• Journal of Nutrition and Health
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• v.53 no.6
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• pp.688-701
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• 2020

Purpose: This study was performed to evaluate the importance and satisfaction of the selective attributes of delivery food and to analyze the factors affecting customer satisfaction. Methods: A total of 574 responses were collected from customers who had ordered delivery food for data analysis. Statistical analyses were conducted using the SPSS program (ver. 25.0) for frequency analysis, χ2 tests, t-test, factor analysis, Pearson correlation, multiple regression analysis, and Importance-Performance Analysis (IPA). Results: The importance of delivery food selection attributes was higher in the order of 'hygiene control level (4.72)', 'taste of food (4.64)', and 'delivery accuracy (4.40)'. Satisfaction assessment was higher in the order of 'taste of food (4.32)', 'delivery accuracy (4.26)', and 'convenience of using the delivery app (4.21)'. According to the results of IPA, items that were priorities for improvement were charges for delivery, discount offers, sufficient description of the menu, and rapid handling of customer complaints. On an average, overall customer satisfaction score of delivery food was 4.01 out of 5 points. Additionally, five satisfaction factors were extracted by exploratory factor analysis. According to the results of multiple regression analysis, quality of delivery platform (p < 0.001), quality of delivery service (p < 0.001), convenience and diversity (p < 0.001), quality of delivery food (p < 0.001), and health and safety (p < 0.001) had significant positive effects on overall customer satisfaction. Conclusion: To increase customer satisfaction among delivery food customers, restaurant or delivery platform managers should consistently improve not only the quality of the delivery platform but also the quality of the delivery food and service.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.283-290
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• 2022

In this study, an IoT inspection system that can be linked with a server was developed using a gas timer and ESP-01 Wi-Fi module installed on a gas valve in the home. The server environment of the gas leak IoT inspection system was installed with APM (Apache, PHP, MySQL) to collect gas pressure data by generation so that leakage checks could be performed. In order to control the gas leak IoT inspection system, the app inventory was used to manage the gas leak check value in real time. In addition, user convenience has been enhanced so that membership management, WiFi settings, and leakage check values can be checked through mobile apps. In order to manage subscribers by region, the user list was checked by logging in in in the administrator mode so that the information on whether or not the leak test was conducted and the results could be provided. In addition, when the user presses the gas leak check button, the pressure is automatically checked, and the measured value is stored in the server, and when a gas leak occurs, the leakage check is performed after alarm and repair so that it can be used if normal. In addition, in order to prevent overlapping membership, membership management can be performed based on MAC addresses.

• Journal of Ginseng Research
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• v.47 no.3
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• pp.458-468
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• 2023

Background: As a complication of Type II Diabetes Mellitus (T2DM), the etiology, pathogenesis, and treatment of cognitive dysfunction are still undefined. Recent studies demonstrated that Ginsenoside Rg1 (Rg1) has promising neuroprotective properties, but the effect and mechanism in diabetes-associated cognitive dysfunction (DACD) deserve further investigation. Methods: After establishing the T2DM model with a high-fat diet and STZ intraperitoneal injection, Rg1 was given for 8 weeks. The behavior alterations and neuronal lesions were judged using the open field test (OFT) and Morris water maze (MWM), as well as HE and Nissl staining. The protein or mRNA changes of NOX2, p-PLC, TRPC6, CN, NFAT1, APP, BACE1, NCSTN, and Ab1-42 were investigated by immunoblot, immunofluorescence or qPCR. Commercial kits were used to evaluate the levels of IP3, DAG, and calcium ion (Ca²⁺) in brain tissues. Results: Rg1 therapy improved memory impairment and neuronal injury, decreased ROS, IP3, and DAG levels to revert Ca²⁺ overload, downregulated the expressions of p-PLC, TRPC6, CN, and NFAT1 nuclear translocation, and alleviated Aβ deposition in T2DM mice. In addition, Rg1 therapy elevated the expression of PSD95 and SYN in T2DM mice, which in turn improved synaptic dysfunction. Conclusions: Rg1 therapy may improve neuronal injury and DACD via mediating PLC-CN-NFAT1 signal pathway to reduce Aβ generation in T2DM mice.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.281-290
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• 2020

With the spread of smartphones, services that want to use personalized data are increasing. In particular, healthcare-related services deal with a variety of data, and data visualization techniques are used to effectively show this. As data visualization techniques are used, interactions in visualization are also naturally emphasized. In the PC environment, since the interaction for data visualization is performed with a mouse, various filtering for data is provided. On the other hand, in the case of interaction in a mobile environment, the screen size is small and it is difficult to recognize whether or not the interaction is possible, so that only limited visualization provided by the app can be provided through a button touch method. In order to overcome the limitation of interaction in such a mobile environment, we intend to enable data visualization interactions through conversations with chatbots so that users can check individual data through various visualizations. To do this, it is necessary to convert the user's query into a query and retrieve the result data through the converted query in the database that is storing data periodically. There are many studies currently being done to convert natural language into queries, but research on converting user queries into queries based on visualization has not been done yet. Therefore, in this paper, we will focus on query generation in a situation where a data visualization technique has been determined in advance. Supported interactions are filtering on task x-axis values and comparison between two groups. The test scenario utilized data on the number of steps, and filtering for the x-axis period was shown as a bar graph, and a comparison between the two groups was shown as a line graph. In order to develop a natural language processing model that can receive requested information through visualization, about 15,800 training data were collected through a survey of 1,000 people. As a result of algorithm development and performance evaluation, about 89% accuracy in classification model and 99% accuracy in query generation model was obtained.

• Radiation Oncology Journal
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• v.24 no.2
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• pp.110-115
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• 2006

Purpose: This study was performed to determine the prognostic factors influencing relapse pattern, overall and disease-free survival in patients treated with postoperative radiotherapy for endometrial carcinoma. Materials and Methods: The records of 54 patients with endometrial adenocarcinoma treated postoperative radiotherapy at Pusan National University Hospital between April 1992 and May 2003 were reviewed retrospectively. Median age of the patients was 55 (range $35{\sim}76$). The distribution by surgical FIGO stages were 63.0% for 0Stage I, 14.8% for Stage II, 22.2% for Stage III. All patients received postoperative external radiotherapy up to $41.4{\sim}54Gy$ (median: 50.4 Gy). Additional Intravaginal brachytherapy was app led to 20 patients (37.0% of all). Median follow-up time was 35 months ($5{\sim}115$ months). Significant factors of this study: histologic grade, Iymphovascular space invasion and myometrial invasion depth were scored (GLM score) and analyzed. Survival analysis was peformed using Kaplan-Meier method. The log-rank test was used for univariate analysis and the Cox regression model for multivariate analysis. Results: 5-year overall and disease-free survival rates were 87.7% and 871%, respectively. Prognostic factors related with overall and disease-free survival were histologic grade, Iymphovascular space invasion and myometrial invasion according to the univariate analysis. According to the multivariate analysis, Iymphovascular space invasion was associated with decreased disease-free survival. GLM score was a meaningful factor affecting overall and disease-free survival (p=0.0090, p=0.0073, respectively) and distant recurrence (p=0.0132), which was the sum of points of histologic grade, Iymphovascular space Invasion and myometrial invasion. Total failure rate was 11% with 6 patients. Relapse sites were 2 para-aortic Iymph nodes, 2 lungs, a supraclavicular Iymph node and a vagina. Conclusion: The prognosos in patients with endometrial carcinoma treated by postoperative radiotherapy was closely related with surgical histopathology. If further explorations confirm the system of prognostic factors in endometrial carcinoma, it will help us to predict the progression pattern and to manage.

• Child Health Nursing Research
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• v.7 no.1
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• pp.118-140
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• 2001

The purpose of this study was to measure the effect of safety education program in preschool children for accident prevention and improve their health through more systematic method. Data were collected from 584 preschoolers(247 preschooler are assigned to experimental group and 337 preschoolers are assinged to control group) from 4 to 6 years old using APP paper test which consists of questions and drawings. To experimental group, safety education were done 4 times within the time of 30 minutes per 1 time using education books, drawings, OHP. The findings of this study are as follows: 1. There were significant difference in movement(χ²=18.732, p=.0000), behavioral character(χ²=27.785, p=.000), synthetic judgement(χ²=12.02, p=0.002). So, safety education program have effect on preschooler. 2. In the accident proneness on preschooler between experimental group and control group according to general characteristics, it proved significant difference in the case of accident prevention education were done, reasoning power(χ²=10.48, p=.005), movement speed(χ²=7.341, p=.025) and behavioral character(χ²=18.86, p=.000), in the case of housing pattern is private house(individual house, yard?), reasoning power(χ²=6.683, p=.035), movement speed(χ²=12.76, p= .002) and behavioral character(χ²=12.24, p=.002), in the case of housing pattern is mixed-type, movement speed(χ²=6.935, p= .031) and behavioral character(χ²=10.816, p=.004), in the case of housing pattern is over six stories, movement speed(χ²=7.543, p=.023), in the case of subjects' age is 4 years old, movement speed(χ²=16.5, p= .000) and behavioral character(χ²=12.18, p=.002), in the case of subjects' age is 5 years old, movement speed(χ²=7.519, p= .023), watchfulness(χ²=6.372, p=.041), behavioral character(χ²=14.74, p=0.001) and synthetic judgement(χ²=14.5, p=.001), in the case of subjects' sex is male, life safety(χ²=6.406, p=.041), movement speed(χ²=22.86, p= .000), behavioral character(χ²=13.72, p= .001) and synthetic judgement(χ²=13.82, p=.001), in the case of subjects' sex is female, reasoning power(χ²=12.57, p=.002) and behavioral character(χ²=13.16, p= .001), in the case of childrens have past accidental experience, traffic safety(χ²= 6.683, p=.035), in the case of childrens have no past accidental experience, reasoning power(χ²=8.384, p=.015), movement speed(χ²=20.6, p=.000), behavioral character(χ²=25.1, p=.000) and synthetic judgement(χ² =10.79, p=.005), in the case of children's order is first, reasoning power(χ²=11.15, p=.004), movement speed(χ²=11.92, p= .003) and behavioral character(χ²=7.003, p=.030), in the case of children's order is second, movement speed(χ²=6.694, p= .035), behavioral character(χ²=26.9, p= .000) and synthetic judgement(χ²=14.3, p= .001), in the case of nuclear family, reasoning power(χ²=8.777, p=.012), movement speed(χ²=19.0, p=.000), behavioral character (χ²=26.4, p=0.000) and synthetic judgement (χ²=9.999, p=.007), in the case of mothers' school career is under high school graduate, life safety(χ²=8.023, p=.018), movement speed(χ²=10.99, p=.004) and behavioral character(χ²=6.777, p=.034), in the case of mothers' school career is beyond college graduate, reasoning power(χ²=6.717, p= .035), movement speed(χ²=8.963, p=.011), behavioral character(χ²=25.03, p=.000) and synthetic judgement(χ²=15.19, p=.001), in the case of mothers' age ranged 31-34, movement speed(χ²=12.29, p=.002) and behavioral character(χ²=14.17, p=.001), in the case of mothers' age ranged 35-39, movement speed(χ²=9.859, p=.007), behavioral character(χ²=9.095, p=.011) and synthetic judgement(χ²=7.810, p=.020), in the case of mothers' age is over 40, life safety(χ² =5.593, p=.025), in the case of mothers' job is full-time, traffic safety(χ²=6.032, p=.049) and reasoning power(χ²=8.502, p= .014), in the case of mothers' job is part- time., movement speed(χ²=10.99, p=.004) and behavioral character(χ²=7.895, p= .019), in the case of mothers have no job, movement speed(χ²=6.410, p=.041), movement stability(χ²=6.879, p=.032), behavioral character(χ²=27.72, p=.000) and synthetic judgement(χ²=18.11, p=.000). The difference of accident proneness between experimental group and control group according to general characterists, it also showed that there were significant difference in behavioral character compared to other area.. From this findings, we can guess that safety education program change and guide preschoolers' behavioral character to desirable direction.

• Journal of Nutrition and Health
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• v.52 no.5
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• pp.488-500
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• 2019

Purpose: This study examined the effects of a mobile app-based program to reduce the dietary sugar intake according to the stages of the behavioral change in dietary sugar reduction in female college students. Methods: The program used in this study can monitor the dietary sugar intake after recording the dietary intake and provide education message for the reduction of dietary sugar intake. In an eight-week pre-post intervention study, 68 female college students were instructed to record all the food they consumed daily and received weekly education information. At pre-post intervention, the subjects were asked to answer the questionnaire about sugar-related nutrition knowledge, sugar-intake behavior, and sugar-intake frequency. For statistical analysis, ANOVA and a paired t-test were used for comparative analysis according Precontemplation (PC), Contemplation Preparation (C P), and A M (Action Maintenance) stage. Results: Significant differences were observed in the frequency of snacking, experience of nutrition education, and preference for sweetness according to the stages of behavior change in dietary sugar reduction. After finishing an intervention, the sugar-related nutrition knowledge score was increased significantly in the stages of Precontemplation (PC) and Contemplation Preparation (C P). The score of the sugar intake behavior increased significantly in all stages. The intake frequency of chocolate, muffins or cakes, and drinking yogurt decreased significantly in the PC stage and the intake frequency of biscuits, carbonated beverages, and fruit juice decreased significantly in the C P stage. Subjects in the PC and C P stages had an undesirable propensity in nutrition knowledge, sugar-intake behavior, and sugar-intake frequency compared to the A M stage, but this intervention improved significantly their nutrition knowledge, sugar-intake behavior, and sugar-intake frequency. Conclusion: This program can be an effective educational tool in the stages of PC and C P, and is expected to further increase the usability and sustainability of mobile application if supplemented appropriately to a health platform program.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.30-43
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• 2018

Many studies have been carried out to retrieve images using colors, shapes, and textures which are characteristic of images. In addition, there is also progress in research related to the disease images of the crop. In this paper, to be a help to identify the disease occurred in crops grown in the agricultural field, we propose a similarity-based crop disease search system using the diseases image of horticulture crops. The proposed system improves the similarity retrieval performance compared to existing ones through the combination descriptor without using a single descriptor and applied the weight based calculation method to provide users with highly readable similarity search results. In this paper, a total of 13 Descriptors were used in combination. We used to retrieval of disease of six crops using a combination Descriptor, and a combination Descriptor with the highest average accuracy for each crop was selected as a combination Descriptor for the crop. The retrieved result were expressed as a percentage using the calculation method based on the ratio of disease names, and calculation method based on the weight. The calculation method based on the ratio of disease name has a problem in that number of images used in the query image and similarity search was output in a first order. To solve this problem, we used a calculation method based on weight. We applied the test image of each disease name to each of the two calculation methods to measure the classification performance of the retrieval results. We compared averages of retrieval performance for two calculation method for each crop. In cases of red pepper and apple, the performance of the calculation method based on the ratio of disease names was about 11.89% on average higher than that of the calculation method based on weight, respectively. In cases of chrysanthemum, strawberry, pear, and grape, the performance of the calculation method based on the weight was about 20.34% on average higher than that of the calculation method based on the ratio of disease names, respectively. In addition, the system proposed in this paper, UI/UX was configured conveniently via the feedback of actual users. Each system screen has a title and a description of the screen at the top, and was configured to display a user to conveniently view the information on the disease. The information of the disease searched based on the calculation method proposed above displays images and disease names of similar diseases. The system's environment is implemented for use with a web browser based on a pc environment and a web browser based on a mobile device environment.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.864-881
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• 2021

Purpose: This study aims is to provide a total care solution preventing disaster based on Big Data and AI technology and to service safety considered by individual situations and various risk characteristics. The purpose is to suggest a method that customized comprehensive index services to prevent and respond to safety accidents for calculating the living safety index that quantitatively represent individual safety levels in relation to daily life safety. Method: In this study, we use method of mixing AHP(Analysis Hierarchy Process) and Likert Scale that extracted from consensus formation model of the expert group. We organize evaluation items that can evaluate life safety prevention services into risk indicators, vulnerability indicators, and prevention indicators. And We made up AHP hierarchical structure according to the AHP decision methodology and proposed a method to calculate relative weights between evaluation criteria through pairwise comparison of each level item. In addition, in consideration of the expansion of life safety prevention services in the future, the Likert scale is used instead of the AHP pair comparison and the weights between individual services are calculated. Result: We obtain result that is weights for life safety prevention services and reflected them in the individual risk index calculated through the artificial intelligence prediction model of life safety prevention services, so the comprehensive index was calculated. Conclusion: In order to apply the implemented model, a test environment consisting of a life safety prevention service app and platform was built, and the efficacy of the function was evaluated based on the user scenario. Through this, the life safety index presented in this study was confirmed to support the golden time for diagnosis, response and prevention of safety risks by comprehensively indication the user's current safety level.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.171-180
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• 2023

The three major sleep disorders in Korea are snoring, sleep apnea, and insomnia. Lack of sleep is the root of all diseases. Some of the most serious potential problems associated with sleep deprivation are cardiovascular problems, cognitive impairment, obesity, diabetes, colitis, prostate cancer, etc. To solve these problems, the Korean government provided low-cost national health insurance benefits for polysomnography tests in July 2018. However, insomnia patients still have problems getting treated in terms of time, space, and economic perspectives. Therefore, it would be better for insomnia patients to be allowed to test at home. The measuring device can measure six biosignals (eye movement, tossing and turning, body temperature, oxygen saturation, heart rate, and audio). A gyroscope sensor (MPU9250, InvenSense, USA) was used for eye movement, tossing, and turning. The input range of the sensor was in 258°/sec to 460°/sec, and the data range was in the input range. Body temperature, oxygen saturation range, and heart rate were measured by a sensor (MAX30102, Analog Devices, USA). The body temperature was measured in 30 ℃ to 45 ℃, and the oxygen saturation range was 0% for the unused state and 20 % to 90 % for the used state. The heart rate measurement range was in 40 bpm to 180 bpm. The measurement of audio signal was performed by an audio sensor (AMM2742-T-R, PUIaudio, USA). The was -42 dB ±1 dB frequency range was 20 Hz to 20 kHz. The measured data was successfully received in wireless network conditions. The system configuration was consisted of a PC and a mobile app for bio-signal measurement and data collection. The measured data was collected by mobile phones and desktops. The data collected can be used as preliminary data to determine the stage of sleep and perform the screening function for sleep induction and sleep disturbances. In the future, this convenient sleep measurement device could be beneficial for treating insomnia.