• Proceedings of the KSR Conference
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• 2003.10c
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• pp.316-321
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• 2003

The railroad is a means of large transportation which has many talents such as a safety and a regularity. That is a results from various confidential performance tests and evaluations of the system. The railroad system consist of various subsystems - vehicle, power supply, signal, communications, track structures, operations, etc. Among them, as an item of safety evaluation there is a measurement of wheel/rail force, so called a measurement of derailment coefficient. This is a very important item because a derailment of a train will bring about a big accident. Especially it is more important in high speed rail of which operation speed is over two times as fast as existing rail. In this paper, it is introduced to preprocess the wheelset for measuring wheel/rail force of high speed rail, such as to treat a measuring wheelset, adhesion of strain gauges and static load test, running test result of main line.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.05a
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• pp.153-154
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• 2018

It is required that an evaluation method that can present the performance after remodeling to residents objectively as the increase in demand for remodeling. New construction is able to evaluate through housing performance grading indication system. However, there are some parts that are difficult to apply as assessment criteria of new construction in remodeling. The purpose of this study is to establish the assessment criteria direction for each item in remodeling performance evaluation. In conclusion, we set up institutionalized items for remodeling performance evaluation, and propose to assessment criteria direction based on the characteristics of remodeling on extracted items.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.1-8
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• 2013

Data mining techniques are used to find important and meaningful information from huge databases, and pattern mining is one of the significant data mining techniques. Pattern mining is a method of discovering useful patterns from the huge databases. Frequent pattern mining which is one of the pattern mining extracts patterns having higher frequencies than a minimum support threshold from databases, and the patterns are called frequent patterns. Traditional frequent pattern mining is based on a single minimum support threshold for the whole database to perform mining frequent patterns. This single support model implicitly supposes that all of the items in the database have the same nature. In real world applications, however, each item in databases can have relative characteristics, and thus an appropriate pattern mining technique which reflects the characteristics is required. In the framework of frequent pattern mining, where the natures of items are not considered, it needs to set the single minimum support threshold to a too low value for mining patterns containing rare items. It leads to too many patterns including meaningless items though. In contrast, we cannot mine any pattern if a too high threshold is used. This dilemma is called the rare item problem. To solve this problem, the initial researches proposed approximate approaches which split data into several groups according to item frequencies or group related rare items. However, these methods cannot find all of the frequent patterns including rare frequent patterns due to being based on approximate techniques. Hence, pattern mining model with multiple minimum supports is proposed in order to solve the rare item problem. In the model, each item has a corresponding minimum support threshold, called MIS (Minimum Item Support), and it is calculated based on item frequencies in databases. The multiple minimum supports model finds all of the rare frequent patterns without generating meaningless patterns and losing significant patterns by applying the MIS. Meanwhile, candidate patterns are extracted during a process of mining frequent patterns, and the only single minimum support is compared with frequencies of the candidate patterns in the single minimum support model. Therefore, the characteristics of items consist of the candidate patterns are not reflected. In addition, the rare item problem occurs in the model. In order to address this issue in the multiple minimum supports model, the minimum MIS value among all of the values of items in a candidate pattern is used as a minimum support threshold with respect to the candidate pattern for considering its characteristics. For efficiently mining frequent patterns including rare frequent patterns by adopting the above concept, tree based algorithms of the multiple minimum supports model sort items in a tree according to MIS descending order in contrast to those of the single minimum support model, where the items are ordered in frequency descending order. In this paper, we study the characteristics of the frequent pattern mining based on multiple minimum supports and conduct performance evaluation with a general frequent pattern mining algorithm in terms of runtime, memory usage, and scalability. Experimental results show that the multiple minimum supports based algorithm outperforms the single minimum support based one and demands more memory usage for MIS information. Moreover, the compared algorithms have a good scalability in the results.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.67-74
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• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.2
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• pp.99-105
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• 2005

A quality inspection procedure interchangeably using the performance and surrogate variables is proposed. At the start of the inspection, the continuous performance variable is measured for all items. As soon as iconsecutive items are found to be conforming, the continuous surrogate variable is measured instead of the performance variable. If an item is rejected, the inspection based on the performance variable is resumed. It is assumed that the performance variable and the surrogate variable are jointly normally distributed with known means and standard deviations. The average outgoing quality (AOQ) expression is derived, and the methods of finding the inspection procedure with a specified average outgoing quality limit (AOQL) are presented.

• Journal of Communications and Networks
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• v.6 no.1
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• pp.78-87
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• 2004

This paper presents deterministic, worst-case analysis of a queueing system whose multiple homogeneous input streams are regulated by the associated leaky buckets and the queueing system that has a single stream regulated by the jumping-window. Queueing delay averaged over all items is used for performance measure, and the worst-case input traffic and the worst-case performance are identified for both queueing systems. For the former queueing system, the analysis explores different phase relations among leaky-bucket token generations. This paper observes how the phase differences among the leaky buckets affect the worst-case queueing performance. Then, this paper relates the worst-case performance of the former queueing system with that of the latter (the single stream case, as in the aggregate streams from many users, whose item arrivals are regulated by one jumping-window). It is shown that the worst-case performance of the latter is identical to that of the former in which all leaky buckets have the same phase and have particular leaky bucket parameters.

• KIEAE Journal
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• v.10 no.6
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• pp.55-66
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• 2010

The government is enacted "Housing Performance Grading Indication System" from qualitative housing supply policy and performance of housing under the background of looking for new plan to secure good housing stock and housing performance. This system consists of 5 main performance section, 14 performance categories and 20 detailed performance items. 5 main performance parts are sound insulation related grading(Light-weight impact sound insulation, heavy-weight floor impact sound insulation, noise emission in bathroom, airborne sound insulation for wall between units), Long-life housing related grading(flexibility, remodeling & maintenance, durability), environment related grading(landscape, indoor air quality and ventilation, energy performance), Living environment related grading(common resident facilities such as playground and consideration for the socially underprivileged such as the aged), Fire fire prevention grading(fire fire prevention). The purpose of this research is to analyze characteristics and assessment results of 20 detailed performance items on "Housing Performance Grading Indication System" which was enforced 240 cases from Jan 9th, 2006 to Sep 30th, 2010. The analysis of approval condition of detailed performance items will be important comments for understanding the current domestic level and development of technology.

• Asia-Pacific Journal of Business
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• v.7 no.2
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• pp.77-92
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• 2016

The purpose of this study is to examine the effect of CEO's entrepreneurial orientation on innovation performance and business performance, and the mediating effect of innovation performance on the relationship between entrepreneurial orientation and business performance in small and medium-sized venture-enterprises (SMEs). To test the hypothesized relationships, we have conducted a survey of Korean SMEs. After excluding unanswered and untrustful item questionnaires, the final sample size for this study is 110 SMEs. The major findings of the empirical research are as follows. First, CEO's entrepreneurial orientation had apositive influence on innovation performance of a firm. Second, CEO's entrepreneurial orientation was positively related to business performance of a firm. Third, innovation performance had the partial mediating effect on the relationship between CEO's entrepreneurial orientation and business performance of a firm. That is, this result indicates that CEO's entrepreneurial orientation indirectly effects on business performance through innovation performance. Based on these findings, implications of the research findings are discussed, and recommendation for future research are provided.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.138-145
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• 2003

Performance assessment was introduced to improvement of self-directed learning and method of assessment for differenced learning as the seventh educational curriculum is enforced. Performance assessment is overcoming limitation about problem solving ability and higher thinking abilities assessment that is problem of a written examination and get into the spotlight by way for quality of class and school normalization. But, performance assessment has problems about possibilities of assessment fault by appraisal, fairness, reliability, and validity of grading, ambiguity of grading standard, difficulty about objectivity security etc. This study proposes fuzzy performance assessment system to solve problem of the conventional performance assessment. This paper presented an objective and reliable performance assessment method through fuzzy reasoning, design fuzzy membership function and define fuzzy rule analyzing factor that influence in each sacred ground of performance assessment to account principle subject. Also, performance assessment item divides by formation estimation and subject estimation and designed membership function in proposed performance assessment method. Performance assessment result that is worked through fuzzy performance assessment system can pare down burden about appraisal's fault and provide fair and reliable assessment result through grading that have correct standard and consistency to students.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.608-611
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• 2003

Performance assessment was introduced to improvement of self-directed learning and method of assessment for differenced learning as the seventh educational curriculum is enforced. Performance assessment is overcoming limitation about problem solving ability and higher thinking abilities assessment that is problem of a written examination and get into the spotlight by way for quality of class and school normalization. But performance assessment has problems about possibilities of assessment fault by appraisal, fairness, reliability, and validity of grading, ambiguity of grading standard, difficulty about objectivity security etc. This study proposes fuzzy performance assessment system to solve problem of the conventional performance assessment. This paper presented an objective and reliable performance assessment method through fuzzy reasoning, design fuzzy membership function and define fuzzy rule analyzing factor that influence in each sacred ground of performance assessment to account principle subject. Also, performance assessment item divides by formation estimation and subject estimation and designed membership function in proposed performance assessment method. Performance assessment result that is worked through fuzzy performance assessment system can pare down burden about appraisal's fault and provide fair and reliable assessment result through grading that have correct standard and consistency to students.