The goal of this work is demonstrating, through the gradient observation of a of type linear ( -systems), the possibility for reducing the effect of any disturbances (pollution, radiation, infection, etc.) asymptotically, by a suitable choice of related actuators of these systems. Thus, a class of ( -system) was developed based on finite time ( -system). Furthermore, definitions and some properties of this concept -system and asymptotically gradient controllable system ( -controllable) were stated and studied. More precisely, asymptotically gradient efficient actuators ensuring the weak asymptotically gradient compensation system ( -system) of known or unknown disturbances are examined. Consequently, under convenient hypothesis, the existence and the uniqueness of the control of type optimal, guaranteeing the asymptotically gradient compensation system ( -system), are shown and proven. Finally, an approach that leads to a Mathematical approximation algorithm is explored.
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
... Show MoreWildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
... Show MoreThe first flow injection spectrophotometric method is characterized by its speed and sensitivity which have been developed for the determination of promethazine-HCl in pure and pharmaceutical preparation. It is based on the in situ detection of colored cationic radicals formed via oxidation of the drug with sodium persulphate to pinkish-red species and the same species was determined by using homemade Ayah 3SX3-3D solar flow injection photometer. Optimum conditions were obtained by using the high intensive green light emitted diode as a source. Linear dynamic range for the absorbance versus promethazine-HCl concentration was 0-7 mmol.L-1, with the correlation coefficient (r) was 0.9904 while the percentage linearity (r2%) was 98.09%. the L.
... Show MoreThe study aims to examine the classroom activities of the developed English course (Flying High) for the high school first-grade students, identify creative thinking skills appropriate for this grade, and show the extent the classroom activities involve these skills from the female- teachers ‘point of view. The study adopted the descriptive survey method. The study community consists of all (50) English female-teachers who teach high school first grade in Arar city during the academic year (1440 -1441 A.H, the first semester). The study was applied to all respondents. The researcher used a questionnaire as a study tool. The study revealed that the female-teachers reported their disagreement and refusal of the classroom activities in th
... Show MoreThe research aims to show the relationship between the use of automated accounting systems technology and its impact on enhancing the efficiency and effectiveness of the internal control system in a sample of Bahraini universities in light of the rapid changes in the electronic business environment. Automated accounting and its impact on enhancing the efficiency and effectiveness of the internal control system, and it is concluded through the analytical study of the research sample that there is a percenta
... Show MoreThe study aimed to identify the effect of Total Quality Management on enhancing competitiveness through the opinions of employees of the front- rows of customer service in local Palestinian banks, the researcher adopted an analytical descriptive method through developing a special questionnaire to accomplish the study’s objectives and answer its questions. The study involved all the Palestinian local banks, with their scattered branches in West Bank. The study sample consisted of 3470 executive employees for banking services out of 4753 employees, in the rate of 73%, and the study sample reached (485) employees who were randomly selected working in the front -rows to provide services in the local Palestinian banks during the ye
... Show MoreThe main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola
... Show MoreContents IJPAM: Volume 116, No. 3 (2017)
Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model
Histogram linear Contrast Stretching (MMHLCS) method