• Asian-Australasian Journal of Animal Sciences
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• v.29 no.2
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• pp.299-306
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• 2016

Body temperature (BT) monitoring in cattle could be used to early detect fever from infectious disease or physiological events. Various ways to measure BT have been applied at different locations on cattle including rectum, reticulum, milk, subcutis and ear canal. In other to evaluate the temperature stability and reliability of subcutaneous temperature (ST) in highly fluctuating field conditions for continuous BT monitoring, long term ST profiles were collected and analyzed from cattle in autumn/winter and summer season by surgically implanted thermo-logger devices. Purposes of this study were to assess ST in the field condition as a reference BT and to determine any location effect of implantation on ST profile. In results, ST profile in cattle showed a clear circadian rhythm with daily lowest at 05:00 to 07:00 AM and highest around midnight and rather stable temperature readings (mean${\pm}$standard deviation [SD], $37.1^{\circ}C$ to $37.36^{\circ}C{\pm}0.91^{\circ}C$ to $1.02^{\circ}C$). STs are $1.39^{\circ}C$ to $1.65^{\circ}C$ lower than the rectal temperature and sometimes showed an irregular temperature drop below the normal physiologic one: 19.4% or 36.4% of 54,192 readings were below $36.5^{\circ}C$ or $37^{\circ}C$, respectively. Thus, for BT monitoring purposes in a fever-alarming-system, a correction algorithm is necessary to remove the influences of ambient temperature and animal resting behavior especially in winter time. One way to do this is simply discard outlier readings below $36.5^{\circ}C$ or $37^{\circ}C$ resulting in a much improved mean${\pm}$SD of $37.6^{\circ}C{\pm}0.64^{\circ}C$ or $37.8^{\circ}C{\pm}0.55^{\circ}C$, respectively. For location the upper scapula region seems the most reliable and convenient site for implantation of a thermo-sensor tag in terms of relatively low influence by ambient temperature and easy insertion compared to lower scapula or lateral neck.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.2
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• pp.179-194
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• 2020

A Bayesian approach was introduced to improve the belief of prior distributions of input parameters for the probabilistic safety assessment of radioactive waste repository. A GoldSim-based module was developed using the Markov chain Monte Carlo algorithm and implemented through GSTSPA (GoldSim Total System Performance Assessment), a GoldSim template for generic/site-specific safety assessment of the radioactive repository system. In this study, sequential Bayesian updating of prior distributions was comprehensively explained and used as a basis to conduct a reliable safety assessment of the repository. The prior distribution to three sequential posterior distributions for several selected parameters associated with nuclide transport in the fractured rock medium was updated with assumed likelihood functions. The process was demonstrated through a probabilistic safety assessment of the conceptual repository for illustrative purposes. Through this study, it was shown that insufficient observed data could enhance the belief of prior distributions for input parameter values commonly available, which are usually uncertain. This is particularly applicable for nuclide behavior in and around the repository system, which typically exhibited a long time span and wide modeling domain.

• Journal of Korea Technology Innovation Society
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• v.20 no.3
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• pp.576-606
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• 2017

It is more salient in the high-tech industry to cooperate even among competitors in order to promptly respond to the changes in product architecture. In this sense, 'co-opetition,' which is the combination word between 'cooperation' and 'competition,' is the new business term in the strategic management and represents the two concepts "simultaneously co-exist." From this view, this study set up the research purposes as follows: 1) investigating the corporate managerial and technological behavioral characteristics in the co-opetition of the global display industry. 2) verifying the emerging factors during the co-opetition behavior hereafter. 3) suggesting the strategic direction focusing on the co-opetition behavioral characteristics. To this end, this study used co-word network analysis to understand the structure in context level of the co-opetition. In order to understand topics on each network, we clustered the keywords by community detection algorithm based on modularity and labeled the cluster name. The results show that there were increasing patterns of competition rather than cooperation. Especially, the litigations for mutual control against Korean firms much more severely occurred and increased as time passed by. Investigating these network structure in technological evolution perspective, there were already active cooperation and competition among firms in the early 2000s surrounding the issues of OLED-related technology developments. From the middle of the 2000s, firm behaviors have focused on the acceleration of the existing technologies and the development of futuristic display. In other words, there has been competition to take leadership of the innovation in the level of final products such as the TV and smartphone by applying the display panel products. This study will provide not only better understanding on the context of the display industry, but also the analytical framework for the direction of the predictable innovation through analyzing the managerial and technological factors. Also, the methods can support CTOs and practitioners in the technology planning who should consider those factors in the process of decision making related to the strategic technology management and product development.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.5
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• pp.437-444
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• 2020

This study was focused on the stabilization of surge motions of a moored vessel under irregular head seas. A two-point moored vessel shows strong non-linearity even in regular sea, owing to its inherent non-linear restoring force. A long-crested irregular wave is subjected to the vessel system, resulting in more complex nonlinear behavior of the displacement and velocities than in the case of regular waves. Sliding mode control (SMC) is implemented in the moored vessel to control both surge displacement and surge velocity. The SMC can provide a closed-loop system with performance and robustness against parameter uncertainties and disturbances; however, chattering is the main drawback for implementing SMC. The goal of minimizing the chattering and state convergence with accuracy is achieved using a quasi-sliding mode that approximates the discontinuous function via a continuous sigmoid function. Numerical simulations were conducted to validate the effectiveness of the proposed control algorithm.

• Steel and Composite Structures
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• v.34 no.5
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• pp.743-767
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• 2020

Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R² = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R² = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.5
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• pp.682-692
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• 2007

This study presents an automatic system to predict parturition time in the crated sows. The system relies on ultrasonic transducers mounted from above along the length of the crate. Using a 40 kHz time of flight (TOF) single envelope wave, the momentary distances between the sensors are measured. Therefore, the local momentary height of the sow and the momentary posture, i.e. standing posture (SDP), kneeling posture (KP), sitting posture (STP) and lateral lying posture (LLP) are determined. Crated sows change their postures from standing to lying and vice versa which follows a characteristic pattern. As parturition approaches, sows exhibit uneasiness, restlessness and the stand up sequence (SUS, the posture transition from LLP to SDP) rate increases because of labor pains. In time series, the SUS rate demonstrates a peak and it happens approximately 0-12 h before parturition. In this paper, the basic parturition threshold value method (BPTVM) and the same hour method (SHM) are proposed for predicting parturition, both of which are based on the SUS rate. The BPTVM mainly detects the peak of the SUS rate. As the SUS rate exceeds the threshold value, the parturition becomes predictable. Moreover, the SHM calculates the difference in the SUS rates between a particular time of day and the corresponding time of the preceding day. Compared to the BPTVM, the SHM can eliminate the circadian rhythm of the SUS rate influenced by feeding behavior. Using the SHM the parturition can be approximately predicted within hours. In an attempt to define the threshold parameters of predicting parturition, a data set with 32 sows of the SUS rate are used to estimate assumable predicting probability. The results show the assumable probability of the parturition prediction within 9 h is 96.9% for the SHM and 84.4% for the BPTVM. Moreover, the SHM can even reach a 75% probability of prediction within three hours of parturition. We conclude that the SHM is more accurate and is more useful for parturition time prediction. When parturition is detected, the proposed algorithm generates a warning signal which can inform human personnel to protect the mother and newborn piglets.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.21-28
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• 2015

In the semi-conductor process, a simulation process is performed to detect defects by analyzing the behavior of the impurity through the physical quantity calculation of the inner element. In order to perform the simulation, Finite-Difference Time-Domain(FDTD) algorithm is used. The improvement of semiconductor which is composed of nanoscale elements, the size of simulation is getting bigger. Problems that a processor such as CPU or GPU cannot perform the simulation due to the massive size of matrix or a computer consist of multiple processors cannot handle a massive FDTD may come up. For those problems, studies are performed with parallel/distributed computing. However, in the past, only single type of processor was used. In GPU's case, it performs fast, but at the same time, it has limited memory. On the other hand, in CPU, it performs slower than that of GPU. To solve the problem, we implemented a computing model that can handle any FDTD simulation regardless of size on the cluster which consist of heterogeneous processors. We tested the simulation on processors using MPI libraries which is based on 'point to point' communication and verified that it operates correctly regardless of the number of node and type. Also, we analyzed the performance by measuring the total execution time and specific time for the simulation on each test.

• The Journal of the Acoustical Society of Korea
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• v.7 no.4
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• pp.54-76
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• 1988

In Part Ⅰ of the paper, we have developed various block least mean-square (BLMS) adaptive digital filters (ADF's) based on a unified matrix treatment. In Part Ⅱ we analyze the convergence behaviors of the self-orthogonalizing frequency-domain BLMS (FBLMS) ADF and the unconstrained FBLMS (UFBLMS) ADF both for the overlap-save and overlap-add sectioning methods. We first show that, unlike the FBLMS ADF with a constant convergence factor, the convergence behavior of the self-orthogonalizing FBLMS ADF is governed by the same autocorrelation matrix as that of the UFBLMS ADF. We then show that the optimum solution of the UFBLMS ADF is the same as that of the constrained FBLMS ADF when the filter length is sufficiently long. The mean of the weight vector of the UFBLMS ADF is also shown to converge to the optimum Wiener weight vector under a proper condition. However, the steady-state mean-squared error(MSE) of the UFBLMS ADF turns out to be slightly worse than that of the constrained algorithm if the same convergence constant is used in both cases. On the other hand, when the filter length is not sufficiently long, while the constrained FBLMS ADF yields poor performance, the performance of the UFBLMS ADF can be improved to some extent by utilizing its extended filter-length capability. As for the self-orthogonalizing FBLMS ADF, we study how we can approximate the autocorrelation matrix by a diagonal matrix in the frequency domain. We also analyze the steady-state MSE's of the self-orthogonalizing FBLMS ADF's with and without the constant. Finally, we present various simulation results to verify our analytical results.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.133-143
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• 2017

Data is the most important asset in the financial sector. On average, 71 percent of financial institutions generate competitive advantage over data analysis. In particular, in the card industry, the card transaction data is widely used in the development of merchant information, economic fluctuations, and information services by analyzing patterns of consumer behavior and preference trends of all customers. However, creation of new value through fusion of data is insufficient. This study introduces the analysis and forecasting of consumption trends of credit card companies which convergently analyzed the social data and the sales data of the company's own. BC Card developed an algorithm for linking card and social data with trend profiling, and developed a visualization system for analysis contents. In order to verify the performance, BC card analyzed the trends related to 'Six Pocket' and conducted th pilot marketing campaign. As a result, they increased marketing multiplier by 40~100%. This study has implications for creating a methodology and case for analyzing the convergence of structured and unstructured data analysis that have been done separately in the past. This will provide useful implications for future trends not only in card industry but also in other industries.

• Journal of the Korean School Mathematics Society
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• v.9 no.1
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• pp.105-120
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• 2006

The Seventh Curriculum makes sure that those students who don't have a proper understanding of contents required at a certain stage take a remedial course. But a trend contrary to the intention is formed since there is no systematic education for such a course and thus more students get to fall into the group of low achievement. In particular, solving a simultaneous equation in a rote way without understanding influences negatively students' achievement. Schoenfeld introduced the basic elements of one's own mathematical problem solving process and behavior, referred to Polya's. Employing Schoenfeld's strategy, this study aimed to induce students' active participation in math classes, as well as to focus on a mathematical problem solving process during the study. Two students were selected from a remedial course at 00 Middle School and administered with a qualitative case study method over 17 lessons, each of which lasted for 30 minutes. In the beginning, they used such knowledge as facts and definitions a lot. There was a tendency of their resorting to intuitive knowledge more when they lacked basic knowledge or met with a difficult question. As the lessons were given, however, they improved their ability to implement algorithm procedures and used more familiar ones with the developed common procedures in the area of resources.