Abstract : This paper presents the Design and simulation of a Micro-strip hairpin Bandpass filter using defected ground structure. The filter is designed to operate at the center frequency of 2.22 GHz with a fractional bandwidth of 0.45 on substrate Rogers6006 high permittivity material with a substrate height is 1.27mm. The objective of this paper is to improve the performance of Microwave hairpin Band Pass filters. The simulation is carried out in high-frequency structural software (HFSS) and Improves the Return of the loss of the filter from -26dB to -53dB using a defective ground structure that is very important to analyze the performance of the filter..
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Abstract : A shear connector defines as a metal component through which two dissimilar materials or structures can act as a single entity. Hot-rolled steel I-section beams and concrete slabs are joined monolithically in steel-concrete composite beams by a shear connector. Stud is a conventional type of shear connector typically used in steel-concrete composite construction due to its several benefits. Cost and sustainability are two major essential factors for construction. Cost of manufacturing and installation are the major drawbacks for the stud connector. This paper comes with a solution of introducing an innovative shear connector called a T-shape reinforcement connector as a replacement for conventional stud. In the recent era, high strength steel is gaining popularity due to its strength to weight ratio. The finite element models are initially validated by comparing the results with the experiment reported in the literature. A total of twelve steel-concrete composite beams connected with an innovative shear connector made-up of reinforcement are studied numerically in this paper using finite element commercial package ANSYS15 under the positive moment. The degree of shear cconnection, strength of steel beam, height and diameter of reinforcement are considered primary parameters for this present study to understand the behaviour of reinforcement shear connectors on the steel-concrete composite structure. Load bearing capacity, deformation characteristics, end-slip behaviour, ductility factor and failure modes are presented..
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Abstract : Models’ emission and fate of odorous hydrogen sulphide gas in full-scale plants anoxic/anaerobic/oxic A2/O using a TOXCHEM V4.1 model was used in Karbala sewage treatment plants (STP). Monthly influent and effluent samples were taken during a one year to assess the performance of Karbala STP. pH, COD, BOD5, TSS, NO3, NO2, NH4+, SO42-, H2S, oil and grease, and PO4-3 measurements. Degradation and emissions were two most important processes across the system. Model calibration and validation was applied to ensure that all data was calibrated and validated within the predefined limits, with the root mean square error (RMSE) and R2 are 0.06 and 0.9095 respectively within acceptable boundaries results showing the model to be close to an ideal fit. At 30 °C in summer and 20 °C in winter, 25% and 23.4% of all such gas respectively was released into the atmosphere, 0.01 and 0.04% were discharged with wastewater, 0.11 and 0.13% were absorbed by sludge, and 74.8 and 76.3% were degraded. Total emitted concentration of H2S at Karbala STP was 4.918 ppm in summer and 4.6325 ppm in winter. A sensitivity analysis was also performed to develop a better understanding of H2S fate and emission. Overall, the TOXCHEM V4.1 model performed well with regard to predicting the emission and fate of H2S gas in an A2/O compare with actual data system, and this provides accurate data on the location of the noxious gas emissions, allowing make decisions at any plant to make the right decisions..
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Abstract : Computer Vision and its associated emerging technology prove high potential in advanced agricultural applications. Recently Deep Learning algorithms are much more efficient in producing solution to Computer Vision Problems. In this paper, a review on deep learning algorithms and its uses in agriculture is done. Also, this paper reports the research work on autonomous harvesting system using IOT Technology. Detection of Cashew fruit is an important part of intelligent management in the Cashew harvesting process. For fast and accurate Cashew fruit detection in the complex environment, this paper proposes a fruit detection method using Deep Learning algorithms. We applied SSD mobilenetV2 neural network to get the features of cashew fruits in depth and detect different stages of cashew apple in tree like Immature, Unripe Cashew and Ripe Cashew. This method achieved an average of 92.26% detection rate and the average execution time is 8 seconds. Also, the results are compared with machine learning algorithm and YOLOv4 method. Deep learning method gives better results on accurate detection of cashew fruits and detection time when compared to machine learning algorithm. Compared with YOLOv4, Single shot Detector (SSD) had higher detection rate and confidence. The proposed method detects different colors of Cashew fruit like yellow, red and combination of both and also detects different maturity levels with high recognition rate and in faster speed. This technique also able to detect individual cashew fruit in clusters which effectively helps the harvesting robot for continuous fruit plucking process and for yield estimation. At the end, several problems related to recognition and localization are addressed..
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Abstract : The effective utilization of available sources in equating the load demand on hourly bases can be implemented using unit commitment. This paper presents the novel hybrid method which is the amalgamation of a whale optimization algorithm (WOA) and a self-organizing migrating algorithm (SOMA) for obtaining optimal value of an optimization problem related to unit commitment. The WOA method is applied for assessing optimal strength population from the stochastically generated populations which is essential in a migrating loop. SOMA works on the strategy of ALL to ALL. Two test systems are considered to evaluate the potential of the proposed hybrid method. Initially, a four-unit system is conducted followed by IEEE 39 bus system. The obtained simulation outcome is made comparison with the literature methods to address the effectiveness of the proposed hybrid WAO-SOMA..
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