scholarly journals Application of Spectral Features for Separating Homochromatic Foreign Matter from Mixed Congee

2021 ◽  
pp. 100128
Author(s):  
Jiyong Shi ◽  
Yueying Wang ◽  
Chuanpeng Liu ◽  
Zhihua Li ◽  
Xiaowei Huang ◽  
...  
Keyword(s):  
Spectral Features ◽  
Foreign Matter

Microbulldozing and Microchiseling

1969 ◽  
Vol 27 ◽  
pp. 134-135
Author(s):  
J.N. Ramsey ◽  
D.P. Cameron ◽  
F.W. Schneider
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Material Handling ◽  
Microprobe Analysis ◽  
Foreign Matter ◽  
Specific Location ◽  
Potential Problems ◽  
Knoop Indenter ◽  
Scanning Electron ◽  
Microhardness Tester

As computer components become smaller the analytical methods used to examine them and the material handling techniques must become more sensitive, and more sophisticated. We have used microbulldozing and microchiseling in conjunction with scanning electron microscopy, replica electron microscopy, and microprobe analysis for studying actual and potential problems with developmental and pilot line devices. Foreign matter, corrosion, etc, in specific locations are mechanically loosened from their substrates and removed by “extraction replication,” and examined in the appropriate instrument. The mechanical loosening is done in a controlled manner by using a microhardness tester—we use the attachment designed for our Reichert metallograph. The working tool is a pyramid shaped diamond (a Knoop indenter) which can be pushed into the specimen with a controlled pressure and in a specific location.

PHYSICOCHEMICAL AND MICROBIOLOGICAL EVALUATION OF HONEYS CONSUMED BY THE ELDERLY

2020 ◽  
Vol 5 ◽  
Author(s):  
Lusmarina Rodrigues Silva ◽  
Aline Marques Monte ◽  
Rafael Gomes Abreu Bacelar ◽  
Guilherme Antonio Silva Ribeiro ◽  
Aline Maria Dourado Rodrigues ◽  
...  
Keyword(s):  
Health Center ◽  
Reducing Sugars ◽  
The Elderly ◽  
Indicator Bacteria ◽  
Foreign Matter ◽  
Total Sugars ◽  
Significant Contamination ◽  
Almost All ◽  
Microbiological Analyses ◽  
Current Standards

Objective: to analyze physicochemical, microbiological and dirt parameters in marketed honeys, consumed by the elderly cared for at Integrated Health Center in Teresina, Piauí, Brazil. Method: the following analyses were performed: color, water activity, humidity, ash, pH, acidity, reducing sugars, total sugars, apparent sucrose and insoluble solids. Contamination indicator bacteria, mesophilic microorganisms, filamentous fungi and yeasts, as well as dirt and foreign matter, performed in the period from April to June 2016. Results: analyses of ash, pH, acidity and insoluble solids were outside current standards. Microbiological analyses did not present significant contamination. Also, analyses of dirt showed insect fragments, foreign matter in almost all the samples. Conclusion: parameters of ash, pH, acidity and insoluble solids, as well as dirt and foreign matter, indicated that the samples were not in accordance with current legislation. 

Dialect Identification Using Tonal and Spectral Features in Two Dialects of Ao

2018 ◽  
Author(s):  
Moakala Tzudir ◽  
Priyankoo Sarmah ◽  
S R Mahadeva Prasanna
Keyword(s):  
Spectral Features

Comparative analytical study of Ashuddha Karaveera and Shuddha Karaveera

2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Apeksha D. Patil ◽  
Dhiraj B. Patil
Keyword(s):  
Stainless Steel ◽  
Analytical Study ◽  
Warm Water ◽  
Foreign Matter ◽  
Steel Vessel ◽  
Mild Heat ◽  
Stainless Steel Vessel ◽  
The Impact

Karaveera (Cerebra thevetia Linn.) is reported under Upavisha Dravya in classical ayurvedic pharmacopeias. It is observed that Shodhana (purification procedures) of the mool should be carried out before its internal administration. There are different Shodhana methods mentioned in Ayurveda. In this study Godugdha was used as media. The impact of Shodhana was evaluated by physico analytical study. It clearly proves physico analytical changes during Shodhana. Ashuddha Karaveera was taken on white clean cloth and they dumped in Pottali with Godugdha. Pottali was tied to middle of wooden rod dipped in Godugdha in stainless steel vessel and mild heat given to pottali in Dolayantra. Shuddha Karaveera was obtained and then washed with leuk warm water and dried. Ashuddha Karaveera contains toxin in it which was removed after Shodhana process. So that foreign matter, loss on drying was less in Shuddha Karaveera and due to Shodhan process with Godugdha total ash, acid insoluble ash was more than that of Ashuddha Karaveera.

Correlations of TCS and EELS spectral features for graphite, ZnSe(111) and CdTe(110)

1989 ◽  
Vol 213 (2-3) ◽  
pp. A218
Author(s):  
A. Dittmar-Wituski ◽  
M. Naparty ◽  
J. Skonieczny
Keyword(s):  
Spectral Features

scholarly journals Raman spectroscopic detection of interleukin-10 and angiotensin converting enzyme

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Shuo Zhang ◽  
Frederieke A. M. van der Mee ◽  
Roel J. Erckens ◽  
Carroll A. B. Webers ◽  
Tos T. J. M. Berendschot
Keyword(s):  
Angiotensin Converting Enzyme ◽  
Biomedical Applications ◽  
Interleukin 10 ◽  
Spectral Features ◽  
Converting Enzyme ◽  
Raman Spectroscopic ◽  
Non Invasive ◽  
Confocal Raman ◽  
First Time ◽  
Enzyme Characteristic

AbstractIn this report we present a confocal Raman system to identify the unique spectral features of two proteins, Interleukin-10 and Angiotensin Converting Enzyme. Characteristic Raman spectra were successfully acquired and identified for the first time to our knowledge, showing the potential of Raman spectroscopy as a non-invasive investigation tool for biomedical applications.

scholarly journals A Study of Features and Deep Neural Network Architectures and Hyper-Parameters for Domestic Audio Classification

2021 ◽  
Vol 11 (11) ◽  
pp. 4880
Author(s):  
Abigail Copiaco ◽  
Christian Ritz ◽  
Nidhal Abdulaziz ◽  
Stefano Fasciani
Keyword(s):  
Network Architecture ◽  
Single Channel ◽  
Classification Performance ◽  
Network Size ◽  
Directed Acyclic Graphs ◽  
Spectral Features ◽  
Audio Classification ◽  
Resource Requirements ◽  
Efficient Alternative ◽  
Computational Resources

Recent methodologies for audio classification frequently involve cepstral and spectral features, applied to single channel recordings of acoustic scenes and events. Further, the concept of transfer learning has been widely used over the years, and has proven to provide an efficient alternative to training neural networks from scratch. The lower time and resource requirements when using pre-trained models allows for more versatility in developing system classification approaches. However, information on classification performance when using different features for multi-channel recordings is often limited. Furthermore, pre-trained networks are initially trained on bigger databases and are often unnecessarily large. This poses a challenge when developing systems for devices with limited computational resources, such as mobile or embedded devices. This paper presents a detailed study of the most apparent and widely-used cepstral and spectral features for multi-channel audio applications. Accordingly, we propose the use of spectro-temporal features. Additionally, the paper details the development of a compact version of the AlexNet model for computationally-limited platforms through studies of performances against various architectural and parameter modifications of the original network. The aim is to minimize the network size while maintaining the series network architecture and preserving the classification accuracy. Considering that other state-of-the-art compact networks present complex directed acyclic graphs, a series architecture proposes an advantage in customizability. Experimentation was carried out through Matlab, using a database that we have generated for this task, which composes of four-channel synthetic recordings of both sound events and scenes. The top performing methodology resulted in a weighted F1-score of 87.92% for scalogram features classified via the modified AlexNet-33 network, which has a size of 14.33 MB. The AlexNet network returned 86.24% at a size of 222.71 MB.

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