Biblio

Due to its decentralized trust mechanism, blockchain is increasingly used as a trust intermediary for multi-party cooperation to reduce the cost and risk of maintaining centralized trust nowadays. And as the requirements for privacy and high throughput, consortium blockchain is widely used in data sharing and business cooperation in practical application scenarios. Nowadays, the protection of traditional medicine has been regarded as human intangible cultural heritage in recent years, but this kind of protection still faces the problem that traditional medicine prescriptions are unsuitable for disclosure and difficult to protect. Hyperledger is a consortium blockchain featuring authorized access, high throughput, and tamper-resistance, making it ideal for privacy protection and information depository in traditional medicine protection. This study proposes a solution for intellectual property protection of traditional medicine by using a blockchain platform to record prescription iterations and clinical trial data. The privacy and confidentiality of Hyperledger can keep intellectual property information safe and private. In addition, the author proposes to invite the Patent Offices and legal institutions to join the blockchain network, maintain users' properties and issue certificates, which can provide a legal basis for rights protection when infringement occurs. Finally, the researchers have built a system corresponding to the scheme and tested the system. The test outcomes of the system can explain the usability of the system. And through the test of system throughput, under low system configuration, it can reach about 200 query operations per second, which can meet the application requirements of relevant organizations and governments.

The goals, objectives and criteria of the effectiveness of the creation, maintenance and use of the Digital Information Fund of Intellectual Property (DIFIP) are considered. A formalized methodology is proposed for designing DIFIPs, increasing its efficiency and quality, based on a set of interconnected models, methods and algorithms for analysis, synthesis and normalization distributed information management of DIFIP's structure; classification of databases users of patent and scientific and technical information; synthesis of optimal logical structures of the DIFIP database and thematic databases; assessing the quality of the database and ensuring the required level of data security.

Intellectual Property Rights (IPR) results from years of research and wisdom by property owners, and it plays an increasingly important role in promoting economic development, technological progress, and cultural prosperity. Thus, we need to strengthen the degree of protection of IPR. However, as internet technology continues to open up the market for IPR, the ease of network operation has led to infringement of IPR in some cases. Intellectual property infringement has occurred in some cases. Also, Internet development's concealed and rapid nature has led to the fact that IPR infringers cannot be easily detected. This paper addresses how to protect the rights and interests of IPR holders in the context of the rapid development of the internet. This paper explains the IPR and proposes an algorithm to enhance security for a better security model to protect IPR. This proposes optimization techniques to detect intruder attacks for securing IPR, by using support vector machines (SVM), it provides better results to secure public and private intellectual data by optimizing technologies.

It is common to certify when a file was created in digital investigations, e.g., determining first inventors for patentable ideas in intellectual property systems to resolve disputes. Secure time-stamping schemes can be derived from blockchain-based storage to protect files from backdating/forward-dating, where a file is integrated into a transaction on a blockchain and the timestamp of the corresponding block reflects the latest time the file was created. Nevertheless, blocks' timestamps in blockchains suffer from time errors, which causes the inaccuracy of files' timestamps. In this paper, we propose an accurate blockchain-based time-stamping scheme called Chronos. In Chronos, when a file is created, the file and a sufficient number of successive blocks that are latest confirmed on blockchain are integrated into a transaction. Due to chain quality, it is computationally infeasible to pre-compute these blocks. The time when the last block was chained to the blockchain serves as the earliest creation time of the file. The time when the block including the transaction was chained indicates the latest creation time of the file. Therefore, Chronos makes the file's creation time corresponding to this time interval. Based on chain growth, Chronos derives the time when these two blocks were chained from their heights on the blockchain, which ensures the accuracy of the file's timestamp. The security and performance of Chronos are demonstrated by a comprehensive evaluation.

Firms collaborate with partners in research and development (R&D) of new technologies for many reasons such as to access complementary knowledge, know-how or skills, to seek new opportunities outside their traditional technology domain, to sustain their continuous flows of innovation, to reduce time to market, or to share risks and costs [1]. The adoption of collaborative research agreements (CRAs) or collaboration agreements (CAs) is rising rapidly as firms attempt to access innovation from various types of organizations to enhance their traditional in-house innovation [2], [3]. To achieve the objectives of their collaborations, firms need to share knowledge and jointly develop new knowledge. As more firms adopt open collaborative innovation strategies, intellectual property (IP) management has inevitably become important because clear and fair contractual IP terms and conditions such as IP ownership allocation, licensing arrangements and compensation for IP access are required for each collaborative project [4], [5]. Moreover, the firms need to adjust their IP management strategies to fit the unique characteristics and circumstances of each particular project [5].

Trademarks are recognizable images and/or words used to distinguish various products or services. They become associated with the reputation, innovation, quality, and warranty of the products. Countries around the world have offices for industrial/intellectual property (IP) registration. A new trademark image in application for registration should be distinct from all the registered trademarks. Due to the volume of trademark registration applications and the size of the databases containing existing trademarks, it is impossible for humans to make all the comparisons visually. Therefore, technological tools are essential for this task. In this work we use a pre-trained, publicly available Convolutional Neural Network (CNN) VGG19 that was trained on the ImageNet database. We adapted the VGG19 for the trademark image retrieval (TIR) task by fine tuning the network using two different databases. The VGG19v was trained with a database organized with trademark images using visual similarities, and the VGG19c was trained using trademarks organized by using conceptual similarities. The database for the VGG19v was built using trademarks downloaded from the WEB, and organized by visual similarity according to experts from the IP office. The database for the VGG19c was built using trademark images from the United States Patent and Trademarks Office and organized according to the Vienna conceptual protocol. The TIR was assessed using the normalized average rank for a test set from the METU database that has 922,926 trademark images. We computed the normalized average ranks for VGG19v, VGG19c, and for a combination of both networks. Our method achieved significantly better results on the METU database than those published previously.

The aim of this work is to perform an analysis on Technology Transfer strategies for the development of Serious Games at Public National Universities. The results can be extrapolated to other research topics and institutions. First of all, the University role as a producer of knowledge is studied, and possible scenarios for Technology Transfer to third-parties are considered. Moreover, the actors involved in the research and development processes and their corresponding Intellectual Property rights on the Research Results are identified and analysed. Finally, an Intellectual Property Rights protection analysis is undertaken to the different components of a Serious Game type of product, through the modalities of invention patents, utility models, industrial models and designs, brands and author rights. The work concludes that public universities are best fitted as knowledge factories, and the most promising scenario in Technology Transfer is that universities manage their Intellectual Property Rights and licence them to third-party institutions to handle commercialization, while keeping favorable conditions to finance subsequent research and ensuring that products derived from Research Results will be reachable by the society.

To increase the possibility of patent entitled of artificial intelligence related inventions at the Japanese patent office, this paper analyzes the Japanese patent act and patent examination guidelines. The approach for assessing whether a computer related invention belongs to a eligible subject-matter includes two steps. The first step is whether a computer related invention meets the definition of an "invention" that is "creation of a technical idea utilizing the laws of nature" . The second step is whether a computer related invention meets "idea based on the standpoint of software" . From the perspective of patent analysis, Japan's artificial intelligence technology is leading the world, second only to the United States. In this field, the Japanese patent office is one of the most important intellectual property offices, and its legislation and practice of patent eligibility review for artificial intelligence related inventions have an important impact on the world.

The work defines a multi-factor authentication model in case the application supports multiple authentication factors. The aim of this modeling is to find acceptable authentication methods sufficient to access specifically qualified information. The core of the proposed model is risk-based authentication. Results of simulations of some key scenarios often used in practice are also presented.

The method of choice the control parameters of a complex system based on estimates of the risks is proposed. The procedure of calculating the estimates of risks intended for a choice of rational managing directors of influences by an allocation of the group of the operating factors for the set criteria factor is considered. The purpose of choice of control parameters of the complex system is the minimization of an estimate of the risk of the functioning of the system by mean of a solution of a problem of search of an extremum of the function of many variables. The example of a choice of the operating factors in the sphere of intangible assets is given.

Intellectual property is inextricably linked to the innovative development of mass innovation spaces. The synthetic development of intellectual property and mass innovation spaces will fundamentally support the new economic model of “mass entrepreneurship and innovation”. As such, it is critical to explore intellectual property service standards for mass innovation spaces and to steer mass innovation spaces to the creation of an intellectual property service system catering to “makers”. In addition, it is crucial to explore intellectual cluster management innovations for mass innovation spaces.

Keeping up with rapid advances in research in various fields of Engineering and Technology is a challenging task. Decision makers including academics, program managers, venture capital investors, industry leaders and funding agencies not only need to be abreast of latest developments but also be able to assess the effect of growth in certain areas on their core business. Though analyst agencies like Gartner, McKinsey etc. Provide such reports for some areas, thought leaders of all organisations still need to amass data from heterogeneous collections like research publications, analyst reports, patent applications, competitor information etc. To help them finalize their own strategies. Text mining and data analytics researchers have been looking at integrating statistics, text analytics and information visualization to aid the process of retrieval and analytics. In this paper, we present our work on automated topical analysis and insight generation from large heterogeneous text collections of publications and patents. While most of the earlier work in this area provides search-based platforms, ours is an integrated platform for search and analysis. We have presented several methods and techniques that help in analysis and better comprehension of search results. We have also presented methods for generating insights about emerging and popular trends in research along with contextual differences between academic research and patenting profiles. We also present novel techniques to present topic evolution that helps users understand how a particular area has evolved over time.