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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Korean Institute of Intelligent Systems
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Korean Institute of Intelligent Systems
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Volume & Issues
Volume 25, Issue 6 - Dec 2015
Volume 25, Issue 5 - Oct 2015
Volume 25, Issue 4 - Aug 2015
Volume 25, Issue 3 - Jun 2015
Volume 25, Issue 2 - Apr 2015
Volume 25, Issue 1 - Feb 2015
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Design of Fuzzy Controller for a 2-Dimensional Wire-Driven Heavy Material Lifting System
Lee, Yong-Chan ; Lee, Hyeng-Jun ; Lee, Yun-Jung ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 97~104
DOI : 10.5391/JKIIS.2015.25.2.097
A fuzzy controller and a 2-dimensional wire-driven heavy material lifting system helping human operator are proposed in this paper. The 2-dimensional wire-driven heavy material lifting system is a kind of human-assistive systems in which a human is involved in the control loop. Most of the existing human-assistive control systems cannot consider human operator's characteristic. To consider human operator's characteristic, human's operating motion and requirement of reducing operator's force to lift a heavy material are considered in the design process of the proposed fuzzy controller. The performance of the proposed system is verified by experiments.
A Study on Identification using Particle Swarm Optimization for 3-DOF Helicopter System
Lee, Ho-Woon ; Kim, Tae-Woo ; Kim, Tae-Hyoung ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 105~110
DOI : 10.5391/JKIIS.2015.25.2.105
This study proposes the more improved mathematical model than conventional that for the 3-DOF Helicopter System in Quanser Inc., and checks the validity about the proposed model by performance comparison between the controller based on the conventional model and that based on the proposed model. Research process is next : First, analyze the dynamics for the 3-DOF helicopter system and establish the linear mathematical model. Second, check the eliminated nonlinear-elements in linearization process for establishing the linear mathematical model. And establish the improved mathematical model including the parameters corresponding to the eliminated nonlinear-elements. At that time, it is used for modeling that Particle Swarm Optimization algorithm the meta-heuristic global optimization method. Finally, design the controller based on the proposed model, and verify the validity of the proposed model by comparison about the experimental results between the designed controller and the controller based on the conventional model.
An Effect of Semantic Relatedness on Entity Disambiguation: Using Korean Wikipedia
Kang, In-Su ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 111~118
DOI : 10.5391/JKIIS.2015.25.2.111
Entity linking is to link entity's name mentions occurring in text to corresponding entities within knowledge bases. Since the same entity mention may refer to different entities according to their context, entity linking needs to deal with entity disambiguation. Most recent works on entity disambiguation focus on semantic relatedness between entities and attempt to integrate semantic relatedness with entity prior probabilities and term co-occurrence. To the best of my knowledge, however, it is hard to find studies that analyze and present the pure effects of semantic relatedness on entity disambiguation. From the experimentation on Korean Wikipedia data set, this article empirically evaluates entity disambiguation approaches using semantic relatedness in terms of the following aspects: (1) the difference among semantic relatedness measures such as NGD, PMI, Jaccard, Dice, Simpson, (2) the influence of ambiguities in co-occurring entity mentions' set, and (3) the difference between individual and collective disambiguation approaches.
Development of Sludge Concentration Estimation Method using Neuro-Fuzzy Algorithm
Jang, Sang-Bok ; Lee, Ho-Hyun ; Lee, Dae-Jong ; Kweon, Jin-Hee ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 119~125
DOI : 10.5391/JKIIS.2015.25.2.119
A concentration meter is widely used at purification plants, sewage treatment plants and waste water treatment plants to sort and transfer high concentration sludge and to control the amount of chemical dosage. When the strange substance is contained in the sludge, however, the attenuation of ultrasonic wave could be increased or not be transmitted to the receiver. At that case, the value of concentration meter is higher than the actual density value or vibrated up and down. It has also been difficult to automate the residuals treatment process according to the problems as sludge attachment or damage of a sensor. Multi-beam ultrasonic concentration meter has been developed to solve these problems, but the failure of the ultrasonic beam of a specific concentration measurement value degrade the performance of the entire system. This paper proposes the method to improve the accuracy of sludge concentration rate by choosing reliable sensor values and learning them by proposed algorithm. The prediction algorithm is chosen as neuro-fuzzy model, which is tested by the various experiments.
Establishment of Strategy for Management of Technology Using Data Mining Technique
Lee, Junseok ; Lee, Joonhyuck ; Kim, Gabjo ; Park, Sangsung ; Jang, Dongsik ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 126~132
DOI : 10.5391/JKIIS.2015.25.2.126
Technology forecasting is about understanding a status of a specific technology in the future, based on the current data of the technology. It is useful when planning technology management strategies. These days, it is common for countries, companies, and researchers to establish R&D directions and strategies by utilizing experts' opinions. However, this qualitative method of technology forecasting is costly and time consuming since it requires to collect a variety of opinions and analysis from many experts. In order to deal with these limitations, quantitative method of technology forecasting is being studied to secure objective forecast result and help R&D decision making process. This paper suggests a methodology of technology forecasting based on quantitative analysis. The methodology consists of data collection, principal component analysis, and technology forecasting by logistic regression, which is one of the data mining techniques. In this research, patent documents related to autonomous vehicle are collected. Then, the texts from patent documents are extracted by text mining technique to construct an appropriate form for analysis. After principal component analysis, logistic regression is performed by using principal component score. On the basis of this result, it is possible to analyze R&D development situation and technology forecasting.
A Performance Improvement of GLCM Based on Nonuniform Quantization Method
Cho, Yong-Hyun ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 133~138
DOI : 10.5391/JKIIS.2015.25.2.133
This paper presents a performance improvement of gray level co-occurrence matrix(GLCM) based on the nonuniform quantization, which is generally used to analyze the texture of images. The nonuniform quantization is given by Lloyd algorithm of recursive technique by minimizing the mean square error. The nonlinear intensity levels by performing nonuniformly the quantization of image have been used to decrease the dimension of GLCM, that is applied to reduce the computation loads as a results of generating the GLCM and calculating the texture parameters by using GLCM. The proposed method has been applied to 30 images of
pixels with 256-gray level for analyzing the texture by calculating the 6 parameters, such as angular second moment, contrast, variance, entropy, correlation, inverse difference moment. The experimental results show that the proposed method has a superior computation time and memory to the conventional 256-level GLCM method without performing the quantization. Especially, 16-gray level by using the nonuniform quantization has the superior performance for analyzing textures to another levels of 48, 32, 12, and 8 levels.
Design of Corrective Controllers for Model Matching of Switched Asynchronous Sequential Machines
Yang, Jung-Min ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 139~146
DOI : 10.5391/JKIIS.2015.25.2.139
This paper presents the solution to model matching of switched asynchronous sequential machines by corrective control. We propose a model of switched asynchronous sequential machines, in which the system can have different dynamics of asynchronous machines governed by a pre-determined sequence of switching. The control objective is to derive a corrective control law so that the stable state behavior of the closed-loop system can match that of a prescribed model. A new skeleton matrix is defined to represent the reachability of the switched asynchronous machine, and a novel control scheme is presented that interweaves the switching signal and the corrective control procedure. A design algorithm for the proposed controller is illustrated in a case study.
Human Detection and Fuzzy Temperature Control System for Energy Reduction of Cooling Device in Elevator
Eum, Hyukmin ; Jang, Sukyoon ; Lee, Heejin ; Park, Mignon ; Yoon, Changyong ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 147~154
DOI : 10.5391/JKIIS.2015.25.2.147
In this paper, we propose human detection and fuzzy temperature control system for energy reduction of cooling device in elevator. In order to improve problems of existing cooling device using the refrigerant, energy reduction and efficient management are continuously achieved because of operation of thermoelectric cooling device using the human detection and fuzzy temperature control system. The proposed system confirms the number of passengers in elevator and temperature is then controlled by those numbers and an average temperature for the season in fuzzy system. The human detection method scans the number of passengers using a head part as a feature based on bird's-eye view camera in elevator. The fuzzy system determines elevator internal temperature considering atmospheric temperature and the scanned passenger numbers as a look-up table. The proposed system reduces energy of the cooling device through the human detection and temperature control. In experiment, energy reduction is confirmed and the performance of the proposed system is verified.
Behavior Analysis in Love Model of Romeo and Juliet with Time Delay
Huang, Linyun ; Bae, Young-Chul ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 155~160
DOI : 10.5391/JKIIS.2015.25.2.155
We say that human have an animal of emotion. There are various kind in the emotion of human. One of among them, love has been studied in sociology and psychology as a matter of great concern. In this paper, we propose a novel love model with the delay time as response time for love. We also consider it in the Romeo and Juliet of love model to analyze their romantic behaviors. First we consider the Juliet only have a time delay, Romeo only have a time delay, and both Romeo and Juliet have a time delay. We represent their behaviors as time series and phase portrait, and we analyze their difference.
Circuit Modeling and Simulation for Thermoelectric Cooling System using Condensed Water
Lee, Sang-Yun ; Jang, Sukyoon ; Park, Mignon ; Yoon, Changyong ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 161~167
DOI : 10.5391/JKIIS.2015.25.2.161
In this paper, a novel thermoelectric cooling system utilizing condensed water is introduced and its electrical equivalent circuit model is proposed. The introduced system can deals with the condensed water and improves efficiency by spraying the condensed water on heat sink. The electrical equivalent circuit model is derived by combining the circuit model of the classical thermoelectric cooling system with equation of heat exchange. Because the parameters of the model can be defined from not other experimental data but just the data sheet of the thermoelement, the model can be useful to design and develop the controller of the proposed system. We verify that the proposed model is valid and the introduced system is more efficient than the previous thermoelectric cooling system through simulations.
Interval Type-2 Fuzzy Logic Control System of Flight Longitudinal Motion
Cho, Young-Hwan ; Lee, Hong-Gi ; Jeon, Hong-Tae ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 168~173
DOI : 10.5391/JKIIS.2015.25.2.168
The flight control of aircraft, which has nonlinear time-varying dynamic characteristics depending on the various and unexpected external conditions, can be performed on two motions: longitudinal motion and lateral motion. In the longitudinal motion control of aircraft, pitch and trust are major control parameters and roll and yaw are control ones in the lateral motion control. Until now, a number of efficient and reliable control schemes that can guarantee the stability and maneuverability of the aircraft have been developed. Recently, the intelligent flight control scheme, which differs from the conventional control strategy requiring the various and complicate procedures such as the wind tunnel and environmental experiments, has attracted attention. In this paper, an intelligent longitudinal control scheme has been proposed utilizing Interval Type-2 fuzzy logic which can be recognized as a representative intelligent control methodology. The results will be verified through computer simulation with a F-4 jet fighter.
Prioritizing for Failure Modes of Dynamic Positioning System Using Fuzzy-FMEA
Baek, Gyeongdong ; Kim, Sungshin ; Cheon, Seongpyo ; Suh, Heungwon ; Lee, Daehyung ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 174~179
DOI : 10.5391/JKIIS.2015.25.2.174
Failure Mode and Effects Analysis (FMEA) has been used by Dynamic Positioning (DP) system for risk and reliability analysis. However, there are limitations associated with its implementation in offshore project. 1) since the failure data measured from the SCADA system is missing or unreliable, assessments of Severity, Occurrence, Detection are based on expert's knowledge; 2) it is not easy for experts to precisely evaluate the three risk factors. The risk factors are often expressed in a linguistic way. 3) the relative importance among three risk factors are rarely even considered. To solve these problems and improve the effectiveness of the traditional FMEA, we suggest a Fuzzy-FMEA method for risk and failure mode analysis in Dynamic Positioning System of offshore. The information gathered from DP FMEA report and DP FMEA Proving Trials is expressed using fuzzy linguistic terms. The proposed method is applied to an offshore Dynamic Positioning system, and the results are compared with traditional FMEA.
Latent Keyphrase Extraction Using LDA Model
Cho, Taemin ; Lee, Jee-Hyong ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 180~185
DOI : 10.5391/JKIIS.2015.25.2.180
As the number of document resources is continuously increasing, automatically extracting keyphrases from a document becomes one of the main issues in recent days. However, most previous works have tried to extract keyphrases from words in documents, so they overlooked latent keyphrases which did not appear in documents. Although latent keyphrases do not appear in documents, they can undertake an important role in text summarization and information retrieval because they implicate meaningful concepts or contents of documents. Also, they cover more than one fourth of the entire keyphrases in the real-world datasets and they can be utilized in short articles such as SNS which rarely have explicit keyphrases. In this paper, we propose a new approach that selects candidate keyphrases from the keyphrases of neighbor documents which are similar to the given document and evaluates the importance of the candidates with the individual words in the candidates. Experiment result shows that latent keyphrases can be extracted at a reasonable level.
MCMC Particle Filter based Multiple Preceeding Vehicle Tracking System for Intelligent Vehicle
Choi, Baehoon ; An, Jhonghyun ; Cho, Minho ; Kim, Euntai ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 186~190
DOI : 10.5391/JKIIS.2015.25.2.186
Intelligent vehicle plans motion and navigate itself based on the surrounding environment perception. Hence, the precise environment recognition is an essential part of self-driving vehicle. There exist many vulnerable road users (e.g. vehicle, pedestrians) on vehicular driving environment, the vehicle must percept all the dynamic obstacles accurately for safety. In this paper, we propose an multiple vehicle tracking algorithm using microwave radar. Our proposed system includes various special features. First, exceptional radar measurement model for vehicle, concentrated on the corner, is described by mixture density network (MDN), and applied to particle filter weighting. Also, to conquer the curse of dimensionality of particle filter and estimate the time-varying number of multi-target states, reversible jump markov chain monte carlo (RJMCMC) is used to sampling step of the proposed algorithm. The robustness of the proposed algorithm is demonstrated through several computer simulations.
Generating Firm's Performance Indicators by Applying PCA
Lee, Joonhyuck ; Kim, Gabjo ; Park, Sangsung ; Jang, Dongsik ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 191~196
DOI : 10.5391/JKIIS.2015.25.2.191
There have been many studies on statistical forecasting on firm's performance and stock price by applying various financial indicators such as debt ratio and sales growth rate. Selecting predictors for constructing a prediction model among the various financial indicators is very important for precise prediction. Most of the previous studies applied variable selection algorithms for selecting predictors. However, the variable selection algorithm is considered to be at risk of eliminating certain amount of information from the indicators that were excluded from model construction. Therefore, we propose a firm's performance prediction model which principal component analysis is applied instead of the variable selection algorithm, in order to reduce dimensionality of input variables of the prediction model. In this study, we constructed the proposed prediction model by using financial data of American IT companies to empirically analyze prediction performance of the model.
Zadeh's extension principle for 2-dimensional triangular fuzzy numbers
Kim, Changil ; Yun, Yong Sik ;
Journal of Korean Institute of Intelligent Systems, volume 25, issue 2, 2015, Pages 197~202
DOI : 10.5391/JKIIS.2015.25.2.197
A triangular fuzzy number is one of the most popular fuzzy numbers. Many results for the extended algebraic operations between two triangular fuzzy numbers are well-known. We generalize the triangular fuzzy numbers on
. By defining parametric operations between two regions valued
-cuts, we get the parametric operations for two triangular fuzzy numbers defined on