• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.190-196
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• 2014

This paper proposes a mobile-optimized pedestrian detection method using Cascade of HOG(Histograms of Oriented Gradients) for ADAS(Advanced Driver Assistance System) on smartphones. In order to use the limited resource of mobile platforms efficiently, the method is implemented by the OpenCL(Open Computing Language) library, and its processing time is reduced in the following two aspects. Firstly, the method sets a program build option specifically and adjusts work group sizes as variety of kernels in the host code. Secondly, it utilizes local memory and a LUT(Look-Up Table) in the kernel code to accelerate the program. For performance evaluation, the developed algorithm is compared with the mobile CPU-based OpenCV(Open Computer Vision) for Android function. The experimental results show that the processing speed is 25% faster than the OpenCV hogcascade.

• Journal of Korea Game Society
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• v.14 no.4
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• pp.45-52
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• 2014

We cannot load the entire data for high-resolution terrain model to the GPU memory since its size is too big. Out-of-core approaches are commonly used to solve the problem. However, due to limited bandwidth of the secondary storage, it is difficult to render the terrain in real-time. A method that compresses the DEM data with wavelet transform on GPU, and renders the decoded data is suggested. However, it is inefficient since it has to sample the values from textures, convert them to vertices, and generate a mesh periodically. We propose a method to store the approximation coefficients of wavelet compression as vertex attributes and render the terrain by decoding the data on geometric shader. It can reduce the amount of transferring terrain texture since approximation coefficients are given as an attribute of the vertex. Also, it generate meshes without additional upload of terrain texture.

• 한국지구물리탐사학회:학술대회논문집
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• 2009.10a
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• pp.75-80
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• 2009

Despite its flexibility to complex geometry, three-dimensional (3D) electromagnetic(EM) modeling schemes using finite element method (FEM) have been faced to practical limitation due to the resulting large system of equations to be solved. An efficient 3D FEM modeling scheme has been developed, which can adopt either direct or iterative solver depending on the problems. The direct solver PARDISO can reduce the computing time remarkably by incorporating parallel computing on multi-core processor systems, which is appropriate for single frequency multi-source configurations. When limited memory, the iterative solver BiCGSTAB(1) can provide fast and stable convergence. Efficient 3D simulations can be performed by choosing an optimum solver depending on the computing environment and the problems to be solved. This modeling includes various types of controlled-sources and can be exploited as an efficient engine for 3D inversion.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.56-63
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• 2016

We consider a satellite mission scheduling problem, which is a promising problem in recent satellite industry. This problem has various considerations such as customer importance, due date, limited capacity of energy and memory, distance of the location of each mission, etc. Also we consider the objective of each satellite such as general purpose satellite, strategic mission and commercial satellite. And this problem can be modelled as a general knapsack problem, which is famous NP-hard problem, if the objective is defined as to maximize the total mission score performed. To solve this kind of problem, heuristic algorithm such as taboo and genetic algorithm are applied and their performance are acceptable in some extent. To propose more efficient algorithm than previous research, we applied a particle swarm optimization algorithm, which is the most promising method in optimization problem recently in this research. Owing to limitation of current study in obtaining real information and several assumptions, we generated 200 satellite missions with required information for each mission. Based on generated information, we compared the results by our approach algorithm with those of CPLEX. This comparison shows that our proposed approach give us almost accurate results as just less than 3% error rate, and computation time is just a little to be applied to real problem. Also this algorithm has enough scalability by innate characteristic of PSO. We also applied it to mission scheduling problem of various class of satellite. The results are quite reasonable enough to conclude that our proposed algorithm may work in satellite mission scheduling problem.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.8
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• pp.954-963
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• 2007

As RFID systems are applied to various fields and applications such as supply chain management, asset management, location based applications etc. the requirements becomes diverse. For example, Much higher performance, TCP/IP protocol stack are required in some applications. However, low end processors based systems such as 8051 processor can not meet such requirements due to their low processing capacity and limited size of memory. In this paper a UHF band RFID system which meets the EPC Class-1 Generation-2 specification with ARM920T-based processor is implemented and tested.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.430-435
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• 2018

In this paper, an improved decoding scheme for low-complexity parity-check(LCPC) code with small code length is proposed. The LCPC code is less complex than the turbo code or low density parity check(LDPC) code and requires less memory, making it suitable for communication between internet-of-things(IoT) devices. The IoT devices are required to have low complexity due to limited energy and have a low end-to-end delay time. In addition, since the packet length to be transmitted is small and the signal processing capability of the IoT terminal is small, the LCPC coding system should be as simple as possible. The LCPC code can correct all single errors and correct some of the two errors. In this paper, the proposed decoding scheme improves the bit error rate(BER) performance without increasing the complexity by correcting both errors using the soft value of the modulator output stage. As a result of the simulation using the proposed decoding scheme, the code gain of about 1.1 [dB] was obtained at the bit error rate of $10^{-5}$ compared with the existing decoding method.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.1-18
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• 2008

By using previous similar case plans, the case-based planning (CBP) systems can generate efficiently plans for new problems. However, most existing CBP systems show limited functionalities for case retrieval and case generalization. Moreover, they do not allow their users to participate in the process of plan generation. To support efficient memory use and case retrieval, the proposed case-based planning system, JCBP, groups the set of cases sharing the same goal in each domain into individual case bases and maintains indexes to these individual case bases. The system applies the heuristic knowledge automatically extracted from the problem model to the case adaptation phase. It provides a sort of case generalization through goal regression. Also JCBP can operate in an interactive mode to support a mixed-initiative planning. Since it considers and utilizes user's preference and knowledge for solving the given planning problems, it can generate solution plans satisfying more user's needs and reduce the complexity of plan generation.

• Journal of KIISE:Information Networking
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• v.33 no.2
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• pp.165-174
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• 2006

Data dissemination using either flooding or legacy ad-hoc routing protocol is not realistic approach in the wireless sensor networks, which are composed of sensor nodes with very weak computing power, small memory and limited battery. In this paper, we propose the ELF(Energy-efficient Localized Flooding) protocol. The ELF is energy-efficient data dissemination protocol for wireless sensor networks. In the ELF protocol, there are two data delivery phases between fixed source and mobile sink node. The first phase, before the tracking zone, sensing data are forwarded by unicasting. After that, within the tracking zone, sensing data are delivered by localized flooding. Namely, the ELF Properly combines advantages from both unicasting and flooding. According to evaluation results by simulation, the proposed ELF protocol maintains very high data delivery ratio with using a little energy. Also, the property of average delay is better than others. From our research results, the ELF is very effective data dissemination protocol for wireless sensor networks.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.9
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• pp.503-513
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• 2002

Since CC-NUMA architecture has to access remote memory, the interconnection network determines the performance of the CC-NUMA system. Bus which has been used as a popular interconnection network has many limits in a large-scale system because of the limited physical scalability and bandwidth. The dual ring interconnection network, composed of high-speed point-to-point links, is made to resolve the defects of the bus for the large-scale system. However, it also has a problem, in that the response latency is rapidly increased when many nodes are attached to the snooping based CC-NUMA system with the dual ring. In this paper, we propose a ring architecture with repeater nodes in order to overcome the problem of the dual ring on a snooping based CC-NUMA system, and design a repeater node adapted to this architecture. We will also analyze the effects of proposed architecture on the system performance and the response latency by using a probability-driven simulator.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.1
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• pp.35-45
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• 2007

The log data collected from mobile devices contains diverse meaningful and practical personal information. However, this information is usually ignored because of its limitation of memory capacity, computation power and analysis. We propose a novel method that detects landmarks of meaningful information for users by analyzing the log data in distributed modules to overcome the problems of mobile environment. The proposed method adopts Bayesian probabilistic approach to enhance the inference accuracy under the uncertain environments. The new cooperative modularization technique divides Bayesian network into modules to compute efficiently with limited resources. Experiments with artificial data and real data indicate that the result with artificial data is amount to about 84% precision rate and about 76% recall rate, and that including partial matching with real data is about 89% hitting rate.