• Title/Summary/Keyword: Multi-Network

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Estimation of Duck House Litter Evaporation Rate Using Machine Learning (기계학습을 활용한 오리사 바닥재 수분 발생량 분석)

  • Kim, Dain;Lee, In-bok;Yeo, Uk-hyeon;Lee, Sang-yeon;Park, Sejun;Decano, Cristina;Kim, Jun-gyu;Choi, Young-bae;Cho, Jeong-hwa;Jeong, Hyo-hyeog;Kang, Solmoe
    • Journal of The Korean Society of Agricultural Engineers
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    • v.63 no.6
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    • pp.77-88
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    • 2021
  • Duck industry had a rapid growth in recent years. Nevertheless, researches to improve duck house environment are still not sufficient enough. Moisture generation of duck house litter is an important factor because it may cause severe illness and low productivity. However, the measuring process is difficult because it could be disturbed with animal excrements and other factors. Therefore, it has to be calculated according to the environmental data around the duck house litter. To cut through all these procedures, we built several machine learning regression model forecasting moisture generation of litter by measured environment data (air temperature, relative humidity, wind velocity and water contents). 5 models (Multi Linear Regression, k-Nearest Neighbors, Support Vector Regression, Random Forest and Deep Neural Network). have been selected for regression. By using R-Square, RMSE and MAE as evaluation metrics, the best accurate model was estimated according to the variables for each machine learning model. In addition, to address the small amount of data acquired through lab experiments, bootstrapping method, a technique utilized in statistics, was used. As a result, the most accurate model selected was Random Forest, with parameters of n-estimator 200 by bootstrapping the original data nine times.

Convergence CCTV camera embedded with Deep Learning SW technology (딥러닝 SW 기술을 이용한 임베디드형 융합 CCTV 카메라)

  • Son, Kyong-Sik;Kim, Jong-Won;Lim, Jae-Hyun
    • Journal of the Korea Convergence Society
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    • v.10 no.1
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    • pp.103-113
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    • 2019
  • License plate recognition camera is dedicated device designed for acquiring images of the target vehicle for recognizing letters and numbers in a license plate. Mostly, it is used as a part of the system combined with server and image analysis module rather than as a single use. However, building a system for vehicle license plate recognition is costly because it is required to construct a facility with a server providing the management and analysis of the captured images and an image analysis module providing the extraction of numbers and characters and recognition of the vehicle's plate. In this study, we would like to develop an embedded type convergent camera (Edge Base) which can expand the function of the camera to not only the license plate recognition but also the security CCTV function together and to perform two functions within the camera. This embedded type convergence camera equipped with a high resolution 4K IP camera for clear image acquisition and fast data transmission extracted license plate area by applying YOLO, a deep learning software for multi object recognition based on open source neural network algorithm and detected number and characters of the plate and verified the detection accuracy and recognition accuracy and confirmed that this camera can perform CCTV security function and vehicle number plate recognition function successfully.

Platform Interaction and Strategy from the Perspective of Organizational Ecology (조직 생태학 관점에서 본 플랫폼 이해관계자들간의 상호 작용 및 전략)

  • Lee, Sungho;Bae, Sung Joo
    • Journal of Korea Technology Innovation Society
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    • v.22 no.2
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    • pp.220-241
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    • 2019
  • In order to provide theoretical guidance to research in platform strategy, we build the conceptual framework based on the organizational ecology and analyze symbiotic/competitive relationship between platform entities. Platform owner and service provider (i.e. complementors) make symbiotic relationship, where platform owner provide service provider user-base and platform resources such as marketing tools and platform technology, and service provider provide platform owner services which users utilize. In addition to symbiotic relationships, platform owner has competitive relationship with other platform owners, and service provider builds competitive relationship with other service providers. In these relationships, the strategy of platform owner affects service provider and service provider builds a strategy for their own survival and success. This type of interaction makes competitive dynamics in platform. However, previous platform literature focuses on strategies to enhance network effect from the perspective of platform owner. Thus, there is little attention on interaction among the service providers. Using the framework based on community ecology of organizational ecology, we analyze interaction and strategy between platform owner and service provider in the viewpoint of platform openness strategy and platform pricing strategy. This research contributes to the literature of platform strategy by providing a theoretical framework based on organizational ecology to deeply understand the dynamics of platform.

Research and Application of Fault Prediction Method for High-speed EMU Based on PHM Technology (PHM 기술을 이용한 고속 EMU의 고장 예측 방법 연구 및 적용)

  • Wang, Haitao;Min, Byung-Won
    • Journal of Internet of Things and Convergence
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    • v.8 no.6
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    • pp.55-63
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    • 2022
  • In recent years, with the rapid development of large and medium-sized urban rail transit in China, the total operating mileage of high-speed railway and the total number of EMUs(Electric Multiple Units) are rising. The system complexity of high-speed EMU is constantly increasing, which puts forward higher requirements for the safety of equipment and the efficiency of maintenance.At present, the maintenance mode of high-speed EMU in China still adopts the post maintenance method based on planned maintenance and fault maintenance, which leads to insufficient or excessive maintenance, reduces the efficiency of equipment fault handling, and increases the maintenance cost. Based on the intelligent operation and maintenance technology of PHM(prognostics and health management). This thesis builds an integrated PHM platform of "vehicle system-communication system-ground system" by integrating multi-source heterogeneous data of different scenarios of high-speed EMU, and combines the equipment fault mechanism with artificial intelligence algorithms to build a fault prediction model for traction motors of high-speed EMU.Reliable fault prediction and accurate maintenance shall be carried out in advance to ensure safe and efficient operation of high-speed EMU.

The Future of Countermobility Capability with a Literature Analysis from FASCAM to Terrain Shaping Obstacle(TSO) (미래 대기동 작전 능력의 발전방안 연구 -살포식지뢰(FASCAM)로부터 지형 조성 장애물(TSO) 전력을 중심으로-)

  • Park, Byoung-Ho;Sim, Jaeseong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.6
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    • pp.291-298
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    • 2021
  • In this study, the future of countermobility capability is presented by analyzing the status of the countermobility obstacles focusing on the history of landmines and munitions. The conventional landmine was forbidden globally by the CCW and Ottawa Treaty because it caused civilian damage after the war. Because the inhumanity of those mines had been acknowledged, shatterable mines with a self-destruct (SD) function and M93 "HORNET" anti-tank munition with enhanced sensors have been fielded. In 2016, the Obama administration announced a policy that banned all antipersonnel landmines, leaving a considerable gap in the countermobility capability. To deal with these problems, the developments of "SAVO" and the SLEP program of Volcano mines were conducted. In the sense of a long-term approach, the countermobility obstacles, including mines, were chosen as fundamental forces for Multi-Domain Operations and were improved to Terrain Shaping Obstacles (TSO). TSO has improved sensors and mobility kill capabilities and features an enhanced remote control over each munition on the battlefield through a network established with satellite communication. The combined arms countermobility might be fully capable until 2050 if the TSO program can be completed successfully.

The Effect of Factors on Aggression in Adolescents: Focusing on Individual, Parent, Friend Factors and SNS Usage (청소년의 공격성에 영향을 미치는 요인: 개인·부모·친구 요인과 소셜네트워크서비스(SNS) 이용 정도를 중심으로)

  • Lee, Yejin;Kim, Kyong-Beom;Heo, Min-Hee;Noh, Jin-Won;Im, Yu-Mi
    • The Journal of the Korea Contents Association
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    • v.21 no.4
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    • pp.699-706
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    • 2021
  • This study aims to identify the effects of factors on aggression in adolescents, focusing on the individual, parent, friend factors and SNS usage. In particular, this study is to provide a basis for easing aggression in adolescence by considering the emotional relationship of parents and friends. This study analyzed frequency, t-test, one-way batch distribution analysis(ANOVA), and multi-linear regression, using the data from the 7th year of the Korean Children and Youth Panel Survey. As a result, adolescents who frequently use SNS are more aggressive than adolescents who use less. Among the parental factors, the more abuse and excessive interference were found to be more aggressive, and the higher the coach, the lower the aggressiveness. Furthermore, among the friend factors, it has been shown that the higher the alienation, the more aggressive adolescents are. In order to reduce aggression among adolescents, it is necessary to prepare an integrated program considering the emotional relationship of parents and friends, who are the most influential neighbors, rather than simply restricting the use of SNS.

MLP-based 3D Geotechnical Layer Mapping Using Borehole Database in Seoul, South Korea (MLP 기반의 서울시 3차원 지반공간모델링 연구)

  • Ji, Yoonsoo;Kim, Han-Saem;Lee, Moon-Gyo;Cho, Hyung-Ik;Sun, Chang-Guk
    • Journal of the Korean Geotechnical Society
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    • v.37 no.5
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    • pp.47-63
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    • 2021
  • Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.

A Possibility Analysis of Domestic Terrorism in South Korea by Focusing on Afghanistan under the Taliban Forces (탈레반의 아프가니스탄 장악에 따른 국내 테러 발생 가능성 분석)

  • Oh, Hangil;Ahn, Kyewon;Bae, Byunggul
    • Journal of the Society of Disaster Information
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    • v.17 no.4
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    • pp.848-863
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    • 2021
  • Purpose: On August 16, 2021, the Taliban established the Taliban regime after conquering capital Kabul of the Afghan by using the strong alliance of international terrorist organizations. The Taliban carried out terrorism targeting the Korean people, including the kidnapping of Kim Seon-il in 2004, the abduction of a member of the Saemmul Church in 2007, and the attack on Korean Provincial Reconstruction Team in 2009. Therefore, this research has shown the possibility of Taliban terrorism in Korea. Method: Based on the statistical data on terrorism that occurred in Afghanistan, Taliban's various terrorist activities such as tactics, strategies, and weapons are examined. Consequently, the target facilities and the type of terrorist attacks are analyzed. Result: The Taliban are targeting the Afghan government as their main target of attack, and IS and the Taliban differ in their selection of targets for terrorism. Conclusion: From the result of this research, we recommend Korea need to reinforce the counter terrorism system in soft targets. Because If the Taliban, which has seized control of Afghanistan, and IS, which has established a worldwide terrorism network, cooperate to threaten domestic multi-use facilities with bombing, the Republic of Korea may face a terrorist crisis with insufficient resources and counter-terrorism related countermeasures.

Study on the ICT Device Safety System Application Examples in Mines (광산에서의 ICT 장비 활용 및 안전시스템 운용 사례 연구)

  • Kim, Seung-Jun;Ko, Young-Hun;Kim, Jung-Gyu;Seo, Man-Keun;Kim, Jong-Gwan
    • Tunnel and Underground Space
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    • v.32 no.3
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    • pp.194-202
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    • 2022
  • An increased number of cases have occurred in applying ICT technology in the resource development field due to factors such as safety, eco-friendliness, and low cost since the 2000s. In Korea, the 2nd mining master plan specified the significance of converging the full cycle of mining and ICT, while the 3rd mining master plan highlighted ICT and smart mining such as supporting the supply of an ICT mining device and introducing demonstrational smart mining. This study introduces the application of an ICT device and safety system operation in the Jangseong underground mine of Korea Cement Co., Ltd. Currently, Jangseong mine combines two different kinds of 3D equipment including the handheld 3D scanner and multi-station that provides both the measurement and 3D scanning to perform a 3D measurement of the mine. Taken from the 3D measurement of the mine, it is now possible to identify any hazardous areas and abnormalities in different directions and analyze the safety of the crown pillar between two stopes in different level. Besides, the real-time location tracking and communications system have established highly efficient rescue and evacuation plans to effectively deal with any accidents in the mine.

Development of prediction model identifying high-risk older persons in need of long-term care (장기요양 필요 발생의 고위험 대상자 발굴을 위한 예측모형 개발)

  • Song, Mi Kyung;Park, Yeongwoo;Han, Eun-Jeong
    • The Korean Journal of Applied Statistics
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    • v.35 no.4
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    • pp.457-468
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    • 2022
  • In aged society, it is important to prevent older people from being disability needing long-term care. The purpose of this study is to develop a prediction model to discover high-risk groups who are likely to be beneficiaries of Long-Term Care Insurance. This study is a retrospective study using database of National Health Insurance Service (NHIS) collected in the past of the study subjects. The study subjects are 7,724,101, the population over 65 years of age registered for medical insurance. To develop the prediction model, we used logistic regression, decision tree, random forest, and multi-layer perceptron neural network. Finally, random forest was selected as the prediction model based on the performances of models obtained through internal and external validation. Random forest could predict about 90% of the older people in need of long-term care using DB without any information from the assessment of eligibility for long-term care. The findings might be useful in evidencebased health management for prevention services and can contribute to preemptively discovering those who need preventive services in older people.