• Korean Journal of Radiology
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• 제21권6호
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• pp.660-669
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• 2020

Objective: To evaluate the accuracy of a deep learning-based automated segmentation of the left ventricle (LV) myocardium using cardiac CT. Materials and Methods: To develop a fully automated algorithm, 100 subjects with coronary artery disease were randomly selected as a development set (50 training / 20 validation / 30 internal test). An experienced cardiac radiologist generated the manual segmentation of the development set. The trained model was evaluated using 1000 validation set generated by an experienced technician. Visual assessment was performed to compare the manual and automatic segmentations. In a quantitative analysis, sensitivity and specificity were calculated according to the number of pixels where two three-dimensional masks of the manual and deep learning segmentations overlapped. Similarity indices, such as the Dice similarity coefficient (DSC), were used to evaluate the margin of each segmented masks. Results: The sensitivity and specificity of automated segmentation for each segment (1-16 segments) were high (85.5-100.0%). The DSC was 88.3 ± 6.2%. Among randomly selected 100 cases, all manual segmentation and deep learning masks for visual analysis were classified as very accurate to mostly accurate and there were no inaccurate cases (manual vs. deep learning: very accurate, 31 vs. 53; accurate, 64 vs. 39; mostly accurate, 15 vs. 8). The number of very accurate cases for deep learning masks was greater than that for manually segmented masks. Conclusion: We present deep learning-based automatic segmentation of the LV myocardium and the results are comparable to manual segmentation data with high sensitivity, specificity, and high similarity scores.

• Structural Engineering and Mechanics
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• 제90권2호
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• pp.159-175
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• 2024

In order to solve the problem of calculating the reasonable completed bridge state of a self-anchored hybrid cable-stayed suspension bridge (SA-HCSB), this paper proposes an analytical method. This method simplifies the main beam into a continuous beam with multi-point rigid supports and solves the support reaction forces. According to the segmented catenary theory, it simultaneously solves the horizontal forces of the main span main cables and the stay cables and iteratively calculates the equilibrium force system on the main beam in the collaborative system bridge state while completing the shape finding of the main span main cable and stay cables. Then, the horizontal forces of the side span main cables and stay cables are obtained based on the balance of horizontal forces on the bridge towers, and the shape finding of the side spans are completed according to the segmented catenary theory. Next, the difference between the support reaction forces of the continuous beam with multiple rigid supports obtained from the initial and final iterations is used to calculate the load of ballast on the side span main beam. Finally, the axial forces and strains of each segment of the main beam and bridge tower are obtained based on the loads applied by the main cable and stay cables on the main beam and bridge tower, thereby obtaining analytical data for the bridge in the reasonable completed state. In this paper, the rationality and effectiveness of this analytical method are verified through a case study of a SA-HCSB with a main span of 720m in finite element analysis. At the same time, it is also verified that the equilibrium force of the main beam under the reasonably completed bridge state can be obtained through iterative calculation. The analytical algorithm in this paper has clear physical significance, strong applicability, and high accuracy of calculation results, enriching the shape-finding method of this bridge type.

• 한국농공학회논문집
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• 제61권5호
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• pp.101-108
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• 2019

The domestic duck industry is the sixth-largest among the livestock industries. However, 34.3% of duck houses were the duck houses arbitrarily converted from plastic greenhouses. This type of duck house was difficult to properly manage internal air temperature and humidity environment. Humidity environment inside duck houses is an important factor that directly affects the productivity and disease occurrence of the duck. Although the humidity environments of litters (bedding materials) affect directly the inside environment of duck houses, there are only few studies related to humidity environment of litters. In this study, evaporation rates from litters were evaluated according to air temperature, relative humidity, water contents of litters, and wind speed. The experimental chamber was made to measure evaporation rates from litters. Temperature and humidity controlled chamber was utilized during the conduct of the laboratory experiments. Using the measured data, a multi linear regression analysis was carried out to derive the calculation formula of evaporation rates from litters. In order to improve the accuracy of the multi linear regression model, the partial vapor pressure directly related to evaporation was also considered. Variance inflation factors of air temperature, relative humidity, partial vapor pressure, water contents of litters, and wind speed were calculated to identify multicollinearity problem. The Multiple $R^2$ and adjusted-$R^2$ of regression model were calculated at 0.76 and 0.71, respectively. Therefore, the regression models were developed in this study can be used to estimate evaporation rates from the litter of duck houses.

• Smart Structures and Systems
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• 제15권4호
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• pp.997-1018
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• 2015

Structural health monitoring along with damage detection and assessment of its severity level in non-accessible reinforced concrete members using piezoelectric materials becomes essential since engineers often face the problem of detecting hidden damage. In this study, the potential of the detection of flexural damage state in the lower part of the mid-span area of a simply supported reinforced concrete beam using piezoelectric sensors is analytically investigated. Two common severity levels of flexural damage are examined: (i) cracking of concrete that extends from the external lower fiber of concrete up to the steel reinforcement and (ii) yielding of reinforcing bars that occurs for higher levels of bending moment and after the flexural cracking. The purpose of this investigation is to apply finite element modeling using admittance based signature data to analyze its accuracy and to check the potential use of this technique to monitor structural damage in real-time. It has been indicated that damage detection capability greatly depends on the frequency selection rather than on the level of the harmonic excitation loading. This way, the excitation loading sequence can have a level low enough that the technique may be considered as applicable and effective for real structures. Further, it is concluded that the closest applied piezoelectric sensor to the flexural damage demonstrates higher overall sensitivity to structural damage in the entire frequency band for both damage states with respect to the other used sensors. However, the observed sensitivity of the other sensors becomes comparatively high in the peak values of the root mean square deviation index.

• Steel and Composite Structures
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• 제49권2호
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• pp.161-180
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• 2023

In the previous research, the axial compressive capacity models for the glass fiber-reinforced polymer (GFRP)-reinforced circular concrete compression elements restrained with GFRP helix were put forward based on small and noisy datasets by considering a limited number of parameters portraying less accuracy. Consequently, it is important to recommend an accurate model based on a refined and large testing dataset that considers various parameters of such components. The core objective and novelty of the current research is to suggest a deep learning model for the axial compressive capacity of GFRP-reinforced circular concrete columns restrained with a GFRP helix utilizing various parameters of a large experimental dataset to give the maximum precision of the estimates. To achieve this aim, a test dataset of 61 GFRP-reinforced circular concrete columns restrained with a GFRP helix has been created from prior studies. An assessment of 15 diverse theoretical models is carried out utilizing different statistical coefficients over the created dataset. A novel model utilizing the group method of data handling (GMDH) has been put forward. The recommended model depicted good effectiveness over the created dataset by assuming the axial involvement of GFRP main bars and the confining effectiveness of transverse GFRP helix and depicted the maximum precision with MAE = 195.67, RMSE = 255.41, and R2 = 0.94 as associated with the previously recommended equations. The GMDH model also depicted good effectiveness for the normal distribution of estimates with only a 2.5% discrepancy from unity. The recommended model can accurately calculate the axial compressive capacity of FRP-reinforced concrete compression elements that can be considered for further analysis and design of such components in the field of structural engineering.

• Clinical and Experimental Emergency Medicine
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• 제5권4호
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• pp.264-271
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• 2018

Objective For patients with acute myocardial infarction (AMI), symptoms assessed by emergency medical services (EMS) providers have a critical role in prehospital treatment decisions. The purpose of this study was to evaluate the diagnostic accuracy of EMS provider-assessed cardiac symptoms of AMI. Methods Patients transported by EMS to 4 study hospitals from 2008 to 2012 were included. Using EMS and administrative emergency department databases, patients were stratified according to the presence of EMS-assessed cardiac symptoms and emergency department diagnosis of AMI. Cardiac symptoms were defined as chest pain, dyspnea, palpitations, and syncope. Disproportionate stratified sampling was used, and medical records of sampled patients were reviewed to identify an actual diagnosis of AMI. Using inverse probability weighting, verification bias-corrected diagnostic performance was estimated. Results Overall, 92,353 patients were enrolled in the study. Of these, 13,971 (15.1%) complained of cardiac symptoms to EMS providers. A total of 775 patients were sampled for hospital record review. The sensitivity, specificity, positive predictive value, and negative predictive value of EMS provider-assessed cardiac symptoms for the final diagnosis of AMI was 73.3% (95% confidence interval [CI], 70.8 to 75.7), 85.3% (95% CI, 85.3 to 85.4), 3.9% (95% CI, 3.6 to 4.2), and 99.7% (95% CI, 99.7 to 99.8), respectively. Conclusion We found that EMS provider-assessed cardiac symptoms had moderate sensitivity and high specificity for diagnosis of AMI. EMS policymakers can use these data to evaluate the pertinence of specific prehospital treatment of AMI.

• 해양환경안전학회지
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• 제15권2호
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• pp.157-164
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• 2009

Al, Ag, Au, Cu, Cd, Co, Fe, Ni, Pb, Zn등의 금속은 해수 중에 미량으로 존재하기 때문에 미량금속이라고 하며 일부는 미량영양소로서 생명체의 생리활동에 필요하지만 정해진 한계값을 초과할 때는 독성을 나타낸다. 미량금속(중금속)은 해양환경 및 해양생태계에 악영향을 미칠 수 있기 때문에 지속성 오염물질로 분류되어 다양한 연구가 수행되고 있다. 해수와 담수 등 자연수 중의 미량금속 측정은 정확도와 정밀도에 있어서 큰 오차를 가지고 있음이 장기간 인식되어 왔다. 미국과 유럽에서는 1975년 이후 미량금속의 해수 중 농도가 과거에 인지된 농도의 $1/10{\sim}1/1,000$ 정도로 낮아졌으며, 수직 분포는 생물, 물리, 지화학적인 과정들이 반영되고 있음이 밝혀졌다. 이와 같은 결과는 대부분 미량금속에 대한 분석방법과 기기의 발전에 기인하며, 시료 채취, 보관 및 분석 과정에 발생할 수 있는 오염을 제거해야 하는 세심한 주의가 요구되고 있다. 그러나 국내의 경우 많은 해양환경 관린 조사 및 연구에서 정확성이 결여된 자료가 보고되고 있다. 특히 미량금속 분석에 있어서 시료의 채취, 보관, 분석에 대한 정착한 인식 및 이해 부족은 자료의 질을 저하시키고 있다. 해양환경 연구 및 환경평가에 활용하기 위하여 자연수 중 미량금속의 정확한 자료를 획득하는 주요 과정에 대하여 소개하고자 한다.

• Steel and Composite Structures
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• 제43권6호
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• pp.785-796
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• 2022

Concrete-encased steel (CES) beam, in which structural steel is encased in a reinforced concrete (RC) section, is widely applied in high-rise buildings as transfer beams due to its high load-carrying capacity, great stiffness, and good durability. However, these CES beams are prone to shear failure because of the low shear span-to-depth ratio and the heavy load. Due to the high load-carrying capacity and the brittle failure process of the shear failure, the accurate strength prediction of CES beams significantly influences the assessment of structural safety. In current design codes, design formulas for predicting the shear strength of CES beams are based on the so-called "superposition method". This method indicates that the shear strength of CES beams can be obtained by superposing the shear strengths of the RC part and the steel shape. Nevertheless, in some cases, this method yields errors on the unsafe side because the shear strengths of these two parts cannot be achieved simultaneously. This paper clarifies the conditions at which the superposition method does not hold true, and the shear strength of CES beams is investigated using a compatible truss-arch model. Considering the deformation compatibility between the steel shape and the RC part, the method to obtain the shear strength of CES beams is proposed. Finally, the proposed model is compared with other calculation methods from codes AISC 360 (USA, North America), Eurocode 4 (Europe), YB 9082 (China, Asia), JGJ 138 (China, Asia), and AS/NZS 2327 (Australia/New Zealand, Oceania) using the available test data consisting of 45 CES beams. The results indicate that the proposed model can predict the shear strength of CES beams with sufficient accuracy and safety. Without considering the deformation compatibility, the calculation methods from the codes AISC 360, Eurocode 4, YB 9082, JGJ 138, and AS/NZS 2327 lead to excessively conservative or unsafe predictions.

• Imaging Science in Dentistry
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• 제53권3호
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• pp.199-207
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• 2023

Purpose: The objective of this study was to evaluate the accuracy and effectiveness of an artificial intelligence (AI) program in identifying dental conditions using panoramic radiographs(PRs), as well as to assess the appropriateness of its treatment recommendations. Materials and Methods: PRs from 100 patients(representing 4497 teeth) with known clinical examination findings were randomly selected from a university database. Three dentomaxillofacial radiologists and the Diagnocat AI software evaluated these PRs. The evaluations were focused on various dental conditions and treatments, including canal filling, caries, cast post and core, dental calculus, fillings, furcation lesions, implants, lack of interproximal tooth contact, open margins, overhangs, periapical lesions, periodontal bone loss, short fillings, voids in root fillings, overfillings, pontics, root fragments, impacted teeth, artificial crowns, missing teeth, and healthy teeth. Results: The AI demonstrated almost perfect agreement (exceeding 0.81) in most of the assessments when compared to the ground truth. The sensitivity was very high (above 0.8) for the evaluation of healthy teeth, artificial crowns, dental calculus, missing teeth, fillings, lack of interproximal contact, periodontal bone loss, and implants. However, the sensitivity was low for the assessment of caries, periapical lesions, pontic voids in the root canal, and overhangs. Conclusion: Despite the limitations of this study, the synthesized data suggest that AI-based decision support systems can serve as a valuable tool in detecting dental conditions, when used with PR for clinical dental applications.

• 대한세포병리학회지
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• 제18권2호
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• pp.126-132
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• 2007

The aim of this study was to evaluate the diagnostic value of fine needle aspiration cytology (FNAC) for the assessment of palpable enlarged lymph nodes. The authors reviewed the results of 1,346 FNACs of palpable enlarged lymph nodes performed at Pusan National University Hospital from 1998 to 2004. Of the 1,346 cases, 1,265 (94.0%) were satisfactory and 81 (6.0%) unsatisfactory. Cytologic diagnoses were judged in 488 cases, based on subsequent histologic diagnoses, clinical follow up, or both. Global results for all malignancies (lymphoid and non-lymphoid neoplasms) based on cases with final diagnoses, showed a sensitivity of 87.4% and a specificity of 98.7%. The overall diagnostic accuracy was 93,2%, and the false negative rate reduced from 12,6% to 7,3% when lymphomatous cases were excluded. The annual data for this period showed that the number of diagnostic lymph node biopsies and the rate of inadequately sampled material markedly decreased. Gene rearrangement studies for IgH and TCR ${\gamma}$ were helful in 30 cases. FNAC is a useful initial diagnostic procedure for the evaluation of palpable enlarged lymph nodes. However, the technique should be assisted by the appropriate ancillary studies and by proper interpretation by a cytopathologist.