• Title/Summary/Keyword: internal world model

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A hybrid method for predicting the dynamic response of free-span submarine pipelines

  • Li, Tongtong;Duan, Menglan;Liang, Wei;An, Chen
    • Ocean Systems Engineering
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    • v.6 no.4
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    • pp.363-375
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    • 2016
  • Large numbers of submarine pipelines are laid as the world now is attaching great importance to offshore oil exploitation. Free spanning of submarine pipelines may be caused by seabed unevenness, change of topology, artificial supports, etc. By combining Iwan's wake oscillator model with the differential equation which describes the vibration behavior of free-span submarine pipelines, the pipe-fluid coupling equation is developed and solved in order to study the effect of both internal and external fluid on the vibration behavior of free-span submarine pipelines. Through generalized integral transform technique (GITT), the governing equation describing the transverse displacement is transformed into a system of second-order ordinary differential equations (ODEs) in temporal variable, eliminating the spatial variable. The MATHEMATICA built-in function NDSolve is then used to numerically solve the transformed ODE system. The good convergence of the eigenfunction expansions proved that this method is applicable for predicting the dynamic response of free-span pipelines subjected to both internal flow and external current.

SOC Sustaining Strategy for HEV through State-machine Control (하이브리드 차량의 SOC 유지전략 방법)

  • Byun, Sang-Min;Kim, Beom-Soo;Cha, Suk-Won
    • New & Renewable Energy
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    • v.4 no.4
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    • pp.65-71
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    • 2008
  • Considering the world's environmental problem, HEVs are projected as one of the solution. The keys of the HEV cruise control are expanding the use of electric motor and operating the internal combustion engine in the efficient region. This paper presents a new structure of SOC sustaining model where state-machine control is used. The proposed model defines battery charging and discharging as states and SOC of the battery as control variables. In this paper, we introduce various methods in deterministic rule-based control for HEV and describe a new SOC sustaining controller used by state-machine.

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A STUDY ON INTANGIBLE ASSET EVALUATION MODELING FOR CONSTRUCTION MANAGEMENT EFFICIENCY

  • Soyean Lim;Hyun-Chul Lee;Woo-Sung Yoon;Seong-Seok Go
    • International conference on construction engineering and project management
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    • 2009.05a
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    • pp.876-882
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    • 2009
  • With overall opening of global construction market by World Trade Organization (WTO) agreements, importance of management efficiency of construction industry which considers both tangible and intangible assets is recently being recognized in our nation. That is, efforts for reinforcement of competitiveness must be placed through maximization of values of internal and external intangible assets of construction industry such as management innovation, information, investment in technology and R&D and intellectual property. Accordingly in this study, evaluation criteria for intangible assets of construction industry were investigated and classified. Using such criteria, evaluation index and model were established based on the degree of importance of each criterion. The purpose of this study is to review importance of intangible assets in terms of competitiveness and management efficiency of construction industry and to provide basic data for establishment of intangible assets and revitalization of investment.

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A Study on the Life Prediction of Lithium Ion Batteries Based on a Convolutional Neural Network Model

  • Mi-Jin Choi;Sang-Bum Kim
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.3
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    • pp.118-121
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    • 2023
  • Recently, green energy support policies have been announced around the world in accordance with environmental regulations, and asthe market grows rapidly, demand for batteries is also increasing. Therefore, various methodologies for battery diagnosis and recycling methods are being discussed, but current accurate life prediction of batteries has limitations due to the nonlinear form according to the internal structure or chemical change of the battery. In this paper, CS2 lithium-ion battery measurement data measured at the A. James Clark School of Engineering, University of Marylan was used to predict battery performance with high accuracy using a convolutional neural network (CNN) model among deep learning-based models. As a result, the battery performance was predicted with high accuracy. A data structure with a matrix of total data 3,931 ☓ 19 was designed as test data for the CS2 battery and checking the result values, the MAE was 0.8451, the RMSE was 1.3448, and the accuracy was 0.984, confirming excellent performance.

A Resource Allocation Model for Data QC Activities Using Cost of Quality (품질코스트를 이용한 데이터 QC 활동의 자원할당 모형 연구)

  • Lee, Sang-Cheol;Shin, Wan-Seon
    • IE interfaces
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    • v.24 no.2
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    • pp.128-138
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    • 2011
  • This research proposes a resource allocation model of Data QC (Quality Control) activities using COQ (Cost of Quality). The model has been developed based on a series of research efforts such as COQ classifications, weight determination of Data QC activities, and an aggregation approach between COQ and Data QC activities. In the first stage of this research, COQ was divided into the four typical classifications (prevention costs, appraisal costs, internal failure costs and external failure costs) through the opinions from five professionals in Data QC. In the second stage, the weights of Data QC activities were elicited from the field professionals. An aggregation model between COQ and Data QC activities has been then proposed to help the practitioners make a resource allocation strategy. DEA (Data Envelopment Analysis) was utilized for locating efficient decision points. The proposed resource allocation model has been validated using the case of Korea national defense information system. This research is unique in that it applies the concept of COQ to the data management for the first time and that it demonstrates a possible contribution to a real world case for budget allocation of national defense information.

Camera Calibration And Lens of Distortion Model Constitution for Using Artificial Neural Networks (신경망을 이용한 렌즈의 왜곡모델 구성 및 카메라 보정)

  • Kim, Min-Suk;Nam, Chang-Woo;Woo, Dong-Min
    • Proceedings of the KIEE Conference
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    • 1999.07g
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    • pp.2923-2925
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    • 1999
  • The objective of camera calibration is to determine the internal optical characteristics of camera and 3D position and orientation of camera with respect to the real world. Calibration procedure applicable to general purpose cameras and lenses. The general method to revise the accuracy rate of calibration is using mathematical distortion of lens. The effective og calibration show big difference in proportion to distortion of camera lens. In this paper, we propose the method which calibration distortion model by using neural network. The neural network model implicity contains all the distortion model. We can predict the high accuracy of calibration method proposed in this paper. Neural network can set properly the distortion model which has difficulty to estimate exactly in general method. The performance of the proposed neural network approach is compared with the well-known Tsai's two stage method in terms of calibration errors. The results show that the proposed approach gives much more stable and acceptabke calibration error over Tsai's two stage method regardless of camera resolution and camera angle.

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The Semiconductor Industry and High-Quality Economic Development: An International Perspective

  • Eun-Young Nam;Xiao-Long Wang
    • Journal of Korea Trade
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    • v.26 no.7
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    • pp.77-92
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    • 2022
  • Purpose - This paper is an empirical investigation of the mediation effect of innovation activity in industry transformation considering the relationship between the semiconductor industry and high-quality economic development. The research questions are whether the semiconductor industry drives high-quality economic development and if so, what is the semiconductor industry's role in high-quality development? We found that the semiconductor industry has clearly improved the quality of economic development, and its comparative advantage has significantly increased per capita national incomes. Furthermore, innovation activity proved to be an intermediary factor for the semiconductor industry to promote high-quality economic development. The world economy should aim to reasonably develop the international semiconductor industry and cultivate innovation markets. Design/methodology - Our empirical model considers the relationship between the semiconductor industry, innovation activity, and high-quality economic development. We constructed an analysis framework based on data from 199 World Bank economies between 1995 and 2019, and we used a mediation effect method to calculate the total effect of the semiconductor industry on promoting high-quality economic development, the indirect effect of the semiconductor industry on promoting innovation activity, and the mediation effect of these innovation activities on the promotion of high-quality economic development. Findings - The results show that the semiconductor industry has significantly promoted high-quality economic development. This is true even after the robustness test of grouping and alternative variables was applied. An analysis of the mechanism shows that promoting patents, scientific research, efficient government, and urban management innovation are important mechanisms for the semiconductor industry to release high-quality development dividends. Originality/value - Although it has been shown that specific industries like semiconductors can affect high-quality economic development through industrial upgrading, few researchers have attempted to empirically test the impact of the semiconductor industry on high-quality economic development. In this paper, we use a mediation effect model, alternative variables and a grouping test to find the internal mechanisms of the comparative advantage of the semiconductor industry in high-quality economic development from the perspective of innovation activity.

Automatic Anatomical Classification Model of Esophagogastroduodenoscopy Images Using Deep Convolutional Neural Networks for Guiding Endoscopic Photodocumentation

  • Park, Jung-Whan;Kim, Yoon;Kim, Woo-Jin;Nam, Seung-Joo
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.3
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    • pp.19-28
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    • 2021
  • Esophagogastroduodenoscopy is a method commonly used for early diagnosis of upper gastrointestinal lesions. However, 10-20 percent of the gastric lesions are reported to be missed, due to human error. And countries including the US, the UK, and Japan, the World Endoscopy Organization (WEO) suggested guidelines about essential gastrointestinal parts to take pictures of so that all gastric lesions are observed. In this paper, we propose deep learning techniques for classification of anatomical sites, aiming for the system that informs practitioners whether they successfully did the gastroscopy without blind spots. The proposed model uses pre-processing modules and data augmentation techniques suitable for gastroscopy images. Not only does the experiment result with a maximum F1 score of 99.6%, but it also shows a error rate of less than 4% based on the actual data. Given the performance results, we found the model to be explainable with the potential to be utilized in the clinical area.

Analyzing Box-Office Hit Factors Using Big Data: Focusing on Korean Films for the Last 5 Years

  • Hwang, Youngmee;Kim, Kwangsun;Kwon, Ohyoung;Moon, Ilyoung;Shin, Gangho;Ham, Jongho;Park, Jintae
    • Journal of information and communication convergence engineering
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    • v.15 no.4
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    • pp.217-226
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    • 2017
  • Korea has the tenth largest film industry in the world; however, detailed analyses using the factors contributing to successful film commercialization have not been approached. Using big data, this paper analyzed both internal and external factors (including genre, release date, rating, and number of screenings) that contributed to the commercial success of Korea's top 10 ranking films in 2011-2015. The authors developed a WebCrawler to collect text data about each movie, implemented a Hadoop system for data storage, and classified the data using Map Reduce method. The results showed that the characteristic of "release date," followed closely by "rating" and "genre" were the most influential factors of success in the Korean film industry. The analysis in this study is considered groundwork for the development of software that can predict box-office performance.

A Study on the Modeling of Fueling Hydrogen Tank in Vehicle Using Dispenser (디스펜서를 이용한 차량용 연료 탱크 수소 충전 모델링에 관한 연구)

  • Choi, Ji Ah;Ji, Sang Won;Jang, Ji Seong
    • Journal of Drive and Control
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    • v.19 no.2
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    • pp.36-44
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    • 2022
  • Hydrogen energy as an alternative source of energy has been receiving tremendous support around the world, and research is being actively conducted accordingly. However, most of the studies focus on hydrogen storage tanks and only are few studies on interpreting the hydrogen filling system itself. In this study, with reference to SAE J2601, a hydrogen fueling protocol, a simulation model was developed that can confirm the behavior of the vehicle's internal tank during hydrogen fueling. With respect to factors such as fuel supply temperature, ambient temperature, and pressure increase rate, the developed model can check the change of temperature and pressure in the tank and the state of hydrogen charging during hydrogen fueling. The validity of the developed simulation model was confirmed by comparing the simulation results with the experimental results presented in SAE J2601.