• Journal of the Institute of Convergence Signal Processing
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• v.16 no.4
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• pp.129-133
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• 2015

In this paper, we propose a fast motion estimation algorithm which is important in the performance of video encoding. Conventional fast motion estimation algorithms have serious problems of low prediction quality in some frames and still much computation. In the paper, we propose an algorithm that reduces unnecessary computations only, while keeping prediction quality almost similar to that of the full search. The proposed algorithm uses distribution of probability of motion vectors, divides search range into several groups according to its importance, and applies adaptive block matching criteria for each group of search range. The proposed algorithm takes only 3~5% in computational amount and has decreased prediction quality about 0~0.01dB compared with the fast full search algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.543-545
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• 2019

4차산업혁명 시대가 도래함에 따라서 기존의 단순 지식 습득 위주의 교육에서 코딩을 통한 창의적 사고와 문제 해결능력을 키워주는 교육이 주목받기 시작하였다. 이러한 시대에 흐름에 발맞추어 교육부는 2019년부터 모든 초중고등학교에서 소프트웨어 교육을 정규 교육과정에 포함 시킨다고 밝혔다. 따라서 본 논문에서는 이미 수년 전부터 소프트웨어 중점 교육을 실시하고 있던 해외의 사례를 토대로 피지컬 컴퓨팅(Physical Computing) 기반의 소프트웨어 교육을 위한 초음파센서 블록을 개발하였다. 초음파센서블록은 학생들에게 익숙한 레고 안에 초음파센서와 아두이노를 내장하여 블록코딩을 활용한 콘텐츠 설계가 가능하다. 초음파센서블록을 입력장치로 사용하여 사전 연구를 통해 개발된 스위치, LED, 스피커 블록 등과 연동하여 학생들은 상상한 작품들을 블록코딩을 통해 실제로 구현해 볼 수 있다. 이 과정을 통해 학생들은 재미와 성취감을 느끼고 자발적인 학습 참여가 이루어질 것으로 예상된다.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.463-468
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• 2021

Single image super-resolution (SISR) is an image processing technique, and its main target is to reconstruct the high-quality or high-resolution (HR) image from the low-quality or low-resolution (LR) image. Currently, deep learning-based convolutional neural network (CNN) image super-resolution approaches achieved remarkable improvement over the previous approaches. Furthermore, earlier approaches used hand designed filter to upscale the LR image into HR image. The design architecture of such approaches is easy, but it introduces the extra unwanted pixels in the reconstructed image. To resolve these issues, we propose novel deep learning-based approach known as Lightweight deep CNN-based approach for Single Image Super-Resolution (LDCSIR). In this paper, we propose a new architecture which is inspired by ResNet with Inception blocks, which significantly drop the computational cost of the model and increase the processing time for reconstructing the HR image. Compared with the other state of the art methods, LDCSIR achieves better performance in terms of quantitively (PSNR/SSIM) and qualitatively.

• Animal Bioscience
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• v.34 no.6
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• pp.1061-1069
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• 2021

Objective: This study was conducted to evaluate the effects of feed processing and particle size on growth performance, nutrient digestibility, carcass characteristics, and gastric health in growing-finishing pigs. Methods: A total of 360 growing pigs (22.64±0.014 kg initial body weight [BW]) were allocated to 1 of 6 treatments with 6 replicates by BW and sex, and 10 pigs were housed in one pen in a randomized complete block design. The BW and feed intake were recorded to calculate growth performance. For the digestibility trial, a total of 24 barrows with an initial BW of 33.65±0.372 kg were split into 6 treatments with a completely randomized design. Dietary treatments were designed by a 2×3 factorial arrangement of treatments based on two main factors, particle size (600, 750, 900 ㎛) and feed form (mash and pellet) of diet. Experimental diets were formulated to contain the requirements of the NRC (2012). Results: The BW and average daily gain were not changed by dietary treatments, and the feed intake of finishing pigs (wks 6 to 12) was increased when the pigs were fed a mash diet (p<0.05). For the overall period, the feed efficiency of pigs was improved with the pellet diet (p<0.01) and reduced particle size (p<0.05). The pellet diet had effects on increasing crude fat digestibility (p<0.01) relative to a mash diet, but there was no considerable change in dry matter and crude protein digestibilities by dietary treatments. In the evaluation of gastric health, a trend for an increased incidence of keratinization in the esophageal region was observed as particle size decreased (p = 0.07). Conclusion: Feed efficiency could be improved by pellet diet and reduced particle size. Nutrient digestibility, carcass characteristics, and gastric health were not affected by feed form, and particle size ranged from 600 to 900 ㎛.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.15-21
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• 2010

In the recent years, various researches about the signal processing have been presented to improve the performance of power analysis. Among these signal processing techniques, the research about the signal compression is not enough than a signal alignment and a noise reduction; even though that can reduce considerably the computation time for the power analysis. But, the existing compression method can sometimes reduce the performance of the power analysis because those are the unsophisticated method not considering the characteristic of the signal. In this paper, we propose the new PCA (principal component analysis)-based signal compression method, which can block the loss of the meaningful factor of the original signal as much as possible, considering the characteristic of the signal. Also, we prove the performance of our method by carrying out the experiment.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.3
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• pp.110-115
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• 2021

With the era of the 4th Industrial Revolution, education on artificial intelligence is one of the important topics. However, since existing education is aimed at knowledge, it is not suitable for developing the active problem-solving ability and AI utilization ability required by artificial intelligence education. To solve this problem, we proposes PBL-based education method in which learners learn in the process of solving the presented problem. The problem presented to the learner is a completed project. This project consists of three types: a classification model, the training data of the classification model, and the block code to be executed according to the classified result. The project works, but each component is designed to perform a low level of operation. In order to solve this problem, the learners can expect to improve their computational thinking skills by finding problems in the project through testing, finding solutions through discussion, and improving to a higher level of operation.

• Journal of the Korean Geotechnical Society
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• v.23 no.1
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• pp.51-65
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• 2007

The purpose of this study is the development and application of a high resolution ultrasonic wave imaging system to detect discontinuity plane in lab-scale rock models. This technique is based on received time series which capture the multiple reflections at interface. This study includes the fundamental aspects of ultrasonic wave propagation in rock mass, the selection of the optimal ultrasonic wave transducer, data gathering, a signal processing, imaging methods, and experiments. Experiments are carried out by the horizontal movement and rotation devices. Experimental studies show the discontinuity is well detected by the horizontal movement and rotation devices under water. Furthermore, the discontinuity and the cavity on the plaster block are identified by the rotation device. This study suggests that the new method may be an economical and effective tool for the detection of the discontinuity on rock mass.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.163-166
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• 2021

ICISC'20에서 발표된 경량 블록암호 PIPO는 비트 슬라이스 기법 적용으로 효율적인 구현이 되었으며, 부채널 내성을 지니기에 안전하지 않은 환경에서도 안정적으로 사용 가능한 경량 블록암호이다. 본 논문에서는 ARM 프로세서를 대상으로 PIPO의 병렬 최적 구현을 제안한다. 제안하는 구현물은 8평문, 16평문의 병렬 암호화가 가능하다. 구현에는 최적의 명령어 활용, 레지스터 내부 정렬, 로테이션 연산 최적화 기법을 사용하였다. 구현은 A10x fusion 프로세서를 대상으로 한다. 대상 프로세서상에서, 기존 레퍼런스 PIPO 코드는 64/128, 64/256 규격에서 각각 34.6 cpb, 44.7 cpb의 성능을 가지나, 제안하는 기법은 8평문 64/128, 64/256 규격에서 각각 12.0 cpb, 15.6 cpb, 16평문 64/128, 64/256 규격에서 각각 6.3 cpb, 8.1 cpb의 성능을 보여준다. 이는 기존 대비 각 규격별로 8평문 병렬 구현물은 약 65.3%, 66.4%, 16평문 병렬 구현물은 약 81.8%, 82.1% 더 좋은 성능을 보인다.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.122-129
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• 2024

Though programming education has been stressed recently, the elementary, middle, and high school students are having trouble in programming education. Most programming environments for them are based on block coding, which hinders them from moving to text coding. The traditional PC environment has also troubles such as maintenance problems. In this situation, mobile applications can be considered as alternative programming environments. This paper addresses the design and implementation of coding applications for mobile devices. As a prototype, a Scheme interpreter mobile app is proposed, where Scheme is used for programming courses at MIT since it supports multi-paradigm programming. The implementation has the advantage of not consuming the network bandwidth since it is designed as a standalone application. According to the benchmark result, the execution time on Android devices, relative to that on a desktop, was 131% for the Derivative and 157% for the Tak. Further, the maximum execution times for the benchmark programs on the Android device were 19.8ms for the Derivative and 131.15ms for the Tak benchmark. This confirms that when selecting an Android device for programming education purposes, there are no significant constraints for training.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.102-110
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• 2024

Blockchain records all transactions issued by users, which are then replicated, stored, and shared by participants of the blockchain network. Therefore, the capacity of the ledger stored by participants continues to increase as the blockchain network operates. In order to address this issue, research is being conducted on methods that enhance storage efficiency while ensuring that valid values are stored in the ledger even in the presence of device failures or malicious participants. One direction of research is applying techniques such as Reed-Solomon encoding to the storage of blockchain ledgers. In this paper, we apply Reed-Solomon encoding to the key-value store used for ledger storage in an open-source blockchain, and measure the storage efficiency and increasing computational overhead. Experimental results confirm that storage efficiency increased by 86% while the increase in CPU operations required for encoding was only about 2.7%.