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.
In this study, the possible protective effects of daidzein on ifosfamide-induced neurotoxicity in male rats were examined by the determination of changes in selected oxidant–antioxidant markers of male rats’ brain tissue.
Twenty-eight (28) apparently-healthy Wistar male rats weighing (120-150gm) allocated into 4 groups (n=7) were used in this study. Rats orally-administered 1% tween 20 dissolved in distilled water/Control (Group I); rats were orally-administered daidzein suspension (100mg/kg) for 7 days (Group II); rats intraperitoneally-injected with a single dose of ifosfamide (500 mg/kg) (Group III); rats orally-administered for 7 days with the daidzein (100mg/
... Show MoreRegarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct
... Show MoreA simple and rapid high performance liquid chromatographic with fluorescence detection method for the determination of the aflatoxin B1, B2, G1 and G2 in peanuts, rice and chilli was developed. The sample was extracted using acetonitrile:water (90:10, v/v%) and then purified by using ISOLUTE multimode solid phase extraction. After the pre-column derivatisation, the analytes were separated within 3.7 min using Chromolith performance RP-18e (100–4.6 mm) monolithic column. To assess the possible effects of endogenous components in the food items, matrix-matched calibration was used for the quantification and validation. The recoveries of aflatoxins that were spiked into food samples were 86.38–104.5% and RSDs were <4.4%. The method was
... Show MoreVolleyball is one of the sports that require physical and skill abilities thus many teaching models appeared to teach these abilities like group investigation model. The research aimed at identifying the effect of group investigation model on learning underarm and overhead passing in volleyball. The researchers hypothesized statistical differences between pre and posttests in learning underarm and overhead passing in volleyball as well as differences in posttests of controlling and experimental groups in learning underarm and overhead passing in volleyball. The researcher used the experimental method on (30) second year female students of physical education and sport sciences college/ university of Baghdad. Group investigation model was app
... Show MoreActive Learning And Creative Thinking
The uniform flow distrbiution in the multi-outlets pipe highly depends on the several parameters act togather. Therefor, there is no general method to achieve this goal. The goal of this study is to investigate the proposed approach that can provide significant relief of the maldistribution. The method is based on re-circulating portion of flow from the end of the header to reduce pressure at this region . The physical model consists of main manifold with uniform longitudinal section having diameter of 152.4 mm (6 in), five laterals with diameter of 76.2 mm (3 in), and spacing of 300 mm. At first, The experiment is carried out with conventional manifold, which is a closed-end. Then, small amount of water is allowed
... Show MoreDesign and Construction system for recording Finger print by laser, and separted the signal to noise by holographic element, was done. For safety, total reflection lighting ensures hat aser earns an not enter An operators eyes. Holographic diffraction grating was used instead of computer program to contrast images.