Pub Date : 2021-08-20DOI: 10.1109/CSAIEE54046.2021.9543343
Xingchen Xu, Xiao Huang, Jinhui Ma, Xuejianwei Luo
As the destruction of diabetes is significant to the whole world, we want to focus on it and extract useful information from the correlation between symptoms and disease. The dataset obtained from UCI is the fundamental resource for the research. In order to ensure the accuracy of the project conclusions, three different approaches were used to verify each other: literature analysis, data analysis and machine learning. Literature part mainly contains previous work and large quantities of medical research done on diabetes. Data analysis included data preprocessing and visualization so as to unfold the concealed information of the dataset. Machine learning is to use the inspiration from the previous two parts to attain a suitable model for diabetes prediction. The project finally provides knowledge of different symptoms of diabetes and their relation with diabetes. It also elaborates how symptoms can be used to predict disease. Finally, we put forward suggestions for the prevention of diabetes and monitoring of potential disease.
{"title":"Prediction of Diabetes with its Symptoms Based on Machine Learning","authors":"Xingchen Xu, Xiao Huang, Jinhui Ma, Xuejianwei Luo","doi":"10.1109/CSAIEE54046.2021.9543343","DOIUrl":"https://doi.org/10.1109/CSAIEE54046.2021.9543343","url":null,"abstract":"As the destruction of diabetes is significant to the whole world, we want to focus on it and extract useful information from the correlation between symptoms and disease. The dataset obtained from UCI is the fundamental resource for the research. In order to ensure the accuracy of the project conclusions, three different approaches were used to verify each other: literature analysis, data analysis and machine learning. Literature part mainly contains previous work and large quantities of medical research done on diabetes. Data analysis included data preprocessing and visualization so as to unfold the concealed information of the dataset. Machine learning is to use the inspiration from the previous two parts to attain a suitable model for diabetes prediction. The project finally provides knowledge of different symptoms of diabetes and their relation with diabetes. It also elaborates how symptoms can be used to predict disease. Finally, we put forward suggestions for the prevention of diabetes and monitoring of potential disease.","PeriodicalId":376014,"journal":{"name":"2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126116437","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 : 2021-08-20DOI: 10.1109/CSAIEE54046.2021.9543308
Zixin Huang
Smart homes, which integrate Internet of Things devices by embedding intelligence into sensors and actuators, data, and services, have grown in popularity over the last decade. This paper aims at examining the advantages and applications of IoT-based Smart Home technologies and took a glance of its future prospects. Based on the data and experiments conducted in recent studies, this paper concluded that IoT could connect home with detecting devices and thus improve the home security and energy efficiency in households. The applications of IoT ease the inconveniences faced by the elderly and the disabled in their lives. This paper is optimistic about the future development of smart home, for it would better assist people's lives with better connectivity.
{"title":"Analysis of IoT-based Smart Home Applications","authors":"Zixin Huang","doi":"10.1109/CSAIEE54046.2021.9543308","DOIUrl":"https://doi.org/10.1109/CSAIEE54046.2021.9543308","url":null,"abstract":"Smart homes, which integrate Internet of Things devices by embedding intelligence into sensors and actuators, data, and services, have grown in popularity over the last decade. This paper aims at examining the advantages and applications of IoT-based Smart Home technologies and took a glance of its future prospects. Based on the data and experiments conducted in recent studies, this paper concluded that IoT could connect home with detecting devices and thus improve the home security and energy efficiency in households. The applications of IoT ease the inconveniences faced by the elderly and the disabled in their lives. This paper is optimistic about the future development of smart home, for it would better assist people's lives with better connectivity.","PeriodicalId":376014,"journal":{"name":"2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115008830","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 : 2021-08-20DOI: 10.1109/CSAIEE54046.2021.9543448
Mingwei Shi
Currently, the emotional research of dialogue systems is a hot topic. However, several works mainly focused on acquiring state-of-the-art performance in a dialogue system and paid less attention to the inner emotions' response and lacked interpretability of emotional response mechanism within a dialogue system. Hence, this work proposed an empathic protocol to address this issue via introducing an innovative element (Mirror neuron) from connectionism and neuroscience to gradually design an AMNN (Artificial mirror neuron network) in the dialogue system for clear interpretability firstly. Subsequently, this paper described an empathic protocol to produce and analyze responses between a user and an agent via the self-defined neural network that served as the Central Nervous System of a dialogue agent. By employing this protocol in a traffic-service application, users felt that their emotions were resonated with and understood and communicated with the dialogue agent proactively.
{"title":"Resonating response makes people feel better: An empathetic protocol in dialogue system","authors":"Mingwei Shi","doi":"10.1109/CSAIEE54046.2021.9543448","DOIUrl":"https://doi.org/10.1109/CSAIEE54046.2021.9543448","url":null,"abstract":"Currently, the emotional research of dialogue systems is a hot topic. However, several works mainly focused on acquiring state-of-the-art performance in a dialogue system and paid less attention to the inner emotions' response and lacked interpretability of emotional response mechanism within a dialogue system. Hence, this work proposed an empathic protocol to address this issue via introducing an innovative element (Mirror neuron) from connectionism and neuroscience to gradually design an AMNN (Artificial mirror neuron network) in the dialogue system for clear interpretability firstly. Subsequently, this paper described an empathic protocol to produce and analyze responses between a user and an agent via the self-defined neural network that served as the Central Nervous System of a dialogue agent. By employing this protocol in a traffic-service application, users felt that their emotions were resonated with and understood and communicated with the dialogue agent proactively.","PeriodicalId":376014,"journal":{"name":"2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133892790","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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