ORCID Profile
0000-0002-1920-659X
Current Organisation
Iran University of Science and Technology
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Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: Public Library of Science (PLoS)
Date: 12-06-2020
Publisher: Optica Publishing Group
Date: 15-07-2022
DOI: 10.1364/AO.461473
Abstract: Optical performance monitoring (OPM) is crucial for facilitating the management of future few-mode fiber (FMF)-based transmissions. OPM deploys fault detection and link diagnosis by measuring the physical layer states and provides feedback to the controller. Recently, machine learning (ML) has gained a lot of attention for OPM, and various ML algorithms were developed, wherein the selection of the proper method is a challenge. Ensemble learning (EL) solves this challenge by combining different ML models however, this simultaneous employment suffers from increased complexity and dependency on the performance of each in idual model. Meta-ensemble learning (MEL) provides a promising solution by intelligently selecting the proper ensemble at each instance. In this work, we employ MEL for OPM in FMF systems. We compare the proposed MEL-based OPM method with naive EL (NEL), which is a well-known EL method. The obtained results indicate that proposed MEL-based OPM method provides better performance with the loss data set size compared with NEL-based OPM. Furthermore, the proposed MEL-based OPM method does not need the feature preprocessing, which is an essential step in other ML algorithms such as NEL-based OPM.
Publisher: Elsevier BV
Date: 11-2021
Publisher: IEEE
Date: 24-11-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2019
Publisher: Institution of Engineering and Technology (IET)
Date: 13-04-2022
DOI: 10.1049/SIL2.12124
Publisher: The Scientific and Technological Research Council of Turkey (TUBITAK-ULAKBIM) - DIGITAL COMMONS JOURNALS
Date: 2013
DOI: 10.3906/ELK-1110-46
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institution of Engineering and Technology (IET)
Date: 17-10-2021
DOI: 10.1049/OTE2.12060
Publisher: Institution of Engineering and Technology (IET)
Date: 20-01-2022
DOI: 10.1049/OTE2.12064
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Springer Science and Business Media LLC
Date: 07-01-2021
Publisher: Springer Science and Business Media LLC
Date: 18-06-2020
DOI: 10.1186/S12859-020-03584-5
Abstract: Haplotype information is essential for many genetic and genomic analyses, including genotype-phenotype associations in human, animals and plants. Haplotype assembly is a method for reconstructing haplotypes from DNA sequencing reads. By the advent of new sequencing technologies, new algorithms are needed to ensure long and accurate haplotypes. While a few linked-read haplotype assembly algorithms are available for diploid genomes, to the best of our knowledge, no algorithms have yet been proposed for polyploids specifically exploiting linked reads. The first haplotyping algorithm designed for linked reads generated from a polyploid genome is presented, built on a typical short-read haplotyping method, SDhaP. Using the input aligned reads and called variants, the haplotype-relevant information is extracted. Next, reads with the same barcodes are combined to produce molecule-specific fragments. Then, these fragments are clustered into strongly connected components which are then used as input of a haplotype assembly core in order to estimate accurate and long haplotypes. Hap10 is a novel algorithm for haplotype assembly of polyploid genomes using linked reads. The performance of the algorithms is evaluated in a number of simulation scenarios and its applicability is demonstrated on a real dataset of sweet potato.
Publisher: Elsevier BV
Date: 12-2022
Publisher: IEEE
Date: 15-06-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: Elsevier BV
Date: 2023
Publisher: Elsevier BV
Date: 12-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-03-2023
Publisher: Institution of Engineering and Technology (IET)
Date: 07-2020
Publisher: Cold Spring Harbor Laboratory
Date: 09-01-2020
DOI: 10.1101/2020.01.08.899013
Abstract: Haplotype information is essential for many genetic and genomic analyses, including genotype-phenotype associations in human, animals and plants. Haplotype assembly is a method for reconstructing haplotypes from DNA sequencing reads. By the advent of new sequencing technologies, new algorithms are needed to ensure long and accurate haplotypes. While a few linked-read haplotype assembly algorithms are available for diploid genomes, there are no algorithms yet for polyploids. The first haplotyping algorithm designed for 10X linked reads generated from a polyploid genome is presented, built on a typical short-read haplotyping method, SDhaP. Using the input aligned reads and called variants, the haplotype-relevant information is extracted. Next, reads with the same barcodes are combined to produce molecule-specific fragments. Then, these fragments are clustered into strongly connected components which are then used as input of a haplotype assembly core in order to estimate accurate and long haplotypes. Hap10 is a novel algorithm for haplotype assembly of polyploid genomes using linked reads. The performance of the algorithms is evaluated in a number of simulation scenarios and its applicability is demonstrated on a real dataset of sweet potato.
Publisher: Institution of Engineering and Technology (IET)
Date: 30-04-2023
DOI: 10.1049/ELL2.12803
Abstract: A new method is developed for the Direction of Arrival (DOA) estimation of wideband sources by refining the initial estimates and posing the super‐resolution theory in a non‐convex optimization problem. A gradient‐projection method is conducted for the accurate estimation of DOAs. The proposed method can be performed by any non‐uniform linear array with no need for any focusing matrices. Moreover, a greedy search algorithm is employed to obtain initial estimates for super‐resolution implementation. Numerical simulations show the outstanding accuracy of the proposed method and more robustness to noise compared to some well‐known methods. It is also more effective for DOA estimation of adjacent sources.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Elsevier BV
Date: 02-2023
Publisher: Public Library of Science (PLoS)
Date: 26-03-2019
Location: Iran (Islamic Republic of)
No related grants have been discovered for Mohammad Hossein Kahaei.