• Journal of Korean Society of Rural Planning
• /
• v.23 no.1
• /
• pp.65-83
• /
• 2017

This paper proposes a village level settlement environment diagnostic indices in rural areas which can apply to analyze various conditions at village level. A living space in rural areas has been changed with a diverse aspect according to living infrastructure, industrial structure, accessibility to neighbor city and so on. This indicators considered these mega-regionalization of economy and lifestyle in rural areas. The indicators consists of basic indices for all types villages and convenience service indices for center villages and the other neighbor ones classified by a functionality of their convenience facilities. As the results of delphi expert survey and a field validation, rural village settlement environment diagnostic indicators were selected 3 types, 15 domains, 24 subdomains and 61 items. And these indicators weight were determinted by AHP method. These developed indicators were used to diagnosis settlement conditions of 31 villages, located on county of Yeongdong. to validate a applicability and feasibility.

• Journal of Chest Surgery
• /
• v.50 no.2
• /
• pp.71-77
• /
• 2017

Background: Cardiac computed tomography (CT) has emerged as an alternative to magnetic resonance imaging (MRI) for ventricular volumetry. However, the clinical use of cardiac CT requires external validation. Methods: Both cardiac CT and MRI were performed prior to pulmonary valve implantation (PVI) in 11 patients (median age, 19 years) who had undergone total correction of tetralogy of Fallot during infancy. The simplified contouring method (MRI) and semiautomatic 3-dimensional region-growing method (CT) were used to measure ventricular volumes. Results: All volumetric indices measured by CT and MRI generally correlated well with each other, except for the left ventricular end-systolic volume index (LV-ESVI), which showed the following correlations with the other indices: the right ventricular end-diastolic volume index (RV-EDVI) (r=0.88, p<0.001), the right ventricular end-systolic volume index (RV-ESVI) (r=0.84, p=0.001), the left ventricular end-diastolic volume index (LV-EDVI) (r=0.90, p=0.001), and the LV-ESVI (r=0.55, p=0.079). While the EDVIs measured by CT were significantly larger than those measured by MRI (median RV-EDVI: $197mL/m^2$ vs. $175mL/m^2$, p=0.008; median LV-EDVI: $94mL/m^2$ vs. $92mL/m^2$, p=0.026), no significant differences were found for the RV-ESVI or LV-ESVI. Conclusion: The EDVIs measured by cardiac CT were greater than those measured by MRI, whereas the ESVIs measured by CT and MRI were comparable. The volumetric characteristics of these 2 diagnostic modalities should be taken into account when indications for late PVI after tetralogy of Fallot repair are assessed.

• Journal of Biomedical Engineering Research
• /
• v.29 no.3
• /
• pp.198-204
• /
• 2008

Uroflowmetry is a non-invasive clinical test useful for screening benign prostatic hyperplasia(BPH) common in the aged men. The current standard way to obtain the urinary flow rate is to continuously acquire the urine weight signal proportional to volume over time. The present study proposed an alternative technique measuring pressure to overcome noise problems present in the standard weight measuring technique. Experiments were performed to simultaneously acquire both weight and pressure changes during urination of 9 normal men. Noise components were separated from volume signals converted from both weight and pressure signals based on the polynomial signal model. Signal-to-noise ratio was defined as the ratio of the energies between signal and noise components of the measured volume changes, which was 8.5 times larger in the pressure measuring technique, implying that cleaner signal could be obtained, more immune to noisy environments. When four important diagnostic parameters were estimated, excellent correlation coefficients higher than 0.99 were resulted with mean relative errors less than 5%. Therefore, the present pressure measurement seemed valid as an alternative technique for uroflowmetry.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.36 no.3
• /
• pp.217-224
• /
• 2016

This paper presents a new technique for monitoring the concrete curing process using embedded piezoelectric transducers via admittance measurements. When a piezoelectric transducer is embedded in a structure, the electrical impedance (admittance) of the transducer is coupled with the mechanical impedance of the host structure, which allows monitoring of the structural condition. In this study, the admittance signatures are used for monitoring the concrete curing process. This new method is based on an admittance-based sensor diagnostic process, in which the capacitance values of the piezoelectric transducers are dependent on the strength of the host structure. We numerically and experimentally investigated the variations in capacitive value during the curing process. The results demonstrate that there is a clear relationship between the concrete curing status and the slope, this indicates that the proposed method could be efficiently used for monitoring the curing status of a concrete structure.

• Journal of Korean Medical Science
• /
• v.33 no.53
• /
• pp.342.1-342.6
• /
• 2018

We validated the diagnostic performance of a previously developed blood-based 7-protein biomarker panel, $AptoDetect^{TM}$-Lung (Aptamer Sciences Inc., Pohang, Korea) using modified aptamer-based proteomic technology for lung cancer detection. Non-small cell lung cancer (NSCLC), 200 patients and benign nodule controls, 200 participants were enrolled. In a high-risk population corresponding to ${\geq}55years$ of age and ${\geq}30pack-years$, the diagnostic performance was improved, showing 73.3% sensitivity and 90.5% specificity with an area under the curve of 0.88. $AptoDetect^{TM}$-Lung (Aptamer Sciences Inc.) offers the best validated performance to discriminate NSCLC from benign nodule controls in a high-risk population and could play a complementary role in lung cancer screening.

• Journal of Christian Education in Korea
• /
• v.64
• /
• pp.409-444
• /
• 2020

The purpose of this study is to develop and propose a tool for accurately diagnosing factors influencing academic activities in Christian University. The first, the evaluation area is composed of factors that influence the academic life of students. Then, by developing a tool to diagnose the status in that areas, it is intended to provide a basis for providing appropriate help for students to adjust to university life. This tool composed items through prior research and developed a draft of tool through Delphi research. The draft tool was verified for reliability and validity by analyzing the response values of 182 freshmen at K University. As a result of the analysis, the reliability showed high reliability of .869~.955 for each diagnosis area. In conclusion, through the results of EFA and CFA, a final diagnostic tool was developed and suggested.

• Atmosphere
• /
• v.31 no.5
• /
• pp.473-488
• /
• 2021

A new physical/statistical diagnostic downscale model has been developed for use to improve near-surface air temperature forecasts. The model includes a series of physical and statistical correction methods that account for un-resolved topographic and land-use effects as well as statistical bias errors in a low-resolution atmospheric model. Operational temperature forecasts of the Local Data Assimilation and Prediction System (LDAPS) were downscaled at 100 m resolution for three months, which were used to validate the model's physical and statistical correction methods and to compare its performance with the forecasts of the Korea Meteorological Administration Post-processing (KMAP) system. The validation results showed positive impacts of the un-resolved topographic and urban effects (topographic height correction, valley cold air pool effect, mountain internal boundary layer formation effect, urban land-use effect) in complex terrain areas. In addition, the statistical bias correction of the LDAPS model were efficient in reducing forecast errors of the near-surface temperatures. The new high-resolution downscale model showed better agreement against Korean 584 meteorological monitoring stations than the KMAP, supporting the importance of the new physical and statistical correction methods. The new physical/statistical diagnostic downscale model can be a useful tool in improving near-surface temperature forecasts and diagnostics over complex terrain areas.

• Journal of Veterinary Science
• /
• v.21 no.1
• /
• pp.16.1-16.10
• /
• 2020

Cancer is a major cause of death in dogs worldwide, and the incidence of cancer in dogs is increasing. The attenuated total reflection Fourier transform infrared spectroscopic (ATR-FTIR) technique is a powerful tool for the diagnosis of several diseases. This method enables samples to be examined directly without pre-preparation. In this study, we evaluated the diagnostic value of ATR-FTIR for the detection of cancer in dogs. Cancer-bearing dogs (n = 30) diagnosed by pathologists and clinically healthy dogs (n = 40) were enrolled in this study. Peripheral blood was collected for clinicopathological diagnosis. ATR-FTIR spectra were acquired, and principal component analysis was performed on the full wave number spectra (4,000-650 cm^-1). The leave-one-out cross validation technique and partial least squares regression analysis were used to predict normal and cancer spectra. Red blood cell counts, hemoglobin levels and white blood cell counts were significantly lower in cancer-bearing dogs than in clinically healthy dogs (p < 0.01, p < 0.01 and p = 0.03, respectively). ATR-FTIR spectra showed significant differences between the clinically healthy and cancer-bearing groups. This finding demonstrates that ATR-FTIR can be applied as a screening technique to distinguish between cancer-bearing dogs and healthy dogs.

• International Journal of Computer Science & Network Security
• /
• v.23 no.8
• /
• pp.17-25
• /
• 2023

The alarming global prevalence of Type 2 Diabetes Mellitus (T2DM) has catalyzed an urgent need for robust, early diagnostic methodologies. This study unveils a pioneering approach to predicting T2DM, employing the Extreme Gradient Boosting (XGBoost) algorithm, renowned for its predictive accuracy and computational efficiency. The investigation harnesses a meticulously curated dataset of 4303 samples, extracted from a comprehensive Chinese research study, scrupulously aligned with the World Health Organization's indicators and standards. The dataset encapsulates a multifaceted spectrum of clinical, demographic, and lifestyle attributes. Through an intricate process of hyperparameter optimization, the XGBoost model exhibited an unparalleled best score, elucidating a distinctive combination of parameters such as a learning rate of 0.1, max depth of 3, 150 estimators, and specific colsample strategies. The model's validation accuracy of 0.957, coupled with a sensitivity of 0.9898 and specificity of 0.8897, underlines its robustness in classifying T2DM. A detailed analysis of the confusion matrix further substantiated the model's diagnostic prowess, with an F1-score of 0.9308, illustrating its balanced performance in true positive and negative classifications. The precision and recall metrics provided nuanced insights into the model's ability to minimize false predictions, thereby enhancing its clinical applicability. The research findings not only underline the remarkable efficacy of XGBoost in T2DM prediction but also contribute to the burgeoning field of machine learning applications in personalized healthcare. By elucidating a novel paradigm that accentuates the synergistic integration of multifaceted clinical parameters, this study fosters a promising avenue for precise early detection, risk stratification, and patient-centric intervention in diabetes care. The research serves as a beacon, inspiring further exploration and innovation in leveraging advanced analytical techniques for transformative impacts on predictive diagnostics and chronic disease management.

• Parasites, Hosts and Diseases
• /
• v.61 no.2
• /
• pp.202-209
• /
• 2023

Lophomonas blattarum is an anaerobic protozoan living in the intestine of cockroaches and house dust mites, with ultramicroscopic characteristics such as the presence of a parabasal body, axial filament, and absence of mitochondria. More than 200 cases of Lophomonas infection of the respiratory tract have been reported worldwide. However, the current diagnosis of such infection depends only on light microscopic morphological findings from respiratory secretions. In this study, we attempted to provide more robust evidence of protozoal infection in an immunocompromised patient with atypical pneumonia, positive for Lophomonas-like protozoal cell forms. A direct search of bronchoalveolar lavage fluid via polymerase chain reaction (PCR), transmission electron microscopy (TEM), and metagenomic next-generation sequencing did not prove the presence of protozoal infection. PCR results were not validated with sufficient rigor, while de novo assembly and taxonomic classification results did not confirm the presence of an unidentified pathogen. The TEM results implied that such protozoal forms in light microscopy are actually non-detached ciliated epithelial cells. After ruling out infectious causes, the patient's final diagnosis was drug-induced pneumonitis. These findings underscore the lack of validation in the previously utilized diagnostic methods, and more evidence in the presence of L. blattarum is required to further prove its pathogenicity.