2017 2nd International Conference on Information Technology (INCIT)最新文献_第4页

ADHD assessment and testing system design based on virtual reality 基于虚拟现实的ADHD评估测试系统设计

2017 2nd International Conference on Information Technology (INCIT) Pub Date : 2017-11-01 DOI: 10.1109/INCIT.2017.8257860

Han-Joo Lee, Youdi Li, S. Yeh, Yanyan Huang, Zhengyu Wu, Zanli Du

{"title":"ADHD assessment and testing system design based on virtual reality","authors":"Han-Joo Lee, Youdi Li, S. Yeh, Yanyan Huang, Zhengyu Wu, Zanli Du","doi":"10.1109/INCIT.2017.8257860","DOIUrl":"https://doi.org/10.1109/INCIT.2017.8257860","url":null,"abstract":"Attention deficit hyperactivity disorder (ADHD) is a common psychological and behavioral disorder in children, adolescents, and even some adults. Several symptoms are observed in ADHD patients, such as difficulty in paying attention, hyperactivity, impulsivity, and cognitive abnormalities. In the past, clinical diagnosis of ADHD was mainly conducted through a paper test scale based on relevant standards. Subsequently, although the time efficiency of test based on computer has improved, disadvantages have remained, for those tests being too tedious to attract the interest of individuals and being restricted by the content and the type. In this study, a combination of virtual reality, eye tracking, and electroencephalogram (EEG) signal acquisition technologies was used to conduct diagnostic assessment and testing on patients with ADHD. Selective attention, sustained attention, abstract reasoning, and cognitive transfer abilities were evaluated by performing visual and auditory continuous performance test (CPT) and the Wisconsin card sorting test (WCST) in a 3D virtual classroom with optional distraction factors. This study also preliminarily analyzed the eye tracking and EEG data and validated their effectiveness and convenience in ADHD diagnosis. The system may provide a deeper level of ADHD diagnosis and cognitive rehabilitation.","PeriodicalId":405827,"journal":{"name":"2017 2nd International Conference on Information Technology (INCIT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115232483","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: 8

Regression model for predicting the maximum load of the movement 预测运动最大负荷的回归模型

2017 2nd International Conference on Information Technology (INCIT) Pub Date : 2017-11-01 DOI: 10.1109/INCIT.2017.8257859

Kunkanit Yoopoo, Supakorn Ongsritakul Benjarat Tirasirichai, Worapan Kusakunniran, M. Robinson

引用次数: 0

Banana cultivar classification using scale invariant shape analysis 基于尺度不变形状分析的香蕉品种分类

2017 2nd International Conference on Information Technology (INCIT) Pub Date : 2017-11-01 DOI: 10.1109/INCIT.2017.8257854

Kwankamon Dittakan, Nawanol Theera-Ampornpunt, Waraphon Witthayarat, Sararat Hinnoy, Supawit Klaiwan, Thunyatorn Pratheep

引用次数: 6

Blind 3D sound source direction using stereo microphones based on time-delay estimation and polar-pattern histogram 基于时延估计和极谱直方图的立体声传声器三维声源方向盲研究

2017 2nd International Conference on Information Technology (INCIT) Pub Date : 2017-11-01 DOI: 10.1109/INCIT.2017.8257881

N. Tengtrairat, W. L. Woo

{"title":"Blind 3D sound source direction using stereo microphones based on time-delay estimation and polar-pattern histogram","authors":"N. Tengtrairat, W. L. Woo","doi":"10.1109/INCIT.2017.8257881","DOIUrl":"https://doi.org/10.1109/INCIT.2017.8257881","url":null,"abstract":"In this research, a new 3 dimension sound source direction algorithm was developed for computing the azimuth and elevation direction of the source under a limited space between two microphones in noise free environment. The proposed azimuth-estimation method is based on the time — delay estimation using maximum likelihood estimation by forming a histogram of power weighted spectrum corresponding to attenuation and time-delay index. For estimating elevation angle, the proposed method requires a sole recorded signal which selected the higher sound pressure level between the two recorded signals. The elevation-angle estimation is computed by phase delay of the windowed autocorrelated signal. The windowed autocorrelation process of the selected signal benefits for reducing the influence of the artifacts. A polar-pattern histogram is employed for identify the source position associated to the microphone i.e. above or below. The proposed method has been demonstrated by real-audio signals. Given by a narrow space, the proposed azimuth-estimation method renders a significant better directional performance improvement over the benchmarked method.","PeriodicalId":405827,"journal":{"name":"2017 2nd International Conference on Information Technology (INCIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129251555","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

Sound events separation and recognition using LiSparse complex nonnegative matrix factorization and multi-class mean supervector support vector machine 基于LiSparse复非负矩阵分解和多类均值超向量支持向量机的声音事件分离与识别

2017 2nd International Conference on Information Technology (INCIT) Pub Date : 2017-11-01 DOI: 10.1109/INCIT.2017.8257878

P. Parathai, N. Tengtrairat, W. L. Woo

{"title":"Sound events separation and recognition using LiSparse complex nonnegative matrix factorization and multi-class mean supervector support vector machine","authors":"P. Parathai, N. Tengtrairat, W. L. Woo","doi":"10.1109/INCIT.2017.8257878","DOIUrl":"https://doi.org/10.1109/INCIT.2017.8257878","url":null,"abstract":"This paper proposes a novel single channel sound separation and events recognition method. First, the sound separation step is based on a complex nonnegative matrix factorization (CMF) with probabilistically optimal L1 sparsity which decomposes an information-bearing matrix into twodimensional convolution of factor matrices that represent the spectral basis and temporal code of the sources. The L1 sparsity CMF method can extract recurrent patterns of magnitude spectra that underlie observed complex spectra and the phase estimates of constituent signals, thus enabling the features of the components to be extracted more efficiently. Second, the event recognition step is built by using the multi-class mean supervector support vector (MS-SVM) machine. The separated signal from the first step is segmented by using the sliding window function and then extract features of each block. The major features which are zero-crossing rate, Mel frequency cepstral coefficients, and short-time energy are investigated to classify sound events signal into defined classes. The mean supervector is encoded from the obtained features. The multi-class MS-SVM method has been examined the recognition performance by modeling with various features. The experimental results show the robustness and efficiency of the proposed method.","PeriodicalId":405827,"journal":{"name":"2017 2nd International Conference on Information Technology (INCIT)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126055951","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

ADFS authentication for healthcare system 医疗保健系统的ADFS身份验证

2017 2nd International Conference on Information Technology (INCIT) Pub Date : 2017-11-01 DOI: 10.1109/INCIT.2017.8257851

Pagapom Pengsart, Ana Romana X. Belo, Juliao Ximenes Vaz, Joaozinho Bemvindo Solitario Marques, Enio Junior

{"title":"ADFS authentication for healthcare system","authors":"Pagapom Pengsart, Ana Romana X. Belo, Juliao Ximenes Vaz, Joaozinho Bemvindo Solitario Marques, Enio Junior","doi":"10.1109/INCIT.2017.8257851","DOIUrl":"https://doi.org/10.1109/INCIT.2017.8257851","url":null,"abstract":"Presently, hospitals are using applications in order to access patient's health data. Therefore, the cost for user's identity management is increased as the number of applications increased, and frustration of remembering multiple usernames and passwords would be a cumbersome for hospitals employees, which may lead to low work productivity and slowing down the services at the hospitals. In addition, patient's health data is vulnerable to fraud due to the vulnerability and insecure authentication system, and difficulty in sharing data and resources among hospitals departments also across hospitals network boundary. Thus, active directory federation system (ADFS) authentication for healthcare system is proposed. It is a single sign on (SSO) and identity federation system prototype that uses active directory federation services framework in order to enable user to perform a secure single sign on authentication. Users can access all the available applications as well as make ease for identity federation among healthcare systems. Therefore, it will enhance user's authentication security and reduce user's identity management cost. Moreover, both network resources and patient's health data will be protected and securely shared among the federated hospitals systems.","PeriodicalId":405827,"journal":{"name":"2017 2nd International Conference on Information Technology (INCIT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127904747","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

Wearable rehabilitation assessment system based on complex network 基于复杂网络的可穿戴康复评估系统

2017 2nd International Conference on Information Technology (INCIT) Pub Date : 2017-11-01 DOI: 10.1109/INCIT.2017.8257888

Li-quan Guo, Jing Chen, Tian-Yu Shen, Jiping Wang, Yuanyuan Li, Xian-Jia Yu

{"title":"Wearable rehabilitation assessment system based on complex network","authors":"Li-quan Guo, Jing Chen, Tian-Yu Shen, Jiping Wang, Yuanyuan Li, Xian-Jia Yu","doi":"10.1109/INCIT.2017.8257888","DOIUrl":"https://doi.org/10.1109/INCIT.2017.8257888","url":null,"abstract":"For stroke patients, rehabilitation assessment performs an important reference for diagnosis and treatment in the rehabilitation process. In order to conduct the rehabilitation assessment quickly, accurately and objectively, a wearable multisource upper limb rehabilitation quantitative assessment system based on 9-axis sensors and flex sensors is designed. The data collected by different sensors were assessed quantitatively and classified by complex network algorithm. To verify the performance of the system, an experiment was carried out on four volunteers, including one healthy person and three stroke patients, whose clinical rehabilitation assessment were stage II, stage III and stage IV respectively. The complex network diagrams and metrics results of the volunteers' 10 Bobath handshake actions completed in unconstrained state were researched and analyzed. The results indicated that 10 Bobath handshake actions acted by stroke patients in different stage and healthy person showed significant difference in network connection quantity, average degree, average path length and average clustering coefficient.","PeriodicalId":405827,"journal":{"name":"2017 2nd International Conference on Information Technology (INCIT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128276080","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

Factors influencing teenagers behavior on posting and sharing messages via Facebook 影响青少年通过Facebook发布和分享信息行为的因素

2017 2nd International Conference on Information Technology (INCIT) Pub Date : 2017-11-01 DOI: 10.1109/INCIT.2017.8257852

Kanokporn Cheevasuntorn, B. Watanapa, Suree Funilkul, Worarat Krathu

引用次数: 5

Search space reduction using hierarchical adaptive flood filled for path planning in computer games 基于层次自适应洪水填充的计算机游戏路径规划搜索空间缩减

2017 2nd International Conference on Information Technology (INCIT) Pub Date : 2017-11-01 DOI: 10.1109/INCIT.2017.8257863

Poonlap Tangasanawit, Sumet Pongphankae

引用次数: 1

Association rule mining for analyzing placement test of computer science students 基于关联规则挖掘的计算机学生分班测试分析

2017 2nd International Conference on Information Technology (INCIT) Pub Date : 2017-11-01 DOI: 10.1109/INCIT.2017.8257869

Peerasak Pianprasit, Parinya Seesai, S. Rimcharoen

引用次数: 1