• The korean journal of orthodontics
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• v.34 no.6 s.107
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• pp.473-480
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• 2004

The aim of this study was to establish normative data on the tooth size and arch parameters of Koreans with normal occlusion, This study employed the dental casts of 296 (male: 179; female 117) normal occlusion samples, who were selected from 15,836 adults through a community dental health survey. The mesiodistal diameters of teeth, arch width, and arch length were measured by digital electronic calipers(accurate to 0.01 mm) and Bolton's indices as well as intermaxillary arch width ratios were calculated. In order to ensure reliability, intra- and inter-examiner error were evaluated. Although our dimensional data showed overt differences between genders, the indices and intermaxillary ratios evaluated were the same. The resultant data obtained were compared with the previous data to reveal whether any changes have occurred over the time. The clinical implication of the present findings was also discussed. This biometric study seemed to provide a clinically applicable diagnostic criteria for an individual malocclusion patient.

• The korean journal of orthodontics
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• v.35 no.5 s.112
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• pp.331-340
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• 2005

Angulation and inclination of clinical crown is important for diagnosing, treatment planning and developing convenient orthodontic attachments. The aim of the study was to establish normative data with higher reliability on the angulation and inclination of clinical crown of Koreans with normal occlusion This study employed the dental casts of 307 (male. 187: female. 120) adult normal occlusion samples. The angulation and inclination of clinical crown were measured by set-up model checker In order to ensure reliability, intra- and inter-rater error were evaluated 3 times The resultant data obtained had excellent reliability however when compared with the previous data as well as with gender difference, clinically significant interpretation was impossible because the whithin-dataset normal variation was High which was common pattern of angulation and inclination measuring data of previous research The result of this biometric study seemed 4o suggest more substantive design of the multivariate. high-dimensional interpretation methodology of these normal variation is required if more compatible orthodontic appliance could be developed.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.151-156
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• 2020

The purpose of this study is to design a process for developing wearable sports helmet devices by utilizing IoT server technology, focusing on sports where helmet wear is essential at sports sites. This enables customized training of athletes by continuously accumulating personal biometric information during training, checking players' condition based on data, and informing them of injury prevention and dangerous situations. In addition, the wearable device that can be useful when the training place is likely to damage the physical health due to heat waves or extremes can provide a foundation for improving the performance. Since such technology can be applied not only to the sports field but also to the society such as the industrial field or the underprivileged, it can be expected to be expandable.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.169-178
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• 2017

Recently, as the interest rate and necessity for security is growing, the demands for a visitor recognition system are being increased. In order to recognize a visitor in visitor recognition systems, the various biometric methods are used. In this paper, we propose a visitor recognition system based on face recognition. The visitor recognition system improves the face recognition performance by integrating several open APIs as a single algorithm and by performing the ensemble of the recognition results. For the performance evaluation, we collected the face data for about five months and measured the performance of the visitor recognition system. As the results of the performance measurement, the visitor recognition system shows a higher face recognition rate than using a single face recognition API, meeting the requirements on performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.77-80
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• 2011

Medical robot has four fields. Surgery assistant robot, robotic surgery, Surgery Simulator, rehabilitation robot. Thus, medical robots is often high precision and reliability requirements for operations are being developed. Medical service robot's another sector is care for service robots. Care services robot is the hospital's reception work and biometric data acquisition of patients, the hospital in location and content information provide to patients. But now medical service robot practical acceptance process failed to progress. In this paper were the medical service robot systems design and implementation. Implemented the robot system is using the standard protocols for the exchange of medical information and can be linked with hospital information system. The hospital's patient reception and processing, to provide care waiting number information.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.1-10
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• 2016

Information and network technology become the rapid development, so various online services supplied by multimedia systems are provided through the Internet. Because of intrinsic open characteristic on Internet, network systems need to provide the data protection and the secure authentication. So various researchers including Das, An, and Li&Hwang proposed the biometric-based user authentication scheme but they has some security weakness. To solve their problem, Li et al. proposed new scheme using fuzzy extraction, but it is weak on off-line password attack, authentication without biometrics, denial-of-service and insider attack. So, we proposed security enhanced user authentication scheme with key agreement to address the security problem of authentication schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.75-82
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• 2018

As user of mobile device increases, various user authentication methods are actively researched. The user authentication methods includes a method of using a user ID and a password, a method of using user biometric feature, a method of using location based, and a method of authenticating secondary authentication such as OTP(One Time Password) method is used. In this paper, we propose a user system which improves the problem of existing authentication method and encryption can proceed in a way that user desires. The proposed authentication system is composed of an authentication factor collection module that collects authentication factors using a mobile device, a security key generation module that generates a security key by combining the collected authentication factors, and a module that performs authentication using the generated security key module.

• The Journal of Bigdata
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• v.5 no.1
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• pp.139-145
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• 2020

In the era of the 4th Industrial Revolution, the use of information based on AI APIs has a great influence on industry and life. In particular, the use of artificial intelligence data in the medical field will have many changes and effects on society. This paper is to study the necessary components to implement the "Cognitive Health Advisor model (CHA model)" and to implement the "CHA model using chatbot" based on this. It uses the open Cognitive chatbot to analyze and analyze the health status of users changing in their daily lives. The user's health information analyzed by the biometric sensor and chatbot consultation delivers the information to the user through the chatbot. And it implements a cognitive health advisor model that provides educational information for users' health promotion. Through this implementation, it intends to confirm the possibility of future use and to suggest research directions.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.6-29
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• 2020

Biometrics identification using multiple modalities has attracted the attention of many researchers as it produces more robust and trustworthy results than single modality biometrics. In this paper, we present a novel multimodal recognition system that trains a deep learning network to automatically learn features after extracting multiple biometric modalities from a single data source, i.e., facial video clips. Utilizing different modalities, i.e., left ear, left profile face, frontal face, right profile face, and right ear, present in the facial video clips, we train supervised denoising auto-encoders to automatically extract robust and non-redundant features. The automatically learned features are then used to train modality specific sparse classifiers to perform the multimodal recognition. Moreover, the proposed technique has proven robust when some of the above modalities were missing during the testing. The proposed system has three main components that are responsible for detection, which consists of modality specific detectors to automatically detect images of different modalities present in facial video clips; feature selection, which uses supervised denoising sparse auto-encoders network to capture discriminative representations that are robust to the illumination and pose variations; and classification, which consists of a set of modality specific sparse representation classifiers for unimodal recognition, followed by score level fusion of the recognition results of the available modalities. Experiments conducted on the constrained facial video dataset (WVU) and the unconstrained facial video dataset (HONDA/UCSD), resulted in a 99.17% and 97.14% Rank-1 recognition rates, respectively. The multimodal recognition accuracy demonstrates the superiority and robustness of the proposed approach irrespective of the illumination, non-planar movement, and pose variations present in the video clips even in the situation of missing modalities.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.5
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• pp.1161-1170
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• 2016

In this paper, we provide an authentication technology for verifying dynamic signature made by finger on smart phone. In the proposed method, we are using the Auto-Encoder-based 1 class model in order to effectively distinguish skilled forgery signature. In addition to the basic dynamic signature characteristic information such as appearance and velocity of a signature, we use accelerometer value supported by most of the smartphone. Signed data is re-sampled to give the same length and is normalized to a constant size. We built a test set for evaluation and conducted experiment in three ways. As results of the experiment, the proposed acceleration sensor value and 1 class model shows 6.9% less EER than previous method.