• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.63-73
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• 2003

COSMOS(Cycle, Offset, Split Model for Seoul), a real-time traffic adaptive signal system. estimates queue lengths on each approach on the basis of arithmetic average spot speeds calculated on loop detectors installed at each of two adjacent lanes. In this paper, A new method, a traffic volume-weighted average method, was studied and compared with the existing arithmetic average method. It was found that the relationship between the ratio of volumes of two lanes and the difference of average speed of each lane has a linear form. With field data, The two methods were applied and the proposed method shows more stable and reasonable queue estimation results.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.2
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• pp.38-45
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• 1997

In this paper, the three-dimensional stress effect of thermal oxide is simulated. We developed a three-dimensional finite element numerical simulator including three-dimensional adaptive mesh generator that is able to refine and eliminate nearby moving boundary of oxide, and oxidation solver with stress model. To investigate the behavior of thermal oxidation the simulations of thermal oxidation for island and hole structures are carried out assuming silicon wafer of <100> direction, temperature of $1000^{\circ}C$, oxidation time of 60min, wet ambient, initial oxide thickness of $300\AA$, and nitride thickness of $2, 000\AA$. The main effect of deformation at the corner area of oxide is due to distribution of oxidant, but the deformation of oxide is affected by the stressin theoxide. In the island structure which is the structure mostly covered with nitride and a coner is opended to oxidation, oxidation is reduced at the coner by compressive stress. In the hole structure which is the structure mostly opedned to oxide and a coner is convered with nitride, however, oxidation is increased at the coner by tensile stress.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.137-143
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• 2012

The learners using learning content through the smart devices can access to the Internet from anytime and anywhere. However, with the rapid increase of learning content on the Web, it will be time-consuming for learners to find contents they really want to and need to study. Therefore, e-learning systems should not only provide flexible content delivery, but support adaptive harmonizing fusion content. The harmonizing fusion content it is a very important in fusion e-learning service. The representative method to provide synchronization between fusion content is a provide absolute time value between of the contents. However, this method is occurs a problem transferring time delay. Also, to enter an absolute time value for the duration of the each content is several problems arise. In this paper introduces a new smart e-smart service support the harmonizing media based technology to create synchronized learning presentation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2271-2288
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• 2015

The emerging high efficiency video coding (HEVC) standard adopts the quadtree-structured transform unit (TU) in the residual quadtree (RQT) coding. Each TU allows to be split into four equal sub-TUs recursively. The RQT coding is performed for all the possible transform depth levels to achieve the highest coding efficiency, but it requires a very high computational complexity for HEVC encoders. In order to reduce the computational complexity requested by the RQT coding, in this paper, we propose a fast TU size decision method incorporating an adaptive maximum transform depth determination (AMTD) algorithm and a full check skipping - early termination (FCS-ET) algorithm. Because the optimal transform depth level is highly content-dependent, it is not necessary to perform the RQT coding at all transform depth levels. By the AMTD algorithm, the maximum transform depth level is determined for current treeblock to skip those transform depth levels rarely used by its spatially adjacent treeblocks. Additionally, the FCS-ET algorithm is introduced to exploit the correlations of transform depth level between four sub-CUs generated by one coding unit (CU) quadtree partitioning. Experimental results demonstrate that the proposed overall algorithm significantly reduces on average 21% computational complexity while maintaining almost the same rate distortion (RD) performance as the HEVC test model reference software, HM 13.0.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.178-203
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• 2018

In this paper, authors have been evaluated the Frame Error Rate (FER) performance of IEEE 802.11 a/g/p standard 5 GHz frequency band WLAN over Rayleigh and Rician distributed fading channels in presence of Additive White Gaussian Noise (AWGN). Orthogonal Frequency Division Multiplexing (OFDM) based transceiver is implemented by using real-time signal processing frameworks (IEEE 802.11 Blocks) in GNU Radio Companion (GRC) and Ettus USRP N200 is used to process the symbol over the wireless radio channel. The FER is calculated for each sub-carrier conventional modulation schemes used by OFDM such as BPSK, QPSK, 16, 64-QAM with different punctuated coding rates. More precise SNR is computed by modifying the SNR calculation process of YANS and NIST error rate model to estimate more accurate FER. Here, real-time signal constellations, OFDM signal spectrums etc. are also observed to find the effect of multipath propagation of signals through flat and frequency selective fading channels. To reduce the error rate due to the multipath fading effect and Doppler shifting, channel estimation (CE) and equalization techniques such as Least Square (LS) and training based adaptive Least Mean Square (LMS) algorithm are applied in the receiver. The simulation work is practically verified at GRC by turning into a pair of Software Define Radio (SDR) as a simultaneous transceiver.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1311-1320
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• 2000

In this study, shape memory alloy(SMA) wires and piezoceramic actuators(PZT's) are employed in order to generate higher modes on the beam deformations. Compressive force is generated and applied to the beam by the pre-strained SMA wires attached at both ends of the beam. PZT's apply concentrated moments to several locations on the beam. Combinations of the compressive force and concentrated moments are investigated in order to understand the higher-mode deformation of beams. The first desired mode shape is obtained by controlling the temperature of the SMA wires. The first and third mode shapes are performed experimentally by heating SMA wires up to phase transformation temperature. The adaptive wing is defined as a wing whose shape parameters such as the camber, wing twist and thickness can be varied in order to change the wing shape for various flight conditions. In this research, control of the camber has been studied. The wing model consists of three plates and many ribs. Two of the plates are placed parallel to each other and they are clamped at one edge. Third plate connects the other edges of the parallel plates together. Each rib is made of SMA wire and connected to the parallel plates. It generates concentrated force and applies to the plates in oblique directions. The PZT's are bonded onto the plates and exert concentrated moments upon the plate at several locations. The object of this research is to generate various shape of wing by combining the concentrated forces and moments.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1245-1255
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• 2017

The online learning is a process of obtaining the solution for a given objective function where the data is accumulated in real time or in batch units. The stochastic gradient descent method is one of the most widely used for the online learning. This method is not only easy to implement, but also has good properties of the solution under the assumption that the generating model of data is homogeneous. However, the stochastic gradient method could severely mislead the online-learning when the homogeneity is actually violated. We assume that there are two heterogeneous generating models in the observation, and propose the a new stochastic gradient method that mitigate the problem of the heterogeneous models. We introduce a robust mini-batch optimization method using statistical tests and investigate the convergence radius of the solution in the proposed method. Moreover, the theoretical results are confirmed by the numerical simulations.

• Journal of Ecology and Environment
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• v.38 no.2
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• pp.133-143
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• 2015

Freshwater macrophytes improve the structural heterogeneity of microhabitats in water, often providing an important habitat for zooplankton. Some studies have focused on the overall influence of macrophytes on zooplankton, but the effects of macrophyte in relation to different habitat characteristics of zooplankton (e.g., epiphytic and pelagic) have not been intensively studied. We hypothesized that different habitat structures (i.e., macrophyte habitat) would strongly affect zooplankton distribution. We investigated zooplankton density and diversity, macrophyte characteristics (dry weight and species number), and environmental parameters in 40 shallow wetlands in South Korea. Patterns in the data were analyzed using a self-organizing map (SOM), which extracts information through competitive and adaptive properties. A total of 20 variables (11 environmental parameters and 9 zooplankton groups) were patterned onto the SOM. Based on a U-matrix, 3 clusters were identified from the model. Zooplankton assemblages were positively related to macrophyte characteristics (i.e., dry weight and species number). In particular, epiphytic species (i.e., epiphytic rotifers and cladocerans) exhibited a clear relationship with macrophyte characteristics, while large biomass and greater numbers of macrophyte species supported high zooplankton assemblages. Consequently, habitat heterogeneity in the macrophyte bed was recognized as an important factor to determine zooplankton distribution, particularly in epiphytic species. The results indicate that macrophytes are critical for heterogeneity in lentic freshwater ecosystems, and the inclusion of diverse plant species in wetland construction or restoration schemes is expected to generate ecologically healthy food webs.

• Smart Structures and Systems
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• v.13 no.4
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• pp.587-614
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• 2014

In recent years the interest in online monitoring of lightweight structures with ultrasonic guided waves is steadily growing. Especially the aircraft industry is a driving force in the development of structural health monitoring (SHM) systems. In order to optimally design SHM systems powerful and efficient numerical simulation tools to predict the behaviour of ultrasonic elastic waves in thin-walled structures are required. It has been shown that in real industrial applications, such as airplane wings or fuselages, conventional linear and quadratic pure displacement finite elements commonly used to model ultrasonic elastic waves quickly reach their limits. The required mesh density, to obtain good quality solutions, results in enormous computational costs when solving the wave propagation problem in the time domain. To resolve this problem different possibilities are available. Analytical methods and higher order finite element method approaches (HO-FEM), like p-FEM, spectral elements, spectral analysis and isogeometric analysis, are among them. Although analytical approaches offer fast and accurate results, they are limited to rather simple geometries. On the other hand, the application of higher order finite element schemes is a computationally demanding task. The drawbacks of both methods can be circumvented if regions of complex geometry are modelled using a HO-FEM approach while the response of the remaining structure is computed utilizing an analytical approach. The objective of the paper is to present an efficient method to couple different HO-FEM schemes with an analytical description of an undisturbed region. Using this hybrid formulation the numerical effort can be drastically reduced. The functionality of the proposed scheme is demonstrated by studying the propagation of ultrasonic guided waves in plates, excited by a piezoelectric patch actuator. The actuator is modelled utilizing higher order coupled field finite elements, whereas the homogenous, isotropic plate is described analytically. The results of this "semi-analytical" approach highlight the opportunities to reduce the numerical effort if closed-form solutions are partially available.

• Geomechanics and Engineering
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• v.12 no.3
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• pp.441-464
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• 2017

The determination of the mixture parameters of stabilization has become a great concern in geotechnical applications. This paper presents an effort about the application of artificial intelligence (AI) techniques including radial basis neural network (RBNN), multi-layer perceptrons (MLP), generalized regression neural network (GRNN) and adaptive neuro-fuzzy inference system (ANFIS) in order to predict the unconfined compressive strength (UCS) of silty soil stabilized with bottom ash (BA), jute fiber (JF) and steel fiber (SF) under different freeze-thaw cycles (FTC). The dosages of the stabilizers and number of freeze-thaw cycles were employed as input (predictor) variables and the UCS values as output variable. For understanding the dominant parameter of the predictor variables on the UCS of stabilized soil, a sensitivity analysis has also been performed. The performance measures of root mean square error (RMSE), mean absolute error (MAE) and determination coefficient ($R^2$) were used for the evaluations of the prediction accuracy and applicability of the employed models. The results indicate that the predictions due to all AI techniques employed are significantly correlated with the measured UCS ($p{\leq}0.05$). They also perform better predictions than nonlinear regression (NLR) in terms of the performance measures. It is found from the model performances that RBNN approach within AI techniques yields the highest satisfactory results (RMSE = 55.4 kPa, MAE = 45.1 kPa, and $R^2=0.988$). The sensitivity analysis demonstrates that the JF inclusion within the input predictors is the most effective parameter on the UCS responses, followed by FTC.