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  • Open Access

    ARTICLE

    Research on Asymmetric Fault Location of Wind Farm Collection System Based on Compressed Sensing

    Huanan Yu1, Gang Han1,*, Hansong Luo2, He Wang1

    Energy Engineering, Vol.120, No.9, pp. 2029-2057, 2023, DOI:10.32604/ee.2023.028365

    Abstract Aiming at the problem that most of the cables in the power collection system of offshore wind farms are buried deep in the seabed, which makes it difficult to detect faults, this paper proposes a two-step fault location method based on compressed sensing and ranging equation. The first step is to determine the fault zone through compressed sensing, and improve the data measurement, dictionary design and algorithm reconstruction: Firstly, the phase-locked loop trigonometric function method is used to suppress the spike phenomenon when extracting the fault voltage, so that the extracted voltage value will not have a large error due… More >

  • Open Access

    ARTICLE

    The Management of Mental Health, and Service Networks in Italy

    Silvia Carbone*

    International Journal of Mental Health Promotion, Vol.25, No.8, pp. 927-935, 2023, DOI:10.32604/ijmhp.2023.027784

    Abstract Madness has attracted and frightened for centuries, and talking about this means discussing how this diversity was built and managed in different social contexts and historical periods. Not all societies have had, and still have, the same relationship with madness. It is only with the affirmation of the Modern State, and of Capitalism, that the idea of “normality” indispensable to be able to conceive diversity as something dangerously distant and different from the norm takes over. In our post-modern society, people with mental illness in Italy can resort to specialists and social-health services. But the heterogeneous answers given after the… More > Graphic Abstract

    The Management of Mental Health, and Service Networks in Italy

  • Open Access

    ARTICLE

    Submarine Hunter: Efficient and Secure Multi-Type Unmanned Vehicles

    Halah Hasan Mahmoud1, Marwan Kadhim Mohammed Al-Shammari1, Gehad Abdullah Amran2,3,*, Elsayed Tag eldin4,*, Ala R. Alareqi5, Nivin A. Ghamry6, Ehaa ALnajjar7, Esmail Almosharea8

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 573-589, 2023, DOI:10.32604/cmc.2023.039363

    Abstract Utilizing artificial intelligence (AI) to protect smart coastal cities has become a novel vision for scientific and industrial institutions. One of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles (UVs) for anti-submarine attacks. This study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity strategy. The Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach, and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol… More >

  • Open Access

    ARTICLE

    Enhanced Water Quality Control Based on Predictive Optimization for Smart Fish Farming

    Azimbek Khudoyberdiev1, Mohammed Abdul Jaleel1, Israr Ullah2, DoHyeun Kim3,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5471-5499, 2023, DOI:10.32604/cmc.2023.036898

    Abstract The requirement for high-quality seafood is a global challenge in today’s world due to climate change and natural resource limitations. Internet of Things (IoT) based Modern fish farming systems can significantly optimize seafood production by minimizing resource utilization and improving healthy fish production. This objective requires intensive monitoring, prediction, and control by optimizing leading factors that impact fish growth, including temperature, the potential of hydrogen (pH), water level, and feeding rate. This paper proposes the IoT based predictive optimization approach for efficient control and energy utilization in smart fish farming. The proposed fish farm control mechanism has a predictive optimization… More >

  • Open Access

    ARTICLE

    A Novel Cluster Analysis-Based Crop Dataset Recommendation Method in Precision Farming

    K. R. Naveen Kumar1, Husam Lahza2, B. R. Sreenivasa3,*, Tawfeeq Shawly4, Ahmed A. Alsheikhy5, H. Arunkumar1, C. R. Nirmala1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3239-3260, 2023, DOI:10.32604/csse.2023.036629

    Abstract Data mining and analytics involve inspecting and modeling large pre-existing datasets to discover decision-making information. Precision agriculture uses data mining to advance agricultural developments. Many farmers aren’t getting the most out of their land because they don’t use precision agriculture. They harvest crops without a well-planned recommendation system. Future crop production is calculated by combining environmental conditions and management behavior, yielding numerical and categorical data. Most existing research still needs to address data preprocessing and crop categorization/classification. Furthermore, statistical analysis receives less attention, despite producing more accurate and valid results. The study was conducted on a dataset about Karnataka state,… More >

  • Open Access

    ARTICLE

    Modeling of Sensor Enabled Irrigation Management for Intelligent Agriculture Using Hybrid Deep Belief Network

    Saud Yonbawi1, Sultan Alahmari2, B. R. S. S. Raju3, Chukka Hari Govinda Rao4, Mohamad Khairi Ishak5, Hend Khalid Alkahtani6, José Varela-Aldás7,*, Samih M. Mostafa8

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2319-2335, 2023, DOI:10.32604/csse.2023.036721

    Abstract Artificial intelligence (AI) technologies and sensors have recently received significant interest in intellectual agriculture. Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture. Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques. Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist. With this motivation, this study develops a modified black widow optimization with a… More >

  • Open Access

    REVIEW

    Biochemical association between the prevalence of genetic polymorphism and myocardial infarction

    MOMINA SHAHID1, KANWAL REHMAN2, MUHAMMAD SAJID HAMID AKASH1,*, SHALEEM SUHAIL1, SUMBAL RASHEED1, MUHAMMAD IMRAN3,4, MOHAMMED A. ASSIRI3,4

    BIOCELL, Vol.47, No.3, pp. 473-484, 2023, DOI:10.32604/biocell.2023.025930

    Abstract Genetic polymorphism has a vital role in the pathogenesis and development of myocardial infarction (MI). Single nucleotide polymorphism at any one of the amino acid sequences can result in a diseased state. A single gene can exhibit genetic polymorphism at more than one position giving rise to different variants. Genetic polymorphism of angiotensinogen (AGT) M235T, AGT T174M, and angiotensin-1-converting enzyme (ACE) I/D, endothelial nitric oxide synthase (eNOS), and methylenetetrahydrofolate reductase (MTHFR) can be a risk factor for MI. However, it is important to study the prevalence of genetic polymorphisms of these genes among different populations. MI is influenced by genetic… More >

  • Open Access

    ARTICLE

    Face Attribute Convolutional Neural Network System for Data Security with Improved Crypto Biometrics

    S. Aanjanadevi1,*, S. Aanjankumar2, K. R. Ramela3, V. Palanisamy4

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2351-2362, 2023, DOI:10.32604/csse.2023.031893

    Abstract Due to the enormous usage of the internet for transmission of data over a network, security and authenticity become major risks. Major challenges encountered in biometric system are the misuse of enrolled biometric templates stored in database server. To describe these issues various algorithms are implemented to deliver better protection to biometric traits such as physical (Face, fingerprint, Ear etc.) and behavioural (Gesture, Voice, tying etc.) by means of matching and verification process. In this work, biometric security system with fuzzy extractor and convolutional neural networks using face attribute is proposed which provides different choices for supporting cryptographic processes to… More >

  • Open Access

    ARTICLE

    An Improved Farmland Fertility Algorithm with Hyper-Heuristic Approach for Solving Travelling Salesman Problem

    Farhad Soleimanian Gharehchopogh1,*, Benyamin Abdollahzadeh1, Bahman Arasteh2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 1981-2006, 2023, DOI:10.32604/cmes.2023.024172

    Abstract Travelling Salesman Problem (TSP) is a discrete hybrid optimization problem considered NP-hard. TSP aims to discover the shortest Hamilton route that visits each city precisely once and then returns to the starting point, making it the shortest route feasible. This paper employed a Farmland Fertility Algorithm (FFA) inspired by agricultural land fertility and a hyper-heuristic technique based on the Modified Choice Function (MCF). The neighborhood search operator can use this strategy to automatically select the best heuristic method for making the best decision. Lin-Kernighan (LK) local search has been incorporated to increase the efficiency and performance of this suggested approach.… More >

  • Open Access

    ARTICLE

    Information-Centric IoT-Based Smart Farming with Dynamic Data Optimization

    Souvik Pal1,2,*, Hannah VijayKumar3, D. Akila4, N. Z. Jhanjhi5,6, Omar A. Darwish7, Fathi Amsaad8

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3865-3880, 2023, DOI:10.32604/cmc.2023.029038

    Abstract Smart farming has become a strategic approach of sustainable agriculture management and monitoring with the infrastructure to exploit modern technologies, including big data, the cloud, and the Internet of Things (IoT). Many researchers try to integrate IoT-based smart farming on cloud platforms effectively. They define various frameworks on smart farming and monitoring system and still lacks to define effective data management schemes. Since IoT-cloud systems involve massive structured and unstructured data, data optimization comes into the picture. Hence, this research designs an Information-Centric IoT-based Smart Farming with Dynamic Data Optimization (ICISF-DDO), which enhances the performance of the smart farming infrastructure… More >

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