Ye Lu^1,*, Tao Feng¹, Chunyan Liu², Wenbo Zhang³

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

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 the authorization of attribute private… More >

Hongliang Tian, Junyuan Tian^*

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

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 throughput; Finally, map resource access… More >

Fang Xu^1,2,3, Songhao Jiang^1,2, Yi Ma^1,2,3,*, Manzoor Ahmed^1,3,*, Zenggang Xiong^1,2,3, Yuanlin Lyu^1,2

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

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 the strength of social connections… More >

Zakarya Abdullah Alzamil^*

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

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 of the existing approaches, the… More >

Jason Elroy Martis¹, Sannidhan Manjaya Shetty^2,*, Manas Ranjan Pradhan³, Usha Desai⁴, Biswaranjan Acharya^5,*

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

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 by an observer. Additionally, we… More >

V. Gowri^1,*, V. Vijaya Chamundeeswari²

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

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 and to select the optimum… More >

Savita Bhardwaj¹, Tunisha Verma¹, Ali Raza^2,*, Dhriti Kapoor^1,*

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

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 growth parameters of… More >

Dina Swelam¹, Abdel Hamid Salem², Manal Hassan¹, Mohammed Ali^2,*

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

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 per plant (NS/P), number of… More >

Tauqeer Ahmad Yasir¹, Sobia Aslam¹, Muhammad Shahid Rizwan², Allah Wasaya^1,*, Muhammad Ateeq¹, Muhammad Naeem Khan³, Sikander Khan Tanveer⁴, Walid Soufan⁵, Basharat Ali⁶, Allah Ditta^7,8, Arpna Kumari⁹, Ayman EL Sabagh^10,*

Phyton-International Journal of Experimental Botany, Vol.91, No.11, pp. 2491-2504, 2022, DOI:10.32604/phyton.2022.022473

Abstract In soil biota, higher and enduring concentration of heavy metals like cadmium (Cd) is hazardous and associated with great loss in growth, yield, and quality parameters of most of the crop plants. Recently, in-situ applications of eco-friendly stabilizing agents in the form of organic modifications have been utilized to mitigate the adverse effects of Cd-toxicity. This controlled experiment was laid down to appraise the imprints of various applied organic amendments namely poultry manure (PM), farmyard manure (FYM), and sugarcane press mud (PS) to immobilize Cd in polluted soil. Moreover, phytoavailability of Cd in wheat was also accessed under an alkaline… More >

K. Chola Raja^1,*, S. Kannimuthu²

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

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 training data. Deep learning on… More >