Authors: Hamid Ahmadieh, MD 1 ; ([email protected]) Ramin Taei, MD 1 ; ([email protected]) Masoud Soheilian, MD 1 ; ([email protected]) Mohammad Riazi-Esfahani, MD 2 ; ([email protected]) Reza Karkhaneh, MD; 2 ([email protected]) Alireza Lashay, MD; 2 ([email protected]) Mohsen Azarmina, MD; 1 ([email protected]) Mohammad Hossein Dehghan, MD; 1 ([email protected]) Siamak Mor...

by MOHAMMAD AKRAM HOSSAIN

Ali Meghdari, Seyyed Mohammad H. Lavasani, Mohsen Norouzi and Mir Saman Rahimi Mousavi Robotica / FirstView Article / May 2013, pp 1 ­ 11 DOI: 10.1017/S0263574713000362, Published online: 22 May 2013 Link to this article: http://journals.cambridge.org/abstract_S0263574713000362 How to cite this article: Ali Meghdari, Seyyed Mohammad H. Lavasani, Mohsen Norouzi and Mir Saman Rahimi Mousavi Minim...

An efficient oscillating inertia weight of particle swarm optimisation for tracking optima in dynamic environments Javidan Kazemi Kordestani, Alireza Rezvanian & Mohammad Reza Meybodi To cite this article: Javidan Kazemi Kordestani, Alireza Rezvanian & Mohammad Reza Meybodi (2016) An efficient oscillating inertia weight of particle swarm optimisation for tracking optima in dynamic environments,...

Back, Jung Ho, Hamid Reza Rezvani, Yucui Zhu, Véronique Guyonnet-Duperat, Mohammad Athar, Desiree Ratner, and Arianna L. Kim From Departments of Dermatology, Columbia University Medical Center, New York, NY 10032; Inserm 1035, Bordeaux, F-33076, France; Université Bordeaux Segalen, Bordeaux, F-33076, France; SFR TransBioMed, Plateforme de vectorologie, Université Bordeaux Segalen, Bordeaux, F33...

We describe a classifier to predict the message-level sentiment of English microblog messages from Twitter. This paper describes the classifier submitted to the SemEval-2014 competition (Task 9B). Our approach was to build up on the system of the last year’s winning approach by NRC Canada 2013 (Mohammad et al., 2013), with some modifications and additions of features, and additional sentiment l...

In this paper, we compare feature-based and Neural Network-based approaches on the supervised stance classification task for tweets in SemEval-2016 Task 6 Subtask A (Mohammad et al., 2016). In the feature-based approach, we use external resources such as lexicons and crawled texts. The Neural Network based approach employs Convolutional Neural Network (CNN). Our results show that the feature-ba...