• 태양에너지
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• 제18권3호
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• pp.107-112
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• 1998

Basic design of a solar driven absorption cooling machine(SDACM) with a cooling capacity of 5 USRT was carried out. The SDACM is a single effect cycle driven by low temperature hot water from solar collectors. The SDACM design data were calculated by the steady state simulation program which was developed in this study The variation of COP and cooling capacity of the SDACM were investigated at different off-design conditions. Both the cooling capacity and the system COP were improved with decreasing cooling water temperature. If hot water temperature was increased, the cooling capacity was improved but the system COP was found to be decreased. The decrease of the system COP were basically caused by increased thermal loads in the system components.

• 아태비즈니스연구
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• 제13권4호
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• pp.123-134
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• 2022

Purpose - The purpose of this study is to investigate the effects of entrepreneurial motivation, self-efficacy, and entrepreneurial orientation on the performance of Mongolian entrepreneurs. Design/methodology/approach This study collected data from a survey on 236 entrepreneurs in Mongolia and investigate research hypotheses by empirical analysis. Findings It was found that entrepreneurial motivation (independence, opportunity-driven, achievement motivation) had a positive effect on the startups' performances, and necessity-driven motivation did not have a significant effect on the startups' performances. Entrepreneurial self-efficacy and entrepreneurial orientation had a positive effect on performance of startups. There are differences by gender on the relationships between entrepreneurial motivations and startup performances. Research implications or Originality This paper investigates the effects of entrepreneurial motivation, self-efficacy, and entrepreneurial orientation on the performance of startups in Mongolian.

• 아시아태평양코퍼스연구
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• 제4권1호
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• pp.61-71
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• 2023

This study examines the effects of data-driven learning (DDL)-an approach employing corpora for inductive language pattern learning-on error identification in second language (L2) writing. The data consists of error identification instances from fifty-five participants, compared across different reference materials: the Corpus of Contemporary American English (COCA), dictionaries, and no use of reference materials. There are three significant findings. First, the use of COCA effectively identified collocational and form-related errors due to inductive inference drawn from multiple example sentences. Secondly, dictionaries were beneficial for identifying lexical errors, where providing meaning information was helpful. Finally, the participants often employed a strategic approach, identifying many simple errors without reference materials. However, while maximizing error identification, this strategy also led to mislabeling correct expressions as errors. The author has concluded that the strategic selection of reference materials can significantly enhance the effectiveness of error identification in L2 writing. The use of a corpus offers advantages such as easy access to target phrases and frequency information-features especially useful given that most errors were collocational and form-related. The findings suggest that teachers should guide learners to effectively use appropriate reference materials to identify errors based on error types.

• Asian Journal of Business Environment
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• 제14권2호
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• pp.1-10
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• 2024

Purpose: The purpose of this study is to investigate the essential factors contributing to the growth and success of smart cities, providing a comprehensive analysis of key elements that are crucial in fostering the development of smart cities. This study explored the impacts of technology-driven applications, corporate involvement, the role of experts, citizen co-creation, city-led strategy governance, and sustainable urban practices on overall attitudes towards smart cities. Additionally, the study examined the impact of overall attitude on the growth trajectory of the smart cities and satisfaction. Research design, data and methodology: To collect data, this study employed an online survey conducted by a reputable research organization. Data analysis involved the use of factor analysis, ANOVA, and regression analysis. Results: This study unveiled significant impacts of technology-driven applications, corporate involvement, the role of experts, citizen co-creation, city-led strategy governance, and sustainable urban practices on the overall attitudes. Furthermore, it demonstrated that the overall attitude significantly influences the growth trajectory of smart cities. Conclusions: This study identified key driving factors for smart city development, suggesting that the consideration of sustainable urban practices emerges as the most significant factor influencing the growth of the smart cities.

• International Journal of Advanced Culture Technology
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• 제12권2호
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• pp.167-179
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• 2024

This study addresses the challenge of objectively evaluating the performance of early-stage startups amidst limited information and uncertainty. Focusing on companies selected by TIPS, a leading private sector-driven startup support policy in Korea, the research develops a new indicator to assess technological efficiency. By analyzing various input and output variables collected from Crunchbase and KIND (Korea Investor's Network for Disclosure System) databases, including technology use metrics, patents, and Crunchbase rankings, the study derives technological efficiency for TIPS-selected startups. A prediction model is then developed utilizing machine learning techniques such as Random Forest and boosting (XGBoost) to classify startups into efficiency percentiles (10th, 30th, and 50th). The results indicate that prediction accuracy improves with higher percentiles based on the technical efficiency index, providing valuable insights for evaluating and predicting startup performance in early markets characterized by information scarcity and uncertainty. Future research directions should focus on assessing growth potential and sustainability using the developed classification and prediction models, aiding investors in making data-driven investment decisions and contributing to the development of the early startup ecosystem.

• 한국가시화정보학회지
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• 제15권2호
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• pp.59-67
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• 2017

To verify floatability of ABB (Air bubble barrier), we compared bubble swarm behavior with and without the air-driven ejector. Experiment was conducted using the fabricated air-driven ejector with 5 mm nozzle on the bottom of 1 m3 water tank. Reynolds number of air in the nozzle was ranged 1766-13248. We analyzed data with statistical method using image processing, particle mage velocimetry (PIV) and proper orthogonal decomposition (POD) analysis. As a result of POD analysis, there was no significant eigenmode in bubbly flow generated from the ejector. It means that more complex turbulent flows were formed by the ejector, thereby (1) making bubbles finer, (2) promoting three-dimensional energy transfer between bubble and water, and (3) making evenly distributed velocity profile of water. It is concluded that the air-driven ejector could enhance the performance of ABB.

• 한국의류학회지
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• 제43권6호
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• pp.795-807
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• 2019

This qualitative study delves into consumers' meanings, perceptions, and behaviors toward the anthropomorphism of fashion goods based on personal experiences. Previous studies focused on consumer responses to the marketer-driven anthropomorphism of products, messages, and brands; however, the present study examines consumers' spontaneous anthropomorphism focusing on personal meanings as a possessor and meanings in their social relationships. A qualitative methodology is adopted that involves in-depth interviews with eleven males and females in their 20s and 30s. Participants stated that were engaged in the anthropomorphic practice of fashion goods on a daily basis. Data analysis was based on grounded theory. Findings on consumer-driven anthropomorphism are discussed at personal and interpersonal levels. At the personal level, anthropomorphic objects are their companions that are often called "baby." Interestingly, anthropomorphism reduces the stigmas of materialism from the participants' side. At the interpersonal level, anthropomorphic practice is a ritual of sharing a common interest and assuring intimacy. Implications and suggestions for future research are also discussed.

• Smart Structures and Systems
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• 제20권2호
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• pp.115-126
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• 2017

The modal identification of large civil structures such as bridges under the ambient vibrational conditions has been widely investigated during the past decade. Many operational modal analysis methods have been proposed and successfully used for identifying the dynamic characteristics of the constructed bridges in service. However, there is very limited research available on reliable criteria for the robustness of these identified modal parameters of the bridge structures. In this study, two time-domain operational modal analysis methods, the data-driven stochastic subspace identification (SSI-DATA) method and the covariance-driven stochastic subspace identification (SSI-COV) method, are employed to identify the modal parameters from field recorded ambient acceleration data. On the basis of the SSI-DATA method, the modal contribution indexes of all identified modes to the measured acceleration data are computed by using the Kalman filter, and their applicability to evaluate the robustness of identified modes is also investigated. Here, the benchmark problem, developed by Hong Kong Polytechnic University with field acceleration measurements under different excitation conditions of a cable-stayed bridge, is adopted to show the effectiveness of the proposed method. The results from the benchmark study show that the robustness of identified modes can be judged by using their modal contributions to the measured vibration data. A critical value of modal contribution index of 2% for a reliable identifiability of modal parameters is roughly suggested for the benchmark problem.

• 대한산업공학회지
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• 제40권5호
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• pp.492-500
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• 2014

Activity monitoring has been widely recognized as important and critical tools in system monitoring for detection of abnormal behavior. In this research, we propose a data-driven activity monitoring method to measure relative sales performance which is not sensitive to special event which frequently occur in marketing area. Moreover, the proposed method can automatically updates the monitoring threshold that accommodates a drastically changing business environment. The results from simulation and practical case study from sales of electronic devices demonstrate the usefulness and applicability of the proposed activity monitoring method.

• 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.