• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5287-5303
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• 2018

Handling vast amount of data found in large transactional datasets is an obvious challenge for the conventional data mining algorithms. Addressing this challenge, our paper proposes a parallel approach for proper decomposition of mining problem into sub-problems in order to find frequent patterns from these datasets. The proposed, Pattern Mining for Large Distributed Dataset (PMLDD) approach, ensures minimum dependencies as well as minimum communications among sub-problems. It establishes a linear aggregation of the intermediate results so that it can be adapted to large-scale programming models like MapReduce. In this context, an algorithmic structure for MapReduce programming model is presented. PMLDD guarantees an efficient load balancing among the sub-problems by a specific selection criterion. Further, it optimizes the number of required iterations over the dataset for mining frequent patterns as compared to the existing approaches. Finally, we believe that our approach is scalable enough to handle larger datasets in terms of performance evaluation, and the result analysis justifies all these mentioned concerns.

• Bulletin of the Korean Chemical Society
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• v.15 no.5
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• pp.357-360
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• 1994

The adsorption of cyanide ion on the gold electrode has been investigated by the subtractively normalized interfacial Fourier transform infrared spectroscopy (SNIFTIRS). The observations made by SNIFTIRS were consistent with those obtained by the polarization modulated Fourier transform infrared spectroscopy. According to the surface selection rule, cyanide ion appeared to adsorb on gold via either carbon or nitrogen lone pair electrons assuming a perpendicular orientation with respect to the metal surface. The possibility of presence of bridge-bound species seemed very infeasible. From the ab initio quantum mechanical calculation, adsorbate-to-metal bonding appeared to occur mainly via the $5{\sigma}$ donation from carbon to Au.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5379-5388
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• 2012

In fuzzy modeling for nonlinear process, the fuzzy rules are typically formed by selection of the input variables, the number of space division and membership functions. The Generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, complex nonlinear process can be modeled by generating the fuzzy rules by means of fuzzy division of input space. Therefore, in this paper, rules of non-fuzzy inference systems are generated by partitioning the input space in the scatter form using HCM clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of HCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the consequence parameters of each rule are identified by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process. Through this experiment, we showed that high-dimensional nonlinear systems can be modeled by a very small number of rules.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.4
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• pp.961-972
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• 2016

For securing password-based authentication, a user must select and manage a strong password that has sufficient length and randomness. Unfortunately, however, it is known that many users are likely to choose easy-to-remember weak passwords and very poorly manage them. In this paper, we study a domestic user case of password selection and management. We conducted a survey on 327 domestic users and analyzed their tendency on password creation and update strategies, and also on the password structure and account management. We then analyzed an effect of a server's password creation rule on a structure of a user-chosen password. Our findings include that there are password structures and special characters that users significantly prefer while the effect of server's password creation rule is insignificant.

• Korean Journal of Logic
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• v.19 no.3
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• pp.369-400
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• 2016

If we learn that 'Mrs Lee has two children and at least one of them is a daughter', what is our credence that her two children are all girls? Obviously it is 1/3. By assuming some other obvious theses it seem to be argued that our credence is 1/2. Also by just supposing we learn trivial information about the future, it seem to be argued that we must change our credence 1/3 into 1/2. However all of these arguments are fallacious, cannot be sound. When using the conditionalization rule to evaluate conformation of a hypothesis by an evidence, or to estimate credence change by information intake, there are some points to keep in mind. We must examine whether relevant information was given through a random procedure or a biased procedure. If someone with full information releases to us particular partial information, an observation, a testimony, an evidence selected intentionally by him, which means the particular partial information was not given by chance, or was not given accidentally or naturally to us, then the conditionalization rule should be employed very cautiously or restrictedly.

• Journal of the Korean Society of Costume
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• v.66 no.6
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• pp.17-31
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• 2016

The purpose of this study is to perform historical reconstruction of the court dress coat in the Daehan Empire in order to make replicas of the artifacts. Following steps were undertaken in the study : literature research of the laws of the era, drawing of the design, embroidering gold work, and tailoring of the coat. Embroidering and tailoring experts were consulted to complete an accurate reconstruction of the dress court. The results of this study are as follows. First, Juimgwan's coat, which was the Court Costume Rule in 1905 was selected as an experimental coat. It was revision of the Court Costume Rule in 1900. The process of selection was based on the amount and easiness of embroidery. Second, the design of the back bodice, chevron, pockets and collar is reflected the pattern of the preceding research, which was analyzed from the laws, the drawing document[Gwanbokjandoan], and artifacts. Third, the gold work embroidery in the back bodice, chevron, pockets and collar was done. The embroidery material were composed of gold threads, such as rough purl, smooth purl, check purl, pearl purl, rococo, and spangle. Couching was used as an embroidery method. The coat was tailored after embroidering. The coat and the buttons were made after analyzing the artifacts. The result of this study can be utilized in the field of historical reconstruction of artifacts in the museum, the designing of stage costume in the performances of reenactment events, drama, and movie of Daehan Empire. Furthermore, this study is anticipated to contribute to the fundamental research of culture contents.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.685-691
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• 2008

The selection of classification boundaries in fuzzy rule- based classification systems is an important and difficult problem. So various methods based on learning processes such as neural network, genetic algorithm, and so on have been proposed for it. In a previous study, we pointed out the limitation of the methods and discussed a method for fuzzy partitioning in the overlapped region on feature space in order to overcome the time-consuming when the additional parameters for tuning fuzzy membership functions are necessary. In this paper, we propose a method to determine three types of classification boundaries(i.e., non-overlapping, overlapping, and a boundary point) on the basis of statistical information of the given dataset without learning by extending the method described in the study. Finally, we show the effectiveness of the proposed method through experimental results applied to pattern classification problems using the modified IRIS and standard IRIS datasets.

• Journal of the Korean Society of Safety
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• v.35 no.2
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• pp.8-16
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• 2020

In Article 311 of the Regulation on Occupational Safety and Health Standards requires the use of Korean Industrial Standards Act in accordance with the Industrial Standardization Act. However, the classification, inspection, maintenance, design, selection, and installation of explosion hazard locations for explosion and explosion prevention and internalization of 'safety' in the performance maintenance phase of electrical machinery and equipment There is no technical and institutional management plan for remodeling and alteration. Analysis of actual conditions and problems related to the installation, use, and maintenance of explosion-proof equipment, comparative analysis of domestic and international technical standards and systems, technical, institutional and administrative systems and systems related to installation, use, and maintenance of explosion-proof equipment, technical personnel and qualifications, etc. It is to propose legislation, system improvement, and technical standard establishment related to the maintenance of explosion-proof facility performance through improvement of the necessity and feasibility study for establishment of the legal status of the management site and management plan. As technical measures, KS standard revision (draft), KOSHA guide (draft) and explosion-proof facility performance maintenance manual were presented. In addition, the institutional management plan proposed the revised rule on occupational safety and health standards, the revised rule on the restriction of employment of hazardous work, and the manpower training program related to the maintenance of explosion-proof facilities and the qualification plan. Enhance safety at the installation, use, and maintenance stage of explosion-proof structured electrical machinery. It is expected to be used to classify explosion hazards, select related equipment, and to update and standardize standards related to installation, use and maintenance.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1288-1296
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• 2013

The prominent line at the singe image is the important fact for understanding spatial structure or estimating aesthetic scoring. According to this thesis, the abstraction of the background line helps analyzing vanishing point, reconstitution of 3 dimensions, and determining of image sloppiness. It also makes easy to calculate the rule of thirds. This thesis is composed of section hough transform mapping, prioritizing of the prominent line, and selection of the prominent line. These technologies are departmentalized to be applied abstraction of traffic lane, analyzing of building structure, abstraction of vanishing point, and abstraction of straight line documentation. This gives the choice that users are able to compose technology by considering characteristic of objects and luminous environment. This thesis also can be applied to abstract circle. The interval hough transform is able to select the number of prominent line which users want to abstract. It can analyze important prominent line numbers at the image and then abstract the lines, too. Results of prominent lines by experiments would be show at this thesis.