• The Journal of the Acoustical Society of Korea
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• v.27 no.6
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• pp.296-302
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• 2008

This study investigated that the preference model of soloist performers for both vocal and instrumental types in terms of a stage support parameter, ST1. The test was carried out on a stage of a fan-shaped multi-purpose hall with orchestra shell. Objective measurements were carried out at 15 positions on the stage to evaluate various stage condition. The results showed that ST1 varies between -19.9 and -11.3 dB. Vocal and instrumental players participated in performance evaluation test as they played at 5 selected positions according to ST1 values. Players' preference was evaluated by 5-point rating and rank ordering method. As a result, it was found that the preference model of vocalist is different from that of instrumentalist. It was also found that the ST1 does not correlate well with the performer's preference.

• Korean Journal of Radiology
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• v.1 no.3
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• pp.152-158
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• 2000

Objective: The purpose of this study was to compare the effectiveness of MR urography (MRU) with that of ultrasonography (US) in the evaluation of urinary tract when this failed to opacify during excretory urography (EXU). Materials and Methods: Twelve urinary tracts in 11 patients were studied. In each case, during EXU, the urinary system failed to opacify within one hour of the injection of contrast media, and US revealed dilatation of the pelvocalyceal system. Patients underwent MRU, using a HASTE sequence with the breath-hold technique; multi-slice acquisition was then performed, and the images were reconstructed using maximal intensity projection. Each set of images was evaluated by three radiologists to determine the presence, level, and cause of urinary tract obstruction. Results: Obstruction was present in all twelve cases, and in all of these, MRU accurately demonstrated its level. In this respect, however, US was successful in only ten. The cause of obstruction was determined by MRU in eight cases, but by US in only six. In all of these six, MRU also successfully demonstrated the cause. Conclusion: MRU is an effective modality for evaluation of the urinary tract when this fails to opacify during EXU, and appears to be superior to US in demonstrating the level and cause of obstruction.

• Smart Media Journal
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• v.13 no.4
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• pp.23-32
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• 2024

Large-scale fires and their consequential damages are becoming increasingly common, but confidence in fire detection systems is waning. Recently, widely-used chemical fire detectors frequently generate lots of false alarms, while video-based deep learning fire detection is hampered by its time-consuming and expensive nature. To tackle these issues, this study proposes a fire detection model utilizing an autoencoder approach. The objective is to minimize false alarms while achieving swift and precise fire detection. The proposed model, employing an autoencoder methodology, can exclusively learn from normal data without the need for fire-related data, thus enhancing its adaptability to diverse environments. By amalgamating data from five distinct sensors, it facilitates rapid and accurate fire detection. Through experiments with various hyperparameter combinations, the proposed model demonstrated that out of 14 scenarios, only one encountered false alarm issues. Experimental results underscore its potential to curtail fire-related losses and bolster the reliability of fire detection systems.

• Journal of Veterinary Science
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• v.25 no.4
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• pp.42.1-42.12
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• 2024

Importance: Bovine mastitis, predominantly associated with gram-positive Staphylococcus aureus, poses a significant threat to dairy cows, leading to a decline in milk quality and volume with substantial economic implications. Objective: This study investigated the incidence, virulence, and antibiotic resistance of S. aureus associated with mastitis in dairy cows. Methods: Fifty milk-productive cows underwent a subclinical mastitis diagnosis, and the S. aureus strains were isolated. Genomic DNA extraction, sequencing, and bioinformatic analysis were performed, supplemented by including 124 S. aureus genomes from cows with subclinical mastitis to enhance the overall analysis. Results: The results revealed a 42% prevalence of subclinical mastitis among the cows tested. Genomic analysis identified 26 sequence types (STs) for all isolates, with Mexican STs belonging primarily to CC1 and CC97. The analyzed genomes exhibited multidrug resistance to phenicol, fluoroquinolone, tetracycline, and cephalosporine, which are commonly used as the first line of treatment. Furthermore, a similar genomic virulence repertoire was observed across the genomes, encompassing the genes related to invasion, survival, pathogenesis, and iron uptake. In particular, the toxic shock syndrome toxin (tss-1) was found predominantly in the genomes isolated in this study, posing potential health risks, particularly in children. Conclusion and Relevance: These findings underscore the broad capacity for antibiotic resistance and pathogenicity by S. aureus, compromising the integrity of milk and dairy products. The study emphasizes the need to evaluate the effectiveness of antibiotics in combating S. aureus infections.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.26 no.1
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• pp.69-75
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• 2022

Backgrounds/Aims: Progressive familial intrahepatic cholestasis (PFIC) is an autosomal recessive inherited disease requiring liver transplantation (LT). The objective of this study was to investigate the clinicopathological features and posttransplant courses of seven LT recipients with PFIC. Methods: This was a retrospective single-center study of patients with PFIC who underwent LT from January 2013 to June 2020. Results: Two and five patients were diagnosed with PFIC type 1 and type 2, respectively. For all seven patients, age of PFIC onset was at birth. Jaundice was present in all cases. Mean pretransplant total and direct bilirubin levels were 16.1 ± 8.1 mg/dL and 12.4 ± 6.2 mg/dL, respectively. Median patient age and body weight at LT were 10 months and 7 kg, respectively. Types of donors were mothers of patients in four and deceased donors in three. All five patients with PFIC type 2 recovered uneventfully. One patient each with PFIC type 1 underwent retransplantation due to graft failure or died due to multi-organ failure. Overall graft and patient survival rates at five years were 66.7% and 83.3%, respectively. Bile salt export pump immunohistochemical staining showed normal canalicular expression in two patients with PFIC type 1, focal loss in two patients with PFIC type 2, and total loss in three patients with PFIC type 2. Conclusions: LT is currently the only effective treatment for PFIC-associated end-stage liver diseases. It is mandatory to perform regular follow-up due to the risk of complications including steatohepatitis, especially for patients with PFIC type 1.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.4
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• pp.109-120
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• 2007

In this study, a bridge maintenance system is developed to generate performance-based optimum maintenance strategy by considering the life-cycle cost. A multi-objective combinatorial optimization problem is formulated to generate a tradeoff maintenance scenarios which satisfies the balance among the conflicting objectives such as the performance and cost during the bridge lifetime and a genetic algorithm is applied to the system. By using the developed program, this study proposes a process of optimum maintenance scenario applying to the steel girder bridge of national road. The developed system improves the current methods of establishing the bridge maintenance strategy and can be utilized as an efficient tool to provide the optimum bridge maintenance scenario corresponding to the various constraints and requirements of bridge agency.

• Journal of Korea Water Resources Association
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• v.40 no.10
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• pp.769-781
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• 2007

Factor analysis has been usually employed in reducing quantity of data and summarizing information on a system or phenomenon. In this analysis methodology, variables are grouped into several factors by consideration of statistic characteristics, and the results are used for dropping variables which have lower weight than others. In this study, factor analysis was applied for extracting primary factors influencing multi-dam system operation in the Han River basin, where there are two multi-purpose dams such as Soyanggang Dam and Chungju Dam, and water has been supplied by integrating two dams in water use season. In order to fulfill factor analysis, first the variables related to two dams operation were gathered and divided into five groups (Soyanggang Dam: inflow, hydropower product, storage management, storage, and operation results of the past; Chungju Dam: inflow, hydropower product, water demand, storage, and operation results of the past). And then, considering statistic properties, in the gathered variables, some variables were chosen and grouped into five factors; hydrological condition, dam operation of the past, dam operation at normal season, water demand, and downstream dam operation. In order to check the appropriateness and applicability of factors, a multiple regression equation was newly constructed using factors as description variables, and those factors were compared with terms of objective function used in operation water resources optimally in a river basin. Reviewing the results through two check processes, it was revealed that the suggested approach provided satisfactory results. And, it was expected for extracted primary factors to be useful for making dam operation schedule considering the future situation and previous results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.1
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• pp.11-26
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• 1984

The aim of this study is to establish a synthetical optimal method that simultaneously analyze and design reinforced concrete flat slab-column structures involving multi-constraints and multi-design variables. The variables adopted in this mathematical models consist of design variables including sectional sizes and steel areas of frames, and analysis variable of the ratio of bending moment redistribution. The cost function is taken as the objective function in the formulation of optimal problems. A number of constraint equations, involving the ultimate limit state and the serviceability limit state, is derived in accordance with BSI CP110 requirements on the basis of limit state design theory. Both objective function and constraint equations derived from design variables and an analysis variable generally become high degree nonlinear problems. Using SLP as an analytical method of nonlinear optimal problems, an optimal algorithm is developed so as to analyze and design the structures considered in this study. The developed algorithm is directly applied to a few reinforced concrete flat slab-column structures to assure the validity of it and the possibility of optimization From the research it is found that the algorithm developed in this study is applicable to the optimization of reinforced concrete flat slab column structures and it converges to a optimal solution with 4 to 6 iterations regardless of initial variables. The result shows that an economical design can be possible when compared with conventional designs. It is also found that considering the ratio of bending moment redistribution as a variable is reasonable. It has a great effect on the composition of optimal sections and the economy of structures.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.561-573
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• 2023

National forests have an advantage over private forests in terms of higher investment in capital, technology, and labor, allowing for more intensive management. As such, national forests are expected to serve not only as a strategic reserve of forest resources to address the long-term demand for timber but also to stably perform various essential forest functions demanded by society. However, most forest stands in the current national forests belong to the fourth age class or above, indicating an imminent timber harvesting period amid an imbalanced age class structure. Therefore, if timber harvesting is not conducted based on systematic management planning, it will become difficult to ensure the continuity of the national forests' diverse functions. This study was conducted to determine the optimal volume of timber production in the national forests to improve the age-class structure while sustainably maintaining their economic and public functions. To achieve this, the study first identified areas within the national forests suitable for timber production. Subsequently, a forest management planning model was developed using multi-objective linear programming, taking into account both the national forests' economic role and their public benefits. The findings suggest that approximately 488,000 hectares within the national forests are suitable for timber production. By focusing on management of these areas, it is possible to not only improve the age-class distribution but also to sustainably uphold the forests' public benefits. Furthermore, the potential volume of timber production from the national forests for the next 100 years would be around 2 million m³ per year, constituting about 44% of the annual domestic timber supply.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.