Muhammad Usman Ghani Khan¹, Abid Mehmood², Mourad Elhadef², Shehzad Ashraf Chaudhry^2,3,*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2225-2249, 2023, DOI:10.32604/cmc.2023.038303

Abstract The proliferation of deluding data such as fake news and phony audits on news web journals, online publications, and internet business apps has been aided by the availability of the web, cell phones, and social media. Individuals can quickly fabricate comments and news on social media. The most difficult challenge is determining which news is real or fake. Accordingly, tracking down programmed techniques to recognize fake news online is imperative. With an emphasis on false news, this study presents the evolution of artificial intelligence techniques for detecting spurious social media content. This study shows past, current, and possible methods that… More >

Abdul Rehman, Dongsun Kim^*, Anand Paul

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2289-2307, 2023, DOI:10.32604/cmc.2023.036435

Abstract Disasters such as conflagration, toxic smoke, harmful gas or chemical leakage, and many other catastrophes in the industrial environment caused by hazardous distance from the peril are frequent. The calamities are causing massive fiscal and human life casualties. However, Wireless Sensors Network-based adroit monitoring and early warning of these dangerous incidents will hamper fiscal and social fiasco. The authors have proposed an early fire detection system uses machine and/or deep learning algorithms. The article presents an Intelligent Industrial Monitoring System (IIMS) and introduces an Industrial Smart Social Agent (ISSA) in the Industrial SIoT (ISIoT) paradigm. The proffered ISSA empowers smart… More >

R. Ani^1,*, O. S. Deepa², B. R. Manju¹

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3033-3048, 2023, DOI:10.32604/csse.2023.033807

Abstract The drug development process takes a long time since it requires sorting through a large number of inactive compounds from a large collection of compounds chosen for study and choosing just the most pertinent compounds that can bind to a disease protein. The use of virtual screening in pharmaceutical research is growing in popularity. During the early phases of medication research and development, it is crucial. Chemical compound searches are now more narrowly targeted. Because the databases contain more and more ligands, this method needs to be quick and exact. Neural network fingerprints were created more effectively than the well-known… More >

Nourmeen Lotfy¹, Abdulaziz Shehab^1,2,*, Mohammed Elhoseny^1,3, Ahmed Abu-Elfetouh¹

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1227-1249, 2023, DOI:10.32604/cmc.2023.039185

Abstract Despite the extensive effort to improve intelligent educational tools for smart learning environments, automatic Arabic essay scoring remains a big research challenge. The nature of the writing style of the Arabic language makes the problem even more complicated. This study designs, implements, and evaluates an automatic Arabic essay scoring system. The proposed system starts with pre-processing the student answer and model answer dataset using data cleaning and natural language processing tasks. Then, it comprises two main components: the grading engine and the adaptive fusion engine. The grading engine employs string-based and corpus-based similarity algorithms separately. After that, the adaptive fusion… More >

Kun Liu^1,2, Peiran Li³, Yu Zhang^1,*, Jia Ren¹, Xianyu Wang², Uzair Aslam Bhatti¹

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3257-3274, 2023, DOI:10.32604/cmc.2023.039430

Abstract To obtain the optimal Bayesian network (BN) structure, researchers often use the hybrid learning algorithm that combines the constraint-based (CB) method and the score-and-search (SS) method. This hybrid method has the problem that the search efficiency could be improved due to the ample search space. The search process quickly falls into the local optimal solution, unable to obtain the global optimal. Based on this, the Particle Swarm Optimization (PSO) algorithm based on the search space constraint process is proposed. In the first stage, the method uses dynamic adjustment factors to constrain the structure search space and enrich the diversity of… More >

Jiaqun Zhu¹, Hongda Chen², Yiqing Fan¹, Tongguang Ni^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2267-2283, 2023, DOI:10.32604/cmes.2023.027709

Abstract To create a green and healthy living environment, people have put forward higher requirements for the refined management of ecological resources. A variety of technologies, including satellite remote sensing, Internet of Things, artificial intelligence, and big data, can build a smart environmental monitoring system. Remote sensing image classification is an important research content in ecological environmental monitoring. Remote sensing images contain rich spatial information and multi-temporal information, but also bring challenges such as difficulty in obtaining classification labels and low classification accuracy. To solve this problem, this study develops a transductive transfer dictionary learning (TTDL) algorithm. In the TTDL, the… More >

Kai Yang^*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 317-332, 2023, DOI:10.32604/csse.2023.037266

Abstract With the rapid development of sports, the number of sports images has increased dramatically. Intelligent and automatic processing and analysis of moving images are significant, which can not only facilitate users to quickly search and access moving images but also facilitate staff to store and manage moving image data and contribute to the intellectual development of the sports industry. In this paper, a method of table tennis identification and positioning based on a convolutional neural network is proposed, which solves the problem that the identification and positioning method based on color features and contour features is not adaptable in various… More >

Shroog Alshomrani^*, Muhammad Arif, Mohammed A. Al Ghamdi

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5717-5742, 2023, DOI:10.32604/cmc.2023.038059

Abstract Coronavirus has infected more than 753 million people, ranging in severity from one person to another, where more than six million infected people died worldwide. Computer-aided diagnostic (CAD) with artificial intelligence (AI) showed outstanding performance in effectively diagnosing this virus in real-time. Computed tomography is a complementary diagnostic tool to clarify the damage of COVID-19 in the lungs even before symptoms appear in patients. This paper conducts a systematic literature review of deep learning methods for classifying the segmentation of COVID-19 infection in the lungs. We used the methodology of systematic reviews and meta-analyses (PRISMA) flow method. This research aims… More >

Atheer Joudah^1,*, Souheyl Mallat², Mounir Zrigui¹

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4973-4984, 2023, DOI:10.32604/cmc.2023.036483

Abstract This survey paper aims to show methods to analyze and classify field satellite images using deep learning and machine learning algorithms. Users of deep learning-based Convolutional Neural Network (CNN) technology to harvest fields from satellite images or generate zones of interest were among the planned application scenarios (ROI). Using machine learning, the satellite image is placed on the input image, segmented, and then tagged. In contemporary categorization, field size ratio, Local Binary Pattern (LBP) histograms, and color data are taken into account. Field satellite image localization has several practical applications, including pest management, scene analysis, and field tracking. The relationship… More >

Fahriye Gemci^1,*, Turgay Ibrikci², Ulus Cevik³

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3703-3713, 2023, DOI:10.32604/csse.2023.032706

Abstract The study aims to find a successful solution by using computer algorithms to detect remote homologous proteins, which is a significant problem in the bioinformatics field. In this experimental study, structural classification of proteins (SCOP) 1.53, SCOP benchmark, and the newly created SCOP protein database from the structural classification of proteins—extended (SCOPe) 2.07 were used to detect remote homolog proteins. N-gram method and then Term Frequency-Inverse Document Frequency (TF-IDF) weighting were performed to extract features of the protein sequences taken from these databases. Next, a smoothing process on the obtained features was performed to avoid misclassification. Finally, the proteins with… More >