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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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International Journal of Fuzzy Logic and Intelligent Systems
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Korean Institute of Intelligent Systems
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Volume & Issues
Volume 15, Issue 4 - Dec 2015
Volume 15, Issue 3 - Sep 2015
Volume 15, Issue 2 - Jun 2015
Volume 15, Issue 1 - Mar 2015
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Multiple Instance Mamdani Fuzzy Inference
Khalifa, Amine B. ; Frigui, Hichem ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 217~231
DOI : 10.5391/IJFIS.2015.15.4.217
A novel fuzzy learning framework that employs fuzzy inference to solve the problem of Multiple Instance Learning (MIL) is presented. The framework introduces a new class of fuzzy inference systems called Multiple Instance Mamdani Fuzzy Inference Systems (MI-Mamdani). In multiple instance problems, the training data is ambiguously labeled. Instances are grouped into bags, labels of bags are known but not those of individual instances. MIL deals with learning a classifier at the bag level. Over the years, many solutions to this problem have been proposed. However, no MIL formulation employing fuzzy inference exists in the literature. Fuzzy logic is powerful at modeling knowledge uncertainty and measurements imprecision. It is one of the best frameworks to model vagueness. However, in addition to uncertainty and imprecision, there is a third vagueness concept that fuzzy logic does not address quiet well, yet. This vagueness concept is due to the ambiguity that arises when the data have multiple forms of expression, this is the case for multiple instance problems. In this paper, we introduce multiple instance fuzzy logic that enables fuzzy reasoning with bags of instances. Accordingly, a MI-Mamdani that extends the standard Mamdani inference system to compute with multiple instances is introduced. The proposed framework is tested and validated using a synthetic dataset suitable for MIL problems. Additionally, we apply the proposed multiple instance inference to fuse the output of multiple discrimination algorithms for the purpose of landmine detection using Ground Penetrating Radar.
Design of Simple-Structured Fuzzy Logic Systems for Segway-Type Mobile Robot
Yoo, Hyun-Ho ; Choi, Byung-Jae ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 232~239
DOI : 10.5391/IJFIS.2015.15.4.232
Studies on the control of the inverted pendulum type system have been widely reported. This is because it is a typical complex nonlinear system and may be a good model for verifying the performance of a proposed control system. In this paper, we propose the design of some fuzzy logic control (FLC) systems for controlling a Segway-type mobile robot, which is an inverted pendulum type system. We first derive a dynamic model of the Segway-type mobile robot and then analyze it in detail. Next, we propose the design of some FLC systems that have good performance for the control of any nonlinear system. Then, we design two conventional FLC systems for the position and balance control of the Segway-type mobile robot, and we demonstrate their usefulness through simulations. Next, we point out the possibility of simplifying the design process and reducing the computational complexity,, which results from the skew symmetric property of the fuzzy control rule tables. Finally, we design two other FLC systems for position and balance control of the Segway-type mobile robot. These systems have only one input variable in the FLC systems. Furthermore, we observe that they offer similar control performance to that of the conventional two-input FLC systems.
Direct Adaptive Fuzzy Sliding Mode Control for Under-actuated Uncertain Systems
Su, Shun-Feng ; Hsueh, Yao-Chu ; Tseng, Cio-Ping ; Chen, Song-Shyong ; Lin, Yu-San ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 240~250
DOI : 10.5391/IJFIS.2015.15.4.240
The development of the control algorithms for under-actuated systems is important. Decoupled sliding mode control has been successfully employed to control under-actuated systems in a decoupling manner with the use of sliding mode control. However, in such a control scheme, the system functions must be known. If there are uncertainties in those functions, the control performance may not be satisfactory.In this paper, the direct adaptive fuzzy sliding mode control is employed to control a class of under-actuated uncertain systems which can be regarded as a combination of several subsystems with one same control input. By using the hierarchical sliding control approach, a sliding control law is derived so as to make every subsystem stabilized at the same time. But, since the system considered is assumed to be uncertain, the sliding control law cannot be readily facilitated. Therefore, in the study, based on Lyapunov stable theory a fuzzy compensator is proposed to approximate the uncertain part of the sliding control law. From those simulations, it can be concluded that the proposed compensator can indeed cope with system uncertainties. Besides, it can be found that the proposed compensator also provide good robustness properties.
Ship Detection Using Edge-Based Segmentation and Histogram of Oriented Gradient with Ship Size Ratio
Eum, Hyukmin ; Bae, Jaeyun ; Yoon, Changyong ; Kim, Euntai ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 251~259
DOI : 10.5391/IJFIS.2015.15.4.251
In this paper, a ship detection method is proposed; this method uses edge-based segmentation and histogram of oriented gradient (HOG) with the ship size ratio. The proposed method can prevent a marine collision accident by detecting ships at close range. Furthermore, unlike radar, the method can detect ships that have small size and absorb radio waves because it involves the use of a vision-based system. This system performs three operations. First, the foreground is separated from the background and candidates are detected using Sobel edge detection and morphological operations in the edge-based segmentation part. Second, features are extracted by employing HOG descriptors with the ship size ratio from the detected candidate. Finally, a support vector machine (SVM) verifies whether the candidates are ships. The performance of these methods is demonstrated by comparing their results with the results of other segmentation methods using eight-fold cross validation for the experimental results.
Android-Based E-Board Smart Education Platform Using Digital Pen and Dot Pattern
Cho, Young Im ; Altayeva, Aigerim Bakatkaliyevna ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 260~267
DOI : 10.5391/IJFIS.2015.15.4.260
In the past, we implemented a web-based smart education platform, but this is not efficient in a smart or mobile education environment. Therefore, in this paper, we propose an Android-based e-board smart platform for a smart or mobile education system. Here, we use Anoto digital pen- and dot pattern-based technologies. This Android-based smart education platform is efficient for a smart education environment. Further, we implement the hardware and software parts of the technologies, an Anoto-based trajectory recognition algorithm, and a probabilistic neural network for handwritten digit and hand gesture recognition.
Pattern Recognition of Ship Navigational Data Using Support Vector Machine
Kim, Joo-Sung ; Jeong, Jung Sik ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 268~276
DOI : 10.5391/IJFIS.2015.15.4.268
A ship's sailing route or plan is determined by the master as the decision maker of the vessel, and depends on the characteristics of the navigational environment and the conditions of the ship. The trajectory, which appears as a result of the ship's navigation, is monitored and stored by a Vessel Traffic Service center, and is used for an analysis of the ship's navigational pattern and risk assessment within a particular area. However, such an analysis is performed in the same manner, despite the different navigational environments between coastal areas and the harbor limits. The navigational environment within the harbor limits changes rapidly owing to construction of the port facilities, dredging operations, and so on. In this study, a support vector machine was used for processing and modeling the trajectory data. A K-fold cross-validation and a grid search were used for selecting the optimal parameters. A complicated traffic route similar to the circumstances of the harbor limits was constructed for a validation of the model. A group of vessels was composed, each vessel of which was given various speed and course changes along a specified route. As a result of the machine learning, the optimal route and voyage data model were obtained. Finally, the model was presented to Vessel Traffic Service operators to detect any anomalous vessel behaviors. Using the proposed data modeling method, we intend to support the decision-making of Vessel Traffic Service operators in terms of navigational patterns and their characteristics.
EEG Feature Classification Based on Grip Strength for BCI Applications
Kim, Dong-Eun ; Yu, Je-Hun ; Sim, Kwee-Bo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 277~282
DOI : 10.5391/IJFIS.2015.15.4.277
Braincomputer interface (BCI) technology is making advances in the field of humancomputer interaction (HCI). To improve the BCI technology, we study the changes in the electroencephalogram (EEG) signals for six levels of grip strength: 10%, 20%, 40%, 50%, 70%, and 80% of the maximum voluntary contraction (MVC). The measured EEG data are categorized into three classes: Weak, Medium, and Strong. Features are then extracted using power spectrum analysis and multiclass-common spatial pattern (multiclass-CSP). Feature datasets are classified using a support vector machine (SVM). The accuracy rate is higher for the Strong class than the other classes.
Chaotic Behavior in a Dynamic Love Model with Different External Forces
Bae, Youngchul ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 283~288
DOI : 10.5391/IJFIS.2015.15.4.283
In this paper, we propose a dynamic mathematical model of love involving various external forces, in order to analyze the chaotic phenomena in a love model based on Romeo and Juliet. In addition, we investigate the nonlinear phenomena in a love model with external forces using time series and phase portraits. In order to describe nonlinear phenomena precisely using time series and phase portraits, we vary the type of external force, using models such as a sine wave, chopping wave, and square wave. We also apply various different parameters in the Romeo and Juliet model to acquire chaotic dynamics.
Saliency Score-Based Visualization for Data Quality Evaluation
Kim, Yong Ki ; Lee, Keon Myung ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 289~294
DOI : 10.5391/IJFIS.2015.15.4.289
Data analysts explore collections of data to search for valuable information using various techniques and tricks. Garbage in, garbage out is a well-recognized idiom that emphasizes the importance of the quality of data in data analysis. It is therefore crucial to validate the data quality in the early stage of data analysis, and an effective method of evaluating the quality of data is hence required. In this paper, a method to visually characterize the quality of data using the notion of a saliency score is introduced. The saliency score is a measure comprising five indexes that captures certain aspects of data quality. Some experiment results are presented to show the applicability of proposed method.
Automatic Fortified Password Generator System Using Special Characters
Jeong, Junho ; Kim, Jung-Sook ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 295~299
DOI : 10.5391/IJFIS.2015.15.4.295
The developed security scheme for user authentication, which uses both a password and the various devices, is always open by malicious user. In order to solve that problem, a keystroke dynamics is introduced. A person's keystroke has a unique pattern. That allows the use of keystroke dynamics to authenticate users. However, it has a problem to authenticate users because it has an accuracy problem. And many people use passwords, for which most of them use a simple word such as "password" or numbers such as "1234." Despite people already perceive that a simple password is not secure enough, they still use simple password because it is easy to use and to remember. And they have to use a secure password that includes special characters such as "#!(
)^". In this paper, we propose the automatic fortified password generator system which uses special characters and keystroke feature. At first, the keystroke feature is measured while user key in the password. After that, the feature of user's keystroke is classified. We measure the longest or the shortest interval time as user's keystroke feature. As that result, it is possible to change a simple password to a secure one simply by adding a special character to it according to the classified feature. This system is effective even when the cyber attacker knows the password.
A Low Bit Rate Speech Coder Based on the Inflection Point Detection
Iem, Byeong-Gwan ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 300~304
DOI : 10.5391/IJFIS.2015.15.4.300
A low bit rate speech coder based on the non-uniform sampling technique is proposed. The non-uniform sampling technique is based on the detection of inflection points (IP). A speech block is processed by the IP detector, and the detected IP pattern is compared with entries of the IP database. The address of the closest member of the database is transmitted with the energy of the speech block. In the receiver, the decoder reconstructs the speech block using the received address and the energy information of the block. As results, the coder shows fixed data rate contrary to the existing speech coders based on the non-uniform sampling. Through computer simulation, the usefulness of the proposed technique is shown. The SNR performance of the proposed method is approximately 5.27 dB with the data rate of 1.5 kbps.
Fuzzy Logic Based Navigation for Multiple Mobile Robots in Indoor Environments
Zhao, Ran ; Lee, Dong Hwan ; Lee, Hong Kyu ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 4, 2015, Pages 305~314
DOI : 10.5391/IJFIS.2015.15.4.305
The work presented in this paper deals with a navigation problem for multiple mobile robot system in unknown indoor environments. The environment is completely unknown for all the robots and the surrounding information should be detected by the proximity sensors installed on the robots' bodies. In order to guide all the robots to move along collision-free paths and reach the goal positions, a navigation method based on the combination of a set of primary strategies has been developed. The indoor environments usually contain convex and concave obstacles. In this work, a danger judgment strategy in accordance with the sensors' data is used for avoiding small convex obstacles or moving objects which include both dynamic obstacles and other robots. For big convex obstacles or concave ones, a wall following strategy is designed for dealing with these special situations. In this paper, a state memorizing strategy is also proposed for the "infinite repetition" or "dead cycle" situations. Finally, when there is no collision risk, the robots will be guided towards the targets according to a target positioning strategy. Most of these strategies are achieved by the means of fuzzy logic controllers and uniformly applied for every robot. The simulation experiments verified that the proposed method has a positive effectiveness for the navigation problem.