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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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Online Selective-Sample Learning of Hidden Markov Models for Sequence Classification
Kim, Minyoung ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 3, 2015, Pages 145~152
DOI : 10.5391/IJFIS.2015.15.3.145
We consider an online selective-sample learning problem for sequence classification, where the goal is to learn a predictive model using a stream of data samples whose class labels can be selectively queried by the algorithm. Given that there is a limit to the total number of queries permitted, the key issue is choosing the most informative and salient samples for their class labels to be queried. Recently, several aggressive selective-sample algorithms have been proposed under a linear model for static (non-sequential) binary classification. We extend the idea to hidden Markov models for multi-class sequence classification by introducing reasonable measures for the novelty and prediction confidence of the incoming sample with respect to the current model, on which the query decision is based. For several sequence classification datasets/tasks in online learning setups, we demonstrate the effectiveness of the proposed approach.
Latent Keyphrase Extraction Using Deep Belief Networks
Jo, Taemin ; Lee, Jee-Hyong ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 3, 2015, Pages 153~158
DOI : 10.5391/IJFIS.2015.15.3.153
Nowadays, automatic keyphrase extraction is considered to be an important task. Most of the previous studies focused only on selecting keyphrases within the body of input documents. These studies overlooked latent keyphrases that did not appear in documents. In addition, a small number of studies on latent keyphrase extraction methods had some structural limitations. Although latent keyphrases do not appear in documents, they can still undertake an important role in text mining because they link meaningful concepts or contents of documents and can be utilized in short articles such as social network service, which rarely have explicit keyphrases. In this paper, we propose a new approach that selects qualified latent keyphrases from input documents and overcomes some structural limitations by using deep belief networks in a supervised manner. The main idea of this approach is to capture the intrinsic representations of documents and extract eligible latent keyphrases by using them. Our experimental results showed that latent keyphrases were successfully extracted using our proposed method.
Ranking Tag Pairs for Music Recommendation Using Acoustic Similarity
Lee, Jaesung ; Kim, Dae-Won ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 3, 2015, Pages 159~165
DOI : 10.5391/IJFIS.2015.15.3.159
The need for the recognition of music emotion has become apparent in many music information retrieval applications. In addition to the large pool of techniques that have already been developed in machine learning and data mining, various emerging applications have led to a wealth of newly proposed techniques. In the music information retrieval community, many studies and applications have concentrated on tag-based music recommendation. The limitation of music emotion tags is the ambiguity caused by a single music tag covering too many subcategories. To overcome this, multiple tags can be used simultaneously to specify music clips more precisely. In this paper, we propose a novel technique to rank the proper tag combinations based on the acoustic similarity of music clips.
Analysis of Fault Diagnosis for Current and Vibration Signals in Pumps and Motors using a Reconstructed Phase Portrait
Jung, Young-Ok ; Bae, Youngchul ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 3, 2015, Pages 166~171
DOI : 10.5391/IJFIS.2015.15.3.166
In this paper, we measure the current and vibration signals of one-dimensional time series that occur in a motor and pump, respectively. These machines are representative rotary and pumping machines. We also eliminate unnecessary components such as noise by pre-processing the current and vibration signals. Then, in order to diagnose fault signals for the pump and motor, we transform from one-dimensional time series to a two-dimensional phase portrait using Takens’ embedding method. After this transformation, we review the variation in the pattern according to the fault signals.
Exploring Image Processing and Image Restoration Techniques
Omarov, Batyrkhan Sultanovich ; Altayeva, Aigerim Bakatkaliyevna ; Cho, Young Im ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 3, 2015, Pages 172~179
DOI : 10.5391/IJFIS.2015.15.3.172
Because of the development of computers and high-technology applications, all devices that we use have become more intelligent. In recent years, security and surveillance systems have become more complicated as well. Before new technologies included video surveillance systems, security cameras were used only for recording events as they occurred, and a human had to analyze the recorded data. Nowadays, computers are used for video analytics, and video surveillance systems have become more autonomous and automated. The types of security cameras have also changed, and the market offers different kinds of cameras with integrated software. Even though there is a variety of hardware, their capabilities leave a lot to be desired. Therefore, this drawback is trying to compensate by dint of computer program solutions. Image processing is a very important part of video surveillance and security systems. Capturing an image exactly as it appears in the real world is difficult if not impossible. There is always noise to deal with. This is caused by the graininess of the emulsion, low resolution of the camera sensors, motion blur caused by movements and drag, focus problems, depth-of-field issues, or the imperfect nature of the camera lens. This paper reviews image processing, pattern recognition, and image digitization techniques, which will be useful in security services, to analyze bio-images, for image restoration, and for object classification.
Automatic Intelligent Asymmetry Detection Using Digital Infrared Imaging with K-Means Clustering
Kim, Kwang Baek ; Song, Doo Hoen ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 3, 2015, Pages 180~185
DOI : 10.5391/IJFIS.2015.15.3.180
Digital infrared thermal imaging is a non-invasive adjunctive diagnostic technique that allows an examiner to visualize and quantify changes in skin surface temperature. The asymmetry of temperature differences between the diseased and the contralateral healthy body parts can be automatically analyzed and has been studied in many areas of medical science. In this paper, we propose a method for intelligent automatic asymmetry detection based on a K-means analysis and a YCbCr color model. The implemented software successfully visualizes an asymmetric distribution of colors with respect to the patients’ health status.
Hand Gesture Recognition Using an Infrared Proximity Sensor Array
Batchuluun, Ganbayar ; Odgerel, Bayanmunkh ; Lee, Chang Hoon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 3, 2015, Pages 186~191
DOI : 10.5391/IJFIS.2015.15.3.186
Hand gesture is the most common tool used to interact with and control various electronic devices. In this paper, we propose a novel hand gesture recognition method using fuzzy logic based classification with a new type of sensor array. In some cases, feature patterns of hand gesture signals cannot be uniquely distinguished and recognized when people perform the same gesture in different ways. Moreover, differences in the hand shape and skeletal articulation of the arm influence to the process. Manifold features were extracted, and efficient features, which make gestures distinguishable, were selected. However, there exist similar feature patterns across different hand gestures, and fuzzy logic is applied to classify them. Fuzzy rules are defined based on the many feature patterns of the input signal. An adaptive neural fuzzy inference system was used to generate fuzzy rules automatically for classifying hand gestures using low number of feature patterns as input. In addition, emotion expression was conducted after the hand gesture recognition for resultant human-robot interaction. Our proposed method was tested with many hand gesture datasets and validated with different evaluation metrics. Experimental results show that our method detects more hand gestures as compared to the other existing methods with robust hand gesture recognition and corresponding emotion expressions, in real time.
Comparison of Radio Wave Propagation Models for Mobile Networks
Altayeva, Aigerim Bakatkaliyevna ; Cho, Young Im ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 3, 2015, Pages 192~199
DOI : 10.5391/IJFIS.2015.15.3.192
Heterogeneous cellular networks are gaining momentum in industry and the research community, and are attracting the attention of standard bodies such as 3GPP LTE and IEEE 802.16j, whose objectives are to increase the capacity and coverage of cellular networks. In this article, we provide an overview of expansion strategies, optimal locations of base stations with different characteristics, and radio-planning models.
Observer-Based FL-SMC Active Damping for Back-to-Back PWM Converter with LCL Grid Filter
Gwon, Jin-Su ; Lee, Hansoo ; Kim, Sungshin ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 3, 2015, Pages 200~207
DOI : 10.5391/IJFIS.2015.15.3.200
This paper proposes an active damping control method for a grid-side converter that has an LCL grid filter in the back-to-back converter. To remove the resonant frequency components produced by the LCL filter, it is necessary to measure the grid current. To do this, sensors must be added. However, it is not necessary to add sensors because the grid current is estimated by designing a suboptimal observer. In order to remove the nonlinearity and to gain fast response of control, both feedback linearization and sliding mode control are applied. The proposed method is verified through a simulation.
Intuitionistic Fuzzy Rough Approximation Operators
Yun, Sang Min ; Lee, Seok Jong ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 15, issue 3, 2015, Pages 208~215
DOI : 10.5391/IJFIS.2015.15.3.208
Since upper and lower approximations could be induced from the rough set structures, rough sets are considered as approximations. The concept of fuzzy rough sets was proposed by replacing crisp binary relations with fuzzy relations by Dubois and Prade. In this paper, we introduce and investigate some properties of intuitionistic fuzzy rough approximation operators and intuitionistic fuzzy relations by means of topology.