Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two supervised machine learning classification techniques, Learning Vector Quantization (LVQ) and Support Vector Machine (SVM) classifiers, to achieve better search performance and high classification accuracy in a heterogeneous WBASN. These classification techniques are responsible for categorizing each incoming packet into normal, critical, or very critical, depending on the patient's condition, so that any problem affecting him can be addressed promptly. Comparative analyses reveal that LVQ outperforms SVM in terms of accuracy at 91.45% and 80%, respectively.
Sensitive information of any multimedia must be encrypted before transmission. The dual chaotic algorithm is a good option to encrypt sensitive information by using different parameters and different initial conditions for two chaotic maps. A dual chaotic framework creates a complex chaotic trajectory to prevent the illegal use of information from eavesdroppers. Limited precisions of a single chaotic map cause a degradation in the dynamical behavior of the communication system. To overcome this degradation issue in, a novel form of dual chaos map algorithm is analyzed. To maintain the stability of the dynamical system, the Lyapunov Exponent (LE) is determined for the single and dual maps. In this paper, the LE of the single and dual maps
... Show MoreThe function of internal auditing has become an important function that aims at achieving objectives that are compatible with these developments and changes that have occurred in many countries in the world, which required the emergence of professional associations and institutes in the profession of internal auditing. Improve the guideline of the internal audit units issued by the Federal Audit Bureau to enhance the efficiency of internal audit performance in Iraqi government units. The researchers adopted the statistical method of proving the hypothesis by constructing a questionnaire that included three main axes: supporting the senior management in adopting the current guide, and the second being the importance of improving t
... Show MoreThe aim of this study was to identify the effectiveness of using generative learning model in learning kinetic series on rings and horizontal bar in artistic gymnastics for men ,Also, the two groups were better in learning the two series of movements on the rings and horizontal bar . The experimental method was used to design two parallel groups with pretested and posttest .The sample included third graders at the College of Physical Education and Sports Sciences - University of Baghdad ,The third class (d) was chosen to represent the control group that applied the curriculum in the college, with (12) students per group. After conducting the tribal tests, the main experiment was carried out for (8) weeks at the rate of two units per week di
... Show MoreArtificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
... Show MoreThe postmodern ideas and concepts have produced social, political and economic variables that have been affected by wars, crises, the role of globalization and the information revolution. They have created many variables in concepts and great variables in technological, artistic and cultural innovations. All these changes have contributed to changing the form of the theatrical show aesthetically and intellectually, which cast a shadow over the nature of the actor's performance who has become more demanding to change his performance and to find the mechanisms and new nature of work governing him corresponding to those variables and this prompted the researcher to adopt the subject (the performance variable of the actor's techniques in pos
... Show MoreThis research deals with the fact that arts exit from their familiar context in practice and enter in the context of the fantasy and exoticism picture. In order to understand the theatrical phenomenon and know the way of its production of the fantasy picture, especially the acting performance in its transitions between the real and fantasy. This study consists of: an introduction of the research in which the researcher presented the research problem, importance and objectives.
The theoretical framework dealt with founding a theoretical part for the research consisting of two sections: the first (fantasy: the concept and the working) and the second (techniques of acting perfo
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