Artificial Intelligence (AI) Techniques for Maximizing Value of Power Generating Assets

2018 ◽  
Author(s):  
Komandur Sunder Raj
Keyword(s):  
Artificial Intelligence ◽  
Power Industry ◽  
The Past ◽  
Power Plant Equipment ◽  
Industrial Internet ◽  
Plant Operations ◽  
Plant Equipment ◽  
And Performance ◽  
Self Learning ◽  
Digital Assets

For over two decades, there has been considerable interest in and research devoted to the use of artificial intelligence (AI) for maximizing the value of power generating assets. AI may be thought of as application of intelligence in a systematic and rational manner to power plant equipment, components and processes for self-learning and solving complex problems. AI techniques are increasingly finding applications in the power industry in addressing issues related to performance, reliability, availability, maintenance, automation, cybersecurity, workforce, and others. In the past several years, pace has accelerated in AI techniques, largely stemming from increased speed and power in computing, advances in technology, and utilization of algorithms. The Industrial Internet of Things (IIoT) is rapidly gaining ground by leveraging AI, digital assets and data analytics in managing and optimizing plant operations and performance of power generating assets. This paper provides an overview of how AI techniques are being utilized to maximize the value of power generating assets and prognosis for future use of AI in the power industry.

scholarly journals Knowledge base of wind farm devices in the computer expert system

2018 ◽  
Vol 67 (2) ◽  
pp. 179-190
Author(s):  
Radosław Duer ◽  
Paweł Wrzesień ◽  
Stanisław Duer ◽  
Dariusz Bernatowicz
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Knowledge Base ◽  
Wind Farm ◽  
Diagnostic Information ◽  
Diagnostic Model ◽  
Technical Diagnostics ◽  
Wind Power Plant ◽  
Power Plant Equipment ◽  
Plant Equipment

The article presents the problems of determining diagnostic information for the needs of testing the state of wind farm equipment. To this end, the essence of developing a functional and diagnostic model on the example of wind power plant equipment has been presented and described. Based on the developed model of the examined object, diagnostic information was determined in the form of a set of basic elements and a set of diagnostic signals, which are developed by the designated j-elements in the i-functional units of the object. The article presents a description of the process of building a knowledge base for an expert system. Keywords: technical diagnostics, diagnostic reasoning, multivalent logic, artificial intelligence

NICROFER 6023

Alloy Digest ◽  
1985 ◽  
Vol 34 (5) ◽  
Keyword(s):  
Mechanical Properties ◽  
Elevated Temperatures ◽  
Iron Alloy ◽  
Heat Treating ◽  
Chemical Equipment ◽  
Good Resistance ◽  
Nickel Chromium ◽  
Power Plant Equipment ◽  
Resistance To Oxidation ◽  
Plant Equipment

Abstract NICROFER 6023 is a nickel-chromium-iron alloy containing small quantities of aluminum. It has excellent resistance to oxidation at high temperatures, good resistance in oxidizing sulfur-bearing atmospheres and good resistance to carburizing conditions. The alloy has good mechanical properties at room and elevated temperatures. Its applications include heat treating furnace equipment, chemical equipment in various industries, and power plant equipment. This datasheet provides information on composition, physical properties, elasticity, and tensile properties as well as creep. It also includes information on corrosion resistance as well as forming, heat treating, machining, and joining. Filing Code: Ni-314. Producer or source: Vereingte Deutsche Metallwerke AG.

Progress and Prospects in Translating Nanobiotechnology in Medical Theranostics

2020 ◽  
Vol 16 (5) ◽  
pp. 685-707 ◽  
Author(s):  
Amna Batool ◽  
Farid Menaa ◽  
Bushra Uzair ◽  
Barkat Ali Khan ◽  
Bouzid Menaa
Keyword(s):  
Biological Properties ◽  
Chemical Characteristics ◽  
Intrinsic Properties ◽  
The Past ◽  
Profound Influence ◽  
Functionalized Nanomaterials ◽  
Physico Chemical ◽  
Properties Of Materials ◽  
Targeted Drug ◽  
And Performance

: The pace at which nanotheranostic technology for human disease is evolving has accelerated exponentially over the past five years. Nanotechnology is committed to utilizing the intrinsic properties of materials and structures at submicroscopic-scale measures. Indeed, there is generally a profound influence of reducing physical dimensions of particulates and devices on their physico-chemical characteristics, biological properties, and performance. The exploration of nature’s components to work effectively as nanoscaffolds or nanodevices represents a tremendous and growing interest in medicine for various applications (e.g., biosensing, tunable control and targeted drug release, tissue engineering). Several nanotheranostic approaches (i.e., diagnostic plus therapeutic using nanoscale) conferring unique features are constantly progressing and overcoming all the limitations of conventional medicines including specificity, efficacy, solubility, sensitivity, biodegradability, biocompatibility, stability, interactions at subcellular levels. : This review introduces two major aspects of nanotechnology as an innovative and challenging theranostic strategy or solution: (i) the most intriguing (bare and functionalized) nanomaterials with their respective advantages and drawbacks; (ii) the current and promising multifunctional “smart” nanodevices.

Pupil with Obsessive-Compulsive Disorder

2017 ◽  
Vol 7 (2) ◽  
pp. 7-25
Author(s):  
Karolina Diallo
Keyword(s):  
Obsessive Compulsive Disorder ◽  
School Performance ◽  
School Environment ◽  
Detrimental Effect ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
The Past ◽  
And Performance ◽  
The Impact

Pupil with Obsessive-Compulsive Disorder. Over the past twenty years childhood OCD has received more attention than any other anxiety disorder that occurs in the childhood. The increasing interest and research in this area have led to increasing number of diagnoses of OCD in children and adolescents, which affects both specialists and teachers. Depending on the severity of symptoms OCD has a detrimental effect upon child's school performance, which can lead almost to the impossibility to concentrate on school and associated duties. This article is devoted to the obsessive-compulsive disorder and its specifics in children, focusing on the impact of this disorder on behaviour, experience and performance of the child in the school environment. It mentions how important is the role of the teacher in whose class the pupil with this diagnosis is and it points out that it is necessary to increase teachers' competence to identify children with OCD symptoms, to take the disease into the account, to adapt the course of teaching and to introduce such measures that could help children reduce the anxiety and maintain (or increase) the school performance within and in accordance with the school regulations and curriculum.

The Future of Work and the Changing Workplace

2018 ◽  
Author(s):  
Mahesh K. Joshi ◽  
J.R. Klein
Keyword(s):  
Artificial Intelligence ◽  
Machine Intelligence ◽  
Political Issue ◽  
Digital Innovation ◽  
Future Of Work ◽  
The Past ◽  
The World ◽  
Public Debates ◽  
The Future ◽  
Market Opportunities

The world of work has been impacted by technology. Work is different than it was in the past due to digital innovation. Labor market opportunities are becoming polarized between high-end and low-end skilled jobs. Migration and its effects on employment have become a sensitive political issue. From Buffalo to Beijing public debates are raging about the future of work. Developments like artificial intelligence and machine intelligence are contributing to productivity, efficiency, safety, and convenience but are also having an impact on jobs, skills, wages, and the nature of work. The “undiscovered country” of the workplace today is the combination of the changing landscape of work itself and the availability of ill-fitting tools, platforms, and knowledge to train for the requirements, skills, and structure of this new age.

Artificial Intelligence and Human Rights: Four Realms of Discussion: Summary of Remarks

2020 ◽  
Vol 114 ◽  
pp. 242-245
Author(s):  
Jootaek Lee
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Deep Learning ◽  
Language Processing ◽  
Human Reasoning ◽  
The Past ◽  
Making Choices ◽  
Data Capturing ◽  
Intensive Procedures

The term, Artificial Intelligence (AI), has changed since it was first coined by John MacCarthy in 1956. AI, believed to have been created with Kurt Gödel's unprovable computational statements in 1931, is now called deep learning or machine learning. AI is defined as a computer machine with the ability to make predictions about the future and solve complex tasks, using algorithms. The AI algorithms are enhanced and become effective with big data capturing the present and the past while still necessarily reflecting human biases into models and equations. AI is also capable of making choices like humans, mirroring human reasoning. AI can help robots to efficiently repeat the same labor intensive procedures in factories and can analyze historic and present data efficiently through deep learning, natural language processing, and anomaly detection. Thus, AI covers a spectrum of augmented intelligence relating to prediction, autonomous intelligence relating to decision making, automated intelligence for labor robots, and assisted intelligence for data analysis.

scholarly journals Characterizing Bilingual Effects on Cognition: The Search for Meaningful Individual Differences

2021 ◽  
Vol 11 (1) ◽  
pp. 81
Author(s):  
Kristina C. Backer ◽  
Heather Bortfeld
Keyword(s):  
Individual Differences ◽  
Cognitive Processes ◽  
Language Background ◽  
Bilingual Advantage ◽  
The Past ◽  
General Movement ◽  
And Performance ◽  
Task Irrelevant ◽  
Analytical Approaches ◽  
The Relationship

A debate over the past decade has focused on the so-called bilingual advantage—the idea that bilingual and multilingual individuals have enhanced domain-general executive functions, relative to monolinguals, due to competition-induced monitoring of both processing and representation from the task-irrelevant language(s). In this commentary, we consider a recent study by Pot, Keijzer, and de Bot (2018), which focused on the relationship between individual differences in language usage and performance on an executive function task among multilingual older adults. We discuss their approach and findings in light of a more general movement towards embracing complexity in this domain of research, including individuals’ sociocultural context and position in the lifespan. The field increasingly considers interactions between bilingualism/multilingualism and cognition, employing measures of language use well beyond the early dichotomous perspectives on language background. Moreover, new measures of bilingualism and analytical approaches are helping researchers interrogate the complexities of specific processing issues. Indeed, our review of the bilingualism/multilingualism literature confirms the increased appreciation researchers have for the range of factors—beyond whether someone speaks one, two, or more languages—that impact specific cognitive processes. Here, we highlight some of the most salient of these, and incorporate suggestions for a way forward that likewise encompasses neural perspectives on the topic.

Embodying algorithms, enactive artificial intelligence and the extended cognition: You can see as much as you know about algorithm

2021 ◽  
pp. 016555152098549
Author(s):  
Donghee Shin
Keyword(s):  
Artificial Intelligence ◽  
Embodied Cognition ◽  
Cognitive Processes ◽  
Process Model ◽  
Extended Cognition ◽  
Dual Process ◽  
Personalized Recommendation ◽  
Normative Values ◽  
And Performance ◽  
Concise Guide

The recent proliferation of artificial intelligence (AI) gives rise to questions on how users interact with AI services and how algorithms embody the values of users. Despite the surging popularity of AI, how users evaluate algorithms, how people perceive algorithmic decisions, and how they relate to algorithmic functions remain largely unexplored. Invoking the idea of embodied cognition, we characterize core constructs of algorithms that drive the value of embodiment and conceptualizes these factors in reference to trust by examining how they influence the user experience of personalized recommendation algorithms. The findings elucidate the embodied cognitive processes involved in reasoning algorithmic characteristics – fairness, accountability, transparency, and explainability – with regard to their fundamental linkages with trust and ensuing behaviors. Users use a dual-process model, whereby a sense of trust built on a combination of normative values and performance-related qualities of algorithms. Embodied algorithmic characteristics are significantly linked to trust and performance expectancy. Heuristic and systematic processes through embodied cognition provide a concise guide to its conceptualization of AI experiences and interaction. The identified user cognitive processes provide information on a user’s cognitive functioning and patterns of behavior as well as a basis for subsequent metacognitive processes.

scholarly journals Boundaries Between Research Ethics and Ethical Research Use in Artificial Intelligence Health Research

2021 ◽  
pp. 155626462110027
Author(s):  
Gabrielle Samuel ◽  
Jenn Chubb ◽  
Gemma Derrick
Keyword(s):  
Artificial Intelligence ◽  
Health Research ◽  
Decision Makers ◽  
Societal Impact ◽  
The Past ◽  
Research And Innovation ◽  
The United Kingdom ◽  
Responsible Research ◽  
Past Half

The governance of ethically acceptable research in higher education institutions has been under scrutiny over the past half a century. Concomitantly, recently, decision makers have required researchers to acknowledge the societal impact of their research, as well as anticipate and respond to ethical dimensions of this societal impact through responsible research and innovation principles. Using artificial intelligence population health research in the United Kingdom and Canada as a case study, we combine a mapping study of journal publications with 18 interviews with researchers to explore how the ethical dimensions associated with this societal impact are incorporated into research agendas. Researchers separated the ethical responsibility of their research with its societal impact. We discuss the implications for both researchers and actors across the Ethics Ecosystem.

Sign in / Sign up

Export Citation Format

Share Document