• Title/Summary/Keyword: Identification Infrastructure

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Impact force localization for civil infrastructure using augmented Kalman Filter optimization

  • Saleem, Muhammad M.;Jo, Hongki
    • Smart Structures and Systems
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    • v.23 no.2
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    • pp.123-139
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    • 2019
  • Impact forces induced by external object collisions can cause serious damages to civil engineering structures. While accurate and prompt identification of such impact forces is a critical task in structural health monitoring, it is not readily feasible for civil structures because the force measurement is extremely challenging and the force location is unpredictable for full-scale field structures. This study proposes a novel approach for identification of impact force including its location and time history using a small number of multi-metric observations. The method combines an augmented Kalman filter (AKF) and Genetic algorithm for accurate identification of impact force. The location of impact force is statistically determined in the way to minimize the AKF response estimate error at measured locations and then time history of the impact force is accurately constructed by optimizing the error co-variances of AKF using Genetic algorithm. The efficacy of proposed approach is numerically demonstrated using a truss and a plate model considering the presence of modelling error and measurement noises.

Malicious Trust Managers Identification (MTMI) in Peer to Peer Networks

  • Alanazi, Adwan Alownie
    • International Journal of Computer Science & Network Security
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    • v.21 no.9
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    • pp.91-98
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    • 2021
  • Peer to Peer Networks play an increasing role in today's networks, also it's expected that this type of communication networks evolves more in the future. Since the number of users that is involved in Peer to Peer Networks is huge and will be increased more in the future, security issues will appear and increase as well. Thus, providing a sustainable solution is needed to ensure the security of Peer to Peer Networks. This paper is presenting a new protocol called Malicious Trust Managers Identification (MTMI). This protocol is used to ensure anonymity of trust manager, that computes and stores the trust value for another peer. The proposed protocol builds a secure connection between trust managers by using public key infrastructure. As well as experimental testing has been conducted to validate the proposed protocol.

Study on Integrity Assessment of Pile Foundation Based on Seismic Observation Records

  • KASHIWA, Hisatoshi
    • International Journal of High-Rise Buildings
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    • v.9 no.4
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    • pp.369-376
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    • 2020
  • Given the importance of quickly recovering livelihoods and economic activity after an earthquake, the seismic performance of the pile foundation is becoming more critical than before. In order to promote seismic retrofit of the pile foundations, it is necessary to develop a method for evaluating the seismic performance of the pile foundation based on the experimental data. In this paper, we focus on the building that was suffered severe damage to the pile foundation, conduct simulation analyses of the building, and report the results of evaluating the dynamic characteristics when piles are damaged using a system identification method. As a result, an analysis model that can accurately simulate the behavior of the damaged building during an earthquake was constructed, and it was shown that the system identification method could extract dynamic characteristics that may damage piles.

Definition of Minimum Performance Requirements for RFID Tags Embedded Inside a Pair of Shoes (신발에 삽입되는 RFID 태그의 최소 성능 요구사항 정의)

  • Kwon, Jongwon;Song, Taeseung;Cho, Wonseo;Kim, Jaeuk
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.27 no.1
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    • pp.33-41
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    • 2016
  • Radio Frequency Identification(RFID) can provide visibility and efficiency throughout the entire supply chain in fashion apparel and footwear. The technical analysis of RFID performance is necessarily required to create a sealess omni-channel service using customer experience. Especially, several tagged-item performance specifications, for example read range and multi-read rate, strongly depend on the attached material and real-operating environment. This paper suggests minimum performance requirements for RFID tags embedded inside a pair of shoes to negotiate tagged-item performance between retailers and suppliers.

Development and testing of a composite system for bridge health monitoring utilising computer vision and deep learning

  • Lydon, Darragh;Taylor, S.E.;Lydon, Myra;Martinez del Rincon, Jesus;Hester, David
    • Smart Structures and Systems
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    • v.24 no.6
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    • pp.723-732
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    • 2019
  • Globally road transport networks are subjected to continuous levels of stress from increasing loading and environmental effects. As the most popular mean of transport in the UK the condition of this civil infrastructure is a key indicator of economic growth and productivity. Structural Health Monitoring (SHM) systems can provide a valuable insight to the true condition of our aging infrastructure. In particular, monitoring of the displacement of a bridge structure under live loading can provide an accurate descriptor of bridge condition. In the past B-WIM systems have been used to collect traffic data and hence provide an indicator of bridge condition, however the use of such systems can be restricted by bridge type, assess issues and cost limitations. This research provides a non-contact low cost AI based solution for vehicle classification and associated bridge displacement using computer vision methods. Convolutional neural networks (CNNs) have been adapted to develop the QUBYOLO vehicle classification method from recorded traffic images. This vehicle classification was then accurately related to the corresponding bridge response obtained under live loading using non-contact methods. The successful identification of multiple vehicle types during field testing has shown that QUBYOLO is suitable for the fine-grained vehicle classification required to identify applied load to a bridge structure. The process of displacement analysis and vehicle classification for the purposes of load identification which was used in this research adds to the body of knowledge on the monitoring of existing bridge structures, particularly long span bridges, and establishes the significant potential of computer vision and Deep Learning to provide dependable results on the real response of our infrastructure to existing and potential increased loading.

An Implementation on CIS Management for Underground Social Infrastructure based on Active RFID (능동형 RFID 기반의 지하 매설물 GIS 관리 구현)

  • Baek, Jang-Mi;Hong, In-Sik
    • Journal of Internet Computing and Services
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    • v.8 no.3
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    • pp.45-56
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    • 2007
  • Recently, much research has been actively conducted for a new kind of network environment ubiquitous computing. This paper will define the smart-tag technology required by a ubiquitous environment. We will describe how to apply smart-tag-related Radio Frequency Identification(RFID) research for GIS in underground social infrastructure, a local-area wireless-communication technology. Application development is important that will be able to materialize a network environment. This research promotes various application developments, such reason currently it establishes the IT 839 from domestic. The geographic information system construction is a part of IT 839. The research which is various becomes accomplished for the ubiquitous of social base facility from domestic. Consequently, in this paper analyzes the geographic information system of existing, researches based RFID underground social infrastructure management system development. The Proposed method is complements the method of existing, and is efficient for underground social infrastructure. This system is new management system for underground social infrastructure, and provides safe administrator function using authentication of active RFID tag. It provides real processing and autonomy of administrator.

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A Study on the Identification Metadata of National R&D Information (국가 R&D정보 식별메타데이터에 관한 연구)

  • Kwon, Lee-nam;Kim, Jae-soo
    • Proceedings of the Korea Contents Association Conference
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    • 2007.11a
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    • pp.55-59
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    • 2007
  • A need for sharing the R&D information at a national level regardless of the ministry in charge of it is being aroused. However, this information is being managed by different institutes under different ministries without a standard identifier which makes it difficult to manage the information such as to look up duplicate projects. A URN-based identifier is required for the integrated management and utilization of the national R&D information. In this paper, the concept of the identification metadata for applying the identification system and the status of the information management by each institute will be the subject for discussion. Based on this, the elements required for issuing a unique identification number and identifier to the national R&D projects will be suggested in this paper.

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Experiments and its analysis on the Identification of Indoor Location by Visible Light Communication using LED lights (LED 조명 기반 가시광 무선 통신을 이용한 실내 위치 인식 실험 및 분석)

  • Kong, In-Yeup;Kim, Ho-Jin
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.5
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    • pp.1045-1052
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    • 2011
  • Recently, because of complex cultural space, underground space are becoming larger. Therefore, the demand for location-based services is growing. VLC (Visible Light Communication) is based on the LED lighting infrastructure so that suitable LBS (Location-based service) is possible for the targeted places in indoor space. To experiment with indoor LBS by VLC, we measure the identification distance according to variable angles between LED and photo diode. We send the different ASCII code for each LED light, then we found the maximum identification distance is 1.75m from LED lights. From the results of this experiment, we show that indoor navigation is possible.

A cable tension identification technology using percussion sound

  • Wang, Guowei;Lu, Wensheng;Yuan, Cheng;Kong, Qingzhao
    • Smart Structures and Systems
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    • v.29 no.3
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    • pp.475-484
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    • 2022
  • The loss of cable tension for civil infrastructure reduces structural bearing capacity and causes harmful deformation of structures. Currently, most of the structural health monitoring (SHM) approaches for cables rely on contact transducers. This paper proposes a cable tension identification technology using percussion sound, which provides a fast determination of steel cable tension without physical contact between cables and sensors. Notably, inspired by the concept of tensioning strings for piano tuning, this proposed technology predicts cable tension value by deep learning assisted classification of "percussion" sound from tapping a steel cable. To simulate the non-linear mapping of human ears to sound and to better quantify the minor changes in the high-frequency bands of the sound spectrum generated by percussions, Mel-frequency cepstral coefficients (MFCCs) were extracted as acoustic features to train the deep learning network. A convolutional neural network (CNN) with four convolutional layers and two global pooling layers was employed to identify the cable tension in a certain designed range. Moreover, theoretical and finite element methods (FEM) were conducted to prove the feasibility of the proposed technology. Finally, the identification performance of the proposed technology was experimentally investigated. Overall, results show that the proposed percussion-based technology has great potentials for estimating cable tension for in-situ structural safety assessment.

A Review Study in the Correlation between Pattern Identification of Traditional Chinese Medicine and Western Medicine Examination -Research on CNKI- (중의학 변증과 양방 검사의 상관관계 연구 현황 -CNKI를 이용하여-)

  • Yun, Young-Ju;Cho, Young-Joo;Lee, Ji-Hye;Lim, Jung-Hwa;Seong, Woo-Yong
    • Journal of Oriental Neuropsychiatry
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    • v.24 no.1
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    • pp.13-26
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    • 2013
  • Objectives : The purpose of this study is to investigate the correlation between pattern identification of traditional Chinese medicine (TCM) and western medicine, examined by a systematic research of Chinese medicine papers. Methods : We searched for the papers regarding pattern identification of TCM published from 1994 to 2012 in CNKI (China National Knowledge Infrastructure http://www.cnki.net) at April, 2012. Results : A total of 30 studies were finally included; 18 studies of them were related to stroke (cerebral infarction) and there were 12 studies regarding other diseases, such as hypertension, chronic colonitis, vascular dementia, mild cognitive impairment and etc. All 30 studies were analyzed and classified by diseases, differentiation of syndromes, numbers of subjects, the instrument of pattern identification, items of western medicine examination and statistical results. Conclusions : According to our study, there are some correlations between pattern identification of TCM and various items of western medicine examination. The result suggests a possibility of using the western medicine examination data for pattern identification of TCM.