The Next Tenfold Increase in Accuracy of the Electrical Base Units

1988 ◽  
Author(s):  
Kibble
Keyword(s):  
Tenfold Increase ◽  
Increase In Accuracy ◽  
Base Units

Use of Anomalies in the Design of a Hydrostatic Computer

1954 ◽  
Vol 35 (10) ◽  
pp. 478-480 ◽  
Author(s):  
Vincent E. Lally
Keyword(s):  
Tenfold Increase ◽  
Standard Values ◽  
Absolute Height ◽  
The Absolute ◽  
Increase In Accuracy

The use of deviations from standard values rather than the use of absolute values enables computations to be made with lower precision without any accompanying loss in accuracy. Computation of the altimeter correction rather than the absolute height permits the desigh of a hydrostatic computer with a tenfold increase in accuracy when employing computing elements of similar precision.

Modernization Increases Accuracy and Utility of Spectrographic Computer

1953 ◽  
Vol 7 (1) ◽  
pp. 34-36
Author(s):  
M. M. Adams
Keyword(s):  
Tenfold Increase ◽  
Product Engineering ◽  
Increase In Accuracy ◽  
Made In

This report is a brief description of the component changes and product engineering made in the Phillips 66 Spectro Computer since the earlier models were described in a paper by Morgan and Crawford. The improvements described add greatly to the versatility of the Spectro Computer, as well as make possible approximately a tenfold increase in accuracy. At the same time, the instrument is unitized so as to minimize maintenance problems.

Nested code sequences of Barker — Mersenne — Raghavarao

2019 ◽  
pp. 71-81
Author(s):  
M. B. Sergeev ◽  
V. A. Nenashev ◽  
A. M. Sergeev
Keyword(s):  
Data Transfer ◽  
Radio Channel ◽  
Main Peak ◽  
Synthesis Methods ◽  
Orthogonal Matrices ◽  
Useful Signal ◽  
New Codes ◽  
Increase In Accuracy ◽  
Application Fields ◽  
Barker Codes

Introduction: The problem of noise-free encoding for an open radio channel is of great importance for data transfer. The results presented in this paper are aimed at stimulating scientific interest in new codes and bases derived from quasi-orthogonal matrices, as a basis for the revision of signal processing algorithms.Purpose: Search for new code sequences as combinations of codes formed from the rows of Mersenne and Raghavarao quasi-orthogonal matrices, as well as complex and more efficient Barker — Mersenne — Raghavarao codes.Results: We studied nested code sequences derived from the rows of quasi-orthogonal cyclic matrices of Mersenne, Raghavarao and Hadamard, providing estimates for the characteristics of the autocorrelation function of nested Barker, Mersenne and Raghavarao codes, and their combinations: in particular, the ratio between the main peak and the maximum positive and negative “side lobes”. We have synthesized new codes, including nested ones, formed on the basis of quasi-orthogonal matrices with better characteristics than the known Barker codes and their nested constructions. The results are significant, as this research influences the establishment and development of methods for isolation, detection and processing of useful information. The results of the work have a long aftermath because new original code synthesis methods need to be studied, modified, generalized and expanded for new application fields.Practical relevance: The practical application of the obtained results guarantees an increase in accuracy of location systems, and detection of a useful signal in noisy background. In particular, these results can be used in radar systems with high distance resolution, when detecting physical objects, including hidden ones.

scholarly journals Artificial intelligence-based education assists medical students’ interpretation of hip fracture

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Chi-Tung Cheng ◽  
Chih-Chi Chen ◽  
Chih-Yuan Fu ◽  
Chung-Hsien Chaou ◽  
Yu-Tung Wu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Education ◽  
Hip Fracture ◽  
Medical Students ◽  
Medical Image ◽  
Learning System ◽  
Significant Difference ◽  
Dynamic Collaboration ◽  
Increase In Accuracy ◽  
Image Learning

Abstract Background With recent transformations in medical education, the integration of technology to improve medical students’ abilities has become feasible. Artificial intelligence (AI) has impacted several aspects of healthcare. However, few studies have focused on medical education. We performed an AI-assisted education study and confirmed that AI can accelerate trainees’ medical image learning. Materials We developed an AI-based medical image learning system to highlight hip fracture on a plain pelvic film. Thirty medical students were divided into a conventional (CL) group and an AI-assisted learning (AIL) group. In the CL group, the participants received a prelearning test and a postlearning test. In the AIL group, the participants received another test with AI-assisted education before the postlearning test. Then, we analyzed changes in diagnostic accuracy. Results The prelearning performance was comparable in both groups. In the CL group, postlearning accuracy (78.66 ± 14.53) was higher than prelearning accuracy (75.86 ± 11.36) with no significant difference (p = .264). The AIL group showed remarkable improvement. The WithAI score (88.87 ± 5.51) was significantly higher than the prelearning score (75.73 ± 10.58, p < 0.01). Moreover, the postlearning score (84.93 ± 14.53) was better than the prelearning score (p < 0.01). The increase in accuracy was significantly higher in the AIL group than in the CL group. Conclusion The study demonstrated the viability of AI for augmenting medical education. Integrating AI into medical education requires dynamic collaboration from research, clinical, and educational perspectives.

scholarly journals Pseudogymnoascus destructans growth in wood, soil and guano substrates

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jenny Urbina ◽  
Tara Chestnut ◽  
Jennifer M. Allen ◽  
Taal Levi
Keyword(s):  
Dna Extraction ◽  
Emerging Infectious Diseases ◽  
Transmission Risk ◽  
Pseudogymnoascus Destructans ◽  
White Nose Syndrome ◽  
Management Interventions ◽  
Pathogen Persistence ◽  
Tenfold Increase ◽  
And Control

AbstractUnderstanding how a pathogen can grow on different substrates and how this growth impacts its dispersal are critical to understanding the risks and control of emerging infectious diseases. Pseudogymnoascus destructans (Pd) causes white-nose syndrome (WNS) in many bat species and can persist in, and transmit from, the environment. We experimentally evaluated Pd growth on common substrates to better understand mechanisms of pathogen persistence, transmission and viability. We inoculated autoclaved guano, fresh guano, soil, and wood with live Pd fungus and evaluated (1) whether Pd grows or persists on each (2) if spores of the fungus remain viable 4 months after inoculation on each substrate, and (3) whether detection and quantitation of Pd on swabs is sensitive to the choice to two commonly used DNA extraction kits. After inoculating each substrate with 460,000 Pd spores, we collected ~ 0.20 g of guano and soil, and swabs from wood every 16 days for 64 days to quantify pathogen load through time using real-time qPCR. We detected Pd on all substrates over the course of the experiment. We observed a tenfold increase in pathogen loads on autoclaved guano and persistence but not growth in fresh guano. Pathogen loads increased marginally on wood but declined ~ 60-fold in soil. After four months, apparently viable spores were harvested from all substrates but germination did not occur from fresh guano. We additionally found that detection and quantitation of Pd from swabs of wood surfaces is sensitive to the DNA extraction method. The commonly used PrepMan Ultra Reagent protocol yielded substantially less DNA than did the QIAGEN DNeasy Blood and Tissue Kit. Notably the PrepMan Ultra Reagent failed to detect Pd in many wood swabs that were detected by QIAGEN and were subsequently found to contain substantial live conidia. Our results indicate that Pd can persist or even grow on common environmental substrates with results dependent on whether microbial competitors have been eliminated. Although we observed clear rapid declines in Pd on soil, viable spores were harvested four months after inoculation. These results suggest that environmental substrates and guano can in general serve as infectious environmental reservoirs due to long-term persistence, and even growth, of live Pd. This should inform management interventions to sanitize or modify structures to reduce transmission risk as well early detection rapid response (EDRR) planning.

scholarly journals Turn-to-Turn Fault Diagnosis on Three-Phase Power Transformer Using Hybrid Detection Algorithm

2021 ◽  
Vol 11 (6) ◽  
pp. 2608
Author(s):  
Chien-Hsun Liu ◽  
Willybrordus H. P. Muda ◽  
Cheng-Chien Kuo
Keyword(s):  
Fuzzy System ◽  
Power Transformer ◽  
Detection Algorithm ◽  
Current Response ◽  
Negative Sequence ◽  
Three Phase ◽  
Hybrid Detection ◽  
Incipient Faults ◽  
Increase In Accuracy ◽  
Negative Sequence Current

A power transformer (PT) in power generation or transmission is critical to maintaining electrical continuity. Fault detection on a PT is needed, especially of incipient faults, which are often caused by a turn-to-turn fault (TTF) before it develops into a more severe fault. We use a hybrid algorithm between conventional and modern techniques to detect a developing fault in a PT. The current response signals from a negative sequence current directional algorithm, extended park vector algorithm (EPVA), differential negative sequence current, and EPVA-fuzzy system are combined to distinguish the possibility of a TTF. The subalgorithms are combined using a hybrid detection algorithm to distinguish the faults. The model is a 10 MVA, three-phase PT with Δ-Y configuration 150/300 kV, simulated using MATLAB Simulink software. The results show that by combining the subalgorithms, several limitations are distinguished within the TTF with a slight increase in accuracy.

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