• Journal of information and communication convergence engineering
• /
• v.5 no.3
• /
• pp.233-238
• /
• 2007

An approach to identify Chinese event types is proposed in this paper which combines a good feature selection policy and a Maximum Entropy (ME) model. The approach not only effectively alleviates the problem that classifier performs poorly on the small and difficult types, but improve overall performance. Experiments on the ACE2005 corpus show that performance is satisfying with the 83.5% macro - average F measure. The main characters and ideas of the approach are: (1) Optimal feature set is built for each type according to local feature selection, which fully ensures the performance of each type. (2) Positive and negative features are explicitly discriminated and combined by using one - sided metrics, which makes use of both features' advantages. (3) Wrapper methods are used to search new features and evaluate the various feature subsets to obtain the optimal feature subset.

• The Journal of Industrial Distribution & Business
• /
• v.4 no.2
• /
• pp.31-40
• /
• 2013

Purpose - This study attempted to identify the value promotion clues that may operate as a consumer's motive, by shedding new light on consumer value and by reconstructing each variable analyzed through the means-end chain (MEC) theory. Research design, data, and methodology - In this study, 202 copies of effective questionnaires using the data of Yang and Ju (2012) were subjected to correlation, regression, and SEM. Results - All store selection attributes were verified as having a positive influence on the relationship quality. Although the store selection attributes were verified as exerting a positive influence on the relationship quality, according to the verification result of the mediating effect, consumer value was verified to be influenced only by the relationship quality instead of by the store selection attributes. Conclusion - As a result of path analysis on the proposed model after modification, it was verified that only product factor had a statistically significant positive influence and that social value was completely mediating between relationship quality and emotional value. It may be highlighted that the MEC theory concept would be applicable to the cause-and-effect relationship model.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.46 no.1
• /
• pp.116-131
• /
• 2022

This study used text mining to analyze big data to understand consumers' demand for and perceptions of fashion masks. Based on the text-mining analysis results, a survey was conducted with those living in Korea to investigate the influence of consumers' mask selection criteria on mask brand awareness and purchase intention for fashion masks. "Fashion mask" and "functional mask" were used as the keywords in a text-mining analysis, and an online survey of 242 respondents was conducted. The analysis results were as follows: First, the text-mining analysis extracted commonly appearing words that had a high frequency and TF-IDF, such as "COVID-19," "fashion," "celebrity," "antibacterial," and "filter." This confirmed that during the COVID-19 pandemic, consumers have demanded masks that are both functional and fashionable. Second, among consumers' mask selection criteria, trend and design had positive effects on face-mask brand awareness. Third, face-mask brand awareness had a positive effect on the purchase intention for both brand and fashion masks, and the purchase intention for brand masks had a positive effect on the purchase intention for fashion masks.

• Communications for Statistical Applications and Methods
• /
• v.31 no.4
• /
• pp.441-457
• /
• 2024

Semicontinuous data are characterized by a mixture of a point probability mass at zero and a continuous distribution of positive values. This type of data is often modeled using a two-part model where the first part models the probability of dichotomous outcomes -zero or positive- and the second part models the distribution of positive values. Despite the two-part model's popularity, variable selection in this model has not been fully addressed, especially, in high dimensional data. The objective of this study is to investigate variable selection and prediction performance of penalized regression methods in two-part models. The performance of the selected techniques in the two-part model is evaluated via simulation studies. Our findings show that LASSO and ENET tend to select more predictors in the model than SCAD and MCP. Consequently, MCP and SCAD outperform LASSO and ENET for β-specificity, and LASSO and ENET perform better than MCP and SCAD with respect to the mean squared error. We find similar results when applying the penalized regression methods to the prediction of crime incidents using community-based data.

• Journal of the Korean Dietetic Association
• /
• v.25 no.3
• /
• pp.188-198
• /
• 2019

This study examined the subjective health recognition, motivation, selection property, consumption realties, and generalities of elderly people eating out. The ratio of women eating out in those over 60 years of ages was high and people in that age group ate out most actively. The score of convenience-oriented, gourmet-oriented, and dignity-oriented of the selection property for eating out increased with increasing frequency and expenditure for eating out. With increasing age, a negative (-) relationship with a decrease in the safety-oriented score of the selection property for eating out was predicted. As the number of days eating out increased, a positive (+) relationship with an increase in the safety-oriented score of the selection property for eating out was observed. As the scores of physical and social health perception increased, a positive (+) relationship with an increase in the gourmet oriented score was observed. Based on the results, various research on the relationship between the health recognition and eating out behavior of those over 60 years of age are required.

• Genomics & Informatics
• /
• v.19 no.2
• /
• pp.15.1-15.7
• /
• 2021

The direction of evolution can estimate based on the variation among nonsynonymous to synonymous substitution. The simulative study investigated the nucleotide sequence of closely related strains of respiratory syndrome viruses, codon-by-codon with maximum likelihood analysis, z selection, and the divergence time. The simulated results, dN/dS > 1 signify that an entire substitution model tends towards the hypothesis's positive evolution. The effect of transition/transversion proportion, Z-test of selection, and the evolution associated with these respiratory syndromes, are also analyzed. Z-test of selection for neutral and positive evolution indicates lower to positive values of dN-dS (0.012, 0.019) due to multiple substitutions in a short span. Modified Nei-Gojobori (P) statistical technique results also favor multiple substitutions with the transition/transversion rate from 1 to 7. The divergence time analysis also supports the result of dN/dS and imparts substantiating proof of evolution. Results conclude that a positive evolution model, higher dN-dS, and transition/transversion ratio significantly analyzes the evolution trend of severe acute respiratory syndrome coronavirus 2, severe acute respiratory syndrome coronavirus, and Middle East respiratory syndrome coronavirus.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.5
• /
• pp.411-416
• /
• 2002

Recently, the trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online internet, so it is expected to make a problem more and more. Currently, the general security system based on Internet couldn't cope with the attack properly, if ever, other regular systems have depended on common softwares to cope with the attack. In this paper, we propose the positive selection mechanism and negative selection mechanism of T-cell, which is the biological distributed autonomous system, to develop the self/non-self recognition algorithm, the anomalous behavior detection algorithm, and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. The proposed algorithm can cope with new intrusion as well as existing one to intrusion detection system in the network environment.

• Journal of the Korean Dietetic Association
• /
• v.25 no.4
• /
• pp.257-268
• /
• 2019

This study provides basic data on how stress impacts the processed convenience foods purchase attitudes and the selection attributes of housewives. The stress consists of 3 factors, which were housework stress, family relation stress and economic stress. The processed convenience food purchase attitude consisted of 2 factors, which were peripheral influence purchase and conviction purchase. The processed convenience food selection attribute consisted of 4 factors, which were quality, convenience, packaging and price. Factor loading confirmation and reliability test were conducted, and the reliability was confirmed with Cronbach's alpha coefficients for all the factors exceeding 0.5. The high stress levels showed significantly high stress factors of housework, family relations and economic stress (P<0.001). The high stress group was shown to make purchases by recognizing peripheral influences (P<0.01). When the selection properties of processed convenience foods depending on different stress levels were examined, it was revealed that among the three groups, the low stress group least considered the price aspect (P<0.01). After deducting the factors, AMOS (Analysis of Moment Structure) was used to conduct the confirmatory factor analysis for verifying validity. The structural equation model was used to determine the path coefficient. From the processed convenience foods purchase attitude, the peripheral influence purchase had significantly positive (+) effects on convenience (P<0.05). Also, conviction purchase was shown to have significantly positive (+) effects on quality (P<0.05). Housework and family relation stress were shown to have negative (-) effects on processed convenience foods selection attribute, and economic stress was shown to have positive (+) effects, although no significant relationships were revealed.

• Journal of Labour Economics
• /
• v.26 no.3
• /
• pp.149-179
• /
• 2003

This study is analysing the factors determining individuals' behavior of selecting self-employment not only at the micro-level but also at the macro-level to put a particular emphasis on the financial constraint and unemployment rate representing business cycle. The data used in this study are "Korean Labor and Income Panal Study" of the Korea Labor Institute and "Economically Active Population Survey" of National Statistical Office. The main findings are as follows. First, human capital such as educational attainment and job experience has positive effects on male's selection of self-employment. The effects of job experience, however, changed negative for female's selection of self-employment. Second, real estate is significantly enhancing the selection probabilities of employer selection while the income from financial assets has negative effects. Third, entrepreneurial culture and environment are also raising the self-employment selection probability. Lastly, the regional unemployment rate representing the business cycle has positive effects on the self-employment selection after the financial crisis in 1997 both at the micro and macro level. Moreover, the coefficient of regional unemployment rate has changed positive in the structural model of self-employment selection controlling for selection bias and income opportunities, which means that individual's behavior of self-employment selection is rather complex when accounting for the uncertainties of income opportunities and diverse characteristics of self-employment workforce.

• Asian-Australasian Journal of Animal Sciences
• /
• v.26 no.5
• /
• pp.603-608
• /
• 2013

Hanwoo have been subjected over the last seventy years to intensive artificial selection with the aim of improving meat production traits such as marbling and carcass weight. In this study, we performed a signature of selection analysis to identify recent positive selected regions driven by a long-term artificial selection process called a breeding program using whole genome SNP data. In order to investigate homozygous regions across the genome, we estimated iES (integrated Extended Haplotype Homozygosity SNP) for the each SNPs. As a result, we identified two highly homozygous regions that seem to be strong and/or recent positive selection. Five genes (DPH5, OLFM3, S1PR1, LRRN1 and CRBN) were included in this region. To go further in the interpretation of the observed signatures of selection, we subsequently concentrated on the annotation of differentiated genes defined according to the iES value of SNPs localized close or within them. We also described the detection of the adaptive evolution at the molecular level for the genes of interest. As a result, this analysis also led to the identification of OLFM3 as having a strong signal of selection in bovine lineage. The results of this study indicate that artificial selection which might have targeted most of these genes was mainly oriented towards improvement of meat production.