• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1882-1890
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• 2014

This paper proposes an augmented Lagrange Hopfield network (ALHN) based method for solving multi-objective short term fixed head hydrothermal scheduling problem. The main objective of the problem is to minimize both total power generation cost and emissions of $NO_x$, $SO_2$, and $CO_2$ over a scheduling period of one day while satisfying power balance, hydraulic, and generator operating limits constraints. The ALHN method is a combination of augmented Lagrange relaxation and continuous Hopfield neural network where the augmented Lagrange function is directly used as the energy function of the network. For implementation of the ALHN based method for solving the problem, ALHN is implemented for obtaining non-dominated solutions and fuzzy set theory is applied for obtaining the best compromise solution. The proposed method has been tested on different systems with different analyses and the obtained results have been compared to those from other methods available in the literature. The result comparisons have indicated that the proposed method is very efficient for solving the problem with good optimal solution and fast computational time. Therefore, the proposed ALHN can be a very favorable method for solving the multi-objective short term fixed head hydrothermal scheduling problems.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.5
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• pp.349-355
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• 2014

The resistance test of a high speed craft such as planing ship is performed with a high speed towing carriage instead of ordinary towing carriage because of the speed limitation. In the resistance test using high speed towing carriage, the model ship is fixed to the carriage to restrain the running attitude for enough measuring time. Such method is called fixed model test method. In the fixed model test method, to get the appropriate running attitude, the model test is iteratively repeated until the trim moment and lift force are close to zero. In this research, trim free model test method is investigated to reduce the number of iteration. And, the limitation of towing speed range in the trim free model test method is investigated.

• Korea Trade Review
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• v.46 no.6
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• pp.191-209
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• 2021

In this paper, various time series analysis models and machine learning models are presented for long-term prediction of export growth rate, and the prediction performance is compared and reviewed by RMSE and MAE. Export growth rate is one of the major economic indicators to evaluate the economic status. And It is also used to predict economic forecast. The export growth rate may have a negative (-) value as well as a positive (+) value. Therefore, Instead of using the ReLU function, which is often used for time series prediction of deep learning models, the PReLU function, which can have a negative (-) value as an output value, was used as the activation function of deep learning models. The time series prediction performance of each model for three types of data was compared and reviewed. The forecast data of long-term prediction of export growth rate was deduced by three forecast methods such as a fixed forecast method, a recursive forecast method and a rolling forecast method. As a result of the forecast, the traditional time series analysis model, ARDL, showed excellent performance, but as the time period of learning data increases, the performance of machine learning models including LSTM was relatively improved.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.378-384
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• 2017

In this paper, an efficient short-time Fourier analysis method for the quasi-periodic signals is proposed via an optimal fixed-lag finite impulse response (FIR) smoother approach using a receding horizon scheme. In order to deal with time-varying Fourier coefficients (FCs) of quasi-periodic signals, a state space model including FCs as state variables is augmented with the variants of FCs. Through an optimal fixed-lag FIR smoother, FCs and their increments are estimated simultaneously and combined to produce final estimates. A lag size of the optimal fixed-lag FIR smoother is chosen to minimize the estimation error. Since the proposed estimation scheme carries out the correction process with the estimated variants of FCs, it is highly probable that the smaller estimation error is achieved compared with existing approaches not making use of such a process. It is shown through numerical simulation that the proposed scheme has better tracking ability for estimating time-varying FCs compared with existing ones.

• Physical Therapy Rehabilitation Science
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• v.11 no.1
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• pp.58-65
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• 2022

Objective: The purpose of this study was to investigate the effect of visual feedback bicycle training on running performance, maximal oxygen uptake and quadriceps muscle strength. Design: A randomized controlled trial. Methods: Fifteen healthy adult men with no musculoskeletal or nervous system disease and capable of bicycle training were included. After the pretest, subjects were randomly assigned to visual feedback bicycle training group and general fixed bicycle training group. Both groups were trained two times a week for three weeks, each week for a fixed time and number of repetitions, followed by a six week washout period and then crossing the training method. visual feedback bicycle training provides visual feedback of heart rate in real time using a monitor and a heart rate meter during bicycle training, and general fixed bicycle training performed general bicycle training without visual feedback. After training, each item was measured using a wearable technology, gas analyzer, isokinetic equipment. Results: The results of this study was significant differences in running performance, maximal oxygen uptake and quadriceps muscle strength in visual feedback bicycle training group (p<0.05). The differential effect was found between visual feedback bicycle training group and general fixed bicycle training group in running performance, maximal oxygen uptake, and quadriceps muscle strength (p<0.05). Conclusions: This study suggested that that visual feedback bicycle training can be applied as a useful training method to improve running performance, maximal oxygen uptake and quadriceps muscle strength.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.163-166
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• 1997

In order to shorten head-way time on existing railway lines without any change of signal block length between stations, it is a realistic optional way to change the control method of train signal, i.e. to modernize the cab signal using transponder. A new signalling system of operation pattern control technique is suggested as new model to increase the railway traffic efficiency. Through the computer simulation of this model, the train head-way time by the fixed signalling system and the new pattern control system is analyzed.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.246-254
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• 1997

This paper proposes an improved scheduling model and algorithm which threads in the fixed-priority policy have faster response time and turnaround time than existing ones in SRT system. Sub run queue is added into the system and is used for the quick execution and aging of threads in the fixed-priority policy. Using simulation two method are compared. The results shows that the new scheduling model gets threads in the fixed-priority policy to run faster than existing ones.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.15 no.1
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• pp.107-110
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• 1982

Fixed bed drying method was selected to reduce the initial drying time of squid and the effects of drying air temperature and bed height on the drying rate were investigated, with following results. 1. The drying rate in the fixed bed dryer was faster than that of natural convection type dryer heated indirectly and that of hot air dryer heated directly. 2, Shirai-equation was applicable to squid being dried. Using the equation, drying rate constant obtained was as shown in table 1.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1563-1570
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• 1999

In this paper, we proposed the FPA(Fixed Partition Averaging) algorithm in order to improve the storage requirement and classification time of Memory Based Reasoning method. The proposed method enables us to use the storage more efficiently by extracting representatives out of training patterns. After partitioning the pattern space into a fixed number of equally-sized hyperrectangles, it averages patterns in each hyperrectangle to extract a representative. Also we have used the mutual information between the features and classes as weights for features to improve the classification performance.

• Structural Engineering and Mechanics
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• v.62 no.2
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• pp.247-258
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• 2017

Beam-like structures such as bridge, high building and tower, pipes, flexible connecting rods and some robotic manipulators are often excited by support motions. These structures are important in machines and structures. So, this study proposes an analytic method to accurately predict the dynamic behaviors of the structures during support motions or an earthquake. Using Timoshenko beam theory which is valid even for non-slender beams and for high-frequency responses, the analytic responses of fixed-fixed beams subjected to a real seismic motions at supports are illustrated to show the principled approach to the proposed method. The responses of a slender beam obtained by using Timoshenko beam theory are compared with the solutions based on Euler-Bernoulli beam theory to validate the correctness of the proposed method. The dynamic analysis for the fixed-fixed beam subjected to support motions gives useful information to develop an understanding of the structural behavior of the beam. The bending moment and the shear force of a slender beam are governed by dynamic components while those of a stocky beam are governed by static components. Especially, the maximal magnitudes of the bending moment and the shear force of the thick beam are proportional to the difference of support displacements and they are influenced by the seismic wave velocity.