• KIPS Transactions on Computer and Communication Systems
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• v.1 no.1
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• pp.35-46
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• 2012

The development of wireless communication systems has resulted in the availability of several access technologies at any geographic area, such as 3G networks, wireless local area networks (WLANs) and wireless broadband networks. The development of these technologies is provided for users who have experienced mobile network environments which are slow or fast-movement environment and change distance between the AP(Access Point). This paper describes network performance issues in various environmental changes. Also, Fuzzy logic is applied to evaluate the performance in vehicle networks around users' environmental factors to focusing on the minimizing of transfer time and costs. First, WLAN and 3G networks fixed distance between AP, Second, WLAN and 3G networks random distance between APs, finally above two environmental with vehicle Ad hoc networks is analyzed. These V2I and V2V environmental condition are assumed. Results which based on Fuzzy logic suggest an optimal performance in vehicle network environments according to vehicle speed and distance between APs. Proposed algorithm shows 21% and 13% improvement of networks performance in V2I and V2V environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.420-425
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• 1999

The maximum demand controller is an electrical equipment installed at the consumer side of power system for monitoring the electrical energy consumed during every integrating period and preventing the target maximum demand (MD) being exceeded by disconnecting sheddable loads. By avoiding the peak loads and spreading the energy requirement the controller contributes to maximizing the utility factor of the generator systems. It results in not only saving the energy but also reducing the budget for constructing the natural base facilities by keeping thc number of generating plants ~ninimumT. he conventional MD controllers often bring about the large number of control actions during the every inteyating period and/or undesirable loaddisconnecting operations during the beginning stage of the integrating period. These make the users aviod the MD controllers. In this paper. fuzzy control technique is used to get around the disadvantages of the conventional MD control system. The proposed MD controller consists of the predictor module and the fuzzy MD control module. The proposed forecasting method uses the SOFM neural network model, differently from time series analysis, and thus it has inherent advantages of neural network such as parallel processing, generalization and robustness. The MD fuzzy controller determines the sensitivity of control action based on the time closed to the end of the integrating period and the urgency of the load interrupting action along the predicted demand reaching the target. The experimental results show that the proposed method has more accurate forecastinglcontrol performance than the previous methods.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1069-1077
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• 2008

The railway abrasion measurement system have to satisfy two conditions to increase the measurement accuracy as follows. The laser region which is projected on the rail have to be extracted without the geometrical distortion. The mapping of the acquired laser region data on the rail profile have to be processed exactly. But, the conventional railway abrasion measurement system is deeply effected by the foreign substance( dust, rainwater, and so on ) on the railway or the sensitive response characteristic of the laser to the external measurement circumstance, and then the measurement errors arise from above factors. When the laser region is projected on the rail extracts from the acquired image, the interference of the light with the same frequency as the laser system occurs the serious problems. In the process of the mapping between the railway profile and the extracted laser region, the measurement accuracy is very highly effected by the geometrical distortion and the abnormal variation. In this Paper, we propose the novel method to increase the accuracy of the railway abrasion measurement dramatically. we designed and manufactured the high precision and fast image processing board with DSP Core and FPGA to measure the railway abrasion. The image processing board has the capability that the image of 1024X1280 from camera can be processed with the speed of 480 frame/sec. And, we apply the image processing algorithm base on the wavelet to extract the laser region is projected on the rail exactly. Finally, we developed high precision railway abrasion measurement system with the error range less than +/-0.5mm by which 2D image data is covered 3D data and mapped on the rail profile using the camera model and the perspective transform.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.594-600
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• 2021

Curved beam structures are generally used as components in structures such as railroad bridges and vehicles. The stability analysis of curved beams has been studied by a large number of researchers. Due to the complexities of structural components, it is difficult to obtain an analytical solution for any boundary conditions. In order to overcome these difficulties, the differential quadrature method (DQM) has been applied for a large number of cases. In this study, DQM was used to solve the complicated partial differential equations for buckling analysis of curved beams. The governing differential equation was deduced and solved for beams subjected to uniformly distributed radial loads. Critical loads were calculated with various opening angles, boundary conditions, and parameters. The results of the DQM were compared with exact solutions for available cases, and the DQM gave outstanding accuracy even when only a small number of grid points was used. Critical loads were also calculated for the in-plane inextensional buckling of the asymmetric curved beams, and two theories were compared. The study of a beam with extensibility of the arch axis shows that the effects on the critical loads are significant.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.96-110
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• 2018

As the development of ICT has made it easier to collect various traffic information, research on creating new traffic attributes is drawing attention. Estimation and forecasts of demand and traffic volume are one of the main indicators that are essential to traffic operation, assuming that the traffic pattern at a particular node or link is repeated. Traditionally, a survey method was used to demonstrate this similarity on trip behavior. However, the method was limited to achieving high accuracy with high costs and responses that relied on the respondents' memory. Recently, as traffic data has become easier to gather through ETC system, smart card, studies are performed to identify the regularity of trip in various ways. In, this study, route-level trip data collected in Daegu metropolitan city were analyzed to confirm that individual traveler forms a spatially similar trip chain over several days. For this purpose, we newly define the concept of spatial trip regularity and assess the spatial difference between daily trip chains using the sequence alignment algorithm, Dynamic Time Warping. In addition, we will discuss the applications as the indicators of fixed traffic demand and transportation services.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1143-1153
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• 2018

For TOPS InSAR processing, high-precision image co-registration is required. We propose an image co-registration method suitable for the TOPS mode by comparing the performance of cross correlation method, the geometric co-registration and the enhanced spectral diversity (ESD) matching algorithm based on the spectral diversity (SD) on the Sentinel-1 TOPS mode image. Using 23 pairs of interferometric pairs generated from 25 Sentinel-1 TOPS images, we applied the cross correlation (CC), geometric correction with only orbit information (GC1), geometric correction combined with iterative cross-correlation (GC2, GC3, GC4), and ESD iteration (ESD_GC, ESD_1, ESD_2). The mean of co-registration errors in azimuth direction by cross correlation and geometric matching are 0.0041 pixels and 0.0016 pixels, respectively. Although the ESD method shows the most accurate result with the error of less than 0.0005 pixels, the error of geometric co-registration is reduced to 0.001 pixels by repetition through additional cross correlation matching between the reference and resampled slave image. The ESD method is not applicable when the coherence of the burst overlap areas is low. Therefore, the geometric co-registration method through iterative processing is a suitable alternative for time series analysis using multiple SAR data or generating interferogram with long time intervals.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.27-32
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• 2020

This paper compare the adaptive equalization performance according to the values of adaptive step variation speed for adapting in VS-CCA (Variable Stepsize-Compact Constellation Algorithm) based on nonlinear function function of error signal. The VS-CCA algorithm compacts the 16-QAM nonconstant modulus signal into the 4 groups of 4-QAM constant modulus signal constellation in quadature plane, then the error signal is generated using the constant modulus of transmitted signal statistics. The adaptive equalizer coefficient were updated in order to achieve the minimum cost function by varying step based on the nonlinear function of error signal. In this time, the instantaneous adaptive step is determined according to the value of step variation speed of nonlinear function and the different equalization performance were obtained according to the step variation speed value. The equalizer internal index and external index which represents the robustness of external noise were used for the performance comparison index. As a result of computer simulation, it was confirmed that the value of variation speed less than 1.0 give more superior in every performance index compared to the greater than 1.0 in steady state.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.45-55
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• 2022

The size of the cryptocurrency market is growing. For example, market capitalization of bitcoin exceeded 500 trillion won. Accordingly, many studies have been conducted to predict the price of cryptocurrency, and most of them have similar methodology of predicting stock prices. However, unlike stock price predictions, machine learning become best model in cryptocurrency price predictions, conceptually cryptocurrency has no passive income from ownership, and statistically, cryptocurrency has at least three times higher liquidity than stocks. Thats why we argue that a methodology different from stock price prediction should be applied to cryptocurrency price prediction studies. We propose Reverse Walk-forward Validation (RWFV), which modifies Walk-forward Validation (WFV). Unlike WFV, RWFV measures accuracy for Validation by pinning the Validation dataset directly in front of the Test dataset in time series, and gradually increasing the size of the Training dataset in front of it in time series. Train data were cut according to the size of the Train dataset with the highest accuracy among all measured Validation accuracy, and then combined with Validation data to measure the accuracy of the Test data. Logistic regression analysis and Support Vector Machine (SVM) were used as the analysis model, and various algorithms and parameters such as L1, L2, rbf, and poly were applied for the reliability of our proposed RWFV. As a result, it was confirmed that all analysis models showed improved accuracy compared to existing studies, and on average, the accuracy increased by 1.23%p. This is a significant improvement in accuracy, given that most of the accuracy of cryptocurrency price prediction remains between 50% and 60% through previous studies.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.304-311
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• 2022

Although the SEAD(suppression to enemy air defenses) mission is a strategically important task in modern warfare, the high risk of direct exposure to enemy air defense assets forces to use of unmanned aerial vehicles. this paper proposes a path planning algorithm for SEAD mission for an unmanned aerial vehicle and a method for calculating the mission effectiveness on the planned path. Based on the RRT-based path planning algorithm, a low-altitude ingress/egress flight path that can consider the enemy's short-range air defense threat was generated. The Dubins path-based Intercept path planning technique was used to generate a path that is the shortest path while avoiding the enemy's short-range anti-aircraft threat as much as possible. The ingress/intercept/egress paths were connected in order. In addition, mission effectiveness consisting of fuel consumption, the survival probability, the time required to perform the mission, and the target destruction probability was calculated based on the generated path. The proposed techniques were verified through a scenario.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.