• Journal of the Korean Society of Food Science and Nutrition
• /
• v.34 no.1
• /
• pp.113-119
• /
• 2005

This study was performed to evaluate the effects of the addition of medicinal herb extracts on shelf-life and quality of seasoning beef. The pH of seasoning beef treated with medicinal herbs was more stable than those without medicinal herbs. The moisture content of non-treated group decreased than that of group treated with medicinal herbs. The shear forces of seasoning beef revealed that non-treated group and other group treated with medicinal herbs were higher than those with medicinal herb extracts less than 0.5% adding medicinal herb extracts. As the storage time increased, the redness of group treated with 2.0% medicinal herbs was most stable among the seasoning beef color. The increase of TBA value was observed as the storage period increased. The total bacterial count of non-treated group was detected to 10$^{8}$ CFU/g, but that of group with medicinal herbs was counted from 10$^4$ CFU/g to 10$^{5}$ CFU/g at 6 days of storage time. The sensory evaluation indicated that the changes of group treated with various concentration of medicinal herbs were scored relatively higher than that of non-treated groups.

• Journal of Korea Multimedia Society
• /
• v.8 no.10
• /
• pp.1337-1346
• /
• 2005

In this paper, we describe an algorithm which can automatically recognize human gesture for Human-Robot interaction. In early works, many systems for recognizing human gestures work under many restricted conditions. To eliminate these restrictions, we have proposed the method that can represent 3D and 2D gesture information simultaneously, APM. This method is less sensitive to noise or appearance characteristic. First, the feature vectors are extracted using APM. The next step is constructing a gesture space by analyzing the statistical information of training images with PCA. And then, input images are compared to the model and individually symbolized to one portion of the model space. In the last step, the symbolized images are recognized with HMM as one of model gestures. The experimental results indicate that the proposed algorithm is efficient on gesture recognition, and it is very convenient to apply to humanoid robot or intelligent interface systems.

• Proceedings of the Korean Society of Postharvest Science and Technology of Agricultural Products Conference
• /
• 2003.10a
• /
• pp.143.1-143
• /
• 2003

본 논문은 브랜드 쌀 구매에 영향을 미치는 요인(factor)들이 소비자 특성에 따라 차이가 있는지를 분석하기 위한 목적으로 수행되었다. 분석을 위하여 서울시에 1,000명의 주부를 대상으로 설문조사를 실시하였으며, 그 주요 내용은 다음과 같다. 먼저 주부들이 쌀 구매에 영향을 미치는 11개 항목을 5점 리커르트 척도를 이용하여 분석하였다. 그 결과 소비자들이 가장 높은 점수를 부여하는 것은 쌀의 잔류 농약 정도로서 4.12점이 나왔으며, 영양가 높은 쌀(4.01점), 쌀알의 모양(3.96점) 및 쌀의 생산지(3.88점) 등의 순위가 높았다. 요인분석을 위해 고유치(eigen value) 값이 0.8 이상인 경우를 기준으로 요인 수를 분석한 결과 다섯가지의 요인이 추출되었으며, 그 특징은 유형적 차원과 무형적 차원으로 구분되었다. 전자인 유형적차원은 물리적 속성(완전미 여부, 도정일자, 잔류농약), 지역성(생산지), 외관성(크기, 모양) 및 가격성등의 가시적 차원으로 소비자가 쉽게 판단하거나 쌀간의 비교가 용이한 특성이며, 후자는 심리적 속성이나 상징성을 의미하는 것으로서 브랜드 상표와 품질 인증 마크가 가지는 신뢰성 등이 영향을 미치는 것으로 분석되었다. 무형적 차원인 식품의 안전성이 도시주부간 쌀 구매에 미치는 차별성을 알아보기 위하여 정규성 검정 결과에 따라 독립표본 T-검정을 실시하였다. 분석에서 도시주부가 특성별로 두 집단으로 구분되는 기준은 자의적 분류보다는 공통적인 기준을 이용하고자 평균값(나이, 학력, 소득, 동거가족 수)을 기준으로, 그 외의 경우는 더미변수(주부직업 유무, 주거형태 및 거주지역)를 이용하여 구분하였다. 식품의 안전성으로 추출된 요인 값의 평균에 대해 두 집단간 차이를 검정하였으며, 분석 결과 주거형태가 1％ 유의수준에서, 주부취업 여부 및 거주지역이 각각 5%유의수준에서 통계적 유의성이 있는 것으로 분석되었다. 반면 주부간 나이, 학력, 소득수준 및 동거가족 수에서는 유의미한 결과가 추정되지 못하였다. 본 연구결과를 볼 때, 식품의 안전성을 고려한 쌀의 마케팅 전략은 취업주부, 아파트 거주자 및 강남지역 주부들을 대상으로 한 판매활동 강화가 필요하다. 아울러 통계적으로 유의미한 결과를 나타내는 도시 주부의 특성 변수들을 세밀하게 구분해서 연구·분석하는 시장세분화 연구가 필요하다.

• Journal of the Korea Institute of Building Construction
• /
• v.23 no.2
• /
• pp.197-207
• /
• 2023

Concrete is a widely used material due to its excellent compressive strength and durability. However, depending on the surrounding environment and the characteristics of the materials used in the construction, various defects may occur, such as cracks on the surface and subsidence of the structure. The detects on the surface of the concrete structure occur after completion or over time. Neglecting these cracks may lead to severe structural damage, necessitating regular safety inspections. Traditional visual inspections of concrete walls are labor-intensive and expensive. This research presents a deep learning-based semantic segmentation model designed to detect cracks in concrete walls. The model addresses surface defects that arise from aging, and an image augmentation technique is employed to enhance feature extraction and generalization performance. A dataset for semantic segmentation was created by combining publicly available and self-generated datasets, and notable semantic segmentation models were evaluated and tested. The model, specifically trained for concrete wall fracture detection, achieved an extraction performance of 81.4%. Moreover, a 3% performance improvement was observed when applying the developed augmentation technique.

• Food Science and Preservation
• /
• v.11 no.1
• /
• pp.122-125
• /
• 2004

Factor analysis is estimated using housewives's intention data in Seoul province. Rice consumers considered safety, high nutritive value, shape and cultivation region as important factors in buying rice. The factors of food safety are brand and quality certification mark. The differences of two housewife groups on safety factor are caused by residence type, employment existence and residence region. The marketing strategies for rice containing food safety target housewives living in apartment, Gang Nam region. Also selling extension for target consumers housewives should be employed.