• Asia pacific journal of information systems
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• v.22 no.3
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• pp.53-74
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• 2012

A challenge in fostering virtual communities is the continuous supply of knowledge, namely members' willingness to contribute knowledge to their communities. Previous research argues that giving away knowledge eventually causes the possessors of that knowledge to lose their unique value to others, benefiting all except the contributor. Furthermore, communication within virtual communities involves a large number of participants with different social backgrounds and perspectives. The establishment of mutual understanding to comprehend conversations and foster knowledge contribution in virtual communities is inevitably more difficult than face-to-face communication in a small group. In spite of these arguments, evidence suggests that individuals in virtual communities do engage in social behaviors such as knowledge contribution. It is important to understand why individuals provide their valuable knowledge to other community members without a guarantee of returns. In virtual communities, knowledge is inherently rooted in individual members' experiences and expertise. This personal nature of knowledge requires social interactions between virtual community members for knowledge transfer. This study employs the social capital theory in order to account for interpersonal relationship factors and identity theory for individual and group factors that may affect knowledge contribution. First, social capital is the relationship capital which is embedded within the relationships among the participants in a network and available for use when it is needed. Social capital is a productive resource, facilitating individuals' actions for attainment. Nahapiet and Ghoshal (1997) identify three dimensions of social capital and explain theoretically how these dimensions affect the exchange of knowledge. Thus, social capital would be relevant to knowledge contribution in virtual communities. Second, existing research has addressed the importance of identity in facilitating knowledge contribution in a virtual context. Identity in virtual communities has been described as playing a vital role in the establishment of personal reputations and in the recognition of others. For instance, reputation systems that rate participants in terms of the quality of their contributions provide a readily available inventory of experts to knowledge seekers. Despite the growing interest in identities, however, there is little empirical research about how identities in the communities influence knowledge contribution. Therefore, the goal of this study is to better understand knowledge contribution by examining the roles of social capital and identity in virtual communities. Based on a theoretical framework of social capital and identity theory, we develop and test a theoretical model and evaluate our hypotheses. Specifically, we propose three variables such as cohesiveness, reciprocity, and commitment, referring to the social capital theory, as antecedents of knowledge contribution in virtual communities. We further posit that members with a strong identity (self-presentation and group identification) contribute more knowledge to virtual communities. We conducted a field study in order to validate our research model. We collected data from 192 members of virtual communities and used the PLS method to analyse the data. The tests of the measurement model confirm that our data set has appropriate discriminant and convergent validity. The results of testing the structural model show that cohesion, reciprocity, and self-presentation significantly influence knowledge contribution, while commitment and group identification do not significantly influence knowledge contribution. Our findings on cohesion and reciprocity are consistent with the previous literature. Contrary to our expectations, commitment did not significantly affect knowledge contribution in virtual communities. This result may be due to the fact that knowledge contribution was voluntary in the virtual communities in our sample. Another plausible explanation for this result may be the self-selection bias for the survey respondents, who are more likely to contribute their knowledge to virtual communities. The relationship between self-presentation and knowledge contribution was found to be significant in virtual communities, supporting the results of prior literature. Group identification did not significantly affect knowledge contribution in this study, inconsistent with the wealth of research that identifies group identification as an important factor for knowledge sharing. This conflicting result calls for future research that examines the role of group identification in knowledge contribution in virtual communities. This study makes a contribution to theory development in the area of knowledge management in general and virtual communities in particular. For practice, the results of this study identify the circumstances under which individual factors would be effective for motivating knowledge contribution to virtual communities.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.1-18
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• 2016

Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

• Journal of Mushroom
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• v.14 no.2
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• pp.59-63
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• 2016

A new commercial strain of oyster mushroom (was developed by hyphal anastomosis, and was improved byhybridization between a monokaryotic strain derived from Pleurotus ostreatus ASI 0635 (Gonji 7ho) and a dikaryotic strain derived from P. ostreatus ASI 0666 (Mongdol). The optimum temperatures for mycelial growth and fruiting body development were $25{\sim}30^{\circ}C$ and $12{\sim}18^{\circ}C$, respectively. When PDA (potato dextrose agar medium) and MCM (mushroom complete medium) were compared, mycelial growth was faster in MCM. Similar results were observed with the control strain P. ostreatus ASI 2504 (Suhan 1ho). Analysis of the genetic characteristics of the new cultivar ('Gosol') showed a different DNA profile from that of the control ASI 2504 strain, when RAPD (raurpDNA) primers URP1, 2, 3, and 7 were used. Fruiting body production per bottle was approximately116 g based on a production performance test. In addition, yields from a farm field trial were stably achieved in an inadequate production enviro. The color of the pileus was blackish gray, and the stipe was long and thick. Therefore, we expect that this new strain will satisfy consumer demand for high quality mushrooms.

• Journal of dental hygiene science
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• v.11 no.3
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• pp.265-272
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• 2011

The purpose of this study is to compare oral hygiene status between young adult group and older adult group and to suggest a pathway model of oral health level in self-assessed. Subjects were totally 80 people with young adult group and the older adult group. The data, which was collected by surveying for one month from July 1, 2010 to July 30, was analyzed with SPSS VERSION 19.0 and AMOS 19.0. Oral hygiene test and questionnaire survey were carried out from targeting. 1. The young adult group and older adult group had the same quality in oral health level score and living habit. 2. The oral hygiene status in young adult and older adult group was same in 7 items(58.33%) out of 12 items. 3. Oral health level score in self-assessed of young adult group could be explained with 34% by 3 variables. Older adult group could be explained with 26% by 2 variables. 4. In young adult, the fitness of path model was very good with 0.96 in CFI, 0.94 in TLI, and 0.00 in RMSEA. In older adults, the fitness of path model was very good with 1.00 in CFI, 1.15 in TLI, and 0.00 in RMSEA. This might imply if TMJ disorder level and number of infection is neglected in young aldults, mastication function will be significantly effected in older adults. Thus, development and management of health education program is needed based on self-assessment oral health level by young adults group and older adults group.

• Journal of Animal Science and Technology
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• v.54 no.2
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• pp.95-101
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• 2012

The objective of this study was to examine the effect of amides as a cryoprotectant for semen cryopreservation in Korean Jeju Black Bull. The semen was cryopreserved with extenders containing 5% dimethyl acetamide (DMA), 5% dimethyl formamide (DMF), 5% methyl formamide (MF) or 7% glycerol. Post-thawed sperm were evaluated for sperm motility, viability, acrosome integrity and membrane integrity. Post-thawed sperm motility was significantly higher (p<0.05) in glycerol and DMF ($64.00%{\pm}9.62$ and $59.00%{\pm}5.48$, respectively) than DMA and MF ($50.00%{\pm}3.24$ and $44.00%{\pm}4.18$, respectively). Sperm viability wassignificantly higher (p<0.05) in glycerol and DMF ($58.25%{\pm}7.35$ and $53.05%{\pm}3.77$, respectively) than others. However, for sperm motility and viability, there were no differences among glycerol and DMF. Also, swelling sperm ratio by hypo-osmetic selling test (HOST) was significantly increased (p<0.05) in glycerol and DMF treatments ($45.12%{\pm}25.08$ and $44.95%{\pm}8.58$, respectively). The percentage of capacitated sperm assessed by CTC staining, F pattern was lower (p<0.05) in DMF than others. B pattern was increased (p<0.05) in DMA, DMF and MF when compared with glycerol. AR pattern ratio was decreased (p<0.05) in glycerol and DMF when compared with DMA and MF. These results suggested that amides performed better and could be used as a cryoprotectant for semen freezing of Korean Jeju Black Bull.

• Journal of dental hygiene science
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• v.16 no.6
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• pp.481-487
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• 2016

The elderly population with dementia is rapidly growing in South Korea. The aim of this study was to investigate the relationship between dementia and oral health in 197 subjects aged ${\geq}65$ years. The questionnaire included questions on subjective health status, subjective health concern, subjective oral health status and behavior, mastication ability, Oral Health Impact Profile-14 (OHIP-14), and Korean Dementia Screening Questionnaires (KDSQ). Oral examination was conducted by a single dentist to evaluate upper or lower denture use, and determine the numbers of remaining and functioning teeth, including implant and fixed prosthesis. The subjects who required a dementia test (KDSQ-C [cognition] of ${\geq}6$) had significant differences in systemic disease prevalence rate, subjective health status, subjective health concern, KDSQ-V (vascular disease) score, KDSQ-D (depression) score, subjective oral treatment need, key food mastication ability and OHIP-14 score compared to the healthy subjects. The proportion of denture wearers, total remaining teeth, total functioning teeth, toothbrushing frequency, oral pain severity, symptoms of periodontal disease, subjective oral health status, and subjective oral health concern showed no significant differences between the two groups. KDSQ-C and OHIP-14 scores showed a strong positive relationship, while KDSQ-C score and total remaining teeth or key food mastication ability showed a weak negative relationship. In the multiple regression analysis, the KDSQ-D, KDSQ-V, and OHIP-14 scores influenced the KDSQ-C scores. We suggest a relationship between oral health and cognitive impairment.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• Journal of the Korean Society of Radiology
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• v.10 no.6
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• pp.403-409
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• 2016

MRI scan is a useful method in the diagnosis of musculoskeletal excellent contrast of the organization. Depending on the patient's musculoskeletal examinations state the type of aids provided the aid is used there is also challenging as well as the costs do not vary. This study was produced by the use of 3D printing technology, an MRI aids. Aids in the production process, then through 3D modeling and then convert stl files using (3D MAX.2014, Fusion360) slicing programs (Cubicreater 2.1ver., Cura 15.4ver) converted to G-code printed on the FDM scheme (Cubicon Style, output was MICRO MAKE). Output is, but in the FDM to evaluate the SNR on the MRI images were compared to the test is the case before use, and then to produce a Water Phantom case of a PLA, ABS, a TPU thickness 3mm, using aids before, It was evaluated in a clinical image after qualitatively. Obtaining an image of SNR Warter Phantom appeared to have been evaluated as T1 NON $123.778{\pm}28.492$, PLA $123.522{\pm}28.373$, ABS $124.461{\pm}25.716$, TPU $124.843{\pm}27.272$. T2 NON $127.421{\pm}26.949$, was rated as PLA $124.501{\pm}27.768$, ABS $128.663{\pm}26.549$, TPU $130.171{\pm}25.998$. The results did not show statistically significant differences. The use of assistive devices before and after images Clinical evaluation method palliative $3.20{\pm}0.88$, $3.95{\pm}0.76$ after using the aids used to aid improved the quality of the image. Production of the auxiliary mechanism using a future 3D printing is expected are thought to be used clinically, it can be an aid making safe and comfortable than the inspection of the patient is an alternative to improve the problems of the aids used in the conventional do.

• Journal of Food Hygiene and Safety
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• v.33 no.4
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• pp.272-279
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• 2018

The high pressure processing (HPP) is a technology which can preserve the quality of foods, such as the fresh taste, incense, texture, vitamin content, and so on, by minimizing the heating process. It does so by applying an instantaneous and uniform pressure that is the same as the water pressure that is 60 km deep in the sea. HPP is a technology that can inhibit food poisoning and spoilage caused by microorganisms and is currently an actively studied area. In this study, we investigated the effects of a high pressure treatment (0, 4, 6 min) on sliced ham, which is a typical meat product, at 600 MP a were tested for their effect on freshness. Moisture contents varied from 48 to 69%, salinity varied from 1.07 to 1.11%, and the pH decreased from 6.4~6.5 to 6.1~5.15. However, there was no difference between the control and treatment groups. General bacteria stored at $20^{\circ}C$ after hyper-pressure treatment were found to have no significant microorganisms in all groups until 4 weeks. but exceeded $10^5$ in control group and HPP 6 min treatment group from 5 weeks, At week 7, it was found to exceed $10^6$. The results indicate it was not possible to ingest food in the 4-and 6 minute treatment groups. Coliform was not observed in all groups despite observing for a total of 7 weeks at $20^{\circ}C$ weight test. VBN, a method used to determine the protein freshness of meat, showed a VBN value of less than 1 mg% until the fourth week and a value of 1 to 2 mg% after 5 weeks. The TBA was used as an index of the degree of fat acidosis in the meat tissues. The results showed it was below 0.18 mgMA / kg until the end of 7 weeks; this value was within the range for fresh meat, and there was no difference in treatment group. In this experiment, deformation of the packaging material did not occur and no swelling occurred due to the generation of gas. It is believed that the basic preservation effect was achieved only by blocking with the air due to the close contact of the packaging material.