Ayman Altameem¹, Jaideep Singh Sachdev², Vijander Singh², Ramesh Chandra Poonia³, Sandeep Kumar⁴, Abdul Khader Jilani Saudagar^5,*

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1095-1107, 2022, DOI:10.32604/csse.2022.023256 - 08 February 2022

Abstract Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals; these signals can be recorded, processed and classified into different hand movements, which can be used to control other IoT devices. Classification of hand movements will be one step closer to applying these algorithms in real-life situations using EEG headsets. This paper uses different feature extraction techniques and sophisticated machine learning algorithms to classify hand movements from EEG brain signals to control prosthetic hands for amputated persons. To achieve good classification accuracy, denoising and feature extraction of EEG signals… More >

Mohd Anul Haq^*

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1031-1046, 2022, DOI:10.32604/csse.2022.023221 - 08 February 2022

Abstract To adopt sustainable crop practices in changing climate, understanding the climatic parameters and water requirements with vegetation is crucial on a spatiotemporal scale. The Planetscope (PS) constellation of more than 130 nanosatellites from Planet Labs revolutionize the high-resolution vegetation assessment. PS-derived Normalized Difference Vegetation Index (NDVI) maps are one of the highest resolution data that can transform agricultural practices and management on a large scale. High-resolution PS nanosatellite data was utilized in the current study to monitor agriculture’s spatiotemporal assessment for the Al-Qassim region, Kingdom of Saudi Arabia (KSA). The time series of NDVI was… More >

Nouh Sabri Elmitwally^1,2, Maria Tariq^3,4, Muhammad Adnan Khan^5,*, Munir Ahmad³, Sagheer Abbas³, Fahad Mazaed Alotaibi⁶

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1001-1014, 2022, DOI:10.32604/csse.2022.022017 - 08 February 2022

Abstract In the agricultural industry, rice infections have resulted in significant productivity and economic losses. The infections must be recognized early on to regulate and mitigate the effects of the attacks. Early diagnosis of disease severity effects or incidence can preserve production from quantitative and qualitative losses, reduce pesticide use, and boost ta country’s economy. Assessing the health of a rice plant through its leaves is usually done as a manual ocular exercise. In this manuscript, three rice plant diseases: Bacterial leaf blight, Brown spot, and Leaf smut, were identified using the Alexnet Model. Our research More >

Mohammad Khalid Imam Rahmani¹, Fahmina Taranum², Reshma Nikhat³, Md. Rashid Farooqi³, Mohammed Arshad Khan^4,*

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1181-1198, 2022, DOI:10.32604/csse.2022.022014 - 08 February 2022

Abstract The COVID-19 pandemic is a virus that has disastrous effects on human lives globally; still spreading like wildfire causing huge losses to humanity and economies. There is a need to follow few constraints like social distancing norms, personal hygiene, and masking up to effectively control the virus spread. The proposal is to detect the face frame and confirm the faces are properly covered with masks. By applying the concepts of Deep learning, the results obtained for mask detection are found to be effective. The system is trained using 4500 images to accurately judge and justify… More >

M. Manikandan^1,*, R. Subramanian², M. S. Kavitha³, S. Karthik³

Computer Systems Science and Engineering, Vol.42, No.3, pp. 935-948, 2022, DOI:10.32604/csse.2022.021816 - 08 February 2022

Abstract In today’s world, Cloud Computing (CC) enables the users to access computing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located in remote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and task scheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud is employed since it is a capable solution to process large-scale… More >

S. Prakash^1,*, P. Vishnu Raja², A. Baseera³, D. Mansoor Hussain⁴, V. R. Balaji⁵, K. Venkatachalam⁶

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1273-1287, 2022, DOI:10.32604/csse.2022.021784 - 08 February 2022

Abstract Urban living in large modern cities exerts considerable adverse effects on health and thus increases the risk of contracting several chronic kidney diseases (CKD). The prediction of CKDs has become a major task in urbanized countries. The primary objective of this work is to introduce and develop predictive analytics for predicting CKDs. However, prediction of huge samples is becoming increasingly difficult. Meanwhile, MapReduce provides a feasible framework for programming predictive algorithms with map and reduce functions. The relatively simple programming interface helps solve problems in the scalability and efficiency of predictive learning algorithms. In the… More >

MIN CHEN^1,#, YUAN HUANG^2,#, WEN XU², CHUNLIN SU^2,*

BIOCELL, Vol.46, No.6, pp. 1505-1519, 2022, DOI:10.32604/biocell.2022.016564 - 07 February 2022

Abstract The development of polycystic ovary syndrome (PCOS) is closely related to the chronic inflammatory and obese. Recent studies have found macrophages regulate the chronic inflammation and adipose tissue remodelling, but the underlying mechanisms have not been clarified. In this study, we established a model of PCOS in the offspring rats by high androgen exposure during late pregnancy in parental and established a female rat macrophage eliminating model by rejection of clodronate liposome. Then, the offspring rat macrophage phenotype in offspring female rat adipose tissue, and levels of testosterone, angiogenic factors (PDGF and VEGF) and inflammatory… More >

WEI LI^1,2, YUEYANG DUAN¹, XIAOTONG YAN¹, XIANGXIANG LIU¹, MEILING FAN^3,*, ZI WANG^1,2,*

BIOCELL, Vol.46, No.6, pp. 1417-1423, 2022, DOI:10.32604/biocell.2022.017609 - 07 February 2022

Abstract Ginsenoside Rb3 (G-Rb3) is one of the primary active compounds isolated from Panax ginseng Meyer, which belongs to protopanaxadiol ginsenosides (PPD). Based on the structure-activity relationship (SAR) of ginsenosides, the pentose structure of G-Rb3 limited itself to possess more pharmacological activity to a certain extent. However, pharmacokinetics show that G-Rb3 is processed through deglycosylation in the intestinal tract and converted into more active rare saponins, such as Compound K, F2, etc. A series of studies focused on neuroprotection and the cardiovascular system demonstrating its therapeutic potentials, which was achieved by diminishing oxidative stress and apoptosis. Therefore, More >

Haijie Pan, Lirong Zheng^*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 493-512, 2022, DOI:10.32604/cmes.2022.019069 - 24 January 2022

Abstract The machine learning model converges slowly and has unstable training since large variance by random using a sample estimate gradient in SGD. To this end, we propose a noise reduction method for Stochastic Variance Reduction gradient (SVRG), called N-SVRG, which uses small batches samples instead of all samples for the average gradient calculation, while performing an incremental update of the average gradient. In each round of iteration, a small batch of samples is randomly selected for the average gradient calculation, while the average gradient is updated by rounding of the past model gradients during internal… More >

Ruhui Cheng¹, Xiaomeng Yin², Leilei Chen^1,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 445-464, 2022, DOI:10.32604/cmes.2022.018519 - 24 January 2022

Abstract This paper applies a machine learning technique to find a general and efficient numerical integration scheme for boundary element methods. A model based on the neural network multi-classification algorithm is constructed to find the minimum number of Gaussian quadrature points satisfying the given accuracy. The constructed model is trained by using a large amount of data calculated in the traditional boundary element method and the optimal network architecture is selected. The two-dimensional potential problem of a circular structure is tested and analyzed based on the determined model, and the accuracy of the model is about More >