• Clinics in Shoulder and Elbow
• /
• 제25권1호
• /
• pp.5-14
• /
• 2022

Background: The purpose of this study was to verify the effect of protocatechuic acid (PCA) on tendon healing and fatty degeneration in a chronic rotator cuff model. Methods: Twenty-eight Sprague-Dawley male rats were randomly allocated into two groups: Saline+repair (SR) and PCA+repair (PR). The right shoulder was used for experimental interventions, and the left served as a control. PCA (30 mg/kg/day) was administered intraperitoneally at the site of infraspinatus tendon detachment in rats in the PR group, and the same volume of saline was administered to the same site in the SR group. The torn tendon was repaired 4 weeks after infraspinatus detachment. Four weeks after repair, hematoxylin and eosin (H&E), S100, and CD68 stains were performed to evaluate the degree of fatty degeneration and H&E and Masson trichrome stains were performed to assess tendon healing. Superoxide dismutase (SOD) was measured to test the efficacy of PCA as an antioxidant. Results: Results from histological evaluation indicated that SOD and CD68 levels at the musculotendinous region and collagen fiber parallel to the orientation at the tendon-to-bone junction were not significantly different between the SR and PR groups. The mean load-to-failure of the PR group (20.32±9.37 N) was higher than that of the SR group (16.44±6.90 N), although this difference was not statistically significant (p=0.395). The SOD activity in the operative side infraspinatus muscle of the PR group was higher than that of the SR group, but the difference was not statistically significant (p=0.053). Conclusions: The use of PCA could improve tendon healing and decrease fatty degeneration after rotator cuff repair.

• Structural Engineering and Mechanics
• /
• 제85권5호
• /
• pp.635-644
• /
• 2023

The design of honeycomb sandwich structures is often challenging because these structures can be tailored from a variety of possible cores and face sheets configurations, therefore, the design of sandwich structures is characterized as a time-consuming and complex task. A data-driven computational approach that integrates the analytical method and Artificial Neural Network (ANN) is developed by the authors to rapidly predict the design of sandwich structures for a targeted maximum structural deflection. The elaborated ANN reverse design approach is applied to obtain the thickness of the sandwich core, the thickness of the laminated face sheets, and safety factors for composite sandwich structure. The required data for building ANN model were obtained using the governing equations of sandwich components in conjunction with the Monte Carlo Method. Then, the functional relationship between the input and output features was created using the neural network Backpropagation (BP) algorithm. The input variables were the dimensions of the sandwich structure, the applied load, the core density, and the maximum deflection, which was the reverse input given by the designer. The outstanding performance of reverse ANN model revealed through a low value of mean square error (MSE) together with the coefficient of determination (R2) close to the unity. Furthermore, the output of the model was in good agreement with the analytical solution with a maximum error 4.7%. The combination of reverse concept and ANN may provide a potentially novel approach in designing of sandwich structures. The main added value of this study is the elaboration of a reverse ANN model, which provides a low computational technique as well as savestime in the design or redesign of sandwich structures compared to analytical and finite element approaches.

• 산업경영시스템학회지
• /
• 제45권4호
• /
• pp.53-60
• /
• 2022

In a group-testing method, instead of testing a sample, for example, blood individually, a batch of samples are pooled and tested simultaneously. If the pooled test is positive (or defective), each sample is tested individually. However, if negative (or good), the test is terminated at one pooled test because all samples in the batch are negative. This paper considers a queueing system with a two-stage group-testing policy. Samples arrive at the system according to a Poisson process. The system has a single server which starts a two-stage group test in a batch whenever the number of samples in the system reaches exactly a predetermined size. In the first stage, samples are pooled and tested simultaneously. If the pooled test is negative, the test is terminated. However, if positive, the samples are divided into two equally sized subgroups and each subgroup is applied to a group test in the second stage, respectively. The server performs pooled tests and individual tests sequentially. The testing time of a sample and a batch follow general distributions, respectively. In this paper, we derive the steady-state probability generating function of the system size at an arbitrary time, applying a bulk queuing model. In addition, we present queuing performance metrics such as the offered load, output rate, allowable input rate, and mean waiting time. In numerical examples with various prevalence rates, we show that the second-stage group-testing system can be more efficient than a one-stage group-testing system or an individual-testing system in terms of the allowable input rates and the waiting time. The two-stage group-testing system considered in this paper is very simple, so it is expected to be applicable in the field of COVID-19.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2020년도 학술발표회
• /
• pp.85-85
• /
• 2020

South Korea experiences few large scale erosion and sedimentation problems, however, there are numerous local sedimentation problems. A reliable and consistent approach to modelling and management for sediment processes are desirable in the country. In this study, field measurements of sediment concentration from 34 alluvial river basins in South Korea were used with the Modified Einstein Procedure (MEP) to determine the total sediment load at the sampling locations. And then the Flow Duration-Sediment Rating Curve (FD-SRC) method was used to estimate the specific degradation for all gauging stations. The specific degradation of most rivers were found to be typically 50-300 tons/㎢·yr. A model tree data mining technique was applied to develop a model for the specific degradation based on various watershed characteristics of each watershed from GIS analysis. The meaningful parameters are: 1) elevation at the middle relative area of the hypsometric curve [m], 2) percentage of wetland and water [%], 3) percentage of urbanized area [%], and 4) Main stream length [km]. The Root Mean Square Error (RMSE) of existing models is in excess of 1,250 tons/㎢·yr and the RMSE of the proposed model with 6 additional validations decreased to 65 tons/㎢·yr. Erosion loss maps from the Revised Universal Soil Loss Equation (RUSLE), satellite images, and aerial photographs were used to delineate the geospatial features affecting erosion and sedimentation. The results of the geospatial analysis clearly shows that the high risk erosion area (hill slopes and construction sites at urbanized area) and sedimentation features (wetlands and agricultural reservoirs). The result of physiographical analysis also indicates that the watershed morphometric characteristic well explain the sediment transport. Sustainable management with the data mining methodologies and geospatial analysis could be helpful to solve various erosion and sedimentation problems under different conditions.

• 농업과학연구
• /
• 제50권4호
• /
• pp.773-784
• /
• 2023

In this study, we developed a dynamic model and steering controller model for an autonomous tractor and evaluated their performance. The traction force was measured using a 6-component load cell, and the rotational speed of the wheels was monitored using proximity sensors installed on the axles. Torque sensors were employed to measure the axle torque. The PI (proportional integral) controller's coefficients were determined using the trial-error method. The coefficient of the P varied in the range of 0.1 - 0.5 and the I coefficient was determined in 3 increments of 0.01, 0.05, and 0.1. To validate the simulation model, we conducted RMS (root mean square) comparisons between the measured data of axle torque and the simulation results. The performance of the steering controller model was evaluated by analyzing the damping ratio calculated with the first and second overshoots. The average front and rear axle torque ranged from 3.29 - 3.44 and 6.98 - 7.41 kNm, respectively. The average rotational speed of the wheel ranged from 29.21 - 30.55 rpm at the front, and from 21.46 - 21.63 rpm at the rear. The steering controller model exhibited the most stable control performance when the coefficients of P and I were set at 0.5 and 0.01, respectively. The RMS analysis of the axle torque results indicated that the left and right wheel errors were approximately 1.52% and 2.61% (at front) and 7.45% and 7.28% (at rear), respectively.

• 한국지진공학회논문집
• /
• 제28권4호
• /
• pp.193-203
• /
• 2024

Existing reinforced concrete (RC) building frames constructed before the seismic design was applied have seismically deficient structural details, and buildings with such structural details show brittle behavior that is destroyed early due to low shear performance. Various reinforcement systems, such as fiber-reinforced polymer (FRP) jacketing systems, are being studied to reinforce the seismically deficient RC frames. Due to the step-by-step modeling and interpretation process, existing seismic performance assessment and reinforcement design of buildings consume an enormous amount of workforce and time. Various machine learning (ML) models were developed using input and output datasets for seismic loads and reinforcement details built through the finite element (FE) model developed in previous studies to overcome these shortcomings. To assess the performance of the seismic performance prediction models developed in this study, the mean squared error (MSE), R-square (R²), and residual of each model were compared. Overall, the applied ML was found to rapidly and effectively predict the seismic performance of buildings according to changes in load and reinforcement details without overfitting. In addition, the best-fit model for each seismic performance class was selected by analyzing the performance by class of the ML models.

• 산업경영시스템학회지
• /
• 제47권2호
• /
• pp.1-9
• /
• 2024

New motor development requires high-speed load testing using dynamo equipment to calculate the efficiency of the motor. Abnormal noise and vibration may occur in the test equipment rotating at high speed due to misalignment of the connecting shaft or looseness of the fixation, which may lead to safety accidents. In this study, three single-axis vibration sensors for X, Y, and Z axes were attached on the surface of the test motor to measure the vibration value of vibration. Analog data collected from these sensors was used in classification models for anomaly detection. Since the classification accuracy was around only 93%, commonly used hyperparameter optimization techniques such as Grid search, Random search, and Bayesian Optimization were applied to increase accuracy. In addition, Response Surface Method based on Design of Experiment was also used for hyperparameter optimization. However, it was found that there were limits to improving accuracy with these methods. The reason is that the sampling data from an analog signal does not reflect the patterns hidden in the signal. Therefore, in order to find pattern information of the sampling data, we obtained descriptive statistics such as mean, variance, skewness, kurtosis, and percentiles of the analog data, and applied them to the classification models. Classification models using descriptive statistics showed excellent performance improvement. The developed model can be used as a monitoring system that detects abnormal conditions of the motor test.

• 대한치과보철학회지
• /
• 제55권2호
• /
• pp.144-150
• /
• 2017

목적: 이 연구의 목적은 심미적인 임플란트 지대주의 종류와 두께에 따른 파절 강도를 측정하여 구강 내 저작압에 견디는 최소한의 두께를 평가하기 위함이다. 재료 및 방법: 대조군으로 0.5 mm 두께의 티타늄 임플란트 지대주를(Ti-0.5), 실험군으로 지르코니아 임플란트와 레진 나노 세라믹 지대주를 사용하여 각각 0.5 mm, 0.8 mm, 1.0 mm 두께로 각 그룹에 10개씩 총 70개의 시편을 제작하였다(그룹Zir-0.5, Zir-0.8, Zir-1.0, RNC-0.5, RNC-0.8, RNC-1.0). 모든 시편은 파절 실험 이전에 열순환을 시행하여 구강 내에서의 사용을 재현한 후, universal testing machine을 이용하여 각 시편의 파절 강도를 측정하여 평균값을 측정하였다. 그룹들의 평균 파절 값을 측정하였으며 이원분산분석을 이용하여 통계학적으로 분석하였다. 결과: Zir-1.0군이 가장 높은 파절 강도 $2,476.3{\pm}342.0N$를 보였으며 뒤를 이어 Zir-0.8 ($1,518{\pm}347.9N$), Ti-0.5 ($1,041.8{\pm}237.2N$), Zir-0.5 ($631.4{\pm}149.0N$), 의 순이었다. RNC 그룹의 경우에 Ti와 Zir 그룹에 비교하여 유의하게 낮은 파절 강도값을 나타내었으며(RNC-1.0 $427.5{\pm}72.1$, RNC-0.8 $297.9{\pm}41.2$), 모든 실험군에서 지대주 두께가 감소할수록 파절 강도 값도 유의하게 감소했다(P < .01). RNC-0.5 ($127.4{\pm}35.3N$) 그룹은 다른 모든 군에 비해 유의하게 낮은 값을 보였다(P < .05). 결론: 이번 실험에서 사용된 모든 두께의 지르코니아 지대주는 전치부와 구치부의 교합압을 견딜 수 있는 정도의 파절 강도를 보여주었다. 레진 나노 세라믹 지대주의 경우 0.8 mm 두께 이상에서 전치부의 교합압을 견딜 수 있는 가능성을 보여주었다.

• 대한치과보철학회지
• /
• 제60권2호
• /
• pp.135-142
• /
• 2022

목적: 이번 연구의 목적은 단일구조 지르코니아(monolithic zirconia) 크라운의 서로 다른 부위에서, 감소된 지르코니아의 두께가 파절 저항성에 미치는 복합적인 영향을 평가하기 위한 것이다. 재료 및 방법: 실험을 위해 7개의 니켈-크롬 다이를 제작하였다. 다이는 하악 제 1대구치를 치아 형성한 지대치 3D 모델을 바탕으로 제작되었다. 지대치는 1.5 mm 교합면 삭제를 시행하였고, 변연은 1.0 mm의 deep chamfer로 형성하였다. 이 지대치 형태를 바탕으로 지르코니아 블록(Luxen Zirconia)를 사용하여, 교합면 두께는 0.3 mm, 0.5 mm, 1.5 mm, 축면 두께는 0.3 mm, 0.5 mm, 1.0 mm로 설정한 63개의 지르코니아 크라운을 제작하였다. 이 크라운은 니켈 크롬 다이에 레진 시멘트를 이용하여 접착하였다. 그 다음, electronic universal testing machine을 사용하여 크라운이 파절될 때까지 load-to fracture 시험을 진행하였다. 이후 scanning electron microscope (SEM)를 사용하여 크라운의 파절 형태를 관찰하였다. 통계 분석을 위해 Two-way ANOVA 방법을 사용하였고, 이에 대하여 Tuckey HSD test로 사후 검정을 시행하였다(P < .05). 결과: 모든 지르코니아 크라운의 평균 파절 저항 값은 구치부의 평균 저작력보다 큰 값을 나타냈다. 또한 Two-way ANOVA 결과, 지르코니아 크라운의 교합면 두께와 축면 두께는 파절 저항에 통계적으로 유의한 영향을 미치는 것으로 나타났다(P < .05). 그러나, 지르코니아의 축면 두께가 0.5 mm 이상일 때, 파절 저항에 미치는 영향은 통계적으로 유의한 차이를 보이지 않았다. 나타난 파괴 양상은 균열의 전파 양상에 따라 크라운의 부분 파절 또는 완전 파절로 나타났다. 결론: 이번 연구의 한계 내에서, 극도로 감소된 두께를 가진 CAD-CAM 단일구조 지르코니아 크라운은 구치부 교합력을 견딜 수 있는 적절한 파절 저항을 보였다. 또한, 지르코니아 크라운의 교합면 두께와 축면 두께는 파절 저항에 유의미한 영향을 나타냈으며 복합적인 결과를 보였다.

• 해양환경안전학회지
• /
• 제29권5호
• /
• pp.417-426
• /
• 2023

세종기지가 위치한 마리안 소만은 기후 변화로 인한 빙하후퇴로 다량의 융빙수가 유입되고 있다. 이러한 빙하후퇴에 따른 생태계 반응을 예측하기 위해, 해양 환경 변화의 지시자인 식물플랑크톤 생체량 및 크기 구조와 물리, 화학적 매개변수에 대한 현장 조사를 2021년 12월, 2022년 1월 두 차례 수행하였다. 2022년 1월의 수온과 염분은 평균 1.41 ± 0.13 ℃, 33.9 ± 0.10 psu로 2021년 1월의 수온과 염분인 0.87 ± 0.17 ℃, 34.1 ± 0.12 psu보다 상대적으로 고온, 저염의 양상을 보였다. 조사시기 동안 영양염류는 대체로 높은 농도를 보여 식물 플랑크톤의 제한요소로 작용하지 않은 것으로 판단된다. 식물플랑크톤 생체량의 지표인 엽록소는 2021년 12월, 2022년 1월에 각각 1.03 ± 0.64 ㎍ L^-1, 0.66 ± 0.15 ㎍ L^-1로 나타났으며 부유물질은 전체 조사기간 평균 24.9 ± 3.54 mg L^-1로 나타났다. 부유물질의 농도가 높은 소만내측에서 엽록소는 낮은 농도를 보였는데 이는 융빙수로부터 유입되는 고농도의 부유물질로 인해 수층 내 빛이 강하게 제한되어 식물플랑크톤의 성장이 저해된 것으로 판단된다. 또한, 빙벽 주변 정점에서 크기가 작은 미소 식물플랑크톤이 전체 식물플랑크톤 생체량에서 70% 이상 차지하는 것으로 나타났으며 이는 융빙수 유입으로 유발된 저조도 환경에서 미소 식물플랑크톤의 기여도가 증가할 수 있음을 시사한다. 따라서 본 연구는 빙하후퇴 지역에서 유입되는 담수와 부유물질이 식물플랑크톤의 생체량 및 군집구조 조절 요인이 될 수 있음을 시사하며, 결과 자료는 추후 마리안 소만의 탄소순환 변동을 파악하는 기초자료로 활용될 수 있다.