Machine Learning in Sensors and Imaging

Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens

Life Sciences Program Tasks and Bibliography for FY 1997

This document includes information on all peer reviewed projects funded by the Office of Life and Microgravity Sciences and Applications, Life Sciences Division during fiscal year 1997. This document will be published annually and made available to scientists in the space life sciences field both as a hard copy and as an interactive internet web page

Modelling Emergency Medical Services

Emergency Medical Services (EMS) play a pivotal role in any healthcare organisation. Response and turnaround time targets are always of great concern for the Welsh Ambulance NHS Trust (WAST). In particular, the more rural areas in South East Wales consistently perform poorly with respect to Government set response standards, whilst delayed transfer of care to Emergency Departments (EDs) is a problem publicised extensively in recent years. Many Trusts, including WAST, are additionally moving towards clinical outcome based performance measures, allowing an alternative system-evaluation approach to the traditional response threshold led strategies, resulting in a more patient centred system. Three main investigative parts form this thesis, culminating in a suite of operational and strategic decision support tools to aid EMS managers. Firstly, four novel allocation model methods are developed to provide vehicle allocations to existing stations whilst maximising patient survival. A detailed simulation model then evaluates clinical outcomes given a survival based (compared to response target based) allocation, determining also the impact of the fleet, its location and a variety of system changes of interest to WAST (through ‘what-if?’ style experimentation) on entire system performance. Additionally, a developed travel time matrix generator tool, enabling the calculation and/or prediction of journey times between all pairs of locations from route distances is utilised within the aforementioned models. The conclusions of the experimentation and investigative processes suggest system improvements can in fact come from better allocating vehicles across the region, by reducing turnaround times at hospital facilities and, in application to South East Wales, through alternative operational policies without the need to increase resources. As an example, a comparable degree of improvement in patient survival is witnessed for a simulation scenario where the fleet capacity is increased by 10% in contrast to a scenario in which ideal turnaround times (within the target) occur

Pseudo National Security System of Health in Indonesia

ABstRACt Adolescence is a crucial period where one tends to identify who they are as an individual. However, as a teenager is struggling to find his/her place in this world, it is also a time where they are prone to engaging in risk behaviors, which tend to have an extreme psychological impact. The objective was to explore the experiences of an adolescent who engages in risk behaviors and to understand their level of personal fables. The study was a qualitative design with content analysis with semi-structured interviews of ten male adolescents aged 16-18 years. The major findings of the study indicated that adolescent’s pattern of thinking revolves around the fact that they are invincible and invulnerable. Furthermore, adolescents are aware of the risks they are putting themselves through and how in the process they are hurting others. The implications of the study are to conduct more life skill programs in schools; greater awareness has to be created on the impact and harmful effects of such behaviors