Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

<span lang="EN-GB">This paper highlights the barriers that have led to a delay in the implementation of E-Health services in Iraq. A new framework is proposed to improve the E-Health sector using a SECI model which describes how explicit and tacit knowledge is generated, transferred, and recreated in organizations through main stages (socialization, externalization, combination and internalization). Class association rules (CARs) is integrated to mine the SECI model by extracting related rules which correspond to the medical advice. The proposed framework (SECICAR) can be done through a web portal to assemble healthcare professionals, patients in one environment. SECICAR will be applied to the hypertension community to show th

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

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ABSTRACT:

Objectives: The study aims to know the effectiveness of the educational program in the patient’s adherence to medication and diet and to know the relationship between the effectiveness of the education program and their demographic data related to the patient’s age, gender, marital status, education level, occupation, monthly income and residence.

Methodology: A quasi -experimental design study was performed on patient who attended to Gastroenterology and Hepatology Teaching Hospital, from March 2021 to September 2021. The non-probability sampling including 50 patients for case study and 30 patients for control group. The questionnaire consists of 3 parts, part one the socio

Advertisements containing images of women represent one of the most controversial topics of the advertising industry and has an impact on people and trends. This study aims to determine the typical mental image of women purveyed through visual advertising in the Arab media. It also aims to find out whether these advertisements portray women positively or negatively, in addition to investigating the reasons for the recent negative portrayal of women in commercials. The study adopted a descriptive-analytical approach to achieve these objectives. The results indicate that advertising designs that carry images of women displayed in the Arab media create strong mental images. Repetition reinforces these images, and they emphasize the concept

يتناول البحث شخصية شعرية وأدبية فذة هو محمد صالح بحر العلوم الشاعر العراقي المعروف والمولود في بيت ثوري من بيوتات النجف المعادية للاستعمار البريطاني في مطلع القرن العشرين، وينحدر من أسرة عريقة مشهورة بالعلم والأدب، عاش بحر العلوم شاعراً ينقل بصوره الجمالية كل ما يقع في حواسه، وتجربته تثري من اتصاله ببيئته فنجد الشاعر اشبه بالمصور يستمد صوره من واقع بيئته المتنوع. ونحن في بحثنا هذا نحاول أن نرصد أهم المصادر