• The Korean Journal of Franchise Management
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• v.8 no.4
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• pp.21-32
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• 2017

Purpose - In hotel business, how to build the relationship between leader and employees is very important, because it affects on the customer satisfaction. Thus, this research examines the effect of authentic leadership on job performance in the context of hotel industry and identifies mediating roles of organizational engagement, job satisfaction, and creativity in the relationship between authentic leadership and job performance. This study suggests the guidelines for how hotel companies should improve employee productivity and build a desirable organizational culture by presenting employee attitudes and behavioral models that explain the relationship between leaders and employees. Research design, data, and methodology - This study examines the structural relationship between authentic leadership, organizational engagement, job satisfaction, creativity, and job performance from the employee's perspective. Authentic leadership divide into four sub-dimensions such as self-awareness, balanced process of informations, internalized moral perspective, and relational transparency. In order to test the purposes of this study, research model and hypotheses were developed. All constructs were measured with multiple items developed and tested in the previous studies. The data were collected from 114 franchise hotel employees and were analyzed using SPSS 21.0 and Smart PLS 3.0. program. Result - The results of this study are as follows. First, authentic leadership have significant impacts on organizational engagement and creativity, but does not have impact on job satisfaction directly. Second, organizational engagement have significant impacts on job satisfaction and job performance, but does not have impact on creativity directly. Third, job satisfaction has significant impact on creativity, but does not have impact on job performance. Fourth, creativity has significant impact on job performance. Conclusions - The findings of this study indicate that hotel leaders should properly implement the authentic leadership and consider how to build a corporate culture to improve an organizational and employee productivity through authentic leadership. Due to the nature of the hotel industry, which relies heavily on human resources, hotel companies must manage their employees with authenticity in order to increase organizational engagement, job satisfaction, and creativity that affect hotel and employee productivity. If hotel employees perceive their leader's authentic leadership, they show more organizational engagement that increases creativity and leads to job performance. Finally, hotel employees can propose creative ideas only if they will be satisfied with their jobs. Therefore, the leader should develop non-monetary or monetary reward system for the employees and, make an efforts to foster creativity of the employees.

• Steel and Composite Structures
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• v.48 no.2
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• pp.207-233
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• 2023

Steel-concrete composite box girder bridges are widely used in the construction of highway and railway bridges both domestically and abroad due to their advantages of being light weight and having a large spanning ability and very large torsional rigidity. Composite box girder bridges exhibit the effects of shear lag, restrained torsion, distortion and interface bidirectional slip under various loads during operation. As one of the most commonly used calculation tools in bridge engineering analysis, one-dimensional models offer the advantages of high calculation efficiency and strong stability. Currently, research on the one-dimensional model of composite beams mainly focuses on simulating interface longitudinal slip and the shear lag effect. There are relatively few studies on the one-dimensional model which can consider the effects of restrained torsion, distortion and interface transverse slip. Additionally, there are few studies on vehicle-bridge integrated systems where a one-dimensional model is used as a tool that only considers the calculations of natural frequency, mode and moving load conditions to study the dynamic response of composite beams. Some scholars have established a dynamic analysis model of a coupled composite beam bridge-train system, but where the composite beam is only simulated using a Euler beam or Timoshenko beam. As a result, it is impossible to comprehensively consider multiple complex force effects, such as shear lag, restrained torsion, distortion and interface bidirectional slip of composite beams. In this paper, a 27 DOF vehicle rigid body model is used to simulate train operation. A two-node 26 DOF finite beam element with composed box beams considering the effects of shear lag, restrained torsion, distortion and interface bidirectional slip is proposed. The dynamic analysis model of the coupled composite box girder bridge-train system is constructed based on the wheel-rail contact relationship of vertical close-fitting and lateral linear creeping slip. Furthermore, the accuracy of the dynamic analysis model is verified via the measured dynamic response data of a practical composite box girder bridge. Finally, the dynamic analysis model is applied in order to study the influence of various mechanical effects on the dynamic performance of the vehicle-bridge system.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.113-118
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• 2023

This study analyzed the effects of macroeconomic variables, including housing affordability, and bank loan-related variables on variation in housing prices using multiple regression models. As a result of the analysis, consumer price growth rate, the total currency growth rate, and the housing affordability growth rate had a significant positive effect on changes in housing prices. As a result of analyzing the period of rising and falling housing prices, consumer price growth rate and the total currency growth rate during the period of rising housing prices had a significant positive effect on housing prices. Unlike the period of rising housing prices, the growth rate of household loans was found to have a significant positive effect on changes in housing prices. On the other hand, unlike the period of rising housing prices, the growth rater of mortgage loans was found to have a significant negative effect on changes in housing prices. The growth rate of housing affordability index did not have a significant positive effect on changes in housing prices during a falling housing prices. The determinants of housing prices showed different patterns during the period of rising housing prices and falling housing prices.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.41-51
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• 2023

In this paper, we propose a technique of multi-time window feature extraction for anger detection in gait data. In the previous gait-based emotion recognition methods, the pedestrian's stride, time taken for one stride, walking speed, and forward tilt angles of the neck and thorax are calculated. Then, minimum, mean, and maximum values are calculated for the entire interval to use them as features. However, each feature does not always change uniformly over the entire interval but sometimes changes locally. Therefore, we propose a multi-time window feature extraction technique that can extract both global and local features, from long-term to short-term. In addition, we also propose an ensemble model that consists of multiple classifiers. Each classifier is trained with features extracted from different multi-time windows. To verify the effectiveness of the proposed feature extraction technique and ensemble model, a public three-dimensional gait dataset was used. The simulation results demonstrate that the proposed ensemble model achieves the best performance compared to machine learning models trained with existing feature extraction techniques for four performance evaluation metrics.

• Korean Journal of Schizophrenia Research
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• v.21 no.2
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• pp.43-50
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• 2018

Objectives : Genome-wide association studies (GWASs) and meta-analyses indicate that single-nucleotide polymorphisms (SNPs) in the a-1C subunit of the L-type voltage-dependent calcium channel (CACNA1C) gene increase the risk for schizophrenia and bipolar disorders (BDs). We investigated the association between the genetic variants on CACNA1C and schizophrenia and/or BDs in the Korean population. Methods : A total of 582 patients with schizophrenia, 336 patients with BDs consisting of 179 bipolar I disorder (BD-I) and 157 bipolar II disorder (BD-II), and 502 healthy controls were recruited. Based on previous results from other populations, three SNPs (rs10848635, rs1006737, and rs4765905) were selected and genotype-wise association was evaluated using logistic regression analysis under additive, dominant and recessive genetic models. Results : rs10848635 showed a significant association with schizophrenia (p=0.010), the combined schizophrenia and BD group (p=0.018), and the combined schizophrenia and BD-I group (p=0.011). The best fit model was dominant model for all of these phenotypes. The association remained significant after correction for multiple testing in schizophrenia and the combined schizophrenia and BD-I group. Conclusion : We identified a possible role of CACNA1C in the common susceptibility of schizophrenia and BD-I. However no association trend was observed for BD-II. Further efforts are needed to identify a specific phenotype associated with this gene crossing the current diagnostic categories.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.661-667
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• 2009

Trabecular-bone-mimicking phantoms consisting of parallel-nylon-wire arrays were used to investigate correlations of phase velocity and attenuation coefficient with structural properties in trabecular bone. Trabecular separation (Tb.Sp) of the 7 trabecular-bone-mimicking phantoms ranged from 300 to $900\;{\mu}m$ and volume fraction (VF) from 1.6% to 8.7%. Phase velocity and attenuation coefficient of the phantoms were measured by using a through-transmission method in water, with a matched pair of broadband unfocused transducers with a diameter of 12.7 mm and a center frequency of 1 MHz. Phase velocity and attenuation coefficient at 1 MHz decreased almost linearly with increasing Tb. Sp and increased almost linearly with increasing VF. The simple and multiple linear regression models with phase velocity and attenuation coefficient as independent vanables and Tb.Sp and VF as dependent variables demonstrated that the coefficients of determination for the prediction of VF were higher than those for the prediction of Tb.Sp. The results obtained in the trabecular-bone-mimicking phantoms consisting of parallel-nylon-wire arrays were consistent with those in human trabecular bone suggesting that the structural properties can be estimated from the measurements of phase velocity and attenuation coefficient in trabecular bone.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.306-313
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• 2023

Sepsis is a systemic inflammatory response, with manifestations in multiple organs by pathogenic infection. Currently, there are no promising therapeutic strategies. Signal transducer and activator of transcription 3 (STAT3) is a cell signaling transcription factor. Niclosamide is an anti-helminthic drug approved by the Food and Drug Administration (FDA) as a potential STAT3 inhibitor. C57BL/6 mice were treated with an intraperitoneal injection of lipopolysaccharide (LPS). Niclosamide was administered orally 2 hours after the LPS injection. This study found that Niclosamide improved the survival and lung injury of LPS-induced mice. Niclosamide decreased the levels of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and interleukin-1β (IL-1β), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and lactate dehydrogenase (LDH) in serum. The effects of Niclosamide on phosphoinositide 3-kinase (PI3K), AKT, nuclear factor-κB (NF-κB), and STAT3 signaling pathways were determined in the lung tissue by immunoblot analysis. Niclosamide reduced phosphorylation of PI3K, AKT, NF-κB, and STAT3 significantly. Furthermore, it reduced the phosphorylation of STAT3 by LPS stimulation in RAW 264.7 macrophages. Niclosamide also reduced the LPS-stimulated expression of proinflammatory mediators, including IL-6, TNF-α, and IL-1β. Niclosamide provides a new therapeutic strategy for murine sepsis models by suppressing the inflammatory response through STAT3 inhibition.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.41-55
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• 2023

In order to secure sustainable competitiveness of startups, business model innovation is an important task to achieve competitive advantage by transforming the various elements that make up the business model. This study conducted a multi-case analysis study on leading smart farm companies around the world using an analysis framework based on business model theory. Through this, we sought to identify business model types and their constituent elements. For this, 19 companies were selected from the list of top 10 investment startups of the year for the past three years published by Agfunder, a global investment research company specializing in AgTech. Then data collection and analysis of the company cases were conducted according to the case study protocol. As a result of the study, the business model types were analyzed into four types: large-scale centralized production model, medium-to-large local distributed production model, small-scale hyperlocal modular FaaS model, and small-scale hyperlocal turnkey solution supply model. A comparative analysis was conducted on five business model components for each type, and strategic implications were derived through this. This study is expected to contribute to improving the competitiveness of domestic smart farm startups and diversifying their strategies by identifying the business models of overseas leading companies in the smart farm field using an academic analysis framework.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.165-179
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• 2024

It is crucial to have a comprehensive understanding of inundation and water cycle in urban areas for mitigating flood risks and sustainable water resources management. In this study, we developed a Cellular Automata-based integrated Water cycle model (CAW). A comparative analysis with physics-based and conventional cellular automata-based models was performed in an urban watershed in Portland, USA, to evaluate the adequacy of spatiotemporal inundation simulation in the context of a high-resolution setup. A high similarity was found in the maximum inundation maps by CAW and Weighted Cellular Automata 2 Dimension (WCA2D) model presumably due to the same diffuse wave assumption, showing an average Root-Mean-Square-Error (RMSE) value of 1.3 cm and high scores of binary pattern indices (HR 0.91, FAR 0.02, CSI 0.90). Furthermore, through multiple simulation experiments estimating the effects of land cover and soil conditions on inundation and infiltration, as the impermeability rate increased by 41%, the infiltration decreased by 54% (4.16 mm/m²) while the maximum inundation depth increased by 10% (2.19 mm/m²). It was expected that high-resolution integrated inundation and water cycle analysis considering various land cover and soil conditions in urban areas would be feasible using CAW.