Automatic Assessment via Intelligent Analysis of Students’ Program Output Patterns

2018 ◽  
pp. 238-250
Author(s):  
Chung Keung Poon ◽  
Tak-Lam Wong ◽  
Chung Man Tang ◽  
Jacky Kin Lun Li ◽  
Yuen Tak Yu ◽  
...  
Keyword(s):  
Automatic Assessment ◽  
Intelligent Analysis ◽  
Program Output

INTELLIGENT ANALYSIS OF RADAR DATA BASED ON FUZZY TRANSFORMS

2018 ◽  
Vol 77 (15) ◽  
pp. 1321-1329 ◽  
Author(s):  
S.V. Solonskaya ◽  
V. V. Zhirnov
Keyword(s):  
Radar Data ◽  
Intelligent Analysis

ESTIMATING GAS AND ROCK OUTBURST RISK ON THE BASIS OF KNOWLEDGE AND EXPERIENCE – THE EXPERT SYSTEM BASED ON FUZZY LOGIC

2014 ◽  
Vol 59 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Norbert Skoczylas
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Mining Industry ◽  
Automatic Assessment ◽  
Science Field ◽  
Second Stage ◽  
Two Stages ◽  
Outburst Hazard

Abstract The Author endeavored to consult some of the Polish experts who deal with assessing and preventing outburst hazards as to their knowledge and experience. On the basis of this knowledge, an expert system, based on fuzzy logic, was created. The system allows automatic assessment of outburst hazard. The work was completed in two stages. The first stage involved researching relevant sources and rules concerning outburst hazard, and, subsequently, determining a number of parameters measured or observed in the mining industry that are potentially connected with the outburst phenomenon and can be useful when estimating outburst hazard. Then, the Author contacted selected experts who are actively involved in preventing outburst hazard, both in the industry and science field. The experts were anonymously surveyed, which made it possible to select the parameters which are the most essential in assessing outburst hazard. The second stage involved gaining knowledge from the experts by means of a questionnaire-interview. Subjective opinions on estimating outburst hazard on the basis of the parameters selected during the first stage were then systematized using the structures typical of the expert system based on fuzzy logic.

Privacy-Preserving Speech Analytics for Automatic Assessment of Student Collaboration

2016 ◽  
Author(s):  
Nikoletta Bassiou ◽  
Andreas Tsiartas ◽  
Jennifer Smith ◽  
Harry Bratt ◽  
Colleen Richey ◽  
...  
Keyword(s):  
Privacy Preserving ◽  
Automatic Assessment ◽  
Student Collaboration

Automatic Assessment of Children's L2 Reading for Accuracy and Fluency

2017 ◽  
Author(s):  
Kamini Sabu ◽  
Prakhar Swarup ◽  
Hitesh Tulsiani ◽  
Preeti Rao
Keyword(s):  
Automatic Assessment ◽  
L2 Reading

scholarly journals The design of RIP belts impacts the reliability and quality of the measured respiratory signals

2021 ◽  
Author(s):  
Kristofer Montazeri ◽  
Sigurdur Aegir Jonsson ◽  
Jon Skirnir Agustsson ◽  
Marta Serwatko ◽  
Thorarinn Gislason ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Sleep Apnea ◽  
Automatic Assessment ◽  
Signal Reliability ◽  
Respiratory Airflow ◽  
Flow Quality ◽  
The Mean ◽  
Home Sleep Apnea Testing ◽  
Apnea Testing

Abstract Purpose Evaluate the effect of respiratory inductance plethysmography (RIP) belt design on the reliability and quality of respiratory signals. A comparison of cannula flow to disposable cut-to-fit, semi-disposable folding and disposable RIP belts was performed in clinical home sleep apnea testing (HSAT) studies. Methods This was a retrospective study using clinical HSAT studies. The signal reliability of cannula, thorax, and abdomen RIP belts was determined by automatically identifying periods during which the signals did not represent respiratory airflow and breathing movements. Results were verified by manual scoring. RIP flow quality was determined by examining the correlation between the RIP flow and cannula flow when both signals were considered reliable. Results Of 767 clinical HSAT studies, mean signal reliability of the cut-to-fit, semi-disposable, and disposable thorax RIP belts was 83.0 ± 26.2%, 76.1 ± 24.4%, and 98.5 ± 9.3%, respectively. The signal reliability of the cannula was 92.5 ± 16.1%, 87.0 ± 23.3%, and 85.5 ± 24.5%, respectively. The automatic assessment of signal reliability for the RIP belts and cannula flow had a sensitivity of 50% and a specificity of 99% compared with manual assessment. The mean correlation of cannula flow to RIP flow from the cut-to-fit, semi-disposable, and disposable RIP belts was 0.79 ± 0.24, 0.52 ± 0.20, and 0.86 ± 0.18, respectively. Conclusion The design of RIP belts affects the reliability and quality of respiratory signals. The disposable RIP belts that had integrated contacts and did not fold on top of themselves performed the best. The cut-to-fit RIP belts were most likely to be unreliable, and the semi-disposable folding belts produced the lowest-quality RIP flow signals compared to the cannula flow signal.

Research on the strategy of intelligent analysis to improve sports person psychological experience in the era of artificial intelligence

2021 ◽  
pp. 1-11
Author(s):  
Lei Wu ◽  
Juan Wang ◽  
Long Jin ◽  
P. Hemalatha ◽  
R Premalatha
Keyword(s):  
Artificial Intelligence ◽  
Vital Role ◽  
Performance Ratio ◽  
Psychological Experience ◽  
The Public ◽  
Usable Knowledge ◽  
Intelligent Analysis ◽  
Accuracy Ratio ◽  
Depression Level ◽  
Predictive Research

Artificial intelligence (AI) is an excellent potential technology that is evolving day-to-day and a critical avenue for exploration in the world of computer science & engineering. Owing to the vast volume of data and the eventual need to turn this data into usable knowledge and realistic solutions, artificial intelligence approaches and methods have gained substantial prominence in the knowledge economy and community world in general. AI revolutionizes and raises athletics to an entirely different level. Although it is clear that analytics and predictive research have long played a vital role in sports, AI has a massive effect on how games are played, structured, and engaged by the public. Apart from these, AI helps to analyze the mental stability of the athletes. This research proposes the Artificial Intelligence assisted Effective Monitoring System (AIEMS) for the specific intelligent analysis of sports people’s psychological experience. The comparative analysis suggests the best AI strategies for analyzing mental stability using different criteria and resource factors. It is observed that the growth in the present incarnation indicates a promising future concerning AI use in elite athletes. The study ends with the predictive efficiency of particular AI approaches and procedures for further predictive analysis focused on retrospective methods. The experimental results show that the proposed AIEMS model enhances the athlete performance ratio of 98.8%, emotion state prediction of 95.7%, accuracy ratio of 97.3%, perception level of 98.1%, and reduces the anxiety and depression level of 15.4% compared to other existing models.

scholarly journals Research on Transmission Equipment Defect Detection based on Edge Intelligent Analysis

2021 ◽  
Vol 1828 (1) ◽  
pp. 012087
Author(s):  
H M Shen ◽  
P Fan ◽  
Z Wei ◽  
C Zhao ◽  
S Zhou ◽  
...  
Keyword(s):  
Defect Detection ◽  
Transmission Equipment ◽  
Intelligent Analysis
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