This study aims to investigate Korean fashion-related research trends and knowledge structures on digital transformation through information-based approaches. Accordingly, we first identified the current status of the relevant research in Korean academic literature by year and journal; subsequently, we derived key research topics through network analysis, and then analyzed major research trends and knowledge structures by time. From 2010 to 2020, we collected 159 studies published on Korean academic platforms, cleansed data through Python 3.7, and measured centrality and network implementation through NodeXL 1.0.1. The results are as follows: first, related research has been actively conducted since 2016, mainly concentrated in clothing and art areas. Second, the online platform, AR/VR, appeared as the most frequently mentioned topic, and consumer psychological analysis, marketing strategy suggestion, and case analysis were used as the main research methods. Through clustering, major research contents for each sub-major of clothing were derived. Third, major subject by period was considered, which has, over time, changed from consumer-centered research to strategy suggestion, and design development research of platforms or services. This study contributes to enhancing insight into the fashion field on digital transformation, and can be used as a basic research to design research on related topics.
Journal of the Korean Society for information Management
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v.39
no.2
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pp.233-254
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2022
Link reduction algorithms such as pathfinder network are the widely used methods to overcome problems with the visualization of weighted networks for knowledge domain analysis. This study proposed NetRSQ, an indicator to measure the goodness of fit of a link reduction algorithm for the network visualization. NetRSQ is developed to calculate the fitness of a network based on the rank correlation between the path length and the degree of association between entities. The validity of NetRSQ was investigated with data from previous research which qualitatively evaluated several network generation algorithms. As the primary test result, the higher degree of NetRSQ appeared in the network with better intellectual structures in the quality evaluation of networks built by various methods. The performance of 4 link reduction algorithms was tested in 40 datasets from various domains and compared with NetRSQ. The test shows that there is no specific link reduction algorithm that performs better over others in all cases. Therefore, the NetRSQ can be a useful tool as a basis of reliability to select the most fitting algorithm for the network visualization of intellectual structures.
Journal of Korea Entertainment Industry Association
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v.13
no.4
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pp.107-117
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2019
This paper establishes and propagates the value of the play through the study of the transition process of the yesan play from 1920 to the present, presents an alternative through the unique theatricality of the region and aims to activate it. The theater divided the theater into Yecheon, Chungnam Theater Festival, and Youth Theater Festival, which are currently active, and focused on Yedang International Performing Arts Festival, which is the only one in Yesan. The details of the performance due to the loss of data were not specified as much as possible, but the contents of the yesan play before 1990 were reviewed using the eupji and Myeonji. It also starts with a lack of diversity in plays in the developing direction of Yesan. Children's plays should be dismissed for simple commercial purposes, or the value of traditional Korean plays should be compared to Western ones, to promote the development of local plays through the natural characteristics and the basis of traditional culture, and to sustain the continuity of extreme economic performance and performances through the development of repertoires. Infrastructure deployment can be cited. The in flow of specialized actors and the use of art administrators creates a stable theater environment and activates the reeducation of local actors to promote theatrical imagination. It is also an urgent task to develop a new theatrical form by introducing experimental theatrical methods of young artists in the overseas performance business of theater troupe Yechon. Finally, Yedang International Performing Arts Festival should be characterized and differentiated from other festivals.
In the context of the increasing applications of voice assistants in vehicles, we focused on the association between the visual appeal of the cars and the acoustic characteristics of the voice assistants. This study aimed to investigate the relationship between the visual appeal of the vehicle and the voice assistant based on their emotional characteristics. A total of 15 adjectives were used to assess the emotional characteristics of 12 types of cars and six types of voices. An online interview was carried out, instructing participants to match three adjectives with the presented car images or voices. This was followed with a brief interview to allow the participants to reflect on the adjective matches. Based on the assessments, we performed principal component analysis (PCA) to determine factors. We aimed to deploy the cars and voices and analyze the patterns of clustering. The PCA analysis revealed two factors profiled as "Light-Heavy" and "Comfortable-Radical." Both car and voice stimuli were deployed in a two-dimensional space showing the internal relationship within and between the two substances. Based on the coordination data, a hierarchical cluster grouped the 18 stimuli into four groups labeled as challenge, elegance, majesty, and vigor. This study identified two latent factors describing the emotional characteristics of both car images and voice types clustered into four groups based on their emotional characteristics. The coherent matches between car style and voice type are expected to address the design concept more successfully.
KSII Transactions on Internet and Information Systems (TIIS)
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v.17
no.7
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pp.1951-1975
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2023
Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.
Due to economic development and increasing gross national income, the number of automobiles continues to rise, leading to a serious issue of illegal parking due to limited road conditions and insufficient parking facilities. Illegal parking causes significant inconvenience and displeasure to people and can even result in accidents and loss of lives. The severity of accidents and their consequences, related to the growing number of vehicles and illegal parking, is escalating, particularly in the metropolitan areas. Consequently, efforts are being made to address this problem as a cause of social issues and come up with measures to reduce illegal parking. In particular, half of the public complaints in the metropolitan area are related to illegal parking, and the highest physical and human damage occurs in Gyeonggi. Thus, this study aims to use machine learning techniques based on data related to illegal parking in Suwon city, Gyeonggi, to categorize regional characteristics and propose effective measures to crack down on illegal parking. Additionally, practical, social, policy, and legal measures to decrease illegal parking in the metropolitan area are suggested. This study has academic significance in that it solved the problem of illegal parking, which is mentioned as one of the social problems that cause traffic congestion, by classifying regional characteristics using K-prototype, a machine learning algorithm. Furthermore, the results of this study contribute to practical and social aspects by providing measures to decrease illegal parking in the metropolitan area.
Da Hyun Lee;Ji Eun Park;NakYoung Kim;Seo Young Park;Young-Hoon Kim;Young Hyun Cho;Jeong Hoon Kim;Ho Sung Kim
Korean Journal of Radiology
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v.24
no.3
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pp.235-246
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2023
Objective: It is difficult to predict the treatment response of tissue after stereotactic radiosurgery (SRS) because radiation necrosis (RN) and tumor recurrence can coexist. Our study aimed to predict tumor recurrence, including the recurrence site, after SRS of brain metastasis by performing a longitudinal tumor habitat analysis. Materials and Methods: Two consecutive multiparametric MRI examinations were performed for 83 adults (mean age, 59.0 years; range, 27-82 years; 44 male and 39 female) with 103 SRS-treated brain metastases. Tumor habitats based on contrast-enhanced T1- and T2-weighted images (structural habitats) and those based on the apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) images (physiological habitats) were defined using k-means voxel-wise clustering. The reference standard was based on the pathology or Response Assessment in Neuro-Oncologycriteria for brain metastases (RANO-BM). The association between parameters of single-time or longitudinal tumor habitat and the time to recurrence and the site of recurrence were evaluated using the Cox proportional hazards regression analysis and Dice similarity coefficient, respectively. Results: The mean interval between the two MRI examinations was 99 days. The longitudinal analysis showed that an increase in the hypovascular cellular habitat (low ADC and low CBV) was associated with the risk of recurrence (hazard ratio [HR], 2.68; 95% confidence interval [CI], 1.46-4.91; P = 0.001). During the single-time analysis, a solid low-enhancing habitat (low T2 and low contrast-enhanced T1 signal) was associated with the risk of recurrence (HR, 1.54; 95% CI, 1.01-2.35; P = 0.045). A hypovascular cellular habitat was indicative of the future recurrence site (Dice similarity coefficient = 0.423). Conclusion: After SRS of brain metastases, an increased hypovascular cellular habitat observed using a longitudinal MRI analysis was associated with the risk of recurrence (i.e., treatment resistance) and was indicative of recurrence site. A tumor habitat analysis may help guide future treatments for patients with brain metastases.
In light of recent social concerns related to issues such as water supply pipe deterioration leading to problems like leaks and degraded water quality, the significance of maintenance efforts to enhance water source quality and ensure a stable water supply has grown substantially. In this study, scan statistic was applied to analyze water quality complaints and water leakage accidents from 2015 to 2021 to present a reasonable method to identify areas requiring improvement in water management. SaTScan, a spatio-temporal statistical analysis program, and ArcGIS were used for spatial information analysis, and clusters with high relative risk (RR) were determined using the maximum log-likelihood ratio, relative risk, and Monte Carlo hypothesis test for I city, the target area. Specifically, in the case of water quality complaints, the analysis results were compared by distinguishing cases occurring before and after the onset of "red water." The period between 2015 and 2019 revealed that preceding the occurrence of red water, the leak cluster at location L2 posed a significantly higher risk (RR: 2.45) than other regions. As for water quality complaints, cluster C2 exhibited a notably elevated RR (RR: 2.21) and appeared concentrated in areas D and S, respectively. On the other hand, post-red water incidents of water quality complaints were predominantly concentrated in area S. The analysis found that the locations of complaint clusters were similar to those of red water incidents. Of these, cluster C7 exhibited a substantial RR of 4.58, signifying more than a twofold increase compared to pre-incident levels. A kernel density map analysis was performed using GIS to identify priority areas for waterworks management based on the central location of clusters and complaint cluster RR data.
Analyzing and finding the risk factors in information technology (IT) projects have been discussed because risk management is an important issue in IT project management. This study obtained the risk factor checklists with priorities, analyzed the causal relationship of risk factors, and determined their influences on IT project management. However, only few studies systematically classified IT project risk factors in terms of risk exposure. These studies considered both the probability of occurrence and the degree of risk simultaneously. The present study determined 53 IT project risk factors on the basis of literature and expert group discussions. Additionally, this study presented clustering analysis based on the data of 140 project managers. The IT project risk factor classification framework was divided into four areas (HIHF, HILF, LIHF, and LILF). The present results can be used to help IT project managers establish effective risk management strategies and reduce IT project failures. This study also provides academic implication because it considers both the probability of occurrence and the degree of influence of risk factors.
Qian Fan;Yini Xu;Yingping Xiao;Caimei Yang;Wentao Lyu;Hua Yang
Animal Bioscience
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v.37
no.7
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pp.1213-1224
/
2024
Objective: Enterotypes (ETs) are the clustering of gut microbial community structures, which could serve as indicators of growth performance and carcass traits. However, ETs have been sparsely investigated in waterfowl. The objective of this study was to identify the ileal ETs and explore the correlation of the ETs with growth performance and carcass traits in Muscovy ducks. Methods: A total of 200 Muscovy ducks were randomly selected from a population of 5,000 ducks at 70-day old, weighed and slaughtered. The growth performance and carcass traits, including body weight, dressed weight and evidenced weight, dressed percentage, percentage of apparent yield, breast muscle weight, leg muscle weight, percentage of leg muscle and percentage of breast muscle, were determined. The contents of ileum were collected for the isolation of DNA and 16S rRNA gene sequencing. The ETs were identified based on the 16S rRNA gene sequencing data and the correlation of the ETs with growth performance and carcass traits was performed by Spearman correlation analysis. Results: Three ETs (ET1, ET2, and ET3) were observed in the ileal microbiota of Muscovy ducks with significant differences in number of features and α-diversity among these ETs (p<0.05). Streptococcus, Candida Arthritis, and Bacteroidetes were the presentative genus in ET1 to ET3, respectively. Correlation analysis revealed that Lactococcus and Bradyrhizobium were significantly correlated with percentage of eviscerated yield and leg muscle weight (p<0.05) while ETs were found to have a close association with percentage of eviscerated yield, leg muscle weight, and percentage of leg muscle in Muscovy ducks. However, the growth performance of ducks with different ETs did not show significant difference (p>0.05). Lactococcus were found to be significantly correlated with leg muscle weight, dressed weight, and percentage of eviscerated yield. Conclusion: Our findings revealed a substantial variation in carcass traits associated with ETs in Muscovy ducks. It is implied that ETs might have the potential to serve as a valuable biomarker for assessing duck carcass traits. It would provide novel insights into the interaction of gut microbiota with growth performance and carcass traits of ducks.
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