scholarly journals Improved Surprise Adequacy Tools for Corner Case Data Description and Detection

2021 ◽  
Vol 11 (15) ◽  
pp. 6826
Author(s):  
Tinghui Ouyang ◽  
Vicent Sanz Marco ◽  
Yoshinao Isobe ◽  
Hideki Asoh ◽  
Yutaka Oiwa ◽  
...  
Keyword(s):  
Data Detection ◽  
Design Phase ◽  
Critical Systems ◽  
Classification Problems ◽  
Data Description ◽  
Detection Techniques ◽  
Qualitative And Quantitative ◽  
Improved Performance ◽  
Case Data ◽  
Experiment Analysis

Facing the increasing quantity of AI models applications, especially in life- and property-related fields, it is crucial for designers to construct safety- and security-critical systems. As a major factor affecting the safety of AI models, corner case data and its related description/detection techniques are important in the AI design phase and quality assurance. In this paper, inspired by surprise adequacy (SA), a tool having advantages on capture data behaviors, we developed three modified versions of distance-based-SA (DSA) for detecting corner cases in classification problems. Through the experiment analysis on MNIST, CIFAR, and industrial example data, the feasibility and usefulness of the proposed tools on corner case data detection are verified. Moreover, Qualitative and quantitative experiments validated that the developed DSA tools can achieve improved performance in describing corner cases’ behaviors.

The methods of formaldehyde emission testing of engine: A review

2015 ◽  
Vol 29 (Supplement 1) ◽  
pp. 1530009
Author(s):  
Chunhui Zhang ◽  
Peng Geng ◽  
Erming Cao ◽  
Lijiang Wei
Keyword(s):  
Infrared Spectroscopy ◽  
Sampling Method ◽  
Formaldehyde Emission ◽  
Qualitative And Quantitative Analysis ◽  
Engine Exhaust ◽  
Detection Techniques ◽  
Qualitative And Quantitative ◽  
Emission Testing ◽  
Variable Condition ◽  
Unregulated Emissions

A number of measurements have been provided to detect formaldehyde in the atmosphere, but there are no clear unified standards in engine exhaust. Nowadays, formaldehyde, an unregulated emission from methanol engine, has been attracting increasing attention by researchers. This paper presents the detection techniques for formaldehyde emitted from the engines applied in recent market, introducing the approaches in terms of unregulated emission tests of formaldehyde, which involved gas chromatography, liquid chromatography, chromatography-mass spectrometry, chromatography-spectrum, Fourier infrared spectroscopy and spectrophotometry. The author also introduces the comparison regarding to the advantages of the existing detection techniques based on the principle, to compare with engine exhaust sampling method, the treatment in advance of detection, obtaining approaches accessing to the qualitative and quantitative analysis of chromatograms or spectra. The accuratest result obtained was chromatography though it cannot be used continuously. It also can be utilized to develop high requirements of emissions and other regulations. Fourier infrared spectroscopy has the advantage of continuous detection for a variety of unregulated emissions and can be applied to the bench in variable condition. However, its accuracy is not as good as chromatography. As the conclusion, a detection technique is chosen based on different requirements.

scholarly journals Novel Immune Microlens Imaging for Detection of Antigen and Antibody

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Jiahui Liang ◽  
Xiaotian Ye ◽  
Jiang He ◽  
Jing Liu ◽  
Yaoxiong Huang ◽  
...  
Keyword(s):  
Refractive Index ◽  
Food Safety ◽  
Environmental Science ◽  
Imaging Technique ◽  
Clinical Samples ◽  
Detection Techniques ◽  
Qualitative And Quantitative ◽  
Before And After ◽  
Antibody Reaction ◽  
Antigen Antibody

Detection and analysis of antigen-antibody reaction is one of the most critical detection techniques in the fields of medicine, biology, environmental science, and food safety. Traditional and classical methods for detecting antigen and antibody encounter many problems, such as time-consuming, high cost, and low accuracy. A novel immune microsphere imaging technique by the microlens is used to test the changes of refractive index before and after antigen-antibody reaction. It can quickly perform qualitative and quantitative determination for antigen-antibody reaction without any labeling, premodification, postwashing, and expensive enzymes. Here, we feature and discuss its principle and advantages, structure of a microlens immunoassay instrument, and potential in measuring clinical samples. It is promising to be developed for application to diagnosis of clinical diseases.

scholarly journals Multi-Level-Phase Deep Learning Using Divide-and-Conquer for Scaffolding Safety

2020 ◽  
Vol 17 (7) ◽  
pp. 2391
Author(s):  
Sayan Sakhakarmi ◽  
Jee Woong Park
Keyword(s):  
Deep Learning ◽  
Failure Modes ◽  
Past Research ◽  
Divide And Conquer ◽  
Classification Problems ◽  
Multi Level ◽  
Improved Performance ◽  
Safety Cases ◽  
Global And Local ◽  
Local Levels

A traditional structural analysis of scaffolding structures requires loading conditions that are only possible during design, but not in operation. Thus, this study proposes a method that can be used during operation to make an automated safety prediction for scaffolds. It implements a divide-and-conquer technique with deep learning. As a test scaffolding, a four-bay, three-story scaffold model was used. Analysis of the model led to 1411 unique safety cases for the model. To apply deep learning, a test simulation generated 1,540,000 datasets for pre-training, and an additional 141,100 datasets for testing purposes. The cases were then sub-divided into 18 categories based on failure modes at both global and local levels, along with a combination of member failures. Accordingly, the divide-and-conquer technique was applied to the 18 categories, each of which were pre-trained by a neural network. For the test datasets, the overall accuracy was 99%. The prediction model showed that 82.78% of the 1411 safety cases showed 100% accuracy for the test datasets, which contributed to the high accuracy. In addition, the higher values of precision, recall, and F1 score for the majority of the safety cases indicate good performance of the model, and a significant improvement compared with past research conducted on simpler cases. Specifically, the method demonstrated improved performance with respect to accuracy and the number of classifications. Thus, the results suggest that the methodology could be reliably applied for the safety assessment of scaffolding systems that are more complex than systems tested in past studies. Furthermore, the implemented methodology can easily be replicated for other classification problems.

scholarly journals Establishment and In-House Validation of Simplex and Duplex PCR Methods for Event-Specific Detection of Maize SYN-E3272-5 Using a New Reference Molecule

2010 ◽  
Vol 93 (2) ◽  
pp. 663-675
Author(s):  
Kailin Shen ◽  
Xiang Li ◽  
Shu Wang ◽  
Yingjie Pan ◽  
Zhiyi Shi ◽  
...  
Keyword(s):  
Quantitative Pcr ◽  
Genetically Modified Organisms ◽  
Insertion Site ◽  
Quantitative Detection ◽  
Duplex System ◽  
Detection Techniques ◽  
Qualitative And Quantitative ◽  
Reference Molecule ◽  
Gm Maize ◽  
Pcr Assays

Abstract Despite rapid developments in the detection techniques for genetically modified organisms (GMOs), the event-specific PCR method with high specificity is still the most used technique. In this study, event-specific simplex and duplex qualitative and quantitative detection systems were developed targeting the 3 insertion site of GM maize SYN-E3272-5 (3272) construct. A reference molecule p3272 was constructed to act as positive control and as calibrator for quantitative analysis. The LOD for simplex and duplex qualitative PCR assays was 10 copies of p3272 control DNA. LOD and the LOQ for simplex and duplex quantitative PCR assays were 10 and 25 copies of p3272 DNA, respectively. Furthermore, four practical GM maize samples were quantified using the established simplex and duplex quantitative PCR systems by in-house validation. Results from five operators showed that the bias ranged from 3.44 to 17.24 in the simplex system and from 0.42 to 16.06 in the duplex system, respectively. These results demonstrated that the established event-specific simplex and duplex qualitative and quantitative PCR systems combined with the reference molecule p3272 are suitable for the detection of GM maize 3272 and its derived products.

A Comparative Study of Unsupervised Video Shot Boundary Detection Techniques Using Probabilistic Fuzzy Entropy Measures

2013 ◽  
pp. 228-240 ◽  
Author(s):  
Biswanath Chakraborty ◽  
Siddhartha Bhattacharyya ◽  
Susanta Chakraborty
Keyword(s):  
Boundary Detection ◽  
Fuzzy Entropy ◽  
Detection Technique ◽  
Shot Boundary Detection ◽  
Detection Techniques ◽  
Entropy Measures ◽  
Video Shot ◽  
Shot Boundary ◽  
Improved Performance ◽  
A New Technique

The performance of video shot boundary detection technique in unsupervised video sequence can be improved by the use of different probabilistic fuzzy entropies. In this chapter, the authors present a new technique for identifying as to whether there are any appreciable changes from one video context to another in the available sequence of image frames extracted from a mixture of a numbers of video files. They then compared their technique with an existing technique and found improved performance of the video shot boundary detection techniques using probabilistic fuzzy entropies.

Qualitative Phase Analysis Using an X-Ray Powder Diffractometer

1980 ◽  
Vol 24 ◽  
pp. 91-97
Author(s):  
W. N. Schreiner ◽  
C. Surdukowski ◽  
R. Jenkins
Keyword(s):  
Qualitative Analysis ◽  
Phase Analysis ◽  
Powder Diffraction ◽  
X Ray ◽  
Qualitative And Quantitative ◽  
The Past ◽  
Quantitative Analyses ◽  
Improved Performance ◽  
Qualitative Phase ◽  
Self Consistency

During the past three years we have undertaken the development of a complete X-Ray Powder Diffraction, facility with the goal of fully integrating experimental and analytical procedures. Such an approach potentially offers substantially improved performance over previously existing systems by virtue of its internal self-consistency and it opens the possibility of significantly extending analytic procedures for both qualitative and quantitative analyses. Our work to date has resulted in improved performance and significant extensions in both areas, and today I will report on those advances in the area of qualitative analysis.

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