ABSTRACT Automated and accurate classification of MR brain images is crucially importance for medical analysis interpretation. We proposed a novel automatic system based on particle swarm optimization (PSO) artificial bee colony (ABC), with the aim distinguishing abnormal brains from normal in MRI scanning. The method used stationary wavelet transform (SWT) to extract features images. SWT translation‐invariant performed well even image suffered slight translation. Next, principal component...

Ferromagnetic materials are extensively utilized in industrial settings where the early detection and repair of defects is paramount for ensuring safety. During enhanced magnetic memory micro-defects, many interference signals appear signal, which makes it difficult to accurately extract characteristics micro-defect signals, significantly affecting effectiveness. When improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) employed independently signal...

Abstract For logging pulsed neutron tube with diameter less than 25 mm, a smaller Penning ion source cylindrical plasma volume of Φ8 mm × 9 was designed to investigate the pulse characteristics anode current. The time and amplitude current as function deuterium pressure voltage were studied experimentally. preferred working parameters for this suggested, then obtained in range 1 mA∼ 3.5 mA, shortest delay 5 μs. extract running stably efficiency 22%∼ 27% application.

Finding an appropriate and accurate technology for early detection of disease is significantly important to research treatments. We proposed some novel automatic classification systems based on the stationary wavelet transform (SWT) improved support vector machine (SVM). Magnetic Resonance Imaging (MRI) commonly used brain imaging as a non-invasive diagnostic tool assist pre-clinical diagnosis. However, MRI generates large information set, which poses challenge classification. To deal with...

Under nonequilibrium conditions, inorganic systems can produce a wealth of life-like shapes and patterns which, compared to well-formed crystalline materials, remain widely unexplored. A seemingly simple example is the formation salt deposits during evaporation sessile droplets. These evaporites show great variations in their specific including single rings, creep, small crystals, fractals, featureless disks. We have explored 42 different salts at otherwise constant conditions. Based on...

Aim: Alzheimer's disease patients are increasing rapidly every year. Scholars tend to use computer vision methods develop automatic diagnosis system. (Background) In 2015, Gorji et al. proposed a novel method using pseudo Zernike moment. They tested four classifiers: learning vector quantization neural network, pattern recognition network trained by Levenberg-Marquardt, resilient backpropagation, and scaled conjugate gradient. Keywords: Linear regression classifier, machine learning,...

Multi-objective path finding (MOPF) problems are widely applied in both academic and industrial areas. In order to deal with the MOPF problem more effectively, we propose a novel model that can cope deterministic random variables. For experiment, compared five intelligence-optimization algorithms: genetic algorithm, artificial bee colony (ABC), ant optimization (ACO), biogeography-based (BBO), particle swarm (PSO). After 100-run comparison, found BBO is superior other four algorithms regard...

The Fractional Fourier transform (FRFT) is a relatively novel linear transforms that generalization of conventional (FT). FRFT can particular signal to unified time-frequency domain. In this survey, we try present comprehensive investigation FRFT. Firstl y, provided definition and its three discrete versions (weighted-type, sampling-type, eigendecomposition-type). Secondly, offered theoretical research technological studies consisted hardware implementation, software optimal order selection....

It is of great importance to early detect abnormal brains, in order save social resources.However, potential wavelet decomposition not fully explored and widely used.The wavelet-energy was a successful feature descriptor that achieved excellent performance various applications; hence, we propose based new approach for automated classification MR human brain images.The consisted three-stage system, including decomposition, energy extraction, support vector machines.The results proposed showed...

As time series data with internal correlation, networks traffic can be used for abnormal detection using Recurrent Neural Network (RNN) and its variants, but existing models are difficult to calculate in parallel, gradient explosion or vanishing easily occurs. To address this problem, we propose a Bidirectional Independent (BiIndRNN) parallel computation adjustable gradient, which extract the bidirectional structural features of by forward backward input capture spatial influence flow....

Wind power forecasting is one of the cheapest and direct methods to alleviate negative impacts on system reliability stability from intermittent wind generation. Compared with deterministic forecasts, probabilistic forecasts can provide additional information concerning uncertainty for economic operation efficient trading. However, it far ideal respect accuracy, sharpness, since shows strong variable property. In this paper, a robust method proposed as (RPWPF) that reflect variability...

In this paper, a method for rationally allocating energy storage capacity in high-permeability distribution network is proposed. By constructing bi-level programming model, the optimal of connected to allocated by considering operating cost, load fluctuation, and battery charging discharging strategy. four scenarios with photovoltaic permeability 29%, it was found that decision-making model proposed paper saves 2346.66 yuan 2055.05 yuan, respectively, daily operation cost compared scenario...

The simulation of wind power time series is a key process in renewable allocation planning, operation mode calculation, and safety assessment. Traditional single-point modeling methods discretely generate at each moment; however, they ignore the daily output characteristics are unable to consider both accuracy efficiency. To resolve this problem, model based on typical processes Markov algorithm proposed. First, classification method similarity modified K-means clustering presented. Second,...

Programmers often abbreviate identifiers names in source code to represent single words, i.e. unigrams, or phrases, multigrams. However, the difficulty retrieve original word(s) of an abbreviation during maintenance phase makes more problematic comprehend. Incorrect abbreviations expansion may lead introducing defects code. There are many approaches that automatically expand their unfortunately, they based on predefined patterns and single-words dictionaries which cannot address expandable...