• Restorative Dentistry and Endodontics
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• v.44 no.1
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• pp.5.1-5.9
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• 2019

Objectives: The aim of this in vitro study was to evaluate the push-out bond strength of a novel calcium silicate-based root repair material-BIOfactor MTA to root canal dentin in comparison with white MTA-Angelus (Angelus) and Biodentine (Septodont). Materials and Methods: The coronal parts of 12 central incisors were removed and the roots were embedded in acrylic resin blocks. Midroot dentin of each sample was horizontally sectioned into 1.1 mm slices and 3 slices were obtained from each root. Three canal-like standardized holes having 1 mm in diameter were created parallel to the root canal on each dentin slice with a diamond bur. The holes were filled with MTA-Angelus, Biodentine, or BIOfactor MTA. Wet gauze was placed over the specimens and samples were stored in an incubator at $37^{\circ}C$ for 7 days to allow complete setting. Then samples were subjected to the push-out test method using a universal test machine with the loading speed of 1 mm/min. Data was statistically analyzed using Friedman test and post hoc Wilcoxon signed rank test with Bonferroni correction. Results: There were no significant differences among the push-out bond strength values of MTA-Angelus, Biodentine, and BIOfactor MTA (p > 0.017). Most of the specimens exhibited cohesive failure in all groups, with the highest rate found in Biodentine group. Conclusions: Based on the results of this study, MTA-Angelus, Biodentine, and BIOfactor MTA showed similar resistances to the push-out testing.

• Journal of Dental Anesthesia and Pain Medicine
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• v.21 no.4
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• pp.345-355
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• 2021

Background: This study aimed to evaluate the efficacy of external vibrating devices and counterstimulation on a child's dental anxiety, apprehension, and pain perception during local anesthetic administration. Methods: This was a prospective, randomized, parallel-arm, single-blinded interventional, clinical trial. One hundred children aged 4-11 years, requiring pulp therapy or extraction under local anesthesia (LA), were recruited and allocated equally into two groups (1:1) based on the interventions used: Group BD (n = 50) received vibration using a Buzzy^® device {MMJ Labs, Atlanta, GE, USA} as a behavior guidance technique; Group CS (n = 50) received counterstimulation for the same technique. Anxiety levels [Venham's Clinical Anxiety Rating Scale (VCARS), Venham Picture Test (VPT), Pulse oximeter {Gibson, Fingertip Pulse Oximeter}, Beijing, China)] were assessed before, during, and after LA administration, while pain perception [Wong-Baker Faces Pain Rating Scale (WBFPS), Visual Analogue Scale (VAS)] was evaluated immediately after injection. Statistical analysis was performed using the Student's t-test to assess the mean difference between the two groups and the repeated measures ANOVA for testing the mean difference in the pulse rates. Statistical significance was set at P < 0.05. Results: Significant differences in mean pulse rate values were observed in both groups. In contrast, the children in the BD group had higher diminution (P < 0.05), whereas the mean VCARS and VPT scores were conspicuous (P < 0.05). Based on the mean WBFPS and VAS scores, delayed pain perception after LA injection was more prominent in the BD group than in the CS group. Conclusion: External vibration using a Buzzy^® device is comparatively better than counterstimulation in alleviating needle-associated anxiety in children requiring extraction and pulpectomy.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.415-421
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• 2023

In this study, the piezoresistive properties of cementitious composites enhanced with carbon nanotubes for improved electrical conductivity were analyzed using a deep learning-based transformer algorithm. Experimental execution was performed in parallel for acquisition of training data. Previous studies on mixture design, specimen fabrication, chemical composition analysis, and piezoresistive performance testing are also reviewed in this paper. Notably, specimens in which fly ash substituted 50% of the binder material were fabricated and evaluated in this study, in addition to carbon nanotube-infused specimens, thereby exploring the potential enhancement of piezoresistive characteristics in conductive cementitious materials. The experimental results showed more stable piezoresistive responses in specimens with fly-ash substituted binder. The transformer model was trained using 80% of the gathered data, with the remaining 20% employed for validation. The analytical outcomes were generally consistent with empirical measurements, yielding an average absolute error and root mean square error between 0.069 to 0.074 and 0.124 to 0.132, respectively.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Korean Journal of Optics and Photonics
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• v.26 no.3
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• pp.162-167
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• 2015

In this paper, we developed a MTF (Modulation Transfer Function) measurement system using a knife-edge scanning method for infrared optics. It consists of an objective part to generate the target image, a collimator to make the beam parallel, and a detector to analyze the image. We used a tungsten filament as the light source and MCT (Mercury Cadmium Telluride) to detect the mid-infrared(wavelength $3-5{\mu}m$) image. We measured the MTF of a standard lens (f=5, material ZnSe) to test this instrument and compared the result to the theoretical value calculated using the ZEMAX commercial software. It was found that the difference was within ${\pm}0.035$ at the cut-off frequency (50 1/mm). Also, we calculated the A-type measurement uncertainty to check the reliability of the measurement. The result showed only 0.002 at 20 1/mm in spatial frequency, which means very little variation in the MTF measurement under the same conditions.

• Journal of the Microelectronics and Packaging Society
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• v.24 no.4
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• pp.73-77
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• 2017

Recently, fingerprint sensors have widely used for personal information security, and require quality evaluation to reduce an error of their recognition rate. Quality of fingerprint sensors is evaluated by variation of their electrical resistance introducing by contacts between a probe tip and a sensor electrode, Investigation on the materials compatability and structure optimization of probe is required to reduce deformation of sensor electrode for repeatability of quality testing. Nickel, steel(SK4), beryllium copper, and phosphor bronze were considered as probe materials, and beryllium copper was the most appropriate for materials of probe tips, considering indentation and contact resistance while being contacted probe tips on electrodes. Probes of an inspection part were manufactured with the single-unit structure for physical damage prevention and parallel processing capability. Inspection repeatability was evaluated by voltage variation of fingerprint sensors when the specific current was applied. A single-unit inspection part with beryllium copper probe tips showed excellent repeatability within ${\pm}0.003V$ of its voltage variation.

• Journal of the Korea Concrete Institute
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• v.14 no.5
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• pp.796-803
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• 2002

T-shaped walls have different strength, stiffness and ductility in the two opposite directions parallel to the web when subjected to horizontal in-plane loads. When the flange is in tension, the extent that the flange reinforcement contributes to the flexural strength will be subjected to shear-lag effect. Because of this shear-lag effect, the flange may not participate fully in the action with the web, and the effective flange width is needed for predicting the actual strength and stiffness of structures. The objective of this paper is to evaluate the effective flange width and actual strength of the T-shaped wall with Korean code specified detailing of the wall web. Three specimens were tested with cyclic lateral loading applied at top of the wall. A constant axial load of approximately 0.1f$\_$ck/$.$A$\_$g/ is maintained during the testing. Test results show that the effective flange width increases with increasing drift level, such that the entire overhanging flange of h/3 is effective at the maximum strength level. Therefore, the use of PCI or KBC(Korean Building Code) value of h/10 is unconservative with respect to detailing at the wall web boundary.

• Journal of the Mineralogical Society of Korea
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• v.16 no.1
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• pp.19-31
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• 2003

Chemical composition, crystal structure, refractive index, specific gravity, color, and luster were studied fur pyrope-almandine series garnets. The main coloring agents determining the reddish or brownish garnets were also investigated. It was also examined if there is any relationship between mineralogical properties with respect to the various chemical compositions in the solid solution, in the hope to figure out the existing classification values of R.I. and S.G. using gem- testing facilities to distinguish pyrope from almadine. It was found that 17 out of the 24 specimens belong to pyrope and the rest almandine. R.I. of pyrope goes up to 1.77 and that of almandine is higher than the value.5.5. of pyrope reaches to 3.88 and that of almandine is greater than the value of pyrope. X-ray diffraction data revealed that pyrope-almandine garnets are isometric with space group Ia3d, and also show that the variation of cell parameters are not significant enough to parallel with the chemical compositions of the series. R.I. and S.G. increase with FeO content. Fe and Mn are most responsible to the red-purple and orange coloration of the specimens, respectively. Both zircon and rutile crystals are most common inclusions in the reddish stones.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1000-1015
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• 2010

In this paper, we propose a novel algorithm for hand gesture recognition. The hand detection method is based on human skin color, and we use the boundary energy information to locate the hand region accurately, then the moment method will be employed to locate the hand palm center. Hand gesture recognition can be separated into 2 step: firstly, the hand posture recognition: we employ the parallel NNs to deal with problem of hand posture recognition, pattern of a hand posture can be extracted by utilize the fitting ellipses method, which separates the detected hand region by 12 ellipses and calculates the white pixels rate in ellipse line. the pattern will be input to the NNs with 12 input nodes, the NNs contains 4 output nodes, each output node out a value within 0~1, the posture is then represented by composed of the 4 output codes. Secondly, the hand gesture tracking and recognition: we employed the Kalman filter to predict the position information of gesture to create the position sequence, distance relationship between positions will be used to confirm the gesture. The simulation have been performed on Windows XP to evaluate the efficiency of the algorithm, for recognizing the hand posture, we used 300 training images to train the recognizing machine and used 200 images to test the machine, the correct number is up to 194. And for testing the hand tracking recognition part, we make 1200 times gesture (each gesture 400 times), the total correct number is 1002 times. These results shows that the proposed gesture recognition algorithm can achieve an endurable job for detecting the hand and its' gesture.

• KSBB Journal
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• v.30 no.2
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• pp.58-62
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• 2015

A 3-weeks feeding trial with 288 laying hens were conducted to determine the efficacy of lecithin-free egg yolk at different levels of dietary Ca on performance and Ca absorption. Laying hens were divided into 6 groups according to calcium level and testing agent; 0% calcium feed (A), 0.2% calcium feed (B), 0.4% calcium feed (C, normal feed), 0.6% calcium feed (D), 0.4% calcium feed + 0.2% egg byproduct (C+0.2), 0.4% calcium feed + 0.4% egg byproduct (C+0.4). The final body weight gain of C+0.2 and C+0.4 groups were higher by 1.5% and 7.4% respectively than group C. Tibia ash contents did not show significantly difference, but calcium contents increase (p<0.05) in C+0.2 and C+0.4 groups. Parallel undecalcified tibia joint sections were stained for calcium absorption by the von Kossa's stain. This result show that lecithin free egg byproduct supplementation to normal calcium feed improved growth performance and calcium utilization in laying hens.