Net Bloch, Leaf Scald and Healthy Malting Barley Leaves

Net Bloch infected, Leaf Scald infected and Healthy Malting Barley Leaves dataset it collection of 3012 Malting Barley leaves that are healthy, net blotch infected and leaf scald infected leaves. The dataset is collected starting from August 2021 to December 2021. It is collected from Debre Berhan University Malting Barley farm. The two classes of diseases that are gathered in this dataset are the most fatal malting barley diseases causing a drastic loss in both quality and yield of the crop. The dataset is gathered by using smart phone camera and digital camera as per the conditional requirement while collection. To minimize the time to segment unwanted features out of the image, white paper is used as a background while taking the pictures. Using this dataset CNN based Malting Barley Disease detection is studies with an aim of increasing the performances of CNN models for detecting potential Malting Barley diseases. CNN pretrained models for mobile platforms such as EfficientNetB0, MobileNetV2 and NASNetMobile have been experimented to have an outperforming CNN model . Based on the experiment work EfficientNetB0 has scored a 96% accuracy which is 2 percent increase than the state-of-the -art CNN pretrained model for mobile platforms. In the research work the dataset is portioned in to two classes namely: training and testing dataset. the ratio of partitioning is 90% to 10% respectively. Then K-fold cross validation is used for building sampling independent robust model. Data augmentation technique is used to increase the number of training image dataset. After augmentation, the training image dataset transformed from 2,711 to 13,555. The augmentation technique comprises different arguments such as rotation range, zoom range and width shift. In order to use this dataset you should first understand the problem that you are longing to solve. If it is related with plant disease detection especially Malting Barley, congrats you have a very reliable dataset for your model input. The data can be used after some preprocessing activities based on the researcher's interest.Thank you very much.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Experimental investigation on port-to-channel flow maldistribution in plate heat exchangers

Experiments have been conducted to analyze the flow and pressure distribution in a plate heat exchanger by measuring local port pressure distribution in a commercial plate heat exchanger. Flow rate in channel and channel pressure drops are evaluated by measuring the pressure inside the inlet and exit ports at different locations for different port dimensions. In these experiments, the measurement of pressure is done without disturbing the fluid flow inside the port. This technique also offers the option of manipulating port size without changing the plate characteristics. Direct experimental measurement provides the scope for eliminating other effects, such as gasket, end losses, and improper wetting of channels from the flow maldistribution effect. The measurements indicate the existence of non-uniform flow distribution that increases with flow rate and decreases with port diameter. Results clearly show that it is important to consider the flow maldistribution for better design of plate heat exchangers