4 research outputs found
Automated Wheat Diseases Classification Framework Using Advanced Machine Learning Technique
No full textAround the world, agriculture is one of the important sectors of human life in terms of food, business, and employment opportunities. In the farming field, wheat is the most farmed crop but every year, its ultimate production is badly influenced by various diseases. On the other hand, early and precise recognition of wheat plant diseases can decrease damage, resulting in a greater yield. Researchers have used conventional and Machine Learning (ML)-based techniques for crop disease recognition and classification. However, these techniques are inaccurate and time-consuming due to the unavailability of quality data, inefficient preprocessing techniques, and the existing selection criteria of an efficient model. Therefore, a smart and intelligent system is needed which can accurately identify crop diseases. In this paper, we proposed an efficient ML-based framework for various kinds of wheat disease recognition and classification to automatically identify the brown- and yellow-rusted diseases in wheat crops. Our method consists of multiple steps. Firstly, the dataset is collected from different fields in Pakistan with consideration of the illumination and orientation parameters of the capturing device. Secondly, to accurately preprocess the data, specific segmentation and resizing methods are used to make differences between healthy and affected areas. In the end, ML models are trained on the preprocessed data. Furthermore, for comparative analysis of models, various performance metrics including overall accuracy, precision, recall, and F1-score are calculated. As a result, it has been observed that the proposed framework has achieved 99.8% highest accuracy over the existing ML techniques
Modified physical properties of Ni doped ZnO NPs as potential photocatalyst and antibacterial agents
No full textHazardous organic dyes, present in the effluents of industries, are continuously polluting the environment. Photodegradation of these dyes on catalyst surface under sunlight irradiation is economic, safe and suitable strategy to protect environment. Hence, the synthesis and applications of Zn1-xNixO (x = 0.00, 0.02, 0.04, 0.06) NPs are reported here. Effect of pH and dopant concentration was studied to modify the electrical, magnetic, antibacterial and photocatalytic properties of Ni doped ZnO NPs. The samples were characterized by Scanning electron microscopy (SEM), Powder X-ray diffraction (XRD), UV–Visible spectroscopy (UV–Vis.), Energy-dispersive X-ray spectroscopy (EDS) and Fourier-transform infrared spectroscopy (FTIR) to determine the morphology, crystallite structure, optical properties, elemental composition and functional group detection, respectively. LCR meter and VSM were used to evaluate the dielectric properties and magnetic properties of Ni doped ZnO NPs, respectively. XRD pattern confirmed the presence of hexagonal wurtzite geometry of ZnO NPs. The structural and morphological analysis showed the increase in crystallinity with little effect on shape of doped NPs by increasing the dopant concentration and slight increase of pH. It was observed that the Ni doped ZnO NPs possess good photocatalytic potential by 94% degradation of 20 ppm solution of methyl orange dye (MO) in just 80 min under sunlight. Moreover, the enhancement in antibacterial potential was also observed with increase in dopant concentration and decrease in crystallite size of doped ZnO NPs. Smaller size NPs were found more effective against gram negative bacterial strains. © 2023 The Author(s)King Saud University, KSUAuthors would like to extend their sincere appreciation to the Researchers Supporting Project number (RSP2023R123), King Saud University, Riyadh, Saudi Arabia
Supplementary information files for "Epitaxy of GaSe coupled to graphene: From in situ band engineering to photon sensing"
No full textSupplementary files for article " Epitaxy of GaSe Coupled to Graphene: From In Situ Band Engineering to Photon Sensing"2D semiconductors can drive advances in quantum science and technologies. However, they should be free of any contamination; also, the crystallographic ordering and coupling of adjacent layers and their electronic properties should be well‐controlled, tunable, and scalable. Here, these challenges are addressed by a new approach, which combines molecular beam epitaxy and in situ band engineering in ultra‐high vacuum of semiconducting gallium selenide (GaSe) on graphene. In situ studies by electron diffraction, scanning probe microscopy, and angle‐resolved photoelectron spectroscopy reveal that atomically‐thin layers of GaSe align in the layer plane with the underlying lattice of graphene. The GaSe/graphene heterostructure, referred to as 2semgraphene, features a centrosymmetric (group symmetry D3d) polymorph of GaSe, a charge dipole at the GaSe/graphene interface, and a band structure tunable by the layer thickness. The newly‐developed, scalable 2semgraphene is used in optical sensors that exploit the photoactive GaSe layer and the built‐in potential at its interface with the graphene channel. This proof of concept has the potential for further advances and device architectures that exploit 2semgraphene as a functional building block.© The Author(s) CC BY 4.0</p
