• 정보보호학회논문지
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• 제23권4호
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• pp.655-666
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• 2013

저장장치의 용량이 점차 대형화됨에 따라 대부분의 사용자들은 데이터의 저장 및 관리의 편의를 위하여 저장장치를 논리적으로 여러 개의 파티션으로 나누어 사용한다. 따라서 인위적인 파티션 은닉이나 파티션 손상 등으로부터 안정적으로 파티션을 복구해내는 것은 디지털 포렌식 관점에서 매우 중요한 문제이다. 본 논문은 파티션이 은닉되어 있거나 파티션 영역의 손상으로 인하여 파티션이 구분되지 않는 경우, 각 파일 시스템의 특징을 이용하여 안정적이고 효율적인 분석이 가능한 파티션 복구 알고리즘에 대해 제시한다.

• Smart Structures and Systems
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• 제5권4호
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• pp.317-328
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• 2009

Current maintenance operations and integrity checks on a wide array of structures require personnel entry into normally-inaccessible or hazardous areas to perform necessary nondestructive inspections. To gain access for these inspections, structure must be disassembled and removed or personnel must be transported to remote locations. The use of in-situ sensors, coupled with remote interrogation, can be employed to overcome a myriad of inspection impediments stemming from accessibility limitations, complex geometries, the location and depth of hidden damage, and the isolated location of the structure. Furthermore, prevention of unexpected flaw growth and structural failure could be improved if on-board health monitoring systems were used to more regularly assess structural integrity. A research program has been completed to develop and validate Comparative Vacuum Monitoring (CVM) Sensors for surface crack detection. Statistical methods using one-sided tolerance intervals were employed to derive Probability of Detection (POD) levels for a wide array of application scenarios. Multi-year field tests were also conducted to study the deployment and long-term operation of CVM sensors on aircraft. This paper presents the quantitative crack detection capabilities of the CVM sensor, its performance in actual flight environments, and the prospects for structural health monitoring applications on aircraft and other civil structures.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 춘계학술대회
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• pp.299-302
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• 2010

최근의 악성코드는 백신에 쉽게 탐지 되지 않기 위해 바이러스를 압축파일로 변조시켜 악성코드 패턴을 지연하는 추세이다. 시중에 나와 있는 수많은 백신엔진 중에서는 압축파일로 변조된 악성코드 패턴 및 검사가 가능한지 알아 봐야한다. 본 논문은 다중 압축 파일로 위장 변조된 은닉된 악성코드의 패턴을 검사하여 검출되는지를 검사 엔진을 통해 모의실험을 한다. 은닉된 악성코드의 행위를 분석하며, 호스트 파일 변조와 시스템 드라이버 파일 감염 및 레지스트리 등록이 되는가를 분석한다. 본 연구를 통해 은닉형 악성코드의 검사와 백신 치료 효과를 강화시켜 악성코드로 인한 피해를 감소하는데 기여할 것이다.

• 한국기계가공학회지
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• 제18권9호
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• pp.52-57
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• 2019

The key technology of the fourth industrial revolution is artificial intelligence and machine learning. In this study, FMEA was performed on fuel pumps used as key items in most systems to identify major failure components, and artificial neural networks were built using big data. The main failure mode of the fuel pump identified by the test was coil damage due to overheating. Based on the artificial neural network built, machine learning was conducted to predict the failure and the mean error rate was 4.9% when the number of hidden nodes in the artificial neural network was three and the temperature increased to $140^{\circ}C$ rapidly.

• 한국실내디자인학회논문집
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• 제23권5호
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• pp.14-24
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• 2014

Modern enterprise activity and consuming pattern which have been continued since the industrial revolution are causing a great burden on the environment, so that the strategy for sustainability in the whole industry cannot but be realistic and inevitable alternative. Presently various brands which applied the concept of sustainability exist, however they also can be said to play a part in current environmental damage by creating value aiming at only growth and pursuing short-term profit in accordance with it with simple commercial logic. Hereupon, this research aimed at eventually preparing the base of guidelines of sustainable design of space branding by newly drawing the value of sustainability in the aspect of space branding and systematically deducing design elements along with it. For this, the researcher reestablished value and design elements for sustainability in space branding by comprehending the concept of sustainability, design method of sustainable design and environmental value hidden in it, after comprehending the concept of space branding and brand value suggestion and interrelation through advanced researches. The previous studies related to the existing space branding have had mainly focused on the design of the marketing point of view to promote consumer culture. But this study can be found the meaning that new roles and methods of design in space branding from the perspective of sustainable. Now companies need to figure out a variety of strategic ways to find the right balance depending on their situation between contradictory concept of 'Consumption' and 'Sustainability'.

• 방송공학회논문지
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• 제20권6호
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• pp.938-949
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• 2015

본 논문에서는 외부압력에 의한 외형 손상이나 빛의 방향에 따른 색상 대비변화 등에 견고한 영상기반 속도 제한 표지판 인식 시스템 설계를 제안한다. 속도 제한 표지판 인식을 위해서 최근 패턴 인식 분야에서 뛰어한 성능을 보여주고 있는　CNN (Convolutional neural network)을 사용한다. 하지만 기존의 CNN은 특징 추출을 위해 다수의 은닉층이 사용되고 추출된 결과에 대해 MLP(Multi-layer perceptron) 등과의 완전 연결(fully-connected) 방식을 사용함으로 학습과 테스트 시간이 많이 걸리는 단점이 있다. 본 논문에서는 이러한 단점을 줄이기 위해 2계층의 CNN을 구성하고 패턴 분류를 위해 랜덤 포레스트(Random forest)를 결합하여 완전 연결이 아닌 랜덤 연결 방식을 적용하였다. GTSRB(German Traffic Sign Recognition Benchmark)데이터의 교통안전표지판 중에서 8개 속도 제한 표지판 데이터를 사용하여 제안하는 방식이 SVM (Support Vector Machine)이나 MLP 분류기를 적용할 때 보다 성능이 우수함을 입증하였다.

• Clinical and Experimental Pediatrics
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• 제54권5호
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• pp.212-218
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• 2011

Purpose: The diagnosis of acute pyelonephritis (APN) is often difficult, as its clinical and biological manifestations are non-specific in children. If not treated quickly and adequately, however, APN may cause irreversible renal damage, possibly leading to hypertension and chronic renal failure. We were suspecting the diagnostic value of $^{99m}Tc$-dimercaptosuccinic acid (DMSA) scan by experiences and so compared the results of DMSA scan to those of multi-detector row computed tomography (MDCT). Methods: We retrospectively selected and analyzed 81 patients who were diagnosed as APN by MDCT during evaluation of their acute abdomen in emergency room and then received DMSA scan also for the diagnostic work-up of APN after admission. We evaluated the results of imaging studies and compared the diagnostic value of each method by age groups, <2 years (n=45) and ${\geq}$2 years (n=36). Results: Among total 81 patients with MDCT-proven APN, DMSA scan was diagnostic only in 55 children (68%), while the remaining 26 children (32%) showed false negative normal findings. These 26 patients were predominantly male and most of them, 19 (73.1%) were <2 years of age. Conclusion: DMSA scan holds obvious limitation compared to MDCT in depicting acute inflammatory lesions of kidney in children with APN, especially in early childhood less than 2 years of age. MDCT showed hidden lesions of APN, those were undetectable through DMSA scan in children.

• Smart Structures and Systems
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• 제26권2호
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• pp.175-184
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• 2020

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

• Animal Bioscience
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• 제34권9호
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• pp.1559-1568
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• 2021

Objective: Bedding materials directly contact hooves of dairy cows and they may serve as environmental sources of lameness-associated pathogen. However, the specific composition of bacteria hidden in bedding materials is still not clear. The aim of this study was to determine the effect bedding material and its bacterial composition has on lameness of Holstein heifers. Methods: Forty-eight Holstein heifers with similar body weights were randomly assigned into three groups including sand bedding (SB), concrete floor (CF), and compost bedding (CB). Hock injuries severity and gait performance of dairy cows were scored individually once a week. Blood samples were collected at the end of the experiment and bedding material samples were collected once a week for Illumina sequencing. Results: The CF increased visible hock injuries severity and serum biomarkers of joint damage in comparison to SB and CB groups. Besides, Illumina sequencing and analysis showed that the bacterial community of CB samples had higher similarity to that of SB samples than CF samples. Bacteria in three bedding materials were dominated by gastrointestinal bacteria and organic matter-degrading bacteria, such as Actinobacteria, Firmicutes, and norank JG30-KF-cM45. Lameness-associated Spirochaetaceae and Treponeme were only detected in SB and CB samples with a very low relative abundance (0% to 0.08%). Conclusion: The bacterial communities differed among bedding materials. However, the treponemes pathogens involved in the pathogenesis of lameness may not be a part of microbiota in bedding materials of dairy cows.

• Smart Structures and Systems
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• 제29권2호
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• pp.301-309
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• 2022

Protective coatings are most widely used anticorrosive structures for steel structures. The corrosion under the coating damages the host material, but this damage is completely hidden. Therefore, a field-applicable under-coating-corrosion visualization method has been desired for a long time. Laser ultrasonic technology has been studied in various fields as an in situ nondestructive inspection method. In this study, a comparative analysis was carried out between a guided-wave ultrasonic propagation imager (UPI) and pulse-echo UPI, which have the potential to be used in the field of under-coating-corrosion management. Both guided-wave UPI and pulse-echo UPI were able to successfully visualize the corrosion. Regarding the field application, the guided-wave UPI performing Q-switch laser scanning and piezoelectric sensing by magnetic attachment exhibited advantages owing to the larger distance and incident angle in the laser measurement than those of the pulse-echo UPI. Regarding the corrosion visualization methods, the combination of adjacent wave subtraction and variable time window amplitude mapping (VTWAM) provided acceptable results for the guided-wave UPI, while VTWAM was sufficient for the pule-echo UPI. In addition, the capability of multiple sensing in a single channel of the guided-wave UPI could improve the field applicability as well as the relatively smaller size of the system. Thus, we propose a guided-wave UPI as a tool for under-coating-corrosion management.