• Korean Institute of Interior Design Journal
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• v.17 no.5
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• pp.40-50
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• 2008

This article examined the applicability of spatial configuration to Escher's works through configurative logics and rules and studied the contrasting relations among the unit elements in Escher's works and their characteristics and the creative process of the characteristics. As the results of the study on the bases to maintain and create the partial elements revealed as the characteristics, it was shown that Escher's sequential transformative works demonstrated diverse expressive characteristics as a creative process of Inter-complementary contrasting relations based on the independence of the unit elements. It was also shown that the creative process of the unit elements was actualized through the maintenance base of the fixed and absolute characteristic as the logic for the creation and the creation base of the dynamic and relative characteristic. Therefore, it was interpreted that by applying the logics for creation to Escher's unit elements through the spatial interpretation of the maintenance base and the creation base as well as by configuring the units created in such a way according to the characteristics of Escher's works, spatial possibility canbe derived out from Escher's contrasting tessellation works. The process of spatial configuration is the process to make a balance between various conditions, artists own understanding of the space and his/her intention of the space. From this viewpoint, the logics for maintenance base and for creation base seem to have the potentiality as a spatial configuration to consistently meet the given conditions as well as to derive out novelty through the transformation to maintain the fixed and absolute condition(base) and the characteristics of the independent(additional) transformation arising together with the implicit relations among the transformative units.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.230-236
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• 2011

This paper proposes the possibility which the fuzzy theory can be used to improve the performance of the parabolic SAR(Stop-And-Reverse) indicator in the trading systems for stock market. The simulation results with data of the KOSPI 200 future show that the occurred number of trading signals and the false signals in the proposed fuzzy SAR indicator is less than that in the conventional SAR indicator. In the conventional SAR system, the incremental value of the acceleration factor is usually setted as 0.02 and the maximum value of the acceleration factor is usually limited as 0.2. But in the proposed fuzzy SAR system, the incremental value and the maximum value of the acceleration factor are automatically adjusted by using the fuzzy rules, which are designed based-on the difference between short-term moving average and medium-term moving average and also based-on the slope of short-term moving average.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.480-480
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• 2000

In this paper, we proposed a fuzzy-neuro controller to control the speed of wound rotor induction motor with slip energy recovery. The speed is limited at some range of sub-synchronous speed of the rotating magnetic field. Control speed by adjusting resistance value in the rotor circuit that occurs the efficiency of power are reduced, because of the slip energy is lost when it passes through the rotor resistance. The control system is designed to maintain efficiency of motor. Recently, the emergence of artificial neural networks has made it conductive to integrate fuzzy controllers and neural models for the development of fuzzy control systems, Fuzzy-neuro controller has been designed by integrating two neural network models with a basic fuzzy logic controller. Using the back propagation algorithm, the first neural network is trained as a plant emulator and the second neural network is used as a compensator for the basic fuzzy controller to improve its performance on-line. The function of the neural network plant emulator is to provide the correct error signal at the output of the neural fuzzy compensator without the need for any mathematical modeling of the plant. The difficulty of fine-tuning the scale factors and formulating the correct control rules in a basic fuzzy controller may be reduced using the proposed scheme. The scheme is applied to the control speed of a wound rotor induction motor process. The control system is designed to maintain efficiency of motor and compensate power factor of system. That is: the proposed controller gives the controlled system by keeping the speed constant and the good transient response without overshoot can be obtained.

• Journal of KSNVE
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• v.6 no.1
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• pp.35-44
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• 1996

This paper presents a new type of fuzzy-sliding mode controller for robust tip position control of a single-link flexible manipulator subjected to parameter variations. A sliding mode controller is formulated with an assumption that imposed parameter variations are bounded so that certain deterministic performance can be guaranted. In the design of the sliding mode controller, so called moving sliding surface is adopted to minimize the reaching phase and thus mitigate system sensitivity to the variations. The sliding mode controller is then incorporated with a fuzzy technique to reduce inherently ever-existing chattering which is impediment in position control of flexible manipulators. A set of fuzzy parameters and control rules are obtained from a relation between predetermined sliding surface and representative points in the state space. Computer simulations are undertaken in order to demonstrate superior control performance of the proposed methodology.

• Journal of KIISE
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• v.43 no.4
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• pp.470-479
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• 2016

As the number of various types of media data such as UCC (User Created Contents) increases, research is actively being carried out in many different fields so as to provide meaningful media services. Amidst these studies, a semantic web-based media classification approach has been proposed; however, it encounters some limitations in video classification because of its underlying ontology derived from meta-information such as video tag and title. In this paper, we define recognized objects in a video and activity that is composed of video objects in a shot, and introduce a reasoning approach based on description logic. We define sequential rules for a sequence of shots in a video and describe how to classify it. For processing the large amount of increasing media data, we utilize Spark streaming, and a distributed in-memory big data processing framework, and describe how to classify media data in parallel. To evaluate the efficiency of the proposed approach, we conducted an experiment using a large amount of media ontology extracted from Youtube videos.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.115-119
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• 2018

Defining and measuring non-rigid or flexible parts has been controversial in industry for many years. There are two primary areas of controversy. The first is agreeing on what exactly a non-rigid part is. The second is agreeing on how to define and measure a non-rigid part. The subject of non-rigid parts is further complicated by the brief coverage it receives in the national and international standards. This leaves each company to improvise or create its own rules for non-rigid parts. There are some who believe that Geometrical Dimensioning and Tolerancing (GD&T) should not be used on non-rigid parts. This is not true. The ASME Y14.5M standard applies to rigid parts as a default condition. However, there is no definition given for a rigid part. The term rigid part has been used in industry for so long that it has gained a definition by its general use. When most people in industry say rigid part, they are referring to a part doesn't move (deform or flex) when a force (including gravity) is applied. How much force is relative based on the part characteristics. In reality, all parts will deform (or flex) if enough force is applied. Using this logic, all parts would be considered non-rigid. However, we all know that this is not how parts are treated in industry. Although GD&T defaults to rigid parts, it should also be used on non-rigid parts with a few special techniques. Actually 50~60% of all products designed contain parts or features on parts that are non-rigid. Therefore, we try to suggest the definitions of rigid and non-rigid parts and method to measure non-rigid parts.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.49-57
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• 1999

The fusion of fuzzy set theory and neural networks technologies have concentrated on applying neural networks to obtain the optimal rule bases of fuzzy logic system. Unfortunately, this is very hard to achieve due to limited learning capabilities of neural networks. To overcome this difficulty, we propose a new approach in which rough set theory and neuro-fuzzy fusion are combined to obtain the optimal rule base from input/output data. Compared with conventional FNN, the proposed algorithm is considerably more realistic because it reduces overlapped data when construction a rule base. This results are applied to the construction of inference rules for controlling the temperature at specified points in a refrigerator.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.2070-2079
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• 1997

In this paper, we proposed the FNCAC (fuzzy neural call admission control) scheme of the ATM networks which used the benefits of fuzzy logic controller and the learning abilities of the neural network to solve the call admission control problems. The new call in ATM networks is connected if QoS(quality of service) of the current calls is not affected due to the connection of a new call. The neural network CAC(call admission control) system is predictable system because the neural network is able to learn by the input/output pattern. We applied the fuzzy inference on the learning rate and momentum constant for improving the learning speed of the fuzzy neural network. The excellence of the proposed algorithm was verified using measurement of learning numbers in the traditional neural network method and fuzzy neural network method by simulation. We found that the learning speed of the FNCAC based on the fuzzy learning rules is 5 times faster than that of the CAC method based on the traditional neural network theory.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.5
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• pp.466-476
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• 2013

This paper describes a fuzzy control method to control the output voltage of the three-phase Z-source PWM rectifier. A fuzzy control system is a control system based on fuzzy logic, and the fuzzy controller uses a single input fuzzy theory with its fuzzification. Analytical structure of the simplest fuzzy controller is derived through the triangular membership functions with its fuzzification. By setting the membership functions of the fuzzy rules, fuzzy control is achieved. The PI portion of the output DC voltage controller is controlled by fuzzy method. To confirm the validity of the proposed method, the simulation and experiment were performed, The simulation is performed with PSIM and MATLAB/SIMULINK. For the experiment, we used a DSP(TMS320F28335) controller to compute the reference value and generate the PWM pulses. For the transient state performance of the output DC voltage control of Z-source PWM rectifier, the PI controller and fuzzy controller were compared, also the conventional PWM rectifier and Z-source PWM rectifier were compared. From the results, the Z-source rectifier could allow to buck or boost of the output DC voltage. Through the analysis of the transient state, we could observe that the fuzzy controller has better performance than the conventional PI controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.3
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• pp.14-24
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• 1996

A fuzzy classifier which needs various analyses of features using genetic algorithms is proposed. The fuzzy classifier has a simple structure, which contains a classification part based on fuzzy logic theory and a rule generation ation padptu sing genetic algorithms. The rule generation part determines optimal fuzzy membership functions and inclusior~ or exclusion of each feature in fuzzy classification rules. We analyzed recognition rate of a specific object, then added finer features repetitively, if necessary, to the object which has large misclassification rate. And we introduce repetitive analyses method for the minimum size of string and population, and for the improvement of recognition rates. This classifier is applied to three examples of the classification of iris data, the discrimination of thyroid gland cancer cells and the recognition of confusing handwritten and printed numerals. In the recognition of confusing handwritten and printed numerals, each sample numeral is classified into one of the groups which are divided according to the sample structure. The fuzzy classifier proposed in this paper has recognition rates of 98. 67% for iris data, 98.25% for thyroid gland cancer cells and 96.3% for confusing handwritten and printed numeral!;.