• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.339-346
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• 2019

Various studies have been conducted to evaluate the probabilistic fatigue life of steel railway bridges, but many of them are based on a relatively simple model of crack propagation. The model assumes zero minimum stress and constant loading amplitude, which is not appropriate for the fatigue life evaluation of railway bridges. Thus, this study proposes a new probabilistic method employing an advanced crack propagation model that considers the live-dead load ratio for the fatigue life evaluation of steel railway bridges. In addition, by using the rainflow cycle counting algorithm, it can handle variable-amplitude loading, which is the most common loading pattern for railway bridges. To demonstrate the proposed method, it was applied to a numerical example of a steel railway bridge, and the fatigue lives of the major components and structural system were estimated. Furthermore, the effects of various ratios of live-dead loads on bridge fatigue life were examined through a parametric study. As a result, with the increasing live-dead stress ratio from 0 to 5/6, the fatigue lives can be reduced by approximately 30 years at both the component and system levels.

• Korean Journal of Medicinal Crop Science
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• v.27 no.2
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• pp.96-107
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• 2019

Background: The aim of this study was to compare the fatty acid composition, antioxidant activity, and the content of two major phenolic acids, caffeic and rosmarinic acids, of 45 Perilla accessions collected from Russia. Methods and Results: A total of 45 accessions of the genus Perilla were used in this study. The antioxidant activities of these accessions were analyzed using a spectrophotometer, and their caffeic and rosmarinic acid contents were determined using a reversed-phase ultraperformance liquid chromatography (UPLC) system. The Perilla seed oil was recovered using hexane in a soxhlet extraction method. The fatty acid compositions were analyzed using a Shimadzu QP2010 gas chromatography-mass spectoroscopy system. The results showed that accessions IT226732 and IT274300 had the highest content of caffeic and rosmarinic acid, respectively. A cluster analysis based on antioxidant assay results and concentration of phenolic acids led to the categorization of Perilla accessions into three major groups. The accessions in Group I were characterized by higher caffeic and rosmarinic acid content and antioxidant activity, compared to the accessions in the other two groups (p < 0.05). The total oil content ranged between 28.39 and 46.89%. The compositions of oleic, linoleic, and linolenic acid ranged from 11.83 to 19.55%, 11.92 to 16.71%, and 59.19 to 67.28%, respectively. Conclusions: The results of this study indicated that accessions IT274300, IT226732, IT274293, IT235818, and IT235820 could be used as a source of functional materials.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.2
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• pp.123-131
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• 2021

The buffer is a key component of an engineered barrier system that safeguards the disposal of high-level radioactive waste. Buffers are located between disposal canisters and host rock, and they can restrain the release of radionuclides and protect canisters from the inflow of ground water. Since considerable heat is released from a disposal canister to the surrounding buffer, the thermal conductivity of the buffer is a very important parameter in the entire disposal safety. For this reason, a lot of research has been conducted on thermal conductivity prediction models that consider various factors. In this study, the thermal conductivity of a buffer is estimated using the machine learning methods of: linear regression, decision tree, support vector machine (SVM), ensemble, Gaussian process regression (GPR), neural network, deep belief network, and genetic programming. In the results, the machine learning methods such as ensemble, genetic programming, SVM with cubic parameter, and GPR showed better performance compared with the regression model, with the ensemble with XGBoost and Gaussian process regression models showing best performance.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.441-451
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• 2023

Ultrasound transducers are an essential component of combined photoacoustic and ultrasound imaging systems and play an important role in image evaluation. However, ultrasound transducers are opaque; therefore, light must bypass the ultrasound transducer to reach the target point to produce a photoacoustic image. Providing different paths for the optical and acoustic signals results in a complicated system design, increasing the system volume. To overcome these problems, an optically Transparent Ultrasound Transducer (TUT) was developed. Unlike conventional opaque ultrasound transducers, optically TUT can be fabricated by a variety of manufacturing methods and they are suitable for use with specific piezoelectric elements and serve various purposes. In this study, a comparative analysis of the results of using Lithium Niobate (LNO), Lead Magnesium Niobate-Lead Titanate (PMN-PT), and Polyvinylidene Difluoride (PVDF), which are materials used in piezoelectric element-based TUT. LNO is a piezoelectric element widely used in TUT, and PMN-PT has been actively studied recently with a higher transmission and reception rate than LNO. Existing TUT have lower ultrasound resolution than photoacoustic resolution, but they have recently been manufacturing focused TUT with high ultrasound resolution using PVDF. A comparative analysis of the production results of these TUT was performed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.199-208
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• 2023

Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation(max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.

• Journal of Korean Medicine Rehabilitation
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• v.33 no.4
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• pp.31-44
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• 2023

Objectives The purpose of this study is to check the research trends of pharmacopuncture treatment in nerve entrapment syndrome, identify specific techniques, identify which pharmacopuncture are used, and provide directions for future research. Methods This study was conducted based on the five steps suggested by Arksey and O'Malley. We searched five domestic databases (Research Information Sharing Service, Oriental Medicine Advanced Searching Integrated System, Korean studies Information Service System, Science ON, and KMBASE) and identified studies with key search terms like "nerve entrapment" And "pharmacopuncture" until June 23, 2023. Results Twenty-nine studies were finally selected. among them, 25 papers were non-comparative studies (86.2%). The most common disease was carpal tube syndrome (n=10). All the investigated studies were treated by injecting pharmacopuncture into the pathway of the entraped nerve. The depth of pharmacopuncture injection was mentioned only in 13 studies. As for the pharmacopuncture used, sweet bee venom was 8 studies and bee venom was 6 studies, and about half of the pharmacopuncture manufactured with Bee venom as the main component accounted for. Conclusions This study is a scoping review of the pharmacopuncture treatment for nerve entrapment, which was first conducted in Korea. The treatment is mainly performed on the path way of the entraped nerve. After that, it is necessary to study the standardization of the specific technique method of pharmacopuncture and the uniformity of evaluation criteria.

• Geophysics and Geophysical Exploration
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• v.23 no.4
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• pp.243-252
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• 2020

To share an understanding of trajectory measurement in surveys using borehole, this tutorial summarizes the relevant mathematical principles of the borehole deviation survey based on coordinate transform. For uncased or open holes, calculations of the azimuth-deviation-tool face rotation using three-component accelerometer and magnetometer measurements are summarized. For the steel-cased holes, calculations are based on the time-derivative formula of the coordinate transform matrix; yaw-pitch-roll angles through time are mathematically determined by integrating the threecomponent angular velocity measurements from the gyroscope while also removing the Earth's rotation effect. Sensor and data fusion to increase the accuracy of borehole deviation survey is explained with an example of the method. These principles of borehole deviation surveys can be adapted for attitude estimation in air-borne surveys or for positioning in tunnels where global positioning system (GPS) signals cannot be accessed. Information on the optimization filter that must be incorporated in sensor fusion is introduced to help future research.

• Membrane Journal
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• v.28 no.2
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• pp.136-141
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• 2018

Carbon dioxide ($CO_2$) exists not only as a component of natural gas, biogas, and landfill gas, but also as a major combustion product of fossil fuels which leads to a major contributor to greenhouse gases. Hence it is essential to reduce or eliminate carbon dioxide ($CO_2$) in order to obtain high fuel efficiency of internal combustion engine, to prevent corrosion of gas transportation system, and to cope with climate change preemptively. In recent years, there has been a growing interest in not only conventional membrane-based separation but also new adsorbent-based separation technology. Particularly, in the case of metal-organic frameworks (MOFs), it has been received tremendous attentions due to its unique properties (eg : flexibility, gate effect or strong binding site such as open metal sites) which are different from those of typical porous adsorbents. Therefore, in this study, stereotype of two MOFs have been selected as its flexible MOFs (MIL-53) representative and numerous open metal sites MOFs (MOF-74) representative, and compared each other for $CO_2/CH_4$ separation performance. Furthermore, varying and changeable separation performance conditions depending on the temperature, pressure or samples' unique properties are discussed.

• Korean Journal of Agricultural Science
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• v.44 no.4
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• pp.513-518
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• 2017

Soybean, one of most widely used swine feed component in the world, contains non-starch polysaccharides (NSP). The digestive system of weaned pigs is not yet fully developed, and thus weaned pigs cannot easily digest diets based on corn and soybean meal. Dietary exogenous enzymes supplementation has been intensively investigated to assist digestion of anti-nutritional factors, such as NSP. This experiment was conducted to investigate the effects of dietary enzyme cocktail on growth performance, intestinal morphology, and nutrient digestibility of weaned pigs. A total 36 weaned pigs ($5.92{\pm}0.48kg\;BW$; 28 d old) were randomly allotted to 2 dietary treatments (3 pigs/pen, 6 replicates/treatment) in a randomized complete block design. The dietary treatments were a typical diet based on corn and soybean meal (CON) and CON with 0.05% enzyme cocktail (Cocktail; mixture of xylanase, ${\alpha}-amylase$, protease, ${\beta}-glucanase$, and pectinase). Pigs were fed their respective diets for 6 wk. Growth performance, morphology of ileum, apparent ileal digestibility (AID) and apparent total tract digestibility (ATTD) of dry matter, crude protein, and energy of weaned pigs were measured. No significant differences (p > 0.05) were observed for growth performance for the duration of the experimental period, and morphology of ileum, and nutrient digestibility between CON and Cocktail treatment groups. Therefore, the results from the current study indicated that enzyme cocktail supplementation in diets had no influence on growth performance, intestinal morphology, and nutrient digestibility of weaned pigs.

• KIISE Transactions on Computing Practices
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• v.21 no.12
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• pp.774-779
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• 2015

In this paper, we present the design and implementation of a large-scale qualitative spatial reasoner using Apache Spark, an in-memory high speed cluster computing environment, which is effective for sequencing and iterating component reasoning jobs. The proposed reasoner can not only check the integrity of a large-scale spatial knowledge base representing topological and directional relationships between spatial objects, but also expand the given knowledge base by deriving new facts in highly efficient ways. In general, qualitative reasoning on topological and directional relationships between spatial objects includes a number of composition operations on every possible pair of disjunctive relations. The proposed reasoner enhances computational efficiency by determining the minimal set of disjunctive relations for spatial reasoning and then reducing the size of the composition table to include only that set. Additionally, in order to improve performance, the proposed reasoner is designed to minimize disk I/Os during distributed reasoning jobs, which are performed on a Hadoop cluster system. In experiments with both artificial and real spatial knowledge bases, the proposed Spark-based spatial reasoner showed higher performance than the existing MapReduce-based one.