Blockchain can be defined as distributed ledger technology that can securely and permanently record transactions between parties. The blockchain uses a shared database among many parties, the blockchain can eliminate the need for intermediaries who need to act as trusted third parties to validate, r
Throughout its history, preferably over the last four centuries, the world witnessing game changing and disruptive technologies on certain regular intervals. Wheels, Compass, calendar and pozzolana are some of the remarkable inventions in before Christ (B.C) period. Clock, printing press, steam engines, vaccines, electricity, mechanical computer, telegraph, iron and steel, aero plane, transistors, ARPANET, personal computer and Internet are few outstanding innovations fuelled our world for last four centuries. If we look at the time line of inventions, it is dramatically reduced over the advancement of time. Inventions took centuries in B.C, but needs only a few years or a decade in A.D. We would like to add the blockchain technology in this line up, which could fuel new era of inventions in new dimensions. This technology relies on decentralized concepts, entirely against the present centralized system, the world relies on. Why we still need a third party book keepers or why we still need an third party intermediary for trust and transactions? This article will answer these arguments. This article begins with the conceptual understanding, then reveals its disruptiveness through several case studies across several industries such as Banking, Administration, Supply chain management, Logistics, Asset management, Intellectual property management, Transport and Energy. Blockchain technology has the potential to redefine every one another technology of human beings. Concept of ledger and its evolution, from its voyage from Indian origin single entry ledger to Satoshi Nakamoto’s triple entry ledger has been highlighted, as these are vital to understand the technology behind bit coin. Without mentioning the crypto currencies, the blockchain use cases will not ended up, hence few excerpts of crypto currencies also added. From cryptography in technology, Anti money laundering, Know your customer, Transaction monitoring in Banking to day to day administration as in the case of land records storage, identity management etc., are few contributions of this article. We also covered the case studies from corporate giants such as Amazon, IBM, MAERSK to the startups like EzyRemit, Signzy etc., and from an individual state of administration Andrapradesh to the entire country, Dubai. It is important for the global engineering education needs to identify and nurture the disruptive technologies, which could contribute to our society in meaningful way. We believe that, blockchain technology belongs to the category of future technologies, which could shape up and fuel the development of global economy for next few decades as internet did for past few decades. Through this article, the young generation engineering pupils, matured practitioners and influential decision makers will understand the potential of blockchain technology and provide impetus to global engineering education.
Su Buda, Celimuge Wu, Wugedele Bao, Siri Guleng · 7 authors
In order to enable emerging vehicular Internet of Things (IoT) applications, including fully autonomous driving, more efforts should be done in collecting driving experiences in different road situations. This requires the exchange of information between vehicles as each vehicle has very limited experience. Due to the decentralized feature of vehicular environment, an efficient management of collaborative behaviors among the vehicles becomes particularly important. Blockchain has been attracting great interest recently because it provides a way to reach consensus in decentralized systems. However, existing blockchain systems assume high communication capabilities for vehicles, which is difficult to achieve in a decentralized vehicular environment. Existing studies also assume the existence of networking infrastructure, such as roadside units (RSU). In this paper, we propose a scheme to empower blockchain in vehicular environments without depending on the existing networking infrastructure. The proposed scheme uses a distributed clustering approach to select some vehicles as edge nodes, and the edge nodes maintain the blockchain used to record transactions in a decentralized way. The proposed scheme employs a distributed approach that guides vehicle clustering with the consideration of multiple metrics based on a fuzzy logic algorithm. By using the edge nodes, the proposed scheme solves the communication problem of maintaining a blockchain in a totally decentralized vehicular environment. We use computer simulations to clarify the performance of the proposed scheme in terms of communication performance by comparing it with existing baselines.
Tao Feng, Hongmei Pei, Rong Ma, Youliang Tian · 5 authors
Data privacy is important to the security of our society, and enabling authorized users to query this data efficiently is facing more challenge. Recently, blockchain has gained extensive attention with its prominent characteristics as public, distributed, decentration and chronological characteristics. However, the transaction information on the blockchain is open to all nodes, the transaction information update operation is even more transparent. And the leakage of transaction information will cause huge losses to the transaction party. In response to these problems, this paper combines hierarchical attribute encryption with linear secret sharing, and proposes a blockchain data privacy protection control scheme based on searchable attribute encryption, which solves the privacy exposure problem in traditional blockchain transactions. The user’s access control is implemented by the verification nodes, which avoids the security risks of submitting private keys and access structures to the blockchain network. Associating the private key component with the random identity of the user node in the blockchain can solve the collusion problem. In addition, authorized users can quickly search and supervise transaction information through searchable encryption. The improved algorithm ensures the security of keywords. Finally, based on the DBDH hypothesis, the security of the scheme is proved in the random prediction model.
The evolution of Artificial Intelligence (AI) from centralized models toward decentralized architectures has fundamentally reshaped the paradigms of data management, ownership, and governance. In traditional AI ecosystems, data is consolidated within centralized repositories for model training and analytics, resulting in challenges related to privacy, latency, and compliance with regulatory frameworks. Decentralized AI architectures encompassing federated learning, edge AI, swarm intelligence, and blockchain-based frameworks offer a transformative alternative that aligns technological innovation with distributed data governance principles. These architectures enable AI systems to learn collaboratively across multiple nodes or organizations without transferring raw data, ensuring data sovereignty and compliance with global data protection mandates such as GDPR and CCPA. This review examines how decentralized AI architectures influence distributed data governance by promoting transparency, trust, and accountability in multi-party data ecosystems. The integration of AI with blockchain and distributed ledger technologies provides immutable audit trails and decentralized identity management, enabling verifiable governance across federated networks. Moreover, privacy-preserving techniques such as differential privacy, homomorphic encryption, and secure multiparty computation empower organizations to perform analytics on encrypted datasets while maintaining compliance with ethical and legal data-handling standards. Through a synthesis of academic research and real-world applications, the review highlights the significant advantages of decentralized AI, including enhanced privacy assurance, reduced systemic risks, and improved collaboration among data stakeholders. However, the transition toward decentralized intelligence introduces new challenges related to interoperability, communication overhead, and model convergence in distributed environments. Ensuring fairness, accountability, and explainability within federated systems remains a critical governance issue, as decentralized decision-making increases complexity in auditing and oversight. Furthermore, the governance of AI models themselves rather than just data poses emerging regulatory and ethical questions in globally interconnected ecosystems.
Arterial hypertension affects a third of the world's population and is a significant risk factor for cardiovascular disease. Blood pressure (BP) is one of the most relevant parameters used for monitoring of possible hypertension states in patients at risk of cardiovascular disease. Hence, there exists a need for new monitoring solutions, which allow to increase the frequency between BP assessments, but also allow to reduce the level of occlusion in the attempts. Moens-Korteweg equation is among the main principles to estimate BP by dispensing of any inflatable cuff. This principle might lead to an indirect estimation of BP by measuring the time it takes the pressure pulse to propagate between two pre-established vascular points, accordingly the pulse transit time (PTT) method. This thesis proposes a wearable PTT-based method to estimate central aortic BP (CABP) and, the main milestones of this work included: proof of concept of the proposed method (pilot work), the development of a wearable device (including two stages of validation), the proposition of a miniaturized version (integrated circuit) of the analog front-end of the wearable hardware, and, the development of a novel PTT-based model (PTTBM, i.e., the mathematical relationship between measured variables and estimated BP) suitable for the proposed wearable methodology to estimate BP. The main contributions found at each milestone are presented. One of the contributions of this thesis is the use of the PTT-principle for estimating CABP instead of the peripheral BP (PBP) (as typically used in the literature). The pilot work showed the feasibility of CABP estimation from the PTT principle by using electrocardiogram (ECG) and ballistocardiogram (BCG) recordings from off-the-shelf equipment. Results showed that CABP was more correlated with the proposed methodology in comparison to all PBP variables assessed; confirming our hypothesis that the CABP is the most suitable parameter to collate through the time elapsed from ECG R-wave to the BCG J-wave. That is, considered featured time (RJ-interval) includes the time of a pulse pressure propagating at an aortic district. Bland-Altman plots showed an almost zero mean error (\u\ < 0.02mmHg) and bounded standard deviation o < 5mmHg for all systolic and mean central BP readings. Pilot work provided a landmark in order to develop a compact device that allows the integration of wireless blood pressure monitoring into a wearable system. Another contribution of this thesis is the proposition of a wearable device for PTT-computing by also including design considerations for the signal conditioning chains for ECG and BCG signals. The proposed design procedure takes care of minimizing the impact of spurious delays between physiological signals, which eventually degrade the PTT computation. Further, such a procedure could be suitable for any PTT-acquisition. Filtering with low and controlled delay is required for this biomedical application, and proposed conditioning chains provide less than 2ms group-delay, showing the effectiveness of the proposed approach. In order to provide the methodology with higher autonomy and integration, a highly miniaturized implementation of the filtering approach was also proposed. It includes the design of proposed architectures in CMOS technology to implement the particular low-delay filtering at reduced bandwidth featuring ultra-low-power characteristics. Results show that less than 2ms delay for the ECG QRS-complex can be achieved with a total current consumption of IDD = 2:1nA at VDD = 1:2V of power supply. Such development meant another significant contribution of this work in the conception of highly autonomous wearable devices for PTT acquisition. The first stage of validations on the wearable CABP estimation showed that, when considering data from one volunteer, results achieved with off-the-shelf equipment could be replicated by using a proposed wearable device, and the method could be further validated by using the wearable version. Additionally, CABP estimation from the proposed wearable device could be feasible by using three feature times (FTs) as CABP surrogates; that is, RI, RJ, and IJ intervals (from ECG and BCG wearable recordings). The first validation of the method also showed that CABP could be accurately predicted by the proposed methodology when in the order of daily calibrations are performed. The second stage of validations involved a study with a group of volunteers, and new alternatives were explored (twentyseven: nine PTTBMs along the three FTs) for the CABP estimation. We found that CABP could be accurately estimated (inside AAMI requirements) through the presented methodology by using four of the explored alternatives, whereas the RI interval, an FT lacking any PTT assessment, emerged as the best surrogate for the CABP estimation. Hence, a principle different from the traditional PTT-based method arises as a more advantageous method for the CABP estimation in the light of evidence reported in this validation, and, to our knowledge, this is the first time that CABP has been successfully estimated from a wearable device. The final significant contribution of this thesis meant the last chain-link in the process to achieve an utterly original method to estimate CABP. A novel PTTBM to estimate CABP is proposed, which uses a ow-driven two-element Windkesel network constructed from FTs extracted from the wearable recordings. When classic PTTBMs are applied, the fitting of parameters often leads to values without a physiological basis. Opposite to that in the proposed PTTBM, the parameters have a clear physiological meaning, and the parameter fitting led to values that are consistent with this meaning and more stable throughout calibrations. In conclusion, this thesis introduces a novel device that exploits an alternative and indirect method for CABP estimation. Variants of the principle used, accordingly, PTT method, have been previously explored to estimate PBP but not for central aortic BP. Additionally, the device was designed to be wearable; that is, it is attached to the clothes, causing low discomfort for the user during the measurement, thus, allowing continuous and ambulatory monitoring of aortic pressure. The developed wearable system, validated in a series of volunteers, showed promising results towards the continuous CABP monitoring.
Spatial crowdsourcing is an effective and novel method. In crowdsourcing systems, a centralized platform is traditionally used to allocate tasks and select workers. Centralized platforms always face following challenges: 1) How to ensure the rationality of tasks allocating; 2) How to ensure the payments of workers in the system when dishonest requesters exist; 3) How to ensure the maximum number of tasks are assigned. 4) How to ensure the integrity and reliability of the centralized platform. To solve these problems, this article proposed a distributed blockchain-based crowdsourcing framework - TSWCrowd (Task Select Worker Crowd). In this framework, tasks are sorted according to specific rules, thus tasks with higher priority are assigned to workers earlier. Workers who are available for a task will be selected and return a result. Then the deployed smart contracts will pay the basic payment automatically. At the same time, relevant contracts also calculate and pay the quality payment according to the proposed quality reward formulation. The proposed TSWCrowd framework on-chain involves a public dataset and uses solidity to compile the smart contracts. The framework was deployed on a local private blockchain. The decentralization property of the blockchain ensures the reliable assignment of tasks. Task-select-worker (TSW) algorithm sorts tasks to ensure reliability. In this paper, the proposed framework was compared with the ABCrowd auction mechanism on-chain and the VCG mechanism off-chain. The results show that the average distance is shorter and the payment is higher, thus reaches the reasonability, reliability and availability.
An early stage funding platform using cryptocurrency smart contracts can potentially provide an equity and debt capital raising platform for new ventures compared to crowdfunding, initial coin offerings (ICOs) and seed funding. The existing capital raising methods are less transparent, have limited depth of funding and less diversification. Utilising a cryptocurrency smart contract-based early stage funding platform will allow new ventures to obtain a staged funding environment, starting from seed funding. Each stage of funding can be represented by a smart contract that is aligned to a formal standardised legally binding contract between the venture and investors through the platform. Competition for funds and a transparent smart contract-based platform should allow free markets to price investments in the new venture in a more efficient fashion. Additionally, such a platform should provide more funding opportunities to new ventures that weren't available prior.
This paper investigates the relations between multiple measures of investor sentiment and the returns, volatility, trading volume, and liquidity. Using both data outside and inside market, we find that the Bullishness from socio-finance model are significant related to future realized volatility and trading volume, similar to Tweet, which is thought to capture information of well-informed investors in Bitcoin market
Shaker Atyan K Alharthi, Paul Cerotti, Shaghayegh Maleki Far
In recent years, there have been many problems in information integration among key pharmaceutical supply chain players in KSA. This issue has resulted in problems such as medication shortage, lack of coordination among healthcare stakeholders, product wastage, and lack of demand information. However, blockchain, as a distributed digital ledger technology which ensures transparency, traceability, and security, is showing promise for easing some supply chain management problems. Local and global government, community, and consumer pressures to meet sustainability goals prompt us to further investigate how blockchain can address and aid supply chain sustainability. This study aims to explore the impact of blockchain technology implementation on the sustainability of the pharmaceutical supply chain. The objectives of this study are to identify the current information system infrastructure in the pharmaceutical supply chain of KSA, to examine the barriers and challenges of blockchain adoption, and to examine the barriers and challenges of blockchain implementation. This study will use a qualitative research method and the data will be collected through semi-structured interviews with a sample of 30 participants in KSA. This research is expected to contribute to the development of a framework for blockchain adoption in the pharmaceutical supply chain and to explore the role of blockchain in sustainability efforts. In addition, it will help managers, practitioners, consultants and decision makers who are interested in a deeper understanding of blockchain and its implementation, and will evaluate its influence on SSCM.
A blockchain is a distributed hierarchical data structure. Widely-used applications of blockchain include digital currencies such as Bitcoin and Ethereum. This paper proposes an algorithmic approach to analyze the efficiency of a blockchain as a function of the number of blocks and the average synchronization delay. The proposed algorithms consider a random network model that characterizes the growth of a tree of blocks by adhering to a standard protocol. The model is parametric on two probability distribution functions governing block production and communication delay. Both distributions determine the synchronization efficiency of the distributed copies of the blockchain among the so- called workers and, therefore, are key for capturing the overall stochastic growth. Moreover, the algorithms consider scenarios with a fixed or an unbounded number of workers in the network. The main result illustrates how the algorithms can be used to evaluate different types of blockchain designs, e.g., systems in which the average time of block production can match the average time of message broadcasting required for synchronization. In particular, this algorithmic approach provides insight into efficiency criteria for identifying conditions under which increasing block production has a negative impact on the stability of a blockchain. The model and algorithms are agnostic of the blockchain’s final use, and they serve as a formal framework for specifying and analyzing a variety of non-functional properties of current and future blockchains.
Ever since the invention of Bitcoin by the pseudonymous Satashi Nakamoto, cryptocurrency has provoked debate in banking and finance sectors, and is sometimes considered a potential successor to fiat currency. Blockchain, the new technology underpinning decentralised and immutable databases, has seen much discussion as a potentially game-changing development. Although many industries are exploring its value, the technology has thus far made only minor impacts. A rapidly expanding base of research has emerged on blockchain's role as a potential disruptor in the electrical energy industry. However, it may be difficult to distinguish hype from more imminently plausible impacts. This paper attempts to serve as a guide for engineering management wishing to make sense of blockchain's potential in electricity. This is accomplished by formulating a novel blockchain industry disruption framework, which exists across three tiers. These tiers extend from ideas with the least effect on an industry to total revolutionary concepts that could completely transform an industry. This taxonomy is constructed by examining existing research into disruption hierarchies and blockchain classification methods. Through the lens of this taxonomy, a literature review is performed on blockchain's role in energy to draw out themes and ideas characterising each tier. The potential likelihood of real-world application of various ideas are discussed, giving consideration to how established industries may be affected or disrupted. The authors provide some conjecture here. Finally, courses of action are suggested for those whose sector may be affected by blockchain.
We propose a sociotechnical, yet computational, approach to building decentralized applications that accommodates and exploits blockchain technology. Our architecture incorporates the notion of a declarative, violable contract and enables flexible governance based on formal organizational structures, correctness verification without obstructing autonomy, and a basis for trust.
The article presents blockchain technology for developing national digital economy, efficiency of digitalization and basic principles of digitalization, and a set of blocks requiring material resources. The purpose of the article is to study features of digital economy development and propose application of blockchain technology in national economy sphere. Research methods: The instrumental and methodical apparatus of research based on application, in framework of a systematic approach, general scientific research methods. Implementing blockchain technology in financial system at micro-macro degrees, insurance system, system of government, electron trade system, industrial system, intellectual property account system, education system, health care system was analyzed in this article. Organizing in perfect way the operations to implement the digital economy in Uzbekistan, and develop and establish large financial projects at the state level, moreover, illustrated in details importance of using blockchain technology in national economy industries while developing and establishing large financial projects at the state level.
Edge computing has witnessed a rapid growth in the past few years as more and more and resources are getting connected to the Internet. The Internet is not gaining any benefits from the current implementation of ad hoc and infrequent edge resources. Transparency and trust need to be introduced while distributing the economic benefits equally to both the edge resource provider and edge resource consumer. By completely decentralising the edge resource marketplace these edge resources can be made available to the public in the form of cloud resource. The current project focuses on Blockchain-based Smart contract-driven resource management for Edge Computing.
Abstract This paper proposes a Bayesian estimation algorithm to estimate Generalized Partition of Unity Copulas (GPUC), a class of nonparametric copulas recently introduced by [18]. The first approach is a random walk Metropolis-Hastings (RW-MH) algorithm, the second one is a random blocking random walk Metropolis-Hastings algorithm (RBRW-MH). Both approaches are Markov chain Monte Carlo methods and can cope with ˛at priors. We carry out simulation studies to determine and compare the efficiency of the algorithms. We present an empirical illustration where GPUCs are used to nonparametrically describe the dependence of exchange rate changes of the crypto-currencies Bitcoin and Ethereum.