• 융합보안논문지
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• 제22권4호
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• pp.85-97
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• 2022

빅데이터 기술이 발전하면서 데이터가 전 산업의 혁신 성장을 가속하는 초연결 지능화 사회로 빠르게 진입하고 있다. 고품질의 다양한 데이터를 보유하고 활용하는 융복합 산업이 새로운 성장 동력으로 자리매김하고 있으며, 다양한 전통 산업군에 빅데이터가 융합되어 데이터 기반의 혁신을 통해 디지털 전환이 이루어지고 있다. 특히 의료 분야에서는 전자의무기록 데이터와 같은 정형 데이터와 CT, MRI 등의 비정형 의료 데이터를 함께 활용함으로써, 질병 예측 및 진단의 정확도를 높이고 있다. 현재 의료 산업에서 비정형 데이터의 중요성과 규모는 나날이 증가하고 있지만, 종래의 데이터 보안 기술과 정책은 정형 데이터 중심이며, 비정형 데이터의 보안성과 활용성에 대한 고려는 미비하다. 향후 빅데이터를 활용한 진료가 활성화되려면 데이터의 다양성과 보안성이 데이터 구축, 유통, 활용 단계에서 내재화되고 유기적으로 연계되어야 한다. 본 논문에서는 국내외 데이터 보안 제도와 기술 현황을 분석한다. 이후 의료 분야에서 비정형 데이터가 활발히 사용될 수 있도록 비식별조치 가이드라인에 비정형 데이터 중심의 비식별 기술과 산업에서의 기술 적용 사례를 추가하고, 비정형 데이터에 대한 개인정보 판단 기준을 수립할 것을 제안한다. 더 나아가 개인정보를 침해하지 않고, 비정형 데이터에 활용할 수 있는 객체 특징 기반의 식별 ID를 제안한다.

• Smart Structures and Systems
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• 제22권3호
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• pp.291-302
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• 2018

This paper presents a flexibility based method for damage identification from static measurements in beam-type structures. The response of the beam at the Damaged State is decomposed into the response at the Reference State plus the response at an Incremental State, which represents the effect of damage. The damage is localized by detecting slope discontinuities in the deflection of the structure at the Incremental State. A denoising filtering technique is applied to reduce the effect of experimental noise. The extent of the damage is estimated through comparing the experimental flexural stiffness of the damaged cross-sections with the corresponding values provided by analytical models of cracked beams. The paper illustrates the method by showing a numerical example with two cracks and an experimental case study of a simply supported steel beam with one artificially introduced notch type crack at three damage levels. A Digital Image Correlation system was used to accurately measure the deflections of the beam at a dense measurement grid under a set of point loads. The results indicate that the method can successfully detect and quantify a small damage from the experimental data.

• Smart Structures and Systems
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• 제12권5호
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• pp.523-545
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• 2013

Piezoelectric and dielectric behaviors of a piezoceramic patch adhesively centered on a carbon composite plate are identified using a robust multi-objective optimization procedure. For this purpose, the patch piezoelectric stress coupling and blocked dielectric constants are automatically evaluated for a wide frequency range and for the different identifiable behaviors. Latters' symmetry conditions are coded in the design plans serving for response surface methodology-based sensitivity analysis and meta-modeling. The identified constants result from the measured and computed open-circuit frequencies deviations minimization by a genetic algorithm that uses meta-model estimated frequencies. Present investigations show that the bonded piezoceramic patch has effective three-dimensional (3D) orthotropic piezoelectric and dielectric behaviors. Besides, the sensitivity analysis indicates that four constants, from eight, dominate the 3D orthotropic behavior, and that the analyses can be reduced to the electromechanically coupled modes only; therefore, in this case, and if only the dominated parameters are optimized while the others keep their nominal values, the resulting piezoelectric and dielectric behaviors are found to be transverse-isotropic. These results can help designing piezoceramics smart composites for various applications like noise, vibration, shape, and health control.

• BMB Reports
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• 제40권4호
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• pp.494-500
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• 2007

The endophytic bruchid pest Callosobruchus maculatus causes severe damage to storage cowpea seeds, leading to economical losses. For this reason the use of $\alpha$-amylase inhibitors to interfere with the pest digestion process has been an interesting alternative to control bruchids. With this aim, $\alpha$-amylase inhibitors from baru seeds (Dipteryx alata) were isolated by affinity chromatographic procedures, causing enhanced inhibition of C. maculatus and Anthonomus grandis $\alpha$-amylases. To attempt further purification, this fraction was applied onto a reversed-phase HPLC column, generating four peaks with remarkable inhibition toward C. maculatus $\alpha$-amylases. SDS-PAGE and MALDI-ToF analysis identified major proteins of approximately 5.0, 11.0, 20.0 and 55 kDa that showed $\alpha$-amylase inhibition. Results of in vivo bioassays using artificial seeds containing 1.0% (w/w) of baru crude extract revealed 40% cowpea weevil larvae mortality. These results provide evidence that several $\alpha$-amylase inhibitors classes, with biotechnological potential, can be isolated from a single plant species.

• Journal of Microbiology and Biotechnology
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• 제25권8호
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• pp.1241-1245
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• 2015

The aim of the present work was to examine the putative promoter region of the operon ansPAB and to determine the general elements required for the regulation of transcriptional activity. The transcriptional start site of the ansPAB promoter was determined by using highresolution S1-nuclease mapping. Sequence analysis of this region showed -10 and -35 elements, which were consistent with consensus sequences for R. etli promoters that are recognized by the major form of RNA polymerase containing the σ⁷⁰ transcription factor. Mutation studies affecting several regions located upstream of the transcriptional start site confirmed the importance of these elements on transcriptional expression.

• Journal of Microbiology and Biotechnology
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• 제27권9호
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• pp.1576-1585
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• 2017

Yeasts, filamentous fungi, and bacteria colonize the surface of fermented sausages during the ripening process. The source of this microbiota is their surrounding environment, and is influenced by the maturing conditions and starter cultures. Debaryomyces hansenii was previously isolated from several dry-cured meat products and associated with the lipolytic and proteolytic changes that occur in these products, influencing their taste and flavor. Therefore, this study isolated the yeast microbiota present in the casing from different meat products ("lomo," "chorizo," and "$salchich{\acute{o}}n$") from the Valle de los Pedroches region in southern Spain. D. hansenii was by far the most abundant species in each product, as all 22 selected isolates were identified as D. hansenii by biochemical and/or molecular methods. In contrast, no yeasts were found in the meat batter. These data constitute the first study of the yeasts present in "lomo" sausages and particularly the highly appreciated Valle de los Pedroches "lomo" sausages. Furthermore, the resistance of these isolates to different pHs, temperatures, and saline stress was studied, together with their catabolic characteristics. Based on the results, certain isolates are proposed as valuable candidate starter cultures that could improve both the manufacture and the flavor of such dry-cured meat products, and provide an understanding of new mechanisms involved in stress tolerance. Applied medium-scale industrial tests are currently in progress.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.3112-3112
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• 2001

Near-Infrared Spectroscopy (NIRS) was investigated aiming at the identification of falsified drugs. The identification is based on comparison of the NIR spectrum of a sample with a typical spectra of an authentic drug using multivariate modelling and classification algorithms (PCA/SIMCA). Two spectrophotometers (Brimrose - Luminar 2000 and 2030), based on acoustic-optical filter (AOTF) technology, sharing the same controlling computer, software (Brimrose - Snap 2.03) and the data acquisition electronics, were employed. The Luminar 2000 scans the range 850 1800 nm and was employed for transmitance/absorbance measurements of liquids with a transflectance optical bundle probe with total optical path of 5 mm and a circular area of 0.5 $\textrm{cm}^2$. Model 2030 scans the rage 1100 2400 nm and was employed for reflectance measurement of solids drugs. 300 spectra, acquired in about 20 s, were averaged for each sample. Chemometric treatment of the spectral data, modelling and classification were performed by using the Unscrambler 7.5 software (CAMO Norway). This package provides the Principal Component Analysis (PCA) and SIMCA algorithms, used for modelling and classification, respectively. Initially, NIRS was evaluated for spectrum acquisition of various drugs, selected in order to accomplish the diversity of physico-chemical characteristics found among commercial products. Parameters which could affect the spectra of a given drug (especially if presented as solid tablets) were investigated and the results showed that the first derivative can minimize spectral changes associated with tablet geometry, physical differences in their faces and position in relation to the probe beam. The effect of ambient humidity and temperature were also investigated. The first factor needs to be controlled for model construction because the ambient humidity can cause spectral alterations that should cause the wrong classification of a real drug if the factor is not considered by the model.

• 정보보호학회논문지
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• 제30권4호
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• pp.719-734
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• 2020

본 논문은 최근 개정된 데이터 3법에 맞추어 조직 내 실무자들이 개인정보를 활용함에 있어 비식별 조치 수행 시 위험도에 따른 처리 수준 산정을 위한 새로운 측정방법을 제안한 것이다. 우리가 제안한 방법은 위험도 측정 시 데이터만이 아닌 데이터를 둘러싼 주위 상황을 고려하였고, 모든 분야에 적용이 가능하도록 범용 환경에서 데이터 상황을 크게 데이터 활용방법, 데이터 이용환경, 그리고 데이터(자체) 3가지 카테고리로 나누어 보다 체계적으로 분류하였으며, 제시된 분류에 따라 각 상황별 위험도에 기반하여 정량적으로 계산할 수 있도록 새로운 측정 방법을 제안하였다. 제안한 방법은 기존의 비식별 정보의 위험도 산정을 전문가들의 정성적 판단에만 맡기는 것이 아니라 일반 조직 내 개인정보처리자가 실무에 활용할 수 있도록 정량적인 방법으로 위험도를 산정할 수 있도록 설계하였다.

• 정보보호학회논문지
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• 제32권2호
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• pp.405-416
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• 2022

AI기술은 데이터 기반의 기계학습을 이용하여 삶의 질을 높여주고 있다. 기계학습을 이용시, 분산된 데이터를 전송해 한곳에 모으는 작업은 프라이버시 침해가 발생할 위험성이 있어 비식별화 과정을 거친다. 비식별화 데이터는 정보의 손상, 누락이 있어 기계학 습과정의 성능을 저하시키며 전처리과정을 복잡하게한다. 이에 구글이 2017년에 데이터의 비식별화와 데이터를 한 서버로 모으는 과정없이 학습하는 방법인 연합학습을 발표했다. 본 논문은 실제 금융데이터를 이용하여, K익명성, 차분프라이버시 재현데이터의 비식별과정을 거친 데이터의 학습성능과 연합학습의 성능간의 차이를 비교하여 효용성을 분석하였으며, 이를 통해 연합학습의 우수성을 보여주고자 한다. 실험결과 원본데이터 학습의 정확도는 91% K-익명성을 거친 데이터학습은 k=2일 때 정확도 79%, k=5일 때76%, k=7일 때 62%, 차분프라이버시를 사용한 데이터학습은 𝜖=2일 때 정확도 52%, 𝜖=1일 때 50%, 𝜖=0.1일 때 36% 재현데이터는 정확도 82%가 나왔으며 연합학습의 정확도는 86%로 두번째로 높은 성능을 보여 주었다.

• 한국전자파학회논문지
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• 제28권4호
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• pp.328-335
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• 2017

본 논문에서는 레이다 표적식별 성능을 향상시키기 위하여 고해상도 거리측면도(High Resolution Range Profile: HRRP)에 포함된 잡음을 효과적으로 제거하는 방법을 제안한다. 제안된 기법은 HRRP에 포함된 잡음의 통계적인 특성과 EMD(Empirical Mode Decomposition) 알고리즘을 이용하여 HRRP에 포함된 잡음을 효과적으로 제거한다. 잡음 제거 실험 결과에서는, 본 논문에서 제안한 기법이 잡음을 효과적으로 제거하면서, 표적 식별 성능을 크게 향상시키는 것을 수치적으로 확인할 수 있었다.