• Journal of Korean Society on Water Environment
• /
• v.36 no.6
• /
• pp.611-620
• /
• 2020

Although process-based models have been a preferred approach for modeling freshwater aquatic systems over extended time intervals, the increasing utility of data-driven models in a big data environment has made the data-driven models increasingly popular in recent decades. In this study, international peer-reviewed journals for the relevant fields were searched in the Web of Science Core Collection, and an extensive literature review, which included total 2,984 articles published during the last two decades (2000-2020), was performed. The review results indicated that the rate of increase in the number of published studies using data-driven models exceeded those using process-based models since 2010. The increase in the use of data-driven models was partly attributable to the increasing availability of data from new data sources, e.g., remotely sensed hyperspectral or multispectral data. Consistently throughout the past two decades, South Korea has been one of the top ten countries in which the greatest number of studies using the data-driven models were published. Among the major data-driven approaches, i.e., artificial neural network, decision tree, and Bayesian model, were illustrated with case studies. Based on the review, this study aimed to inform the current state of knowledge regarding the biogeochemical water quality and ecological models using data-driven approaches, and provide the remaining challenges and future prospects.

• Asia pacific journal of information systems
• /
• v.32 no.3
• /
• pp.477-495
• /
• 2022

This paper proposes how to design and implement data-driven strategies by investigating how a firm can increase its value using data science. Drawing on prior studies on architectural innovation, a behavioral theory of the firm, and the knowledge-based view of the firm as well as the analysis of field observations, the paper shows how data science is abused in dealing with meso-level data while it is underused in using macro-level and alternative data to accomplish machine-human teaming and risk management. The implications help us understand why some firms are better at drawing value from intangibles such as data, data-science capabilities, and routines and how to evaluate such capabilities.

• The Korean Journal of Franchise Management
• /
• v.14 no.4
• /
• pp.1-16
• /
• 2023

Purpose: Previous studies show that perceived CSR motives have a significant impact on company evaluations. However, consumer responses to CSR motives vary depending on CSR motives. From this perspective, this study investigates the impact of CSR motives on consumers' responses in the context of food and beverage franchise companies using a scenario. Research design, data, and methodology: For achieving the purposes of the study, an example of a domestic food and beverage franchise company actively carrying out CSR activities was presented. Data was collected from 304 respondents aged 20 or older who were aware of CSR activities. The respondents answered the questionnaire after reading the scenario. The data was analyzed with SPSS 28.0 and SmartPLS 4.0 program. Result: Values-driven motive and strategic motive influence authenticity, while stakeholder-driven motive and egoistic motive did not influence authenticity. Values-driven motive influences on attitude, while stakeholder-driven motive, strategic motive and egoistic motive didn't. Lastly, authenticity influences attitude. Conclusions: Companies need to be aware that consumers may infer different motives for their CSR activities, and pay close attention to consumers' perceived motives from the planning stage of CSR activities. In particular, companies should focus on the values-driven motive and the strategic motive when planning CSR activities.

• Smart Structures and Systems
• /
• v.15 no.3
• /
• pp.897-911
• /
• 2015

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.3 no.3
• /
• pp.235-250
• /
• 2009

An understanding of performance of database driven network applications is critical in combating slow performance of e-commerce web sites, besides efficient web page design, and high quality and well-maintained web server equipment. This paper describes a method of measuring performance from the user viewpoint, which can help enormously in making realistic assessment of true performance of database driven applications. The performance measurements were taken at user locations by using several specially designed JavaScript functions along with ASP scripts. A performance study is presented in this paper, comparing performance of data access using stored procedures with the traditional way of querying a database. It is generally believed that stored procedures have performance benefits as they are pre-compiled. However, our study shows that the data access approach using stored procedures provides significant benefits(by about 30%) over the traditional approach for querying a commercial MySQL database, only when retrieving a substantial amount of data(at least 10,000 rows of data).

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.418-421
• /
• 2007

Using gridded wind-stress products constructed by satellite scatterometers (ERS-1, 2 and QSCAT) data and those by numerical weather prediction(NWP) model(NCEP-reanalysis), we estimate wind-driven transports of the North Pacific subtropical gyre, and compare them in the central portion of the gyre (around 300 N) with geostrophic transports calculated from historical hydrographic data (World Ocean Database 2005). Even if there are some discrepancies between the wind-driven transports by the QSCAT and NCEP products, they are both in good agreement with the geostrophic transports within reasonable errors, except for the regional difference in the eastern part of the zone. The difference in the eastern part is characterized by an anticyclonic deviation of the geostrophic transport resulting from an anti-cyclonic anomalous flow in the surface layer, suggesting that it is related to the Eastern Gyral produced by the thermohaline process associated with the formation of the Eastern Subtropical Mode Water. We also examine the consistency of the Sverdrup transports estimated from these products by comparing them with the transports of the western boundary current, namely the Kuroshio regions, in previous studies. The net southward transport, based on the sum of the Sverdrup transports by QSCAT and NCEP products and the thermohaline transport, agrees well with the net northward transport of the western boundary current, namely the Kuroshio transport. From these results, it is concluded that the Sverdrup balance can hold in the North Pacific subtropical gyre.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.893-903
• /
• 2022

Recently, computer vision (CV)-based safety monitoring (i.e., object detection) system has been widely researched in the construction industry. Sufficient and high-quality data collection is required to detect objects accurately. Such data collection is significant for detecting small objects or images from different camera angles. Although several previous studies proposed novel data augmentation and synthetic data generation approaches, it is still not thoroughly addressed (i.e., limited accuracy) in the dynamic construction work environment. In this study, we proposed a game engine-driven synthetic data generation model to enhance the accuracy of the CV-based object detection model, mainly targeting small objects. In the virtual 3D environment, we generated synthetic data to complement training images by altering the virtual camera angles. The main contribution of this paper is to confirm whether synthetic data generated in the game engine can improve the accuracy of the CV-based object detection model.

• Journal of Korean Academy of Nursing Administration
• /
• v.21 no.3
• /
• pp.308-316
• /
• 2015

Purpose: The purpose of this study was to identify the level of project perception for those nurses from research-driven hospitals and to analyze the effect of research-relevant performance in the health care field focusing on the mediated effect of research capacity and job satisfaction. Methods: Data were collected from June, 2014 to July, 2014, and participants were 106 research nurses in Research-driven hospitals. Descriptive statistics, Independent t-test, One-way ANOVA, structural equation modeling (SEM). Results: As a result, Research-relevant performance according to project perception of research nurses from Research-driven Hospitals was not statistically significant, but research capacity and job satisfaction had a mediating role. Evaluation System Perception was significantly different from Research Capacity (p<.001), Research Capacity was significantly different from Job Satisfaction (p<.001), Job Satisfaction was significantly different from Research Performance (p<.001) Conclusion: The results indicate that research capacity building and job security research nurses are able to contribute to improving research performance of research-driven hospitals.

• Proceedings of the KAIS Fall Conference
• /
• 2003.11a
• /
• pp.99-104
• /
• 2003

In this research, we proposed the mechanism to develop self evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most former researchers tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, thy have some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, many of researchers had tried to develop an automatic knowledge extraction and refining mechanisms. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, in this study, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference. Our proposed mechanism has five advantages empirically. First, it could extract and reduce the specific domain knowledge from incomplete database by using data mining algorithm. Second, our proposed mechanism could manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it could construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems). Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic. Fifth, RDB-driven forward and backward inference is faster than the traditional text-oriented inference.

• Journal of Oriental Neuropsychiatry
• /
• v.32 no.4
• /
• pp.303-320
• /
• 2021

Objectives: Although medical typologies based on indigenous biopsychological ideas have been described, their integrity has been questioned due to its theory-driven nature in categorization. Therefore, studies on the Sasang typology, a temperament-based traditional Korean medicine, are needed to examine whether it is possible to classify types of specific biopsychological profiles using data-driven analysis. Methods: Psychological measures of the Eastern Sasang Personality Questionnaire (SPQ) and Western NEO-Personality Inventory (NEO-PI) along with physical measures and Sasang types were acquired from 2,049 participants. Latent groups based on the SPQ and NEO-PI subscale scores were extracted using Latent Profile Analysis. Their psychosomatic features were then compared with those of Sasang types. Results: Three SPQ-based latent groups showed distinctive psychological and physical features consistent with those of Sasang types. However, four NEOPI-based latent groups presented only psychological features. Furthermore, SPQ-High and SPQ-Low latent groups demonstrated similar psychosomatic profiles to those of So-Yang and So-Eum Sasang types, respectively. Conclusions: This study illustrates that biopsychological profiles of Sasang types are supported by psychosomatic features of latent groups based on SPQ of Eastern psychology, signifying that the categorization of Sasang typology have acceptable validity and reliability.