• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.55-75
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• 2010

Sequential pattern mining aims to discover interesting sequential patterns in a sequence database, and it is one of the essential data mining tasks widely used in various application fields such as Web access pattern analysis, customer purchase pattern analysis, and DNA sequence analysis. In general sequential pattern mining, only the generation order of data element in a sequence is considered, so that it can easily find simple sequential patterns, but has a limit to find more interesting sequential patterns being widely used in real world applications. One of the essential research topics to compensate the limit is a topic of weighted sequential pattern mining. In weighted sequential pattern mining, not only the generation order of data element but also its weight is considered to get more interesting sequential patterns. In recent, data has been increasingly taking the form of continuous data streams rather than finite stored data sets in various application fields, the database research community has begun focusing its attention on processing over data streams. The data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. In data stream processing, each data element should be examined at most once to analyze the data stream, and the memory usage for data stream analysis should be restricted finitely although new data elements are continuously generated in a data stream. Moreover, newly generated data elements should be processed as fast as possible to produce the up-to-date analysis result of a data stream, so that it can be instantly utilized upon request. To satisfy these requirements, data stream processing sacrifices the correctness of its analysis result by allowing some error. Considering the changes in the form of data generated in real world application fields, many researches have been actively performed to find various kinds of knowledge embedded in data streams. They mainly focus on efficient mining of frequent itemsets and sequential patterns over data streams, which have been proven to be useful in conventional data mining for a finite data set. In addition, mining algorithms have also been proposed to efficiently reflect the changes of data streams over time into their mining results. However, they have been targeting on finding naively interesting patterns such as frequent patterns and simple sequential patterns, which are found intuitively, taking no interest in mining novel interesting patterns that express the characteristics of target data streams better. Therefore, it can be a valuable research topic in the field of mining data streams to define novel interesting patterns and develop a mining method finding the novel patterns, which will be effectively used to analyze recent data streams. This paper proposes a gap-based weighting approach for a sequential pattern and amining method of weighted sequential patterns over sequence data streams via the weighting approach. A gap-based weight of a sequential pattern can be computed from the gaps of data elements in the sequential pattern without any pre-defined weight information. That is, in the approach, the gaps of data elements in each sequential pattern as well as their generation orders are used to get the weight of the sequential pattern, therefore it can help to get more interesting and useful sequential patterns. Recently most of computer application fields generate data as a form of data streams rather than a finite data set. Considering the change of data, the proposed method is mainly focus on sequence data streams.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.359-366
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• 2016

In order to provide useful services for user in ubiquitous environment, a technique that can get the helpful information considering user activity and preference is needed and also user's interest actually changes as time passes. Therefore, the discovering method which reflects the concern degree of service information is needed. In this paper, we present the finding method of frequent pattern with dynamic weight on individual item based on service ontology we design. Our method can be applied to provide interested service information for user depending on context.

• Journal of KIISE:Databases
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• v.36 no.5
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• pp.341-351
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• 2009

Recently high utility pattern (HUP) mining is one of the most important research issuer in data mining since it can consider the different weight Haloes of items. However, existing mining algorithms suffer from the performance degradation because it cannot easily apply Apriori-principle for pattern mining. In this paper, we introduce new high utility pattern mining approach by using a prefix-tree as in FP-Growth algorithm. Our approach stores the weight value of each item into a node and utilizes them for pruning unnecessary patterns. We compare the performance characteristics of three different prefix-tree structures. By thorough experimentation, we also prove that our approach can give performance improvement to a degree.

• Journal of Digital Contents Society
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• v.19 no.3
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• pp.471-477
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• 2018

As time changes, users change their interest. In this paper, we propose a method to provide suitable service for users by dynamically weighting service interests in the context of age, timing, and seasonal changes in ubiquitous environment. Based on the service history data presented to users according to the age or season, we also offer useful services by continuously adding the most recent service rules to reflect the changing of service interest. To do this, a set of services is considered as a transaction and each service is considered as an item in a transaction. And also we represent the association of services in a graph and extract frequent service items that refer to the latest information services for users.

• Journal of the Korean Society of School Health
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• v.27 no.3
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• pp.121-129
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• 2014

Purpose: The purpose of this study were to compare general characteristic of high school girls according to menarcheal age and to investigate the factors associated with the menarcheal age of high school girls. Methods: This study utilized the data of the 2013 Korean Youth Risk Behavior Web-based Survey (KYRBWS). The sample included 18,077 high school girls who experienced menarche. The questionnaires used for this study assessed menacheal age, grade, place of residence, family affluence, height, weight, diet pattern, physical activity, sleep duration, and stress level. Data was analyzed using the complex sample analysis (${\chi}^2$-test, ANOVA and multiple regression analysis). Results: Higher BMI, frequent vegetable consumption, short sleep duration, and higher stress level were associated with an earlier menarcheal age among high school girls. Conclusion: The findings of this study indicate intervention strategies to control the timing of menarche.

• Journal of the Korean Society of Food Culture
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• v.25 no.4
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• pp.366-377
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• 2010

We surveyed 553 middle school students living in Incheon using questionnaires to compare their food behaviors and snack intake patterns according to weight groups based on BMI. Mean BMI was 20.3 for males and 19.6 for females. The rate of underweight, normalweight and overweight students was 33.3, 51.7, and 15.0%, respectively. Compared to the other two groups, the overweight students perceived their body shape more accurately (p<0.01). Regarding the reasons for skipping dinner, the most frequent answer by the underweight students was 'because of snacks', while that of the overweight students was 'to lose weight' (p<0.01). The normalweight students were found to eat a Korean traditional type breakfast more frequently than the other weight groups (p<0.05). The overweight female group was more likely to overeathabitually, whereas the normalweight and underweight groups tended to overeat when they were under stress (p<0.05). As for the amount of the snack intake, the overweight male students replied that they eat quite a lot of snacks. As a conclusion, the problems found in the underweight group were unbalanced diet and the disturbance of regular meal patterns due to inappropriate snack intake. The problems shown in the overweight group were overeating due to habit or stress, fast eating speed and large amount of snack intake.

• Korean Journal of Community Nutrition
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• v.8 no.4
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• pp.485-494
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• 2003

In order to investigate the ramyeon intake patterns, food value recognition, and their effects on blood pressure and blood lipid levels, a total of 385 male students aged 13- 15 years living in rural area were sampled randomly, and they were surveyed using questionnaire. Blood pressure and fasting serum lipids levels of 123 subjects selected among the total were determined. Of the total subjects 80.3％ either liked or liked very much ramyeon and 42.2％ of them were eating ramyeon from 1 to 2 times a week,21.1％ 5-6 times a week, while 11.7％ more than once a day, and 13.1％ less than once a month. They took ramyeon from one (56.8％) to two (25.4％) packs each time. Two-third of subjects consumed entire ramyeon soup or more than half of it. Mostly they added egg or onion to ramyeon and took along with kimchi, cooked rice, danmuji, or dried laver. The food value recognition score about ramyeon was 41.33 out of 100 full grade. Comparing to underweight or normal weight subjects, overweight students tended to take ramyeon more frequently when playing with friends and tended to consume less soup of ramyeon. There was a significant negative correlation between ramyeon intake frequencies and HDL-cholesterol levels (r = -.223 p < .05). Moreover, among the normal body weight students (n = 72) adjusted with relative weight, ramyeon intake frequencies showed not only a significant negative correlation with HDL-cholesterol level (r = -.244 p < .05), but also significant positive correlations with atherogenic index (r : .249 p < .05) and systolic blood pressure (r : .259 p < .05) . These results suggested that frequent intake of ramyeon with limited sidedishes as a whole meal might have negative influences on blood pressure and serum lipid levels. Nutrition education is needed to have correct food value recognition and proper consumption of ramyeon along with the balanced diet. (Korean J Community Nutrition 8(4) : 485-494, 2003)

• Journal of Preventive Medicine and Public Health
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• v.27 no.3 s.47
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• pp.465-473
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• 1994

This study was carried out to evaluate the relations between sociodemographic, work-related factors and health related behaviors in a group of 1,042 workers in Taejeon and Chungnam area. The results were as followings: The older workers took more irregularly meals, more cigarette and more alcohol than the younger. Men had more appropriate sleeping time, more regular exercise than women, but more frequent alcohol consumption and cigarette smoking. The married had more regular sleeping habit than the unmarried. The group of married were smoking more and obese. In view of monthly income which represent the socioeconomic state of workers, the group of more than 1 million won had more frequent alcohol ingestion, more heavier body weight than another group of less than 1 million won. Workers having their work hours exceed 9 hours had inappropriate sleep duration, and shift workers took more irregularly meals. The group having poor self-rated health status showed more regular diet, exercise and overweight. Workers recently experienced chronic illness were more overweight and lesser smokers. Above results showed that the health related behaviors were related to the sociodemographic characteristics and occupation-related characteristics. The study for relationship between variant factors affecting health behavior and disease or mortality is need and it should be emphasized that the publicity and education of health related behavior for industrial workers is necessary.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.165-167
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• 2022

The proportion of cat cats among companion animals has been increasing at an average annual rate of 25.4% since 2012. Cats have strong wildness compared to dogs, so they have a characteristic of hiding diseases well. Therefore, when the guardian finds out that the cat has a disease, the disease may have already worsened. Symptoms such as anorexia (eating avoidance), vomiting, diarrhea, polydipsia, and polyuria in cats are some of the symptoms that appear in cat diseases such as diabetes, hyperthyroidism, renal failure, and panleukopenia. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia (drinking a lot of water), polyuria (a large amount of urine), and frequent urination (urinating frequently) more quickly. In this paper, 1) Efficient version of DeepLabCut for posture prediction running on an artificial intelligence server, 2) yolov4 for object detection, and 3) LSTM are used for behavior prediction. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the main server system.

• Journal of the Korean Dietetic Association
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• v.7 no.3
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• pp.248-257
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• 2001

The purpose of this study was to investigate the effect of smoking on dietary behavior and nutrient intake among the male college students. The subjects were divided into three groups; non smoker(n=84), moderate smoker(n=68), and heavy smoker(n=89) according to duration and degree of smoking. And they were asked for general characteristics, life style, eating pattern, food frequency, and nutrient intake using questionnaire and 24-hr recall method. The mean age, height, weight, and BMI of the subjects were 26.2$\pm$6.2 years, 173.3$\pm$5.3㎝, 66.5$\pm$9.3㎏, and 22.1$\pm$2.7㎏/$m^2$, respectively. The type of residence and frequency of alcohol drinking were significantly different among three groups; the frequency of self-boarding and alcohol drinking in moderate smoker and heavy smoker was higher than those in non smoker. Comparing with non smoker, the frequency of skipping meals, especially breakfast and supper, was significantly high in moderate smoker and heavy smoker. The most common reason why heavy smoker skipped meals was ‘eating habit’, while it was ‘lack of time’ in non smoker. The results showed that the heavy smoker tended to drink coffee more often compared to the other two groups. There were no significant differences in nutrient intakes among three groups. In conclusion, heavy smoking students have unhealthy dietary behaviors in terms of high frequency of alcohol drinking, habit of skipping meals and frequent coffee drinking showing a strong need of proper education on smoking withdrawal and meal practice for them.