• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.3
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• pp.35-43
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• 2003

The randomization of scalar multiplication in ECC is one of the fundamental concepts in defense methods against side-channel attacks. This paper proposes a countermeasure against simple and differential power analysis attacks through randomizing the transformed m-ary method based on a random m-ary receding algorithm. The proposed method requires an additional computational load compared to the standard m-ary method, yet the power consumption is independent of the secret key. Accordingly, since computational tracks using random window width can resist against SPA and DPA, the proposed countermeasure can improve the security for smart cards.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.1
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• pp.43-47
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• 2021

This paper investigates the network throughput of PLC (Power Line Communication) system in the in-building network. The OFDM (Orthogonal Frequency Division Multiplexing) modulation format and adaptive bit loading algorithm is used to minimize the effect of signal loss and noise on transmission performance in the power line channel characterized by frequency selective fading. The network throughput of the PLC system which consists of gateway and CPE（Customer Premise Equipment) PLC modem in the in-building network is measured by network performance measurement tool, iperf and analyzed according to the TCP (Transmission Control Protocol) window size.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.633-640
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• 2024

This study develops AI-based 3D body shape modeling technology that can be utilized in the healthcare sector, proposing a system that enables monitoring of users' body shape changes and health status. Utilizing data from Size Korea, the study developed a model to generate 3D body shape images from 2D images, and compared various models to select the one with the best performance. Ultimately, by proposing a system process through the developed technology, including personalized health management, exercise recommendations, and dietary suggestions, the study aims to contribute to disease prevention and health promotion.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6B
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• pp.325-333
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• 2007

An OS requires the device driver to control hardware IPs at application level. Development of a device driver requires specific acknowledge for target hardware and OS. In this paper, we present a system which generates a device driver together with an interface circuit. In the proposed system, an efficient device driver is generated by selecting a basic device driver skeleton, a function module code, and a header file table from the pre-constructed library and an interface circuit is constructed such that the generated device driver operates correctly. The proposed system is evaluated by generating a TFT-LCD device driver on the ARM922T core with 3.5 inch Samsung TFT-LCD in ARM-Linux environment. Experiment result shows that the writing time on the LCD is decreased by 1.12% and the compiled code size is increased by 0.17% compared to the manually generated one. The automatically generated device driver has no performance degradation in the latency of hardware control at the application program level. The system development time can be reduced using the proposed device driver generation system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.61-68
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• 2012

Recommender Systems have gained much popularity among researchers and is applied in a number of applications. The exponential growth of users and products poses some key challenges for recommender systems. Recommender Systems mostly suffer from scalability and accuracy. The accuracy of Recommender system is somehow inversely proportional to its scalability. In this paper we proposed a Context Aware Hybrid Recommender System using matrix reduction for Hybrid model and clustering technique for predication of item features. In our approach we used user item-feature rating, User Demographic information and context information i.e. specific time and day to improve scalability and accuracy. Our Algorithm produce better results because we reduce the dimension of items features matrix by using different reduction techniques and use user demographic information, construct context aware hybrid user model, cluster the similar user offline, find the nearest neighbors, predict the item features and recommend the Top N- items.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.879-883
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• 2006

본 연구는 현장에서 측정되는 수질데이터를 실시간 수집하여 데이터의 적절성을 모니터링하고 모형입력자료로써 신뢰성을 유지하도록 구성되는 시스템과 이를 2차원 수질 해석 모형인 CE-QUAL W2모형의 입력자료로 연계 활용함으로써 그 결과를 그래프 및 하천 변화 모의 동영상으로 표출하는 시스템을 개발하는데 그 목적이 있다. 수질 모형은 물 관련 모형가운데 특히 다량의 자료와 정확한 자료를 입력자료로 사용하며 그 결과 표출에 있어서도 전체적인 결과부터 세밀한 요소자료까지 결과자료가 필요하다. 본 연구에서 개발한 RTMMS(Real-time Turbidity Monitoring & Modeling System)는 현장 계측기로부터 수집되는 실시간 자료를 이용하여 데이터를 모니터링하고 CE-QUAL W2 모형을 이용하여 모델링을 수행한 후 결과를 그래프로 도출 할 수 있도록 하는 시스템이다. 특히 일반적인 어플리케이션의 GUI 환경에서 벗어나 일반 사용자들이 쉽게 프로그램을 사용할 수 있고 공간 활용도를 높이기 위하여 웹 형식의 GUI로 구성하였다. RTMMS는 기본 크기가 가로 800 픽셀, 세로 600 픽셀로 고정 사이즈이며, 주요 화면 구성으로는 좌측에 네 개의 항목이 있고 우측에는 실시간 모니터링 지점에 대한 유역도가 표시되어 사용자 편의환경을 제공하였다. 사용자는 해당 지점을 선택하여 주요 지점에 대한 정보를 분석할 수 있다. 또한 우측에는 선택된 지점에 대한 정보와 실시간 감시 내용을 조회할 수 있는 탭이 존재한다. 각각의 메뉴 항목은 주요지점의 모니터링 현황을 파악할 수 있는 기능, 수질모형의 입력자료로 변환하도록 하는 자료 동화 기능, CE-QUAL W2 모형을 수행하는 기능 및 결과자료를 분석하는 기능으로 구성되어 있으며, 각 기능을 선택하면 해당 화면으로 GUI가 전환된다. 따라서 다량의 측정자료의 신뢰성을 유지하고 이를 모형의 입력자료로 활용하는 일련의 과정을 시스템화하기 때문에 자료의 이상적 유지 관리가 이루어지며 복잡한 2차원 수질해석 모형을 수월하게 운영할 수 있는 시스템으로 개발하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.17-22
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• 2024

This paper introduces the implementation of a secondhand clothing trading system equipped with virtual fitting functionality based on deep learning. The proposed system provides users with the ability to visually try on secondhand clothing items online and assess their fit. To achieve this, it utilizes the Convolutional Neural Network (CNN) algorithm to create virtual representations of users considering their body shape and the design of the clothing. This enables buyers to pre-assess the fit of clothing items online before actually wearing them, thereby aiding in their purchase decisions. Additionally, sellers can present accurate clothing sizes and fits through the system, enhancing customer satisfaction. This paper delves into the CNN model's training process, system implementation, user feedback, and validates the effectiveness of the proposed system through experimental results.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.11-17
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• 2017

In this paper, an 8-direction switched beamforming antenna system at 28GHz frequency band is described for 5th generation wireless communication. This system is composed of an $8{\times}8$ Butler matrix and an 8-element patch array antenna. The antenna system switches beams in 8-direction in the wide range of ${\pm}40^{\circ}$. The antenna spacing is $0.65{\lambda}$ to achieve ${\pm}40^{\circ}$ steering range. Designed results show that the 8-direction beams are placed at ${\pm}6^{\circ}$, ${\pm}17^{\circ}$, ${\pm}28^{\circ}$, ${\pm}40^{\circ}$ offset from the center. Parasitic radiation effect from the large dimension Butler matrix need to be suppressed by employing a stripline structure.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.23-29
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• 2018

A stand-alone Photovoltaic (PV) system is one of the most important energy system for Mongolian nomadic herders. Basically, a stand-alone PV system uses two DC-DC converters. This makes the system costly, size bigger and difficult to move from one place to another place for the nomadic herders. A combined control algorithm for charging the battery using Stage of Charge (SOC) and Maximum Power Point Tracking (MPPT) is proposed in this paper. The batteries are charged by the three stage method; bulk, absorption and float charge. In the bulk stage used the MPPT function in this study. The performance of the proposed control algorithm is evaluated in both steady and changing weather conditions. The results are obtained using PSIM software. The results obtained in this paper are useful in designing a stand-alone PV system in the rural life like Mongolian nomadic herders.