Artificial intelligence evaluating primary thoracic lesions has an overall lower error rate compared to veterinarians or veterinarians in conjunction with the artificial intelligence

2020 ◽  
Vol 61 (6) ◽  
pp. 619-627
Author(s):  
Emilie Boissady ◽  
Alois de La Comble ◽  
Xiaojuan Zhu ◽  
Adrien‐Maxence Hespel
1987 ◽  
Vol 31 (5) ◽  
pp. 533-535 ◽  
Author(s):  
William P. Marshak ◽  
Gilbert Kuperman ◽  
Eric G. Ramsey ◽  
Denise Wilson

The effectiveness of ego-centered (moving map) and earth-centered (moving plane) displays was studied with subjects monitoring an animated aircraft situational awareness display. Other independent variables were subject experience (aircrew vs non-aircrew) and path complexity (straight vs turning). Periodically, the display blanked and probe questions were asked concerning the relationship of the aircraft to the simulated world. Questions included judgements about angles, distances, time and terrain. Simple paths elicited a 28 percent lower error rate than did complex paths. Moving map displays had a 32 percent lower error rate than moving plane displays. No other significant effects were observed. Subjective ratings by subjects after the experiment revealed unanimous preference for the moving plane display and that the moving plane condition was believed to be easier! This contradiction indicates subjective data is limited in determining display effectiveness.


2012 ◽  
Vol 472-475 ◽  
pp. 2588-2591
Author(s):  
Yan Liu

This article presents a flow measurement sampling method based on the application group, which identify the received message and then trasmit the identified packets to the corresponding application packet sample space, after this sampling each space packet independently. Thus to ensure the network to restore the situation in the application of fine-grained has lower error rate, thereby reducing the distortion of the application distribution.


2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Bo Xu ◽  
Guangjie Liu ◽  
Yuewei Dai

Image splicing is an image editing method to copy a part of an image and paste it onto another image, and it is commonly followed by postprocessing such as local/global blurring, compression, and resizing. To detect this kind of forgery, the image rich models, a feature set successfully used in the steganalysis is evaluated on the splicing image dataset at first, and the dominant submodel is selected as the first kind of feature. The selected feature and the DCT Markov features are used together to detect splicing forgery in the chroma channel, which is convinced effective in splicing detection. The experimental results indicate that the proposed method can detect splicing forgeries with lower error rate compared to the previous literature.


2021 ◽  
Vol 12 ◽  
Author(s):  
Kongyang Zhu ◽  
Panxin Du ◽  
Jianxue Xiong ◽  
Xiaoying Ren ◽  
Chang Sun ◽  
...  

The MGISEQ-2000 sequencer is widely used in various omics studies, but the performance of this platform for paleogenomics has not been evaluated. We here compare the performance of MGISEQ-2000 with the Illumina X-Ten on ancient human DNA using four samples from 1750BCE to 60CE. We found there were only slight differences between the two platforms in most parameters (duplication rate, sequencing bias, θ, δS, and λ). MGISEQ-2000 performed well on endogenous rate and library complexity although X-Ten had a higher average base quality and lower error rate. Our results suggest that MGISEQ-2000 and X-Ten have comparable performance, and MGISEQ-2000 can be an alternative platform for paleogenomics sequencing.


2021 ◽  
Author(s):  
Oscar Gonzalez-Recio ◽  
Monica Gutierrez-Rivas ◽  
Ramon Peiro-Pastor ◽  
Pilar Aguilera-Sepulveda ◽  
Cristina Cano-Gomez ◽  
...  

Nanopore sequencing has emerged as a rapid and cost-efficient tool for diagnostic and epidemiological surveillance of SARS-CoV-2 during the COVID-19 pandemic. This study compared results from sequencing the SARS-CoV-2 genome using R9 vs R10 flow cells and Rapid Barcoding Kit (RBK) vs Ligation Sequencing Kit (LSK). The R9 chemistry provided a lower error rate (3.5%) than R10 chemistry (7%). The SARS-CoV-2 genome includes few homopolymeric regions. Longest homopolymers were composed of 7 (TTTTTTT) and 6 (AAAAAA) nucleotides. The R10 chemistry resulted in a lower rate of deletions in timine and adenine homopolymeric regions than R9, at expenses of a larger rate (~10%) of mismatches in these regions. The LSK had a larger yield than RBK, and provided longer reads than RBK. It also resulted in a larger percentage of aligned reads (99% vs 93%) and also in a complete consensus genome. The results from this study suggest that the LSK used on a R9 flow cell could maximize the yield and accuracy of the consensus sequence when used in epidemiological surveillance of SARS-CoV-2.


2020 ◽  
Author(s):  
Tian Ye ◽  
Fumikazu Furumi ◽  
Daniel Catarino da Silva ◽  
Antonia Hamilton

In a busy space, people encounter many other people with different viewpoints, but classic studies of VPT examine only one agent at a time. This paper explores the issue of selectivity in VPT when different people are available to interact with. We consider the hypothesis that humanisation impacts on VPT in four studies using virtual reality methods. Experiment 1 & 2 use the Director Task to show that for more humanised agents (an in-group member or a virtual human agent), participants were more likely to use VPT to achieve lower error rate. Experiment 3 & 4 used a two-agent social mental rotation task to show that participants are faster and more accurate to recognise items which are oriented towards a more humanised agent (an in-group member or a naturally-moving agent). All results support the claim that humanisation alters the propensity to engage in VPT in rich social contexts.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ze Gao ◽  
Lin Lin

With the development of technology and the times, the development of new media technology and interactive installation art has slowly entered the vision of our audience. It is simply “silent art.” The public no longer “retires” like the traditional one, but participates in it and swims with the artists in the world of art. This article is aimed at studying the application of artificial intelligence and wireless network communication to the application of interactive installation art. Through the optimization of various communication equipment and the continuous advancement of various algorithms, we can strengthen the communication and connection between our interactive installation art. This article proposes that with the addition of artificial intelligence and wireless network communication, the interaction between artists and audiences may be more fun, so that we can be more colorful in our lives. The experimental results in this article show that when performing wireless network communication, the communication delay rate of the intelligent algorithm with artificial intelligence is much lower than that of the one without it, which shows that they can better transmit information to the control end. When affected by the outside world, the bit error rate of wireless network communication will increase, however, the artificial intelligence algorithm is added to his impact range, and his bit error rate increase is obviously not so high. In the process of wireless network communication, the improved algorithm is definitely better than the nonimproved algorithm in terms of energy consumption, communication delay, and bit error rate. Through the enhancement of signals and the selection of materials for communication equipment, these are all in continuous progress, and in this respect, are in continuous exploration. Compared with other algorithms, the ml algorithm has improved positioning accuracy by about 70%, 65%, and 30%. Increasing the number of nodes in the transmission signal can greatly reduce the number of hops between nodes, correspondingly reducing the hop distance error, correspondingly reducing the distance estimation error, and improving the positioning accuracy. It can solve the technical barriers of interactive installation art faster.


2020 ◽  
Vol 1 (2) ◽  
pp. 85-95
Author(s):  
Alwi Dahlan Permana

The increase in covid-19 positive patients in Indonesia, especially in West Java, is unpredictable, resulting in unpreparedness in dealing with covid-19 cases. People in monitoring and patients under supervision are the category that is breast-positive patients after passing the incubation period for 14 days. Fuzzy logic is one derivative of artificial intelligence that is able to predict a thing.The study used the fuzzy logic of the Tsukamoto method to predict the percentage increase in positive cases of covid-19 with measures performed are fuzzification, rule formation, inference, and defuzzification. The results showed a 4.5% error rate indicating that predicting covid-19 using the fuzzy logic of the Tsukamoto method was successful.


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