• Journal of Nutrition and Health
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• v.40 no.1
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• pp.78-88
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• 2007

The purpose of this study was to investigate dietary fat and individual fatty acids intake pattern of 174 college women living in Seoul and Gyong-gi province through internet nutritional assessment system. Each of the subjects was required to input their own food intake for three days, which included two days during the week and one day of the weekend, on the web program directly and all of the data collected were used for statistical analysis. The mean daily caloric intake of the subjects was 1,500.9 kcal which was at 71.5% of Estimated Energy Requirement (EER). Dietary fat contributed 27.6% of the total caloric intake which was slightly higher than the recommended limit of 25%. Daily cholesterol intake was 310.0 mg, which was also high to some degree. Mean daily N6 and N3 fatty acid intake was 6.1 g and 0.9 g, respectively, and calory % calculated from each were 3.63% and 0.53%. This result showed the intake of N3 fatty acid fell in Acceptable Macronutrient Distribution Ranges (AMR) $0.5\sim1.0%$ but that of N6 fatty acid was somewhat lower than the AMDR $4\sim8%$. N6/N3 ratio 8.5/l, however, was within the desirable range $4\sim10/1$. Considering overall dietary fatty acids intake, oleic acid was the most abundant, followed by linoleic and palmitic acid. And among polyunsaturated fatty acids intake, linoleic acid was exclusively high, accounting for 97.4% of total N6 fatty acid intake. On the contrary, three fatty acids, linolenic (67.3%), DHA (21.1%) and EPA (10.0%), together supplied 98.4% of total N3 fatty acid intake. Mean P/M/S was 0.9/l.1/1.0. The subjects' intake of fat, many fatty acids and cholesterol came from diverse food groups including meats, fats and oils, milk and milk products, eggs, fish, and soybean products. Nevertheless, the subjects tended to show unfavorable fat and fatty acids intake pattern in terms of quantity and quality. Based on these results, it is important to monitor dietary fat intake pattern of the general population continuously and an internet program such as the one used for this study would be valuable, especially for assessing dietary patterns in the younger generation.

• Journal of the Korean Society of Food Science and Nutrition
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• v.29 no.6
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• pp.1177-1184
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• 2000

본 연구는 영양분야의 전문 웹사이트로서 인터넷 상에서 이용할 수 있는 영양평가 시스템을 개발하기 위하여 수행되었다. 프로그램의 구성은 표준체중 및 열량필요량 자료, 식품 및 음식의 영양소 함량, 영양소별 20순위 식품, 식사섭취자료, 한국인 영양권장량 자료 등을 데이터베이스로 하여 사용자의 신체계측치와 활동정도에 따른 비만도 및 열량필요량의 분석과 섭취한 음식에 대하여 영양섭취상태를 평가받고 영양소별 함유량이 높은 식품과 음식에 대한 열량 및 영양소의 정보를 제공받을 수 있도록 웹 페이지 형식으로 만들어졌으며, 사용자는 인터넷 사이트로 들어가 자신의 이름, 성별, 나이, 키, 체중 및 활동정도를 입력함으로서 자신의 체중범위, 표준체중, 체격지수, 비만도, 기초대사량, 1일 열량필요량 및 이들의 섭취열량과의 과부족을 비교 평가한 자료를 얻을수 있으며, 만약 사용자가 비만이라면 체중을 감소하기 위한 1일 열량필요량도 얻을 수 있다. 또한 사용자는 음식입력 항목을 선택하여 날짜별, 식사별로 자신이 하루동안 섭취한 음식 및 섭취량 등을 입력하고 영양섭취상태를 클릭하면 식사섭취상태의 진단과 평가를 받을 수 있다. 즉 열량과 각 영양소에 대한 하루의 섭취량 및 아침, 점심, 저녁 및 간식의 섭취량이 분석되어지며 이들중 권장량이 정해진 영양소는 다시 사용자의 섭취량에 대한 권장량광의 비율을 그래프로 나타냄으로서 섭취된 영양소의 과부족을 쉽게 평가받을 수 있다. 지방질 역시 구성지방산과 콜레스테롤의 섭취 상태가 분석되어 이들의 표준섭취비율과 비교해 제시됨으로서 그릇된 섭취형태를 평가받을 수 있다. 이 밖에 식사별 열량영양소 구성비가 표준섭취비율과 비교 평가되어 그래프로 나타나며 급원식품에 대한 영양소 정보를 줄 수 있는 식품군별 영양소 섭취상태와 동식물성 식품 섭취상태도 평가되어진다. 따라서 본 프로그램은 인터넷을 이용하여 누구라도 자신의 영양섭취상태를 평가받고 과부족이 되기 쉬운 영양소의 급원 식품과 음식에 대한 영양정보도 제공받을 수 있도록 할 뿐 아니라 식이요법을 필요로 하는 질환의 영양상담을 위한 기본 프로그램으로 활용될 수 있도록 하는데 그 의의가 있다.

• Journal of the Korean Society of Food Science and Nutrition
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• v.31 no.5
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• pp.847-885
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• 2002

The purpose of this study was to develop a web-based internet program for nutritional assessment and diet Prescription by renal diseases. Renal diseases were classified by nephrotic syndrome, renal failure, hemodialysis and peritoneal dialysis. The system consisted of five parts according to their functions and contents. The first part is to assess the general health status such as body weight, obesity index, basal metabolic rate and total energy requirement by the input of age, sex, height, weight and degree of activity. The second part was designed to investigate dietary history of patient, that is, to find out his inappropriate dietary habit and give him some suggestions for appropriate dietary behavior by investigating his dietary history. This part also offers the diet and nutrition management by personal status with renal disease, and the information for food selection, snacks, convenience foods, dine-out, behavioral modification, cooking methods, food exchange lists and terms. The third part is evaluating their energy and nutrients intake by comparing with recommended dietary allowance for Koreans or standardized data for patient with renal disease. In this part, it is also analyzing energy and nutrients of food consumed by food group and meals, and evaluating the status of nutrient intake. The fort]1 one, a major part of the system, is implementing the diet and menu planning by using food exchange lists. This Part Provides the patient with menus lists and I day menu suitable to his weight, activity and the status of renal disease. The fifth part is providing information on energy and nutrients of foods and drinks, and top 20 foods classified by nutrients. These results are finally displayed as tabular forms and graphical forms on the computer screen.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.158-168
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• 2024

There is hardly any person in modern times who has not taken soft drinks instead of drinking water. The rate of people taking soft drinks being surprisingly high, researchers around the world have cautioned from time to time that these drinks lead to weight gain, raise the risk of non-communicable diseases and so on. Therefore, in this work an image-based tool is developed to monitor the nutritional information of soft drinks by using deep convolutional neural network with transfer learning. At first, visual saliency, mean shift segmentation, thresholding and noise reduction technique, collectively known as 'pre-processing' are adopted to extract the location of drinks region. After removing backgrounds and segment out only the desired area from image, we impose Discrete Wavelength Transform (DWT) based resolution enhancement technique is applied to improve the quality of image. After that, transfer learning model is employed for the classification of drinks. Finally, nutrition value of each drink is estimated using Bag-of-Feature (BoF) based classification and Euclidean distance-based ratio calculation technique. To achieve this, a dataset is built with ten most consumed soft drinks in Bangladesh. These images were collected from imageNet dataset as well as internet and proposed method confirms that it has the ability to detect and recognize different types of drinks with an accuracy of 98.51%.