Path planning algorithm for a car-like robot based on cell decomposition method

This project proposes an obstacle avoiding path planning algorithm based on cell decomposition method for a car-like robot. Dijkstra’s algorithm is applied in order to find the shortest path. Using cell decomposition, the free space of the robot is exactly partitioned into cells. Then, the connectivity graph is created followed by calculating the shortest path by Dijkstra’s algorithm. This project also concerns the robot kinematic constraints such as minimum turning radius. Thus, kinematic modeling and Bezier curve have been used to obtain a feasible path. The algorithm is able to obtain a curvature bounded path with sub-optimal curve length while taking cell decomposition as reference skeleton. The C-space concept has been applied in this situation. The obstacles on the map are expanded according to the size of car-like robot, so that the robot could be treated as points on this map and the coordinates of the map is corresponding to these points. The simulation and experimental result shows the algorithm can obtain the collision free path which satisfies the curvature constraint and approaches the minimal curve length for a car-like robot

Analysis and Life Cycle Assessment of Printed Antennas for Sustainable Wireless Systems

Siirretty Doriast

Survey instrument for measuring level of preparedness amongst healthcare personnel in radiation emergency

Drills and exercises are globally practiced to investigate the level of preparedness towards disaster events. However, these activities are rarely conducted because they require substantial investment, specifically to budget and time. A self-reported survey may serve as an alternative approach, although it may not be as effective as drills and exercises. As part of the survey development process, this article discusses preliminary validation of a survey instrument to measure the level of preparedness towards radiation emergency amongst healthcare personnel. Prior to this validation process, extensive literature reviews pointed out that the instrument consists of three constructs of preparedness, namely readiness, willingness, and ability. A total of seven subject matter experts were invited to judge the contents for verification purposes. Randolph Kappa analysis was then conducted to analyse their judgment to allow irrelevant items to be filtered from the rest prior to any improvements. Initially, the survey instrument consisted of 69 items; however, the analysis omitted 16 of them. The following values for each preparedness construct were: Readiness (0.77), Willingness (0.70), and Ability (0.73). These findings indicate that contents of the instrument are valid. Further analysis should be fulfilled to complete validation process to ensure its practicality prior to using it as an evaluation tool

Systems Engineering

The book "Systems Engineering: Practice and Theory" is a collection of articles written by developers and researches from all around the globe. Mostly they present methodologies for separate Systems Engineering processes; others consider issues of adjacent knowledge areas and sub-areas that significantly contribute to systems development, operation, and maintenance. Case studies include aircraft, spacecrafts, and space systems development, post-analysis of data collected during operation of large systems etc. Important issues related to "bottlenecks" of Systems Engineering, such as complexity, reliability, and safety of different kinds of systems, creation, operation and maintenance of services, system-human communication, and management tasks done during system projects are addressed in the collection. This book is for people who are interested in the modern state of the Systems Engineering knowledge area and for systems engineers involved in different activities of the area. Some articles may be a valuable source for university lecturers and students; most of case studies can be directly used in Systems Engineering courses as illustrative materials

Optimization of C.I Engine Parameters Using Artificial Neural

Optimization of Compression Ignition Engines through advanced artificial neural network is the modern process in mechanization and best utilization of modern technology for better economic scenarios in coming generation. This project deals with the feasibility of using artificial neural networks in combination with genetic algorithms to optimize the diesel engine settings. The engine is operated by using diesel and sunflower oil blends and the output parameters are calculated theoretically with the standard mechanical formulae and those manual experimental calculated values are used for training several neural networks with different various hidden layer [ n x m ] matrix combinations. The output values given by these trained networks are compared with experimental values and out of which the trained error values are taken for all networks

Smart Bolometer: Toward Monolithic Bolometer with Smart Functions

The content of this chapter refers to uncooled resistive bolometers amd the challenge that consists in their integration into monolithic devices exhibiting smart functions. Uncooled resistive bolometers are the essential constitutive element of the majority of existing uncooled infrared imaging systems; they are referred to as microbolometer pixels in that type of application where matrixes of such elementary devices are used. uncooled bolometers represent more than 95% of the market of infrared imaging systems in 2010 (yole 2010) and infrared imaging systems are required for more and more applications