Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent $\left({}\right)$

This paper proposes a completion that can allow fracturing four zones in a single trip in the well called “Y” (for confidential reasons) of the field named “X” (for confidential reasons). The steps to design a well completion for multiple fracturing are first to select the best completion method then the required equipment and the materials that it is made of. After that, the completion schematic must be drawn by using Power Draw in this case, and the summary installation procedures explained. The data used to design the completion are the well trajectory, the reservoir data (including temperature, pressure and fluid properties), the production and injection strategy. The results suggest that multi-stage hydraulic fracturing can

The research aims to identify the level of functional engagement and hope-based thinking of kindergarten teachers, identify if there is a significant difference in functional engagement and hope-based thinking in terms of specialization and years of service for kindergarten teachers, identify if there is a significant correlation between functional engagement and hope-based thinking of kindergarten teachers. The current research is determined by kindergarten teachers in the Second Rusafa Baghdad Education Directorate for the academic year (2022-2023). In order to achieve the objectives of the research, the researcher prepared a functional engagement scale, which consists of (45) items in three areas: Perceptual and functional engagement

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

The present study evaluates the effects of Ginkgo biloba extract as monotherapy on the glycemic status, insulin resistance (IR), body mass index (BMI), and visceral adiposity index (VAI), in addition to the inflammatory markers, oxidative status and leptin level in patients with metabolic syndrome in comparison with metformin.

The study is a randomized, double-blind pilot study conducted during the period May to September, 2020. Fifty patients were recruited in the study and they were allocated into two groups (25 per each group): Ginkgo biloba and Metformin groups, they received (120 mg Ginkgo biloba extract/ capsule) and (500 mg Metformin/ capsule) respectively; orally as a single dose for 90 days. Blood samples were taken at z

Abstract

     In this investigation, Al₂O₃ nano material of 50nm particles size were added to the 6061 Al aluminium alloy by using the stir casting technique to fabricate the nanocomposite of 10wt% Al₂O₃. The experimental results observed that the addition of 10wt% Al₂O₃ improved the fatigue life and strength of constant and cumulative fatigue. Comparison between the S-N curves behaviour of metal matrix (AA6061) and the nanocomposite 10wt% Al₂O₃ has been made. The comparison revealed that 12.8% enhancement in fatigue strength at 10⁷cycles due to 10wt% nano reinforcement. Also cumulative fatigue l