Xiong Luo^1,*, Yongqiang Cheng², Zhifang Liao³

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 7-11, 2024, DOI:10.32604/cmes.2024.056214 - 20 August 2024

Abstract This article has no abstract. More >

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 - 26 May 2023

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 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 - 03 April 2023

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… 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 - 28 December 2022

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… 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 - 31 October 2022

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,… 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 - 29 September 2022

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 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 - 22 September 2022

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 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 - 15 June 2022

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… More >

Ashit Kumar Dutta^1,*, Yasser Albagory², Manal Al Faraj¹, Majed Alsanea³, Abdul Rahaman Wahab Sait⁴

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1419-1432, 2023, DOI:10.32604/csse.2023.027377 - 15 June 2022

Abstract Accurate soil prediction is a vital parameter involved to decide appropriate crop, which is commonly carried out by the farmers. Designing an automated soil prediction tool helps to considerably improve the efficacy of the farmers. At the same time, fuzzy logic (FL) approaches can be used for the design of predictive models, particularly, Fuzzy Cognitive Maps (FCMs) have involved the concept of uncertainty representation and cognitive mapping. In other words, the FCM is an integration of the recurrent neural network (RNN) and FL involved in the knowledge engineering phase. In this aspect, this paper introduces… More >

Ahmed S. Almasoud^*

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1485-1498, 2023, DOI:10.32604/csse.2023.025190 - 15 June 2022

Abstract The latest advancements in computer vision and deep learning (DL) techniques pave the way to design novel tools for the detection and monitoring of forest fires. In this view, this paper presents an intelligent wild forest fire detection and alarming system using deep learning (IWFFDA-DL) model. The proposed IWFFDA-DL technique aims to identify forest fires at earlier stages through integrated sensors. The proposed IWFFDA-DL system includes an Integrated sensor system (ISS) combining an array of sensors that acts as the major input source that helps to forecast the fire. Then, the attention based convolution neural More >