• Asia pacific journal of information systems
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• v.19 no.3
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• pp.99-124
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• 2009

Many firms in Korea have adopted and used advanced information technology in an effort to boost efficiency. The process of adapting to the new technology, at the same time, can vary from one firm to another. As such, this research focuses on several relevant factors, especially the roles of social interaction as a key variable that influences the technology adaptation process and the outcomes. Thus far, how a firm goes through the adaptation process to the new technology has not been yet fully explored. Previous studies on changes undergone by a firm or an organization due to information technology have been pursued from various theoretical points of views, evolved from technological and institutional views to an integrated social technology views. The technology adaptation process has been understood to be something that evolves over time and has been regarded as cycles between misalignments and alignments, gradually approaching the stable aligned state. The adaptation process of the new technology was defined as "appropriation" process according to Poole and DeSanctis (1994). They suggested that this process is not automatically determined by the technology design itself. Rather, people actively select how technology structures should be used; accordingly, adoption practices vary. But concepts of the appropriation process in these studies are not accurate while suggested propositions are not clear enough to apply in practice. Furthermore, these studies do not substantially suggest which factors are changed during the appropriation process and what should be done to bring about effective outcomes. Therefore, research objectives of this study lie in finding causes for the difference in ways in which advanced information technology has been used and adopted among organizations. The study also aims to explore how a firm's interaction with social as well as technological factors affects differently in resulting organizational changes. Detail objectives of this study are as follows. First, this paper primarily focuses on the appropriation process of advanced information technology in the long run, and we look into reasons for the diverse types of the usage. Second, this study is to categorize each phases in the appropriation process and make clear what changes occur and how they are evolved during each phase. Third, this study is to suggest the guidelines to determine which strategies are needed in an individual, group and organizational level. For this, a substantially grounded theory that can be applied to organizational practice has been developed from a longitudinal comparative case study. For these objectives, the technology appropriation process was explored based on Structuration Theory by Giddens (1984), Orlikoski and Robey (1991) and Adaptive Structuration Theory by Poole and DeSanctis (1994), which are examples of social technology views on organizational change by technology. Data have been obtained from interviews, observations of medical treatment task, and questionnaires administered to group members who use the technology. Data coding was executed in three steps following the grounded theory approach. First of all, concepts and categories were developed from interviews and observation data in open coding. Next, in axial coding, we related categories to subcategorize along the lines of their properties and dimensions through the paradigm model. Finally, the grounded theory about the appropriation process was developed through the conditional/consequential matrix in selective coding. In this study eight hypotheses about the adaptation process have been clearly articulated. Also, we found that the appropriation process involves through three phases, namely, "direct appropriation," "cooperate with related structures," and "interpret and make judgments." The higher phases of appropriation move, the more users represent various types of instrumental use and attitude. Moreover, the previous structures like "knowledge and experience," "belief that other members know and accept the use of technology," "horizontal communication," and "embodiment of opinion collection process" are evolved to higher degrees in their dimensions of property. Furthermore, users continuously create new spirits and structures, while removing some of the previous ones at the same time. Thus, from longitudinal view, faithful and unfaithful appropriation methods appear recursively, but gradually faithful appropriation takes over the other. In other words, the concept of spirits and structures has been changed in the adaptation process over time for the purpose of alignment between the task and other structures. These findings call for a revised or extended model of structural adaptation in IS (Information Systems) literature now that the vague adaptation process in previous studies has been clarified through the in-depth qualitative study, identifying each phrase with accuracy. In addition, based on these results some guidelines can be set up to help determine which strategies are needed in an individual, group, and organizational level for the purpose of effective technology appropriation. In practice, managers can focus on the changes of spirits and elevation of the structural dimension to achieve effective technology use.

• The Journal of the Petrological Society of Korea
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• v.7 no.2
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• pp.132-145
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• 1998

The coal-bearing siliciclastic rocks of the Lower Permian Jangseong Formation, Samcheog coalfield, represent a megacyclothem which shows cyclic repetitions of sandstone, shale, coaly shale, and coals. Petrographic, geochemical, and SEM studies for sandstone samples, and XRD analysis for clay minerals were carried out to understand diagenesis in the sandstones of the Jangseong Formation. The Jangseong sandstones are composed of 60% quartz (mainly monocrystalline quartz) and 36% clay matrix and cement with minor amounts of feldspar, lithic fragments and accessory minerals (less than 4%). Jangseong sandstones are classified mostly as quartzwackes and partly as lithic graywackes according to the scheme of Dott(1964). The textural relationships between authigenic minerals and cements in thin sections and SEM photomicrographs suggest the paragenetic sequence as follows; (1) mechanical compaction, (2) cementation by quartz overgrowth, (3) formation of authigenic clay minerals (illite, kaolinite), (4) dissolution of framework grains and development of secondary porosity, and (5) later-stage pore-filling by pyrophyllite. We propose that these diagenetic processes might be due to organic-inorganic interaction between the dominant framework grains and the formation water. The Al, Si ions and organic acid, derived from dewatering of interbedded organic-rich shale and coals, were transported into the Jangseong sandstones. This caused changes in the chemistry of the formation water of the sandstones, and resulted in overgrowth of quartz and precipitation of authigenic clay minerals of kaolinite and illite. The secondary pores, produced during dissolution of clay and framework grains by organic acid and $CO_2$ gas, were conduit for silica-rich solution into the Jangseong sandstones and the influx of silica-rich solution produced the late-stage pyrophyllite after the expanse of kaolinite. The origin of the solution that formed pyrophyllite is not likely to be the organic-rich formation water based on the observation of fracture-filling pyrophyllite in the Jangseong sandstones, but the process of pyrophyllite pore-filling was indirectly related to organic-inorganic interaction.

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.

• Journal of Dental Rehabilitation and Applied Science
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• v.25 no.4
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• pp.361-374
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• 2009

For successful osteogenesis around the implants, interaction between implant surface and surrounding tissue is important. Biomechanical bonding and biochemical bonding are considered to influence the response of adherent cells. But the focus has shifted surface chemistry. The purpose of this study is to evaluate the MC3T3-E1 osteoblast like cell responses of magnesium (Mg) ion implanted titanium surface produced using a plasma source ion implantation method. Commercially pure titanium disc was used as substrates. The discs were prepared to produce four different surface, A: Machine turned surface, B: Mg implanted surface, C: sandblasted surface, D: sandblasted and Mg implanted surface. MC3T3 El osteoblastic like cells were cultured on the disc specimens. Cell adhesion, proliferation, differentiation, and synthesis of extracellular matrix were evaluated. The cell adhesion morphology was evaluated by SEM. RT PCR assay was used for assessment of cell adhesion, proliferation and differentiation. ALP activity was measured for cell differentiation. The results of this study were as follows: 1. SEM showed that cell on Mg ion groups was more proliferative than that of non Mg ion groups. On the machine turned surface, cell showed some degree of contact guidance in aligning with the machining grooves. 2. In RT PCR analysis, osteonectin and c-fos mRNA were more expressed on sandblasted and Mg ion implanted group. 3. ALP activity was not significantly different among all groups. Within the limitations of this study, the following conclusions were drawn: It might indicate Mg ion implanted titanium surface induce better bone response than non Mg ion groups.

• Tuberculosis and Respiratory Diseases
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• v.52 no.2
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• pp.117-127
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• 2002

Backgroud : MUC1 mucin is a heavily glycosylated large glycoprotein and is expressed aberrantly in carcinoma. CD44 is polymorphic family of cell surface glycoproteins participating in cell-cell adhesion and modulation of the cell-matrix interaction. MUC1 mucin and CD44 expression have been implicated in a tumor invasion and metastasis in certain malignancies. In this study, the expression of MUC1 and the standard form of CD44 (CD44s) was examined in non-small cell lung cancer (NSCLC). Methods : Immunohistochemical staining using monoclonal antibodies including MUC1 glycoprotein and CD44s was performed on 80 NSCLC surgical specimens. The association between MUC1 and CD44s expression and the histological type and tumor stage was investigated. Results : Depolarized MUC1 expression in more than 10% of cancer cells was found in 12 (27.9%) out of 43 squamous cell carcinomas (SCCs) and 12 (32.4%) out of 37 adenocarcinomas (ACs). It was not associated with the tumor histological type and the TNM-stage in SCCs. Depolarized MUC1 expression correlated with the N-stage in ACs (p=0.036). CD44s was expressed in 36 (83.7%) out of 43 SCCs and 14 (37.8%) out of 37 ACs. Reduced CD44s expression correlated with the N-stage (p=0.031) and the TNM-stage (p=0.006) in SCCs. Conclusions : Depolarized MUC1 expression was related to the nodal stage in NSCLC adenocarcinoma. Reduced CD44s expression was related to nodal involvement and the TNM-stage in squamous cell carcinoma. This suggests that MUC1 and CD44s expression in NSCLC might play important roles in tumor progression and cap be used as prognostic variables.

• Information Systems Review
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• v.21 no.4
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• pp.1-29
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• 2019

The knowledge resources take a role in promoting the sustainable growth of organization. Therefore, it is important for the members of organization to acquire knowledge consistently so that the company can continue to grow. Knowledge service is the field that provides information and infrastructure which enable the members of organization to acquire new knowledge. As we recognized the importance of knowledge services, we analyzed the level of knowledge service management and development through the impact of knowledge quality on user capabilities. First, the matrix of knowledge patterns was presented based on the type of information and the level of customer interaction. According to patterns, the knowledge service was classified into three types of information providing, information analysis, and infrastructure, and then the results of structural model analysis were presented for each type. It found that the impact of knowledge service quality on user competence was different according to the type of service. The results suggested new indicators for measuring the performance of knowledge services, and provided information for reconstructing services based on the user considering the integrated operation of knowledge service and organizational designing knowledge service.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Journal of Chest Surgery
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• v.39 no.1 s.258
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• pp.1-11
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• 2006

Background: CD44 is a glycoprotein on the cell surface which is involved in the cell-to-cell and cell-to-matrix interaction. The standard form, CD44s and multiple isoforms are determined by alternative splicing of 10 exons. Recent studies have suggested that CD44 may help invasion and metastasis of various epithelial tumors as well as activation of Iymphocytes and monocytes. The expression pattern of CD44 can be different according to tumor types. The author studied the expression pattern of CD44s and one of its variants, CD44v6 in non-small cell lung carcinomas (NSCLC) to find their implications on clinicopathologic aspects, including the survival of the patients. Material and Method: A total of 89 primary NSCLSs (48 squamous cell carcinomas, 33 adenocarcinomas, and 8 undifferentiated large cell carcinomas) were retrieved during the years between 1985 to 1994. The immunohisto chemistry was done by using monoclonal antibodies and the CD44 expression for angiogenesis was evaluated by counting the number of tumor microvessels. Result: Seventy-one (79.8$\%$) and 64 (71 .9$\%$) among 89 NSCLSs revealed the expression of CD44s and CD44v6, respectively. The expression of CD44s was well correlated with that of CD44v6 (r=0.710, p < 0.0001). The expression of CD44s and CD44v6 was associated with the histopathologic type of the NSCLCs, and squamous cell carcinoma was the type that showed the highest expression of CD44s and CD44v6 (p < 0.0001). Microvessel count was the highest in adenocarcinomas (113.6$\pm$69.7 on 200-fold magnification and 54.8$\pm$41.1 on 400-fold magnification) and correlated with the tumor size of TNM system (r=0.217, p=0.043) and CD44s expression (r=0.218, p=0.040). In adenocarcinoma, the patients with higher CD44s expression survived shorter than those with lower CD44s expression (p=0.0194) but there was no statistical significance on multivariate analysis(p=0.3298). Conclusion: The expression of both CD44s and CD44v6 may be associated with the squamous differentiation in non-small cell lung carcinomas. The relationship of CD44s expression with micro-vessel density of the tumor suggests an involvement of CD44s in tumor angiogenesis, which in turn would help tumor growth.

• Tuberculosis and Respiratory Diseases
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• v.45 no.4
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• pp.861-869
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• 1998

Backgrounds: The injury of a tissue results in the infalmmation, and the imflammed tissue is replaced by the normal parenchymal cells during the process of repair. But, constitutional or repetitive damage of a tissue causes the deposition of collagen resulting in the loss of its function. These lesions are found in the lung of patients with idiopathic pulmonary fibrosis, complicated fibrosis after diffuse alveolar damage (DAD) and inorganic dust-induced lung fibrosis. The tissue from lungs of patients undergoing episodes of active and/or end-stage pulmonary fibrosis shows the accumulation of inflammatory cells, such as mononuclear cells, neutrophils, mast cells and eosinophils, and fibroblast hyperplasia. In this regard, it appears that the inflammation triggers fibroblast activation and proliferation with enhanced matrix synthesis, stimulated by inflammatory mediators such as interleukin-1 (IL-1) and/or tumor necrosis factor (TNF). It has been well known that TGF-$\beta$ enhance the proliferation of fibroblasts and the production of collagen and fibronectin, and inhibit the degradation of collagen. In this regard, It is likely that TGF-$\beta$ undergoes important roles in the pathogenesis of pulmonary fibrosis. Nevertheless, this single cytokine is not the sole regulator of the pulmonary fibrotic response. It is likely that the balance of many cytokines including TGF-$\beta$, IL-1, IL-6 and TNF-$\alpha$ regulates the pathogenesis of pulmonary fibrosis. In this study, we investigate the interaction of TGF-$\beta$, IL-1$\beta$, IL-6 and TNF-$\alpha$ and their effect on the proliferation of fibroblasts. Methods: We used a human fibroblast cell line, MRC-5 (ATCC). The culture of MRC-5 was confirmed by immunofluorecent staining. First, we determined the concentration of serum in cuture medium, in which the proliferation of MRC-5 is supressed but the survival of MRC-5 is retained. Second, we measured optical density after staining the cytokine-stimulated cells with 0.5% naphthol blue black in order to detect the effect of cytokines on the proliferation of MRC-5. Result: In the medium containing 0.5% fetal calf serum, the proliferation of MRC-5 increased by 50%, and it was maintained for 6 days. IL-1$\beta$, TNF-$\alpha$ and IL-6 induced the proliferation of MRC-5 by 45%, 160% and 120%, respectively. IL-1$\beta$ and TNF-$\alpha$ enhanced TGF-$\beta$-induced proliferation of MRC-5 by 64% and 159%, but IL-6 did not affect the TGF-$\beta$-induced proliferation. And lNF-$\alpha$-induced proliferation of MRC-5 was reduced by IL-1$\beta$ in 50%. TGF-$\beta$, TNF-$\alpha$ and both induced the proliferation of MRC-5 to 89%, 135% and 222%, respectively. Conclusions: TNF-$\alpha$, TGF-$\beta$ and IL-1$\beta$, in the order of the effectiveness, showed the induction of MRC-5 proliferation of MRC-5. TNF-$\alpha$ and IL-1$\beta$ enhance the TGF-$\beta$-induced proliferation of MRC-5, but IL-6 did not have any effect TNF-$\alpha$-induced proliferation of MRC-5 is diminished by IL-1, and TNF-$\alpha$ and TGF-$\beta$ showed a additive effect.