• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.980-984
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• 1990

In order to find the optimal control law for the precise trajectory tracking of a robot manipulator, a perturbational control method is proposed based on a linearized manipulator dynamic model which can be obtained in a very compact and computationally efficient manner using the dual number algebra. Manipulator control can be decomposed into two parts: the nominal control and the corrective perturbational control. The nominal control is precomputed from the inverse dynamic model using the quantities of a desired trajectory. The perturbational control is obtained by applying the second-variational method on the linearized dynamic model. Simulation results for a PUMA-560 robot show that, by using this controller, the desired trajectory tracking performance of the robot can be achieved, even in the presence of large initial positional disturbances.

• International Journal of Contents
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• v.6 no.3
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• pp.19-24
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• 2010

Task scheduling is an integrated component of computing with the emergence of grid computing. In this paper, we address two different task scheduling models, which are static Round-Robin (RR) and dynamic Fastest Site First (FSF) task scheduling method, using extended timed marked graphs, which is a special case of Stochastic Petri Nets (SPN). Stochastic reward nets (SRN) is an extension of SPN and provides compact modeling facilities for system analysis. We build hierarchical SRN models to compare two task scheduling methods. The upper level model simulates task scheduling and the lower level model implements task serving process for different sites with multiple servers. We compare these two models and analyze their performances by giving reward measures in SRN.

• Proceedings of the Membrane Society of Korea Conference
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• 2003.07a
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• pp.77-80
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• 2003

Hydrocarbon-hydrocarbon separations are one of the most important processes in petroleum refining. Distillation process has been used for separating hydrocarbons, but this conventional process is very energy consuming. Pervaporation separation through polymeric membranes is an emerging process alternative to distillation because of energy savings, compact system installation, reduced capital investment, and other performance attributes. In hydrocarbon separations, polymeric membranes are easily swollen by hydrocarbons and can lose mechanical strength. Chemically robust membranes are needed for the separation of hydrocarbons. In this study, the blend membrane was applied to separate benzene and cyclohexane. This is a model system for aliphatic and aromatic separation. Cyclohexane is also physically very similar to benzene and as a result of the very closing boiling points (0.6$^{\circ}C$), benzene and cyclohexane form an azetrope. Thus the system provides a good model for azeotrope breaking by pervaporation. The semi-quantitative thermodynamic model predicts that the calculated selectivity increases with increasing Hydrin contents in the blend membranes. Pervaporation experiments utilizing various operating temperatures and feed concentrations with different blend membranes are compared with the result from semi-quantitative thermodynamic calculations.

• Electronics and Telecommunications Trends
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• v.34 no.2
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• pp.40-50
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• 2019

Considerable accuracy improvements in deep learning have recently been achieved in many applications that require large amounts of computation and expensive memory. However, recent advanced techniques for compacting and accelerating the deep learning model have been developed for deployment in lightweight devices with constrained resources. Lightweight deep learning techniques can be categorized into two schemes: lightweight deep learning algorithms (model simplification and efficient convolutional filters) in nature and transferring models into compact/small ones (model compression and knowledge distillation). In this report, we briefly summarize various lightweight deep learning techniques and possible research directions.

• Bulletin of the Korean Mathematical Society
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• v.59 no.6
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• pp.1439-1470
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• 2022

In this paper, we study the uniform attractor of the 2D nonautonomous tropical climate model in an arbitrary unbounded domain on which the Poincaré inequality holds. We prove that the uniform attractor is compact not only in the L²-spaces but also in the H¹-spaces. Our proof is based on the concept of asymptotical compactness. Finally, for the quasiperiodical external force case, the dimension estimates of such a uniform attractor are also obtained.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.136-141
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• 2023

The continuous shrinking of transistors in integrated circuits leads to difficulties in improving performance, resulting in the emerging transistors such as nanosheet field-effect transistors. In this paper, we propose a TCAD-machine learning framework of nanosheet FETs to model the current-voltage characteristics. Sentaurus TCAD simulations of nanosheet FETs are performed to obtain a large amount of device data. A machine learning model of I-V characteristics is trained using the multi-layer perceptron from these TCAD data. The weights and biases obtained from multi-layer perceptron are implemented in a PSPICE netlist to verify the accuracy of I-V and the DC transfer characteristics of a CMOS inverter. It is found that the proposed machine learning model is applicable to the prediction of nanosheet field-effect transistors device and circuit performance.

• Korean Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.1-19
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• 1996

Non-manifold topological representations can provide a single unified representation for mixed dimensional models or cellular models and thus have a great potential to be applied in many application areas. Various boundary representations for non-manifold topology have been proposed in recent years. These representations are mainly interested in describing the sufficient adjacency relationships and too redundant as a result. A model stored in these representations occupies too much storage space and is hard to be manipulated. In this paper, we proposed a compact hierarchical non-manifold boundary representation that is extended from the half-edge data structure for solid models by introducing the partial topological entities to represent some non-manifold conditions around a vertex, edge or face. This representation allows to reduce the redundancy of the existing schemes while full topological adjacencies are still derived without the loss of efficiency. To verify the statement above, the storage size requirement of the representation is compared with other existing representations and present some main procedures for querying and traversing the representation. We have also implemented a set of the generalized Euler operators that satisfy the Euler-Poincare formula for non-manifold geometric models.

• Journal of Sensor Science and Technology
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• v.15 no.5
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• pp.334-340
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• 2006

A compact biosignal monitoring device was developed. Electrodes for electrocardiogram (ECG) and a LED and silicon detector for photoplethysmogram (PPG) were used. A lead II type was arranged for ECG measurement and reflected light was measured at the finger tip for PPG. A single chip microprocessor (model ADuC812, Analog Device) controlled a measurement protocol and processed measured signals. PPG and ECG had a sampling rate of 300 Hz with 8-bit resolution. The maximum power consumption was 100 mW. The microprocessor computed pulse transit time (PTT) between the R-wave of ECG and the peak of PPG. To increase the resolution of PTT, analog peak detectors obtained the peaks of ECG and PPG whose interval was calculated using an internal clock cycle of 921.6 kHz. The device was designed to be operated by 3-volt battery. Biosignals can be measured for $2{\sim}3$ days continuously without the external interruptions and data is stored to an on-board memory. Our system was successfully tested with human subjects.

• Geomechanics and Engineering
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• v.10 no.1
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• pp.109-124
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• 2016

In this paper, process of dynamic powder compaction is investigated experimentally using impact of drop hammer and die tube. A series of test is performed using aluminum powder with different grain size. The energy of compaction of powder is determined by measuring height of hammer and the results presented in term of compact density and rupture stress. This paper also presents a mathematical modeling using experimental data and neural network. The purpose of this modeling is to display how the variations of the significant parameters changes with the compact density and rupture stress. The closed-form obtained model shows very good agreement with experimental results and it provides a way of studying and understanding the mechanics of dynamic powder compaction process. In the considered energy level (from 733 to 3580 J), the relative density is varied from 63.89% to 87.41%, 63.93% to 91.52%, 64.15% to 95.11% for powder A, B and C respectively. Also, the maximum rupture stress are obtained for different types of powder and the results shown that the rupture stress increases with increasing energy level and grain size.

• Journal of Mechanical Science and Technology
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• v.17 no.9
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• pp.1268-1275
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• 2003

In this paper, a compact 3-DOF mobile microrobot with sub-micron resolution is presented. It has many outstanding features : it is as small as a coin ; its precision is of sub-micrometer resolution on the plane ; it has an unlimited travel range ; and it has simple and compact mechanisms and structures which can be realized at low cost. With the impact actuating mechanism, this system enable both fast coarse motion and highly precise fine motion with a pulse wave input voltage controlled. The 1 -DOF impact actuating mechanism is modeled by taking into consideration the friction between the piezoelectric actuator and base. This modeling technique is extended to simulate the motion of the 3-DOF mobile robot. In addition, experiments are conducted to verify that the simulations accurately represent the real system. The modeling and simulation results will be used to design the model-based controller for the target system. The developed system can be used as a robotic positioning device in the micromanipulation system that determines the position of micro-sized components or particles in a small space, or assemble them in the meso-scale structure.