• Journal of Positioning, Navigation, and Timing
• /
• v.8 no.2
• /
• pp.41-47
• /
• 2019

Recently, number of intentional jamming has increased significantly. If GNSS jammers are activated, user receivers can be largely influenced due to the vulnerable characteristic of the GNSS (Global Navigation Satellite System) signal. When the reception power of the jamming signal and that of the navigation signal are similar, the C/A (Coarse Acquisition) chip delay error can occur in the delay locked loop. To evaluate the jamming effect, a new measurement model is formulated based on previous research works. The new model explains how the jamming to signal ratio affects the ranging measurement accuracy and other parameters. To evaluate the validity of the newly formulated model, the experiment results of the previous research works under actual jamming environment are utilized. By evaluating the consistency of the carrier-to-noise ratio (C/N0) and the position error with the actual jamming environment, the validity of the newly formulated model is verified.

• Steel and Composite Structures
• /
• v.41 no.6
• /
• pp.887-898
• /
• 2021

This paper presents a simplified model to capture the nonlinear behavior of steel frames depending on the spread of plasticity method. New interaction formulae were derived to evaluate the plastic strength for I-shaped steel sections under uniaxial bending moment and axial compression load. Also, new empirical formulae were derived to evaluate the tangent stiffness modulus of steel I-shaped cross-sections considering the effect of the residual stresses suggested by the specifications in European Convention for Construction Steelworks (ECCS). The secant stiffness which depends on the tangent modulus is used to evaluate the internal forces. Based on stiffness matrix method, a finite element analysis program was developed for the nonlinear analysis of space steel frames using the derived formulae. Comparison between the proposed model results with those given by the fiber model shows very good agreement. Numerical examples were introduced to verify, check the accuracy, and evaluate the efficiency of the proposed model. The analysis results show that the new proposed model is accurate and able to minimize the solution time.

• Proceedings of the KIEE Conference
• /
• 2006.10c
• /
• pp.111-113
• /
• 2006

FOUNDATION fieldbus provides scheduling and token-passing services for cyclic and sporadic data respectively. In this paper, we evaluate the delay performance of token-passing mechanism in FOUNDATION fieldbus network system using an experimental model. This paper introduces a method of developing an experimental model which consists of 10 nodes of FOUNDATION fieldbus communication device. Using the experimental model, we evaluate the delay performance of time-critical and time-available data with respect to change of TTRT parameter.

• Journal of Auto-vehicle Safety Association
• /
• v.8 no.4
• /
• pp.31-37
• /
• 2016

Since real road experiments have many restrictions, a multi-vehicle traffic simulator can be an effective tool to develop and evaluate fully automated driving systems. This paper presents multi-vehicle environment simulation tool to develop and evaluate motorway automated driving systems. The proposed simulation tool consists of following two main parts: surrounding vehicle model and environment sensor model. The surrounding vehicle model is designed to quickly generate rational complex traffic situations of motorway. The environment sensor model depicts uncertainty of environment sensor. As a result, various traffic situations with uncertainty of environment sensor can be proposed by the multi-vehicle environment simulation tool. An application to automated driving system has been conducted. A lane changing algorithm is evaluated by performance indexes from the multi-vehicle environment simulation tool.

• Proceedings of the KSR Conference
• /
• 2009.05b
• /
• pp.233-237
• /
• 2009

In this study, we suggest that several approaches to evaluate the collision acceleration value of a car in the article 35 and the guideline 16 of Korean rolling stock safety regulation. There are various methods to evaluate collision acceleration such as; a displacement comparison method by the double integration of filtered acceleration data, a velocity comparison method by the integration of filtered acceleration data, an analysis method of time-velocity curve, or a differential method of time-velocity curve. We compared these methods one another using 1D dynamic simulation model composed of nonlinear dampers, springs and bars, and masses. Also, we applied these methods to a hybrid model, which is made of 3D shell element model and 2D collision dynamics model, in order to evaluate whether 1D force-displacement curve modeling for energy absorbing structures have an effect on the collision acceleration levels or not.

• Journal of Auto-vehicle Safety Association
• /
• v.9 no.3
• /
• pp.19-23
• /
• 2017

This paper presents a lateral driver model with neuromuscular system to evaluate the performance of electric power steering (EPS). Output of most previously developed driver models is steering angle. However, in order to evaluate EPS system, driver model which results in steering torque output is needed. The proposed lateral driver model mainly consists of 2 parts: desired steering angle calculation and conversion of steering angle into steering torque. Desired steering angle calculation part results in steering angle to track desired yaw rate for path tracking. Conversion of steering angle into torque is consideration with neuromuscular system. The proposed driver model is investigated via actual driving data. Compared to other algorithms, the proposed algorithm shows similar pattern of steering angle with human driver. The proposed driver can be utilized to efficiently evaluate EPS system in simulation level.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.9
• /
• pp.3730-3744
• /
• 2020

This study proposes a deep learning-based evolutionary recommendation model for heterogeneous big data integration, for which collaborative filtering and a neural-network algorithm are employed. The proposed model is used to apply an individual's importance or sensory level to formulate a recommendation using the decision-making feedback. The evolutionary recommendation model is based on the Deep Neural Network (DNN), which is useful for analyzing and evaluating the feedback data among various neural-network algorithms, and the DNN is combined with collaborative filtering. The designed model is used to extract health information from data collected by the Korea National Health and Nutrition Examination Survey, and the collaborative filtering-based recommendation model was compared with the deep learning-based evolutionary recommendation model to evaluate its performance. The RMSE is used to evaluate the performance of the proposed model. According to the comparative analysis, the accuracy of the deep learning-based evolutionary recommendation model is superior to that of the collaborative filtering-based recommendation model.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.5 no.2
• /
• pp.87-93
• /
• 2009

In this paper, we propose and evaluate the availability of single sensor node using a hierarchial modeling approach. We divides a sensor node into a software and hardware and analyze failures of each component. We construct Markov chains to represent the components of a sensor node, and then we construct a hierarchical model which use fault tree in upper level and Markov chains in lower level. We evaluate the availability and down of single sensor node.

• Proceedings of the Korean Society of Agricultural Engineers Conference
• /
• 2005.10a
• /
• pp.288-293
• /
• 2005

In this study, SWAT model was applied to the Soyang Dam upstream watershed in order to evaluate the model applicability for estimating runoff, sediment, and nutrients loadings from the watershed. By trial and error method, the model parameters related with runoff, sediment, nitrogen and phosphorus were calibrated step by step. Then the simulated runoff, sediment, and nutrients loadings by the model were compared with the observed data measured at the Soyang Dam, the outlet of the watershed. And several statistical criteria were calculated to evaluate the model performance. From the comparison and statistical criteria, good agreement between simulated and observed stream flows was found. For sediment and nutrients, it was not reliable to quantitatively model the observed values, but the model could simulate the trend with reasonable accuracy. Hence, it was concluded that the model can be applied for the long-term non-point modeling in a large watershed.

• Journal of Software Engineering Society
• /
• v.29 no.1
• /
• pp.13-21
• /
• 2020

As CNN model is applied to various domains such as image classification and object detection, the performance of CNN model which is used to safety critical system like autonomous vehicles should be reliable. To evaluate that CNN model can sustain the performance in various environments, we developed an image data augmentation apparatus which generates images that is changed background. If an image which contains object is entered into the apparatus, it extracts an object image from the entered image and generate s composed images by synthesizing the object image with collected background images. A s a method to evaluate a CNN model, the apparatus generate s new test images from original test images, and we evaluate the CNN model by the new test image. As a case study, we generated new test images from Pascal VOC2007 and evaluated a YOLOv3 model with the new images. As a result, it was detected that mAP of new test images is almost 0.11 lower than mAP of the original test images.