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.
عملية تغيير حجم الصورة في مجال معالجة الصور باستخدام التحويلات الهندسية بدون تغيير دقة الصورة تعرف ب image scaling او image resizing. عملية تغيير حجم الصورة لها تطبيقات واسعة في مجال الحاسوب والهاتف النقال والاجهزة الالكترونية الاخرى. يقترح هذا البحث طريقة لتغيير حجم الصورة باستخدام المعادلات الخاصة بمنحني Bezier وكيفية الحصول على افضل نتائج. تم استخدام Bezier curve في اعمال سابقة في مجالات مختلفة ولكن في هذا البحث تم استخد
... Show MoreSeveral studies have indicated an unprecedented increase in the number of Arab youth who watch music videos. It is also a custom in Arab countries to broadcast songs at their happy parties such as weddings, engagements and birthdays. We see that guests and party owners interact by dancing and singing with the songs, while the viewership rates of Arab music videos have reached millions on YouTube. The researcher decided to study the image of women through the lyrics of these songs, due to their importance in shaping the image of women in the minds of young people and shaping the (self-image) of young women. Twenty songs were selected from the most watched songs on YouTube for the year 2024, and it was found that the negative qualities of t
... Show MoreDeveloping an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal
... Show MoreThis study produces an image of theoretical and experimental case of high loading stumbling condition for hip prosthesis. Model had been studied namely Charnley. This model was modeled with finite element method by using ANSYS software, the effect of changing the design parameters (head diameter, neck length, neck ratio, stem length) on Charnley design, for stumbling case as impact load where the load reach to (8.7* body weight) for impact duration of 0.005sec.An experimental rig had been constructed to test the hip model, this rig consist of a wood box with a smooth sliding shaft where a load of 1 pound is dropped from three heights.
The strain produced by this impact is measured by using rosette strain gauge connected to Wheatstone
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
... Show MorePortable devices such as smartphones, tablet PCs, and PDAs are a useful combination of hardware and software turned toward the mobile workers. While they present the ability to review documents, communicate via electronic mail, appointments management, meetings, etc. They usually lack a variety of essential security features. To address the security concerns of sensitive data, many individuals and organizations, knowing the associated threats mitigate them through improving authentication of users, encryption of content, protection from malware, firewalls, intrusion prevention, etc. However, no standards have been developed yet to determine whether such mobile data management systems adequately provide the fu
... Show MoreThe transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the
... Show MoreThe precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences
... Show MoreSentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l
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Abstract
Due to the lack of previous statistical study of the behavior of payments, specifically health insurance, which represents the largest proportion of payments in the general insurance companies in Iraq, this study was selected and applied in the Iraqi insurance company.
In order to find the convenient model representing the health insurance payments, we initially detected two probability models by using (Easy Fit) software:
First, a single Lognormal for the whole sample and the other is a Compound Weibull for the two Sub samples (small payments and large payments), and we focused on the compoun
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