In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

The purpose of this paper is to identify the statistical indicators of the searched variables and identify the relationship between the cognitive learning outcome and the performance of the two mastering skills by parallel spherical standing and equilibrium on the balance beam. And the identification of the percentage of the cognitive learning outcome contribution to the performance of the two mastering skills by parallel spherical standing and the equilibrium on the balance beam. The two researchers used the descriptive approach in the survey method and the correlational relations, being the most appropriate to the nature of the research problem. The research community for the second stage students in the College of Physical Education and

The importance of the research lies in preparing exercises using a proposed device to learn the skill of thehuman wheel on a machine rug of ground movements of the artistic gymnastics. As for the research problem:Through the presence of the two researchers as teachers and observers of this sport in the gymnastics hall,they noticed that there is difficulty in the students’ performance of the skill of the round off on the machineof the mat of ground movements, according to the researchers’ opinion, the reason for this is that skillsare taught with the limited availability of assistive devices, as well as the lack of use of these devices inexercises according to biomechanical variables, although they facilitate the learning process

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

Cyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public image sets. Results show DGEN beats AES, chaos tricks, and other GAN ideas. Entropy reached 7.99 bits per pix

Methods of teaching plays an important vole in the educational process
because is the link between the teacher and the learner. The process of
teaching doesut fulfill the desirable results unless the methods of guiding and
teaching are provided and through a qualified educationalist capable of
communicating the syllabus to the students in an easy and clear way. In spite
of the diversity of the methods of teaching ,there is no one way suitable for all
the educational purposes , all the sciences ,all the subjects ,all the levels of
growth ,levels of teaching, maturity and intelligences ,all teachers and
educationalists and all the circum stances surrounding the teaching processes
.The teacher is the one who choos

Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines