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

Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.

Intellectual and material displacement is one of the design strategies through many mechanisms and means, and depends on the idea of changing the shape within the internal spaces at times and has concepts related to the transformation at other times. And represented by the boxes for travelers, the research problem emerged through the following question: (What is the effectiveness of displacement in the formal structures in the interior design of historical sites), and the aim of the study is to reveal the reality of the use of historical internal spaces and to determine the formal displacement that occurs as a result of change and transformation, and it included two topics, the first topic Transformation and the effectiveness of formal d

The research deals with the interchange of the sign transformed from the universal to the local in the theatrical show through the direction processing in the production of a communicative artistic discourse and message, thus making the process of reading the speech and recognizing it by taking into account the cultural differences, customs and local rituals of each country, region, or area. The problem of the research was focused on answering the following question: What are the requirements for the sign in terms of its transformation between the universality and locality in the read-out?

               The importance of research is to determine the requiremen

End of the twentieth century witnessed by the technological evolution Convergences between the visual arts aesthetic value and objective representation of the image in the composition of the design of the fabric of new insights and unconventional potential in atypical employment. It is through access to the designs of modern fabrics that address the employment picture footage included several scenes footage from the film, which focuses on research and analytical as a study to demonstrate the elements of the picture and the organization of its rules and how to functioning in the design of fabrics, Thus, it has identified the problem by asking the following: What are the elements of the picture footage and how the functioning of the struct

In this paper, the continuous classical boundary optimal control problem (CCBOCP) for triple linear partial differential equations of parabolic type (TLPDEPAR) with initial and boundary conditions (ICs & BCs) is studied. The Galerkin method (GM) is used to prove the existence and uniqueness theorem of the state vector solution (SVS) for given continuous classical boundary control vector (CCBCV). The proof of the existence theorem of a continuous classical boundary optimal control vector (CCBOCV) associated with the TLPDEPAR is proved. The derivation of the Fréchet derivative (FrD) for the cost function (CoF) is obtained. At the end, the theorem of the necessary conditions for optimality (NCsThOP) of this problem is stated and prov

This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed