2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)最新文献_第3页

Convolution Based Face Recognition Using DWT and HOG 基于DWT和HOG的卷积人脸识别

2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2018-10-01 DOI: 10.1109/ICIIBMS.2018.8550025

J. Ravikumar, A. Ramachandra, K. Raja, V. R.

引用次数: 7

Rapid, Noninvasive Diagnosis of Demodex Mite by Using a Low Cost, Portable, Full-Field OCT 低成本、便携、全视野OCT快速、无创诊断蠕形螨

2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2018-10-01 DOI: 10.1109/ICIIBMS.2018.8549939

Yi-Cheng Liu, Ting-Wei Chang, Hung-Chih Chiang, Chir-Weei Chang, Yuan-Chin Lee

引用次数: 0

Research on Network Trading System Using Blockchain Technology 基于区块链技术的网络交易系统研究

2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2018-10-01 DOI: 10.1109/ICIIBMS.2018.8550004

Yuan Wanjun, Wu Yuan

{"title":"Research on Network Trading System Using Blockchain Technology","authors":"Yuan Wanjun, Wu Yuan","doi":"10.1109/ICIIBMS.2018.8550004","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8550004","url":null,"abstract":"Blockchain technology is actually a distributed database technology. It adopts a series of security technologies such as P2P network technology, asymmetric encryption technology and smart contract technology to ensure the security and reliability of transactions. It has advantages of decentralization, anonymity and traceability. In view of the problems existing in the current centralized network transaction mode, this paper creatively proposes the design scheme of “network trading system based on blockchain technology”, and proposes a safe and feasible network transaction system model to ensure the transaction in network data transmission, data processing and other aspects of security. In-depth research and elaboration of some key technologies and principles in the network trading system. Comprehensive application of P2P network technology, asymmetric encryption technology, consensus mechanism, smart contract and other technologies to solve the security problem of network transaction systems. The specific implementation process is given for the transaction system from the aspects of demand analysis, transaction process, interface design, data model design and storage scalability design. Finally, it summarizes the application of blockchain technology in network transactions and points out the future research direction. (Abstract)","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122412685","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: 16

Face Tracking based on Temperature Distribution of Thermal Images for Real-Time Psychophysiological States Evaluation using Facial Skin Temperature 基于热图像温度分布的人脸跟踪，利用面部皮肤温度实时评估心理生理状态

2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2018-10-01 DOI: 10.1109/ICIIBMS.2018.8549966

Hiroki Ito, K. Oiwa, A. Nozawa

引用次数: 5

Effects of Carbon Nanoparticles on Bacteria and Application Potential as Biosensors of Pollution Detection of Ocean Water Carbon Nanoparticles as Antibiotics and Biosensors of Ocean Water 纳米碳对细菌的影响及其在海水污染检测中的应用前景纳米碳作为抗生素和海水生物传感器

2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2018-10-01 DOI: 10.1109/ICIIBMS.2018.8550011

Akerke Altaikyzy, Haiyan Fan, Yingqiu Xie

{"title":"Effects of Carbon Nanoparticles on Bacteria and Application Potential as Biosensors of Pollution Detection of Ocean Water Carbon Nanoparticles as Antibiotics and Biosensors of Ocean Water","authors":"Akerke Altaikyzy, Haiyan Fan, Yingqiu Xie","doi":"10.1109/ICIIBMS.2018.8550011","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8550011","url":null,"abstract":"Bacterial infections have been clinically treated with variety of antibiotics. The excessive use of antibiotic nowadays, however, has caused severe drug resistance by the emergence of bacteria strains. The improper management of antibiotic usage has led to the contamination of the environment that threatens people's life. Therefore, it becomes critical to develop novel antibacterial agents that will reduce the risk of drug resistance to its minimum. As the nanomaterial and nanotechnology find their ways to anchor on nearly every aspect of our daily life, the antibacterial properties of nanoparticles have been studied and have shown promising effect while treating different strains of bacteria. Metal containing nanomaterials, though very effective, may potentially accumulate in human body and become cytotoxic. Recently, carbon nano dots derived from natural product have shown comparable antibacterial effect but are low cytotoxicity to human cells and cost. In this study, bactericidal effect of dates-derived carbon nanoparticles (CNPs) on survival of different gram-negative or gram-positive strains was tested. Dates-derived CNPs exhibited strong antibacterial effect against both gram-positive and gram-negative bacteria. Impressively, complete inhibition in the growth of all bacterial strains used in this research was achieved using as prepared CNPs. Moreover, the as prepared CNP was discovered as a great sensor to detect the pollution in ocean water. In deed, an enzyme kit was developed for the ocean water pollution detection. Thus CNP has great potential as biosensor both in medicine and pollution detection of ocean water.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131483418","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

Performance Prediction of Jupyter Notebook in JupyterHub using Machine Learning 基于机器学习的Jupyter Notebook在JupyterHub中的性能预测

2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2018-10-01 DOI: 10.1109/ICIIBMS.2018.8550030

Pariwat Prathanrat, Chantri Polprasert

引用次数: 10

A Design of TSK-Based ELM for Prediction of Electrical Power in Combined Cycle Power Plant 基于tsk的联合循环电厂功率预测ELM设计

2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2018-10-01 DOI: 10.1109/ICIIBMS.2018.8549989

Chan-Uk Yeom, Keun-Chang Kwak

{"title":"A Design of TSK-Based ELM for Prediction of Electrical Power in Combined Cycle Power Plant","authors":"Chan-Uk Yeom, Keun-Chang Kwak","doi":"10.1109/ICIIBMS.2018.8549989","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8549989","url":null,"abstract":"This paper is concerned with the prediction of full load electrical power output of a base load operated Combined Cycle Power Plant (CCPP) based on Takai-Sugeno-Kang (TSK)-based Extreme Learning Machine (ELM). Here TSK-based ELM is designed by a systematic approach to producing automatic fuzzy if-then rules, while the conventional ELM is designed without knowledge information. The design of TSK-ELM consists of two main steps. In the first step, an initial randomly partition matrix is generated and cluster centers for random clustering are estimated. These centers are used to determine the premise part of fuzzy rules. Next, the linear parameters of the TSK fuzzy type in consequent part are estimated using the Least Squares Estimate (LSE) method. The experiments were performed on prediction of electrical power in CCPP by the presented TSK-ELM. The input variables include hourly average ambient variables temperature, ambient pressure, relative humidity and exhaust vacuum. The output variable is used to predict the net hourly electrical energy output. The experimental results revealed that the presented TSK-ELM showed good performance in compared to the original ELM.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116162205","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

Gesture Recognition for Home Automation Using Transfer Learning 基于迁移学习的家庭自动化手势识别

2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2018-10-01 DOI: 10.1109/ICIIBMS.2018.8549921

Sehoon Yang, Sang-Joon Lee, Yungcheo l Byun

引用次数: 7

Spatial Domain Face Recognition System Using Convolution of PDV and LBP 基于PDV和LBP卷积的空间域人脸识别系统

2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2018-10-01 DOI: 10.1109/ICIIBMS.2018.8549957

Munikrishna D C, K. Raja, V. R.

引用次数: 4

Identifying Severity Level of Cybersickness from EEG signals using CN2 Rule Induction Algorithm 利用CN2规则归纳法从脑电信号中识别晕动症的严重程度

2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2018-10-01 DOI: 10.1109/ICIIBMS.2018.8549968

Evi Septiana Pane, Alfi Zuhriya Khoirunnisaa, A. Wibawa, M. Purnomo

{"title":"Identifying Severity Level of Cybersickness from EEG signals using CN2 Rule Induction Algorithm","authors":"Evi Septiana Pane, Alfi Zuhriya Khoirunnisaa, A. Wibawa, M. Purnomo","doi":"10.1109/ICIIBMS.2018.8549968","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8549968","url":null,"abstract":"One of the typical gaming disorder is cybersickness. Cybersickness is the condition that occurs during or after exposed by the virtual environment. The increasing of cybersickness symptoms in gamers can lead to the poor health condition. Prior studies in investigating cybersickness employ subjective self-reports questionnaire, i.e., simulator sickness questionnaire (SSQ). However, the objective measurement is required to determine the actual condition of subjects due to cybersickness severity level. Therefore, this paper proposed identification of cybersickness severity level using electroencephalograph (EEG) signals. From the EEG, we extract the best feature such as percentage change (PC) of power percentage (PP) in beta and theta frequency band from pre- to post-stimulation. We found a specific pattern of cybersickness that marked by the sudden decreasing of $mathbf{PP}beta$ during the recording between baseline segment (4 minutes) and the last part (4 minutes) of game playing. Unlike previous studies, this paper proposed the rules-based algorithm i.e. CN2 Rules Induction for identifying cybersickness severity level. This giving ease for medical-expert to determine appropriate diagnosis and treatment towards patients. The classification yields the best accuracy of 88.9% using the CN2 rule induction. It is outperforming other classifiers accuracies such as decision tree (72.2%) and SVM (83.3 %). According to the results, incorporating PC of the $mathbf{PP}beta$ feature with the rules-based algorithm is working well for identifying cybersickness severity level from EEG.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"6 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120894047","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: 17