scholarly journals A Belief Update System Using an Event Model for Location of People in a Smart Home

2021 ◽  
pp. 17-32
Author(s):  
Marie Bernert ◽  
Fano Ramparany
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Smart Home ◽  
Current Knowledge ◽  
Sequence Of Events ◽  
New Information ◽  
Event Model ◽  
Location Inference

AbstractArtificial Intelligence applications often require to maintain a knowledge base about the observed environment. In particular, when the current knowledge is inconsistent with new information, it has to be updated. Such inconsistency can be due to erroneous assumptions or to changes in the environment. Here we considered the second case, and develop a knowledge update algorithm based on event logic that takes into account constraints according to which the environment can evolve. These constraints take the form of events that modify the environment in a well-defined manner. The belief update triggered by a new observation is thus explained by a sequence of events. We then apply this algorithm to the problem of locating people in a smart home and show that taking into account past information and move’s constraints improves location inference.

INTRODUCTION

PEDIATRICS ◽  
1976 ◽  
Vol 57 (4) ◽  
pp. 591-591
Keyword(s):  
Current Knowledge ◽  
Arterial Oxygen Tension ◽  
Historical Background ◽  
Arterial Oxygen ◽  
Retrolental Fibroplasia ◽  
Serial Measurement ◽  
Sequence Of Events ◽  
New Information ◽  
Practice Of Medicine ◽  
Newborn Intensive Care

With the lowering of mortality rates and improved survival, particularly in the smallest infants, it is becoming increasingly apparent that the risk of developing retrolental fibroplasia (RLF) is still a serious problem. This is true even in the most advanced newborn intensive care units where the administration of oxygen is strictly controlled by means of serial measurement of arterial oxygen tension. Indeed, there is evidence that any concentration of oxygen in excess of that in air is associated with the risk of developing RLF. The identification of oxygen as a major factor causing the development of RLF greatly reduced the impetus for additional research in RLF after 1956. However, today we realize there are still many unresolved problems, and the need for further research in this field is essential. There has also been an increase in public discussion of and interest in this disease because of new litigation concerning cases originating as far back as 1949. Patients and physicians are both uncertain about what actually occurred with respect to the evolution of new information concerning the use of oxygen and the development of RLF. To recreate the sequence of events, the Committee on Fetus and Newborn of the American Academy of Pediatrics has endeavored to present the facts largely through the writings of those who participated in the search for a solution to RLF, and to trace the important steps that led to the discovery of the major cause of this puzzling disease. In recreating events, attention has been paid to the historical background of modern premature care (particularly the use of oxygen), the practice of medicine when oxygen was first used on premature infants in the light of current knowledge, and the process of dissemination of new information.

scholarly journals Voice control and management in smart home system by artificial intelligence

2021 ◽  
Vol 1032 ◽  
pp. 012007
Author(s):  
I S Balabanova ◽  
S S Kostadinova ◽  
V I Markova ◽  
S M Sadinov ◽  
G I Georgiev
Keyword(s):  
Artificial Intelligence ◽  
Smart Home ◽  
Voice Control ◽  
Control And Management

scholarly journals Mapping the Landscape and Structure of Research on Education for Sustainable Development: A Bibliometric Review

2020 ◽  
Vol 12 (5) ◽  
pp. 1947 ◽  
Author(s):  
Philip Hallinger ◽  
Vien-Thong Nguyen
Keyword(s):  
Sustainable Development ◽  
Knowledge Base ◽  
English Language ◽  
Current Knowledge ◽  
Empirical Studies ◽  
Education For Sustainable Development ◽  
Intellectual Structure ◽  
Geographic Diversification ◽  
The Past ◽  
K 12

This systematic review of research used science mapping as a means of analyzing the knowledge base on education for sustainable development (ESD) in K-12 schooling. The review documented the size, growth trajectory and geographic distribution of this literature, identified high impact scholars and documents, and visualized the “intellectual structure” of the field. The database examined in this review consisted of 1842 English language, Scopus-indexed documents published between 1990 and 2018. The review found that the knowledge base on ESD has grown dramatically over the past 30 years, with a rapidly accelerating rate of publication in the past decade. Although the field has been dominated by scholarship from Anglo-American_European nations, there is evidence of increasing geographic diversification of the ESD knowledge base over the past 15 years. Citation analyses identified authors who have had a significant influence on the development of this literature. Author co-citation analysis revealed three “schools of thought” that comprise the “intellectual structure” of this knowledge base: Education for Sustainable Development, Developing a Sustainability Mindset, Teaching and Learning for Sustainability. Document content analyses led to the conclusion that the current knowledge base is heavily weighted towards critical, descriptive and prescriptive papers, with an insufficient body of analytical empirical studies. Several recommendations are offered for strengthening this literature.

The ideological divide in public perceptions of self-driving cars

2020 ◽  
Vol 29 (4) ◽  
pp. 436-451
Author(s):  
Yilang Peng
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Scientific Literacy ◽  
Autonomous Vehicles ◽  
The United States ◽  
Public Perceptions ◽  
New Information ◽  
Nationally Representative ◽  
Self Driving Cars ◽  
Social Conservatism

Applications in artificial intelligence such as self-driving cars may profoundly transform our society, yet emerging technologies are frequently faced with suspicion or even hostility. Meanwhile, public opinions about scientific issues are increasingly polarized along the ideological line. By analyzing a nationally representative panel in the United States, we reveal an emerging ideological divide in public reactions to self-driving cars. Compared with liberals and Democrats, conservatives and Republicans express more concern about autonomous vehicles and more support for restrictively regulating autonomous vehicles. This ideological gap is largely driven by social conservatism. Moreover, both familiarity with driverless vehicles and scientific literacy reduce respondents’ concerns over driverless vehicles and support for regulation policies. Still, the effects of familiarity and scientific literacy are weaker among social conservatives, indicating that people may assimilate new information in a biased manner that promotes their worldviews.

Adenomyosis – its possible effect on endometrial function and receptivity

2021 ◽  
Vol 86 (3) ◽  
pp. 205-209
Author(s):  
Karel Crha ◽  
◽  
Michal Ješeta ◽  
Radovan Pilka ◽  
Pavel Ventruba ◽  
...  
Keyword(s):  
Epithelial Mesenchymal Transition ◽  
Current Knowledge ◽  
Histopathological Examination ◽  
Transvaginal Ultrasound ◽  
Embryo Implantation ◽  
Diagnostic Methods ◽  
Mesenchymal Transition ◽  
New Information

Summary Objective: There have been many studies on adenomyosis, which can impair the quality of life of a woman. There are various kinds of opinions on the pathogenesis, diagnostics and treatment of adenomyosis. The goal of this article is to present the current knowledge of adenomyosis and its impact on the endometrial function and receptivity. Methods: PubMed/Medline, Web of Sciences and Scopus were searched for the articles in English indexed until February 2021 with terms of: adenomyosis, endometrial receptivity, and infertility. Results: Recent studies on angiogenesis and epithelial-mesenchymal transition in the endometrium bring new information on the ethiology and pathogenesis of adenomyosis. In clinical practice, the main diagnostic methods of adenomyosis include transvaginal ultrasound, magnetic resonance imaging or hysteroscopy, although the definitive confirmation is set by histopathological examination. The rules of #Enzian classification of endometriosis should be applied for the classification of adenomyosis. The treatment of adenomyosis should consider individual clinical presentation and reproductive plans of a patient and should be performed in centers for the treatment of endometriosis. Conclusion: Adenomyosis affects endometrial vascularisation and epithelial-mesenchymal transition/mesenchymal-epithelial transition; thus, it can be the cause of irregular uterine bleeding or embryo implantation failure. The research and analysis of endometrial proteome could lead to the new ways of adenomyosis treatment.

scholarly journals Artificial intelligence, dynamic efficiency and Economics

2021 ◽  
pp. 337-350
Author(s):  
Vincent Wolters
Keyword(s):  
Artificial Intelligence ◽  
Optimization Problems ◽  
Evolutionary Process ◽  
Human Action ◽  
Medical Doctor ◽  
Dynamic Efficiency ◽  
Demand And Supply ◽  
New Information ◽  
Back Ground ◽  
The Brain

In this work I will lend support to the theory of «dynamic efficien - cy», as outlined by Prof. Huerta de Soto in The Theory of Dynamic Efficiency (2010a). Whereas Huerta de Soto connects economics with ethics, I will take a different approach. Since I have a back-ground in Artificial Intelligence (A.I.), I will show that this and related fields have yielded insights that, when applied to the study of economics, may call for a different way of looking at the eco-nomy and its processes. At first glance, A.I. and economics do not seem to have a lot in common. The former is thought to attempt to build a human being; the latter is supposed to deal with depressions, growth, inflation, etc. That view is too simplistic; in fact there are strong similarities. First, economics is based on (inter-)acting individuals, i.e. on human action. A.I. tries to understand and simulate human (and animal) behavior. Second, economics deals with information pro-cessing, such as how the allocation of resources can best be orga-nized. A.I. also investigates information processing. This can be in specific systems, such as the brain, or the evolutionary process, or purely in an abstract form. Finally, A.I. tries to answer more philosophical questions like: what is intelligence? What is a mind? What is consciousness? Is there free will? These topics play a less prominent role in economics, but are sometimes touched upon, together with the related topic of the «entrepreneurial function». The paradigm that was dominant in the early days of A.I. is static in nature. Reaching a solution is done in different steps. First: gathering all necessary information. Second: processing this in - formation. Finally: the outcome of this process, a clear conclusion. Each step in the process is entirely separate. During information gathering no processing is done, and during processing, no new information is added. The conclusion reached is final and cannot change later on. Logical problems are what is mostly dealt with, finding ways in which a computer can perform deductions based on the information that is represented as logical statements. Other applications are optimization problems, and so-called «Expert Systems», developed to perform the work of a judge reaching a verdict, or a medical doctor making a diagnosis based on the symptoms of the patient. This paradigm is also called «top-down», because information flows to a central point where it is processed, or «symbolic processing», referring to deduction in formal logic.1 In economics there is a similar paradigm, and it is still the do-minant one. This is the part of economics that deals with opti - mization of resources: given costs and given prices, what is the allocation that will lead to the highest profit? Also belonging to this paradigm are the equilibrium models. Demand and supply curves are supposed to be knowable and unchangeable, and the price is a necessary outcome. The culmination is central planning that supposes all necessary information, such as demand and supply curves and available resources to be known. Based on this, the central planner determines prices.

On techniques of expert systems on the example of the Akinator program

2020 ◽  
Vol 25 (2) ◽  
pp. 7-13
Author(s):  
Zhangozha A.R. ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Neural Networks ◽  
Expert Systems ◽  
Knowledge Base ◽  
Hybrid Systems ◽  
Online Game ◽  
Basic Principles ◽  
The Moment ◽  
Definition Of

On the example of the online game Akinator, the basic principles on which programs of this type are built are considered. Effective technics have been proposed by which artificial intelligence systems can build logical inferences that allow to identify an unknown subject from its description (predicate). To confirm the considered hypotheses, the terminological analysis of definition of the program "Akinator" offered by the author is carried out. Starting from the assumptions given by the author's definition, the article complements their definitions presented by other researchers and analyzes their constituent theses. Finally, some proposals are made for the next steps in improving the program. The Akinator program, at one time, became one of the most famous online games using artificial intelligence. And although this was not directly stated, it was clear to the experts in the field of artificial intelligence that the program uses the techniques of expert systems and is built on inference rules. At the moment, expert systems have lost their positions in comparison with the direction of neural networks in the field of artificial intelligence, however, in the case considered in the article, we are talking about techniques using both directions – hybrid systems. Games for filling semantics interact with the user, expanding their semantic base (knowledge base) and use certain strategies to achieve the best result. The playful form of such semantics filling programs is beneficial for researchers by involving a large number of players. The article examines the techniques used by the Akinator program, and also suggests possible modifications to it in the future. This study, first of all, focuses on how the knowledge base of the Akinator program is built, it consists of incomplete sets, which can be filled and adjusted as a result of further iterations of the program launches. It is important to note our assumption that the order of questions used by the program during the game plays a key role, because it determines its strategy. It was identified that the program is guided by the principles of nonmonotonic logic – the assumptions constructed by the program are not final and can be rejected by it during the game. The three main approaches to acquisite semantics proposed by Jakub Šimko and Mária Bieliková are considered, namely, expert work, crowdsourcing and machine learning. Paying attention to machine learning, the Akinator program using machine learning to build an effective strategy in the game presents a class of hybrid systems that combine the principles of two main areas in artificial intelligence programs – expert systems and neural networks.

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