• Korean Journal of Veterinary Research
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• v.36 no.3
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• pp.657-663
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• 1996

The API STAPH system was compared with conventional methods for identification of 214 strains of Staphylococcus hyicus subsp. hyicus isolated from cases of exudative epidermitis in piglets, skin of healthy pigs, skin of healthy chickens and bovine intramammary infections, and biochemical characteristics among the swine, avian and bovine strains were also compared. All of the swine and bovine strains produced acid within 24 hours from fructose, lactose and trehalose by conventional methods, but some of the avian strains showed a delayed positive reaction in these carbohydrates. These delayed positive strains in conventional methods gave usually negative results for them in the API STAPH system. With the API STAPH system, eighteen different profile numbers were encountered in 214 strains of swine, avian and bovine origin. The swine and bovine strains, respectively, were distributed among 4 profiles, while the avian strains were distributed among 17 profiles. The profile number observed most frequently in the strains of each animal species was uniformly 6 516 153. By conventional methods, approximately 96% of the swine strains were positive for ${\beta}$-glucuronidase, but not in any strains from chickens and cattle. For hyaluronidase production determined by degradation of sodium hyaluronidate in a solid culture medium, all the swine and bovine strains were positive, but only 37.5% of the avian strains were positive for it. From these findings, there were differences in the production of extracellular active substances between swine strains of Staphylococcus hyicus subsp. hyicus and those isolated from chickens and cattle.

• Animal Bioscience
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• v.36 no.6
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• pp.980-989
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• 2023

Objective: Iris pattern recognition system is well developed and practiced in human, however, there is a scarcity of information on application of iris recognition system in animals at the field conditions where the major challenge is to capture a high-quality iris image from a constantly moving non-cooperative animal even when restrained properly. The aim of the study was to validate and identify Black Bengal goat biometrically to improve animal management in its traceability system. Methods: Forty-nine healthy, disease free, 3 months±6 days old female Black Bengal goats were randomly selected at the farmer's field. Eye images were captured from the left eye of an individual goat at 3, 6, 9, and 12 months of age using a specialized camera made for human iris scanning. iGoat software was used for matching the same individual goats at 3, 6, 9, and 12 months of ages. Resnet152V2 deep learning algorithm was further applied on same image sets to predict matching percentages using only captured eye images without extracting their iris features. Results: The matching threshold computed within and between goats was 55%. The accuracies of template matching of goats at 3, 6, 9, and 12 months of ages were recorded as 81.63%, 90.24%, 44.44%, and 16.66%, respectively. As the accuracies of matching the goats at 9 and 12 months of ages were low and below the minimum threshold matching percentage, this process of iris pattern matching was not acceptable. The validation accuracies of resnet152V2 deep learning model were found 82.49%, 92.68%, 77.17%, and 87.76% for identification of goat at 3, 6, 9, and 12 months of ages, respectively after training the model. Conclusion: This study strongly supported that deep learning method using eye images could be used as a signature for biometric identification of an individual goat.

• 대한상한금궤의학회지
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• v.8 no.1
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• pp.53-65
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• 2016

Objective : The purpose of this paper is to report the improved contact dermatitis(CD) treated with the herbal medication based on Shanghanlun disease pattern identification diagnostic system. The level V steroid ointments were no use to the patient 3weeks before the treatment. Methods : In this case, the patient was diagnosed according to 'Disease Pattern Identification Diagnostic System based on Shanghanlun Provisions' and took Mahwang-tang for 36days since the final diagnosis was Taeyang-byung, number 46 provision. The photographs of patient's hands were taken to observe the process of the skin status and the discomfort from CD was measured with DLQI(Dermatologic Life Quality Index) and NRS(Numeric Rating Scale). Results : The DLQI score changed from 24 to 7 and NRS of itching changed form 8 to under 4. Conclusions : This case report shows that the herbal medication through the diagnostic system could be a remedy on CD, dealing with the skin status with no use of the level V steroid ointments. It is needed proving an alternative possibility of Korean Medicine, on other skin diseases, with later studies since there are many reports on the side-effects after some long-term steroid treatments.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1566-1577
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• 2018

This paper presents a stability analysis of AC-DC power system feeding a speed controlled DC motor in which this load behaves as a constant power load (CPL). A CPL can significantly degrade power system stability margin. Hence, the stability analysis is very important. The DQ and generalized state-space averaging methods are used to derive the mathematical model suitable for stability issues. The paper analyzes the stability of power systems for both speed control natural frequency and DC-link parameter variations and takes into account controlled speed motor dynamics. However, accurate DC-link filter and DC motor parameters are very important for the stability study of practical systems. According to the measurement errors and a large variation in a DC-link capacitor value, the system identification is needed to provide the accurate parameters. Therefore, the paper also presents the identification of system parameters using the adaptive Tabu search technique. The stability margins can be then predicted via the eigenvalue theorem with the resulting dynamic model. The intensive time-domain simulations and experimental results are used to support the theoretical results.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.19 no.3
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• pp.141-149
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• 2015

Objectives Recently the fuzzy logic is widely used in the decision making, identification, pattern recognition, optimization in various fields. In this study, we propose the fuzzy logic as the objective method of distinguishing hot and cold, the basis of diagnosis in Korean medicine. Methods We developed fuzzy inference system to distinguish whether the subjects had hot or cold. The cold and hot questionnaire of Korean traditional university textbook, the pulse rate and the DITI value of face used in the system. These three kinds of information were defined as 'fuzzy sets,' and 54 fuzzy rules were established on the basis of clinical practitioners' knowledge. The fuzzy inference was performed by using the Mamdani's method. To evaluate the usefulness of the fuzzy inference system, 200 cases of data measured in the Woosuk university hospital of oriental medicine were used to compare the determining hot, normal, cold results obtained from the experts and from the proposed system. Results As a result, 100 cases of "cold", 54 cases of "normal", and 34 cases of "hot" were matched between the experts and the proposed system. This fuzzy system showed the conformity degree of 94%(${\kappa}=0.853$). Conclusions In this study, we could express the process of distinguishing hot-cold using the fuzzy logic for objectification and quantification of hot-cold identification. This is the first study that introduce a fuzzy logic for distinguish pattern identification. The degree of the heat characteristic of the patients inferred by this system could provide a more objective basis for diagnosing the hot-cold of patients.

• The Journal of Internal Korean Medicine
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• v.43 no.3
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• pp.327-343
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• 2022

Objective: The purpose of this study was to develop a standard tool for identifying idiopathic pulmonary fibrosis patterns. Methods: Textbooks, published literature, and references with comments on patterns were reviewed. Using the Delphi method, we determined pattern identification based on the advice of a committee consisting of 11 Korean respiratory internal medicine professors. Results: Four pattern identifications were selected by the Delphi method: qi difficiency (氣虛), yin difficiency (陰虛), phlegm dampness (痰飮), blood stasis (瘀血). The tool was developed in a question-and-answer format containing 38 questions. Conclusions: An IPF pattern identification tool that can analyze IPF patterns for standardized diagnostics was developed with the consent of experts. Further research is needed on its reliability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2A
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• pp.215-222
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• 2008

This paper introduces an experimental verification of a tension estimation method based on system identification approach for a double hanger system on a suspension bridge. A laboratory model of such double hanger system has been made for this study. Total nine cases of the vibration tests have been conducted with respect to three levels of applied tension and three cases of the location of clamp. For a set of the collected acceleration response data, modal analysis has been followed in order to extract the natural frequencies and mode shapes of the selected cable systems. For the extracted modal parameters, the existing tension estimation methods based on the string theory and axially loaded beam theory have been firstly applied to estimate the tensile force on the double hanger cable system. Next, the tensile force on cables has been estimated by the system identification approach. It is seen that the errors in the tension estimation using the frequency-based system identification technique are about 3% for all cases while the estimation error using the existing method is up to 53.1%.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.122-130
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• 2021

This study is about an Artificial Intelligence-based fake news identification system and its methods to determine the authenticity of content distributed over the Internet. Among the news we encounter is news that an individual or organization intentionally writes something that is not true to achieve a particular purpose, so-called fake news. In this study, we intend to design a system that uses Artificial Intelligence techniques to identify fake content that exists within the news. The proposed identification model will propose a method of extracting multiple unit factors from the target content. Through this, attempts will be made to classify unit factors into different types. In addition, the design of the preprocessing process will be carried out to parse only the necessary information by analyzing the unit factor. Based on these results, we will design the part where the unit fact is analyzed using the deep learning prediction model as a predetermined unit. The model will also include a design for a database that determines the degree of fake news in the target content and stores the information in the identified unit factor through the analyzed unit factor.

• Structural Monitoring and Maintenance
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• v.1 no.1
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• pp.1-45
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• 2014

The developments and implementations of the structural health monitoring (SHM) system for large infrastructures have been gradually recognized by researchers, engineers and administrative authorities in the last decades. This paper summarizes an updated review on innovations and applications in SHM for infrastructures carried out by researchers at Dalian University of Technology. Invented sensors and data acquisition system are firstly briefly described. And then, some proposed theories and methods including the sensing technology, sensor placement method, signal processing and data fusion, system identification and damage detection are discussed in details. Following those, the activities on the standardization of SHM and several case applications on specific types of structure are reviewed. Finally, existing problems and promising research efforts in the field of SHM are given.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.3
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• pp.35-43
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• 2012

Medium size rotorcraft consist of approximately 5,000 key components. The components must satisfy the target weight and performance requirement through optimization. Therefore a rotorcraft component has approximately 100 times higher unit cost for mass production than the equivalent of an automobile's, along with huge development cost. Configuration management consists of four main parts : configuration identification, configuration control, configuration audit, and data management. In development programme, configuration management is one of the methods to save development cost, and setting a well-structured configuration management system according to the Military Standard is an important factor in success of the programme. The paper proposes a configuration management system suitable for development of various multi-use components development and presents that the configuration management was performed successfully during dual-use component development programme using the established system.