Incorporation of a SMAC analyzer into the data-processing procedures of a computer-assisted laboratory.

Abstract This paper describes the incorporation of a SMAC (Technicon) analyzer into data-processing techniques that have been developed on existing computer hardware during several years. The SMAC system is interfaced directly to a small computer, and suitable peripherals produce a manageable form of result tabulation for subsequent reporting, as well as provide quality-control information to the SMAC operators in real time. The design is such as to facilitate the performance analysis of the SMAC system during its initiation period and during normal service operation.

Download Full-text

Vibro-acoustic quality control using laser vibrometers and optimized data processing techniques

10.1117/12.468153 ◽

2002 ◽

Cited By ~ 1

Author(s):

Georg Wirth ◽

Helmut Selbach

Keyword(s):

Quality Control ◽

Data Processing ◽

Acoustic Quality ◽

Processing Techniques

Download Full-text

New Monitoring Strategy for the Quality Control in the Processing Practice of Scutellariae Radix

Current Pharmaceutical Analysis ◽

10.2174/1573412915666190314121434 ◽

2020 ◽

Vol 16 (3) ◽

pp. 303-311

Author(s):

Qi Huang ◽

Chunsong Cheng ◽

Lili Li ◽

Daiyin Peng ◽

Cun Zhang

Keyword(s):

Quality Control ◽

Monitoring Strategy ◽

Scutellariae Radix ◽

Chromatographic Fingerprints ◽

New Strategy ◽

Processed Products ◽

Main Components ◽

Processing Techniques ◽

Multivariate Monitoring

Background: Scutellariae Radix (Huangqin) is commonly processed into 3 products for different clinical applications. However, a simple analytical method for quality control has rarely been reported to quickly estimate the degree of processing Huangqin or distinguish differently processed products or unqualified Huangqin products. Objective: To study a new strategy for quality control in the processing practice of Huangqin. Methods: Seven kinds of flavonoids that mainly exist in Huangqin were determined by HPLC-DAD. Chromatographic fingerprints were established to study the variation and discipline of the 3 processed products of Huangqin. PCA and OPLS-DA were used to classify differently processed products of Huangqin. Results: The results showed that baicalin and wogonoside were the main components in the crude and the alcohol Huangqin herb while baicalein and wogonin mainly existed in carbonized Huangqin. The results of mathematical statistics revealed that the processing techniques can make the quality of medicinal materials more uniform. Conclusion: This multivariate monitoring strategy is suitable for quality control in the processing of Huangqin.

Download Full-text

Raw Data Processing Techniques for Material Classification of Objects in Dual Energy X-ray Baggage Inspection Systems

Radiation Physics and Chemistry ◽

10.1016/j.radphyschem.2021.109512 ◽

2021 ◽

pp. 109512

Author(s):

R. Kayalvizhi ◽

Amit kumar ◽

S. Malarvizhi ◽

Anita Topkar ◽

P. Vijayakumar

Keyword(s):

Data Processing ◽

Dual Energy ◽

Raw Data ◽

X Ray ◽

Material Classification ◽

Inspection Systems ◽

Processing Techniques

Download Full-text

Designing computer-assisted problem-based learning (CAPBL) environment for performance analysis of isolation forest algorithm

Journal of Physics Conference Series ◽

10.1088/1742-6596/1524/1/012103 ◽

2020 ◽

Vol 1524 ◽

pp. 012103

Author(s):

R D Hastuti ◽

I Waspada ◽

P W Wirawan ◽

N Bahtiar

Keyword(s):

Performance Analysis ◽

Problem Based Learning ◽

Computer Assisted ◽

Isolation Forest

Download Full-text

Review of data processing techniques for density profile evaluation from broadband FM-CW reflectometry on ASDEX Upgrade

Nuclear Fusion ◽

10.1088/0029-5515/46/9/s05 ◽

2006 ◽

Vol 46 (9) ◽

pp. S693-S707 ◽

Cited By ~ 30

Author(s):

P Varela ◽

M.E Manso ◽

A Silva ◽

the CFN Team ◽

the ASDEX Upgrade Team

Keyword(s):

Data Processing ◽

Density Profile ◽

Processing Techniques

Download Full-text

Investigating the Impact of the Bit Depth of Fluorescence-Stained Images on the Performance of Deep Learning-Based Nuclei Instance Segmentation

Diagnostics ◽

10.3390/diagnostics11060967 ◽

2021 ◽

Vol 11 (6) ◽

pp. 967

Author(s):

Amirreza Mahbod ◽

Gerald Schaefer ◽

Christine Löw ◽

Georg Dorffner ◽

Rupert Ecker ◽

...

Keyword(s):

Deep Learning ◽

State Of The Art ◽

Computer Assisted ◽

Important Criterion ◽

Histological Image ◽

Computer Mediated ◽

Image Patches ◽

Processing Techniques ◽

The Impact ◽

Instance Segmentation

Nuclei instance segmentation can be considered as a key point in the computer-mediated analysis of histological fluorescence-stained (FS) images. Many computer-assisted approaches have been proposed for this task, and among them, supervised deep learning (DL) methods deliver the best performances. An important criterion that can affect the DL-based nuclei instance segmentation performance of FS images is the utilised image bit depth, but to our knowledge, no study has been conducted so far to investigate this impact. In this work, we released a fully annotated FS histological image dataset of nuclei at different image magnifications and from five different mouse organs. Moreover, by different pre-processing techniques and using one of the state-of-the-art DL-based methods, we investigated the impact of image bit depth (i.e., eight bits vs. sixteen bits) on the nuclei instance segmentation performance. The results obtained from our dataset and another publicly available dataset showed very competitive nuclei instance segmentation performances for the models trained with 8 bit and 16 bit images. This suggested that processing 8 bit images is sufficient for nuclei instance segmentation of FS images in most cases. The dataset including the raw image patches, as well as the corresponding segmentation masks is publicly available in the published GitHub repository.

Download Full-text