Energy markets are based on energy transactions with a central control entity, where the players are companies. In this research work, we propose an IoT (Internet of Things) system for the accounting of energy flows, as well as a blockchain approach to overcome the need for a central control entity. This allows for the creation of local energy markets to handle distributed energy transactions without needing central control. In parallel, the system aggregates users into communities with target goals and creates new markets for players. These two approaches (blockchain and IoT) are brought together using a gamification approach, allowing for the creation and maintenance of a community for electricity market participation based on pre-defined goals. This community approach increases the number of market players and creates the possibility of traditional end users earning money through small coordinated efforts. We apply this approach to the aggregation of batteries from electrical vehicles so that they become a player in the spinning reserve market. It is also possible to apply this approach to local demand flexibility, associated with the demand response (DR) concept. DR is aggregated to allow greater flexibility in the regulation market based on an OpenADR approach that allows the turning on and off of predefined equipment to handle local microgeneration.
Assessing service quality has become a major issue in the healthcare sector. Although direct evaluation has already taken place, literature is scarce in terms of the impact the distance covered by the user has on perceived service quality. The aim of this study was to assess the influence distance has on perceived service quality when no similar service alternatives are available. The Servperf instrument was used to collect data. All women who delivered babies in autumn 2011 were respondents to the questionnaire. Exploratory analysis was used to test research hypotheses. Cronbach's alphas were computed to assess internal consistency. Findings show that Assurance is the quality dimension that contributes the most to patients' perceived service quality and Tangibles is the one that contributes the least. It was also possible to conclude that the distance the patient has to cover to be served and its educational level influence patients' perception of the service provided.
Purpose Supply chain relationships have often been analysed from the macro-perspective of the companies involved, but there is less evidence of how relationships relate to the micro-perspective of persons involved. The purpose of this paper is to investigate, in IT outsourcing (ITO), how the buyer–supplier relationship type strengthens buyer performance from the perspective of consultants. Design/methodology/approach IT consultants were surveyed, and analysis was performed considering the aggregated values of variables that characterise buyer–supplier relationships adjusted to ITO. Findings The results show that strategic relationships are associated with higher supplier investment in relational management than in transactional ones. Similarly, in this type of relationship, higher levels of trust are linked to the recognition of more activities shared between parties involved than in transactional relationships. The improvement of supplier development by buyers was also found to improve buyers’ performance. Research limitations/implications The model proposed here was developed for nonspecific industries but tested in the context of ITO. Further research should be undertaken to broaden generalisability. Originality/value The paper provides an understanding of the influence of the buyer–supplier relationship type on buyer performance based both on relational management and, more specifically, how the formal dimension of supplier development can also contribute to performance. ITO is increasing worldwide, and relational management affects outsourcing outcomes in broad supply chain integration. This analysis is usually visited from buyer and supplier perspectives using decision makers. This paper assesses it from the perspective of consultants.
The smart city concept, in which data from different systems are available, contains a multitude of critical infrastructures. This data availability opens new research opportunities in the study of the interdependency between those critical infrastructures and cascading effects solutions and focuses on the smart city as a network of critical infrastructures. This paper proposes an integrated resilience system linking interconnected critical infrastructures in a smart city to improve disaster resilience. A data-driven approach is considered, using artificial intelligence and methods to minimize cascading effects and the destruction of failing critical infrastructures and their components (at a city level). The proposed approach allows rapid recovery of infrastructures’ service performance levels after disasters while keeping the coverage of the assessment of risks, prevention, detection, response, and mitigation of consequences. The proposed approach has the originality and the practical implication of providing a decision support system that handles the infrastructures that will support the city disaster management system—make the city prepare, adapt, absorb, respond, and recover from disasters by taking advantage of the interconnections between its various critical infrastructures to increase the overall resilience capacity. The city of Lisbon (Portugal) is used as a case to show the practical application of the approach.
A vessel monitoring system (VMS) is responsible for real-time vessel movement tracking. At sea, most of the tracking systems use satellite communications, which have high associated costs. This leads to a less frequent transmission of data, which reduces the reliability of the vessel location. Our research work involves the creation of an edge computing approach on a local VMS, creating an intelligent process that decides whether the collected data needs to be transmitted or not. Only relevant data that can indicate abnormal behavior is transmitted. The remaining data is stored and transmitted only at ports when communication systems are available at lower prices. In this research, we apply this approach to a fishing control process increasing the data collection process from once every 10 min to once every 30 s, simultaneously decreasing the satellite communication costs, as only relevant data is transmitted in real-time to the competent central authorities. Findings show substantial communication savings from 70% to 90% as only abnormal vessel behavior is transmitted. Even with a data collection process of once every 30 s, findings also show that the use of more stable fishing techniques and fishing areas result in higher savings. The proposed approach is assessed as well in terms of the environmental impact of fishing and potential fraud detection and reduction.
Medicine is a knowledge area continuously experiencing changes. Every day, discoveries and procedures are tested with the goal of providing improved service and quality of life to patients. With the evolution of computer science, multiple areas experienced an increase in productivity with the implementation of new technical solutions. Medicine is no exception. Providing healthcare services in the future will involve the storage and manipulation of large volumes of data (big data) from medical records, requiring the integration of different data sources, for a multitude of purposes, such as prediction, prevention, personalization, participation, and becoming digital. Data integration and data sharing will be essential to achieve these goals. Our work focuses on the development of a framework process for the integration of data from different sources to increase its usability potential. We integrated data from an internal hospital database, external data, and also structured data resulting from natural language processing (NPL) applied to electronic medical records. An extract-transform and load (ETL) process was used to merge different data sources into a single one, allowing more effective use of these data and, eventually, contributing to more efficient use of the available resources.
City parking is increasingly complex and available parking spaces are scarce. Being able to identify a space to park their cars can lead many drivers to drive around the intended parking area several times, increasing traffic density and pollution. In this research, we propose a collaborative blockchain solution with gamification for parking. Users collaborate to report free spaces and receive free parking minutes for their service to the community. In parallel, this approach can be used to collect beacon information from the parked vehicles and create a low-cost collaborative approach for managing a parking control process platform Blockchain that can handle this distributed process and the gamification platform increases users' participation.
In this work we propose and develop a classification model to be used in a quality control system for clothing manufacturing using machine learning algorithms. The system consists of using pictures taken through mobile devices to detect defects on production objects. In this work a defect can be a missing component or a wrong component in a production object. Therefore, the function of system is to classify the components that compose a production object through the use of a classification model. As a manufacturing business progresses, new objects are created, thus, the classification model must be able to learn the new classes without losing previous knowledge. However, most classification algorithms do not support an increase of classes, these need to be trained from scratch with all classes. In this work, we make use of an incremental learning algorithm to tackle this problem. This algorithm classifies features extracted from pictures of the production objects using a convolutional neural network (CNN), which have proven to be very successfully in image classification problems. We apply the current developed approach to a process in clothing manufacturing. Therefore, the production objects correspond to clothing items.
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