Optimization of optical lens-controlled scanning electron microscopic resolution using generalized regression neural network and genetic algorithm

2010 ◽  
Vol 37 (1) ◽  
pp. 182-186 ◽  
Author(s):  
Byungwhan Kim ◽  
Sanghee Kwon ◽  
Dong Hwan Kim
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Generalized Regression Neural Network ◽  
Electron Microscopic ◽  
Optical Lens ◽  
Scanning Electron Microscopic ◽  
Generalized Regression ◽  
Scanning Electron

The Distribution of Teaching Staff in Colleges and Universities based on Neuropsychology

2021 ◽  
Vol 7 (5) ◽  
pp. 4682-4692
Author(s):  
Ruolin Yang ◽  
Dan Guo
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Colleges And Universities ◽  
Quality Education ◽  
Generalized Regression Neural Network ◽  
Teaching Staff ◽  
Actual Situation ◽  
Teacher Resources ◽  
Calculation Process ◽  
Generalized Regression

Objectives: At present, quality education has gradually been recognized by the whole society, and a consensus has been reached on its importance, which has put forward stricter requirements for the distribution of faculty in universities. Methods: In this paper, based on neuropsychology, the distribution of teaching staff in colleges and universities was studied, and the model of talent evaluation and distribution was constructed. Results: Firstly, the generalized regression neural network was optimized by genetic algorithm. Then, the genetic algorithm’s generalized regression neural network calculation process was designed. Conclusion: Finally, with the example of teacher resources in a university, the algorithm in this paper was tested. The results show that the results of the generalized regression neural network optimized by genetic algorithm can match the actual situation very well, and the method is feasible with certain advantages.

An approach to carbon emissions prediction using generalized regression neural network improved by genetic algorithm

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Zhida Guo ◽  
Jingyuan Fu
Keyword(s):  
Neural Network ◽  
Carbon Dioxide ◽  
Genetic Algorithm ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Total Carbon ◽  
Generalized Regression Neural Network ◽  
Improved Method ◽  
Target Values ◽  
Generalized Regression

The study on scientific analysis and prediction of China’s future carbon emissions is conducive to balancing the relationship between economic development and carbon emissions in the new era, and actively responding to climate change policy. Through the analysis of the application of the generalized regression neural network (GRNN) in prediction, this paper improved the prediction method of GRNN. Genetic algorithm (GA) was adopted to search the optimal smooth factor as the only factor of GRNN, which was then used for prediction in GRNN. During the prediction of carbon dioxide emissions using the improved method, the increments of data were taken into account. The target values were obtained after the calculation of the predicted results. Finally, compared with the results of GRNN, the improved method realized higher prediction accuracy. It thus offers a new way of predicting total carbon dioxide emissions, and the prediction results can provide macroscopic guidance and decision-making reference for China’s environmental protection and trading of carbon emissions.

Scanning Electron Microscopic Study of the Cell Surface

1969 ◽  
Vol 27 ◽  
pp. 36-37 ◽  
Author(s):  
Toichiro Kuwabara
Keyword(s):  
Tissue Fluid ◽  
Biological Application ◽  
Biological Structure ◽  
Electron Microscopic ◽  
Surface Appearance ◽  
Minute Amount ◽  
Scanning Electron Microscopic Study ◽  
Scanning Electron Microscopic ◽  
True Structure ◽  
Scanning Electron

Although scanning electron microscopy has a great potential in biological application, there are certain limitations in visualization of the biological structure. Satisfactory techniques to demonstrate natural surfaces of the tissue and the cell have been reported by several investigators. However, it is commonly found that the surface cell membrane is covered with a minute amount of mucin, secretory substance or tissue fluid as physiological, pathological or artefactual condition. These substances give a false surface appearance, especially when the tissue is fixed with strong fixatives. It seems important to remove these coating substances from the surface of the cell for demonstration of the true structure.

A scanning electron microscopic study on dissolving process of cholesterol gallstones by chenodeoxycholic acid (CDCA)

1978 ◽  
Vol 36 (2) ◽  
pp. 522-523
Author(s):  
T. Kanetaka ◽  
M. Cho ◽  
S. Kawamura ◽  
T. Sado ◽  
K. Hara
Keyword(s):  
Electron Microscope ◽  
Chenodeoxycholic Acid ◽  
Outer Surface ◽  
Electron Microscopic ◽  
Cholesterol Gallstones ◽  
The Core ◽  
Scanning Electron Microscopic Study ◽  
Scanning Electron Microscopic ◽  
Acceleration Voltage ◽  
Scanning Electron

The authors have investigated the dissolution process of human cholesterol gallstones using a scanning electron microscope(SEM). This study was carried out by comparing control gallstones incubated in beagle bile with gallstones obtained from patients who were treated with chenodeoxycholic acid(CDCA).The cholesterol gallstones for this study were obtained from 14 patients. Three control patients were treated without CDCA and eleven patients were treated with CDCA 300-600 mg/day for periods ranging from four to twenty five months. It was confirmed through chemical analysis that these gallstones contained more than 80% cholesterol in both the outer surface and the core.The specimen were obtained from the outer surface and the core of the gallstones. Each specimen was attached to alminum sheet and coated with carbon to 100Å thickness. The SEM observation was made by Hitachi S-550 with 20 kV acceleration voltage and with 60-20, 000X magnification.

A Comparative Study of Fractographic Replicas

1974 ◽  
Vol 32 ◽  
pp. 566-567
Author(s):  
Loren Anderson ◽  
Pat Pizzo ◽  
Glen Haydon
Keyword(s):  
Electron Microscopy ◽  
Electron Microscopic Examination ◽  
Direct Examination ◽  
Electron Microscopic ◽  
Reliable Technique ◽  
Service Failures ◽  
Transmission Electron ◽  
Mode Of Failure ◽  
Scanning Electron Microscopic ◽  
Scanning Electron

Transmission electron microscopy of replicas has long been used to study the fracture surfaces of components which fail in service. Recently, the scanning electron microscope (SEM) has gained popularity because it allows direct examination of the fracture surface. However, the somewhat lower resolution of the SEM coupled with a restriction on the sample size has served to limit the use of this instrument in investigating in-service failures. It is the intent of this paper to show that scanning electron microscopic examination of conventional negative replicas can be a convenient and reliable technique for determining mode of failure.

A Scanning Electron Microscopic Study of the Uriniferous Tubules

1973 ◽  
Vol 31 ◽  
pp. 622-623
Author(s):  
Peter M. Andrews
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Renal Glomerulus ◽  
Electron Microscopic ◽  
Vascular Perfusion ◽  
Scanning Electron Microscopic Study ◽  
Scanning Electron Microscopic ◽  
Collecting Tubules ◽  
Bowman's Capsule ◽  
Scanning Electron

Although there have been a number of recent scanning electron microscopic reports on the renal glomerulus, the advantages of scanning electron microscopy have not yet been applied to a systematic study of the uriniferous tubules. In the present investigation, scanning electron microscopy was used to study the ultrastructural morphology of the proximal, distal, thin loop, and collecting tubules. Material for observation was taken from rat kidneys which were fixed by vascular perfusion, sectioned by either cutting or fracturing technigues, and critically point dried.The brush border characterising proximal tubules is first detected on the luminal surface of Bowman's capsule adjacent to the urinary pole orifice. In this region one frequently finds irregular microvilli characterized by broad and flattened bases with occasional bulbous structures protruding from their surfaces.

Sign in / Sign up

Export Citation Format

Share Document