• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.87-96
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• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.353-373
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• 2012

The instrumented Canton Tower is a 610 m high-rise structure, which has been considered as a benchmark problem for structural health monitoring (SHM) research. In this paper, an improved automatic modal identification method is presented based on a natural excitation technique in conjunction with the eigensystem realization algorithm (NExT/ERA). In the proposed modal identification method, damping ratio, consistent mode indicator from observability matrices (CMI_O) and modal amplitude coherence (MAC) are used as criteria to distinguish the physically true modes from spurious modes. Enhanced frequency domain decomposition (EFDD), the data-driven stochastic subspace identification method (SSI-DATA) and the proposed method are respectively applied to extract the modal parameters of the Canton Tower under different environmental conditions. Results of modal parameter identification based on output-only measurements are presented and discussed. User-selected parameters used in those methods are suggested and discussed. Furthermore, the effect of environmental conditions on the dynamic characteristics of Canton tower is investigated.

• Smart Structures and Systems
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• v.23 no.3
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• pp.279-293
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• 2019

To ensure high quality data being used for data mining or feature extraction in the bridge structural health monitoring (SHM) system, a practical sensor fault diagnosis methodology has been developed based on the similarity of symmetric structure responses. First, the similarity of symmetric response is discussed using field monitoring data from different sensor types. All the sensors are initially paired and sensor faults are then detected pair by pair to achieve the multi-fault diagnosis of sensor systems. To resolve the coupling response issue between structural damage and sensor fault, the similarity for the target zone (where the studied sensor pair is located) is assessed to determine whether the localized structural damage or sensor fault results in the dissimilarity of the studied sensor pair. If the suspected sensor pair is detected with at least one sensor being faulty, field test could be implemented to support the regression analysis based on the monitoring and field test data for sensor fault isolation and reconstruction. Finally, a case study is adopted to demonstrate the effectiveness of the proposed methodology. As a result, Dasarathy's information fusion model is adopted for multi-sensor information fusion. Euclidean distance is selected as the index to assess the similarity. In conclusion, the proposed method is practical for actual engineering which ensures the reliability of further analysis based on monitoring data.

• Smart Structures and Systems
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• v.28 no.6
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• pp.827-838
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• 2021

The dynamic displacement is considered to be an important indicator of structural safety, and becomes an indispensable part of Structural Health Monitoring (SHM) system for high-speed railway bridges. This paper proposes an indirect strain based dynamic displacement reconstruction methodology for high-speed railway box girders. For the typical box girders under eccentric train load, the plane section assumption and elementary beam theory is no longer applicable due to the bend-torsion coupling effects. The monitored strain was decoupled into bend and torsion induced strain, pre-trained multi-output support vector regression (M-SVR) model was employed for such decoupling process considering the sensor layout cost and reconstruction accuracy. The decoupled strained based displacement could be reconstructed respectively using box girder plate element analysis and mode superposition principle. For the transformation modal matrix has a significant impact on the reconstructed displacement accuracy, the modal order would be optimized using particle swarm algorithm (PSO), aiming to minimize the ill conditioned degree of transformation modal matrix and the displacement reconstruction error. Numerical simulation and dynamic load testing results show that the reconstructed displacement was in good agreement with the simulated or measured results, which verifies the validity and accuracy of the algorithm proposed in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.487-490
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• 2018

As the fourth industrial revolution 4.0 era arrives, the role of smart factory is emerging, which establishes a communication system between production devices and products through the Internet of Things and optimizes the entire production process. Germany wants to use smart factory technologies and data to upgrade and standardize the industry as a whole to create factories around the world, and the United States is aiming to create new business models and revenue streams by analyzing big data and improving productivity based on the technological prowess and innovation across ICT. In addition, Japan and China are also working to change and upgrade their manufacturing industries through smart factories. Accordingly, Korea is attempting to introduce smart factory based on the production industry 3.0. Therefore, this study describes the industrial trends of the fourth industrial revolution and smart factory and compares the major underlying technologies and introduction cases of smart factory.

• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.153-158
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• 2017

The certification for Smart Factory supoort successful management of organization while providing strategic plans to the issue of manufacturing process. In Korea, these standards are prepared as the national standards since 2015, and also, there are actions being taken to adpot the certification for Smart Factory. However, to adopt such certification, it is required that the certification operation system needs to be organized, as well as that the society in general should understand about Smart Factory. Accordingly, it is even more required an review on the adoption of the system. This study has the purpose in surveying a variety of atakeholders' perception for the adoption of Smart Factory certification given the circumstance that the cetitification is implemented through literature review and in-depth interviews. This study will be provide significant implication to build a successful plan for the adoption of Smart Factory certification by reviewing perception of professional and problem, strategy of this certification.

• The Korean Journal of Food And Nutrition
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• v.29 no.3
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• pp.363-370
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• 2016

The purpose of this study is to investigate the dietary life status according to smart device use among university students. In 2015, data was collected during a 3 month survey of the eating behaviors, lifestyles, eating habits, and use of smart devices of 550 university students, as well as their dependency on smartphones. Ultimately, 520 subjects (94.5% analysis rate) were divided into three groups based on their daily use time of smart device: low-use group (<4.7 hours, n=173), medium-use group (${\geq}4.7hours$ and <6.4 hours, n=174), and high-use group (${\geq}6.4hours$, n=173). The more frequent use groups showed a higher level of dependency on the smartphone. Breakfast was found to be the most commonly skipped meal; and the high-use group showed a higher response of irregular meals than low-use group. In assessment of eating habits, the subjects with less smart device usage ate more regularly and at fixed times, did not overeat, drank milk everyday, and did not consume processed food as often. To sum up, more irregularity of meal and undesirable eating habits were found among university students with higher use of smart devices. These results suggest that a control of smart device usage would lead to a more desirable dietary life in university students.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.146-156
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• 2021

A smart city refers to an intelligent city solving problems arising from the concentration its population using IT technology. Various services such as safety, transportation, environment, education, and medical care are provided in a smart city. Still, the degree of service experienced by the residents is lower compared to the technological maturity. Hence, the service acceptance intention factor needs to be improved. In this study, User Characteristic and Service Characteristic variables were identified separately to improve the awareness and experience of smart services among citizens of the smart city and analyze the intention of easy service acceptance. Based on the results, the present study is expected to improve citizen's quality of life and form a happy society. This improvement in citizens and society is achieved by drawing active participation from citizens and investments from the government and private enterprise through solving various problems in the city.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.215-222
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• 2019

Advances in technologies about 3D (three-dimensional) printing and smart factory related issues will have the effect of reducing the cost of building a smart factory and making various types of service available. Manufacturers and service providers of small assets work with outside experts to provide small amounts of customized ordering services. If customers have to disclose their private information to subscribe to a new service, they may be reluctant to use it and the availability of developed technology may cause slow progress. We propose a new protocol for customized order service for smart factory. The proposed approach is designed to meet requirements of security and based on smart contract in IoT convergence network. We analyzed the requirements of the proposed approach which provided anonymity, privacy, fairness, and non-repudiation. We compared it with closely related studies to show originality and differences.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.478-480
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• 2022

Smart Railway as a next generation railway technology is expected to have rapid evolution with developments of information and communications tehchology. Especially, smart railway will be progressed more evolved transportation means for railway operation and costomer service based with spread of commercial 5G communication. So, it is very important to investigate and analyze trends of smart railway related tehcnology of 5G mobile communication for samrt railway infra structure, server technolgy for AI, big data, deep learning, information security technology, sensor and IoT. In this paper, 5G based communicaion technology and application techology related smart railway is described and trends of new techlogy on this communication tehnology is investigated. The results of this study can be used for smart railway study and implementation, research and development for smart railway communicaion technology, etc.