• School Mathematics
• /
• v.6 no.4
• /
• pp.389-409
• /
• 2004

This article presents a case study in which three middle school students developed models in modeling activity using a tool. We research the interaction of model development process and the activities operating a tool in the modeling. And we investigate whether students are able to create generalizable model, after a tool mediates students' thought process and students internalize the perceptive activity operating a tool. The analysis of our case study led to three results. First, as students were able to integrate perceptive activity operating a tool and cognitive activity, they reasoned about the relationships among changing quantities and developed the model. Second, students corrected and refined developed models with reflecting the perceptive activity operating a tool. Third, as students internalized perceptive activity, students were able to create generalizable model, which is a graph of height as a function of the amount of water that's in the beaker.

• The Journal of Korean Association of Computer Education
• /
• v.9 no.2
• /
• pp.27-36
• /
• 2006

This study intends to present essential models for collaborative learning in e-learning environment as well as to analyze learning behavior elements appearing in collaborative learning activities. In order to achieve goal of the study, the researchers analyzed existing cooperative learning models for face-to-face classroom, collaborative activity models based on instructional theory, and the structures and activities elements of learning community and collaborative activity models focusing on e-learning environment. As a result of the study, the researchers produced a generalizable collaborative learning model for e-learning which include general collaborative learning model, and further analyzed specific learning behaviors performed by learners while they proceed in this model based learning processes. The adequacy of this model and reliability of learning behavior elements were tested through experts' review meetings. The research result, suggesting generalizable collaborative learning model as well as learning behaviors elements which might occur within e-learning based collaborative learning, might work as a foundational model for software infrastructure and e-learning solution business. Moreover, its value might be maximized if its being used for enhancing learning content interoperability and reuse as well as for establishing international standardization for collaborative technology.

• Journal of Educational Research in Mathematics
• /
• v.14 no.4
• /
• pp.403-419
• /
• 2004

The perspective on this study assumes that the mathematical modeling activity provides students with the environment which promotes metacognitive thinking. The purposes of this paper are to investigate metacognitive thinking on the mathematical modeling with the result of case study. The study revealed that development of students' model was accompanied with the control and monitoring of modeling activities. Also students refined the model by self-assessment and peer-assessment in small group modeling activities and developed generalizable model.

• Journal of Korean Institute of Industrial Engineers
• /
• v.2 no.1
• /
• pp.93-100
• /
• 1976

Given a fixed production process and facility capacity, the ability to respond to market fluctuations in terms of changes in production, work force, and inventory is the major task of production management. The costs involved are primarily payroll (regular and overtime), inventory carrying, and hiring and firing. The magnitude of these costs is usually a significant portion of the operating costs of the firm and consequently a small percentage saving due to astute aggregate scheduling can mean substantial absolute saving. At least three demonstrably optimal techniques have been developed for solving this aggregate scheduling problem. These three optimal are apparently LDR, PPP, and SDR. By combining these three different approaches, another optimal solution was obtained by me. I call this CDR (Combined Decision Rule). This approach appears to be useful. This approach may be generalizable to aggregate scheduling involving a short term resources.

• Health Policy and Management
• /
• v.5 no.2
• /
• pp.173-201
• /
• 1995

A causal model of organizational commitment on the basis of Western literature was tested with a sample of 1,164 employees from two university hospitals in Korea. The model contains three groups of determinants : environmental variables(job opportunity, spouse support, and parent support), psychological variables(met expectations, work involvement, positive affectivity, and negative affectivity), and structural variables(job autonomy, work unit control, routinization, supervisor support, coworker support, role ambiguity, role conflict, workload, resource inadequacy, distributive justice, promotional chances, job security, job hazarda, and pay). The data were colleted with questionnaires and analyzed with the LISREL maximum likelihood method. It is found that (1) the following variables, listed in order of size, have significant total effects on organizational commitment : job satisfaction, met expectations, supervisor support, job security, routinization, job opportunity, negative affectivity, work involvement, distributive justice, and promotional opportunity, (2) the model explains fifty-nine percent of the variance in organizational commitment, and (3) the link with expectancy theory is justified by the results for met expectations. Two conclusions can be drawn from these findings. First, the model of organizational commitment appears to be generalizable to Korean hospitals. Second, the model of organizational commitment should include such theoretical variables as environmental, psychological, and structural factors.

• Investigative Magnetic Resonance Imaging
• /
• v.25 no.4
• /
• pp.293-299
• /
• 2021

Purpose: To accelerate magnetic resonance fingerprinting (MRF) by developing a flexible deep learning reconstruction method. Materials and Methods: Synthetic data were used to train a deep learning model. The trained model was then applied to MRF for different organs and diseases. Iterative reconstruction was performed outside the deep learning model, allowing a changeable encoding matrix, i.e., with flexibility of choice for image resolution, radiofrequency coil, k-space trajectory, and undersampling mask. In vivo experiments were performed on normal brain and prostate cancer volunteers to demonstrate the model performance and generalizability. Results: In 400-dynamics brain MRF, direct nonuniform Fourier transform caused a slight increase of random fluctuations on the T2 map. These fluctuations were reduced with the proposed method. In prostate MRF, the proposed method suppressed fluctuations on both T1 and T2 maps. Conclusion: The deep learning and iterative MRF reconstruction method described in this study was flexible with different acquisition settings such as radiofrequency coils. It is generalizable for different in vivo applications.

• The Journal of Information Systems
• /
• v.15 no.4
• /
• pp.149-170
• /
• 2006

This research investigates the determinants of the customer's acceptance intuition for the ads on cellular phone. For this purpose, this research set up a model with such variables as entertainment information irritation, credibility, flow experience, attitudes and acceptance intention based on TAM and Flow theory. For the more reasonable and generalizable results, this study targets two different customer groups in Korea and Japan and compare the responses from these two groups using AMOS, the structural equation modeling and a second-generation multi - variant techniques.

• Journal of the Korean Physical Society
• /
• v.73 no.12
• /
• pp.1908-1917
• /
• 2018

The binding affinity between the T-cell receptors (TCRs) and antigenic peptides mainly determines immunological recognition. It is not a trivial task that T cells identify the digital sequences of peptide amino acids by simply relying on the integrated binding affinity between TCRs and antigenic peptides. To address this problem, we examine whether the affinity-based discrimination of peptide sequences is learnable and generalizable by artificial neural networks (ANNs) that process the digital experimental amino acid sequence information of receptors and peptides. A pair of TCR and peptide sequences correspond to the input for ANNs, while the success or failure of the immunological recognition correspond to the output. The output is obtained by both theoretical model and experimental data. In either case, we confirmed that ANNs could learn the immunological recognition. We also found that a homogenized encoding of amino acid sequence was more effective for the supervised learning task.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.614-616
• /
• 2021

The world faces difficulties in terms of eye care, including treatment, quality of prevention, vision rehabilitation services, and scarcity of trained eye care experts. However, it is difficult to develop a method for classifying various ocular diseases because the existing dataset for retinal image disclosure does not consist of various diseases found in clinical practice. We propose a method for classifying ocular diseases using the Retinal Fundus Multi-disease Image Dataset (RFMiD), a dataset published in the ISBI-2021 challenge. Our goal is to develop a robust and generalizable model for screening retinal images into normal and abnormal categories. The performance of the proposed model shows a value of 0.9782 for the test dataset as an area under the curve (AUC) score.

• Analyses & Alternatives
• /
• v.1 no.2
• /
• pp.2-12
• /
• 2017

Research on democratic transitions has relatively ignored the question of why some countries experience a regressive form of political pacts, while others do not. This paper develops a simple game-theoretic model to explain the phenomenon of collusive pacts in the process of democratization. Trasformismo is a term that refers to a system of political exchange based on informal clientelistic politics. The existing studies of the politics of trasformismo have emphasized the timing of industrialization and the tradition of strong state as conditions of the politics of trasformismo. However, not every late industrializers and not every strong states experienced some variants of collusive political pacts in their trajectories of democratization. In this paper, I contend that the politics of trasformismo is rather a generalizable pattern of political elites' behavior under particular circumstances. By developing a simple game theoretic model, this paper suggests the conditions under which political actors are likely to collude to a regressive form of political pacts. The model shows that the likelihood of collusion to a regressive form of political pacts is a function of a set of parameters. First, a higher level of incumbency advantage in electoral competition is likely to be associated with a higher probability of collusive political pacts. Second, a higher degree of the monopoly of political representation of political parties without a close link with a variety of societal forces is likely to induce collusive behavior among politicians. Third, the ruling party leader's expectations about the likelihood of a safe extrication are related to collusive political pacts. This paper then engages in a case study of the 1990 three-party merger in South Korea. The 1990 Korean case is interesting in that the ruling party created a new party after having merged with two opposition parties. This case can be considered a result of political maneuver in a context of democratization. The case study suggests the empirical relevance of the game-theoretic model. As the game of trasformismo and the case study of the 1990 three-party merger in South Korea have shown, the collusive political pact was neither determined by a certain stage of economic development nor by a particular cultural systems. Rather, it was a product of the art of trasformismo based on party leaders' rational calculations of the expected likelihood of taking governing power.