• Geomechanics and Engineering
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• v.38 no.3
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• pp.231-247
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• 2024

The use of lime stabilization and geosynthetic reinforcement is a common approach to improve the performance of fine-grained soils in geotechnical applications. However, the impact of this combination on the soil-geosynthetic interaction remains unclear. This study addresses this gap by evaluating the interface efficiency and soil-geosynthetic interaction parameters of lime-stabilized clay (2%, 4%, 6%, and 8% lime content) reinforced with geotextile or geogrid using direct shear tests at various curing times (1, 7, 14, and 28 days). Additionally, machine learning algorithms (Support Vector Machine and Artificial Neural Network) were employed to predict soil shear strength. Findings revealed that lime stabilization significantly increased soil shear strength and interaction parameters, particularly at the optimal lime content (4%). Notably, stabilization improved the performance of soil-geogrid interfaces but had an adverse effect on soil-geotextile interfaces. Furthermore, machine learning algorithms effectively predicted soil shear strength, with sensitivity analysis highlighting lime percentage and geosynthetic type as the most significant influencing factors.

• Computers and Concrete
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• v.25 no.6
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• pp.565-574
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• 2020

Over the years, several machine learning approaches have been proposed and utilized to create a prediction model for the high-performance concrete (HPC) slump flow. Despite HPC is a highly complex material, predicting its pattern is a rather ambitious process. Hence, choosing and applying the correct method remain a crucial task. Like some other problems, prediction of HPC slump flow suffers from abnormal attributes which might both have an influence on prediction accuracy and increases variance. In recent years, different studies are proposed to optimize the prediction accuracy for HPC slump flow. However, more state-of-the-art regression algorithms can be implemented to create a better model. This study focuses on several methods with different mathematical backgrounds to get the best possible results. Four well-known algorithms Support Vector Regression, M5P Trees, Random Forest, and MLPReg are implemented with optimum parameters as base learners. Also, redundant features are examined to better understand both how ingredients influence on prediction models and whether possible to achieve acceptable results with a few components. Based on the findings, the MLPReg algorithm with optimum parameters gives better results than others in terms of commonly used statistical error evaluation metrics. Besides, chosen algorithms can give rather accurate results using just a few attributes of a slump flow dataset.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.4
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• pp.13-23
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• 2007

This paper focuses on providing a practical approach for decision making in Performance-Based Design (PBD). Satisfactory performance is defined by several performance objectives that place limits on direct (monetary) loss and on a tolerable probability of collapse. No specific limits are placed on conventional engineering parameters such as forces or deformations, although it is assumed that sound capacity design principles are followed in the design process. The proposed design procedure incorporates different performance objectives up front, before the structural system is created, and assists engineers in making informed decisions on the choice of an effective structural system and its stiffness (period), base shear strength, and other important global structural parameters. The tools needed to implement this design process are (1) hazard curves for a specific ground motion intensity measure, (2) mean loss curves for structural and nonstructural subsystems, (3) structural response curves that relate, for different structural systems, a ground motion intensity measure to the engineering demand parameter (e.g., interstory drift or floor acceleration) on which the subsystem loss depends, and (4) collapse fragility curves. Since the proposed procedure facilitates decision making in the conceptual design process, it is referred to as a Design Decision Support System, DDSS. Implementation of the DDSS is illustrated in an example to demonstrate its practicality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.105-112
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• 2006

To improve the performance of identification for radars in an ES(Electronic warfare Support) system, it is necessary to estimate scan characteristics as well as the basic identification parameters such as frequency, pulse repetition interval and pulse width of radars. This paper presents the method of estimating the scan period and the scan beam width of circular scanning radars. The proposed method estimates the scan period using the quality of the autocorrelation of a periodic signal. And, it estimates the scan beam width using the linear interpolation and the proposed method of estimating the scan period. Simulation results are presented to show the performance of the proposed method.

• Journal of Distribution Science
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• v.14 no.11
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• pp.29-36
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• 2016

Purpose - Intense debate is occurring over support for farmers in Korea, specifically on the justification, policy design, and equality issues of the farm support programs. Given this debate, a new type of farm program in the US, a market flexible revenue program(the Average Crop Revenue Election, ACRE), is examined. ACRE stands in contrast to traditional programs that tie payments to price and have parameters that are fixed or change only infrequently. Research design, data, and methodology - Based on the ACRE program formulas, the potential payments are estimated by crop year, program crop and geographical area using the FSA acreage and payment rate data. Results - If all US farm program acres were in ACRE over the 2009-2013 crop years, payments would have totaled $7.95 billion or 1.2 percent of average market receipts for US crops. Enacting ACRE as a revenue program instead of a similarly-structured price-only program increased payments by $1.75 billion or 28 percent. Conclusions - Potential payments by ACRE largely reflected the distribution of the value of production across the program crops eligible for ACRE as well as across state geographical areas. If program parameters can be made acceptable and if data availability issues can be addressed, market flexible revenue programs offer a farm policy option that can address many of the concerns that have arisen over farm policy in Korea.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.64-71
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• 2017

Considering the volatility, intermittent and random of photovoltaic (PV) generation systems, accurate forecasting of PV power output is important for the grid scheduling and energy management. In order to improve the accuracy of short-term power forecasting of PV systems, this paper proposes a prediction model based on environmental factors and support vector machine optimized by genetic algorithm (GA-SVM). In order to improve the prediction accuracy of this model, weather conditions are divided into three types, and the gray correlation coefficient algorithm is used to find out a similar day of the predicted day. To avoid parameters optimization into local optima, this paper uses genetic algorithm to optimize SVM parameters. Example verification shows that the prediction accuracy in three types of weather will remain at between 10% -15% and the short-term PV power forecasting model proposed is effective and promising.

• The Journal of Korean Physical Therapy
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• v.10 no.1
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• pp.127-138
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• 1998

This study was carried out tn invstigate and compare biomechanical characteristics during free speed gait in hemiplegic patients after stroke who took therapeutic exercise by analyzing kinematic and kinetic data in the sagital plane and electromyographic data. Six patients($41\~69$ years old) and age-matched six volunteers in good health(51-61 years old) wire studied. The patients were sorted into two groups, depending on their self-speed of walking : fast speed group(3 patients) and slow speed group(3 patients). The results were as fellows. : 1. In spatio-temparal parameters, affected and unaffected side of fast group showed symetry but blew group showed asymetry of single limb support, opposite foot contact and stance phase (p<0.05). Compared with normal group, patient group showed slower velocity, shoter stride length and longer double limb support (p<0.05). 2. In the pelvic anterior tilt, patient group showed lower valued than normal group. It. In the ground reaction force-vertical force, fast group showed similar double peak gragh compared with normal group, butvslow group showed lower values without double peak (p<0.05).

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.57-62
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• 2005

Microarray gene expression profiling technology is one of the most important research topics in clinical diagnosis of disease. Given thousands of genes, only a small number of them show strong correlation with a certain phenotype. To identify such an optimal subset from thousands of genes is intractable, which plays a crucial role when classify multiple-class genes express models from tumor samples. This paper proposes an efficient classifier design method to simultaneously select the most relevant genes using an intelligent genetic algorithm (IGA) and design an accurate classifier using Support Vector Machine (SVM). IGA with an intelligent crossover operation based on orthogonal experimental design can efficiently solve large-scale parameter optimization problems. Therefore, the parameters of SVM as well as the binary parameters for gene selection are all encoded in a chromosome to achieve simultaneous optimization of gene selection and the associated SVM for accurate tumor classification. The effectiveness of the proposed method IGA/SVM is evaluated using four benchmark datasets. It is shown by computer simulation that IGA/SVM performs better than the existing method in terms of classification accuracy.

• Journal of the Korean Society of Physical Medicine
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• v.8 no.4
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• pp.559-566
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• 2013

PURPOSE: The present study examines how feedback respiratory exercise affects gait performance of stroke patients. METHODS: Forty stroke patients were randomly divided into an experiment group and a control group. For the former group, patients went through a half-hour of training therapy and a half-hour of feedback respiratory device exercise. For the latter group, patients went through 30 minutes of training therapy and a half-hour of motomed exercise. All participants had five training sessions each week for four weeks. For measurement, a GAITRite system was used to examine spatial parameters, and functional ambulation performance before and after the training. RESULT: In terms of spatial parameters, double support ratio, stance phase increased significantly in the experiment group after the walking exercise(p<.05). FAP rose more significantly in the experiment group than in the control group(p<.05). In comparison of two exercise groups, double support ratio, Stance phase, gait velocity, FAP was significant difference(p<.05). CONCLUSION: The experiment results showed that feedback respiratory exercise is effective in enhancing gait performance.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.623-628
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• 2000

Video-on-demand system in which users can request any video through the network at any time is made possible by rapid increase in network bandwidth and capacity of the media server. However true video-on-demand system cannot support all requests since bandwidth requirement is still too demanding. Therefore efficient bandwidth reduction algorithm is necessary. both the piggybacking method and the batching method are novel solutions that can provide more logical number of streams than the physical system can support. Of course each of them has its pros and cons. hence piggybacking with batching-by-size can take advantage of both the schemes. Some parameters such as the size of batch and the size of the catch-up window should be adjusted and order to maximize the bandwidth reduction for piggybacking with batching-by-size method. One of the most important parameters is decided optimally in this paper. Simulation shows that the optimized parameter can achieve considerable reductionand consequently remarkable enhancement in performance.