• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.63-66
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• 2001

본 논문에서는 TI사의 TMS320C6201 DSP를 이용하여 H.263 동영상 부호화기를 실시간 구현하고자 한다. 구현한 부호화기는 QCIF 형식의 영상을 사용하여 ITU-T H.263 권고안의 기본 모드를 따라 주로 C 언어와 intrinsics를 사용하여 구현하였다. 특히, 속도 향상을 위해서 고속 메모리의 사용을 극대화하는데 중점을 두었고, 연산량이 많은 모듈에 대한 최적화와 데이터의 병렬 처리 및 DMA (Direct Memory Access) 전송 등을 고려하여 구현하였다.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.493-496
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• 2000

본 논문에서는 TMS320C6201 DSP (Digial Signal Processor)를 이용하여 실시간 영상 부호화기를 구현하였다. 기본적인 영상 압축 방법으로는 baseline-JPEG을 사용하였고 이에 움직임 검출 알고리즘을 부가하여 영상의 시간적인 중복성을 제거하였다. 특히 저속 메모리와 고속 메모리의 효율적인 분배 사용, 계산량이 많은 모듈의 최적화, 데이터의 병렬 연산과 DMA (Direct Memory Access)를 이용한 데이터 전송 등의 방법을 통하여 실시간 영상 부호화기의 고속 영상 처리에 중점을 두었다.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.403-403
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• 2006

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.149-153
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• 1995

본 논문에서는 TI(Texas Instrument)사의 범용 디지탈 프로세서인 TMS320C30을 이용하여 MPEG-2 계층2(Layer II) 오디오 부호화 알고리듬의 실시간 처리가 가능한 시스템을 구현하였다. 구현한 시스템은 1 채널의 오디오 신호를 처리하기 위한 Slave 보드 5개와 채널 멀티플렉싱과 부가 처리를 위한 Master 보드 1개로 이루어져 있다. MPEG-2 알고리듬의 각 단계별 소요시간을 계산한 후, 이를 바탕으로 각 프로세서에 할당하는 작업량을 조정하여 실시간 처리에 적합한 시스템을 구현하였다.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2784-2786
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• 2000

Mobile robots include control modules for autonomous obstacle avoidance and navigation. They are range modules to detect and avoid obstacles. motor control modules to operate two wheels. and encoder modules for localization. There is needed an appropriate controller for each modules. In this paper. a control system. including 18 channels for Sonar sensors. 4 channels for PWM modules. and 4 channels for encoder modules. is proposed using TMS320C32 DSP adopted with CAN. The board communicates with other modules by CAN. so that mobile robots can perform several tasks in real time. So we can realize on autonomous mobile robot with basic functions such as obstacle avoidance by using the developed controller. Especially. this controller has 100 msec scan time for 16 sonar sensors and can detect closer objects comparing with standard sonar sensors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4909-4926
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• 2020

Cyberattacks penetrate the server and perform various malicious acts such as stealing confidential information, destroying systems, and exposing personal information. To achieve this, attackers perform various malicious actions by infecting endpoints and accessing the internal network. However, the current countermeasures are only anti-viruses that operate in a signature or pattern manner, allowing initial unknown attacks. Endpoint Detection and Response (EDR) technology is focused on providing visibility, and strong countermeasures are lacking. If you fail to respond to the initial attack, it is difficult to respond additionally because malicious behavior like Advanced Persistent Threat (APT) attack does not occur immediately, but occurs over a long period of time. In this paper, we propose a technique that detects an unknown attack using an event log without prior knowledge, although the initial response failed with anti-virus. The proposed technology uses a combination of AutoEncoder and 1D CNN (1-Dimention Convolutional Neural Network) based on semi-supervised learning. The experiment trained a dataset collected over a month in a real-world commercial endpoint environment, and tested the data collected over the next month. As a result of the experiment, 37 unknown attacks were detected in the event log collected for one month in the actual commercial endpoint environment, and 26 of them were verified as malicious through VirusTotal (VT). In the future, it is expected that the proposed model will be applied to EDR technology to form a secure endpoint environment and reduce time and labor costs to effectively detect unknown attacks.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.827-830
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• 2000

3GPP and ETSI adopted AMR(Adaptive Multi-Rate) as a standard for next generation IMT-2000 service. In this paper, we analyzed algorithm about AMR and optimized ANSI C source on the C complier and assembly language of Texas Instrument . The implemented AMR speech codec requires 28.2MIPS of complexity for encoder and 5.5MIPS for decoder. we performed real-time implementation of AMR speech codec using 82% of TMS320C5402 with 40 MIPS specification. We give proof that the output speech of the implemented speech codec on DSP board is identical with result of C source program simulation. Also the reconstructed speech is verified in the real-time environment consisted of microphone and speaker.

• The Journal of the Acoustical Society of Korea
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• v.16 no.3E
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• pp.56-61
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• 1997

In this paper, we describe a real-time implementation of a multi-channel auido codec system that is based on the MPEG-1 audio algorithm. The major feature of this system is that it has a flexible multi-DSP system that can be adapted for various applications with using up to four TMS320C40 DSPs. The purpose of this paper is to present the problems of the system and is to describe the optimized methods to solve the problems in the view of hardware and software. Our audio codec is composed of an encoder an a decoder system and the bit rate of bitstream is up to 384 kbps. Fast input/output interfaces, DSP overloads, and inter-DSP communications methods with high speed are considered in multi-DSP H/W. Also, to run real-time in S/W, optimizing methods of algorithm are considered. After implementation of system, the subjective assessment method, and 'triple stimulus/hidden reference/double blind' that recommended by ITU-R TG10/3 is adopted for the quality of our system. All test items except one are awarded difference grades(diffgrade) better than 1-. Form the results, multi-channel audio system can be used for HDTV service.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.868-874
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• 2007

A real-time frame-layer rate control algorithm with a token bucket traffic shaper is proposed for minimizing video duality variation. The proposed rate control method uses a non-iterative optimization method for low computational complexity, and performs bit allocation at the frame level to minimize variation in distortion between frames. In order to reduce the quality fluctuation, we use a sliding window scheme which does not require the pre-analysis process. Therefore, the proposed algorithm does not produce the delay from encoding, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better PSNR performance than the existing rate control method.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.