Oldenlandia umbellata L., commonly known as 'chay root', belongs to the family Rubiaceae and is one of the unexplored dye-yielding plants. The roots from this plant are the sources of red dye. Extraction protocol and dye characterisation have not been completely studied so far in this plant. Hence, in this article we have used UV spectrophotometry, thin layer chromatography, GC-MS, high-performance liquid chromatography and NMR to identify the five major colouring compounds, including 1,2,3-trimethoxyanthraquinone, 1,3-dimethoxy-2-hydroxyanthraquinone, 1,2-dimethoxyanthraquinone, 1-methoxy-2-hydroxyanthraquinone and 1,2-dihydroxyanthraquinone. It showed application feasibility as a new pH indicator.
Smart farming is a vital notion for the development of agriculture and food processing industries globally. Industrial revolution in computing and digital network turned agriculture industry to a digitalized and automated technology. Manual and mechanical tools are replaced by tools that are controlled by mobile phones, drones and Web-based applications. IoT is the major applicant in smart farming that controls sensors in devices and data analysis by remote servers. Security is deployed as builtin mechanisms in the devices or as software tools implemented in the mobile devices, sensor systems and machines that are remotely controlled. Protocol-based security is provided to data that are collected from the fields and to the data that are transmitted to remote servers for processing. However, in recent years vulnerabilities in smart farming applications are demoralized which ensued smart farming systems being victimized to cyber-attacks. This research work provides insight analysis on several security threats that are being subjugating smart farming devices and processes. This paper will provide intrigue on vulnerabilities existing in smart farming systems and the threats that exploit them.
IntroductıonSmart farming encompasses automation in agriculture and food processing systems. As information technology has stimulated to the radical revolution in industrial development, there is a tremendous advancement in the agriculture, manufacturing of tools used in forms, food production and preservation industries. The swift in increasing population, unpredicted climatic conditions, decline in availability of natural resources and restraints in pest control are the major hurdles in the modern
Gender classification is the most challenging task in forensic investigation. In this paper, a new approach to estimate gender by multiresolutional analysis of fingerprints is proposed. Discrete Wavelet Transform (DWT) is used to analyze the fingerprints in the frequency domain. The classification task is modeled by gaussian mixtures. DWT coefficients are used as features and only dominant features selected by ranking are fed into GMM for classification. This system carried out with the database of 180 persons in which 80 are females and 100 are males. The results show that the proposed system achieves 92.67% at 3rd level DWT decomposition with 16 gaussian densities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.