• The korean journal of orthodontics
• /
• v.41 no.4
• /
• pp.268-279
• /
• 2011

Objective: The purpose of this study was to compare self-drilling orthodontic mini-implants of different surfaces, namely, machined (untreated), etched (acid-etched), RBM (treated with resorbable blasting media) and hybrid (RBM + machined), with respect to the following criteria: physical appearance of the surface, measurement of surface roughness, and insertion pattern. Methods: Self-drilling orthodontic mini-implants (Osstem implant, Seoul, Korea) with the abovementioned surfaces were obtained. Surface roughness was measured by using a scanning electron microscope and surface-roughness-testing machine, and torque patterns and vertical loadings were measured during continuous insertion of mini-implants into artificial bone (polyurethane foam) by using a torque tester of the driving-motor type (speed, 12 rpm). Results: The mini-implants with the RBM, hybrid, and acid-etched surfaces had slightly increased maximum insertion torque at the final stage ($p$ < 0.05). Implants with the RBM surface had the highest vertical load for insertion ($p$ < 0.05). Testing for surface roughness revealed that the implants with the RBM and hybrid surfaces had higher Ra values than the others ($p$ < 0.05). Scanning electron microscopy showed that the implants with the RBM surface had the roughest surface. Conclusions: Surface-treated, self-drilling orthodontic mini-implants may be clinically acceptable, if controlled appropriately.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.11
• /
• pp.183-190
• /
• 2012

Conventional physical activity monitoring systems, which use accelerometers, global positioning system (GPS), heartbeats, or body temperature information, showed limited performances due to their own restrictions on measurement environment and measurable activity types. To overcome these limitations, we developed a portable exercise analysis system that can analyze aerobic exercises as well as isotonic exercises. For bioelectric signal acquisition during exercise, waist belt with two body contact electrodes was used. For exercise analysis, the measured signals were firstly divided into two signal groups with different frequency ranges which can represent respiration related signal and muscular motion related signal, respectively. After then, power values, differential of power values, and median frequency values were selected for feature values. Selected features were used as inputs of support vector machine (SVM) to classify the exercise types. For verification of statistical significance, ANOVA and multiple comparison test were performed. The experimental results showed 100% accuracy for classification of aerobic exercise and isotonic resistance exercise. Also, classification of aerobic exercise, isotonic resistance exercise, and hybrid types of exercise revealed 92.7% of accuracy.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1996.06c
• /
• pp.283-292
• /
• 1996

This study was performed to determine the physical properties of rice hull and straw which could be used for an optimum design and operation of the handling facilities for these rice crop by-products. The properties measured were kinetic friction coefficient , bulk density, and dynamic and static angle of repose. Rice hulls with moisture content of 13% and 21% were used throughout the test while rice straws of 10% and 16% moisture were chopped into 10mm length and used for the test. Friction coefficient was calculated from the horizontal traction forces measurement when a container holding the mass of rice hull and straw was pulled over mild steel. PVC, stainless steel, and galvanized steel surface by a universal testing machine. Bulk density was measured by an apparatus consisting of filling fundel and a receiving vessel. Dynamic angle of repose which is the angle at which the material will stand when piled was calculated from the photos of bulk samples after they were flowed by gravity and accumulated on a circular surface. Static angle of repose which is the angle between the horizontal and the sloping side of the material left in the container when discharging was also measured in the similar way. Results and conclusions from this study are summarized as follows . 1. Kinetic friction coefficient of both rice hull and straw were in the range of 0.26 -0.52 and increased with the moisture content. The magnitude of friction increased in the order of galvanized steel, stainless steel, PVC ,and mild steel. 2. Bulk densities of rice hull decreased while those of rice straw increased with moisture content increase . Average bulk densities of rice hull and straw were 96.8 and 74.7kg/㎥, respectively. 3. Average dynamic angle of repose for rice straw was 32.6$^{\circ}$ and those for 13% and 21% moisture rice hull were 38.9$^{\circ}$ and 44.9$^{\circ}$ , respectively. 4. Static angles of repose for both rice hull and straw showed increase with the moisture content. The values were 75.2\ulcorner and 80.2$^{\circ}$ for 13% and 21% moisture rice hull, respectively. Rice straws having 10% and 16% moisture content showed 87.3% and 89.2$^{\circ}$ static angle of repose, respectively.

• Progress in Medical Physics
• /
• v.12 no.2
• /
• pp.147-153
• /
• 2001

We have discussed that the total body irradiation(TBI) dose distribution of 6 and 10 MV photon beams, also differences between calculation dose use of compensator sheet and measurements in humanoid phantom. Total body irradiation and hemi-body irradiation(HBI) can be effectively performed when uniformity of dose distribution is estabilished. The method of TBI and HBI dosimatry requires special considerations related to technique, long distance and very large field, machine parameter, patient positioning. TBI and HBI with megavoltage photon beams requires basic dosimatric data which have to be measured directly or derived from the standard beam data. The semiconductor detector and ion chamber were positioned at a dmax depth, mid depth, and its specific ratio was determined using a scanning data by RFA-7 3-dimensional water phantom and solid phantom. The effective source axis distance 380 cm, the field size from 120 cm to 152 cm, isodose distributions were analyzed as a function of the thickness in phantom. Also, have discussed that the measurement of basic data for clinical photon beams for dosage calculations, data calculation sheet and the use of tissue compensation to improve dose uniformity. We have improved a dose uniformity in the TBI and HBI method.

• Journal of the Korea Concrete Institute
• /
• v.26 no.6
• /
• pp.679-686
• /
• 2014

In this research, the mix proportion of the antiwashout underwater concrete with the mineral admixture was evaluated. It can reduce the amount used of the antiwashout admixture (hereinafter referred to as "AWA") and satisfy the properties of concrete. In addition, the review for the difference of the test and practical affairs were conducted. Optimized unit quantity of water of antiwashout underwater concrete and the amount used of AWA was revealed by $190kg/m^3$, 0.9%/W, respectively. In particularly, the mix design is reduced by 5% than the W/B of target strength even though the W and AWA reduced. Therefore, it will have the economical feasibility and qualities including the material separation, resistance characteristic and compressive strength, and etc. The stable value was shown in 1 point of minute passed in the measurement of the turbidity amounts using the turbidimeter after the checker insertion. However, it needs to be reviewed for the interrelationship between turbidity measuring machine and KCI-AD102 standard method. There were no significant differences of compressive strength of specimens in the water depending on the production methods.

• Journal of Convergence for Information Technology
• /
• v.11 no.11
• /
• pp.57-65
• /
• 2021

We propose a novel method to detect abnormal data of specific symptoms using deep learning in air pollution measurement system. Existing methods generally detect abnomal data by classifying data showing unusual patterns different from the existing time series data. However, these approaches have limitations in detecting specific symptoms. In this paper, we use DeepLab V3+ model mainly used for foreground segmentation of images, whose structure has been changed to handle one-dimensional data. Instead of images, the model receives time-series data from multiple sensors and can detect data showing specific symptoms. In addition, we improve model's performance by reducing the complexity of noisy form time series data by using 'piecewise aggregation approximation'. Through the experimental results, it can be confirmed that anomaly data detection can be performed successfully.

• Food Engineering Progress
• /
• v.14 no.4
• /
• pp.322-327
• /
• 2010

Wheat is widely used in food industry because of its low price, convenience, protein-rich resource, easy processibility, and so on. However, people who have wheat-gluten allergy need gluten-free products. Especially, gluten-free products are desirable to early childhood even though they may or may not be sensitive to wheat-gluten. As the alternative of wheat flour, recently, rice flour is gaining popularity. Hence, we developed the puffed rice snack for the baby. In order to prepare for rice extrudate, 1 kg rice flour, 450 g water, and 6 g salt were mixed together and then steamed for 1 hr. The rice extrudate was shredded into pieces (0.5 cm${\times}$0.5 cm) and dried up to 4.5% moisture content. The dried rice shreds were puffed at $257^{\circ}C$ in a puffing machine. The puffed rice snack was oval-shaped having thickness of 0.5 cm, white in color with brown flakes. Appearance and texture of the puffed rice snacks were evaluated by the measurement of the texture, isothermal water absorption, expansion, and the color. Puffed rice was more porous, because rice increased up to about two times larger than its original volume. Texture of the rice puffing snack was suitable for early childhood. Rice puffing snack showed potentials including soft, low-allergenic, and easily digestible properties. It is concluded that rice puffing snack has potential in the food markets for early childhood.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.29 no.1
• /
• pp.24-35
• /
• 2023

Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.116-116
• /
• 2021

자연 하천에서의 부유사 농도 계측은 주로 재래식 채집방식을 활용한 직접계측 방식에 의존하여 비용과 시간이 많이 소요되며 점 계측 방식으로 고해상도의 시공간 자료를 측정하기엔 한계가 존재한다. 이러한 한계점을 극복하기 위해 최근 위성영상과 드론을 활용하여 촬영된 다분광 혹은 초분광 영상을 통해 고해상도의 부유사 농도 시공간분포를 측정하는 기법에 대한 연구가 활발히 진행되고 있다. 하지만, 다른 하천 물리량 계측에 비해 부유사 계측 연구는 하천에 따라 부유사가 비균질적으로 분포하여 원격탐사를 통해 정확하고 전역적인 농도 분포를 재현하기는 어려운 실정이다. 이러한 부유사의 비균질성은 부유사의 입도분포, 광물특성, 침강성 등이 하천에서 다양하게 분포하기 때문이며 이로 인해 부유사는 지역별로 다양한 분광특성을 가지게 된다. 따라서, 본 연구에서는 이러한 영향을 고려한 전역적인 부유사 농도 예측 모형을 개발하기 위해 실내 실험을 통해 부유사 특성별 고유 분광 라이브러리를 구축하고 실규모 수로에서 다양한 부유사 조건에 대한 초분광 스펙트럼과 부유사 농도를 측정하는 실험을 수행하였다. 실제 부유사 농도는 광학 기반 센서인 LISST-200X와 샘플링을 통한 실험실 분석을 통해 계측되었으며, 초분광 스펙트럼 자료는 초분광 카메라를 통해 촬영한 영상에서 부유사 계측 지점에 대한 픽셀의 스펙트럼을 추출하여 구축하였다. 이렇게 생성된 자료들의 분광 다양성을 주성분 분석(Principle Component Analysis; PCA)를 통해 분석하였으며, 부유사의 입도 분포, 부유사 종류, 수온 등과의 상관관계를 통해 분광 특성과 가장 상관관계가 높은 물리적 인자를 규명하였다. 더불어 구축된 자료를 바탕으로 기계학습 기반 주요 특징 선택 알고리즘인 재귀적 특징 제거법 (Recursive Feature Elimination)과 기계학습기반 회귀 모형인 Support Vector Regression을 결합하여 초분광 영상 기반 부유사 농도 예측 모형을 개발하였으며, 이 결과를 원격탐사 계측 연구에서 일반적으로 사용되어 오던 최적 밴드비 분석 (Optimal Band Ratio Analysis; OBRA) 방법으로 도출된 회귀식과 비교하였다. 그 결과, 기존의 OBRA 기반 방법은 비선형성을 증가시켜도 좁은 영역의 파장대만을 고려하는 한계점으로 인해 부유사의 다양한 분광 특성을 반영하지 못하였으며, 본 연구에서 제시한 기계학습 기반 예측 모형은 420 nm~1000 nm에 걸쳐 폭 넓은 파장대를 고려함과 동시에 높은 정확도를 산출하였다. 최종적으로 개발된 모형을 적용해 다양한 유사 조건에 대한 부유사 시공간 분포를 매핑한 결과, 시공간적으로 고해상도의 부유사 농도 분포를 산출하는 것으로 밝혀졌다.

• Korean Chemical Engineering Research
• /
• v.62 no.3
• /
• pp.274-280
• /
• 2024

Machine learning techniques utilizing neural networks have been employed in various fields such as disease gene discovery and diagnosis, drug development, and prediction of drug-induced liver injury. Disease features can be investigated by molecular information of DNA. In this study, we developed a neural network to predict the length of DNA and the number of DNA species in mixture solution which are representative molecular information of DNA. In order to address the time-consuming limitations of gel electrophoresis as conventional analysis, we analyzed the dynamic data of a microfluidic concentrating device. The dynamic data were reconstructed into a spatiotemporal map, which reduced the computational cost required for training and prediction. We employed a convolutional neural network to enhance the accuracy to analyze the spatiotemporal map. As a result, we successfully performed single DNA length prediction as single-variable regression, simultaneous prediction of multiple DNA lengths as multivariable regression, and prediction of the number of DNA species in mixture as binary classification. Additionally, based on the composition of training data, we proposed a solution to resolve the problem of prediction bias. By utilizing this study, it would be effectively performed that medical diagnosis using optical measurement such as liquid biopsy of cell-free DNA, cancer diagnosis, etc.