scholarly journals Special Equipment Safety Supervision System Architecture Based on Blockchain Technology

2020 ◽  
Vol 10 (20) ◽  
pp. 7344
Author(s):  
Zhipeng Liang ◽  
Keping Zhou ◽  
Rugao Gao ◽  
Kaixin Gao
Keyword(s):  
System Architecture ◽  
New Technology ◽  
Special Equipment ◽  
Supervision System ◽  
Equipment Safety ◽  
Blockchain Technology ◽  
Efficient Data ◽  
Safety Accident ◽  
Technical Features ◽  
Future Work

With the use of the traditional safety supervision system of special equipment, the job burnout of supervision participants and other supervision problems emerge endlessly, which leads to the supervision for the prevention of safety accidents being greatly weakened. In recent years, the significance of introducing new technology to improve the original supervision system for safety accident prevention has been constantly growing. In this paper, based on the current situation of China’s special equipment safety supervision, we summarize several specific requirements for improving the supervision system, namely efficient accident responsibility tracing, more transparent, more efficient data sharing, and integrating more functions. On this basis, we have designed a new system architecture, by introducing the permissioned blockchain technology, which can meet all the improvement requirements and adapt to the technical features of safety supervision work. The extensibility design of the system architecture can meet the new requirements in future work. The design idea of the system architecture can not only be used in the field of special equipment, but can also be used for reference by other fields with safety supervision requirements.

Applications of blockchain in healthcare (Preprint)

2020 ◽  
Author(s):  
Pranav C
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Review Paper ◽  
New Technology ◽  
Personal Identification ◽  
Healthcare Industry ◽  
Healthcare Organizations ◽  
Paper Briefly ◽  
Blockchain Technology ◽  
Audit Trails

UNSTRUCTURED The word blockchain elicits thoughts of cryptocurrency much of the time, which does disservice to this disruptive new technology. Agreed, bitcoin launched in 2011 was the first large scale implementation of blockchain technology. Also, Bitcoin’s success has triggered the establishment of nearly 1000 new cryptocurrencies. This again lead to the delusion that the only application of blockchain technology is for the creation of cryptocurrency. However, the blockchain technology is capable of a lot more than just cryptocurrency creation and may support such things as transactions that require personal identification, peer review, elections and other types of democratic decision-making and audit trails. Blockchain exists with real world implementations beyond cryptocurrencies and these solutions deliver powerful benefits to healthcare organizations, bankers, retailers and consumers among others. One of the areas where blockchain technology can be used effectively is healthcare industry. Proper application of this technology in healthcare will not only save billions of money but also will contribute to the growth in research. This review paper briefly defines blockchain and deals in detail the applications of blockchain in various areas particularly in healthcare industry.

Accounting Information Systems in Public Sector towards Blockchain Technology Application: The Role of Accountants’ Emotional Intelligence in the Digital Age

2021 ◽  
Vol 12 (1) ◽  
pp. 73-94
Author(s):  
Pham Quang Huy ◽  
Vu Kien Phuc
Keyword(s):  
Emotional Intelligence ◽  
Public Sector ◽  
New Technology ◽  
Accounting Information ◽  
Accounting Information System ◽  
Accounting Information Systems ◽  
Technology Application ◽  
Public Sector Organization ◽  
Blockchain Technology ◽  
The Impact

Abstract This research ferreted out to inspect the interconnection between emotional intelligence (EI), Blockchain technology application (BLO) and the effectiveness of Accounting information system (AIS). Survey-based data obtained from 412 respondents were applied to validate the model hypotheses. Building on the statistical analysis with the support of SPSS 25.0 and SMART- PLS (partial least squares) 3.2.8 software package, the model results inferred the impact of EI on BLO. Besides, the outputs of the study accentuated on the importance of BLO on the effectiveness of AIS. These significant additions will optimistically inspire other scholars to carry on exploring the relationship between EI and BLO in enhancing the effectiveness of AIS in research settings as well as in explaining the results. On the other hand, taking these results into consideration could promote much better solutions for issues relevant to EI and new technology application among public sector organization (PSO) in term of increasing the performance of AIS.

Exploring sectoral diversity in the timing of organizational blockchain adoption

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Cigdem Turhan ◽  
Ibrahim Akman
Keyword(s):  
New Technology ◽  
Organizational Factors ◽  
Ease Of Use ◽  
Least Square ◽  
Management Support ◽  
Perceived Ease Of Use ◽  
Organizational Strategies ◽  
Content Type ◽  
Factors Affecting ◽  
Blockchain Technology

PurposeBlockchain is a relatively new technology. Although it has a high potential to influence organizational strategies for adoption into respective operations, it has not been widely explored yet. This study aims to assess the sectoral diversity in the timing of organizational adoption of blockchain through selected organizational factors.Design/methodology/approachA survey was conducted based on a sample of 208 IT professionals. The data was collected using an instrument containing 17 questions. The existence of sector diversity was statistically analyzed using the Least Square Regression method.FindingsThe results indicate that, except for management support and perceived ease of use, all the other factors in the analysis significantly influence sector diversity in terms of blockchain adoption timing.Originality/valueAlthough blockchain has received attention from researchers, to the best of the authors' knowledge, there is no published work in the literature that explores the organizational factors influencing sectoral differences in the timing of blockchain technology adoption. Therefore, our work is unique in the related literature since we present analyses for the diversity between public and private sectors by modeling the factors affecting the intentions for the timing of blockchain adoption as part of the organizations' IT infrastructure.

scholarly journals Intelligent Devices in Rural Wireless Networks

2014 ◽  
Vol 2 (4) ◽  
pp. 23-30
Author(s):  
Daniel Fuentes ◽  
Rosalía Laza ◽  
Antonio Pereira
Keyword(s):  
Wireless Networks ◽  
System Architecture ◽  
New Technologies ◽  
New Technology ◽  
Internet Access ◽  
Age Group ◽  
Experience Level ◽  
The World ◽  
Intelligent Devices ◽  
The Cost

The rural wireless networks are increasingly in demand by associations and autarchies to expand Internet access in this type of areas. The problem of such solutions centers not only in network deployment and its maintenance, but also in the equipment installation on clients, which always has big costs. This installation and configuration must be performed by a technician on site, so that the equipment can be integrated in the infrastructure. To try to mitigate this problem, it is presented a solution that allows the clients to install, with transparency, the device at home, reducing not only the cost for the management entity but also for the clients. This way, for info-excluded people or with new technology low experience level, it is the user that integrates himself in the network, making him part of the process, fostering the network usage.In this article are specified not only the system architecture but also the way that it works and how it obtains the desirable result. The tests made to the solution show the quickness, reliability and autonomy in the execution of the tasks, making it a benefit for rural wireless networks.This solution, by its robustness and simplicity, allowed an uptake to the IT by people who never thought to do it, namely an advanced age group (elderly) who want to join the world of the new technologies

Finance Strategies for Medium-Sized Enterprises

2021 ◽  
pp. 1323-1345
Author(s):  
Chen Liu
Keyword(s):  
Best Practice ◽  
Balance Sheet ◽  
Investment Decisions ◽  
Capital Management ◽  
Working Capital ◽  
Working Capital Management ◽  
Artificial Intelligent ◽  
Blockchain Technology ◽  
Supply Chain Finance ◽  
Future Work

This chapter discusses how FinTech—technology-enabled financial solutions and services—can optimize finance strategies of medium-sized enterprises. Using a balance sheet model, the chapter integrates medium-sized companies' financing strategies, working capital management, and investment decisions and discusses FinTech solutions in each area to suggest best practice. Specifically, the chapter first discusses how crowdfunding and its different types could provide alternative financing for medium-sized enterprises. Second, FinTech solutions for online payment and transfer, invoice finance, supply chain finance, and trade finance help medium-sized enterprises optimize their working capital management. Third, blockchain technology and artificial intelligent (AI)-based decisions tools could potentially help medium-sized businesses optimize their decision-making process. This chapter also suggests future work that will allow us to better understand FinTech applications in medium-sized enterprises.

Future Blockchain Technology for Autonomous Applications/Autonomous Vehicle

2022 ◽  
pp. 1027-1038
Author(s):  
Arnab Kumar Show ◽  
Abhishek Kumar ◽  
Achintya Singhal ◽  
Gayathri N. ◽  
K. Vengatesan
Keyword(s):  
Autonomous Vehicles ◽  
New Technology ◽  
Autonomous Vehicle ◽  
The Self ◽  
Third Party ◽  
Traffic Information ◽  
Online Transactions ◽  
The Third ◽  
Blockchain Technology ◽  
Self Driving Cars

The autonomous industry has rapidly grown for self-driving cars. The main purpose of autonomous industry is trying to give all types of security, privacy, secured traffic information to the self-driving cars. Blockchain is another newly established secured technology. The main aim of this technology is to provide more secured, convenient online transactions. By using this new technology, the autonomous industry can easily provide more suitable, safe, efficient transportation to the passengers and secured traffic information to the vehicles. This information can easily gather by the roadside units or by the passing vehicles. Also, the economical transactions can be possible more efficiently since blockchain technology allows peer-to-peer communications between nodes, and it also eliminates the need of the third party. This chapter proposes a concept of how the autonomous industry can provide more adequate, proper, and safe transportation with the help of blockchain. It also examines for the possibility that autonomous vehicles can become the future of transportation.

scholarly journals Evaluation of a VERT-based module for proton radiotherapy education and training

2020 ◽  
pp. 1-5
Author(s):  
Amber Rabus ◽  
Mike C. Kirby ◽  
Laura Nasole ◽  
Pete Bridge
Keyword(s):  
Assessment Tool ◽  
New Technology ◽  
Statistical Significance ◽  
Basic Knowledge ◽  
Teaching Session ◽  
Open Questions ◽  
Before And After ◽  
Long Term Impact ◽  
Dose Deposition ◽  
Future Work

Abstract Introduction: In many countries, there is a skills gap in proton therapy with many staff unprepared to work with the new technology. The new Virtual Environment for Radiotherapy Training (VERT) proton module provides learners with a simulated proton machine 3D environment. This project aimed to evaluate the role of VERT in training the radiotherapy workforce for the future use of protons. Methods: A practical teaching session using VERT was deployed after a traditional teaching session had provided basic knowledge. A questionnaire deployed before and after VERT enabled comparison of knowledge while a combination of Likert and open questions gathered participant feedback concerning the initiative. Results: A total of 38 students provided evaluation of the session. Overall, there were high levels of satisfaction and enjoyment with 35 participants reporting enjoyment and 36 indicating that the event be repeated. Discussion: Participants felt that they had learned from the experience, although quantitative data lacked statistical significance to demonstrate this. All participants agreed that VERT had provided improved understanding of proton dose deposition arising from visualisation of beams and dose deposition. Most participants agreed that the simulation was realistic and that it had improved their understanding. Feedback in relation to future sessions concerned smaller group sizes, more patient cases, more time and additional clinical datasets. Conclusion: A proton simulation module has been shown to be an enjoyable teaching tool that improves students’ confidence in their knowledge of the underpinning theory and clinical usage of the modality. Learners felt better prepared to encounter protons in clinical practice. Future work will build on these findings using smaller group work and a more robust assessment tool to identify long-term impact of the training.

scholarly journals SABlockFL: a blockchain-based smart agent system architecture and its application in federated learning

2020 ◽  
Vol 4 (2) ◽  
pp. 133-147
Author(s):  
Zhizhao Zhang ◽  
Tianzhi Yang ◽  
Yuan Liu
Keyword(s):  
Neural Network ◽  
System Architecture ◽  
Data Exchange ◽  
Privacy Preserving ◽  
Agent System ◽  
Content Type ◽  
New Era ◽  
Agent Model ◽  
Blockchain Technology ◽  
Smart Contract

Purpose The purpose of this work is to bridge FL and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. FL is an emerging collaborative machine learning technique that trains a model across multiple devices or servers holding private data samples without exchanging their data. The locally trained results are aggregated by a centralized server in a privacy-preserving way. However, there is an assumption where the centralized server is trustworthy, which is impractical. Fortunately, blockchain technology has opened a new era of data exchange among trustless strangers because of its decentralized architecture and cryptography-supported techniques. Design/methodology/approach In this study, the author proposes a novel design of a smart agent inspired by the smart contract concept. Specifically, based on the proposed smart agent, a fully decentralized, privacy-preserving and fair deep learning blockchain-FL framework is designed, where the agent network is consistent with the blockchain network and each smart agent is a participant in the FL task. During the whole training process, both the data and the model are not at the risk of leakage. Findings A demonstration of the proposed architecture is designed to train a neural network. Finally, the implementation of the proposed architecture is conducted in the Ethereum development, showing the effectiveness and applicability of the design. Originality/value The author aims to investigate the feasibility and practicality of linking the three areas together, namely, multi-agent system, FL and blockchain. A blockchain-FL framework, which is based on a smart agent system, has been proposed. The author has made several contributions to the state-of-the-art. First of all, a concrete design of a smart agent model is proposed, inspired by the smart contract concept in blockchain. The smart agent is autonomous and is able to disseminate, verify the information and execute the supported protocols. Based on the proposed smart agent model, a new architecture composed by these agents is formed, which is a blockchain network. Then, a fully decentralized, privacy-preserving and smart agent blockchain-FL framework has been proposed, where a smart agent acts as both a peer in a blockchain network and a participant in a FL task at the same time. Finally, a demonstration to train an artificial neural network is implemented to prove the effectiveness of the proposed framework.

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