2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)最新文献_第5页

A study of fall detection monitoring system for elderly people through IOT and mobile based application devices in indoor environment 基于物联网和基于移动的室内环境应用设备的老年人跌倒检测监控系统研究

2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) Pub Date : 2020-11-25 DOI: 10.1109/CITISIA50690.2020.9371773

Padam Gharti

{"title":"A study of fall detection monitoring system for elderly people through IOT and mobile based application devices in indoor environment","authors":"Padam Gharti","doi":"10.1109/CITISIA50690.2020.9371773","DOIUrl":"https://doi.org/10.1109/CITISIA50690.2020.9371773","url":null,"abstract":"This research presents the structure and framework for identifying falls by remote observing of old individuals in indoor environments by taking advantages of the Internet of things as well as mobile-based applications. This smart framework identifies fall occurred to older individuals who are living alone or living in residential nursing homes. To monitor the fall it uses real-time monitoring by use of open source camera and wearable devices. The system is carried out by pose recognition and object detection method for identifying the object taken by an open-source camera.A systematic review was performed using the Primo Search tool for finding eBooks, articles, and journals from the CSU library database. To provide a high efficiency using this information all inclusion criteria were meet by choosing the journal article which was closely related to the topic. The proposed study of fall detection monitoring system for older people living in geriatric residents allows data for caregivers and clinicians to provide better control in monitoring the health status of older patients and allows closer communication with the patients’ family members and relatives. This study can be used as an approach for improving the cost of care in elderly population.","PeriodicalId":145272,"journal":{"name":"2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125929488","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}

引用次数: 7

Rule Based Approach to Extract Metadata from Scientific PDF Documents 基于规则的科学PDF文档元数据提取方法

2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) Pub Date : 2020-11-25 DOI: 10.1109/CITISIA50690.2020.9371784

Ahmer Maqsood Hashmi, M. Afzal, S. Rehman

引用次数: 1

Mobile-Enabled Virtual Reality Visualisation Improves Learning And Training In Health Care 移动虚拟现实可视化改善了医疗保健领域的学习和培训

2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) Pub Date : 2020-11-25 DOI: 10.1109/CITISIA50690.2020.9371824

G. Truong, P. Prasad, Angelika Maag, Moshiur Bhuiyan

{"title":"Mobile-Enabled Virtual Reality Visualisation Improves Learning And Training In Health Care","authors":"G. Truong, P. Prasad, Angelika Maag, Moshiur Bhuiyan","doi":"10.1109/CITISIA50690.2020.9371824","DOIUrl":"https://doi.org/10.1109/CITISIA50690.2020.9371824","url":null,"abstract":"Working in the health care sector required high skill sets and intensive training. Emerging technologies with realistic visualisation and practical such as virtual reality (VR) are being applied to the training process of the health care practitioners. Many researches have done studies in virtual reality and its implementation in education, more specifically in learning and training of a certain skill and enhancing user learning experiences. However, these studies usually remained in the development or research stage and have not widely implemented in real-life training due to various reasons. This research aims to review the effectiveness of virtual reality in the health care sector, its current solutions to the problem within different areas and analyse different VR research processes to encourage more practical implementation of VR. A literature review was performed to review 15 papers that implemented VR technology in learning and training skill for healthcare practitioners, rehabilitation and diagnoses as well as other aspects of virtual reality that can be considered within the health care sector.","PeriodicalId":145272,"journal":{"name":"2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129989801","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}

引用次数: 0

A Novel Softmax Regression Enhancement for Handwritten Digits Recognition using Tensor Flow Library 基于张量流库的手写体数字识别的新型Softmax回归增强

2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) Pub Date : 2020-11-25 DOI: 10.1109/CITISIA50690.2020.9371821

Aman Arora, O. H. Alsadoon, T. Khairi, Tarik A. Rashid

{"title":"A Novel Softmax Regression Enhancement for Handwritten Digits Recognition using Tensor Flow Library","authors":"Aman Arora, O. H. Alsadoon, T. Khairi, Tarik A. Rashid","doi":"10.1109/CITISIA50690.2020.9371821","DOIUrl":"https://doi.org/10.1109/CITISIA50690.2020.9371821","url":null,"abstract":"Background and Aim: Handwritten Digit Recognition has a wide variety of applications in postal mail order, phone records search, automatic car number plate recognition, and in the medical sector that observed how Machine Learning makes the daily tasks simpler and more efficient. This paper aims to improve the classification accuracy of existing handwritten digit systems, thus improve their efficiency. Methodology: The proposed system consists of an enhanced decision function by adding a “Bias Probability” Function. The function adds negative weights to the output classes (0-9) that have a high positive bias and add a positive weight to the output classes that have a high negative bias to neutralize the effect of this high negative bias. Therefore, the Bayesian Classifier function has been enhanced thereby improving the accuracy of classification, which will further improve the performance of the multiclass probability categorization. Result: An increase of 5.6% was observed in the overall accuracy of handwritten digit classification using the Modified National Institute of Standards and Technology (MNIST) Dataset. Conclusion: From the results, it is clear that the proposed system, enhances the main decision function to further improve the accuracy with no significant increase in the processing time.","PeriodicalId":145272,"journal":{"name":"2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)","volume":"14 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120998657","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}

引用次数: 0

IEEE CSU Student Branch IEEE科罗拉多州立大学学生分会

2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) Pub Date : 2020-11-25 DOI: 10.1109/citisia50690.2020.9371823

引用次数: 0

Improving the quality of education system using Data Science Technologies: Survey 利用数据科学技术提高教育系统的质量:调查

2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) Pub Date : 2020-11-25 DOI: 10.1109/CITISIA50690.2020.9371793

Pattinige Ravindra R Fernando

{"title":"Improving the quality of education system using Data Science Technologies: Survey","authors":"Pattinige Ravindra R Fernando","doi":"10.1109/CITISIA50690.2020.9371793","DOIUrl":"https://doi.org/10.1109/CITISIA50690.2020.9371793","url":null,"abstract":"Education is the most important and silent weapon in a country for both individual and country’s economy. However lower level of adoption in the education system, poor decision making with less accuracy levels, adoption to new curriculums or subjects, teaching and learning styles are the main issues in education systems. These factors also have further long-term consequences for a country such as unemployment rates rises high, lack of suitable workforce for the demanding fields, individual dissatisfaction while being unemployed as well as in the community and socially. Unemployment rates are risen in Australia from past few years and this as a factor will be an ongoing issue if the government does not take any further actions to overcome these issues will definitely be direct hit to their economy in relation to work force in the present and future. Therefore the right technology should be implemented in order to obtain extract insights, obtain accurate decisions and high level adoption in education sector, as an example technologies such as data warehousing, big data, data mining, business intelligence and data analytics are in the peak of other industries such as aviation, retail, banking and other financial institutions. The main objective of this project is to facilitate a guide or a review for having data science technologies implemented in education sector in order to accomplish better education, as well as emphasis potential advantages of data technologies if it has been implemented in and around education systems.","PeriodicalId":145272,"journal":{"name":"2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127061149","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}

引用次数: 0

[CITISIA 2020 Front cover] [CITISIA 2020年封面]

2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) Pub Date : 2020-11-25 DOI: 10.1109/citisia50690.2020.9371825

引用次数: 0

A Decentralised Registry for Firearm Tracking using Blockchain Technology 使用区块链技术进行枪支跟踪的分散注册

2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) Pub Date : 2020-11-25 DOI: 10.1109/CITISIA50690.2020.9371845

Mahsa Mohaghegh, Rudra Sakhardande

{"title":"A Decentralised Registry for Firearm Tracking using Blockchain Technology","authors":"Mahsa Mohaghegh, Rudra Sakhardande","doi":"10.1109/CITISIA50690.2020.9371845","DOIUrl":"https://doi.org/10.1109/CITISIA50690.2020.9371845","url":null,"abstract":"The problem of illegal firearm trade and the resulting consequences have been the subject of much debate with respect to their causes and the solutions that need to be implemented in order to curb their devastating effects. The lack of a robust infrastructure for tracking firearms in the USA has been one of the major reasons contributing to lack of accountability concerning firearm ownership in the nation. The paper proposes the design of a decentralised system based on blockchain technology that would not only aid in tracking firearm ownership but also provide an infrastructure for managing firearm licenses and trading firearms while maintaining user privacy. The artifact was designed in 5 phases with incremental developments performed at the end of each phase. The software artifact was then subjected to analysis followed by expert evaluation where each feature was assessed to gauge its feasibility with respect to real world operational and regulatory constraints. The system was found to successfully provide a decentralised platform for recording gun ownership data as well as trading firearms. The system also illustrates that the entire firearm tracing process can be decentralised through the voting system designed. The system however was still found to require more operational planning with respect to situations involving human interactions and regulations in order that the user privacy is not compromised.","PeriodicalId":145272,"journal":{"name":"2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)","volume":"67 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126020203","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}

引用次数: 0

Proactive Big Data Analysis for Traffic Accident Prediction1 面向交通事故预测的前瞻性大数据分析

2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) Pub Date : 2020-11-25 DOI: 10.1109/CITISIA50690.2020.9371796

A. Finogeev, M. Deev, A. Finogeev, Ilja Kolesnikoff

{"title":"Proactive Big Data Analysis for Traffic Accident Prediction1","authors":"A. Finogeev, M. Deev, A. Finogeev, Ilja Kolesnikoff","doi":"10.1109/CITISIA50690.2020.9371796","DOIUrl":"https://doi.org/10.1109/CITISIA50690.2020.9371796","url":null,"abstract":"The article, the authors presented a system for proactive monitoring and forecasting of the risks of road traffic accidents, depending on the influence of external factors. To solve the problem, a method for analysis and predictive modeling of changes in the road transport infrastructure has been developed to predict the risks of occurrence and development of destructive events under the influence of external factors. The purpose is to determine, assess and predict the dynamics of changes in factors that affect the likelihood of the occurrence of risks of accidents, depending on the current situation on the monitored road sections. For predictive risk analysis, information on the parameters of negative events and possible influencing factors obtained from various sources is presented in the form of a spectrum of time series. Comparative analysis of time series of event parameters and factors allows us to identify the causes of incidents and the correlation between factors and events. As factors of influence, meteorological conditions, parameters of auto-mobile and pedestrian traffic on road sections, the state of the road surface, characteristics of road sections, etc. are investigated. The monitoring system is implemented using a multi-agent approach, which involves the use of software agents on photoradar complexes for photo and video registration of road events and mobile communications. Agents solve a number of tasks of collecting, parsing, consolidating, analyzing and visualizing big sensory data.","PeriodicalId":145272,"journal":{"name":"2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134177863","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}

引用次数: 2

Analysis of Algorithms in Automated Marking in Education: A Proposed Hybrid Algorithm 教育自动化阅卷算法分析:一种混合算法

2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA) Pub Date : 2020-11-25 DOI: 10.1109/CITISIA50690.2020.9371783

Binita Prasain, Simi Bajaj

{"title":"Analysis of Algorithms in Automated Marking in Education: A Proposed Hybrid Algorithm","authors":"Binita Prasain, Simi Bajaj","doi":"10.1109/CITISIA50690.2020.9371783","DOIUrl":"https://doi.org/10.1109/CITISIA50690.2020.9371783","url":null,"abstract":"Automated grading of student’s assignments and exam papers has been studied for more than a decade. This technique can be used to automatically grade student’s assignments as well as exam papers without spending much time and effort. Many schools and universities are using this technology whereas, others are still struggling to find the best system which can accurately evaluate and provide the best result. The main aim of this research is to find how automated marking system work and how this can be used to improve the teaching and learning process. This paper provides a brief overview of existing research being carried out in the field of natural language processing and machine learning algorithms to develop automated marking system and will present a sample framework which uses the data from the exam papers of students from different schools and universities and from some datasets and evaluates student answer based on the model answer provided to the system. The system finds similarity between the student answer and model answer and grade student answer based on the degree of similarity between them. Through this paper, the reader will be able to get an overview of the recent development in the field of education with the use of an automated marking system to evaluate student’s performance. This technology help teachers to save their time and effort whereas, students can get timely feedback which helps to improve their performance.","PeriodicalId":145272,"journal":{"name":"2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131363862","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}

引用次数: 4