Mohammed A. Al Ghamdi^*

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 881-894, 2023, DOI:10.32604/cmc.2023.037826

Abstract Considerable resources, technology, and efforts are being utilized worldwide to eradicate the coronavirus. Although certain measures taken to prevent the further spread of the disease have been successful, efforts to completely wipe out the coronavirus have been insufficient. Coronavirus patients have symptoms similar to those of chest Tuberculosis (TB) or pneumonia patients. Chest tuberculosis and coronavirus are similar because both diseases affect the lungs, cause coughing and produce an irregular respiratory system. Both diseases can be confirmed through X-ray imaging. It is a difficult task to diagnose COVID-19, as coronavirus testing kits are neither excessively available nor very reliable. In… More >

R. Surendran^1,*, Youseef Alotaibi², Ahmad F. Subahi³

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3371-3386, 2023, DOI:10.32604/csse.2023.034465

Abstract High precision and reliable wind speed forecasting have become a challenge for meteorologists. Convective events, namely, strong winds, thunderstorms, and tornadoes, along with large hail, are natural calamities that disturb daily life. For accurate prediction of wind speed and overcoming its uncertainty of change, several prediction approaches have been presented over the last few decades. As wind speed series have higher volatility and nonlinearity, it is urgent to present cutting-edge artificial intelligence (AI) technology. In this aspect, this paper presents an intelligent wind speed prediction using chicken swarm optimization with the hybrid deep learning (IWSP-CSODL) method. The presented IWSP-CSODL model… More >

Ibrahim M. Alwayle¹, Badriyya B. Al-onazi², Mohamed K. Nour³, Khaled M. Alalayah¹, Khadija M. Alaidarous¹, Ibrahim Abdulrab Ahmed⁴, Amal S. Mehanna⁵, Abdelwahed Motwakel^6,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2947-2961, 2023, DOI:10.32604/csse.2023.034456

Abstract Online reviews regarding purchasing services or products offered are the main source of users’ opinions. To gain fame or profit, generally, spam reviews are written to demote or promote certain targeted products or services. This practice is called review spamming. During the last few years, various techniques have been recommended to solve the problem of spam reviews. Previous spam detection study focuses on English reviews, with a lesser interest in other languages. Spam review detection in Arabic online sources is an innovative topic despite the vast amount of data produced. Thus, this study develops an Automated Spam Review Detection using… More >

Hala J. Alshahrani¹, Abdulkhaleq Q. A. Hassan², Khaled Tarmissi³, Amal S. Mehanna⁴, Abdelwahed Motwakel^5,*, Ishfaq Yaseen⁵, Amgad Atta Abdelmageed⁵, Mohamed I. Eldesouki⁶

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4255-4272, 2023, DOI:10.32604/cmc.2023.034821

Abstract Nowadays, the usage of social media platforms is rapidly increasing, and rumours or false information are also rising, especially among Arab nations. This false information is harmful to society and individuals. Blocking and detecting the spread of fake news in Arabic becomes critical. Several artificial intelligence (AI) methods, including contemporary transformer techniques, BERT, were used to detect fake news. Thus, fake news in Arabic is identified by utilizing AI approaches. This article develops a new hunter-prey optimization with hybrid deep learning-based fake news detection (HPOHDL-FND) model on the Arabic corpus. The HPOHDL-FND technique undergoes extensive data pre-processing steps to transform… More >

Firas Abedi¹, Hayder M. A. Ghanimi², Mohammed A. M. Sadeeq³, Ahmed Alkhayyat^4,*, Zahraa H. Kareem⁵, Sarmad Nozad Mahmood⁶, Ali Hashim Abbas⁷, Ali S. Abosinnee⁸, Waleed Khaild Al-Azzawi⁹, Mustafa Musa Jaber^10,11, Mohammed Dauwed¹²

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3359-3374, 2023, DOI:10.32604/cmc.2023.034221

Abstract Recent economic growth and development have considerably raised energy consumption over the globe. Electric load prediction approaches become essential for effective planning, decision-making, and contract evaluation of the power systems. In order to achieve effective forecasting outcomes with minimum computation time, this study develops an improved whale optimization with deep learning enabled load prediction (IWO-DLELP) scheme for energy storage systems (ESS) in smart grid platform. The major intention of the IWO-DLELP technique is to effectually forecast the electric load in SG environment for designing proficient ESS. The proposed IWO-DLELP model initially undergoes pre-processing in two stages namely min-max normalization and… More >

Minh Thanh Vo¹, Anh H. Vo², Huong Bui³, Tuong Le^4,5,*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3029-3041, 2023, DOI:10.32604/iasc.2023.034636

Abstract Nowadays, air pollution is a big environmental problem in developing countries. In this problem, particulate matter 2.5 (PM2.5) in the air is an air pollutant. When its concentration in the air is high in developing countries like Vietnam, it will harm everyone’s health. Accurate prediction of PM2.5 concentrations can help to make the correct decision in protecting the health of the citizen. This study develops a hybrid deep learning approach named PM25-CBL model for PM2.5 concentration prediction in Ho Chi Minh City, Vietnam. Firstly, this study analyzes the effects of variables on PM2.5 concentrations in Air Quality HCMC dataset. Only… More >

Badriyya B. Al-onazi¹, Mohamed K. Nour², Hassan Alshamrani³, Mesfer Al Duhayyim^4,*, Heba Mohsen⁵, Amgad Atta Abdelmageed⁶, Gouse Pasha Mohammed⁶, Abu Sarwar Zamani⁶

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2529-2544, 2023, DOI:10.32604/iasc.2023.034623

Abstract Gender analysis of Twitter could reveal significant socio-cultural differences between female and male users. Efforts had been made to analyze and automatically infer gender formerly for more commonly spoken languages’ content, but, as we now know that limited work is being undertaken for Arabic. Most of the research works are done mainly for English and least amount of effort for non-English language. The study for Arabic demographic inference like gender is relatively uncommon for social networking users, especially for Twitter. Therefore, this study aims to design an optimal marginalized stacked denoising autoencoder for gender identification on Arabic Twitter (OMSDAE-GIAT) model.… More >

Mohandu Anjaneyulu, Mohan Kubendiran^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1641-1656, 2023, DOI:10.32604/cmc.2023.035056

Abstract Traffic flow prediction in urban areas is essential in the Intelligent Transportation System (ITS). Short Term Traffic Flow (STTF) prediction impacts traffic flow series, where an estimation of the number of vehicles will appear during the next instance of time per hour. Precise STTF is critical in Intelligent Transportation System. Various extinct systems aim for short-term traffic forecasts, ensuring a good precision outcome which was a significant task over the past few years. The main objective of this paper is to propose a new model to predict STTF for every hour of a day. In this paper, we have proposed… More >

Fahad F. Alruwaili^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 99-115, 2023, DOI:10.32604/cmc.2023.034752

Abstract The Internet of Things (IoT) paradigm enables end users to access networking services amongst diverse kinds of electronic devices. IoT security mechanism is a technology that concentrates on safeguarding the devices and networks connected in the IoT environment. In recent years, False Data Injection Attacks (FDIAs) have gained considerable interest in the IoT environment. Cybercriminals compromise the devices connected to the network and inject the data. Such attacks on the IoT environment can result in a considerable loss and interrupt normal activities among the IoT network devices. The FDI attacks have been effectively overcome so far by conventional threat detection… More >

Mudiyala Aparna, Battula Srinivasa Rao^*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6909-6932, 2023, DOI:10.32604/cmc.2023.034796

Abstract Neurological disorders such as Alzheimer’s disease (AD) are very challenging to treat due to their sensitivity, technical challenges during surgery, and high expenses. The complexity of the brain structures makes it difficult to distinguish between the various brain tissues and categorize AD using conventional classification methods. Furthermore, conventional approaches take a lot of time and might not always be precise. Hence, a suitable classification framework with brain imaging may produce more accurate findings for early diagnosis of AD. Therefore in this paper, an effective hybrid Xception and Fractalnet-based deep learning framework are implemented to classify the stages of AD into… More >