• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1091-1102
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• 2014

The power analysis attack is a cryptanalytic technique to retrieve an user's secret key using the side-channel power leakage occurred during the execution of cryptographic algorithm embedded on a physical device. Especially, many power analysis attacks have targeted on an exponentiation algorithm which is composed of hundreds of squarings and multiplications and adopted in public key cryptosystem such as RSA. Recently, a new correlation power attack, which is tried when two modular multiplications have a same input, is proposed in order to recover secret key. In this paper, after reviewing the principle of side-channel attack based on input collisions in modular multiplications, we analyze the vulnerability of some exponentiation algorithms having regularity property. Furthermore, we present an improved exponentiation countermeasure to resist against the input collision-based CPA(Correlation Power Analysis) attack and existing side channel attacks and compare its security with other countermeasures.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.3
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• pp.477-489
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• 2014

Based on some flaws occurred for implementing a public key cryptosystem in the embedded security device, many side-channel attacks to extract the secret private key have been tried. In spite of the fact that the cryptographic exponentiation is basically composed of a sequence of multiplications and squarings, a new Square Always exponentiation algorithm was recently presented as a countermeasure against side-channel attacks based on trading multiplications for squarings. In this paper, we propose Known Power Collision Analysis and modified Doubling attacks to break the Right-to-Left Square Always exponentiation algorithm which is known resistant to the existing side-channel attacks. And we also present a Collision-based Combined Attack which is a combinational method of fault attack and power collision analysis. Furthermore, we verify that the Square Always algorithm is vulnerable to the proposed side-channel attacks using computer simulation.

• Journal of KIISE
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• v.43 no.7
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• pp.781-785
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• 2016

Learning from human behaviors in the real world is essential for human-aware intelligent systems such as smart assistants and autonomous robots. Most of research focuses on correlations between sensory patterns and a label for each activity. However, human activity is a combination of several event contexts and is a narrative story in and of itself. We propose a novel approach of human activity prediction based on event cognition. Egocentric multi-sensor data are collected from an individual's daily life by using a wearable device and smartphone. Event contexts about location, scene and activities are then recognized, and finally the users" daily activities are predicted from a decision rule based on the event contexts. The proposed method has been evaluated on a wearable sensor data collected from the real world over 2 weeks by 2 people. Experimental results showed improved recognition accuracies when using the proposed method comparing to results directly using sensory features.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.169-171
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• 2012

일반적인 경로 생성 기법에서는 거리가 가장 짧은 최단경로 및 시간이 적게 소요되는 빠른 경로와 같이 사용자의 이동 성향을 고려하지 않고 경로를 생성하였다. 하지만 사용자들은 시간, 거리, 도로 혼잡도와 같은 속성들에 의해 선호하는 경로가 있기 때문에 사용자의 이동 성향에 맞는 경로를 생성하는 기법들이 필요하다. 기존의 기법들은 이동 성향을 고려하여 경로를 생성하기 위해서는 사용자의 이동 성향 정보를 추가적으로 입력하여야 한다. 하지만 네비게이션 및 모바일 장치의 불편한 인터페이스 특성상 이러한 정보 입력은 거의 하지 않고 출발지와 목적지만을 입력하여 경로를 추천 받는 경향이 있다. 따라서 본 논문에서는 추가적인 이동 성향에 대한 정보 입력 없이 과거 궤적 데이터를 통해 사용자의 이동 성향을 암시적으로 추출하고 이동 성향에 맞는 경로를 생성하는 기법을 제안한다. 성능평가를 통해 최소 시간 경로나 최단 거리 경로와 비교하여 제안하는 기법이 사용자의 이동 성향을 고려한 경로가 생성됨을 입증한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1469-1476
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• 2022

Recently, many researches have been conducted to estimate blood pressure using ECG(Electrocardiogram) and PPG(Photoplentysmography) signals. In this paper, we designed and implemented a mobile system to monitor blood pressure in real time by using 1-D convolutional neural networks. The proposed model consists of deep 11 layers which can learn to extract various features of ECG and PPG signals. The simulation results show that the more the number of convolutional kernels the learned neural network has, the more detailed characteristics of ECG and PPG signals resulted in better performance with reduced mean square error compared to linear regression model. With receiving measurement signals from wearable ECG and PPG sensor devices attached to the body, the developed system receives measurement data transmitted through Bluetooth communication from the devices, estimates systolic and diastolic blood pressure values using a learned model and displays its graph in real time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.325-333
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• 2006

Recently, in the case of observing the global environment, satellite remote sensing technology has been important. It's because satellite remote sensing is valuable for assessing relatively large areas. But now, small scale remote sensing techniques are needed which can be applicable to the detail investigation of plant tree areas which afforest land after the large scale construction of roads, dams and airports. In this study, we tried to develop and propose a lower altitude sensing technique which can be used in ground remote sensing by using a CCD camera. As a result of this investigation the following can be concluded: We recognized the transference characteristics of filters which were used in comparative tests about the four ground remote sensing devices. We also found that the near-IR camera could be used for an imaging spectral radiometer in the extraction of the vegetation index. Furthermore, we found that the vegetation index has varied hour by hour during the day of the experiment. Finally, we brought about an increase phase of the NDVI in a forest fire, which caused considerable damage, by developing new ground remote sensing technology.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.265-271
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• 2023

Recently, location information services are gradually expanding due to the development of information and communication technology. RSSI is widely used to extract indoor and outdoor locations. The indoor and outdoor location estimation methods using RSSI are less accurate due to the influence of radio wave paths, interference, and surrounding wireless devices. In order to improve this problem, a distance estimation method that takes into account the wireless propagation environment is necessary. Therefore, in this study, we propose a distance estimation algorithm that takes into account the radio wave environment. The proposed method estimates the distance by learning RSSI input and output considering the RBF neural network and the propagation environment. To evaluate the performance of the proposed method, the performance of estimating the location of the receiver within a range of up to 55[m] using a BLE beacon transmitter and receiver was compared with the average filter and Kalman filter. As a result, the distance estimation accuracy of the proposed method was 6.7 times higher than that of the average filter and Kalman filter. As shown in the results of this performance evaluation, if the method of this study is applied to location services, more accurate location estimation will be possible.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.31-36
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• 2024

Recently, mobile apps that utilize AI technologies are increasing. In the personal mobile environment, performance degradation may occur during the training phase of large AI workload due to limitations in memory capacity. In this paper, we extract memory reference traces of AI workloads and analyze their characteristics. From this analysis, we observe that AI workloads can cause frequent storage access due to weak temporal locality and irregular popularity bias during memory write operations, which can degrade the performance of mobile devices. Based on this observation, we discuss ways to efficiently manage memory write operations of AI workloads using persistent memory-based swap devices. Through simulation experiments, we show that the system architecture proposed in this paper can improve the I/O time of mobile systems by more than 80%.

• Applied Biological Chemistry
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• v.39 no.5
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• pp.368-373
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• 1996

Korean general medicinal herbs-sasam, gilkyung, jakyak, danggwi, hwangki, and chunkung-were added In the normal brewing procedure as a raw material or in the distilling procedure as a packing material. The distillates from the former procedure and those from the latter procedure were compared in quality and distillation properties. As distillation proceeded, pH of the medicinal herb wine distillate and the control(not added herbs) distillates were decreased, whereas that of the herb packing distillate was increased slowely of $0.05{\sim}0.97$ during $1{\sim}4$ fractions and decreased remarkably of $0.92{\sim}0.98$ afterward. Average pH was the highest of 5.70 in jakyak and lowest of 4.37 In gilkyung. Absorbances of the herb Packing distillate were decreased rapidly of $0.60{\sim}1.59$ in the $1{\sim}4$ fractions but slowely of $0.19{\sim}0.54$ in the next fractions. During distillation both fractional alcohol concentration of the distillates and distillation rate were decreased. Their values were decreased more slowly than the control. Distillation rates of medicinal herb wine distillate were varied by medicinal herb varieties and alcohol concentration of fermented wine. Danggwi and control showed the highest average distillation rate as $0.12\;m{\ell}/sec$ and gilkyung the lowest value as $0.073\;m{\ell}/sec$. Maximum concentration of index component, paeoniflorin of jakyak was observed as 293 mg% in the 5th fraction of herb packing distillate and decrusin of danggwi as 3514 mg% In the 1st fraction of herb packing distillate. The extraction rate was 41.3% for paeoniflorin and 20.5% for decrusin. From sensory evaluation, the highest overall Qualify was observed in the medicinal herb wine distillate of hwangki added wine, the next in those of danggwi and jakyak added wine.

• Journal of Biosystems Engineering
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• v.21 no.4
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• pp.414-421
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• 1996

한국과 일본의 경우 건표고를 외관의 품질상태 에 따라 12등급에서 16등급으로 구분하고 있다. 그리고 등급판정 작업은 임의로 추출한 샘플을 대상으로 전문 감정가에 의해 수작업으로 수행되고 있다. 건표고의 품질을 결정짓는 외관의 품질인자들은 갓과 내피에 고루 분포하고 있다. 본 논문에서는 컴퓨터 영상처리 시스템에 의거하여 개발한 건표고 자동 등급판정 및 선별 시작시스템의 구조와 기능 그리고 성능에 대하여 설명하였다. 개발한 시작시스템은 표고의 이송과 취급자동화를 위한 진동이송기, 반전장치, 컨베이어 이송장치와 두 세트의 컴퓨터 영상처리 시스템, 그리고 시스템 통괄제어를 위한 IBM PC AT호환 컴퓨터, 디지털 입출력 보드, 전공압실린더 구동제어를 위한 PLC등으로 구성하였다. 등급판정의 효율성 및 실시간 작업시스템을 고려하여 건표고의 등급판정은 두 세트의 컴퓨터 영상처리 시스템을 이용하여 이송되는 건표고의 갓 또는 내피 중 어디가 위를 향하는 지에 따라 두 단계에 걸쳐 독립적으로 판정을 수행하도록 하였다. 첫 번째 영상처리부에서는 갓표면 영상으로부터 4등급의 고품질 표고를 분류하며 두 번째 영상처리부에서는 내피표면 영상으로부터 중간 및 저품질 표고를 8개의 등급으로 분류한다. 실시간 영상정보처리를 목적으로 기존에 개발한 신경회로망을 이용한 등급판정 알고리즘을 시작시스템에 적용하였다. 개발한 시작기는 88% 이상의 등급판정 정확도를 보여 주었으며, 전공압시스템의 구동제약으로 인하여 표고 1개당 약0.7초의 선별시간이 소요되었다. 일조 선별라인의 경우 본 연구에서 제안한 시작기의 선별능력은 표고가 일차 처리부로 갓이 위로 올라와 있는 상태로 계속 공급된다면 시간당 대략 5,000여 개의 표고를 처리할 수 있을 것으로 기대된다.보강하여 가능하면 B-Pillar의 Middle이 Bending type collapse을 방지하여 Pelvis와 Door가 먼저 접촉하는 방법 등이 적용가능하다. 제작하기 이전에 설계된 부품에 대한 스프링 상수 및 내구특성을 체계적으로 규명하여 제품 시험의 횟수를 줄이고, 보다 정밀한 제품을 제작할 수 있도록 하기 위한 것이다.세포수는 초기 배반포기배에서 팽윤 배반포기배로 진행됨에 따라 두배에서 세배 정도 증가되었음을 알 수 있었다. 또한, differential labelling과 bisbenzimide기법에서 얻어진 각각의 총세포수를 비교하였을 때 총세포수는 발달의 진행 정도에 따라 증가되며 그와 동시에 동일한 군 간의 세포수도 거의 유사함을 알 수 있었다. 따라서, ICM과 TE를 differential labelling하는 기법은 수정란의 quality를 평가하는데 매우 유용한 기법으로서 착상전 embryo 발달을 연구하는데 효과적으로 이용될 수 있다는 것을 시사한다. 고도의 유의차를 나타낸 반면 비수구, 초생수로구 및 Bromegrass 목초구 간에는 아무런 유의차가 인정되지 않았다. 7. 농지보전 처리구인 배수구와 초생수로구는 비처리구에 비해 낮은 침두 유출량과 낮은 토양유실량을 나타내었다.구보다 14% 절감되는 것으로 나타났다.작용하는 것으로 사료된다.된다.정량 분석한 결과이다. 시편의 조성은 33.6 at% U, 66.4 at% O의 결과를 얻었다. 산화물 핵연료의 표면 관찰 및 정량 분석 시험시 시편 표면을 전도성 물질로 증착시키지 않고, Silver Paint 에 시편을 접착하는 방법으로도 만족한 시험 결과를 얻을 수 있었다.째, 회복기 중에 일어나는 입자들의 유입은 자기폭풍의 지속시간을 연장시키는 경향을 보이며 큰