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  • Open Access

    ARTICLE

    Automatic Sentimental Analysis by Firefly with Levy and Multilayer Perceptron

    D. Elangovan1,*, V. Subedha2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2797-2808, 2023, DOI:10.32604/csse.2023.031988

    Abstract The field of sentiment analysis (SA) has grown in tandem with the aid of social networking platforms to exchange opinions and ideas. Many people share their views and ideas around the world through social media like Facebook and Twitter. The goal of opinion mining, commonly referred to as sentiment analysis, is to categorise and forecast a target’s opinion. Depending on if they provide a positive or negative perspective on a given topic, text documents or sentences can be classified. When compared to sentiment analysis, text categorization may appear to be a simple process, but number of challenges have prompted numerous… More >

  • Open Access

    ARTICLE

    Multi-Layer Fog-Cloud Architecture for Optimizing the Placement of IoT Applications in Smart Cities

    Mohammad Aldossary*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 633-649, 2023, DOI:10.32604/cmc.2023.035414

    Abstract In the smart city paradigm, the deployment of Internet of Things (IoT) services and solutions requires extensive communication and computing resources to place and process IoT applications in real time, which consumes a lot of energy and increases operational costs. Usually, IoT applications are placed in the cloud to provide high-quality services and scalable resources. However, the existing cloud-based approach should consider the above constraints to efficiently place and process IoT applications. In this paper, an efficient optimization approach for placing IoT applications in a multi-layer fog-cloud environment is proposed using a mathematical model (Mixed-Integer Linear Programming (MILP)). This approach… More >

  • Open Access

    ARTICLE

    Design an Artificial Neural Network by MLP Method; Analysis of the Relationship between Demographic Variables, Resilience, COVID-19 and Burnout

    Chao-Hsi Huang1, Tsung-Shun Hsieh2,3, Hsiao-Ting Chien4, Ehsan Eftekhari-Zadeh5,*, Saba Amiri6

    International Journal of Mental Health Promotion, Vol.24, No.6, pp. 825-841, 2022, DOI:10.32604/ijmhp.2022.021899

    Abstract In addition to the effect that the COVID-19 pandemic has had on the physical and mental health of individuals, it has also led to a change in the mental and emotional state of many employees. Especially among businesses and private companies, which faced many restrictions due to the special conditions of the pandemic. Therefore, the present study aimed to design an artificial neural network with MLP technique to analyze the relationship between demographic variables, resilience, COVID-19 and burnout in start-ups in Iran. The research method was quantitative. Managers and employees of start-ups formed the statistical population of the study, based… More >

  • Open Access

    ARTICLE

    Impact of Portable Executable Header Features on Malware Detection Accuracy

    Hasan H. Al-Khshali1,*, Muhammad Ilyas2

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 153-178, 2023, DOI:10.32604/cmc.2023.032182

    Abstract One aspect of cybersecurity, incorporates the study of Portable Executables (PE) files maleficence. Artificial Intelligence (AI) can be employed in such studies, since AI has the ability to discriminate benign from malicious files. In this study, an exclusive set of 29 features was collected from trusted implementations, this set was used as a baseline to analyze the presented work in this research. A Decision Tree (DT) and Neural Network Multi-Layer Perceptron (NN-MLPC) algorithms were utilized during this work. Both algorithms were chosen after testing a few diverse procedures. This work implements a method of subgrouping features to answer questions such… More >

  • Open Access

    ARTICLE

    Tasks Scheduling in Cloud Environment Using PSO-BATS with MLRHE

    Anwar R Shaheen*, Sundar Santhosh Kumar

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2963-2978, 2023, DOI:10.32604/iasc.2023.025780

    Abstract Cloud computing plays a significant role in Information Technology (IT) industry to deliver scalable resources as a service. One of the most important factor to increase the performance of the cloud server is maximizing the resource utilization in task scheduling. The main advantage of this scheduling is to maximize the performance and minimize the time loss. Various researchers examined numerous scheduling methods to achieve Quality of Service (QoS) and to reduce execution time. However, it had disadvantages in terms of low throughput and high response time. Hence, this study aimed to schedule the task efficiently and to eliminate the faults… More >

  • Open Access

    ARTICLE

    Predict the Chances of Heart Abnormality in Diabetic Patients Through Machine Learning

    Monika Saraswat*, A. K. Wadhwani, Sulochana Wadhwani

    Journal on Artificial Intelligence, Vol.4, No.2, pp. 61-76, 2022, DOI:10.32604/jai.2022.028140

    Abstract Today, more families are affected by Diabetes Mellitus (DM) disease on account of its continually increasing occurrence. Most patients remain unknown about their health quality or the DM’s risk factors prior to diagnosis. The medical world has witnessed that individuals are affected by two different diabetes namely a) Type-1 diabetes (T1D), as well as b) Type-2 diabetes (T2D). As Type 2 Diabetes affects the other organs of the body, the proposed system concentrates specifically on Type 2 Diabetes. This work aims to ascertain the cardiac disorder in T2D patients. As of the ECG dataset, the requisite data is gathered it… More >

  • Open Access

    ARTICLE

    Multi-Layer and Multi-Objective Optimization Design of Supporting Structure of Large-Scale Spherical Solar Concentrator for the Space Solar Power Station

    Yang Yang, Jun Hu, Lin Zhu*, Mengchen Pei

    Journal of Renewable Materials, Vol.10, No.11, pp. 2835-2849, 2022, DOI:10.32604/jrm.2022.021840

    Abstract Space solar power station is a novel renewable energy equipment in space to provide the earth with abundant and continuous power. The Orb-shaped Membrane Energy Gathering Array, one of the alternative construction schemes in China, is promising for collecting space sunlight with a large-scale spherical concentrator. Both the structural and optical performances such as root mean square deformation, natural frequency, system mass, and sunlight blocking rate have significant influences on the system property of the concentrator. Considering the comprehensive performance of structure and optic, this paper proposes a novel mesh grid based on normal polyhedron projection and spherical arc bisection… More > Graphic Abstract

    Multi-Layer and Multi-Objective Optimization Design of Supporting Structure of Large-Scale Spherical Solar Concentrator for the Space Solar Power Station

  • Open Access

    ARTICLE

    An Efficient Ensemble Model for Various Scale Medical Data

    Heba A. Elzeheiry*, Sherief Barakat, Amira Rezk

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1283-1305, 2022, DOI:10.32604/cmc.2022.027345

    Abstract Electronic Health Records (EHRs) are the digital form of patients’ medical reports or records. EHRs facilitate advanced analytics and aid in better decision-making for clinical data. Medical data are very complicated and using one classification algorithm to reach good results is difficult. For this reason, we use a combination of classification techniques to reach an efficient and accurate classification model. This model combination is called the Ensemble model. We need to predict new medical data with a high accuracy value in a small processing time. We propose a new ensemble model MDRL which is efficient with different datasets. The MDRL… More >

  • Open Access

    ARTICLE

    Voice to Face Recognition Using Spectral ERB-DMLP Algorithms

    Fauzi A. Bala1,2,*, Osman N. Ucan1, Oguz Bayat1

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2187-2204, 2022, DOI:10.32604/cmc.2022.024205

    Abstract Designing an authentication system for securing the power plants are important to allow only specific staffs of the power plant to access the certain blocks so that they can be restricted from using high risk-oriented equipment. This authentication is also vital to prevent any security threats or risks like compromises of business server, release of confidential data etc. Though conventional works attempted to accomplish better authentication, they lacked with respect to accuracy. Hence, the study aims to enhance the recognition rate by introducing a voice recognition system as a personal authentication based on Deep Learning (DL) due to its ability… More >

  • Open Access

    ARTICLE

    An Experimental and Numerical Study on the Ballistic Performance of Multi-Layered Moderately-Thick Metallic Targets against 12.7-mm Projectiles

    Kailei Wang, Mingjing Li*, Peng Yan, Leiting Dong*

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 165-197, 2022, DOI:10.32604/cmes.2022.019188

    Abstract The main goal of this work is to study the ballistic performance of multi-layered moderately-thick metallic targets. Several target configurations have been considered in this work, with various types of interlayer connection (spaced, contacted and adhesive) and the number of layers (four and eight), and the influence of target configurations on ballistic performance has been studied experimentally and numerically. In the experiments, the targets were impacted by 12.7-mm projectiles at a velocity around 820 m/s. The experimental results show that, with similar total thickness, the contacted and adhesive targets exhibit better ballistic performance than the monolithic targets, and the four-layered targets… More >

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