Origin-Destination Matrix Adjustment using Split Ratios of Network Nodes

, M.Sc. Thesis Sharif University of Technology Asgarian, Mahya (Author) ; Shafahi, Yousef (Supervisor)

Abstract

This research presents a model to adjust origin-destination (OD) matrix using split ratios of network nodes. Conventional direct methods for OD estimation are resource intensive and time consuming therefore developing indirect methods which are less costly is important. Split ratios of network nodes can be obtained from nowadays technologies such as Bluetooth sensors with acceptable accuracy. An iterative bilevel estimation framework is presented that uses split ratios and link flows as observations. The upper level problem is to minimize a weighted objective function of the deviation between observed and estimated data. In the lower level the OD matrix is assigned to the network. This model...

Towards an efficient method for spreading information in social network

, Article 2009 3rd Asia International Conference on Modelling and Simulation, AMS 2009, Bandung, Bali, 25 May 2009 through 26 May 2009 ; 2009 , Pages 152-157 ; 9780769536484 (ISBN) Ahmadi, H ; Mehrbakhsh, A ; Asgarian, E ; Sharif University of Technology

2009

Abstract

Nowadays, content distribution is of high attention in peer to peer information systems. There are two main problems that could be mentioned in this context. The first problem is how to disseminate fragments of information efficiently and the next is to avoid missing same rare fragments towards end of download. For overcoming these problems, a new mechanism is presented in this paper which uses gossip algorithms on basis of social networks. Our mechanism maintains simplicity of gossip and has low overhead. This mechanism includes two phases for managing traffic and solving bottleneck problem: one for spreading rumors inside the social network and finding network of interests and the other...

A combination of PSO and K-means methods to solve haplotype reconstruction problem

, Article 2009 International Conference on Innovations in Information Technology, IIT '09, 15 December 2009 through 17 December 2009 ; 2009 , Pages 190-194 ; 9781424456987 (ISBN) Sharifian R, S ; Baharian, A ; Asgarian, E ; Rasooli, A ; Sharif University of Technology

2009

Abstract

Disease association study is of great importance among various fields of study in bioinformatics. Computational methods happen to be advantageous specifically when experimental approaches fail to obtain accurate results. Haplotypes are believed to be the most responsible biological data for genetic diseases. In this paper, the problem of reconstructing haplotypes from error-containing SNP fragments is discussed For this purpose, two new methods have been proposed by a combination of k-means clustering and particle swarm optimization algorithm. The methods and their implementation results on real biological and simulation datasets are represented which shows that they outperform the methods...

Damage detection in jacket-type offshore platforms via generalized flexibility matrix and optimal genetic algorithm (GFM-OGA)

, Article Ocean Engineering ; Volume 281 , 2023 ; 00298018 (ISSN) Aghaeidoost, V ; Afshar, S ; Ziaie Tajaddod, N ; Asgarian, B ; Rahman Shokrgozar, H ; Sharif University of Technology

Elsevier Ltd 2023

Abstract

Jacket-type offshore platforms are crucial infrastructure assets that can be damaged, disrupting operations and causing significant economic losses. To manage these risks, Structural Health Monitoring (SHM) is crucial in extending the lifespan of these structures. Recent years have seen the development of innovative vibration-based methods for SHM, which are based on the principle that changes in the dynamic model specifications of a structure indicate damage. The aim of this paper is to present an effective process for detecting structural damage through vibrational analysis and determining its location and severity. The proposed method uses vibrational characteristics of the structure,...

Solving MEC and MEC/GI problem models, using information fusion and multiple classifiers

, Article Innovations'07: 4th International Conference on Innovations in Information Technology, IIT, Dubai, 18 November 2007 through 20 November 2007 ; 2007 , Pages 397-401 ; 9781424418411 (ISBN) Asgarian, E ; Moeinzadeh, M. H ; Mohammadzadeht, J ; Ghazinezhad, A ; Habibi, J ; Najafi Ardabili, A ; Sharif University of Technology

IEEE Computer Society 2007

Abstract

Mutations in Single Nucleotide Polymorphisms (SNPs - different variant positions (1%) from human genomes) are responsible for some genetic diseases. As a consequence, obtaining all SNPs from human populations is one of the primary goals of recent studies in human genomics. Two sequences of mentioned SNPs in diploid human organisms are called haplotypes. In this paper, we study haplotype reconstruction from SNP-fragments with and without genotype information, problems. Designing serial and parallel classifiers was center of our research. Genetic algorithm and K-means were two components of our approaches. This combination helps us to cover the single classifier's weaknesses. ©2008 IEEE

Solving haplotype reconstruction problem in MEC model with hybrid information fusion

, Article EMS 2008, European Modelling Symposium, 2nd UKSim European Symposium on Computer Modelling and Simulation, Liverpool, 8 September 2008 through 10 September 2008 ; 2008 , Pages 214-218 ; 9780769533254 (ISBN) Asgarian, E ; Moeinzadeh, M. H ; Habibi, J ; Sharifian-R, S ; Rasooli-V, A ; Najafi-A, A ; Sharif University of Technology

2008

Abstract

Single Nucleotide Polymorphisms (SNPs), a single DNA base varying from one individual to another, are believed to be the most frequent form responsible for genetic differences. Genotype is the conflated information of a pair of haplotypes on homologous chromosomes. Although haplotypes have more information for disease associating than individual SNPs and genotype, it is substantially more difficult to determine haplotypes through experiments. Hence, computational methods which can reduce the cost of determining haplotypes become attractive alternatives. MEC, as a standard model for haplotype reconstruction, is fed by fragments as input to infer the best pair of haplotypes with minimum error...

Finding feasible timetables with particle swarm optimization

, Article Innovations'07: 4th International Conference on Innovations in Information Technology, IIT, Dubai, 18 November 2007 through 20 November 2007 ; 2007 , Pages 387-391 ; 9781424418411 (ISBN) Qarouni Fard, D ; Najafi Ardabifi, A ; Moeinzadeh, M. H ; Sharifian R, S ; Asgarian, E ; Mohammadzadeh, J ; Sharif University of Technology

IEEE Computer Society 2007

Abstract

A Timetabling problem is usually defined as assigning a set of events to a number of rooms and timeslots such that they satisfy a number of constraints. Particle swarm optimization (PSO) is a stochastic, population-based computer problem-solving algorithm; it is a kind of swarm intelligence that is based on social-psychological principles and provides insights into social behavior, as well as contributing to engineering applications. This paper applies the Particle Swarm Optimization algorithm to the classic Timetabling problem. This is inspired by similar attempts belonging to the evolutionary paradigm in which the metaheuristic involved is tweaked to suit the grouping nature of problems...

Solving MEC model of haplotype reconstruction using information fusion, single greedy and parallel clustering approaches

, Article 6th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2008, Doha, 31 March 2008 through 4 April 2008 ; 2008 , Pages 15-19 ; 9781424419685 (ISBN) Asgarian, E ; Moeinzadeh, M. H ; Sharifian-R, S ; Najafi-A, A ; Ramezani, A ; Habibi, J ; Mohammadzadeh, J ; Sharif University of Technology

2008

Abstract

Haplotype information has become increasingly important in analyzing fine-scale molecular genetics data, Due to the mutated form in human genome; SNPs (Single Nucleotide Polymorphism) are responsible for some genetic diseases. As a consequence, obtaining all SNPs from human populations is one of the primary goals of studies in human genomics. In this paper, a data fusion method based on multiple parallel classifiers for reconstruction of haplotypes from a given sample Single Nucleotide Polymorphism (SNP) is proposed. First, we design a single greedy algorithm for solving haplotype reconstructions. [2] is used as an efficient approach to be combined with first classification method. The...

Observations on using probabilistic c-means for solving a typical bioinformatics problem

, Article EMS 2008, European Modelling Symposium, 2nd UKSim European Symposium on Computer Modelling and Simulation, Liverpool, 8 September 2008 through 10 September 2008 ; 2008 , Pages 236-239 ; 9780769533254 (ISBN) Mohammadzadeh, J ; Ghazinezhad, A ; Rasooli Valaghozi, A ; Nadi, A ; Asgarian, E ; Salmani, V ; Najafi Ardabili, A ; Moeinzadeh, M. H ; Sharif University of Technology

2008

Abstract

Recently, there has been great interest in Bio informatics among researches from various disciplines such as computer science, mathematics, statistics and artificial intelligence. Bioinformatics mainly deals with solving biological problems at molecular levels. One of the classic problems of bioinformatics which has gain a lot attention lately is Haplotyping, the goal of which is categorizing SNP-fragments into two clusters and deducing a haplotype for each. Since the problem is proved to be NP-hard, several computational and heuristic methods have addressed the problem seeking feasible answers. In this work it is shown that using PCM to solve Haplotyping problem in DALY dataset yields...