scholarly journals Mode Optimization and Rule Management of Intellectual Property Rights Protection of Educational Resource Data Based on Machine Learning Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jiawei Cao
Keyword(s):  
Machine Learning ◽  
Intellectual Property ◽  
Learning Objects ◽  
Current Status ◽  
Educational Resource ◽  
Learning Technology ◽  
Rule Management ◽  
Intellectual Property Rights Protection ◽  
Study Results ◽  
Resource Data

Educational resource data are a collection of final documents obtained by users, including full-text journals, books, dissertations, newspapers, conference papers, and other database materials. While searching for information in the educational resource database, these resources also have functions such as copying, downloading, reproduction, and dissemination, which raise the issue of expression and protection of intellectual property. Machine learning takes how computers simulate human learning behaviors as the main research content, which can independently determine learning objects, construct their characteristics, perform additional operations beyond the limitations of preset instructions, and discover value from the expression of relative works. On the basis of summarizing and analyzing previous research works, this paper expounded the current research status and significance of intellectual property expression and protection of educational resource data; elaborated the development background, current status, and future challenges of machine learning technology; introduced the methods and principles of data classification algorithm and protection authority identification; performed the technical framework design and expression system establishment of the intellectual property expression of educational resource data based on machine learning; analyzed the mode optimization and rule management of intellectual property protection of educational resource data based on machine learning; and finally conducted a simulation experiment and its result analysis. The results show that the machine learning technology can build a subject-oriented, highly integrated, and time-changing educational resource data storage environment; the comprehensive, analysis-oriented decision-supporting system formed by machine learning can give full play to the potential role of data integration and value discovery and is therefore of great significance for the intellectual property expression and protection of integrated and complexly-related educational resource data. The study results of this paper provide a reference for further research on the intellectual property expression and protection of educational resource data based on machine learning.

scholarly journals Smart Grids and Machine Learning in Chinese and Western Intellectual Property Law

2021 ◽  
Author(s):  
Stefan Papastefanou
Keyword(s):  
Machine Learning ◽  
Intellectual Property ◽  
Smart Grids ◽  
Power Grids ◽  
Learning Technology ◽  
Property Law ◽  
Intellectual Property Law ◽  
Smart Systems ◽  
Basic Functions ◽  
The Right

AbstractHaving huge power grids successfully integrate sustainable energy sources requires a smart and flexible power grid management system. Such smart systems have to adapt fast and accurately to a great amount of data input – a task which is made easier by applying modern machine learning technology. Solutions crafted by dynamic and powerful computing algorithms have the potential to surpass human cognitive capabilities. The question arises whether and how intellectual property law can be used to set the right incentives. This paper initially describes the basic functions of smart grids and the corresponding necessity of machine learning. Subsequently, it will analyze the current approaches of the most relevant patent offices in dealing with the challenges of AI-related smart grid inventions. Ultimately, it will be demonstrated that the contemporary discussions fail to focus on practical considerations of market entry possibilities that might be more promising than the approach of creating new exclusionary intellectual property rights.

scholarly journals Applications of Machine Learning to Imaging of Spinal Disorders: Current Status and Future Directions

2021 ◽  
Vol 11 (1_suppl) ◽  
pp. 23S-29S
Author(s):  
Zamir A. Merali ◽  
Errol Colak ◽  
Jefferson R. Wilson
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Spine Surgery ◽  
Human Performance ◽  
Automated Analysis ◽  
Learning Technologies ◽  
Current Status ◽  
Learning Technology ◽  
Spinal Disorders ◽  
Pubmed Database

Study Design: Narrative review. Objectives: We aim to describe current progress in the application of artificial intelligence and machine learning technology to provide automated analysis of imaging in patients with spinal disorders. Methods: A literature search utilizing the PubMed database was performed. Relevant studies from all the evidence levels have been included. Results: Within spine surgery, artificial intelligence and machine learning technologies have achieved near-human performance in narrow image classification tasks on specific datasets in spinal degenerative disease, spinal deformity, spine trauma, and spine oncology. Conclusion: Although substantial challenges remain to be overcome it is clear that artificial intelligence and machine learning technology will influence the practice of spine surgery in the future.

EFFICIENCY IMPROVEMENT OF ROAD SURFACE INSPECTION USING MACHINE LEARNING TECHNOLOGY

2017 ◽  
Vol 73 (2) ◽  
pp. I_409-I_415
Author(s):  
Naoko FUKUSHI ◽  
Daishiro KOBAYASHI ◽  
Seiji IWAO ◽  
Ryosuke KASAHARA ◽  
Nobuyoshi YABUKI
Keyword(s):  
Machine Learning ◽  
Road Surface ◽  
Surface Inspection ◽  
Learning Technology ◽  
Efficiency Improvement

From Market Access to Cumulative Innovation

2017 ◽  
Author(s):  
Adrian Kuenzler
Keyword(s):  
Intellectual Property ◽  
Market Access ◽  
Step Test ◽  
Property Law ◽  
Intellectual Property Law ◽  
Rights Protection ◽  
Intellectual Property Rights Protection ◽  
Property Rights Protection ◽  
Production Output

This chapter argues for a reinvigorated role of the market access doctrine and references a number of important antitrust and intellectual property law decisions in which courts have given priority to market access. It finds a novel function for market access to play within antitrust and intellectual property law liability: courts that grant plaintiffs access to a defendant’s production output should refer to a three-step test under which they inquire (1) whether the inventor, through first-mover advantages, has reaped a sufficient reward such that contractual or intellectual property rights protection would no longer be required to facilitate innovation, (2) whether competitors were able to challenge the proprietary platform’s position in the market without the possibility of granting access, and (3) whether competitors seeking to benefit from market access will make use of it to facilitate the introduction of new goods rather than merely to copy the initial invention.

Protecting User Interfaces

2017 ◽  
Author(s):  
Noam Shemtov
Keyword(s):  
Intellectual Property ◽  
Property Rights ◽  
Intellectual Property Rights ◽  
User Interfaces ◽  
Patent Protection ◽  
The United States ◽  
Graphical User Interfaces ◽  
Unfair Competition ◽  
European Patent ◽  
Intellectual Property Rights Protection

This chapter examines the scope of protection to which graphical user interfaces may be eligible under various intellectual property rights: namely, trade marks, unfair-competition laws, design rights, copyright, and patents. It first considers the extent of copyright protection over a software product’s ‘look-and-feel’ elements, with particular emphasis on graphical user interfaces protection under US and EU laws. It then discusses trade-mark, trade-dress, and unfair-competition protection for graphical user interfaces, along with intellectual property rights protection for design patents and registered designs. Finally, it describes the patent protection for graphical user interfaces in the United States and at the European Patent Office.

scholarly journals Complex Dynamical Behaviors of a Mixed Duopoly Game Based on Intellectual Property Rights Protection

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Tong Chu ◽  
Yu Yu ◽  
Xiaoxue Wang
Keyword(s):  
Intellectual Property ◽  
Property Rights ◽  
Intellectual Property Rights ◽  
Mixed Duopoly ◽  
Fractal Structures ◽  
Rights Protection ◽  
Intellectual Property Rights Protection ◽  
Dynamical Behaviors ◽  
Property Rights Protection ◽  
Coexistence Of Attractors

Based on the oligopoly game theory and the intellectual property rights protection policy, we investigate the complex dynamical behaviors of a mixed duopoly game with quadratic cost. In the new system, a few parameters are improved by considering intellectual property rights protection and the stability conditions of the Nash equilibrium point are discussed in detail. A set of the two-dimensional bifurcation diagrams is demonstrated by using numerical modeling, and these diagrams show abundant complex dynamical behaviors, such as coexistence of attractors, different bifurcation, and fractal structures. These dynamical properties can present the long-run effects of strengthening intellectual property protection.

scholarly journals Feasibility of Using Floor Vibration to Detect Human Falls

2020 ◽  
Vol 18 (1) ◽  
pp. 200
Author(s):  
Yu Shao ◽  
Xinyue Wang ◽  
Wenjie Song ◽  
Sobia Ilyas ◽  
Haibo Guo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Human Body ◽  
Nearest Neighbor ◽  
Body Movement ◽  
Modern Society ◽  
Recognition System ◽  
Machine Learning Algorithms ◽  
K Nearest Neighbor ◽  
Study Results ◽  
Floor Vibration

With the increasing aging population in modern society, falls as well as fall-induced injuries in elderly people become one of the major public health problems. This study proposes a classification framework that uses floor vibrations to detect fall events as well as distinguish different fall postures. A scaled 3D-printed model with twelve fully adjustable joints that can simulate human body movement was built to generate human fall data. The mass proportion of a human body takes was carefully studied and was reflected in the model. Object drops, human falling tests were carried out and the vibration signature generated in the floor was recorded for analyses. Machine learning algorithms including K-means algorithm and K nearest neighbor algorithm were introduced in the classification process. Three classifiers (human walking versus human fall, human fall versus object drop, human falls from different postures) were developed in this study. Results showed that the three proposed classifiers can achieve the accuracy of 100, 85, and 91%. This paper developed a framework of using floor vibration to build the pattern recognition system in detecting human falls based on a machine learning approach.

scholarly journals Automobile tire life prediction based on image processing and machine learning technology

2021 ◽  
Vol 13 (3) ◽  
pp. 168781402110027
Author(s):  
Jianchen Zhu ◽  
Kaixin Han ◽  
Shenlong Wang
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Life Prediction ◽  
Traffic Accidents ◽  
Confusion Matrix ◽  
Small Sample ◽  
Image Feature ◽  
Engineering Practice ◽  
Learning Technology ◽  
K Nearest Neighbor

With economic growth, automobiles have become an irreplaceable means of transportation and travel. Tires are important parts of automobiles, and their wear causes a large number of traffic accidents. Therefore, predicting tire life has become one of the key factors determining vehicle safety. This paper presents a tire life prediction method based on image processing and machine learning. We first build an original image database as the initial sample. Since there are usually only a few sample image libraries in engineering practice, we propose a new image feature extraction and expression method that shows excellent performance for a small sample database. We extract the texture features of the tire image by using the gray-gradient co-occurrence matrix (GGCM) and the Gauss-Markov random field (GMRF), and classify the extracted features by using the K-nearest neighbor (KNN) classifier. We then conduct experiments and predict the wear life of automobile tires. The experimental results are estimated by using the mean average precision (MAP) and confusion matrix as evaluation criteria. Finally, we verify the effectiveness and accuracy of the proposed method for predicting tire life. The obtained results are expected to be used for real-time prediction of tire life, thereby reducing tire-related traffic accidents.

Analysis of Customer-Oriented Information for Tourism Enterprises Under the Social Media Environment

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ziwei Yang
Keyword(s):  
Social Media ◽  
Market Competition ◽  
Virtual Community ◽  
Current Status ◽  
Information Analysis ◽  
Value Analysis ◽  
Media Environment ◽  
The Social ◽  
Study Results ◽  
Tourism Enterprises

Abstract Social media is a virtual community or network platform that the public uses to achieve self-creation and it’s sharing with others; under the social media environment, self-media channels become more abundant, and the autonomy and originality of content dissemination are also continuously enhanced. When tourism enterprises face increasing market competition, personalized and targeted promotional programs will, to a certain extent, have a certain appeal to competitors’ potential customer groups, thereby providing tourism enterprise customers with relevant benefits for oriental information, and also serving as an important way for companies to develop new customers. Based on the summary and analysis of previous literature works, this paper expounded the research status and significance of social media environment, elaborated the development background, current status and future challenges of customer-oriented information analysis for tourism enterprises, introduced the methods and principles of customer’s transfer value and life cycle and social media environment’s cognitive composition, proposed a sentiment model of tourist-oriented information analysis under the social media environment, and analysed the management strategy and scheduling platform of customer-oriented information, constructed an analysis system of customer-oriented information in social media environment, performed the reliability, validity, transfer and perception value analysis of customer-oriented information and finally conducted case simulation and its result analysis. The study results of this paper provide a reference for further researches on the customer-oriented information analysis for tourism enterprises under the social media environment.

Sign in / Sign up

Export Citation Format

Share Document