• Title/Summary/Keyword: data characteristics

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A Regression Equation of Tank Model Parameters for Daily Runoff Estimation in a Region with Insufficient Hydrological Data (미계측유역의 일유출량 추정을 위한 탱크모형 매개변수의 회귀식 산정(수공))

  • 김선주;김필식;윤찬영
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2000.10a
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    • pp.412-418
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    • 2000
  • The purpose of this study is estimation of daily runoff in the watershed with insufficient hydrological data using tank model. In order to estimate, twentysix watersheds were selected to calibrate tank model parameters that were defined by a trial and error method. Results were correlated with characteristics of watershed. Relationships between the parameters and the watershed characteristics were derived by a multiple regression analysis. The simulation results were in agreement with the observed data.

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Characteristics of 5/8 Modulation Code of Misalignments for Holographic Data Storage (홀로그래픽 저장장치용 5/8변조 부호의 어긋남 특성)

  • Kim, Jin-Young;Lee, Jae-Jin
    • Transactions of the Society of Information Storage Systems
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    • v.6 no.2
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    • pp.47-51
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    • 2010
  • We investigate misalignment characteristics of 5/8 modulation code for holographic data storage. The 5/8 modulation code does not have any isolated patterns that is the most unwanted problem for holographic data storage. As the results, the 5/8 modulation code showed a strong side of misalignments, and the code has the best performance among uncoded, 5/9, and 6/8 modulation codes when there are large misalignments.

The Characteristics and Spatio-temporal Distribution of Fish Schools during Summer in the Marine Ranching Area (MRA) of Yeosu using Acoustic Data (음향 자료를 이용한 하계 여수 바다목장 해역에서 어군의 시·공간 분포와 특징)

  • Yoon, Eun-A;Hwang, Doo-Jin;Kim, Ho-Sang;Lee, Kyung-Seon
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.47 no.3
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    • pp.283-291
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    • 2014
  • This study assessed dominant fish species, and the characteristics and spatio-temporal distribution of fish schools using acoustic and catch data in the marine ranching area (MRA) of Yeosu in July and August 2013. Acoustic data were collected using a 200-kHz dual beam transducer, and catch data were analyzed through auction data generated by a set net installed in the MRA. More fish schools were detected by acoustic methods in July than in August. The temporal distribution of fish schools differed between July and August, but, many schools demonstrated a high mean volume scattering strength (SV) around artificial reefs. Additionally, the characteristics of fish schools detected by echograms and the species caught by set nets differed between July and August. The dominant fish species were Engraulis japonicus, Pampus argenteus, Scomberomorus niphonius, and Pampus echinogaster in July, and approximately 85% of the catch in August consisted of Scomberomorus niphonius. Therefore, hydro-acoustic tools are useful for estimating fish school characteristics in large areas over a short period. To determine species, it is important to conduct net sampling surveys during the acoustic surveys. However, if a database of fish school characteristics organized by species is constructed through continuous study, it could be possible to identify fish species through acoustic methods alone.

The Relationship among Characteristics of Fashion Influencers, Relationship Immersion, and Purchase Intention

  • KIM, Juhyun;KIM, Naeeun;KIM, Mi-Sook
    • The Journal of Industrial Distribution & Business
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    • v.12 no.4
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    • pp.35-51
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    • 2021
  • Purpose: As the digital environment has expanded opportunity for consumers to acquire information from social media and social network services(SNS), With this environment, influencer has not only promoted products, but also participated in distribution and influencing on their followers. Despite the increasing interest in influencers, there has not been enough research on the structure of fashion influencer, relationship of immersion and purchase intention. This study examined the effects of fashion influencers' characteristics to the immersion of relationship with followers and purchase intention. Research design, data and methodology: For data collection, a pilot survey and the final survey were conducted. The pilot survey data was conducted to 50 female SNS users following fashion influencers. Based on the pilot tests, questionnaire was revised and the final survey was conducted online from august 22 to September 1, 2019 to female SNS users who have followed fashion influencer. A total of 408 data were collected, and exploratory factor analysis, correlation analysis, and structural equational modeling techniques were employed for the data analyses using AMOS 26.0 and SPSS 26.0. Results: First, five factors were extracted for the fashion influencers' characteristics: interactivity, similarity, reliability, expertise and attractiveness. Second, fashion influences' reliability, expertise, similarity, interactivity have a positive (+) effects on relationship immersion; however, attractiveness has no effect on relationship immersion with followers and fashion influencer. It was also determined that relationship immersion had positive (+) influences on purchase intention. The relationship immersion has been found to have a partially mediated effect and similarity has complete mediated effects between interactivity, reliability, and expertise of fashion influencers and purchasing intentions. In terms of fashion opinion leadership, it was found to have a significant influence on purchase intention only for low fashion leadership groups. Conclusions: The present study found the structural relationships among the influencer characteristics, relationship immersion and purchase intentions to provide framework for succeeding research. This research revealed academic association of intention of purchasing through use of fashion social media and fashion influencer marketing. The results also showed the practical implications that fashion influencers' expertise and reliability perceived by their followers are key determinants to success in influencer marketing.

A Study on GPR Image Classification by Semi-supervised Learning with CNN (CNN 기반의 준지도학습을 활용한 GPR 이미지 분류)

  • Kim, Hye-Mee;Bae, Hye-Rim
    • The Journal of Bigdata
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    • v.6 no.1
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    • pp.197-206
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    • 2021
  • GPR data is used for underground exploration. The data gathered are interpreted by experts based on experience as the underground facilities often reflect GPR. In addition, GPR data are different in the noise and characteristics of the data depending on the equipment, environment, etc. This often results in insufficient data with accurate labels. Generally, a large amount of training data have to be obtained to apply CNN models that exhibit high performance in image classification problems. However, due to the characteristics of GPR data, it makes difficult to obtain sufficient data. Finally, this makes neural networks unable to learn based on general supervised learning methods. This paper proposes an image classification method considering data characteristics to ensure that the accuracy of each label is similar. The proposed method is based on semi-supervised learning, and the image is classified using clustering techniques after extracting the feature values of the image from the neural network. This method can be utilized not only when the amount of the labeled data is insufficient, but also when labels that depend on the data are not highly reliable.

Comparison of Epistemic Characteristics of Using Primary and Secondary Data in Inquiries about Noise Conducted by Elementary School Preservice Teachers: Focusing on the Cases of Science Inquiry Reports (소음에 대한 초등 예비교사들의 탐구에서 나타나는 1차 데이터와 2차 데이터 활용의 인식적 특징 비교 - 과학탐구 보고서 사례를 중심으로 -)

  • Chang, Jina;Na, Jiyeon
    • Journal of Korean Elementary Science Education
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    • v.43 no.1
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    • pp.81-94
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    • 2024
  • This study explores and conducts an in-depth comparison of the epistemic characteristics in different data types utilized in the science inquiries of preservice teachers regarding noise as a risk in everyday life. Focusing on primary and secondary data in the context of science inquiries about noise, we examined how these data types differ in science inquires in terms of inquiry design, data collection, and analyses. The findings reveal that sensor-based primary data enable direct measurement and observation of key phenomena. Conversely, secondary data rely on predetermined measurement methods within a public data system. These differences require different epistemic considerations during the inquiry process. Based on these findings, we discuss the educational implications concerning teaching approaches for science inquiries, teacher education for inquiry teaching, and the development of risk response competencies in preparation for the VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) era.

Side-Channel Archive Framework Using Deep Learning-Based Leakage Compression (딥러닝을 이용한 부채널 데이터 압축 프레임 워크)

  • Sangyun Jung;Sunghyun Jin;Heeseok Kim
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.34 no.3
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    • pp.379-392
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    • 2024
  • With the rapid increase in data, saving storage space and improving the efficiency of data transmission have become critical issues, making the research on the efficiency of data compression technologies increasingly important. Lossless algorithms can precisely restore original data but have limited compression ratios, whereas lossy algorithms provide higher compression rates at the expense of some data loss. There has been active research in data compression using deep learning-based algorithms, especially the autoencoder model. This study proposes a new side-channel analysis data compressor utilizing autoencoders. This compressor achieves higher compression rates than Deflate while maintaining the characteristics of side-channel data. The encoder, using locally connected layers, effectively preserves the temporal characteristics of side-channel data, and the decoder maintains fast decompression times with a multi-layer perceptron. Through correlation power analysis, the proposed compressor has been proven to compress data without losing the characteristics of side-channel data.

Analysis of Soil Moisture Characteristics in Nut Pine Forest about Seasons and Soil Layers (잣나무림에서의 시기별 토층별 토양수분 특성분석)

  • Hong, Eun-Mi;Choi, Jin-Yong;Yoo, Seung-Hwan;Nam, Won-Ho
    • Journal of The Korean Society of Agricultural Engineers
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    • v.54 no.4
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    • pp.105-114
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    • 2012
  • Soil moisture plays a pivotal role in hydrological processes, especially in the forest which covers more than 64% of the national land. Soil moisture was monitored to analyze soil moisture change characteristics in terms of time and soil layers in this study. 2 Years soil moisture change data was obtained from the experimental nut pine forest and statistical analysis including auto-correlation and cross-corelation among soil moisture data from different soil layers was conducted. Using the monitored soil moisture data, a relationship between soil moisture change and precipitation was analyzed and seasonal soil moisture change characteristics were analyzed. From the result of inter-relationships among soil layers in terms of season and time lag, soil moisture change characteristics in the nut pine forest were upper soil layers were much sensitive than lowers, and seasonal variation if soil moisture for upper soil layers were bigger than lowers showing low correlation with precipitation in winter and spring due to freezing and snowfalls.

Analysis on the Characterstics of Consumers on Social commerce

  • Kim, Pan-Jin;Jung, Yeon-Hee
    • Journal of Distribution Science
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    • v.10 no.11
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    • pp.5-10
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    • 2012
  • Purpose - The purpose of this study is to investigate the impact of awareness on the characteristics of a consumers' social commerce. This study examines whether the characteristics of social commerce influence the purchase intentions in accommodating these types of social commerce. Research design, data, methodology - The data for the study were collected and analyzed from a sample of 126 adult customers, comprising both males and females, using social commerce. The survey was conducted and the results aggregated through distributing a copy to each participant. For statistical analysis of the data collected, SPSS 18.0 statistical package was used. Results - The results can be summarized as follows. First, the perceptions about the characteristics of Social Commerce demonstrated a significant effect for attitudes. Second, the attitudes demonstrated positive effects on purchase intention. Third, the subjective norm affected the purchase intention. Fourth, perceived behavioral control influenced the purchase intentions. Conclusions - As a result, perceptions about the characteristics of Social Commerce may be seen in the positive effects on purchase intention. Using social commerce in the future, retailers would need to increase the scope of the study, through applying more diverse characteristics of Social Commerce.

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A Study on the Flow Characteristics of the Spray Nozzle (관창의 유동특성에 관한 연구)

  • 이동명
    • Fire Science and Engineering
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    • v.17 no.3
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    • pp.55-60
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    • 2003
  • This study established analysis theory for flow characteristics prediction of the spray nozzle and predicted discharge and discharge type of the spray nozzle from numerical analysis. It could know that discharge type of the spray nozzle from prediction data determine to position of nozzle and needle, and flow characteristics prediction of the spray nozzle could know that the characteristics according to shape of nozzle and needle is decided. New model of the spray nozzle that can maximize efficiency of fire suppression from flow characteristics and prediction data of the spray nozzle is presented. The result of this study utilize to data necessary to develop new model of the spray nozzle. Also the result of this study wish to contribute to resource technology security of the spray nozzle, technique ripple effect enlargement of same kind industry and technical development activation of fire protection field etc.