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A review on deep learning-based structural health monitoring of civil infrastructures

  • Ye, X.W.;Jin, T.;Yun, C.B.
    • Smart Structures and Systems
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    • v.24 no.5
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    • pp.567-585
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    • 2019
  • In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

A Standardized River Data Model Based on River Network for Building Multi-dimensional River Information System (다차원 하천 정보 체계 구축 위한 하천네트워크 기반 표준 하천 데이터 모델 개발)

  • Choi, Seoung Soo;Kim, Dongsu;You, Hojun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.177-177
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    • 2017
  • 최근 ADCP 등 첨단장비를 활용한 유량 및 하상측정, 각종 하천기본계획 수립 시 확보되는 횡단측정 자료, 식생 및 서식처 등 하천환경과 생태자료, 드론 등을 활용한 영상자료 등 방대한 하천 정보가 확보되고 있으며, 다기능보 등 다양한 하천구조물 및 친수구역이 증가하는 등 이전과 비교하여 괄목할만한 수준으로 정보의 양이 증가하고 있다. 이에 따라 다양한 하천정보를 체계적으로 저장, 관리, 공유하기 위하여 표준화된 데이터 모델(Data Model)의 수립이 필요하다. 하천 정보의 경우 하천 시설물, 하천 단면측량 자료, 하천 시계열 측정 자료 등이 특정 하천을 중심으로 관리되는 반면, 기존 데이터 모델 연구에서는 특정 주제도에 기반하여 하천 정보가 레이어 형식으로 제공되어 상호 연계되지 않아 하천 정보의 효율적 관리측면에서 적합하지 않았다. 또한 신규 정보를 추가 시 기존 데이터 모델의 과다한 수정이 필요하고, 기존의 데이터 모델의 경우 표준화되지 않아 활용성이 매우 낮고, 유역중심으로 구성되어 특정 조건에 해당되는 하천 정보 검색이 어려운 단점이 존재하였다. 본 연구에서는 기존의 주제도 및 레이어 형식으로 구성되어 있던 데이터 모델 형식에서 벗어나 하천흐름선을 기준으로 데이터모델을 구축하는 방안을 제시하였으며, 하천흐름선과 하천 시설물, 단면 측량 자료, 계측 자료를 순차적으로 수용하고, 기존에 존재하지 않던 하천 정보의 추가 시 기존 데이터 모델의 형식을 수정하지 않고 유연하게 대응할 수 있는 관계형 데이터 모델을 구상하였다. 또한, 하천과 유역의 논리적 저장방안 고려하여 한 개의 하천을 다수의 세그먼트(Reach)로 구분하여 코드(Reach Code)를 부여하는 방안을 제시하였으며, 구상한 데이터모델을 통하여 국가하천과 지방하천 등 유역의 다양성을 포함하는 한강권역의 섬강유역을 시범하천으로 구축하였다. 제시된 하천 정보 데이터 모델을 활용하여 DB를 구축한다면 하천망을 기준으로 하천 정보가 저장되고, 기존의 유역단위의 하천 정보 제공 방식에서 하천과 유역을 모두 포함하여 검색 가능한 시스템을 구축하여 하천 정보의 관리와 제공이 수월해질 것으로 기대된다.

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Performance Analysis of Drone-type Base Station on the mmWave According to Radio Resource Management Policy (무선자원 운용방안에 따른 밀리미터파 대역에서의 드론형 기지국 성능분석)

  • Jeong, Min-Woo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.5
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    • pp.917-926
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    • 2019
  • At present, TICN has been developed and distributed for military command control. TICN is known as the 3.5G mobile communication technology based on WiBro, which shows technical limitation in the field operation situation. Accordingly, the drone-type base station platform is attracting attention as an alternative to overcome technical limitations such as difficulty in securing communication LoS and limiting expeditious network configuration. In this study, we performed simulation performance evaluation of drone-type base station operation in 28 GHz that is considered most suitable for cellular communication within mmWave frequency band. Specifically, we analyzed the changes in throughput and fairness performance according to radio resource management policies such as frequency reuse and scheduling in multi-cell topology. Through this, we tried to provide insights on the operation philosophy on drone-type base station.

SMIL Authoring System for Multi-media synchronization and representation (멀티미디어 동기화 및 표현을 위한 SMIL 저작 시스템)

  • Ham, Jong-Wan;Jin, Du-Seok;Choi, Bong-Kyu;Cao, Ke-Rang;Park, Man-Seob;Jung, Hoe-Kyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.05a
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    • pp.653-656
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    • 2009
  • Currently with development of development and the hardware of the superhigh speed network about increase is spreading out at the rapid pace the many multimedia contents quite from internet. The production environment is growing about the multimedia contents because of such as circumstance, as well as multimedia contents will increase. However, Numerous voice, the picture, with text etc. the time of the same multimedia contents and problem of spatial synchronization occur, started. W3C(World Wide Web Consortium) solves like this problem point presented the method for. Does so, SMIL(Synchronized Multimedia Integration Language) where puts a base in XML(Extensible Markup Language) will be able to compose the expression of the multimedia contents which is various standard was proposed. SMIL the individual multimedia object of chain with time will be able to integrate with the multimedia presentation which is synchronized spatial in order. In this paper a variety of multimedia content and synchronization of the time and space, to be represented by integrating the design and implementation of SMIL authoring system.

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ANP-based Decision Support System Design for Selecting Function of Weapon Systems (무기체계의 기능 선정을 위한 ANP 기반의 의사결정 지원시스템 설계)

  • Oh, Seongryeong;Seo, Yoonho
    • Journal of the Korea Society for Simulation
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    • v.25 no.3
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    • pp.85-95
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    • 2016
  • In National Defense field, the importance of M&S and T&E has been increased due to complexity of modern Weapon System. And research reducing time and cost is being conducted continually on using limited resources efficiently. In the existing research, Weapon System's Performance Evaluation System using the Process-based method has been in progress. But, Objective basis or scientific method is insufficient in selecting appropriate function of a target to performance evaluation. Due to this, it's difficult to select functions suitable to the situation in same type. Also, Requirements of user and interrelation of evaluation factors can't be reflected systematically. In this research, it proposes the method to reflecting requirements of user, interrelation of elements in realistic situation for selecting evaluation object in Performance Evaluation Simulation. First, Evaluation Objects is selected using ANP which is multi-criterion decision making method. Second, decision support system is constructed using Programming Language(C#) based on the research result.

Deoxypodophyllotoxin Inhibits Cell Growth and Induces Apoptosis by Blocking EGFR and MET in Gefitinib-Resistant Non-Small Cell Lung Cancer

  • Kim, Han Sol;Oh, Ha-Na;Kwak, Ah-Won;Kim, Eunae;Lee, Mee-Hyun;Seo, Ji-Hye;Cho, Seung-Sik;Yoon, Goo;Chae, Jung-Il;Shim, Jung-Hyun
    • Journal of Microbiology and Biotechnology
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    • v.31 no.4
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    • pp.559-569
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    • 2021
  • As one of the major types of lung cancer, non-small cell lung cancer (NSCLC) accounts for the majority of cancer-related deaths worldwide. Treatments for NSCLC includes surgery, chemotherapy, and targeted therapy. Among the targeted therapies, resistance to inhibitors of the epidermal growth factor receptor (EGFR) is common and remains a problem to be solved. MET (hepatocyte growth factor receptor) amplification is one of the major causes of EGFR-tyrosine kinase inhibitor (TKI) resistance. Therefore, there exists a need to find new and more efficacious therapies. Deoxypodophyllotoxin (DPT) extracted from Anthriscus sylvestris roots exhibits various pharmacological activities including anti-inflammation and anti-cancer effects. In this study we sought to determine the anti-cancer effects of DPT on HCC827GR cells, which are resistant to gefitinib (EGFR-TKI) due to regulation of EGFR and MET and their related signaling pathways. To identify the direct binding of DPT to EGFR and MET, we performed pull-down, ATP-binding, and kinase assays. DPT exhibited competitive binding with ATP against the network kinases EGFR and MET and reduced their activities. Also, DPT suppressed the expression of p-EGFR and p-MET as well as their downstreat proteins p-ErbB3, p-AKT, and p-ERK. The treatment of HCC827GR cells with DPT induced high ROS generation that led to endoplasmic-reticulum stress. Accordingly, loss of mitochondrial membrane potential and apoptosis by multi-caspase activation were observed. In conclusion, these results demonstrate the apoptotic effects of DPT on HCC827GR cells and signify the potential of DPT to serve as an adjuvant anti-cancer drug by simultaneously inhibiting EGFR and MET.

A Validation of Effectiveness for Intrusion Detection Events Using TF-IDF (TF-IDF를 이용한 침입탐지이벤트 유효성 검증 기법)

  • Kim, Hyoseok;Kim, Yong-Min
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.6
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    • pp.1489-1497
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    • 2018
  • Web application services have diversified. At the same time, research on intrusion detection is continuing due to the surge of cyber threats. Also, As a single-defense system evolves into multi-level security, we are responding to specific intrusions by correlating security events that have become vast. However, it is difficult to check the OS, service, web application type and version of the target system in real time, and intrusion detection events occurring in network-based security devices can not confirm vulnerability of the target system and success of the attack A blind spot can occur for threats that are not analyzed for problems and associativity. In this paper, we propose the validation of effectiveness for intrusion detection events using TF-IDF. The proposed scheme extracts the response traffics by mapping the response of the target system corresponding to the attack. Then, Response traffics are divided into lines and weights each line with an TF-IDF weight. we checked the valid intrusion detection events by sequentially examining the lines with high weights.

Draft Design of AI Services through Concept Extension of Connected Data Architecture (Connected Data Architecture 개념의 확장을 통한 AI 서비스 초안 설계)

  • Cha, ByungRae;Park, Sun;Oh, Su-Yeol;Kim, JongWon
    • Smart Media Journal
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    • v.7 no.4
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    • pp.30-36
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    • 2018
  • Single domain model like DataLake framework is in spotlight because it can improve data efficiency and process data smarter in big data environment, where large scaled business system generates huge amount of data. In particular, efficient operation of network, storage, and computing resources in logical single domain model is very important for physically partitioned multi-site data process. Based on the advantages of Data Lake framework, we define and extend the concept of Connected Data Architecture and functions of DataLake framework for integrating multiple sites in various domains and managing the lifecycle of data. Also, we propose the design of CDA-based AI service and utilization scenarios in various application domain.

Intelligent Home appliances Power Control using Android and Arduino (안드로이드와 아두이노를 이용한 지능형 가전제품 전력 컨트롤)

  • Park, Sung-hyun;Kim, A-Yong;Kim, Wung-Jun;Bae, Keun-Ho;Yoo, Sang-keun;Jung, Hoe-kyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.854-856
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    • 2014
  • Has been released of make it possible to control the using for smart devices of a wide variety home appliances and electronics in smart appliances in accordance with the one person multi devices. In addition, is increasing rapidly for the number of the product on cleaning robot and refrigerator, air conditioning, TV, etc. these devices are using the implement up DLNA system. And at home and abroad for development and has provided with Iot and Alljoyn such systems. But currently using home appliances or electronic devices of there are a lot of the operating system non installed than the installed products. In addition, smart appliances do not use for user than buying existing electronic products a lot more. In addition, more occur for smart appliances of that do not use for the user on smart appliances rather than buying existing electronics. In this paper, Suggested and implemented for system of control such as smart devices to existed home appliance on not have an operating system, Using mobile device for want users to quantify the data to transfer from arduino board.

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Efficient Inference of Image Objects using Semantic Segmentation (시멘틱 세그멘테이션을 활용한 이미지 오브젝트의 효율적인 영역 추론)

  • Lim, Heonyeong;Lee, Yurim;Jee, Minkyu;Go, Myunghyun;Kim, Hakdong;Kim, Wonil
    • Journal of Broadcast Engineering
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    • v.24 no.1
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    • pp.67-76
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    • 2019
  • In this paper, we propose an efficient object classification method based on semantic segmentation for multi-labeled image data. In addition to various pixel unit information and processing techniques such as color information, contour, contrast, and saturation included in image data, a detailed region in which each object is located is extracted as a meaningful unit and the experiment is conducted to reflect the result in the inference. We use a neural network that has been proven to perform well in image classification to understand which object is located where image data containing various class objects are located. Based on these researches, we aim to provide artificial intelligence services that can classify real-time detailed areas of complex images containing various objects in the future.