• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.11-19
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• 2009

A RAM-based Neural Net(RBNN) which has multi-discriminators is more effective than RBNN with a discriminator. Experience Sensitive Cumulative Neural Network and 3-D Neuro System(3DNS) that accumulate the features point improved the performance of BNN, which were enabled to train additional and repeated patterns and extract a generalized pattern. In recognition process of Neural Net with multi-discriminator, the selection of class was decided by the value of MRD which calculates the accumulated sum of each class. But they had a saturation problem of its memory cells caused by learning volume increment. Therefore, the decision of MRD has a low performance because recognition rate is decreased by saturation. In this paper, we propose the method which improve the MRD ability. The method consists of the optimum MRD and the matching ratio prototype to generalized image, the cumulative filter ratio, the gap of prototype response MRD. We experimented the performance using NIST database of NIST without preprocessor, and compared this model with 3DNS. The proposed MRD method has more performance of recognition rate and more stable system for distortion of input pattern than 3DNS.

• Industry Promotion Research
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• v.8 no.3
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• pp.181-199
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• 2023

E-commerce is gradually upgrading from traditional text and image formats to short video and livestreaming formats. Livestreaming e-commerce enriches the content and forms of information dissemination and product display, enhances the consumer's shopping experience, and gradually becomes the mainstream new consumer scene. However, there are many negative phenomena in the development of livestreaming e-commerce, such as false propaganda, counterfeit goods, and various negative events, which seriously affect the level of consumer trust in livestreaming e-commerce. Trust is the core competitive factor of livestreaming e-commerce. Based on previous research on trust theory and combined with the characteristic elements of "people, goods, and scenes" of livestreaming e-commerce, this article constructs a trust model for livestreaming e-commerce, proposes hypotheses, and proves through empirical research that factors such as store characteristics, livestream host characteristics, brand image, product information, platform reputation, livestreaming situation, and trust tendency have a significant positive impact on consumer trust. Based on the research conclusions, this article provides insights and management suggestions, such as emphasizing the construction of store characteristic indicators, creating desirable livestream host characteristics, focusing on product brand building and selection, maintaining the display of product information, selecting suitable livestreaming platforms, and creating rich content for livestreaming situations.

• Korean Journal of Culture and Social Issue
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• v.19 no.1
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• pp.69-86
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• 2013

The recent findings proposed and found that people from Eastern cultures could experience strong cognitive dissonance only when certain conditions, such as other-related choices, normative attitudes, were fulfilled. Even though such interesting findings are intuitively convincing on the basis of common understanding of individualist and collectivist cultures, the psychological mechanisms underlying the cultural variations of cognitive dissonance remain untested. The present study examined the role of attitude importance in cognitive dissonance by using the free-choice paradigm. After completing a pretest of individualism-collectivism scales, 60 college students ranked their preference to 10 items of either beverage or traffic regulations twice. Between the two ranking tasks, they were asked to engage in behavioral selection among their 5^th and 6^th preferred items. They also rated the personal importance of the preference. The results showed that attitude importance was positively correlated with attitude change and it could play a major role in experiencing cognitive dissonance beyond cultural orientation and situational factors. The current findings were discussed in universality of cognitive dissonance across cultures.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.10
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• pp.291-298
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• 2023

In this paper, we study whether the programming questions of the Informatics·Computer recruitment tests were suitable for selecting teachers with required programming skills. The average points of the programming questions constituted 38%(20.8 points) of the total scores for the entire curriculum based on the results from analyzing the previous questions in the past 5 years. Moreover, the distribution of points for each evaluation criteria within programming and data structure, two exam subjects which have a high proportion of programming questions, demonstrated a large deviation ranging from 0% to 47% and 0% to 53% respectively. In this study, a questionnaire survey was conducted on 31 teachers to examine if the previous programming questions were suitable for measuring teachers' competency in programming abilities required in the actual teaching experience. Computational thinking ability was ranked the highest at 58% in response to the area that needs to be evaluated in the recruitment test. In response to the relevance of previous questions, problem solving ability was ranked the highest at 2.84 on a 5-point scale, but the overall appropriateness was deemed low. C language and Python were regarded as the computer languages suitable to be tested for programming questions with each ranked 55% and 45%. The finding confirms that teachers preferred Python and the incumbent C language to others. Based on the results of the questionnaire, we recommend changes in the programming questions to improve the selection criteria.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.185-200
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• 2024

This study explored the changes in the elementary science teaching expertise of teachers who participated in an in-school professional learning community for elementary science instructional research. Six elementary school teachers from grades 4, 5, and 6 at an 18-class S elementary school in a medium-sized city in Chungcheongbuk-do conducted collaborative instructional research on elementary science lessons as part of an in-school professional learning community, which was held 26 times over 7 months in 2020. During the professional learning community, video and audio recordings of the activities, research lessons, course materials, and professional learning community reflection activities were collected for analysis. The collected data were analyzed using qualitative research methods; data processing, reading, note-taking, description, classification, interpretation, reporting, and visualization; and the instructional professionalism elements were extracted based on the instructional professionalism framework. In the early professional learning community activity stages, the participating teachers first discussed their teaching perspectives, their experiences, and their goals for teaching science, which resulted in a selection of research questions. The teachers then collaboratively designed and implemented research lessons for each grade level, after which lesson reflections were conducted. The teachers' abilities to engage in qualitative reflection on the research questions improved after each reflection iteration. It was found that this professional learning community collaborative lesson study experience positively contributed to teaching expertise development. Based on the study findings, the implications for using professional learning communities to improve elementary teachers' science teaching expertise are given.

• Journal of The Korean Association For Science Education
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• v.29 no.6
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• pp.626-638
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• 2009

The purpose of this study was to investigate the perception of the scientifically gifted high school students to the research and education (R&E) program. 270 scientifically gifted high school students participating in R&E program were sampled and surveyed according to the R&E' purpose, the process of topic selection, the advantage, and disadvantage of R&E. 4 students among them were interviewed in depth. Students perceived the purposes and advantages of R&E as fostering the scientist' qualifications, providing the research opportunities, and improving the inquiry ability and the disadvantages of R&E as the time consumption in research, the participation as a sideline, and the difficulty of contents. The R&E program was mainly composed of a pre-determined topic, fixed procedures, and expert's settlements in the problem-emerging situation and was not cognitive but technical apprenticeship. In addition, students considered the participation of R&E as a chance of experience about the high techniques and the valuable instruments instead of the improvement on the creative problem-solving ability. The role of mentors in the R&E program is so important that it affects largely on the productive participation and the perceptions of science and scientists.

• Journal of Chest Surgery
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• v.57 no.1
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• pp.62-69
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• 2024

Background: Cervical esophageal cancer is a rare malignancy that requires specialized care. While definitive chemoradiation is the standard treatment approach, surgery remains a valuable option for certain patients. This study examined the surgical outcomes of patients with cervical esophageal cancer. Methods: The study involved a retrospective review and analysis of 24 patients with cervical esophageal cancer. These patients underwent surgical resection between September 1994 and December 2018. Results: The mean age of the patients was 61.0±10.2 years, and 22 (91.7%) of them were male. Furthermore, 21 patients (87.5%) had T3 or T4 tumors, and 11 (45.8%) exhibited lymph node metastasis. Gastric pull-up with esophagectomy was performed for 19 patients (79.2%), while 5 (20.8%) underwent free jejunal graft with cervical esophagectomy. The 30-day operative mortality rate was 8.3%. During the follow-up period, complications included leakage at the anastomotic site in 9 cases (37.5%) and graft necrosis of the gastric conduit in 1 case. Progression to oral feeding was achieved in 20 patients (83.3%). Fifteen patients (62.5%) displayed tumor recurrence. The median time from surgery to recurrence was 10.5 months, and the 1-year recurrence rate was 73.3%. The 1-year and 3-year survival rates were 75% and 33.3%, respectively, with a median survival period of 17 months. Conclusion: Patients with cervical esophageal cancer who underwent surgical resection faced unfavorable outcomes and relatively poor survival. The selection of cases and decision to proceed with surgery should be made cautiously, considering the risk of severe complications.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.221-231
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• 2024

The aim of this study was to enhance the safety and care of mental health for seafarer working in passenger ship workspaces. Brightness, color values, and color distribution were investigated with issues and improvement ways identified through seafarers' interviews. Firstly, previous studies, references, current policy, regulations, and accident case studies were reviewed. Color compositions of wheelhouse and engine room of M Ship were then surveyed in the field. Color values of each space were analyzed using a colorimeter. Colormeter analysis of brightness and color measurements in the wheelhouse and engine areas indicated that ceilings, walls, and floors were generally dark, with the engine area being very dark. Regarding color, green and blue were distributed in the ceiling of the wheelhouse and engine area, while red and blue were in the walls and floors of the wheelhouse and engine area. According to interviews with seafarers currently working at engine rooms, they responded about their experience of near miss incidents due to a decrepit indoor environment, a dark working environment, slippery and bright flooring, and stairs that were not suitable for domestic users. Thus, when installing lighting in the future, the brightness of the space should be improved by distinguishing between night and day. A lighting plan considering the location of lighting, level of shadow formation and contrast, reflectance of the facility, glare, color of light, floor color plan, and material selection is needed. A facility design suitable for domestic users is also needed.

• Journal of the Korea Society for Simulation
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• v.33 no.1
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• pp.1-17
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• 2024

Forest management is known to beneficially influence stand structure and wood production, yet quantitative understanding as well as an illustrative depiction of the effects of different management approaches on tree growth and stand dynamics are still scarce. Long-term management of beech forests must balance public interests with ecological aspects. Efficient forest management requires the reliable prediction of tree growth change. We aimed to develop a novel hybrid simulation approach, which realistically simulates short- as well as long-term effects of different forest management regimes commonly applied, but not limited, to German low mountain ranges, including near-natural forest management based on single-tree selection harvesting. The model basically consists of three modules for (a) natural seedling regeneration, (b) mortality adjustment, and (c) tree growth simulation. In our approach, an existing validated growth model was used to calculate single year tree growth, and expanded on by including in a newly developed simulation process using calibrated modules based on practical experience in forest management and advice from the local forest. We included the following different beech forest-management scenarios that are representative for German low mountain ranges to our simulation tool: (1) plantation, (2) continuous cover forestry, and (3) reserved forest. The simulation results show a robust consistency with expert knowledge as well as a great comparability with mid-term monitoring data, indicating a strong model performance. We successfully developed a hybrid simulation that realistically reflects different management strategies and tree growth in low mountain range. This study represents a basis for a new model calibration method, which has translational potential for further studies to develop reliable tailor-made models adjusted to local situations in beech forest management.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.30-40
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• 2024

Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO₂ emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.