H.3. Artificial Intelligence
Designing a Serious Game for Children with Autism using Reinforcement Learning and Fuzzy Logic

Amirhossein Khabbaz; Mansoor Fateh; Ali Pouyan; Mohsen Rezvani

Volume 11, Issue 3 , July 2023, , Pages 375-390

https://doi.org/10.22044/jadm.2023.12638.2417

Abstract
  Autism spectrum disorder (ASD) is a collection of inconstant characteristics. Anomalies in reciprocal social communications and disabilities in perceiving communication patterns characterize These features. Also, exclusive repeated interests and actions identify ASD. Computer games have affirmative effects ...  Read More

H.3.2.6. Games and infotainment
An Adaptive Learning Game for Autistic Children using Reinforcement Learning and Fuzzy Logic

A.H. Khabbaz; A. Pouyan; M. Fateh; V. Abolghasemi

Volume 7, Issue 2 , April 2019, , Pages 321-329

https://doi.org/10.22044/jadm.2018.6010.1709

Abstract
  This paper, presents an adapted serious game for rating social ability in children with autism spectrum disorder (ASD). The required measurements are obtained by challenges of the proposed serious game. The proposed serious game uses reinforcement learning concepts for being adaptive. It is based on ...  Read More

H.3. Artificial Intelligence
A Sensor-Based Scheme for Activity Recognition in Smart Homes using Dempster-Shafer Theory of Evidence

V. Ghasemi; A. Pouyan; M. Sharifi

Volume 5, Issue 2 , July 2017, , Pages 245-258

https://doi.org/10.22044/jadm.2017.845

Abstract
  This paper proposes a scheme for activity recognition in sensor based smart homes using Dempster-Shafer theory of evidence. In this work, opinion owners and their belief masses are constructed from sensors and employed in a single-layered inference architecture. The belief masses are calculated using ...  Read More

H.3.12. Distributed Artificial Intelligence
A topology control algorithm for autonomous underwater robots in three-dimensional space using PSO

Z. Amiri; A. Pouyan; H Mashayekhi

Volume 3, Issue 2 , July 2015, , Pages 191-201

https://doi.org/10.5829/idosi.JAIDM.2015.03.02.08

Abstract
  Recently, data collection from seabed by means of underwater wireless sensor networks (UWSN) has attracted considerable attention. Autonomous underwater vehicles (AUVs) are increasingly used as UWSNs in underwater missions. Events and environmental parameters in underwater regions have a stochastic nature. ...  Read More

Feature selection using genetic algorithm for classification of schizophrenia using fMRI data

Hossein Shahamat; Ali A. Pouyan

Volume 3, Issue 1 , March 2015, , Pages 30-37

https://doi.org/10.5829/idosi.JAIDM.2015.03.01.04

Abstract
  In this paper we propose a new method for classification of subjects into schizophrenia and control groups using functional magnetic resonance imaging (fMRI) data. In the preprocessing step, the number of fMRI time points is reduced using principal component analysis (PCA). Then, independent component ...  Read More

On improving APIT algorithm for better localization in WSN

Seyed M. Hosseinirad; M. Niazi; J Pourdeilami; S. K. Basu; A. A. Pouyan

Volume 2, Issue 2 , July 2014, , Pages 97-104

https://doi.org/10.22044/jadm.2014.148

Abstract
  In Wireless Sensor Networks (WSNs), localization algorithms could be range-based or range-free. The Approximate Point in Triangle (APIT) is a range-free approach. We propose modification of the APIT algorithm and refer as modified-APIT. We select suitable triangles with appropriate distance between anchors ...  Read More

An Enhanced Median Filter for Removing Noise from MR Images

S. Arastehfar; Ali A. Pouyan; A. Jalalian

Volume 1, Issue 1 , March 2013, , Pages 13-17

https://doi.org/10.22044/jadm.2013.110

Abstract
  In this paper, a novel decision based median (DBM) filter for enhancing MR images has been proposed. The method is based on eliminating impulse noise from MR images. A median-based method to remove impulse noise from digital MR images has been developed. Each pixel is leveled from black to white like ...  Read More