• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.183-194
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• 2009

In this paper, we propose a new method for detecting objectionable images with an active shape model. Our method first learns the shape of breast lines through principle component analysis and alignment as well as the distribution of intensity values of corresponding landmarks, and then extracts breast lines with the learned shape and intensity distribution. To accurately select the initial position of active shape model, we obtain parameters on scale, rotation, and translation. After positioning the initial location of active shape model using scale and rotation information, iterative searches are performed. We can identify adult images by calculating the average of the distance between each landmark and a candidate breast line. The experiment results show that the proposed method can detect adult images effectively by comparing various results.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.4
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• pp.291-299
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• 2007

To operate a permanent magnet synchronous motor (PMSM) at a maximum torque per ampere (MTPA) operation point, the exact values of machine parameters such as inductances and back-EMF constant, which are sensitive to motor phase currents and temperature respectively, should be blown. An adaptive estimation method for on-line estimation of the machine parameters is not suitable for practical applications since it has difficulties in estimating exact values and requires complex mathematical calculations. The purpose of this paper is to present a simple MTPA operation point tracking control strategy for vector controlled PMSM drives with slow dynamic loads. The proposed method searches MTPA operation points by modulating current phase angle and observing the variation in command power. The current angle modulation strategy is designed to sense the effect of load variations in the command power. Therefore, the proposed method can track the MTPA operation points of the PMSM regardless of load variations. Computer simulation and experimental study is also presented to show the effectiveness of the proposed method.

• Journal of the Korea Fashion and Costume Design Association
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• v.20 no.4
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• pp.57-71
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• 2018

Since consumers have become more comfortable with providing and receiving information online, 'online word of mouth' has been gaining consideration as one of the major information sources. Also, the shopping orientation of consumers has been proven to be an important determinant of consumer behavior. Therefore, the study investigated the differences in online WOM behavior based on shopping orientation. Hedonic, loyal, and syntonic styles were the types of shopping orientation considered, and the study focused on information retrieval tendencies, the motivation of online WOM search, searching online WOM sources, and the contents for the online WOM behavior. The research conducted an off-line survey targeting females in their twenties. The total number of data sets used in the empirical study was 125, and these were analyzed by SPSS 20.0: factors analysis, Cronbach's ${\alpha}$, k-means cluster, ANOVA, Duncan's multiple range test, Kruskal-Wallis, Mann-Whitney, and Bonferroni correction. The participants were divided into 3 kinds of shopping orientation groups named 'trend-pursuit', 'passive', and 'loyal'. As a result, there were significant differences in online WOM behavior discovered between the groups. Firstly, the 'trend-pursuit' group had the highest number of ongoing searches while the 'loyal' group had the highest number of pre-purchase search. Secondly, the 'trend-pursuit' and 'loyal' groups both had the motivations of online WOM search, hedonic and utility, whereas the 'passive' group had the lowest motivations for both motivations. Thirdly, the 'loyal' group frequently referred to reviews on shopping malls as online WOM sources. The research provided a better understanding of the online WOM behavior of present consumers and suggests that fashion related corporations map out marketing strategies with the understanding of these behaviors.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.787-793
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• 2022

After COVID-19, with the emergence of social distancing, non-face-to-face services, and home economics, visiting dining out is rapidly being replaced by non-face-to-face dining out. The purpose of this study is to find ways to create a safe dining culture centered on living quarantine in line with the changing trend of the restaurant industry after the outbreak of COVID-19, establish the direction of food culture improvement projects, and enhance the effectiveness of the project. This study used TEXTOM to collect and refine search frequency, perform TF-IDF analysis, and Ucinet6 programs to implement visualization using NetDraw from January 1, 2018 to October 31, 2019 and December 31, 2021, and identified the network between nodes of key keywords. Finally, clustering between them was performed through Concor analysis. As a result of the study, if you check the frequency of searches before and after COVID-19, it can be seen that the COVID-19 pandemic greatly affects the changes in the restaurant industry.

• Restorative Dentistry and Endodontics
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• v.46 no.3
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• pp.41.1-41.23
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• 2021

Objectives: This study aimed to evaluate the efficacy of various local anesthesia (LA) in vital asymptomatic teeth. Materials and Methods: Randomized controlled trials comparing pulpal anesthesia of various LA on vital asymptomatic teeth were included in this review. Searches were conducted in the Cochrane CENTRAL, MEDLINE (via PubMed), EMBASE, ClinicalTrials.gov, Google Scholar and 3 field-specific journals from inception to May 3, 2019. Study selection, data extraction, and risk of bias assessment using Cochrane Risk of Bias Tool were done by 2 independent reviewers in duplicate. Network meta-analysis (NMA) was performed within the frequentist setting using STATA 15.0. The LA was ranked, and the surface under the cumulative ranking (SUCRA) line was plotted. The confidence of the NMA estimates was assessed using the CINeMA web application. Results: The literature search yielded 1,678 potentially eligible reports, but only 42 were included in this review. For maxillary buccal infiltration, articaine 4% with epinephrine 1:100,000 was more efficacious than lidocaine 2% with epinephrine 1:100,000 (odds ratio, 2.11; 95% confidence interval, 1.14-3.89). For mandibular buccal infiltration, articaine 4% with epinephrine 1:100,000 was more efficacious than various lidocaine solutions. The SUCRA ranking was highest for articaine 4% with epinephrine when used as maxillary and mandibular buccal infiltrations, and lidocaine 2% with epinephrine 1:80,000 when used as inferior alveolar nerve block. Inconsistency and imprecision were detected in some of the NMA estimates. Conclusions: Articaine 4% with epinephrine is superior when maxillary or mandibular infiltration is required in vital asymptomatic teeth.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.876-884
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• 2003

It is essential to identify both the pupil and iris boundaries for iris recognition. The circular edge detector proposed by Daugman is the most common and powerful method for the iris region extraction. The method is accurate but requires lots of computational time since it is based on the exhaustive search. Some heuristic methods have been proposed to reduce the computational time, but they are not as accurate as that of Daugman. In this paper, we propose a pupil and iris boundary finding algorithm which is faster than and as accurate as that of Daugman. The proposed algorithm searches the boundaries using the Daugman's circular edge detector, but reduces the search region using the problem domain knowledge. In order to find the pupil boundary, the search region is restricted in the maximum and minimum bounding circles in which the pupil resides. The bounding circles are obtained from the binarized pupil image. Two iris boundary points are obtained from the horizontal line passing through the center of the pupil region obtained above. These initial boundary points, together with the pupil point comprise two bounding circles. The iris boundary is searched in this bounding circles. Experiments show that the proposed algorithm is faster than that of Daugman and more accurate than the conventional heuristic methods.

• Proceedings of the Botanical Society of Korea Conference
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• 2002.04a
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• pp.62-72
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• 2002

This study has investigated the biosynthesis and function of the heavy metal binding peptides, the phytochelatins, in plants. PCs are synthesised enzymatically from glutathione by the enzyme PC synthase in the presence of heavy metal ions. Using Arabidopsis thaliana as a model organism cadmium-sensitive, phytochelatin-deficient mutants have been isolated and characterised in previous studies. The cadl mutants have wildtype levels of glutathione, are PC deficient and lack PC synthase activity. Thus, the CADl gene has been proposed to encode PC synthase. The CADl gene was isolated by a positional cloning strategy The gene was mapped and a candidate identified. Each of four cadl mutants had a single base pair change in the candidate gene and the cadmium-sensitive, cadl phenotype was complemented by the candidate gene. This demonstrated the CADl gene had been cloned. A homologous gene in the fission yeast, Schizosaccharomyces pombe was identified through database searches. A targeted-deletion mutation of this gene was constructed and the mutant, like cadl mutants of Arabidopsis, was cadmium-sensitive and PC-deficient. A comparison of the redicted amino acid sequences reveals a highly conserved N-terminal region Presumed to be the catalytic domain and a variable C-terminal region containing multiple Cys residues proposed to be involved in activation of the enzyme by metal ions. Similar genes were also identified in animal species. The Arabidopsis CADl/AtPCSl and S. pombe SpbPCS genes were expressed in E. coli and were shown to be sufficient for glutathione-dependent, heavy metal activate PC synthesis in vitro, thus demonstrating these genes encode PC synthase enzymes. Using RT-PCR, AtPCSl expression appeared to be independent of Cd exposure. However, at higher levels of Cd exposure a AtPCSl-CUS reporter gene construct appeared to be more highly expressed. Using the reporter gene construct, AtPCSl was expressed most tissues. Expression appeared to be greater in younger tissues and same higher levels of expression was observed in some regions, including carpels and the base of siliques. AtPCS2 was a functional gene encoding an active PC synthase. However, its Pattern of expression and the phenotype of a mutant (or antisense line) have not been determined. Assuming the gene is functional then it has clearly been maintained through evolution and must provide some selective advantage. This implies that, at least in some cells or tissue, it is likely to be the dominant PC synthase expressed. This remains to be determined

• Asia pacific journal of information systems
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• v.17 no.3
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• pp.25-53
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• 2007

The Expectation Confirmation Model (ECM) of information systems investigates the continued information systems usage behavior. This paper expands the original post-adoption beliefs and searches the applications in the emerging hedonic information systems. Previous IS researches focused on the organizational environments. However as the information technology (especially internet) evolves, information systems have not only emerged for the organizations but also for the individual users, such as internet portals, internet communities, on-line games etc. These information systems so called Hedonic Information Systems aims to provide self-fulfilling value rather than instrumental value to the users. Researches in other disciplines, including marketing and consumer behavior research, illustrate that the hedonic and utilitarian perspective of goods and services have different influence on the consumer behavior. Goods and services used to be classified into either hedonic or utilitarian aspect but now they may belong to both aspects simultaneously. Moreover consumer's goals or tasks have both hedonic utilitarian aspects. When a consumer makes a decision to purchase or repurchase goods or services, he/she compares the hedonic and utilitarian perspectives of goods to find most suitable ones to satisfy their goals/tasks. Finally, consumer's behavior is determined by the trade-off between what the goods can provide to the consumers and in what extent the goods fulfill consumer's purchase behavior. Consumer also shows that the salience of hedonic perspective is relatively greater when consumer decides which of several items to give up (forfeiture choices) than the time when they decide which item to acquire (acquisition choices). Some researches in MIS discipline have found out that the information systems also have both hedonic and utilitarian perspectives. The decision process of whether to use information systems or not is similar to that of a consumer's decision of purchasing or repurchasing goods or services. However most of researches in MIS tend to focus on the extrinsic motivation variables which only cover the utilitarian perspective of information systems. It is only recent that researches start to investigate the intrinsic motivation variable - Perceived Enjoyment - for the hedonic perspective. Considering the consumer's purchasing decision process, users of information systems evaluate the systems through balancing between intrinsic (hedonic) and extrinsic (utilitarian) variables according to their main tasks or tendencies. This paper proposes a model that is based on the ECM of IS Continuance model modified from Expectation Confirmation Model to fit into the continued usage of information system. It first started from the decision process regarding hedonic and utilitarian perspectives in the consumer behavior literatures. The model deals with continued usage of information systems beyond the mere technology adoption as in most of the previous MIS researches. This research is particularly important to the hedonic information systems, because their business model depends on the frequent usages rather simple adoption at the beginning. Because the basic model only considered the extrinsic motivations (perceived usefulness) to explain the users' behavior and as the information systems can have both hedonic and utilitarian dimensions, it should consider both perspectives. Therefore, this newly proposed model considers intrinsic variable (perceived enjoyment) as well. Since the individual user can have a preference on either aspects that is between the hedonic and utilitarian perspective depending on his/her main tasks or goals, some variables (Hedonic Orientation and Utilitarian Orientation) meaning the extents of users' pursuing from the information system were additionally studied.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.2
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• pp.164-172
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• 2021

Purpose: The purpose of this study was to analyze the level of interest that common Internet users have in dental implant using a Google Trends, and to compare the level of interest with big data from National Health Insurance Service. Materials and methods: Google Trends provides a relative search volume for search keywords, which is the average data that visualizes the frequency of searches for those keywords over a specific period of time. Implant was selected as the search keyword to evaluate changes in time flows of general Internet users' interest from 2015 to 2019 with trend line and 6 month moving average. Relative search volume for implant was analyzed with the number of patients who received National Health Insurance coverage for implant. Interest in implant and conventional denture was compared and popular related search keywords were analyzed. Results: Relative search volume for implant has increased gradually and showed a significant positive correlation with the total number of patients (P<.01). Interest in implant was higher than denture for most of the time. Keywords related to implant cost were most frequently observed in all years and related search on implant procedure was increasing. Conclusion: Within the limitations of this study, the public interest in dental implant was gradually increasing and specific areas of interest were changing. Web-based Google Trends data was also compared with traditional data and significant correlation was confirmed.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.