• 한국간호교육학회지
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• 제20권2호
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• pp.300-311
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• 2014

Purpose: This study was conducted to identify influence of emotional awareness, ambivalence over emotional expressiveness and emotional regulation style on nursing student adjustment. Method: One hundred and sixty nine nursing students completed the questionnaires from May to June, 2013. Data analysis was done using descriptive statistics, independent t-test, ANOVA, Pearson correlation coefficient, and multiple regression with SAS v 9.3. Results: Ambivalence over positive emotional expressiveness, motivation of application for nursing-aptitude, emotional awareness-mood labeling, avoidant/distractive style of emotion regulation, and parents-both alive were identified as factors influencing nursing student adjustment. The model explained 37% of variance in nursing student adjustment. Conclusion: The results of this study suggest that programs for promoting mood labeling and reducing ambivalence over positive emotional expressiveness and avoidant/distractive style of emotion regulation are important for college adjustment in nursing students. In addition, aptitude test for nursing applicants can be considered.

• Journal of Dairy Science and Biotechnology
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• 제33권4호
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• pp.253-262
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• 2015

The authentication and implications of misleading labeling in milk and dairy products is important to protect against cheating consumers from adulteration and to alert sensitive consumers to any undeclared potential allergens. This need to support milk and dairy products labeling has led to the development of specific analytical techniques for the analysis of milk and dairy products ingredients. Recently, several methods based on polymerase chain reaction (PCR), including restriction fragment length polymorphism (PCR-RFLP), multiplex PCR, species-specific PCR, and real-time PCR, have been proposed as useful means for identifying species of origin in milk and dairy products, as well as quantifying and detecting any adulteration. These methods have particular advantages owing to their high specificity and sensitivity, as well as rapid processing time. In this review, we provide an updated and extensive overview of the PCR-based methods used for milk and dairy products authentication with a particular focus on the application of PCR methods to detect adulteration.

• The Journal of Asian Finance, Economics and Business
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• 제8권8호
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• pp.565-572
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• 2021

The role of the garment and textile industry is particularly important in the economies of many countries in the context of international goods trade. There is no denying that the garment and textile industry contributes significantly to the economic growth in the global economy. The study seeks to investigate the relationship between control variables and Vietnamese consumers' intention to buy Chinese garment products. While previous research has found some control variables influencing consumers' intention to buy products, little research has been done about the influence of control variables on consumers' intention to buy Chinese garment products, in developing countries like Vietnam. In particular, the textile industry plays an important role in export, but outsourcing is accounting for a high proportion of trade, hence, it is necessary to increase innovation to increase consumers' intention to buy domestic garment products. The data is collected from a survey of 406 Vietnamese consumers' in Hanoi city and Ho Chi Minh City. The methodology includes a mixed-method, i.e. qualitative method and quantitative method. The quantitative method applies SPSS analysis to measure the control variables' influence on Vietnamese consumers' intention to buy Chinese garment products. The results identify 1 control variable that impacts Vietnamese consumers' intention to buy Chinese garment products, which is domicile.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 춘계학술발표대회
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• pp.510-512
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• 2023

In order to enhance a model's capability for detecting facial expressions, this research suggests a pipeline that makes use of the GradCAM component. The patching module and the pseudo-labeling module make up the pipeline. The patching component takes the original face image and divides it into four equal parts. These parts are then each input into a 2Dconvolutional layer to produce a feature vector. Each picture segment is assigned a weight token using GradCAM in the pseudo-labeling module, and this token is then merged with the feature vector using principal component analysis. A convolutional neural network based on transfer learning technique is then utilized to extract the deep features. This technique applied on a public dataset MMI and achieved a validation accuracy of 96.06% which is showing the effectiveness of our method.

• 대한지역사회영양학회지
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• 제21권6호
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• pp.574-579
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• 2016

Objectives: Vitamin C has various functions such as antioxidative effect and supporting absorption of iron (Fe). Aim of this present study was to provide vitamin C nutrition information and to briefly evaluate absorption interaction of vitamin C and Fe content of vitamin C emphasized products. Methods: Vitamin C emphasized foods including beverages, cereal, snacks, chocolate products, other cocoa products, and sugary products were examined by HPLC. Fe contents in samples after dry-ashing were examined by ICP. Results: Vitamin C content ranges in various products tested were the following: beverages (n=11) $20.15{\pm}0.08{\sim}845.41{\pm}6.07mg$, cereal (n=11) $52.50{\pm}0.23{\sim}262.50{\pm}0.07mg$, snacks (n=1) $50.00{\pm}0.25mg$, chocolate products (n=1) $311.73{\pm}2.44mg$, other cocoa products (n=1) $311.73{\pm}2.44mg$, other sugary products (n=2) $52.50{\pm}0.23{\sim}262.50{\pm}0.07mg$. Vitamin C (n=27) analysis values ranged from 82 to 450% of the labeled value. Vitamin C content in vitamin C emphasized food (n=6) was estimated 7.7 times~56.6 times more than Fe content. Conclusions: Analyzed samples ranged more than 80% of the labeled value in vitamin C emphasized products, which complied with food labeling regulation. But, beverages (n=3), cereal (n=4), chocolate products (n=1) were 2 times more than the labeled value. To provide accurate nutrition information, food manufactures should supervise nutrition labeling and understand the interactions between nutrients. Also, consumer should decide about the adequate amount of nutrient intake by thoroughly checking nutrition labeling.

• 한국항해항만학회지
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• 제39권4호
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• pp.307-312
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• 2015

ARPA(Automatic Radar Plotting Aid)는 자동레이더 플로팅 장치로써, 레이더 물표의 상대침로와 상대방위로 구성된 운동벡터에 본선의 침로와 방위로 구성되는 운동벡터를 가감 연산(벡터연산)하여, 물표의 진침로와 진방위 및 최근접점과 근접시간을 계산하는 장치를 말한다. 본 연구의 목적은 ARPA 레이더를 구현하기 위한 물표의 획득 및 추적 기술을 개발하는 것으로, 이에 관한 여러 선행 연구를 검토하여 적용 가능한 알고리듬 및 기법을 조합하여 기초적인 ARPA 기능을 개발하였다. 주요 연구내용으로, 레이더 영상에서 물표를 획득하기 위하여, 회색조 변환, 가운시안 평활 필터 적용, 이진화 및 라벨링(Labeling)과 같은 순차적 영상 처리 방법을 고안하였고, 이전 영상에서의 물표가 다음 영상에서의 어느 물표인지를 결정하는데 근접이웃탐색알고리듬을 사용하였으며, 물표의 진침로와 진방위를 계산하는 거동해석에 칼만필터를 사용하였다. 또한 이러한 기법을 전산 구현하여 실선실험을 수행하였고, 이를 통해 개발된 ARPA의 기능이 실용상 사용가능함을 검증하였다.

• Journal of Positioning, Navigation, and Timing
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• 제12권2호
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• pp.91-100
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• 2023

The existing indoor localization method using Wi-Fi fingerprinting has a high collection cost and relatively low accuracy, thus requiring integrated correction of convergence with other technologies. This paper proposes a new method that significantly reduces collection costs compared to existing methods using Wi-Fi fingerprinting. Furthermore, it does not require labeling of data at collection and can estimate pedestrian travel paths even in large indoor spaces. The proposed pedestrian movement path estimation process is as follows. Data collection is accomplished by setting up a feature area near an indoor space intersection, moving through the set feature areas, and then collecting data without labels. The collected data are processed using Kernel Linear Discriminant Analysis (KLDA) and the valley point of the Euclidean distance value between two data is obtained within the feature space of the data. We build learning data by labeling data corresponding to valley points and some nearby data by feature area numbers, and labeling data between valley points and other valley points as path data between each corresponding feature area. Finally, for testing, data are collected randomly through indoor space, KLDA is applied as previous data to build test data, the K-Nearest Neighbor (K-NN) algorithm is applied, and the path of movement of test data is estimated by applying a correction algorithm to estimate only routes that can be reached from the most recently estimated location. The estimation results verified the accuracy by comparing the true paths in indoor space with those estimated by the proposed method and achieved approximately 90.8% and 81.4% accuracy in two experimental spaces, respectively.

• Journal of Plant Biotechnology
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• 제37권2호
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• pp.196-204
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• 2010

With the completion of genome sequencing of several organisms, attention has been focused to determine the function and functional network of proteins by proteome analysis. The recent techniques of proteomics have been advanced quickly so that the high-throughput and systematic analyses of cellular proteins are enabled in combination with bioinformatics tools. Furthermore, the development of proteomic techniques helps to elucidate the functions of proteins under stress or diseased condition, resulting in the discovery of biomarkers responsible for the biological stimuli. Ultimate goal of proteomics orients toward the entire proteome of life, subcellular localization, biochemical activities, and their regulation. Comprehensive analysis strategies of proteomics can be classified as three categories: (i) protein separation by 2-dimensional gel electrophoresis (2-DE) or liquid chromatography (LC), (ii) protein identification by either Edman sequencing or mass spectrometry (MS), and (iii) quanitation of proteome. Currently MS-based proteomics turns shiftly from qualitative proteome analysis by 2-DE or 2D-LC coupled with off-line matrix assisted laser desorption ionization (MALDI) and on-line electrospray ionization (ESI) MS, respectively, to quantitative proteome analysis. Some new techniques which include top-down mass spectrometry and tandem affinity purification have emerged. The in vitro quantitative proteomic techniques include differential gel electrophoresis with fluorescence dyes, protein-labeling tagging with isotope-coded affinity tag, and peptide-labeling tagging with isobaric tags for relative and absolute quantitation. In addition, stable isotope labeled amino acid can be in vivo labeled into live culture cells through metabolic incorporation. MS-based proteomics extends to detect the phosphopeptide mapping of biologically crucial protein known as one of post-translational modification. These complementary proteomic techniques contribute to not only the understanding of basic biological function but also the application to the applied sciences for industry.

• 말소리와 음성과학
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• 제6권3호
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• pp.139-145
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• 2014

The paper describes methods of conducting vowel analysis from a large-scale corpus with the aids of forced alignment and optimal formant ceiling methods. 'Read Style Corpus of Standard Korean' is used for building the forced alignment system and a subset of the corpus for the processing and extraction of features for vowel analysis based on optimal formant ceiling. The results of the vowel analysis are reliable and comparable to the results obtained using traditional analytical methods. The findings indicate that the methods adopted for the analysis can be extended and be used for more fine-grained analysis without time-consuming manual labeling without losing accuracy and reliability.

• Journal of Korean Neurosurgical Society
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• 제49권1호
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• pp.26-30
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• 2011

Objective: The primary objective of this study was to perform a retrospective evaluation of the radiological and pathological features influencing the formation of peritumoral brain edema (PTBE) in meningiomas. Methods: The magnetic resonance imaging (MRI) and pathology data for 86 patients with meningiomas, who underwent surgery at our institution between September 2003 and March 2009, were examined. We evaluated predictive factors related to peritumoral edema including gender, tumor volume, shape of tumor margin, presence of arachnoid plane, the signal intensity (SI) of the tumor in T2-weighted image (T2WI), the WHO histological classification (GI, GII/GIII) and the Ki-67 antigen labeling index (LI). The edema-tumor volume ratio was calculated as the edema index (EI) and was used to evaluate peritumoral edema. Results: Gender (p=0.809) and pathological finding (p=0.084) were not statistically significantly associated with peritumoral edema by univariate analysis. Tumor volume was not correlated with the volume of peritumoral edema. By univariate analysis, three radiological features, and one pathological finding, were associated with PTBE of statistical significance: shape of tumor margin (p=0.001), presence of arachnoid plane (p=0.001), high SI of tumor in T2WI (p=0.001), and Ki-67 antigen LI (p=0.049). These results suggest that irregular tumor margins, hyperintensity in T2WI, absence of arachnoid plane on the MRI, and high Ki-67 LI can be important predictive factors that influence the formation of peritumoral edema in meningiomas. By multivariate analysis, only SI of the tumor in T2WI was statistically significantly associated with peritumoral edema. Conclusion: Results of this study indicate that irregular tumor margin, hyperintensity in T2WI, absence of arachnoid plane on the MRI, and high Ki-67 LI may be important predictive factors influencing the formation of peritumoral edema in meningiomas.