• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.491-498
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• 2019

Digital twin is a technology that virtualizes physical objects of the real world on a computer. It is used by collecting sensor data through IoT, and using the collected data to connect physical objects and virtual objects in both directions. It has an advantage of minimizing risk by tuning an operation of virtual model through simulation and responding to varying environment by exploiting experiments in advance. Recently, artificial intelligence and machine learning technologies have been attracting attention, so that tendency to virtualize a behavior of physical objects, observe virtual models, and apply various scenarios is increasing. In particular, recognition of each robot's motion is needed to build digital twin for co-robot which is a heart of industry 4.0 factory automation. Compared with modeling based research for recognizing motion of co-robot, there are few attempts to predict motion based on sensor data. Therefore, in this paper, an experimental environment for collecting current and inertia data in co-robot to detect the motion of the robot is built, and a motion prediction model based on the collected sensor data is proposed. The proposed method classifies the co-robot's motion commands into 9 types based on joint position and uses current and inertial sensor values to predict them by accumulated learning. The data used for accumulating learning is the sensor values that are collected when the co-robot operates with margin in input parameters of the motion commands. Through this, the model is constructed to predict not only the nine movements along the same path but also the movements along the similar path. As a result of learning using SVM, the accuracy, precision, and recall factors of the model were evaluated as 97% on average.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.999-1004
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• 2005

An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.

• The Journal of the Acoustical Society of Korea
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• v.14 no.2
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• pp.101-112
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• 1995

In order to construct a feature map-based phoneme classification system for speech recognition, two procedures are usually required. One is clustering and the other is labeling. In this paper, we present a phoneme classification system based on the Kohonen's Self-Organizing Feature Map (SOFM) for clusterer and labeler. It is known that the SOFM performs self-organizing process by which optimal local topographical mapping of the signal space and yields a reasonably high accuracy in recognition tasks. Consequently, SOFM can effectively be applied to the recognition of phonemes. Besides to improve the performance of the phoneme classification system, we propose the learning algorithm combined with the classical K-mans clustering algorithm in fine-tuning stage. In order to evaluate the performance of the proposed phoneme classification algorithm, we first use totaly 43 phonemes which construct six intra-class feature maps for six different phoneme classes. From the speaker-dependent phoneme classification tests using these six feature maps, we obtain recognition rate of $87.2\%$ and confirm that the proposed algorithm is an efficient method for improvement of recognition performance and convergence speed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.4
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• pp.582-593
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• 1999

This paper presents the design and fabrication of the diplexer for a KOREASAT-III Ka-band satellite transponder. The transmission characteristics of the diplexer is analyzed by calculating the generalized scattering matrix using mode matching method. It is composed of 2 bandpass filters, coupled with H-plane T-junction having symmetrical inductive iris and E-plane metal insert structures. Compared with the size and weight of the Rx and Tx filter loaded with a transponders respectively, those of the diplexer can be effectively reduced. In a high power transmission, the variation of the filter characteristics is minimized by the scheme that irises are extended to the exterior of H-plane of the waveguide. This scheme needs no extra heat sinks for dissipating high power. The diplexer is designed to improve the simplification, durability and reliability by eliminating tuning screws, which have been used to compensate for the characteristics of fabricated filters. The bandpass filters of the diplexer show the insertion loss of less than 1.2 dB and the return loss in excess of 15 dB. The isolations of more than 65 dB have been achieved between Rx and Tx filter.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.1
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• pp.18-24
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• 2006

Reactor core and internal structures of a liquid metal reactor (LMR) can not be visually examined due to an opaque liquid sodium. The under-sodium viewing technique by using an ultrasonic wave should be applied far the visual inspection of reactor internals. In this study, an ultrasonic waveguide sensor with a strip plate has been developed for an application to the under-sodium viewing technique. The Lamb wave propagation of a waveguide sensor has been analyzed and the zero-order antisymmetric $A_0$ plate wave was selected as the application mode of the sensor. The $A_0$ plate wave can be propagated in the dispersive low frequency range by using a liquid wedge clamped to the waveguide. A new technique is presented which is capable of steering the radiation beam angle of a waveguide sensor without a mechanical movement of the sensor assembly The steering function of the ultrasonic radiation beam can be achieved by a frequency tuning method of the excitation pulse in the dispersive range of the $A_0$ mode. The technique provides an opportunity to overcome the scanning limitation of a waveguide sensor. The beam steering function has been evaluated by an experimental verification. The ultrasonic C-scanning experiments are performed in water and the feasibility of the ultrasonic waveguide sensor has been verified.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.8-15
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• 2020

A forecasting method using deep learning does not have consistent results due to the differences in the characteristics of the dataset, even though they have the same forecasting models and parameters. For example, the forecasting model X optimized with dataset A would not produce the optimized result with another dataset B. The forecasting model with the characteristics of the dataset needs to be optimized to increase the accuracy of the forecasting model. Therefore, this paper proposes novel optimization steps for outlier removal, dataset classification, and a CNN-LSTM-based hyperparameter tuning process to forecast the daily power usage of a university campus based on the hourly interval. The proposing model produces high forecasting accuracy with a 2% of MAPE with a single power input variable. The proposing model can be used in EMS to suggest improved strategies to users and consequently to improve the power efficiency.

• Journal of Drive and Control
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• v.12 no.4
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• pp.60-70
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• 2015

A front-end loader (FEL) mounted on an agricultural tractor is one of the most commonly used implements for farm work. However, when the tractor carries material using the bucket attached to the FEL on a sloping ground, the materials can spill or roll back over the operator due to the tilted body, thereby requiring the bucket surface to remain level at a constant value regardless of varying slopes. In this study, an active system for controlling the angle of the FEL bucket on a tractor based on the real-time measurement of ground slopes was developed to enable the bucket to constantly remain level. A FEL simulator operated based on an electro hydraulic proportional valve (EHPV) was constructed in the laboratory to develop a proportional-integral-derivative (PID) controller forming a virtual electronic control unit (ECU) on the computer, which could automatically adjust the bucket angles depending on varying input angles while sending SAE-J1939 associated messages via CAN BUS to the EHPV. The different parameter values for the PID controller due to the gravity effect of the bucket were determined using a manual PID tuning method while assuming that the tractor travels on either an ascending slope or a descending slope. The developed PID control-based self-leveling system showed a mean of steady-state errors of within $1^{\circ}$ and a mean of delayed times of ~ 0.8s when the step input of $+20^{\circ}$ was given, implying that the developed system and control algorithm would be effective in maintaining the bucket angle at a certain value. Future studies include the improvement of the control algorithm to reduce such a time delay as well as the application of the developed algorithm to the FEL mounted on a tractor tested at a testing ground.

• Korean Journal of Optics and Photonics
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• v.15 no.5
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• pp.455-460
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• 2004

We have developed a mode-locked ultra-short pulse C $r^{4+}$:YAG laser, as well as a continuous wave C $r^{4+}$:YAG laser. The laser was pumped by a Nd:YAG laser and its characteristics were investigated. In continuous wave mode, we obtained as much as 600 mW at 1.436 ${\mu}{\textrm}{m}$ with pumping power of 6 W, by using an output coupler with a reflectivity of 98%. The power slope efficiency was 10%, when the gain medium was cooled to 19$^{\circ}C$. The tuning range was varied from 1.39 ${\mu}{\textrm}{m}$ to 1.55 ${\mu}{\textrm}{m}$ and the maximum power was 400 mW at 1.492 ${\mu}{\textrm}{m}$ with a 3-plate birefringent filter. The C $r^{4+}$:YAG laser was mode-locked by a Kerr lens mode locking method. Mode locking at 1.436 ${\mu}{\textrm}{m}$was initiated by slightly rocking a mirror mount. But the pulses were very unstable because of the strong water absorption at this region. So we shifted the lasing wavelength to 1.492 ${\mu}{\textrm}{m}$ by using a 3-plate birefringent filter. Then we obtained stable state mode-locking with the maximum average power of 280 mW for a pumping power of 6 W. The pulse width of 43 fs was measured using an autocorrelator and the repetition rate was 104.5 MHz.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.93-102
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• 2012

The purpose of this research is to create a preferable corporate culture under the SmartWork environment. There is growing interests in SmartWork, which can satisfy the compatible conditions of government's carbon emission restriction policy, corporate efficient expense reduction, productivity maximization, and each individual's work and a family. Due to the interests and the rapid development of IT technology, a realistic condition for SmartWork is established but the promotion without a sufficient preparation, such as legal examination and relevant systems, created much confusion and very few companies are introducing it. This paper discusses that a social agreement should be reached through adjustments among parties interested, such as government, companies, and employees, studies the WIN-WIN plan that individuals and organization can grow together, and proposes a new corporate culture under the SmartWork environment. SmartWork has more than the simple meaning of 'remote working'. SmartWork, a method of smart working, means a transition to a new paradigm that minimizes moving for work and work & human move together, and a change from a work-oriented culture to a human-oriented culture. This paper summarized the role of government and companies for the successful introduction of SmartWork, and proposed that a government level 'SmartWork Activation Executive Committee (tentative name)' with a strong promotional power would create a new culture of SmartWork and form a civilian consultative body to support SmartWork corporate culture creation & expansion in the private corporate area, in a tuning with Ministry of Public Administration & Security, Ministry of Labor, Ministry of Gender, and Communications Commission.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.