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  • Open Access

    ARTICLE

    Fault Diagnosis of Power Electronic Circuits Based on Adaptive Simulated Annealing Particle Swarm Optimization

    Deye Jiang1, Yiguang Wang2,*

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 295-309, 2023, DOI:10.32604/cmc.2023.039244

    Abstract In the field of energy conversion, the increasing attention on power electronic equipment is fault detection and diagnosis. A power electronic circuit is an essential part of a power electronic system. The state of its internal components affects the performance of the system. The stability and reliability of an energy system can be improved by studying the fault diagnosis of power electronic circuits. Therefore, an algorithm based on adaptive simulated annealing particle swarm optimization (ASAPSO) was used in the present study to optimize a backpropagation (BP) neural network employed for the online fault diagnosis of a power electronic circuit. We… More >

  • Open Access

    ARTICLE

    Alzheimer’s Disease Stage Classification Using a Deep Transfer Learning and Sparse Auto Encoder Method

    Deepthi K. Oommen*, J. Arunnehru

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 793-811, 2023, DOI:10.32604/cmc.2023.038640

    Abstract Alzheimer’s Disease (AD) is a progressive neurological disease. Early diagnosis of this illness using conventional methods is very challenging. Deep Learning (DL) is one of the finest solutions for improving diagnostic procedures’ performance and forecast accuracy. The disease’s widespread distribution and elevated mortality rate demonstrate its significance in the older-onset and younger-onset age groups. In light of research investigations, it is vital to consider age as one of the key criteria when choosing the subjects. The younger subjects are more susceptible to the perishable side than the older onset. The proposed investigation concentrated on the younger onset. The research used… More >

  • Open Access

    ARTICLE

    A Novel Color Image Watermarking Method with Adaptive Scaling Factor Using Similarity-Based Edge Region

    Kali Gurkahraman1,*, Rukiye Karakis2, Hidayet Takci1

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 55-77, 2023, DOI:10.32604/csse.2023.037798

    Abstract This study aimed to deal with three challenges: robustness, imperceptibility, and capacity in the image watermarking field. To reach a high capacity, a novel similarity-based edge detection algorithm was developed that finds more edge points than traditional techniques. The colored watermark image was created by inserting a randomly generated message on the edge points detected by this algorithm. To ensure robustness and imperceptibility, watermark and cover images were combined in the high-frequency subbands using Discrete Wavelet Transform and Singular Value Decomposition. In the watermarking stage, the watermark image was weighted by the adaptive scaling factor calculated by the standard deviation… More >

  • Open Access

    ARTICLE

    Ensemble Learning for Fetal Health Classification

    Mesfer Al Duhayyim1,*, Sidra Abbas2, Abdullah Al Hejaili3, Natalia Kryvinska4,*, Ahmad Almadhor5, Huma Mughal6

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 823-842, 2023, DOI:10.32604/csse.2023.037488

    Abstract : Cardiotocography (CTG) represents the fetus’s health inside the womb during labor. However, assessment of its readings can be a highly subjective process depending on the expertise of the obstetrician. Digital signals from fetal monitors acquire parameters (i.e., fetal heart rate, contractions, acceleration). Objective:: This paper aims to classify the CTG readings containing imbalanced healthy, suspected, and pathological fetus readings. Method:: We perform two sets of experiments. Firstly, we employ five classifiers: Random Forest (RF), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LGBM) without over-sampling to classify CTG readings into three categories:… More >

  • Open Access

    ARTICLE

    Adaptive Butterfly Optimization Algorithm (ABOA) Based Feature Selection and Deep Neural Network (DNN) for Detection of Distributed Denial-of-Service (DDoS) Attacks in Cloud

    S. Sureshkumar1,*, G .K. D. Prasanna Venkatesan2, R. Santhosh3

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1109-1123, 2023, DOI:10.32604/csse.2023.036267

    Abstract Cloud computing technology provides flexible, on-demand, and completely controlled computing resources and services are highly desirable. Despite this, with its distributed and dynamic nature and shortcomings in virtualization deployment, the cloud environment is exposed to a wide variety of cyber-attacks and security difficulties. The Intrusion Detection System (IDS) is a specialized security tool that network professionals use for the safety and security of the networks against attacks launched from various sources. DDoS attacks are becoming more frequent and powerful, and their attack pathways are continually changing, which requiring the development of new detection methods. Here the purpose of the study… More >

  • Open Access

    ARTICLE

    Design and Development of an Intelligent Energy Management System for a Smart Grid to Enhance the Power Quality

    Nisha Vasudevan1,*, Vasudevan Venkatraman2, A. Ramkumar1, T. Muthukumar3, A. Sheela4, M. Vetrivel5, R. J. Vijaya Saraswathi6, F. T. Josh7

    Energy Engineering, Vol.120, No.8, pp. 1747-1761, 2023, DOI:10.32604/ee.2023.027821

    Abstract MigroGrid (MG) has emerged to resolve the growing demand for energy. But because of its inconsistent output, it can result in various power quality (PQ) issues. PQ is a problem that is becoming more and more important for the reliability of power systems that use renewable energy sources. Similarly, the employment of nonlinear loads will introduce harmonics into the system and, as a result, cause distortions in the current and voltage waveforms as well as low power quality issues in the supply system. Thus, this research focuses on power quality enhancement in the MG using hybrid shunt filters. However, the… More >

  • Open Access

    ARTICLE

    Observational Study of Family Behaviors during the Terminal Palliative Phase

    Étude observationnelle des comportements familiaux durant la phase palliative terminale

    A. Van Lander, A. Bioy, V. Guastella

    Psycho-Oncologie, Vol.16, No.2, pp. 234-242, 2022, DOI:10.3166/pson-2022-0196

    Abstract Supporting those around a patient suffering from a serious, progressive, or terminal illness is a legal obligation (Law 99 Art. L.1er B) and requires professionals informed about specific mechanisms. Main objective: discover the family psycho-adaptive mechanisms during the terminal phase. Methods: The method is qualitative from a participant observation in a palliative care inpatient service between January 2016 and January 2020. Results: observation of 649 families reveal specific distresses, a relationship that is both caring and fusional, and a negative pact. family communication about dying is deleterious. Conclusion: it’s essential to adapt palliative care to the functioning of family, the… More >

  • Open Access

    ARTICLE

    A Fault Feature Extraction Model in Synchronous Generator under Stator Inter-Turn Short Circuit Based on ACMD and DEO3S

    Yuling He, Shuai Li, Chao Zhang*, Xiaolong Wang

    Structural Durability & Health Monitoring, Vol.17, No.2, pp. 115-130, 2023, DOI:10.32604/sdhm.2023.022317

    Abstract This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators. Different from the past methods focused on the current or voltage signals to diagnose the electrical fault, the stator vibration signal analysis based on ACMD (adaptive chirp mode decomposition) and DEO3S (demodulation energy operator of symmetrical differencing) was adopted to extract the fault feature. Firstly, FT (Fourier transform) is applied to the vibration signal to obtain the instantaneous frequency, and PE (permutation entropy) is calculated to select the proper weighting coefficients. Then, the signal is decomposed by ACMD, with the instantaneous frequency and… More >

  • Open Access

    ARTICLE

    Modified Sine Cosine Optimization with Adaptive Deep Belief Network for Movie Review Classification

    Hala J. Alshahrani1, Abdulbaset Gaddah2, Ehab S. Alnuzaili3, Mesfer Al Duhayyim4,*, Heba Mohsen5, Ishfaq Yaseen6, Amgad Atta Abdelmageed6, Gouse Pasha Mohammed6

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 283-300, 2023, DOI:10.32604/iasc.2023.035334

    Abstract Sentiment analysis (SA) is a growing field at the intersection of computer science and computational linguistics that endeavors to automatically identify the sentiment presented in text. Computational linguistics aims to describe the fundamental methods utilized in the formation of computer methods for understanding natural language. Sentiment is classified as a negative or positive assessment articulated through language. SA can be commonly used for the movie review classification that involves the automatic determination that a review posted online (of a movie) can be negative or positive toward the thing that has been reviewed. Deep learning (DL) is becoming a powerful machine… More >

  • Open Access

    ARTICLE

    Sensor-Based Adaptive Estimation in a Hybrid Environment Employing State Estimator Filters

    Ashvini Kulkarni1,2, P. Augusta Sophy Beulet1,*

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 127-146, 2023, DOI:10.32604/iasc.2023.035144

    Abstract It is widely acknowledged that navigation is a significant source of between sites. The Global Positioning System (GPS) has numerous navigational advancements, and hence it is used widely. GPS navigation can be compromised at any level between position, location, and estimation, to the detriment of the user. Consequently, a navigation system requires the precise location and underpinning tracking of an object without signal loss. The objective of a hybrid environment prediction system is to foresee the location of the user and their territory by employing a variety of sensors for position estimation and monitoring navigation. This article presents a state… More >

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