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  • Open Access

    ARTICLE

    Morphometric Attributes of Two Native Forage Species According to Water Source Distance in Semiarid Central Grasslands of Argentina

    Carla Etel Suárez1,*, María Sol Rossini1,3, Ernesto Francisco Atilio Morici1, Héctor Daniel Esterlich1,2

    Phyton-International Journal of Experimental Botany, Vol.93, No.8, pp. 2063-2074, 2024, DOI:10.32604/phyton.2024.053193 - 30 August 2024

    Abstract The semiarid grasslands of Argentina’s central region have been modified by domestic livestock grazing, both in their composition and structure. The increase in the proportion of woody and non-forage species and the decrease in forage species are some of the most evident results of this process. There is limited available information about the effect of differential grazing pressures on morphometric attributes of native species, and it also depends on the life histories of the species in this grassland. The objective of this work was to evaluate some morphometric aspects in the grasses Poa ligularis Nees ex… More >

  • Open Access

    ARTICLE

    A Blockchain and CP-ABE Based Access Control Scheme with Fine-Grained Revocation of Attributes in Cloud Health

    Ye Lu1,*, Tao Feng1, Chunyan Liu2, Wenbo Zhang3

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2787-2811, 2024, DOI:10.32604/cmc.2023.046106 - 27 February 2024

    Abstract The Access control scheme is an effective method to protect user data privacy. The access control scheme based on blockchain and ciphertext policy attribute encryption (CP–ABE) can solve the problems of single—point of failure and lack of trust in the centralized system. However, it also brings new problems to the health information in the cloud storage environment, such as attribute leakage, low consensus efficiency, complex permission updates, and so on. This paper proposes an access control scheme with fine-grained attribute revocation, keyword search, and traceability of the attribute private key distribution process. Blockchain technology tracks… More >

  • Open Access

    ARTICLE

    A Blockchain-Based Access Control Scheme for Reputation Value Attributes of the Internet of Things

    Hongliang Tian, Junyuan Tian*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1297-1310, 2024, DOI:10.32604/cmc.2024.047058 - 30 January 2024

    Abstract The Internet of Things (IoT) access control mechanism may encounter security issues such as single point of failure and data tampering. To address these issues, a blockchain-based IoT reputation value attribute access control scheme is proposed. Firstly, writing the reputation value as an attribute into the access control policy, and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control; Secondly, storing a large amount of resources from the Internet of Things in Inter Planetary File System (IPFS) to improve system More >

  • Open Access

    ARTICLE

    Enhancing Data Forwarding Efficiency in SIoT with Multidimensional Social Relations

    Fang Xu1,2,3, Songhao Jiang1,2, Yi Ma1,2,3,*, Manzoor Ahmed1,3,*, Zenggang Xiong1,2,3, Yuanlin Lyu1,2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1095-1113, 2024, DOI:10.32604/cmc.2023.046577 - 30 January 2024

    Abstract Effective data communication is a crucial aspect of the Social Internet of Things (SIoT) and continues to be a significant research focus. This paper proposes a data forwarding algorithm based on Multidimensional Social Relations (MSRR) in SIoT to solve this problem. The proposed algorithm separates message forwarding into intra- and cross-community forwarding by analyzing interest traits and social connections among nodes. Three new metrics are defined: the intensity of node social relationships, node activity, and community connectivity. Within the community, messages are sent by determining which node is most similar to the sender by weighing More >

  • Open Access

    ARTICLE

    Software Coupling and Cohesion Model for Measuring the Quality of Software Components

    Zakarya Abdullah Alzamil*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3139-3161, 2023, DOI:10.32604/cmc.2023.042711 - 26 December 2023

    Abstract Measuring software quality requires software engineers to understand the system’s quality attributes and their measurements. The quality attribute is a qualitative property; however, the quantitative feature is needed for software measurement, which is not considered during the development of most software systems. Many research studies have investigated different approaches for measuring software quality, but with no practical approaches to quantify and measure quality attributes. This paper proposes a software quality measurement model, based on a software interconnection model, to measure the quality of software components and the overall quality of the software system. Unlike most… More >

  • Open Access

    ARTICLE

    Text-to-Sketch Synthesis via Adversarial Network

    Jason Elroy Martis1, Sannidhan Manjaya Shetty2,*, Manas Ranjan Pradhan3, Usha Desai4, Biswaranjan Acharya5,*

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 915-938, 2023, DOI:10.32604/cmc.2023.038847 - 08 June 2023

    Abstract In the past, sketches were a standard technique used for recognizing offenders and have remained a valuable tool for law enforcement and social security purposes. However, relying on eyewitness observations can lead to discrepancies in the depictions of the sketch, depending on the experience and skills of the sketch artist. With the emergence of modern technologies such as Generative Adversarial Networks (GANs), generating images using verbal and textual cues is now possible, resulting in more accurate sketch depictions. In this study, we propose an adversarial network that generates human facial sketches using such cues provided More >

  • Open Access

    ARTICLE

    Classifying Big Medical Data through Bootstrap Decision Forest Using Penalizing Attributes

    V. Gowri1,*, V. Vijaya Chamundeeswari2

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3675-3690, 2023, DOI:10.32604/iasc.2023.035817 - 15 March 2023

    Abstract Decision forest is a well-renowned machine learning technique to address the detection and prediction problems related to clinical data. But, the traditional decision forest (DF) algorithms have lower classification accuracy and cannot handle high-dimensional feature space effectively. In this work, we propose a bootstrap decision forest using penalizing attributes (BFPA) algorithm to predict heart disease with higher accuracy. This work integrates a significance-based attribute selection (SAS) algorithm with the BFPA classifier to improve the performance of the diagnostic system in identifying cardiac illness. The proposed SAS algorithm is used to determine the correlation among attributes… More >

  • Open Access

    ARTICLE

    Silicon and Nitric Oxide-Mediated Regulation of Growth Attributes, Metabolites and Antioxidant Defense System of Radish (Raphanus sativus L.) under Arsenic Stress

    Savita Bhardwaj1, Tunisha Verma1, Ali Raza2,*, Dhriti Kapoor1,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.3, pp. 763-782, 2023, DOI:10.32604/phyton.2023.025672 - 29 November 2022

    Abstract

    Arsenic (As) contaminated food chains have emerged as a serious public concern for humans and animals and are known to affect the cultivation of edible crops throughout the world. Therefore, the present study was designed to investigate the individual as well as the combined effects of exogenous silicon (Si) and sodium nitroprusside (SNP), a nitric oxide (NO) donor, on plant growth, metabolites, and antioxidant defense systems of radish (Raphanus sativus L.) plants under three different concentrations of As stress, i.e., 0.3, 0.5, and 0.7 mM in a pot experiment. The results showed that As stress reduced the

    More >

  • Open Access

    ARTICLE

    Conditional Generative Adversarial Network Approach for Autism Prediction

    K. Chola Raja1,*, S. Kannimuthu2

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 741-755, 2023, DOI:10.32604/csse.2023.025331 - 01 June 2022

    Abstract Autism Spectrum Disorder (ASD) requires a precise diagnosis in order to be managed and rehabilitated. Non-invasive neuroimaging methods are disease markers that can be used to help diagnose ASD. The majority of available techniques in the literature use functional magnetic resonance imaging (fMRI) to detect ASD with a small dataset, resulting in high accuracy but low generality. Traditional supervised machine learning classification algorithms such as support vector machines function well with unstructured and semi structured data such as text, images, and videos, but their performance and robustness are restricted by the size of the accompanying… More >

  • Open Access

    ARTICLE

    Breeding Enrichment of Genetic Variation of Grain Yield and Its Attributes in Bread Wheat under Drought Stress and Well Irrigation

    Dina Swelam1, Abdel Hamid Salem2, Manal Hassan1, Mohammed Ali2,*

    Phyton-International Journal of Experimental Botany, Vol.91, No.12, pp. 2699-2717, 2022, DOI:10.32604/phyton.2022.022651 - 29 August 2022

    Abstract Drought stress (DS) is one of the most critical environmental abiotic stresses for wheat production in the arid environments. Selection of high-yielding genotypes tolerant to DS can play a significant role in mitigation the negative impacts associated with DS. In the present study, generation means analysis (GMA) was used to study the performance of two crosses under well irrigation (WI) and deficit irrigation [cross I (Line 44 × Shandweel-1) and cross II (Line 20 × Sakha 93)]. Significant differences were observed for days to heading (DH), days to maturity (DM), plant height (PH), spike length (SL), number of spikes… More >

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