• Structural Engineering and Mechanics
• /
• v.48 no.3
• /
• pp.291-308
• /
• 2013

Structural health monitoring is crucial to maintain the structural performance safely. Moreover, the Kullback-Leibler divergence (KLD) is applied usually to asset the similarity between different probability density functions in the pattern recognition. In this study, the KLD is employed to detect the damage. However the asymmetry of the KLD is a shortcoming for the damage detection, to overcoming this shortcoming, two other divergences and one statistic distribution are proposed. Then the damage identification by the KLD and its three descriptions from the symmetric point of view is investigated. In order to improve the reliability and accuracy of the four divergences, the gapped smoothing method (GSM) is adopted. On the basis of the damage index approach, the new damage index (DI) for detect damage more accurately based on the four divergences is developed. In the last, the grey relational coefficient and hypothesis test (GRCHT) is utilized to obtain the more precise damage identification results. Finally, a clear remarkable improvement can be observed. To demonstrate the feasibility and accuracy of the proposed method, examples of an isotropic beam with different damage scenarios are employed so as to check the present approaches numerically. The final results show that the developed approach successfully located the damaged region in all cases effect and accurately.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.2
• /
• pp.101-106
• /
• 2006

The geoidal undulations are needed for determining the orthometric heights from the Global Positioning System GPS-derived ellipsoidal heights. There are several methods for geoidal undulation determination. The paper presents a method employing a simple architecture Two Layer Multiquadric-Biharmonic Artificial Neural Network (TLMB-ANN) to approximate an area of 4200 square kilometres quasigeoid surface with GPS-levelling data. Hardy’s Multiquadric-Biharmonic functions is used as the hidden layer neurons’ activation function and Levenberg-Marquardt algorithm is used to train the artificial neural network. In numerical examples five surfaces were compared: the gravimetric geometry hybrid quasigeoid, Support Vector Machine (SVM) model, Hybrid Fuzzy Neural Network (HFNN) model, Traditional Three Layer Artificial Neural Network (ANN) with tanh activation function and TLMB-ANN surface approximation. The effectiveness of TLMB-ANN surface approximation depends on the number of control points. If the number of well-distributed control points is sufficiently large, the results are similar with those obtained by gravity and geometry hybrid method. Importantly, TLMB-ANN surface approximation model possesses good extrapolation performance with high precision.

• Journal of the Korean Institute of Navigation
• /
• v.15 no.3
• /
• pp.1-11
• /
• 1991

As increasing needs of marine transportation , world merchant fleet and ship's size were enlarged and it caused frequent disasters in human lives and natural environment. By the reason of the above, they started to establish the Vessel Traffic System (VTS) at the European coast in 1960' and most of advanced contries established and managed it to prevent the sea traffic accidents in these days. The concept of traffic control at sea can be divided into three types. First, the initial gathering of informations about ship's identity and movement etc.. Second, monitoring of the traffic flow and amendment of instructions. Third , organization and direction of ships by allocating routes and speeds. Where the goal of traffic control is safety of traffics and developing effectiveness of navigation channel, if traffic volume is less tan channel capacity then the above first or second level of control would be sufficient but if it is bigger than that , more positive policy of control should be adopted as same as third type of the above. In this paper where the strategy of VTS is focused on the control of traffic density to be spread equality, as possible , all over the navigation channels and also improvement of effectiveness , it suggests algorithm to assign the vessels to the channels with balanced traffic density , and other algorithms using D.P. to sequence the vessels assigned to one channel in optimum order which decreases the mean waiting time in sense of channel effectiveness with numerical examples.

• Journal of Information Technology Services
• /
• v.15 no.4
• /
• pp.41-62
• /
• 2016

In Internet of Things (IoT) era, more diverse types of information are collected and the environment of information usage, distribution, and processing is changing. Recently, there have been a growing number of cases involving breach and infringement of personal information in IoT services, for examples, including data breach incidents of Web cam service or drone and hacking cases of smart connected car or individual monitoring service. With the evolution of IoT, concerns on personal information protection has become a crucial issue and thus the risk analysis and management method of personal information should be systematically prepared. This study shows risk factors in IoT regarding possible breach of personal information and infringement of privacy. We propose "a risk analysis framework of protecting personal information in IoT environments" consisting of asset (personal information-type and sensitivity) subject to risk, threats of infringement (device, network, and server points), and social impact caused from the privacy incident. To verify this proposed framework, we conducted risk analysis of IoT services (smart communication device, connected car, smart healthcare, smart home, and smart infra) using this framework. Based on the analysis results, we identified the level of risk to personal information in IoT services and suggested measures to protect personal information and appropriately use it.

• Smart Structures and Systems
• /
• v.15 no.1
• /
• pp.57-80
• /
• 2015

Extended Kalman Filter (EKF) has been widely used for structural identification and damage detection. However, conventional EKF approaches require that external excitations are measured. Also, in the conventional EKF, unknown structural parameters are included as an augmented vector in forming the extended state vector. Hence the sizes of extended state vector and state equation are quite large, which suffers from not only large computational effort but also convergence problem for the identification of a large number of unknown parameters. Moreover, such approaches are not suitable for intelligent structural damage detection due to the limited computational power and storage capacities of smart sensors. In this paper, a two-stage and two-step algorithm is proposed for the identification of structural damage as well as unknown external excitations. In stage-one, structural state vector and unknown structural parameters are recursively estimated in a two-step Kalman estimator approach. Then, the unknown external excitations are estimated sequentially by least-squares estimation in stage-two. Therefore, the number of unknown variables to be estimated in each step is reduced and the identification of structural system and unknown excitation are conducted sequentially, which simplify the identification problem and reduces computational efforts significantly. Both numerical simulation examples and lab experimental tests are used to validate the proposed algorithm for the identification of structural damage as well as unknown excitations for structural health monitoring.

• The Korean journal of helicobacter and upper gastrointestinal research
• /
• v.18 no.3
• /
• pp.157-161
• /
• 2018

Liquid biopsy, the analysis of circulating biomarkers from peripheral blood, such as circulating tumor cells (CTCs) and circulating tumor DNA, and exosomes, offers a less invasive, new source of cancer-derived materials that may reflect the status of the disease better and thereby contribute to personalized treatment. Recent advances in microfluidics and molecular analysis technologies have resulted in greatly improved CTC enumeration and detection. In this article, we review commercially available technologies used to isolate CTCs from peripheral blood, including immunoaffinity and label-free, physical property-based isolation methods. Although enormous technological progress has been made, especially within the last decade, only a few CTC detection methods have been approved for routine clinical use. Here, we provide an overview of the current CTC isolation methods and examples of their potential application for early diagnosis, prognosis, treatment monitoring, and prediction of resistance to cancer therapy. Furthermore, the challenges that remain to be addressed before such tools are implemented for routine use in clinical settings are discussed.

• Geomechanics and Engineering
• /
• v.17 no.1
• /
• pp.1-9
• /
• 2019

This paper proposes a new numerical approach to model geocell reinforced soils, where the geocell is described as membrane elements and the complex interaction between geocell and soil is realized by coupling their degrees of freedom. The effectiveness and robustness of this approach are demonstrated using two examples, i.e., a geocell-reinforced foundation and a large scale retaining wall project. The first example validates the approach against established solutions through a comprehensive parametrical study to understand the influence of geocell on the improvement of bearing capacity of foundations. The study results show that reducing the geocell pocket size has a strong effect on improving the bearing capacity. In addition, when the aspect ratio maintains the same value, the bearing capacity improvement with increasing geocell height is insignificant. Comparing with the field monitoring and measurement in the project, the second example investigates the application of the approach to practical engineering projects. This paper provides a practically feasible and efficient modelling approach, where no explicit interface or contact is required. This allows geocell reinforced soils in large scale project can be effectively modelled where the mechanism for complex geocell-soil interaction can be explicitly observed.

• Journal of the Korean Geosynthetics Society
• /
• v.21 no.1
• /
• pp.33-48
• /
• 2022

This paper presents illustrative examples of the application of advanced digital image correlation (DIC) technology in the geotechnical laboratory tests, such as shallow footing test, trapdoor test, retaining wall test, and wide width tensile test on geogrid. The theoretical background of the DIC technique is first introduced together with fundamental equations. Relevant reduced-scale model tests were then performed using standard sand while applying the DIC technique to capture the movement of target materials during tests. A number of different approaches were tried to obtain optimized images that allow efficient tracking of material speckles based on the DIC technique. In order to increase the trackability of soil particles, a mix of dyed and regular sand was used during the model tests while specially devised painted speckles were applied to the geogrid. A series of images taken during tests were automatically processed and analyzed using software named VIC-2D that automatically generates displacements and strains. The soil deformation field and associated failure patterns obtained from the DIC technique for each test were found to compare fairly well with the theoretical ones. Also shown is that the DIC technique can also general strains appropriate to the wide width tensile test on geogrid, It is demonstrated in this study that the advanced DIC technique can be effectively used in monitoring the deformation and strain field during a reduced-scale geotechnical model laboratory test.

• Structural Monitoring and Maintenance
• /
• v.9 no.1
• /
• pp.59-80
• /
• 2022

In the present study, the objective is to detect the structural damages using the responses obtained from the sensors at the optimal location under uncertainty conditions. Reducing the error rate in damage detection process due to responses' noise is an important goal in this study. In the proposed algorithm for optimal sensor placement, the noise of responses recorded from the sensors is initially reduced using the principal component analysis. Afterward, the optimal sensor placement is obtained by the damage detection equation based sensitivity analysis. The sensors are placed on degrees of freedom corresponding to the minimum error rate in structural damage detection through this procedure. The efficiency of the proposed method is studied on a truss bridge, a space dome, a double-layer grid as well as a three-story experimental frame structure and the results are compared. Moreover, the performance of the suggested method is compared with three other algorithms of Average Driving Point Residue (ADPR), Effective Independence (EI) method, and a mass weighting version of EI. In the examples, young's modulus, density, and cross-sectional areas of the elements are considered as uncertainty parameters. Ultimately, the results have demonstrated that the presented algorithm under uncertainty conditions represents a high accuracy to obtain the optimal sensor placement in the structures.

• Journal of Research and Publication Ethics
• /
• v.3 no.1
• /
• pp.13-16
• /
• 2022

Purpose: The purpose of this study was to remind the importance of research ethics in research and publication, and to suggest the direction of research ethics by taking examples of research ethics recently implemented by KJFHC. Research design, data and methodology: With reference to the research of existing researchers, why research ethics is important, what are the violations of research ethics, and the efforts of the editorial committee of KJFHC to strengthen research ethics are presented as an example. Results: It is a reality that the concept of research ethics is becoming more complex and important with the introduction of various new academic fields. At this point in time, researchers need to pay more attention to the easily overlooked concept of research ethics. In research ethics, the most important thing is not punishment through monitoring and supervision, but prevention activities of research ethics that can prevent research misconduct before it occurs. As a preventive activity for research ethics, it can be said that the most important is the establishment of a systematic education system and active educational activities of universities and related institutions. Conclusions: This study avoids the general status and solutions for research ethics, and explains the case of the actual academic journal KJFHC and suggests alternatives.