• 대한안전경영과학회지
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• 제4권2호
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• pp.11-22
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• 2002

In this study, an asymmetric lifting posture prediction model was developed, which was a three-dimensional model with 12 links and 23 degrees of freedom open kinematic chains. Although previous researchers have proposed biomechanical, psychophysical, or physiological measures as cost functions, for solving redundancy, they lack in accuracy in predicting actual lifting postures and most of them are confined to the two-dimensional model. To develop an asymmetric lifting posture prediction model, we used the resolved motion method for accurately simulating the lifting motion in a reasonable time. Furthermore, in solving the redundant problem of the human posture prediction, a moment weighted Joint Range Availability (JRA) was used as a cost function in order to consider dynamic lifting. However, it is known that the moment weighted JRA as a cost function predicted the lower extremity and L5/S1 joint motions better than the upper extremities, while the constant weighted JRA as a cost function predicted the latter better than the former. To compensate for this, we proposed a hybrid moment weighted JRA as a new cost function with moment weighted for only the lower extremity. In order to validate the proposed cost function, the predicted and real lifting postures for various lifting conditions were compared by using the root mean square(RMS) error. This hybrid JRA reduced RMS more than the previous cost functions. Therefore, it is concluded that the cost function of a hybrid moment weighted JRA can be used to predict three-dimensional lifting postures. To compare with the predicted trajectories and the real lifting movements, graphical validations were performed. The results also showed that the hybrid moment weighted cost function model was found to have generated the postures more similar to the real movements.

• 전기의세계
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• 제26권1호
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• pp.87-90
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• 1977

Various simulation techniques were developed in the modeling of biological system during the last decades. Mostly analog and hybrid simulation techniques have been used. The authors chose the Digital Analog Simulation (DAS) technique by using the MIMIC language to simulate the saccadic eye movement system performances on the digital computer. There have been various models presented by many investigators after Young & Stark's sampled-data model. The eye movement model chosen by the authors is Robinson's model III which shows the parallel information processing characteristics clearly to the double-step input stimuli. In the process of simulation, the parameter and constants used were based on the neurophysiological data of the human and animals. The analog model blocks were converted to the corresponding MIMIC block diagrams and programmed into the MIMIC statements. The program was run on the CDC Cyber 72-14 computer. The essential input stimulus was double-step of 5 and 10 degrees, and target durations chosen were 50,100 and 150 msec. The results obtained by the DAS technqiue were in good agreement with analog simulation carried out by other investigators as well as with the experimental human saccadic eye movement responses to double-step target movements.

• 로봇학회논문지
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• 제2권2호
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• pp.119-128
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• 2007

Emotion interaction between human and robot is an important element for natural interaction especially for service robot. We propose a hybrid emotion generation architecture and detailed design of reactive process in the architecture based on insight about human emotion system. Reactive emotion generation is to increase task performance and believability of the service robot. Experiment result shows that it seems possible for the reactive process to function for those purposes, and reciprocal interaction between different layers is important for proper functioning of robot's emotion generation system.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.957-958
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• 2008

The human facial appearances vary globally and locally according to identity, pose, illumination, and expression variations. In this paper, we propose a hybrid-nonsmooth nonnegative matrix factorization (hybrid-nsNMF) based appearance model to represent various facial appearances which vary globally and locally. Instead of using single smooth matrix in nsNMF, we used two different smooth matrixes and combine them to extract global and local basis at the same time.

• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.651-657
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• 1998

In this study, an intelligent scheduling with hybrid architecture, which integrates expert system and neural network, is proposed. Neural network is trained with the data acquired from simulation model of FMC to obtain the knowledge about the relationship between the state of the FMC and its best dispatching rule. Expert system controls the scheduling of FMC by integrating the output of neural network, the states of FMS, and user input. By applying the hybrid system to a scheduling problem, the human knowledge on scheduling and the generation of non-logical knowledge by machine teaming, can be processed in one scheduler. The computer simulation shows that comparing with MST(Minimum Slack Time), there is a little increment in tardness, 5% growth in flow time. And at breakdown, tardness is not increased by expert system comparing with EDD(Earliest Due Date).

• Genomics & Informatics
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• 제9권4호
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• pp.194-196
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• 2011

Promoter prediction is a very important problem and is closely related to the main problems of bioinformatics such as the construction of gene regulatory networks and gene function annotation. In this context, we developed an integrated promoter prediction program using hybrid methods, PromoterWizard, which can be employed to detect the core promoter region and the transcription start site (TSS) in vertebrate genomic DNA sequences, an issue of obvious importance for genome annotation efforts. PromoterWizard consists of three main modules and two auxiliary modules. The three main modules include CDRM (Composite Dependency Reflecting Model) module, SVM (Support Vector Machine) module, and ICM (Interpolated Context Model) module. The two auxiliary modules are CpG Island Detector and GCPlot that may contribute to improving the predictive accuracy of the three main modules and facilitating human curator to decide on the final annotation.

• Journal of Multimedia Information System
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• 제6권2호
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• pp.87-90
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• 2019

Machine learning techniques have been applied in almost all the domains of human life to aid and enhance the problem solving capabilities of the system. The field of medical science has improved to a greater extent with the advent and application of these techniques. Efficient expert systems using various soft computing techniques like artificial neural network, Fuzzy Logic, Genetic algorithm, Hybrid system, etc. are being developed to equip medical practitioner with better and effective diagnosing capabilities. In this paper, a comparative study to evaluate the predictive performance of subtractive clustering based ANFIS hybrid system (SCANFIS) with Fuzzy C-Means (FCM) based ANFIS system (FCMANFIS) for Alzheimer disease (AD) has been taken. To evaluate the performance of these two systems, three parameters i.e. root mean square error (RMSE), prediction accuracy and precision are implemented. Experimental results demonstrated that the FCMANFIS model produce better results when compared to SCANFIS model in predictive analysis of Alzheimer disease (AD).

• BMB Reports
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• 제29권6호
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• pp.545-548
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• 1996

CA(1-8)ME(1-12), the CA-ME hybrid peptide of the amino terminal segments of cecropin A (CA) and melittin (ME), has been reported to have a broad spectrum and improved potency without a hemolytic property. In order to obtain new synthetic peptides with powerful antibacterial activity without hemolytic activity, several hybrid peptides were designed from the sequences of CA, ME, magainin 2, bombinin and lactoferricin. All hybrid peptides were constructed to form an amphipathically basic-flexible-hydrophobic structure and synthesized by the solid phase method. Their hemolytic activities against human red blood cells and antibacterial activities against both Gram-positive and Gram-negative bacteria were detennined. CA(1-8)MA(1-12), CA(1-8)BO(1-12), MA(10-17)ME(1-12) and LF(20-29)ME(1-12) showed comparable activities with broad spectra against both Gram-positive and Gram-negative bacteria relative to CA(1-8)ME(1-12) but without hemolytic properties. These hybrid peptides, therefore, could be useful as model peptides to design a novel peptide with improved antibacterial activity and study on structure-activity relationships of antimicrobial peptides.

• Structural Engineering and Mechanics
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• 제31권4호
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• pp.439-451
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• 2009

The paper deals with the problem related to the modelling of riveted assemblies for crashworthiness analysis of full-scale complete aircraft structures. Comparisons between experiments and standard FE computations on high-energy accidental situations onto aluminium riveted panels show that macroscopic plastic strains are not sufficiently localised in the FE shells connected to rivet elements. The main reason is related to the structural embrittlement caused by holes, which are currently not modelled. Consequently, standard displacement FE models do not succeed in initialising and propagating the rupture in sheet metal plates and along rivet rows as observed in the experiments. However, the literature survey show that it is possible to formulate super-elements featuring defects that both give accurate singular strain fields and are compatible with standard displacement finite elements. These super-elements can be related to the displacement model of the hybrid-Trefftz principle of the finite element method, which is a kind of domain decomposition method. A feature of hybrid-Trefftz finite elements is that they are mainly used for elastic computations. It is thus proposed to investigate the possibility of formulating a hybrid displacement finite element, including the effects of a hole, dedicated to crashworthiness analysis of full-scale aeronautic structures.

• Journal of Magnetics
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• 제21권3호
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• pp.442-449
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• 2016

In this paper, an effective numerical analysis method is proposed for calculating dosimetry of the wireless power transfer system operating low-frequency ranges. The finite-difference time-domain (FDTD) method is widely used to analyze bio-electromagnetic field problems, which require high resolution, such as a heterogeneous whole-body voxel human model. However, applying the standard method in the low-frequency band incurs an inordinate number of time steps. We overcome this problem by proposing a modified finite-difference time-domain method which utilizes a quasi-static approximation with the surface equivalence theorem. The analysis results of the simple model by using proposed method are in good agreement with those from a commercial electromagnetic simulator. A simulation of the induced electric fields in a human head voxel model exposed to a wireless power transmission system provides a realistic example of an application of the proposed method. The simulation results of the realistic human model with the proposed method are verified by comparing it with the conventional FDTD method.