• Applied Chemistry for Engineering
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• v.24 no.1
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• pp.87-92
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• 2013

Nonthermal plasma hybridized with photocatalysts is proven to be an effective tool to degrade toxic organics in wastewater. In this study, a specially designed dielectric barrier discharge (DBD) plasma system combined with photocatalysts was applied to decompose pestiticides such as dichlorovos, carbofuran and methidathon, which are frequently used in the golf courses and the orange plantations. The degradations of the pesticides in single and coupled systems were evaluated. The single system was used with ozone plasma which consisted of electrons, radicals, ions produced by oxygen gas and air, with and without ultra-violet (UV) irradiation, respectively. The coupled systems utilized the air-derived ozone plasma combined with zinc oxide, titanium dioxide and graphite oxide photocatalyst activated by UV. The graphite oxide was synthesized by a modified Hummer's method and characterized using FTIR spectrometer. It was elucidated that the plasma reaction with graphite oxide (0.01 g/L) brought about almost 100% of degradation degrees for dichlorovos and carbofuran in 60 min, as compared with the performances showed by no catalyst condition. The photocatalyst-hybridized plasma in the presence of UV irradiation was proven to be an effective alternative for degrading pesticides.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.480-488
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• 2006

Industrial and economical importance of CP(Cellular Phone) is growing rapidly. Combined with IT technology, CP is one of the most attractive technologies of today. However, unless we find a new breakthrough in the technology, its growth may slow down soon. RT(Robot Technology) is considered one of the most promising next generation technologies. Unlike the industrial robot of the past, today's robots require advanced features, such as soft computing, human-friendly interface, interaction technique, speech recognition object recognition, among many others. In this paper, we present a new technological concept named RCP (Robotic Cellular Phone) which integrates RT and CP in the vision of opening a combined advancement of CP, IT, and RT, RCP consists of 3 sub-modules. They are $RCP^{Mobility}$(RCP Mobility System), $RCP^{Interaction}$, and $RCP^{Integration}$. The main focus of this paper is on $RCP^{Mobility}$ which combines an autonomous navigation system of the RT mobility with CP. Through $RCP^{Mobility}$, we are able to provide CP with robotic functions such as auto-charging and real-world robotic entertainment. Ultimately, CP may become a robotic pet to the human beings. $RCP^{Mobility}$ consists of various controllers. Two of the main controllers are trajectory controller and self-localization controller. While the former is responsible for the wheel-based navigation of RCP, the latter provides localization information of the moving RCP With the coordinates acquired from RFID-based self-localization controller, trajectory controller refines RCP's movement to achieve better navigation. In this paper, a prototype of $RCP^{Mobility}$ is presented. We describe overall structure of the system and provide experimental results on the RCP navigation.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.730-736
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• 2011

In this paper, we designed the models for pattern classification which can reflect the latest trend in time series. It has been shown that fusion models based on statistical and AI methods are superior to traditional ones for the pattern classification model supporting decision making. Especially, the hit rates of pattern classification models combined with fuzzy theory are relatively increased. The statistical SVM models combined with fuzzy membership function, or the models combining neural network and FCM has shown good performance. BPN, PNN, FNN, FCM, SVM, FSVM, Decision Tree, Time Series Analysis, and Regression Analysis were used for pattern classification models in the experiments of this paper. The economical indices DB with time series properties of the financial market(Korea, KOSPI200 DB) and the electrocardiogram DB of arrhythmia patients in hospital emergencies(USA, MIT-BIH DB) were used for data base.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.759-765
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• 2006

In this paper, it is proposed an effective face expression recognition LDA mixed mode using a triangularity membership fuzzy function and wavelet basis. The proposal algorithm gets performs the optimal image, fuzzy wavelet algorithm and Expression recognition is consisted of face characteristic detection step and face Expression recognition step. This paper could applied to the PCA and LDA in using some simple strategies and also compares and analyzes the performance of the LDA mixed model which is combined and the facial expression recognition based on PCA and LDA. The LDA mixed model is represented by the PCA and the LDA approaches. And then we calculate the distance of vectors dPCA, dLDA from all fates in the database. Last, the two vectors are combined according to a given combination rule and the final decision is made by NNPC. In a result, we could showed the superior the LDA mixed model can be than the conventional algorithm.

• Structural Engineering and Mechanics
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• v.82 no.1
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• pp.107-120
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• 2022

The bracing members capable of active control against seismic loads to reduce earthquake damage have been widely utilized in construction projects. Effectively reducing the structural damage caused by earthquake events, bracing systems equipped with retrofitting damper devices, which take advantage of the energy dissipation and impact absorption, have been widely used in practical construction sites. Shape Memory Alloys (SMAs) are a new generation of smart materials with the capability of recovering their predefined shape after experiencing a large strain. This is mainly due to the shape memory effects and the superelasticity of SMA. These properties make SMA an excellent alternative to be used in passive, semi-active, and active control systems in civil engineering applications. In this research, a new system in diagonal braces with slit damper combined with SMA is investigated. The diagonal element under the effect of tensile and compressive force turns to shear force in the slit damper and creates tension in the SMA. Therefore, by creating shear forces in the damper, it leads to yield and increases the energy absorption capacity of the system. The purpose of using SMA, in addition to increasing the stiffness and strength of the system, is to create reversibility for the system. According to the results, the highest capacity is related to the case where the ratio of the width of the middle section to the width of the end section (b₁/b) is 1.0 and the ratio of the height of the middle part to the total height of the damper (h₁/h) is 0.1. This is mainly because in this case, the damper section has the highest cross-section. In contrast, the lowest capacity is related to the case where b₁/b=0.1 and the ratio h₁/h=0.8.

• Smart Structures and Systems
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• v.33 no.5
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• pp.365-374
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• 2024

This paper adopts a new approach in which nonlinear vibrations can be controlled using fuzzy controllers by optimal grey evolutionary algorithm. If the fuzzy controller cannot stabilize the systems, then the high frequency is injected into the system to assist the controller, and the system is asymptotically stabilized by adjusting the parameters. This paper uses the GM (grey model) and the neural network prediction model. The structure of the neural network is improved from a single factor, and multiple data inputs are extended to various factors and numerous data inputs. The improved model expands the applicable range of uncontrolled elements and improves the accuracy of controlled prediction, using the model that has been trained and stabilized by multiple learning. The simulation results show that the improved gray neural network model has higher prediction accuracy and reliability than the traditional GM model, improving controlled management and pre-control ability. In the combined prediction, the time series parameters and the predicted values obtained from the GM (1,1) (Grey Model of first order and one variable) are simultaneously used as the input terms of the neural network, considering the influence of the non-equal spacing of the data, which makes the results of the combined gray neural network model more rationalized. By adjusting the model structure and system parameters to simulate and analyze the controlled elements, the corresponding risk change trend graphs and prediction numerical calculation results are obtained, which also realize the effective prediction of controlled elements. According to the controlled warning principle and objective, the fuzzy evaluation method establishes the corresponding early warning response method. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage.

• Journal of Korean Association for Spatial Structures
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• v.11 no.2
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• pp.71-79
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• 2011

Due to the self-equilibrium status of the cable system, the loss of the tensioning in the cable system results in other cables carrying larger tension forces than those initially calculated by structural engineers. Also, turn-buckle systems, which have been widely used to pre-tension and/or re-tension the cables, are limited to use for small cables and to provide a rough estimation for tension forces. In this study, the re-tensioning cable connection systems were developed to overcome the problems mentioned above. The main objective of the proposed system is to re-tension large cables and measure the exact amount of tension forces of the cable systems. This connection system is also combined with the wireless signal monitoring module so that engineers are able to measure the tension forces any place where the internet is available. This paper presents the development of the re-tensioning cable connection systems and experiment using the real-scale cable systems to verify the fe-tensioning and signal monitoring systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.555-565
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• 1999

The optimal identification algorithm of fuzzy systems is presented for rule-based fuzzy modeling of nonlinear complex systems. Nonlinear systems are expressed using the identification of structure such as input variables and fuzzy input subspaces, and parameters of a fuzzy model. In this paper, the rule-based fuzzy modeling implements system structure and parameter identification using the fuzzy inference methods and hybrid structure combined with two types of optimization theories for nonlinear systems. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. The proposed hybrid optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Here, a genetic algorithm is utilized for determining initial parameters of membership function of premise fuzzy rules, and the improved complex method which is a powerful auto-tuning algorithm is carried out to obtain fine parameters of membership function. Accordingly, in order to optimize fuzzy model, we use the optimal algorithm with a hybrid type for the identification of premise parameters and standard least square method for the identification of consequence parameters of a fuzzy model. Also, an aggregate performance index with weighting factor is proposed to achieve a balance between performance results of fuzzy model produced for the training and testing data. Two numerical examples are used to evaluate the performance of the proposed model.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.3
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• pp.1-14
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• 2024

Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

• Journal of Internet Computing and Services
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• v.8 no.1
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• pp.47-55
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• 2007

In this paper, we propose and observe a system that adopts Common-MCS (Modulation and Coding Scheme) level over all layer and Independent-MCS level for each layer in the combined AMC-V-BLAST (Adaptive Modulation and Coding-Vertical-Bell-lab Layered Space-Time) system. Also, comparing with the combined system using Common-MCS level, we observe throughput performance improvement in case of Independent-MCS level. As a result of simulation, Independent-MCS level case adapts modulation and coding scheme for maximum throughput to each channel condition in separate layer, resulting in improved throughput compared to Common-MCS level case. Especially, the results show that the combined AMC-V-BLAST system with Independent-MCS level achieves a gain of 700kbps in $7{\sim}9dB$ SNR (Signal-to-Noise Ratio) range against using Common-MCS level. In addition, the combined AMC-V-BLAST system using MMSEnulling method with receive diversity is verified that the difference of throughput between Independent MCS level system and common MCS level system in $7dB{\sim}9dB$ SNR is about 350kbps more or less.