Alzheimer's disease (AD) imposes a considerable burden on those diagnosed. Faced with a neurodegenerative decline for which there is no effective cure or prevention method, sufferers of the disease are subject to judgement, both self-imposed and otherwise, that can have a great deal of effect on their lives. The burden of this stigma is more than just psychological, as reluctance to face an AD diagnosis can lead people to avoid early diagnosis, treatment, and research opportunities that may be beneficial to them, and that may help progress towards fighting AD and its progression. In this review, we discuss how recent advents in information technology may be employed to help fight this stigma. Using artificial intelligence (AI) technologies, specifically natural language processing (NLP), to classify the sentiment and tone of texts, such as those of online posts on various social media sites, has proven to be an effective tool for assessing the opinions of the general public on certain topics. These tools can be used to analyze the public stigma surrounding AD. Additionally, there is much concern among individuals that an AD diagnosis, or evidence of pre-clinical AD such as a biomarker or imaging test results, may wind up unintentionally disclosed to an entity that may discriminate against them. The lackluster security record of many medical institutions justifies this fear to an extent. Adopting more secure and decentralized methods of data transfer and storage, and giving patients enhanced ability to control their own data, such as a blockchain-based method, may help to alleviate some of these fears.
Abstract Objective: In order to cope with a sudden outbreak of new coronavirus infection, a large number of potential infected persons need to be isolated. A new smart monitoring system which integrates Internet of things and blockchain technology to monitor isolated people in real time was design and studied.Methods: A internet of things devices will collects the location and physical data of isolated people, the data will be sent to master devices which will integrate and format those data and transfer to a smart contract. A smart contract compares and analyses the data with the threshold which is predefined. When the data exceed the threshold, the smart contract will alert the master device, which will notify the isolated person and center for disease control and prevention, the event will be stored in the consortium blockchain. The blockchain does not store the isolated people's details, which are stored in electronic health records linked to the blockchain to guarantee the data safety.Results: This system realizes the effective real-time monitoring of isolators including their physical condition and geographical position on the premise of protecting their privacy and security.Conclusion: By the system, the center for disease control and prevention can respond quickly according to their alerts. It has the advantages of good integrity, tamper-proof, and transparency to isolators.
Tianrui Chen, Amjad Saeed Khan, Gan Zheng, Sangarapillai Lambotharan
This letter presents a secure user offloading mechanism in heterogeneous wireless networks (HWNs), where a macrocell base station (MBS) offloads its users to small cell access points (SCAs) using Vickrey auction. Additionally, a user-in-the-loop (UIL) strategy is exploited to encourage the unserved users to move to desired locations for connections. As the participants in the conventional auction-based trading may collude or take selfish actions, we employ Ethereum framework for trustless, secure and distributed auctioning. Simulation results are presented to demonstrate the advantages of the proposed user offloading methodology. The security aspects of the blockchain framework are also discussed.
Fiscal decentralization is a form of delegated authority of the central government to local governments in matters of financial management. Local governments are given the authority to explore potential sources of local revenue in accordance with applicable regulations. Submission sources of revenue for local governments in the region should ideally be able to encourage selffinance its expenditure. Minimum local governments are able to finance expenditures of local government employee nevertheless remains dependent on central government transfers, it is shown by the local government is still dependent on the balance of funds by the central government through the DAU, DAK and other legal equalization funds. This study aims to determine the level of regional dependency on the central government decentralization era during his journey in the past 10 years (2001-2011). The sample in this study are some regencies/districts and cities in the Province of West Java. The results showed that the degree of independence of local government is still low, which means dependence on the central government is still high. Some areas even shows for local income can not afford to finance recurrent expenditure.
Sebastian Kummer, David M. Herold, Mario Dobrovnik, Jasmin Mikl · 5 authors
Potential blockchain applications in logistics and transport (LSCM) have gained increasing attention within both academia and industry. However, as a field in its infancy, blockchain research often lacks theoretical foundations, and it is not clear which and to what extent organizational theories are used to investigate blockchain technology in the field of LSCM. In response, based upon a systematic literature review, this paper: (a) identifies the most relevant organizational theories used in blockchain literature in the context of LSCM; and (b) examines the content of the identified organizational theories to formulate relevant research questions for investigating blockchain technology in LSCM. Our results show that blockchain literature in LSCM is based around six organizational theories, namely: agency theory, information theory, institutional theory, network theory, the resource-based view and transaction cost analysis. We also present how these theories can be used to examine specific blockchain problems by identifying blockchain-specific research questions that are worthy of investigation.
Smart contracts have enabled blockchain systems to evolve from simple cryptocurrency platforms, such as Bitcoin, to general transactional systems, such as Ethereum. Catering for emerging business requirements, a new architecture called execute-order-validate has been proposed in Hyperledger Fabric to support parallel transactions and improve the blockchain's throughput. However, this new architecture might render many invalid transactions when serializing them. This problem is further exaggerated as the block formation rate is inherently limited due to other factors beside data processing, such as cryptography and consensus. In this work, we propose a novel method to enhance the execute-order-validate architecture, by reducing invalid transactions to improve the throughput of blockchains. Our method is inspired by state-of-the-art optimistic concurrency control techniques in modern database systems. In contrast to existing blockchains that adopt database's preventive approaches which might abort serializable transactions, our method is theoretically more fine-grained. Specifically, unserializable transactions are aborted before ordering and the remaining transactions are guaranteed to be serializable. For evaluation, we implement our method in two blockchains respectively, FabricSharp on top of Hyperledger Fabric, and FastFabricSharp on top of FastFabric. We compare the performance of FabricSharp with vanilla Fabric and three related systems, two of which are respectively implemented with one standard and one state-of-the-art concurrency control techniques from databases. The results demonstrate that FabricSharp achieves 25% higher throughput compared to the other systems in nearly all experimental scenarios. Moreover, the FastFabricSharp's improvement over FastFabric is up to 66%.
Soteria is a user right management system designed to safeguard user-data privacy in a transparent and provable manner in compliance to regulations such as GDPR and CCPA. Soteria represents user data rights as formal executable sharing agreements, which can automatically be translated into a human readable form and enforced as data are queried. To support revocation and to prove compliance, an indelible, audited trail of the hash of data access and sharing agreements are stored on a two-layer distributed ledger. The main chain ensures partition tolerance and availability (PA) properties while side chains ensure consistency and availability (CA), thus providing the three properties of the CAP (consistency, availability, and partition tolerance) theorem. Besides depicting the two-layer architecture of Soteria, this paper evaluates representative consensus protocols and recommends side-chain and inter-chain management strategies for improving latency and throughput.
Ajay K. Gogineni, S. Swayamjyoti, Devadatta Sahoo, Κ. K. Sahu · 5 authors
Vulnerability detection and safety of smart contracts are of paramount importance because of their immutable nature. Symbolic tools like OYENTE and MAIAN are typically used for vulnerability prediction in smart contracts. As these tools are computationally expensive, they are typically used to detect vulnerabilities until some predefined invocation depth. These tools require more search time as the invocation depth increases. Since the number of smart contracts is increasing exponentially, it is difficult to analyze the contracts using these traditional tools. Recently a machine learning technique called Long Short Term Memory (LSTM) has been used for binary classification, i.e., to predict whether a smart contract is vulnerable or not. This technique requires nearly constant search time as the invocation depth increases. In the present article, we have shown a multi-class classification, where we classify a smart contract in Suicidal, Prodigal, Greedy, or Normal categories. We used Average Stochastic Gradient Descent Weight-Dropped LSTM (AWD-LSTM), which is a variant of LSTM, to perform classification. We reduced the class imbalance (a large number of normal contracts as compared to other categories) by considering only the distinct opcode combination for normal contracts. We have achieved a weighted average Fbeta score of 90.0%. Hence, such techniques can be used to analyze a large number of smart contracts and help to improve the security of these contracts.
This paper studies of the multifractal dynamics in 84 cryptocurrencies. It fills an important gap in the literature, by studying this market using two alternative multi-scaling methodologies. We find compelling evidence that cryptocurrencies have different degree of long range dependence, and --more importantly -- follow different stochastic processes. Some of them follow models closer to monofractal fractional Gaussian noises, while others exhibit complex multifractal dynamics. Regarding the source of multifractality, our results are mixed. Time series shuffling produces a reduction in the level of multifractality, but not enough to offset it. We find an association of kurtosis with multifractality.
The last decade has experienced a vast interest in Blockchain-based cryptocurrencies with a specific focus on the applications of this technology. However, slow confirmation times of transactions and unforeseeable high fees hamper their wide adoption for micro-payments. The idea of establishing payment channel networks is one of the many proposed solutions to address this scalability issue where nodes, by utilizing smart contracting, establish payment channels between each other and perform off-chain transactions. However, due to the way these channels are created, both sides have a certain one-way capacity for making transactions. Consequently, if one sides exceeds this one-way capacity, the channel becomes useless in that particular direction, which causes failures of payments and eventually creates an imbalance in the overall network. To keep the payment channel network sustainable, in this paper, we aim to increase the overall success rate of payments by effectively exploiting the fact that end-users are usually connected to the network at multiple points (i.e., gateways) any of which can be used to initiate the payment. We propose an efficient method for selection of the gateway for a user by considering the gateway's inbound and outbound payment traffic ratio. We then augment this proposed method with split payment capability to further increase success rate especially for large transactions. The evaluation of the proposed method shows that compared to greedy and maxflow-based approaches, we can achieve much higher success rates, which are further improved with split payments.
This letter expands the studies of the informational efficiency in the cryptocurrency market. Most studies have focused on Bitcoin, the foremost known cryptocurrency, and a few more coins. However, this market is more diverse, with cryptocurrencies entering and leaving the market on a weekly basis. This letter fills an important gap in the literature, by studying the informational efficiency using a multi-scaling methodology, which represents a new approach. We compute the generalized Hurst exponent of eighty-four cryptoassets daily returns. The multi-scaling methodology used in this paper find compelling evidence that cryptocurrencies have different degree of long range dependence, and --more importantly -- follow different stochastic processes. Some of them follow traditional monofractal models consistent with fractional Brownian motion, while others exhibit complex multifractal dynamics.
The convergence of fifth-generation (5G) communication and the Internet-of-Things (IoT) has dramatically increased the diversity and complexity of the network. This change diversifies the attacker’s attack vectors, increasing the impact and damage of cyber threats. Cyber threat intelligence (CTI) technology is a proof-based security system which responds to these advanced cyber threats proactively by analyzing and sharing security-related data. However, the performance of CTI systems can be significantly compromised by creating and disseminating improper security policies if an attacker intentionally injects malicious data into the system. In this paper, we propose a blockchain-based CTI framework that improves confidence in the source and content of the data and can quickly detect and eliminate inaccurate data for resistance to a Sybil attack. The proposed framework collects CTI by a procedure validated through smart contracts and stores information about the metainformation of data in a blockchain network. The proposed system ensures the validity and reliability of CTI data by ensuring traceability to the data source and proposes a system model that can efficiently operate and manage CTI data in compliance with the de facto standard. We present the simulation results to prove the effectiveness and Sybil-resistance of the proposed framework in terms of reliability and cost to attackers.
Blockchain technology and artificial intelligence (AI) are current hot topics\nin research and practice. However, the potentials of their combination have\nbeen studied just recently to a larger extend. While different use cases for\ncombining AI and blockchain have been discussed, the idea of enabling\nblockchain-based smart contracts to perform "smarter" decisions by using AI or\nmachine learning (ML) models has only been considered on the conceptual level\nso far. It remained open, how such AI-enabled smart contracts could be\nimplemented in a robust way for real-world applications. Therefore, in this\npaper a new, enterprise-class implementation of AI-enabled smart contracts is\npresented and first insights regarding its feasibility are discussed.\n
There is A finite amount of portable water which is decreasing day by day. Rapid degradation of useful water on earth results in an unkind impact on livelihood. In future, people may have to face (DAY 0) problem therefore, conservation of water is essential. A solution has been proposed to this problem that is “decentralized water management system” using blockchain technology. Blockchain technology can help to use water more efficiently so that every household can lend/borrow the required/extra water from its peer household in the network. In this research work, water ledger architecture has been proposed. This architecture can serve as the basis for Blockchain implementation which can help inbuilding transparency in the water management system with the ultimate goal of Water Conservation. To purpose a system architecture that meets the “demand and supply” of all consumers in a peer-to-peer network so that water can be conserved. A smart contract has been written for transactions (P2P network of 10 household) using Ethereum as a platform. A web interface is created for consumers. Hence, the overall objective is to create a smart water management system for 10 households using blockchain technology to conserve water by medium of sharing water among peer-to-peer as per their needs.
The security and accountability issues are a challenge to the traditional structure from still widespread elections. General e-voting system use a centralized system, where one organization manages overall system. These organisations have full control over the database and system, allowing manipulation of the database. There should be no e-voting system to secure data and potential attacks should be able to withstand. Blockchain technology should solve certain voting problems. In this paper we are implementing an ethereum blockchain based electronic voting system. Ethereum blockchain networks are used to transfer money and store data. Networks are organized by one or more machines. Every node is a machine that running an ethereum client. The eligible one can run the node. By adopting blockchain in e-voting system database distribution, one of the cheating sources of database manipulation and data loss can be reduced. This can be a better solution for the currently existing issues over rigging the electronic voting machines to win elections by the political parties in our government.
Blockchain governance is a subject of ongoing research and an interdisciplinary view of blockchain governance is vital to aid in further research for establishing a formal governance framework for this nascent technology. In this paper, the position of blockchain governance within the hierarchy of Institutional governance is discussed. Blockchain governance is analyzed from the perspective of IT governance using Nash equilibrium to predict the outcome of different governance decisions. A payoff matrix for blockchain governance is created and simulation of different strategy profiles is accomplished for computation of all Nash equilibria. The paper elaborates upon payoff matrices for different kinds of blockchain governance, which are used in the proposition of novel mathematical formulae usable to predict the best governance strategy that minimizes the occurrence of a hard fork as well as predicts the behavior of the majority during protocol updates. The paper also includes validation of the proposed formulae using real Ethereum data.
The combined cooling, heating and power (CCHP) system is a typical distributed, electricity-gas integrated energy scheme in a community. First, it generates electricity by use of gas, and then exploits the waste heat to supply community with heat and cooling. In this paper, we consider a smart city consisting of a number of communities (CCHPs) and an agent of power grid (APG), where CCHPs can sell energy to the APG according to its bid. To study all utilities of entities in such a city from energy trading, a noncooperative Stackelberg game between APG and CCHPs is formulated. Here, the APG gives a bid for buying the energy from CCHPs, then CCHPs respond to the APG with their optimal energy supply that maximizing their utilities according to this bid. We show that the maximum profit to the APG and utilities to the CCHPs can be obtained at the Stackelberg equilibrium, which is guaranteed to exist and unique. Because the complete information about energy supply of each CCHP is unknown to the APG in advance, we propose a distributed algorithm that is able to find the point of equilibrium through a limited number of iterations. Taking privacy protection and transaction security into consideration, we design a blockchain-enabled energy management system. This system is composed of Internet of Energy (IoE) sub-system and blockchain sub-system, where the information interactions as well as energy transactions between APG and CCHPs can be carried out effectively and safely. Finally, security analysis and numerical simulations show the effectiveness and accuracy of our proposed mechanism.
The combined cooling, heating and power (CCHP) system is a typical distributed, electricity-gas integrated energy scheme in a community. First, it generates electricity by use of gas, and then exploits the waste heat to supply community with heat and cooling. In this paper, we consider a smart city consisting of a number of communities (CCHPs) and an agent of power grid (APG), where CCHPs can sell energy to the APG according to its bid. To study all utilities of entities in such a city from energy trading, a noncooperative Stackelberg game between APG and CCHPs is formulated. Here, the APG gives a bid for buying the energy from CCHPs, then CCHPs respond to the APG with their optimal energy supply that maximizing their utilities according to this bid. We show that the maximum profit to the APG and utilities to the CCHPs can be obtained at the Stackelberg equilibrium, which is guaranteed to exist and unique. Because the complete information about energy supply of each CCHP is unknown to the APG in advance, we propose a distributed algorithm that is able to find the point of equilibrium through a limited number of iterations. Taking privacy protection and transaction security into consideration, we design a blockchain-enabled energy management system. This system is composed of Internet of Energy (IoE) sub-system and blockchain sub-system, where the information interactions as well as energy transactions between APG and CCHPs can be carried out effectively and safely. Finally, security analysis and numerical simulations show the effectiveness and accuracy of our proposed mechanism.
Blockchain governance is a subject of ongoing research and an interdisciplinary view of blockchain governance is vital to aid in further research for establishing a formal governance framework for this nascent technology. In this paper, the position of blockchain governance within the hierarchy of Institutional governance is discussed. Blockchain governance is analyzed from the perspective of IT governance using Nash equilibrium to predict the outcome of different governance decisions. A payoff matrix for blockchain governance is created and simulation of different strategy profiles is accomplished for computation of all Nash equilibria. The paper elaborates upon payoff matrices for different kinds of blockchain governance, which are used in the proposition of novel mathematical formulae usable to predict the best governance strategy that minimizes the occurrence of a hard fork as well as predicts the behavior of the majority during protocol updates. The paper also includes validation of the proposed formulae using real Ethereum data.
Cem Çağrı Dönmez, Ahmet Fatih Dereli, Muhammed Bilal Horasan, Cagri Yıldız
The focus of this research is to describe and discuss future blockchain technology in relation to different forms of digital cryptocurrencies by investigating distinct characteristics and common features of cryptocurrencies on the market. This research explores significant relationships between the major cryptocurrencies on the complex cryptocurrency market ecosystem, particularly Bitcoin and the most prominent altcoins based on historical market capitalization data for the last two years. In this work cross-correlations between different cryptocurrencies are examined in terms of changes in the market capitalization value. For the comparative analysis minimum spanning tree (MST) and hierarchical structure tree (HST) methods are applied in the context of economic behaviour of cryptocurrencies with regard to global cryptocurrency market trends.
M. Akhil Sai, K. Sarath Chandra Sai, M. Manu Koushik, K. Gowri Raghavendra Narayan
ML and AI-helped exchanging have pulled in developing enthusiasm for as far back as not many years.We examine day-by-day information for different digital currencies over some stretch of time. We show that straightforward exchanging methodologies helped by innovative AI calculations outflank standard benchmarks. We have picked two Machine Learning Algorithms to play out a Comparative Study to foresee cost of a Bitcoin; we have utilized Decision tree regressor and LSTM Algorithms and watched execution of every calculation as far as anticipating the cost of Bitcoin. We saw that Decision tree regressor gives progressively effective and precise outcomes when contrasted with others.
Blockchain technology is expected to bring about exciting developments across a variety of fields, such as politics, economy, culture, industry, and business model. Blockchain is no doubt one key infrastructure technology to lead the Fourth Industrial Revolution. This paper is a general overview of the main features of blockchain technology. Three types of blockchains (public, private, and consortium) will be presented within a discussion of their major case studies. In addition, the latest trends and developments in blockchain technology will be briefly reviewed. The terminology of blockchain infrastructure technology has the potential to foster technological innovation across various industrial sectors as well as improve mutual harmony and understanding of complex structures and diverse phenomena in human society, especially antagonism, confrontation, and ideological conflict. With such progress in social innovation, blockchain technology will result in a fairer and more transparent human society. Greater attention will also be given to a blockchain-based mobile voting system that will enable the realization of direct democracy in a representative democracy. Furthermore, this paper offers solutions to a trilemma of problems (scalability, security, decentralization) in blockchain.
This study measures the volatility of cryptocurrency by utilizing the symmetric (GARCH 1, 1) and asymmetric (EGARCH, TGARCH, PGARCH) model of GARCH family using a daily database designated in different digital monetary standards. The results for an explicit set of currencies for entire period provide evidence of volatile nature of cryptocurrency and in most of the cases, the PGARCH is a better-fitted model with student’s t distribution. The findings show positive shocks heavily affected conditional volatility as a contrast with negative stuns. Those additional analyses can be provided further support their findings and worthwhile information for economic thespians who are engrossed in adding cryptocurrency to their equity portfolios or are snooping about the capabilities of cryptocurrency as a financial asset.