• Journal of the Korean earth science society
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• v.45 no.3
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• pp.260-276
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• 2024

The purpose of this study is to explore whether pre-service teachers majoring in earth science improve their perception of computational thinking through STEAM classes focused on engineering-based wave power plants. The STEAM class involved designing the most efficient wave power plant model. The survey on computational thinking practices, developed from previous research, was administered to 15 Earth science pre-service teachers to gauge their understanding of computational thinking. Each group developed an efficient wave power plant model based on the scientific principal of turbine operation using waves. The activities included problem recognition (problem solving), coding (coding and programming), creating a wave power plant model using a 3D printer (design and create model), and evaluating the output to correct errors (debugging). The pre-service teachers showed a high level of recognition of computational thinking practices, particularly in "logical thinking," with the top five practices out of 14 averaging five points each. However, participants lacked a clear understanding of certain computational thinking practices such as abstraction, problem decomposition, and using bid data, with their comprehension of these decreasing after the STEAM lesson. Although there was a significant reduction in the misconception that computational thinking is "playing online games" (from 4.06 to 0.86), some participants still equated it with "thinking like a computer" and "using a computer to do calculations". The study found slight improvements in "problem solving" (3.73 to 4.33), "pattern recognition" (3.53 to 3.66), and "best tool selection" (4.26 to 4.66). To enhance computational thinking skills, a practice-oriented curriculum should be offered. Additional STEAM classes on diverse topics could lead to a significant improvement in computational thinking practices. Therefore, establishing an educational curriculum for multisituational learning is essential.

• Journal of forensic and investigative science
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• v.2 no.2
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• pp.5-20
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• 2007

During the period from 2001 to 2005, 29,892 burglaries took place in Korea with the approximate average annual number - 5,978 cases. This study was conducted to analyze the reported burglaries and the result was summarized as follows. There were 8,605 residential invasion burglaries (28.8%) as the most frequent characteristic pattern. The exit was used as the most frequent invasion route for 4,031 invasion burglaries (64.3%), and an unlocked exit door or window was used as the most frequent invasion method for 2,462 invasion burglaries (28.6%). The hours just after midnight (between 00:00 and 04:00) were the most frequent time for invasion burglary to occur. Also, 5,652 burglaries occurred on Wednesday which was twice higher than on Sunday (2,988 burglaries). It was shown that the number of persons injured during burglaries were 260 deaths and 10,610 injuries. The places of the highest occurrence were the street with 10,183 burglaries (34%) and then residential place with 7,527 burglaries (approximately 25%). One-man burglary was the highest complicity: 15,012 offenders (56.1%). The knife was used as the most frequent instrument for 6,498 burglaries (24,3%) what is rare, while no criminal tool or instrument was used for 15,631 burglaries (58.4). During the period from 2001 to 2006, 1,506 burglaries occurred in Daegu and the average annual number was 251 burglaries. Among those,515 residential invasion burglaries (34.2%) took place and the average annual number was approximately 86 cases. The hours just after midnight (between 00:00 and 04:00) were the most frequent time for invasion burglary to occur (194 cases, 37.7%), the place of the highest invasion occurrence was the residential place (259 cases, 50.3%), and the exit was used as the most frequent invasion route (87 cases, 37.7%). An unlocked exit door or window was the most frequent invasion method (65 cases, 25.1%). In addition, pretending to be a delivery man, visitor or following the victim methods were used for 26 burglaries (10%). It is apparent that personal preventive measures against crimes, as well as governmental and social measures, play an important role in preventing burglaries. In particular, based on the analyzed result that an unlocked window or exit door was most frequently used for reported burglaries, it seems that there is a lack of understanding of crime prevention while little effort has been made to prevent crimes. Although everyone knows that locking a door is one of the basic measures to prevent crimes, many people tend to pay little attention to lock a door properly so burglary takes place. This study, therefore, is intended to encourage people to pay more careful attention to crime prevention, in order to help reduce the probability of burglary. With the recent improvement in social understanding of scientific crime investigation, a wide variety of police professions, including crime analysts, crime victim police counselors and coroners, have been prepared to develop the scientific crime investigation and crime analysis. In addition, it is hoped that further this study will contribute to encourage studies on crime prevention to be carried out in the future.

• Journal of Chest Surgery
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• v.41 no.1
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• pp.12-24
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• 2008

Background: It is currently thought that tissue valve degeneration is related to an animal's immune response, which is mainly due to cell surface ${\alpha}$-Gal epitopes. Cell surface ${\alpha}$-Gal epitopes are known to be degraded by the enzyme called green coffee bean ${\alpha}$-Galactosidase. It is also well known that ${\alpha}$-Gal epitopes are immunologically stained by Griffonia Simplicifolia isolectin type B4. We know that many commercially available tissue valves are made of aortic valves and pericardial tissue of pig. So, we investigated whether ${\alpha}$-Gal epitopes of the aortic valve and pericardial tissue of a pig can be removed by green coffee bean ${\alpha}$-Galactosidase, and we did so by comparing immunologic staining of the tissues before and after the enzyme treatment. Material and method: After treating fresh porcine aortic valve and pericardial tissue with green coffee bean ${\alpha}$-Galactosidase at concentrations of 0.5 unit/mL, 1.0 unit/mL, 2.0 unit/mL, respectively, under the condition of pH 6.5, temperature. $4^{\circ}C$ and 24 hours of incubation, each sample was stained with Griffonia Simplicifolia isolectin type B4 immunpfluorescent labeling. We then examined whether the ${\alpha}$-Gal epitopes were reduced or abolished in each consecutive. concentration of green coffee bean ${\alpha}$-Galactosidase by comparing the degree of the Griffonia Simplicifolia isolectin B4 staining in each sample. Result: In the pig aortic valve tissue, a 1.0 unit/mL concentration of green coffee bean ${\alpha}$-Galactosidase at pH 6.5, $4^{\circ}C$ and reaction for 24 hours was enough for complete removal of ${\alpha}$-Gal epitopes from the cell sur face on the immunostaining with Griffonia Simplicifolia isolectin B4. On the other hand, more ${\alpha}$-Gal epitopes were present in the pig pericardial tissue on Griffonia Simplicifolia isolectin B4 staining before the enzyme treatment, and 1.0 unit/mL of galactosidase was not sufficient for complete removal of ${\alpha}$-Gal from the tissue. 2.0 units/mL of green coffee bean ${\alpha}$-Galactosidase was needed to completely remove the ${\alpha}$-Gal epitopes from the pericardial tissue on immunostaining. Conclusion: The ${\alpha}$-Gal epitopes of the pig's aortic valve and pericardial tissue were successfully stained with Griffonia Simplicifolia isolectin B4. We could remove nearly all the ${\alpha}$-Gal epitopes using green coffee bean ${\alpha}$-Galactosidase at the concentration of 1.0 unit/mL in the aortic valve. Of pig, and 2.0 unit/mL was need to nearly completely remove all the ${\alpha}$-Gal epitopes in the pericardial tissue of pig under the condition of pH 6.5, $4^{\circ}C$ and 24 hours of reaction time. In the near future, removal of ${\alpha}$-Gal epitapes in the pig's aortic valve and pericardial tissue will become a powerful tool for the improvement of the tissue valve durability. It needs to be determined if ${\alpha}$-galactosidase treated pig tissue is immune to human anti-Gal antibody or anit-Gal mooclonal antibodies.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• Journal of Distribution Research
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• v.16 no.4
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• pp.65-93
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• 2011

As relationship between buyer and seller has been brought closer and long-term relationship has been more important in B2B markets, the importance of service and service convenience increases as well as product. In homogeneous markets, where service offerings are similar and therefore not key competitive differentiator, providing greater convenience may enable a competitive advantage. Service convenience, as conceptualized by Berry et al. (2002), is defined as the consumers' time and effort perceptions related to buying or using a service. For this reason, B2B customers are interested in how fast the service is provided and how much save non-monetary cost like time or effort by the service convenience along with service quality. Therefore, this study attempts to investigate the impact of service convenience on relationship factors such as relationship satisfaction, relationship commitment, and relationship performance. The purpose of this study is to find out whether service convenience can be a new antecedent of relationship quality and relationship performance. In addition, this study tries to examine how five-dimensional service convenience constructs (decision convenience, access convenience, transaction convenience, benefit convenience, post-benefit convenience) affect customers' relationship satisfaction, relationship commitment, and relationship performance. The service convenience comprises five fundamental components - decision convenience (the perceived time and effort costs associated with service purchase or use decisions), access convenience(the perceived time and effort costs associated with initiating service delivery), transaction convenience(the perceived time and effort costs associated with finalizing the transaction), benefit convenience(the perceived time and effort costs associated with experiencing the core benefits of the offering) and post-benefit convenience (the perceived time and effort costs associated with reestablishing subsequent contact with the firm). Earlier studies of perceived service convenience in the industrial market are none. The conventional studies that have dealt with service convenience have usually been made in the consumer market, or they have dealt with convenience aspects in the service process. This service convenience measure for consumer market can be useful tool to estimate service quality in B2B market. The conceptualization developed by Berry et al. (2002) reflects a multistage, experiential consumption process in which evaluations of convenience vary at each stage. For this reason, the service convenience measure is good for B2B service environment which has complex processes and various types. Especially when categorizing B2B service as sequential stage of service delivery like Kumar and Kumar (2004), the Berry's service convenience measure which reflect sequential flow of service deliveries suitable to establish B2B service convenience. For this study, data were gathered from respondents who often buy business service and analyzed by structural equation modeling. The sample size in the present study is 119. Composite reliability values and average variance extracted values were examined for each variable to have reliability. We determine whether the measurement model supports the convergent validity by CFA, and discriminant validity was assessed by examining the correlation matrix of the constructs. For each pair of constructs, the square root of the average variance extracted exceeded their correlations, thus supporting the discriminant validity of the constructs. Hypotheses were tested using the Smart PLS 2.0 and we calculated the PLS path values and followed with a bootstrap re-sampling method to test the hypotheses. Among the five dimensional service convenience constructs, four constructs (decision convenience, transaction convenience, benefit convenience, post-benefit convenience) affected customers' positive relationship satisfaction, relationship commitment, and relationship performance. This result means that service convenience is important cue to improve relationship between buyer and seller. One of the five service convenience dimensions, access convenience, does not affect relationship quality and performance, which implies that the dimension of service convenience is not important factor of cumulative satisfaction. The Cumulative satisfaction can be distinguished from transaction-specific customer satisfaction, which is an immediate post-purchase evaluative judgment or an affective reaction to the most recent transactional experience with the firm. Because access convenience minimizes the physical effort associated with initiating an exchange, the effect on relationship satisfaction similar to cumulative satisfaction may be relatively low in terms of importance than transaction-specific customer satisfaction. Also, B2B firms focus on service quality, price, benefit, follow-up service and so on than convenience of time or place in service because it is relatively difficult to change existing transaction partners in B2B market compared to consumer market. In addition, this study using partial least squares methods reveals that customers' satisfaction and commitment toward relationship has mediating role between the service convenience and relationship performance. The result shows that management and investment to improve service convenience make customers' positive relationship satisfaction, and then the positive relationship satisfaction can enhance the relationship commitment and relationship performance. And to conclude, service convenience management is an important part of successful relationship performance management, and the service convenience is an important antecedent of relationship between buyer and seller such as the relationship commitment and relationship performance. Therefore, it has more important to improve relationship performance that service providers enhance service convenience although competitive service development or service quality improvement is important. Given the pressure to provide increased convenience, it is not surprising that organizations have made significant investments in enhancing the convenience aspect of their product and service offering.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Journal of Distribution Research
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• v.15 no.2
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• pp.1-34
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• 2010

Introduction As consumers' purchase behavior change into a rational and practical direction, the discount store industry came to have keen competition along with rapid external growth. Therefore as a solution, distribution businesses are concentrating on developing PB(Private Brand) which can realize differentiation and profitability at the same time. And as improvement in customer loyalty beyond customer satisfaction is effective in surviving in an environment with keen competition, PB is being used as a strategic tool to improve customer loyalty. To improve loyalty among PB users, it is necessary to develop PB by examining properties of a customer group, first of all, quality level perceived by consumers should be met to obtain customer satisfaction and customer trust and consequently induce customer loyalty. To provide results of systematic analysis on relations between antecedents influenced perceived quality and variables affecting customer loyalty, this study proposed a research model based on causal relations verified in prior researches and set 16 hypotheses about relations among 9 theoretical variables. Data was collected from 400 adult customers residing in Seoul and the Metropolitan area and using large scale discount stores, among them, 375 copies were analyzed using SPSS 15.0 and Amos 7.0. The findings of the present study followed as; We ascertained that the higher company reputation, brand reputation, product experience and brand familiarity, the higher perceived quality. The study also examined the higher perceived quality, the higher customer satisfaction, customer trust and customer loyalty. The findings showed that the higher customer satisfaction and customer trust, the higher customer loyalty. As for moderating effects between PB and NB in terms of influences of perceived quality factors on perceived quality, we can ascertain that PB was higher than NB in the influences of company reputation on perceived quality while NB was higher than PB in the influences of brand reputation and brand familiarity on perceived quality. These results of empirical analysis will be useful for those concerned to do marketing activities based on a clearer understanding of antecedents and consecutive factors influenced perceived quality. At last, discussions about academical and managerial implications in these results, we suggested the limitations of this study and the future research directions. Research Model and Hypotheses Test After analyzing if antecedent variables having influence on perceived quality shows any difference between PB and NB in terms of their influences on them, the relation between variables that have influence on customer loyalty was determined as Figure 1. We established 16 hypotheses to test and hypotheses are as follows; H1-1: Perceived price has a positive effect on perceived quality. H1-2: It is expected that PB and NB would have different influence in terms of perceived price on perceived quality. H2-1: Company reputation has a positive effect on perceived quality. H2-2: It is expected that PB and NB would have different influence in terms of company reputation on perceived quality. H3-1: Brand reputation has a positive effect on perceived quality. H3-2: It is expected that PB and NB would have different influence in terms of brand reputation on perceived quality. H4-1: Product experience has a positive effect on perceived quality. H4-2: It is expected that PB and NB would have different influence in terms of product experience on perceived quality. H5-1: Brand familiarity has a positive effect on perceived quality. H5-2: It is expected that PB and NB would have different influence in terms of brand familiarity on perceived quality. H6: Perceived quality has a positive effect on customer satisfaction. H7: Perceived quality has a positive effect on customer trust. H8: Perceived quality has a positive effect on customer loyalty. H9: Customer satisfaction has a positive effect on customer trust. H10: Customer satisfaction has a positive effect on customer loyalty. H11: Customer trust has a positive effect on customer loyalty. Results from analyzing main effects of research model is shown as