• Mass Spectrometry Letters
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• 제10권3호
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• pp.71-78
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• 2019

For several decades, cancer has been the primary cause of mortality worldwide. New diagnosis and regimens have been developed to improve the chemotherapeutic efficacy and the quality of life of the patients. However, cancer tissues are complex and difficult to assess. Understanding the various properties of the tumor and its environment is crucial for cancer and pharmaceutical research. Several analytical techniques have been providing new insights into cancer research. Recently, matrix-assisted laser desorption ionization (MALDI)-mass spectrometry imaging (MSI), an advanced analytical technique, has been applied to translational research. Proteomic and lipidomic profiling obtained by MALDI-MSI has been critical for biomarker discovery and for monitoring heterogenous tumor tissues. In this review, we discuss technical approaches, benefits and recent applications of MALDI-MSI as a valuable tool in cancer research, namely for diagnosis, therapy, prognosis.

• 대한치과의사협회지
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• 제57권7호
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• pp.403-411
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• 2019

A cracked tooth is defined as an incomplete fracture initiated from the crown and extending subgingivally and usually directed mesiodistally. Cracked teeth were most frequently involved in mandibular and maxillary molars at the age of 50s. Cracks occurred mainly in nonbonded restorations such as gold and amalgam, and majority of cracks were found in intact teeth. A pulpal and periapical diagnosis is dependent on the extent of the crack and duration of the symptom. The pulp of a cracked tooth might become inflamed because of microleakage, which induces thermal sensitivity. Once the crack has extended and exposed the pulp, severe pulp and periapical pathosis will likely be present. In addition, the extended crack can cause a bony dehiscence with a resulting narrow and deep periodontal pocket. Therefore, early diagnosis of the cracked tooth and proper treatment planning are important for clinician.

• Journal of Oral Medicine and Pain
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• 제45권4호
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• pp.115-119
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• 2020

Infectious myositis, an infection of the skeletal muscles, is a rare condition and potentially life-threatening if not detected and treated in the early stages. This clinical entity may arise from various pathogens, such as bacteria, fungi, parasites, and viruses. A propagation of contiguous infection, penetrating trauma, vascular insufficiency, or hematogenous spreading of microorganisms can cause infectious myositis. Though several cases have been reported in large muscle groups in the lower extremities, there are only a few reports on infectious myositis of the masticatory muscles. We report three cases of infectious myositis presenting jaw pain and trismus. Unlike a common head and neck infection caused by the spreading of odontogenic origin, the early diagnosis of infectious myositis was difficult because no specific lesion suspected to be the infection source was observed in the physical examination and the plain radiographs. Advanced imaging modalities such as computed tomography and magnetic resonance imaging, and laboratory evaluation is useful for the early detection of infectious myositis.

• The Plant Pathology Journal
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• 제38권5호
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• pp.503-512
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• 2022

Lilies (Lilium spp.) are one of the most important ornamental flower crops grown in Korea. Most viral diseases in lilies are transmitted by infected bulbs, which cause serious economic losses due to reduced yields. Various diagnostic techniques and high-throughput sequencing methods have been used to detect lily viruses. According to Oxford Nanopore Technologies (ONT), MinION is a compact and portable sequencing device. In this study, three plant viruses, lily mottle, lily symptomless, and plantago asiatica mosaic virus, were detected in lily samples using the ONT platform. As a result of genome assembly of reads obtained through ONT, 100% coverage and 90.3-93.4% identity were obtained. Thus, we show that the ONT platform is a promising tool for the diagnosis and characterization of viruses that infect crops.

• 항공우주의학회지
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• 제28권2호
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• pp.19-22
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• 2018

Obstructive sleep apnea syndrome (OSAS) can lead to severe complications if left untreated, and therefore should be adequately diagnosed and treated, especially in airline workers. The aviation medical examiner (AME) should induce the patient to cooperate for the diagnosis and treatment of OSAS, by notifying the subject that it does not cause disqualification of the air service and that it is a disease that can be sufficiently controlled and treated by various treatment options. AME should also warn about medical complications and the possibility of serious air accident risks when untreated, and encourage the subject to receive appropriate diagnosis and steady treatment such as continuous positive airway pressure and/or surgical treatment.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• 제27권4호
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• pp.197-205
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• 2024

T-lymphocytic intestinal leiomyositis is a rare cause of "pediatric intestinal pseudo-obstructions." Diagnosis may be difficult and requires full-thickness bowel biopsies during laparotomy or laparoscopy with possible enterostomy. Currently, immunosuppressive therapy is the only available treatment. A delay in diagnosis and therapy may negatively affect the prognosis because of ongoing fibrotic alterations; therefore, early diagnosis and consequent treatment are crucial. This review summarizes the available information on the nosology, diagnostic steps, and treatment modalities. Here, we report the youngest case of enteric leiomyositis reported in the last two decades and analyze its management by reviewing previous cases.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.235-238
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• 2000

This article presents an adaptive decision tree algorithm for dynamically reasoning machine failure cause out of real-time, large-scale machine status database. On the basis of experiment using semiconductor etching machine, it has been verified that our model outperforms previously proposed decision tree models.

• 산업경영시스템학회지
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• 제40권1호
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.

• Computers and Concrete
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• 제9권2호
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• pp.99-118
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• 2012

Marine Structures are very costly and need a continuous inspection and maintenance routine. The most effective way to control the structural health is the application of an expert system that can evaluate the importance of any distress on the structure and provide a maintenance program. An extensive literature review, interviews with expert supervisors and a national survey are used to build a decision support system for concrete structures in sea environment. Decision trees are the main rules in this system. The system input is inspection information and the system output is the main cause(s) of distress(es) and the best repair method(s). Economic condition, severity of distress, distress situation, and new technologies and the most repeated classical methods are considered to choose the best repair method. A case study demonstrates the application of the developed decision support system for a type of marine structure.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
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• pp.141-143
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• 2006

Dissolved gas analysis (DGA) is widely used to detect incipient faults in oil-filled electrical equipment. KEPCO make a rule of DGA in 1985. They have been diagnosing power transformer using their DGA criteria. In this paper, we analysis the result of DGA data about transformer in the substation. We try to find out what is cause of an error in DGA diagnosis considering accuracy in extracting gases from mineral oil in transformer. The carbon-monoxide was primary reason of warning in DGA data. We specially consider that aging is a cause of generating of carbon-monoxide in power transformer.