• Wind and Structures
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• 제29권5호
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• pp.299-312
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• 2019

Due to the rugged terrain, metro lines in mountain city across numerous wide rivers and deep valleys, resulting in instability of high-pier bridge and insecurity of metro train under crosswind. Compared with the conditions of no-wind, crosswind triggers severer vibration of the dynamic system; compared with the short-pier viaduct, the high-pier viaduct has worse stability under crosswind. For these reasons, the running safety of the metro vehicle traveling on a high-pier viaduct under crosswind is analyzed to ensure the safe operation in metro lines in mountain cities. In this paper, a dynamic model of the metro vehicle-track-bridge system under crosswind is established, in which crosswind loads model considering the condition of wind zone are built. After that, the evaluation indices and the calculation parameters have been selected, moreover, the basic characteristics of the dynamic system with high-pier under crosswind are analyzed. On this basis, the response varies with vehicle speed and wind speed are calculated, then the corresponding safety zone is determined. The results indicate that, crosswind triggers drastic vibration to the metro vehicle and high-pier viaduct, which in turn causes running instability of the vehicle. The corresponding safety zone for metro vehicle traveling on the high-pier is proposed, and the metro traffic on the high-pier bridge under crosswind should not exceed the corresponding limited vehicle speed to ensure the running safety.

• Journal of the Korea Society of Computer and Information
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• 제22권1호
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• pp.15-21
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• 2017

In this paper, we present a solution to the problems caused by using only text - based information as an index element when a commercialized missing person indexing system indexes missing persons registered in the database. The existing system could not be used for the missing persons inquiry because it could not formalize the image of the missing person registered together when registering the missing person. To solve these problems, we propose a method to extract the similarity of images by using OpenCV image processing and TensorFlow deep - running image processing, and to process images of missing persons to process them into meaningful information. In order to verify the indexing method used in this paper, we constructed a Web server that operates to provide the information that is most likely to be needed to users first, using the image provided in the non - regular environment of the same subject as the search element.

• Water for future
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• 제6권2호
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• pp.30-37
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• 1973

The coefficient of the current meter generally determined by the maker Its coefficient is subject to being changed with time. Therefore the coefficient of the current meter has to be checked up before it is ready to be used Such an inspection is termed a current meter rating The current meter equipped an electronic apparatus and all the others are to be rated in a rating flume. The price current meter which is most widely used for measuring flow velocities ranging between 0.3m/sec and 3.5m/sec has been used in this study. The length of the flume and the optimum range of the rating in the cross section are determined in the range of 20∼120cm deep, 50∼160cm wide of the flume. In this study, the 23 different kinds of the current meter rating enabled us to determine the constants a and b of the following equation. V=an+b(m/sec) where, n is number of revolution per second(n=N/T) V is velocity(v=D/T) The above constant can be determined by the least squares method and plotting, using the velocity(V=D/T) and the number of revolution per second(n=N/T) obtained from the running distance(D), time(T), the number of revolutin(N), and the running number(m). From the experiments the following conclusions are drawn: 1) The rating flume is large enough if the flume is 110∼120cm deep, and 40∼50m long. 2) The optimum depth for rating of a current meter is in the range of h=40∼50cm.

• Korea Real Estate Review
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• 제27권3호
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• pp.71-86
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• 2017

The purpose of this study was to apply the deep running method to real estate price index predicting and to compare it with the time series analysis method to test the possibility of its application to real estate market forecasting. Various real estate price indices were predicted using the DNN (deep neural networks) and LSTM (long short term memory networks) models, both of which draw on the deep learning method, and the ARIMA (autoregressive integrated moving average) model, which is based on the time seies analysis method. The results of the study showed the following. First, the predictive power of the deep learning method is superior to that of the time series analysis method. Second, among the deep learning models, the predictability of the DNN model is slightly superior to that of the LSTM model. Third, the deep learning method and the ARIMA model are the least reliable tools for predicting the housing sales prices index among the real estate price indices. Drawing on the deep learning method, it is hoped that this study will help enhance the accuracy in predicting the real estate market dynamics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.367-369
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• 2022

With the development of web technology, the web provides customized information that meets the needs of users. Information is provided according to the input form and the user's query, and a web service that provides information that is difficult to search with a search engine is called an in-depth web. These deep webs contain more information than surface webs, but it is difficult to collect information with general crawling, which collects information at the time of the visit. The deep web provides users with information on the server by running script languages such as javascript in their browsers. In this paper, we propose an algorithm capable of exploring dynamically changing websites and collecting information by analyzing scripts for deep web collection. In this paper, the script of the bulletin board of the Korea Centers for Disease Control and Prevention was analyzed for experiments.

• Steel and Composite Structures
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• 제44권2호
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• pp.271-281
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• 2022

This study discusses challenges of running expandable profile liners (EPLs) to isolate trouble zones in directional section of a deep well, and summary the expandable profile liner technology (EPLT) field trial experience. Technically, the trial result reveals that it is feasible to apply the EPLT solving lost-circulation control problem and wellbore instability in the deep directional section. Propose schemes for optimizing the EPLT operation procedure to break through the existing bottleneck of EPLT in the deep directional section. Better-performing transition joints are developed to improve EPL string reliability in high borehole curvature section. High-performing and reliable expanders reduce the number of trips, offer excellent mechanical shaping efficiency, simplify the EPLT operation procedure. Application of the expansion and repair integrated tool could minimize the risk of insufficient expansion and increase the operational length of the EPL string. The new welding process and integrated automatic welding equipment improve the welding quality and EPL string structural integrity. These optimization schemes and recent new advancements in EPLT can bring significant economic benefits and promote the application of EPLT to meet future challenges.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제17권5호
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• pp.119-124
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• 2017

In 1997, IBM's DeepBlue won the world chess championship, Garry Kasparov, and recently, Google's AlphaGo won all three games against Ke Jie, who was ranked 1st among all human Baduk players worldwide, interest in deep running has increased rapidly. DeepPurple, proposed in this paper, is a AI chess engine based on deep learning. DeepPurple Chess Engine consists largely of Monte Carlo Tree Search and policy network and value network, which are implemented by convolution neural networks. Through the policy network, the next move is predicted and the given situation is calculated through the value network. To select the most beneficial next move Monte Carlo Tree Search is used. The results show that the accuracy and the loss function cost of the policy network is 43% and 1.9. In the case of the value network, the accuracy is 50% and the loss function cost is 1, respectively.

• Electronics and Telecommunications Trends
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• 제34권4호
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• pp.23-31
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• 2019

Deep learning is a hot topic in both academic and industrial fields. Deep learning applications can be categorized into two areas. The first category involves applications such as Google Alpha Go using interfaces with human operators to run complicated inference engines in high-performance servers. The second category includes embedded applications for mobile Internet-of-Things devices, automotive vehicles, etc. Owing to the characteristics of the deployment environment, applications in the second category should be bounded by certain H/W and S/W restrictions depending on their running environment. For example, image recognition in an autonomous vehicle requires low latency, while that on a mobile device requires low power consumption. In this paper, we describe issues faced by embedded applications and review popular inference engines. We also introduce a project that is being development to satisfy the H/W and S/W requirements.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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• pp.217-226
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• 1993

As results of not selecting and using farm well pump properly , it's running regime is far away from high efficient zone and running efficiency of farm well pump is lower. The paper analyses unhealthy tendencies of technical state of diving-electric pump, deep well and centrifugal pump which are commonly used in our country. The paper also summarizes several technical innovation plans to raise efficiency : stage change plan, diameter change plan, speed change plan and synthetic technical innovation . Each plan gives a detailed introduction of designing and construction manners, through practical measuring , the synthetic efficiency of innovated well pumps raise above 30 percent. Economic benefit is evident.

• Proceedings of the Korean Institute of Building Construction Conference
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• 한국건축시공학회 2021년도 봄 학술논문 발표대회
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• pp.17-18
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• 2021

The unit-water content of concrete is one of the important factors in determining the quality of concrete and is directly related to the durability of the construction structure, and the current method of measuring the unit-water content of concrete is applied by the Air Meta Act and the Electrostatic Capacity Act. However, there are complex and time-consuming problems with measurement methods. Therefore, high frequency moisture sensor was used for quick and high measurement, and unit-water content of mortar was evaluated through machine running and deep running based on measurement big data.