• Nuclear Engineering and Technology
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• v.35 no.3
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• pp.234-242
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• 2003

The full energy peak efficiency of a hyper pure germanium (HPGe) detector was calibrated in a wide energy range from 0.06 to 11 MeV. Both the experimental technique and the Monte Carlo method were used for the efficiency calibration. The measurement was performed using the standard radioisotopes in the low energy region of $60{\sim}1408$ keV, which was further extended up to 11 MeV by using the $^{14}N(n,r)\;and\;^{35}Cl(n,r)$ reactions. The GEANT Monte Carlo code was used for efficiency calculation. The calculated efficiency had the same dependency on the r-ray energy with the measurement, and the discrepancy between the calculation and the measurement was minimized by fine-tuning of the detector geometry. From the calculated result, the efficiency curve of the HPGe detector was reliably determined particularly in the high energy region above several MeV, where the number of measured efficiency points is relatively small despite the wide energy region. The calculated efficiency agreed with the measurement within about $7\%$. In addition to the efficiency calculation, the origin of the local minimum near 600 keV on the efficiency curve was analyzed as a general characteristics of a HPGe detector.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.65-68
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• 2001

RBFN has some problem that because the basis function isnt orthogonal to each others the number of used basis function goes to big. In this reason, the Wavelet Neural Network which uses the orthogonal basis function in the hidden node appears. In this paper, we propose the composition method of the actual function in hidden layer with the scaling function which can represent the region by which the several wavelet can be represented. In this method, we can decrease the size of the network with the pure several wavelet function. In addition to, when we determine the parameters of the scaling function we can process rough approximation and then the network becomes more stable. The other wavelets can be determined by the global solutions which is suitable for the suggested problem using the genetic algorithm and also, we use the back-propagation algorithm in the learning of the weights. In this step, we approximate the target function with fine tuning level. The complex neural network suggested in this paper is a new structure and important simultaneously in the point of handling the determination problem in the wavelet initialization.

• Korean Journal of Agricultural Science
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• v.44 no.3
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• pp.318-324
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• 2017

With the development of next-generation sequencing (NGS), a cutting-edge technology, genotype-by-sequencing (GBS) became available at a low cost per sample. GBS makes it possible to customize the process of library preparation to obtain high-quality single nucleotide polymorphisms (SNPs) in the most efficient way. However, a GBS library is hard to construct due to fine-tuning of concentration of each reagent and set-up. The major reason for this is the presence of undigested genomic DNA (gDNA) owing to the efficiency of different restriction enzymes for different species with unknown reasons. Therefore, this proof-concept study is to demonstrate the unpredictable patterns of enzyme digestion from various plants in order to make the reader aware of the caution needed when choosing restriction enzymes for their GBS library preparations. Indeed, no pattern was found for the digestibility of gDNA samples and restriction enzymes in the current study. We suggest that more data should be accumulated on this matter to help researchers who want to apply GBS technologies in a variety of genetic approaches.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.1
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• pp.68-73
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• 2002

This paper presents the implementation of wide-band RFIC amplifier operating from near 50 MHz to 3 GHz using Tachyonics SiGe HBT foundry. Voltage shunt feedback is used for the flat gain and the broad band impedance matching. Initial design parameters are calculated through the low frequency small signal analysis. Since the HBT model was not available at the design time, discrete tuning board was made for fine adjustment in the low frequency range. Fabricated amplifier shows 12 dB gain with 1 dB fluctuation and P1 dB reaches 15 dBm at 850 MHz.

• Journal of Information Technology Applications and Management
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• v.12 no.3
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• pp.111-128
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• 2005

This paper examines the validity of the newly developed IT consulting SERVQUAL measurement tool. In an attempt to measure Ire IS customers' expectations and perceived quality of the services they received, the researchers developed a diagnostic tool of SERVQUAL based on the solid theoretical background, which can specifically be applied to the IT consulting service sector. This on-going research so far, has been applied to six (6) different organizations that have received IT consulting services over the past years. From the preliminary data collected, the correlation and the factor analyses were conducted to understand the underlying concept and refinement of the measurement tool. Although the correlation analysis showed a little tendency of collinearity among some of the variables, all showed sound relationship of the proposed hypotheses. The exploratory factor analytic approach was chosen because it does not set any priori constraints on the estimation of components or the number of components to be extracted. The number of different factor solutions was extracted and tested to see which solution represents better grouping of the variables. The Crombach's Alpha was computed on different combinations of the factor solutions to ensure validity. The results show 8-dimensional IT consulting SERVQUAL measures which they are, assurance, knowledge & skill, customer relationship, support, empathy, process management, expertise, and education, seem more appropriate than the originally proposed 6 dimensions. The study approach was non-experimental cross-sectional research design. The longitudinal design of follow-up studies to periodically revise and refine current measure is strongly recommended for fine tuning of the tool.

• Nuclear Engineering and Technology
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• v.46 no.1
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• pp.73-80
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• 2014

A concrete cask is an option for spent nuclear fuel interim storage. A concrete cask usually consists of a metallic canister which confines the spent nuclear fuel assemblies and a concrete overpack. When the overpack undergoes a missile impact, which might be caused by a tornado or an aircraft crash, it should sustain an acceptable level of structural integrity so that its radiation shielding capability and the retrievability of the canister are maintained. A missile impact against a concrete overpack produces two damage modes, local damage and global damage. In conventional approaches [1], those two damage modes are decoupled and evaluated separately. The local damage of concrete is usually evaluated by empirical formulas, while the global damage is evaluated by finite element analysis. However, this decoupled approach may lead to a very conservative estimation of both damages. In this research, finite element analysis with material failure models and element erosion is applied to the evaluation of local and global damage of concrete overpacks under high speed missile impacts. Two types of concrete overpacks with different configurations are considered. The numerical simulation results are compared with test results, and it is shown that the finite element analysis predicts both local and global damage qualitatively well, but the quantitative accuracy of the results are highly dependent on the fine-tuning of material and failure parameters.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.65-70
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• 2021

Waste accumulation is becoming a significant challenge in most urban areas and if it continues unchecked, is poised to have severe repercussions on our environment and health. The massive industrialisation in our cities has been followed by a commensurate waste creation that has become a bottleneck for even waste management systems. While recycling is a viable solution for waste management, it can be daunting to classify waste material for recycling accurately. In this study, transfer learning models were proposed to automatically classify wastes based on six materials (cardboard, glass, metal, paper, plastic, and trash). The tested pre-trained models were ResNet50, VGG16, InceptionV3, and Xception. Data augmentation was done using a Generative Adversarial Network (GAN) with various image generation percentages. It was found that models based on Xception and VGG16 were more robust. In contrast, models based on ResNet50 and InceptionV3 were sensitive to the added machine-generated images as the accuracy degrades significantly compared to training with no artificial data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1795-1811
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• 2019

In order to achieve rapid and accurate detection of vehicle objects in complex traffic conditions, we propose a novel vehicle detection method. Firstly, more contextual and small-object vehicle information can be obtained by our Joint Feature Network (JFN). Secondly, our Evolved Region Proposal Network (EPRN) generates initial anchor boxes by adding an improved version of the region proposal network in this network, and at the same time filters out a large number of false vehicle boxes by soft-Non Maximum Suppression (NMS). Then, our Mask Network (MaskN) generates an example that includes the vehicle occlusion, the generator and discriminator can learn from each other in order to further improve the vehicle object detection capability. Finally, these candidate vehicle detection boxes are optimized to obtain the final vehicle detection boxes by the Fine-Tuning Network(FTN). Through the evaluation experiment on the DETRAC benchmark dataset, we find that in terms of mAP, our method exceeds Faster-RCNN by 11.15%, YOLO by 11.88%, and EB by 1.64%. Besides, our algorithm also has achieved top2 comaring with MS-CNN, YOLO-v3, RefineNet, RetinaNet, Faster-rcnn, DSSD and YOLO-v2 of vehicle category in KITTI dataset.

• BMB Reports
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• v.52 no.8
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• pp.514-519
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• 2019

Osteoclasts are multinucleated giant cells derived from myeloid progenitors. Excessive bone resorption by osteoclasts can result in serious clinical outcomes for which better treatment options are needed. Here, we identified fibronectin leucine-rich transmembrane protein 2 (Flrt2), a ligand of the Unc5 receptor family for neurons, as a novel target associated with the late/maturation stage of osteoclast differentiation. Flrt2 expression is induced by stimulation with receptor activator of nuclear factor-kB ligand (RANKL). Flrt2 deficiency in osteoclasts results in reduced hyper-multinucleation, which could be restored by RNAi-mediated knockdown of Unc5b. Treatment with Netrin1, another ligand of Unc5b which negatively controls osteoclast multinucleation through down regulation of RANKL-induced Rac1 activation, showed no inhibitory effects on Flrt2-deficient cells. In addition, RANKL-induced Rac1 activation was attenuated in Flrt2-deficient cells. Taken together, these results suggest that Flrt2 regulates osteoclast multinucleation by interfering with Netrin 1-Unc5b interaction and may be a suitable therapeutic target for diseases associated with bone remodeling.

• BMB Reports
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• v.52 no.8
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• pp.502-507
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• 2019

Translation is a costly, but inevitable, cell maintenance process. To reduce unnecessary ATP consumption in cells, a fine-tuning mechanism is needed for both ribosome biogenesis and translation. Previous studies have suggested that the ribosome functions as a hub for many cellular signals such as ribotoxic stress response, mammalian target of rapamycin (mTOR), and ribosomal S6 kinase (RSK) signaling. Therefore, we investigated the relationship between ribosomes and mitogen-activated protein kinase (MAPK) activation under ribotoxic stress conditions and found that the activation of c-Jun N-terminal kinases (JNKs) was suppressed by ribosomal protein knockdown but that of p38 was not. In addition, we found that JNK activation is driven by the association of inactive JNK in the 80S monosomes rather than the polysomes. Overall, these data suggest that the activation of JNKs by ribotoxic stress is attributable to 80S monosomes. These 80S monosomes are active ribosomes that are ready to initiate protein translation, rather than polysomes that are already acting ribosomes involved in translation elongation.