• Knowledge Management Research
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• v.16 no.3
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• pp.149-169
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• 2015

In this study, we try to understand the role of online social recommendation and the similarity of preferences between the recommender and the recommendee on consumer decisions in the framework of the two stage purchase decision-making process. Applying construal level theory to our context, we expect that the role of social recommendation and the similarity of preferences would vary over the stages in the two-stage decision making process. To test our hypotheses, we collected the data through an incentive compatible experiment, and analyzed the data with nested logit model. As a result, we found that the role of online social recommendation varies over the stages. Consumers take recommendation from similar others at the stage of consideration set formation, but no longer consider it at the stage of final choice. Consumers take recommendation from dissimilar others at the stage of consideration set formation. At the stage of final choice, however, consumers avoid choosing the option recommended by dissimilar others. The results of our study enrich the understanding about the role of social recommendation, and have implication to marketing practitioners who attempt to make online social recommendation system more efficient.

• Structural Monitoring and Maintenance
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• v.6 no.2
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• pp.85-101
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• 2019

The effects of foundation scour depth and riverbed condition on the natural frequencies of a typical cross-river integral abutment bridge have been studied. The conventional operational modal analysis technique has been employed in order to extract the modal properties of the bridge and the results have been used in the Finite Element (FE) model updating procedure. Two tests have been carried out in two different levels of water and wet condition of the riverbed. In the first test, the riverbed was in dry condition for two subsequent years and the level of water was 10 meter lower than the natural riverbed. In the second test, the river was opened to water flow from the upstream dam and the level of water was 2 meter higher than the natural riverbed. The results of these two tests have also been used in order to find to what extend the presence of water flow in the river and saturation of the surrounding soil affect the bridge natural frequencies. Finally, the updated FE model of the bridge has been applied in a series of parametric analyses incorporating the effect of piles' relative scour depth on the bridge natural frequency of the first four vibration modes.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.1
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• pp.5-19
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• 2015

Literatures on open innovation have two major limitations. First, either on a firm level or on an industry level did they analyze the open innovation issues. The results of a firm's innovation can be diffused through the whole network and the firm can learn back from the network knowledge. Prior literatures did not consider the feedback loop among firms and network in which the firms are involved. Second, most open innovation research had a static perspective on firm's innovation performance. Since the diffusion, spill-over and learning among network members are involved over time, the open innovation is intrinsically dynamic. From the dynamic perspective, we can appreciate the fundamental attributes of the open innovation network which involves diverse firms, research institutes, and universities. In order to overcome the limitations, we suggest a dynamic model for open innovation network. We build an agent-based model which consists of heterogeneous firms. The firms are connected through a scale-free network which is formed by preferential attachment. Through the diverse scenario of simulation, we collect massive data on the firm level and analyze them both on firm and industry level. From the analysis, we found that, on industry level, the overall performance of open innovation increases as the internal research capability, absorptive capacity, and learning curve coefficient increase. Noticeably, as the deprecation rate of knowledge increases, the variability of knowledge increases. From the firm level analysis, we found that the industry-level variables had a significant effect on the firm's innovation performance lasting through all the time, whereas the firm-level variables had only on the early phase of innovation.

• PNF and Movement
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• v.20 no.3
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• pp.359-370
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• 2022

Purpose: Physical therapists are required to properly choose the most appropriate treatment for each patient within the framework of the International Classification of Functioning, Disability, and Health (ICF model). The aims of this study were to determine whether neurological physical therapists in clinical settings in South Korea know about the ICF model and to investigate the current trends of outcome measures (OMs) used by them. Methods: Two hundred and one physical therapists who worked with patients with neurological disorders participated in this study. The survey was conducted via e-mail and asked about commonly used OMs and the considerations for selecting OMs. Results: All physical therapists involved in this study responded completely, and 45.8% of participants learned about the ICF model, while 37.3% understood the detailed information related to the ICF model. The rest of the participants did not know or just heard about the ICF model. The most frequently used tools at the body function/structure level were the Range of Motion (98%), Manual Muscle Test (97%), Berg Balance Scale (83.1%), and Modified Ashworth Scale (70.6%) when allowing repetition. At the activity level, the 10-meter walk test (71.1%), 6-minute walk test (54.2%), and Functional Ambulatory Category (43.3%) were used, while the Activity-Specific Balance Confidence Scale (23.9%) was used at the participation level. There was a positive relationship between the number of tools used and years of work, as well as the level of understanding of the ICF model. Conclusion: The results of this study suggest that it is necessary to learn the ICF model in a clinical setting. In addition, the medical system needs to be modified to encourage physical therapists in South Korea to use proper OMs within the ICF model.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.565-575
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• 2022

Recently, in the field of water resource engineering, interest in predicting time series water levels and flow rates using deep learning technology that has rapidly developed along with the Fourth Industrial Revolution is increasing. In addition, although water-level and flow-rate prediction have been performed using the Long Short-Term Memory (LSTM) model and Gated Recurrent Unit (GRU) model that can predict time-series data, the accuracy of flow-rate prediction in rivers with rapid temporal fluctuations was predicted to be very low compared to that of water-level prediction. In this study, the Paldang Bridge Station of the Han River, which has a large flow-rate fluctuation and little influence from tidal waves in the estuary, was selected. In addition, time-series data with large flow fluctuations were selected to collect water-level and flow-rate data for 2 years and 7 months, which are relatively short in data length, to be used as training and prediction data for the LSTM and GRU models. When learning time-series water levels with very high time fluctuation in two models, the predicted water-level results in both models secured appropriate accuracy compared to observation water levels, but when training rapidly temporal fluctuation flow rates directly in two models, the predicted flow rates deteriorated significantly. Therefore, in this study, in order to accurately predict the rapidly changing flow rate, the water-level data predicted by the two models could be used as input data for the rating curve to significantly improve the prediction accuracy of the flow rates. Finally, the results of this study are expected to be sufficiently used as the data of flood warning system in urban rivers where the observation length of hydrological data is not relatively long and the flow-rate changes rapidly.

• Journal of Korean Port Research
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• v.13 no.2
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• pp.279-288
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• 1999

This paper is concerned with developing a standard costing model based on the case study of PECT and GCT in order to improve operation efficiency and design business strategy. In doing so the model can be a useful tool to analyze current calculation system of lease charge at the two terminals and to judge whether the level of lease charge currently applied to them is justifiable for thier profitability.

• Advanced Composite Materials
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• v.16 no.3
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• pp.245-258
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• 2007

The single-modal Weibull model has been assessed on Tyranno ZMI Si-Zr-C-O fiber if a set of shape and scale parameters accurately reproduced the effect of the size of the diameter on strength. The tensile data of a single fiber have been divided into two expedient groups as 'small diameter' group and 'large diameter' group in deriving the parameters, which should be consistent if the Weibull model accurately reproduced the size effect. However, the derived Weibull parameters were inconsistent between the two groups. Thereby the authors have concluded that the parameters of the single-modal Weibull model are dependent on the fiber diameter, so that the model is inadequate to reproduce the strength size effect. On the other hand, Weibull parameters were found consistent between the two groups by excluding the data of 'large mirror zone' sample, which was defined as the sample around 10% mirror zone area of the fracture surface. What is more, the exclusion reduced the strength variance more drastically in the 'large diameter' group than in the 'small diameter' group, even though the 'large mirror zone' samples were found identical in the percentage between the two groups. The authors therefore conclude that diameter limitation to the 'small diameter' group level can lead to drastically less distributed strength values than the estimated strength through the Weibull scaling on the present Tyranno ZMI Si-Zr-C-O fiber.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.97-110
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• 2021

Fog can cause large-scale human and economic damages, including traffic systems and agriculture. So, Korea Meteorological Administration is operating about 290 visibility meters to improve the observation level of fog. However, it is still insufficient to detect very localized fog. In this study, high-resolution grid-type visibility data were retrieved from irregularly distributed visibility data across the country. To this end, three objective analysis techniques (Inverse Distance Weighting (IDW), Ordinary Kriging (OK) and Universal Kriging (UK)) were used. To find the best method and parameters, sensitivity test was performed for the effective radius, power parameter and variogram model that affect the level of objective analysis. Also, the effect of data distribution characteristics (level of normality) on the performance level of objective analysis was evaluated. IDW showed a relatively high level of objective analysis in terms of bias, RMSE and correlation, and the performance is inversely proportional to the effective radius and power parameter. However, the two Krigings showed relatively low level of objective analysis, in particular, greatly weakened the variability of the variables, although the level of output was different depending on the variogram model used. As the level of objective analysis is greatly influenced by the distribution characteristics of data, power, and models used, care should be taken when selecting objective analysis techniques and parameters.

• Journal of Biomedical Engineering Research
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• v.36 no.6
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• pp.276-282
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• 2015

Recently, during the multi-level fusion with pedicle screws, interspinous spacer are sometimes substituted for the most superior level of the fusion in an attempt to reduce the number of fusion level and likelihood of degeneration process at the adjacent level. In this study, a finite element (FE) study was performed to assess biomechanical efficacies of the interspinous spacer combined with posterior lumbar fusion with a previously-validated 3-dimensional FE model of the intact lumbar spine (L1-S1). The post-operative models were made by modifying the intact model to simulate the implantation of interspinous spacer and pedicle screws at the L3-4 and L4-5. Four different configurations of the post-op model were considered: (1) a normal spinal model; (2) Type 1, one-level fusion using posterior pedicle screws at the L4-5; (3) Type 2, two-level (L3-5) fusion; (4) Type 3, Type 1 plus Coflex$^{TM}$ at the L3-4. hybrid protocol (intact: 10 Nm) with a compressive follower load of 400N were used to flex, extend, axially rotate and laterally bend the FE model. As compared to the intact model, Type 2 showed the greatest increase in Range of motion (ROM) at the adjacent level (L2-3), followed Type 3, and Type 1 depending on the loading type. At L3-4, ROM of Type 2 was reduced by 34~56% regardless of loading mode, as compared to decrease of 55% in Type 3 only in extension. In case of normal bone strength model (Type 3_Normal), PVMS at the process and the pedicle remained less than 20% of their yield strengths regardless of loading, except in extension (about 35%). However, for the osteoporotic model (Type 3_Osteoporotic), it reached up to 56% in extension indicating increased susceptibility to fracture. This study suggested that substitution of the superior level fusion with the interspinous spacer in multi-level fusion may be able to offer similar biomechanical outcome and stability while reducing likelihood of adjacent level degeneration.

• Journal of Radiation Protection and Research
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• v.16 no.1
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• pp.53-72
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• 1991

An integrated model is developed in this paper for the performance assessment of high level radioactive waste repository. This integrated model consists of two simple mathematical models. One is a multiple-barrier failure model of the repository system based on constant failure rates which provides source terms to biosphere. The other is a biosphere model which has multiple pathways for radionuclides to reach to human. For the parametric uncertainty and sensitivity analysis for the risk assessment of high level radioactive waste repository, Latin hypercube sampling and rank correlation techniques are applied to this model. The former is cost-effective for large computer programs because it gives smaller error in estimating output distribution even with smaller number of runs compared to crude Monte Carlo technique. The latter is good for generating dependence structure among samples of input parameters. It is also used to find out the most sensitive, or important, parameter groups among given input parameters. The methodology of the mathematical modelling with statistical analysis will provide useful insights to the decision-making of radioactive waste repository selection and future researches related to uncertain and sensitive input parameters.