When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

1. baumannii is an aerobic gram negative coccobacilli, it is considered multidrug resistance pathogen (MDR) and causes several infections that are difficult to treat. This study is aims to employ physical methods in sterilization and inactivation of A. baumannii, as an alternative way to reduce the using of drugs and antibiotics.

            Cold Atmospheric Plasma was generated by one electrode at 20KV, 4 power supply and distance between electrode and sample was fixed on 1mm. A. baumannii (ATCC 19704 and HHR1) were exposed to  Dielectric Barrier Discharge type of Cold Atmospheric Plasma (DBD-CAP) for several periods

There are numerous bidirectional interactions between the reproductive system and the liver. Sex steroids regulate metabolic health through signaling effects in both peripheral and central metabolic tissues, including adipose tissue, liver, skeletal muscle, and brain, and have a role in the etiology of structural and functional liver diseases. Blood samples were obtained from 90 healthy women (control group) and 90 women that have hormonal changes (patients’ group). The levels of reproductive hormones (follicle stimulation hormone/FSH, luteinizing hormone/LH, estradiol/E2, progesterone/P4) were measured by using fully automated Cobas E411, whereas those of liver enzymes (alanine transaminase /ALT, aspartate aminotransferase/AST, a

Parkinson’s disease (PD) consider as a progressive ageing neurodegenerative disease, Parkinson’s consider as a heterogenous disease, with mainly initiate through correlation between genetic and epigenetic by inducing of different factors on some related genes, these factors like (environmental, toxicants, nutrition, heavy metals, pesticides, some drugs) and also(trauma on head ,strokes) in addition to unknown reasons which cause an idiopathic PD .Current study aims to focusing on specific related PD gene called SNCA by single nucleotides polymorphism (rs2619363) as a risk factor for PD initiation disease in PD patients in addition to study the effect of polymorphisms on random Iraqi patients with different gastrointestinal

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)

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

The researcher attempts to diagnose the level of the effect  of strategic thinking skills (intuition, meditation, creativity) of the managers in the Ministry of Health in Iraq and some of its institutions in the formulation of human resources management: (selection, training, incentivence , performance appraisal (Recognizing the importance of the subjects studied, and because of the importance of the expected results of th

Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.