H. Herath, M. Ekanayake, G. Godaliyadda, J. Wijayakulasooriya
{"title":"Multi-feature based hand-gesture recognition","authors":"H. Herath, M. Ekanayake, G. Godaliyadda, J. Wijayakulasooriya","doi":"10.1109/ICTER.2015.7377668","DOIUrl":"https://doi.org/10.1109/ICTER.2015.7377668","url":null,"abstract":"The work presents a comprehensive methodology for recognition of temporally progressing hand gestures. Motion measurements associated with the hand position, orientation and finger bending are considered as time-series data sets and utilized for the recognition process. In addressing the hand gesture recognition problem in its multi-feature nature, a novel methodology for discovering relevant features for each gesture class is proposed. The two staged comparison approach with the proposed stratification of gesture classes based on their relevant features enabled the methodology to handle the available large number of gesture classes. Gesture comparison is based on a subspace produced by Fisher Linear Discriminant Analysis (FLDA) of temporal features in a manner that rhythmic differences between gesture trials are minimized. Results of the overall methodology have been elaborated for available AUSLAN hand-gesture datasets.","PeriodicalId":142561,"journal":{"name":"2015 Fifteenth International Conference on Advances in ICT for Emerging Regions (ICTer)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125760715","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}
{"title":"Effective clinical decision-making from Practice-Based Evidence","authors":"Hamzah Osop, T. Sahama","doi":"10.1109/ICTER.2015.7377707","DOIUrl":"https://doi.org/10.1109/ICTER.2015.7377707","url":null,"abstract":"This is an ongoing research investigating the use of health information technologies (HIT) to improve clinical decisionmaking processes. Effective and timely clinical decision-making can lead to positive improvements in patient's health outcome. The primary hypothesis of this research is that a Practice-Based Evidence (PBE) approach by utilisation of Electronic Health Records (EHR), improves clinical decision-making capabilities of healthcare professionals. This study therefore looks to answer the following research questions. (I) What is the current practice by healthcare professionals when making clinical decisions? (2) What limits the ability to make well-informed clinical decisions? and (3) How EHR and PBE assisting improvements to the clinical decision-making capabilities?","PeriodicalId":142561,"journal":{"name":"2015 Fifteenth International Conference on Advances in ICT for Emerging Regions (ICTer)","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124641600","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}
Malintha Amarasinghe, Sasikala Kottegoda, A. Arachchi, Shashika Ranga Muramudalige, H. Bandara, A. Azeez
{"title":"Cloud-based driver monitoring and vehicle diagnostic with OBD2 telematics","authors":"Malintha Amarasinghe, Sasikala Kottegoda, A. Arachchi, Shashika Ranga Muramudalige, H. Bandara, A. Azeez","doi":"10.4018/IJHCR.2015100104","DOIUrl":"https://doi.org/10.4018/IJHCR.2015100104","url":null,"abstract":"We present a cloud-based vehicular data acquisition and analytics system for real-time driver behavior monitoring, trip analysis, and vehicle diagnostics. Our system consists of an On Board Diagnostics (OBD) port to Bluetooth dongle, a mobile app running on a smart phone, and a cloud-based backend. We use a Complex Event Processor (CEP) at both the smart phone and the backend to detect and notify unsafe and anomalous events in real time. For example, CEP engine at the smart phone can alert the driver about rising coolant temperature and rapid fuel drops. It also provides a trip log and filter out what messages to be send to the backend, saving both the bandwidth and power. CEP on the cloud detects reckless driving in real time based on the sensor data provided through the OBD port. Historical data is also used by the backend CEP engine to detect driving anomalies and to predict impeding sensor failures. The mobile app visualizes both real-time data from sensors and alerts. A web-based interface is provided to access the backend information. We tested the system on actual vehicles and demonstrated that the computing, bandwidth, and power consumption of the smart phone is reasonable. App is currently available in Google Play.","PeriodicalId":142561,"journal":{"name":"2015 Fifteenth International Conference on Advances in ICT for Emerging Regions (ICTer)","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121629581","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}