The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. This paper uses image histograms of oriented gradients (HOG) features and an SVM model to discuss a character recognition model for identifying partial and blurred Qin seal script characters. The model achieves accurate recognition on a small, imbalanced dataset. Firstly, a dataset of Qin seal script image samples is established, and Gaussian filtering is employed to remove image noise. Subsequently, the gamma transformation algorithm adjusts the image brightness and enhances the contrast between font structures and image backgrounds. After a s

In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

In this work, chemical oxidation was used to polymerize conjugated polymer "Polypyrrole" at room temperature Graphene nanoparticles were added by in situ-polymerization to get (PPY-GN) nano. Optical and Electrical properties were studied for the nanocomposites. optical properties of the nanocomposites were studied by UV-Vis spectroscopy at wavelength range (200 -800 nm). The result showed optical absorption spectra were normally determined and the result showed that the maximum absorbance wave length at 280nm and 590nm. The optical energy gap has been evaluated by direct transition and the value has decreased from (2.1 eV for pure PPy) to (1.3 eV for 5 %wt. of GN). The optical constants such as the band tail width ΔE was evaluated, the

This study was done to investigate the impact of different nanoparticles on diesel fuel characteristics, Iraqi diesel fuel was supplied from al-Dura refinery and was treated to enhance performance by improving its characteristics. Two types of nanoparticles were mixed with Iraqi diesel fuel at various weight fractions of 30, 60, 90, and 120 ppm. The diesel engine was tested and run at a constant speed of 1600 rpm to examine and evaluate the engine's performance and determine emissions. In general, ZnO additives' performance analysis showed they are more efficient for diesel fuel engines than CeO. The performance of engine diesel fuel tests showed that the weight fraction of nanoparticles at 90 and 120 ppm give a similar

The impact of cartoon concepts strategy in the Achievement of the first grade student's average in geography and visual thinking

The study aimed to measure the impact of cartoon concepts strategy to Achievement, visual thinking in the first grade students in the average geographical material.

Find sample consisted of 52 students were divided into two groups, the first experimental studied strategy cartoon concepts and the control group was studied in the traditional manner of parity between the two variables (chronological age, the overall rate, prior knowledge, the degree of intelligence, visual) thinking.

This study was done to investigate the impact of different nanoparticles on diesel fuel characteristics, Iraqi diesel fuel was supplied from al-Dura refinery and was treated to enhance performance by improving its characteristics. Two types of nanoparticles were mixed with Iraqi diesel fuel at various weight fractions of 30, 60, 90, and 120 ppm. The diesel engine was tested and run at a constant speed of 1600 rpm to examine and evaluate the engine's performance and determine emissions. In general, ZnO additives' performance analysis showed they are more efficient for diesel fuel engines than CeO. The performance of engine diesel fuel tests showed that the weight fraction of nanoparticles at 90 and 120 ppm give a similar performance,

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator