The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

Objectives To tailor composites of polyethylene–hydroxyapatite to function as a new intracanal post for the restoration of endodontically treated teeth (ETT). Methods Silanated hydroxyapatite (HA) and zirconium dioxide (ZrO2) filled low-density polyethylene (LDPE) composites were fabricated by a melt extrusion process and characterised using infrared spectroscopy (FTIR), differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA). The flexural strength and modulus were determined in dry state and post ageing in simulated body fluid and fractured surfaces analysed by SEM. The water uptake and radiographic appearance of the experimental composites were also measured and compared with a commercially known endodontic fibre

Operated Alandziahih "drift theory" as a science talk in most of the cash and technical studies in the early twentieth century, making him and the sciences, arts and culture both fields of experiences, in an attempt to explore the institutions that theory, a number of laws which took control in the internal structures of those acts, resulting in for those institutions to be actively contribute their ideas to guide the pace on the right track. And thus lay the foundations of this theory, which was a big affair in the early twentieth century and still vigorous pace to this day, particularly their applications in various fields of the arts.Although each type of Arts, both in the composition or the theater or means of communication, took joi

This study deals with the role that social work profession plays in all its fields to reduce social extremismat home, or school or within society. The study aims to: examine the historical roots of social work in the Iraqi society, investigate the objectives of the developmental role of social work, review the theories of social extremism, its characteristics, and causes, and to analyze the developmental role of social work to limit social extremism. To meet the objectives of the study, a descriptive analytical approach has been adopted. It involves using the social sampling survey method, i.e., a questionnaire tool in the University of Baghdad community-College of Media. The sample was randomly selected to include (100) students from th

This research laid the recruitment & use of IT Animatic digital TV drama & inviting ways of working is simple &effective in the level of producing images especially in TV drama, so the entry of this technology has created the concepts of new technology, and simple & effective at the same time with high level of modernity & technical innovation, this research deals with three chapters that includes two topics the animatic modes & the stages of production , & what is the atheistic aspects that is provided by this technology with the researcher reviewing the use of some TV dramatic Production series that was mentioned through this research.Which afterwards the researcher has analyzed a sample that was selected fo

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti