• Korean Journal of Computational Design and Engineering
• /
• v.8 no.4
• /
• pp.243-253
• /
• 2003

This paper presents a new geometric morphing algorithm for polygons based on a simple geometric structure called direction map, which is mainly composed of a circular list of direction vectors defined by two neighboring vertices of a polygon. To generate a sequence of intermediate morphing shapes, first we merge direction maps of given control shapes based on a certain ordering rule of direction vectors, and scale the length of each direction vectors using Bezier or blossom controls. We show that the proposed algorithm is an improvement of the previous methods based on Minkowski sum (or convolution) in th aspects of computational efficiency and geometric properties.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.3
• /
• pp.38-51
• /
• 2020

A bottleneck and congestion occur when a freeway is closed due to maintenance and construction activities on the freeway. Although various traffic managements have been developed to improve the traffic efficiency at freeway work zones, such as merge control, there is a limit to those controls with human drivers. On the other hand, the wireless communication of connected and automated vehicles (CAVs) enables the operation of advanced traffic management. This study developed a traffic control strategy that integrates Dynamic Merge Control (DMC) and Lane Change Control (LCC) in a CAV environment. DMC operates as an either early or late merge based on the occupancy rate of upstream of the work zone. The LCC algorithm determines the number of vehicles that need to change their lane to balance the traffic volume on open lanes. The simulation results showed that integrated control improves the cumulative vehicle count, average speed upstream, and average network travel time.

• Journal of IKEEE
• /
• v.22 no.4
• /
• pp.1099-1103
• /
• 2018

Platooning of vehicles is an efficient traffic management model that improves traffic flow and fuel consumption. Especially, it is necessary to reduce computational load and networking overhead in automated connected vehicle systems. Because it is important to maintain the size of the platoon group appropriately for efficient platoon operation, this study proposed a dynamic grouping scheme for platooning in an automated vehicle system. The proposed scheme is analyzed by a mathematical model based on Markov chain. From the performance evaluation, it was confirmed that the proposed scheme appropriately controls the size of the platoon group.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.8
• /
• pp.659-665
• /
• 2000

In this paper a platoon merging control system is considered as a remotely located system with state represented by a stochastic process. in the system it is common to encounter situations where a single decision maker controls a large number of subsystems and observation and control signals are sent over a communication channel with finite capacity and significant transmission delays. Unlike a classical estimation problem where the observation is a continuous process corrupted by additive noise there is a constraint that the observation must be coded and transmitted over a digital communication channel with fintie capacity. A recursive coder-estimator sequence is a state estimation scheme based on observations transmitted with finite communication capacity constraint. in this paper we introduce a stochastic model for the lead vehicle in a platoon of vehicles in a lane considering the angle between the road surface and a horizontal plane as a stochastic process. In order to merge two platoons the lead vehicle of the following platoon is controlled by a remote control station. Using the observation transmitted over communication channel the remote control station designs the feedback controller. The simulation results show that the intervehicle spacings and the deviations from the desired intervehicle spacing are well regulated.

• Journal of Multimedia Information System
• /
• v.8 no.4
• /
• pp.233-242
• /
• 2021

Various anatomical MRI imaging biomarkers for Alzheimer's Disease (AD) identification have been recognized so far. Cortical and subcortical volume, hippocampal, amygdala volume, and genetics patterns have been utilized successfully to diagnose AD patients from healthy. These fundamental sMRI bio-measures have been utilized frequently and independently. The entire possibility of anatomical MRI imaging measures for AD diagnosis might thus still to analyze fully. Thus, in this paper, we merge different structural MRI imaging biomarkers to intensify diagnostic classification and analysis of Alzheimer's. For 54 clinically pronounce Alzheimer's patients, 58 cognitively healthy controls, and 99 Mild Cognitive Impairment (MCI); we calculated 1. Cortical and subcortical features, 2. The hippocampal subfield, amygdala nuclei volume using Freesurfer (6.0.0) and 3. Genetics (APoE ε4) biomarkers were obtained from the ADNI database. These three measures were first applied separately and then combined to predict the AD. After feature combination, we utilize the sequential feature selection [SFS (wrapper)] method to select the top-ranked features vectors and feed them into the Multi-Kernel SVM for classification. This diagnostic classification algorithm yields 94.33% of accuracy, 95.40% of sensitivity, 96.50% of specificity with 94.30% of AUC for AD/HC; for AD/MCI propose method obtained 85.58% of accuracy, 95.73% of sensitivity, and 87.30% of specificity along with 91.48% of AUC. Similarly, for HC/MCI, we obtained 89.77% of accuracy, 96.15% of sensitivity, and 87.35% of specificity with 92.55% of AUC. We also presented the performance comparison of the proposed method with KNN classifiers.

• Journal of Korean Society of Transportation
• /
• v.26 no.1
• /
• pp.215-223
• /
• 2008

Due partly to lack of actual lane-changing data and partly to few studies on simulation functions to consider the lane-changing behavior, it may result in significant difference between simulation-based and real conditions. The objectives of this study are to estimate the set of mandatory lane-changing models and to analyze their features, depending on the merge control strategies under the lane-closed work zone operations. To achieve them, first, the elaborated calibration is required to simulate the mandatory lane-changing behaviors with the actual field data. Second, one can estimate their models with the logistic regression models, to obtain traffic variables as well as the lane-changing frequencies under the various levels of work zone traffic conditions. As a result, one can state that the well-calibrated simulation has the potential to properly reflect the target mandatory lane-changing behaviors. In addition, it should be mentioned that the set of proposed models is not practicable but preliminary result needed to identify the relations between the actual traffic conditions and lane-changing maneuvers and to develop their practical models for the actual applications.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.43 no.1 s.307
• /
• pp.9-16
• /
• 2006

This Paper proposes an adaptive error diffusioThis paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, and the MGD values are filled within a local window to merge the potential text segments. Isolated segments are then eliminated in the non-text region filtering process. After the left segmentation, a conventional error diffusion method is applied to the background, while the edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, the gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) prevents the printing of successive dots around the text region boundaries. The error diffusion algorithm with edge enhancement is extended to halftone color images to sharpen the tort regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, the additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. By using the proposed algorithm, the text of a scanned image is sharper than that with a conventional error diffusion without changing background.