• Journal of The Korean Society of Inherited Metabolic disease
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• v.22 no.1
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• pp.15-20
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• 2022

The most common urea cycle disorder is ornithine transcarbamylase deficiency. More than 80 percent of patients with symptomatic ornithine transcarbamylase deficiency are late-onset, which can present various phenotypes from infancy to adulthood. With no regards to the severity of the disease, characteristic fluctuating courses due to hyperammonemia may develop unexpectedly, and can be precipitated by various metabolic stressors. Late-onset ornithine transcarbamylase deficiency is not merely related to a type of genetic variation, but also to the complex relationship between genetic and environmental factors that result in hyperammonemia; therefore, it is difficult to predict the prevalence of neurological symptoms in late-onset ornithine transcarbamylase deficiency. Most common acute neurological manifestations include psychological changes, seizures, cerebral edema, and death; subacute neurological manifestations include developmental delays, learning disabilities, intellectual disabilities, attention-deficit/hyperactivity disorder, executive function deficits, and emotional and behavioral problems. This review aims to increase awareness of late-onset ornithine transcarbamylase deficiency, allowing for an efficient use of biochemical and genetic tests available for diagnosis, ultimately leading to earlier treatment of patients.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.49 no.4
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• pp.233-238
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• 2023

Schwannomas exhibit histopathological variation that leads to diagnostic dilemmas, although less frequent in the oral cavity. We describe a case with unique histopathology and no relevant clinical history that adds to the breadth of literature on the diversity presented by Schwannoma. A 60-year-old female patient presented with a small dome-shaped, asymptomatic swelling on the alveolar ridge 6 years in duration. Histopathologically, it showed rich cellular pathology with a unique arrangement of tumor cells forming irregular rosettes. Each rosette presented with a central core of fibrin-collagenous material and the tumor cells were arranged on the periphery, exhibiting epithelioid change with evidence of mild cellular and nuclear pleomorphism. On immunohistochemical evaluation, the cells were strongly and diffusely positive for S-100 and negative for Ki-67. A diagnosis of benign Schwannoma with a rosette-like arrangement with epithelioid change was made. The case report emphasizes the risk of misdiagnosis and the importance of awareness regarding rare histopathological variants of Schwannoma.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.361-369
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• 2017

Hemodynamic information in the carotid artery bifurcation is very important for understanding the development and progression mechanisms of cerebrovascular disease and for its early diagnosis and prediction of the progress. In this paper, we constructed a mock pulsatile blood circulation system using an anthropomorphic elastic vessel of the carotid artery bifurcation and ex vivo pig blood to acquire ultrasound images from blood and vessels synchronized with internal pressure while controlling the blood flow. Echogenicity, blood flow velocity, and blood vessel wall motion from the ultrasound images, and internal blood pressure were extracted over a cycle averaged from five cycles when the pulsatile pump rates are 20 r/min, 40 r/min, and 60 r/min. As a result, respectively, the peak systolic blood flow velocities were 20 cm/s, 25 cm/s, and 40 cm/s, the blood pressure differences were 30 mmHg, 70 mmHg, and 85 mmHg, the arterial walls were expanded to 0.05 mm, 0.15 mm, and 0.25 mm. Time-delayed cyclic variation of echogenicity compared to blood flow and pressure was observed, but the variation was minimal at 20 r/min. Time-synchronized cyclic variations of these parameters are important information for accurate input parameters and validation of the computational hemodynamic experiments which will provide useful information for the development and progress mechanisms of carotid artery stenosis.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.29-38
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• 2012

The noise generated in the process of obtaining the medical image acts as the element obstructing the image interpretation and diagnosis. To restore the true image from the image polluted from the noise, the total variation optimization algorithm was proposed by the R.O. F (L.Rudin, S Osher, E. Fatemi). This method removes the noise by fitting the balance of the regularity and fidelity. However, the blurring phenomenon of the border area generated in the process of performing the iterative operation cannot be avoided. In this paper, we propose the adaptive total variation method by mapping the control parameter to the proposed transfer function for minimizing boundary error. The proposed transfer function is determined by the noise variance and the local property of the image. The proposed method was applied to 464 tooth images. To evaluate proposed method performance, PSNR which is a indicator of signal and noise's signal power ratio was used. The experimental results show that the proposed method has better performance than other methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1087-1094
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• 2010

We have developed a cylindrical multi-terminal capacitive-conductive sensor that could be attached to the internal surface of cooling system pipe to evaluate capacitance and conductivity of heat transfer fluid. It was used as measuring system to diagnose insulating condition, by which was kept a insulating resistance of inner stack and at the same time was cooled electrochemical heat of reaction of FCEV(fuel cell electric vehicle) stack that used a compressed hydrogen gas reacting with oxygen in accordance with variation on thermal degradation of nonconductive heat transfer fluid. Also to assess diagnosis characteristics of heat transfer fluid, i.e. coolant, we have performed accelerated aging test using developed sensor attached to cooling system. Consequently, it was measured dielectric and electric resistance of coolant to estimate and analyse for dielectric properties by degradation condition.

• Journal of the korean academy of Pediatric Dentistry
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• v.31 no.4
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• pp.659-664
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• 2004

Dens invaginatus is a developmental variation resulting from invasination of the tooth crown of root before calcification. Teeth most affected are maxillary lateral incisors. The malformation shows a broad spectrum of morphologic variations and frequently results in early pulp necrosis. Root canal therapy may present severe problems because of the complex anatomy of the teeth. So, the early diagnosis of such malformation is crucial and a preventive approach has been recommended. This report describes three cases of dens invaginatus treatment.

• Restorative Dentistry and Endodontics
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• v.42 no.1
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• pp.60-64
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• 2017

Root canal anatomy is complex, and the recognition of anatomic variations could be a challenge for clinicians. This case report describes the importance of cone beam computed tomographyic (CBCT) imaging during endodontic treatment. A 23 year old woman was referred by her general dental practitioner with the chief complaint of spontaneous pain in her right posterior maxilla. From the clinical and radiographic findings, a diagnosis of symptomatic irreversible pulpitis was made and endodontic treatment was suggested to the patient. The patient underwent CBCT examination, and CBCT scan slices revealed seven canals: three mesiobuccal (MB1, MB2, and MB3), two distobuccal (DB1 and DB2), and two palatal (P1 and P2). Canals were successfully treated with reciprocating files and filled using single-cone filling technique. Precise knowledge of root canal morphology and its variation is important during root canal treatment. CBCT examination is an excellent tool for identifying and managing these complex root canal systems.

• Journal of Preventive Medicine and Public Health
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• v.26 no.2 s.42
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• pp.293-309
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• 1993

With expanded and extended coverage of the national medical insurance and fast growing health care expenditures, appropriateness of health service utilization and quality of care are concerns of both health care providers and insurers as well as patients. An accurate patient classification system is a basic tool for effective health care policies and efficient health services management. A classification system applicable to Korean medical information-Korean Diagnosis Related Groups (K-DRGs)-was developed based on the U.S. Refined DRGs, and the performance of the developed system was assessed in this study. In the process of the development, first the Korean coding systems for diagnoses and procedures were converted to the systems used in the definition of the U.S. Refined DRGs using the mapping tables formulated by physician panels. Then physician panels reviewed the group definition, and identified medical practice patterns different in two countries. The definition was modified for the differences in K-DRGs. The process resulted in 1,199 groups in the system. Several groups in Refined DRGs could not be differentiated in K-DRGs due to insufficient medical information, and several groups could not be defined due to procedures which were not practiced in Korea. However, the classification structure of Refined DRGs was retained in K-DRGs. The developed system was evaluated fur its performance in explaining variations in resource use as measured by charges and length of stay(LOS), for both all and non-extreme discharges. The data base used in this evaluation included 373,322 discharges which was a random sample of discharges reviewed and payed by the medical insurance during the five-month period from September 1990. The proportion of variance in resource use which was reduced by classifying patients into K-DRGs-r-square-was comparable to the performance of the U.S. Refined DRGs: .39 for charges and .25 for LOS for all discharges, and .53 for charges and .31 for LOS for non-extreme discharges. Another measure analyzed to assess the performance was the coefficient of variation of charges within individual K-DRGs. A total of 966 K-DRGs (87.7%) showed a coefficient below 100%, and the highest coefficient among K-DRGs with more than 30 discharges was 159%.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.241-241
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• 2012

Semiconductor industry has been taking the advantage of improvements in process technology in order to maintain reduced device geometries and stringent performance specifications. This results in semiconductor manufacturing processes became hundreds in sequence, it is continuously expected to be increased. This may in turn reduce the yield. With a large amount of investment at stake, this motivates tighter process control and fault diagnosis. The continuous improvement in semiconductor industry demands advancements in process control and monitoring to the same degree. Any fault in the process must be detected and classified with a high degree of precision, and it is desired to be diagnosed if possible. The detected abnormality in the system is then classified to locate the source of the variation. The performance of a fault detection system is directly reflected in the yield. Therefore a highly capable fault detection system is always desirable. In this research, time series modeling of the data from an etch equipment has been investigated for the ultimate purpose of fault diagnosis. The tool data consisted of number of different parameters each being recorded at fixed time points. As the data had been collected for a number of runs, it was not synchronized due to variable delays and offsets in data acquisition system and networks. The data was then synchronized using a variant of Dynamic Time Warping (DTW) algorithm. The AutoRegressive Integrated Moving Average (ARIMA) model was then applied on the synchronized data. The ARIMA model combines both the Autoregressive model and the Moving Average model to relate the present value of the time series to its past values. As the new values of parameters are received from the equipment, the model uses them and the previous ones to provide predictions of one step ahead for each parameter. The statistical comparison of these predictions with the actual values, gives us the each parameter's probability of fault, at each time point and (once a run gets finished) for each run. This work will be extended by applying a suitable probability generating function and combining the probabilities of different parameters using Dempster-Shafer Theory (DST). DST provides a way to combine evidence that is available from different sources and gives a joint degree of belief in a hypothesis. This will give us a combined belief of fault in the process with a high precision.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1031-1031
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• 2001

The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.