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Rice is the most significant cultivated harvests everywhere throughout the world, specifically in Asian nations. Nowadays the evaluation of rice quality has a great impact on the market due to adulteration by plastic rice and stones. The assessment of rice is prepared physically by experienced a rancher which is a tedious and monotonous errand and in particular it is a dangerous strategy where the rice might be pulverized by growth pollution. In this paper, a quick, programmed and non-destructive assessment practice is endeavored to measure the nature of rice based on deep learning neural system model. The pre-processing is started by the Median channel to expel noises from the input pictures. By utilizing Fuzzy c-means clustering, the edges of the rice pictures are appropriately depicted. The features like contour, edge, and region are chosen with the assistance of a genetic algorithm. A probabilistic neural system is created to characterize the portioned rice picture. The presentation of PNN model is introduced to show its viability with regards to exactness, accuracy, f-score, and review, and the outcomes are compared with the existing SVM method.
S. Mohanraj; B. Narenthiran; S. Manivannan; R. Arul Murugan; V. Raj Kumar. Classification of Rice Grains Based on Quality Using Probabilistic Neural Network. Recent Advances in Computational Mechanics and Simulations 2021, 867 -886.
AMA StyleS. Mohanraj, B. Narenthiran, S. Manivannan, R. Arul Murugan, V. Raj Kumar. Classification of Rice Grains Based on Quality Using Probabilistic Neural Network. Recent Advances in Computational Mechanics and Simulations. 2021; ():867-886.
Chicago/Turabian StyleS. Mohanraj; B. Narenthiran; S. Manivannan; R. Arul Murugan; V. Raj Kumar. 2021. "Classification of Rice Grains Based on Quality Using Probabilistic Neural Network." Recent Advances in Computational Mechanics and Simulations , no. : 867-886.
A novel phenomenon known as Industry X.0 is becoming extremely popular for digitizing and reinventing business organizations through the adaption of rapid and dynamic technological, innovational, and organizational changes for attaining the profitable revenue. This work investigates the die-casted commercially pure aluminum alloyed with 9% silicon and 3% copper (AlSi9Cu3) that is produced through the gravity die casting process. Further, the degradation of surface coating on die-casted AlSi9Cu3 alloy was explored. The acrylic paint electrodeposition (ED) coat, 2-coat polyester without primer and 3-coat polyester with epoxy primer powder coatings were used in this study. Moreover, the 3.5 wt.% of sodium chloride (3.5 wt.% of NaCl) test solution was used for electrochemical and salt spray test and the tools used to assess electrochemical properties were electrochemical impedance spectroscopy (EIS), potentiodynamic polarization, and neutral salt spray test (NSS). The microstructure of AlSi9Cu3 after corrosion exposure was investigated; also, the microstructure of coated and uncoated AlSi9Cu3 samples was analyzed by SEM microscopy after corrosion exposure. Besides, the electrochemical studies were also carried out on the Al alloy die casting. It was found that acrylic paint ED coatings exhibited higher corrosion resistance than 2-coat polyester without primer & 3-coat polyester with epoxy primer powder coatings. Acrylic paint ED coating showed higher corrosion resistance in AC and a lower value in DC and 3-coat polyester with epoxy primer powder coating displayed higher corrosion resistance in DC and a lower value in AC.
Yuh-Chung Hu; Senthil Kumaran Selvaraj; Manivannan Subramanian; Kathiravan Srinivasan; Srinivasan Narayanan. Ultrasonic Sensors-Assisted Corrosion Studies on Surface Coated AlSi9Cu3 Alloy Die Castings. Coatings 2020, 10, 85 .
AMA StyleYuh-Chung Hu, Senthil Kumaran Selvaraj, Manivannan Subramanian, Kathiravan Srinivasan, Srinivasan Narayanan. Ultrasonic Sensors-Assisted Corrosion Studies on Surface Coated AlSi9Cu3 Alloy Die Castings. Coatings. 2020; 10 (1):85.
Chicago/Turabian StyleYuh-Chung Hu; Senthil Kumaran Selvaraj; Manivannan Subramanian; Kathiravan Srinivasan; Srinivasan Narayanan. 2020. "Ultrasonic Sensors-Assisted Corrosion Studies on Surface Coated AlSi9Cu3 Alloy Die Castings." Coatings 10, no. 1: 85.
The corrosion behaviour of Mg–6Al–1Zn+XCe (where X=0.5, 1.0, 1.5 and 2.0wt% Ce) alloys, aged for 18h at different temperatures of 180°C, 200°C, 220°C and 240°C, was studied in 3.5wt% NaCl solution. The salt spray test was conducted in accordance with ASTM-B117 standard (fog test). The corrosion morphologies, corrosion rate and the composition of the corrosion products were investigated by X-ray Diffraction (XRD), Optical Microscopy (OM) and Scanning Electron Microscopy (SEM) techniques. The results show the cerium addition and ageing treatment has significantly influenced the corrosion morphologies and the corrosion rate. In AZ61 alloy, the intermetallic β (Mg17Al12) phase acts as a corrosion barrier and upon ageing the Al4Ce phase precipitates along the α grain boundaries. The precipitation modifies the β phase to form more continuous network which subsequently reduces the corrosion attack in the chlorine environment. Salt spray test result shows the AZ61 alloy with 1.5wt% Ce aged at 220°C exhibits the better corrosion resistance
Selvambigai Manivannan; Sarathy Kannan Gopalakrishnan; S.P. Kumaresh Babu; Srinivasan Sundarrajan. Effect of cerium addition on corrosion behaviour of AZ61 + X Ce alloy under salt spray test. Alexandria Engineering Journal 2016, 55, 663 -671.
AMA StyleSelvambigai Manivannan, Sarathy Kannan Gopalakrishnan, S.P. Kumaresh Babu, Srinivasan Sundarrajan. Effect of cerium addition on corrosion behaviour of AZ61 + X Ce alloy under salt spray test. Alexandria Engineering Journal. 2016; 55 (1):663-671.
Chicago/Turabian StyleSelvambigai Manivannan; Sarathy Kannan Gopalakrishnan; S.P. Kumaresh Babu; Srinivasan Sundarrajan. 2016. "Effect of cerium addition on corrosion behaviour of AZ61 + X Ce alloy under salt spray test." Alexandria Engineering Journal 55, no. 1: 663-671.