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Search Results (34)
  • Open Access

    ARTICLE

    Systematic Security Guideline Framework through Intelligently Automated Vulnerability Analysis

    Dahyeon Kim1, Namgi Kim2, Junho Ahn2,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3867-3889, 2024, DOI:10.32604/cmc.2024.046871

    Abstract This research aims to propose a practical framework designed for the automatic analysis of a product’s comprehensive functionality and security vulnerabilities, generating applicable guidelines based on real-world software. The existing analysis of software security vulnerabilities often focuses on specific features or modules. This partial and arbitrary analysis of the security vulnerabilities makes it challenging to comprehend the overall security vulnerabilities of the software. The key novelty lies in overcoming the constraints of partial approaches. The proposed framework utilizes data from various sources to create a comprehensive functionality profile, facilitating the derivation of real-world security guidelines. Security guidelines are dynamically generated… More >

  • Open Access

    ARTICLE

    Efficient and Secure IoT Based Smart Home Automation Using Multi-Model Learning and Blockchain Technology

    Nazik Alturki1, Raed Alharthi2, Muhammad Umer3,*, Oumaima Saidani1, Amal Alshardan1, Reemah M. Alhebshi4, Shtwai Alsubai5, Ali Kashif Bashir6,7,8,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3387-3415, 2024, DOI:10.32604/cmes.2023.044700

    Abstract The concept of smart houses has grown in prominence in recent years. Major challenges linked to smart homes are identification theft, data safety, automated decision-making for IoT-based devices, and the security of the device itself. Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features. This paper proposes a smart home system based on ensemble learning of random forest (RF) and convolutional neural networks (CNN) for programmed decision-making tasks, such as categorizing gadgets as “OFF” or “ON” based… More >

  • Open Access

    ARTICLE

    Integrated Generative Adversarial Network and XGBoost for Anomaly Processing of Massive Data Flow in Dispatch Automation Systems

    Wenlu Ji1, Yingqi Liao1,*, Liudong Zhang2

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2825-2848, 2023, DOI:10.32604/iasc.2023.039618

    Abstract Existing power anomaly detection is mainly based on a pattern matching algorithm. However, this method requires a lot of manual work, is time-consuming, and cannot detect unknown anomalies. Moreover, a large amount of labeled anomaly data is required in machine learning-based anomaly detection. Therefore, this paper proposes the application of a generative adversarial network (GAN) to massive data stream anomaly identification, diagnosis, and prediction in power dispatching automation systems. Firstly, to address the problem of the small amount of anomaly data, a GAN is used to obtain reliable labeled datasets for fault diagnosis model training based on a few labeled… More >

  • Open Access

    ARTICLE

    Cost Efficient Automated Fog Spraying Machine: A Covid-19 Hand Sanitization Solution

    M. Atikur Rahman*, Amranur Rahman, Arman Hossain, Arifur Rahman Bhuiyan

    Journal of New Media, Vol.5, No.1, pp. 33-43, 2023, DOI:10.32604/jnm.2023.038676

    Abstract As a result of the introduction of new infectious illnesses, key infection prevention measures were implemented. Now, a new coronavirus (SARS-CoV-2) epidemic has expanded swiftly, causing the coronavirus illness 2019 (COVID-19). Many microorganisms spread illness via hospital surfaces due to environmental pollution. This virus has been associated to close contact between persons in tight situations such as houses, hospitals, assisted living, and residential institutions. Aside from health care settings, public buildings, faith-based community centers, marketplaces, transportation, and corporate environments are prone to COVID-19 transmission. Physical contact to the sanitizer device may cause for spread Covid virus. That’s why we have… More >

  • Open Access

    ARTICLE

    Home Automation-Based Health Assessment Along Gesture Recognition via Inertial Sensors

    Hammad Rustam1, Muhammad Muneeb1, Suliman A. Alsuhibany2, Yazeed Yasin Ghadi3, Tamara Al Shloul4, Ahmad Jalal1, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2331-2346, 2023, DOI:10.32604/cmc.2023.028712

    Abstract Hand gesture recognition (HGR) is used in a numerous applications, including medical health-care, industrial purpose and sports detection. We have developed a real-time hand gesture recognition system using inertial sensors for the smart home application. Developing such a model facilitates the medical health field (elders or disabled ones). Home automation has also been proven to be a tremendous benefit for the elderly and disabled. Residents are admitted to smart homes for comfort, luxury, improved quality of life, and protection against intrusion and burglars. This paper proposes a novel system that uses principal component analysis, linear discrimination analysis feature extraction, and… More >

  • Open Access

    ARTICLE

    Real Time Automation and Ratio Control Using PLC & SCADA in Industry 4.0

    Basant Tomar*, Narendra Kumar, Mini Sreejeth

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1495-1516, 2023, DOI:10.32604/csse.2023.030635

    Abstract Industrial Control Systems (ICS) and SCADA (Supervisory Control and Data Acquisition) systems play a critical role in the management and regulation of critical infrastructure. SCADA systems brings us closer to the real-time application world. All process and equipment control capability is typically provided by a Distributed Control System (DCS) in industries such as power stations, agricultural systems, chemical and water treatment plants. Instead of control through DCS, this paper proposes a SCADA and PLC (Programmable Logic Controller) system to control the ratio control division and the assembly line division inside the chemical plant. A specific design and implementation method for… More >

  • Open Access

    ARTICLE

    IC Pattern Based Power Factor Maximization Model for Improved Power Stabilization

    N. Hariharan1,*, Y. Sukhi2, N. Kalaiarasi1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 401-414, 2023, DOI:10.32604/iasc.2023.030768

    Abstract The voltage fluctuation in electric circuits has been identified as key issue in different electric systems. As the usage of electricity growing in rapid way, there exist higher fluctuations in power flow. To maintain the flow or stability of power in any electric circuit, there are many circuit models are discussed in literature. However, they suffer to maintain the output voltage and not capable of maintaining power stability. To improve the performance in power stabilization, an efficient IC pattern based power factor maximization model (ICPFMM) in this article. The model is focused on improving the power stability with the use… More >

  • Open Access

    ARTICLE

    DeepQ Based Automated Irrigation Systems Using Deep Belief WSN

    E. Gokulakannan*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3415-3427, 2023, DOI:10.32604/iasc.2023.030965

    Abstract Deep learning is the subset of artificial intelligence and it is used for effective decision making. Wireless Sensor based automated irrigation system is proposed to monitor and cultivate crop. Our system consists of Distributed wireless sensor environment to handle the moisture of the soil and temperature levels. It is automated process and useful for minimizing the usage of resources such as water level, quality of the soil, fertilizer values and controlling the whole system. The mobile app based smart control system is designed using deep belief network. This system has multiple sensors placed in agricultural field and collect the data.… More >

  • Open Access

    ARTICLE

    Early Detection of Heartbeat from Multimodal Data Using RPA Learning with KDNN-SAE

    A. K. S. Saranya1,*, T. Jaya2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 545-562, 2023, DOI:10.32604/csse.2023.029975

    Abstract Heartbeat detection stays central to cardiovascular an electrocardiogram (ECG) is used to help with disease diagnosis and management. Existing Convolutional Neural Network (CNN)-based methods suffer from the less generalization problem thus; the effectiveness and robustness of the traditional heartbeat detector methods cannot be guaranteed. In contrast, this work proposes a heartbeat detector Krill based Deep Neural Network Stacked Auto Encoders (KDNN-SAE) that computes the disease before the exact heart rate by combining features from multiple ECG Signals. Heartbeats are classified independently and multiple signals are fused to estimate life threatening conditions earlier without any error in classification of heart beat.… More >

  • Open Access

    ARTICLE

    Real Time Control System for Metro Railways Using PLC & SCADA

    Ishu Tomar*, Indu Sreedevi, Neeta Pandey

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1403-1421, 2023, DOI:10.32604/iasc.2023.028163

    Abstract This paper proposes to adopt SCADA and PLC technology for the improvement of the performance of real time signaling & train control systems in metro railways. The main concern of this paper is to minimize the failure in automated metro railways system operator and integrate the information coming from Operational Control Centre (OCC), traction SCADA system, traction power control, and power supply system. This work presents a simulated prototype of an automated metro train system operator that uses PLC and SCADA for the real time monitoring and control of the metro railway systems. Here, SCADA is used for the visualization… More >

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