This paper introduces gamification as an innovative approach for police officers to develop the required competencies for upholding the ethics, principles, and values that the Ecuadorian institution and society demand of them. The main goal of game thinking is to motivate and engage learners by using game-like techniques.
OCTAVE PARALLEL PROFESSIONAL
Gamification and serious games have been involved in the rapid adaptation of professional training. The incorporation of game elements in non-game contexts is a subject of interest in various sectors, such as business, marketing, engineering, medicine, and military. Qt is used for creating the cross-stage application.
OCTAVE PARALLEL CODE
All the independent tools used for the Verilog code simulation are integrated onto a single platform. It is a combination of many dependencies that are used for synthesis, placement, layout viewing and routing in a fabrication process. There are multiple tools integrated with this tool to assure the simulation process. Qflow is a tool used in synthesizing a VLSI circuit from the Verilog source code. This paper deals with the idea to solve the above issue by creating a Graphical User Interface for the open source VLSI tool called QFlow. Hence, creating a user friendly interface will help many developers and users to work easily. There are efficient tools that already exist in open source in VLSI stream but are not used widely because of their command line user interface.
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There is a need for Free and open source tools in this stream so as to make them accessible to everyone.
There are many tools that are used for simulation in the domain of VLSI technology but none of them are easily accessible. The evaluated times indicate accelerations of 20% on average in recognition of crop lines, demonstrating a notable improvement in the performance of the parallel algorithm over the sequential one. The results obtained were statistically validated using the T-Student test in the R programming language. Matlab (Parallel Computing Toolbox) libraries were used for parallel and sequential implementation in a multicore CPU to contrast execution times in a set of 300 images. In the present work, the use of parallel programming is proposed for the implementation of an existing algorithm for the detection of curved and straight lines of crops, based on micro-ROI (Small regions of interest), with images captured in corn-fields during the early stages of growth. Specifically, in precision agriculture (PA) Image analysis for the automatic detection of crop lines is essential for the use of autonomous systems applied to different agricultural processes in real-time. The use of heterogeneous architectures in the systematization of processes is an alternative to obtain better processing times, optimizing computational resources, through the interaction between CPU (Central Processing Unit) and GPU (Graphics Processing Unit) architectures for parallel processing. With technological advancement, current computer applications generate large volumes of heterogeneous data (text, images, video, audio), causing a considerable increase in processing execution times. This widespread in-field validation allowed showing good performances not only in speedup but also in efficiency using Dragonfly. Finally, this tool has been tested on different computer systems from standard commodity environments to medium size clusters using a set of applications from different scientific fields. These functionalities allow obtaining good performance metrics such as: execution time, scalability and efficiency. To distribute the workload, it has a flexible system, where programmers can select the computational resources, create clusters and assign weights to balance properly tasks across the distributed environment (MATLAB and OCTAVE instances machines) with different computational power. Dragonfly can be used under multi-platform (Linux, Windows, Mac) and multi-environment configurations (e.g.
OCTAVE PARALLEL SOFTWARE
In this paper, we present Dragonfly, a free open-source software toolkit that allows creating a parallel collaboration environment between MATLAB and/or OCTAVE instances, allowing us to have a robust system, which is flexible, transparent and interoperable.
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