scholarly journals Recent Advances in Blockchain and Artificial Intelligence Integration: Feasibility Analysis, Research Issues, Applications, Challenges, and Future Work

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Zhonghua Zhang ◽  
Xifei Song ◽  
Lei Liu ◽  
Jie Yin ◽  
Yu Wang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Research Work ◽  
Three Dimensional ◽  
Large Data ◽  
Point Of View ◽  
Point System ◽  
Research Issues ◽  
Artificial Intelligence Technology ◽  
Point To Point ◽  
Future Work

Blockchain constructs a distributed point-to-point system, which is a secure and verifiable mechanism for decentralized transaction validation and is widely used in financial economy, Internet of Things, large data, cloud computing, and edge computing. On the other hand, artificial intelligence technology is gradually promoting the intelligent development of various industries. As two promising technologies today, there is a natural advantage in the convergence between blockchain and artificial intelligence technologies. Blockchain makes artificial intelligence more autonomous and credible, and artificial intelligence can prompt blockchain toward intelligence. In this paper, we analyze the combination of blockchain and artificial intelligence from a more comprehensive and three-dimensional point of view. We first introduce the background of artificial intelligence and the concept, characteristics, and key technologies of blockchain and subsequently analyze the feasibility of combining blockchain with artificial intelligence. Next, we summarize the research work on the convergence of blockchain and artificial intelligence in home and overseas within this category. After that, we list some related application scenarios about the convergence of both technologies and also point out existing problems and challenges. Finally, we discuss the future work.

Research on the university intelligent learning analysis system based on AI

2021 ◽  
pp. 1-10
Author(s):  
Meng Huang ◽  
Shuai Liu ◽  
Yahao Zhang ◽  
Kewei Cui ◽  
Yana Wen
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Academic Performance ◽  
Clustering Algorithm ◽  
Back Propagation ◽  
Three Dimensional ◽  
Training Model ◽  
Future Trend ◽  
Artificial Intelligence Technology ◽  
Visualization Technology

The integration of Artificial Intelligence technology and school education had become a future trend, and became an important driving force for the development of education. With the advent of the era of big data, although the relationship between students’ learning status data was closer to nonlinear relationship, combined with the application analysis of artificial intelligence technology, it could be found that students’ living habits were closely related to their academic performance. In this paper, through the investigation and analysis of the living habits and learning conditions of more than 2000 students in the past 10 grades in Information College of Institute of Disaster Prevention, we used the hierarchical clustering algorithm to classify the nearly 180000 records collected, and used the big data visualization technology of Echarts + iView + GIS and the JavaScript development method to dynamically display the students’ life track and learning information based on the map, then apply Three Dimensional ArcGIS for JS API technology showed the network infrastructure of the campus. Finally, a training model was established based on the historical learning achievements, life trajectory, graduates’ salary, school infrastructure and other information combined with the artificial intelligence Back Propagation neural network algorithm. Through the analysis of the training resulted, it was found that the students’ academic performance was related to the reasonable laboratory study time, dormitory stay time, physical exercise time and social entertainment time. Finally, the system could intelligently predict students’ academic performance and give reasonable suggestions according to the established prediction model. The realization of this project could provide technical support for university educators.

scholarly journals Tweaking Business Planning With Artificial Intelligence

2021 ◽  
Vol 2 (4) ◽  
pp. 1-22
Author(s):  
Jing Rui Chen ◽  
P. S. Joseph Ng
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Data Analysis ◽  
Learning Experience ◽  
Compulsory Education ◽  
Large Data ◽  
Data Sets ◽  
Chinese Market ◽  
Artificial Intelligence Technology ◽  
Education Support

Griffith AI&BD is a technology company that uses big data platform and artificial intelligence technology to produce products for schools. The company focuses on primary and secondary school education support and data analysis assistance system and campus ARTIFICIAL intelligence products for the compulsory education stage in the Chinese market. Through big data, machine learning and data mining, scattered on campus and distributed systems enable anyone to sign up to join the huge data processing grid, and access learning support big data analysis and matching after helping students expand their knowledge in a variety of disciplines and learning and promotion. Improve the learning process based on large data sets of students, and combine ai technology to develop AI electronic devices. To provide schools with the best learning experience to survive in a competitive world.

scholarly journals Application of modern 3d image acquisition systems to the morphological analysis of faces: a novel approach for the assessment of facial growth

2020 ◽  
Vol 7 (4) ◽  
pp. 268-273
Author(s):  
Gibelli Daniele Maria ◽  
◽  
Poppa Pasquale ◽  
Cappella Annalisa ◽  
Rosati Riccardo ◽  
...  
Keyword(s):  
Morphological Analysis ◽  
Three Dimensional ◽  
Laser Scanner ◽  
3D Models ◽  
Point Of View ◽  
Topographic Map ◽  
Facial Growth ◽  
General Increase ◽  
Novel Approach ◽  
Point To Point

Introduction The assessment of facial growth has always had a relevant importance in anatomy and morphological sciences. This article aims at presenting a method of facial superimposition between 3D models which provides a topographic map of those facial areas modified by growth. Methodology Eight children aged between 6 and 10 years were recruited. In December 2010 they underwent a 3D scan by the Vivid 910 laser scanner (Konica Minolta, Osaka, Japan). The same procedures were performed another five times, in June 2011, September 2011, January 2012 and September 2012; in total 6 analyses were performed on the same subjects in a time span of 21 months. Three-dimensional digital models belonging to the same individual were then superimposed on each other according to 11 facial landmarks. Three comparisons were performed for each individual, referring to the period between December 2010 and June 2011, between June 2011 and January 2012 and between January and September 2012. Results Results show that the protocol of superimposition gives a reliable image of facial growth with high sensibility: in detail, even the slight facial modifications due to different expressions are recorded. The method can also quantify the point-to-point difference between the two models, and therefore give an indication concerning the general increase or decrease of facial volume. Conclusion This approach may provide useful indications for the analysis of facial growth on a large sample and give a new point of view of the complex field of face development.

scholarly journals Risks and Ethical-Legal Models of Using Artificial Intelligence Systems

2019 ◽  
pp. 1-11
Author(s):  
Dmitrii V. Bakhteev
Keyword(s):  
Artificial Intelligence ◽  
Autonomous Vehicles ◽  
Code Of Ethics ◽  
Personal Data ◽  
Point Of View ◽  
Negative Consequences ◽  
Weapon Systems ◽  
Intelligence Studies ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Systems

The matter under research of the legal patterns of interaction between the society and individuals and artificial intelligence technologies. Elements of the matter under research is the technological grounds for functioning of artificial intelligence systems, potential risks and negative consequences of using this technology based on the example of intellectual processing personal data and autonomous vehicles and weapon systems, ethical and legal approaches to its regulation. Bakhteev analyzes approaches to describing positions of artificial intelligence systems and whether these systems have personalities and thus certain rights. The research is based on the method of modelling that is used to describe stages of ethical-legal research of artificial intelligence technology. The author also describes different kinds of responses of the society to the development of the aforesaid technology. The main conclusions of the research is the description of stages of artificial intelligence studies, in particular, analysis of the technology itself, associated risks and responses of the society and creation of ethical and then legal grounds for regulation of this technology. The author gives the results of the analysis of possible ethical-legal models of subjectivity of artificial intelligence systems from the point of view of the need and possibility to grant them certain rights. These models include instrumental, tolerant, xenophobic and empathetic. The author also states the main provisions of the code of ethics for developer and user of artificial intelligence systems. 

scholarly journals Artificial Intelligence and the Use of Databases as Related Rights Objects

Lex Russica ◽  
2020 ◽  
pp. 62-69
Author(s):  
N. V. Buzova
Keyword(s):  
Artificial Intelligence ◽  
Personal Data ◽  
Large Data ◽  
Third Parties ◽  
High Tech ◽  
Intellectual Activity ◽  
Strong Artificial Intelligence ◽  
Short Period ◽  
Artificial Intelligence Technology ◽  
Legitimate Interests

The development of digital technologies and creation of high-tech services constitute one of the directions of strategic development of Russia. Modern technologies are already capable of searching, systematizing and analyzing large data amounts within a short period of time. But the state sets additional tasks: to process and synthesize speech, to prepare analytical materials for making complex decisions, to perform tasks at the level of results achieved by a human being, to train and even automatically self-learn and eventually create a “strong” artificial intelligence. Adopted legal acts and legal acts under consideration define the main objectives, tasks and expected results to be achieved through the application of artificial intelligence technology in the immediate period. However, the application of artificial intelligence technology raises additional questions related to the creation of new technical solutions and works and the application of the protected results of intellectual activity, exclusive rights to which belong to third parties. The search for data for further analysis is carried out, inter alia, in databases that are objects of related rights, limited access to which is provided through information and telecommunications Internet network. In this regard, the lawfulness of such search and processing of information from protected databases requires clarification. The paper gives examples of judicial practice that show the difficulty of establishing and proving the fact of using materials from databases accessed through high-tech services. The paper also identifies the risks of violation of the rights and legitimate interests of third parties whose personal data are posted in databases that can be accessed via the Internet.

Automated 3-D cell population analysis in thick tissue sections using laser-scanning confocal-microscopy data

1993 ◽  
Vol 51 ◽  
pp. 562-563
Author(s):  
Hakan Ancin
Keyword(s):  
Laser Scanning ◽  
Population Analysis ◽  
Three Dimensional ◽  
Large Data ◽  
Laser Scanning Confocal Microscopy ◽  
Tissue Slices ◽  
Scanning Confocal Microscopy ◽  
Tissue Sections ◽  
Spatially Adaptive ◽  
Microscopy Data

This paper presents methods for performing detailed quantitative automated three dimensional (3-D) analysis of cell populations in thick tissue sections while preserving the relative 3-D locations of cells. Specifically, the method disambiguates overlapping clusters of cells, and accurately measures the volume, 3-D location, and shape parameters for each cell. Finally, the entire population of cells is analyzed to detect patterns and groupings with respect to various combinations of cell properties. All of the above is accomplished with zero subjective bias.In this method, a laser-scanning confocal light microscope (LSCM) is used to collect optical sections through the entire thickness (100 - 500μm) of fluorescently-labelled tissue slices. The acquired stack of optical slices is first subjected to axial deblurring using the expectation maximization (EM) algorithm. The resulting isotropic 3-D image is segmented using a spatially-adaptive Poisson based image segmentation algorithm with region-dependent smoothing parameters. Extracting the voxels that were labelled as "foreground" into an active voxel data structure results in a large data reduction.

GROUNDWATER TIME SERIES

1970 ◽  
Vol 1 (3) ◽  
pp. 181-205 ◽  
Author(s):  
ERIK ERIKSSON
Keyword(s):  
Time Series ◽  
Point Of View ◽  
Hydrologic Models ◽  
Physical Point ◽  
Run Off ◽  
Fort Collins ◽  
Statistical Sense ◽  
Full Benefit ◽  
Future Work ◽  
Prediction Problems

The term “stochastic hydrology” implies a statistical approach to hydrologic problems as opposed to classic hydrology which can be considered deterministic in its approach. During the International Hydrology Symposium, held 6-8 September 1967 at Fort Collins, a number of hydrology papers were presented consisting to a large extent of studies on long records of hydrological elements such as river run-off, these being treated as time series in the statistical sense. This approach is, no doubt, of importance for future work especially in relation to prediction problems, and there seems to be no fundamental difficulty for introducing the stochastic concepts into various hydrologic models. There is, however, some developmental work required – not to speak of educational in respect to hydrologists – before the full benefit of the technique is obtained. The present paper is to some extent an exercise in the statistical study of hydrological time series – far from complete – and to some extent an effort to interpret certain features of such time series from a physical point of view. The material used is 30 years of groundwater level observations in an esker south of Uppsala, the observations being discussed recently by Hallgren & Sands-borg (1968).

Innovative Marketing Strategies for Select E-Commerce Companies in India - A Review.

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Amit Kumar Bhanja ◽  
P.C Tripathy
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Business Environment ◽  
Marketing Strategies ◽  
Point Of View ◽  
Digital Marketing ◽  
Customer Base ◽  
Innovative Methods ◽  
Online Shoppers ◽  
Drastic Increase

Innovation is the key to opportunities and growth in today’s competitive and dynamic business environment. It not only nurtures but also provides companies with unique dimensions for constant reinvention of the existing way of performance which enables and facilitates them to reach out to their prospective customers more effectively. It has been estimated by Morgan Stanley that India would have 480 million shoppers buying products online by the year 2026, a drastic increase from 60 million online shoppers in the year 2016. E-commerce companies are aggressively implementing innovative methods of marketing their product offerings using tools like digital marketing, internet of things (IoT)and artificial intelligence to name a few. This paper focuses on outlining the innovative ways of marketing that the E-Commerce sector implements in orders to increase their customer base and aims at determining the future scope of this area. A conceptual comparative study of Amazon and Flipkart helps to determine which marketing strategies are more appealing and beneficial for both the customers and companies point of view.

Sign in / Sign up

Export Citation Format

Share Document