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A central problem of fuzzy modelling is the generation of fuzzy rules that fit the data to the highest possible extent. In this study, we present a method for automatic generation of fuzzy rules from data. The main advantage of the proposed method is its ability to perform data clustering without the requirement of predefining any parameters including number of clusters. The proposed method creates...
It was noted earlier that the accuracy of defect diagnosis may be improved if certain tests are removed from consideration by the defect diagnosis procedure. This paper observes that the effects, which support the removal of tests, also support the removal of observable outputs from consideration during defect diagnosis. Specifically, a test may create an output response that a defect diagnosis procedure...
This paper focuses on a RFID-Based dynamic positioning scheme, aiming to locate an object by using a moving RFID reader and reference tags without recording any measurement data, e.g., the time of arrival (TOA) of the signal, or the received signal strength indication (RSSI). To address the problem of blindness of location path, a RFID-based positioning scheme with MATLAB GUI, is proposed based on...
The problem of sampling a signal with interval T is present in preparing continuous-time processes for discrete-time signal processing algorithms and in down-sampling a discrete-time signal to a larger time scale. The important issue is whether invariance in time or in frequency domain is preferred. The time domain approach preserves the covariance function at time shifts KT, while the frequency domain...
A key issue in system identification is how to cope with high system complexity. In this contribution we stress the importance of taking the application into account in order to cope with this issue. We define the concept “cost of complexity” which is a measure of the minimum required experimental effort (e.g. used input energy) as a function of the system complexity, the noise properties, and the...
The aim of this paper is to propose a general methodology to improve the linguistic-accuracy trade-off of fuzzy models, applicable to any rule-based fuzzy model. Here, the neuro-fuzzy system FasArt (Fuzzy Adaptive System ART based) is used to obtain rule-based fuzzy models, as shown in previous papers and works. FasArt, however, has the usual drawbacks, from the linguistic point of view, of most (precise)...
In order to enhance the accuracy of the dynamic equivalence of wind farm (WF) under different wind conditions (WCs), this paper proposed a Dynamic Multi-Turbine Multi-State (DMTMS) Model of WF based on the historical wind data. The proposed model could represent the dynamic characteristics of WF under different WCs with high accuracy. Support vector clustering (SVC), whose cluster partition is completed...
Personalization and adaptation are at the core of Intelligent Tutoring Systems. The Bayesian Knowledge Tracing (BKT) Student Model is a time-tested method that maintains information about students' knowledge levels for the different skills in the topic domain. In our previous work, we had proposed the Personalized, Clustered, Bayesian Knowledge Tracing (PC-BKT) model that individualizes the learning...
Over recent years, the world has experienced a huge growth in the volume of shared web texts. Its users generate daily a huge volume of comments and reviews related to different aspects of their lives. In general, opinion mining/sentiment analysis refers to the task of identifying positive and negative opinions, emotions and evaluations related to an article, news, products, services, etc [1]. Arabic...
Mobility-aware cloud services such as fleet management systems need to understand the positions of mobile devices accurately in a real-time manner. Generally speaking, positioning accuracy and data traffic load are in a trade-off relation. Highly accurate real-time positioning requires frequent location data upload and hence results in heavy data traffic load. Although not all data are equally important,...
EIT is a simple and robust imaging technique that is vastly applied for both medical and industrial process imaging. One of the biggest influencing factors in deciding the accuracy of the reconstructed image lies in the model. As EIT is an underdetermined, nonlinear system, if the number of elements in a discretized model that needs to be solved becomes too large, and the number of available measurements...
Introduction: The ECG Bayesian filtering framework has been shown to be a promising method to extract the foetal electrocardiogram (FECG) from abdominal recordings. This framework requires an estimation of the ECG morphology, which is obtained by approximating an average beat with a number of Gaussian kernels. This approximation results in a high dimensional nonlinear optimization problem (finding...
Percussion instruments play a significant role in Carnatic music concerts. The percussion artist enjoys a great degree of freedom in improvising within the defined tāla structure of a composition. The objective of this paper is to transcribe the improvisations, treating the percussion strokes as syllables or aksharas.
Online dynamic security assessment involves analyzing the effect of a large number of contingencies in a short time. This is a computationally demanding task, and use of energy function method reduces the computational burden. Energy function method involves determination of a quantity called critical energy which requires system simulation for a short duration. In spite of the use of energy function...
This paper proposes a method to identify the arohana-avarohana of carnatic raga. Carnatic raga is broadly classified as melakarta (parent) and janya (child) raga. Arohana-avarohana of 10 different ragas is collected from 16 different singers. 16 audio data are collected for each raga. 11 among the 16 are used in the training phase and the remaining 5 are used for testing. The acoustic feature, MFCC...
Online reviews evolve rapidly over time, which demands much more efficient and flexible algorithms for sentiment analysis than the current approaches. Current approaches detect the overall sentiment of a document, without performing an in-depth analysis to discover. We propose a Document level sentiment classification in conjunction with topic detection and topic sentiment analysis of bigrams simultaneously...
In this paper we propose a novel spatially stratified sampling technique for evaluating the likelihood function in particle filters. In particular, we show that in the case where the measurement function uses spatial correspondence, we can greatly reduce computational cost by exploiting spatial structure to avoid redundant computations. We present results which quantitatively show that the technique...
In this work we address the problem of design of an efficient Recommender system based on collaborative filtering framework which achieves improved accuracy with reduced computational complexity and shorter run times. This work is based on representing the low rank constraint as the Ky-Fan norm instead of the commonly employed nuclear norm term. Our formulation uses majorization minimization approach...
In this paper, we develop a novel framework for action recognition in videos. The framework is based on automatically learning the discriminative trajectory groups that are relevant to an action. Different from previous approaches, our method does not require complex computation for graph matching or complex latent models to localize the parts. We model a video as a structured bag of trajectory groups...
Diagnosis is an important task in medical science because of its criticality, efficiency and accuracy in determining whether or not a patient has a particular disease. This shall further decide the most suitable line of treatment. There has been a large increase in the number of thyroid cases over the past few years. Since thyroid has a complex relation with metabolism and body weight, it is extremely...
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