• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.75-90
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• 1998

The improper use of input and output factors in DEA has a critical and negative impact on the efficiency measurement and the discernment of decision making units(DMUs) : hence the proper selection Process of the factors should precede the actual applications of DEA. In this paper, we propose a new approach to selecting proper factors based on Tofallis' partial efficiency evaluation method(1996). With the approach, the factors aye clustered by measuring their respective partial efficiencies and analyzing the rank correlations of them. The method and procedure we propose in this paper are then applied to measure the efficiencies of the public libraries in Seoul District area, and the results show that the proposed approach can provide meaningful information to improve discernment of the DMUs while using less number of input factors (and less information). The proposed method can be effectively used in the situation where the number of the DMUs to be considered is relatively small compared to the number of available input and output factors, which usually lessens the power to identify the inefficient units in DEA.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.207-214
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• 2010

This paper proposes about decentralized control approach based Leader-Follower formation control using LOS (Line of Sight) algorithm and unknown input observer. The position of robots which is a basic information in multi-robot or single robot motion control is determined by localization algorithm fusing UPS (Ultrasonic Position System) and kinematics model. For formation control, a decentralized control approach individually installing a local controller in leader and follower robot is adopted. Leader robot is controlled to track a specified trajectory by LOS algorithm, and the other robots follow the leader by local controller based on tracking platoon level function, self-sensing data and estimated information from unknown input observer. The performance of proposed method is proven through the formation experiment of two vehicle models.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.6
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• pp.91-103
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• 1994

As CAD systems are introduced in the filed of engineering design, the necessities for automatic drawing input are increased . In this paper, we propose a method for realizing automatic drawing input by separation of text regions and graphic regions, extraction of line vectors from graphic regions, and recognition of circular arcs and circles from line vectors. Sizes of isolated regions, on a drawing are used for separating text regions and graphic regions. Thinning and maximum allowable error method are used to extract line vectors. And geometric structures of line vectors are analyzed to recognize circular arcs and circles. By processing text regions and graphic regions separately, 30~40% of vector information can be reduced. Recognition of circular arcs and circles can increase the utilization of automatic drawing input function.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.201-209
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• 2013

For censored regression, it is often the case that some input variables are not important, while some input variables are more important than others. We propose a novel algorithm for selecting such important input variables for censored kernel regression, which is based on the penalized regression with the weighted quadratic loss function for the censored data, where the weight is computed from the empirical survival function of the censoring variable. We employ the weighted version of ANOVA decomposition kernels to choose optimal subset of important input variables. Experimental results are then presented which indicate the performance of the proposed variable selection method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.34-42
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• 2007

The sphere decoder (SD) has recently been proposed to perform maximum likelihood (ML) decoding for multi-input multi-output systems. Employing a 'breadth-first' searching algorithm for closet points in a lattice, we propose a novel ML decoding scheme for multi-input multi-output systems. Simulation results show that the proposed scheme has the same bit error rate performance as the conventional ML decoders while allowing significantly lower computational burden than the SD.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.92-102
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• 2014

In recent years, there has been growing interest in secure pairing, which refers to the establishment of a secure communication channel between two mobile devices. There are a number of descriptions of the various types of out-of-band (OOB) channels, through which authentication data can be transferred under a user's control and involvement. However, none have become widely used due to their lack of adaptability to the variety of mobile devices. In this paper, we introduce a new OOB channel, which uses accelerometer-based gesture input. The gesture-based OOB channel is suitable for all kinds of mobile devices, including input/output constraint devices, as the accelerometer is small and incurs only a small computational overhead. We implemented and evaluated the channel using an Apple iPhone handset. The results demonstrate that the channel is viable with completion times and error rates that are comparable with other OOB channels.

• Journal of Power Electronics
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• v.12 no.5
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• pp.689-698
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• 2012

This paper investigates the effects of applying different input current waveshapes on the performance of a continuous-conduction-mode (CCM) power-factor-correction (PFC) boost pre-regulator. It is found that the output voltage ripple of the pre-regulator can be reduced if the input current is modified to include controlled amount of higher order harmonics. This finding allows us to balance the performance of output regulation and the harmonic current emission when coming to the design of the pre-regulator. An experimental PFC boost pre-regulator prototype is constructed to verify the analysis and show the benefit of the pre-regulator operating with input current containing higher order harmonics.

• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1107-1120
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• 2004

This study proposes a new scheme for the sampled-data representation of nonlinear systems with time-delayed multi-input. The proposed scheme is based on the Taylor-series expansion and zero-order hold assumption. The mathematical structure of a new discretization scheme is explored. On the basis of this structure, the sampled-data representation of nonlinear systems including time-delay is derived. The new scheme is applied to nonlinear systems with two inputs and then the delayed multi-input general equation is derived. The resulting time-discretization provides a finite-dimensional representation of nonlinear control systems with time-delay enabling existing controller design techniques to be applied to them. In order to evaluate the tracking performance of the proposed scheme, an algorithm is tested for some of the examples including maneuvering of an automobile and a 2-DOF mechanical system.

• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.214-220
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• 2021

In this study, we constructed several scenarios that are required for LED lighting, and we designed and implemented an LED lighting control system to operate these scenarios to confirm their behavior. An LED lighting control system is a hybrid control board that is designed by combining LED controllers and SMPS, consisting of an AC/DC power supply part that converts AC 220 V into DC 12 V, and a drive and control part that controls the scenario and color of the LED module. Conventional LED light controllers have an input power of DC 12 V, so when using the input AC 220 V, the SMPS must be connected to the LED light controller. To eliminate this inconvenience, a hybrid LED lighting control system was configured to combine LED lighting controllers and SMPS into one control system. Furthermore, we designed a control system to represent the most appropriate color according to the input of the distance and illumination using a fuzzy control system to conduct computer simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3243-3257
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• 2021

Deep neural networks provide excellent performance in pattern recognition, audio classification, and image recognition. It is important that they accurately recognize input data, particularly when they are used in autonomous vehicles or for medical services. In this study, we propose a data correction method for increasing the accuracy of an unknown classifier by modifying the input data without changing the classifier. This method modifies the input data slightly so that the unknown classifier will correctly recognize the input data. It is an ensemble method that has the characteristic of transferability to an unknown classifier by generating corrected data that are correctly recognized by several classifiers that are known in advance. We tested our method using MNIST and CIFAR-10 as experimental data. The experimental results exhibit that the accuracy of the unknown classifier is a 100% correct recognition rate owing to the data correction generated by the proposed method, which minimizes data distortion to maintain the data's recognizability by humans.