The advancements of AI techniques and its transformation made an intelligent automated process using Internet of Things (IoT), machine optimization in various industrial applications. One of the notable change happens in the healthcare industry witnessed significant progress, leading to the emergence of Health 4.0. This new era encompasses a wide range of cutting-edge technologies including the Internet of Things (IoT), Internet of Services (IoS), Medical Cyber-Physical Systems (CPS), Health Cloud, Health Fog etc. The largest barrier to electronic healthcare is securing all medical equipment that are connected to the internet. Blockchain, a distributed and immutable ledger or database, has gained popularity across various sectors, including healthcare, due to its efficiency and reliability by offering features such as decentralization, enhanced security, and immutability. This chapter aims to explore the advantages and challenges associated with implementing blockchain technology in healthcare 4.0 by providing factual evaluation of block chain's progress in healthcare.
Daniel Haberly, Duncan MacDonald-Korth, Michael Urban, Dariusz WĂłjcik
While contemporary technological disruption is increasingly conceptualized in terms of the logic and paradoxes of the digital platform economy, discussions of âFinTechâ have only engaged to a limited extent with these debatesâparticularly from an economic geographic standpoint. Here we fill this gap by proposing an adapted Global Financial Network (GFN) framework for conceptualizing the organizational and geographic logic of the digital platform economy in finance, and applying it to examine the impact of the digital platform model on asset management. As we will show, asset management is being profoundly disrupted by what we dub digital asset management platformsâor DAMPsâwhich encompass services including index fund and ETF provision, robo-advising, and analytics and trading support. Like other digital platforms, DAMPs do not so much leverage technology to enhance their competitiveness within markets, as to radically restructure the market itself. Also, like other platforms, their rise has produced a winner-take-all paradox of centralization through democratization that defies predictions of technology-enabled industry decentralization. However, the logic and implications of the rise of DAMPs diverges, in other respects, from non-financial digital platforms, as finance has long possessed an informational intensity and regulatory and organizational fluidity characteristic of the digital platform economy. Consequently, the digital platform model has mostly developed endogenously in asset management through incremental innovation by major financial firmsâin a process that has reinforced the position of leading incumbent asset management centers, and above all New Yorkârather than being introduced from the outside by upstart technology firms and clusters.
After 2001 Serbia started the process of democratization and socio-economic transition. Within the overall reform of public administration and the public finance system, the process of fiscal decentralization has started to strengthen the position of local self-governments. Decentralization in every respect, and especially fiscal, is the most important assumption of local development. In order for the decentralized state to function well, it is important that these three forms of decentralization: political, administrative and fiscal, be well coordinated with one another. Fiscal decentralization refers to the collection and consumption of funds at various levels of government. The paper outlines the reasons justifying the process of fiscal decentralization, as well as the reasons that are against fiscal decentralization, i.e. the reasons that speak of the limitations it carries with it. The goal of properly implemented fiscal decentralization is to strengthen the role of cities and municipalities, as well as their fiscal autonomy, that the Republic entrusted the local authorities with numerous important competencies and that the local budgets are multiplied. Decentralization in Serbia has not progressed satisfactorily. Serbia put fiscal decentralization at the heart of public administration reform. Local self-government financing in Serbia changed in this period, which led to instability. Only in the period between 2008 and 2015 the legal frameworks of the system of financing of local self-governments changed several times and thus the process of budget execution and financial management at the local level was impaired. The mentioned changes in the legal framework for the ultimate consequence had the reduction of the budgets of local governments, which jeopardized their ability to perform their communal, investment and other functions.
Blockchain technology has provided a platform for the decentralized execution of smart contracts. A smart contract is an agreement that is automatically executed when certain conditions have been met. The immutability, decentral nature, and consensus mechanisms that are characteristic to blockchain technology make the smart contract and its development cycle a new field of study in software engineering. A novel economic and defensive thinking is needed to develop workable, secure smart contracts. Motivated by the need for a novel approach to development, this thesis proposes a model-driven approach to smart contract development.\nModel-Driven Engineering (MDE) is an approach to information system development in which models and model technologies are applied to raise the level of abstraction at which developers create and evolve software, with the goal of both simplifying and formalizing the various activities and tasks that comprise the Software Development Life Cycle (SDLC). Model-Driven Architecture (MDA) is a framework for this approach. This thesis aims to apply this framework to create a method which describes the development phase from domain knowledge to smart contract foundation.\nThe creation of a method has two main aims, namely (i) to bridge the semantic gap between domain knowledge and smart contract by lowering the threshold for domain experts, and (ii) support developers in creating less vulnerable smart contracts that accurately represent the problem domain. This is done by constructing a model-driven method based on existing research that applies MDE to smart contract development. A literature study into this field yields the requirements and techniques for the method, which is consequently constructed based on these requirements and techniques.\nThe method is evaluated in twofold. First, the value is assessed through a case study, which shows that the developer benefits from a structured approach and the reduction of manual programming. Second, by an experiment which shows that people are better able to comprehend and communicate about models containing functional aspects of the smart contract if a computational independent model is included. By doing so it fulfills the aim of lowering the threshold for domain experts to participate in the smart contract development cycle.
KuoâHui Yeh, Chunhua Su, Jia-Li Hou, Wayne Chiu · 5 authors
Recently, the popularity and universality of smart-devices has led to rapid advancement in the development of applications for mobile commerce around the world. Novel mobile payment schemes, such as Apple pay, Android pay, and Samsung pay are becoming an increasingly popular ways to conduct online transactions, no matter what type of smart devices are used. Due to the attendant growth in the importance of security, significant attention has been devoted to the challenge of designing and implementing a robust mobile payment scheme for securing online transactions. In this paper, we demonstrate a robust mobile payment scheme based on sturdy certificateless signatures with bilinear pairing. We elegantly refine the proposed mobile payment scheme to make it suitable for computation-constrained mobile devices. The practicability of the proposed mobile payment scheme is then certified via a rigorous security analysis and thorough performance evaluation using the Raspberry PI as the implementation platform for our proposed scheme. Furthermore, we implement a transaction repository with the aid of smart contract technology. The simulation results, based on Ethereum, demonstrate the feasibility of employing the smart contract technology to secure mobile payments.
Abstract Cryptocurrencies are expected to have a significant impact on banking, finance, and monetary systems. Due to the uncertainty as to the possible future trajectories of the evolving cryptocurrency ecosystem, governments have taken a relatively hands-off approach to regulating such currencies. This approach may be justified within the theoretical information-economics framework of this paper, which draws parallels between the information economics of money and quasi-money creation within the current central banking, commercial banking, and shadow banking systems with that of the cryptocurrency ecosystem. In particular, drawing lessons from the literature on the role of information in creating âsafe assetsâ, in this paper the authors find that by building on symmetric (common) knowledge as to the inner workings of the Bitcoin Blockchainâthough in a different wayâbitcoin possesses a degree of endogenous information insensitivity typical of safe assets. This endogenous information insensitivity could support bitcoinâs promise of maturing into a viable store of value and a niche medium of exchange. This finding should not be overlooked in the policy discussions for potential future regulatory interventions in the cryptocurrency ecosystem.
Unspent Transaction Outputs (UTXOs) are the internal mechanism used in many cryptocurrencies to represent coins. Such representation has some clear benefits, but also entails some complexities that, if not properly handled, may leave the system in an inefficient state. Specifically, inefficiencies arise when wallets (the software responsible for transferring coins between parties) do not manage UTXOs properly when performing payments. In this paper, we study three cryptocurrencies: Bitcoin, Bitcoin Cash and Litecoin, by analysing the state of their UTXO sets, that is, the status of their sets of spendable coins. These three cryptocurrencies are the top-3 UTXO-based cryptocurrencies by market capitalization. Our analysis shows that the usage of each cryptocurrency presents some differences, and led to different results. Furthermore, it also points out that the management of the transactions has not always been performed efficiently and therefore, the current state of the UTXO sets is far from ideal.
Modern retail banking creates a kind of panopticon for consumer behaviour, ultimately promising to implement a mechanism that binds all of the financial activities undertaken by an individual to a single, unitary identity. In the age of Big Data, consumers have legitimate reasons to resist such surveillance, particularly in cases wherein monitoring is carried out without their knowledge and judgments based upon such monitoring are used to disincentivise or punish legitimate activities. The risk to consumers increases with the ever-increasing share of financial transactions that are performed electronically. Cryptocurrencies offer an alternative to traditional methods of electronic value exchange, promising anonymous, cash-like electronic transfers, but in practice they fall short for several key reasons. We consider the false choice between total surveillance, as represented by banking as currently implemented by institutions, and impenetrable lawlessness, as represented by privacy-enhancing cryptocurrencies as currently deployed. We identify a range of alternatives between those two extremes, and we consider two potential compromise approaches that offer both the auditability required for regulators and the anonymity required for users
Cryptocurrencies are digital tokens built on blockchain technology. This allows for a product that is fully decentralized, with no need for a third-party intermediary like a government or financial institution. Cryptocurrency creators use initial coin offerings (ICOs) to raise capital to build their tokens. Cryptocurrency ICOs are problematic because they do not fit neatly within either of two traditional categoriesâsecurities or commodities. Each of these categories has their own regulatory agency: the SEC for securities and the CFTC for commodities. At first blush, ICOs seem to be a sale of securities subject to regulation by the SEC, but this is far from clear and creates regulatory difficulties. This is because the Howey test, which determines whether an asset is a security or not, does not cleanly apply to nontraditional assets, like tokens. This Note argues for a revised standard that reconciles Howey with cryptocurrencies. This standard would require cryptocurrency creators to show how essential blockchain technology is to their token if they want to fall beyond the scope of the Howey test, and consequently SEC regulation. This standard would still preserve regulatory protections from fraud, which the CFTC provides for investors while loosening regulatory restrictions on the cryptocurrencies that leverage blockchain technology most usefully.
Abstract This study investigates the profitability of an algorithmic trading strategy based on training SVM model to identify cryptocurrencies with high or low predicted returns. A tail set is defined to be a group of coins whose volatility-adjusted returns are in the highest or the lowest quintile. Each cryptocurrency is represented by a set of six technical features. SVM is trained on historical tail sets and tested on the current data. The classifier is chosen to be a nonlinear support vector machine. The portfolio is formed by ranking coins using the SVM output. The highest ranked coins are used for long positions to be included in the portfolio for one reallocation period. The following metrics were used to estimate the portfolio profitability: %ARC (the annualized rate of change), %ASD (the annualized standard deviation of daily returns), MDD (the maximum drawdown coefficient), IR1, IR2 (the information ratio coefficients). The performance of the SVM portfolio is compared to the performance of the four benchmark strategies based on the values of the information ratio coefficient IR1, which quantifies the risk-weighted gain. The question of how sensitive the portfolio performance is to the parameters set in the SVM model is also addressed in this study.
In a world full of new technology, the risk of fraud is constantly increasing. In the securities industry, this risk existed long before the use of technology. Congress enacted the Securities Act of 1933 to combat the risk of fraud and misrepresentation in the sale of securities. By requiring full disclosure, investors have the opportunity to make informed decisions prior to investing. However, Distributed Autonomous Organizations (âDAOsâ), through the use of blockchains and smart-contracts, engage in the sale of securities without fully disclosing the risks or complying with the registration requirements of the Securities Act of 1933. Compliance with the burdensome requirements of registration, however, would destroy this new technology and method of conducting business. To avoid this set-back, Congress must amend the registration requirements to provide an exemption for DAOs. This exemption, although reducing current registration burdens, must still require DAOs to disclose certain information, thereby ensuring investors are informed prior to investing. Furthermore, due to the unique nature of the blockchain, smartcontract, and DAOs, Congress must impose a fiduciary duty on the creators of DAOs to ensure compliance with the disclosure requirements. Further, Congress should consider the allowance of burden-shifting following the initial crowdsale.
Predicting currency prices remains a difficult endeavour. Investors are continually seeking new ways to extract \nmeaningful information about the future direction of price changes. Recently, cryptocurrencies have attracted \nhuge attention due to their unique way of transferring value as well as its value as a hedge. A method proposed \nin this project involves using data mining techniques: mining text documents such as news articles and tweets \ntry to infer the relationship between information contained in such items and cryptocurrency price direction. \nThe Long Short-Term Memory Recurrent Neural Network (LSTM RNN) assists in creating a hybrid model \nwhich comprises of sentiment analysis techniques, as well as a predictive machine learning model. The success \nof the model was evaluated within the context of predicting the direction of Bitcoin price changes. Findings \nreported here reveal that our system yields more accurate and real-time predictions of Bitcoin price fluctuations \nwhen compared to other existing models in the market.
Abstract Blockchain technology is transforming traditional financial systems. Cross-border money remittance industry is in a crossroad being challenged. The traditional SWIFT system is facing new comers like Ripple system which is based on the blockchain distributed ledger technology with its own crypto tokens. This paper conducts a SWOT analysis on both technologies to find out whether the blockchain technology has the potential to transform a traditional industry and how this may be possible. We conclude that Ripple has all of the advantages over SWIFT despite some minor issues. In short-term, SWIFT will still take the lead in the remittance market due to the economy of scale. However, in long-term, emerging technology like Ripple will eventually revolutionize the remittance industry or even other financial systems.
Distributed ledger technology (DLT), commonly referred to as 'blockchain' and originally invented to create a peerto-peer digital currency, is rapidly attracting interest in other sectors. The aim in this paper is (1) to investigate the applications of DLT within the built environment, and the challenges and opportunities facing its adoption; and (2) develop a multi-dimensional emergent framework for DLT adoption within the construction sector.