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Combination of harmony search and linear discriminate analysis to improve classification
, Article 2009 3rd Asia International Conference on Modelling and Simulation, AMS 2009, Bandung, Bali, 25 May 2009 through 26 May 2009 ; 2009 , Pages 131-135 ; 9780769536484 (ISBN) ; Asgarian, E ; Zanjani, M ; Rezaee, A ; Seidi, M ; Universitas Katolik Parahyangan; Nottingham Trent University; UKSim; IEEE Computer Society; Asia Modelling and Simulation Society, AMSS ; Sharif University of Technology
2009
Abstract
An appropriate pre-processing algorithm in classification is not only of great importance with respect to classifier choice, but also would be more crucial. In this paper, a pre-processing step is proposed in order to increase accuracy of classification. The aim of this approach is finding a transformation matrix causes classes to be more discriminable by transforming data into the new space and consequently, increases the classification accuracy. This transformation matrix is computed through two methods based on linear discrimination. In the first method, we use class independent LDA to increase classification accuracy by finding a transformation that maximizes the between-class scatter...
An integrated software environment for finite element simulation of powder compaction processes
, Article Journal of Materials Processing Technology ; Volume 130-131 , 2002 , Pages 168-174 ; 09240136 (ISSN) ; Sharif University of Technology
2002
Abstract
In this paper, an integrated software environment is demonstrated for computational simulation of powder forming processes. The powder compaction software, PCS_SUT, is designed in both popularity and functionality with the development of user-friendly pre- and post-processing software. Pre-processing software is used to create the model, generate an appropriate finite element grid, apply the appropriate boundary conditions, and view the total model. Post-processing provides visualization of the computed results. In PCS_SUT, a numerical model is developed based on a Lagrangian finite element formulation for large deformations, a cap plasticity theory for non-linear behaviour of material, and...
PCS_SUT: A finite element software for simulation of powder forming processes
, Article Journal of Materials Processing Technology ; Volume 125-126 , 2002 , Pages 602-607 ; 09240136 (ISSN) ; Sharif University of Technology
2002
Abstract
As product complexity increases and economic constraints result in a demand for greater efficiency, industry must invest in new innovative ways to assist design and manufacture. As a first step in the long-term development of such a system, a computer software environment has been developed for pre- and post-processing for unstructured grid-based computational simulation. This paper describes the powder compaction software (PCS_SUT), which is designed for pre- and post-processing for computational simulation of the compaction of powder. Pre-processing software is used to create the model, generate an appropriate finite element grid, apply the appropriate boundary conditions, and view the...
Novel approaches for online modal estimation of power systems using PMUs data contaminated with outliers
, Article Electric Power Systems Research ; Volume 124 , July , 2015 , Pages 74-84 ; 03787796 (ISSN) ; Hatami, M ; Parniani, M ; Sharif University of Technology
Elsevier Ltd
2015
Abstract
One of the most important issues in modal estimation of power systems using PMUs data is the negative effect of outliers. Hence, in addition to the techniques of analyzing PMUs data, the necessity of implementing some kinds of approach to overcome these outliers is tangible. This paper aims to present different approaches to overcome outliers and also estimate the electromechanical modes of the system accurately when there is suspicion that the PMUs data may be contaminated by discordant measurements. Proposed approaches are generally categorized into two main classifications: the first category detects and modifies outliers in the pre-processing stage adaptively and then prepares the...
Enhancing physionet electrocardiogram records for fetal heart rate detection algorithm
, Article Proceedings - 2015 2nd International Conference on Biomedical Engineering, ICoBE 2015 ; 2015 ; 9781479917495 (ISBN) ; Ali, M. A. M ; Zahedi, E ; Sharif University of Technology
Abstract
The noninvasive fetal electrocardiogram (ECG) data available from Physionet data bank are suitable for developing fetal heart rate (FHR) detection algorithms. The data have been collected from single subject with a broad range of gestation weeks, and have a total data length of more than 9 hours arranged in 55 data sets. However, there are three additional data features which are currently not directly available from Physionet to facilitate the easy usage of these data: (1) the fetal peak visibility evaluation, (2) the gestation week, and (3) the data length. This article presents an improvement to the data bank by providing the additional features. The required pre-processing of the data is...
ITSAT: An efficient SAT-based temporal planner
, Article Journal of Artificial Intelligence Research ; Volume 53 , 2015 , Pages 541-632 ; 10769757 (ISSN) ; Ghassem Sani, G ; Sharif University of Technology
AI Access Foundation
2015
Abstract
Planning as satisfiability is known as an efficient approach to deal with many types of planning problems. However, this approach has not been competitive with the state-space based methods in temporal planning. This paper describes ITSAT as an efficient SAT-based (satisfiability based) temporal planner capable of temporally expressive planning. The novelty of ITSAT lies in the way it handles temporal constraints of given problems without getting involved in the difficulties of introducing continuous variables into the corresponding satisfiability problems. We also show how, as in SAT-based classical planning, carefully devised preprocessing and encoding schemata can considerably improve the...
Pixel-level alignment of facial images for high accuracy recognition using ensemble of patches
, Article Journal of the Optical Society of America A: Optics and Image Science, and Vision ; Volume 35, Issue 7 , 2018 , Pages 1149-1159 ; 10847529 (ISSN) ; Sayyafan, A ; Ghojogh, B ; Sharif University of Technology
OSA - The Optical Society
2018
Abstract
The variation of pose, illumination, and expression continues to make face recognition a challenging problem. As a pre-processing step in holistic approaches, faces are usually aligned by eyes. The proposed method tries to perform a pixel alignment rather than eye alignment by mapping the geometry of faces to a reference face while keeping their own textures. The proposed geometry alignment not only creates a meaningful correspondence among every pixel of all faces, but also removes expression and pose variations effectively. The geometry alignment is performed pixel-wise, i.e., every pixel of the face is corresponded to a pixel of the reference face. In the proposed method, the information...
Designing a deep neural network model for finding semantic similarity between short persian texts using a parallel corpus
, Article 7th International Conference on Web Research, ICWR 2021, 19 May 2021 through 20 May 2021 ; 2021 , Pages 91-96 ; 9781665404266 (ISBN) ; Tabatabayiseifi, S ; Izadi, M ; Tavakoli, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
Text processing, as one of the main issues in the field of artificial intelligence, has received a lot of attention in recent decades. Numerous methods and algorithms are proposed to address the task of semantic textual similarity which is one of the sub-branches of text processing. Due to the special features of the Persian language and its non-standard writing system, finding semantic similarity is an even more challenging task in Persian. On the other hand, producing a proper corpus that can be used for training a model for finding semantic similarities, is of great importance. In this study, the main purpose is to propose a method for measuring the semantic similarity between short...
Nonrigid registration of breast MR images using residual complexity similarity measure
, Article Iranian Conference on Machine Vision and Image Processing, MVIP, Zanjan ; Sept , 2013 , Pages 241-244 ; 21666776 (ISSN); 9781467361842 (ISBN) ; Ghaffari, A ; Fatemizadeh, E ; Sharif University of Technology
IEEE Computer Society
2013
Abstract
Elimination of motion artifact in breast MR images is a significant issue in pre-processing step before utilizing images for diagnostic applications. Breast MR Images are affected by slow varying intensity distortions as a result of contrast agent enhancement. Thus a nonrigid registration algorithm considering this effect is needed. Traditional similarity measures such as sum of squared differences and cross correlation, ignore the mentioned distortion. Therefore, efficient registration is not obtained. Residual complexity is a similarity measure that considers spatially varying intensity distortions by maximizing sparseness of the residual image. In this research, the results obtained by...
Linear discourse segmentation of multi-party meetings based on local and global information
, Article IEEE/ACM Transactions on Speech and Language Processing ; Volume 23, Issue 11 , July , 2015 , Pages 1879-1891 ; 23299290 (ISSN) ; Sameti, H ; Liu, Y ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2015
Abstract
Linear segmentation of a meeting conversation is beneficial as a stand-alone system (to organize a meeting and make it easier to access) or as a preprocessing step for many other meeting related tasks. Such segmentation can be done according to two different criteria: topic in which a meeting is segmented according to the different items in its agenda, and function in which the segmentation is done according to the meeting's different events (like discussion, monologue). In this article we concentrate on the function segmentation task and propose new unsupervised methods to segment a meeting into functionally coherent parts. The first proposed method assigns a score to each possible boundary...
Critical object recognition in millimeter-wave images with robustness to rotation and scale
, Article Journal of the Optical Society of America A: Optics and Image Science, and Vision ; Volume 34, Issue 6 , 2017 , Pages 846-855 ; 10847529 (ISSN) ; Ghojogh, B ; Faezi, S ; Shabany, M ; Sharif University of Technology
OSA - The Optical Society
2017
Abstract
Locating critical objects is crucial in various security applications and industries. For example, in security applications, such as in airports, these objects might be hidden or covered under shields or secret sheaths. Millimeter-wave images can be utilized to discover and recognize the critical objects out of the hidden cases without any health risk due to their non-ionizing features. However, millimeter-wave images usually have waves in and around the detected objects, making object recognition difficult. Thus, regular image processing and classification methods cannot be used for these images and additional pre-processings and classification methods should be introduced. This paper...
Application of base-line correction methods to obtain permanent displacements of a near-source ground motion: The 2003 bam earthquake
, Article Journal of Earthquake Engineering ; Volume 13, Issue 3 , 2009 , Pages 313-327 ; 13632469 (ISSN) ; Khatam, H ; Farahi Jahromi, H ; Sharif University of Technology
2009
Abstract
In this article, two base-line correction methods for correcting the near-source strong motions were studied on the near-source recording of the 2003, Bam earthquake. To obtain permanent ground displacements at Bam station, two methods were applied with some modifications and without using any kind of filtering. Even though it is difficult to calculate true permanent displacements from data attained by present accelerograms, the results of this study show that the rational limit of permanent ground displacements can be successfully achieved by rational choosing of effective parameters. In addition, it is observed that some pre-processing steps suggested in literature have no considerable...
Estimating the fractional order of orthogonal rational functions used in the identification
, Article 2008 International Conference on Control, Automation and Systems, ICCAS 2008, Seoul, 14 October 2008 through 17 October 2008 ; December , 2008 , Pages 1130-1134 ; 9788995003893 (ISBN) ; Haeri, M ; Tavazoei, M.S ; Sharif University of Technology
2008
Abstract
This paper deals with the identification of fractional order systems via orthogonal rational functions. These functions have widely been used in system identification of classical integer order systems. It has been shown that due to some properties such as the presence of non-exponentional aperiodic multimodes in the fractional order systems, it is much better to use fractional orthogonal rational functions in approximation of these systems. One problem which arises in this area is the estimation of fractional order of these orthogonal rational functions. In the existing methods, these parameters have been found by trial and error which requires a large amount of calculations. To reduce the...
SUT-DAM: An integrated software environment for multi-disciplinary geotechnical engineering
, Article Advances in Engineering Software ; Volume 37, Issue 11 , 2006 , Pages 728-753 ; 09659978 (ISSN) ; Gharehbaghi, S. A ; Azami, A. R ; Tabarraie, A. R ; Sharif University of Technology
Elsevier Ltd
2006
Abstract
As computer simulation increasingly supports engineering design, the requirement for a computer software environment providing an integration platform for computational engineering software increases. A key component of an integrated environment is the use of computational engineering to assist and support solutions for complex design. In the present paper, an integrated software environment is demonstrated for multi-disciplinary computational modeling of structural and geotechnical problems. The SUT-DAM is designed in both popularity and functionality with the development of user-friendly pre- and post-processing software. Pre-processing software is used to create the model, generate an...
Persian sentiment analysis of an online store independent of pre-processing using convolutional neural network with fastText embeddings
, Article PeerJ Computer Science ; Volume 7 , 2021 , Pages 1-22 ; 23765992 (ISSN) ; Yazdinejad, M ; Guo, Y ; Sharif University of Technology
PeerJ Inc
2021
Abstract
Sentiment analysis plays a key role in companies, especially stores, and increasing the accuracy in determining customers’ opinions about products assists to maintain their competitive conditions. We intend to analyze the users’ opinions on the website of the most immense online store in Iran; Digikala. However, the Persian language is unstructured which makes the pre-processing stage very difficult and it is the main problem of sentiment analysis in Persian. What exacerbates this problem is the lack of available libraries for Persian pre-processing, while most libraries focus on English. To tackle this, approximately 3 million reviews were gathered in Persian from the Digikala website using...
Developing an evolutionary neural network model for stock index forecasting
, Article Communications in Computer and Information Science, 18 August 2010 through 21 August 2010 ; Volume 93 CCIS , August , 2010 , Pages 407-415 ; 18650929 (ISSN) ; 3642148301 (ISBN) ; Ghanbari, A ; Abbasian Naghneh, S ; Sharif University of Technology
2010
Abstract
The past few years have witnessed a growing rate of attraction in adoption of Artificial Intelligence (AI) techniques and combining them to improve forecasting accuracy in different fields. Besides, stock market forecasting has always been a subject of interest for most investors and professional analysts. Stock market forecasting is a tough problem because of the uncertainties involved in the movement of the market. This paper proposes a hybrid artificial intelligence model for stock exchange index forecasting, the model is a combination of genetic algorithms and feedforward neural networks. Actually it evolves neural network weights by using genetic algorithms. We also employ preprocessing...
Noise reduction algorithm for robust speech recognition using MLP neural network
, Article PACIIA 2009 - 2009 2nd Asia-Pacific Conference on Computational Intelligence and Industrial Applications, 28 November 2009 through 29 November 2009 ; Volume 1 , 2009 , Pages 377-380 ; 9781424446070 (ISBN) ; Razzazi, F ; Sameti, H ; Dabbaghchian, S ; BabaAli, B ; Sharif University of Technology
Abstract
We propose an efficient and effective nonlinear feature domain noise suppression algorithm, motivated by the minimum mean square error (MMSE) optimization criterion. Multi Layer Perceptron (MLP) neural network in the log spectral domain minimizes the difference between noisy and clean speech. By using this method as a pre-processing stage of a speech recognition system, the recognition rate in noisy environments is improved. We can extend the application of the system to different environments with different noises without re-training it. We need only to train the preprocessing stage with a small portion ofnoisy data which is created by artificially adding different types of noises from the...
Robust speech recognition using MLP neural network in log-spectral domain
, Article IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2009, 14 December 2009 through 16 December 2009, Ajman ; 2009 , Pages 467-472 ; 9781424459506 (ISBN) ; Sametit, H ; Razzazi, F ; BabaAli, B ; Dabbaghchiarr, S ; Sharif University of Technology
Abstract
In this paper, we have proposed an efficient and effective nonlinear feature domain noise suppression algorithm, motivated by the minimum mean square error (MMSE) optimization criterion. A Multi Layer Perceptron (MLP) neural network in the log spectral domain has been employed to minimize the difference between noisy and clean speech. By using this method, as a pre-processing stage of a speech recognition system, the recognition rate in noisy environments has been improved. We extended the application ofthe system to different environments with different noises without retraining HMMmodel. We trained the feature extraction stage with a small portion of noisy data which was created by...
Construction and application of SVM model and wavelet-PCA for face recognition
, Article 2009 International Conference on Computer and Electrical Engineering, , 28 December 2009 through 30 December 2009, Dubai ; Volume 1 , 2009 , Pages 391-398 ; 9780769539256 (ISBN) ; Kasaei, S ; Alemi, H ; Sharif University of Technology
Abstract
This work presents a method to increase the face recognition accuracy using a combination of Wavelet, PCA, and SVM. Pre-processing, feature extraction and classification rules are three crucial issues for face recognition. This paper presents a hybrid approach to employ these issues. For pre-processing and feature extraction steps, we apply a combination of wavelet transform and PCA. During the classification stage, SVMs incorporated with a binary tree recognition strategy are applied to tackle the multi-class face recognition problem to achieve a robust decision in presence of wide facial variations. The binary trees extend naturally, the pairwise discrimination capability of the SVMs to...
Comparison of ECG fiducial point extraction methods based on dynamic bayesian network
, Article 2017 25th Iranian Conference on Electrical Engineering, ICEE 2017, 2 May 2017 through 4 May 2017 ; 2017 , Pages 95-100 ; 9781509059638 (ISBN) ; Shamsollahi, M. B ; Jutten, C ; Sharif University of Technology
Abstract
Cardiovascular diseases are one of the major causes of mortality in humans. One way to diagnose heart diseases and abnormalities is processing of cardiac signals such as electrocardiogram (ECG) signal. In many ECG analysis, location of peak, onset and offset of ECG waves must be extracted as a preprocessing step. These points are called ECG fiducial points (FPs) and convey clinically useful information. In this paper, we compare some FP extraction methods including three methods proposed recently by our research team. These methods are based on extended Kalman filter (EKF), hidden Markov model (HMM) and switching Kalman filter (SKF). Results are given for ECG signals of QT database. For all...