• The KIPS Transactions:PartC
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• v.19C no.4
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• pp.239-246
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• 2012

The function of location estimation in WPAN has been studied and specified on the ultra wide band optionally. But the devices based on CSS(Chirp Spread Spectrum) specification has been used widely in the market because of its functionality, cheapness and support of development. As the CSS device uses 2.4GHz for a carrier frequency and the sampling frequency is lower than that of the UWB, the resolution of a timestamp is very coarse. Then actually the error of a measured distance is very large about 30cm~1m at 10 m depart. And the location error in ($10m{\times}10m$) environment is known as about 1m~2m. So for some applications which require more accurate location information, it is very natural and important to develop a sophisticated post processing algorithm after distance measurements. In this paper, we have studied extended Kalman filter with the frequency offsets of anchor nodes, and proposed a novel algorithm frequency offset compensated extended Kalman filter. The frequency offsets are composed with a variable as a common frequency offset and constants as individual frequency offsets. The proposed algorithm shows that the accurate location estimation, less than 10cm distance error, with CSS WPAN nodes is possible practically.

• Archives of design research
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• v.12 no.4
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• pp.89-98
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• 1999

The application of tool which has grown rapidly by the age was used for the product development, however as today the computer digitalization has been fixed to the necessary process in every factory-made mass production, making the sensitive desire of designer the digitalization through systematic, rational information database building from the planning level of product to the final mass production in such a environment change. It should satisfy a variety of needs of consumer. The enterprise that hopes to get a winner in the present age brought in computer with useful tool to process information efficiently. The computer has displayed much more excellent computation ability than human to come up to their expectation and the growth of electronic technology was possible to make the computer's high-efficiency, economy and integration. No matter what we have a good economy and integration. No matter what we have a good information there is no meaning unless we are able to use it' so we should take it out by the our need. Therefore, this paper observes a future-oriented possibility of computer & Telecommunication in information society, information-oriented design environment and the trends of minimal and integrated computer. We will improve the designer's ability to develop a novel product that have the diversification of them using application, aiming at computer utilization and image identification design strategy of product in the age of network telecommunication.

• Journal of Korea Water Resources Association
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• v.53 no.8
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• pp.569-582
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• 2020

Recently, Korea has faced a change in the pattern of water use due to urbanization, which has caused difficulties in understanding the rainfall-runoff process and optimizing the allocation of available water resources. In this perspective, spatially downscaled analysis of the water balance is required for the efficient operation of water resources in the National Water Management Plan and the River Basin Water Resource Management Plan. However, the existing water balance analysis does not fully consider water circulation and availability in the basin, thus, the obtained results provide limited information in terms of decision making. This study aims at developing a novel water circulation analysis model that is designed to support a quasi-real-time assessment of water availability along the river. The water circulation model proposed in this study improved the problems that appear in the existing water balance analysis. More importantly, the results showed a significant improvement over the existing model, especially in the low flow simulation. The proposed modeling framework is expected to provide primary information for more realistic hydrological drought monitoring and drought countermeasures by providing streamflow information in quasi-real-time through a more accurate natural flow estimation approach with highly complex network.

• Journal of Animal Science and Technology
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• v.60 no.12
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• pp.32.1-32.10
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• 2018

Background: Necdin (NDN), a member of the melanoma antigen family showing imprinted pattern of expression, has been implicated as causing Prader-Willi symptoms, and known to participate in cellular growth, cellular migration and differentiation. The region where NDN is located has been associated to QTLs affecting reproduction and early growth in cattle, but location and functional analysis of the molecular mechanisms have not been established. Methods: Here we report the sequence variation of the entire coding sequence from 72 samples of cattle, yak, buffalo, goat and sheep, and discuss its variation in Bovidae. Median-joining network analysis was used to analyze the variation found in the species. Synonymous and non-synonymous substitution rates were determined for the analysis of all the polymorphic sites. Phylogenetic analysis were carried out among the species of Bovidae to reconstruct their relationships. Results: From the phylogenetic analysis with the consensus sequences of the studied Bovidae species, we found that only 11 of the 26 nucleotide changes that differentiate them produced amino acid changes. All the SNPs found in the cattle breeds were novel and showed similar percentages of nucleotides with non-synonymous substitutions at the N-terminal, MHD and C-terminal (12.3, 12.8 and 12.5%, respectively), and were much higher than the percentage of synonymous substitutions (2.5, 2.6 and 4.9%, respectively). Three mutations in cattle and one in sheep, detected in heterozygous individuals were predicted to be deleterious. Additionally, the analysis of the biochemical characteristics in the most common form of the proteins in each species show very little difference in molecular weight, pI, net charge, instability index, aliphatic index and GRAVY (Table 4) in the Bovidae species, except for sheep, which had a higher molecular weight, instability index and GRAVY. Conclusions: There is sufficient variation in this gene within and among the studied species, and because NDN carry key functions in the organism, it can have effects in economically important traits in the production of these species. NDN sequence is phylogenetically informative in this group, thus we propose this gene as a phylogenetic marker to study the evolution and conservation in Bovidae.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.155-170
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• 2018

Predicting a company's financial bankruptcy is traditionally one of the most crucial forecasting problems in business analytics. In previous studies, prediction models have been proposed by applying or combining statistical and machine learning-based techniques. In this paper, we propose a novel intelligent prediction model based on the simulated annealing which is one of the well-known optimization techniques. The simulated annealing is known to have comparable optimization performance to the genetic algorithms. Nevertheless, since there has been little research on the prediction and classification of business decision-making problems using the simulated annealing, it is meaningful to confirm the usefulness of the proposed model in business analytics. In this study, we use the combined model of simulated annealing and machine learning to select the input features of the bankruptcy prediction model. Typical types of combining optimization and machine learning techniques are feature selection, feature weighting, and instance selection. This study proposes a combining model for feature selection, which has been studied the most. In order to confirm the superiority of the proposed model in this study, we apply the real-world financial data of the Korean companies and analyze the results. The results show that the predictive accuracy of the proposed model is better than that of the naïve model. Notably, the performance is significantly improved as compared with the traditional decision tree, random forests, artificial neural network, SVM, and logistic regression analysis.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.59-66
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• 2021

Humans mainly recognize surrounding objects using visual and auditory information among the five senses (sight, hearing, smell, touch, taste). Major research related to the latest object recognition mainly focuses on analysis using image sensor information. In this paper, after emitting various chirp audio signals into the observation space, collecting echoes through a 2-channel receiving sensor, converting them into spectral images, an object recognition experiment in 3D space was conducted using an image learning algorithm based on deep learning. Through this experiment, the experiment was conducted in a situation where there is noise and echo generated in a general indoor environment, not in the ideal condition of an anechoic room, and the object recognition through echo was able to estimate the position of the object with 83% accuracy. In addition, it was possible to obtain visual information through sound through learning of 3D sound by mapping the inference result to the observation space and the 3D sound spatial signal and outputting it as sound. This means that the use of various echo information along with image information is required for object recognition research, and it is thought that this technology can be used for augmented reality through 3D sound.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.461-469
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• 2022

This paper presents a novel training data extraction approach using semi-supervised learning (SSL)-based classification without the analyst intervention for time-series land-cover mapping. The SSL-based approach first performs initial classification using initial training data obtained from past images including land-cover characteristics similar to the image to be classified. Reliable training data from the initial classification result are then extracted from SSL-based iterative classification using classification uncertainty information and class labels of neighboring pixels as constraints. The potential of the SSL-based training data extraction approach was evaluated from a classification experiment using unmanned aerial vehicle images in croplands. The use of new training data automatically extracted by the proposed SSL approach could significantly alleviate the misclassification in the initial classification result. In particular, isolated pixels were substantially reduced by considering spatial contextual information from adjacent pixels. Consequently, the classification accuracy of the proposed approach was similar to that of classification using manually extracted training data. These results indicate that the SSL-based iterative classification presented in this study could be effectively applied to automatically extract reliable training data for time-series land-cover mapping.

• Advances in nano research
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• v.13 no.6
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• pp.575-585
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• 2022

Due to its biofilm formation and colonization of the osteocyte-lacuno canalicular network (OLCN), Staphylococcus aureus (S.aureus) implant-associated bone infection (SIABI) is difficult to cure thoroughly, and may occur recurrently subsequently after a long period dormant. It is essential to explore an alternative therapeutic strategy that can eradicate the pathogens in the infected foci. To address this, the polymethylmethacrylate (PMMA) bone cement and Fe3O4 nanoparticles compound cylinder were developed as implants based on their size and mechanical properties for the alternative magnetic field (AMF) induced thermal ablation, The PMMA mixed with optimized 2% Fe₃O₄ nanoparticles showed an excellent antibacterial efficacy in vitro. It was evaluated by the CFU, CT scan and histopathological staining on a rabbit 1-stage transtibial screw model. The results showed that on week 7, the CFU of infected soft tissue and implants, and the white blood cells (WBCs) of the PMMA+2% Fe₃O₄+AMF group decreased significantly from their controls (p<0.05). PMMA+2% Fe₃O₄+AMF group did not observe bone resorption, periosteal reaction, and infectious reactive bone formation by CT images. Further histopathological H&E and Gram Staining confirmed there was no obvious inflammatory cell infiltration, neither pathogens residue nor noticeably burn damage around the infected screw channel in the PMMA+2% Fe₃O₄+AMF group. Further investigation of nanoparticle distributions in bone marrow medullary and vital organs of heart, liver, spleen, lung, and kidney. There were no significantly extra Fe₃O₄ nanoparticles were observed in the medullary cavity and all vital organs either. In the current study, PMMA+2% Fe₃O₄+AMF shows promising therapeutic potential for SIABI by providing excellent mechanical support, and promising efficacy of eradicating the residual pathogenic bacteria in bone infected lesions.

• Journal of Veterinary Science
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• v.24 no.3
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• pp.44.1-44.17
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• 2023

Background: Antibiotic resistance is a significant public health concern around the globe. Antimicrobial peptides exhibit broad-spectrum and efficient antibacterial activity with an added advantage of low drug resistance. The higher water content and 3D network structure of the hydrogels are beneficial for maintaining antimicrobial peptide activity and help to prevent degradation. The antimicrobial peptide released from hydrogels also hasten the local wound healing by promoting epithelial tissue regeneration and granulation tissue formation. Objective: This study aimed at developing sodium alginate based hydrogel loaded with a novel antimicrobial peptide Chol-37(F34-R) and to investigate the characteristics in vitro and in vivo as an alternative antibacterial wound dressing to treat infectious wounds. Methods: Hydrogels were developed and optimized by varying the concentrations of crosslinkers and subjected to various characterization tests like cross-sectional morphology, swelling index, percent water contents, water retention ratio, drug release and antibacterial activity in vitro, and Pseudomonas aeruginosa infected wound mice model in vivo. Results: The results indicated that the hydrogel C proved superior in terms of cross-sectional morphology having uniformly sized interconnected pores, a good swelling index, with the capacity to retain a higher quantity of water. Furthermore, the optimized hydrogel has been found to exert a significant antimicrobial activity against bacteria and was also found to prevent bacterial infiltration into the wound site due to forming an impermeable barrier between the wound bed and external environment. The optimized hydrogel was found to significantly hasten skin regeneration in animal models when compared to other treatments in addition to strong inhibitory effect on the release of pro-inflammatory cytokines (interleukin-1β and tumor necrosis factor-α). Conclusions: Our results suggest that sodium alginate -based hydrogels loaded with Chol-37(F34-R) hold the potential to be used as an alternative to conventional antibiotics in treating infectious skin wounds.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.309-330
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• 2022

Intellectual structure analysis, which quantitatively identifies the structure, characteristics, and sub-domains of fields, has rapidly increased in recent years. Analysis techniques traditionally used to conduct intellectual structure analysis research include bibliographic coupling analysis, co-citation analysis, co-occurrence analysis, and author bibliographic coupling analysis. This study proposes a novel intellectual structure analysis method, Keyword Bibliographic Coupling Analysis (KBCA). The Keyword Bibliographic Coupling Analysis (KBCA) is a variation of the author bibliographic coupling analysis, which targets keywords instead of authors. It calculates the number of references shared by two keywords to the degree of coupling between the two keywords. A set of 1,366 articles in the field of 'Open Data' searched in the Web of Science were collected using the proposed KBCA technique. A total of 63 keywords that appeared more than 7 times, extracted from 1,366 article sets, were selected as core keywords in the open data field. The intellectual structure presented by the KBCA technique with 63 key keywords identified the main areas of open government and open science and 10 sub-areas. On the other hand, the intellectual structure network of co-occurrence word analysis was found to be insufficient in the overall structure and detailed domain structure. This result can be considered because the KBCA sufficiently measures the relationship between keywords using the degree of bibliographic coupling.