| 1 | Modelling of electric vehicle charging station and controlled by fuzzy logic controller with different modes of operation显示文摘The main objective of implementing charging stations is to ensure the good charging to theElectric Vehicles by using a solar PV array which is interconnected to the battery energy storagesystems. The charging station regulates the supply voltage and frequency without the use of amechanical speed governor. It also assures that energy gained from grid or by the DG set willhave the unity power factor (UPF) when the load is nonlinear. Besides this, the Point of CommonCoupling (PCC) voltage is synchronised with the grid/generator voltage in order to providecontinuous charging. In order to increase the optimal efficiency of the charging stations, thecharging stations will perform the active/reactive power transfer from the vehicle to grid, vehicleto house and vehicle to vehicle (V2V) power transfer. The operational experiment of the chargingstation is simulated and verified by using MATLAB/SIMULINK. | S.C.Vijay Kumar K.Karunanithi S.P.Raja S.Ramesh P.Chandrasekar R.Obulupathy | 2023 | Journal of Control and Decision2023，10，1： | 0 |
| 2 | A Construction of Object Detection Model for Acute Myeloid Leukemia显示文摘The evolution of bone marrow morphology is necessary in Acute Mye-loid Leukemia(AML)prediction.It takes an enormous number of times to ana-lyze with the standardization and inter-observer variability.Here,we proposed a novel AML detection model using a Deep Convolutional Neural Network(D-CNN).The proposed Faster R-CNN(Faster Region-Based CNN)models are trained with Morphological Dataset.The proposed Faster R-CNN model is trained using the augmented dataset.For overcoming the Imbalanced Data problem,data augmentation techniques are imposed.The Faster R-CNN performance was com-pared with existing transfer learning techniques.The results show that the Faster R-CNN performance was significant than other techniques.The number of images in each class is different.For example,the Neutrophil(segmented)class consists of 8,486 images,and Lymphocyte(atypical)class consists of eleven images.The dataset is used to train the CNN for single-cell morphology classification.The proposed work implies the high-class performance server called Nvidia Tesla V100 GPU(Graphics processing unit). | K.Venkatesh S.Pasupathy S.P.Raja | 2023 | Intelligent Automation & Soft Computing2023，，4： | 0 |
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