<title>Abstract</title> Current atmospheric turbulence degradation image simulations struggle to meet the efficiency requirements of modern large-scale datasets. This paper applies Principal Component Analysis, Kolmogorov-Arnold Network and FiLM structures simulation computations, proposing an accelerated algorithm for simulation. Experimental results show that our achieves average processing time 3.08 seconds per image, which is significantly faster compared traditional phase screen...

This paper proposed a novel spectrometric quantification method for nitrate and COD concentration in water using double-channel 1-D convolution neural network relatively long UV-vis absorption spectra data (2600 points). To improve the model's ability to resist turbidity disturbance, new dataset augmentation was applied of under different disturbances were successfully simulated. Compared PLSR model, value RRMSEP CNN model reduced from 6.1% 1.4% solution 4.5% 1.3% solution. regression...

Accurate and rapid detection of single-nucleotide polymorphism (SNP) in pathogenic mutants is crucial for many fields such as food safety regulation disease diagnostics. Current methods involve laborious sample preparations expensive characterizations. Here, we investigated a single locked nucleic acid (LNA) approach, facilitated by nanopore single-molecule sensor, to accurately determine SNPs Shiga toxin producing Escherichia coli (STEC) serotype O157:H7, cancer-derived EGFR L858R KRAS G12D...

Chemical Oxygen Demand (COD) is one of the indicators organic pollution in water bodies. The rapid and accurate detection COD great significance to environmental protection. To address problem retrieval errors absorption spectrum method for fluorescent matter solutions, a synchronous absorption-fluorescence proposed. Based on one-dimensional convolutional neural network 2D Gabor transform, an fusion algorithm developed improve accuracy retrieval. Results show that RRMSEP 0.32% amino acid...

Ground-based remote observation systems are vulnerable to atmospheric turbulence, which can lead image degradation. While some methods mitigate this turbulence distortion, many have issues such as long processing times and unstable restoration effects. Furthermore, the physics of is often not fully integrated into reconstruction algorithms, making their theoretical foundations weak. In paper, we propose a method for mitigation using optical flow convolutional neural networks (CNN). We first...

This paper introduces a novel customers' demand forecasting model based on least squares support vector machines (LS-SVM) for e-business enterprises. Firstly, the presents actual state of e-business, and discusses some factors that block advance in China. Then, common techniques used are briefly reviewed together with their shortcomings respectively. To solve these disadvantages, reviews fundamental theory regression, analyses merits theory. At last, theory, proposes to forecast pure water...

The imaging equipment working in the atmosphere will not only be limited by performance of system, but also affected turbulence. In fields astronomical observation, ground-based remote sensing and monitoring, there is an urgent need for corresponding methods technologies to eliminate impact atmospheric turbulence obtain clear images. With development computer technology, optics theory image processing more researchers hope combine deep learning technology with reduce on stable this paper, a...

We obtain an intrinsic optical turbulence model using a data-driven method named complete ensemble empirical mode decomposition. First, the measured profile of refractive index structure parameter is decomposed into set functions and residue. The components are tested against white noise to determine statistical significance. Meanwhile, physical meanings IMFs revealed meteorological data that agrees with previous research. Second, effect noisy oscillations, quasi-cyclical variations, trend...

Recent years, research on the detection of heavy metals in Traditional Chinese Medicine (TCM) by laser induced breakdown spectroscopy (LIBS) have gradually increased. Current main methods establishing calibration curve are based grounding and pelleting tested samples. Although compared to digested samples, sample is already quite simple, it cannot fully reflect advantages LIBS: rapid analysis, and, also, uneven distribution TCM ignored. In order avoid grinding be tested, achieve microdamage...

Aerosol robotic network (AERONET) data from Dongsha Island (20.699N, 116.729E) and Taiping (35.90N, 3.03W) over the South China Sea (SCS) January 2018 to December 2020 were used analyze discuss temporal evolution properties of aerosols in Sea. Surrounding AERONET stations (Hong Kong, NSPO, Nha Trang Singapore) also regional characteristics. High aerosol loads strongly associated with anthropogenic fine particle transport southeastern coast occasional advection desert dust Mongolian areas....

A new method for load forecasting based on LS-SVM, PSO and wavelet transform is proposed. The adopted to decompose the historical data, so approximate part several detail parts are obtained. results of predicted by a separate LS-SVM predictor. employed determine these parameters SVM model. novel forecast model integrates advantage WT, LS-SVM. Compared with other predictors, this has greater generality ability higher accuracy.

Ultraviolet-visible absorption spectroscopy is widely used to monitor water quality, and rapid optical signal detection a key technology in the process of spectrum measurement. In this paper, an ultrafast spectrophotometer system that can achieve data acquisition single flash xenon lamp (within 200 ns) introduced, real-time denoising method for implemented on field programmable gate array (FPGA) work cooperatively with nanosecond system, order guarantee quality signals without losing running...

Most existing risk prediction methods focus on constructing element sets and analyzing their uncertainties but do not deeply explore the correlation types intensities of factors, resulting in large errors comprehensive results. In this paper, a new integrated method is proposed based tasks defense task planning execution. The approach mainly includes following steps: First, difference sequence mode action link tasks, three (hierarchical, synergistic, independent) are defined among them,...

An efficient protocol for separating inorganic mercury and methylmercury from marine biota high-precision isotopic analysis.

To evaluate the effects of intermittency and stratification on propagation laser beams, we analyze experimental radiosonde profiles using complete ensemble empirical mode decomposition. First, extract at different scales from original Cn2 profiles. Second, establish an intrinsic optical turbulence model (IOTM), which includes fine structures. Third, calculate several moments IOTM. The results quantitatively variations typical parameters relevant to effects.

In Three-dimensional (3D) Integrated Circuit (IC), dummy TSVs are often required for thermal and thinning concerns. this paper, we propose to use those "timing wasteful" timing optimization in on-chip memory, that is replace bit line delay cells with TSVs. The time measured different TSV sizes, arrays, technology nodes. Three memories employed verify the feasibility reliability of proposed technology.

As an effective tool in pattern recognition and machine learning, support vector (SVM) has been adopted abroad. In developing a successful SVM classifier, eliminating noise extracting feature are very important. This paper proposes the application of kernel PCA to for extraction. Then PSO Algorithm is optimization these parameters SVM. The novel time series analysis model integrates advantage wavelet, PSO, KPCA Compared with other predictors, this greater generality ability higher accuracy.