2018 4th International Conference on Computer and Technology Applications (ICCTA)最新文献_第4页

Software tools for environmental monitoring of the Northern part of the Caspian sea 里海北部环境监测的软件工具

2018 4th International Conference on Computer and Technology Applications (ICCTA) Pub Date : 2018-05-01 DOI: 10.1109/CATA.2018.8398661

G. D. Kaziyeva, S. Sagnayeva, G. Sembina, A. Ismailova

引用次数: 1

RPN+ fast boosted tree: Combining deep neural network with traditional classifier for pedestrian detection RPN+快速提升树:将深度神经网络与传统分类器相结合用于行人检测

2018 4th International Conference on Computer and Technology Applications (ICCTA) Pub Date : 2018-05-01 DOI: 10.1109/CATA.2018.8398672

Jiaxiang Zhao, Jun Li, Yingdong Ma

引用次数: 8

A new combined system using ANN and complex wavelet transform for tissue density classification in mammography images 基于神经网络和复小波变换的乳腺x线图像组织密度分类新方法

2018 4th International Conference on Computer and Technology Applications (ICCTA) Pub Date : 2018-05-01 DOI: 10.1109/CATA.2018.8398679

H. Yaşar, Uğurhan Kutbay, F. Hardalaç

引用次数: 4

A new clustering approach to identify the values to query the deep web access forms 一种新的聚类方法来识别深网访问表单的值

2018 4th International Conference on Computer and Technology Applications (ICCTA) Pub Date : 2018-05-01 DOI: 10.1109/CATA.2018.8398666

Yasser Saissi, A. Zellou, A. Idri

引用次数: 1

A method of verification of software based on CPN 一种基于CPN的软件验证方法

2018 4th International Conference on Computer and Technology Applications (ICCTA) Pub Date : 2018-05-01 DOI: 10.1109/CATA.2018.8398660

Tao Sun, Haifen Ren, Linjing Zhang

引用次数: 0

Decision support system for diagnosing anemia 贫血诊断决策支持系统

2018 4th International Conference on Computer and Technology Applications (ICCTA) Pub Date : 2018-05-01 DOI: 10.1109/CATA.2018.8398684

S. Belginova, Indira Uvaliyeva, Aigerim Ismukhamedova

引用次数: 16

A novel approach for estimation of coronary artery calcium score class using ANN and body mass index, age and gender data 一种利用神经网络和身体质量指数、年龄和性别数据估计冠状动脉钙评分等级的新方法

2018 4th International Conference on Computer and Technology Applications (ICCTA) Pub Date : 2018-05-01 DOI: 10.1109/CATA.2018.8398680

H. Yaşar, S. Serhatlioglu, Uğurhan Kutbay, F. Hardalaç

{"title":"A novel approach for estimation of coronary artery calcium score class using ANN and body mass index, age and gender data","authors":"H. Yaşar, S. Serhatlioglu, Uğurhan Kutbay, F. Hardalaç","doi":"10.1109/CATA.2018.8398680","DOIUrl":"https://doi.org/10.1109/CATA.2018.8398680","url":null,"abstract":"Cardiovascular diseases group is the one that causes most death in the world. There is a strong association between coronary artery disease and coronary artery calcium score. Therefore; coronary artery calcium score and class are important for the determination of risk of heart attack. In this study, a new automated assessment system is proposed to estimate the Agatston coronary artery calcium score class without need for measurement. In the estimation study performed under two different titles on the basis of three classes and five classes for Agatston coronary artery calcium score; ANN, body mass index, age and gender were used. In the study, the data collected from a total of 260 patients (105 female, 155 male), ages ranging between 29 and 77 years (an average of 45.56 years), were used. As a result of the study, it was seen that a successful estimation rate of 67.69% was reached in estimating the class of Agatston coronary artery calcium score for the patients correctly when an estimation was made with five classes were taken as basis. In the study, a rate of success of 91.15% was achieved in the estimation based on three classes.","PeriodicalId":231024,"journal":{"name":"2018 4th International Conference on Computer and Technology Applications (ICCTA)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128816243","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

Responsive web design commitment by the web developers in Palestine 响应式网页设计承诺的网页开发人员在巴勒斯坦

2018 4th International Conference on Computer and Technology Applications (ICCTA) Pub Date : 2018-05-01 DOI: 10.1109/CATA.2018.8398658

Fawwaz Yousef Alnawaj'ha, Mohammed AbuTaha

引用次数: 1

Image denoising method by endorsement of neighborhood pixels 基于邻域像素背书的图像去噪方法

2018 4th International Conference on Computer and Technology Applications (ICCTA) Pub Date : 2018-05-01 DOI: 10.1109/CATA.2018.8398678

Ayesha Saadia, A. Rashdi

引用次数: 1

Comparative analysis on features extraction strategies for GPCR classification GPCR分类特征提取策略的比较分析

2018 4th International Conference on Computer and Technology Applications (ICCTA) Pub Date : 2018-05-01 DOI: 10.1109/CATA.2018.8398676

Safia Bekhouche, Yamina Mohamed Ben Ali

{"title":"Comparative analysis on features extraction strategies for GPCR classification","authors":"Safia Bekhouche, Yamina Mohamed Ben Ali","doi":"10.1109/CATA.2018.8398676","DOIUrl":"https://doi.org/10.1109/CATA.2018.8398676","url":null,"abstract":"Protein is an alphabetical sequence of amino acids, this form of sequence can never be processed by data mining and machine learning algorithms that are needed for numerical data. Feature extraction strategies are used to transform the alphabetical sequence into a feature vector representing the properties of this sequence. But each method produces an attributes vector of different size and properties to others. Our work aims to compare three most used feature extraction strategies that are AAC, PseAAC and DC using five selected machine learning algorithms deployed on weka platform, they are evaluated based on Accuracy, F-measure, MCC and error rate measures. This comparison helps us to decide what feature extraction strategy is best suited to work while applying computationally expensive selected machine learning algorithms on a protein sequence data. Experiments suggested that AAC, PseAAC and DC methods would be optimal on GPCR classification at sub sub-family level using MLP algorithm. While working with other classifiers would be optimal if we do not use a huge subset of data so a grand class number. Hence this study concludes that a better performance would be reached when a good classifier is established.","PeriodicalId":231024,"journal":{"name":"2018 4th International Conference on Computer and Technology Applications (ICCTA)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129440262","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