Francisco López Rupérez, Isabel García García, Eva Expósito Casas
The territorial organization of Spain into regions (autonomous communities) involves a remarkable decentralization. Therefore, it is interesting to make a comparative efficiency analysis of the public spending in education among regions that can to shed light on both the educational policies at the regional level, and the corrective state actions of inter-territorial imbalances. Furthermore, equity of the results of the education system is an indisputable goal of any society that aspires to justice and social cohesion. This research poses, firstly, an estimation of educational effectiveness and efficiency of public spending using a secondary analysis of PISA 2015 data that takes into account the value of ESCS. Subsequently, two educational equity parameters are estimated. The triple empirical categorization of autonomous communities, according to the efficiency and equity results, allows the derivation of policy recommendations of interest both at the regional and central government levels.
Mokka is a partial-synchronous, strong consistent BFT consensus algorithm for reaching the consensus about a certain value in open networks. This algorithm has some common approaches nested from RAFT, but its nature and design make Mokka a better solution for DLT (distributed ledger).
In the Internet of Vehicles (IoV), data sharing among vehicles is critical for improving driving safety and enhancing vehicular services. To ensure security and traceability of data sharing, existing studies utilize efficient delegated proof-of-stake consensus scheme as hard security solutions to establish blockchain-enabled IoV (BIoV). However, as the miners are selected from miner candidates by stake-based voting, defending against voting collusion between the candidates and compromised high-stake vehicles becomes challenging. To address the challenge, in this paper, we propose a two-stage soft security enhancement solution: 1) miner selection and 2) block verification. In the first stage, we design a reputation-based voting scheme to ensure secure miner selection. This scheme evaluates candidates' reputation using both past interactions and recommended opinions from other vehicles. The candidates with high reputation are selected to be active miners and standby miners. In the second stage, to prevent internal collusion among active miners, a newly generated block is further verified and audited by standby miners. To incentivize the participation of the standby miners in block verification, we adopt the contract theory to model the interactions between active miners and standby miners, where block verification security and delay are taken into consideration. Numerical results based on a real-world dataset confirm the security and efficiency of our schemes for data sharing in BIoV.
Sung-Hwa Han, Ju-Hyung Kim, Won-Seok Song, Gwang-Yong Gim
Healthcare is not only a requirement for the extension of life, but also an integral part of personal happiness. Currently, medical services are rapidly expanding with the increase of medical personnel and the development of medical technology, which are the result of the development of medical technology. The development of medical devices, and the improvement of medical services. The development of medical service gives positive effect, but it provides negative effect too. Although administrative, technical, policy, and financial problems are being reinforced, it is pointed out that medical disputes caused by medical accidents are consistently increasing, and loss of medical research due to data error results in loss. In order to solve this problem, it is indispensable to satisfy the reliability, integrity and traceability of medical information used in medical research and medical disputes, and a method of applying blockchain technology to medical information service is proposed as a technical alternative.
Nikos Fotiou, Vasilios A. Siris, George C. Polyzos
Despite technological advances, most smart objects in the Internet of Things\n(IoT) cannot be accessed using technologies designed and developed for\ninteracting with powerful Internet servers. IoT use cases involve devices that\nnot only have limited resources, but also they are not always connected to the\nInternet and are physically exposed to tampering. In this paper, we describe\nthe design, development, and evaluation of a smart contract-based solution that\nallows end-users to securely interact with smart devices. Our approach enables\naccess control, Thing authentication, and payments in a fully decentralized\nsetting, taking at the same time into consideration the limitations and\nconstraints imposed by both blockchain technologies and the IoT paradigm. Our\nprototype implementation is based on existing technologies, i.e., Ethereum\nsmart contracts, which makes it realistic and fundamentally secure.\n
Alberto Sonnino, Michał Król, Argyrios G. Tasiopoulos, Ioannis Psaras
Recent developments in blockchains and edge computing allows to deploy decentralized shared economy with utility tokens, where altcoins secure and reward useful work. However, the majority of the systems being developed, does not provide mechanisms to pair workers and clients, or rely on manual and insecure resolution. AStERISK bridges this gap allowing to perform sealed-bid auctions on blockchains, automatically determine the most optimal price for services, and assign clients to the most suitable workers. AStERISK allows workers to specify a minimal price for their work, and hide submitted bids as well the identity of the bidders without relying on any centralized party at any point. We provide a smart contract implementation of AStERISK and show how to deploy it within the Filecoin network, and perform an initial benchmark on Chainspace.
techniques in association with the access rights of the members of the group workspaces. So, to utilize the off-blockchain storage more securely, it is desirable to prevent the external
Blockchain is a merging technology for decentralized management and data security, which was first introduced as the core technology of cryptocurrency, e.g., Bitcoin. Since the first success in financial sector, blockchain has shown great potentials in various domains, e.g., internet of things and mobile networks. In this paper, we propose a novel blockchain-based architecture for content delivery networks (B-CDN), which exploits the advances of the blockchain technology to provide a decentralized and secure platform to connect content providers (CPs) with users. On one hand, the proposed B-CDN will leverage the registration and subscription of the users to different CPs, while guaranteeing the user privacy thanks to virtual identity provided by the blockchain network. On the other hand, the B-CDN creates a public immutable database of the requested contents (from all CPs), based on which each CP can better evaluate the user preference on its contents. The benefits of B-CDN are demonstrated via an edge-caching application, in which a feature-based caching algorithm is proposed for all CPs. The proposed caching algorithm is verified with the realistic Movielens dataset. A win-win relation between the CPs and users is observed, where the B-CDN improves user quality of experience and reduces cost of delivering content for the CPs.
In this paper we analyse the correctness of Istanbul BFT (IBFT), which is a Byzantine-fault-tolerant (BFT) proof-of-authority (PoA) blockchain consensus protocol that ensures immediate finality. We show that the IBFT protocol does not guarantee Byzantine-fault-tolerant consistency and liveness when operating in an eventually synchronous network, and we propose modifications to the protocol to ensure both Byzantine-fault-tolerant consistency and liveness in eventually synchronous settings.
We have investigated processes of analysis, integration, and content generation, taking into consideration the needs of the user in cryptocurrency. By using the developed formal model and the performed critical analysis of methods and technologies for predicting the exchange rate of cryptocurrency, we have built a general architecture of the content processing system that acquires data from different cryptocurrency Internet stock exchanges. General functional requirements to the intelligent cryptocurrency system that target the Internet users have been stated. We have investigated methods, models, and tools to improve the effective support for developing structural elements in the model of a decision support system that manages content according to the user’s needs. general architectures of the backend and frontend parts of an intelligent cryptocurrency system have been devised. We also developed software for the system of integration and generation of content considering the cryptocurrency needs of users. An analysis of results of experimental verification of the proposed method for content integration and generation taking into consideration the cryptocurrency needs of users has been performed. A special feature of the system is that it analyzes information from social media and builds a forecast of currency rates based on the acquired information. A given system makes it possible to guess the trend in an exchange rate fluctuation. Conferences of a particular cryptocurrency, new implementations, government decrees from different countries, affect a trend as well, so it too must be taken into consideration. In order to account for most cases, it is necessary to constantly accumulate information on the subject and to assign it to Tables in a database. A given process takes place using a specialized software bot that collects and indexes information. The system is characterized by the following features that favorably distinguish it from analogs: the speed of page generation; the presence of SSL certificate and TLS encryption; content of better quality as it is updated every minute; there are no inactive sections of the service; the mobile web-site layout does not copy content at subdomain; automated checks against e-mail spam messages on the exchange rate. The focus of the system is on the frequency of updates at the speed of data aggregation from the Internet stock exchanges and social networks.
Daniel Traian Pele, Miruna Mazurencu-Marinescu-Pele
In this paper we investigate the ability of several econometrical models to forecast value at risk for a sample of daily time series of cryptocurrency returns. Using high frequency data for Bitcoin, we estimate the entropy of intraday distribution of logreturns through the symbolic time series analysis (STSA), producing low-resolution data from high-resolution data. Our results show that entropy has a strong explanatory power for the quantiles of the distribution of the daily returns. Based on Christoffersen's tests for Value at Risk (VaR) backtesting, we can conclude that the VaR forecast build upon the entropy of intraday returns is the best, compared to the forecasts provided by the classical GARCH models.
Distribution system operators (DSOs) are interested in demand side participation programs as an efficient and secure resource to manage electricity supply and demand. However, it is usually difficult for DSOs to aggregate demand response of large/small consumers. Thus, in some electricity markets, an entity called an aggregator is defined to aggregate the load response of consumers. In this paper a bilevel scheduling model is proposed to determine the long-term optimal contract price between the DSO and aggregator for executing direct load control in smart distribution systems. The DSO and aggregator are considered as two different agents with individual objectives in the proposed bilevel scheduling model. On the one hand, the aggregator maximizes its profit by bidding load reduction of the large consumers to the DSO by executing a direct load control (DLC) mechanism, and on the other hand, the DSO tries to minimize its overall cost to supply all consumers. The DSO has two options to follow the variation of its consumers' demand: purchasing energy from the electricity market and executing DLC programs. The bilevel programming formulation is transferred into an equivalent single level programming problem using its Karush-Kuhn-Tucker optimality conditions. Moreover, the uncertainties of the electricity market price, demand of consumers, and generation of a wind power plant are modeled via point estimate method. Two typical case studies are implemented to demonstrate the effectiveness of the proposed scheduling model.
This paper provides a critical look at how blockchain technology is currently being developed and used to facilitate responsible business conduct, and offers suggestions for how responsible business conduct can be integrated into emerging blockchain initiatives in an effective way, in alignment with the OECD Guidelines for Multinational Enterprises. This paper is a contribution to a broader effort to promote and coordinate best practice and policy coherence in the area of supply chain due diligence.
The Blockchain technology was initially adopted to implement various cryptocurrencies. Currently, Blockchain is foreseen as a general purpose technology with a huge potential in many areas. Blockchain-based applications have inherent characteristics like authenticity, immutability and consensus. Beyond that, records stored on Blockchain ledger can be accessed any time and from any location. Blockchain has a great potential for managing and maintaining educational records. This paper presents a Blockchain-based Educational Record Repository (BcER2) that manages and distributes educational assets for academic and industry professionals. The BcER2 system allows educational records like e-diplomas and e-certificates to be securely and seamless transferred, shared and distributed by parties.
BACKGROUND: (MHPF) and the mechanisms by which these reforms can be structured and financed in the context of fiscal constraint. METHODS: A situational analysis guided by a newly developed analytical framework for sustainable mental health financing was conducted. The review was followed by qualitative, indepth interviews with a range of expert national stakeholders. RESULTS: Although the MHPF is said to be consistent with ongoing efforts toward the implementation of National Health Insurance (NHI), there is clear evidence of discordance between the MHPF and the NHI. The most promising strategies for sustainable mental health financing include: increased decentralization of resources to primary and community mental health services; active integration of mental health into ongoing NHI implementation including expanding the mandate of District hospitals and drawing on the private sector; submission of costed budget bids to support a mental health conditional grant and ensuring that explicit outcomes and deliverables are in place to monitor Provincial implementation. CONCLUSION: This paper has suggested several ways in which existing reforms may be leveraged to incorporate the objectives of the MHPF and achieve better mental health outcomes for South Africans, revealing critical opportunities for mental health service scale-up to be embedded in South Africa's future health delivery strategy. The realization of a conditional grant for mental health will require technical expertise to cost existing services towards the development of an investment case for mental health service scale-up nationally, projecting potential resource requirements and returns on investment of a strong service platform. In the longer-term, the NHI benefit package must be expanded to include comprehensive mental health services at all levels. Explicit results-based financing mechanisms within the NHI Fund must also be incorporated for mental health to incentivise quality of care. Private providers engaged by the NHI must commit to make use of evidence-based mental health interventions.
We provide a trend prediction classification framework named the random sampling method (RSM) for cryptocurrency time series that are non-stationary. This framework is based on deep learning (DL). We compare the performance of our approach to two classical baseline methods in the case of the prediction of unstable Bitcoin prices in the OkCoin market and show that the baseline approaches are easily biased by class imbalance, whereas our model mitigates this problem. We also show that the classification performance of our method expressed as the F-measure substantially exceeds the odds of a uniform random process with three outcomes, proving that extraction of deterministic patterns for trend classification, and hence market prediction, is possible to some degree. The profit rates based on RSM outperformed those based on LSTM, although they did not exceed those of the buy-and-hold strategy within the testing data period, and thus do not provide a basis for algorithmic trading.
The cryptocurrency market is a very huge market without effective\nsupervision. It is of great importance for investors and regulators to\nrecognize whether there are market manipulation and its manipulation patterns.\nThis paper proposes an approach to mine the transaction networks of exchanges\nfor answering this question.By taking the leaked transaction history of Mt. Gox\nBitcoin exchange as a sample,we first divide the accounts into three categories\naccording to its characteristic and then construct the transaction history into\nthree graphs. Many observations and findings are obtained via analyzing the\nconstructed graphs. To evaluate the influence of the accounts' transaction\nbehavior on the Bitcoin exchange price,the graphs are reconstructed into series\nand reshaped as matrices. By using singular value decomposition (SVD) on the\nmatrices, we identify many base networks which have a great correlation with\nthe price fluctuation. When further analyzing the most important accounts in\nthe base networks, plenty of market manipulation patterns are found. According\nto these findings, we conclude that there was serious market manipulation in\nMt. Gox exchange and the cryptocurrency market must strengthen the supervision.\n
The cryptocurrency market is a very huge market without effective supervision. It is of great importance for investors and regulators to recognize whether there are market manipulation and its manipulation patterns. This paper proposes an approach to mine the transaction networks of exchanges for answering this question. By taking the leaked transaction history of Mt. Gox Bitcoin exchange as a sample, we first divide the accounts into three categories according to its characteristic and then construct the transaction history into three graphs. Many observations and findings are obtained via analyzing the constructed graphs. To evaluate the influence of the accounts' transaction behavior on the Bitcoin exchange price, the graphs are reconstructed into series and reshaped as matrices. By using singular value decomposition (SVD) on the matrices, we identify many base networks which have a great correlation with the price fluctuation. When further analyzing the most important accounts in the base networks, plenty of market manipulation patterns are found. According to these findings, we conclude that there was serious market manipulation in Mt. Gox exchange and the cryptocurrency market must strengthen the supervision.
In this paper, we consider the problem of generating fair randomness in a deterministic, multi-agent context (for instance, a decentralised game built on a blockchain). The existing state-of-the-art approaches are either susceptible to manipulation if the stakes are high enough, or they are not generally applicable (specifically for massive game worlds as opposed to games between a small set of players). We propose a novel method based on game theory: By allowing agents to bet on the outcomes of random events against the miners (who are ultimately responsible for the randomness), we are able to align the incentives so that the distribution of random events is skewed only slightly even if miners are trying to maximise their profit and engage in block withholding to cheat in games.
Nasr Al-Zaben, Md Mehedi Hassan Onik, Chul-Soo Kim, Jinhong Yang
Today we can use technologies like switched Ethernet, TCP/IP, high-speed wide area networks, and high-performance low-cost computers very easily. However, protocols designed for those communication are inefficient or not energy efficient. Smart home, smart grid, blockchain, Internet of Things (IoT) all these technologies are coming very rapidly with higher communication facilities demands an energy efficient Ethernet. Due to controller and network equipment use a huge quantity of energy. Layer to layer communication making our communication method more complex and costly. In this work, we propose an architecture, which will make the communication of sensor devices to outside world easier. Our proposed system removes certain layer from TCP-IP communication. We used a communication interface identifier protocol (CIIP) which can be used for smaller IoT sensors.
Conventional railway operations employ specialized software and hardware to ensure safe and secure train operations. Track occupation and signaling are governed by central control offices, while trains (and their drivers) receive instructions. To make this setup more dynamic, the train operations can be decentralized by enabling the trains to find routes and make decisions which are safeguarded and protocolled in an auditable manner. In this paper, we present the case study findings of a first-of-its-kind blockchain-based prototype implementation for railway control, based on decentralization but also ensuring that the overall system state remains conflict-free and safe. We also show how a blockchain-based approach simplifies usage billing and enables a train-to-train/machine-to-machine economy. Finally, first ideas addressing the use of blockchain technology as a life-cycle approach for condition-based monitoring and predictive maintenance in train operations are outlined.
Conventional railway operations employ specialized software and hardware to\nensure safe and secure train operations. Track occupation and signaling are\ngoverned by central control offices, while trains (and their drivers) receive\ninstructions. To make this setup more dynamic, the train operations can be\ndecentralized by enabling the trains to find routes and make decisions which\nare safeguarded and protocolled in an auditable manner. In this paper, we\npresent the findings of a first-of-its-kind blockchain-based prototype\nimplementation for railway control, based on decentralization but also ensuring\nthat the overall system state remains conflict-free and safe. We also show how\na blockchain-based approach simplifies usage billing and enables a\ntrain-to-train/machine-to-machine economy. Finally, first ideas addressing the\nuse of blockchain as a life-cycle approach for condition based monitoring and\npredictive maintenance in train operations are outlined.\n
Blockchains are attracting the attention of stakeholders in many industrial domains, including the logistics and supply chain industries. Blockchain technology can effectively contribute in recording every single asset throughout its flow on the supply chain, contribute in tracking orders, receipts, and payments, while track digital assets such as warranties and licenses in a unified and transparent way. The paper provides, through its methodology, a detailed analysis of the blockchain fit in the supply chain industry. It defines the specific elements of blockchain that affect supply chain such as scalability, performance, consensus mechanism, privacy considerations, location proof and cost, and details on the impact that blockchains will have in disrupting the supply chain industry. Discussing the tradeoff between consensus cost, throughput and validation time it proceeds with a suggested high-level architectural approach, and concludes as a result with a discussion on changes needed and challenges faced for an in-vivo deployment of blockchains in the supply chain industry. While the technological features of modern blockchains can effectively facilitate supply chain uses cases, the various challenges that still remain, bring in front of us a wide set of needed changes and further research efforts for achieving a global, production level blockchain for the supply chain industry.