Articles Related to Clustering
Detection of Early Blight Using K-Means Clustering
Early blight is one of the major diseases of tomatoes that affects the leaves and fruit quality. Detection and estimation of the
disease severity are performed using the visual observation method. Visual detection requires significant time for visual
inspection of a large cultivated area. Thus, image processing techniques have proven to be an effective method as compared to visual analysis. In this study, digital image processing methods and techniques were used to detect early blight of
tomato, estimate the disease severity, and classify tomato leaves. Totally, 198 infected plants were randomly taken from the
Haramaya University research site "Raree" at four different times. Diseased potato leaf images were captured, resized, and
stored for experimentation. The stored images were processed using median filtering to remove noise while preserving
useful features in an image and image enhancement. The RGB images were transformed to gray scale and CIELAB color
space, and the k-means clustering was applied to estimate the disease severity of the potato leaves, and Otsu’s thresholding
algorithm was applied to estimate the disease severity of both the detached and live leaves. MATLAB algorithms will be
developed to determine the total area and infected lesion area of the leaf samples.
Role of Water Layer on Hydrophobic and Hydrophilic Self-Assembled Monolayer Surface
The water layer adjacent to the hydrophobic and hydrophilic moieties of self-assembled monolayer surface plays an important role on formation of densely packed self-assembled monolayers. Fourier transforms infrared spectroscopy and atomic force microscopy based study shows that the quality of self-assembled monolayer of thiols is dependent on re-structuring of surrounded water molecules.
Characteristic Human Scent Compounds Trapped on Natural and Synthetic Fabrics as analyzed by SPME-GC/MS
The collection of human odor volatiles is of interest to forensic applications as a path to investigate canine scent discriminations in
legal investigations. A study using a selected array of previously identified human odor compounds has been conducted to determine
the retention and release capabilities of five (5) natural and synthetic fabric types, cotton (mercerized fabric and gauze matrix),
polyester, rayon and wool.