ISSN: 1683-3198
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e-ISSN: 2309-4524
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DOI: 10.34028/iajit
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The International Arab Journal of Information Technology
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SHARD-FEMF: Adaptive Forensic Evidence Management Framework using Blockchain Sharding and IPFS
Praveen Dhulavvagol,Sashikumar Totad,Atrey Anagal
#Blockchain
#sharding
#ethereum
#base64
#IPFS
Software Component Selection: An Optimized Selection Criterion for Component-based Software Engineering (CBSE)
Ahmad Nabot
#Multi-criteria decision making
#assessment
#evidential reasoning
#software component
#quality criteria
SHARD-FEMF: Adaptive Forensic Evidence Management Framework using Blockchain Sharding and IPFS
Praveen Dhulavvagol,Sashikumar Totad,Atrey Anagal
#Blockchain
#sharding
#ethereum
#base64
#IPFS
Software Component Selection: An Optimized Selection Criterion for Component-based Software Engineering (CBSE)
Ahmad Nabot
#Multi-criteria decision making
#assessment
#evidential reasoning
#software component
#quality criteria
An Unsupervised Feed Forward Neural Network Method for Efficient Clustering
Roya Asadi,Mitra Asadi,Shokoofeh Asadi
#Artificial neural network
#feed forward neural network
#unsupervised learning
#clustering
#real weight
An Effective Reference-Point-Set (RPS) Based Bi-Directional Frequent Itemset Generation
Ambily Balaram,Nedunchezhian Raju
#Reference point
#reference-point-set
#transactional buckets
#sparse region
#dense region
Exact Algorithm for Batch Scheduling on Unrelated Machine
Hemmak Allaoua
#Scheduling
#unrelated machine
#exact method
#parallel machine
#batch scheduling
New Model of Feature Selection based Chaotic Firefly Algorithm for Arabic Text Categorization
Meryeme Hadni,Hassane Hjiaj
#Chaotic method
#firefly algorithm
#arabic text categorization
#feature selection
A Hybrid Grey Wolf-Whale Optimization Algorithm for Classification of Corona Virus Genome Sequences using Deep Learning
Muthulakshmi Murugaiah,Murugeswari Ganesan
#Corona virus genome
#deep learning
#feature selection
#GWO
#hybrid optimization
#WOA
Retina Disorders Classification via OCT Scan: A Comparative Study between Self-Supervised Learning and Transfer Learning
Saeed Shurrab,Yazan Shannak,Rehab Duwairi
#OCT images
#retina disorders
#self-supervised learning
#transfer learning
#resnet34
A Method of Extracting Malware Features Based on Gini Impurity Increment and Improved TF-IDF
Shimiao Sun,Yashu Liu
#Gini impurity increment
#TF-IDF
#feature selection
#dimensionality reduction
Privacy-Preserving Data Mining in Homogeneous
Department of Communication Electronics and Compute r Engineering, Helwan University, Egypt
#
Optimum Threshold Parameter Estimation of
MohammadMotiur Rahman1, MithunKumar Pk1, and MohammadShorif Uddin2 1Department of Computer Science and Engineering, Maw lana Bhashani Science and
#
211
Rangan Kodandaram, Shashank Mallikarjun, Manikantan Krishnamuthan, and Ramachandran Sivan
# FR
# feature extraction
# discrete wavelet transform
# DCT
# feature selection
# BPSO
Implementation of Image Processing System using Handover Technique with Map Reduce Based on Big Data in the Cloud Environment
#
An Intelligent CRF Based Feature Selection for
1
#
Fuzzy and Neuro-Fuzzy Modeling of a Fermentation Process
Abstract: Neuro-fuzzy modeling may be qualified as a grey-box technique, since it combines the transparency of rule-based
#Yeast fermentation
# fed-batch
# takagi-sugeno model
# levenberg-marquardt algorithm
Computing Environment
# Distributed computing
# cloud computing
# knowledge d iscovery
# rough set
Impulse Noise Reduction for Texture Images Using Real Word Spelling Correction Algorithm and
1Faculty of Computer Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran 2Department of Computer Science and Engineering, Shiraz University, Shiraz, Iran
#Image noise reduction
# local binary pattern
# real word spelling correction
# texture analysis
Machine Learning based Intelligent Framework for Data Preprocessing
Abstract: Data preprocessing having a pivotal role in data mining ensures reduction in cost by catering inconsistent,
#Machine learning
# hidden markov model
# conditional random fields
# preprocessing
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