Purpose - The purpose of this study is to provide practical implications for Korean companies searching for new market opportunities. From the experimental analysis, the impact of country image on product-country image and purchase intention of Korean products are measured. In addition, this study disaggregates the impacts of country image and product-country image and purchase intention among ethnic groups in South Africa for searching further useful implications. Design/methodology - To examine South African consumers' country image and product-country image towards Korean products, data were collected between June and July 2019 through an online questionnaire, and 335 questionnaires were used for analysis. Firstly, the multivariate analysis was conducted to examine the general tendency of South African consumers' perceptions of country image to Korea, product-country image, and purchase intention among three ethnic group consumers. Then in order to verify the country image model and hypotheses of the study, we analyzed the structural models for each of the three ethnic groups and compared the sizes of the path coefficients for each groups. To compare the difference of path coefficients across ethnic groups, configural invariance, metric invariance, and scalar invariance tests were conducted sequentially. Findings - In the black and white ethnic groups, the country image had a statistically significant impact on product-country image, but it did not affect the purchase intention to Korean products. The product-country image showed a statistically significant impact on the purchase intention to Korean products in both ethnic group. However, in the coloured ethnic group consumer, the country image had a significant effect on the product-country image, but it did not affect the purchase intention of Korean products. In addition, the product-country image did not have a significant influence on the purchase intention of coloured ethnic group consumers unlike black and white ethnic group consumers. The results of this study suggest that even though differences in terms of the impact of CoI on PCI and PI were investigated for the sample of white, coloured, and black respondents, the groups seemed to respond in a reasonably comparable manner. Originality/value - South Africa occupies more than 20% of Africa's total GDP in sub-Saharan Africa and is a hub for Southern African logistics as a hub for Korean companies to enter Africa. However, it is rare to find a study focused on the determinants of consumer behavior in South Africa. In particular, this study disaggregates the impacts of country image and product-country image on consumer behavior across ethnic groups in South Africa. Therefore, this study could provide practical implications for Korean firms which desire to diversify their export markets and pioneer future markets.
Journal of the Korea Society of Computer and Information
/
v.26
no.12
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pp.151-158
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2021
Internet of Things (IoT) technology, which provides services by connecting various objects in the real world and objects in the virtual world based on the Internet, is emerging as a technology that enables a hyper-connected society in the era of the 4th industrial revolution. Since IoT technology is a convergence technology that encompasses devices, networks, platforms, and services, various studies are being conducted. Among these studies, studies on measures that can measure service quality provided by IoT software are still insufficient. IoT software has hardware parts of the Internet of Things, technologies based on them, features of embedded software, and network features. These features are used as elements defining IoT software quality measurement metrics. However, these features are considered in the metrics related to IoT software quality measurement so far. Therefore, this paper presents a metric for reusability measurement among various quality factors of IoT software in consideration of these factors. In particular, since IoT software is used through IoT devices, services in IoT software must be designed to be changed, replaced, or expanded, and metrics that can measure this are very necessary. In this paper, we propose three metrics: changeability, replaceability, and scalability that can measure and evaluate the reusability of IoT software services were presented, and the metrics presented through case studies were verified. It is expected that the service quality verification of IoT software will be carried out through the metrics presented in this paper, thereby contributing to the improvement of users' service satisfaction.
Journal of the Korea Society of Computer and Information
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v.26
no.12
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pp.53-59
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2021
In this paper, we propose a BERGPT-chatbot, a domestic AI chatbot that can alleviate negative emotions based on text input such as 'Replika'. We made BERGPT-chatbot into a chatbot capable of mitigating negative emotions by pipelined two models, KR-BERT and KoGPT2-chatbot. We applied a creative method of giving emotions to unrefined everyday datasets through KR-BERT, and learning additional datasets through KoGPT2-chatbot. The development background of BERGPT-chatbot is as follows. Currently, the number of people with depression is increasing all over the world. This phenomenon is emerging as a more serious problem due to COVID-19, which causes people to increase long-term indoor living or limit interpersonal relationships. Overseas artificial intelligence chatbots aimed at relieving negative emotions or taking care of mental health care, have increased in use due to the pandemic. In Korea, Psychological diagnosis chatbots similar to those of overseas cases are being operated. However, as the domestic chatbot is a system that outputs a button-based answer rather than a text input-based answer, when compared to overseas chatbots, domestic chatbots remain at a low level of diagnosing human psychology. Therefore, we proposed a chatbot that helps mitigating negative emotions through BERGPT-chatbot. Finally, we compared BERGPT-chatbot and KoGPT2-chatbot through 'Perplexity', an internal evaluation metric for evaluating language models, and showed the superity of BERGPT-chatbot.
Objective: The aim of this study was to investigate diffusion tensor (DT) imaging-derived properties of benign oligemia, true "at risk" penumbra (TP), and the infarct core (IC) during the first 3 hours of stroke onset. Materials and Methods: The study was approved by the local animal care and use committee. DT imaging data were obtained from 14 rats after permanent middle cerebral artery occlusion (pMCAO) using a 7T magnetic resonance scanner (Bruker) in room air. Relative cerebral blood flow and apparent diffusion coefficient (ADC) maps were generated to define oligemia, TP, IC, and normal tissue (NT) every 30 minutes up to 3 hours. Relative fractional anisotropy (rFA), pure anisotropy (rq), diffusion magnitude (rL), ADC (rADC), axial diffusivity (rAD), and radial diffusivity (rRD) values were derived by comparison with the contralateral normal brain. Results: The mean volume of oligemia was $24.7{\pm}14.1mm^3$, that of TP was $81.3{\pm}62.6mm^3$, and that of IC was $123.0{\pm}85.2mm^3$ at 30 minutes after pMCAO. rFA showed an initial paradoxical 10% increase in IC and TP, and declined afterward. The rq, rL, rADC, rAD, and rRD showed an initial discrepant decrease in IC (from -24% to -36%) as compared with TP (from -7% to -13%). Significant differences (p < 0.05) in metrics, except rFA, were found between tissue subtypes in the first 2.5 hours. The rq demonstrated the best overall performance in discriminating TP from IC (accuracy = 92.6%, area under curve = 0.93) and the optimal cutoff value was -33.90%. The metric values for oligemia and NT remained similar at all time points. Conclusion: Benign oligemia is small and remains microstructurally normal under pMCAO. TP and IC show a distinct evolution of DT-derived properties within the first 3 hours of stroke onset, and are thus potentially useful in predicting the fate of ischemic brain.
Dietary niches can support the coexistence of sympatric species in marine ecosystems, which can lead to the presence of greater abundances of those species. Stomach contents of silver croaker (Pennahia argentata) and Japanese sillago (Sillago japonica) inhabiting the Nakdong River estuary, Korea were analyzed to determine diet compositions and the presence of any size-related and inter-specific feeding relationships. These species were bottom-feeding predators that consumed mainly benthic crustaceans and mollusks, but polychaetes were also important in the S. japonica diets. Non-metric multidimensional scaling (nMDS) ordination and multivariate analyses based on weight contributions of the different prey taxa to stomach contents revealed significant inter-specific dietary differences. Size-related change was also significant for P. argentata diets, but not for S. japonica. Canonical analysis of principal coordinate (CAP) ordination plot further demonstrated that differences in the type and range of prey ingested by the two species contributed such an inter-specific difference in the diet compositions. The results from this study provide clear evidence of niche segregation between co-occurring P. argentata and S. japonica in the Nakdong River estuary, which would reduce the likelihood of inter-specific competition for food resources.
De-identification is a method by which the remaining information can not be referred to a specific individual by removing the personal information from the data set. As a result, de-identification can lower the exposure risk of personal information that may occur in the process of collecting, processing, storing and distributing information. Although there have been many studies in de-identification algorithms, protection models, and etc., most of them are limited to structured data, and there are relatively few considerations on de-identification of unstructured data. Especially, in the medical field where the unstructured text is frequently used, many people simply remove all personally identifiable information in order to lower the exposure risk of personal information, while admitting the fact that the data utility is lowered accordingly. This study proposes a new method to perform de-identification by applying the k-anonymity protection model targeting unstructured text in the medical field in which de-identification is mandatory because privacy protection issues are more critical in comparison to other fields. Also, the goal of this study is to propose a new utility metric so that people can comprehend de-identified data set utility intuitively. Therefore, if the result of this research is applied to various industrial fields where unstructured text is used, we expect that we can increase the utility of the unstructured text which contains personal information.
Kato, Talita;Mastelini, Saulo Martiello;Campos, Gabriel Fillipe Centini;Barbon, Ana Paula Ayub da Costa;Prudencio, Sandra Helena;Shimokomaki, Massami;Soares, Adriana Lourenco;Barbon, Sylvio Jr.
Asian-Australasian Journal of Animal Sciences
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v.32
no.7
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pp.1015-1026
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2019
Objective: The objective of this study was to evaluate three different degrees of white striping (WS) addressing their automatic assessment and customer acceptance. The WS classification was performed based on a computer vision system (CVS), exploring different machine learning (ML) algorithms and the most important image features. Moreover, it was verified by consumer acceptance and purchase intent. Methods: The samples for image analysis were classified by trained specialists, according to severity degrees regarding visual and firmness aspects. Samples were obtained with a digital camera, and 25 features were extracted from these images. ML algorithms were applied aiming to induce a model capable of classifying the samples into three severity degrees. In addition, two sensory analyses were performed: 75 samples properly grilled were used for the first sensory test, and 9 photos for the second. All tests were performed using a 10-cm hybrid hedonic scale (acceptance test) and a 5-point scale (purchase intention). Results: The information gain metric ranked 13 attributes. However, just one type of image feature was not enough to describe the phenomenon. The classification models support vector machine, fuzzy-W, and random forest showed the best results with similar general accuracy (86.4%). The worst performance was obtained by multilayer perceptron (70.9%) with the high error rate in normal (NORM) sample predictions. The sensory analysis of acceptance verified that WS myopathy negatively affects the texture of the broiler breast fillets when grilled and the appearance attribute of the raw samples, which influenced the purchase intention scores of raw samples. Conclusion: The proposed system has proved to be adequate (fast and accurate) for the classification of WS samples. The sensory analysis of acceptance showed that WS myopathy negatively affects the tenderness of the broiler breast fillets when grilled, while the appearance attribute of the raw samples eventually influenced purchase intentions.
Objectives: The Korean Dizziness Handicap Inventory (KDHI), which includes 25 patient-reported items, has been used to assess self-reported dizziness in Korean patients with Parkinson disease (PD). Nevertheless, few studies have examined the KDHI based on item-response theory within this population. The aim of our study was to address the feasibility and clinimetric properties of the KDHI instrument using polytomous Rasch measurement analysis. Methods: The unidimensionality, scale targeting, separation reliability, item difficulty (severity), and response category utility of the KDHI were statistically assessed based on the Andrich rating scale model. The utilities of the orderedresponse categories of the 3-point Likert scale were analyzed with reference to the probability curves of the response categories. The separation reliability of the KDHI was assessed based on person separation reliability (PSR), which is used to measure the capacity to discriminate among groups of patients with different levels of balance deficits. Results: Principal component analyses of residuals revealed that the KDHI had unidimensionality. The KHDI had satisfactory PSR and there were no disordered thresholds in the 3-point rating scale. However, the KDHI showed several issues for inappropriate scale targeting and misfit items (items 1 and 2) for Rasch model. Conclusions: The KDHI provide unidimensional measures of imbalance symptoms in patients with PD with adequate separation reliability. There was no statistical evidence of disorder in polytomous rating scales. The Rasch analysis results suggest that the KDHI is a reliable scale for measuring the imbalance symptoms in PD patients, and identified parts for possible amendments in order to further improve the linear metric scale.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.26
no.3
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pp.167-182
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2021
This study was carried out to investigate temporal and spatial distribution of macrobenthic community and elucidate effects of environmental factors on change of community structure in an intertidal flat, Hakseong-ri, Boryeong, Korea. Field surveys were seasonally conducted to collect samples of sediment and macrobenthos using can core in triplicate at nine stations in 2016 and 2017. Our results showed that sediment had high mud content (above 60%) in most samples and mean content of loss on ignition was 2.3% in 2016. A total of 79 species was collected in the study site during the study period. Mean density and biomass were 611 ind./m2 and 64.1 gWWt/m2, respectively. Heteromastus filiformis was the dominant species (48.6%, 297 ind./m2) followed by Macrophthalmus japonicus (10.1%, 62 ind./m2) and Upogebia major (6.9%, 42 ind./m2). Three assembly groups resulted from cluster analysis were more distinguished by interaction between organisms and frequency of dominant species than by physical and chemical environment characteristics. In addition, macrobenthic community in the Hakseong intertidal flat showed seasonal changes based on non metric multidimensional scaling using species abundance.
Due to the coronavirus pandemic and diplomatic disputes, governments are actively developing a policy to revitalize·reshore manufacturing and to diversify international cooperations. In order to develop such a policy, it is very important to compare and analyze domestic·international geospatial information. Over the decade, the US·EC governments have conducted a series of national researches to build data-based tools that can monitor·analyze regional geospatial information driven by government R&D investments. In the case of the EC system, it can compare geospatial information in domestic and international(including Korea) regions. Compared to US·EC cases, Korean examples of national researches with available data analplatform need future improvements. Current study is investigating an automated analysis methodologies using "National Institute of Science and Technology Information (NTIS)" DB, which was national security data until recently. Research on data-mining regional geospatial information can contribute to support policy fields that need to discover new issues in response to unexpected social problems such as recently faced corona and trade disputes.
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