E. Stolov, N. Krinitsyn, V. Kurochkin, Maksim Murin, Ivan Shcherbakov
Robot localization is a fundamental task in autonomous mobile robot designing, since actual position data is a necessary parameter for many robot algorithms. Mostly, for the data obtaining, Global Navigation Satellite Systems (GNSS) are used which error can reach 5m. This article presents a developed GNSS coordinate refining algorithm and its testing results. The algorithm operation is based on GNSS coordinates and distance data between multiple devices (here robots) received through Ultra-Wide Band (UWB) transceivers. The coordinates can be refined locally in the device coordinate system and in the global coordinate system, if high-precision of GNSS data are available for at least one device.
{"title":"Algorithm of Agent Localization in a Group Using Ultra-Wideband Communication Technology","authors":"E. Stolov, N. Krinitsyn, V. Kurochkin, Maksim Murin, Ivan Shcherbakov","doi":"10.1145/3459104.3459132","DOIUrl":"https://doi.org/10.1145/3459104.3459132","url":null,"abstract":"Robot localization is a fundamental task in autonomous mobile robot designing, since actual position data is a necessary parameter for many robot algorithms. Mostly, for the data obtaining, Global Navigation Satellite Systems (GNSS) are used which error can reach 5m. This article presents a developed GNSS coordinate refining algorithm and its testing results. The algorithm operation is based on GNSS coordinates and distance data between multiple devices (here robots) received through Ultra-Wide Band (UWB) transceivers. The coordinates can be refined locally in the device coordinate system and in the global coordinate system, if high-precision of GNSS data are available for at least one device.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124602932","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}
Face alignment, as an important part of facial tasks, will affect the final efficiency and accuracy. Face alignment is to locate the exact shape of a detected face bounding box. There are amount of challenges in face alignment because of large poses, occlusions and illuminations in real-world conditions. The approaches to tackle these challenges can be categorized in methods based on regression, which require operators in feature extraction, and methods based on deep learning, in which the feature extraction is data driven. Methods applies regression include Supervised Descent Method and Face Alignment by Coarse-to-Fine Shape Searching. Deep Convolutional Neural Networks, Tasks-Constrained Deep Convolutional Network and Multi-task Cascaded Convolutional Networks apply cascaded CNN and they are representational approaches of deep learning method. This article is devoted to the elaboration and summary of these mainstream methods.
{"title":"A Survey for Conventional Regression- and Deep Learning-based Face Alignment Methods","authors":"Tong Gao","doi":"10.1145/3459104.3459191","DOIUrl":"https://doi.org/10.1145/3459104.3459191","url":null,"abstract":"Face alignment, as an important part of facial tasks, will affect the final efficiency and accuracy. Face alignment is to locate the exact shape of a detected face bounding box. There are amount of challenges in face alignment because of large poses, occlusions and illuminations in real-world conditions. The approaches to tackle these challenges can be categorized in methods based on regression, which require operators in feature extraction, and methods based on deep learning, in which the feature extraction is data driven. Methods applies regression include Supervised Descent Method and Face Alignment by Coarse-to-Fine Shape Searching. Deep Convolutional Neural Networks, Tasks-Constrained Deep Convolutional Network and Multi-task Cascaded Convolutional Networks apply cascaded CNN and they are representational approaches of deep learning method. This article is devoted to the elaboration and summary of these mainstream methods.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124686318","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}
Jincheng Zhang, Baojun Wang, W. Shi, Jucai Lin, Jun Yin
The aim of surveillance is to detect the occurrence of dangerous events. Recently, with the widely use of deep learning, video surveillance had get dramatically improvement. For audio event detection in surveillance, the deep learning means are applied in hazardous sound classification task. However, due to the low frequency of dangerous sounds occurred and the high cost of collection, there is no corresponding large-scale dataset. Large-scale dataset is essential to achieve an ideal result for deep learning methods. Therefore, how to obtain richer audio events has become an urgent problem. Nowadays, researchers have use a variety of data augmentation methods in computer vision, making performance improvement obviously. And these approaches are gradually being used in various sound pattern recognition or ASR (auto-speech recognition), but there is little research on the classification of hazardous sounds with less data set. In this paper, various data augmentation methods are adopted for hazardous sound classification. Our results show that data augmentation has bring big improvement on all four class dataset. The classification accuracy has increased by 0.5% on average. As the scale of data augmentation increases, the classification accuracy has increased to about 1.5%.
{"title":"Hazardous Sound Detection Based on Audio Augmentation","authors":"Jincheng Zhang, Baojun Wang, W. Shi, Jucai Lin, Jun Yin","doi":"10.1145/3459104.3459174","DOIUrl":"https://doi.org/10.1145/3459104.3459174","url":null,"abstract":"The aim of surveillance is to detect the occurrence of dangerous events. Recently, with the widely use of deep learning, video surveillance had get dramatically improvement. For audio event detection in surveillance, the deep learning means are applied in hazardous sound classification task. However, due to the low frequency of dangerous sounds occurred and the high cost of collection, there is no corresponding large-scale dataset. Large-scale dataset is essential to achieve an ideal result for deep learning methods. Therefore, how to obtain richer audio events has become an urgent problem. Nowadays, researchers have use a variety of data augmentation methods in computer vision, making performance improvement obviously. And these approaches are gradually being used in various sound pattern recognition or ASR (auto-speech recognition), but there is little research on the classification of hazardous sounds with less data set. In this paper, various data augmentation methods are adopted for hazardous sound classification. Our results show that data augmentation has bring big improvement on all four class dataset. The classification accuracy has increased by 0.5% on average. As the scale of data augmentation increases, the classification accuracy has increased to about 1.5%.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123855209","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}
C. Li, H. Gurulingappa, P. Karmalkar, J. Raab, Aastha Vij, Gerard Megaro, C. Henke
Randomized clinical trials are the core data source for meta- analyses and relative efficacy analyses. As of today, there are missing links between large portions of trials registered in clinical trial registries and their reported outcomes published in scientific journals. This missing citation information makes it difficult to identify all relevant publications for evidence synthesis and decision support. Therefore, we propose a novel natural language processing-based system to establish links between clinical trials and their published outcomes in literature. Different approaches leveraging information retrieval and machine learning with embedding features were systematically developed and evaluated. Results show that shallow machine learning approach with embeddings provide promising results indicating the value it can add to circumvent the limitations of manual search and analyses.
{"title":"Automate Clinical Evidence Synthesis by Linking Trials to Publications with Text Analytics","authors":"C. Li, H. Gurulingappa, P. Karmalkar, J. Raab, Aastha Vij, Gerard Megaro, C. Henke","doi":"10.1145/3459104.3459168","DOIUrl":"https://doi.org/10.1145/3459104.3459168","url":null,"abstract":"Randomized clinical trials are the core data source for meta- analyses and relative efficacy analyses. As of today, there are missing links between large portions of trials registered in clinical trial registries and their reported outcomes published in scientific journals. This missing citation information makes it difficult to identify all relevant publications for evidence synthesis and decision support. Therefore, we propose a novel natural language processing-based system to establish links between clinical trials and their published outcomes in literature. Different approaches leveraging information retrieval and machine learning with embedding features were systematically developed and evaluated. Results show that shallow machine learning approach with embeddings provide promising results indicating the value it can add to circumvent the limitations of manual search and analyses.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116209048","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}
Navya Thirumaleshwar Hegde, V. George, C. G. Nayak
This paper gives the dynamic modeling and design of a controller for autonomous Vertical take-off and landing (VTOL) Tri-Tilt rotor hybrid Unmanned Aerial Vehicle (UAV). Nowadays, UAVs have experienced remarkable progress and mainly categorized into fixed-wing UAVs and rotary-wing UAVs. The Tri Tiltrotor UAV models are derived mathematically using Euler's force and moment equations for VTOL to horizontal flight and vice-versa using MATLAB. The development of fully autonomous and self-guided UAVs would reduce the risk to human life. The applications consist of inspection of coasts, terrain, border, patrol buildings, rescue teams, police, and pipelines. A Proportional-Integral-Derivative control method is proposed for UAVs attitude and altitude stabilization. The results reveal that the controller accomplishes adaptability, robust performance and stability in the transition mode.
{"title":"Tri-Tilting Rotor Fixed-Wing VTOL UAV: Dynamic Modelling and Transition Flight Control","authors":"Navya Thirumaleshwar Hegde, V. George, C. G. Nayak","doi":"10.1145/3459104.3459118","DOIUrl":"https://doi.org/10.1145/3459104.3459118","url":null,"abstract":"This paper gives the dynamic modeling and design of a controller for autonomous Vertical take-off and landing (VTOL) Tri-Tilt rotor hybrid Unmanned Aerial Vehicle (UAV). Nowadays, UAVs have experienced remarkable progress and mainly categorized into fixed-wing UAVs and rotary-wing UAVs. The Tri Tiltrotor UAV models are derived mathematically using Euler's force and moment equations for VTOL to horizontal flight and vice-versa using MATLAB. The development of fully autonomous and self-guided UAVs would reduce the risk to human life. The applications consist of inspection of coasts, terrain, border, patrol buildings, rescue teams, police, and pipelines. A Proportional-Integral-Derivative control method is proposed for UAVs attitude and altitude stabilization. The results reveal that the controller accomplishes adaptability, robust performance and stability in the transition mode.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128093237","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}
Julian Nickerl, David Mödinger, Jan-Hendrik Lorenz
Peer-to-peer protocols often take longer, are less efficient or can't complete lookup queries with increasing network diameter. Peers could mitigate this by increasing their degree, i.e., their amount of open connections, but this increases the operational cost for each peer. We propose a novel peer-to-peer network formation protocol based on a game-theoretic approach, guaranteeing that diameter and maximum degree do not surpass given thresholds throughout the network. The game generalizes the local network formation game with more versatile strategies and cost functions. This allows for a trade off between operational cost and efficiency based on the individual interest of peers. We show that for any given diameter k and maximum degree d a Nash equilibrium, i.e., a graph with the desired properties, can be reached by improvement steps. We validate the practical applicability of these theoretical results on networks of 5–50 participants with various strategies and configurations. The experimental results show a fast approximation of the desired properties while taking some time to reach a stable state. We make out several strategies with which the protocol performs well. In particular, a stable state is found quickly when the initial network was already close to a stable state. This property enables the efficient dynamic treatment of the in practice often occurring scenario of nodes joining or leaving the network.
{"title":"From Local Network Formation Game to Peer-to-Peer Protocol","authors":"Julian Nickerl, David Mödinger, Jan-Hendrik Lorenz","doi":"10.1145/3459104.3459184","DOIUrl":"https://doi.org/10.1145/3459104.3459184","url":null,"abstract":"Peer-to-peer protocols often take longer, are less efficient or can't complete lookup queries with increasing network diameter. Peers could mitigate this by increasing their degree, i.e., their amount of open connections, but this increases the operational cost for each peer. We propose a novel peer-to-peer network formation protocol based on a game-theoretic approach, guaranteeing that diameter and maximum degree do not surpass given thresholds throughout the network. The game generalizes the local network formation game with more versatile strategies and cost functions. This allows for a trade off between operational cost and efficiency based on the individual interest of peers. We show that for any given diameter k and maximum degree d a Nash equilibrium, i.e., a graph with the desired properties, can be reached by improvement steps. We validate the practical applicability of these theoretical results on networks of 5–50 participants with various strategies and configurations. The experimental results show a fast approximation of the desired properties while taking some time to reach a stable state. We make out several strategies with which the protocol performs well. In particular, a stable state is found quickly when the initial network was already close to a stable state. This property enables the efficient dynamic treatment of the in practice often occurring scenario of nodes joining or leaving the network.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130118168","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}
Verónica Rojas-Mendizabal, C. Castillo-Olea, Jocelyn Gomez Siono, C. Zuniga
Sarcopenia is the loss of muscle mass associated with the ageing process. Moreover, it is a progressive disease affecting older people. In 2017, about 12 million mexican elder people suffered from Sarcopenia; nevertheless, many of them are not aware of their condition. A study conducted by the Instituto Mexicano del Seguro Social (IMSS) estimates that 72.10% of people with Sarcopenia were women, while the rest were men [1]. This study analyses a database which includes the information of 166 geriatric patients from Tijuana, Baja California state. The database encompasses 90 variables, including biomedical information and some demographic information such as age, gender, address, schooling, marital status, level of education, income, profession, and financial support. An analysis to find the weight factors that impact the development of sarcopenia was carried out by generating a decision tree using the database provided by the General Hospital of Tijuana and the support of Orange software. Based on the creation of this tree, the relation and impact of the most important factors was analyzed. Among the three most important risk factors for this disease, besides senescence, the results from the analysis showed that Major Neurocognitive Disorder (MND), Systolic Arterial Hypertension (SAH), and malnutrition are the most important conditions to consider. These obtained results were compared with results retrieved from a study where the analysis was done through a Python simulation using machine learning methods with the same database.
肌肉减少症是与衰老过程相关的肌肉质量损失。此外，这是一种影响老年人的进行性疾病。2017年，约有1200万墨西哥老年人患有肌肉减少症;然而，他们中的许多人并没有意识到自己的状况。墨西哥社会研究所(Instituto Mexicano del Seguro Social, IMSS)的一项研究估计，72.10%的肌肉减少症患者为女性，其余为男性[1]。本研究分析了一个数据库，其中包括来自下加利福尼亚州蒂华纳的166名老年患者的信息。该数据库包含90个变量，包括生物医学信息和一些人口统计信息，如年龄、性别、地址、学校教育、婚姻状况、教育水平、收入、职业和财政支持。利用Tijuana总医院提供的数据库和Orange软件的支持，通过生成决策树，对影响肌肉减少症发展的体重因素进行了分析。在建立该树的基础上，分析了各重要因素之间的关系和影响。在本病的三个最重要的危险因素中，除衰老外，分析结果显示，主要神经认知障碍(MND)、收缩期动脉高血压(SAH)和营养不良是最需要考虑的因素。将这些获得的结果与从一项研究中检索到的结果进行比较，该研究通过使用具有相同数据库的机器学习方法的Python模拟进行分析。
{"title":"Analysis of factors impacting Sarcopenia in geriatric patients through the use of data sciences: A Case Study in Tijuana, Mexico","authors":"Verónica Rojas-Mendizabal, C. Castillo-Olea, Jocelyn Gomez Siono, C. Zuniga","doi":"10.1145/3459104.3459195","DOIUrl":"https://doi.org/10.1145/3459104.3459195","url":null,"abstract":"Sarcopenia is the loss of muscle mass associated with the ageing process. Moreover, it is a progressive disease affecting older people. In 2017, about 12 million mexican elder people suffered from Sarcopenia; nevertheless, many of them are not aware of their condition. A study conducted by the Instituto Mexicano del Seguro Social (IMSS) estimates that 72.10% of people with Sarcopenia were women, while the rest were men [1]. This study analyses a database which includes the information of 166 geriatric patients from Tijuana, Baja California state. The database encompasses 90 variables, including biomedical information and some demographic information such as age, gender, address, schooling, marital status, level of education, income, profession, and financial support. An analysis to find the weight factors that impact the development of sarcopenia was carried out by generating a decision tree using the database provided by the General Hospital of Tijuana and the support of Orange software. Based on the creation of this tree, the relation and impact of the most important factors was analyzed. Among the three most important risk factors for this disease, besides senescence, the results from the analysis showed that Major Neurocognitive Disorder (MND), Systolic Arterial Hypertension (SAH), and malnutrition are the most important conditions to consider. These obtained results were compared with results retrieved from a study where the analysis was done through a Python simulation using machine learning methods with the same database.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130470459","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}
Ying Sun, Christopher L. Hunt, Wally Niu, Ziwei Li, G. Cyrino, R. Cavalcante, E. Lamounier, A. Soares, N. Thakor
In recent years, virtual reality (VR) and augmented reality (AR) technologies have been shown to be promising avenues for improving the security, convenience, and efficacy of rehabilitative prosthesis training systems. Despite their rise in popularity, it is still unclear what advantages these paradigms have over one another when applied to complex motor tasks. In this study, we aim to determine which paradigm, AR or VR, is better suited for the completion of dexterous motor control tasks needed for effective upper-limb prosthesis use. We evaluate a population of able-bodied (N=5) subjects. Each of them performed 50 3-dimensional object manipulation tasks in analogous AR and VR environments respectively, with 100 trials for each subject. During each trial, subjects operate a virtual upper-limb prosthesis to perform reach-grasp-relocation manipulations via a myoelectric pattern recognition (MPR) algorithm. We report an average improvement in Fitts’ throughput (+20.94% and +21.26%) from all subjects when comparing VR to AR task performance in the reach and relocation phase. Additionally, we observe an increase in overall task completion rate (+3.60%) and mean path efficiency (+9.59% and +6.73%) during the reach and relocation phases of motion. What's more, we report a statistically significant decrease in mean task completion time during both reach and relocation phases when comparing AR to VR-based trials (p<0.05). Based on these functional results, we conclude that as a paradigm, VR promotes more efficient motion, resulting in higher task completion rates and path efficiency. On the other hand, AR allows subjects to perform motor tasks with shorter time consumed compared with VR.
{"title":"A Comparison between Virtual Reality and Augmented Reality on Upper-limb Prosthesis Control","authors":"Ying Sun, Christopher L. Hunt, Wally Niu, Ziwei Li, G. Cyrino, R. Cavalcante, E. Lamounier, A. Soares, N. Thakor","doi":"10.1145/3459104.3459189","DOIUrl":"https://doi.org/10.1145/3459104.3459189","url":null,"abstract":"In recent years, virtual reality (VR) and augmented reality (AR) technologies have been shown to be promising avenues for improving the security, convenience, and efficacy of rehabilitative prosthesis training systems. Despite their rise in popularity, it is still unclear what advantages these paradigms have over one another when applied to complex motor tasks. In this study, we aim to determine which paradigm, AR or VR, is better suited for the completion of dexterous motor control tasks needed for effective upper-limb prosthesis use. We evaluate a population of able-bodied (N=5) subjects. Each of them performed 50 3-dimensional object manipulation tasks in analogous AR and VR environments respectively, with 100 trials for each subject. During each trial, subjects operate a virtual upper-limb prosthesis to perform reach-grasp-relocation manipulations via a myoelectric pattern recognition (MPR) algorithm. We report an average improvement in Fitts’ throughput (+20.94% and +21.26%) from all subjects when comparing VR to AR task performance in the reach and relocation phase. Additionally, we observe an increase in overall task completion rate (+3.60%) and mean path efficiency (+9.59% and +6.73%) during the reach and relocation phases of motion. What's more, we report a statistically significant decrease in mean task completion time during both reach and relocation phases when comparing AR to VR-based trials (p<0.05). Based on these functional results, we conclude that as a paradigm, VR promotes more efficient motion, resulting in higher task completion rates and path efficiency. On the other hand, AR allows subjects to perform motor tasks with shorter time consumed compared with VR.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131616623","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 realize the automatic and non-inductive reimbursement of invoices and eliminate the various inconveniences and risks caused by artificial reimbursement, this article proposes to combine blockchain technology with electronic invoices to complete the consumption, reimbursement, and tax payment through the blockchain network system. The node paperless invoice interactive process, and realize the automatic processing of off-chain data through the Internet of Things technology, seamless connection with the on-chain, while using a dual-chain structure to ensure the subsequent identification and business separation, through the combination of theory and technical architecture, Sense the invoice reimbursement system, thereby reducing China's overall reimbursement costs and promoting the improvement of the taxation system.
{"title":"An Overall Architecture Design of a Hybrid Blockchain Technology that Solves the Separation of Basic Data and Business Data","authors":"Feng Liu, Aohua Li, Xuanyong Wu, De Gao, Ningbo Wang, Qinwen Xu","doi":"10.1145/3459104.3459179","DOIUrl":"https://doi.org/10.1145/3459104.3459179","url":null,"abstract":"In order to realize the automatic and non-inductive reimbursement of invoices and eliminate the various inconveniences and risks caused by artificial reimbursement, this article proposes to combine blockchain technology with electronic invoices to complete the consumption, reimbursement, and tax payment through the blockchain network system. The node paperless invoice interactive process, and realize the automatic processing of off-chain data through the Internet of Things technology, seamless connection with the on-chain, while using a dual-chain structure to ensure the subsequent identification and business separation, through the combination of theory and technical architecture, Sense the invoice reimbursement system, thereby reducing China's overall reimbursement costs and promoting the improvement of the taxation system.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129389471","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 fluctuation of stock market is affected by many factors, such as human psychology, macro-economy, operation state of listed companies and industry. These factors can be regarded as risk factors that affect the excess return of stocks. According to the Arbitrage Pricing Theory, excess return and risk are closely related, and the excess return of stock is brought by taking certain risks. With the development of Chinese stock market, more and more risk factors that affect stock return are quantified. Among them, technical factors and fundamental factors are the most important two categories. Technical factors mainly reflect the trend of stock price and the trading activity of the market. Fundamental factors mainly reflect the operation and profitability of listed companies. These two kinds of factors are also the most commonly used in the quantitative model. Based on these two kinds of factors, we proposed a two branch risk factors model, which can combine these two kinds of factors to select stocks.
{"title":"Two Branch Risk Factors Model for Stock Prediction","authors":"Chaochao Jia, Weimin Pan, Lixian Li","doi":"10.1145/3459104.3459163","DOIUrl":"https://doi.org/10.1145/3459104.3459163","url":null,"abstract":"The fluctuation of stock market is affected by many factors, such as human psychology, macro-economy, operation state of listed companies and industry. These factors can be regarded as risk factors that affect the excess return of stocks. According to the Arbitrage Pricing Theory, excess return and risk are closely related, and the excess return of stock is brought by taking certain risks. With the development of Chinese stock market, more and more risk factors that affect stock return are quantified. Among them, technical factors and fundamental factors are the most important two categories. Technical factors mainly reflect the trend of stock price and the trading activity of the market. Fundamental factors mainly reflect the operation and profitability of listed companies. These two kinds of factors are also the most commonly used in the quantitative model. Based on these two kinds of factors, we proposed a two branch risk factors model, which can combine these two kinds of factors to select stocks.","PeriodicalId":142284,"journal":{"name":"2021 International Symposium on Electrical, Electronics and Information Engineering","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130765645","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：