This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivotal role in expediting diagnosis and treatment processes during medical emergencies. This study introduces an innovative protocol termed collaborative binary Naive Bayes decision tree (CBNBDT) designed to enhance packet classification and transmission prioritization. Through the utilization of this protocol, incoming packets are categorized based on their respective classes, enabling subsequent prioritization. Thorough simulations have demonstrated the superior performance of the proposed CBNBDT protocol compared to baseline approaches.
Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
... Show MoreDisease 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
... Show MoreGiven a matrix, the Consecutive Ones Submatrix (C1S) problem which aims to find the permutation of columns that maximizes the number of columns having together only one block of consecutive ones in each row is considered here. A heuristic approach will be suggested to solve the problem. Also, the Consecutive Blocks Minimization (CBM) problem which is related to the consecutive ones submatrix will be considered. The new procedure is proposed to improve the column insertion approach. Then real world and random matrices from the set covering problem will be evaluated and computational results will be highlighted.
The body concept in the human sciences received significant attention through study and investigation, and has been dealt with by many studies, yet this research is an attempt to reveal the body transformations and its concept in the visualized picture (drawing field) in general and in the drawings of the artist Muhammed Mehraddin in specific. Therefore, the approach of the body, philosophically and technically, in this field has its nature and specificity in revealing the structures and relations in employing the body as a visual, spatially and temporally indicator through the drawing fields of the artist Muhammed Mehraddin, assuming that the body, for the artist's works, constitutes a cultural, artistic performance focus in his a
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Abstract
The human mind knew the philosophy and logic in the ancient times, and the history afterwards, while the semiotics concept appeared in the modern time, and became a new knowledge field like the other knowledge fields. It deals, in its different concepts and references, with the processes that lead to and reveals the meaning through what is hidden in addition to what is disclosed. It is the result of human activity in its pragmatic and cognitive dimensions together. The semiotic token concept became a knowledge key to access all the study, research, and investigation fields, due to its ability of description, explanation, and dismantling. The paper is divided into two sections preceded by a the
... Show MoreThe basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P
... Show MoreThis paper is an attempt to clarify the impact of Postcolonialism, one of the most
challenging fields of study that has emerged in recent years, on representations of women in
once-colonised countries and in Western locations. It discusses the influence of cultural
differences on the status and identity of a woman who experience ‗multiculturalism‘. The
study is an analytical reading of a contemporary novel written by the Iraqi writer Betool Al-
Kudairi. The emphasis lies on the clash between two different cultures and traditions
represented by the British mother and the Iraqi father and its effect on the life and identity of
the protagonist. The main focus is on idea of ‗hybrid identity‘ and the absence of th
This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ
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