]>
2014
12
3
79
Speech Emotion Recognition Based on Learning Automata in Fuzzy Petri-net
Speech Emotion Recognition Based on Learning Automata in Fuzzy Petri-net
en
en
This paper explores how fuzzy features’ number and reasoning rules can influence the rate of emotional speech recognition. The speech emotion signal is one of the most effective and neutral methods in individuals’ relationships that facilitate communication between man and machine. This paper introduces a novel method based on mind inference and recognition of speech emotion recognition. The foundation of the proposed method is the inference of rules in Fuzzy Petri-net (FPN) and the learning automata. FPN is a new method of classification which is introduced for the first time on emotion speech recognition. This method helps to analyze different rules in a dynamic environment like human’s mind. The input of FPN is computed by learning automata. Therefore learning automata has been used to adjust the membership functions for each feature vector in the dynamic environment. The proposed algorithm is divided into different parts: preprocessing; feature extraction; learning automata; fuzzification; inference engine and defuzzification. The proposed model has been compared with different models of classification. Experimental results show that the proposed algorithm outperforms other models.
173
185
Sara
Motamed
Saeed
Setayeshi
Zeinab
Farhoudi
Ali
Ahmadi
Emotional Speech
Fuzzy Rules
Learning Automata
Mel frequency Cepstral coefficients (MFCC)
Fuzzy Petri-net.
Article.1.pdf
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[1]
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]
T-rough Fuzzy Subgroups of Groups
T-rough Fuzzy Subgroups of Groups
en
en
The rough set theory was introduced by Pawlak in 1982. It was proposed for presentation equivalence relations. But the concept of fuzzy set was introduced by Zadeh in 1965. In this paper,the concepts of the rough sets,T-rough sets,T-rough fuzzy sets, T-rough fuzzy subgroups, T-rough fuzzy ideals, and set-valued homomorphism of groups will be given. A necessery and sufficient condition for a fuzzy subgroup(ideal) and fuzzy prime ideal of a group under a set-valued homomorphism to be a T-rough fuzzy subgroup(ideal) and T-rough fuzzy prime ideal is stated. The purpose of this paper is to introduce and discuss the concept of T-rough fuzzy groups of groups that those have been proved in several papers. Also, we proved that intersection two fuzzy subgroups(ideals) of a set under a set-valued homomorphism is a T-rough fuzzy subgroup of other set.
186
195
Eshagh
Hosseinpour
Approximation space
T-rough set
T-rough fuzzy set
Fuzzy subgroups
Fuzzy ideals
set-valued homomorphism.
Article.2.pdf
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]
A Generalization of Iteration-free Search Vectors of Abs Methods
A Generalization of Iteration-free Search Vectors of Abs Methods
en
en
Recently, we introduced iteration-free search vectors of the ABS methods and showed how they can be used to compute the search directions of primal--dual interior point methods, when the coefficient matrix of the constraints of the linear programming problem is square. Here, we generalize those results for the general case when, the coefficient matrix is non-square.
196
200
Mostafa
Khorramizadeh
Interior point methods
Infeasible interior pointmethods
Primal--dual algorithms
ABS algorithms
Searchdirection.
Article.3.pdf
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]
Structural Cryptanalysis of the Message Based Random Variable Length Key Encryption Algorithm (mrvlk)
Structural Cryptanalysis of the Message Based Random Variable Length Key Encryption Algorithm (mrvlk)
en
en
This article has presented a Structural cryptanalysis on MRVLK (Message Based Random Variable Length Key Encryption). In this cipher, key length is started from small amount of bits and then will be grown in size. The cipher has variable rounds, random bitwise rotations and dynamic key length that provide resistance to linear and differential cryptanalysis. In spite of these advantages, some disadvantages are observed such as correlation between the ciphertexts in each stage which facilitates structural attack. Even random mechanism such as S-box in this cipher cannot prevent this attack. The attack performs analysis on the final ciphertext and reveals the plaintext of MRVLK by exploiting the fact that the structure of the ciphertext is obvious and weak. The presented attack efficiently utilizes this information and prompts the operations cryptanalysis. Performance of this attack is evaluated in terms of running time. The results show that the original plaintext is achievable to minimal cost.
201
210
Azam
Davahli
Hamid
Mirvaziri
Media
Aminian
Cryptanalysis
Block Cipher
MRVLK
Structural Attack
Random key.
Article.4.pdf
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Pushpendra Pardeep, Kumar Pateriya, PC1-RC4 and PC2-RC4 Algorithms: Pragmatic Enrichment Algorithms to Enhance RC4 Stream Cipher Algorithm, International Journal of Computer Science and Network, 1(3) (2012), 1-36
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M. Khorsi, A. Bozorgi-Amiri, B. Ashjari, A Nonlinear Dynamic Logistics Model for Disaster Response under Uncertainty, Journal of Mathematics and Computer Science, 7(1) (2013), 63-72
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J. Biazar, M. Hosami, Two Efficient Approaches based on Radial Basis Functions to Nonlinear Time-dependent Partial Differential Equations, Journal of Mathematics and Computer Science, 9(1) (2014), 1-11
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]
Attribute Based Level Adaptive Thresholding Algorithm (ablata) for Image Compression and Transmission
Attribute Based Level Adaptive Thresholding Algorithm (ablata) for Image Compression and Transmission
en
en
Image processing plays a vital role in the computer vision because most of the scenarios require object extraction and recognition. But there lies a self-concatenated issue with it because such an algorithm is also supposed to simultaneously solves the problem of image restoration and transmission. In order to achieve this objective we furthered the effective ABLATA algorithm for the same Once the image is denoised and features are extracted then it can be resized to the half of the actual image, compressing it in a mathematical equation that shall help it restore with the half of the data and thus can readily be restored with the half of the actual imagery data to reproduce it, while maintaining the high image quality. The advantage of such a process is the low storage cost and image transmission requires less time than that required by the original one.
211
218
Ankush
Rai
Computer Vision
Object Extraction
Image denoising Image Compression
Transmission.
Article.5.pdf
[
[1]
Yang Wang, Haomin Zhou, Total Variation Wavelet-Based Medical Image Denoising, International Journal of Biomedical Imaging, 2006 (2006), 1-6
##[2]
Ahmed Badawi, Scatterer Density in Nonlinear Diffusion for Speckle Reduction in Ultrasound Imaging: The Isotropic Case, International Journal of Biological and Life Sciences, 2 (2006), 149-167
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Fernanda Palhano, Xavier de Fontes, Guillermo Andrade Barroso, Pierre Hellier, Real time ultrasound image denoising, Journal of Real-Time Image Processing, 1 (2010), 15-22
##[4]
Shujun Fu, Qiuqi Ruan, Wenqia Wang, Yu Li, Feature Preserving Nonlinear Diffusion for Ultrasonic Image Denoising and Edge Enhancement, World Academy of Science, Engineering and Technology, 2 (2005), 148-151
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Tanaphol Thaipanich, Jay Kuo, An Adaptive Nonlocal Means Scheme for Medical Image Denoising, In Proceedings of SPIE Medical Imaging, Vol. 7623, San Diego, CA, USA (2010)
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Su Cheol Kang, Seung Hong Hong, A Speckle Reduction Filter using Wavelet- Based Methods for Medical Imaging Application, In Proceedings of 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Istanbul, Turkey, 3 (2001), 2480-2483
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Jose V. Manjón, Neil A. Thacker, Juan J. Lull, Gracian Garcia-Marti, Luis Marti-Bonmati, Montserrat Robles, Multicomponent MR Image Denoising, Journal of Biomedical Imaging, 2009 (2009), 1-27
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Robles Manjon, Thacker, Multispectral MRI de-noising using non-local means, In Proceedings of MIUA, Aberystwyth, (2007), 41-46
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##[11]
Seyyed Mohammad Reza Farshchi, Mahdi Yaghoobi, A Novel Fuzzy Expert System Using Image Processing for Sale Car Shape with Online Membership Function, Journal of Mathematics and Computer Science (JMCS), 2 (2011), 222-232
##[12]
Moslem Taghizadeh, Mohammad Reza Mahzoun , Bidirectional Image Thresholding algorithm using combined Edge Detection and P-Tile algorithms, Journal of Mathematics and Computer Science (JMCS), 2 (2011), 255-261
##[13]
Khosro Jalali, Mostafa Heydari, Asma Tanavar, Image Segmentation with Improved Distance Measure in SOM and K Means Algorithms, Journal of Mathematics and Computer Science (JMCS) , 8 (2014), 367-376
##[14]
J. Vahidi, M. Gorji, The Confusion-Diffusion Image Encryption Algorithm with Dynamical Compound Chaos, Journal of Mathematics and Computer Science (JMCS), 9 (2014), 451-457
##[15]
Ankush Rai, Attribute Based Level Adaptive Thresholding Algorithm for Object Extraction, Journal of Advancement in Robotics, 1 (2014), 29-33
]
Compact Topological Semigroups Associated with Oids
Compact Topological Semigroups Associated with Oids
en
en
The known theory for a discrete oid \(T\) shows that how to find a subset \(T^{\infty}\) of \(\beta T\) which is a compact right topological semigroup (see section 2 for details).In this paper we try to find an analogue of almost periodic functions for oids. We discover, new compact semigroups by using a certain subspace of functions \(u^{\infty}(T)\) of \(C(T)\) for an oid \(T\) for which \(f\beta\) is continuous on \(T^{\infty}\times(T\cup T^{\infty}\cup TT^{\infty})\),where \((T\cup T^{\infty}\cup TT^{\infty})\) is a suitable subspace of \(\beta T\) for a wide range.
219
234
Abdol Mohammad
Aminpour
Mehrdad
Seilani
Oid
Jointly continuous function
Compact topological semigroup.
Article.6.pdf
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]
Fuzzy Adaptive Pso Approach for Portfolio Optimization Problem
Fuzzy Adaptive Pso Approach for Portfolio Optimization Problem
en
en
The mean-variance model of Markowitz is the most common and popular approach in the investment selection; besides, the mathematical planning model proposed by Markowitz is the most effective method of the optimal portfolio selection. However, if there are a lot of investing assets and a lot of market’s restrictions, the common optimizing methods are not useful. Moreover, the portfolio optimization problem cannot be solved easily by applying the mathematical methods. In the present study, the heuristic Fuzzy Adaptive Particle Swarm Optimization (PSO) method is proposed to solve three highly applied models of the portfolio problem. Therefore, to fulfil this task the efficient frontier of the investment is drawn by applying the price information of the 50 shares accepted in Tehran stock market from October of 2009 to October of 2013. Results of this study manifest the efficiency of the used method in relation to other heuristic methods.
235
242
M.
Soleimanivareki
A. Fakharzadeh
J.
M.
Poormoradi
portfolio optimization
fuzzy adaptive particle swarm optimization
mean-variance model
the efficient frontier
Article.7.pdf
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Aspect-oriented Software Maintainability Assessment Using Adaptive Neuro Fuzzy Inference System (anfis)
Aspect-oriented Software Maintainability Assessment Using Adaptive Neuro Fuzzy Inference System (anfis)
en
en
Aspect-oriented development is a relatively new approach that emphasizes dealing with crosscutting concerns. In aspect-oriented programming, concern networks and requirement networks are independent and can easily be added to or removed from a model of system; therefore maintenance and modifying in aspect-oriented system models are easier than object-oriented ones. Software maintenance is an important activity in software development and one of the most expensive activities. Also, its vagueness in prediction at early stage of development makes the process more complex. Researchers and developers are working on devising various techniques/ algorithms for better prediction. The aim of the paper is to show that ANFIS can more accurately predict maintainability as compared to other models such as Fuzzy Logic. For this we selected four metrics and used them for training, testing and validation.
243
252
Hossein
Momeni
Shiva
Zahedian
Maintainability
Assessment
Fuzzy Logic
Adaptive Neuro Fuzzy Inference System (ANFIS)
Aspect-Oriented
maintenance.
Article.8.pdf
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