Original/Review Paper
Energy-Efficient Timing Assignment of Tasks to Actors in WSANs

M. R. Okhovvat; M. T. Kheirabadi; A. Nodehi; M. Okhovvat

Volume 10, Issue 3 , July 2022, Pages 303-310


  Minimizing make-span and maximizing remaining energy are usually of chief importance in the applications of wireless sensor actor networks (WSANs). Current task assignment approaches are typically concerned with one of the timing or energy constraints. These approaches do not consider the types and various ...  Read More

Original/Review Paper
A Simulated Annealing-based Throughput-aware Task Mapping Algorithm for Manycore Processors

A.R. Tajary; H. Morshedlou

Volume 10, Issue 3 , July 2022, Pages 311-320


  With the advent of having many processor cores on a single chip in many-core processors, the demand for exploiting these on-chip resources to boost the performance of applications has been increased. Task mapping is the problem of mapping the application tasks on these processor cores to achieve lower ...  Read More

Original/Review Paper
Determining parameters of DBSCAN Algorithm in Dynamic Environments Automatically using Dynamic Multi-objective Genetic Algorithm

Z. Falahiazar; A.R. Bagheri; M. Reshadi

Volume 10, Issue 3 , July 2022, Pages 321-332


  Spatio-temporal (ST) clustering is a relatively new field in data mining with great popularity, especially in geographic information. Moving objects are a type of ST data where the available information on these objects includes their last position. The strategy of performing the clustering operation ...  Read More

Applied Article
Classification of Skin Lesions By Tda Alongside Xception Neural Network

N. Elyasi; M. Hosseini Moghadam

Volume 10, Issue 3 , July 2022, Pages 333-344


  In this paper, we use the topological data analysis (TDA) mapper algorithm alongside a deep convolutional neural network in order to classify some medical images.Deep learning models and convolutional neural networks can capture the Euclidean relation of a data point with its neighbor data points like ...  Read More

Original/Review Paper F.2. Numerical Analysis
Upgrading the Human Development Index (HDI) to control pandemic mortality rates: A data mining approach to COVID-19

S. Sareminia

Volume 10, Issue 3 , July 2022, Pages 345-360


  In recent years, the occurrence of various pandemics (COVID-19, SARS, etc.) and their widespread impact on human life have led researchers to focus on their pathology and epidemiology components. One of the most significant inconveniences of these epidemics is the human mortality rate, which has highly ...  Read More

Original/Review Paper
A Novel Classification and Diagnosis of Multiple Sclerosis Method using Artificial Neural Networks and Improved Multi-Level Adaptive Conditional Random Fields

Seyedeh R. Mahmudi Nezhad Dezfouli; Y. Kyani; Seyed A. Mahmoudinejad Dezfouli

Volume 10, Issue 3 , July 2022, Pages 361-372


  Due to the small size, low contrast, variable position, shape, and texture of multiple sclerosis lesions, one of the challenges of medical image processing is the automatic diagnosis and segmentation of multiple sclerosis lesions in Magnetic resonance images. Early diagnosis of these lesions in the first ...  Read More

Original/Review Paper H.3.8. Natural Language Processing
A Transformer-based Approach for Persian Text Chunking

P. Kavehzadeh; M. M. Abdollah Pour; S. Momtazi

Volume 10, Issue 3 , July 2022, Pages 373-383


  Over the last few years, text chunking has taken a significant part in sequence labeling tasks. Although a large variety of methods have been proposed for shallow parsing in English, most proposed approaches for text chunking in Persian language are based on simple and traditional concepts. In this paper, ...  Read More

Automatic Control and Guidance of Mobile Robot using Machine Learning Methods

S. Ghandibidgoli; H. Mokhtari

Volume 10, Issue 3 , July 2022, Pages 385-400


  In many applications of the robotics, the mobile robot should be guided from a source to a specific destination. The automatic control and guidance of a mobile robot is a challenge in the context of robotics. So, in current paper, this problem is studied using various machine learning methods. Controlling ...  Read More

Original/Review Paper
Voice Activity Detection using Clustering-based Method in Spectro-Temporal Features Space

N. Esfandian; F. Jahani bahnamiri; S. Mavaddati

Volume 10, Issue 3 , July 2022, Pages 401-409


  This paper proposes a novel method for voice activity detection based on clustering in spectro-temporal domain. In the proposed algorithms, auditory model is used to extract the spectro-temporal features. Gaussian Mixture Model and WK-means clustering methods are used to decrease dimensions of the spectro-temporal ...  Read More

Q-LVS: A Q-Learning-based Algorithm for Video Streaming in Peer-to-Peer Networks Considering a Token-Based Incentive Mechanism

Z. Imanimehr

Volume 10, Issue 3 , July 2022, Pages 411-422


  Peer-to-peer video streaming has reached great attention during recent years. Video streaming in peer-to-peer networks is a good way to stream video on the Internet due to the high scalability, high video quality, and low bandwidth requirements. In this paper the issue of live video streaming in peer-to-peer ...  Read More

Applied Article
Video Prediction Using Multi-Scale Deep Neural Networks

N. Shayanfar; V. Derhami; M. Rezaeian

Volume 10, Issue 3 , July 2022, Pages 423-431


  In video prediction it is expected to predict next frame of video by providing a sequence of input frames. Whereas numerous studies exist that tackle frame prediction, suitable performance is not still achieved and therefore the application is an open problem. In this article multiscale processing is ...  Read More

Original/Review Paper
A random scheme to implement m-connected k-covering wireless sensor networks

V. Ghasemi; A. Ghanbari Sorkhi

Volume 10, Issue 3 , July 2022, Pages 433-447


  Deploying m-connected k-covering (MK) wireless sensor networks (WSNs) is crucial for reliable packet delivery and target coverage. This paper proposes implementing random MK WSNs based on expected m-connected k-covering (EMK) WSNs. We define EMK WSNs as random WSNs mathematically expected to be both ...  Read More