• Journal of Mechanical Science and Technology
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• v.18 no.12
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• pp.2174-2181
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• 2004

The metal processing system usually consists of various components such as motors, work rolls, backup rolls, idle rolls, sensors, etc. Even a simple fault in a single component in the system may cause a serious damage on the final product. It is, therefore, necessary to diagnose the faults of the components to detect and prevent a system failure. Especially, the defects in a work roll are critical to the quality of strip. In this study, a new 3-D diagnosis method was developed for roll shape defects in rolling processes. The new method was induced from analyzing the rolling mechanism by using a rolling force model, a tension model, the Hitchcock's equation, and measurement of the strip thickness, etc. Computer simulation shows that the proposed method is very useful in the diagnosis of the 3-D roll shape.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.169-174
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• 2012

Reduction unit is one of the most important components for railway vehicle because torque of motor must be transmitted to wheels of vehicle by reduction unit. However, According to advanced studies, it has been often broke down due to the damage, fatigue and wear of gear. To solve this problem, defect diagnosis methods of gear have been mainly using the vibration diagnosis technology through vibration waveform and frequency analysis. However, We should know vibration characteristics of normal state reduction unit prior to defect diagnosis. So in this paper, We had analyzed vibration characteristics of reduction unit in order to utilize monitoring system development. Comparison of targets is the vibration characteristics of normal state reduction unit about Electric Multiple Unit(EMU) and the High-speed trains(KTX, KTX II).

• Journal of Yeungnam Medical Science
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• v.36 no.1
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• pp.8-15
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• 2019

Connective tissue diseases (CTDs) can affect all compartments of the lungs, including airways, alveoli, interstitium, vessels, and pleura. CTD-associated lung diseases (CTD-LDs) may present as diffuse lung disease or as focal lesions, and there is significant heterogeneity between the individual CTDs in their clinical and pathological manifestations. CTD-LDs may presage the clinical diagnosis a primary CTD, or it may develop in the context of an established CTD diagnosis. CTD-LDs reveal acute, chronic or mixed pattern of lung and pleural manifestations. Histopathological findings of diverse morphological changes can be present in CTD-LDs airway lesions (chronic bronchitis/bronchiolitis, follicular bronchiolitis, etc.), interstitial lung diseases (nonspecific interstitial pneumonia/fibrosis, usual interstitial pneumonia, lymphocytic interstitial pneumonia, diffuse alveolar damage, and organizing pneumonia), pleural changes (acute fibrinous or chronic fibrous pleuritis), and vascular changes (vasculitis, capillaritis, pulmonary hemorrhage, etc.). CTD patients can be exposed to various infectious diseases when taking immunosuppressive drugs. Histopathological patterns of CTD-LDs are generally nonspecific, and other diseases that can cause similar lesions in the lungs must be considered before the diagnosis of CTD-LDs. A multidisciplinary team involving pathologists, clinicians, and radiologists can adequately make a proper diagnosis of CTD-LDs.

• Journal of Drive and Control
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• v.20 no.4
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• pp.54-63
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• 2023

High and intermittent loading cycles induce fatigue damage to transmission components, resulting in premature gearbox failure. To identify gearbox defects, numerous vibration-based diagnostics techniques, using several artificial intelligence (AI) algorithms, have recently been presented. In this paper, an optimized deep belief network (DBN) model for gearbox problem diagnosis was designed based on time-frequency visual pattern identification. To optimize the hyperparameters of the model, a particle swarm optimization (PSO) approach was integrated into the DBN. The proposed model was tested on two gearbox datasets: a wind turbine gearbox and an experimental gearbox. The optimized DBN model demonstrated strong and robust performance in classification accuracy. In addition, the accuracy of the generated datasets was compared using traditional ML and DL algorithms. Furthermore, the proposed model was evaluated on different partitions of the dataset. The results showed that, even with a small amount of sample data, the optimized DBN model achieved high accuracy in diagnosis.

• Smart Structures and Systems
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• v.13 no.5
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• pp.869-890
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• 2014

In this study, a damage detection approach using train-induced vibration response of the bridge is proposed, utilizing only direct structural analysis by means of introducing soft computing methods. In this approach, the possible damage patterns of the bridge are assumed according to theoretical and empirical considerations at first. Then, the running train-induced dynamic response of the bridge under a certain damage pattern is calculated employing a developed train-bridge interaction analysis program. When the calculated result is most identical to the recorded response, this damage pattern will be the solution. However, owing to the huge number of possible damage patterns, it is extremely time-consuming to calculate the bridge responses of all the cases and thus difficult to identify the exact solution quickly. Therefore, the soft computing methods are introduced to quickly solve the problem in this approach. The basic concept and process of the proposed approach are presented in this paper, and its feasibility is numerically investigated using two different train models and a simple girder bridge model.

• Journal of Environmental Science International
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• v.29 no.5
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• pp.551-558
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• 2020

This study aims to increase the ability to adapt to the ecosystem and promote a sustainable use of the natural environment, by classifying the types of damaged lands according to various factors, such as the characteristics of the target area and form, cause, and impact of damage. Moreover, the study suggests the development of evaluation categories and criteria by each type. The results obtained are as follows: first, for the assessment of damaged lands, the changed areas were identified utilizing land cover maps. Video analysis was performed to increase the accuracy, and 88 sites were obtained. Second, the types of damage were classified into ecological infrastructure and ecological environment, and the sub-factors of the cause of damage were classified into 12 factors. Third, each evaluation system for the types of damage was composed of four steps, considering each type of damage and the level of evaluators being higher than paraprofessionals. To supplement this study, it will be necessary to utilize the database of damaged lands other than the Seoul Metropolitan Area and conduct an on-site survey for verification in the future.

• Smart Structures and Systems
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• v.5 no.4
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• pp.427-442
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• 2009

In this paper, the acceptability of system identification results for health monitoring of instrumented bridges is addressed. This is conducted by comparing the confidence intervals of identified modal parameters for a bridge in California, namely Truckee I80/Truckee river bridge, with the change of these parameters caused by several damage scenarios. A challenge to the accuracy of the identified modal parameters involves consequences regarding the damage detection and health monitoring, as some of the identified modal information is essentially not useable for acquiring a reliable damage diagnosis of the bridge system. Use of strong motion data has limitations that should not be ignored. The results and conclusions underline these limitations while presenting the opportunities offered by system identification using strong motion data for better understanding and monitoring the health of bridge systems.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.1
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• pp.44-50
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• 2013

The persons in charge of management request diagnosis and prescription to tree hospitals in order to get consultation about the problems like blight that occur in landscape tree management. This study aims to analyze what the main problems and questions raised by landscape gardeners are and those concerned in landscape tree management. This is done by investigating landscape tree-related questions and answers uploaded on the online consultation boards of the plant diagnostic centers approved in Korea including the Seoul National University Plant Clinic, the Chungbuk National University Plant Hospital, and the Kangwon Diagnostic Center. As a result, those concerned in landscape occupied the most as 81.4% among the questioners. However, only 11.5% did explain the plant management history or surrounding environment, which is essential for landscape tree diagnosis when asking questions. This shows that those concerned in landscape lack basic knowledge or interest about plant diagnosis. Among 263 questions about landscape trees, questions about physiological damage included 94 cases that were the most taking up 35.8%. Moreover, the next were damage by insects and damage by disease in order. It is thought that due to the characteristics of physiological problems that occur by various sorts of stress and with no signs, they tend to request diagnosis or prescription the most. The most frequent reasons for physiological damage are water stress and temperature stress. About damage by disease, there exist many types of diseases, and there are many complex damages accompanied by physiological causes. About damage by insects, the most common include damage by moths. In consideration of this result, universities or technician training centers should provide education for landscape tree management so that landscape technicians and students can acquire essential knowledge and information about landscape tree management and increase their interest in it. In particular, it is necessary to provide profound learning opportunities for plant physiology, and the technicians should make efforts themselves. In addition, it is needed to build organizations to which they can ask technical questions about landscape planting and management in order to understand landscape industry in general and the actual status of landscape planting technique and the actual field. Moreover, to elevate systemicity and expertise in the area of landscape tree management not yet equipped with the foundation, it is needed to cultivate the technicians intensively and conduct research by those concerned both in academic and industrial circles.

• Clinical and Experimental Pediatrics
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• v.53 no.11
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• pp.931-935
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• 2010

Juvenile idiopathic arthritis (JIA) is comprised of a heterogeneous group of several disease subtypes that are characterized by the onset of arthritis before the age of 16 years and has symptoms lasting at least 6 weeks. The previous classification of JIA included seven different categories, whereas its current classification was compiled by the International League of the Association for Rheumatology, and replaced the previous terms of "juvenile chronic arthritis" and "juvenile rheumatoid arthritis," which were used in Europe or North America, respectively, with the single nomenclature of JIA. As mentioned above, JIA is defined as arthritis of unknown etiology that manifests itself before the age of 16 years and persists for at least 6 weeks, while excluding other known conditions. The clinical symptoms of JIA can be quite variable. Several symptoms that are characteristic of arthritis are not necessarily diagnostic of JIA and may have multiple etiologies that can be differentiated with careful examination of patient history. The disease may develop over days or sometimes weeks, thereby making the diagnosis difficult at the time of presentation. To make a clinical diagnosis of JIA, the first step is to exclude arthritis with known etiologies. Of note, late treatment due to excessive delay of diagnosis can cause severe damage to joints and other organs and impair skeletal maturation. Therefore, early detection of JIA is critical to ensure prompt treatment and to prevent long-term complications including the likelihood of disability in childhood.

• Journal of the Korean Society of Hazard Mitigation
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• v.1 no.2 s.2
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• pp.63-74
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• 2001

In this paper the feasibility of Nondestructive Damage Detection (NDD) in large structures is demonstrated via simulating vibration monitoring of such structures. The theory of NDD for truss type structures is formulated. To examine the feasibility of the theory, a finite element model of a 3-D truss structure, which consists of sixteen bays and includes 246 elements, is developed to simulate damage. Four damage cases are simulated numerically and the cases range from the structure being damaged in one location to the structure being damaged in three locations. For the given modal parameters, this study reveals very good results for small amounts of damage as well as large damage.