• Journal of The Korean Association For Science Education
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• v.29 no.8
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• pp.793-811
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• 2009

The purpose of this study is to understand how a teacher's teaching can be changed while he or she teaches the same contents in different classes. The qualitative research method was used in this study. Data were collected from classroom observations, several in-depth interviews, and stimulated-recall interviews after each class. All the data were transcribed and analyzed interpretively, and then, the results of the analysis were checked by each participating teacher. The results are as follows: First, changes appeared in each class in terms of the teaching items, tools, sequence, and time, even though the same teacher taught the same contents. It showed that the teacher's teaching practice changed immediately and intuitively in class. Second, teachers tried to implement "exploratory teaching" or "move-testing teaching" to address the emerging problems during their teaching. They then reflected on and modified their own teaching. This type of change, which happened during the teaching practice, can be an example of "Reflection-in-practice." Thus, the results of this study can provide helpful insights into how teachers might adapt and reflect in their teaching. It suggests that teachers need to recognize their subconscious teaching changes and learn "Reflection-in-practice."

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.3-10
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• 2024

The purpose of this study is to analyze the effects of smart construction equipment applied at the construction site of the first smart city in the Korea and derive an application strategy for the utilization of smart construction equipment. To achieve this, aythors examined the practical effects and issues of safety systems and construction systems utilizing machine guidance (MG) technology, which is a representative smart construction equipment used in civil engineering construction sites. Both the MG safety system and MG construction system were found to be sufficiently effective in improving construction productivity. However, there are challenges that need to be addressed, such as the approval process for work results using MG systems, system changes due to frequent replacement of on-site equipment, and usability improvements for elderly on-site workers. The study presented some solutions that have been implemented on-site to address these issues. The utilization effects and issues presented in the study were analyzed through direct feedback from workers and managers who have utilized the MG technology on-site for a considerable period of time. These results can be used as preliminary data for the similar construction projects, considering the limited availability of empirical analysis data for equipment automation.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.1
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• pp.10-20
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• 2024

RNA-sequencing (RNA-seq) is a technique used for providing global patterns of transcriptomes in samples. However, it can only provide the average gene expression across cells and does not address the heterogeneity within the samples. The advances in single-cell RNA sequencing (scRNA-seq) technology have revolutionized our understanding of heterogeneity and the dynamics of gene expression at the single-cell level. For example, scRNA-seq allows us to identify the cell types in complex tissues, which can provide information regarding the alteration of the cell population by perturbations, such as genetic modification. Since its initial introduction, scRNA-seq has rapidly become popular, leading to the development of a huge number of bioinformatic tools. However, the analysis of the big dataset generated from scRNA-seq requires a general understanding of the preprocessing of the dataset and a variety of analytical techniques. Here, we present an overview of the workflow involved in analyzing the scRNA-seq dataset. First, we describe the preprocessing of the dataset, including quality control, normalization, and dimensionality reduction. Then, we introduce the downstream analysis provided with the most commonly used computational packages. This review aims to provide a workflow guideline for new researchers interested in this field.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.27 no.4
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• pp.206-214
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• 2024

Purpose: Few studies have reported the prevalence of inflammatory bowel disease unclassified (IBDU) among Korean pediatric IBD (PIBD) population. To address this gap, we used two tertiary centers and nationwide population-based healthcare administrative data to estimate the prevalence of Korean pediatric IBDU at the time of diagnosis. Methods: We identified 136 patients aged 2-17 years with newly diagnosed IBD (94 Crohn's disease [CD] and 42 ulcerative colitis [UC]) from two tertiary centers in Korea between 2005 and 2017. We reclassified these 136 patients using the revised Porto criteria. To estimate the population-based prevalence, we analyzed Korean administrative healthcare data between 2005 and 2016, which revealed 3,650 IBD patients, including 2,538 CD and 1,112 UC. By extrapolating the reclassified results to a population-based dataset, we estimated the prevalence of PIBD subtypes. Results: Among the 94 CD, the original diagnosis remained unchanged in 93 (98.9%), while the diagnosis of one (1.1%) patient was changed to IBDU. Among the 42 UC, the original diagnosis remained unchanged in 13 (31.0%), while the diagnoses in 11 (26.2%), 17 (40.5%), and one (2.4%) patient changed to atypical UC, IBDU, and CD, respectively. The estimated prevalences of CD, UC, atypical UC, and IBDU in the Korean population were 69.5%, 9.4%, 8.0%, and 13.1%, respectively. Conclusion: This study is the first in Korea to estimate the prevalence of pediatric IBDU. This prevalence (13.1%) aligns with findings from Western studies. Large-scale prospective multicenter studies on PIBDU are required to examine the clinical features and outcomes of this condition.

• Journal of Technology Innovation
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• v.32 no.2
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• pp.23-58
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• 2024

Despite the important roles of institutions and their collaboration in producing knowledge for innovation, the lack of accurate methods for identifying such knowledge-producing institutions has restricted empirical research on the role of institutions in innovation. This study explores methods to enhance the accuracy of identifying institutions involved in innovation process. To this end, we propose ways to improve accuracy in both aspects of information - data and algorithms - using bibliographic information in the digital health field. Specifically, in the data processing stage before applying algorithms, we address contextual inaccuracies of bibliographic information; in the algorithm application stage, we propose methods to improve the ambiguity of institution names (IND). When compared with the PKG dataset, which is publicly available datasets based on the same bibliographic information, our methods doubled the number of cases available for subsequent analysis. We also discovered that the contribution of Korean institutions in the digital health field is either underestimated or overestimated. The method presented in this study is expected to contribute to empirically researching the role of knowledge-producing institutions in innovation process and ecosystem.

• Therapeutic Science for Rehabilitation
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• v.13 no.3
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• pp.23-36
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• 2024

Objective : This study investigated the mediating effect of social networks on the relationship between social networking service (SNS) dependence and healthy lifestyle among university students. Methods : Data from 374 university students were collected via online surveys. Sociodemographic data, SNS dependence, social networks, and healthy lifestyle were assessed. Mediation analysis using bootstrapping was conducted to examine the mediating effect of social networks on the relationship between SNS dependence and healthy lifestyle. Results : A total of 374 university students participated in this study. The average age of the participants was 21.8 years (standard deviation = 2.1), and 70.3% were females. Mediation analysis revealed that SNS dependence had a direct effect on healthy lifestyle (β = -.078, standard error [SE] = .052, p = .128), which was not statistically significant. However, a statistically significant indirect effect was observed through social networks (β = -.052, SE = .020, p = .011). The total effect of SNS dependence on a healthy lifestyle was significant (β = -.130, SE = .053, p = .014). Conclusion : Social networks play a critical role in promoting a healthy lifestyle. Health professionals should prioritize interventions to address SNS dependence and leverage social networks to encourage healthier behaviors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.747-761
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• 2024

Recently, modern vehicles have been controlled by Electronic Control Units (ECUs), by which the safety and convenience of drivers are highly improved. It is known that a luxury vehicle has more than 100 ECUs to electronically control its function. However, the modern vehicles are getting targeted by cyber attacks because of this computer-based automotive system. To address the cyber attacks, automotive manufacturers have been developing some methods for securing their vehicles, such as automotive Intrusion Detection System (IDS). This development is only allowed to the automotive manufacturers because they have databases for their in-vehicle network (i.e., DBC Format File) which are highly confidential. This confidentiality poses a significant challenge to external researchers who attempt to conduct automotive security researches. To handle this restricted information, in this paper, we propose a method to partially understand the DBC Format File by analyzing in-vehicle network traffics. Our method is designed to analyze Controller Area Network (CAN) traffics so that checksum signals are identified in CAN Frame Data Field. Also, our method creates a Lookup Set by which a checksum signal is correctly estimated for a given message. We validate our method with the publicly accessible dataset as well as one from a real vehicle.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.107-120
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• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.

• Journal of Korean Ophthalmic Optics Society
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• v.18 no.3
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• pp.231-239
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• 2013

Purpose: To design and fabricate the auto pattern maker for the development. Methods: we got the necessary data, needed in design, by using CAD. Based on the these data, we fabricated the trial product for the development of the auto pattern maker. Results: The auto pattern maker were composed with combinations of many elements; pattern making assembly, control panel, frame attachment and prober unit. The pattern making assembly was comprised of the cutter, the pattern holder, pattern remover and silence cover which could minimize the sound during the cutting process. The control panel was designed to be connected and operated with the main printed circuit board. The prober could get the eye shape data by scanning of 1.8 degrees around the groove of the frame through the encoding data according to the address. After starting, scanning was carried out in two passes, i.e. one right-handed and one left-handed. Communication connector could send the eye shape data from auto pattern maker to outer system with the RS232C transmission system. By using the one-way analysis of variance, we got the error rate of cut pattern size for ${\Phi}22mm$, ${\Phi}55mm$ and ${\Phi}62mm$. Because F-value was 0.510 and p-value was 0.601, no statistically significant differences were found. Also, the mean cutting error of the auto pattern maker was 0.0274 mm. Conclusions: we could succeed in making the trial product by applying it to the development of the auto pattern maker. The role of this auto pattern maker is to find a exact required size of lens to fit the frame by measuring the frame. The acquired data are transferred to outer system for grinding and finishing with patternless process. Also, the trial product can produce pattern to fit the frame. Therefore, it was confidently expected that the optometrists could handily produce pattern to fit the frame with this trial product and dispense the ophthalmic lens because of its efficiency and convenience compared to the past.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.145-162
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• 2008

One of the big concerns in e-society is privacy issue. In special, in developing robust ubiquitous smart space and corresponding services, user profile and preference are collected by the service providers. Privacy issue would be more critical in context-aware services simply because most of the context data themselves are private information: user's current location, current schedule, friends nearby and even her/his health data. To realize the potential of ubiquitous smart space, the systems embedded in the space should corporate personal privacy preferences. When the users invoke a set of services, they are asked to allow the service providers or smart space to make use of personal information which is related to privacy concerns. For this reason, the users unhappily provide the personal information or even deny to get served. On the other side, service provider needs personal information as rich as possible with minimal personal information to discern royal and trustworthy customers and those who are not. It would be desirable to enlarge the allowable personal information complying with the service provider's request, whereas minimizing service provider's requiring personal information which is not allowed to be submitted and user's submitting information which is of no value to the service provider. In special, if any personal information required by the service provider is not allowed, service will not be provided to the user. P3P (Platform for Privacy Preferences) has been regarded as one of the promising alternatives to preserve the personal information in the course of electronic transactions. However, P3P mainly focuses on preserving the buyers' personal information. From time to time, the service provider's business data should be protected from the unintended usage from the buyers. Moreover, even though the user's privacy preference could depend on the context happened to the user, legacy P3P does not handle the contextual change of privacy preferences. Hence, the purpose of this paper is to propose a mutual P3P-based negotiation mechanism. To do so, service provider's privacy concern is considered as well as the users'. User's privacy policy on the service provider's information also should be informed to the service providers before the service begins. Second, privacy policy is contextually designed according to the user's current context because the nomadic user's privacy concern structure may be altered contextually. Hence, the methodology includes mutual privacy policy and personalization. Overall framework of the mechanism and new code of ethics is described in section 2. Pervasive platform for mutual P3P considers user type and context field, which involves current activity, location, social context, objects nearby and physical environments. Our mutual P3P includes the privacy preference not only for the buyers but also the sellers, that is, service providers. Negotiation methodology for mutual P3P is proposed in section 3. Based on the fact that privacy concern occurs when there are needs for information access and at the same time those for information hiding. Our mechanism was implemented based on an actual shopping mall to increase the feasibility of the idea proposed in this paper. A shopping service is assumed as a context-aware service, and data groups for the service are enumerated. The privacy policy for each data group is represented as APPEL format. To examine the performance of the example service, in section 4, simulation approach is adopted in this paper. For the simulation, five data elements are considered: $\cdot$ UserID $\cdot$ User preference $\cdot$ Phone number $\cdot$ Home address $\cdot$ Product information $\cdot$ Service profile. For the negotiation, reputation is selected as a strategic value. Then the following cases are compared: $\cdot$ Legacy P3P is considered $\cdot$ Mutual P3P is considered without strategic value $\cdot$ Mutual P3P is considered with strategic value. The simulation results show that mutual P3P outperforms legacy P3P. Moreover, we could conclude that when mutual P3P is considered with strategic value, performance was better than that of mutual P3P is considered without strategic value in terms of service safety.