Stream Learning in Energy IoT Systems: A Case Study in Combined Cycle Power Plants

The prediction of electrical power produced in combined cycle power plants is a key challenge in the electrical power and energy systems field. This power production can vary depending on environmental variables, such as temperature, pressure, and humidity. Thus, the business problem is how to predict the power production as a function of these environmental conditions, in order to maximize the profit. The research community has solved this problem by applying Machine Learning techniques, and has managed to reduce the computational and time costs in comparison with the traditional thermodynamical analysis. Until now, this challenge has been tackled from a batch learning perspective, in which data is assumed to be at rest, and where models do not continuously integrate new information into already constructed models. We present an approach closer to the Big Data and Internet of Things paradigms, in which data are continuously arriving and where models learn incrementally, achieving significant enhancements in terms of data processing (time, memory and computational costs), and obtaining competitive performances. This work compares and examines the hourly electrical power prediction of several streaming regressors, and discusses about the best technique in terms of time processing and predictive performance to be applied on this streaming scenario.This work has been partially supported by the EU project iDev40. This project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 783163. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Germany, Belgium, Italy, Spain, Romania. It has also been supported by the Basque Government (Spain) through the project VIRTUAL (KK-2018/00096), and by Ministerio de Economía y Competitividad of Spain (Grant Ref. TIN2017-85887-C2-2-P)

Blockchain Mediated Control: A Case Study of Implementation Strategies in Permissioned and Permissionless Blockchain Projects

Blockchain could improve existing business processes by enabling networks of users, businesses, partners, and others to execute transactions trusted through cryptography, decentralization, and consensus. The financial technology (fintech) industry has been the first adopter of blockchain technology, which has set an example for other industries to translate blockchain’s unique attributes to other use cases. However, blockchain could disrupt existing organizational governance and decision-making. Lacking knowledge of the complex landscape in which blockchain operates, concerns arise, driving organizations and researchers alike to investigate technological- and organizational outcomes. In this dissertation, we investigate how Blockchain can function as a Technology-Mediated Control technology and how this can affect network participants. To evaluate various adoption intentions, we employ a case study in conjunction with a literature review. Interviews with project managers from various Norwegian organizations utilizing either permissioned or permissionless blockchains provided us with their perspective on the processes and potential structural changes. Legacy systems in processes outside the jurisdiction of the respective organizations was a common concern, according to both research papers and interviews. Consequently, the maturity of technological factors is a significant barrier for organizations to implement blockchain, necessitating a new standard of cooperation between organizations. According to the research, the most significant contribution is the theory of blockchain-mediated control, whereas blockchain functions as the technology that mediates control. In addition, we identified a potential risk propagation within the theory that eludes current solutions: the oracle problem in smart contracts

Blockchain Mediated Control: A Case Study of Implementation Strategies in Permissioned and Permissionless Blockchain Projects

Blockchain could improve existing business processes by enabling networks of users, businesses, partners, and others to execute transactions trusted through cryptography, decentralization, and consensus. The financial technology (fintech) industry has been the first adopter of blockchain technology, which has set an example for other industries to translate blockchain’s unique attributes to other use cases. However, blockchain could disrupt existing organizational governance and decision-making. Lacking knowledge of the complex landscape in which blockchain operates, concerns arise, driving organizations and researchers alike to investigate technological- and organizational outcomes. In this dissertation, we investigate how Blockchain can function as a Technology-Mediated Control technology and how this can affect network participants. To evaluate various adoption intentions, we employ a case study in conjunction with a literature review. Interviews with project managers from various Norwegian organizations utilizing either permissioned or permissionless blockchains provided us with their perspective on the processes and potential structural changes. Legacy systems in processes outside the jurisdiction of the respective organizations was a common concern, according to both research papers and interviews. Consequently, the maturity of technological factors is a significant barrier for organizations to implement blockchain, necessitating a new standard of cooperation between organizations. According to the research, the most significant contribution is the theory of blockchain-mediated control, whereas blockchain functions as the technology that mediates control. In addition, we identified a potential risk propagation within the theory that eludes current solutions: the oracle problem in smart contracts

Probabilistic Computability and Choice

We study the computational power of randomized computations on infinite objects, such as real numbers. In particular, we introduce the concept of a Las Vegas computable multi-valued function, which is a function that can be computed on a probabilistic Turing machine that receives a random binary sequence as auxiliary input. The machine can take advantage of this random sequence, but it always has to produce a correct result or to stop the computation after finite time if the random advice is not successful. With positive probability the random advice has to be successful. We characterize the class of Las Vegas computable functions in the Weihrauch lattice with the help of probabilistic choice principles and Weak Weak K\H{o}nig's Lemma. Among other things we prove an Independent Choice Theorem that implies that Las Vegas computable functions are closed under composition. In a case study we show that Nash equilibria are Las Vegas computable, while zeros of continuous functions with sign changes cannot be computed on Las Vegas machines. However, we show that the latter problem admits randomized algorithms with weaker failure recognition mechanisms. The last mentioned results can be interpreted such that the Intermediate Value Theorem is reducible to the jump of Weak Weak K\H{o}nig's Lemma, but not to Weak Weak K\H{o}nig's Lemma itself. These examples also demonstrate that Las Vegas computable functions form a proper superclass of the class of computable functions and a proper subclass of the class of non-deterministically computable functions. We also study the impact of specific lower bounds on the success probabilities, which leads to a strict hierarchy of classes. In particular, the classical technique of probability amplification fails for computations on infinite objects. We also investigate the dependency on the underlying probability space.Comment: Information and Computation (accepted for publication

Automated Support for the Design and Validation of Fault Tolerant Parameterized Systems: a case study

We propose a methodology to use the infinite state model checker MCMT, based on Satisfiability Modulo Theory techniques, for assisting in the design of fault tolerant algorithms. To prove the practical viability of our methodology, we apply it to formally check the agreement property of the reliable broadcast protocols of Chandra and Toueg

Phenomenology of Philosophy of Science: OPERA data

I observe that, as the physics side of the OPERA-anomaly story is apparently unfolding, there can still be motivation for philosophy of science to analyze the six months of madness physicists spent chasing the dream of a new fundamental-physics revolution. I here mainly report data on studies of the OPERA anomaly that could be relevant for analyses from the perspective of phenomenology of philosophy of science. Most of what I report is an insider's perspective on the debate that evolved from the original announcement by the OPERA collaboration of evidence of superluminal neutrinos. I also sketch out, from a broader perspective, some of the objectives I view as achievable for the phenomenology of philosophy of science.Comment: 13 pages, LaTe