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A Study of Unmanned Aerial Vehicle Path Planning using Reinforcement Learning
Kim, Cheong Ghil The Korean Society Of SemiconductorDisplay Technol 2018 반도체디스플레이기술학회지 Vol.17 No.1
Currently drone industry has become one of the fast growing markets and the technology for unmanned aerial vehicles are expected to continue to develop at a rapid rate. Especially small unmanned aerial vehicle systems have been designed and utilized for the various field with their own specific purposes. In these fields the path planning problem to find the shortest path between two oriented points is important. In this paper we introduce a path planning strategy for an autonomous flight of unmanned aerial vehicles through reinforcement learning with self-positioning technique. We perform Q-learning algorithm, a kind of reinforcement learning algorithm. At the same time, multi sensors of acceleraion sensor, gyro sensor, and magnetic are used to estimate the position. For the functional evaluation, the proposed method was simulated with virtual UAV environment and visualized the results. The flight history was based on a PX4 based drones system equipped with a smartphone.
An Implementation and Performance Evaluation of Fast Web Crawler with Python
Kim, Cheong Ghil The Korean Society Of SemiconductorDisplay Technol 2019 반도체디스플레이기술학회지 Vol.18 No.3
The Internet has been expanded constantly and greatly such that we are having vast number of web pages with dynamic changes. Especially, the fast development of wireless communication technology and the wide spread of various smart devices enable information being created at speed and changed anywhere, anytime. In this situation, web crawling, also known as web scraping, which is an organized, automated computer system for systematically navigating web pages residing on the web and for automatically searching and indexing information, has been inevitably used broadly in many fields today. This paper aims to implement a prototype web crawler with Python and to improve the execution speed using threads on multicore CPU. The results of the implementation confirmed the operation with crawling reference web sites and the performance improvement by evaluating the execution speed on the different thread configurations on multicore CPU.
( Cheong Ghil Kim ),( Yong Soo Choi ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.2
Stereo vision has become an important technical issue in the field of 3D imaging, machine vision, robotics, image analysis, and so on. The depth map extraction from stereo video is a key technology of stereoscopic 3D video requiring stereo correspondence algorithms. This is the matching process of the similarity measure for each disparity value, followed by an aggregation and optimization step. Since it requires a lot of computational power, there are significant speed-performance advantages when exploiting parallel processing available on processors. In this situation, multi-core CPU may allow many parallel programming technologies to be realized in users computing devices. This paper proposes parallel implementations for calculating disparity map using a shared memory programming and exploiting the streaming SIMD extension technology. By doing so, we can take advantage both of the hardware and software features of multi-core processor. For the performance evaluation, we implemented a parallel SAD algorithm with OpenMP and SSE2. Their processing speeds are compared with non parallel version on stereoscopic streaming video. The experimental results show that both technologies have a significant effect on the performance and achieve great improvements on processing speed.
A Study of the Performance Prediction Models of Mobile Graphics Processing Units
Kim, Cheong Ghil The Korean Society Of SemiconductorDisplay Technol 2019 반도체디스플레이기술학회지 Vol.18 No.1
Currently mobile services are on the verge of full commercialization ahead of 5G mobile communication (5G). The first goal could be to preempt the 5G market through realistic media services utilizing VR (Virtual Reality) and AR (Augmented Reality) technologies that users can most easily experience. Basically this movement is based on the advanced development of smart devices and high quality graphics processing computing power of mobile application processors. Accordingly, the importance of mobile GPUs is emerging and the most concern issue becomes a model for predicting the power and performance for smooth operation of high quality mobile contents. In many cases, the performance of mobile GPUs has been introduced in terms of power consumption of mobile GPUs using dynamic voltage and frequency scaling and throttling functions for power consumption and heat management. This paper introduces several studies of mobile GPU performance prediction model with user-friendly methods not like conventional power centric performance prediction models.
Parallel JPEG Color Conversion on Multi-Core Processor
Cheong Ghil Kim,Yong-Ho Seo 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.2
Multi-core processors have become the dominant market trend because they provide a great opportunity in increasing processing performance by exploiting various parallelisms. In JPEG (Joint Photographic Experts Group) compression, color space conversion is one of the major kernels known as a computationally expensive module. This paper presents a fast solution for color space conversion with multi-core parallel computation. For this purpose, we utilize Threading Building Blocks (TBB), a runtime library based on C++, and OpenMP (Open Multi-processing), a shared programming language. A RGB image is transformed into a luminance-chrominance color space such as YCbCr. The implementation results show that parallel implementations achieve greater performance improvement regarding processing speed compared with the serial implementation.