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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 21, Issue 6 - Dec 2011
Volume 21, Issue 5 - Oct 2011
Volume 21, Issue 4 - Aug 2011
Volume 21, Issue 3 - Jun 2011
Volume 21, Issue 2 - Apr 2011
Volume 21, Issue 1 - Feb 2011
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Analysis on Boundary Condition for Standing Balance of Four-Legged Robots
Kim, Byoung-Ho ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 673~678
DOI : 10.5391/JKIIS.2011.21.6.673
This paper analyzes the standing balance of four-legged robots which are useful for delivering objects or investigating of information. For this, we specify an effective model of general four-legged robots and propose a boundary condition based on the standing stability of the four-legged walking. To verify such a standing balance, we consider some exemplary free motions at the standing mode of the robot and discuss on the robot's balance margin. The analysis specified in this paper will be applicable for effective balancing control of various quadruped robotic walking.
Algorithm of Analysing Electric Power Signal for Home Electric Power Monitoring in Non-Intrusive Way
Park, Sung-Wook ; Wang, Bo-Hyeun ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 679~685
DOI : 10.5391/JKIIS.2011.21.6.679
This paper presents an algorithm identifying devices that generate observed mixed signals that are collected at main power-supply line. The proposed algorithm, which is necessary for low cost electric power monitoring system at appliance-level, that is non-intrusive load monitoring system, divides incoming mixed signal into multiple time intervals, calculating difference-signals between consecutive time interval, and identifies which device is operating at the time interval by analysing the difference-signals. Since the features of one device can remain when the time interval is short enough and the features are independent and additive, well-known classification algorithms can be used to classify the difference-signals with features of N individual devices, otherwise
features might be necessary. The proposed algorithm was verified using data mixed in a laboratory with individual devices's data collected from field. When maximum 4 devices operate or stop sequentially and when features satisfy the requirements of proposed algorithm, the proposed algorithm resulted nearly 100% success rate under the constrained test condition. In order to apply the proposed algorithm in real world, the number devices shall increase, the time interval shall be smaller and the pattern of mixture shall be more diverse. However we can expect, if features used follow guidelines of proposed algorithm, future system could have certain level of performance without the guideline.
Design of IG-based Fuzzy Models Using Improved Space Search Algorithm
Oh, Sung-Kwun ; Kim, Hyun-Ki ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 686~691
DOI : 10.5391/JKIIS.2011.21.6.686
This study is concerned with the identification of fuzzy models. To address the optimization of fuzzy model, we proposed an improved space search evolutionary algorithm (ISSA) which is realized with the combination of space search algorithm and Gaussian mutation. The proposed ISSA is exploited here as the optimization vehicle for the design of fuzzy models. Considering the design of fuzzy models, we developed a hybrid identification method using information granulation and the ISSA. Information granules are treated as collections of objects (e.g. data) brought together by the criteria of proximity, similarity, or functionality. The overall hybrid identification comes in the form of two optimization mechanisms: structure identification and parameter identification. The structure identification is supported by the ISSA and C-Means while the parameter estimation is realized via the ISSA and weighted least square error method. A suite of comparative studies show that the proposed model leads to better performance in comparison with some existing models.
A Study on Hybrid Wheeled and Legged Mobile Robot with Docking Mechanism
Lee, Bo-Hoon ; Lee, Chang-Seok ; Kim, Yong-Tae ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 692~697
DOI : 10.5391/JKIIS.2011.21.6.692
There are many researches to develop robots that improve its mobility to adapt in various uneven environments. In the paper, a hybrid mobile robot that can dock with the other robot and transforms between wheeled robot and legged robot is proposed. The hybrid mobile robot platform has docking device with a peg and a cup module. In addition, the robot is possible to walk and drive according to condition of the road. A navigation algorithm of the hybrid mobile robot is proposed to improve the mobility of robots using docking algorithm based on image processing on the broken road and uneven terrain. The proposed method recognizes road condition through PSD sensor attached in front and bottom of the robot and selects an appropriate navigation method according to terrain surface. The proposed docking and navigation methods are verified through experiments using hybrid mobile robots.
Study on applying Quad-Tree & R-Tree for building the analysis system using massive ship position data
Lee, Sang-Jae ; Park, Gyei-Kark ; Kim, Do-Yeon ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 698~704
DOI : 10.5391/JKIIS.2011.21.6.698
This study aims to facilitate and increase the performance of the Traffic Analysis System which receives the location information of vessels sailing along the coast all over the country in real time and analyzes the vessels' sailing situation. Especially, the research has a signification that the system is designed with the application of Quad-Tree and R-Tree data structure in order for system users to search necessary information quickly and effectively, and it verifies the improvement of the performance by showing experiment results comparing the existing Traffic Analysis System to newly upgraded Traffic Analysis System.
A Vehicle License Plate Recognition Using the Feature Vectors based on Mesh and Thinning
Park, Seung-Hyun ; Cho, Seong-Won ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 705~711
DOI : 10.5391/JKIIS.2011.21.6.705
This paper proposes an effective algorithm of license plate recognition for industrial applications. By applying Canny edge detection on a vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are compared with the pre-learned weighting values by backpropagation neural network to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.
Scheduling Management Agent using Bayesian Network based on Location Awareness
Yeon, Sun-Jung ; Hwang, Hye-Jeong ; Lee, Sang-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 712~717
DOI : 10.5391/JKIIS.2011.21.6.712
Recently, diverse schedule management agents are being researched for the efficient schedule management of smart devices users, but they remain at a confirmatory level. In order to efficiently manage user's schedules, execution of planned schedules should be monitored to help users properly execute their schedules, or feedback must be given so that when setting up new schedules, users can plan their schedule according to their schedule establishment patterns. This research proposes a schedule management agent that infers the user's behaviors by using acquired user context, and provides schedule related feedback depending on the user's behavior patterns, when users are executing their schedules or planning new schedules. For this, collected user context information is preprocessed and user's behavior is inferred by Bayesian network. Also, in order to provide feedbacks necessary for confirming the user's schedule execution and new schedule establishment, a context tree pattern matching method for the user's schedule, location and time contexts was applied, then verified with 6 weeks of user simulation in a mobile environment.
Visual Multi-touch Input Device Using Vision Camera
Seo, Hyo-Dong ; Joo, Young-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 718~723
DOI : 10.5391/JKIIS.2011.21.6.718
In this paper, we propose a visual multi-touch air input device using vision cameras. The implemented device provides a barehanded interface which copes with the multi-touch operation. The proposed device is easy to apply to the real-time systems because of its low computational load and is cheaper than the existing methods using glove data or 3-dimensional data because any additional equipment is not required. To do this, first, we propose an image processing algorithm based on the HSV color model and the labeling from obtained images. Also, to improve the accuracy of the recognition of hand gestures, we propose a motion recognition algorithm based on the geometric feature points, the skeleton model, and the Kalman filter. Finally, the experiments show that the proposed device is applicable to remote controllers for video games, smart TVs and any computer applications.
Implementation of Search Method based on Sequence and Adjacency Relationship of User Query
So, Byung-Chul ; Jung, Jin-Woo ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 724~729
DOI : 10.5391/JKIIS.2011.21.6.724
Information retrieval is a method to search the needed data by users. Generally, when a user searches some data in the large scale data set like the internet, ranking-based search is widely used because it is not easy to find the exactly needed data at once. In this paper, we propose a novel ranking-based search method based on sequence and adjacency relationship of user query by the help of TF-IDF and n-gram. As a result, it was possible to find the needed data more accurately with 73% accuracy in more than 19,000 data set.
Pattern Classification Model Design and Performance Comparison for Data Mining of Time Series Data
Lee, Soo-Yong ; Lee, Kyoung-Joung ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 730~736
DOI : 10.5391/JKIIS.2011.21.6.730
In this paper, we designed the models for pattern classification which can reflect the latest trend in time series. It has been shown that fusion models based on statistical and AI methods are superior to traditional ones for the pattern classification model supporting decision making. Especially, the hit rates of pattern classification models combined with fuzzy theory are relatively increased. The statistical SVM models combined with fuzzy membership function, or the models combining neural network and FCM has shown good performance. BPN, PNN, FNN, FCM, SVM, FSVM, Decision Tree, Time Series Analysis, and Regression Analysis were used for pattern classification models in the experiments of this paper. The economical indices DB with time series properties of the financial market(Korea, KOSPI200 DB) and the electrocardiogram DB of arrhythmia patients in hospital emergencies(USA, MIT-BIH DB) were used for data base.
Application of Recent Approximate Dynamic Programming Methods for Navigation Problems
Min, Dae-Hong ; Jung, Keun-Woo ; Kwon, Ki-Young ; Park, Joo-Young ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 737~742
DOI : 10.5391/JKIIS.2011.21.6.737
Navigation problems include the task of determining the control input under various constraints for systems such as mobile robots subject to uncertain disturbance. Such tasks can be modeled as constrained stochastic control problems. In order to solve these control problems, one may try to utilize the dynamic programming(DP) methods which rely on the concept of optimal value function. However, in most real-world problems, this trial would give us many difficulties; for examples, the exact system model may not be known; the computation of the optimal control policy may be impossible; and/or a huge amount of computing resource may be in need. As a strategy to overcome the difficulties of DP, one can utilize ADP(approximate dynamic programming) methods, which find suboptimal control policies resorting to approximate value functions. In this paper, we apply recently proposed ADP methods to a class of navigation problems having complex constraints, and observe the resultant performance characteristics.
Collaborative Tracking Algorithm for Intelligent Video Surveillance Systems Using Multiple Network Cameras
Lee, Deog-Yong ; Jeon, Hyoung-Seok ; Joo, Young-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 743~748
DOI : 10.5391/JKIIS.2011.21.6.743
In this paper, we propose a collaborative tracking algorithm for intelligent video surveillance systems using the multiple network cameras. To do this, each camera detects a moving object and it's movement direction by motion templates. Once a moving object is detect, the Kalman filter is used to reduce noises, and a collaborative tracking camera is selected according to the movement direction and the camera state. In this procedure, Pan-Tilt-Zoom(PTZ) parameters are assigned to obtain clear images. Finally, some experiments show the validity of the proposed method.
Design of Optimized pRBFNNs-based Face Recognition Algorithm Using Two-dimensional Image and ASM Algorithm
Oh, Sung-Kwun ; Ma, Chang-Min ; Yoo, Sung-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 749~754
DOI : 10.5391/JKIIS.2011.21.6.749
In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.
Improvement of Positioning Accuracy of Laser Navigation System using Particle Filter
Cho, Hyun-Hak ; Kim, Jung-Min ; Do, Joo-Cheol ; Kim, Sung-Shin ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 755~760
DOI : 10.5391/JKIIS.2011.21.6.755
This paper presents a method for improving the positioning accuracy of the laser navigation. As a wireless navigation system, the laser navigation which is more flexible than a wired guidance system is used for the localization and control of an AGV(automatic guided vehicle). However, the laser navigation causes the large positioning error while the AGV turns or moves fast. To solve the problem, we propose the method for improving the positioning accuracy of the laser navigation using particle filter which has robust and reliable performance in non-linear/non-gaussian systems. For the experiment, we use the actual fork-type AGV. The AGV has a gyro, two encoders and a laser navigation. To verify the performance, the proposed method is compared with the laser navigation which is a product. In the experimental result, we verified that the proposed method could improve the positioning accuracy by approximately 66.5%.
Constructing Tagged Corpus and Cue Word Patterns for Detecting Korean Hedge Sentences
Jeong, Ju-Seok ; Kim, Jun-Hyeouk ; Kim, Hae-Il ; Oh, Sung-Ho ; Kang, Sin-Jae ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 761~766
DOI : 10.5391/JKIIS.2011.21.6.761
A hedge is a linguistic device to express uncertainties. Hedges are used in a sentence when the writer is uncertain or has doubt about the contents of the sentence. Due to this uncertainty, sentences with hedges are considered to be non-factual. There are many applications which need to determine whether a sentence is factual or not. Detecting hedges has the advantage in information retrieval, and information extraction, and QnA systems, which make use of non-hedge sentences as target to get more accurate results. In this paper, we constructed Korean hedge corpus, and extracted generalized hedge cue-word patterns from the corpus, and then used them in detecting hedges. In our experiments, we achieved 78.6% in F1-measure.
Development of Inverter fault diagnostic algorithm based on CT for small-sized wind turbine system
Moon, Dae-Sun ; Kim, Sung-Ho ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 767~774
DOI : 10.5391/JKIIS.2011.21.6.767
In recent years, wind turbine system has been considered as the most efficient renewable energy source. Wind turbine system is a complex system which is composed of blade, generator and inverter systems. Recently, lots of researches on fault detection and diagnosis of wind turbine system have been done. Most of them are related with the fault diagnosis of mechanical elements using bivration signal. In this work, a new type of inverter fault detection and diagnstic algorithm is proposed. Furthermore, extensive simulation studies and practical experiments are carried out to verify the proposed algorithm.
A Study on Data Fusion of ARPA/AIS using Euclidean Distance
Kim, Young-Ki ; Park, Gyei-Kark ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 775~780
DOI : 10.5391/JKIIS.2011.21.6.775
GPS, ARPA, AIS, NAVTEX, VHF as modern aids-to-navigation equipments improve the safe navigation and help to reach a reduction in marine accidents by providing images, numeric values, texts, audio-based information for mates, However, we also noticed that it's complicate and difficult for a mate to acquire and analyze such information from these devices while he should devote himself to bridge watchkeeping especially in the urgent situation. Language is another way to get information and free the eyes and hands, so, to solve the problem above, we are trying to propose a new aids-to-navigation system, which can understand and merge multimedia marine safety information, analyze the situation and provide the necessary information in language. In this paper, we try to fuse data of ARPA/AIS using Euclidean distance for providing integrated information.
Filterness of Soft Sets
Park, Jin-Han ; Park, Yong-Beom ; Kwun, Young-Chel ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 781~785
DOI : 10.5391/JKIIS.2011.21.6.781
The notions of soft filters, ultra soft filters and bases of a soft filter are introduced and their basic properties are investigated. The adherence and convergence of soft filters in soft topological spaces with related results is also discussed.
Optimal EEG Feature Extraction using DWT for Classification of Imagination of Hands Movement
Chum, Pharino ; Park, Seung-Min ; Ko, Kwang-Eun ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 786~791
DOI : 10.5391/JKIIS.2011.21.6.786
An optimal feature selection and extraction procedure is an important task that significantly affects the success of brain activity analysis in brain-computer interface (BCI) research area. In this paper, a novel method for extracting the optimal feature from electroencephalogram (EEG) signal is proposed. At first, a student's-t-statistic method is used to normalize and to minimize statistical error between EEG measurements. And, 2D time-frequency data set from the raw EEG signal was extracted using discrete wavelet transform (DWT) as a raw feature, standard deviations and mean of 2D time-frequency matrix were extracted as a optimal EEG feature vector along with other basis feature of sub-band signals. In the experiment, data set 1 of BCI competition IV are used and classification using SVM to prove strength of our new method.
Rule-based Hybrid Discretization of Discrete Particle Swarm Optimization for Optimal PV System Allocation
Song, Hwa-Chang ; Ko, Jae-Hwan ; Choi, Byoung-Wook ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 6, 2011, Pages 792~797
DOI : 10.5391/JKIIS.2011.21.6.792
This paper discusses the application of a hybrid discretiziation method for the discretization procedure that needs to be included in discrete particle swarm optimization (DPSO) for the problem of allocating PV (photovoltaic) systems onto distribution power systems. For this purpose, this paper proposes a rule-based expert system considering the objective function value and its optimizing speed as the input parameters and applied it to the PV allocation problem including discrete decision variables. For multi-level discretization, this paper adopts a hybrid method combined with a simple rounding and sigmoid funtion based 3-step and 5-step quantization methods, and the application of the rule based expert system proposing the adequate discretization method at each PSO iteration so that the DPSO with the hybrid discretization can provide better performance than the previous DPSO.