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Automated abnormalities detection in mammography using deep learning
Breast cancer is the second most prevalent cause of cancer death and the most common malignancy among women, posing a life-threatening risk....
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Microscopic Damage Analysis of Structural Strength and Fatigue Life of Rotor of Automotive Drive Motor Under Cyclic Operating Conditions
In order to study the structural strength change of automotive drive motor rotor under different cyclic conditions, and the fatigue life change after...
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Short-term wind power prediction based on ICEEMDAN-Correlation reconstruction and BWO-BiLSTM
To solve the problems of high volatility and low prediction accuracy of wind farm output power, this paper proposes a short-term wind power...
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Advanced lower order harmonic torque suppression by P-PWM in high-performance scalar-controlled IM drives
VSI-operated IM drives at low switching per fundamental frequency in a quarter cycle ( N s ) are highly prone to lower order harmonic torque in addition...
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UMGAN: multi-scale graph attention network for grid parameter identification
Parameter identification of transmission lines plays a crucial role in power systems, and many deep learning methods have been continuously applied...
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Study of SVPWM control algorithm with voltage balancing based on simplified vector for cascaded H-bridge energy storage converters
DC-side voltage balancing is a critical problem to be solved for cascaded H-bridge energy storage converters. Aiming at inner-phase voltage balancing...
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Fuzzy nominal sets
In this paper, we use two approaches to define the concept of fuzzy nominal sets: classic and universal algebraic. We see that the fuzzy nominal sets...
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An artificial bee colony algorithm for the minimum edge-dilation K-center problem
This paper studies the minimum edge-dilation K -center (MEDKC) problem for edge-weighted, undirected and connected graphs. This problem which is
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Some New Concepts of Interval-Valued Picture Fuzzy Graphs and Their Application Toward the Selection Criteria
Interval-valued picture fuzzy sets (IVPFSs) being the most advanced form of fuzzy sets (FSs) has more capacity to analyze the network state more...
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A Multi-strategy Improved Grasshopper Optimization Algorithm for Solving Global Optimization and Engineering Problems
This paper presents a multi-strategy improved grasshopper optimization algorithm (MSIGOA), which aims to address the shortcomings of the grasshopper...
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Prototype as query for few shot semantic segmentation
Few-shot Semantic Segmentation (FSS) was proposed to segment unseen classes in a query image, referring to only a few annotated examples named...
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Strong s-box construction approach based on Josephus problem
There are two basic requirements for symmetric encryption algorithms. The first of these is diffusion. The second and most important is confusion. In...
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Performance evaluation of PI and FLC controller for shunt active power filters
Shunt active power filters (SAPF) play a vital role in power systems. Integration of renewable energy sources and electrical vehicle (EV) charging...
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Intrusion detection system and fuzzy ant colony optimization based secured routing in wireless sensor networks
Recent advances in wireless sensor networks (WSNs) have brought the sensor based monitoring developments to the surface in many applications. In such...
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New characterizations of partial orders induced by a class of non-divisible t-norms
In this article, we deal with the algebraic structures of the partial orders induced by non-divisible t-norms. We first give a condition for the...
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Generating fuzzy sets using rearranged nested family and the mathematical formula in decomposition theorem
The purpose of this paper is to propose a mechanical procedure to generate fuzzy data from the observed real number data. The observed data may be...
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On join-complete implication algebras
In this paper, first, we consider an algebra that has a binary operation and a join of arbitrary nonempty subset. A lattice implication algebra is a...
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Predicting the potential toxicity of the metal oxide nanoparticles using machine learning algorithms
Over the years, machine learning (ML) algorithms have proven their ability to make reliable predictions of the toxicity of metal oxide nanoparticles....
