The main task of creating new digital images of different skin diseases is to increase the resolution of the specific textures and colors of each skin disease. In this paper, the performance of generative adversarial networks has been optimized to generate multicolor and histological color digital images of a variety of skin diseases (melanoma, birthmarks, and basal cell carcinomas). Two architectures for generative adversarial networks were built using two models: the first is a model for generating new images of dermatology through training processes, and the second is a discrimination model whose main task is to identify the generated digital images as either real or fake. The gray wolf swarm algorithm and the whale swarm alg

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Environmental controls, especially for temperature and humidity, are essential to maintain the safety, purity and effectiveness of drugs. The measurement of humidity can be particularly difficult and important in climatic and thermostatic chambers (warehouses, ovens, cold rooms, fridges, drying rooms, insulated boxes, etc.).
The old method of monitoring and qualification of climatic and thermostatic chambers requires placing a defined number of recorders, then programming and store them. After that, to examine the values recorded to revolve the status of the climatic and thermostatic chambers, if they are compliant or not-complaint at any time, so all that goes to waste time and efficiency of values.
We can do the monitoring and qu

                  In light of the corona pandemic, educational institutions have moved to learning and teaching via the Internet and e-learning ,and this is considered a turning  point in course of higher education in Iraq in particular and education in general, which generated a great challenge for educational institutions to achieve the highest possible levels in practices and processes to reach the highest quality of their outputs from graduate students to the labor market that auditing performance by adopting e-learning standards is one of the effective tools that help the management of educational institutions by providing information on the ex

 Neuroimaging is a description, whether in two-dimensions (2D) or three-dimensions (3D), of the structure and functions of the brain. Neuroimaging provides a valuable diagnostic tool, in which a limited approach is used to create images of the focal sensory system by medicine professionals. For the clinical diagnosis of patients with Alzheimer's Disease (AD) or Mild Cognitive Impairs (MCI), the accurate identification of patients from normal control persons (NCs) is critical. Recently, numerous researches have been undertaken on the identification of AD based on neuroimaging data, including images with radiographs and algorithms for master learning. In the previous decade, these techniques were also used slowly to differentiate AD a

       Performance issues could be appearing from anywhere in a computer system, finding the root cause of those issues is a troublesome issue due to the complexity of the modern systems and applications. Microsoft builds multiple mechanisms to make their engineers understand what is happening inside All Windows versions including Windows 10 Home and the behavior of any application working on it whether Microsoft services or even third-party applications, one of those mechanisms is the Event Tracing for Windows (ETW) which is the core of logging and tracing in Windows operating system to trace the internal events of the system and its applications. This study goes deep into internal process activities to investigat

Text documents are unstructured and high dimensional. Effective feature selection is required to select the most important and significant feature from the sparse feature space. Thus, this paper proposed an embedded feature selection technique based on Term Frequency-Inverse Document Frequency (TF-IDF) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) for unstructured and high dimensional text classificationhis technique has the ability to measure the feature’s importance in a high-dimensional text document. In addition, it aims to increase the efficiency of the feature selection. Hence, obtaining a promising text classification accuracy. TF-IDF act as a filter approach which measures features importance of the te