Plant Disease Diagnosing Based on Deep Learning Techniques: A Survey and Research Challenges

Agriculture crops are highly significant for the sustenance of human life and act as an essential source for national income development worldwide. Plant diseases and pests are considered one of the most imperative factors influencing food production, quality, and minimize losses in production. Farmers are currently facing difficulty in identifying various plant diseases and pests, which are important to prevent plant diseases effectively in a complicated environment. The recent development of deep learning techniques has found use in the diagnosis of plant diseases and pests, providing a robust tool with highly accurate results. In this context, this paper presents a comprehensive review of the literature that aims to identify the state of the art of the use of convolutional neural networks (CNNs) in the process of diagnosing and identification of plant pest and diseases. In addition, it presents some issues that are facing the models performance, and also indicates gaps that should be addressed in the future. In this regard, we review studies with various methods that addressed plant disease detection, dataset characteristics, the crops, and pathogens. Moreover, it discusses the commonly employed five-step methodology for plant disease recognition, involving data acquisition, preprocessing, segmentation, feature extraction, and classification. It discusses various deep learning architecture-based solutions that have a faster convergence rate of plant disease recognition. From this review, it is possible to understand the innovative trends regarding the use of CNN’s algorithms in the plant diseases diagnosis and to recognize the gaps that need the attention of the research community

Creating Capacity for Research Data Services at Regional Universities: A Case Study

Understanding the processes of research design and of data collection, organization, storage, preservation, and sharing is critical to the success of any project, regardless of the scope of the research. From research design and conceptualization to the potential sharing of data with other researchers for replicability, as well as preserving data for the benefit of the wider research community, unique challenges, as well as opportunities for research data management (RDM) and research data services (RDS) teams, are presented; these include problems, issues, and concerns regarding how to prepare a data management plan (DMP) and how to manage data collection, analysis, storage, and preservation. In response to these concerns, academic institutions typically have structured RDS for students and faculty through the support of many stakeholders: academic librarians who are familiar with the disciplinary resources and have skills in archives, data curation, and institutional repositories; information technology services staff who provide solutions to infrastructure issues regarding storage and archiving; and other campus research administration entities that deal with the funding, integrity, and administration aspects of the research

The UV Continuum of Quasars: Models and SDSS Spectral Slopes

We measure long (2200-4000 ang) and short (1450-2200 ang) wavelength spectral slopes \alpha (F_\nu proportional to \nu^\alpha) for quasar spectra from the Sloan Digital Sky Survey. The long and short wavelength slopes are computed from 3646 and 2706 quasars with redshifts in the z=0.76-1.26 and z=1.67-2.07 ranges, respectively. We calculate mean slopes after binning the data by monochromatic luminosity at 2200 ang and virial mass estimates based on measurements of the MgII line width and 3000 ang continuum luminosity. We find little evidence for mass dependent variations in the mean slopes, but a significant luminosity dependent trend in the near UV spectral slopes is observed with larger (bluer) slopes at higher luminosities. The far UV slopes show no clear variation with luminosity and are generally lower (redder) than the near UV slopes at comparable luminosities, suggesting a slightly concave quasar continuum shape. We compare these results with Monte Carlo distributions of slopes computed from models of thin accretion disks, accounting for uncertainties in the mass estimates. The model slopes produce mass dependent trends which are larger than observed, though this conclusion is sensitive to the assumed uncertainties in the mass estimates. The model slopes are also generally bluer than observed, and we argue that reddening by dust intrinsic to the source or host galaxy may account for much of the discrepancy.Comment: To be published in ApJ, 18 pages, 10 figure

Healthcare Barriers of Residents at a Subsidized Housing Community

Introduction: Despite expanded healthcare programs, the low income and elderly lack coverage of vision, hearing, and dental services. Community services are often asked to fill these gaps. To evaluate the situation in Burlington, VT, we surveyed staff and residents in Burlington Housing Authority (BHA) subsidized housing to (1) identify gaps in healthcare coverage and (2) assess barriers to accessing those services in this population.https://scholarworks.uvm.edu/comphp_gallery/1207/thumbnail.jp

Evolution of an Emerging Symmetric Quantum Cryptographic Algorithm

With the rapid evolution of data exchange in network environments, information security has been the most important process for data storage and communication. In order to provide such information security, the confidentiality, data integrity, and data origin authentication must be verified based on cryptographic encryption algorithms. This paper presents a new emerging trend of modern symmetric encryption algorithm by development of the advanced encryption standard (AES) algorithm. The new development focuses on the integration between Quantum Key Distribution (QKD) and an enhanced version of AES. A new quantum symmetric encryption algorithm, which is abbreviated as Quantum-AES (QAES), is the output of such integration. QAES depends on generation of dynamic quantum S-Boxes (DQS-Boxes) based quantum cipher key, instead of the ordinary used static S-Boxes. Furthermore, QAES exploits the specific selected secret key generated from the QKD cipher using two different modes (online and off-line)

Preparation and Characterization of Organic Nanoparticles of Oxadiazole Derivative in Aqueous Media

A novel  oxadiazole derivative, 2,5-disubstituted-1,3,4-oxadiazole (Z)-4-((1-(5-(4-hydroxyphenyl)-1,3,4-oxadiazol-2-yl)prop-1-en-2-yl)amino)-1,5-dimethyl-2-phenyl-1H-pyrazol-3(2H)-one (HOPA) was synthesized from reaction of (Z)-3-[(1,5-dimethyl-3-oxo-2-phenyl-2,3-dihydro-1H-pyrazol-4-yl)amino]but-2-enehydrazide, with 4-hydroxybenzaldehyde in the presence of iodine as catalyst .The structure of HOPA was characterized by using IR,1H-NMR and mass spectroscopy. Nanoparticles of the prepared compound HOPA have been fabricated in aqueous media using re-precipitation method. Characterizations of the organic nanoparticles (ONPs) have been performed by using UV-Vis spectrophotometry, and scanning electron microscope (SEM). The HOPA NPs were approximately monodisperse even without using capping agent or surfactant. The size of the nanoparticles were around 150-200 nm as indicated by SEM. The maximum of absorption spectrum of the dispersed nanoparticles is red shifted by 5 nm from the molecular absorption spectra of the HOPA in the solution, which indicate head to head alignment (J aggregate) of the molecules of HOPA during the aggregation. The well dispersed organic nanoparticles in aqueous media holds potential application in future to be used as a tag for biomedical imagining. Keywords: Nanoscience, Organic Nanoparticle, Reprecipitation, Oxdiazoles

Gravitational Collapse of Dust with a Cosmological Constant

The recent analysis of Markovic and Shapiro on the effect of a cosmological constant on the evolution of a spherically symmetric homogeneous dust ball is extended to include the inhomogeneous and degenerate cases. The histories are shown by way of effective potential and Penrose-Carter diagrams.Comment: 2 pages, 2 figures (png), revtex. To appear in Phys. Rev.