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

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

The necessities of steganography methods for hiding secret message into images have been ascend. Thereby, this study is to generate a practical steganography procedure to hide text into image. This operation allows the user to provide the system with both text and cover image, and to find a resulting image that comprises the hidden text inside. The suggested technique is to hide a text inside the header formats of a digital image. Least Significant Bit (LSB) method to hide the message or text, in order to keep the features and characteristics of the original image are used. A new method is applied via using the whole image (header formats) to hide the image. From the experimental results, suggested technique that gives a higher embe

One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

The chemical, physical and toxicological effects on health of synthetic dyes that used as tracking dye in the electrophoresis requires seriously search about alternative tracking dye. The present study is aimed to find an alternative dye from safe food dyes which commonly used in food coloring. Five dyes were selected depending on their chemical properties and the availability in local market: Brilliant Blue FCF, Tartrazine, Sunset Yellow FCF, Carmoisine, and green traditional, three dyes were chosen to be mixed as loading buffer: Brilliant Blue FCF, Sunset Yellow FCF as a basic because it give the whole range size of most traditional loading buffers that available in market, and adding the Carmoisine as a new indicator for the bands less t

Granular carbon can be used after conventional filtration of suspended matter or, as a combination of filtration - adsorption medium. The choice of equipment depends on the severity of the organic removal problem, the availability of existing equipment, and the desired improvement of adsorption condition.
Design calculations on dechlorination by granular - carbon filters considering the effects of flow rate, pH , contact time, head loss and bed expansion in backwashing , particle size, and physical characteristics were considered assuming the absence of bacteria or any organic interface .

This research aims to analyse the problem of organizations in general and universities in particular, in dealing with �quality subjects� in a world where these organizations face the risks of becoming side lined and possibly vanished without looking for solutions that allow them to move in an open arena where change becomes the key to those solutions. Change here must be strategic and planning must adopts a way for organizations to develop mechanisms to manage change itself. Management leaders play a central role in achieving the principle required to chart new trends for universities in dealing with quality as a strategy that allows excellence and competition in light of the success of the processes of change. Change through reengineer