Ground-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holl

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

It has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlighting the diff

It has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlight

Cloud computing (CC) is a fast-growing technology that offers computers, networking, and storage services that can be accessed and used over the internet. Cloud services save users money because they are pay-per-use, and they save time because they are on-demand and elastic, a unique aspect of cloud computing. However, several security issues must be addressed before users store data in the cloud. Because the user will have no direct control over the data that has been outsourced to the cloud, particularly personal and sensitive data (health, finance, military, etc.), and will not know where the data is stored, the user must ensure that the cloud stores and maintains the outsourced data appropriately. The study's primary goals are to mak

Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be int

Background: The demand for better esthetic during orthodontic treatment has increased nowadays, so orthodontists starting using esthetic arch wires, brackets and ligatures.Tooth colored brackets were introduced in different types of materials. Sapphire ceramic brackets are one type of esthetic brackets and their color stability remains the main concern for the clinicians and patients at the same time. The present study design to evaluate the effect of three different staining materials (pepsi, black tea and cigarette smoke) on the stainability of sapphire ceramic brackets bonded with three types of light cure orthodontic adhesives which include: Resilience, Enlight and Transbond. Materials and Methods: The sample consisted of three hundre

Iron oxide(Fe3O4) nanoparticles of different sizes and shapes were synthesized by solve-hydrothermal reaction assisted by microwave irradiation using ferrous ammonium sulfate as a metal precursor, oleic acid as dispersing agent, ethanol as reducing agent and NaOH as precipitating agent at pH=12. The synthesized Fe3O4 nano particles were characterized by X-ray diffraction (XRD), FTIR and thermal analysis TG-DTG. Sizes and shapes of Fe3O4 nanoparticles were characterized by Scanning Electron Microscopy (SEM), and atomic force microscopy (AFM).

This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them