• Journal of Software Assessment and Valuation
• /
• v.14 no.2
• /
• pp.1-9
• /
• 2018

The proportion of users and companies using open source continues to grow. The size of open source software market is growing rapidly not only in foreign countries but also in Korea. However, compared to the continuous development of open source software, there is little research on open source software subject classification, and the classification system of software is not specified either. At present, the user uses a method of directly inputting or tagging the subject, and there is a misclassification and hassle as a result. Research on open source software classification can also be used as a basis for open source software evaluation, recommendation, and filtering. Therefore, in this study, we propose a method to classify open source software by using machine learning model and propose performance comparison by machine learning model.

• Journal of Biomedical Engineering Research
• /
• v.44 no.5
• /
• pp.346-353
• /
• 2023

In this paper, we propose an innovative approach that leverages deep learning to find optimal reference points for achieving precise tooth segmentation in three-dimensional tooth point cloud data. A dataset consisting of 350 aligned maxillary and mandibular cloud data was used as input, and both end coordinates of individual teeth were used as correct answers. A two-dimensional image was created by projecting the rendered point cloud data along the Z-axis, where an image of individual teeth was created using an object detection algorithm. The proposed algorithm is designed by adding various modules to the Unet model that allow effective learning of a narrow range, and detects both end points of the tooth using the generated tooth image. In the evaluation using DSC, Euclid distance, and MAE as indicators, we achieved superior performance compared to other Unet-based models. In future research, we will develop an algorithm to find the reference point of the point cloud by back-projecting the reference point detected in the image in three dimensions, and based on this, we will develop an algorithm to divide the teeth individually in the point cloud through image processing techniques.

• Current Optics and Photonics
• /
• v.8 no.1
• /
• pp.38-44
• /
• 2024

Under the influence of atmospheric turbulence, a star's point image will shake back and forth erratically, and after exposure the originally small star point will spread into a huge spot, which will affect the ground calibration of the star sensor. To analyze the impact of atmospheric turbulence on the positioning accuracy of the star's center of mass, this paper simulates the atmospheric turbulence phase screen using a method based on a sparse spectrum. It is added to the static-star-simulation device to study the transmission characteristics of atmospheric turbulence in star-point simulation, and to analyze the changes in star points under different atmospheric refractive-index structural constants. The simulation results show that the structure function of the atmospheric turbulence phase screen simulated by the sparse spectral method has an average error of 6.8% compared to the theoretical value, while the classical Fourier-transform method can have an error of up to 23% at low frequencies. By including a simulation in which the phase screen would cause errors in the center-of-mass position of the star point, 100 consecutive images are selected and the average drift variance is obtained for each turbulence scenario; The stronger the turbulence, the larger the drift variance. This study can provide a basis for subsequent improvement of the ground-calibration accuracy of a star sensitizer, and for analyzing and evaluating the effect of atmospheric turbulence on the beam.

• Resources Recycling
• /
• v.19 no.4
• /
• pp.41-50
• /
• 2010

A fundamental study was carried out to develop a process for recycling tungsten and cobalt from WC-Co hardmetal sludge generated in the manufacturing process of hardmetal tools. The complete extraction of cobalt and simultaneous formation of tungstic was achieved by treating the sludge using aqua regia. The effect of aqua regia concentration, reaction temperature and time, pulp density on cobalt leaching and tungstic acid formation was investigated. The complete leaching of cobalt was attained at the optimum conditions: 100 vol.% aqua regia concentration, $100^{\circ}C$ temperature, 60 min. reaction time and 400 g/L pulp density. A complete conversion of tungsten carbide of the sludge to tungstic acid was however, obtained at the pulp densities lower than 150 g/L under the above condition. The progress of reaction during the aqua regia treatment of the sludge was monitored through the XRD phase identification of the residue. The metallic impurities in the tungstic acid so produced could be further removed as insoluble residues by dissolving the tungsten values in ammonia solution. The ammonium paratungstate($(NH_4)_{10}{\cdot}H_2W_{12}O_{42}{\cdot}4H_2O$) of 99.85% purity was prepared from the ammonium polytungstate solution by the evaporation crystallization method.

• Journal of the Korean Institute of Telematics and Electronics D
• /
• v.36D no.10
• /
• pp.9-16
• /
• 1999

When the conventional IPD (inter-poly-dielctrics) layer with ONO(oxide-nitride-oxide) structure was used in the Flash EEPROM cell, its data retention characteristics were significanfly degraded because the top oxide of the ONO layer was etched off due to the cleaning process used in the gate oxidation process for the peripheral MOSFETs. When the IPD layer with the ONON(oxide-nitride-oxide-nitride) was used there, however, its data retention characteristics were much improved because the top nitride of the ONON layer protected the top oxide from being etched in the cleaning process. For the modelling of the data retention characteristics of the Flash EEPROM cell with the ONON IPD layer, the decrease of the threshold voltage cue to the charge loss during the bake was here given by the empirical relation ${\Delta}V_t\; = \;{\beta}t^me^{-ea/kT}$ and the values of the ${\beta}$=184.7, m=0.224, Ea=0.31 eV were obtained with the experimental measurements. The activation energy of 0.31eV implies that the decrease of the threshold voltage by the back was dur to the movement of the trapped electrons inside the inter-oxide nitride layer. On the other hand, the results of the computer simulation using the model were found to be well consistent with the results of the electrical measurements when the thermal budget of the bake was not high. However, the latter was larger then the former in the case of the high thermal budger, This seems to be due to the leakage current generated by the extraction of the electrons with the bake which were injected into the inter-oxide niride later and were trapped there during the programming, and played the role to prevent the leakage current. To prevent the generation of the leakage current, it is required that the inter-oxide nitride layer and the top oxide layer be made as thin and as thick as possible, respectively.

• Maxillofacial Plastic and Reconstructive Surgery
• /
• v.27 no.1
• /
• pp.1-8
• /
• 2005

This study was aimed to characterize osteogenic potential of rat bone marrow stromal cells (BMSC) isolated with standard flushing method and investigate the plasticity of transdifferentiation between osteoblastic and adipocytic lineage of cultured BMSC. Unlike aspiration method in human, rat bone marrow was extracted by means of irrigation with culture media that elevates the possibility of co-extraction of committed osteoprogenitor, or preosteoblast or other progenitor cells of several types present inside bone marrow. The cultured stromal cells showed high ALP activity which is representative marker of osteoblast without any treatment. Osteogenic inducers such as Dex and BMP-2 were examined for the evaluation of their effect on osteogenic and adipocytic differentiation of stromal cells, because they function as osteoinductive agent in stromal cells, but simultaneously induce adipogenic differentiation. Osteogenic differentiation was evaluated by measuring alkaline phosphatase activity or mRNA expression of osteoblast markers such as osteopontin, bone sialoprotein, collagen type I and CbfaI, and in vitro matrix mineralization by von Kossa staining. Oil red staining method was used to detect adipocyte and adipocytic marker, aP2 and $PPAR{\gamma}2$ expression was examined using RT-PCR. It can be supposed that irrigation procedure resulted in high portion of already differentiation-committed osteoprogenitor cell showing elevated ALP activity and strong mineralization only under the supplement of $100{\mu}M$ ascorbic 2-phosphate and 10mM ${\beta}$-glycerophosphate without any treatment of osteogenic inducers such as Dex and BMP-2. Dex and BMP-2 seemed to transdifferentiate osteoprogenitor cells having high ALP activity into adipocytes temporarily, but continuous treatment redifferentiated into osteoblast and developed in vitro matrix mineralization. This property must be considered either in tissue engineering for bone regeneration, or in research of characterization of osteogenic differentiation, with rat BMSC isolated by the standard irrigation method.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.10
• /
• pp.150-161
• /
• 2013

This paper presents a new system which produces high resolution 3D contents by capturing multiview images of an object using multiple cameras, and estimating geometric and texture information of the object from the captured images. Even though a variety of multiview image-based 3D reconstruction systems have been proposed, it was difficult to generate high resolution 3D contents because multiview image-based 3D reconstruction requires a large amount of memory and computation. In order to reduce computational complexity and memory size for 3D reconstruction, the proposed system predetermines the regions in input images where an object can exist to extract object boundaries fast. And for fast computation of a visual hull, the system represents silhouettes and 3D-2D projection/back-projection relations by chain codes and 1D homographies, respectively. The geometric data of the reconstructed object is compactly represented by a 3D segment-based data format which is called DoCube, and the 3D object is finally reconstructed after 3D mesh generation and texture mapping are performed. Experimental results show that the proposed system produces 3D object contents of $800{\times}800{\times}800$ resolution with a rate of 2.2 seconds per frame.

• Journal of dental hygiene science
• /
• v.8 no.1
• /
• pp.35-42
• /
• 2008

This survey was compared and analyzed about the primary factor that dental office's working environment effect on physical subjective symptom and based on self-filling survey, 656 dental hygienists on July through August 2006, and analyzed using descriptive statics, ANOVA and Multiple Regression Analysis. The result of satisfaction degree of hospital working environment was pretty low about office air condition. Most people have complained that office's air quality makes it difficult to their work and mentioned that they were sore and dull all over the back, shoulder, and neck. The odor is major factor to be satisfied with office environment. Proper ventilates the way open the window more often was essential to maintain fresh indoor air quality and keep the extraction materials by separator and sealing tightly for remove the odor. Other factors were temperature, lighting fixture, ventilation facilities, and freshness of air. Dental hygienist was unsatisfied with hospital air condition and this polluted air condition was the cause of physical subjective symptom in work place. Furthermore, this research would be applied for improvement of working environment by decreasing of indoor air pollution.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.10
• /
• pp.6019-6023
• /
• 2013

Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images.

• Agricultural and Biosystems Engineering
• /
• v.4 no.1
• /
• pp.8-15
• /
• 2003

In Korea, quality evaluation of dried oak mushrooms are done first by classifying them into more than 10 different categories based on the state of opening of the cap, surface pattern, and colors. And mushrooms of each category are further classified into 3 or 4 groups based on its shape and size, resulting into total 30 to 40 different grades. Quality evaluation and sorting based on the external visual features are usually done manually. Since visual features of mushroom affecting quality grades are distributed over the entire surface of the mushroom, both front (cap) and back (stem and gill) surfaces should be inspected thoroughly. In fact, it is almost impossible for human to inspect every mushroom, especially when they are fed continuously via conveyor. In this paper, considering real time on-line system implementation, image processing algorithms utilizing artificial neural network have been developed for the quality grading of a mushroom. The neural network based image processing utilized the raw gray value image of fed mushrooms captured by the camera without any complex image processing such as feature enhancement and extraction to identify the feeding state and to grade the quality of a mushroom. Developed algorithms were implemented to the prototype on-line grading and sorting system. The prototype was developed to simplify the system requirement and the overall mechanism. The system was composed of automatic devices for mushroom feeding and handling, a set of computer vision system with lighting chamber, one chip microprocessor based controller, and pneumatic actuators. The proposed grading scheme was tested using the prototype. Network training for the feeding state recognition and grading was done using static images. 200 samples (20 grade levels and 10 per each grade) were used for training. 300 samples (20 grade levels and 15 per each grade) were used to validate the trained network. By changing orientation of each sample, 600 data sets were made for the test and the trained network showed around 91 % of the grading accuracy. Though image processing itself required approximately less than 0.3 second depending on a mushroom, because of the actuating device and control response, average 0.6 to 0.7 second was required for grading and sorting of a mushroom resulting into the processing capability of 5,000/hr to 6,000/hr.