• 정보관리연구
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• 제42권1호
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• pp.137-156
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• 2011

본 연구에서는 SNS라는 사용자 중심의 온라인 정보서비스를 대상으로, SNS사용자 만족 및 정보공유에 영향을 미치는 요인들을 규명해 보고자 한다. 구체적으로, 애착 이론과 자기표현 이론을 중심으로 사용자들의 SNS에 대한 감정적 애착 및 자아표현이 사용자 만족 및 SNS에서의 정보공유에 미치는 영향을 연구하였다. 본 연구를 위해 문헌연구와 더불어 설문조사를 실시하였으며, 수집된 자료는 PLS(Partial Least Square)를 이용하여 측정모형 및 가설검증을 실시하였다. 분석결과, SNS사용자의 감정적 애착이 사용자 만족 및 정보공유에 긍정적 영향을 미치며, 사용자의 자기표현은 사용자 만족에는 긍정적 영향을 미치나 정보공유에는 유의한 영향을 미치지 않는 것으로 나타났다. 또한 사용자 만족은 정보공유에 대해 긍정적인 영향을 미치는 것으로 나타났다. 이 외에 본 연구결과에 대한 의의 및 한계점을 논의하였으며, 향후 연구에 대한 시사점도 언급하였다.

• 한국컴퓨터정보학회논문지
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• 제21권5호
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• pp.167-175
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• 2016

The volatile component analysis of 82 commercialized liquors(44 samples of single malt whisky, 20 samples of blended whisky and 18 samples of brandy) was carried out by gas chromatography after liquid-liquid extraction with dichloromethane. Pattern recognition techniques such as principle component analysis(PCA), cluster analysis(CA), linear discriminant analysis(LDA) and partial least square discriminant analysis(PLSDA) were applied for the discrimination of different liquor categories. Classification rules were validated by considering sensitivity and specificity of each class. Both techniques, LDA and PLSDA, gave 100% sensitivity and specificity for all of the categories. These results suggested that the common characteristics and identities as typification of whiskies and brandys was founded by using multivariate data analysis method.

• 한국연초학회지
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• 제27권1호
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• pp.141-152
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• 2005

This study focused on the relationships among leaf and smoke components and sensory properties following tobacco leaf blending. A completely randomized experimental design was used to evaluate components of leaf and smoke and sensory properties for sample cigarettes with four mixtures of flue cured and burley tobacco (40:60, 60:40, 80:20 and 100:0). Eleven leaf components, six smoke components, and eight sensory properties of smoking taste were analyzed. A sensory evaluation method known as quantitative descriptive analysis was used to evaluate perceptual strength on a fifteen score scale. Raw data from ten trained panelists were obtained and statistically analyzed. Based on the MANOVA, clustering analysis, correlation matrix and partial least square (PLS) method were applied to find out which smoke component most affected sensory properties. The PLS method was used to remove the influence between explanatory variables in the leaf, smoke components derived from the results. High correlations (p<0.0l) were found among ten specific leaf and smoke components and sensory attributes. Total nitrogen, ammonia, total volatile base, and nitrate in the leaf were significantly correlated (p<0.05) with impact, bitterness, tobacco taste, irritation, smoke volume, and smoke pungency. From the results of PLS analysis, influence variables are used to explain about the correlation. In terms of bitterness, with only two explanatory variables, Leaf $NO_3$ and Leaf crude fiber were enough for guessing their correlation. In the distance weighted least square fitting analysis, carbon monoxide highly influenced bitterness, hay like taste, and smoke volume.

• Journal of Information Processing Systems
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• 제9권3호
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• pp.405-424
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• 2013

This research paper proposes a secured, robust approach of information security using steganography. It presents two component based LSB (Least Significant Bit) steganography methods for embedding secret data in the least significant bits of blue components and partial green components of random pixel locations in the edges of images. An adaptive LSB based steganography is proposed for embedding data based on the data available in MSB's (Most Significant Bits) of red, green, and blue components of randomly selected pixels across smooth areas. A hybrid feature detection filter is also proposed that performs better to predict edge areas even in noisy conditions. AES (Advanced Encryption Standard) and random pixel embedding is incorporated to provide two-tier security. The experimental results of the proposed approach are better in terms of PSNR and capacity. The comparison analysis of output results with other existing techniques is giving the proposed approach an edge over others. It has been thoroughly tested for various steganalysis attacks like visual analysis, histogram analysis, chi-square, and RS analysis and could sustain all these attacks very well.

• 생약학회지
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• 제44권4호
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• pp.332-335
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• 2013

Geographical classification of A. gigas was performed in the present study using UHPLC-DAD combined with multivariate data analysis techniques. Six active constituents were isolated from A. gigas; nodakenin, marmesin, decursinol, demethylsuberosin, decursin and decursinol angelate. One hundred sixty eight A. gigas samples were simultaneously determined using UHPLC-DAD. A principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) was used to classify the samples according to geographical origins (Korea and China). The origins of A. gigas from Korea and China were correctly classified by 81.6% and 93.8% using PLS-DA Y prediction. This result demonstrates the potential use of UHPLC-DAD combined with multivariate analysis techniques as an accurate and rapid method to classify A. gigas according to their geographical origin.

• 국제강구조저널
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• 제18권5호
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• pp.1684-1698
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• 2018

Fragility functions are determined for braced steel moment frames (SMFs) with plans such as square-, T-, L-, U-, trapezoidal-, and semicircular-shaped, subjected to blast. The frames are designed for gravity and seismic loads, but not necessarily for the blast loads. The blast load is computed for a wide range of scenarios involving different parameters, viz. charge weight, standoff distance, and blast location relative to plan of the structure followed by nonlinear dynamic analysis of the frames. The members failing in rotation lead to partial collapse due to plastic mechanism formation. The probabilities of partial collapse of the SMFs, with and without bracing system, due to the blast loading are computed to plot fragility curves. The charge weight and standoff distance are taken as Gaussian random input variables. The extent of propagation of the uncertainties in the input parameters onto the response quantities and fragility of the SMFs is assessed by computing Sobol sensitivity indices. The probabilistic analysis is conducted using Monte Carlo simulations. The frames have least failure probability for blasts occurring in front of their corners or convex face. Further, the unbraced frames are observed to have higher fragility as compared to counterpart braced frames for far-off detonations.

• Journal of Animal Science and Technology
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• 제64권3호
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• pp.531-538
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• 2022

In Italy, buffalo mozzarella is a largely sold and consumed dairy product. The fraudulent adulteration of buffalo milk with cheaper and more available milk of other species is very frequent. In the present study, Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis by partial least square (PLS) regression, was applied to quantitatively detect the adulteration of buffalo milk with cow milk by using a fully automatic equipment dedicated to the routine analysis of the milk composition. To enhance the heterogeneity, cow and buffalo bulk milk was collected for a period of over three years from different dairy farms. A total of 119 samples were used for the analysis to generate 17 different concentrations of buffalo-cow milk mixtures. This procedure was used to enhance variability and to properly randomize the trials. The obtained calibration model showed an R² ≥ 0.99 (R² cal. = 0.99861; root mean square error of cross-validation [RMSEC] = 2.04; R² val. = 0.99803; root mean square error of prediction [RMSEP] = 2.84; root mean square error of cross-validation [RMSECV] = 2.44) suggesting that this method could be successfully applied in the routine analysis of buffalo milk composition, providing rapid screening for possible adulteration with cow's milk at no additional cost.

• 한국국제농업개발학회지
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• 제31권4호
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• pp.378-383
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• 2019

본 연구는 FT-IR 스펙트럼 데이터를 기반으로 다변량통계분석을 이용하여 생육 온도변화에 따른 파파야(Carica papaya L.)의 대사체 수준 식별을 통해 기후 변화에 대응하여 작물의 육종 연구의 기초자료로 활용하고자 한다. 1. FT-IR 스펙트럼 데이터로부터 PCA(principal component analysis), PLS-DA(partial least square discriminant analysis) 그리고 HCA(hierarchical clustering analysis) 분석을 실시하였다. 2. 파파야 품종은 1700-1500, 1500-1300, 1100-950 cm^-1부위에서 대사체의 양적, 질적 패턴 변화가 FT-IR 스펙트럼상에서 나타났다. FT-IR 스펙트럼의 1700-1500 cm^-1부위는 주로 Amide I 과 II을 포함하는 아미노산 및 단백질계열의 화합물들의 질적, 양적 정보를 나타내고, 1500-1300 cm^-1부위는 phosphodiester group을 포함한 핵산 및 인지질의 정보가 반영이 되고, 1100-950 cm^-1부위는 단당류나 복합 다당류를 포함하는 carbohydrates 계열의 화합물들이 질적, 양적 정보가 반영되는 부위이다. 3. PCA score plot 상측으로부터 +0℃(A)에서 +4℃(C)로 변화하는 것을 볼 수 있다. (A) 그룹은 주로 현재 기온에서 재배되는 파파야가 분포되면서 그룹을 형성하고 있고, (B) 그룹은 평년 기온에서 +2℃ 증가한 것을 가정하여 재배된 파파야가 그룹을 형성하였다. 또한, (C) 그룹은 (B) 그룹에서 +2℃, 평년 기온에서 +4℃ 증가한 것을 가정하여 재배된 파파야가 그룹을 형성하였다. 4. PLS-DA 분석의 경우 PCA 분석보다 생육온도에 따른 그룹 간 식별이 뚜렷하게 나타났다. 5. 본 연구에서 확립된 파파야 생육온도에 따른 대사체 수준 식별 기술은 파파야의 품종, 계통의 신속한 선발 수단으로 활용이 가능할 것으로 기대되며 육종을 통한 신품종개발 가속화에 기여할 수 있을 것으로 예상된다.

• 농업과학연구
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• 제38권4호
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• pp.761-767
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• 2011

The objective of this study was to predict total bacteria count of pork meats by using the portable electronic nose systems developed throughout two stages of the prototypes. Total bacteria counts were measured for pork meats stored at $4^{\circ}C$ for 21days and compared with the signals of the electronic nose systems. PLS(Partial least square), PCR (Principal component regression), MLR (Multiple linear regression) models were developed for the prediction of total bacteria count of pork meats. The coefficient of determination ($R_p{^2}$) and root mean square error of prediction (RMSEP) for the models were 0.789 and 0.784 log CFU/g with the 1st system for the pork loin, 0.796 and 0.597 log CFU/g with the 2nd system for the pork belly, and 0.661 and 0.576 log CFU/g with the 2nd system for the pork loin respectively. The results show that the developed electronic system has potential to predict total bacteria count of pork meats.

• 한국경영정보학회:학술대회논문집
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• 한국경영정보학회 2007년도 추계학술대회
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• pp.487-492
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• 2007

This research focuses on the development and empirical validation of a model of software piracy behavior on the basis of deterrence theory, expected utility theory and the theory of reasoned action. The total of sample numbered 86 and PLS (Partial Least Square) was utilized for analysis. The test of this study revealed that punishment severity was the greatest significant factor to influence to software piracy and subjective norms was also significantly related to it. However punishment certainty and software cost do not significantly affect to software piracy.