Loading...
Search for:
test-data
0.004 seconds
Total 27 records
Web graph compression by edge elimination
, Article Data Compression Conference, DCC 2006, Snowbird, UT, 28 March 2006 through 30 March 2006 ; 2006 , Pages 459- ; 10680314 (ISSN) ; Khalili, H ; Nourbakhsh, E ; Ghodsi, M ; Brandeis University ; Sharif University of Technology
2006
Functional fault model definition for bus testing
, Article Proceedings of IEEE East-West Design and Test Symposium, EWDTS 2013, Rostov-on-Don ; 2013 ; 9781479920969 (ISBN) ; Haghbayan, M. H ; Maleki, A ; Tabandeh, M ; Sharif University of Technology
2013
Abstract
In this paper we present a new fault model for testing bus components using their functionality. With the aim of a new fault model definition all components in a bus except cores of the SoC will be tested as fast as possible. According to the proposed method in this paper, at first, wires and small components will be tested by marching test patterns as the test data and, after that based on a proposed method; the new format faults for the bus will be used. Using AMBA-AHB as the experimental result, the new fault model shows efficiency in comparison with corresponding stuck-at
Monte Carlo simulation of recrystallization with hardness input of cold worked metal
, Article Materials Science and Engineering A ; Volume 496, Issue 1-2 , 2008 , Pages 389-392 ; 09215093 (ISSN) ; Sharif University of Technology
2008
Abstract
A Monte Carlo model on the basis of hardness input is developed to predict the annealing microstructure of deformed specimens in tensile, compression, and tensile + compression tests. From experimental value of hardness, the stored energy of the deformed specimens is calculated and entered into the Monte Carlo model. The consistency between the simulation results and experimental data shows that the developed model based on hardness input can be more practical since the effect of different deformation states is considered for estimating of stored energy. © 2008 Elsevier B.V. All rights reserved
One-shot learning from demonstration approach toward a reciprocal sign language-based HRI
, Article International Journal of Social Robotics ; 2021 ; 18754791 (ISSN) ; Taheri, A ; Alemi, M ; Meghdari, A ; Sharif University of Technology
Springer Science and Business Media B.V
2021
Abstract
This paper addresses the lack of proper Learning from Demonstration (LfD) architectures for Sign Language-based Human–Robot Interactions to make them more extensible. The paper proposes and implements a Learning from Demonstration structure for teaching new Iranian Sign Language signs to a teacher assistant social robot, RASA. This LfD architecture utilizes one-shot learning techniques and Convolutional Neural Network to learn to recognize and imitate a sign after seeing its demonstration (using a data glove) just once. Despite using a small, low diversity data set (~ 500 signs in 16 categories), the recognition module reached a promising 4-way accuracy of 70% on the test data and showed...
Test data compression strategy while using hybrid-BIST methodology
, Article Proceedings of IEEE East-West Design and Test Symposium, EWDTS 2013, Rostov-on-Don ; Sept , 2013 ; 9781479920969 (ISBN) ; Tabandeh, M ; Haghbayan, M. H ; Sharif University of Technology
2013
Abstract
In this paper a strategy is proposed for compressing the test data while using concurrent hybrid-BIST methodologyfor testing SoCs. In the proposed method, in addition tousing BIST strategy for testing cores with deterministic sequential test patterns in an SoC( Without using scan chains), (ATE) is used for testing cores with deterministic test patterns through Test Access Mechanism (TAM) or functional bus. As will be shown in experimental results, this process compresses hybrid-BIST overall test patterns considerably that affects the overall Test Application Time (TAT) in comparison with pure deterministic, pure pseudo random, and combination of deterministic and pseudo random test patterns
A linear genetic programming approach for the prediction of solar global radiation
, Article Neural Computing and Applications ; Volume 23, Issue 3-4 , 2013 , Pages 1197-1204 ; 09410643 (ISSN) ; Saeedi Ramyani, S ; Sharif University of Technology
2013
Abstract
In this article, the linear genetic programming (LGP) is utilized to predict the solar global radiation. The solar radiation is formulated in terms of several climatological and meteorological parameters. Comprehensive databases containing monthly data collected for 6 years (1995-2000) in two nominal cities in Iran are used to develop LGP-based models. Separate models are established for each city. To verify the performance of the proposed models, they are applied to estimate the solar global radiation of test data of database. The contribution of the parameters affecting the solar radiation is evaluated through a sensitivity analysis. The results indicate that the LGP models give precise...
An nnovative test bed for verification of attitude control system
, Article IEEE Aerospace and Electronic Systems Magazine ; Volume 32, Issue 6 , 2017 , Pages 16-22 ; 08858985 (ISSN) ; Faghihinia, A ; Kalhor, A ; Sharif University of Technology
Abstract
A 3 DOF platform was constructed in the Georgia Institute of Technology to perform new control strategies in an experimental framework. Also in this simulator, there isn't any sensor used by a real satellite for attitude determination. The setup was structured on data transmitting and synchronization of distributed elements for ADCS tests. In such a plan, not only can different elements of the test bed be used individually, but also they can support an integrated hardware in the loop test. Accordingly, reusing the hardware sources causes a cost reduction of development. Furthermore the geometric interferences of different parts are minimized in this plan. So, the test bed can be developed...
Software Test Data Generation Using Genetic Algorithms
, M.Sc. Thesis Sharif University of Technology ; Mahdavi Amiri, Nezameddin (Supervisor)
Abstract
In software testing, it is often desirable to find test inputs that exercise specific program features. Good testing means uncovering as many faults as possible with a potent set of tests. Thus, a test series that has the potential to uncover many faults is better than one that can only uncover a few. To find these inputs by hand is extremely time-consuming, especially when the software is complex. Therefore, many attempts have been made to automate the process. There are three major methods to generate software test data: Random test data generation, Symbolic test data generation and Dynamic test data generation. Dynamic test data generation, such as those using genetic algorithms, is...
Reservoir Characterization and Parameter Estimation Using Ensemble Kalman Filter
, M.Sc. Thesis Sharif University of Technology ; Pishvaei, Mahmood Reza (Supervisor) ; Bozorgmehri Boozarjmehri, Ramin (Supervisor)
Abstract
Management decisions, enhanced oil recovery, and reservoir development plans in petroleum industries are based on predictions by reservoir simulation. Due to uncertainties in model parameters or engineering assumptions, the simulation results are not accurate, while they are correct. For more accurate estimation of unknown production quantities, it is required to characterize the unknown parameters and its uncertainty. By using static data alone the result of characterization is unreliable and unsure, therefore dynamic data use practically. In reservoir engineering literature, this is called “History Matching”.The ensemble Kalman filter is an optimal recursive data processing algorithm based...
Test Reuse in GUI-Based Applications Using Word Embedding
,
M.Sc. Thesis
Sharif University of Technology
;
Heydarnoori, Abbas
(Supervisor)
Abstract
Testing is one of the most important and time-consuming steps in the Software Development Life Cycle. Especially, in recent methodologies like agile in which change is an important feature and they take place in iterations with each iteration taking place in a limited time. Recent studies suggest approaches to automatically generate test cases for the applications. For GUI-based applications, test cases are composed of a chain of events that are activated by the user. For these applications, we can generate test cases by simulating the chain of events that get activated by the user. Semantic-based approaches use the semantic matching of the events and their related widgets, to generate test...
Speaker phone mode classification using Gaussian mixture models
, Article SPA 2011 - Signal Processing: Algorithms, Architectures, Arrangements, and Applications - Conference Proceedings, 29 September 2011 through 30 September 2011 ; September , 2011 , Pages 112-117 ; 9781457714863 (ISBN) ; Sobhan Manesh, F ; Sameti, H ; BabaAli, B ; Sharif University of Technology
2011
Abstract
This study focuses on the mode classification of phones speaker modes using GMM 1. In this regard, speech data in both enabled and disabled speaker modes of cell phones and telephones were collected, processed and classified into two different categories. The different mixture numbers (1 to 4) of GMM and wave files sizes of 10, 20, 40 and 80 kb were tested in order to obtain an optimal condition for classification. The GMM method attained 87.99% correct classification rate on test data. This classification is important for speech enabled IVR 2 systems [1], dialog systems and many systems in speech processing in the sense that it could help to load an optimum model for increasing system...
Multiple-chi-square tests and their application on distinguishing attacks
, Article 2011 8th International ISC Conference on Information Security and Cryptology, ISCISC 2011, 14 September 2011 through 15 September 2011, Mashhad ; 2011 , Pages 55-60 ; 9781467300773 (ISBN) ; Salmasizadeh, M ; Mohajeri, J ; Sharif University of Technology
2011
Abstract
Chi-square tests are vastly used for distinguishing random distributions, but extra care must be taken when using them on several independent variables. We noticed, the chisquare statistics, in some previous works, was computed half of its real value. Thus, to avoid possible future confusions, we formulize multiple-chi-square tests. To show the application of multiple-chi-square tests, we introduce two new tests and apply them to Trivium as a special case. These tests are modifications of ANF monomial test and, when applied to Trivium with the same number of rounds, the data complexity of them is roughly 24 times smaller than that of previous ANF monomial test
Lexical pattern generalization for ontology learning and population: A survey
, Article Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010, 17 March 2010 through 19 March 2010 ; 2010 , Pages 551-554 ; 9789881701282 (ISBN) ; Sayadiharikandeh, M ; Zibanezhad, B ; Sharif University of Technology
Abstract
Information extraction and refinement systems rely on a set of extraction patterns in pattern based approaches in order to construct taxonomies and finding instances of concepts in a corpus. Pattern based methods have high precision and suffer from low recall. Pattern generalization and modeling techniques can increase matching power and decrease GAP between training and test data
Application of genetic algorithm in automatic software testing
, Article Communications in Computer and Information Science, 7 July 2010 through 9 July 2010 ; Volume 88 CCIS, Issue PART 2 , 2010 , Pages 545-552 ; 18650929 (ISSN) ; 9783642143052 (ISBN) ; Hatamizadeh, A ; Babamir, S. M ; Dabbaghian, M ; Norouzi, A ; Sharif University of Technology
Abstract
One of the major challenge and time-consuming work is optimum test data generation to assure software quality. Researchers have proposed several methods over years to generate automatically solution which have different drawbacks. In this paper, we propose Genetic Algorithm (GA) based tester with different parameters to automate the structural-oriented test data generation on the basis of internal program structure. Our proposed fitness function is intended to traverse paths of the program as more as possible. This integration improves the GA performance in search space exploration and exploitation fields with faster convergence. At last, we present some results according to our experiment...
Generalization of ANN-based aircraft dynamics identification techniques into the entire flight envelope
, Article IEEE Transactions on Aerospace and Electronic Systems ; Volume 52, Issue 4 , 2016 , Pages 1866-1880 ; 00189251 (ISSN) ; Saghafi, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
Abstract
In this paper, an approach has been proposed in order to extend the applicability of artificial neural network (ANN) techniques for flight dynamics identification into the entire flight envelope. In general, the aircraft flight dynamics is a nonlinear and coupled system whose modeling by ANNs is only possible to a limited degree around an operational point. Therefore, it cannot be expected that an ANN trained at a specific Mach and altitude will have satisfactory results in various flight conditions. Most recent studies on ANN-based identification and modeling of aircraft dynamics have been carried out primarily at specific Mach and altitudes. In this study, by introducing a new approach...
Fuzzy classification by multi-layer averaging: An application in speech recognition
, Article 3rd International Conference on Informatics in Control, Automation and Robotics, ICINCO 2006, Setubal, 1 August 2006 through 5 August 2006 ; Volume SPSMC , 2006 , Pages 122-126 ; 9728865619 (ISBN); 9789728865610 (ISBN) ; Shouraki, S. B ; Halavati, R ; Sharif University of Technology
2006
Abstract
This paper intends to introduce a simple fast space-efficient linear method for a general pattern recognition problem. The presented algorithm can find the closest match for a given sample within a number of samples which has already been introduced to the system. The fact of using averaging and fuzzy numbers in this method encourages that it may be a noise resistant recognition process. As a test bed, a problem of recognition of spoken words has been set forth to this algorithm. Test data contain clean and noisy samples and results have been compared to that of a widely used speech recognition method, HMM
Comparative analysis of hydrate formation pressure applying cubic equations of state (eos), artificial neural network (ann) and adaptive neuro-fuzzy inference system (anfis)
, Article International Journal of Thermodynamics ; Volume 15, Issue 2 , 2012 , Pages 91-101 ; 13019724 (ISSN) ; Saber, M ; Ameri, A ; Sharif University of Technology
Abstract
The objective of this work is making comparison between thermodynamic models and data-driven techniques accuracy in prediction of hydrate formation pressure as a function of temperature and composition of gas mixtures. The Peng-Robinson (PR) and Patel-Teja (PT) equations of state are used for thermodynamic modeling and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are used as data-driven models. The capability of each method is evaluated by comparison with the experimental data collected from literature. It is shown that there is a good agreement between thermodynamic modeling and the experimental data in most of the cases; however, the prediction...
Deformation prediction of mouse embryos in cell injection experiment by a feedforward artificial neural network
, Article Proceedings of the ASME Design Engineering Technical Conference, 28 August 2011 through 31 August 2011 ; Volume 2, Issue PARTS A AND B , August , 2011 , Pages 543-550 ; 9780791854792 (ISBN) ; Ahmadian, M. T ; Vossoughi, G. R ; Sharif University of Technology
2011
Abstract
In this study, neural network models have been used to predict the mechanical behaviors of mouse embryos. In addition, sensitivity analysis has been carried out to investigate the influence of the significance of input parameters on the mechanical behavior of mouse embryos. In order to reach these purposes two neural network models have been implemented. Experimental data earlier deduced-by [Flückiger, M. (2004). Cell Membrane Mechanical Modeling for Microrobotic Cell Manipulation. Diploma Thesis, ETHZ Swiss Federal Institute of Technology, Zurich, WS03/04]-were collected to obtain training and test data for the neural network. The results of these investigations show that the correlation...
HMM based semi-supervised learning for activity recognition
, Article SAGAware'11 - Proceedings of the 2011 International Workshop on Situation Activity and Goal Awareness, 18 September 2011 through 18 September 2011, Beijing ; September , 2011 , Pages 95-99 ; 9781450309264 (ISBN) ; Rabiee, H. R ; Pourdamghani, N ; Khanipour, P ; Sharif University of Technology
2011
Abstract
In this paper, we introduce a novel method for human activity recognition that benefits from the structure and sequential properties of the test data as well as the training data. In the training phase, we obtain a fraction of data labels at constant time intervals and use them in a semi-supervised graph-based method for recognizing the user's activities. We use label propagation on a k-nearest neighbor graph to calculate the probability of association of the unlabeled data to each class in this phase. Then we use these probabilities to train an HMM in a way that each of its hidden states corresponds to one class of activity. These probabilities are used to learn the transition probabilities...
Constitutive modeling of rubberlike materials based on consistent strain energy density functions
, Article Polymer Engineering and Science ; Volume 50, Issue 5 , 2010 , Pages 1058-1066 ; 00323888 (ISSN) ; Naghdabadi, R ; Kargarnovin, M. H ; Sharif University of Technology
Abstract
Rubberlike materials are characterized by high deformability and reversibility of deformation. From the continuum viewpoint, a strain energy density function is postulated for modeling the behavior of these materials. In this paper, a general form for the strain energy density of these materials is proposed from a phenomenological point of view. Based on the Valanis-Landel hypothesis, the strain energy density of incompressible materials is expressed as the sum of independent functions of the principal stretches meeting the essential requirements on the form of the strain energy density. It is cleared that the appropriate mathematical expressions for constitutive modeling of these materials...