Ideal Nasal Preferences: A Quantitative Investigation with 3D Imaging in the Iranian Population
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- Archives of Plastic Surgery
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- v.50 no.4
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- pp.340-347
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- 2023
Background Though in facial plastic surgery, the ideal nasal characteristics are defined by average European-American facial features known as neoclassical cannons, many ethnicities do not perceive these characteristics as suitable. Methods To investigate the preferences for nasofrontal angle, nasolabial angle, dorsal height, alar width, and nasal tip projection, manipulated pictures of one male and one female model were shown to 203 volunteer patients from a tertiary university hospital's facial plastic clinic. Results The most aesthetically preferred nasofrontal angles were 137.64 ± 4.20 degrees for males and 133.55 ± 4.53 degrees for females. Acute nasofrontal angles were more desirable in participants aged 25 to 44. The most preferred nasolabial angles were 107.56 ± 5.20 degrees and 98.92 ± 4.88 degrees, respectively. Volunteers aged 19 to 24 preferred more acute male nasolabial angles. A straight dorsum was the most desirable in both genders (0.03 ± 0.78 and 0.26 ± 0.75 mm, respectively). The ideal male and female alar widths were -0.51 ± 2.26 and -1.09 ± 2.18 mm, respectively. More 45- to 64-year-old volunteers preferred alar widths equal to intercanthal distance. The ideal female and male tip projections were 0.57 ± 0.01 and 0.56 ± 0.01, respectively. Conclusion Results indicate that the general Iranian patients prefer thinner female noses with wider nasofrontal angles for both genders. However, the ideal nasolabial angles, dorsal heights, and tip projections were consistent with the neoclassical cannons. Besides ethnic differences, the trend of nasal beauty is also affected by gender, age, and prior history of aesthetic surgery.
The purpose of this study was to elucidate the size and morphologic characteristics of maxillary primary first molars in Korean children using three-dimensional laser scanner and compare three-dimensional image with preformed stainless steel crown. Scanned three-dimensional images of dental cast taken from 132 children(male 62, female 70) by three-dimensional laser scanner(Breuckmann opto-Top HE100, INUS, Korea) were used. Mesiodistal diameter, buccolingual diameter, occlusogingival height and crown shape of each image were calculated by Rapidform 2004 program(INUS, Korea). The values were statistically compared by independent samples t-test with 95% of significant level. The results were as follows : 1. No significant difference in crown size was found between left and right maxillay primary first molar(p>0.05). 2, Significant difference in mesiodistal diameter, buccolingual diameter, buccal occlusogingival height was found between male and female (p<0.05), and crown size of male was bigger than that of female. 3. Average image of maxillay primary first molar was shaped three-dimensionally and measured. In comparison with 3M stainless steel crown, this image was similar with No.4 or No.5 SS crown in male, No.4 in female. In comparison with ILSUNG SS crown, this image was similar with No.5 in male, No.4 in female. 4 Mesiolingual line angle area, distolingual line angle area and buccogingival ridge were more obvious in average image than 3M stainless steel crown. ILSUNG SS crown was more square and had longer mesiodistal diameter than average 3D image.
Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.
Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.
We present the results of far-ultraviolet (FUV) observations of comet C/2001 Q4 (NEAT) obtained with Far-ultraviolet Imaging Spectrograph (FIMS) on board the Korean microsatellite STSAT-1, which operated at an altitude of 700 km in a sun-synchronous orbit. FIMS is a dual channel imaging spectrograph (S-channel 900-1150
In this paper, an automatic mobile robot system for a intelligent path planning using the detection scheme of the spatial coordinates based on stereo camera is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity map obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation. From some experiments on robot driving with 240 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the mobile robot and the objects, and relative distance between the other objects is found to be very low value of
Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN(Convolutional Neural Network), which is known as the effective solution for recognizing and classifying images or voices, has been popularly applied to classification and prediction problems. In this study, we investigate the way to apply CNN in business problem solving. Specifically, this study propose to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. As mentioned, CNN has strength in interpreting images. Thus, the model proposed in this study adopts CNN as the binary classifier that predicts stock market direction (upward or downward) by using time series graphs as its inputs. That is, our proposal is to build a machine learning algorithm that mimics an experts called 'technical analysts' who examine the graph of past price movement, and predict future financial price movements. Our proposed model named 'CNN-FG(Convolutional Neural Network using Fluctuation Graph)' consists of five steps. In the first step, it divides the dataset into the intervals of 5 days. And then, it creates time series graphs for the divided dataset in step 2. The size of the image in which the graph is drawn is
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
DEM(Digital Elevation Model) is used widely in image processing, water resources, construction, GIS, landscape architecture, telecommunication, military operations and other related areas. And it is used especially in producing ortho-photo based on specific DEM and developing 3D GIS database vividly. As LiDAR(Light and Detection And Ranging) system emerged recently, DEM could be developed in urban area more efficiently and more economically, compared to the conventional DEM Production. Traditional method using check points for elevation has tome limitations in structure's height accuracy by LiDAR, because it uses only terrain height. Accordingly after the downtown of Chungju city was selected as a test field in this paper and DEM and digital ortho images was produced by way of LiDar survey, the accuracy was evaluated through analytical plotting map. The result shows that in case of buildings in LiDAR DEM, the accuracy is 0.30 m in X, 0.62 m in Y and RMS is 1.17 m. The difference distribution between DEM and plotting map in range of