• Title/Summary/Keyword: Test Network

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Research on Impact Sensors for Developing the Electronic Body Protector of Taekwondo (태권도 전자호구 개발을 위한 충격감지 센서 연구)

  • Ki, Jae-Sug;Jeong, Dong-Hwa;Lee, Hyun-Jun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.4
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    • pp.648-655
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    • 2019
  • This paper proposes the differential development of a Taekwondo electronic body protector. For this development, the most suitable sensor system was selected after analyzing and testing various sensor methods (magnetic sensors, electric capacity sensors, contact switch sensors, and piezo-film sensors) that could be applied in the electronic body protector, the selected sensors were distributed to the body and feet to make a more precise hit score, unlike the existing system in which all sensors are centralized on the body. Furthermore, it aims to illuminate using a lightweight film-type piezoelectric sensor on the body protector. In the case of an existing electronic body protector, all sensors and network device were concentrated on the body protector, so users need to purchase a set if they want it. On the other hand, the proposed system cloud can be used individually using a smart scoring WEP program. The effects of decreasing weight by up to 20% were compared with those of the existing system. Setting up a test facility is very difficult, so more study will be needed to analyze the effects of a hit.

Forecasting daily peak load by time series model with temperature and special days effect (기온과 특수일 효과를 고려하여 시계열 모형을 활용한 일별 최대 전력 수요 예측 연구)

  • Lee, Jin Young;Kim, Sahm
    • The Korean Journal of Applied Statistics
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    • v.32 no.1
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    • pp.161-171
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    • 2019
  • Varied methods have been researched continuously because the past as the daily maximum electricity demand expectation has been a crucial task in the nation's electrical supply and demand. Forecasting the daily peak electricity demand accurately can prepare the daily operating program about the generating unit, and contribute the reduction of the consumption of the unnecessary energy source through efficient operating facilities. This method also has the advantage that can prepare anticipatively in the reserve margin reduced problem due to the power consumption superabundant by heating and air conditioning that can estimate the daily peak load. This paper researched a model that can forecast the next day's daily peak load when considering the influence of temperature and weekday, weekend, and holidays in the Seasonal ARIMA, TBATS, Seasonal Reg-ARIMA, and NNETAR model. The results of the forecasting performance test on the model of this paper for a Seasonal Reg-ARIMA model and NNETAR model that can consider the day of the week, and temperature showed better forecasting performance than a model that cannot consider these factors. The forecasting performance of the NNETAR model that utilized the artificial neural network was most outstanding.

A Study on the Changes in Korean Ocean Carriers' Financial Ratios and Profitability Before and After the Bankruptcy of the H-Line Carrier (H선사 파산전후 국적외항선사의 재무비율 차이분석과 영향요인 연구)

  • Kim, Myung-Jae;Ahn, Ki-Myung
    • Journal of Navigation and Port Research
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    • v.44 no.6
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    • pp.541-549
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    • 2020
  • This study conducts differential analysis on the financial positions of Korean shipping companies before and after the bankruptcy of the H carrier, looking specifically at their financial ratios, profit and loss patterns, and other factors related to their financial operation. Firstly, it was discovered that major measures of financial health, such as average assets per carrier, were not affected by the bankruptcy of the H carrier. However, despite this, most carriers experienced large changes in profits and losses, with total sales and shipping revenues averaging 424.5 billion won and 381.7 billion won respectively before the bankruptcy, but falling by half to 252.1 billion won and 234.6 billion won after the bankruptcy. Additionally, charter revenues and expenses also dropped by more than half. EBIT/sales and pre-tax revenue margins were also heavily affected after the bankruptcy, with both figures averaging 8% and 3% respectively before the bankruptcy, but falling into the negative range at -2% and -8% post-bankruptcy, resulting in significant deterioration in operational profitability. The study concludes that there is an urgent need to establish a global sales network, improve cost structures, and consistently secure stable cargo in order to increase Korean carriers' profitability. Of all financial measures, liquidity and total asset efficiency were identified as the most severely-impacted by the H carrier bankruptcy, thereby requiring the most pressing policy addressing.

The mediating effect between the degree to provide emotional labor and personal relationship in the intent to stay for Care worker (돌봄 여성노동자의 감정노동수행정도와 직무지속의사와의 관계에 있어 대인관계의 매개효과)

  • Ji, Eun Gu;Kim, Min Ju;Lee, Won Ju
    • 한국사회정책
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    • v.20 no.3
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    • pp.141-170
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    • 2013
  • The purpose of this study is to find out the relationship among the degree to provide emotional labor, personal relationship and the intent to stay of female care service workers. Specifically, this study focuses on the mediating effect of the personal relationship (client and agency relation). The path analysis and structural equation modeling analysis were performed on the collected data using SPSS18.0. and AMOS 8.0. And Sobel test conducted for examine the mediating effect. The results are the followings. First, the result of the analysis showed that agency relationship was an indirect factor as the partial mediating effect on relationship between the degree to provide emotional labor and the intent to stay for the care women workers. The result suggests that education utilizing various techniques and strategies to overcome the difficulty accompanied by emotional labor such as communication education and the government try to effort managing and controlling the agency which impact on the labor condition of care workers. Second, the government also tries to provide the trust and collaboration network system which construct a good relationship between the care worker and the agency.

Predicting Acculturation for Chinese International Students in Korea: The Role of Social Support through SNS (SNS 이용 동기와 사회적 지지가 문화적응에 미치는 영향 - 국내 거주 중국인 유학생의 문화적응을 중심으로)

  • Moon, Shin-Il;Jia, Liao;Lee, Hyunjoo;Kim, Kitae
    • The Journal of the Korea Contents Association
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    • v.21 no.1
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    • pp.722-732
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    • 2021
  • A recent rapid growth in the number of Chinese international students in Korea has generated interest in the key factors to affect their acculturation in domestic culture. In accordance with the growing interest, the present study aims to empirically test and analyze the effects of demographics (gender, age, the length of stay, the length of Korean language education and the level of Korean language skills), SNS use patterns (personal network sizes and hours of use for Korean and Chinese SNS, and motivations of Korean or Chinese SNS uses), and social support through Korean and Chinese SNS on acculturation for Chinese international students in Korea. A total of 322 Chinese international students in Korea participated in the online survey. Results showed that use of Chinese SNS for entertainment had an negative impact on the acculturation, while the use of Korean SNS had an overall positive impact. Finally, this study suggests that the practitioners regarding the issue of acculturation for international students in Korea should focus more on specific guidelines to help their appropriate SNS uses rather than on to prevent their SNS addiction problems.

The Prediction of Cryptocurrency on Using Text Mining and Deep Learning Techniques : Comparison of Korean and USA Market (텍스트 마이닝과 딥러닝을 활용한 암호화폐 가격 예측 : 한국과 미국시장 비교)

  • Won, Jonggwan;Hong, Taeho
    • Knowledge Management Research
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    • v.22 no.2
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    • pp.1-17
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    • 2021
  • In this study, we predicted the bitcoin prices of Bithum and Coinbase, a leading exchange in Korea and USA, using ARIMA and Recurrent Neural Networks(RNNs). And we used news articles from each country to suggest a separated RNN model. The suggested model identifies the datasets based on the changing trend of prices in the training data, and then applies time series prediction technique(RNNs) to create multiple models. Then we used daily news data to create a term-based dictionary for each trend change point. We explored trend change points in the test data using the daily news keyword data of testset and term-based dictionary, and apply a matching model to produce prediction results. With this approach we obtained higher accuracy than the model which predicted price by applying just time series prediction technique. This study presents that the limitations of the time series prediction techniques could be overcome by exploring trend change points using news data and various time series prediction techniques with text mining techniques could be applied to improve the performance of the model in the further research.

Automatic Bee-Counting System with Dual Infrared Sensor based on ICT (ICT 기반 이중 적외선 센서를 이용한 꿀벌 출입 자동 모니터링 시스템)

  • Son, Jae Deok;Lim, Sooho;Kim, Dong-In;Han, Giyoun;Ilyasov, Rustem;Yunusbaev, Ural;Kwon, Hyung Wook
    • Journal of Apiculture
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    • v.34 no.1
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    • pp.47-55
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    • 2019
  • Honey bees are a vital part of the food chain as the most important pollinators for a broad palette of crops and wild plants. The climate change and colony collapse disorder (CCD) phenomenon make it challenging to develop ICT solutions to predict changes in beehive and alert about potential threats. In this paper, we report the test results of the bee-counting system which stands out against the previous analogues due to its comprehensive components including an improved dual infrared sensor to detect honey bees entering and leaving the hive, environmental sensors that measure ambient and interior, a wireless network with the bluetooth low energy (BLE) to transmit the sensing data in real time to the gateway, and a cloud which accumulate and analyze data. To assess the system accuracy, 3 persons manually counted the outgoing and incoming honey bees using the video record of 360-minute length. The difference between automatic and manual measurements for outgoing and incoming scores were 3.98% and 4.43% respectively. These differences are relatively lower than previous analogues, which inspires a vision that the tested system is a good candidate to use in precise apicultural industry, scientific research and education.

Visibility Analysis of Iridium Communication for SNIPE Nano-Satellite (SNIPE 초소형위성용 Iridium 통신 모듈의 가시성 분석)

  • Cho, Dong-Hyun;Kim, Hongrae;Kim, Hae-Dong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.2
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    • pp.127-135
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    • 2022
  • Compared to the continuous increase of domestic nano-satellite development cases, the initial communication success rate is relatively low. In a situation where communication cases of LEO satellites using commercial satellite communication networks are increasing recently. In this situation, the SNIPE project developed by the KASI(Korea Astronomy and Space Science Institute), KARI(Korea Aerospace Research Institute), and Yonsei University apply an Iridium module for communication test to the SNIPE nano-satellites. Therefore, in this paper, the visibility analysis of the iridium module on the SNIPE satellite was analyzed under considering the orbital and communication environment of the iridium satellite constellation and the attitude control mode. In the case of LEO satellites, the communication possibility was limited due to the relatively small iridium communication coverage for high altitude and the high doppler shift considered in the iridium communication network. For this reason, in this paper, it could be simulated that there was a more performance difference according to the difference in relative RAAN(Right Ascension of Ascending Node) angle with the Iridium constellation. Finally, by checking the visibility of communication module under the tumbling situation that occurred during the initial deployment of the nano-satellite, the possibility of using the iridium communication technology was analyzed.

The Prediction of Durability Performance for Chloride Ingress in Fly Ash Concrete by Artificial Neural Network Algorithm (인공 신경망 알고리즘을 활용한 플라이애시 콘크리트의 염해 내구성능 예측)

  • Kwon, Seung-Jun;Yoon, Yong-Sik
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.5
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    • pp.127-134
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    • 2022
  • In this study, RCPTs (Rapid Chloride Penetration Test) were performed for fly ash concrete with curing age of 4 ~ 6 years. The concrete mixtures were prepared with 3 levels of water to binder ratio (0.37, 0.42, and 0.47) and 2 levels of substitution ratio of fly ash (0 and 30%), and the improved passed charges of chloride ion behavior were quantitatively analyzed. Additionally, the results were trained through the univariate time series models consisted of GRU (Gated Recurrent Unit) algorithm and those from the models were evaluated. As the result of the RCPT, fly ash concrete showed the reduced passed charges with period and an more improved resistance to chloride penetration than OPC concrete. At the final evaluation period (6 years), fly ash concrete showed 'Very low' grade in all W/B (water to binder) ratio, however OPC concrete showed 'Moderate' grade in the condition with the highest W/B ratio (0.47). The adopted algorithm of GRU for this study can analyze time series data and has the advantage like operation efficiency. The deep learning model with 4 hidden layers was designed, and it provided a reasonable prediction results of passed charge. The deep learning model from this study has a limitation of single consideration of a univariate time series characteristic, but it is in the developing process of providing various characteristics of concrete like strength and diffusion coefficient through additional studies.

A Study on the Policy Direction for the Introduction and Activation of Smart Factories by Korean SMEs (우리나라 중소기업의 스마트 팩토리 수용 및 활성화 제고를 위한 정책 방향에 대한 연구)

  • Lee, Yong-Gyu;Park, Chan-Kwon
    • Korean small business review
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    • v.42 no.4
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    • pp.251-283
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    • 2020
  • The purpose of this study is to provide assistance to the establishment of related policies to improve the level of acceptance and use of smart factories for SMEs in Korea. To this end, the Unified Technology Acceptance Model (UTAUT) was extended to select additional factors that could affect the intention to accept technology, and to demonstrate this. To achieve the research objective, a questionnaire composed of 7-point Likert scales was prepared, and a survey was conducted for manufacturing-related companies. A total of 136 questionnaires were used for statistical processing. As a result of the hypothesis test, performance expectation and social influence had a positive (+) positive effect on voluntary use, but effort expectation and promotion conditions did not have a significant effect. As an extension factor, the network effect and organizational characteristics had a positive (+) effect, and the innovation resistance had a negative effect (-), but the perceived risk had no significant effect. When the size of the company is large, the perceived risk and innovation resistance are low, and the level of influencing factors for veterinary intentions, veterinary intentions, and veterinary behaviors are excluded. Through this study, factors that could have a positive and negative effect on the adoption (reduction) of smart factory-related technologies were identified and factors to be improved and factors to be reduced were suggested. As a result, this study suggests that smart factory-related technologies should be accepted.