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School trip attraction modeling using neural & fuzzy-neural approaches
, Article 8th International IEEE Conference on Intelligent Transportation Systems, Vienna, 13 September 2005 through 16 September 2005 ; Volume 2005 , 2005 , Pages 1068-1073 ; 0780392159 (ISBN); 9780780392151 (ISBN) ; Abrishami, E. S ; Sharif University of Technology
2005
Abstract
Trip attraction has long been considered as a major element in trip demand estimation. Many models have been presented for this purpose. Models use socio-economic variables in order to predict trip attraction. Neural networks and neuro-fuzzy systems are suitable approaches to establish proper models. This paper develops neural and fuzzy-neural models to predict school trip attraction. Neural networks are organized in different architectures and the results have been compared in order to determine the best fitting one. Then an adaptive neural fuzzy inference system (ANFIS) is used to estimate number of school trip attraction. Different models were trained, validated and tested with a real...
A robust free size OCR for omni-font persian/arabic printed document using combined MLP/SVM
, Article 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Havana, 15 November 2005 through 18 November 2005 ; Volume 3773 LNCS , 2005 , Pages 601-610 ; 03029743 (ISSN); 3540298509 (ISBN); 9783540298502 (ISBN) ; Mehran, R ; Razzazi, F ; Sharif University of Technology
2005
Abstract
Optical character recognition of cursive scripts present a number of challenging problems in both segmentation and recognition processes and this attracts many researches in the field of machine learning. This paper presents a novel approach based on a combination of MLP and SVM to design a trainable OCR for Persian/Arabic cursive documents. The implementation results on a comprehensive database show a high degree of accuracy which meets the requirements of commercial use. © Springer-Verlag Berlin Heidelberg 2005
SkipTree: A Scalable range-queryable distributed data structure for multidimensional data
, Article 16th International Symposium on Algorithms and Computation, ISAAC 2005, Hainan, 19 December 2005 through 21 December 2005 ; Volume 3827 LNCS , 2005 , Pages 298-307 ; 03029743 (ISSN); 3540309357 (ISBN); 9783540309352 (ISBN) ; Toossi, M ; Ghodsi, M ; Sharif University of Technology
2005
Abstract
This paper presents the SkipTree, a new balanced, distributed data structure for storing data with multidimensional keys in a peer-to-peer network. The SkipTree supports range queries as well as single point queries which are routed in O(log n) hops. SkipTree is fully decentralized with each node being connected to O(logn) other nodes. The memory usage for maintaining the links at each node is O(log n log log n) on average and O(log2 n) in the worst case. Load balance is also guaranteed to be within a constant factor. © Springer-Verlag Berlin Heidelberg 2005
Composition of MPEG-7 color and edge descriptors based-on human vision perception
, Article Visual Communications and Image Processing 2005, Beijing, 12 July 2005 through 15 July 2005 ; Volume 5960, Issue 1 , 2005 , Pages 568-575 ; 0277786X (ISSN) ; Kialashaki, N ; Ghonoodi, A ; Soltani, M ; Sharif University of Technology
2005
Abstract
In content based image retrieval similarity measurement is one of the most important aspects in a large image database for efficient search and retrieval to find the best answer for a user query. Color and texture are among the more expressive of the visual features. Considerable work has been done in designing efficient descriptors for these features for applications such as similarity retrieval. The MPEG-7 specifies a standard set of descriptors for color, texture and shape. In the Human Vision System (HVS), visual information is not perceived equally; some information may be more important than other information. The purpose of this paper is to show how the MPEG-7 descriptor based on...
Evolution of speech recognizer agents by artificial life
, Article Wec 05: Fourth World Enformatika Conference, Istanbul, 24 June 2005 through 26 June 2005 ; Volume 6 , 2005 , Pages 237-240 ; 9759845857 (ISBN) ; Bagheri Shouraki, S ; Harati Zadeh, S ; Lucas, C ; Ardil C ; Sharif University of Technology
2005
Abstract
Artificial Life can be used as an agent training approach in large state spaces. This paper presents an artificial life method to increase the training speed of some speech recognizer agents which where previously trained by genetic algorithms. Using this approach, vertical training (genetic mutations and selection) is combined with horizontal training (individual learning through reinforcement learning) and results in a much faster evolution than simple genetic algorithm. The approach is tested and a comparison with GA cases on a standard speech data base is presented. COPYRIGHT © ENFORMATIKA
Sustainable transport indicators: Definition and integration
, Article International Journal of Environmental Science and Technology ; Volume 2, Issue 1 , 2005 , Pages 83-96 ; 17351472 (ISSN) ; Vaziri, M ; Sharif University of Technology
CEERS
2005
Abstract
In this paper, a different interpretation of sustainable transportation, is introduced, in which sustainability with respect to transportation sector for the selected countries is evaluated. This interpretation characterizes "sustainable development" through "harmonic development". It means sustainable development with special focus on transportation can be measured by the degree of conformity between environment, economy, and social aspects on one hand, and transportation on the other hand. The best indicator to perform such a measurement is elasticity. The database used for the study encompasses a series of national indicators for each country Seventy nine countries were initially selected...
World city mode choice: Choice of rail public transportation
, Article Scientia Iranica ; Volume 11, Issue 4 , 2004 , Pages 320-331 ; 10263098 (ISSN) ; Tabatabaee, N ; Kermanshah, M ; Aashtiani, H. Z ; Toobaei, S ; Sharif University of Technology
Sharif University of Technology
2004
Abstract
The choice of technology to transport passengers in large metropolitan areas is an important issue everywhere. There are many factors involved in this choice. This paper deals with the possibility of the objective use of available information in the analysis of the suitability of a rail public transport system for a city. A database has been made from publications on public city transportation and country level information. Logit models of choice have been calibrated by the maximum likelihood and nonlinear least square methods based on the acquired information. Each city is treated as an "individual", choosing rail or non-rail modes for its trips. Only cities with a population of more than...
Syllable duration prediction for Farsi text-to-speech systems
, Article Scientia Iranica ; Volume 11, Issue 3 , 2004 , Pages 225-233 ; 10263098 (ISSN) ; Nayebi, K ; Sheikhzadeh, H ; Sharif University of Technology
Sharif University of Technology
2004
Abstract
In this paper, two different statistical approaches are used for duration prediction of the Farsi language. These two statistical models are Neural Networks (NN) and Classification And Regression Trees (CART). The first step in this work was to create a database and develop a flexible feature extraction and selection module. In the next step, the output of the feature selection module was used to train both models. The results of the trained models are further studied to determine the most important parameters affecting the syllable duration in Farsi, The model accuracy is evaluated by using separate training and test data. In the third step of this work, ah automatic rule generator module...
Feature extraction from optimal time-frequency and time-scale transforms for the classification of the knee joint vibroarthrographic signals
, Article 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003, 14 December 2003 through 17 December 2003 ; 2003 , Pages 709-712 ; 0780382927 (ISBN); 9780780382923 (ISBN) ; Shamsollahi, M. B ; Rahimi, A ; Behzad, M ; Afkari, P ; Zamani, E. A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2003
Abstract
In this study knee joint vibroarthrographic (VAG) signals are recorded during active knee movements, which are essentially non-stationary. Because of this nature, common frequency methods are unable to represent the signals, accurately. Both time-frequency and time-scale transforms are used in this research which are good tools for studying non-stationary signals. By optimizing the utilized transforms, it was concluded that the wavelet packet, having the ability of multiresolutional analysis, is a more promising method to extract features from the VAG signals. The performance of different feature extraction techniques were compared by using three new recorded and extensive databases,...
ECG beat classification based on a cross-distance analysis
, Article 6th International Symposium on Signal Processing and Its Applications, ISSPA 2001, Kuala Lumpur, 13 August 2001 through 16 August 2001 ; Volume 1 , 2001 , Pages 234-237 ; 0780367030 (ISBN); 9780780367036 (ISBN) ; Nayebi, K ; Sharif University of Technology
IEEE Computer Society
2001
Abstract
This paper presents a multi-stage algorithm for QRS complex classification into normal and abnormal categories using an unsupervised sequential beat clustering and a cross-distance analysis algorithm. After the sequential beat clustering, a search algorithm based on relative similarity of created classes is used to detect the main normal class. Then other classes are labeled based on a distance measurement from the main normal class. Evaluated results on the MIT-BIH ECG database exhibits an error rate less than 1% for normal and abnormal discrimination and 0.2% for clustering of 15 types of arrhythmia existing on the MIT-BIH database. © 2001 IEEE
DONE: Distributed approximate newton-type method for federated edge learning
, Article IEEE Transactions on Parallel and Distributed Systems ; Volume 33, Issue 11 , 2022 , Pages 2648-2660 ; 10459219 (ISSN) ; Tran, N. H ; Nguyen, T. D ; Bao, W ; Balef, A. R ; Zhou, B. B ; Zomaya, A. Y ; Sharif University of Technology
IEEE Computer Society
2022
Abstract
There is growing interest in applying distributed machine learning to edge computing, forming federated edge learning. Federated edge learning faces non-i.i.d. and heterogeneous data, and the communication between edge workers, possibly through distant locations and with unstable wireless networks, is more costly than their local computational overhead. In this work, we propose ${{sf DONE}}$DONE, a distributed approximate Newton-type algorithm with fast convergence rate for communication-efficient federated edge learning. First, with strongly convex and smooth loss functions, ${{sf DONE}}$DONE approximates the Newton direction in a distributed manner using the classical Richardson iteration...
BIM and machine learning in seismic damage prediction for non-structural exterior infill walls
, Article Automation in Construction ; Volume 139 , 2022 ; 09265805 (ISSN) ; TohidiFar, A ; Alvanchi, A ; Sharif University of Technology
Elsevier B.V
2022
Abstract
Despite the seismic vulnerability of non-structural Exterior Infill Walls (EIWs), their resilient design has received minimal attention. This study addresses the issue by proposing a novel framework for predicting possible damage states of EIWs. The framework benefits from an automated combination of Building Information Modeling as a visualized 3D database of the building's components and the Machine Learning classification as the prediction engine. The framework's applicability is studied in a Proof of Concept example of the exterior walls of the buildings damaged in the 2017 earthquake in Kermanshah, Iran. The Extremely Randomized Trees classifier produced the best results for predicting...
Pan-cancer analysis of microRNA expression profiles highlights microRNAs enriched in normal body cells as effective suppressors of multiple tumor types: A study based on TCGA database
, Article PLoS ONE ; Volume 17, Issue 4 April , 2022 ; 19326203 (ISSN) ; Kamal, A ; Es, H. A ; Farhadi, F ; Ebrahimi, M ; Chitsaz, H ; Sharifi Zarchi, A ; Baharvand, H ; Sharif University of Technology
Public Library of Science
2022
Abstract
Background MicroRNAs (miRNAs) are frequently deregulated in various types of cancer. While antisense oligonucleotides are used to block oncomiRs, delivery of tumour-suppressive miRNAs holds great potential as a potent anti-cancer strategy. Here, we aim to determine, and functionally analyse, miRNAs that are lowly expressed in various types of tumour but abundantly expressed in multiple normal tissues. Methods The miRNA sequencing data of 14 cancer types were downloaded from the TCGA dataset. Significant differences in miRNA expression between tumor and normal samples were calculated using limma package (R programming). An adjusted p value < 0.05 was used to compare normal versus tumor miRNA...
MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments
, Article PLoS Computational Biology ; Volume 18, Issue 6 , 2022 ; 1553734X (ISSN) ; Modegh, R. G ; Rabiee, H. R ; Sarbandi, E. R ; Rezaie, N ; Tam, K. T ; Forrest, A. R. R ; Sharif University of Technology
Public Library of Science
2022
Abstract
Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly...
Location Privacy Preservation for Secondary Users in a Database-Driven Cognitive Radio Network
, Article ISeCure ; Volume 14, Issue 2 , 2022 , Pages 215-227 ; 20082045 (ISSN) ; Ahmadian Attari, M ; Aref, M. R ; Jannati, H ; Sharif University of Technology
Iranian Society of Cryptology
2022
Abstract
Since their introduction, Cognitive Radio Networks (CRN), as a new solution to the problem of spectrum scarcity, have received great attention from the research society. An important field in database-driven CRN studies is pivoted on their security issues. A critical issue in this context is user’s location privacy, which is potentially under serious threat. The query process by secondary users (SU) from the database is one of the points where the problem rises. In this paper, we propose a Privacy-Preserving Query Process (PPQP), accordingly. This method lets SUs deal in the process of spectrum query without sacrificing their location information. Analytical assessment of PPQP’s privacy...
Towards more secure constructions of adjustable join schemes
, Article IEEE Transactions on Dependable and Secure Computing ; Volume 19, Issue 2 , 2022 , Pages 1078-1089 ; 15455971 (ISSN) ; Rafiee, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2022
Abstract
An adjustable join (AdjoinAdjoin) scheme [4] is a symmetric-key primitive that enables a user to securely outsource his database to a server, and later to issue join queries for a pair of columns. When queries are extended to a list of columns, the 3Partition3Partition security of Adjoin schemes [8] does not capture the expected security. To address this deficiency, we introduce the syntax and security notion of multi-adjustable join (M-AdjoinM-Adjoin) schemes. We propose a new security notion for this purpose, which we refer to as M3PartitionM3Partition. The 3Partition3Partition security of AdjoinAdjoin extends to the M3PartitionM3Partition security of M-AdjoinM-Adjoin in a straightforward...
Security of multi-adjustable join schemes: separations and implications
, Article IEEE Transactions on Dependable and Secure Computing ; Volume 19, Issue 4 , 2022 , Pages 2535-2545 ; 15455971 (ISSN) ; Khazaei, S ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2022
Abstract
Database management systems (DBMS) are one of cloud services with major applications in industry and business. In the use of such services, since the cloud service provider cannot be entrusted with the plain data, the databases are typically encrypted prior to outsourcing. One of the most challenging issues in designing these services is supporting SQL join queries on the encrypted database. The multi-adjustable join scheme (M-Adjoin) [Khazaei-Rafiee 2020], an extension of Adjoin [Popa-Zeldovich 2012 and Mironov-Segev-Shahaf 2017], is a symmetric-key primitive that supports the join queries for a list of column labels on an encrypted database. In previous works, the following security...