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  • Open Access

    ARTICLE

    A Cloud Based Sentiment Analysis through Logistic Regression in AWS Platform

    Mohemmed Sha*

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 857-868, 2023, DOI:10.32604/csse.2023.031321 - 16 August 2022

    Abstract The use of Amazon Web Services is growing rapidly as more users are adopting the technology. It has various functionalities that can be used by large corporates and individuals as well. Sentiment analysis is used to build an intelligent system that can study the opinions of the people and help to classify those related emotions. In this research work, sentiment analysis is performed on the AWS Elastic Compute Cloud (EC2) through Twitter data. The data is managed to the EC2 by using elastic load balancing. The collected data is subjected to preprocessing approaches to clean More >

  • Open Access

    ARTICLE

    Big Data Analytics: Deep Content-Based Prediction with Sampling Perspective

    Waleed Albattah, Saleh Albahli*

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 531-544, 2023, DOI:10.32604/csse.2023.021548 - 16 August 2022

    Abstract The world of information technology is more than ever being flooded with huge amounts of data, nearly 2.5 quintillion bytes every day. This large stream of data is called big data, and the amount is increasing each day. This research uses a technique called sampling, which selects a representative subset of the data points, manipulates and analyzes this subset to identify patterns and trends in the larger dataset being examined, and finally, creates models. Sampling uses a small proportion of the original data for analysis and model training, so that it is relatively faster while… More >

  • Open Access

    ARTICLE

    SA-MSVM: Hybrid Heuristic Algorithm-based Feature Selection for Sentiment Analysis in Twitter

    C. P. Thamil Selvi1,*, R. PushpaLakshmi2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2439-2456, 2023, DOI:10.32604/csse.2023.029254 - 01 August 2022

    Abstract One of the drastically growing and emerging research areas used in most information technology industries is Bigdata analytics. Bigdata is created from social websites like Facebook, WhatsApp, Twitter, etc. Opinions about products, persons, initiatives, political issues, research achievements, and entertainment are discussed on social websites. The unique data analytics method cannot be applied to various social websites since the data formats are different. Several approaches, techniques, and tools have been used for big data analytics, opinion mining, or sentiment analysis, but the accuracy is yet to be improved. The proposed work is motivated to do… More >

  • Open Access

    ARTICLE

    Design of Online Vitals Monitor by Integrating Big Data and IoT

    E. Afreen Banu1,*, V. Rajamani2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2469-2487, 2023, DOI:10.32604/csse.2023.021332 - 01 August 2022

    Abstract In this work, we design a multisensory IoT-based online vitals monitor (hereinafter referred to as the VITALS) to sense four bedside physiological parameters including pulse (heart) rate, body temperature, blood pressure, and peripheral oxygen saturation. Then, the proposed system constantly transfers these signals to the analytics system which aids in enhancing diagnostics at an earlier stage as well as monitoring after recovery. The core hardware of the VITALS includes commercial off-the-shelf sensing devices/medical equipment, a powerful microcontroller, a reliable wireless communication module, and a big data analytics system. It extracts human vital signs in a… More >

  • Open Access

    ARTICLE

    Modeling of Optimal Deep Learning Based Flood Forecasting Model Using Twitter Data

    G. Indra1,*, N. Duraipandian2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1455-1470, 2023, DOI:10.32604/iasc.2023.027703 - 19 July 2022

    Abstract A flood is a significant damaging natural calamity that causes loss of life and property. Earlier work on the construction of flood prediction models intended to reduce risks, suggest policies, reduce mortality, and limit property damage caused by floods. The massive amount of data generated by social media platforms such as Twitter opens the door to flood analysis. Because of the real-time nature of Twitter data, some government agencies and authorities have used it to track natural catastrophe events in order to build a more rapid rescue strategy. However, due to the shorter duration of… More >

  • Open Access

    ARTICLE

    Intelligent Smart Grid Stability Predictive Model for Cyber-Physical Energy Systems

    Ashit Kumar Dutta1,*, Manal Al Faraj1, Yasser Albagory2, Mohammad zeid M Alzamil1, Abdul Rahaman Wahab Sait3

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1219-1231, 2023, DOI:10.32604/csse.2023.026467 - 15 June 2022

    Abstract A cyber physical energy system (CPES) involves a combination of processing, network, and physical processes. The smart grid plays a vital role in the CPES model where information technology (IT) can be related to the physical system. At the same time, the machine learning (ML) models find useful for the smart grids integrated into the CPES for effective decision making. Also, the smart grids using ML and deep learning (DL) models are anticipated to lessen the requirement of placing many power plants for electricity utilization. In this aspect, this study designs optimal multi-head attention based… More >

  • Open Access

    ARTICLE

    Big Data Analytics with Optimal Deep Learning Model for Medical Image Classification

    Tariq Mohammed Alqahtani*

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1433-1449, 2023, DOI:10.32604/csse.2023.025594 - 15 June 2022

    Abstract In recent years, huge volumes of healthcare data are getting generated in various forms. The advancements made in medical imaging are tremendous owing to which biomedical image acquisition has become easier and quicker. Due to such massive generation of big data, the utilization of new methods based on Big Data Analytics (BDA), Machine Learning (ML), and Artificial Intelligence (AI) have become essential. In this aspect, the current research work develops a new Big Data Analytics with Cat Swarm Optimization based deep Learning (BDA-CSODL) technique for medical image classification on Apache Spark environment. The aim of… More >

  • Open Access

    ARTICLE

    Big Data Analytics with Artificial Intelligence Enabled Environmental Air Pollution Monitoring Framework

    Manar Ahmed Hamza1,*, Hadil Shaiba2, Radwa Marzouk3, Ahmad Alhindi4, Mashael M. Asiri5, Ishfaq Yaseen1, Abdelwahed Motwakel1, Mohammed Rizwanullah1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3235-3250, 2022, DOI:10.32604/cmc.2022.029604 - 16 June 2022

    Abstract Environmental sustainability is the rate of renewable resource harvesting, pollution control, and non-renewable resource exhaustion. Air pollution is a significant issue confronted by the environment particularly by highly populated countries like India. Due to increased population, the number of vehicles also continues to increase. Each vehicle has its individual emission rate; however, the issue arises when the emission rate crosses the standard value and the quality of the air gets degraded. Owing to the technological advances in machine learning (ML), it is possible to develop prediction approaches to monitor and control pollution using real time… More >

  • Open Access

    ARTICLE

    Foundation Treatment in Urban Underground Engineering Using Big Data Analysis for Smart City Applications

    Fei Liu1,2, Yunkai Zhang1,2, Jian Zhang3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 153-172, 2022, DOI:10.32604/cmes.2022.017967 - 02 June 2022

    Abstract A core element of the sustainable approach to global living quality improvement can now become the intensive and organized usage of underground space. There is a growing interest in underground building and growth worldwide. The reduced consumption of electricity, effective preservation of green land, sustainable wastewater and sewage treatment, efficient reverse degradation of the urban environment, and reliable critical infrastructure management can improve the quality of life. At the same time, technological innovations such as artificial intelligence (AI), cloud computing (CC), the internet of things (IoT), and big data analytics (BDA) play a significant role… More >

  • Open Access

    ARTICLE

    Week Ahead Electricity Power and Price Forecasting Using Improved DenseNet-121 Method

    Muhammad Irfan1, Ali Raza2,*, Faisal Althobiani3, Nasir Ayub4,5, Muhammad Idrees6, Zain Ali7, Kashif Rizwan4, Abdullah Saeed Alwadie1, Saleh Mohammed Ghonaim3, Hesham Abdushkour3, Saifur Rahman1, Omar Alshorman1, Samar Alqhtani8

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4249-4265, 2022, DOI:10.32604/cmc.2022.025863 - 21 April 2022

    Abstract In the Smart Grid (SG) residential environment, consumers change their power consumption routine according to the price and incentives announced by the utility, which causes the prices to deviate from the initial pattern. Thereby, electricity demand and price forecasting play a significant role and can help in terms of reliability and sustainability. Due to the massive amount of data, big data analytics for forecasting becomes a hot topic in the SG domain. In this paper, the changing and non-linearity of consumer consumption pattern complex data is taken as input. To minimize the computational cost and… More >

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