In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

The present paper describes and analyses three proposed cogeneration plants include back pressure steam-turbine system, gas turbine system, diesel-engine system, and the present Dura refinery plant. Selected actual operating data are employed for analysis. The same amount of electrical and thermal product outputs is considered for all systems to facilitate comparisons. The theoretical analysis was done according to 1st and 2nd law of thermodynamic. The results demonstrate that exergy analysis is a useful tool in performance analysis of cogeneration systems and permits meaningful comparisons of different cogeneration systems based on their merits, also the result showed that the back pressure steam-turbine is more efficient than other pro

NH₃ gas sensor was fabricated based on deposited of Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) suspension on filter paper substrates using suspension filtration method. The structural, morphological and optical properties of the MWCNTs film were characterized by XRD, AFM and FTIR techniques. XRD measurement confirmed that the structure of MWCNTs is not affected by the preparation method. The AFM images reflected highly ordered network in the form of a mat. The functional groups and types of bonding have appeared in the FTIR spectra. The fingerprint (C-C stretch) of MWCNTs appears in 1365 cm^-1, and the backbone of CNTs observed at 1645 cm^-1. A homemade sensi

In this paper, variable gain nonlinear PD and PI fuzzy logic controllers are designed and the effect of the variable gain characteristic of these controllers is analyzed to show its contribution in enhancing the performance of the closed loop system over a conventional linear PID controller. Simulation results and time domain performance characteristics show how these fuzzy controllers outperform the conventional PID controller when used to control a nonlinear plant and a plant that has time delay.

In this paper, variable gain nonlinear PD and PI fuzzy logic controllers are designed and the effect of the variable gain characteristic of these controllers is analyzed to show its contribution in enhancing the performance of the closed loop system over a conventional linear PID controller. Simulation results and time domain performance characteristics show how these fuzzy controllers outperform the conventional PID controller when used to control a nonlinear plant and a plant that has time delay.

In Iraq most of the small buildings deployed a conventional air conditioning technology which typically uses electrically driven compressor systems which exhibits several clear disadvantages such as high energy consumption, high electricity at peak loads. In this work a thermal performance of air conditioning system combined with a solar collector is investigated theoretically. The hybrid air conditioner consists of a semi hermetic compressor, water cooled shell and tube condenser, thermal expansion valve and coil with tank evaporator. The theoretical analysis included a simulation for the solar assisted air-conditioning system using EES software to analyze the effect of different parameters on the power consumption of c