Self-Adaptive Global-Best Harmony Search Algorithm-Based Airflow Control of a Wells-Turbine-Based Oscillating-Water Column

The Harmony Search algorithm has attracted a lot of interest in the past years because of its simplicity and efficiency. This led many scientists to develop various variants for many applications. In this paper, four variants of the Harmony search algorithm were implemented and tested to optimize the control design of the Proportional-Integral-derivative (PID) controller in a proposed airflow control scheme. The airflow control strategy has been proposed to deal with the undesired stalling phenomenon of the Wells turbine in an Oscillating Water Column (OWC). To showcase the effectiveness of the Self-Adaptive Global Harmony Search (SGHS) algorithm over traditional tuning methods, a comparative study has been carried out between the optimized PID, the traditionally tuned PID and the uncontrolled OWC system. The results of optimization showed that the Self-Adaptive Global Harmony Search (SGHS) algorithm adapted the best to the problem of the airflow control within the wave energy converter. Moreover, the OWC performance is superior when using the SGHS-tuned PID.This work was supported in part by the Basque Government, through project IT1207-19 and by the MCIU/MINECO through RTI2018-094902-B-C21 / RTI2018-094902-B-C22 (MCIU/AEI/FEDER, UE)

Self-Efficacy and Post-Secondary First-Term Student Achievement

Generalized self-efficacy is the overall belief in one’s ability and Specific self-efficacy is task related. The study examined the extent and manner in which self-efficacy explains variation in first-term GPA. The General Self-Efficacy Scale was adapted and used with a sample of N = 194 students (34% male and 66% female) enrolled in a for-profit career education urban college. The data from two factors derived using an exploratory factor analysis, General self-efficacy and Specific self-efficacy, had alpha reliabilities of .73 and .75, respectively. General self-efficacy was correlated r = .18 with GPA and multiple regression analysis demonstrated that General incremented the explanation of variance 5% in GPA (p \u3c .01). Specific correlated r = .17 with GPA (p \u3c .05). General and Specific were significantly correlated (r = .42, p \u3c .001). The two independent variables were equal predictors of success

Self-Management of Chronic Fatigue Syndrome in Adolescents

Chronic fatigue syndrome (CFS) or myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a condition of unknown aetiology that commonly follows an infection. There are no known predictors for recovery or established treatments. At the Royal Children’s Hospital (RCH) in Melbourne, Australia, the majority of young people with CFS are provided with symptom management and lifestyle guidance in an outpatient setting. However, for some, educational or social issues preclude progress and for those who request this assistance, since 2012, the Victorian Paediatric Rehabilitation Service has offered an Intensive Self-Management Program. For this program, participants engage in both group and individual sessions, attending 3 days per week for 4 weeks in small groups of 3–4. Interdisciplinary input is from Occupational Therapy, Physiotherapy, Education and Psychology to assist with goal setting and strategies. Outcome measures are obtained at initial assessment, 6 weeks and 6 months post-program. Support is offered for 12 months post-program. For both the outpatient program and the intensive program the outcomes and feedback from patient and family has influenced the approach and focus. This chapter outlines the current approach and how it has evolved over time

Self-Efficacy, Trait Mindfulness, and Self-Compassion as Predictors of Risk of Substance Use Relapse

Previous research has demonstrated relationships among mindfulness, self-efficacy, and substance use relapse. Contrasting research has found mindfulness and self-efficacy are not consistently negatively associated with substance use relapse demonstrating a need for further research. An additional factor that has been found to associated with substance use is self-compassion; however, it has yet to be examined in relation to the process of relapse. The current study assessed self-efficacy, self-compassion, and mindfulness and their associations with substance use relapse, with the aim of predicting relapse risk. Higher levels of relapse risk were found to be negatively associated with self-efficacy, trait mindfulness, and self-compassion. Additionally, through a hierarchical regression, self-efficacy was found to significantly predict relapse risk. After adding trait mindfulness into the regression model, significantly more variance was explained for relapse risk. However, when self-compassion was added into the model, it was found to be still predictive of relapse risk but did not add a significant amount of variance to the model. Findings suggest that individuals with higher levels of self-compassion, self-efficacy and trait mindfulness are less likely to relapse while in recovery from substance use. The current study’s findings indicate these three variables play a role in substance use relapse and have potential to be utilized in integrated relapse prevention treatments. Implications for substance use programs and integrated treatments are discussed, as well as strengths and limitations of the study and suggestions for future research

Self-Forecasting Energy Load Stakeholders for Smart Grids

The unpredictability of energy loads is responsible for a significant portion of efficiency loss in power grids. In order to reduce load uncertainties, emerging Smart Grid business models call for the active participation of traditionally passive stakeholders. The contribution of this work enables self-forecasting energy load stakeholders whose deterministic load behaviour make them reliable resources that can greatly benefit themselves and other Smart Grid stakeholders

Self-Organised Schools

Self-Organised Schools: Educational Leadership and Innovative Learning Environments describes the results of the research we carried out at fourteen Italian schools that highlight how there is a positive correlation between the capabilities of school self-organization and the innovativeness of learning environments: in other words, the more self-organized schools are, the more innovative learning environments are. The results of this work are part of the strand of research of bottom-up emergency and self-organization, an extremely fruitful trend as shown by Sugata Mitra, the founder of the Self-Organized Learning Environments, according to whom, "education is a self-organized system where learning is an emerging phenomenon". This book gives new insights on self-organization studies, and most of all, to the idea that change - organizational and educational innovation - sparks from the bottom. This book is aimed specifically at school principals of all levels, scholastic reformers, educational scholars, organisation and management consultants who want to innovate learning and management of learning. These actors will benefit drawing useful examples from more than thirty different learning environments worldwide, fourteen examples of schools that self-organize, two frameworks - and two ready-to-use questionnaires - measuring the innovativeness of a learning environment, and the capability of a school to self-organize. Self-organization is the most fascinating future of innovative principal

Self-Motivated Composition of Strategic Action Policies

In the last 50 years computers have made dramatic progress in their capabilities, but at the same time their failings have demonstrated that we, as designers, do not yet understand the nature of intelligence. Chess playing, for example, was long offered up as an example of the unassailability of the human mind to Artificial Intelligence, but now a chess engine on a smartphone can beat a grandmaster. Yet, at the same time, computers struggle to beat amateur players in simpler games, such as Stratego, where sheer processing power cannot substitute for a lack of deeper understanding. The task of developing that deeper understanding is overwhelming, and has previously been underestimated. There are many threads and all must be investigated. This dissertation explores one of those threads, namely asking the question “How might an artificial agent decide on a sensible course of action, without being told what to do?”. To this end, this research builds upon empowerment, a universal utility which provides an entirely general method for allowing an agent to measure the preferability of one state over another. Empowerment requires no explicit goals, and instead favours states that maximise an agent’s control over its environment. Several extensions to the empowerment framework are proposed, which drastically increase the array of scenarios to which it can be applied, and allow it to evaluate actions in addition to states. These extensions are motivated by concepts such as bounded rationality, sub-goals, and anticipated future utility. In addition, the novel concept of strategic affinity is proposed as a general method for measuring the strategic similarity between two (or more) potential sequences of actions. It does this in a general fashion, by examining how similar the distribution of future possible states would be in the case of enacting either sequence. This allows an agent to group action sequences, even in an unknown task space, into ‘strategies’. Strategic affinity is combined with the empowerment extensions to form soft-horizon empowerment, which is capable of composing action policies in a variety of unknown scenarios. A Pac-Man-inspired prey game and the Gambler’s Problem are used to demonstrate this selfmotivated action selection, and a Sokoban inspired box-pushing scenario is used to highlight the capability to pick strategically diverse actions. The culmination of this is that soft-horizon empowerment demonstrates a variety of ‘intuitive’ behaviours, which are not dissimilar to what we might expect a human to try. This line of thinking demonstrates compelling results, and it is suggested there are a couple of avenues for immediate further research. One of the most promising of these would be applying the self-motivated methodology and strategic affinity method to a wider range of scenarios, with a view to developing improved heuristic approximations that generate similar results. A goal of replicating similar results, whilst reducing the computational overhead, could help drive an improved understanding of how we may get closer to replicating a human-like approach

Self-Defense to Cyber Force: Combatting the Notion of \u27Scale and Effect\u27

The ability to reach out, with a few keystrokes or a couple lines of code, through the interconnected world of cyberspace and create militarily advantageous effects 10,000 miles away has changed warfare as previously conceived, perhaps more than any other advancement in any other domain of war. Cyber weapons are weapons, and whatever law applies to conventional weapons equally applies to cyber weapons. Long before cyber operations were even science fiction, there was much debate over what constituted a use of force that would justify force in response. In many ways, the debate over what constitutes cyber-attacks has been pasted on top of that older debate, but the unique form of harm that cyber-attacks cause adds novel questions to these older debates. Lacking a physical instrument, yet possessing the potential to cause greater harm, cyber-attacks seem simultaneously less and more forceful. How one views that dichotomy, coupled with how they generally view the Charter regarding conventional force, has led to varying answers to the salient question: what is the threshold of cyber force required to justify the use of counterforce in self-defense