scholarly journals Quality Assessment of Digital Picture. Recent Trendes of Picture Quality Evaluation Methods for Digital Images.

1999 ◽  
Vol 53 (9) ◽  
pp. 1184-1189
Author(s):  
Junji Kamada
Keyword(s):  
Quality Assessment ◽  
Quality Evaluation ◽  
Digital Images ◽  
Evaluation Methods ◽  
Picture Quality ◽  
Digital Picture

scholarly journals Research on Evaluation Method of Ecological Environment Quality Based on the Improvement of Human Settlement Environment

2021 ◽  
Vol 261 ◽  
pp. 04017
Author(s):  
Xi Chen ◽  
Xia Gao ◽  
Xianyue Li
Keyword(s):  
Quality Assessment ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Evaluation Research ◽  
Development Trend ◽  
Evaluation Methods ◽  
Research Field ◽  
Assessment System ◽  
Ecological Environment ◽  
Environment Quality

Against the background that ecological environment quality has become a hot research topic in recent years, ecological environment quality assessment has emerged as an emerging discipline. By adopting scientific methods, it objectively and quantitatively reveals the real situation of ecological environment quality, and is committed to providing support basis for environmental protection and comprehensive prevention and control. Therefore, how to develop a reasonable eco-environmental quality assessment system has become the focus of attention. Based on this, this paper summarizes the research results in this field at home and abroad, and discusses and illustrates the main existing evaluation methods and evaluation models through horizontal and vertical analysis. The development status of ecological environment quality evaluation research field and the application characteristics of different evaluation methods are analyzed, some problems in theoretical innovation, model construction and application of conclusions are discussed, and the development trend of ecological environment quality evaluation research is proposed based on this.

scholarly journals Quality assessment of brands of erythromycin stearate tablets marketed in Abuja, Nigeria

2020 ◽  
Vol 17 (1) ◽  
pp. 29-33
Author(s):  
Kudirat B. Mustapha ◽  
Marlene D. Ekpo ◽  
Isa H. Galadima ◽  
Rukaiyatu A. Kirim ◽  
Olubukola A. Odeniran ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Quality Evaluation ◽  
Hardness Test ◽  
Spectrophotometric Analysis ◽  
Assessment Study ◽  
Uniformity Test ◽  
Quality Assessment Study ◽  
Percentage Weight ◽  
Pharmaceutical Industries ◽  
Erythromycin Stearate

Erythromycin is one of the most frequently prescribed antibiotics. With the increasing number of pharmaceutical industries, the possibility of  purchasing a substandard product is on the high side. This makes it necessary to subject various commercially produced brands of erythromycin to quality evaluation in order to ascertain the quality. In this quality assessment study, six (6) brands of erythromycin tablets were subjected to physicochemical assay using standard physical methods and UV/VIS spectrophotometric analysis at 480 nm. The calibration curve for reference erythromycin was linear over a concentration range of 10-100 μg/ml with a correlation coefficient (R2) of 0.999. All the brands had standard deviation of weight greater than ±5 for the weight uniformity test. 66.67% of the brands passed the test for content of active ingredient. 83.33% of the brands examined passed the hardness test. All the brands failed the friability test because the percentage weight loss are greater than 1% as specified in the official book. Keywords: Erythromycin stearate; Tablets; Brands; Pharmaceutical Industries

scholarly journals No-Reference Image Quality Assessment with Multi-Scale Orderless Pooling of Deep Features

2021 ◽  
Vol 7 (7) ◽  
pp. 112
Author(s):  
Domonkos Varga
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Multiple Scales ◽  
Digital Images ◽  
Input Image ◽  
Perceptual Quality ◽  
Reference Image ◽  
Benchmark Datasets ◽  
In The Wild

The goal of no-reference image quality assessment (NR-IQA) is to evaluate their perceptual quality of digital images without using the distortion-free, pristine counterparts. NR-IQA is an important part of multimedia signal processing since digital images can undergo a wide variety of distortions during storage, compression, and transmission. In this paper, we propose a novel architecture that extracts deep features from the input image at multiple scales to improve the effectiveness of feature extraction for NR-IQA using convolutional neural networks. Specifically, the proposed method extracts deep activations for local patches at multiple scales and maps them onto perceptual quality scores with the help of trained Gaussian process regressors. Extensive experiments demonstrate that the introduced algorithm performs favorably against the state-of-the-art methods on three large benchmark datasets with authentic distortions (LIVE In the Wild, KonIQ-10k, and SPAQ).

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