Hybrid MPPT approach using Cuckoo Search and Grey Wolf Optimizer for PV systems under variant operating conditions

Photovoltaic(PV)systems are adversely affected by partial shading and non-uniform conditions.Meanwhile,the addition of a bypass shunt diode to each PV module prevents hotspots.It also produces numerous peaks in the PV array’s power-voltage characteristics,thereby trapping conventional maximum power point tracking(MPPT)methods in local peaks.Swarm optimization approaches can be used to address this issue.However,these strategies have an unreasonably long convergence time.The Grey Wolf Optimizer(GWO)is a fast and more dependable optimization algorithm.This renders it a good option for MPPT of PV systems operating in varying partial shading.The conventional GWO method involves a long conversion time,large steady-state oscillations,and a high failure rate.This work attempts to address these issues by combining Cuckoo Search(CS)with the GWO algorithm to improve the MPPT performance.The results of this approach are compared with those of conventional MPPT according to GWO and MPPT methods based on perturb and observe(P&O).A comparative analysis reveals that under non-uniform operating conditions,the hybrid GWO CS(GWOCS)approach presented in this article outperforms the GWO and P&O approaches.

Influence of Recycled Construction Materials Aggregate on Mechanical and Physical Properties of Concrete

The main purpose of this research is to study the properties of re-use different types of construction materials such as PVC （polyvinylchloride） scraps, clay brick and recycled concrete as a partial replacement of coarse aggregate. Different proportions （1%, 3%, 5% and 7%） by weight were used for PVC. scrap, （10%, 20%, 30%, and 40%） by weight were used for recycled concrete and （5%, 10%, 15%, and 20%） by weight were used for clay brick. Mechanical tests such as compressive and tensile strength tests and physical tests such as ultrasonic pulse velocity, bulk density, porosity, specific gravity and water absorption tests were done to the samples after curing in normal water for 28 days. Test results showed slightly degradation in mechanical and physical engineering properties of concrete specimens that used partial replacement of recycled concrete coarse aggregate, degradation increased with increasing of replacement but test results still closely to reference samples. Use of polyvinyl chloride in proportions not more than 5% as a partial replacement of coarse aggregates given acceptable results in comparison with reference samples but all test results degraded at 7% replacements. Test results of partial replacement of crushed brick coarse aggregates unacceptable and the range of degradation are wide because of increased （water： cement） ratio to improve the concrete workability.

Auto Opening Door and Car Identification

Design an Automatic Door System using a unique wireless ID by using infrared ray or Bluetooth technology. That consists of a sensing unit, control unit and drive unit to open and close doors at the entrance of a car that has the unique ID. This process is controlled by using Arduino Leonard programmed with IDE free open source software, that receives the signal code from the car which sends the ID through IR LED or Bluetooth by using a mobile application, decode it. And switch ON the driver that controls the DC motor. This system was designed considering some factors such as low cost and low power requirements, availability of components and low distance so there is no interference. The hardware design and software development are described, and all of the tests indicate that all component goes according to the initial design of this research.

Human-Animal Affective Robot Touch Classification Using Deep Neural Network

Touch gesture recognition is an important aspect in human-robot interaction,as it makes such interaction effective and realistic.The novelty of this study is the development of a system that recognizes human-animal affective robot touch(HAART)using a deep learning algorithm.The proposed system was used for touch gesture recognition based on a dataset provided by the Recognition of the Touch Gestures Challenge 2015.The dataset was tested with numerous subjects performing different HAART gestures;each touch was performed on a robotic animal covered by a pressure sensor skin.A convolutional neural network algorithm is proposed to implement the touch recognition system from row inputs of the sensor devices.The leave-one-subject-out cross-validation method was used to validate and evaluate the proposed system.A comparative analysis between the results of the proposed system and the state-of-the-art performance is presented.Findings show that the proposed system could recognize the gestures in almost real time(after acquiring the minimum number of frames).According to the results of the leave-one-subject-out cross-validation method,the proposed algorithm could achieve a classification accuracy of 83.2%.It was also superior compared with existing systems in terms of classification ratio,touch recognition time,and data preprocessing on the same dataset.Therefore,the proposed system can be used in a wide range of real applications,such as image recognition,natural language recognition,and video clip classification.

Enhancement of FSO Communications Links Under Complex Environment

Free space optical communication is a line-of-sight （LOS） technology that uses lasers to provide optical bandwidth connections. Potential disturbance arising from the weather condition is one of the most effective factors that influence the bi-directional free space optics （FSO） performance. The complex weather condition in the Middle East region and Arabian Gulf has been dominated by dust storms activities. Dust storms directly affect the characteristics of FSO and consequently lead to an increase in the bit error rate （BER） and deterioration Q-factor to bad levels due to the high attenuation factor. In this research, the authors compare the differences between two bi-directional FSOs. One is the traditional link, and the other has been developed to enhance the system performance under the dust storms condition. The proposed design consists of dual FSO channels, and each one includes erbium-doped fiber amplifier （EDFA） optical amplifiers. This design has demonstrated the proficiency in addressing the attenuation that occurs due to weather stickers. The results prove there is an improvement in performance by measuring the Q-factor. In addition, BER can be significantly improved, and further communicating distance can be achieved by utilizing 1550nm with multiple channels and EDFA.

Photovoltaic Properties of Thermally-Grown Selenium-Doped Silicon Photodiodes for Infrared Detection Applications

In this work, the photovoltaic properties of selenium-doped silicon photodiodes were studied. Influence of illumination of the impurity absorption range on the current-voltage and spectral characteristics of the fabricated device were considered. The photoresponse dependencies on the electric intensity, current, and radiation power at the sample were observed. Results obtained in this work showed that the current-sensitivity of the fabricated structures at the forward bias was rather higher than that of photoresistors. The photosensitivity and detectivity were up to 2.85 × 10^- 6 W.Hz^-1/2 and 2.1 × 10^11 cm.Hz^1/2w^-1, respectively.

Characteristics of Heat-Annealed Silicon Homojunction Infrared Photodetector Fabricated by Plasma-Assisted Technique

In this work, the effect of thermal annealing on the characteristics of silicon homojunction photodetector was studied. This homojunction photodetector was fabricated by means of plasma-induced etching of p-type silicon substrate and plasma sputtering of n-type silicon target in vacuum. The electrical and spectral characteristics of this photodetector were determined and optimized before and after the annealing process. The maximum surface reflectance of 1.89% and 1.81%, the maximum responsivity of 0.495A/W and 0.55A/W, the ideality factor of 1.80 and 1.99, the maximum external quantum efficiency of 76% and 83.5%, and the built-in potential of 0.79V and 0.72 V were obtained before and after annealing, respectively.

Characterization of Polycrystalline Nickel Cobaltite Nanostructures Prepared by DC Plasma Magnetron Co-Sputtering for Gas Sensing Applications

In this work, a gas sensor is fabricated from polycrystalline nickel cobaltite nano films deposited on transparent substrates by closed-field unbalanced dual-magnetrons （CFUBDM） co-sputtering technique. Two targets of nickel and cobalt are mounted on the cathode of discharge system and co-sputtered by direct current （DC） argon discharge plasma in presence of oxygen as a reactive gas. The total gas pressure is 0.5 mbar and the mixing ratio of Ar：O2 gases is 5：1. The characterization measurements performed on the prepared films show that their transmittance increases with the incident wavelength, the polycrystalline structure includes 5 crystallographic planes, the average particle size is about 35nm, the electrical conductivity is linearly increasing with increasing temperature, and the activation energy is about 0.41 eV. These films show high sensitivity to ethanol vapor.