• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3092-3107
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• 2019

Visible-infrared image fusion is a process of synthesizing an infrared image and a visible image into a fused image. This process synthesizes the complementary advantages of both images. The infrared image is able to capture a target object in dark or foggy environments. However, the utility of the infrared image is hindered by the blurry appearance of objects. On the other hand, the visible image clearly shows an object under normal lighting conditions, but it is not ideal in dark or foggy environments. In this paper, we propose a multi-guided filter and a real-time image fusion method. The proposed multi-guided filter is a modification of the guided filter for multiple guidance images. Using this filter, we propose a real-time image fusion method. The speed of the proposed fusion method is much faster than that of conventional image fusion methods. In an experiment, we compare the proposed method and the conventional methods in terms of quantity, quality, fusing speed, and flickering artifacts. The proposed method synthesizes 57.93 frames per second for an image size of $320{\times}270$. Based on our experiments, we confirmed that the proposed method is able to perform real-time processing. In addition, the proposed method synthesizes flicker-free video.

• Research in Mathematical Education
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• v.22 no.1
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• pp.19-33
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• 2019

While the field of mathematics education strives to promote equitable mathematics learning and identifies it as a core instructional practice, less is known about its effective enactment. As teachers' teaching practices are dependent on their views and beliefs, this study investigated 133 elementary pre-service teachers' (PSTs') interpretations of diverse learners' learning experiences and proposed accommodations for them as reflected in their lesson planning process. Findings showed that PSTs came up with some strategies that are often suggested in teacher education literature, such as using multiple modes of representation and various grouping strategies. However, their responses were generic in nature rather than specific to diverse learners. Also, it was noted that many PSTs' interchangeably referred to the English Language Learners (ELLs), struggling learners, and culturally diverse learners, inferring that they thought that culturally diverse students must have been ELLs and that ELLs or culturally diverse students must have been weaker students in math. We found that the PSTs used their own frames while filtering and discarding information about diverse student populations to develop instructional plans, rather than based on the results of assessments of learning. We suggest that it is the critical first step to unwrap PSTs' unproven assumptions to better equip them for working with all of their future students.

• Earthquakes and Structures
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• v.20 no.3
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• pp.279-293
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• 2021

Most of the existing seismic codes for RC buildings consider only a scenario earthquake for analysis, often characterized by the response spectrum at the specified location. However, any real earthquake event often involves occurrences of multiple earthquakes within a few hours or days, possessing similar or even higher energy than the first earthquake. This critically impairs the rehabilitation measures thereby resulting in the accumulation of structural damages for subsequent earthquakes after the first earthquake. Also, the existing seismic provisions account for the non-linear response of an RC building frame implicitly by specifying a constant response modification factor (R) in a linear elastic design. However, the 'R' specified does not address the changes in structural configurations of RC moment-resisting frames (RC MRFs) viz., building height, number of bays present, bay width, irregularities arising out of mass and stiffness changes, etc. resulting in changed dynamic characteristics of the structural system. Hence, there is an imperative need to assess the seismic performance under sequential earthquake ground motions, considering the adequacy of code-specified 'R' in the representation of dynamic characteristics of RC buildings. Therefore, the present research is focused on the evaluation of the non-linear response of medium-rise 3D RC MRFs with and without vertical irregularities under bi-directional sequential earthquake ground motions using non-linear dynamic analysis. It is evident from the results that collapse probability increases, and 'R' reduces significantly for various RC MRFs subjected to sequential earthquakes, pronouncing the vulnerability and inadequacy of estimation of design base shear by code-specified 'R' under sequential earthquakes.

• Smart Structures and Systems
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• v.28 no.6
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• pp.811-825
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• 2021

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.374-375
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• 2022

Recently, Metaverse service has been widely used to naturally communicate with a remote location, freeing from time and spatial constraints. In order to produce such contents, it is necessary to restore and synthesize a 3D model based on real space data. In this paper, a 3D-generated reconstruction model is produced based on continuous images using multiple cameras and a technique to correct the reconstructed 3D model is presented. For this. offline multi-camera setup was performed, errors were analyzed on the 3D model created through images obtained from various angles, and correction was performed using a matching technique between image frames. It is expected that 3D reconstructed data can be utilized in various service fields such as culture, tourism, and medical care.

• ETRI Journal
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• v.45 no.5
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• pp.836-846
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• 2023

Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light detection and ranging (LiDAR) point cloud in crowded environments. The pedestrian detection quickly segments a sparse 3D point cloud into individual pedestrians using a lightweight convolutional autoencoder and connected-component algorithm. The multi-pedestrian tracking identifies the same pedestrians considering motion and appearance cues in continuing frames. In addition, it estimates pedestrians' dynamic movements with various patterns by adaptively mixing heterogeneous motion models. We evaluate the computational speed and accuracy of each module using the KITTI dataset. We demonstrate that our integrated system, which rapidly and accurately recognizes pedestrian movement and appearance using a sparse 3D LiDAR, is applicable for robot navigation in crowded spaces.

• Advances in Computational Design
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• v.8 no.4
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• pp.327-351
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• 2023

This article explores how multi-objective optimization techniques can be used to design cost-effective and structurally optimal spatial steel structures, highlighting that optimizing performance can be as important as minimizing costs in real-world engineering problems. The study includes the minimization of maximum horizontal displacement, the maximization of the first natural frequency of vibration, the maximization of the critical load factor concerning the first global buckling mode of the structure, and weight minimization as the objectives. Additionally, it outlines a systematic approach to selecting the best design by employing four different evolutionary algorithms based on differential evolution and a multi-criteria decision-making methodology. The paper's contribution lies in its comprehensive consideration of multiple conflicting objectives and its novel approach to simultaneous consideration of bracing system, column orientation, and commercial profiles as design variables.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.17-25
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• 2007

In most electronic imaging applications, image with high resolution(HR) are desired. HR means that pixel density within an image is high, and therefore HR image can offer more details that may be critical in various applications. Digital images that are captured by CCD and CMOS cameras usually have a very low resolution, which significantly limits the performance of image recognition systems. Image super-resolution techniques can be applied to overcome the limits of these imaging systems. Super-resolution techniques have been proposed to increase the resolution by combining information from multiple images. To techniques were consisted of the registration algorithm for estimation and shift, the nearest neighbor interpolation using weight of acquired frames and presented frames. In this paper, it is proposed the image interpolation techniques using the wavelet base function. This is applied to embody a correct edge image and natural image when expend part of the still image by applying the wavelet base function coefficient to the conventional Super-Resolution interpolation method. And the proposal algorithm in this paper is confirmed to improve the image applying the nearest neighbor interpolation algorithm, bilinear interpolation algorithm.,bicubic interpolation algorithm through the computer simulation.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.255-274
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• 2006

Moving object boundary is very important for the accurate segmentation of moving object. We extract the moving object boundary from the moving object edge. But the object boundary shows broken boundaries so we develop a novel boundary linking algorithm to link the broken boundaries. The boundary linking algorithm forms a quadrant around the terminating pixel in the broken boundaries and searches for other terminating pixels to link in concentric circles clockwise within a search radius in the forward direction. The boundary linking algorithm guarantees the shortest distance linking. We register the background from the image sequence using the stationary background filtering. We construct two object masks, one object mask from the boundary linking and the other object mask from the initial moving object, and use these two complementary object masks to segment the moving objects. The main contribution of the proposed algorithms is the development of the novel object boundary linking algorithm for the accurate segmentation. We achieve the accurate segmentation of moving object, the segmentation of multiple moving objects, the segmentation of the object which has a hole within the object, the segmentation of thin objects, and the segmentation of moving objects in the complex background using the novel object boundary linking and the background automatically. We experiment the algorithms using standard MPEG-4 test video sequences and real video sequences of indoor and outdoor environments. The proposed algorithms are efficient and can process 70.20 QCIF frames per second and 19.7 CIF frames per second on the average on a Pentium-IV 3.4GHz personal computer for real-time object-based processing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.1-7
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• 2020

In modern society, as technology has advanced and human life area has expanded, there has been an increasing demand for high-quality voice and video communications services without restrictions on time and place. In response to this demand, satellite communications systems that provide a wide range of communications and that offer multiple access are evolving day by day. In satellite communications systems such as Digital Video Broadcasting - Return Channel Via Satellite (DVB-RCS) and Warfighter Information Network-Tactical (WIN-T), the multi-frequency time division multiple access (MF-TDMA) demand assigned multiple access (DAMA) scheme is used for efficient resource allocation. In this scheme, since the satellite terminals periodically request resources from the network controller, and the network controller dynamically allocates resources, it is necessary to arrange resource allocation information from time to time. Shortening of the alignment time is a more important factor in a satellite communications system in which a long transmission delay occurs due to long-distance transmission and reception. In this paper, we propose a sorting algorithm variable-selection scheme that shortens the sorting time by cross-selecting the sorting algorithm based on a threshold value, while setting the number of frames in the MF-TDMA DAMA satellite communications system as the threshold value.