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 series of preprocessing operations, the oriented gradient histograms (HOG) features are extracted from the images. During model training, different weights are assigned to classes with varying sample quantities to address the issue of class imbalance and improve the model's classification accuracy. Results show that the model achieves an accuracy of 95.30%. This research can help historians quickly identify and extract the text content on newly discovered Qin slip cultural relics, shortening the cycle of building a historical database.
The research aims to identify the importance of applying resource consumption accounting in the Iraqi industrial environment in general, and oil in particular, and its role in reducing the costs of activities by excluding and isolating idle energy costs, as the research problem represents that the company faces deficiencies and challenges in applying strategic cost tools. The research was based on The hypothesis that the application of resource consumption accounting will lead to the provision of appropriate information for the company through the allocation of costs properly by resource consumption accounting and then reduce the costs of activities. To prove the hypothesis of the research, the Light Derivatives Authority - Al-Dora Refin
... Show MoreThe electrospun nanofibers membranes have gained considerable interest in water filtration applications. In this work, the fabrication and characterization of the electrospun polyacrylonitrile-based nonwoven nanofibers membrane are reported. Then, the membrane's performance and antifouling properties were evaluated in removing emulsified oil using a cross flow filtration system. The membranes were fabricated with different polyacrylonitrile (PAN) concentrations (8, 11, and 14 wt. %) in N, N-Dimethylformamide (DMF) solvent resulted in various average fiber sizes, porosity, contact angle, permeability, oil rejection, and antifouling properties. Analyses of surface morphology of the fabricated membranes before and after oil removal revealed
... Show MoreThis research is concerned with documenting and chronicling the art of NFTs art in the Saudi artistic cultural scene, the importance of which stems from the lack of scientific sources that document this field until the preparation of this research and aims to trace historically the emergence of the field of NFTs art in the Kingdom of Saudi Arabia in the arts sector through the experiences of Saudi artists. The most prominent events for the culture, arts and technology sector, and other Saudi sectors. The research dealt with the history of the emergence of the field of NFTs art, which extends from the history of digital arts, and reviewed the most famous works of NFTs art.
As a result of the technical revolution and the artistic move
Molecularly imprinted polymers (MIPs) are an effective method for separating enantiomeric compounds. The main objective of this research is to synthesize D-arabinitol MIPs, which can selectively separate D-arabinitol and its potential application to differentiate it from its enantiomer compound through a non-covalent approach. A macroporous polymer was synthesized using D-arabinitol as a template, acrylamide as a functional monomer, ethylene glycol dimethacrylate (EGDMA) being a cross-linker, dimethylsulfoxide (DMSO) being a porogen, as well as benzoyl peroxide being an initiator. After polymer synthesis, D-arabinitol was removed by a mixture of methanol and acetic acid (4:1, v/v). Fourier-Transform Infrared spectroscopy (FT-IR) and Scan
... Show MoreThis paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them
Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using
... Show MoreWireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
... Show MoreUnconfined compressive strength (UCS) of rock is the most critical geomechanical property widely used as input parameters for designing fractures, analyzing wellbore stability, drilling programming and carrying out various petroleum engineering projects. The USC regulates rock deformation by measuring its strength and load-bearing capacity. The determination of UCS in the laboratory is a time-consuming and costly process. The current study aims to develop empirical equations to predict UCS using regression analysis by JMP software for the Khasib Formation in the Buzurgan oil fields, in southeastern Iraq using well-log data. The proposed equation accuracy was tested using the coefficient of determination (R²), the average absolute
... Show MorePorosity plays an essential role in petroleum engineering. It controls fluid storage in aquifers, connectivity of the pore structure control fluid flow through reservoir formations. To quantify the relationships between porosity, storage, transport and rock properties, however, the pore structure must be measured and quantitatively described. Porosity estimation of digital image utilizing image processing essential for the reservoir rock analysis since the sample 2D porosity briefly described. The regular procedure utilizes the binarization process, which uses the pixel value threshold to convert the color and grayscale images to binary images. The idea is to accommodate the blue regions entirely with pores and transform it to white in r
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