• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.89-98
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• 2004

In this paper, we implement a digital holographic security card system that combines digital holographic memory using random phase encoded reference beams with electrical biometrics. Digitally encoded data including a document, a picture of face, and a fingerprint are recorded by multiplexing of holographic memory. A random phase mask encoding reference beams are used as a decoded key to protect illegal counterfeit. As a result, we can achieve a raw BER of 3.6${\times}$10-4 and shift selectivity of 4${\mu}{\textrm}{m}$ using the 2D random phase mask. Also, we develop a recording pattern and image processing which are suitable for a low cost reader without a position sensing photo-detector for real time data extraction and remove danger of fraud from unauthorized person by comparing the reconstructed holographic data with the live fingerprint data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.102-112
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• 2012

In this paper, we propose a texture classification using wavelet-domain BDIP (block difference of inverse probabilities) and BVLC (block variance of local correlation coefficients) features with WPCA (whitened principal component analysis) classifier. In the proposed method, the wavelet transform is first applied to a query image. The BDIP and BVLC operators are next applied to the wavelet subbands. Global moments for each subband of BDIP and BVLC are then computed and fused into a feature vector. In classification, the WPCA classifier, which is usually adopted in the face identification, searches the training feature vector most similar to the query feature vector. Experimental results show that the proposed method yields excellent texture classification with low feature dimension for test texture image DBs.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.1
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• pp.417-435
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• 2016

Relevance judgment is important in terms of improving the effectiveness of information retrieval systems, and it has been dominant for users to search and use images utilizing internet and digital technologies. However, in the field of image retrieval, there have been only a few studies in terms of identifying relevance criteria. The purpose of this study aims to identify and characterize the non-relevance criteria from the failed image searches. In order to achieve the purpose of this study, a total of 135 participants were recruited and a total of 1,452 criteria items were collected for this study. Analyses and identification on the data set found thirteen criteria such as 'topicality', 'visual content', 'accuracy', 'visual feature', 'completeness', 'appeal to user', 'focal point', 'bibliographic information', 'impression', 'posture', 'face feature', 'novelty', and 'time frame'. Among these criteria, 'visual content' and 'focal point' were introduced in this current study, while 'action' criterion identified in previous studies was not shown in this current study. When image needs and image uses are analyzed with these criteria, there are distinctive differences depending on different image needs and uses.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.31-36
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• 2017

In this paper, we try to search and reproduce the image part of a specific cast from a large number of images. The conventional method must manually set the offset value when searching for a scene or viewing a corner. However, in this paper, the proposed method learns the main character 's face, then finds the main character in the image recognition and moves to the scene where the main character appears to reproduce the image. Data for specific performers is extracted and collected using crawl techniques. Based on the collected data, we learn using convolutional neural network algorithm and perform performance evaluation using it. The performance evaluation measures the accuracy by extracting and judging a specific performer learned in the extracted key frame while playing the drama. The performance confirmation of how quickly and accurately the learned scene is searched has obtained about 93% accuracy. Based on the derived performance, it is applied to the image service such as viewing, searching for person and detailed information retrieval per corner

• Imaging Science in Dentistry
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• v.51 no.3
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• pp.279-290
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• 2021

Purpose: Using images in the facial image comparison process poses a challenge for forensic experts due to limitations such as the presence of facial expressions. The aims of this study were to analyze how morphometric changes in the face during a spontaneous smile influence the facial image comparison process and to evaluate the reproducibility of measurements obtained by digital stereophotogrammetry in these situations. Materials and Methods: Three examiners used digital stereophotogrammetry to obtain 3-dimensional images of the faces of 10 female participants(aged between 23 and 45 years). Photographs of the participants' faces were captured with their faces at rest (group 1) and with a spontaneous smile (group 2), resulting in a total of 60 3-dimensional images. The digital stereophotogrammetry device obtained the images with a 3.5-ms capture time, which prevented undesirable movements of the participants. Linear measurements between facial landmarks were made, in units of millimeters, and the data were subjected to multivariate and univariate statistical analyses using Pirouette^® version 4.5 (InfoMetrix Inc., Woodinville, WA, USA) and Microsoft Excel^® (Microsoft Corp., Redmond, WA, USA), respectively. Results: The measurements that most strongly influenced the separation of the groups were related to the labial/buccal region. In general, the data showed low standard deviations, which differed by less than 10% from the measured mean values, demonstrating that the digital stereophotogrammetry technique was reproducible. Conclusion: The impact of spontaneous smiles on the facial image comparison process should be considered, and digital stereophotogrammetry provided good reproducibility.

• Journal of Genetic Medicine
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• v.15 no.2
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• pp.102-106
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• 2018

Aggrecan is a proteoglycan in the extracellular matrix of growth plate and cartilaginous tissues. Aggrecanopathy has been reported as a genetic cause not only for severe skeletal dysplasia but also for autosomal dominant short stature with normal to advanced bone age. We report a novel heterozygous mutation of ACAN in a Korean family with proportionate short stature identified through targeted exome sequencing. We present a girl of 4 years and 9 months with a family history of short stature over three generations. The paternal grandmother is 143 cm tall (-3.8 as a Korean standard deviation score [SDS]), the father 155 cm (-3.4 SDS), and the index case 96.2 cm (-2.9 SDS). Evaluation for short stature showed normal growth hormone (GH) peaks in the GH provocation test and a mild delayed bone age for chronological age. This subject had clinical characteristics including a triangular face, flat nasal bridge, prognathia, blue sclerae, and brittle teeth. The targeted exome sequencing was applied to detect autosomal dominant growth palate disorder. The novel variant c.910G>A (p.Asp304Asn) in ACAN was identified and this variant was found in the subject's father using Sanger sequencing. This is the first case of Korean familial short stature due to ACAN mutation. ACAN should be considered for proportionate idiopathic short stature, especially in cases of familial short stature.

• Journal of Convergence for Information Technology
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• v.9 no.7
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• pp.100-105
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• 2019

As IoT Technology develops and Era of Hyperconnectivity comes, various kinds of customized services became available. As a next-generation display, a smart mirror accesses multimedia devices and provides various services, so it can serve as a social learning tool for the children and the old ones, as well as adults who need information. Smart Mirror must be able to identify users for individualized services. However, since the Smart Mirror is an easily accessible device, there is a possibility that information such as an individual's pattern and habit stored in the smart mirror may be exposed to the outside. Also, the other possibility of leakage of personal location information is through personal schedule or appointment stored in the smart mirror, and another possibility that privacy can be violated is through checking the health state via personal photographs. In this research, we propose a system that identify users by the information the users registered about their physique just like their face, one that provides individually customized service to users after identifying them, and one which provides minimal information and service for unauthenticated users.

• Journal of Oral Medicine and Pain
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• v.45 no.4
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• pp.97-109
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• 2020

Purpose: Cervicogenic headache (CGH) is pain referred to the head/ face from the structures in vicinity of upper cervical spinal nerves via trigeminocervical pathway. Ponticulus Posticus (PP) and Elongated Styloid Process (ESP) are anatomical structures that cause compression of vasculature present around upper cervical nerve plexus. Recently, computational fluid dynamics (CFD) has shown to play an essential role in identification of these high-pressure zones in the brain. The aim of this research is to study the association of ESP and PP in patients with CGH and to develop a hypothesis by CFD to analyse vertebrobasilar insufficiency as a contributing factor in occurrence of CGH. Methods: Retrospective analysis of 4500 full skull CBCT scans was done for the presence of partial or complete PP and length of Styloid Process (SP). Research was divided into two phases; In first Preliminary Phase, 150 scans that showed the presence of PP and ESP were analysed, and only 134 patients gave consent to fill the questionnaire containing 96 question items pertaining to symptoms associated with CGH. In the second phase, simulation of Vertebral and Carotid Artery was done using Fluent 14.5 Software and by CFD, pressure distribution on arteries was obtained that helped to identify high pressure regions. Results: Both PP and ESP showed a statistically significant association with CGH (p<0.001). By CFD analysis, both steady and transient phases of simulation showed drop in pressure due to constriction of internal carotid and vertebral artery by ESP and PP respectively and were found to decrease the volume of blood reaching the brain, 0.12 /0.13 mL and 0.06 mL respectively. Conclusions: Our analysis proves ESP and PP as contributing factors towards CGH. Hence for proper diagnosis and management of headache disorders, clinicians should have adequate knowledge about these anatomical structures and their resulting clinical symptoms.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.77-90
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• 2023

Today, crops face many characteristics/diseases. Insect damage is one of the main characteristics/diseases. Insecticides are not always effective because they can be toxic to some birds. It will also disrupt the natural food chain for animals. A common practice of plant scientists is to visually assess plant damage (leaves, stems) due to disease based on the percentage of disease. Plants suffer from various diseases at any stage of their development. For farmers and agricultural professionals, disease management is a critical issue that requires immediate attention. It requires urgent diagnosis and preventive measures to maintain quality and minimize losses. Many researchers have provided plant disease detection techniques to support rapid disease diagnosis. In this review paper, we mainly focus on artificial intelligence (AI) technology, image processing technology (IP), deep learning technology (DL), vector machine (SVM) technology, the network Convergent neuronal (CNN) content Detailed description of the identification of different types of diseases in tomato and potato plants based on image retrieval technology (CBIR). It also includes the various types of diseases that typically exist in tomato and potato. Content-based Image Retrieval (CBIR) technologies should be used as a supplementary tool to enhance search accuracy by encouraging you to access collections of extra knowledge so that it can be useful. CBIR systems mainly use colour, form, and texture as core features, such that they work on the first level of the lowest level. This is the most sophisticated methods used to diagnose diseases of tomato plants.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.154-160
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• 1996

The control of diamond turning is usually achieved through a laser-interferometer feedback of slide position. The limitation of this control scheme is that the feedback signal does not account for additional dynamics of the tool post and the material removal process. If the tool post is rigid and the material removal process is relatively static, then such a non-collocated position feedback control scheme may surfice. However, as the accuracy requirement gets tighter and desired surface cnotours become more complex, the need for a direct tool-tip sensing becomes inevitable. The physical constraints of the machining process prohibit any reasonable implementation of a tool-tip motion measurement. It is proposed that the measured force normal to the face of the workpiece can be filtered through an appropriate admittance transfer function to result in the estimated dapth of cut. This can be compared to the desired depth of cut to generate the adjustment control action in additn to position feedback control. In this work, the design methodology on the admittance model-based control with a conventional controller is presented. The recursive least-squares algorithm with forgetting factor is proposed to identify the parameters and update the cutting process in real time. The normal cutting forces are measured to identify the cutting dynamics in the real diamond turning process using the precision dynamoneter. Based on the parameter estimation of cutting dynamics and the admitance model-based nanodynamic control scheme, simulation results are shown.