• Advances in concrete construction
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• v.13 no.5
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• pp.385-394
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• 2022

Recently, an increasing number of cutting-edged studies have shown that designing a smart active control for real-time implementation requires piles of hard-work criteria in the design process, including performance controllers to reduce the tracking errors and tolerance to external interference and measure system disturbed perturbations. This article proposes an effective artificial-intelligence method using these rigorous criteria, which can be translated into general control plants for the management of civil engineering installations. To facilitate the calculation, an efficient solution process based on linear matrix (LMI) inequality has been introduced to verify the relevance of the proposed method, and extensive simulators have been carried out for the numerical constructive model in the seismic stimulation of the active rigidity. Additionally, a fuzzy model of the neural network based system (NN) is developed using an interconnected method for LDI (linear differential) representation determined for arbitrary dynamics. This expression is constructed with a nonlinear sector which converts the nonlinear model into a multiple linear deformation of the linear model and a new state sufficient to guarantee the asymptomatic stability of the Lyapunov function of the linear matrix inequality. In the control design, we incorporated H Infinity optimized development algorithm and performance analysis stability. Finally, there is a numerical practical example with simulations to show the results. The implication results in the RMS response with as well as without tuned mass damper (TMD) of the benchmark building under the external excitation, the El-Centro Earthquake, in which it also showed the simulation using evolved bat algorithmic LMI fuzzy controllers in term of RMS in acceleration and displacement of the building.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.5
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• pp.367-374
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• 2023

As the Fourth Industrial Revolution accelerating, countries worldwide are developing technologies to digitize and automate various industrial sectors. Building smart factories not only reduces costs through improved process productivity but also allows for preemptive identification and removal of risk factors through the practice of Health, Safety, and Environment (HSE) management, thereby reducing industrial accident risks. In this study, we visualized pressure, temperature, power, and wind speed data measured in real-time via a monitoring GUI, enabling field managers and workers to easily access related information. Through the work environment monitoring system developed in this study, it is possible to conduct economic analysis on per-unit basis, based on the digitization of production management elements and the tracking of required resources. By implementing HSE in shipyards, potential risk factors can be improved, and gas and electrical leaks can be identified, which are expected to reduce production costs.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.17-28
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• 2005

About 91.1% of Railway-Highway Crossings (RHC) in Korea use a Constant Distance Warning System(CDWS), while about 8.9% use a Constant Warning Time System(CWTS). The CDWS does not recognize speed differences of approaching trains and provides only waiting times to vehicles and pedestrians based on the highest speed of approaching trains. Under the CDWS, therefore, low speed trains provide unnecessary waiting times at crossings which often generates complains to vehicle drivers and pedestrians and may cause wrong decisions to pass the crossings. The objective of this research is to improve the safety of the RHC by developing accurate a CWTS. In this research a train speed and location detection system was developed with ultra sonic detectors. Locations of the detectors was decided based on the highest speed and the minimum warning time of Saemaul of 160 km/h. To validate the algorithms of the newly developed systems the lab tests were conducted. The results show that the train detection system provides accurate locations of trains and the maximum error between real speeds of trains and those of the system was 0.07m/s.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.6
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• pp.507-517
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• 2019

Multi-function radar(MFR) is a system that uses various functions such as detection, tracking, and classification. To operate the functions in real-time, the detection stage in MFR usually uses radar signals for short measurement time. We can utilize several conventional detectors in the MFR system to detect low radar cross section maritime targets in the sea-clutter; however, the detectors, which have been developed to be effective for radar signals measured for a longer time, may be inappropriate for MFR. In this study, we proposed a modelling technique of sea-clutter short measurement time. We combined the modeled sea-clutter signal with the maritime-target signal, which was obtained by the numerical analysis method. Using this combined model, we exploited four independent detectors and analyzed the detection performances.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.780-788
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• 2008

Modeling hand poses and tracking its movement are one of the challenging problems in computer vision. There are two typical approaches for the reconstruction of hand poses in 3D, depending on the number of cameras from which images are captured. One is to capture images from multiple cameras or a stereo camera. The other is to capture images from a single camera. The former approach is relatively limited, because of the environmental constraints for setting up multiple cameras. In this paper we propose a method of reconstructing 3D hand poses from a 2D input image sequence captured from a single camera by means of Belief Propagation in a graphical model and recognizing a finger clicking motion using a hidden Markov model. We define a graphical model with hidden nodes representing joints of a hand, and observable nodes with the features extracted from a 2D input image sequence. To track hand poses in 3D, we use a Belief Propagation algorithm, which provides a robust and unified framework for inference in a graphical model. From the estimated 3D hand pose we extract the information for each finger's motion, which is then fed into a hidden Markov model. To recognize natural finger actions, we consider the movements of all the fingers to recognize a single finger's action. We applied the proposed method to a virtual keypad system and the result showed a high recognition rate of 94.66% with 300 test data.

• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.38-41
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• 2008

In this research, we propose a new method for tracking the release rate using the concentration data obtained from the sensor. We used a sensor network that has already been set surrounding the area where hazardous gas releases can occur. From the real-time sensor data, we detected and analyzed releases of harmful materials and their concentrations. Based on the results, the release rate is estimated using the neural network. This model consists of 14 input variables (sensor data, material properties, process information, meteorological conditions) and one output (release rate). The dispersion model then performs the simulation of the expected dispersion consequence by combining the sensor data, GIS data and the diagnostic result of the source term. The result of this study will improve the safety-concerns of residents living next to storage facilities containing hazardous materials by providing the enhanced emergency response plan and monitoring system for toxic gas releases.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.48-58
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• 2003

Recently in order to extinguish the large scale of forest fire efficiently and rapidly the forest fire extinguishment equipment such as helicopters and vehicles has been mobilized. In this situation, the most consideration for the effective extinguishment is to understand the forest fire surrounding area and situation very well and arrange and manage the extinguishment equipment timely. In this paper, the client/serve-based forest fire extinguishment helicopter management system was constructed by integrating GPS(global positioning system) and GIS(geographic information system) technologies. This system manages and considers not only extinguishment equipment information such as helicopters and vehicles including manpower arrangement but also extinguishment environment information such as storing reservoir status and road situation and so on. For this, the real time tracking of helicopter location was first acquired through GPS technology then all the information about forest fire surrounding area was offered through the user-friendly interface of GIS concept. The result of constructing this system helps to extinguish a large scale of forest fire rapidly and effectively within shorter time then reduces physical damage and much manpower mobilization.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.29-37
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• 2024

In this paper, we propose an efficient image processing system to detect and track the movement of specific objects such as patients. The proposed system extracts the outline area of an object from a binarized difference image by applying a thinning algorithm that enables more precise detection compared to previous algorithms and is advantageous for mixed-mode design. The binarization and thinning steps, which require a lot of computation, are designed based on RTL (Register Transfer Level) and replaced with optimized hardware blocks through logic circuit synthesis. The designed binarization and thinning block was synthesized into a logic circuit using the standard 180n CMOS library and its operation was verified through simulation. To compare software-based performance, performance analysis of binary and thinning operations was also performed by applying sample images with 640 × 360 resolution in a 32-bit FPGA embedded system environment. As a result of verification, it was confirmed that the mixed-mode design can improve the processing speed by 93.8% in the binary and thinning stages compared to the previous software-only processing speed. The proposed mixed-mode system for object recognition is expected to be able to efficiently monitor patient movements even in an edge computing environment where artificial intelligence networks are not applied.

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.101-107
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• 2020

We propose a realistic seeing through visualization methods in mixed reality environment. When a user wants to see specific location beyond a wall in indoor environment. The proposed system recognizes and registers the selected area using environment modelling and feature-based tracking. Then the selected area is diminished and the specific location is visualized in real-time. With the proposed seeing through methods, a user can understand spatial relationship of the building and can easily find the target location. We conducted a user study comparing the seeing through method to conventional indoor navigation service in order to investigate the potential of the proposed seeing through method. The proposed seeing through method was evaluated in navigation time in comparison with conventional approach. The proposed method enable users to navigate target locations 30% faster than the conventional approach.

• Journal of the Korea Computer Graphics Society
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• v.23 no.5
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• pp.67-73
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• 2017

We propose several techniques which can be employed in a 3D fitness program for monitoring and correcting user's posture. To implement a 3D fitness program, improved reference motion generating techniques and visualizing techniques are necessary. First, in order to understand the difference between the user and the reference movement of a professional, a retargeting method between two different body shapes are studied. Second, the problem of self-occlusion, which occurs when using a low-cost depth sensor to represent complex motions, is solved by using a sample database and time consistency. The system proposed in this paper evaluates the user's posture considering the physical characteristics of the user, and then provides feedback to the user.