data, map information and pedestrian motion state","authors":"Jiqiu Cui","doi":"10.1145/3558819.3565106","DOIUrl":"https://doi.org/10.1145/3558819.3565106","url":null,"abstract":"Recently, the positioning technology has advanced rapidly, however, the outdoor positioning technology with high positioning accuracy can't be applied effectively indoors. Therefore applied to indoor positioning methods such as inertial positioning system has always been a research hot spot. This paper presents an indoor location method integrating inertial data, map information and pedestrian motion state. This method involves collecting the inertial data of pedestrian motion in real-time, calculating the current coordinates of the pedestrian, detecting pedestrian movement state in real-time, and correcting positioning coordinates. Based on the characteristics of indoor key landmarks and the motion state characteristics of pedestrians at key landmarks. Firstly, collecting the motion data of pedestrians by inertial sensors placed on the pedestrian's waist, then extract the features from the data and use the classifier to establish the pedestrian movement state model. Last, utilizing this model to identify the pedestrian motion state, and then infer the key landmark type where the pedestrian is located. Through the simulation demonstrate that this method can make the positioning error always be in a narrower range, fulfill the indoor scenario of low precision inertial sensor positioning requirements, and has the value of application and promotion.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124970984","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}
Accurately predicting the mortality of ICU patients is a tricky problem in modern clinical medicine. Promoting the mortality prediction can effectively improve the ICU utilization and allow patients in need to enter the ICU as soon as possible. Due to the incomplete collection of patient vital signs, the prediction of patient death usually involves a large component of manual intervention. For example, doctors need to pre-classify patient background information and manually judge whether the patient will die In the light of their experience, etc. There is no complete set of vector features that can be used. ICU mortality prediction in ICU still lacks a unified vector for feature selection. This paper used random forest to predict and analysed ICU patient death according to the data set downloaded from Kaggle website which emphasis on the chronic condition of diabetes, through data from MIT's GOSSIS (Global Open-Source Severity of Illness Score) initiative. Our model approaches encouraging performance (Accuracy=0.9241, F1-score=0.96, Recall=0.99, Precision=0.93), and the most important features are selected, the feasibility of unified vector modelling is proved.
{"title":"Study of ICU Mortality Prediction and Analysis based on Random Forest","authors":"Z. Li","doi":"10.1145/3558819.3565171","DOIUrl":"https://doi.org/10.1145/3558819.3565171","url":null,"abstract":"Accurately predicting the mortality of ICU patients is a tricky problem in modern clinical medicine. Promoting the mortality prediction can effectively improve the ICU utilization and allow patients in need to enter the ICU as soon as possible. Due to the incomplete collection of patient vital signs, the prediction of patient death usually involves a large component of manual intervention. For example, doctors need to pre-classify patient background information and manually judge whether the patient will die In the light of their experience, etc. There is no complete set of vector features that can be used. ICU mortality prediction in ICU still lacks a unified vector for feature selection. This paper used random forest to predict and analysed ICU patient death according to the data set downloaded from Kaggle website which emphasis on the chronic condition of diabetes, through data from MIT's GOSSIS (Global Open-Source Severity of Illness Score) initiative. Our model approaches encouraging performance (Accuracy=0.9241, F1-score=0.96, Recall=0.99, Precision=0.93), and the most important features are selected, the feasibility of unified vector modelling is proved.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116575005","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 solve the problems of low user satisfaction and high customer complaint rate in campus logistics service, a campus logistics improvement model based on Fuzzy Kano model and IPA analysis is constructed to determine the improvement weight of campus logistics service quality elements. Through empirical research, users' satisfaction and perceived importance of campus logistics service quality elements are obtained, and the optimal solution is obtained, It verifies the feasibility and effectiveness of the model, and provides practical guidance for improving the elements of campus logistics service quality.
{"title":"Research on campus logistics performance intelligent evaluation based on Fuzzy Kano model and IPA analysis","authors":"Yi Cao","doi":"10.1145/3558819.3565075","DOIUrl":"https://doi.org/10.1145/3558819.3565075","url":null,"abstract":"In order to solve the problems of low user satisfaction and high customer complaint rate in campus logistics service, a campus logistics improvement model based on Fuzzy Kano model and IPA analysis is constructed to determine the improvement weight of campus logistics service quality elements. Through empirical research, users' satisfaction and perceived importance of campus logistics service quality elements are obtained, and the optimal solution is obtained, It verifies the feasibility and effectiveness of the model, and provides practical guidance for improving the elements of campus logistics service quality.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131409540","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}
A self powered CO2 sensor with energy optimization and intelligent measurement concept based on stm300 radio module is designed and implemented. Based on energy acquisition technology, with solar panel as the power supply core, stm300 module as the control core and gss-cozir CO2 sensor as the acquisition module, the effective power supply and accurate concentration acquisition of CO2 sensor in photovoltaic mode are realized. Aiming at the problem of short service life of sensor power supply, a dynamic power consumption analysis method of balancing power supply by using its working cycle and low-power off mode is proposed, and an automatic calibration method for error under long-term trial is given.
{"title":"Design and implementation of carbon dioxide sensor based on energy acquisition technology","authors":"Ren Chen, Hon-ting. Cheng","doi":"10.1145/3558819.3565173","DOIUrl":"https://doi.org/10.1145/3558819.3565173","url":null,"abstract":"A self powered CO2 sensor with energy optimization and intelligent measurement concept based on stm300 radio module is designed and implemented. Based on energy acquisition technology, with solar panel as the power supply core, stm300 module as the control core and gss-cozir CO2 sensor as the acquisition module, the effective power supply and accurate concentration acquisition of CO2 sensor in photovoltaic mode are realized. Aiming at the problem of short service life of sensor power supply, a dynamic power consumption analysis method of balancing power supply by using its working cycle and low-power off mode is proposed, and an automatic calibration method for error under long-term trial is given.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134486055","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 recent years, with the rapid spread of Internet of Things technology, wireless communication technology has been developed and applied faster. Due to the rapid development of the Internet and modern communication technology, ZigBee wireless transmission technology based on IEEE802.15.4 has become another promising future after Bluetooth communication due to its advantages of short distance, less loss of functions, low cost and strong security. wireless transmission technology. In the future, ZigBee technology will become a short-range wireless transmission technology with competitive advantages. This paper introduces the definition and characteristics of ZigBee wireless transmission technology in detail, analyzes the application of ZigBee in some fields, and briefly discusses the application prospect. On the basis of understanding the knowledge of ZigBee technology wireless monitoring network system, and on the premise of studying its latest standard communication protocol, a wireless monitoring system based on this technology is designed, which provides a certain reference value for wide application.
{"title":"Zigbee Wireless Communication Technology and Its Application","authors":"Xueli Wang","doi":"10.1145/3558819.3561832","DOIUrl":"https://doi.org/10.1145/3558819.3561832","url":null,"abstract":"In recent years, with the rapid spread of Internet of Things technology, wireless communication technology has been developed and applied faster. Due to the rapid development of the Internet and modern communication technology, ZigBee wireless transmission technology based on IEEE802.15.4 has become another promising future after Bluetooth communication due to its advantages of short distance, less loss of functions, low cost and strong security. wireless transmission technology. In the future, ZigBee technology will become a short-range wireless transmission technology with competitive advantages. This paper introduces the definition and characteristics of ZigBee wireless transmission technology in detail, analyzes the application of ZigBee in some fields, and briefly discusses the application prospect. On the basis of understanding the knowledge of ZigBee technology wireless monitoring network system, and on the premise of studying its latest standard communication protocol, a wireless monitoring system based on this technology is designed, which provides a certain reference value for wide application.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131861379","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}
The text of power grid business cost demand is complex and the description cannot be unified and standardized. As a single text description involves multiple business types, it is difficult to judge the business cost type. This paper presents a classification method of clustering specific cost types for business cost requirements text. Firstly, the business cost requirement text is transformed, and the key weight parameters in the Chinese word segmentation model are improved iteratively according to the cost representation report to obtain the global semantic vector. At the same time, the weights of recognition loss values of different samples were dynamically modified according to the difficulty of sample fitting. In this paper, the existing text clustering model is improved by k-means clustering algorithm model, and the cost types of 450 real business cost demand texts in the province are identified. The results show that the performance index value of the text classification method proposed in this paper is better than the commonly used text classification method, and the F1 value of the algorithm in this paper reaches more than 93%. The value of F1 is more than 3.5% higher than that of single BERT model.
{"title":"Research on classification method of business requirement text based on deep learning","authors":"Weibing Ding, S. Jin, Yan Ren, Fangzhou Liu","doi":"10.1145/3558819.3565082","DOIUrl":"https://doi.org/10.1145/3558819.3565082","url":null,"abstract":"The text of power grid business cost demand is complex and the description cannot be unified and standardized. As a single text description involves multiple business types, it is difficult to judge the business cost type. This paper presents a classification method of clustering specific cost types for business cost requirements text. Firstly, the business cost requirement text is transformed, and the key weight parameters in the Chinese word segmentation model are improved iteratively according to the cost representation report to obtain the global semantic vector. At the same time, the weights of recognition loss values of different samples were dynamically modified according to the difficulty of sample fitting. In this paper, the existing text clustering model is improved by k-means clustering algorithm model, and the cost types of 450 real business cost demand texts in the province are identified. The results show that the performance index value of the text classification method proposed in this paper is better than the commonly used text classification method, and the F1 value of the algorithm in this paper reaches more than 93%. The value of F1 is more than 3.5% higher than that of single BERT model.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132601353","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}
The key challenges of the financial industry are the volatility and complexity of the stock market, so how to make optimal trading strategy to maximize the total profit in all market conditions has become an important issue to the professional researchers and investors. This paper describes a hybrid stock trading strategy model based on long short-term memory (LSTM) networks. The Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm and sample entropy (SE), combined with LSTM, are used to construct the integrated prediction model, which has dramatically improved the forecast precision. On the premise of accurate prediction, the extreme value theory (EVT) is introduced to improve the predictive ability of dynamic value at risk (VaR), which can manage the risk of portfolio. To forecast stock trends, the approach of analytic hierarchy process (AHP) is applied to assign weights to related factors. The final trading decisions are made by establishing trading signals and scoring models. Based on models above, the integrated trading strategy model is constructed as an automated trading decision tool. Taking Gold and Crude oil as examples, the profit results are proved to be decent through trading simulations.
{"title":"Algorithm Optimization Model of Trading Strategy based on CEEMDAN-SE-LSTM and Artificial Intelligence","authors":"Jingwen Zhang, Lei Fan, Kaijie Gu","doi":"10.1145/3558819.3565218","DOIUrl":"https://doi.org/10.1145/3558819.3565218","url":null,"abstract":"The key challenges of the financial industry are the volatility and complexity of the stock market, so how to make optimal trading strategy to maximize the total profit in all market conditions has become an important issue to the professional researchers and investors. This paper describes a hybrid stock trading strategy model based on long short-term memory (LSTM) networks. The Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm and sample entropy (SE), combined with LSTM, are used to construct the integrated prediction model, which has dramatically improved the forecast precision. On the premise of accurate prediction, the extreme value theory (EVT) is introduced to improve the predictive ability of dynamic value at risk (VaR), which can manage the risk of portfolio. To forecast stock trends, the approach of analytic hierarchy process (AHP) is applied to assign weights to related factors. The final trading decisions are made by establishing trading signals and scoring models. Based on models above, the integrated trading strategy model is constructed as an automated trading decision tool. Taking Gold and Crude oil as examples, the profit results are proved to be decent through trading simulations.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133530955","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}
Affected by repeated discharges, the frequency modulation control deviation and voltage fundamental frequency fluctuate greatly in each area of the power system. For this reason, a power system coordinated control method based on source-grid-load-storage optimization is proposed. The model gives full play to the effect of frequency regulation to excavate the system's operational synergy ability to absorb uncertainty at the decision-making level, and effectively considers the unit's backup response process, so as to clarify for whom the backup is prepared, and to achieve a friendly connection between scheduling and control. The comparative analysis of the simulation results and the results of other solving methods shows that the algorithm can effectively take into account the global convergence and the diversity of Pareto non-inferior scheduling schemes, and has high efficiency and robustness.
{"title":"Research on Intelligent Business Collaboration System of Computer Cloud and Edge Computing","authors":"Wenpan Liu, Lei Wen, Y. Li","doi":"10.1145/3558819.3565224","DOIUrl":"https://doi.org/10.1145/3558819.3565224","url":null,"abstract":"Affected by repeated discharges, the frequency modulation control deviation and voltage fundamental frequency fluctuate greatly in each area of the power system. For this reason, a power system coordinated control method based on source-grid-load-storage optimization is proposed. The model gives full play to the effect of frequency regulation to excavate the system's operational synergy ability to absorb uncertainty at the decision-making level, and effectively considers the unit's backup response process, so as to clarify for whom the backup is prepared, and to achieve a friendly connection between scheduling and control. The comparative analysis of the simulation results and the results of other solving methods shows that the algorithm can effectively take into account the global convergence and the diversity of Pareto non-inferior scheduling schemes, and has high efficiency and robustness.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117336320","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}
Zhi Xiong, Feng Chen, Hongsheng Zhao, Qiliang Wu, Junqi Wang
In order to meet the requirements of high torque response speed of electric excitation synchronous motor to improve renewable energy consumption, this paper analyzes the essential reason for the improvement of torque response speed of current-coordinated control strategy on electric excitation synchronous motor. The effectiveness of the control strategy is verified by comparing the simulation analysis with the traditional air gap flux orientation vector control strategy.
{"title":"Dynamic Characteristic Analysis of Current-coordinated Control Strategy to Improve Renewable Energy Consumption","authors":"Zhi Xiong, Feng Chen, Hongsheng Zhao, Qiliang Wu, Junqi Wang","doi":"10.1145/3558819.3565112","DOIUrl":"https://doi.org/10.1145/3558819.3565112","url":null,"abstract":"In order to meet the requirements of high torque response speed of electric excitation synchronous motor to improve renewable energy consumption, this paper analyzes the essential reason for the improvement of torque response speed of current-coordinated control strategy on electric excitation synchronous motor. The effectiveness of the control strategy is verified by comparing the simulation analysis with the traditional air gap flux orientation vector control strategy.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114792175","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 reduce the power consumption of carbon dioxide sensor and meet the application needs of multi-sensor long-distance load of coal mine safety monitoring system, carbon dioxide gas molecules are used in 4.2 ∼ 4.32 μ A low-power carbon dioxide sensor based on led-pr optical structure is designed. Based on the analysis of the principle of infrared carbon dioxide detection, LED light source and PR detector are studied.The design principle of LED light source driving circuit and the working mechanism of realizing low-power measurement, photoelectric signal processing circuit and software program flow are introduced. The power consumption of infrared carbon dioxide sensor is reduced to 0.06 W, which meets the needs of low-power detection applications in coal mines.
{"title":"Research on carbon dioxide sensor based on non dispersive infrared technology","authors":"Zhixing Li, Xuemei Li, Yurong Wang, Peng Yu","doi":"10.1145/3558819.3565175","DOIUrl":"https://doi.org/10.1145/3558819.3565175","url":null,"abstract":"In order to reduce the power consumption of carbon dioxide sensor and meet the application needs of multi-sensor long-distance load of coal mine safety monitoring system, carbon dioxide gas molecules are used in 4.2 ∼ 4.32 μ A low-power carbon dioxide sensor based on led-pr optical structure is designed. Based on the analysis of the principle of infrared carbon dioxide detection, LED light source and PR detector are studied.The design principle of LED light source driving circuit and the working mechanism of realizing low-power measurement, photoelectric signal processing circuit and software program flow are introduced. The power consumption of infrared carbon dioxide sensor is reduced to 0.06 W, which meets the needs of low-power detection applications in coal mines.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116792421","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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