• Earthquakes and Structures
• /
• v.22 no.2
• /
• pp.185-201
• /
• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Journal of Korea Entertainment Industry Association
• /
• v.14 no.2
• /
• pp.97-107
• /
• 2020

This Study designed to examine the effects of participation motivation of Dance Sports Activation. The dance sports club participants were selected by systematic stratifies cluster random sampling method. The questionnaire was given to 320 members of badminton club members and engaging in the range activity from March 2019 to April 2019. After collecting the questionnaires, I exclude 20 unreliable questionnaires which were incomplete, incorrectly marked or double marked, and used 300 questionnaires for the study. The conclusion of this research was as follows: First, Participation motivation had a effect on enjoyment factor in dance sports club participants. Second, Participation motivation had a effect on exercise dependence in dance sports club participants. Third. Enjoyment factor had a effect on exercise dependence in dance sports club participants. It was concluded that participation motivation would be beneficial for enjoyment factor and exercise dependence in dance sports club participants.

• Land and Housing Review
• /
• v.13 no.2
• /
• pp.81-90
• /
• 2022

This study is based on social needs for green healing spaces assumed to enhance mental health in a city. This study proposes development directions through the analysis of modern social recognition factors for neighborhood gardens. As a research method, web information data was collected using Textom among big data tools. Text Mining was conducted to extract elements and analyze their relationship through keyword analysis, network analysis, and cluster analysis. As a result, first, the healing space and the healing environment were creating an eco-friendly healthy environment in a space close to the neighborhood within the city. Second, neighborhood gardens included projects and activities that involved government, local administration, and citizens by linking facilities as well as living culture and urban environments. These gardens have been reinforced through green welfare and service programs. In conclusion, friendly gardens in the neighborhood for the purpose of public interest, which are beneficial to mental health, are green infrastructures as a healing environment that can produce positive effects.

• Korean Journal of Culture and Social Issue
• /
• v.25 no.3
• /
• pp.203-229
• /
• 2019

The purpose of this study was to identify the factors that constitute masculine norms of masculine in Korean society. The definition of masculinity was to conform to the male-dominated standard formed socially and culturally. The results of in-depth interviews with 20 male participants were used for a concept mapping analysis to explore the configural representations of Korean masculine norms. After extracting the key sentences related to masculine norms, the participants sorted the 55 key sentences based on similarities and assessed the importance, which was then analyzed with multidimensional scaling method and cluster analysis. The result showed two dimensions, one representing social-personal domain and the other implying dominance-support domain as well as six clusters of caregiver, leadership, emotion suppression, job ability and organizational social adaptation, Expects the masculine abilities, power and control. Finally, the implications of this study, limitations, and the suggestions for future research were discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.8
• /
• pp.2188-2208
• /
• 2023

Quality of Service (QoS) is a critical feature of Wireless Sensor Networks (WSNs) with routing algorithms. Data packets are moved between cluster heads with QoS using a number of energy-efficient routing techniques. However, sustaining high scalability while increasing the life of a WSN's networks scenario remains a challenging task. Thus, this research aims to develop an energy-balancing component that ensures equal energy consumption for all network sensors while offering flexible routing without congestion, even at peak hours. This research work proposes a Gravitational Blackhole Search Optimised splay tree routing framework. Based on the splay tree topology, the routing procedure is carried out by the suggested method using three distinct steps. Initially, the proposed GBSO decides the optimal route at initiation phases by choosing the root node with optimum energy in the splay tree. In the selection stage, the steps for energy update and trust update are completed by evaluating a novel reliance function utilising the Parent Reliance (PR) and Grand Parent Reliance (GPR). Finally, in the routing phase, using the fitness measure and the minimal distance, the GBSO algorithm determines the best route for data broadcast. The model results demonstrated the efficacy of the suggested technique with 99.52% packet delivery ratio, a minimum delay of 0.19 s, and a network lifetime of 1750 rounds with 200 nodes. Also, the comparative analysis ensured that the suggested algorithm surpasses the effectiveness of the existing algorithm in all aspects and guaranteed end-to-end delivery of packets.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.17 no.1
• /
• pp.133-144
• /
• 2015

A study was conducted to examine treatment method, proper concentration, and treatment time of gibberellin(GA₃) for human labor saving at harvest in 'Campbell Early' grapevine. Fruit berry thinning reduced labor by GA₃ 40ppm treatment of 5 days prior to full bloom, and, at GA₃ 10, 20, and 40ppm during full bloom, by 14.27~19.15 minutes/tree. Therefore, although labor was reduced by dipping treatment at 40ppm of 5 days prior to full bloom and 20 and 40 ppm during full bloom, severe shattering was observed at 40ppm dipping treatment, and soluble solids decreased, which suggests difficulty with commercialization. The result suggests that proper time and concentration of GA₃ fruit cluster dipping treatment at full bloom and 10 and 20ppm, respectively.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.5
• /
• pp.129-153
• /
• 2023

This study was conducted in the context of the Covid-19 pandemic by analyzing a large amount of press report frames regarding the Covid-19 vaccine which is of great public interest, in order to explore the role and direction of trusted media as core elements of crisis communication. The study period lasted for eight months beginning in November 2020 when the development of the Covid-19 vaccine was in progress until June 2021. Set-up as research subjects were the Chosun Ilbo, Joongang Ilbo, Dong-A Ilbo and Hankyoreh according to their public confidence rankings and number of readers.The analysis method used structured topic Modeling (STM) and semantic network analysis. As a result, based on a clear cluster of word structures and a central analysis value, a total of 64 relevant frames, 16 for each news company, were gathered. In the third phase a comparative analysis of the four news companies was carried out to verify the organizational degree of the frames and substantial differences.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.11
• /
• pp.169-178
• /
• 2009

There are various approaches that retrieve information from video. However, previous approaches have considered just object information and relationship between objects without story information to retrieve contents. To retrieve exact information at video, we need analyzing approach based on characters and community since these are body of story proceeding. Therefore, this paper describes video information retrieval methodology based on character information. Characters progress story to form relationship through conversations. We can analyze the relationship between characters in a story with the methods that classifies role grades and clusters communities of characters. In this paper, for these, we propose the Character-net and describe how to classify role grades and cluster communities at Character-net. And we show this method to be efficient.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.168-168
• /
• 2020

This study is to evaluate the drought-related bigdata characteristics published from South Korean by developing crawler. The 5 years (2013 ~ 2017) drought-related posted articles were collected from Korean internet search engine 'NAVER' which contains 13 main and 81 local daily newspapers. During the 5 years period, total 40,219 news articles including 'drought' word were found using crawler. To filter the homonyms liken drought to soccer goal drought in sports, money drought economics, and policy drought in politics often used in South Korea, the quality control was processed and 47.8 % articles were filtered. After, the 20,999 (52.2 %) drought news articles of this study were classified into four categories of water deficit (WD), water security and support (WSS), economic damage and impact (EDI), and environmental and sanitation impact (ESI) with 27, 15, 13, and 18 drought-related keywords in each category. The WD, WSS, EDI, and ESI occupied 41.4 %, 34.5 %, 14.8 %, and 9.3 % respectively. The drought articles were mostly posted in June 2015 and June 2017 with 22.7 % (15,097) and 15.9 % (10,619) respectively. The drought news articles were spatiotemporally compared with SPI (Standardized Precipitation Index) and RDI (Reservoir Drought Index) were calculated. They were classified into administration boundaries of 8 main cities and 9 provinces in South Korea because the drought response works based on local government unit. The space-time clustering between news articles (WD, WSS, EDI, and ESI) and indices (SPI and RDI) were tried how much they have correlation each other. The spatiotemporal clusters detection was applied using SaTScan software (Kulldorff, 2015). The retrospective and prospective cluster analyses were conducted for past and present time to understand how much they are intensive in clusters. The news articles of WD, WSS and EDI had strong clusters in provinces, and ESI in cities.

• Annual Conference of KIPS
• /
• 2023.05a
• /
• pp.357-359
• /
• 2023

This paper proposes a hybrid recommendation system (RS) model that overcomes the limitations of traditional approaches such as data sparsity, cold start, and scalability by combining collaborative filtering and context-aware techniques. The objective of this model is to enhance the accuracy of recommendations and provide personalized suggestions by leveraging the strengths of collaborative filtering and incorporating user context features to capture their preferences and behavior more effectively. The approach utilizes a novel method that combines contextual attributes with the original user-item rating matrix of CF-based algorithms. Furthermore, we integrate k-mean++ clustering to group users with similar preferences and finally recommend items that have highly rated by other users in the same cluster. The process of partitioning is the use of the rating matrix into clusters based on contextual information offers several advantages. First, it bypasses of the computations over the entire data, reducing runtime and improving scalability. Second, the partitioned clusters hold similar ratings, which can produce greater impacts on each other, leading to more accurate recommendations and providing flexibility in the clustering process. keywords: Context-aware Recommendation, Collaborative Filtering, Kmean++ Clustering.