Current Issue : April - June Volume : 2020 Issue Number : 2 Articles : 5 Articles
The variability of forest reflectance among hemiboreal forests can be described with a few\nbasis functions. Five basis functions describe almost 98% of variability of directional reflectance\nspectra in the optical spectral domain (400â??1700 nm) in forest stands at the top of a canopy in nadir.\nA statistical forest reflectance model (SFRM) was developed, the input parameters of which are the\nforest parameters measured in the course of regular forest inventory. Nadir spectral reflectance of\na forest stand is expressed in the SFRM as a linear combination of basis functions, the weights of\nwhich are linear combinations of the 15 stand parameters in the forest inventory database. Multiple\ncorrelations of the weights on the forest inventory parameters are determined separately for pine,\nspruce, and broadleaf forests. The basis functions are found from low altitude airborne measurements\nover managed forests in southeastern Estonia, where a forest management database is available. The\nmodel was validated against more than 3000 spectral signatures of forest stands from Sentinel-2\nMultispectral Imager (MSI) measurements over a test site in southeastern Estonia. In most cases, the\nmodel predicts the forest reflectance spectrum at nadir with a relative error about 20â??40%. The errors\nof reflectance values are less than 0.02 in most cases. The sole exception is the reflectance of broadleaf\nstands, which in near infrared bands of Sentinel-2 MSI is overestimated by 0.02â??0.05....
The organizations used quality tools to develop their processes and gain satisfaction\nfrom the customers. The main objective of this study is to develop\nlevels of quality in the construction industry through the use of the seven basic\nquality control tools. Such tools are extremely crucial tools which are used\nworldwide in the industries for continual improvement. The seven basic\nquality tools are Check Sheet, Histogram, Pareto Chart, Fishbone Diagram,\nControl Chart, Flowchart and Scatter Diagram. They were implemented in\nvarious steps of the process in order to define the problems, measure its impacts,\nfind out its root causes and solve these problems to ensure the production\nof non-defective items. The study shows how the seven basic tools of\nquality are very useful and effective in identifying and removal of defects\nfrom the manufacturing process. These tools are helpful in every stage of the\ndefect removal process. This study was conducted on Cleopatra Group Company.\nThis company succeeded to serve the public and private projects in the\nEgyptian construction sectors....
The need to have an express regulation covering nanotechnology has been the\nsubject of debate in the scientific literature and identified as one of the main\nsubsets of nanotechnology field research. However, most countries still do\nnot have regulatory framework in order to guarantee consumer safety. This is\nthe case of Costa Rica, one of the most promising countries in Latin America\nin terms of biotechnology and nanotechnology. This article presents a statistical\nstudy about the position of industry, academia and government institutions\non the need to expressly regulate nanotechnology in Costa Rica. A qualitative\nstudy consisting of a survey of 79 forms was done to individuals\nrepresenting the community involved with nanotechnology and institutions\nresponsible for ensuring the safety of the citizenâ??s health, to conclude that the\nnanotechnology regulation should be created to protect the consumer in\nCosta Rica. The research also proposes aspects that should be taken into account\nin its drafting as well as the variables on which decisions should be\nmade to authorize the commercialization of nanomaterials based on the\nfindings of the literature....
The article presents the results of a study of the influence of silkworm feeding\nconditions enriched with mulberry leaves on the quality of cocoons and\nproperties of the cocoon shell....
In order to solve the problem that the traditional radial basis function (RBF)\nneural network is easy to fall into local optimal and slow training speed in the\ndata fusion of multi water quality sensors, an optimization method of RBF\nneural network based on improved cuckoo search (ICS) was proposed. The\nmethod uses RBF neural network to construct a fusion model for multiple\nwater quality sensor data. RBF network can seek the best compromise between\ncomplexity and learning ability, and relatively few parameters need to\nbe set. By using ICS algorithm to find the best network parameters of RBF\nnetwork, the obtained network model can realize the non-linear mapping between\ninput and output of data sample. The data fusion processing experiment\nwas carried out based on the data released by Zhejiang province surface water\nquality automatic monitoring data system from March to April 2018. Compared\nwith the traditional BP neural network, the experimental results show\nthat the RBF neural network based on gradient descent (GD) and genetic algorithm\n(GA), the new method proposed in this paper can effectively fuse the\nwater quality data and obtain higher classification accuracy of water quality....
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