Fares Abdulhafidh Dael^1,*, Ömer Çağrı Yavuz², Uğur Yavuz¹

Computer Systems Science and Engineering, Vol.47, No.1, pp. 19-35, 2023, DOI:10.32604/csse.2023.037903

Abstract The key indication of a nation’s economic development and strength is the stock market. Inflation and economic expansion affect the volatility of the stock market. Given the multitude of factors, predicting stock prices is intrinsically challenging. Predicting the movement of stock price indexes is a difficult component of predicting financial time series. Accurately predicting the price movement of stocks can result in financial advantages for investors. Due to the complexity of stock market data, it is extremely challenging to create accurate forecasting models. Using machine learning and other algorithms to anticipate stock prices is an interesting area. The purpose of… More >

Iyad Katib¹, Mahmoud Ragab^2,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3749-3765, 2023, DOI:10.32604/csse.2023.036796

Abstract The concept of smart healthcare has seen a gradual increase with the expansion of information technology. Smart healthcare will use a new generation of information technologies, like artificial intelligence, the Internet of Things (IoT), cloud computing, and big data, to transform the conventional medical system in an all-around way, making healthcare highly effective, more personalized, and more convenient. This work designs a new Heap Based Optimization with Deep Quantum Neural Network (HBO-DQNN) model for decision-making in smart healthcare applications. The presented HBO-DQNN model majorly focuses on identifying and classifying healthcare data. In the presented HBO-DQNN model, three stages of operations… More >

Nabil Almalki^1,2, Mrim M. Alnfiai^1,3, Fahd N. Al-Wesabi⁴, Mesfer Alduhayyem⁵, Anwer Mustafa Hilal^6,*, Manar Ahmed Hamza⁶

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6719-6736, 2023, DOI:10.32604/cmc.2023.034417

Abstract Mobile communication and the Internet of Things (IoT) technologies have recently been established to collect data from human beings and the environment. The data collected can be leveraged to provide intelligent services through different applications. It is an extreme challenge to monitor disabled people from remote locations. It is because day-to-day events like falls heavily result in accidents. For a person with disabilities, a fall event is an important cause of mortality and post-traumatic complications. Therefore, detecting the fall events of disabled persons in smart homes at early stages is essential to provide the necessary support and increase their survival… More >

Mesfer Al Duhayyim^1,*, Saud S. Alotaibi², Shaha Al-Otaibi³, Fahd N. Al-Wesabi⁴, Mahmoud Othman⁵, Ishfaq Yaseen⁶, Mohammed Rizwanullah⁶, Abdelwahed Motwakel⁶

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3315-3332, 2023, DOI:10.32604/cmc.2023.033250

Abstract Proper waste management models using recent technologies like computer vision, machine learning (ML), and deep learning (DL) are needed to effectively handle the massive quantity of increasing waste. Therefore, waste classification becomes a crucial topic which helps to categorize waste into hazardous or non-hazardous ones and thereby assist in the decision making of the waste management process. This study concentrates on the design of hazardous waste detection and classification using ensemble learning (HWDC-EL) technique to reduce toxicity and improve human health. The goal of the HWDC-EL technique is to detect the multiple classes of wastes, particularly hazardous and non-hazardous wastes.… More >

Liaqat Ali¹, Saif E. A. Alnawayseh², Mohammed Salahat³, Taher M. Ghazal^4,5,*, Mohsen A. A. Tomh⁶, Beenu Mago⁷

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1095-1104, 2023, DOI:10.32604/iasc.2023.031335

Abstract The immediate international spread of severe acute respiratory syndrome revealed the potential threat of infectious diseases in a closely integrated and interdependent world. When an outbreak occurs, each country must have a well-coordinated and preventative plan to address the situation. Information and Communication Technologies have provided innovative approaches to dealing with numerous facets of daily living. Although intelligent devices and applications have become a vital part of our everyday lives, smart gadgets have also led to several physical and psychological health problems in modern society. Here, we used an artificial intelligence AI-based system for disease prediction using an Artificial Neural… More >

Nidhi Agarwal^1,2, M. Gokilavani³, S. Nagarajan⁴, S. Saranya⁵, Hadeel Alsolai⁶, Sami Dhahbi^7,*, Amira Sayed Abdelaziz⁸

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 141-152, 2023, DOI:10.32604/cmc.2023.030074

Abstract In recent times, wireless sensor network (WSN) finds their suitability in several application areas, ranging from military to commercial ones. Since nodes in WSN are placed arbitrarily in the target field, node localization (NL) becomes essential where the positioning of the nodes can be determined by the aid of anchor nodes. The goal of any NL scheme is to improve the localization accuracy and reduce the localization error rate. With this motivation, this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme (IAOAB-NLS) for WSN. The presented IAOAB-NLS model makes use of anchor nodes to… More >

Manar Ahmed Hamza^1,*, Hadeel Alsolai², Jaber S. Alzahrani³, Mohammad Alamgeer^4,5, Mohamed Mahmoud Sayed⁶, Abu Sarwar Zamani¹, Ishfaq Yaseen¹, Abdelwahed Motwakel¹

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6563-6577, 2022, DOI:10.32604/cmc.2022.031541

Abstract Intelligent Transportation System (ITS) is one of the revolutionary technologies in smart cities that helps in reducing traffic congestion and enhancing traffic quality. With the help of big data and communication technologies, ITS offers real-time investigation and highly-effective traffic management. Traffic Flow Prediction (TFP) is a vital element in smart city management and is used to forecast the upcoming traffic conditions on transportation network based on past data. Neural Network (NN) and Machine Learning (ML) models are widely utilized in resolving real-time issues since these methods are capable of dealing with adaptive data over a period of time. Deep Learning… More >

Ahmed Ali Ajmi^1,2, Noor Shakir Mahmood^1,2, Khairur Rijal Jamaludin^1,*, Hayati Habibah Abdul Talib¹, Shamsul Sarip¹, Hazilah Mad Kaidi¹

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5025-5039, 2022, DOI:10.32604/cmc.2022.031239

Abstract The literature that a lack of integration between the performance shaping factors (PSFs) and the energy management performance (EMP) is one of the critical problems that prevent performance improvement and reduces the power plant’s efficiency. To solve this problem, this article aims to achieve two main objectives: (1) Systematically investigate and identify the critical success factors (CSFs) for integration with PSFs and EMP; (2) Develop a novel modelling approach to predict the performance of power plants based on innovative integrated strategies. The research methodology is grounded on the theoretical and practical approach to improving performance. The Newcastle Ottawa Scale (NOS)… More >

Thavavel Vaiyapuri¹, S. Srinivasan², Mohamed Yacin Sikkandar³, T. S. Balaji^4,5, Seifedine Kadry⁶, Maytham N. Meqdad⁷, Yunyoung Nam^8,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5543-5557, 2022, DOI:10.32604/cmc.2022.023919

Abstract In past decades, retinal diseases have become more common and affect people of all age grounds over the globe. For examining retinal eye disease, an artificial intelligence (AI) based multilabel classification model is needed for automated diagnosis. To analyze the retinal malady, the system proposes a multiclass and multi-label arrangement method. Therefore, the classification frameworks based on features are explicitly described by ophthalmologists under the application of domain knowledge, which tends to be time-consuming, vulnerable generalization ability, and unfeasible in massive datasets. Therefore, the automated diagnosis of multi-retinal diseases becomes essential, which can be solved by the deep learning (DL)… More >

Nasser Ali Aljarallah^1,2, Ashit Kumar Dutta^3,*, Majed Alsanea⁴, Abdul Rahaman Wahab Sait⁵

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1853-1868, 2023, DOI:10.32604/csse.2023.028755

Abstract A learning management system (LMS) is a software or web based application, commonly utilized for planning, designing, and assessing a particular learning procedure. Generally, the LMS offers a method of creating and delivering content to the instructor, monitoring students’ involvement, and validating their outcomes. Since mental health issues become common among studies in higher education globally, it is needed to properly determine it to improve mental stability. This article develops a new seven spot lady bird feature selection with optimal sparse autoencoder (SSLBFS-OSAE) model to assess students’ mental health on LMS. The major aim of the SSLBFS-OSAE model is to… More >