Original/Review Paper H.3. Artificial Intelligence
A New Hybrid Method to Detect Risk of Gastric Cancer using Machine Learning Techniques

Ali Zahmatkesh Zakariaee; Hossein Sadr; Mohamad Reza Yamaghani

Volume 11, Issue 4 , November 2023, Pages 505-515


  Machine learning (ML) is a popular tool in healthcare while it can help to analyze large amounts of patient data, such as medical records, predict diseases, and identify early signs of cancer. Gastric cancer starts in the cells lining the stomach and is known as the 5th most common cancer worldwide. ...  Read More

Original/Review Paper H.6.3.2. Feature evaluation and selection
Auto-UFSTool: An Automatic Unsupervised Feature Selection Toolbox for MATLAB

Farhad Abedinzadeh Torghabeh; Yeganeh Modaresnia; Seyyed Abed Hosseini

Volume 11, Issue 4 , November 2023, Pages 517-524


  Various data analysis research has recently become necessary in to find and select relevant features without class labels using Unsupervised Feature Selection (UFS) approaches. Despite the fact that several open-source toolboxes provide feature selection techniques to reduce redundant features, data ...  Read More

Original/Review Paper H.3. Artificial Intelligence
Autoencoder-PCA-based Online Supervised Feature Extraction-Selection Approach

Amir Mehrabinezhad; Mohammad Teshnelab; Arash Sharifi

Volume 11, Issue 4 , November 2023, Pages 525-534


  Due to the growing number of data-driven approaches, especially in artificial intelligence and machine learning, extracting appropriate information from the gathered data with the best performance is a remarkable challenge. The other important aspect of this issue is storage costs. The principal component ...  Read More

Methodologies H.3. Artificial Intelligence
Identification of Influential Nodes in Social Networks based on Profile Analysis

Zeinab Poshtiban; Elham Ghanbari; Mohammadreza Jahangir

Volume 11, Issue 4 , November 2023, Pages 535-545


  Analyzing the influence of people and nodes in social networks has attracted a lot of attention. Social networks gain meaning, despite the groups, associations, and people interested in a specific issue or topic, and people demonstrate their theoretical and practical tendencies in such places. Influential ...  Read More

Technical Paper H.5. Image Processing and Computer Vision
Using Convolutional Neural Network to Enhance Classification Accuracy of Cancerous Lung Masses from CT Scan Images

Mohammad Mahdi Nakhaie; Sasan Karamizadeh; Mohammad Ebrahim Shiri; Kambiz Badie

Volume 11, Issue 4 , November 2023, Pages 547-559


  Lung cancer is a highly serious illness, and detecting cancer cells early significantly enhances patients' chances of recovery. Doctors regularly examine a large number of CT scan images, which can lead to fatigue and errors. Therefore, there is a need to create a tool that can automatically detect and ...  Read More

Original/Review Paper H.3. Artificial Intelligence
LSTM Modeling and Optimization of Rice (Oryza sativa L.) Seedling Growth using Intelligent Chamber

Hamid Ghaffari; Hemmatollah Pirdashti; Mohammad Reza Kangavari; Sjoerd Boersma

Volume 11, Issue 4 , November 2023, Pages 561-571


  An intelligent growth chamber was designed in 2021 to model and optimize rice seedlings' growth. According to this, an experiment was implemented at Sari University of Agricultural Sciences and Natural Resources, Iran, in March, April, and May 2021. The model inputs included radiation, temperature, carbon ...  Read More

Original/Review Paper H.3. Artificial Intelligence
Fast COVID-19 Infection Prediction with In-House Data Using Machine Learning Classification Algorithms: A Case Study of Iran

Ali Rebwar Shabrandi; Ali Rajabzadeh Ghatari; Nader Tavakoli; Mohammad Dehghan Nayeri; Sahar Mirzaei

Volume 11, Issue 4 , November 2023, Pages 573-585


  To mitigate COVID-19’s overwhelming burden, a rapid and efficient early screening scheme for COVID-19 in the first-line is required. Much research has utilized laboratory tests, CT scans, and X-ray data, which are obstacles to agile and real-time screening. In this study, we propose a user-friendly ...  Read More

Original/Review Paper H.3. Artificial Intelligence
Investigating Shallow and Deep Learning Techniques for Emotion Classification in Short Persian Texts

Mahdi Rasouli; Vahid Kiani

Volume 11, Issue 4 , November 2023, Pages 587-598


  The identification of emotions in short texts of low-resource languages poses a significant challenge, requiring specialized frameworks and computational intelligence techniques. This paper presents a comprehensive exploration of shallow and deep learning methods for emotion detection in short Persian ...  Read More

Technical Paper G.3.7. Database Machines
A Multi-layered Hidden Markov Model for Real-Time Fraud Detection in Electronic Financial Transactions

Abdul Aziz Danaa Abukari; Mohammed Daabo Ibrahim; Alhassan Abdul-Barik

Volume 11, Issue 4 , November 2023, Pages 599-608


  Hidden Markov Models (HMMs) are machine learning models that has been applied to a range of real-life applications including intrusion detection, pattern recognition, thermodynamics, statistical mechanics among others. A multi-layered HMMs for real-time fraud detection and prevention whilst reducing ...  Read More

Technical Paper B.3. Communication/Networking and Information Technology
Exploring Impact of Data Noise on IoT Security: a Study using Decision Tree Classification in Intrusion Detection Systems

S. Mojtaba Matinkhah; Roya Morshedi; Akbar Mostafavi

Volume 11, Issue 4 , November 2023, Pages 609-626


  The Internet of Things (IoT) has emerged as a rapidly growing technology that enables seamless connectivity between a wide variety of devices. However, with this increased connectivity comes an increased risk of cyber-attacks. In recent years, the development of intrusion detection systems (IDS) has ...  Read More

Original/Review Paper H.3. Artificial Intelligence
Applying Twin-Hybrid Feature Selection Scheme on Transient Multi-Trajectory Data for Transient Stability Prediction

Seyed Alireza Bashiri Mosavi; Omid Khalaf Beigi

Volume 11, Issue 4 , November 2023, Pages 627-638


  A speedy and accurate transient stability assessment (TSA) is gained by employing efficient machine learning- and statistics-based (MLST) algorithms on transient nonlinear time series space. In the MLST’s world, the feature selection process by forming compacted optimal transient feature space ...  Read More

Methodologies H.6. Pattern Recognition
Parallel Incremental Mining of Regular-Frequent Patterns from WSNs Big Data

Sadegh Rahmani Rahmani-Boldaji; Mehdi Bateni; Mahmood Mortazavi Dehkordi

Volume 11, Issue 4 , November 2023, Pages 639-648


  Efficient regular-frequent pattern mining from sensors-produced data has become a challenge. The large volume of data leads to prolonged runtime, thus delaying vital predictions and decision makings which need an immediate response. So, using big data platforms and parallel algorithms is an appropriate ...  Read More