• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.927-934
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• 2021

AI(Artificial intelligence) is gradually taking up a large part of our lives, and the pace of AI development is accelerating. It is called ACT that develop students' computational thinking in the way artificial intelligence learns. Among ACTs, pattern recognition is an essential factor in efficiently solving problems. Pattern analysis is part of the pattern recognition process. In fact, Netflix's personalized movie recommendation service and what it named Covid-19 after repeated symptoms are all the results of pattern analysis. While the importance of ACT, including pattern recognition, is highlighted, software education for kindergarten and elementary school lower grades is much insufficient compared to foreign countries. Therefore, this study aims to design and develop textbooks for the development of artificial intelligence-based computational thinking through pattern analysis for kindergarten students.

• Journal of Power Electronics
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• v.12 no.1
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• pp.1-9
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• 2012

This study investigates an application of the Hamming network-dual extended Kalman filter (DEKF) based on pattern recognition for high accuracy state-of-charge (SOC)/capacity estimation and state-of-health (SOH) prediction at various temperatures. The averaged nine discharging/charging voltage-temperature (DCVT) patterns for ten fresh Li-Ion cells at experimental temperatures are measured as representative patterns, together with cell model parameters. Through statistical analysis, the Hamming network is applied to identify the representative pattern that matches most closely with the pattern of an arbitrary cell measured at any temperature. Based on temperature-checking process, model parameters for a representative DCVT pattern can then be applied to estimate SOC/capacity and to predict SOH of an arbitrary cell using the DEKF. This avoids the need for repeated parameter measuremet.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.190-195
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• 2004

We propose a pattern classification algorithm using self-nonself discrimination principle of immune cells and apply it to DNA pattern classification problem. Pattern classification problem in bioinformatics is very important and frequent one. In this paper, we propose a classification algorithm based on the negative selection of the immune system to classify DNA patterns. The negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes ${\eta}$ groups of antigenic receptor for ${\eta}$ different patterns, these receptor groups can classify into ${\eta}$ patterns. We propose a pattern classification algorithm based on the negative selection in nucleotide base level and amino acid level. Also to show the validity of our algorithm, experimental results of RNA group classification are presented.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.623-634
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• 2016

Most of existing frequent pattern mining methods address time efficiency and greatly rely on the primary memory. However, in the era of big data, the size of real-world databases to mined is exponentially increasing, and hence the primary memory is not sufficient enough to mine for frequent patterns from large real-world data sets. To solve this problem, there are some researches for frequent pattern mining method based on disk, but the processing time compared to the memory based methods took very time consuming. There are some researches to improve scalability of frequent pattern mining, but their processes are very time consuming compare to the memory based methods. In this paper, we present PPFP as a novel disk-based approach for mining frequent itemset from big data; and hence we reduced the main memory size bottleneck. PPFP algorithm is based on FP-growth method which is one of the most popular and efficient frequent pattern mining approaches. The mining with PPFP consists of two setps. (1) Constructing an IFP-tree: After construct FP-tree, we assign index number for each node in FP-tree with novel index numbering method, and then insert the indexed FP-tree (IFP-tree) into disk as IFP-table. (2) Mining frequent patterns with PPFP: Mine frequent patterns by expending patterns using stack based PUSH-POP method (PPFP method). Through this new approach, by using a very small amount of memory for recursive and time consuming operation in mining process, we improved the scalability and time efficiency of the frequent pattern mining. And the reported test results demonstrate them.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.607-608
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• 2012

• The KIPS Transactions:PartB
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• v.14B no.1 s.111
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• pp.13-22
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• 2007

In this paper, we propose an audience counting method in an auditorium based on pattern comparison. The previous counting methods based on object detection can't exactly count the audience in real time because auditorium has coarse illumination condition and so many audiences. Therefore, in this paper, we count the audience in an auditorium with fixed seats by the method which the pattern from each reference seat is compared to the pattern from each input seat. Especially, to overcome limitations based on either illumination or noise, two pattern comparison methods are efficiently employed and combined. One is based on the amplitude projection, and the other is based on Walsh-Hadamard Kernel. Walsh-Hadamard Kernel has the characteristic which complements amplitude projection. Therefore, we ran achieve the accurate counting in the presence of coarse illumination and noise. The experimental results show that our method performs well on sequences of images acquired in an auditorium. We also verify a realistic possibility for other applications applying our method to the parking positioning system.

• Korean Journal of Community Nutrition
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• v.20 no.2
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• pp.87-95
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• 2015

Objectives: Maintaining a balanced diet and thus health is crucial for adolescents, and the first step for balanced diet practice is meal planning. Adolescents, however, find it difficult to plan their meals. This study thus was set out to design an easier way of planning meals for adolescent girls. Methods: A dish-based target pattern for adolescent girls was tabulated, and validity of this was examined. Meal plan applying a dish-based target pattern was prepared by 150 female middle school students, and nutritional adequacies of those meal plans were examined. Validity and adequacy were tested by energy content, energy contribution ratio, nutrient adequacy ratio (NAR), probability of nutrient inadequacy, index of nutritional quality (INQ) calculation. Results: A dish-based target pattern with 11 dish groups was validated for nutritional adequacy. Though the NAR of calcium was 0.96, the INQ of calcium was 1.00. The average energy supply from the meal plans was 2,379 kcal, higher than the estimated energy requirement of a female middle school student, but the energy contribution ratio of carbohydrates, proteins, and fats were all adequate according to the acceptable macronutrient distribution range (AMDR). NAR of all nutrients examined were 1.0, except for calcium. The NAR and INQ of calcium were 0.87 and 0.75, respectively, and the meal plans at risk for calcium inadequacy was 19.30%. Conclusions: A dish-based target pattern proposed for adolescent girls was valid, but the meal plan prepared by female middle school students using this approach was high in energy and low in calcium supply. To cut down the energy supply from the meal plan, it is necessary to recommend dishes low in fat and use low fat cooking methods. To increase the calcium supply, it is important to recommend seaweed and legume group dishes with higher Ca INQ food items.

• Korean Journal of Community Nutrition
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• v.27 no.1
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• pp.1-11
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• 2022

Objectives: Away-from-home (AFH) eating has been associated with poor diet quality and health outcomes like obesity in developed countries. AFH eating is also emerging in low-income countries, but its influence on overall diet quality is under-researched. We examined the prevalence of AFH eating and its influence on the dietary patterns of Ugandan adults. Methods: This cross-sectional study employed a web-based survey to interview Ugandan adults aged 18 ~ 65 years. A qualitative food frequency questionnaire was used to assess the food group intake, which was then converted into daily intake frequencies. Principal component analysis was used to derive dietary patterns. The participants were then classified based on the tertiles (T) of dietary pattern scores. Results: About 75% of the 375 participants reported eating AFH. The young men, food insecure, and urban dwellers were more likely to eat AFH ≥ 5 times/week. Three dietary patterns emerged; the animal-based, beverage pattern; the high fat, sweet pattern; and the traditional, plant-based pattern. Participants who frequently ate AFH were 2.85 times and 5.64 times more likely to be in the second and third tertiles, respectively, of the animal-based, beverage pattern compared to the rare eaters (OR = 2.85, 95% CI: 1.35-6.06 for T2 vs T1; and OR = 5.64, 95% CI: 2.50-12.73 for T3 vs T1). The odds of being in the second tertile of the high fat, sweet pattern was significantly higher for frequent AFH eaters compared to the rare eaters (OR = 2.61, 95% CI:1.23-5.52). Conclusions: The prevalence of AFH eating was high. Frequent AFH eating was common among the young, male, food insecure, and urban dwellers, and was associated with unhealthy dietary patterns.

• The Research Journal of the Costume Culture
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• v.25 no.2
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• pp.224-236
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• 2017

Kimono sleeves have continuously appeared in modern fashion as a design motif and this trend has become increasingly prevalent recently. However for research in the area of clothing composition for kimono sleeves in Korea, there has been a lack of development of master patterns based on basic data from the analysis of the standard body type of Korean people and finalized designs based on comparative experiments and analysis of pre-existing research Thus, there is no ideal master kimono sleeve pattern development research based on the examination of the results of the analysis of the standard body type of Korean people. Therefore by recognizing the importance of developing a master kimono sleeve pattern, this research aims to present a practical master kimono sleeve pattern for the standard body type of someone in their 30s. First, the four master patterns were collected and a dressing evaluation was conducted, and by selecting and improving one of these master designs, a final research master pattern was developed after a second dressing evaluation. Through this research, it was possible to design a master kimono sleeve pattern appropriate both externally and functionally for the standard body type of someone in their 30s, which has not been a consideration in previous research.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.65-71
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• 2017

This paper proposes a smart phone authentication method based on user's behavior and habit that is an authentication method against shoulder surfing attack and brute force attack. As smart phones evolve not only storage of personal data but also a key means of financial services, the importance of personal information security in smart phones is growing. When user authentication of smart phone, pattern authentication method is simple to use and memorize, but it is prone to leak and vulnerable to attack. Using the features of the smart phone pattern method of the user, the pressure applied when touching the touch pad with the finger, the size of the area touching the finger, and the time of completing the pattern are used as feature vectors and applied to user authentication security. First, a smart phone user models and stores three parameter values as prototypes for each section of the pattern. Then, when a new authentication request is made, the feature vector of the input pattern is obtained and compared with the stored model to decide whether to approve the access to the smart phone. The experimental results confirm that the proposed technique shows a robust authentication security using subjective data of smart phone user based on habits and behaviors.