2016 2nd International Conference on Science in Information Technology (ICSITech)最新文献_第3页

Big data properties designed for customer engagement information via multi-channel digital services 通过多渠道数字服务为客户参与信息设计的大数据属性

2016 2nd International Conference on Science in Information Technology (ICSITech) Pub Date : 2016-10-01 DOI: 10.1109/ICSITECH.2016.7852635

Panant Krairojananan, Sakuna Anuvareepong

引用次数: 1

User difficulties in e-learning system 电子学习系统中的用户困难

2016 2nd International Conference on Science in Information Technology (ICSITech) Pub Date : 2016-10-01 DOI: 10.1109/ICSITECH.2016.7852626

Ramadiani, R. Atan, M. Selamat, R. Abdullah, Noraini Che Pa, Azainil

引用次数: 5

Implementation of the Cellular Automata Algorithm for developing an educational game 元胞自动机算法在教育游戏开发中的实现

2016 2nd International Conference on Science in Information Technology (ICSITech) Pub Date : 2016-10-01 DOI: 10.1109/ICSITECH.2016.7852628

N. Fauzia, D. Rohendi, L. Riza

引用次数: 7

A system to diagnose learning disability in children of special need 诊断有特殊需要的儿童的学习障碍的系统

2016 2nd International Conference on Science in Information Technology (ICSITech) Pub Date : 2016-10-01 DOI: 10.1109/ICSITECH.2016.7852606

M. Rasim, Chepy Cahyadi, L. Riza

引用次数: 2

Vehicle detection and tracking based on corner and lines adjacent detection features 基于拐角和直线相邻检测特征的车辆检测与跟踪

2016 2nd International Conference on Science in Information Technology (ICSITech) Pub Date : 2016-10-01 DOI: 10.1109/ICSITECH.2016.7852641

M. D. Enjat Munajat, D. H. Widyantoro, R. Munir

{"title":"Vehicle detection and tracking based on corner and lines adjacent detection features","authors":"M. D. Enjat Munajat, D. H. Widyantoro, R. Munir","doi":"10.1109/ICSITECH.2016.7852641","DOIUrl":"https://doi.org/10.1109/ICSITECH.2016.7852641","url":null,"abstract":"This paper discusses a new method in detecting moving objects, which is differ from most of the methods used such as Gaussian Mixture Model, and Haar-Like approach. The focus is on utilizing corner detection and line adjacent detection features through thresholding process creating black and white images to detect the corner of each object in each frame. The process divides a frame length into 4 parts, whereas the first part acted as initiation process of moving object recognition while the rest of the frame functioning as vehicle tracking, speed measurement, and number of vehicles calculation. The initiation process started by identifying corner spots of the moving objects that must be recognized as a single object. The lines surpassing through two points are later identified to determine whether those spots have dark color (0) or light color (1). The moving objects is represented by light color (1) and the walking objects is represented by dark color (0). A group of corner spots, identified and connected by two-point-line equation to be recognized as one unified object by using corner and line adjacent method. The identified vehicle objects can be more easily tracked and identified by the average speed in order to obtain the number of passing vehicles. The research result shows that in the initiation phase, the corner and line adjacent features able to detect moving object and distinguish it with different objects. Furthermore, in tracking phase, system is able to track the vehicle position, measuring the speed and number of vehicles. The system is proven to be able to recognize the moving objects quickly and accurately resulting in the more feasible process of speed measurement and tracking.","PeriodicalId":447090,"journal":{"name":"2016 2nd International Conference on Science in Information Technology (ICSITech)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121913542","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

Privacy and security of sharing referral medical record for health care system 卫生保健系统转诊病历共享的隐私与安全

2016 2nd International Conference on Science in Information Technology (ICSITech) Pub Date : 2016-10-01 DOI: 10.1109/ICSITECH.2016.7852639

Mike Yuliana, Haryadi Amran Darwito, Amang Sudarsono, Gabymars Yofie

引用次数: 2

Path analysis method to identify factors affecting consumer interest on online shopping 路径分析法识别影响消费者网上购物兴趣的因素

2016 2nd International Conference on Science in Information Technology (ICSITech) Pub Date : 2016-10-01 DOI: 10.1109/ICSITECH.2016.7852601

R. Purwaningsih, Belan Adison

{"title":"Path analysis method to identify factors affecting consumer interest on online shopping","authors":"R. Purwaningsih, Belan Adison","doi":"10.1109/ICSITECH.2016.7852601","DOIUrl":"https://doi.org/10.1109/ICSITECH.2016.7852601","url":null,"abstract":"Current research indicates that a novelty, exciting and engaging shopping experience can positively affect consumer buying behavior. Identifying factors that influence the consumer behavior on use a virtual world for shopping will help retailers to create and maintain a presence in a virtual world, while positive impacting purchases and returns intentions. Therefore, the objectives of this study are to understand what factors affect consumer intention to shop in a virtual world and to analyze the relationships among these factors. Particularly, this study explores consumer innovativeness (consumer novelty seeking and consumer independent judgment making) as an external variable that influences consumer intention indirectly through its effects on consumer experiences with the virtual world application (ease of use, control, concentration, and enjoyment). Path analysis method is used to identify the variable given significant influence to consumer intention to shop. The finding indicates that independent variables Consumer Novelty Seeking and Consumer Independent Judgment Making have influence to Perceived concentration, Perceived enjoyment, and Ease of Use. These three variables give significant influence to consumer intention to shop.","PeriodicalId":447090,"journal":{"name":"2016 2nd International Conference on Science in Information Technology (ICSITech)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114931539","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

Cloud computing sensitive data protection using multi layered approach 云计算敏感数据保护采用多层方法

2016 2nd International Conference on Science in Information Technology (ICSITech) Pub Date : 2016-10-01 DOI: 10.1109/ICSITECH.2016.7852610

Haifaa Jassim Muhasin, R. Atan, Marzanah A. Jabar, Salfarina Abdullah

引用次数: 6

Car detection based on road direction on traffic surveillance image 基于道路方向的交通监控图像车辆检测

2016 2nd International Conference on Science in Information Technology (ICSITech) Pub Date : 2016-10-01 DOI: 10.1109/ICSITECH.2016.7852660

A. Prahara, Murinto

{"title":"Car detection based on road direction on traffic surveillance image","authors":"A. Prahara, Murinto","doi":"10.1109/ICSITECH.2016.7852660","DOIUrl":"https://doi.org/10.1109/ICSITECH.2016.7852660","url":null,"abstract":"One of the challenges in car detection is to be able to detect car in any viewpoint from traffic surveillance camera. The size, shape, and appearance of car are different if they are viewed from various viewpoint of traffic surveillance cameras. Car also has the most variety of models compared to the other vehicle. However, car poses usually follow road direction. Therefore, this research proposes a method to detect car based on road direction. The method utilizes 3D car models to generate car poses, groups them into four pairs of viewpoint orientation: 1) front / back view, 2) top left / bottom right view, 3) top right / bottom left view, and 4) left side / right side view, then builds car detectors corresponding to each orientation. On traffic surveillance image, road area is extracted to localize the detection area and road direction is estimated to determine the car detector that will be used by Linear-Support Vector Machine (Linear-SVM). Finally, SVM classifies the features extracted by Histogram of Oriented Gradients (HOG) to detect cars. The test result on various viewpoints of traffic surveillance image gives 0.9098 of Balance Accuracy (BAC).","PeriodicalId":447090,"journal":{"name":"2016 2nd International Conference on Science in Information Technology (ICSITech)","volume":"19 814 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121387875","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: 5

The determinants affecting e-loyalty: Hospitality industry in Indonesia 影响电子忠诚度的决定因素:印度尼西亚的酒店业

2016 2nd International Conference on Science in Information Technology (ICSITech) Pub Date : 2016-10-01 DOI: 10.1109/ICSITECH.2016.7852621

V. U. Tjhin, R. Tavakoli, Perwiro Atmojo Robertus Nugroho

引用次数: 7