Graphic design constitutes the human necessity for the design action, so there is no design achievement that is not considered in its founding project and its final realization as a response to a specific necessity. As a result of knowledge, which is the product of experience and is the result of applied science, design is based on observation, study and development, leading to the main goal, which is the utilitarian and aesthetic function that is put into the final consideration of design, and drug packaging design has an important role in all marketing fields, as companies compete with each other to attract the largest number Possible from consumers in a way that guarantees them material profit, and in order to achieve this, it always

The significance of the research lies in the fact that electronic technologies represent an important step in evaluating legal situations, and the research problem centered on the lack of attention to visual requirements and the absence of a clear image of legal situations that may be difficult for the referee to apply correctly in addition to the lack of focus on visual requirements and the unclear depiction of some legal cases which make it difficult for the referee to interpret them correctly This is because the referee's main tool is visual perception, which interprets live situations such as violations, fouls, and other cases that arise during a game Moreover, there are numerous responses and challenges in evaluating legal situ

In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

Nanofiltration (NF) ceramic membrane have found increasing applications particularly in wastewater and water treatment. In order to estimate and optimize the performance of NF membranes, the membrane should be characterized correctly in terms of their basic parameters such as effective pore radius (r_p) and equivalent effective thickness as well as effective surface charge ( ), the effective charge density ( ) and Donnan potential ( ). The impact of electrokinetic (zeta) potential on the membrane surface charge density, effective membrane charge density and Donnan potential at two different concentrations of the reference solutions 0.001, 0.01 M sodium chloride at various pH values from 3 to 9, and effective po

KE Sharquie, AA Noaimi, MS Abass, American Journal of Dermatology and Venereology, 2019 - Cited by 4

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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