• 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.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.155-162
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• 2008

Biological sequences such as DNA sequences and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological dataset with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with the fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. As the result, the experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

• Journal of Physiology & Pathology in Korean Medicine
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• v.27 no.5
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• pp.487-496
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• 2013

This article is a study on to which categories of modern diseases qi deficiency pattern types are assigned by reference to modern clinical papers to analyze and understand modern diseases with the perspective of Korean Medicine. Clinical papers were searched in China Academic Journals(CAJ) of China National Knowledge Infrastructure(CNKI) from 1994 to 2013. Conclusions are as follows. First, qi deficiency pattern types are roughly classified as qi deficiency pattern, qi-yin dual deficiency pattern and qi deficiency pattern related with viscera and bowels. Second, there are many patterns combined with static blood, qi stagnation, phlegm, dampness, heat, toxin, water or fluid deficiency and the level of pattern designation is more specific than pattern types in Korean Standard Classification of Diseases(KCD), which makes the pattern types more useful to clinical application. Third, static blood due to qi deficiency is the most frequent combined pattern and diseases related with blood circulation such as angina, atherosclerosis, hyperlipidemia and chronic obstructive pulmonary disease(COPD) were reported on that pattern. The detailed relation between modern diseases and pattern types can be an another topic.

• Journal of Information Processing Systems
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• v.6 no.4
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• pp.521-536
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• 2010

Spatio-temporal patterns extracted from historical trajectories of moving objects reveal important knowledge about movement behavior for high quality LBS services. Existing approaches transform trajectories into sequences of location symbols and derive frequent subsequences by applying conventional sequential pattern mining algorithms. However, spatio-temporal correlations may be lost due to the inappropriate approximations of spatial and temporal properties. In this paper, we address the problem of mining spatio-temporal patterns from trajectory data. The inefficient description of temporal information decreases the mining efficiency and the interpretability of the patterns. We provide a formal statement of efficient representation of spatio-temporal movements and propose a new approach to discover spatio-temporal patterns in trajectory data. The proposed method first finds meaningful spatio-temporal regions and extracts frequent spatio-temporal patterns based on a prefix-projection approach from the sequences of these regions. We experimentally analyze that the proposed method improves mining performance and derives more intuitive patterns.

• Nutrition Research and Practice
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• v.4 no.1
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• pp.43-50
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• 2010

The aim of this study was to provide descriptive information on meal and snack patterns and to investigate snacks in relation to energy intake and food choice according to the meal patterns of employed people in Korea. 683 employed people (292 males, 391 females) were interviewed to collect one day dietary data by using 24-h dietary recall. A recorded day was divided into 3 meal and 3 snack periods by the respondent's criteria and the time of consumption. To analyze the eating pattern participants were divided as the more frequent snack eaters (MFSE) and the less frequent snack eaters (LFSE). They were also categorized into 6 groups according to the frequency of all eating occasions. The common meal pattern in nearly half of the subjects (47.6%) was composed of three meals plus one or two snacks per day. A trend of an increasing the number of snacks in between main meals emerges, although the conventional meal pattern is still retained in most employed Korean adults. Women, aged 30-39, and urban residents, had a higher number of being MFSE than LFSE. Increasing eating occasions was associated with higher energy, protein, and carbohydrate intakes, with the exception of fat intakes. 16.8% of the total daily energy intake came from snack consumption, while the 3 main meals contributed 83.2%. Energy and macronutrient intakes from snacks in the MFSE were significantly higher than the LFSE. Instant coffee was the most popular snack in the morning and afternoon, whereas heavy snacks and alcohol were more frequently consumed by both of the meal skipper groups ($\leq$2M+2,3S and $\leq$2M+0,1S) in the evening. In conclusion, meal pattern is changing to reflect an increase of more snacks between the three main meals. Meal and snack patterns may be markers for the energy and macronutrient intakes of employed people in Korea.

• Nutrition Research and Practice
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• v.5 no.2
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• pp.124-131
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• 2011

Because excessive consumption of sugar-sweetened beverages may reduce the quality of nutritional intake, this study examined the consumption patterns of commercial beverages, lifestyle, dietary habits, and perception of sweet taste. Participants were 407 male university students in Kyeooggido, Korea, and information was collected by self-administered questionnaire. Among them, 58 nonsmokers volunteered to participate in the taste test. Participants were divided into three groups according to the frequency of commercial beverage consumptions: 120 rare (< 1 serving/week), 227 moderate (1-3 servings/week) and 133 frequent (> 3 servings/week) consumption groups. More subjects from the rare consumption group chose water, tea, and soy milk, and more from the frequent consumption group chose carbonated soft drinks and coffee (P=0.031) as their favorite drinks. Frequent consumption group consumed fruit juice, coffee, and sports and carbonated soft drinks significantly more often (P=0.002, P=0.000, P=0.000, respectively), but not milk and tea. Frequent consumption group consumed beverages casually without a specific occasion (P=0.000) than rare consumption group. Frequent drinking of commercial beverages was associated with frequent snacking (P=0.002), meal skipping (P=0.006), eating out (P=0.003), eating delivered foods (P=0.000), processed foods (P=0.001), and sweets (P=0.002), and drinking alcoholic beverages (P=0.029). Frequent consumption group tended to have a higher threshold of sweet taste without reaching statistical significance. The results provide information for developing strategies for evidence-based nutrition education program focusing on reducing consumption of unnecessary sugar-sweetened commercial beverages.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.11-17
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• 2022

Design-bid-build (DBB) is the most common project delivery method among highway projects. State Highway Agencies (SHAs) usually apply a low-bid approach to select contractors for their DBB projects. In this approach, the Federal Highway Agency suggests SHAs heighten contractors' competition to lower bid prices. However, these attempts may become ineffective due to collusive bidding arrangements among certain contractors. One common strategy is the rotation of winning bidders of a group of contractors who bid on many of the same projects. These arrangements may also be specific to a particular region or vary in time. Despite the practices' adverse effects on bidding outcomes, an effective model to detect red-flag bidding patterns is lacking. This study fills the gap by proposing a novel framework that utilizes pattern mining techniques and statistical tests for unusual pattern detection. A case study with historical data from an SHA is conducted to illustrate the proposed framework.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.383-393
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• 2013

Data stream mining is a technique to obtain the useful information by analyzing the data generated in real time. In data stream mining technology, frequent itemset mining is a method to find the frequent itemset while data is transmitting, and these itemsets are used for the purpose of pattern analyze and marketing in various fields. Existing techniques of finding frequent itemset mining are having problems when a malicious attacker sniffing the data, it reveals data provider's real-time information. These problems can be solved by using a method of inserting dummy data. By using this method, a attacker cannot distinguish the original data from the transmitting data. In this paper, we propose a method for privacy preserving frequent itemset mining by using the technique of inserting dummy data. In addition, the proposed method is effective in terms of calculation because it does not require encryption technology or other mathematical operations.

• Genomics & Informatics
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• v.10 no.1
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• pp.44-50
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• 2012

Pattern discovery in biological sequences (e.g., DNA sequences) is one of the most challenging tasks in computational biology and bioinformatics. So far, in most approaches, the number of occurrences is a major measure of determining whether a pattern is interesting or not. In computational biology, however, a pattern that is not frequent may still be considered very informative if its actual support frequency exceeds the prior expectation by a large margin. In this paper, we propose a new interesting measure that can provide meaningful biological information. We also propose an efficient index-based method for mining such interesting patterns. Experimental results show that our approach can find interesting patterns within an acceptable computation time.

• The Journal of Korean Obstetrics and Gynecology
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• v.29 no.2
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• pp.113-120
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• 2016

Objectives: This study aims to report the effects of Korean medicine treatment by pattern identification and Sweet Bee Venom Pharmacopuncture on Chronic Relapsing Cystitis Methods: The patients was treated with Korean medicine by pattern identification and Sweet Bee Venom Pharmacopuncture at Qugu (CV2), Guanyuan (CV4). We evaluated treatment effects by changes of symptoms and urine analysis (UA) finding. Results: After treatments, the clinical symptoms such as painful urination, dysuria, frequent urination were improved and the state of urinalysis was improved. Conclusions: This clinical study suggests that Korean medicine treatment by pattern identification and Sweet Bee Venom Pharmacopuncture are significantly effective in treatment of a Chronic Relapsing Cystitis