• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.66-75
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• 2021

The research is centered towards analyzing the usage status of YouTube platform and the nature of content supplied to YouTube by selecting Korean two Traffic Broadcastings Based on TBS(Traffic Broadcasting System) and TBN(Traffic Broadcasting Network). TBS operates 'Citizen's Broadcasting', which has 1.1 million subscribers among 13 YouTube channels, as its main channel. TBN has only 15,000 subscribers to its main 'TBN Tong', and YouTube channels in 12 local networks. TBS which has a dedicated YouTube manpower, is far ahead of TBN in terms of YouTube channel management and content composition. Both broadcasters are passive about creating new media content due to job stability. For the development of the YouTube platform for these two broadcasters, organizational changes within traffic broadcasting and changes in the perception of members are required, and live broadcasting and discovery of star creators are required. In the changing media environment two traffic broadcastings need a program distribution strategy that can be included in various media platforms.

• Journal of Family Resource Management and Policy Review
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• v.26 no.2
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• pp.53-70
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• 2022

This study aimed to develop a scale to measure the family strength of single-parent families. We analyzed the everyday life and demands of single-parent families using the theory of family strength to draw 78 items that encompass family basis, relationships, roles, social networks and family culture. Using a sample of 286 single-parent families through an online survey platform, we examined the factor structure of the items and selected 48 items based on the results of the factor analysis. Reliability, criterion and construct validity were also examined. The final scale comprised of five domains ; basis, parents' role, work-life balance, social network, lifestyle and household management. This scale can be used as an assessment measure of the family strength of single-parent families for consulting, case management and suggesting various programs in the field. This merit will help enhance the quality of programing for single-parent families at the Healthy Family Support Center and the development of family strength scales for various types of families.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.151-166
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• 2022

Museum is the carrier and symbol of history and cultural accumulation, and the museum cultural relics are clues with the spirit of history. Moreover, the museum cultural and creative products are portable history. Museum has changed form the traditional "object-basic" model to the modern "people-basic" model, which pays more attention to its living inheritance. Therefor, the museum cultural and creative products is also the way of expression of its living inheritance. This paper analyzes the opportunities and difficulties of cultural and creative products of Chinese museums by means of network survey, field survey and expert interview. In order to improve the design method of cultural and creative products. By exploring the cultural connotation, broadening the functional factors, innovating the design factors and creating the empathy factor between products and people to explore and the verify. Trying to make up the imperfect design methods of cultural and creative products in small and medium-sized museums which leads to the lack of function, innovation and communication of cultural and creative products. We try to attract more people's attention, spread traditional culture and realize the resonance between people and objects.

• Journal of the Korean Society of Radiology
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• v.16 no.1
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• pp.1-6
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• 2022

Deep learning is a collection of algorithms that enable learning by summarizing the key contents of large amounts of data; it is being developed to diagnose lesions in the medical imaging field. To evaluate the accuracy of the cerebral hemorrhage diagnosis, we used a convolutional neural network (CNN) to derive the diagnostic accuracy of cerebral parenchyma computed tomography (CT) images and the cerebral parenchyma CT images of areas where cerebral hemorrhages are suspected of having occurred. We compared the accuracy of CNN with different numbers of hidden layers and discovered that CNN with more hidden layers resulted in higher accuracy. The analysis results of the derived CT images used in this study to determine the presence of cerebral hemorrhages are expected to be used as foundation data in studies related to the application of artificial intelligence in the medical imaging industry.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.319-325
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• 2022

The variation of utterance lengths is a representative factor that can degrade the performance of speaker verification systems. To handle this issue, previous studies had attempted to extract speaker features from various branches or to use convolution layers with different receptive fields. Combining the advantages of the previous two approaches for variable-length input, this paper proposes integrated receptive field diversification that extracts speaker features through more diverse receptive field. The proposed method processes the input features by convolutional layers with different receptive fields at multiple time-axis branches, and extracts speaker embedding by dynamically aggregating the processed features according to the lengths of input utterances. The deep neural networks in this study were trained on the VoxCeleb2 dataset and tested on the VoxCeleb1 evaluation dataset that divided into 1 s, 2 s, 5 s, and full-length. Experimental results demonstrated that the proposed method reduces the equal error rate by 19.7 % compared to the baseline.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.326-334
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• 2022

In this paper, we propose speech enhancement algorithm as a pre-processing for robust speech recognition in noisy environments. Auxiliary-function-based Independent Vector Analysis (AuxIVA) is performed with weighted covariance matrix using time-varying variances with scaling factor from target masks representing time-frequency contributions of target speech. The mask estimates can be obtained using Neural Network (NN) pre-trained for speech extraction or diffuseness using Coherence-to-Diffuse power Ratio (CDR) to find the direct sounds component of a target speech. In addition, outputs for omni-directional noise are closely chained by sharing the time-varying variances similarly to independent subspace analysis or IVA. The speech extraction method based on AuxIVA is also performed in Independent Low-Rank Matrix Analysis (ILRMA) framework by extending the Non-negative Matrix Factorization (NMF) for noise outputs to Non-negative Tensor Factorization (NTF) to maintain the inter-channel dependency in noise output channels. Experimental results on the CHiME-4 datasets demonstrate the effectiveness of the presented algorithms.

• 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 the Korea Society of Computer and Information
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• v.28 no.1
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• pp.17-26
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• 2023

In this paper, we propose a several smoothing techniques are compared and applied to increase the application of the LSTM-based learning model and its effectiveness. The applied smoothing technique is Savitky-Golay, exponential smoothing, and weighted moving average. Through this study, the LSTM algorithm with the Savitky-Golay filter applied in the preprocessing process showed significant best results in prediction performance than the result value shown when applying the LSTM model to Bitcoin data. To confirm the predictive performance results, the learning loss rate and verification loss rate according to the Savitzky-Golay LSTM model were compared with the case of LSTM used to remove complex factors from Bitcoin price prediction, and experimented with an average value of 20 times to increase its reliability. As a result, values of (3.0556, 0.00005) and (1.4659, 0.00002) could be obtained. As a result, since crypto-currencies such as Bitcoin have more volatility than stocks, noise was removed by applying the Savitzky-Golay in the data preprocessing process, and the data after preprocessing were obtained the most-significant to increase the Bitcoin prediction rate through LSTM neural network learning.

• Korean Journal of Psychosomatic Medicine
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• v.30 no.2
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• pp.55-65
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• 2022

Although humans exist as Homo Empathicus, human society is actually constantly divided and conflicted between groups. The human empathy response is very sensitive to the justice of others, and depending on the level of others' justice, they may feel empathy or schadenfreude to the suffering of them. However, our empathy to others' suffering are not always fair, and have inherent limitations of ingroup-biased empathy. Depending on whether the suffering other persons belongs to an ingroup or an outgroup, we may feel biased empathy or biased schadenfreude to them without even realizing it. Recent advances in information and communication technology facilitate biased access to ingroup-related SNS or ingroup media, thereby deepening the establishment of a more biased semantic information network related groups. These processes, through interacting with the inherent limitation of empathy, can form a vicious cycle of more biased ingroup empathy and ingroup-related activities, and accelerate divisions and conflicts. This research investigated the properties and limitations of empathy by reviewing studies on the neural mechanism of empathy. By examining the relationship between empathy and justice from a neuroscientific point of view, this research tried to illuminate the modern society of division and conflict in a different dimension from the classical perspective of social science.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.4
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• pp.73-92
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• 2022

This study intends to design a model that can effectively service policy data necessary for the implementation of new national agenda in order to provide high-quality policy information services that go beyond those of the existing Policy Information Portal (POINT) of National Sejong Library. To this end, it was determined that providing an integrated search environment, in lieu of data search through individual access, was necessary. Subsequently, four possible models for a national agenda service model were presented. First, designing a computerized system for both interface and electronic information source aspects was proposed for the national agenda service system operation. Second, designing the Linked Open Data system and the time-series service system for national policy information, providing the translation service of overseas original data, and securing the researcher's desired data were presented for the national agenda service information source operation. Third, strengthening public relations for policy users, building and promoting the site brand, operating SNS channels, and reinforcing the activation of auxiliary materials and the accessibility of external services were proposed for public relations of national agenda service. Fourth, expanding the information network with Open API, cloud service, and overseas libraries was proposed for collaborating and cooperating with the agenda service.