scholarly journals Complete Automation of Metro Stations through Artificial Intelligence

2012 ◽  
pp. 56-69
Author(s):  
Rittick Datta ◽  
Prachi Taksali
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Travel Time ◽  
Travel Cost ◽  
Domain Experts ◽  
Metropolitan Cities ◽  
Complete Automation ◽  
Transportation Resource

Metro stations have become an invaluable transportation resource and will be spreading out of the metropolitan cities soon. It has reduced travel time and travel cost. We intend to research the possibility of unmanned metro stations through the application of artificial intelligence, one of which is expert systems. Expert systems —that are able to hold the accumulated knowledge of different domain experts can be implemented to guide the commuter about the optimum travel route. In this way the metro stations can be turned into self-sustainable structures.

scholarly journals Use of artificial intelligence in analytical systems for the clinical laboratory

1995 ◽  
Vol 17 (1) ◽  
pp. 1-15 ◽  
Author(s):  
John F. Place ◽  
Alain Truchaud ◽  
Kyoichi Ozawa ◽  
Harry Pardue ◽  
Paul Schnipelsky
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Expert Systems ◽  
Language Processing ◽  
Knowledge Engineering ◽  
Clinical Laboratory ◽  
Failure Detection ◽  
Domain Experts ◽  
Clinical Laboratories ◽  
The Neural Network

The incorporation of information-processing technology into analytical systems in the form of standard computing software has recently been advanced by the introduction of artificial intelligence (AI), both as expert systems and as neural networks.This paper considers the role of software in system operation, control and automation, and attempts to define intelligence. AI is characterized by its ability to deal with incomplete and imprecise information and to accumulate knowledge. Expert systems, building on standard computing techniques, depend heavily on the domain experts and knowledge engineers that have programmed them to represent the real world. Neural networks are intended to emulate the pattern-recognition and parallel processing capabilities of the human brain and are taught rather than programmed. The future may lie in a combination of the recognition ability of the neural network and the rationalization capability of the expert system.In the second part of the paper, examples are given of applications of AI in stand-alone systems for knowledge engineering and medical diagnosis and in embedded systems for failure detection, image analysis, user interfacing, natural language processing, robotics and machine learning, as related to clinical laboratories.It is concluded that AI constitutes a collective form of intellectual propery, and that there is a need for better documentation, evaluation and regulation of the systems already being used in clinical laboratories.

SISTEM PAKAR MENDIAGNOSA VIRUS MAYORA DENGAN METODE VARIABLE CENTERED INTELLIGENT RULE SYSTEM (VCIRS)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Siti Nurhena ◽  
Nelly Astuti Hasibuan ◽  
Kurnia Ulfa
Keyword(s):  
Artificial Intelligence ◽  
Immune System ◽  
Expert System ◽  
Expert Systems ◽  
Dengue Hemorrhagic Fever ◽  
Hemorrhagic Fever ◽  
Visual Basic ◽  
Artificial Intelligence Techniques ◽  
Individual Needs ◽  
Rule System

The diagnosis process is the first step to knowing a type of disease. This type of disease caused by mosquitoes is one of the major viruses (MAVY), dengue hemorrhagic fever (DHF) and malaria. Sometimes not everyone can find the virus that is carried by this mosquito, usually children who are susceptible to this virus because the immune system that has not been built perfectly is perfect. To know for sure which virus is infected by mosquitoes, it can diagnose by seeing symptoms perceived symptoms. Expert systems are one of the most used artificial intelligence techniques today because expert systems can act as consultations. In this case the authors make a system to start a diagnosis process with variable centered intelligent rule system (VCIRS) methods through perceived symptoms. With the facilities provided for users and administrators, allowing both users and administrators to use this system according to their individual needs. This expert system is made with the Microsoft Visual Basic 2008 programming language.Keywords: Expert System, Mayora Virus, Variable Centered Intelligent Rule System (VCIRS)The diagnosis process is the first step to knowing a type of disease. This type of disease caused by mosquitoes is one of the major viruses (MAVY), dengue hemorrhagic fever (DHF) and malaria. Sometimes not everyone can find the virus that is carried by this mosquito, usually children who are susceptible to this virus because the immune system that has not been built perfectly is perfect. To know for sure which virus is infected by mosquitoes, it can diagnose by seeing symptoms perceived symptoms.Expert systems are one of the most used artificial intelligence techniques today because expert systems can act as consultations. In this case the authors make a system to start a diagnosis process with variable centered intelligent rule system (VCIRS) methods through perceived symptoms.With the facilities provided for users and administrators, allowing both users and administrators to use this system according to their individual needs. This expert system is made with the Microsoft Visual Basic 2008 programming language.Keywords: Expert System, Mayora Virus, Variable Centered Intelligent Rule System (VCIRS)

Principles of induction and approaches to attribute based induction

1991 ◽  
Vol 6 (4) ◽  
pp. 307-333 ◽  
Author(s):  
G. Kalkanis ◽  
G. V. Conroy
Keyword(s):  
Artificial Intelligence ◽  
Pattern Recognition ◽  
Cognitive Psychology ◽  
Expert Systems ◽  
Basic Principles ◽  
Inductive Approach ◽  
Induction Process

AbstractThis paper presents a survey of machine induction, studied mainly from the field of artificial intelligence, but also from the fields of pattern recognition and cognitive psychology. The paper consists of two parts: Part I discusses the basic principles and features of the machine induction process; Part II uses these principles and features to review and criticize the major supervised attribute-based induction methods. Attribute-based induction has been chosen because it is the most commonly used inductive approach in the development of expert systems and pattern recognition models.

Seven Things Every Trainer Must Know about Artificial Intelligence

1991 ◽  
Vol 20 (2) ◽  
pp. 153-156
Author(s):  
Mahima Ranjan Kundu
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Business Management ◽  
Human Mind ◽  
Educational Programs ◽  
Training Environment ◽  
Training And Education ◽  
Training Systems ◽  
Potential Benefits

This article provides information about the prospects and limitations of the Artificial Intelligence and Expert Systems as they relate to training systems and educational programs. The article describes the potential benefits of expert systems and how it can be gainfully employed in training environment, industry, and business management to perform complex jobs. The limitations of the applications of the Artificial Intelligence are discussed as some tend to believe that human mind and computers think alike and AI machines can function like a real expert in every aspect of training and education.

scholarly journals To Play and To Be Played: Exploring the Design of Urban Machines for Playful Placemaking

2021 ◽  
Vol 3 ◽  
Author(s):  
Louis Chew ◽  
Luke Hespanhol ◽  
Lian Loke
Keyword(s):  
Artificial Intelligence ◽  
Urban Landscape ◽  
Active Role ◽  
Public Spaces ◽  
Active Player ◽  
Metropolitan Cities ◽  
Street Furniture ◽  
Design Case Study ◽  
Speculative Design

Within the paradigm of the smart and playable city, the urban landscape and street furniture have provided a fertile platform for pragmatic and hedonic goals of urban liveability through technology augmentation. Smart street furniture has grown from being a novelty to become a common sight in metropolitan cities, co-opted for improving the efficiency of services. However, as we consider technologies that are increasingly smarter, with human-like intelligence, we navigate towards uncharted waters when discussing the consequences of their integration with the urban landscape. The implications of a new genre of street furniture embedded with artificial intelligence, where the machine has autonomy and is an active player itself, are yet to be fully understood. In this article, we analyse the evolving design of public benches along the axes of smartness and disruption to understand their qualities as playful, urban machines in public spaces. We present a concept-driven speculative design case study, as an exploration of a smart, sensing, and disruptive urban machine for playful placemaking. With the emergence of artificial intelligence, we expand on the potential of urban machines to partake an increasingly active role as co-creators of play and playful placemaking in the cities of tomorrow.

scholarly journals Artificial Intelligence, Expert Systems and Law

2012 ◽  
Vol 5 (1) ◽  
pp. 105-116 ◽  
Author(s):  
Richard Susskind
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems

Artificial Intelligence, Expert Systems and Law

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