This study confirms the ubiquitin conjugating enzyme 2B (Rad6) plays a significant role in the DNA repair pathway also because the ubiquitin-conjugating pathway. The DNA repair pathway could be a variety of bypass repair mechanism where the broken base pair is bypassed by permitting the replication fork to labor under the site of injury. This is often done by a shift mechanism wherever deoxyribonucleic acid enzyme - δ is switched with DNA enzyme - η (DNAP - η). Site of DNAP - η is massive enough to permit the broken ester to labor under, and so bypass the broken nucleotide. However, this is often potential solely through the involvement of Proliferating cell nuclear antigen (PCNA) that could be a processivity issue and it acts as a plat

Various visual media are becoming an increasingly important and active instrument of communication. This fact has led some political parties and leading personalities in Iraq to make use of them as an accepted forum for the discussion of public affairs usually in a manner that conforms to their declared policy. They have to draw as much popular support as they could for the causes which they fight for. As a result, a state of great confusion has been created from the contradictory statements made by the contending parties and gave left grave consequences on all types of the audience receiving them. The problem of the study can be summarized in one major question: What is the opinions of the audience as regards the statements made by the

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

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