The heat exchanger is a device used to transfer heat energy between two fluids, hot and cold. In this work, an output feedback adaptive sliding mode controller is designed to control the temperature of the outlet cold water for plate heat exchanger. The measurement of the outlet cold temperature is the only information required. Hence, a sliding mode differentiator was designed to estimate the time derivative of outlet hot water temperature, which it is needed for constructing a sliding variable. The discontinuous gain value of the sliding mode controller is adapted according to a certain adaptation law. Two constraints which imposed on the volumetric flow rate of outlet cold (control input) were considered within the rules of the proposed

Topic management is the awareness of how speakers deal with initiating, developing, changing, and ending a topic and how they fix the relationship when a misunderstanding occurs. It is such an important unit of conversation as it includes the transition from one strategy to the other to be accomplished in a systematic and orderly manner. These strategies are impaired in dementia patients thus lead to communication breakdown. This study aims at detecting the dementia patients' topic management strategies in selected speeches and answering the questions of which of these strategies are fully or partially detected in these speeches. The researchers use a qualitative method to examine the speeches of those patients and they adopt an eclectic

To evaluate and improve the efficiency of photovoltaic solar modules connected with linear pipes for water supply, a three-dimensional numerical simulation is created and simulated via commercial software (Ansys-Fluent). The optimization utilizes the principles of the 1st and 2nd laws of thermodynamics by employing the Response Surface Method (RSM). Various design parameters, including the coolant inlet velocity, tube diameter, panel dimensions, and solar radiation intensity, are systematically varied to investigate their impacts on energetic and exergitic efficiencies and destroyed exergy. The relationship between the design parameters and the system responses is validated through the development of a predictive model. Both single and mult

The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

                The advertising mail is considered as one of potential tools that followed to transfer the printed messages to the consumers and public customers whom are located at homes or works. This type of advertising is preferable due to the zero expense to receive the announcements of products, which became recently one of the successful procedures to create new customers and keep them in touch with direct communication. It is also possible to send them to specific group of people who can be classified by the advertisers to select even by name their own clients to give the personality to the clients for a long term of communication.

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Background: Suffering from recurrent boils (furunclosis) is a common problem in our locality as it is noticed by many dermatologists especially in association with increasingly hot weather. The most common causative organisms are staphylococci. Objective: The aim of the study was to shed the light upon this problem and compare two systemic therapeutic agents for the prevention of recurrence, doxycycline and rifampicin. Patient and method: One hundred thirty-five (135) Patients with recurrent boils from Al-Yarmouk teaching hospital dermatology outpatient department were included in this study; age ranged from 10 to 64 years old and out of total patients 32 were males and 103 were females. Patients were assessed by full history and cl

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D