• Korean Circulation Journal
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• v.53 no.6
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• pp.406-417
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• 2023

Background and Objectives: Pathophysiological changes of right ventricle (RV) after repair of tetralogy of Fallot (TOF) are coupled with a highly compliant low-pressure pulmonary artery (PA) system. This study aimed to determine whether pulmonary vascular function was associated with RV parameters and exercise capacity, and its impact on RV remodeling after pulmonary valve replacement. Methods: In a total of 48 patients over 18 years of age with repaired TOF, pulmonary arterial elastance (Ea), RV volume data, and RV-PA coupling ratio were calculated and analyzed in relation to exercise capacity. Results: Patients with a low Ea showed a more severe pulmonary regurgitation volume index, greater RV end-diastolic volume index, and greater effective RV stroke volume (p=0.039, p=0.013, and p=0.011, respectively). Patients with a high Ea had lower exercise capacity than those with a low Ea (peak oxygen consumption [peak VO₂] rate: 25.8±7.7 vs. 34.3±5.5 mL/kg/min, respectively, p=0.003), while peak VO₂ was inversely correlated with Ea and mean PA pressure (p=0.004 and p=0.004, respectively). In the univariate analysis, a higher preoperative RV end-diastolic volume index and RV end-systolic volume index, left ventricular end-systolic volume index, and higher RV-PA coupling ratio were risk factors for suboptimal outcomes. Preoperative RV volume and RV-PA coupling ratio reflecting the adaptive PA system response are important factors in optimal postoperative results. Conclusions: We found that PA vascular dysfunction, presenting as elevated Ea in TOF, may contribute to exercise intolerance. However, Ea was inversely correlated with pulmonary regurgitation (PR) severity, which may prevent PR, RV dilatation, and left ventricular dilatation in the absence of significant pulmonary stenosis.

• Journal of The Korean Association For Science Education
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• v.36 no.1
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• pp.177-190
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• 2016

The purpose of this study is to validate learning progressions for Earth's motion and solar system from two different perspectives of validity. One is construct validity, that is whether a hypothetical pathway derived from our study of LPs is supported by empirical evidence of children's substantive development. The other is consequential validity, which refers to the impact of LP-based adaptive instruction on children's improved learning outcomes. For this purpose, 373 fifth-grade students and 17 teachers from six elementary schools in Seoul, Kangwon province, and Gwangju participated. We designed LP-based adaptive instruction modules delving into the unit of 'Solar system and stars.' We also employed 13 ordered multiple-choice items and analyzed the transitions of children's achievement levels based on the results of pre-test and post-test. For testing construct validity, 64 % of children in the experimental group showed improvement according to the hypothetical pathways. Rasch analysis also supports this results. For testing consequential validity, the analysis of covariance between experimental and control groups revealed that the improvement of experimental group is significantly higher than the control group (F=30.819, p=0.000), and positive transitions of children's achievement level in the experimental group are more dominant than in the control group. In addition, the findings of applying Rasch model reveal that the improvement of students' ability in the experimental group is significantly higher than that of the control group (F=11.632, p=0.001).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.63-68
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• 2010

The Color Management System in recent printers adopts ICC profiles for both monitors and printers. However, the ICC profile doesn't contain the characteristics of reproduced color on each monitor, because the color on each monitor is changed by user adjustment such as color temperature, brightness, and contrast adjustment. It is also depended on the backlight type and lifetime. As a result, unwanted color is reproduced on the printed paper, not like that on the monitor. To overcome the color difference between monitors and printers, it is needed to control the information of ICC profile. That is, first, the ICC profile is generated by the measurement of monitors having user set, then, through the CMS, the color on monitors can be produced on printed paper. However, it is difficult to apply the above system for normal users due to absence of measuring equipment and time consuming process. Therefore, this paper proposes a novel color matching technique based on the estimation of condition for each monitor having user set. The estimation is performed by a simple comparison visual test using a test image on printed paper and monitor. Then, the condition of monitor is applied to the ICC profile. As a result, the new ICC profile contains the color difference between user monitor and printer. The experimental results show the printed images using our proposed method have almost similar color with those on monitors.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.65 no.4
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• pp.274-283
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• 2020

Seed dormancy is an adaptive trait in which seeds do not germinate under unfavorable environmental conditions. Low dormancy seeds are easily germinated under optimal environmental conditions, and these characteristics greatly reduce the yield and quality of crops. In the present study, we compared the pre-harvest sprouting (PHS) rate of two cultivars, Joun and Jopyeong, using the Winkler scale after heading day and temperature of the test. The PHS rate increased as the Winkler scale after heading day increased from 700℃ to 1100℃ and the temperature of the test increased. In all conditions, the PHS rate of Jopyeong was higher than that of Joun. RNA-sequencing was used to analyze the cause of the high PHS rate. We analyzed the biological metabolic processes related to the abscisic acid (ABA) metabolite pathway using the KEGG mapper with selected differentially expressed genes in PHS seeds. We found that the expression of ABA biosynthesis genes (OsNCEDs) was down-regulated and that ABA catabolic genes (OsCYP707As) was up-regulated in PHS seeds. However, the quantitative real-time PCR results showed that Joun had a higher expression of OsNCEDs than that of Jopyeong, but OsCYP707As did not yield a significant result. Joun displayed higher ABA content than that of Jopyeong not only during ripeness time but also during PHS treatment. Taken together, we provided evidence that the ABA content remaining in the seed is important to the PHS rate, which is determined by the expression level of the ABA biosynthesis gene OsNCEDs.

• 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.

• 대한공업교육학회지
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• v.41 no.2
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• pp.1-23
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• 2016

This study was conducted to analyze the effect Meister high school students' career maturity with respect to the impact on school maladjustment. Also, this study clarify the relationship. This study purpose is to permanently provide Meister as the basis for the vocational education sector career education needed to faithfully serve as a special purpose high schools. Tools used for the survey is maladaptive measurement tools developed by Leegyumi (2004) and Career maturity measurement tools developed at Korea Research Institute for Vocational Education and Training (2012). Using these tools, a reliability test was conducted. Meister students' career maturity was conducted correlation analysis and multiple regression analysis to analyze the impact of school maladjustment. Independent variables are consisted of career maturity and independence, attitude toward the job, planning, self-understanding, rational decision-making, information retrieval, knowledge of the desired job, career exploration and ready for action. Meister high school student's career maturity according to the students' background variables are little girls was higher than boys, but it was not statistically significant. T-test was conducted to ascertain the career maturity and school maladjustment differences of adaptation groups and maladaptive group in meister school students in background variables. A career maturity and school maladjustment between adaptive and maladaptive population groups showed a statistically significant difference in background variables.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.3
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• pp.304-315
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• 2001

In this paper, we peformed the real-time implementation of AMR(Adaptive Multi-Rate) speech coding algorithm which is adopted for IMT-2000 service using TMS320C6201, i.e., a Texas Instrument´s fixed-point DSP. With the ANSI C source code released from ETSI, optimization is performed to make it run in real-time with memory as small as possible using the C compiler and assembly language. Implemented AMR speech codec has the size of 32.06 kWords program memory, 9.75 kWords data RAM memory, and 19.89 kWords data ROM memory. And, The time required for processing one frame of 20 ms length speech data is about 4.38 ms, and it is short enough for real-time operation. It is verified that the decoded result of the implemented speech codec on the DSP is identical with the PC simulation result using ANSI C code for test sequences. Also, actual sound input/output test using microphone and speaker demonstrates its proper real-time operation without distortions or delays.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.97-111
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• 2009

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.

• Journal of Energy Engineering
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• v.28 no.2
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• pp.1-17
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• 2019

This article analyzes causal relationships among gross domestic product(GDP), electricity consumption, carbon dioxide($CO_2$) emission and foreign direct investments(FDI) inflow of Korea over the period from 1976 to 2014, using unit root test, cointegration test, and vector error correction model(VECM). As the results, this article found (1) a long-run bi-directional causality between GDP and electricity consumption, which may imply a negative impact of electricity consumption-saving policy on economic growth, (2) uni-directional short- and long-run causalities running from $CO_2$ emission to GDP, and a uni-directional long-run causality running from $CO_2$ emission to electricity consumption, which can result in a negative impact of $CO_2$ emission reduction policy on economic growth and electricity consumption, (3) a uni-directional long-run causality running from FDI to GDP, and uni-directional short- and long-run causalities running from FDI to electricity consumption, which may result from relatively lower electricity prices than investing countries, (4) no causality between FDI and $CO_2$ emission, which is based on the characteristics of FDI composed of service industries. Considering the above causal relationships among the four variables, the policy implication needs to focus on the electricity demand management based on the relevant R&Ds, and on the gradual transition from fossil fuel- to renewable-energy. Adaptive policy to increase the FDI inflow is also needed.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.