• Knowledge Management Research
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• v.24 no.4
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• pp.103-129
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• 2023

This study aims to analyze the network structure of technological innovation resources in SMEs, especially manufacturing firms, and reveal the differences between innovative and non-innovative firms. The study first analyzes connection centrality, flow-mediated centrality, and power centrality for all firms, and derives structural equivalence through CONCOR analysis. Then, the network structure of innovative and non-innovative firms was compared and analyzed according to innovation performance and creation. The results show that entrepreneurship and corporate innovation strategy have a significant impact on the analysis of technological innovation resources of all firms. According to the CONCOR analysis, the innovation resources of SMEs are organized into seven clusters, which can be defined as intrinsic product innovation resources, competitive advantage promotion resources, cooperative activities resources, information system resources, and innovation protection resources. The network analysis of innovative and non-innovative firms showed that innovative firms focused on enhancing competitiveness and improving quality, while non-innovative firms tended to focus more on existing products and customers. In addition, innovative firms had eight clusters, while non-innovative firms had six clusters, suggesting that innovative firms utilize resources diversely to pursue structural change and new value creation, while non-innovative firms operate technological innovation resources in a more stable form. This study emphasizes the importance of entrepreneurship and corporate innovation strategy in SMEs' technological innovation, and suggests that strong internal efforts are needed to increase innovativeness. These findings have important implications for strategy formulation and policy development for technological innovation in SMEs.

• Information Systems Review
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• v.20 no.3
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• pp.17-31
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• 2018

In recent years, success of information system projects to possess competitive advantage in business has become very important for stakeholders. Stakeholders who are interested in the success of information system projects typically consist of users who need the system, developers who build it, and project managers who are responsible for project success. However, recently, there has been increasing in the number of business analysts engaged in bridging relationships among these stakeholders in information system projects. So far, there have been many researches on the competence of users, developers or project managers. But, the research on the competencies of business analysts has not been done much. So, in this study, what competencies are needed for business analysts who are engaged in information system projects are researched, and the level and difference of stakeholders' expectations and satisfaction with them are identified, using IPA techniques. The results of this study are expected to contribute greatly to providing basic information on the development of competency models or training programs needed for recruitment, evaluation and training of business analysts who are or will be engaged in information system projects.

• Information Systems Review
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• v.20 no.4
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• pp.79-96
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• 2018

This study started by focusing on the internalization of the technology appraisal model into the credit rating model to increase the discriminative power of the credit rating model not only for SMEs but also for all companies, reflecting the items related to the financial stability of the enterprises among the technology appraisal items. Therefore, it is aimed to verify whether the technology appraisal model can be applied to identify high-stability SMEs in advance. We classified companies into industries (manufacturing vs. non-manufacturing) and the age of company (initial vs. non-initial), and defined as a high-stability company that has achieved an average debt ratio less than 1/2 of the group for three years. The C5.0 was applied to verify the discriminant power of the model. As a result of the analysis, there is a difference in importance according to the type of industry and the age of company at the sub-item level, but in the mid-item level the R&D capability was a key variable for discriminating high-stability SMEs. In the early stage of establishment, the funding capacity (diversification of funding methods, capital structure and capital cost which taking into account profitability) is an important variable in financial stability. However, we concluded that technology development infrastructure, which enables continuous performance as the age of company increase, becomes an important variable affecting financial stability. The classification accuracy of the model according to the age of company and industry is 71~91%, and it is confirmed that it is possible to identify high-stability SMEs by using technology appraisal items.

• Composites Research
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• v.37 no.3
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• pp.209-214
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• 2024

Graphene oxide (GO), known for its high stiffness, thermal conductivity, and electrical conductivity, is being utilized as a reinforcement in nanocomposite materials. This study evaluates the mechanical properties of epoxy nanocomposites incorporating GO and edge modified GO (E-GO), which has hydroxyl groups substituted only on its edges. GO/E-GO was uniformly dispersed in epoxy resin using ultrasonic dispersion, and mechanical properties were assessed through tensile testing. The results showed that the addition of nanoparticles increased both tensile strength and toughness. The tensile strength of the epoxy without nanoparticles was 74.4 MPa, while the highest tensile strength of 90.7 MPa was observed with 0.3 wt% E-GO. Additionally, the modulus increased from 2.55 GPa to 3.53 GPa with the addition of nanoparticles. Field emission scanning electron microscopy of the fracture surface revealed that the growth of cracks was impeded by the nanoparticles, preventing complete fracture and causing the cracks to split in multiple directions. E-GO, with surface treatment only on the edges, exhibited higher mechanical properties than GO due to its superior dispersion and surface treatment effects. These results highlight the importance of nanoparticle surface treatment in developing high-performance nanocomposite materials.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.383-390
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• 2024

We conducted this study to identify factors that influence college students' willingness to perform CPR. The subjects of the study were 229 college students from J City and D City. A URL was distributed to those who agreed to the study and a non-face-to-face survey was conducted using a questionnaire form. The research results were analyzed using SPSS/WIN 23.0. 155 out of 229 people (67.7%) responded that they would perform CPR if they found a patient suffering from cardiac arrest. Factors that differences between the CPR performing group and the non-performing group include gender, grade, experience of practice, number of CPR training, period of last CPR training, Have a CPR certification, and knowledge of CPR, Confidence of CPR. There was a statistically significant difference(p<0.05). Factors affecting the willingness to perform CPR include those who have actual experience of CPR, those who have CPR certification, and the higher their confidence in CPR, the higher the willingness to perform CPR. Accordingly, in order to increase confidence in CPR, we emphasize the importance of realistic performance experience and propose the development and application of various educational methods to increase the implementation rate through sufficient simulation learning.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.493-498
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• 2024

With the rapid advancement of generative artificial intelligence technology, there is growing interest in how to utilize it in practical applications. Additionally, the importance of prompt engineering to generate results that meet user demands is being newly highlighted. Exploring the new possibilities of generative AI can hold significant value. This study aims to utilize ChatGPT 4.0, a leading generative AI, to propose an effective method for evaluating user experience through the analysis of online customer review data. The user experience evaluation method was based on the six-layer elements of user experience: 'functionality', 'reliability', 'usability', 'convenience', 'emotion', and 'significance'. For this study, a literature review was conducted to enhance the understanding of prompt engineering and to grasp the clear concept of the user experience hierarchy. Based on this, prompts were crafted, and experiments for the user experience evaluation method were carried out using the analysis of collected online customer review data. In this study, we reveal that when provided with accurate definitions and descriptions of the classification processes for user experience factors, ChatGPT demonstrated excellent performance in evaluating user experience. However, it was also found that due to time constraints, there were limitations in analyzing large volumes of data. By introducing and proposing a method to utilize ChatGPT 4.0 for user experience evaluation, we expect to contribute to the advancement of the UX field.

• Korean Journal of Cognitive Science
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• v.35 no.1
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• pp.23-48
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• 2024

Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4274-4281
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• 2023

Blanket is of vital importance for engineering application of the fusion reactor. Nuclear heat deposition in materials is the main heat source in blanket structure. In this paper, the three-dimensional method for thermal-hydraulics/neutronics coupling analysis is developed and applied for the full-scale module of the helium-cooled ceramic breeder tritium breeding blanket (HCCB TBB) designed for China Fusion Engineering Test Reactor (CFETR). The explicit coupling scheme is used to support data transfer for coupling analysis based on cell-to-cell mapping method. The coupling algorithm is realized by the user-defined function compiled in Fluent. The three-dimensional model is established, and then the coupling analysis is performed using the paralleled Coupling Analysis of Thermal-hydraulics and Neutronics Interface Code (CATNIC). The results reveal the relatively small influence of the coupling analysis compared to the traditional method using the radial fitting function of internal heat source. However, the coupling analysis method is quite important considering the nonuniform distribution of the neutron wall loading (NWL) along the poloidal direction. Finally, the structure optimization of the blanket is carried out using the coupling method to satisfy the thermal requirement of all materials. The nonlinear effect between thermal-hydraulics and neutronics is found during the blanket structure optimization, and the tritium production performance is slightly reduced after optimization. Such an adverse effect should be thoroughly evaluated in the future work.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.67-84
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• 2023

In some areas of the Republic of Korea, the designation and management of conservation areas do not adequately reflect regional characteristics and often impose behavioral regulations without considering the local context. One prominent example is the Busan EDC area. As a result, conflicts may arise, including large-scale civil complaints, regarding the conservation and utilization of these areas. Therefore, for the efficient designation and management of protected areas, it is necessary to consider various ecosystem factors, changes in land use, and regional characteristics. In this study, we specifically focused on the Busan EDC area and applied machine learning techniques to analyze the habitat of regional species. Additionally, we employed Explainable Artificial Intelligence techniques to interpret the results of our analysis. To analyze the regional characteristics of the waterfront area in the Busan EDC district and the habitat of migratory birds, we used bird observations as dependent variables, distinguishing between presence and absence. The independent variables were constructed using land cover, elevation, slope, bridges, and river depth data. We utilized the XGBoost (eXtreme Gradient Boosting) model, known for its excellent performance in various fields, to predict the habitat probabilities of 11 bird species. Furthermore, we employed the SHapley Additive exPlanations technique, one of the representative methodologies of XAI, to analyze the relative importance and impact of the variables used in the model. The analysis results showed that in the EDC business district, as one moves closer to the river from the waterfront, the likelihood of bird habitat increases based on the overlapping habitat probabilities of the analyzed bird species. By synthesizing the major variables influencing the habitat of each species, key variables such as rivers, rice fields, fields, pastures, inland wetlands, tidal flats, orchards, cultivated lands, cliffs & rocks, elevation, lakes, and deciduous forests were identified as areas that can serve as habitats, shelters, resting places, and feeding grounds for birds. On the other hand, artificial structures such as bridges, railways, and other public facilities were found to have a negative impact on bird habitat. The development of a management plan for conservation areas based on the objective analysis presented in this study is expected to be extensively utilized in the future. It will provide diverse evidential materials for establishing effective conservation area management strategies.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.461-470
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• 2024

This study aimed to predict total phosphorus (T-P) to address early eutrophication caused by nutrient influx from various human activities. Traditional T-P monitoring systems are labor-intensive and time-consuming, leading to a global trend of using direct reading sensors. Therefore, this study utilized water quality parameters obtained from direct reading sensors in a two-stage T-P prediction process. The importance of turbidity (Tur) in T-P prediction was examined, and an analysis was conducted to determine if T-P prediction is possible using only direct reading sensor parameters by adding automatic water quality analyzer parameters. The study found that T-P concentrations were higher in the mid-lower reaches of the Nakdong River basin compared to the upper reaches. Pearson correlation analysis identified water quality parameters highly correlated with T-P at each site, which were then used in multiple linear regression analysis to predict T-P. The analysis was conducted with and without the inclusion of Tur, and the performance of models incorporating automatic water quality analyzer parameters was compared with those using only direct reading sensor parameters. The results confirmed the significance of Tur in T-P prediction, suggesting that it can be used as a foundational element in the development of measures to prevent eutrophication.