2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)最新文献_第7页

The Effect of the Internet of Things (IoT) on Education Business Model 物联网(IoT)对教育商业模式的影响

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.74

Maryam Bagheri, Siavosh H. Movahed

引用次数: 137

An Analysis to Overcome Shortcomings to Improve the Accessibility for the Blind: A Case Study on Facebook's Homepage 分析如何克服不足，改善盲人无障碍:以Facebook主页为例

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.75

Petra Gröber, Julia Koster

引用次数: 7

Preventing Disclosure of Personal Data in IoT Networks 防止物联网网络中的个人数据泄露

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.68

Ilaria Torre, G. Adorni, Frosina Koceva, Odnan Ref Sanchez

{"title":"Preventing Disclosure of Personal Data in IoT Networks","authors":"Ilaria Torre, G. Adorni, Frosina Koceva, Odnan Ref Sanchez","doi":"10.1109/SITIS.2016.68","DOIUrl":"https://doi.org/10.1109/SITIS.2016.68","url":null,"abstract":"Sharing data among applications is a growing phenomenon. With the IoT, this phenomenon becomes more significant. As already studied in social networks, data sharing has the drawback of privacy risks. Authorization protocols and cryptographic systems may not be enough to ensure that user data and metadata are not used for non-legitimate purposes. There are different scenarios and several personal data management proposals aimed to improve privacy protection. However, a risk that is always present is related to the possibility of processing and aggregating public and authorized data to infer sensitive information and data that the user may not want to share. These approaches, often called inference attacks, concern the disclosure of personal user data and have been widely studied in social networks. In this paper we describe the problem and some techniques to face it, showing its relevance in the IoT. Then we present the concept of an Adaptive Inference Discovery Service AID-S, conceived as a service that may support users to prevent this kind of information leakage and that can be integrated into personal data managers.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121815850","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: 9

A Computer-Aided System for Differential Count from Peripheral Blood Cell Images 计算机辅助外周血细胞图像鉴别计数系统

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.26

A. Loddo, Lorenzo Putzu, C. D. Ruberto, G. Fenu

{"title":"A Computer-Aided System for Differential Count from Peripheral Blood Cell Images","authors":"A. Loddo, Lorenzo Putzu, C. D. Ruberto, G. Fenu","doi":"10.1109/SITIS.2016.26","DOIUrl":"https://doi.org/10.1109/SITIS.2016.26","url":null,"abstract":"The differential count and analysis of blood cells in microscope images can provide useful information concerning the health of patients. There are three major blood cell types, namely, erythrocytes (RBCs), leukocytes (WBCs), and platelets. Automated blood cell analysers can provide RBCs, WBCs and platelets count but the presence of abnormal cells could affect the cells counting, that should be checked manually. This is why today the conventional practice for such procedure is executed manually by pathologists under light microscope. However, the manual visual inspection is tedious, time consuming, repetitive and it is strongly influenced by the operator's capabilities and tiredness. Therefore, a good clinical decision support system for cells counting and classification has always become a necessity. Few examples of automated systems that can analyse and classify blood cells have been reported in the literature. This research proposes a computer-aided systems that simulates a human visual inspection to automate the process of detection and identification of WBCs and RBCs from blood smear images. The proposed method has been tested on public datasets of blood cell images and demonstrates a reliable and effective system for differential counting, obtaining an average accuracy value of 99.2% for WBCs and 98% for RBCs, outperforming the state-of-the-art.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123805026","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

Eye Shape and Corners Detection in Periocular Images Using Particle Filters 基于粒子滤波的眼周图像的眼形和角检测

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.12

D. Borza, R. Danescu

引用次数: 3

Some Numerical Remarks on a Meshless Approximation Method 关于无网格近似法的数值说明

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.116

E. Francomano, G. Micale, M. Paliaga, G. Ala

引用次数: 1

Towards Using Cognitive Word Associates to Create Functional Remote Associates Test Problems 利用认知词关联创建功能远端关联测试问题的探讨

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.101

Ana-Maria Olteţeanu

引用次数: 1

Analyzing Surface Defects in Apples Using Gabor Features 利用Gabor特征分析苹果表面缺陷

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.36

P. Jolly, S. Raman

引用次数: 11

An Intelligent System to Classify Epileptic and Non-Epileptic EEG Signals 一种癫痫与非癫痫脑电信号的智能分类系统

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.44

Emad-ul-Haq Qazi, M. Hussain, Hatim Aboalsamh, Wadood Abdul, Saeed Bamatraf, I. Ullah

{"title":"An Intelligent System to Classify Epileptic and Non-Epileptic EEG Signals","authors":"Emad-ul-Haq Qazi, M. Hussain, Hatim Aboalsamh, Wadood Abdul, Saeed Bamatraf, I. Ullah","doi":"10.1109/SITIS.2016.44","DOIUrl":"https://doi.org/10.1109/SITIS.2016.44","url":null,"abstract":"Epilepsy is a neurological disorder disease that affects more than 55 million people in the world. In this paper, we have proposed an efficient intelligent pattern recognition system for the classification of epileptic and non-epileptic electroencephalogram (EEG) signals. For this purpose, we used state-of-the-art machine learning technique, i.e., SVM (support vector machines) to classify epileptic and non-epileptic signals. Two (02) different classes of signals are used in this study, i.e., non-epileptic with open eyes and epileptic in seizure condition. One hundred (100) subjects from each class were employed for extraction of discriminatory features and classification purpose. After pre-processing of EEG signals, we use discrete wavelet transform (DWT) to decompose signals upto level 5. Then various features, i.e., energy, entropy and standard deviation are extracted from wavelet bands. Next, we use these features in the classification of signals. We achieved the classification accuracy of 100 % at delta band (0 to 3 Hz) and theta band (3 to 6 Hz). The comparisons with the previous studies show the significance of this system, which can be utilized in real-time as well as in offline clinical applications.","PeriodicalId":403704,"journal":{"name":"2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130865626","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: 12

Sparse Multi-Model Based Denoising 基于稀疏多模型的去噪

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI: 10.1109/SITIS.2016.30

Rajesh Bhatt, V. Subramanian

引用次数: 0