• Advances in aircraft and spacecraft science
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• v.9 no.4
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• pp.301-318
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• 2022

This paper presents the free vibration analysis of 3D printed sandwich beams by using high-order theories based on the Carrera Unified Formulation (CUF). In particular, the component-wise (CW) approach is adopted to achieve a high fidelity model of the printed part. The present model has been used to build an accurate database for collecting first natural frequency of the beams, then predicting Young's modulus based on an inverse problem formulation. The database is built from a set of randomly generated material properties of various values of modulus of elasticity. The inverse problem then allows finding the elastic modulus of the input parameters starting from the information on the required set of the output achieved experimentally. The natural frequencies evaluated during the experimental test acquired using a Digital Image Correlation method have been compared with the results obtained by the means of CUF-CW model. The results obtained from the free-vibration analysis of the FDM beams, performed by higher-order one-dimensional models contained in CUF, are compared with ABAQUS results both first five natural frequency and degree of freedoms. The results have shown that the proposed 1D approach can provide 3D accuracy, in terms of free vibration analysis of FDM printed sandwich beams with a significant reduction in the computational costs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.1
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• pp.9-19
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• 2024

Deep learning-based computer vision anomaly detection algorithms are widely utilized in various fields. Especially in the manufacturing industry, the difficulty in collecting abnormal data compared to normal data, and the challenge of defining all potential abnormalities in advance, have led to an increasing demand for unsupervised learning methods that rely on normal data. In this study, we conducted a comparative analysis of deep learning-based unsupervised learning algorithms that define and detect abnormalities that can occur when transparent contact lenses are immersed in liquid solution. We validated and applied the unsupervised learning algorithms used in this study to the existing anomaly detection benchmark dataset, MvTecAD. The existing anomaly detection benchmark dataset primarily consists of solid objects, whereas in our study, we compared unsupervised learning-based algorithms in experiments judging the shape and presence of lenses submerged in liquid. Among the algorithms analyzed, EfficientAD showed an AUROC and F1-score of 0.97 in image-level tests. However, the F1-score decreased to 0.18 in pixel-level tests, making it challenging to determine the locations where abnormalities occurred. Despite this, EfficientAD demonstrated excellent performance in image-level tests classifying normal and abnormal instances, suggesting that with the collection and training of large-scale data in real industrial settings, it is expected to exhibit even better performance.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.893-903
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• 2018

The necessity of automatic precise georeferencing is increasing with the increase applications of high-resolution satellite imagery. One of the methods for collecting ground control points (GCPs) for precise georeferencing is to use chip images obtained by extracting a subset of an image map such as an ortho-aerial image, and can be automated using an image matching technique. In this case, the importance of the image matching success rate is increased due to the limitation of the number of the chip images for the known reference points such as the unified control point. This study aims to propose a method to improve the success rate of image matching between KOMPSAT-3A images and GCP chip images from aerial ortho-images. We performed the image matching with 7 cases of band pair using KOMPSAT-3A panchromatic (PAN), multispectral (MS), pansharpened (PS) imagery and GCP chip images, then compared matching success rates. As a result, about 10-30% of success rate is increased to about 40-50% when using PS imagery by using PAN and MS imagery. Therefore, using PS imagery for image matching of KOMPSAT-3A images and aerial ortho-images would be helpful to improve the matching success rate.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.45-52
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• 2000

Genomic approach produces massive amount of data within a short time period, New high-throughput automatic sequencers can generate over a million nucleotide sequence information overnight. A typical DNA chip experiment produces tens of thousands expression information, not to mention the tens of megabyte image files, These data must be handled automatically by computer and stored in electronic database, Thus there is a need for systematic approach of data collection, processing, and analysis. DNA sequence information is translated into amino acid sequence and is analyzed for key motif related to its biological and/or biochemical function. Functional genomics will play a significant role in identifying novel drug targets and diagnostic markers for serious diseases. As an enabling technology for functional genomics, bioinformatics is in great need worldwide, In Korea, a new functional genomics project has been recently launched and it focuses on identi☞ing genes associated with cancers prevalent in Korea, namely gastric and hepatic cancers, This involves gene discovery by high throughput sequencing of cancer cDNA libraries, gene expression profiling by DNA microarray and proteomics, and SNP profiling in Korea patient population, Our bioinformatics team will support all these activities by collecting, processing and analyzing these data.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.943-944
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• 2006

In this paper, we implemented the autonomous mobile robot which can recognize and avoid obstacles, then move to its destination using a camera and ultrasonic sensors. The mobile robot can avoid both stationary obstacles with a camera and moving obstacles with ultrasonic sensors. It can find the self-location with the map-based system, that is, it attempts to localize by collecting sensor data, then updating some belief about its position with respect to a map of the environment.

• The Research Journal of the Costume Culture
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• v.11 no.5
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• pp.683-696
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• 2003

In the post-modern society, creativity is redefined as a capability which collects a wide range of information and recombines them in diverse manners. With a such trend, the characteristics of collage - a method of making a creative image by combining pieces which have no relevance - is becoming prevalent in the post-modern culture. The purpose of this research is to develop a model which generates ideas in fashion design by use of collage techniques. With regard to research methodology, a literature survey was undertaken to find out and understand characteristics of collage. Analytic and positive studies were also done on the styles of fashion design of the 2003 SS collections to which collage techniques applied. In order to generate ideas in fashion design, the following mechanism using collage techniques can be used. Above all, pluralism is realized by collecting incoherent elements. Secondly, deconstruction is made by changing scales and configuration. Lastly, relativity is attained by using parts of ready-made goods and respecting their independency.

• East Asian mathematical journal
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• v.33 no.4
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• pp.431-451
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• 2017

This is a descriptive study with the intent of providing a rich characterization of teachers' perceptions of rate of change. The nature of teachers' perceptions and differences among teachers were examined by collecting data through a survey on teachers' conceptions of rate of change in terms of learning goals, prerequisites, and beliefs about teaching and learning of rate of change, and an interview individually assessing teachers' concept images and definitions. The participating 13 teachers were selected to provide a range of similar and contrasting levels of experiences based on the teachers' educational background and the number of years they had been teaching. Findings and implications of this study are discussed.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.674-675
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• 2015

A 3D indoor model becomes an indiscernible component of BIM (Building Information Modeling) and GIS (Geographic Information System). However, a huge amount of time and human resources are inevitable for collecting spatial measurements and creating such a 3D indoor model. Also, a varied forms of 3D indoor models exist depending on their purpose of use. Thus, in this study, three different 3D indoor models are defined as 1) omnidirectional images, 2) a 3D realistic model, and 3) 3D indoor as-built model. A series of reconstruction methods is then introduced to construct each type of 3D indoor models: they are an omnidirectional image acquisition method, a hybrid surveying method, and a terrestrial LiDAR-based method. The reconstruction methods are applied to a large and complex atrium, and their 3D modeling results are compared and analyzed.

• Asia pacific journal of information systems
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• v.27 no.1
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• pp.38-53
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• 2017

As sensor technologies and image processing technologies make collecting information on users' behavior easy, many researchers have examined automatic emotion recognition based on facial expressions, body expressions, and tone of voice, among others. Specifically, many studies have used normal cameras in the multimodal case using facial and body expressions. Thus, previous studies used a limited number of information because normal cameras generally produce only two-dimensional images. In the present research, we propose an artificial neural network-based model using a high-definition webcam and Kinect to recognize users' emotions from facial and bodily expressions when watching a movie trailer. We validate the proposed model in a naturally occurring field environment rather than in an artificially controlled laboratory environment. The result of this research will be helpful in the wide use of emotion recognition models in advertisements, exhibitions, and interactive shows.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.27-32
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• 2024

Recently, there has been a growing interest in integrating physical toys into video gaming within the game content business. This paper introduces a novel method that leverages low-cost camera as an alternative to using sensor attachments to meet this rising demand. We address the limitations associated with low-cost cameras and propose an optical design tailored to the specific environment of model car recognition. We overcome the inherent limitations of low-cost cameras by proposing an optical design specifically tailored for model car recognition. This approach primarily focuses on recognizing the underside of the car and addresses the challenges associated with this particular perspective. Our method employs a transfer learning model that is specifically trained for this task. We have achieved a 100% recognition rate, highlighting the importance of collecting data under various camera exposures. This paper serves as a valuable case study for incorporating low-cost cameras into vision systems.