• 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 Semiconductor & Display Technology
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• v.21 no.4
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• pp.65-70
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• 2022

In manufacturing and semiconductor industries, transfer robots increase productivity through accurate and continuous work. Due to the nature of the semiconductor process, there are environments where humans cannot intervene to maintain internal temperature and humidity in a clean room. So, transport robots take responsibility over humans. In such an environment where the manpower of the process is cutting down, the lack of maintenance and management technology of the machine may adversely affect the production, and that's why it is necessary to develop a technology for the machine failure diagnosis system. Therefore, this paper tries to identify various causes of failure of transport robots that are widely used in semiconductor automation, and the Prognostics and Health Management (PHM) method is considered for determining and predicting the process of failures. The robot mainly fails in the driving unit due to long-term repetitive motion, and the core components of the driving unit are motors and gear reducer. A simulation drive unit was manufactured and tested around this component and then applied to 6-axis vertical multi-joint robots used in actual industrial sites. Vibration data was collected for each cause of failure of the robot, and then the collected data was processed through signal processing and frequency analysis. The processed data can determine the fault of the robot by utilizing machine learning algorithms such as SVM (Support Vector Machine) and KNN (K-Nearest Neighbor). As a result, the PHM environment was built based on machine learning algorithms using SVM and KNN, confirming that failure prediction was partially possible.

• Journal of Korean Society of Transportation
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• v.29 no.5
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• pp.121-138
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• 2011

More affordable and available cutting-edge technologies (e.g., wireless vehicle communication) are regarded as a possible alternative to the fixed infrastructure-based traffic information system requiring the expensive infrastructure investments and mostly implemented in the uninterrupted freeway network with limited spatial system expansion. This paper develops an advanced decentralized traveler information System (ATIS) using vehicle-to-vehicle (V2V) communication system whose performance (drivers' travel time savings) are enhanced by three complementary functions (autonomous automatic incident detection algorithm, reliable sample size function, and driver behavior model) and evaluates it in the typical $6{\times}6$ urban grid network with non-recurrent traffic state (traffic incident) with the varying key parameters (traffic flow, communication radio range, and penetration ratio), employing the off-the-shelf microscopic simulation model (VISSIM) under the ideal vehicle communication environment. Simulation outputs indicate that as the three key parameters are increased more participating vehicles are involved for traffic data propagation in the less communication groups at the faster data dissemination speed. Also, participating vehicles saved their travel time by dynamically updating the up-to-date traffic states and searching for the new route. Focusing on the travel time difference of (instant) re-routing vehicles, lower traffic flow cases saved more time than higher traffic flow ones. This is because a relatively small number of vehicles in 300vph case re-route during the most system-efficient time period (the early time of the traffic incident) but more vehicles in 514vph case re-route during less system-efficient time period, even after the incident is resolved. Also, normally re-routings on the network-entering links saved more travel time than any other places inside the network except the case where the direct effect of traffic incident triggers vehicle re-routings during the effective incident time period and the location and direction of the incident link determines the spatial distribution of re-routing vehicles.

• Journal of Biomedical Engineering Research
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• v.23 no.5
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• pp.351-364
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• 2002

Conventional 3D ultrasound imaging using mechanical ID arrays suffers from poor elevation resolution due to the limited depth-of-focus (DOF). On the other hand, 3D imaging systems using 2D phased arrays have a large number of active channels and hence require a very expensive and bulky beamforming hardware. To overcome these limitations, a new real-time volumetric imaging method using curved 2-D arrays is presented, in which a small subaperture, consisting of 256 elements, moves across the array surface to scan a volume of interest. For this purpose, a 2-D curved array is designed which consists of 90$\times$46 elements with 1.5λ inter-element spacing and has the same view angles along both the lateral and elevation directions as those of a commercial mechanical 1-D array. In the proposed method, transmit and receive subapertures are constructed by cutting the four corners of a rectangular aperture to obtain a required image qualify with a small number of active channels. In addition the receive subaperture size is increased by using a sparse array scheme that uses every other elements in both directions. To suppress the grating lobes elevated due to the increase in clement spacing, fold-over array scheme is adopted in transmit, which doubles the effective size of a transmit aperture in each direction. Computer simulation results show that the proposed method can provide almost the same and greatly improved resolutions in the lateral and elevation directions, respectively compared with the conventional 3D imaging with a mechanical 1-D array.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7B
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• pp.608-618
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• 2006

The increasing popularity of multimedia streaming services introduces new challenges in content distribution. Especially, it is important to provide the QoS guarantees as they are increasingly expected to support the multimedia applications. The service providers can improve the performance of multimedia streaming by caching the initial segment (prefix) of the popular streams at proxies near the requesting clients. The proxy can initiate transmission to the client while requesting the remainder of the stream from the server. In this paper, in order to apply the prefix caching service based on IETF's RTSP environment to the wireless networks, we propose the effective RTSP handling scheme that can adapt to the radio situation in wireless network and reduce the cutting phenomenon. Also, we propose the traffic based caching algorithm (TSLRU) to improve the performance of caching proxy. TSLRU classifies the traffic into three types, and improve the performance of caching proxy by reflecting the several elements such as traffic types, recency, frequency, object size when performing the replacement decision. In simulation, TSLRU and RTSP handling scheme performs better than the existing schemes in terms of byte hit rate, hit rate, startup latency, and throughput.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.303-303
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• 2017

Japanese agriculture has faced to several threats: aging and decrease of farmer population, global competition, and the risk of climate change as well as harsh and variable weather. On the other hands, the number of large scale farms is increasing, because farm lands have been being aggregated to fewer numbers of farms. Cost cutting, development of efficient ways to manage complicatedly scattered farm lands, maintaining yield and quality under variable weather conditions, are required to adapt to changing environments. Information and communications technology (ICT) would contribute to solve such problems and to create innovative technologies. Thus we have been developing an early warning and decision support system to reduce weather and climate risks for rice, wheat and soybean production in Japan. The concept and prototype of the system will be shown. The system consists of a weather data system (Agro-Meteorological Grid Square Data System, AMGSDS), decision support contents where information is automatically created by crop models and delivers information to users via internet. AMGSDS combines JMA's Automated Meteorological Data Acquisition System (AMeDAS) data, numerical weather forecast data and normal values, for all of Japan with about 1km Grid Square throughout years. Our climate-smart system provides information on the prediction of crop phenology, created with weather forecast data and crop phenology models, as an important function. The system also makes recommendations for crop management, such as nitrogen-topdressing, suitable harvest time, water control, pesticide spray. We are also developing methods to perform risk analysis on weather-related damage to crop production. For example, we have developed an algorism to determine the best transplanting date in rice under a given environment, using the results of multi-year simulation, in order to answer the question "when is the best transplanting date to minimize yield loss, to avoid low temperature damage and to avoid high temperature damage?".

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.551-564
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• 2016

Earthworks are the fundamental steps in a construction job, and are mainly comprised of smaller tasks performed by construction machinery. The productivity of the construction job can be improved by optimizing excavation, filling, and other such operations. Earthworks involve a lot of mechanical work performed by the collaboration between various kinds of construction equipment, which in turn leads to higher fuel consumption. Actual earthworks depend mostly on the intuition and experience of the driver of the machines, thus leading to inefficiency and environmental problems caused by unnecessary emission of carbon, Recently automated and information-oriented technologies are consistently being researched towards the improvement of efficiency of earthworks in the construction industry. The present research involves the introduction and understanding of the decision-making elements of heuristics which can be applied to the earthwork planning. A method is also suggested for creating an effective work path for construction machine to perform task packages (TP) for cutting and filling processes. A simulation test is performed to verify the effectiveness of suggested methods in terms of space interference and total moving distance of construction equipment.

• Journal of Internet Computing and Services
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• v.19 no.3
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• pp.49-56
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• 2018

Euclidean distance (ED) between error distribution and Dirac delta function has been used as an efficient performance criterion in impulsive noise environmentsdue to the outlier-cutting effect of Gaussian kernel for error signal. The gradient of ED for its minimization has two components; $A_k$ for kernel function of error pairs and the other $B_k$ for kernel function of errors. In this paper, it is analyzed that the first component is to govern gathering close together error samples, and the other one $B_k$ is to conduct error-sample concentration on zero. Based upon this analysis, it is proposed to normalize $A_k$ and $B_k$ with power of inputs which are modified by kernelled error pairs or errors for the purpose of reinforcing their roles of narrowing error-gap and drawing error samples to zero. Through comparison of fluctuation of steady state MSE and value of minimum MSE in the results of simulation of multipath equalization under impulsive noise, their roles and efficiency of the proposed normalization method are verified.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.165-178
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• 2011

A gigantic ship is constructed by assembling various types of ship blocks, each block being made by cutting and piecing the steel-plates together. The steel-plate piling process as the initial stage of ship construction sorts and manages the steel-plates according to the ship blocks that the steel-plates are used to make. The steel-plate piling process poses some problems such as process delay due to piling errors, safety vulnerability due to the handling of extra heavy-weight objects, and the uncertainty of work plan due to lack of information management in the pile spaces. We constructed a steel-plate piling process system based on the context-aware computing to resolve such problems. We built simulation system that can simulate the piling process and then established a smart space within the system by using tags, sensors and a real-time location system in order to collect context information. Workers receive an appropriate or intelligent service from the system.

• Journal of Korea Water Resources Association
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• v.45 no.7
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• pp.643-656
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• 2012

There has been an increase for the landslide areas and restoration expenses due, in large part, to the increased locally heavy rains caused by recent climate change as well as the reckless development. This study carried out a slope stability analysis by the application of distributed wetness index, using the GIS-based infinite slope stability model, which took the root cohesion effect into consideration, for part of Mt. Umyeon in Seoul, where landslide occurred in July 2011, in order to compensate the defects of existing analysis method, and subsequently compared its result with the case on the exploitation of lumped wetness index. In addition, this study estimated the distributed wetness index by methodology, applying three methods of specific catchment area calculation: single flow direction (SFD), multiple flow direction (MFD), and infinity flow direction (IFD), for catchment area, one of the variables of distributed wetness indices, and finally implemented a series of comparative analysis for slope stability by methodology. The simulation results showed that most unstable areas within the study site were dominantly located in cutting-area surroundings along with the residential area and the mountaintop and unstable areas of IFD and lumped wetness index method were similar while SFD and MFD provided smaller unstable areas than the two former methods.