The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

Hellenistic architecture represents an important example of the reflection of ancient Greek architecture in the art of oriental architecture in the countries of the ancient world, including those states spread across North Africa that were under the authority of the Ptolemies and who were able to transmit those artistic values and traditions of Greek architecture to those regions. The current research deals with a detailed study of those important transformations of civil and religious architecture, as well as the most important features of that architecture through the constituents of location and geographical location.

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

This research deals with compound sentences in the German language and how to transform them and transfer them into a main sentence, touching on their functions and characteristics. Actual to nominative, which is a unique feature of the German language, with some diverse examples taken from various sources.
This case is distinguished, like other grammatical cases

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

Despite the history of Baghdad city extends into a long history, most of the contemporary buildings of Baghdad have been shaped in the era of modernity. Furthermore, most of the buildings of modernity in Baghdad are types of modernity buildings in Iraq as a whole, and due to all the joints of change and development are taking place in Iraq starts from Baghdad. Accordingly, all selected buildings, which would be presented as case studies of modernity will be exclusively in Baghdad. Although the importance of this significant modernist product, which represents the identity of Baghdad, which should be preserved by the renewal and preservation policies, the problem of research was emerged as follow: new fin

  The current research is interested in studying the symbol, due to its significant role in the architecture and arts in the holy shrines regardless of their architecture and artistic patterns, through which the symbolic and philosophical connotations insides the holy shrines are revealed. Due to the importance of the topic of the symbol, Almighty God remarked in the holy Quran (He said, "My Lord, make for me a sign." He Said, "Your sign is that you will not [be able to] speak to the people for three days except by gesture. And remember your Lord much and exalt [Him with praise] in the evening and the morning.") (Surat Al-Imran, verse 41). The research consists of two dimensions dealing with symbol and symbolism in its linguistic an