The aim of this research is to develop qualitative workouts based on certain sensory perceptions for the development of offensive basketball abilities and to determine their impact on female pupils. Several findings, based on the au-thor's extensive expertise instructing basketball materials and our closeness to the sample, revealed deficits in some sensory perceptions “in the game of basketball”, which impair the accuracy of passing the ball to the best team-mate. It also affects the pace of dribbling and the difficulty of selecting the op-timal moment and distance to fire. Therefore, the researcher designs qualita-tive activities based on many sensory experiences, including distance, speed, force, and direction shift. In addition, the researcher used the experimental technique with a design “one group with a pre- and post-test” to accommo-date the nature of the issue and attain the study goals. For the 2020–2021 school year, 25 female students were chosen at random from 102 applicants. Female pupils were able to master offensive abilities in basketball (long han-dling from the top of the shoulder-high dribble-free throw) according to the qualitative workouts based on sensory impressions. The most essential sug-gestions are the necessity to pay attention to the sensory perceptions of the basketball game while learning the sample members, and the need to investi-gate some additional sensory perceptions and understand their influence on learning offensive basketball abilities for female students.
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
... Show MoreHigh Q-factor based on absorption can be achieved by tuning (the reflection and the transition percentage). In this work, the simple design and simulated in S-band have been investigated. The simulation results of G-shape resonator are shown triple band of absorption peaks 60%, 91.5%, and 70.3%) at resonance frequency 2.7 GHz, 3.26 GHz, and 4.05 GHz respectively. The results exhibited very high of the Q-factor ( 271 ) at resonance frequency ( 3.26 GHz ). The high Q-factor can be used to enhance the sensor sensing, narrowband band filter and image sensing.
In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn
... Show MoreThis work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it
... Show MoreOne of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th
... Show MoreThis 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
... Show MoreThis work presents a symmetric cryptography coupled with Chaotic NN , the encryption algorithm process the data as a blocks and it consists of multilevel( coding of character, generates array of keys (weights),coding of text and chaotic NN ) , also the decryption process consists of multilevel (generates array of keys (weights),chaotic NN, decoding of text and decoding of character).Chaotic neural network is used as a part of the proposed system with modifying on it ,the keys that are used in chaotic sequence are formed by proposed key generation algorithm .The proposed algorithm appears efficiency during the execution time where it can encryption and decryption long messages by short time and small memory (chaotic NN offer capacity of m
... Show MoreBlockchain has garnered the most attention as the most important new technology that supports recent digital transactions via e-government. The most critical challenge for public e-government systems is reducing bureaucracy and increasing the efficiency and performance of administrative processes in these systems since blockchain technology can play a role in a decentralized environment and execute a high level of security transactions and transparency. So, the main objectives of this work are to survey different proposed models for e-government system architecture based on blockchain technology implementation and how these models are validated. This work studies and analyzes some research trends focused on blockchain
... Show MoreFree-Space Optical (FSO) can provide high-speed communications when the effect of turbulence is not serious. However, Space-Time-Block-Code (STBC) is a good candidate to mitigate this seriousness. This paper proposes a hybrid of an Optical Code Division Multiple Access (OCDMA) and STBC in FSO communication for last mile solutions, where access to remote areas is complicated. The main weakness effecting a FSO link is the atmospheric turbulence. The feasibility of employing STBC in OCDMA is to mitigate these effects. The current work evaluates the Bit-Error-Rate (BER) performance of OCDMA operating under the scintillation effect, where this effect can be described by the gamma-gamma model. The most obvious finding to emerge from the analysis
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