At the level of both individuals and companies, Wireless Sensor Networks (WSNs) get a wide range of applications and uses. Sensors are used in a wide range of industries, including agriculture, transportation, health, and many more. Many technologies, such as wireless communication protocols, the Internet of Things, cloud computing, mobile computing, and other emerging technologies, are connected to the usage of sensors. In many circumstances, this contact necessitates the transmission of crucial data, necessitating the need to protect that data from potential threats. However, as the WSN components often have constrained computation and power capabilities, protecting the communication in WSNs comes at a significant performance pena

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

School administration has an effective role in stimulating academic achievement, as it is the ideal regulation and activation of material and human power to achieve the goals of the educational process. This role has axes in the form of interests, aids, and specific procedures exercised by the school administration in improving the educational process, and assisting researchers in achieving the highest levels of academic achievement. This activation is achieved through stages of planning, organizing, coordinating, and evaluating.

To achieve the aims of this research, the researcher pursued the descriptive analytical approach, which is considered one of the most appropriate approaches to the nature of this type of research. The qu

Verbal Antonyms: A research in the relationship in meaning Between the words in Arabic language

The lexical connotation is one of the types of connotation that linguists have dealt with, and stipulated in their studies, meaning access to the real meanings of the words, that the lexicon can address after tracing the real meaning of the metaphorical meanings, if any, and this is known to the semantics additional significance, and the rhetorical meaning Figuratively.
The miraculous Qur'an in its systems often refers to the metaphorical uses of the words as well as the real use. The significance of the words in the Holy Qur'an came in a variety of contexts, making each word a special significance that belongs to it exclusively. This is the miracle of the Holy Qur'an. The coming of the slow walk, with its eight words (came, came, cam

The dramatic series on television have a great impact on people’sattitudes towards dialects of language varieties, by relating theconceptual pictures or prototypes presented by series’ characters tothose dialects. This study aims to show the influence of TV series onIraqi university learners’ gender and age in relating positive ornegative semantic qualities to their dialects. To this end, 150 Iraqi EFLlearners have participated in this study to examine their attitudestowards Baghdadi, Mousli and Nasiriya dialects. The data arecollected by Lambert, Hodgson, Gardner, Fillenbaum's (1960)matched guise technique and then labeled by Willmorth’s (1988)subjective reaction test. A structured interview is conducted to supportthe data

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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