• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.315-333
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• 2021

Due to the Global Navigation Satellite System (GNSS) modernization, recently launched GNSS satellites transmit signals at various frequency bands such as L1, L2 and L5. Considering the Korean Positioning System (KPS) signal and other GNSS augmentation signals in the future, there is a high probability of applying more complex communication techniques to the new GNSS signals. For the reason, GNSS receivers based on flexible Software Defined Radio (SDR) concept needs to be developed to evaluate various experimental communication techniques by accessing each signal processing module in detail. This paper proposes a novel SDR-based A-GNSS receiver capable of processing multi-GNSS/RNSS signals at multi-frequency bands. Due to the modular structure, the proposed receiver has high flexibility and expandability. For real-time implementation, A-GNSS server software is designed to provide immediate delivery of satellite ephemeris data on demand. Due to the sampling bandwidth limitation of RF front-ends, multiple SDRs are considered to process the multi-GNSS/RNSS multi-frequency signals simultaneously. To avoid the overflow problem of sampled RF data, an efficient memory buffer management strategy was considered. To collect and process the multi-GNSS/RNSS multi-frequency signals in real-time, the proposed SDR A-GNSS receiver utilizes multiple threads implemented on a CPU and multiple NVIDIA CUDA GPGPUs for parallel processing. To evaluate the performance of the proposed SDR A-GNSS receiver, several experiments were performed with field collected data. By the experiments, it was shown that A-GNSS requirements can be satisfied sufficiently utilizing only milliseconds samples. The continuous signal tracking performance was also confirmed with the hundreds of milliseconds data for multi-GNSS/RNSS multi-frequency signals and with the ten-seconds data for multi-GNSS/RNSS single-frequency signals.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.13-22
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• 2000

To apply the queueing network theory in evaluating performances of flexible manufacturing systems, it is generally assumed that the processing times are distributed exponentially. However, in FMS, processing times are usually deterministic. In this study the performance measures of FMS are approximated under the assumption that processing times are usually deterministic. Multi-classes of parts and single server and multi-server stations are considered in the model. This study also that, in the numerical example, this approach yields better solutions than those obtained by the pure Linearizer algorithm, when the processing times are deterministic.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.111-118
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• 2001

In this paper, in order to implement the multi-layered perceptron neural network using pure digital logic circuit model, we propose the new logic neuron structure, the digital canonical multi-layered logic neural network structure, and the multi-stage multi-layered logic neural network structure for pattern recognition applications. And we show that the proposed approach provides an incremental additive learning algorithm, which is very simple and effective.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.454-456
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• 2015

스마트 폰이 보급화 되면서 구인관련 앱이 많이 생겨나고 있다. 하지만 전공을 특화시킨 어플리케이션은 보급화 되어 있지 않은 상태이다. 본 논문은 대학생 및 이직을 원하는 사람들에게 전공 관련 기업의 정보를 제공하고, 자신의 능력에 맞는 기업을 소개해주는 방식으로 설계 및 구현을 하였다. 이 앱을 통하여 대학생 및 이직을 생각하는 사람들에게 많은 정보와 기회를 제공할 것으로 예상된다.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1401-1408
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• 2011

This dissertation present a chip with Multi-Access Memory System(MAMS) and parallel processor for 16 Processing Elements of image processing purpose. MAMS is a kind of parallel access memory system and can simultaneously access to random pixel datas with eight types. It is possible to set a interval about pixel datas to access, too. The parallel processor built-in MAMS actually has been realized in 2003 but its performance fell short of a real time process for high-definition images. I designed a improved parallel processing system by means of addition and expansion of Memory Modules and Processing Elements of previous one. It is feasible to perform a Morphological Closing at the speed of 3 times of the previous one and 6 times of serial system.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1259-1276
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• 2017

As technologies related to sensor network are currently emerging and the use of GeoSensor is increasing along with the development of Internet of Things (IoT) technology, spatial query processing systems to efficiently process spatial sensor data are being actively studied. However, existing spatial query processing systems do not support a spatial-temporal data type and a spatial-temporal operator for processing spatialtemporal sensor data. Therefore, they are inadequate for processing spatial-temporal sensor data like GeoSensor. Accordingly, this paper developed a spatial-temporal query processing system, for efficient spatial-temporal query processing of spatial-temporal sensor data in a sensor network. Lastly, this paper verified the utility of System through a scenario, and proved that this system's performance is better than existing systems through performance assessment of performance time and memory usage.

• Journal of Aerospace System Engineering
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• v.13 no.5
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• pp.1-8
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• 2019

Recently, avionics has been migrating from a federated architecture to an integrated modular architecture based on a multi-core to reduce the number of systems, weight, power consumption, and platform redundancy. The volume of data which must bo provided to the pilot through the display device has increased, because an integrated single device performs multiple functions. For this reason, the volume of data processed by the graphic processor within a fixed operation period has increased. In this paper, we provide a multi-core-based rendering engine in to perform more graphics processing within a fixed operation period. We assume the proposed method uses a multi-core-based partitioning operating system using the AMP (Asymmetric Multi-Processing) architecture.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.951-956
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• 2007

This paper suggests a high-speed control method which is suitable for multi-joint robots using a real-time stand-alone controller for general-purpose. The fast processing controller consists of a PCI Interface Board and 2-axe PWM drivers. The PCI Interface Board consists of 32-channel PWM output ports, 32-channel Encoder Counters, 32-channel A/D Converters and 48-channel Digital I/O ports, and all the I/O data transmissions are completed within 1ms. And The 2-axe PWM driver can be redesigned easily in order to embed in each link. Experimental implementations show that the high-speed control method can be used for the real-time control which is essential to controlling of multi-body robots such as humanoid robots. Especially, it is efficient for realizing the model-based motion control in demand of much calculation time by the high I/O communication speed.

• Journal of Industrial Technology
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• v.30 no.A
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• pp.25-29
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• 2010

In this paper, we implement a multi-touch system using FIDR. The implementation consists of hardware manufacture and development of image processing system. In the hardware system, touch screen, infrared LED placements and infrared camera are made. The image processing procedure is to extract each pointer's coordinates from image data and includes binary-coding, noise-elimination, labeling and calculation of mass center. From the implementation, we are able to make a multi-touch system with considerably lower cost than the existing ones.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.439-449
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• 2023

This paper deals with a resource efficient artificial intelligence (AI) service architecture for multi-channel video streams. As an AI service, we consider the object detection model, which is the most representative for video applications. Since most object detection models are basically designed for a single channel video stream, the utilization of the additional resource for multi-channel video stream processing is inevitable. Therefore, we propose a resource efficient AI service framework, which can be associated with various AI service models. Our framework is designed based on the modular architecture, which consists of adaptive frame control (AFC) Manager, multiplexer (MUX), adaptive channel selector (ACS), and YOLO interface units. In order to run only a single YOLO process without regard to the number of channels, we propose a novel approach efficiently dealing with multi-channel input streams. Through the experiment, it is shown that the framework is capable of performing object detection service with minimum resource utilization even in the circumstance of multi-channel streams. In addition, each service can be guaranteed within a deadline.