53 research outputs found
Blockchain based Decentralized Applications: Technology Review and Development Guidelines
Blockchain or Distributed Ledger Technology is a disruptive technology that
provides the infrastructure for developing decentralized applications enabling
the implementation of novel business models even in traditionally centralized
domains. In the last years it has drawn high interest from the academic
community, technology developers and startups thus lots of solutions have been
developed to address blockchain technology limitations and the requirements of
applications software engineering. In this paper, we provide a comprehensive
overview of DLT solutions analyzing the addressed challenges, provided
solutions and their usage for developing decentralized applications. Our study
reviews over 100 blockchain papers and startup initiatives from which we
construct a 3-tier based architecture for decentralized applications and we use
it to systematically classify the technology solutions. Protocol and Network
Tier solutions address the digital assets registration, transactions, data
structure, and privacy and business rules implementation and the creation of
peer-to-peer networks, ledger replication, and consensus-based state
validation. Scaling Tier solutions address the scalability problems in terms of
storage size, transaction throughput, and computational capability. Finally,
Federated Tier aggregates integrative solutions across multiple blockchain
applications deployments. The paper closes with a discussion on challenges and
opportunities for developing decentralized applications by providing a
multi-step guideline for decentralizing the design of traditional systems and
implementing decentralized applications.Comment: 30 pages, 8 figures, 9 tables, 121 reference
Social Factors in P2P Energy Trading Using Hedonic Games
Lately, the energy communities have gained a lot of attention as they have
the potential to significantly contribute to the resilience and flexibility of
the energy system, facilitating widespread integration of intermittent
renewable energy sources. Within these communities the prosumers can engage in
peer-to-peer trading, fostering local collaborations and increasing awareness
about energy usage and flexible consumption. However, even under these
favorable conditions, prosumer engagement levels remain low, requiring trading
mechanisms that are aligned with their social values and expectations. In this
paper, we introduce an innovative hedonic game coordination and cooperation
model for P2P energy trading among prosumers which considers the social
relationships within an energy community to create energy coalitions and
facilitate energy transactions among them. We defined a heuristic that
optimizes the prosumers coalitions, considering their social and energy price
preferences and balancing the energy demand and supply within the community. We
integrated the proposed hedonic game model into a state-of-the-art
blockchain-based P2P energy flexibility market and evaluated its performance
within an energy community of prosumers. The evaluation results on a
blockchain-based P2P energy flexibility market show the effectiveness in
considering social factors when creating coalitions, increasing the total
amount of energy transacted in a market session by 5% compared with other game
theory-based solutions. Finally, it shows the importance of the social
dimensions of P2P energy transactions, the positive social dynamics in the
energy community increasing the amount of energy transacted by more than 10%
while contributing to a more balanced energy demand and supply within the
community.Comment: to be submitted to journa
ORGANIZATIONAL PERFORMANCE IS HIGHLY INFLUENCED BY MOTIVATION. A CASE STUDY OF THE PUBLIC HEALTH DIRECTORATE
High productivity is of primary concern to individuals, the management of any organization and to the national economy at large. Performance management in the health sector is essential for access to health services and for the provision of quality services. It is generally regarded as a well-known fact that an organization’s employees are a key asset for success. One of the most fascinating questions for specialists, but also one that causes headaches for managers in organizations, is “why are people motivated to do something?”. A human’s ambitions and goals may differ from one person to another, so motivation is a crucial aspect of health care management. Management can guide people to achieve the organization’s goals by identifying their unique qualities and potentials. The main objective of the study was to analyze the factors that motivate and demotivate employees in the Public Health Directorate, in order to find, or demonstrate that workplace satisfaction is influenced by a combination of factors, each of them having their own effect, contributing to the final result, which can be decisive in creating or not an productive equilibrum within the organizations that were subjected to research. Research methods: qualitative-quantitative analysis through the questionnaire-based survey method. Research thesis: Motivation plays a crucial role in organizational performance. This article concluded that not only financial benefits are important to both male and female employees, but also non-financial benefits and Managers must attach significant importance to motivational factors because these are the only ones capable of guaranteeing the success of such an approach
Povezanost polimorfizma rs1437396 gena CCDC88A s poremećajem zloporabe alkohola
Girdin is a protein involved in neuronal migration and hippocampal development. It is encoded by the coiled-coil domain-containing 88A (CCDC88A) gene, located on the short arm of chromosome 2 (2p). The CCDC88A gene is modulated by the intergenic single-nucleotide polymorphism (SNP) of the rs1437396, situated 9.5 kb downstream from its transcription stop site. As recent genome-wide research has associated the T allele of the SNP with increased risk of alcohol use disorder (AUD), we wanted to validate this finding in an independent cohort and to test further for an association with comorbid major depressive disorder (MDD). The study included 226 AUD patients (AUD group), 53 patients with comorbid MDD, and 391 controls selected randomly. The participants were genotyped for the rs1437396 polymorphism using the real-time polymerase chain reaction. The association between the rs1437396 polymorphism and increased risk of AUD and AUD+MDD was tested with logistic regression. Our results show significantly higher frequency of the T risk allele in the AUD group (p=0.027) and even higher in the AUD+MDD group (p=0.016). In conclusion, this is the first study that has validated the association between the rs1437396 polymorphism of the CCDC88A gene and AUD with or without MDD. Studies on larger samples of patients are needed to further investigate the mechanism of this association.Girdin je protein koji sudjeluje u neuronskoj migraciji i razvoju hipokampusa, a kodira ga gen 88A koji sadržava domenu sa smotanom zavojnicom (eng. coiled-coil domain-containing 88A gene, krat. CCDC88A) koja se nalazi na kraćem kraku kromosoma 2 (2p). Gen CCDC88A mijenja se s međugenskim jednonukleotidnim polimorfizmom (eng. single-nucleotide polymorphism, krat. SNP) na mjestu rs1437396, 9,5 kb nizvodno od svojega transkripcijskog završetka. Budući da je u nedavnom istraživanju na razini genoma zamijećena povezanost alela T ovoga polimorfizma s povećanim rizikom od poremećaja zloporabe alkohola (eng. alcohol use disorder), htjeli smo provjeriti tu povezanost u neovisnoj kohorti randomiziranih ispitanika i dodatno ispitati je li polimorfizam povezan i s popratnim povratnim depresivnim poremećajem (eng. major depressive disorder). Ispitivanje je obuhvatilo 226 bolesnika s poremećajem zloporabe alkohola, 51 bolesnika s popratnim povratnim depresivnim poremećajem i 391 kontrolnog ispitanika. Ispitanici su genotipizirani radi utvrđivanja onih koji imaju polimorfizam rs1437396 pomoću polimerazne lančane reakcije u stvarnom vremenu (eng. real-time polymerase chain reaction) te je logaritamskom regresijskom analizom utvrđena povezanost polimorfizma rs1437396 s rizikom od poremećaja zloporabe alkohola s popratnim povratnim depresivnim poremećajem ili bez njega. Naši podatci upućuju na značajno veću učestalost alela T u bolesnika s poremećajem zloporabe alkohola (p=0,027) te na još značajniju učestalost u bolesnika s obama poremećajima (p=0,016). Ovo je prvo istraživanje koje je potvrdilo povezanost između polimorfizma rs1437396 gena CCDC88A i poremećaja zloporabe alkohola s popratnim povratnim depresivnim poremećajem ili bez njega. Daljnja istraživanja mehanizama ove povezanosti potrebno je provesti na većim uzorcima
Edge Offloading in Smart Grid
The energy transition supports the shift towards more sustainable energy
alternatives, paving towards decentralized smart grids, where the energy is
generated closer to the point of use. The decentralized smart grids foresee
novel data-driven low latency applications for improving resilience and
responsiveness, such as peer-to-peer energy trading, microgrid control, fault
detection, or demand response. However, the traditional cloud-based smart grid
architectures are unable to meet the requirements of the new emerging
applications such as low latency and high-reliability thus alternative
architectures such as edge, fog, or hybrid need to be adopted. Moreover, edge
offloading can play a pivotal role for the next-generation smart grid AI
applications because it enables the efficient utilization of computing
resources and addresses the challenges of increasing data generated by IoT
devices, optimizing the response time, energy consumption, and network
performance. However, a comprehensive overview of the current state of research
is needed to support sound decisions regarding energy-related applications
offloading from cloud to fog or edge, focusing on smart grid open challenges
and potential impacts. In this paper, we delve into smart grid and
computational distribution architec-tures, including edge-fog-cloud models,
orchestration architecture, and serverless computing, and analyze the
decision-making variables and optimization algorithms to assess the efficiency
of edge offloading. Finally, the work contributes to a comprehensive
understanding of the edge offloading in smart grid, providing a SWOT analysis
to support decision making.Comment: to be submitted to journa
Smart Grid Management using Blockchain: Future Scenarios and Challenges
Decentralized management and coordination of energy systems are emerging
trends facilitated by the uptake of the Internet of Things and Blockchain
offering new opportunities for more secure, resilient, and efficient energy
distribution. Even though the use of distributed ledger technology in the
energy domain is promising, the development of decentralized smart grid
management solutions is in the early stages. In this paper, we define a layered
architecture of a blockchain-based smart grid management platform featuring
energy data metering and tamper-proof registration, business enforcement via
smart contracts, and Oracle-based integration of high computational services
supporting the implementation of future grid management scenarios. Three such
scenarios are discussed from the perspective of their implementation using the
proposed blockchain platform and associated challenges: peer to peer energy
trading, decentralized management, and aggregation of energy flexibility and
operation of community oriented Virtual Power Plants.Comment: Accepted and presented at: 19th RoEduNet Conference: Networking in
Education and Research, December 11-12, 202
A Deep Q-Learning based Smart Scheduling of EVs for Demand Response in Smart Grids
Economic and policy factors are driving the continuous increase in the
adoption and usage of electrical vehicles (EVs). However, despite being a
cleaner alternative to combustion engine vehicles, EVs have negative impacts on
the lifespan of microgrid equipment and energy balance due to increased power
demand and the timing of their usage. In our view grid management should
leverage on EVs scheduling flexibility to support local network balancing
through active participation in demand response programs. In this paper, we
propose a model-free solution, leveraging Deep Q-Learning to schedule the
charging and discharging activities of EVs within a microgrid to align with a
target energy profile provided by the distribution system operator. We adapted
the Bellman Equation to assess the value of a state based on specific rewards
for EV scheduling actions and used a neural network to estimate Q-values for
available actions and the epsilon-greedy algorithm to balance exploitation and
exploration to meet the target energy profile. The results are promising
showing that the proposed solution can effectively schedule the EVs charging
and discharging actions to align with the target profile with a Person
coefficient of 0.99, handling effective EVs scheduling situations that involve
dynamicity given by the e-mobility features, relying only on data with no
knowledge of EVs and microgrid dynamics.Comment: Submitted to journa
Quantum-Safe Protocols and Application in Data Security of Medical Records
The use of traditional cryptography based on symmetric keys has been replaced with the revolutionary idea discovered by Diffie and Hellman in 1976 that fundamentally changed communication systems by ensuring a secure transmission of information over an insecure channel. Nowadays public key cryptography is frequently used for authentication in e-commerce, digital signatures and encrypted communication. Most of the public key cryptosystems used in practice are based on integer factorization (the famous RSA cryptosystem proposed by Rivest, Shamir and Adlemann), respectively on the discrete logarithm (in finite curves or elliptic curves). However these systems suffer from two potential drawbacks like efficiency because they must use large keys to maintain security and of course security breach with the advent of the quantum computer as a result of Peter Shor\u27s discovery in 1999 of the polynomial algorithm for solving problems such factorization of integers and discrete logarithm
Expert System for Nutrition Care Process of Older Adults
This paper presents an expert system for a nutrition care process tailored for the specific needs of elders. Dietary knowledge is defined by nutritionists and encoded as Nutrition Care Process Ontology, and then used as underlining base and standardized model for the nutrition care planning. An inference engine is developed on top of the ontology, providing semantic reasoning infrastructure and mechanisms for evaluating the rules defined for assessing short and long term elders’ self-feeding behaviours, to identify unhealthy dietary patterns and detect the early instauration of malnutrition. Our expert system provides personalized intervention plans covering nutrition education, diet prescription and food ordering adapted to the older adult’s specific nutritional needs, health conditions and food preferences. In-lab evaluation results are presented proving the usefulness and quality of the expert system as well as the computational efficiency, coupling and cohesion of the defined ontology
A service-based system for malnutrition prevention and self-management
Malnutrition is considered one of the root causes for the occurrence of other diseases. It is particularly common in the ageing population, where it requires more efficient handling and management to enable longer home independent living. However, to achieve this, a number of related challenges need to be overcome, especially those related to management of health and disease let alone other social and logistical barriers. This paper presents the design of a distributed system that enables homecare management in the context of self-feeding and malnutrition prevention through balanced nutritional intake. The design employs a service-based system that incorporates a number of services including monitoring of activities, nutritional reasoning for assessing feeding habits, diet recommendation for food planning, and marketplace invocation for automating food shopping to meet dietary requirements. The solution is deployed in a small pilot in 12 elder adult houses that, in early results, demonstrates its holistic user-centred scalable approach for malnutrition self-management
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