• International journal of advanced smart convergence
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• v.1 no.1
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• pp.6-13
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• 2012

An improved algorithm for image quality assessment is presented. First a simple model of human visual system, consisting of a nonlinear function and a 2-D filter, processes the input images. This filter has one user-defined parameter, whose value depends on the reference image. This way the algorithm can adapt to different scenarios. In the next step the average value of locally computed correlation coefficients between the two processed images is found. This criterion is closely related to the way in which human observer assesses image quality. Finally, image quality measure is computed as the average value of locally computed correlation coefficients, adjusted by the average correlation coefficient between the reference and error images. By this approach the proposed measure differentiates between the random and signal dependant distortions, which have different effects on human observer. Performance of the proposed quality measure is illustrated by examples involving images with different types of degradation.

• Korean Journal of Computational Design and Engineering
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• v.18 no.4
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• pp.275-282
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• 2013

This paper proposes a method for human identification using teeth contours extracted from dental images that are captured from the frontal views of subjects each of who opens his or her mouth slightly. Each dental image has a black-colored region containing the subject's teeth contours which are usually different from subject to subject. This means that this black-colored region has bio-mimetic information useful for human identification. The basic idea of the method is to extract the upper and lower teeth contours from the dental image of each subject and to encode their geometric patterns using a back-propagation neural network model. After acquiring 400 teeth images form 10 university students, we used 300 images for the training data of the neural network model and 100 images for its verification. Experimental results have shown that the proposed neural network-based method can be used as an alternative solution for identification among a small group of humans with a low cost and simple setup.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.124-129
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• 1992

The goal of the proposed Intelligent Assisting System - IAS is to assist human operators in an intelligent way, while leaving decision and goal planning instances for the human. To realize the IAS the very important issue of manipulation skill identification and analysis has to be solved, which then is stored in a Skill Data Base. Using this data base the IAS is able to perform complex manipulations on the motion control level and to assist the human operator flexibly. We propose a model for manipulation skill based on the dynamics of the grip transformation matrix, which describes the dynamic transformation between object space and finger joint space. Interaction with a virtual world simulator allows the calculation and feedback of appropriate forces through controlled actuators of the sensor glove with 10 degrees-of-freedom. To solve the sensor glove calibration problem, we learn the nonlinear calibration mapping by an artificial neural network(ANN). In this paper we also describe the experimental system setup of the skill acquisition and transfer system as a first approach to the IAS. Some simple manipulation examples and simulation results show the feasibility of the proposed manipulation skill model.

• Journal of the Ergonomics Society of Korea
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• v.30 no.6
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• pp.715-725
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• 2011

Objective: This study is aimed at developing Articulated Human Models(AHM) using superquadrics to improve the geometric accuracy of the body shape. Background: The previous work presents the AHM with geometrical simplification such as ellipsoids to improve analysis efficiency. However, because of the simplicity, their physical properties such as a center of mass and moment of inertia are computed with errors compared to their actual values. Method: This paper introduces a three steps method to present the AHM with superquadrics. First, a 3D whole body scan data are divided into 17 body segments according to body joints. Second, superquadric fitting is employed to minimize the Euclidean distance between body segments and superquadrics. Finally, Fee-Form Deformation is used to improve accuracy over superquadric fitting. Results: Our computational experiment shows that the superquadric models give better accuracy of dynamic analysis than that of ellipsoid ones. Conclusion: We generate the AHM composed of 17 superquadrics and 16 joints using superquadric fitting. Application: The AHM using superquadrics can be used as the base model for dynamics and ergonomics applications with better accuracy because it presents the human motion effectively.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.91-98
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• 2023

Human-object interaction(HOI) detection requires both object detection and interaction recognition, and requires a large amount of data to learn a detection model. Current opened dataset is insufficient in scale for training model enough. In this paper, we propose an easy and effective data augmentation method called Simple Quattro Augmentation(SQA) and Random Quattro Augmentation(RQA) for human-object interaction detection. We show that our proposed method can be easily integrated into State-of-the-Art HOI detection models with HICO-DET dataset.

• Journal of Industrial and Engineering Chemistry
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• v.68
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• pp.220-228
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• 2018

In this study, we found a simple surface biofunctionalization of biphasic calcium phosphate (BCP) based on the high affinity between alendronate and the calcium ions of BCP, and the strong interaction between heparin and bone morphogenic protein-2 (BMP-2). The biofunctionalized BCP did not be precipitated well and display a remarkable enhancement of osteogenic activity of human adipose-derived stem cells by showing increased alkaline phosphatase (ALP), calcium deposition and osteogenic-related genes (i.e., Runx-2, ALP, osteocalcin, and osteopontin), and bone regeneration in the calvarial defect model. Therefore, this simple surface technique can be used to easily functionalize various calcium phosphates.

• Journal of the Korea Computer Graphics Society
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• v.4 no.1
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• pp.21-29
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• 1998

This paper deals with character animation using motion capture. The captured motion requires the editing process to smooth the jerky motion by the sensor noise, or to combine several clip-motion libraries. For this purpose, we describe a simple technique for editing the captured motion using the Kalman filter technique. Our formulation allows the generated motion to satisfy the kinematic constraints of the human model. Furthermore, it provides us with a multi-level control mechanism of the motion resolution by changing the uncertainty of the measurement model and the seamless motion transition.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.5
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• pp.62-67
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• 2007

A simple dimension measuring method for the measurement of human bust has been developed using projection moire. The 3-D data of a human bust was calculated from the 2dimensional image information obtained by the stripe using projection moire. The creation of 3-D geometric shape by digitizing real objects has been widely investigated in reverse engineering(RE). This procedure generally consists of three basic steps: data capture, data alignment and model reconstruction. In order to achieve a complete model, multiple scans must be taken and aligned.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.15-23
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• 2016

Polycyclic aromatic hydrocarbons (PAHs) are primarily formed as a result of thermal treatment of food, especially barbecuing or grilling. Contamination by PAHs is due to generation by direct pyrolysis of food nutrients and deposition from smoke produced through incomplete combustion of thermal agents. PAHs are ubiquitous compounds, well-known to be carcinogenic, which can reach the food in different ways. As an important human exposure pathway of contaminants, dietary intake of PAHs is of increasing concern for assessing cancer risk in the human body. In addition, the risks associated with consumption of barbecued meat may increase if consumers use cooking practices that enhance the concentrations of contaminants and their bioaccessibility. Since total PAHs always overestimate the actual amount that is available for absorption by the body, bioaccessibility of PAHs is to be preferred. Bioaccessibility of PAHs in food is the fraction of PAHs mobilized from food matrices during gastrointestinal digestion. An in vitro human digestion model was chosen for assessing the bioaccessibility of PAHs in food as it offers a simple, rapid, low cost alternative to human and animal studies; providing insights which may not be achievable in in vivo studies. Thus, this review aimed not only to provide an overview of general aspects of PAHs such as the formation, carcinogenicity, sources, occurrence, and factors affecting PAH concentrations, but also to enhance understanding of bioaccessibility assessment using an in vitro digestion model.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.532-541
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• 2018

Decision support systems are a key focus of research on developing control rooms to aid operators in making reliable decisions and reducing incidents caused by human errors. For this purpose, models of complex systems can be developed to diagnose causes or consequences for specific alarms. Models applied in safety systems of complex and safety-critical systems require rigorous and reliable model building and testing. Multilevel flow modeling is a qualitative and discrete method for diagnosing faults and has previously only been validated by subjective and qualitative means. To ensure reliability during operation, this work aims to synthesize a procedure to measure model performance according to diagnostic requirements. A simple procedure is proposed for validating and evaluating the concept of multilevel flow modeling. For this purpose, expert statements, dynamic process simulations, and pilot plant experiments are used for validation of simple multilevel flow modeling models of a hydrocyclone unit for oil removal from produced water.