The 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 into BRAC, BRAF, and KRAS categories. Our comprehensive methodology includes rigorous data preprocessing, model training, and a multi-faceted evaluation approach. The adapted U-Net model exhibited exceptional performance, achieving an overall accuracy of 0.96. The model also achieved high precision and recall rates across the classes, with precision ranging from 0.93 to 1.00 and recall between 0.95 and 0.97 for the key markers BRAC, BRAF, and KRAS. The F1-score for these critical markers ranged from 0.95 to 0.98. These empirical results substantiate the architecture’s capability to capture local and global features in DNA sequences, affirming its applicability for critical, sequence-based bioinformatics challenges
The concept of aesthetics is one of the postmodern propositions, and it is one of the branches of philosophy that examines beauty, its standards and theories, and it is a holistic concept that includes several concepts, including the beautiful, the ugly, and the sublime.
The concept of aesthetics dealt with several studies in general (and in the field of architecture in particular), and the problem of aesthetics is in the blurring of the relationship between aesthetics and architectural criticism, based on the research hypothesis which states that there is a relationship between aesthetics and architectural criticism. The importance of the research in accommodating aesthetic standards and bases of evaluation that increases the possi
Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing
... Show MoreSkull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no
... Show MoreAfter the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
... Show MoreDeep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec
... Show MoreSatire is genre of the literary arts that has always been the source of human interest. Because it is difficult to accept direct criticism, Satire appears as a literary tool in which vices, follies, abuses and shortcomings are held up to ridicule, with the intent of shaming individuals, corporations, government, or society itself into improvement. A satirical critic usually employs irony to attain this goal. Although satire is usually meant to be humorous, its greater purpose is often profitable social criticism, using wit to draw at
... Show MoreRecommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o
... Show MoreRhythm is considered one of the creative concepts in the recent architectural thought; it has emerged clearly as a mean of creating the highest levels of creativity in architecture, especially in contemporary architectural movements. The importance of rhythm has emerged, especially, when the architecture , its beginnings concentrated on the principle of the links with poetic structures. Many architectural studies deal with concept of rhythm in architecture with different ways various according to the trend of each study, this show the importance of studying the concept of rhythm in the architectural field in general. This study try to focus on the utilization of rhythm as creative system in architecture of heritage and contemporary
... Show MoreThe authentic traditional architecture proved that it is very convenient to the environmental and social regulations where it appeared and lasted for hundred of years.
This traditional architecture got the intelligence in providing thermal comfort for their occupants by the intelligent usage of the building materials and the intelligent planning and designs which took in consideration the climatic condition and the aerodynamics of the whole city as one ecological system starting from the cold breeze passing through its narrow streets till it enters the dwelling units and glides out through the wind catchers.
This architecture had been neglected and replaced by modern imported architecture which had collap
... Show MoreRecently new trends of mosques’ architecture have appeared. These trends differed from those of traditional ones in charictaristics which include two and three dimentional level. The traditional mosques' architecture are affected by several factors, so the research problem is (lack of knoweledge about factors forming traditional mosques' architecture and its effect on contemporary trends of mosques' architecture).The hypotheses of research is (the functional, aesthetic and symbolic religious factors of style are the most active factors in forming contemporary trends of mosques' architecture than religious and environmental factor).The research conclusion is that the symbolic functional factor is most effective factor i
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