Open Access
ARTICLE
Nabilah Abughazalah1, Mohsin Iqbal2, Majid Khan3,*, Iqtadar Hussain4,5
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2022.031859
Abstract The substitution box, often known as an S-box, is a nonlinear
component that is a part of several block ciphers. Its purpose is to protect
cryptographic algorithms from a variety of cryptanalytic assaults. A MultiCriteria Decision Making (MCDM) problem has a complex selection procedure because of having many options and criteria to choose from. Because
of this, statistical methods are necessary to assess the performance score of
each S-box and decide which option is the best one available based on this
score. Using the Pythagorean Fuzzy-based Technique for Order of Preference
by Similarity to Ideal Solution (TOPSIS) method, the major… More >
Open Access
ARTICLE
Fatma Harby1, Adel Thaljaoui1, Durre Nayab2, Suliman Aladhadh3,*, Salim EL Khediri3,4, Rehan Ullah Khan3
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2022.029420
Abstract In the machine learning (ML) paradigm, data augmentation serves
as a regularization approach for creating ML models. The increase in the
diversification of training samples increases the generalization capabilities,
which enhances the prediction performance of classifiers when tested on
unseen examples. Deep learning (DL) models have a lot of parameters, and
they frequently overfit. Effectively, to avoid overfitting, data plays a major
role to augment the latest improvements in DL. Nevertheless, reliable data
collection is a major limiting factor. Frequently, this problem is undertaken
by combining augmentation of data, transfer learning, dropout, and methods
of normalization in batches. In this… More >
Open Access
ARTICLE
Manish Kumar1,2,*, Nitai Pal1
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2022.032971
Abstract Increasing energy demands due to factors such as population,
globalization, and industrialization has led to increased challenges for existing
energy infrastructure. Efficient ways of energy generation and energy consumption like smart grids and smart homes are implemented to face these
challenges with reliable, cheap, and easily available sources of energy. Grid
integration of renewable energy and other clean distributed generation is
increasing continuously to reduce carbon and other air pollutants emissions.
But the integration of distributed energy sources and increase in electric
demand enhance instability in the grid. Short-term electrical load forecasting
reduces the grid fluctuation and enhances the robustness… More >
Open Access
ARTICLE
Nebras M. Sobahi1,*, Ahteshamul Haque2, V S Bharath Kurukuru2, Md. Mottahir Alam1, Asif Irshad Khan3
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2022.028340
Abstract Increasing renewable energy targets globally has raised the requirement for the efficient and profitable operation of solar photovoltaic (PV)
systems. In light of this requirement, this paper provides a path for evaluating
the operating condition and improving the power output of the PV system
in a grid integrated environment. To achieve this, different types of faults
in grid-connected PV systems (GCPVs) and their impact on the energy loss
associated with the electrical network are analyzed. A data-driven approach
using neural networks (NNs) is proposed to achieve root cause analysis
and localize the fault to the component level in the system.… More >
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