The application of artificial intelligence and virtual reality in the auxiliary teaching of American science fiction literature

2021 ◽  
pp. 1-10
Author(s):  
Jin Xu ◽  
Tong Li
Keyword(s):  
Artificial Intelligence ◽  
Virtual Reality ◽  
Science Fiction ◽  
Point Cloud ◽  
Nearest Neighbors ◽  
K Nearest Neighbors ◽  
Denoising Method ◽  
Virtual Technology ◽  
Teaching System ◽  
American Science

In order to improve the teaching effect of American science fiction literature, based on artificial intelligence virtual reality technology, this paper constructs an auxiliary teaching system of intelligent American science fiction literature. Moreover, this paper analyzes the time complexity and space complexity of constructing point cloud spatial topological relations and finding the nearest k neighboring points. Simultaneously, this paper uses CUDA to find k nearest neighbors on the GPU, analyzes the point cloud denoising technology, uses the KD-tree to construct the point cloud topology in the DBSCAN-based denoising method, searches for the k nearest neighbors to complete the mark of the core point and the boundary point. In addition, this paper combines artificial intelligence virtual technology and intelligent algorithms to construct the framework of the auxiliary teaching system of American science fiction literature, and analyze its functional modules. Finally, this paper designs experiments to verify the performance of the model. The research results show that the system constructed in this paper can meet the needs of auxiliary teaching of American science fiction literature.

scholarly journals Application of the k - nearest neighbors algorithm for predicting blast - induced ground vibration in open - pit coal mines: a case study

2020 ◽  
Vol 61 (6) ◽  
pp. 22-29
Author(s):  
Hoang Nguyen . ◽  
Keyword(s):  
Artificial Intelligence ◽  
Coal Mine ◽  
Empirical Model ◽  
Ground Vibration ◽  
Nearest Neighbors ◽  
Superior Performance ◽  
Open Pit ◽  
K Nearest Neighbors ◽  
Open Pit Mines

Blasting is considered as one of the most effective methods for rock fragmentation in open - pit mines. However, its side effects are significant, especially blast - induced ground vibration. Therefore, this study aims to develop and apply artificial intelligence in predicting blast - induced ground vibration in open - pit mines. Indeed, the k - nearest neighbors (KNN) algorithm was taken into account and developed for predicting blast - induced ground vibration at the Deo Nai open - pit coal mine (Vietnam) as a case study. An empirical model (i.e., USBM) was also developed to compare with the developed KNN model aiming to highlight the advantage of the KNN model. Accordingly, 194 blasting events were collected and analyzed for this aim. This database was then divided into two parts, 80% for training and 20% for testing. The MinMax scale and 10 - fold cross - validation techniques were applied to improve the accuracy, as well as avoid overfitting of the KNN model. Root - mean - squared error (RMSE) and determination coefficient (R2) were used as the performance metrics for models’ evaluation and comparison purposes. The results indicated that the KNN model yielded better superior performance than those of the USBM empirical model with an RMSE of 1.157 and R2 of 0.967. In contrast, the USBM model only provided a weak performance with an RMSE of 4.205 and R2 of 0.416. With the obtained results, the KNN can be introduced as a potential artificial intelligence model for predicting and controlling blast - induced ground vibration in practical engineering, especially at the Deo Nai open - pit coal mine.

conservatism 105; referendum 103, tactility 7, 40, 104, 121–22; haptic space 106; separation 99; sovereignty 49, 110–11; interactive 10; association 105–6; speech of de interface 8; telephasis 89, 94 Gaulle 100; see also gaps in television 2, 7, 41, 54, 56–7, 63, 67, historical experience 87, 92, 122; écriture télévisuelle 43; tv object 93; in France 45–7; signals racism 108–9 48; primal time 53; Société nationale Régie française de publicité (RFP) 46 de télévision de la première chaîne reification 112–15; and contemplative (TF1) 44; tele-vision 87 attitude 115 theatre 83, 120; electric 101 reversibility 94–5 transinteractivity 11–12 Rome 4, 13 translation 118–20; and table of conversions 25–6 tribalism 4, 19, 41, 102; Africa 93, 108; schizophrenia 49, 112; and Afro-Americans 108–9; as archaic postmodernity 65 thought 107; like the Beatles 5, 103; science fiction 79, 121 different 106; drum 107–8; ear 107; semioclasty 75 exotic 106–7; electric 116; French semiologue 75 Canadian 5, 92; good savage 110; semiotrophy 76 and hippies 100, 106; liberalism 103; semiurgy 8, 64, 69–73, 76, 81, 86; and Native Americans 108–9; New Age artistic strategy 36, 74; as 109; retribalize 4, 116; savages 100; manipulation of signs 66; and territorialization 105 massage 8, 64, 68–9, 72; and metallurgy 71; pan-sémie 73; radical 65–8; media 68; -urgies/-logies 74 University of Nottingham 40 silent majorities 3 University of Toronto 8, 16, 34; simulacra 67, 85, 99, 112; simulacrum McLuhan Program in Culture and 3, 91; hyperreality 67, 70, 100; Technology 9, 11 orders 90–1, 112–13, 115 Situationist 83, 114 Virtual Reality Artists’ Access Program space studies 110–11; acoustic space (VRAAP) 10 7, 40, 51 virtual technology 71; and tactility 11 spectacle 12, 83 structuralism 18–20, 22, 25–6, 31, 25, war 3–4, 16–17, 26, 101; speed and 75; McLuhan as amateur implosion 95–7 structuralist 22; poststructuralism 38, 48 style 22–5 x-ray 26; see also figure and ground surfing 9 surrealism 58 year 2000 99, 103; see also pataphysics symbolic exchange 78–80, 85–6, York University 40 109–10, 112

2002 ◽  
pp. 150-150
Keyword(s):  
Virtual Reality ◽  
Native Americans ◽  
Science Fiction ◽  
New Age ◽  
Virtual Technology ◽  
University Of Toronto ◽  
Symbolic Exchange ◽  
Acoustic Space ◽  
Year 2000 ◽  
Access Program

scholarly journals Incident forecasting model for motorcycle driving based on IoT and artificial intelligence

2021 ◽  
Vol 24 (1) ◽  
pp. 444
Author(s):  
Esteban Alejandro Cárdenas-Lancheros ◽  
Nelson Enrique Vera-Parra
Keyword(s):  
Artificial Intelligence ◽  
Nearest Neighbors ◽  
Forecasting Model ◽  
Accident Risk ◽  
Classification Models ◽  
Road Accidents ◽  
K Nearest Neighbors ◽  
Accelerometer Sensor ◽  
Technological Tools ◽  
And Storage

Internet of things (IoT) and artificial intelligence provide more and more solutions to the exercise of capturing data effectively, taking them through processing and analysis stages to extract valuable information. Currently, technological tools are applied to counteract incidents in motorcycle driving, whether they are part of the same vehicle or are externally involved in the environment. Incidents in motorcycle driving are increasing due to the demand for the acquisition of these vehicles, which makes it important to generate an approach towards reducing the risk of road accidents based on the analysis of dynamic behavior while driving. The development of this research began with the detection and storage of data associated with the dynamic acceleration variable of a motorcycle while driving, this with the help of a 3-axis accelerometer sensor generating a dataset, which was processed and analyzed for later be taken by three predictive classification models based on machine learning which were decision trees, K-Nearest neighbors and random forests. The performance of each model was evaluated in the task of better classifying the level of accident risk, concerning the driving style based on certain levels of acceleration. The random forest model showed a slightly better performance compared to that shown by the other two models, with 97.24% accuracy and recall, 97.16% precision and 97.17% F1 score.

scholarly journals Embedded VR Video Image Control System in the Ideological and Political Teaching System Based on Artificial Intelligence

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Fengzhen Jia ◽  
Shiqiang Xu ◽  
Jiaofei Huo
Keyword(s):  
Artificial Intelligence ◽  
Virtual Reality ◽  
Control System ◽  
Performance Optimization ◽  
Control Algorithm ◽  
Detection Algorithm ◽  
Video Image ◽  
Teaching System ◽  
Multimedia Teaching ◽  
Video Images

With the increasing development of multimedia teaching, the combination of virtual reality (VR) and video image control has very attractive development prospects in ideological and political teaching, for example, the use of virtual technology in games and so on. However, most virtual reality environments are currently built, and the functional development of artificial intelligence multimedia teaching systems is not comprehensive. An artificial intelligence VR video image control system is constructed for the multimedia teaching system. This article analyzes the development of artificial intelligence multimedia teaching systems and compares the detection performance and efficiency of traditional methods and artificial intelligence multimedia VR ideological and political teaching. Research shows that, in the use of VR to control the images of ideological and political teaching, the average accuracy of these ten video images is 75.68%. This shows that the video image classification and detection algorithm model based on artificial intelligence in this paper can extract deeper and more abstract features to classify the target. The artificial intelligence VR video image control algorithm constructed in this paper can reduce the maximum failure rate by 49.16%, 61.02%, and 66.94%, respectively. Compared with the traditional algorithm, the artificial intelligence VR video image control algorithm constructed in this paper can reduce the storage access delay time of 10 different video images by an average of 15.93%, can obtain about 9.37% performance optimization, and can reduce the video image control time by 7.28% and 10.63%, respectively. For pictures, the artificial intelligence VR video image control system in this article can increase the performance by up to 28.49%.

Boundary Points De-Noising and Simplification Based on Spatial Connectivity

2013 ◽  
Vol 392 ◽  
pp. 815-819
Author(s):  
Wei Zhu ◽  
Fang Di ◽  
Jian Li Li ◽  
Li Tian
Keyword(s):  
Uniform Distribution ◽  
Point Cloud ◽  
Grid Method ◽  
Nearest Neighbors ◽  
Experimental Result ◽  
K Nearest Neighbors ◽  
Spatial Connectivity ◽  
Boundary Points ◽  
Spatial Topology ◽  
Relationship Of

A de-noising and simplification approach based on spatial connectivity is proposed which is applied to deal with the boundary points of point cloud. First, grid method is used to represent the spatial topology relationship of the scattered point cloud and calculate the k-nearest neighbors for each data point. Then boundary points are extracted according to uniform distribution of point cloud. And next, an algorithm for boundary points simplification of point cloud is presented to further simplify boundary points. Consequently, not only the details characteristics are reserved well, but also the boundary points are simplified. The experimental result shows that the proposed approach can not only reserve characteristics of both details and boundaries but also realize de-noising and simplification of point cloud.

scholarly journals Capital as Artificial Intelligence

2015 ◽  
Vol 49 (4) ◽  
pp. 685-709 ◽  
Author(s):  
GERRY CANAVAN
Keyword(s):  
Artificial Intelligence ◽  
Short Stories ◽  
Cold War ◽  
Science Fiction ◽  
Financial Markets ◽  
Final Section ◽  
Global Capitalism ◽  
Player Piano ◽  
American Science ◽  
The Cold War

This article examines science-fictional allegorizations of Soviet-style planned economies, financial markets, autonomous trading algorithms, and global capitalism writ large as nonhuman artificial intelligences, focussing primarily on American science fiction of the Cold War period. Key fictional texts discussed include Star Trek, Isaac Asimov's Machine stories, Terminator, Kurt Vonnegut's Player Piano (1952), Charles Stross's Accelerando (2005), and the short stories of Philip K. Dick. The final section of the article discusses Kim Stanley Robinson's novel 2312 (2012) within the contemporary political context of accelerationist anticapitalism, whose advocates propose working with “the machines” rather than against them.

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