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 supervised machine learning classification techniques, Learning Vector Quantization (LVQ) and Support Vector Machine (SVM) classifiers, to achieve better search performance and high classification accuracy in a heterogeneous WBASN. These classification techniques are responsible for categorizing each incoming packet into normal, critical, or very critical, depending on the patient's condition, so that any problem affecting him can be addressed promptly. Comparative analyses reveal that LVQ outperforms SVM in terms of accuracy at 91.45% and 80%, respectively.
The job that confronts players with the effectiveness of shooting with an air rifle is high, so it requires necessary functional adaptations that differ in their degrees from other sports. Regular training in air rifle shooting leads to physiological changes in most of the body's internal systems, and changes and responses can be identified. The functional accompanying physical activity through the presence of body components that reflect these physiological changes in the form of changes in some components, and the importance of research lies in studying the physiological changes accompanying the maximum physical effort and the consequent development of the level of achievement in the effectiveness of shooting with air rifle and body
... Show MoreThe role of the green areas lies in being one of the systems that plays the vital role in achieving the environmental dimension besides the socio-cultural body and the economic dimension in the hidden value of ecosystem services. However, many developing countries are characterized by a state of low community environmental awareness, which coincides with the basic need for land for housing and other uses, to take precedence over nature protection strategies. In the absence of clear planning and long-term planning strategies, all this led to abuses and violations of urban land use. In Iraq, the situation became more apparent due to the political, security and social conditions that followed the year 2003. Hence, the resea
... Show MoreThe aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).
The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA
... Show MoreTarget tracking is a significant application of wireless sensor networks (WSNs) in which deployment of self-organizing and energy efficient algorithms is required. The tracking accuracy increases as more sensor nodes are activated around the target but more energy is consumed. Thus, in this study, we focus on limiting the number of sensors by forming an ad-hoc network that operates autonomously. This will reduce the energy consumption and prolong the sensor network lifetime. In this paper, we propose a fully distributed algorithm, an Endocrine inspired Sensor Activation Mechanism for multi target-tracking (ESAM) which reflecting the properties of real life sensor activation system based on the information circulating principle in the endocr
... Show MoreBackground: Hair loss is a common distressing disease and challenging problem for many dermatologist. Telogen effluvium is the most common hair loss disease in which nutritional deficiencies may precipitate the disease through their effect on hair structure and growth.
Study Aim : Validating role of serum ferritin level and body mass index in Chronic Telogen Effluvium and analyzing association between these factors with socioeconomic, demographic, gynecological factors and weight loss effect. Establishing a nutritional preventive advice to improve treatment successfulness and decrease the disease occurrence.
... Show More
Background: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver.
Objectives: To assess age, sex, and body
... Show MoreThe performance measures and traditional methods used in management accounting is no longer able to provide convenient to evaluate the performance of economic units in the modern manufacturing environment information، and so this information is more important and feasibility must be Mistohat of all the company's activities and functions، and it is a problem Find the inadequacy of information management accounting that contribute to meet the needs of the upper levels of management to cope with the problems resulting from the increased size and complexity of the business، and lack of management accounting information and methods used in the performance evaluation، which reflected negatively on the value chain activities and then on the
... Show More