2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)最新文献

筛选
英文 中文
A MATLAB/OCTAVE toolbox for analysis of BACTEC MGIT 960 data for mycobacterial growth 用于分析分枝杆菌生长的BACTEC MGIT 960数据的MATLAB/OCTAVE工具箱
2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2020-11-18 DOI: 10.1109/ICIIBMS50712.2020.9336199
E. Postnikov, M. Dogonadze, A. Lavrova
{"title":"A MATLAB/OCTAVE toolbox for analysis of BACTEC MGIT 960 data for mycobacterial growth","authors":"E. Postnikov, M. Dogonadze, A. Lavrova","doi":"10.1109/ICIIBMS50712.2020.9336199","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336199","url":null,"abstract":"We present a toolbox for automatized processing files, which contain output data on mycobacterial growth from BACTEC MGIT 960 system, and mathematical models addressed to peculiarities in the growth dynamics revealed from high-resolution records. The data processing includes reading a standardised spreadsheet, its formatting into datasets with respect to the hours of recording and BACTEC intensity units prepared for the subsequent analysis. The case studies reveal the combination of a general trend satisfying the Gompertz growth curve and a series of repeating growth shapes hypothesised as an exhibition of bacterial synchronization phenomena.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"326 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123578948","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
Assessing of frequency dynamics of EEG signals in a visualization experiment related to crime deterrence 犯罪威慑可视化实验中脑电图信号的频率动态评估
2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2020-11-18 DOI: 10.1109/ICIIBMS50712.2020.9336207
Rafael H. A. de Castro, M. Peña-Sarmiento, Ervyn Norza, Camilo A. Sanchez, Erick Gillen, Yeizon A. Duarte, Luis O. Jimenez
{"title":"Assessing of frequency dynamics of EEG signals in a visualization experiment related to crime deterrence","authors":"Rafael H. A. de Castro, M. Peña-Sarmiento, Ervyn Norza, Camilo A. Sanchez, Erick Gillen, Yeizon A. Duarte, Luis O. Jimenez","doi":"10.1109/ICIIBMS50712.2020.9336207","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336207","url":null,"abstract":"The purpose of this document is to assess Electroencephalographic (EEG) signal frequency dynamics in visual stimuli related to crime deterrence from an inexpensive device. The signals were acquired from 4 participants, with an EMOTIV EPOC 14 channel EEG device, while visual stimuli (deterrence and neutral) were presented, also an eye-tracking device was used to follow the participants visual path through the images, the experimental design was developed in the Paradigm software and the signal processing in Python using MNE for the EEG data analysis. Methods: The signal pass by a preprocessing which includes filtering, denoising and ICA object rejection, then the Global Field Power (GFP) is calculated to track the temporal dynamics of frequency bands theta, alpha, beta and gamma, finally differential GFP for theta and alpha bands is calculated and maximal temporal frequency responses are represented. The process applied shows dynamic characteristics of frequency bands and allows maximal localization of its responses.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121988870","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: 3
Assessment of Disaster Rescue Sign Detection based Image Processing 基于图像处理的灾害救援标志检测评估
2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2020-11-18 DOI: 10.1109/iciibms50712.2020.9336422
Zacharie Mbaitiga, Tanaka Shosaku
{"title":"Assessment of Disaster Rescue Sign Detection based Image Processing","authors":"Zacharie Mbaitiga, Tanaka Shosaku","doi":"10.1109/iciibms50712.2020.9336422","DOIUrl":"https://doi.org/10.1109/iciibms50712.2020.9336422","url":null,"abstract":"This paper proposes a practical, robust and efficient new search and detection scheme to quickly detect and locate any person stuck in their home or underground during any disaster and facilitate the rescue team task and consequently save lives The most important thing a bout this new approach is that the person waiting for the rescue team posts outdoor a rescue sign that they can make with any items they can find around them and should not be coincided with any familiar existing sign. Two detection mehodlogy is use. (1) create a maximum color database with value normalization regonition. (2) pattern recognition will be sue for the sign detection, then evaluation","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130537420","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
Emergency evacuation model of panic group based on Big data 基于大数据的恐慌群体应急疏散模型
2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2020-11-18 DOI: 10.1109/ICIIBMS50712.2020.9336400
Miao Zhang, Y. Wan-jun, Huai-Lin Zhao, Yu Tian, Jun-Yi Tang, M. Zhang
{"title":"Emergency evacuation model of panic group based on Big data","authors":"Miao Zhang, Y. Wan-jun, Huai-Lin Zhao, Yu Tian, Jun-Yi Tang, M. Zhang","doi":"10.1109/ICIIBMS50712.2020.9336400","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336400","url":null,"abstract":"In order to study the effect of panic group behavior on the efficiency of crowd evacuation in emergencies, a crowd emergency evacuation model was constructed based on the theory of big data technology and ant colony algorithm. The panic factor and panic group factor are considered in the model, making the model closer to the actual situation. Based on the complexity of model calculation, the ant colony algorithm is used to solve the model. The research results show that in the emergency evacuation process, attention needs to be paid to the evacuation of key nodes (current restricted areas), and due to the different effects of the panic degree of the evacuated crowd in the evacuation road network on the road sections, attention should be paid to the evacuation process of key road sections to avoid occurrence Crowded stampede and other incidents.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"31 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125702763","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: 1
EMG-Based Interface Using Machine Learning 使用机器学习的基于肌电图的界面
2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2020-11-18 DOI: 10.1109/iciibms50712.2020.9336203
Shinto Takahashi, H. Higa
{"title":"EMG-Based Interface Using Machine Learning","authors":"Shinto Takahashi, H. Higa","doi":"10.1109/iciibms50712.2020.9336203","DOIUrl":"https://doi.org/10.1109/iciibms50712.2020.9336203","url":null,"abstract":"This paper presents an EMG (electromyogram)-based input interface using machine learning for people with physical disabilities of the extremities. We have developed a virtual hand that can be operated in virtual environment using EMG signals. In this paper, we performed a lifting object task and box and block test task with the virtual hand. From the experimental results of the lifting object tasks, it was confirmed that six wrist joint movements were classified, and that an experimental subject appropriately lifted objects with the virtual hand in the virtual space. In the box and block tests task, it was confirmed that he moved block(s) to the opposite side of the box 9 times within 60 sec.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"2006 21","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132678031","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
Automatic Transcription and Captioning System for Bahasa Indonesia in Multi-Speaker Environment 多语环境下印尼语自动转录与字幕系统
2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2020-11-18 DOI: 10.1109/ICIIBMS50712.2020.9336388
Muhammad Bagus Andra, T. Usagawa
{"title":"Automatic Transcription and Captioning System for Bahasa Indonesia in Multi-Speaker Environment","authors":"Muhammad Bagus Andra, T. Usagawa","doi":"10.1109/ICIIBMS50712.2020.9336388","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336388","url":null,"abstract":"Compared to the more established languages, such as English, Bahasa Indonesia, which is still considered a low-resource language, remains deficient in terms of communication-assisting technology development. This research paper proposes a new method for automatically transcribing simultaneous speech in Bahasa Indonesia. The proposed method could be used as an assistive tool in situations that involve simultaneous speech, such as online discussions and remote conferences. The proposed method uses pitch-aware gain-based speech separation to distinguish the speech between speakers, and a recurrent neural network (RNN) is used to generate a transcription of the speech. This method can detect and transcribe a mixed speech signal of up to three speakers and demonstrates enhanced performance in single-speaker situations compared to the baseline method.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131268545","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
Applying Neural Network to Predict Roadway Surrounding Rock Displacement 应用神经网络预测巷道围岩位移
2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2020-11-18 DOI: 10.1109/ICIIBMS50712.2020.9336394
Tang Jun-Yi, Zhang Min, Z. Miao, Y. Wan-jun, Tian Yu
{"title":"Applying Neural Network to Predict Roadway Surrounding Rock Displacement","authors":"Tang Jun-Yi, Zhang Min, Z. Miao, Y. Wan-jun, Tian Yu","doi":"10.1109/ICIIBMS50712.2020.9336394","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336394","url":null,"abstract":"Apply artificial intelligence methods to solve underground engineering problems. First, the factors affecting the displacement of the surrounding rock of the mine roadway are analyzed, and the four indexes that affect the displacement of the roadway are used as the input layer of the neural network. Then, the approach rate of the roadway is used as the output layer of the network to construct the neural network prediction model of the roadway surrounding rock displacement. Finally, learn and train the model. The prediction result shows that it has a certain practical value.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116405065","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
Comparison of CNN-Uni-LSTM and CNN-Bi-LSTM based on single-channel EEG for sleep staging 基于单通道脑电图的CNN-Uni-LSTM与CNN-Bi-LSTM睡眠分期的比较
2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2020-11-18 DOI: 10.1109/ICIIBMS50712.2020.9336419
Qianyu Li, Bei Wang, Jing Jin, Xingyu Wang
{"title":"Comparison of CNN-Uni-LSTM and CNN-Bi-LSTM based on single-channel EEG for sleep staging","authors":"Qianyu Li, Bei Wang, Jing Jin, Xingyu Wang","doi":"10.1109/ICIIBMS50712.2020.9336419","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336419","url":null,"abstract":"Sleep staging is an effective method for diagnosing sleep disorder and monitoring sleep quality. With the rapid development of machine learning technology, the automatic staging methods of sleep gradually replace the traditional manual interpretation which can improve the efficiency on sleep staging for medical research. LSTM networks can save the historical information as a reference for the current moment, which is undoubtedly a good way to improve sleep staging performance. In this paper, a convolutional neural network (CNN) is constructed to extract the features from a single-channel EEG. The Uni-directional Long Short-Term Memory (Uni-LSTM) network and Bi-directional Long Short-Term Memory (Bi-LSTM) network are combined with CNN to realize automatic sleep staging. The obtained results showed that the two presented network frameworks are effective and feasible on sleep staging. The Bi-LSTM which has more enriched sequence information got better classification performance than the Uni-LSTM.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123064465","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: 5
The spherical harmonic based resolution increase and decrease method for cell mesh model with the vertex and face numbers consistency 基于球面谐波的顶点数与面数一致的网格模型分辨率增减方法
2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2020-11-18 DOI: 10.1109/ICIIBMS50712.2020.9336403
Chin-Yi Cheng, Y. Heryanto, Ryo Yamada
{"title":"The spherical harmonic based resolution increase and decrease method for cell mesh model with the vertex and face numbers consistency","authors":"Chin-Yi Cheng, Y. Heryanto, Ryo Yamada","doi":"10.1109/ICIIBMS50712.2020.9336403","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336403","url":null,"abstract":"To understand the life cycle, status and mechanisms of cells, the analyses of cell shape, morphology, deformation, features on the cell membrane and movement play very important roles in those studies. With the growth of imaging, scanning, microscopy, and computational technologies, we now can obtain the image data of the cells and then reconstruct the 3D mesh models of the cells in quicker and more convenient ways. However, due to some limitations, the high-resolution cell image cannot be obtained and it will cause the low-resolution of the 3D cell mesh model after the 3D mesh model reconstruction. On the other hand, too much high resolution of the cell image will turn out to be largely time-consuming when analyzing the membrane or morphology of the cells. To study the changes of cell membrane or morphology like protrusions in the different time points, the vertex and face numbers consistency of the 3D cell mesh models will greatly help to reduce the efforts of data preprocessing. In this study, we proposed the method that applied spherical harmonic, a widely applied method to cell morphology study, to increase and decrease the resolution of cell mesh model from the low- or high-resolution cell images, and reconstruct the 3D cell mesh models with the consistence numbers of vertex and face.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122700036","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: 1
Text Classification Based on Title Semantic Information 基于标题语义信息的文本分类
2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2020-11-18 DOI: 10.1109/ICIIBMS50712.2020.9336401
Y. Liu, Qi Xu, Chunya Wang
{"title":"Text Classification Based on Title Semantic Information","authors":"Y. Liu, Qi Xu, Chunya Wang","doi":"10.1109/ICIIBMS50712.2020.9336401","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336401","url":null,"abstract":"with the rapid development of big data technology, text classification plays an important role in practical application, its applications span a wide range of activities such as sentiment analysis, spam detection, etc. Traditionally, we model the relationship between document and label. However, in many scenarios, document have specific relationship with corresponding title. Inspired by this, a text classification model based on title Semantic Information is proposed in this study. In our model, long short-term memory(LSTM)is used to learn title embedding, document embedding is obtained by using promoted LSTM(TS-LSTM) which take into account the title information. The experimental results on the standard text classification datasets show that its performance is better than the existing state-of-the-art text classification algorithms.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121777140","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: 1
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信