2018 International Conference on Signal Processing and Information Security (ICSPIS)最新文献_第2页

Fetal ECG Extraction Using Independent Components and Characteristics Matching 基于独立分量和特征匹配的胎儿心电图提取

2018 International Conference on Signal Processing and Information Security (ICSPIS) Pub Date : 2018-11-01 DOI: 10.1109/CSPIS.2018.8642725

M. Alkhodari, A. Rashed, Meera Alex, Nai-Shyong Yeh

{"title":"Fetal ECG Extraction Using Independent Components and Characteristics Matching","authors":"M. Alkhodari, A. Rashed, Meera Alex, Nai-Shyong Yeh","doi":"10.1109/CSPIS.2018.8642725","DOIUrl":"https://doi.org/10.1109/CSPIS.2018.8642725","url":null,"abstract":"In this paper, further investigations into a simpler automated use of Independent Component Analysis (ICA) in the process of Fetal ECG (FECG) extraction are performed. Extracting FECG signals through abdominal electrodes helps clinicians in diagnosing the overall health of the fetus non-invasively. In the ICA technique, FECG signals are separated from Abdominal ECG (AECG) mixtures containing maternal and noise signals. 300,000 Data samples of three AECG recordings are obtained from PhysioNet database at 1 kHz sampling frequency. Data are pre-processed through MATLAB software by centering, whitening, and filtering techniques. Then, a simpler Fast ICA algorithm is developed and used to smoothly distinguish between AECG components through automatic signal characteristics matching. Moreover, further analysis of the extracted FECG signal is performed to determine the fetus heart rate. Results successfully show efficient automatic separation between the FECG, Maternal ECG (MECG), and noise from the AECG recordings. In addition, the developed characteristics matching algorithm automatically identified the fetus signal and smoothed it to be ready for further fetal health observations. The integration of AECG signal characteristics as a prior information into the ICA algorithm promises to assist clinicians in decision making when diagnosing fetal health conditions non-invasively.","PeriodicalId":251356,"journal":{"name":"2018 International Conference on Signal Processing and Information Security (ICSPIS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121168480","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

Using Virtual Agent for Facilitating Online Questionnaire Surveys 使用虚拟代理促进在线问卷调查

2018 International Conference on Signal Processing and Information Security (ICSPIS) Pub Date : 2018-11-01 DOI: 10.1109/CSPIS.2018.8642712

Daiki Takatsuki, S. Saiki, Masahide Nakamura

引用次数: 1

Modelling access control for CIM based graph model in Smart Grids 基于CIM的智能电网图模型访问控制建模

2018 International Conference on Signal Processing and Information Security (ICSPIS) Pub Date : 2018-11-01 DOI: 10.1109/CSPIS.2018.8642760

Ivana Kovacevic, A. Erdeljan, Miroslav Zarić, Nikola Dalčeković, I. Lendák

{"title":"Modelling access control for CIM based graph model in Smart Grids","authors":"Ivana Kovacevic, A. Erdeljan, Miroslav Zarić, Nikola Dalčeković, I. Lendák","doi":"10.1109/CSPIS.2018.8642760","DOIUrl":"https://doi.org/10.1109/CSPIS.2018.8642760","url":null,"abstract":"Consumption of electricity has grown, and that tendency will continue according to Energy Information Administration (EIA). Most modern distribution networks, evolving into Smart Grids, are managed through sophisticated software, such as advanced distribution management systems (ADMS). Their operations are based on gathering, analysis and transformation of data coming from the different devices in distribution network. Data volume in Smart Grids is increasing rapidly. Therefore, handling that growing amount of data may pose significant challenges for relational databases in the future, as they may struggle with demand for execution of complex queries. In some cases, like in modeling power system network, the data model is naturally represented by a graph, hence graph databases could provide viable, more efficient alternative. The paper is proposing an approach to include sensitive data access permissions in a graph oriented database – enabling us to decide who can access the sensitive data and who cannot. We have performed analysis on security controls to limit the access to personal data using a realistic data model derived from an existing network model of power distribution utility based in Europe, but described approach is also applicable to other sensitive data. We concluded that the proposed approach would provide ability for implementing access management security controls, while each approach would differently affect the levels of overall system performances.","PeriodicalId":251356,"journal":{"name":"2018 International Conference on Signal Processing and Information Security (ICSPIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132358027","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

Deep Learning Approach To Update Road Network using VGI Data 利用VGI数据更新道路网络的深度学习方法

2018 International Conference on Signal Processing and Information Security (ICSPIS) Pub Date : 2018-11-01 DOI: 10.1109/CSPIS.2018.8642728

Prajowal Manandhar, P. Marpu, Z. Aung

引用次数: 1

Improving the Detection Accuracy of Frequency Modulated Continuous Wave Radar 提高调频连续波雷达的探测精度

2018 International Conference on Signal Processing and Information Security (ICSPIS) Pub Date : 2018-11-01 DOI: 10.1109/CSPIS.2018.8642764

Aamna Al Teneiji, Muhammed Saeed Khan, N. Ali, Ahmed A. Al-Tunaiji

引用次数: 5

Characterizing and Compensating for Errors in a Leap Motion using PCA 用PCA对跳跃运动误差进行表征和补偿

2018 International Conference on Signal Processing and Information Security (ICSPIS) Pub Date : 2018-11-01 DOI: 10.1109/CSPIS.2018.8642792

Hussein Walugembe, Chris Phillips, Jesús Requena-Carrión, T. Timotijevic

{"title":"Characterizing and Compensating for Errors in a Leap Motion using PCA","authors":"Hussein Walugembe, Chris Phillips, Jesús Requena-Carrión, T. Timotijevic","doi":"10.1109/CSPIS.2018.8642792","DOIUrl":"https://doi.org/10.1109/CSPIS.2018.8642792","url":null,"abstract":"This paper concerns a rehabilitation framework that makes use of a low cost \"off-the-shelf\" device. The device is a visual markerless sensor system called the Leap Motion controller (LM). However, before deploying the LM, we investigate its accuracy and limitations in measuring finger joint angles. During a rehabilitation procedure, patients will be flexing and extending their fingers and accurate feedback is a prerequisite for them to benefit effectively from the exercises. During finger joint angle error analysis, we conducted a series of experiments to assess the accuracy of the LM in terms of parameters like elevation, lateral (side-to-side) positioning, forward-backward positioning, and rotation of the hand relative to the LM. We used an \"artist’s hand\" placed above the LM. The artist’s hand is more accurate than a human hand in performing static hand gestures as it can maintain a fixed posture as long as is necessary. According to the results of the error analysis, we apply Principal Component Analysis (PCA) to the LM raw data to see whether the algorithm can compensate for these errors. The experimental results show that the PCA algorithm is feasible, effective and can be applied such that fairly accurate measurements can be obtained and therefore suitable feedback can be provided to the patient using the LM for hand rehabilitation purposes.","PeriodicalId":251356,"journal":{"name":"2018 International Conference on Signal Processing and Information Security (ICSPIS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133377858","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

Fractional Brownian Bridge Model for Alzheimer Disease Detection from EEG Signal 基于分数阶布朗桥模型的脑电信号阿尔茨海默病检测

2018 International Conference on Signal Processing and Information Security (ICSPIS) Pub Date : 2018-11-01 DOI: 10.1109/CSPIS.2018.8642720

Martin Dlask, J. Kukal, P. Sovka

引用次数: 3

Evaluating Feasibility of Image-Based Cognitive APIs for Home Context Sensing 评估基于图像的家庭环境感知认知api的可行性

2018 International Conference on Signal Processing and Information Security (ICSPIS) Pub Date : 2018-11-01 DOI: 10.1109/CSPIS.2018.8642772

Sinan Chen, S. Saiki, Masahide Nakamura

引用次数: 6

[Title page] (标题页)

2018 International Conference on Signal Processing and Information Security (ICSPIS) Pub Date : 2018-11-01 DOI: 10.1109/cspis.2018.8642719

引用次数: 0

Detection of Water-Bodies Using Semantic Segmentation 基于语义分割的水体检测

2018 International Conference on Signal Processing and Information Security (ICSPIS) Pub Date : 2018-11-01 DOI: 10.1109/CSPIS.2018.8642743

Mina Talal, A. Panthakkan, Husameldin Mukhtar, W. Mansoor, S. Almansoori, Hussain Al-Ahmad

引用次数: 13