• 산경연구논집
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• 제11권4호
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• pp.19-30
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• 2020

Purpose: The purpose of this study examines the mediating effect of clan leadership in the relationship between hierarchy culture and organizational commitment. Most previous research focused on the relationship between organizational culture and organizational performance or organizational culture and job satisfaction. There are few empirical studies that focus on organizational commitment data because it is difficult to collect in many cases of export-driven small and medium sized enterprises. However, this research measures affective commitment, continuance commitment, and normative commitment differently than previous research, which is mostly focused on the hierarchy culture, clan leadership, and organizational commitment measurements. Research design, data, methodology: Conceptual research model is based on the studies of Cameron and Quinn (2011), and Gungor and Sahin (2018). The model is designed with three constructs such as hierarchy culture, organizational commitment, and clan leadership. The monitor culture and coordinator culture are as proxy for the hierarchy culture. The affective commitment, continuance commitment, and normative commitment are as proxy for the organizational commitment. And also the facilitator leadership and mentor leadership are as proxy for the clan leadership. Based on three hundred cases such as export-driven small and medium sized enterprises (SMEs), this study verify the hypothesis. Hypothesis was analyzed with the structural equation modeling. Results: In case of export-driven small and medium sized enterprises (SMEs), clan leadership acts as a mediator in the relationship between hierarchy culture and organizational commitment. In case of export-driven small and medium sized enterprises (SMEs) with high organizational commitment, clan leadership acts as a mediator in the relationship between hierarchy culture and organizational commitment. In case of export-driven small and medium sized enterprises (SMEs) with low organizational commitment, clan leadership did not act as a mediator in the relationship between hierarchy culture and organizational commitment. Conclusions: By controlling for the mediating effect of clan culture, this study have improved the academic contributions as well as policy and practical implications through empirical study of clan leadership that affect organizational commitment in the fields of hierarchy culture. In addition, this study means that the mediating effects on the variables of clan leadership were examined.

• Journal of Ecology and Environment
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• 제47권2호
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• pp.49-62
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• 2023

Background: Over the past three decades, gradual eustatic sea-level rise has been considered a primary exogenous factor in the increased frequency of flooding and biological changes in several salt marshes. Under this paradigm, the potential importance of short-term events, such as ocean storminess, in coastal hydrology and ecology is underrepresented in the literature. In this study, a simulation was developed to evaluate the influence of wind waves driven by atmospheric oscillations on sedimentary and vegetation dynamics at the Skallingen salt marsh in southwestern Denmark. The model was built based on long-term data of mean sea level, sediment accretion, and plant species composition collected at the Skallingen salt marsh from 1933-2006. In the model, the submergence frequency (number yr^-1) was estimated as a combined function of wind-driven high water level (HWL) events (> 80 cm Danish Ordnance Datum) affected by the North Atlantic Oscillation (NAO) and changes in surface elevation (cm yr^-1). Vegetation dynamics were represented as transitions between successional stages controlled by flooding effects. Two types of simulations were performed: (1) baseline modeling, which assumed no effect of wind-driven sea-level change, and (2) experimental modeling, which considered both normal tidal activity and wind-driven sea-level change. Results: Experimental modeling successfully represented the patterns of vegetation change observed in the field. It realistically simulated a retarded or retrogressive successional state dominated by early- to mid-successional species, despite a continuous increase in surface elevation at Skallingen. This situation is believed to be caused by an increase in extreme HWL events that cannot occur without meteorological ocean storms. In contrast, baseline modeling showed progressive succession towards the predominance of late-successional species, which was not the then-current state in the marsh. Conclusions: These findings support the hypothesis that variations in the NAO index toward its positive phase have increased storminess and wind tides on the North Sea surface (especially since the 1980s). This led to an increased frequency and duration of submergence and delayed ecological succession. Researchers should therefore employ a multitemporal perspective, recognizing the importance of short-term sea-level changes nested within long-term gradual trends.

• Biotechnology and Bioprocess Engineering:BBE
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• 제11권1호
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• pp.67-71
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• 2006

This paper compares regression and neural network modeling approaches to predict competitive biosorption equilibrium data. The regression approach is based on the fitting of modified Langmuir-type isotherm models to experimental data. Neural networks, on the other hand, are non-parametric statistical estimators capable of identifying patterns in data and correlations between input and output. Our results show that the neural network approach outperforms traditional regression-based modeling in correlating and predicting the simultaneous uptake of copper and cadmium by a microbial biosorbent. The neural network is capable of accurately predicting unseen data when provided with limited amounts of data for training. Because neural networks are purely data-driven models, they are more suitable for obtaining accurate predictions than for probing the physical nature of the biosorption process.

• ETRI Journal
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• 제32권5호
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• pp.810-818
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• 2010

This paper presents a new framework for integrating untranscribed spoken content into the acoustic training of an automatic speech recognition system. Untranscribed spoken content plays a very important role for under-resourced languages because the production of manually transcribed speech databases still represents a very expensive and time-consuming task. We proposed two new methods as part of the training framework. The first method focuses on combining initial acoustic models using a data-driven metric. The second method proposes an improved acoustic training procedure based on unsupervised transcriptions, in which word endings were modified by broad phonetic classes. The training framework was applied to baseline acoustic models using untranscribed spoken content from parliamentary debates. We include three types of acoustic models in the evaluation: baseline, reference content, and framework content models. The best overall result of 18.02% word error rate was achieved with the third type. This result demonstrates statistically significant improvement over the baseline and reference acoustic models.

• 한국수소및신에너지학회논문집
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• 제35권4호
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• pp.437-450
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• 2024

Sustainable shipping depends on eco-friendly energy solutions. This paper reviews methods for predicting marine fuel cell performance, including empirical approaches, physical modeling, data-driven techniques, and hybrid methods. Accurate prediction models tailored to the marine environment's unique conditions are crucial for operational efficiency. By evaluating the strengths and weaknesses of each method, this study provides a comprehensive analysis of effective strategies for forecasting polymer electrolyte membrane fuel cell and solid oxide fuel cell performance in marine applications. These insights contribute to the advancement of eco-friendly shipping technologies and enhance fuel cell performance in challenging marine environments.

• 대한산업공학회지
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• 제37권3호
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• pp.264-270
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• 2011

A new method for creating a logical data model is proposed. The logical data model developed by the method defines table, primary key, foreign key, and fields. The framework of the logical data model is constructed by modeling the relationships between events and their related entity types. The proposed method consists of a series of objective and quantitative decisions such as maximum cardinality of relationships and functional dependency between the primary key and attributes. Even beginners to database design can use the methology as long as they understand such basic concepts about relational databases as primary key, foreign key, relationship cardinality, parent-child relationship, and functional dependency. The simple and systematic approach minimizes decision errors made by a database designer. In practial database design the method creates a logical data model in Boyce-Codd normal form unless the user of the method makes a critical decision error, which is very unlikely.

• Journal of Information Processing Systems
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• 제6권3호
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• pp.385-402
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• 2010

Most of the data warehouse (DW) requirements engineering approaches have not distinguished the early requirements engineering phase from the late requirements engineering phase. There are very few approaches seen in the literature that explicitly model the early & late requirements for a DW. In this paper, we propose an AGDI (Agent-Goal-Decision-Information) model to support the early and late requirements for the development of DWs. Here, the notion of agent refers to the stakeholders of the organization and the dependency among agents refers to the dependencies among stakeholders for fulfilling their organizational goals. The proposed AGDI model also supports three interrelated modeling activities namely, organization modeling, decision modeling and information modeling. Here, early requirements are modeled by performing organization modeling and decision modeling activities, whereas late requirements are modeled by performing information modeling activities. The proposed approach has been illustrated to capture the early and late requirements for the development of a university data warehouse exemplifying our model's ability of supporting its decisional goals by providing decisional information.

• 한국지반신소재학회논문집
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• 제11권4호
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• pp.71-77
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• 2012

본 연구에서는 지반구조물에서 수집된 계측데이터를 대상으로 확률통계적 방법을 사용한 상태평가를 위한 분석기법과 자동화 프로그램을 개발하였다. 복잡한 지반구조물에 설치한 계측시스템으로부터 수집된 계측자료의 평가를 위해서는 자료처리(data driven) 기반의 비모수적(non-parametric) 모델링 방법이 유용할 것으로 판단된다. 실제 지반구조물(보강토옹벽 및 터널)에서 수집된 센싱 데이터를 이용하여 개발된 평가기법의 검증을 실시한 결과 환경적 요인과는 구별되는 구조적 거동을 확인할 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.18-18
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• 1996

This paper reviews some of the most prominent and promising areas of chemical process control both in relations to batch and continuous processes. These areas include the modeling, optimization, control and monitoring of chemical processes and entire plants. Most of these areas explicitly utilize a model of the process. For this purpose the types of models used are examined in some detail. These types of models are categorized in knowledge-driven and datadriven classes. In the areas of modeling and optimization, attention is paid to batch reactors using the Tendency Modeling approach. These Tendency models consist of data- and knowledge-driven components and are often called Gray or Hybrid models. In the case of continuous processes, emphasis is placed in the closed-loop identification of a state space model and their use in Model Predictive Control nonlinear processes, such as the Fluidized Catalytic Cracking process. The effective monitoring of multivariate process is examined through the use of statistical charts obtained by the use of Principal Component Analysis (PMC). Static and dynamic charts account for the cross and auto-correlation of the substantial number of variables measured on-line. Centralized and de-centralized chart also aim in isolating the source of process disturbances so that they can be eliminated. Even though significant progress has been made during the last decade, the challenges for the next ten years are substantial. Present progress is strongly influenced by the economical benefits industry is deriving from the use of these advanced techniques. Future progress will be further catalyzed from the harmonious collaboration of University and Industrial researchers.

• International Journal of Aeronautical and Space Sciences
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• 제15권4호
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• pp.345-355
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• 2014

This paper focuses on aerodynamic and inertial modeling of the propeller for its applications in flight dynamics analyses of a propeller-driven airplane. Unsteady aerodynamic and inertial loads generated by the propeller are formulated using the blade element method, where the local velocity and acceleration vectors for each blade element are obtained from exact kinematic relations for general maneuvering conditions. Vortex theory is applied to obtain the flow velocities induced by the propeller wake, which are used in the computation of the aerodynamic forces and moments generated by the propeller and other aerodynamic surfaces. The vortex lattice method is adopted to obtain the induced velocity over the wing and empennage components and the related influence coefficients are computed, taking into account the propeller induced velocities by tracing the wake trajectory trailing from each of the propeller blades. Aerodynamic forces and moments of the fuselage and other aerodynamic surfaces are computed by using the wind tunnel database and applying strip theory to incorporate viscous flow effects. The propeller models proposed in this paper are applied to predict isolated propeller performances under steady flight conditions. Trimmed level forward and turn flights are analyzed to investigate the effects of the propeller on the flight characteristics of a propeller-driven light-sports airplane. Flight test results for a series of maneuvering flights using a scaled model are employed to run the flight dynamic analysis program for the proposed propeller models. The simulations are compared with the flight test results to validate the usefulness of the approach. The resultant good correlations between the two data sets shows the propeller models proposed in this paper can predict flight characteristics with good accuracy.