• Journal of Nutrition and Health
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• v.49 no.2
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• pp.88-98
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• 2016

Purpose: We recruited 118 women in their early 20's to examine the relationship between sodium intake and salty taste thresholds and preference. We also examined the association of salty taste preference with sodium-related dietary behaviors and major dishes contributing to sodium intake. Methods: Daily sodium intake was estimated using a 127-item dish-frequency questionnaire. Salty taste thresholds and preference were measured using rating scales using water solution of NaCl and a self-administered questionnaire based on a Likert scale, respectively. Results: Salty taste preference showed positive correlation with daily sodium intake and sodium intake-increasing behaviors, and inverse association with sodium intake-decreasing behaviors, including salt and soy sauce use at the table, the frequency of eating out and home delivery of foods, broth consumption of soup, stew or noodle soup, the use of ready-to-serve or processed foods, fresh vegetable intake, and the accommodating attitude toward bland food. Intake of sodium-contributing dishes, including ramen, spicy soft-tofu stew, radish kimchi, and dishes containing kimchi, also showed positive association with salty taste preference. Unexpectedly, detection and recognition thresholds of salty taste showed no association with salty taste preference, sodium intake, and sodium-related dietary behaviors. Conclusion: These findings suggest that salty taste preference could reflect sodium intake of individuals rather than thresholds of saltiness, and may be used as a simple and effective proxy for usual sodium intake.

• Journal of the Korean Dietetic Association
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• v.6 no.2
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• pp.125-135
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• 2000

Hypertension is a well-known degenerative disease whose prevalence rate increases with age. Management of high blood pressure is a critical concern in preventive strategies to reduce the morbidity and mortality for cardiovascular disease. The purpose of this study was to examine the dietary characteristics of hypertensive program participants, and to establish strategies based on their nutritional needs. Hypertensive patients were enrolled in the program in a public health center or in a local elderly center, at Suwon, in 1999-2000. Trained dietitians interviewed 62 enrollees(24-hour recall) and related variables. Mean body mass index of the subjects was 25.0kg/m². 30.7% of the subjects had a family history of hypertension. The majority of them ate regularly and partook of all available side dishes. They consumed grains and vegetables regularly, but seldom ate dairy products or food prepared with oil. Male enrollees frequently consumed more processed food and animal fat than did female enrollees(p<0.05). An analysis of the percentage of RDA(Recommended Dietary Allowances of Korea 1995) showed that but for ascorbic acid, enrollees consumed nutrients below the RDA. The food group intake pattern was not diverse, thus only 8.1% of enrollees consumed all food groups in a day. An analysis of eating attitude showed that 64.5% of enrollees always added salt to beef soup. Male enrollees showed low food-related self-efficacy compared to female enrollees, especially with reference to reduction of instant food intake(p<0.01), increase in vegetable intake(p<0.01), reduction of monosodium glutamate(MSG) intake(p<0.01). and not overeating(p<0.05). Their perceived barriers for participating in hypertension nutrition programs included lack of time, program necessity non-recognition, and program comprehension difficulty. These results suggest that nutrition education program necessity non-recognition, and program comprehension difficulty. These results suggest that nutrition education programs for community hypertensive patients should focus on increasing participant consumption of foods, expecially dairy products, and desirable eating attitudes. It also suggests that the program should consider should consider encouraging self-efficacy in changing eating behavior.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.10
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• pp.1243-1252
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• 2017

There are limited programs for low sodium intake based on the nutrition education model for housewives who cook family meals. The objective of this study was to evaluate the effects of model-based nutrition programs for low sodium intake among housewives residing in Seoul by incorporating social cognitive theory. A questionnaire survey before and after education was conducted on 140 housewives who participated in the 'Low Sodium Nutritional Education Program' delivered by a district public health center for 12 weeks from November 2015 to January 2016. The contents of the nutrition education program and program evaluation items were based on the action plans for 'Less Sodium Healthy Practice' suggested by the Ministry of Food and Drug Safety. The results show that program participants showed a lower preference for sodium, higher selection of low sodium dishes from restaurants or cafeteria if available, and increased awareness of the need of restaurants to serve low sodium dishes compared to before. In terms of behavioral changes, there were significant improvements in checking nutrition labeling and selection of foods with low sodium, use of low sodium food products, use of natural seasonings to reduce salt intake, and consumption of fast foods and processed foods. On the other hand, requesting less salty meals when ordering and introducing restaurants or cafeterias with healthy and low sodium menus turned out to be difficult to put into practice. In conclusion, the nutrition education program for sodium intake reduction for housewives was effective in increasing knowledge, environment recognition, and behaviors related to low sodium intake but not behaviors related to physical environmental factors. Therefore, further nutrition education programs and practices for sodium intake reduction should be comprehensively implemented with improvement of physical environments for low sodium intake.

• Nutrition Research and Practice
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• v.6 no.5
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• pp.466-473
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• 2012

The change in people's dietary life has led to an increase in an intake of processed foods and food chemicals, raising awareness about taste education for preschoolers whose dietary habits start to grow. This study aims to evaluate the effectiveness and satisfaction of parents and childcare personnel after developing a taste education program and demonstrating it in class. A part of the curriculum developed by Piusais and Pierre was referred for the program. After educating 524 preschoolers in child care facilities in Seoul, a satisfaction survey was conducted on the program. The data in this study were analyzed using SPSS 14.0. Statistical analysis was conducted based on the frequency after collecting the data. Mean ${\pm}$ SD used to determine satisfaction with taste education, with preferences marked on a five-point scale and the alpha was set at 0.05. The program includes five teachers' guides with subjects of sweetness, saltiness, sourness, bitterness and harmony of flavor, and ten kinds of teaching tools. For the change in parents' recognition of the need for taste education based on five-point scale, the average of $4.06{\pm}0.62$ before the program has significantly increased to $4.32{\pm}0.52$ (P < 0.01). Regarding the change in the preferences for sweetness, saltiness, sourness, and bitterness, the average has increased to $3.83{\pm}0.61$, $3.62{\pm}0.66$, $3.64{\pm}0.66$, and $3.56{\pm}0.75$ respectively. In an evaluation of instructors in child care facilities, the average scores for education method, education effect, education contents and nutritionists, and teaching tools were at $4.15{\pm}0.63$, $3.91{\pm}0.50$, $4.18{\pm}0.50$, and $3.80{\pm}0.56$ respectively. In addition, the need for a continuous taste education scored $4.42{\pm}0.67$. This program has created a positive change in preschoolers' dietary life, therefore the continuation and propagation of the taste education program should be considered.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.