• Hip & pelvis
• /
• v.36 no.2
• /
• pp.129-134
• /
• 2024

Purpose: Preoperative planning has become essential in performance of total hip arthroplasty (THA). However, data regarding the effect of the planner's experience on the accuracy of digital preoperative planning is limited. The objective of this study was to assess the accuracy of digital templating in THA based on the surgeon's experience. Materials and Methods: A retrospective study was conducted. An analysis of 98 anteroposterior pelvic radiographs, which were individually templated by four surgeons (two hip surgeons and two orthopaedic residents) using TraumaCad^® digital planning, was performed. A comparison of preoperatively planned sizes with implanted sizes was performed to evaluate the accuracy of predicting component size. The results of preoperative planning performed by hip surgeons and orthopaedic residents were compared for testing of the planner's experience. Results: Femoral stem was precisely predicted in 32.4% of cases, acetabular component in 40.3%, and femoral offset in 76.7%. Prediction of cup size showed greater accuracy than femoral size among all observers. No differences in any variable were observed among the four groups (acetabular cup P=0.07, femoral stem P=0.82, femoral offset P=0.06). All measurements showed good reliability (intraclass correlation coefficient [ICC] acetabular cup: 0.76, ICC femoral stem: 0.79). Conclusion: The results of this study might suggest that even though a surgeon's experience supports improved precision during the planning stage, it should not be restricted only to surgeons with a high level of experience. We consider preoperative planning an essential part of the surgery, which should be included in training for orthopaedics residents.

• Tribology and Lubricants
• /
• v.15 no.3
• /
• pp.257-264
• /
• 1999

Recently as electronics and semi-conductor industry develop, ultra-precision machine tools that use air-spindle with externally pressurized air bearing appear in need of ultra-precision products which demand high precision property. Effects of air compressibility absorbs the vibration of shaft, this is called averaging effect, however, the higher running accuracy is demanded by degrees, the more important factor is machining errors that affect running accuracy of shaft. Actually, it would be very important in the view points of running accuracy to understand effects of machining errors on the running accuracy of the spindle system quantitatively to design and manufacture precision spindle system in the aspect that efficiency in manufacturing spindle system and performance in operation. So fu, there are some researches on the effects that machining error affect running accuracy. However, because these researches deal with one bearing of spindle system, these results aren't enough to explain how much machining errors affect running accuracy in the typical spindle system overall. In this study, we investigate the effects of the perpendicularity error of bearing and shaft on running accuracy of spindle system that consists of journal and thrust bearing theoretically, and suggest design guideline about shape tolerances.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.1144-1149
• /
• 2003

It is very important to measure circular motion accuracy of NC lathes it affects accuracy, performance, interchange ability and quality of machine parts machined by the NC lathes in industries. So, in this study, measuring units system to measure circular motion accuracy two axes circular motion accuracy of NC lathes was composed of two optical linear scales installed on the z and x-axes of work coordinate system on NC lathe and a computer inserted with PC counter card enables to obtain measuring data. Here, ATC(Automatic Tool Changer) and moving part of linear scales are fixed with magnet bases in order to measure circular motion accuracy of the ATC of NC lathe. And next, computer software was developed in order to measure the circular motion accuracy of NC lathe under resolution of 0.1 $\mu\textrm{m}$ using two linear scales, and also computer softwares were developed so that measuring data could be modeled on plots and be analyzed numerically,

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.5
• /
• pp.415-423
• /
• 2020

GNSS (Global Navigation Satellite System) is mostly used for high-precise surveys due to its accuracy and efficiency. But this technique does not always fulfill the demanding accuracy in harsh operational environments such as urban canyon and forest. One of the remedies for overcoming this barrier is to compose a heterogeneous surveying network by adopting terrestrial measurements (i.e., distances and angles). Hence, this study dealt with the adjustment of heterogeneous surveying networks consisted of GNSS baseline vectors, distances, horizontal and vertical angles with a view to enhancing their accuracy and so as to derive an appropriate scheme of the measurement combination. Reviewing some technical issues of the network adjustments, the simulation, and experimental studies have been carried out, showing that the inclusion of the terrestrial measurements in the GNSS standalone overall increased the accuracy of the adjusted coordinates. Especially, if the distances, the horizontal angles, or both of them were simultaneously adjusted with GNSS baselines, the accuracy of the GNSS horizontal component was improved. Comparing the inclusion of the horizontal angles with those of the distances, the former has been more influential on accuracy than the latter even though the same number of measurements were employed in the network. On the other hand, results of the GNSS network adjustment together with the vertical angles demonstrated the enhancement of the vertical accuracy. As conclusion, this paper proposes a simultaneous adjustment of GNSS baselines and the terrestrial measurements for an effective scheme that overcomes the limitation of GNSS control surveys.

• International Journal of Computer Science & Network Security
• /
• v.24 no.5
• /
• pp.53-63
• /
• 2024

Alzheimer's disease is a brain disorder that worsens over time and affects millions of people around the world. It leads to a gradual deterioration in memory, thinking ability, and behavioral and social skills until the person loses his ability to adapt to society. Technological progress in medical imaging and the use of artificial intelligence, has provided the possibility of detecting Alzheimer's disease through medical images such as magnetic resonance imaging (MRI). However, Deep learning algorithms, especially convolutional neural networks (CNNs), have shown great success in analyzing medical images for disease diagnosis and classification. Where CNNs can recognize patterns and objects from images, which makes them ideally suited for this study. In this paper, we proposed to compare the performances of Alzheimer's disease detection by using two deep learning methods: You Only Look Once (YOLO), a CNN-enabled object recognition algorithm, and Visual Geometry Group (VGG16) which is a type of deep convolutional neural network primarily used for image classification. We will compare our results using these modern models Instead of using CNN only like the previous research. In addition, the results showed different levels of accuracy for the various versions of YOLO and the VGG16 model. YOLO v5 reached 56.4% accuracy at 50 epochs and 61.5% accuracy at 100 epochs. YOLO v8, which is for classification, reached 84% accuracy overall at 100 epochs. YOLO v9, which is for object detection overall accuracy of 84.6%. The VGG16 model reached 99% accuracy for training after 25 epochs but only 78% accuracy for testing. Hence, the best model overall is YOLO v9, with the highest overall accuracy of 86.1%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.21 no.1
• /
• pp.27-36
• /
• 2003

Generally, the latest acquisition method of geo-spatial informations in urban area is executed by generation of digital elevation model (DEM) and digital ortho image by digital photogrammetry method which is used large scale photo image. However, the biggest problem of this method is coarse accuracy of DEM which is automatically generated by digital photogrammetry workstation system. The coarse accuracy of DEM caused geo-spatial information in urban area to reduce of accuracy. Therefore, this study is purposed to increase of DEM accuracy which is applied to method terrain classification in urban area. As the results of this study, the proposed method of this study which is increased to accuracy of DEM by classification of terrain is better than accuracy of DEM which is automatically generated by digital photogrammetry workstaion system. And, the edge detection method which is proposed by this study is established to capability of 3D digital mapping in urban area.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.6 no.1
• /
• pp.109-124
• /
• 1996

This study was performed to evaluate the performance of three passive samplers made in U.S.A. Three passive samplers selected for this study included products made by 3M, Gilian, and SKC in U.S.A. Three organic solvents, such as toluene, trichloroethylene, and n-hexane which are used frequently in Korean industry were selected for the study. Conclusions obtained from this study are summarized as follows. 1. For toluene and trichloroethylene, the overall accuracy of the results from all of three products was within 25 %, which is the criteria recommended by the U.S. National Institute for Occupational Safety and Health (NIOSH). For n-hexane, the overall accuracy of the results from two products except 3M was exceeding 25 %. Thus 3M product showed the best accuracy among three products. 2. When passive samplers collected organic vapors were exposed to clean air for two hours, there were 12 - 16 % loss of organic vapors due to reverse diffusion in Gilian products. There was no significant loss in results from other two products. 3. Air velocity affected greatly on the performance of passive samplers which did not have permeation membrane. At high velocity, 100 cm/sec, accuracies of results from Gilian and SKC were 57 - 108 and 128 - 164 %, respectively. However, the results from 3M samplers, which contain permeation membrane, indicated accuracy below 25 %. 4. When passive samplers collected organic vapors for eight hours, the accuracy was reduced. Thus, it is recommended that passive samplers be used for less than four hours.

• Nutrition Research and Practice
• /
• v.15 no.5
• /
• pp.613-627
• /
• 2021

BACKGROUND/OBJECTIVES: Despite the widespread use of dietary assessment tools, the validity of food records has not been evaluated in Koreans. We assessed the accuracy of estimated food records and the effect of a short education session in young Korean women. SUBJECTS/METHODS: Thirty women (aged 18-23 yrs) each completed 3 food records during a controlled-feeding study. One educational session was provided on day 2 of the study. Food records were analyzed for the accuracy of food items and portion size estimation according to food group (grains; meat, fish, eggs, and beans; vegetables; fruit; dairy; and oils and sugars) and type of dish (rice, kimchi, soup, side dishes, spreads, beverages, and snacks). Reported food items were categorized as exact, close, or far matches, exclusions, or intrusions. Portion sizes were evaluated as accurate, similar, or inaccurate estimates, or missing. The means of days 2 and 3 were used to assess post-education results. Paired t-tests were performed to assess the effects of the education session. RESULTS: The mean percentages of exact matches, close matches, far matches, and exclusions on day 1 were 80.9%, 10.9%, 2.0%, and 6.2%, respectively, and mean intrusions observed were 0.1. The education session slightly increased the accuracy of recorded food items. The percentages of accurate, similar, and inaccurate estimates, and missing portion sizes were 11.7%, 19.8%, 12.2%, and 56.3%, respectively, at baseline. The percentage of missing portion size estimates decreased to 14.0% after the education session, resulting in an increase in the percentages of all other estimates. An increase was observed in the accuracy of reported portion sizes of vegetables, rice, and kimchi. CONCLUSIONS: In young Korean women, estimated food records are highly accurate for food items but not for portion size estimates without prior education. A short education session can improve the accuracy of portion size estimation.

• Korean Journal of Agricultural Science
• /
• v.49 no.3
• /
• pp.431-440
• /
• 2022

Hanwoo cattle are a unique and historical breed in Korea that have been genetically improved and maintained by the national evaluation and selection system. The aim of this study was to provide information that can help improve the accuracy of the estimated breeding values in Hanwoo cattle by showing the difference between the imputation reference chip platforms of genomic data and the scaling factor of the genetic relationship matrix (GRM). In this study, nine sets of data were compared that consisted of 3 reference platforms each with 3 different scaling factors (-0.5, 0 and 0.5). The evaluation was performed using MTG2.0 with nine different GRMs for the same number of genotyped animals, pedigree, and phenotype data. A five multi-trait model was used for the evaluation in this study which is the same model used in the national evaluation system. Our results show that the Hanwoo custom v1 platform is the best option for all traits, providing a mean accuracy improvement by 0.1 - 0.3%. In the case of the scaling factor, regardless of the imputation chip platform, a setting of -1 resulted in a better accuracy increased by 0.5 to 1.6% compared to the other scaling factors. In conclusion, this study revealed that Hanwoo custom v1 used as the imputation reference chip platform and a scaling factor of -0.5 can improve the accuracy of the estimated breeding value in the Hanwoo population. This information could help to improve the current evaluation system.

• Journal of Animal Science and Technology
• /
• v.65 no.4
• /
• pp.720-734
• /
• 2023

In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (M_e) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between M_e and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between M_e and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the M_e, the higher the accuracy of EBV.