• Smart Structures and Systems
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• v.24 no.3
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• pp.403-414
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• 2019

Offshore drilling has become a key process for obtaining oil. Offshore platforms have many applications, including oil exploration and production, navigation, ship loading and unloading, and bridge and causeway support. However, vibration problems caused by severe environmental loads, such as ice, wave, wind, and seismic loads, threaten the functionality of platform facilities and the comfort of workers. These concerns may result in piping failures, unsatisfactory equipment reliability, and safety concerns. Therefore, the vibration control of offshore platforms is essential for assuring structural safety, equipment functionality, and human comfort. In this study, an optimal multiple tuned mass damper (MTMD) system was proposed to mitigate the excessive vibration of a three-dimensional offshore platform under ice and earthquake loadings. The MTMD system was designed to control the first few dominant coupled modes. The optimal placement and system parameters of the MTMD are determined based on controlled modal properties. Numerical simulation results show that the proposed MTMD system can effectively reduce the displacement and acceleration responses of the offshore platform, thus improving safety and serviceability. Moreover, this study proposes an optimal design procedure for the MTMD system to determine the optimal location, moving direction, and system parameters of each unit of the tuned mass damper.

• International Journal of Contents
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• v.18 no.2
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• pp.32-46
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• 2022

In recent years, large-scale and high-density use of LED on facades has exposed some disadvantages, such as light pollution, high energy consumption, unsustainability, and poor interactivity. Because of the development of smartphones and augmented reality (AR), AR has emerged as a new technology available to users to interact with the media façade. As an augmented reality app for public space, the AR map app can superimpose virtual images on the surface of a building to form an AR media façade, which can be applied in the fields of navigation, advertising, interactive public art, smart retail, etc. This study establishes the variables influencing usage intention and the consequent outcomes of Huawei AR map app and uses the technology acceptance model (TAM) to discuss their relationship. Results show that consumer innovativeness, information quality, and design quality have a strong influence on perceived ease of use. Information quality has a positive impact on perceived usefulness, but design quality has a weak influence. Also, the design quality of Huawei AR map app and consumer innovativeness have a higher effect on perceived enjoyment than information quality. Users' usage attitude and perceived usefulness when using Huawei AR map app are key factors determining their usage intention. This study inspires city planners, architects, developers, and designers of AR apps that augmented reality can partly replace media façade, and that investment in augmented reality will achieve significant sustainable economic and social benefits.

• Smart Structures and Systems
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• v.30 no.4
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• pp.411-420
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• 2022

Monitoring large structures is a significant issue involving public health on which new studies are constantly carried out. Although the Global Navigation Satellite System (GNSS) is the most preferable method for measuring structural displacements, total stations, one of the classical geodetic instruments, are the first devices that come to mind in cases that require complementary usage and auxiliary measurement methods. In this study, the relative displacements of the structural movements of a tower were determined using robotic total stations (RTS) and GNSS. Two GNSS receivers and two RTS observations were carried out simultaneously for 10 hours under normal weather conditions. The spectral analysis of the GNSS data was performed using fast Fourier transform (FFT), and while the dominant modal frequencies were determined, the total station data were balanced with the least-squares technique, and the position and position errors were calculated for each measurement epoch. It has been observed that low-frequency structural movements can be determined by both methods. This result shows that total station measurements are a helpful alternative method for monitoring large structures in situations where measurements are not possible due to the basic handicaps of GNSS or where it is necessary to determine displacements with short observations.

• Smart Structures and Systems
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• v.32 no.4
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• pp.235-251
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• 2023

A method that can estimate global deformation and internal forces using a limited amount of displacement data and based on the shape superposition technique and a neural network has been recently developed. However, it is difficult to directly measure sufficient displacement data owing to the limitations of conventional displacement meters and the high cost of global navigation satellite systems (GNSS). Therefore, in this study, the previously developed estimation method was extended by combining displacement, slope, and strain to improve the estimation accuracy while reducing the need for high-cost GNSS. To validate the proposed model, the global deformation and internal forces of a cable-stayed bridge were estimated using limited multi-response data. The effect of multi-response data was analyzed, and the estimation performance of the extended method was verified by comparing its results with those of previous methods using a numerical model. The comparison results reveal that the extended method has better performance when estimating global responses than previous methods.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.37-47
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• 2024

This study presents the results of designing a system that determines the location of a person in an indoor environment based on a single IMU sensor attached to the tip of a person's shoe in an area where GPS signals are inaccessible. By adjusting for human footfall, it is possible to accurately determine human location and trajectory by correcting errors originating from the Inertial Measurement Unit (IMU) combined with advanced machine learning algorithms. Although there are various techniques to identify stepping, our study successfully recognized stepping with 98.7% accuracy using an artificial intelligence model known as Long Short-Term Memory (LSTM). Drawing upon the enhancements in our methodology, this article demonstrates a novel technique for generating a 200-meter trajectory, achieving a level of precision marked by a 2.1% error margin. Indoor pedestrian navigation systems, relying on inertial measurement units attached to the feet, have shown encouraging outcomes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.203-215
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• 2017

Recently, interest in Pedestrian Navigation Service (PNS) is being increased due to the diffusion of smart phone and the improvement of location determination technology and it is efficient to use landmarks in route guidance for pedestrians due to the characteristics of pedestrians' movement and success rate of path finding. Accordingly, researches on extracting landmarks have been progressed. However, preceding researches have a limit that they only considered the difference between buildings and did not consider visual attention of maps in display of PNS. This study improves this problem by defining building attributes as local variable and global variable. Local variables reflect the saliency of buildings by representing the difference between buildings and global variables reflects the visual attention by representing the inherent characteristics of buildings. Also, this study considers the connectivity of network and solves the overlapping problem of landmark candidate groups by network voronoi diagram. To extract landmarks, we defined building attribute data based on preceding researches. Next, we selected a choice point for pedestrians in pedestrian network data, and determined landmark candidate groups at each choice point. Building attribute data were calculated in the extracted landmark candidate groups and finally landmarks were extracted by principal component analysis. We applied the proposed method to a part of Gwanak-gu, Seoul and this study evaluated the extracted landmarks by making a comparison with labels and landmarks used by portal sites such as the NAVER and the DAUM. In conclusion, 132 landmarks (60.3%) among 219 landmarks of the NAVER and the DAUM were extracted by the proposed method and we confirmed that 228 landmarks which there are not labels or landmarks in the NAVER and the DAUM were helpful to determine a change of direction in path finding of local level.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1000-1007
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• 2011

Home Networking will be implementing the interactive network by home appliances over wireless/wireline network framwork. That is, Home appliances, which are being operated within home space configure the network through wireline/wireless network infrastructure for interworking and interacitive services by external internet access. Based on home networking, smarthome is home space where can use automatic telecommunication and interactive service by home appliances. we can call smarthome based on home networking infrastructure as the conceptual gateway for evolving future converged space like u-city. From simple home control service to home automation service over home networking infrastructure, smarthome service is evolving to up-to-date intelligent life environment in growth of IT technology. however, its service model development was based on supplier-centered based on advanced IT technology. because of this situation, smarthome service has not been acknowledged IT underprivileged people as well as IT early-adaptor. so, this research paper will consider and try to find out what will be the feasible factors to make the best service for IT underprivileged people.

• Journal of Advanced Navigation Technology
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• v.7 no.1
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• pp.38-50
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• 2003

In this paper, a new high resolution reflectometry scheme, time-frequency domain reflectometry (TFDR), is proposed to detect and locate fault in wiring. Traditional reflectometry methods have been achieved in either the time domain or frequency domain only. However, time-frequency domain reflectometry utilizes time and frequency information of a transient signal to detect and locate the fault. The time-frequency domain reflectometry approach described in this paper is characterized by time-frequency reference signal design and post-processing of the reference and reflected signals to detect and locate the fault. Design of the reference signal in time-frequency domain reflectometry is based on the determination of the frequency bandwidth of the physical properties of cable under test. The detection and estimation of the fault on the time-frequency domain reflectometry relies on the time-frequency domain reflectometry is compared with commercial time domain reflectomtery (TDR) instrument. In these experiments provided in this paper, TFDR locates the fault with smaller error than TDR. Knowledge of time and frequency localized information for the reference and reflected signal gained via time-frequency analysis, allows one to detect the fault and estimate the location accurately.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.437-445
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• 2018

IMO (International Maritime Organization) has been strengthening the regulations of ship emission gas such as sulfur oxides (SOX), nitrogen oxides (NOX) and carbon dioxides (CO2) to protect the marine environment. Especially, ECA (Emission Control Area) has been set and operated in the USA and US. As a countermeasure against these environmental regulations, the demand for environmentally, friendly and highly efficient vessels has led to a growing interest in technology related research with respect to electric propulsion systems capable of reducing exhaust gas. Container ships were excluded from the application coverage of the electric propulsion systems for reasons of operation at economical speed. However, in the future, the need for electric propulsion system is expected to rise, because it is easy to monitor and control so that it can be an applicate to smart ship which are represented by fourth industrial revolution technology. In this study, research was carried out to design a generator and battery capacity through the load analysis of the 6,800TEU container ship to apply the electric propulsion system of the container ship. A capacity design based on the load analysis has an advantage that the generator can be operated in a high efficiency section through the load distribution control using the battery.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.620-626
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• 2020

This research propose and simulate a solar power generation system monitoring system based on Modbus TCP communication using RaspberryPi, an IOT equipment, as a master and an inverter as a slave. In this model, various sensors are added to the RaspberryPi to add necessary information for monitoring solar power plants, and power generation prediction and monitoring information are transmitted to the smart phone through real-time power generation prediction. In addition, information that is continuously generated by the solar power plant is built on the server as big data, and a deep learning model for predicting power generation is trained and updated. As a result of the study, stable communication was possible based on Modbus TCP with the Raspberry Pi in the inverter, and real-time prediction was possible with the deep learning model learned in the Raspberry Pi. The server was able to train various deep learning models with big data, and it was confirmed that LSTM showed the best error with a learning error of 0.0069, a test error of 0.0075, and an RMSE of 0.0866. This model suggested that it is possible to implement a real-time monitoring system that is simpler, more convenient, and can predict the amount of power generation for inverters of various manufacturers.