scholarly journals Robotic Railway Multi-Sensing and Profiling Unit Based on Artificial Intelligence and Data Fusion

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6876
Author(s):  
Marius Minea ◽  
Cătălin Marian Dumitrescu ◽  
Mihai Dima
Keyword(s):  
Artificial Intelligence ◽  
Data Fusion ◽  
Fault Management ◽  
Field Tests ◽  
Relevant Information ◽  
Water Flooding ◽  
Railway Vehicle ◽  
Management Service ◽  
Railway Capacity ◽  
Human Operators

This article presents the research and results of field tests and simulations regarding an autonomous/robotic railway vehicle, designed to collect multiple information on safety and functional parameters of a surface railway and/or subway section, based on data fusion and machine learning. The maintenance of complex railways, or subway networks with long operating times is a difficult process and intensive resources consuming. The proposed solution delivers human operators in the fault management service and operations from the time-consuming task of railway inspection and measurements, by integrating several sensors and collecting most relevant information on railway, associated automation equipment and infrastructure on a single intelligent platform. The robotic cart integrates autonomy, remote sensing, artificial intelligence, and ability to detect even infrastructural anomalies. Moreover, via a future process of complex statistical filtering of data, it is foreseen that the solution might be configured to offer second-order information about infrastructure changes, such as land sliding, water flooding, or similar modifications. Results of simulations and field tests show the ability of the platform to integrate several fault management operations in a single process, useful in increasing railway capacity and resilience.

Automating intellectual freedom: Artificial intelligence, bias, and the information landscape

IFLA Journal ◽  
2021 ◽  
pp. 034003522110571
Author(s):  
Catherine Smith
Keyword(s):  
Artificial Intelligence ◽  
Intellectual Freedom ◽  
Digital Information ◽  
Personal Freedom ◽  
Library Users ◽  
Human Operators ◽  
Information Landscape ◽  
Resource Description

Anxieties over automation and personal freedom are challenging libraries’ role as havens of intellectual freedom. The introduction of artificial intelligence into the resource description process creates an opportunity to reshape the digital information landscape—and loss of trust by library users. Resource description necessarily manipulates a library’s presentation of information, which influences the ways users perceive and interact with that information. Human catalogers inevitably introduce personal and cultural biases into their work, but artificial intelligence may perpetrate biases on a previously unseen scale. The automation of this process may be perceived as a greater threat than the manipulation produced by human operators. Librarians must understand the risks of artificial intelligence and consider what oversight and countermeasures are necessary to mitigate the harm to libraries and their users before ceding resource description to artificial intelligence in place of the “professional considerations” the IFLA Statement on Libraries and Intellectual Freedom calls for in providing access to library materials.

ARTIFICIAL INTELLIGENCE IN DENTISTRY: A MILESTONE

2021 ◽  
pp. 49-52
Author(s):  
Gaurvi Vikram Kamra ◽  
Ankur Sharma
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Virtual Reality ◽  
Augmented Reality ◽  
Treatment Planning ◽  
Computational Models ◽  
Improve Patient Care ◽  
Relevant Information ◽  
Documented Information ◽  
Improve Patient

The concept of "articial intelligence" (AI) refers to machines that are capable of executing human-like tasks. AI can also be dened as a eld concerned with computational models that can reason and act intelligently. Perspicacious software for data computation has become a necessity as the amount of documented information and patient data has increased dramatically. The applicability, limitations, and potential future of AI-based dental diagnoses, treatment planning, and conduct are described in this concise narrative overview. AI has been used in a variety of ways, from processing of data and locating relevant information to using neural networks for diagnosis and the introduction of augmented reality and virtual reality in dental education. AI-based apps will improve patient care by relieving the dental workforce of tedious routine duties, improving population health at lower costs, and eventually facilitating individualized, anticipatory, prophylactic, and collaborative dentistry. The convergence of AI and digitization has ushered in a new age in dentistry, with tremendously promising future prospects.The applicability, limitations, and potential future of AI-based dental diagnoses, treatment planning, and conduct are described in this concise narrative overview.

Modern Approaches to Software Engineering in the Compositional Era

2011 ◽  
pp. 1-20
Author(s):  
Ali Dogru ◽  
Pinar Senkul ◽  
Ozgur Kaya
Keyword(s):  
Artificial Intelligence ◽  
Software Engineering ◽  
Software Development ◽  
Fault Management ◽  
Management Systems ◽  
Rule Based ◽  
Rule Based Approach ◽  
Computational Element ◽  
Do So

The amazing evolution fuelled by the introduction of the computational element has already changed our lives and continues to do so. Initially, the fast advancement in hardware partially enabled an appreciation for software potency. This meant that engineers had to have a better command over this field that was crucial in the solution of current and future problems and requirements. However, software development has been reported as not adequate, or mature enough. Intelligence can help closing this gap. This chapter introduces the historical and modern aspects of software engineering within the artificial intelligence perspective. Also an illustrative example is included that demonstrates a rule-based approach for the development of fault management systems.

Modern Approaches to Software Engineering in the Compositional Era

2012 ◽  
pp. 1903-1923
Author(s):  
Ali Dogru ◽  
Pinar Senkul ◽  
Ozgur Kaya
Keyword(s):  
Artificial Intelligence ◽  
Software Engineering ◽  
Software Development ◽  
Fault Management ◽  
Management Systems ◽  
Rule Based ◽  
Rule Based Approach ◽  
Computational Element ◽  
Do So

The amazing evolution fuelled by the introduction of the computational element has already changed our lives and continues to do so. Initially, the fast advancement in hardware partially enabled an appreciation for software potency. This meant that engineers had to have a better command over this field that was crucial in the solution of current and future problems and requirements. However, software development has been reported as not adequate, or mature enough. Intelligence can help closing this gap. This chapter introduces the historical and modern aspects of software engineering within the artificial intelligence perspective. Also an illustrative example is included that demonstrates a rule-based approach for the development of fault management systems.

A Language and Algorithm for Automatic Merging of Ontologies

2011 ◽  
pp. 381-404 ◽  
Author(s):  
Alma-Delia Cuevas-Rasgado ◽  
Adolfo Guzman-Arenas
Keyword(s):  
Artificial Intelligence ◽  
Relevant Information ◽  
Automatic Method ◽  
Knowledge Processing ◽  
Artificial Intelligence Techniques ◽  
Business Transactions ◽  
Computer Aided

Ontologies are becoming important repositories of information useful for business transactions and operations since they are amenable to knowledge processing using artificial intelligence techniques. They offer the potential of amassing large contents of relevant information, but until now the fusion or merging of ontologies, needed for knowledge buildup and its exploitation by machine, was done manually or through computer-aided ontology editors. Thus, attaining large ontologies was expensive and slow. This chapter offers a new, automatic method of joining two ontologies to obtain a third one. The method works well in spite of inconsistencies, redundancies, and different granularity of information.

The Current Bottleneck of Knowledge Management and How Information Technology can be Successfully Used to Reduce it

2011 ◽  
pp. 289-315
Author(s):  
Ricardo Salim ◽  
Carlos Ferran
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Knowledge Management ◽  
Natural Selection ◽  
Field Tests ◽  
Cultural Selection

Knowledge is generated and propogated by cultural selection, a process that—like it genetic counterpart, natural selection—consumes much time and resources in contrasting every new (or mutated) information with reality. However, if we hasten to minimize the field tests or marketing tests—forms of cultural selection—we run into the risk of not testing the knowledge sufficiently and make a deficient contrast with reality. In this chapter we present the concept of pragmatic minimization as the compromise of minimizing the amount of resources invested in contrasting the newly acquired knowledge with reality, while not falling into a lack of realism—blind idealism—or a cominatorial explosion of mental possibilities. Then, we advocate “simulated praxis” and a “more pragmatic artificial intelligence” as new avenues to optimally solve the problem of pragmatic minimization.

OS4ES – Open System for Energy Services

2015 ◽  
Vol 63 (11) ◽  
Author(s):  
Martin Zanner ◽  
Andrea Schröder ◽  
Christoph Kahlen
Keyword(s):  
Open System ◽  
Distribution System ◽  
Service System ◽  
Field Tests ◽  
Electrical Energy ◽  
Congestion Management ◽  
Management Service ◽  
Energy Services ◽  
Open Service ◽  
Reliability And Robustness

AbstractToday, mass presence of distributed energy resources (DERs) connected to the grid is often seen as having adverse effects on grid reliability and robustness. The apprehension is that it complicates or even compromises network management by distribution system operators (DSOs).The central aim of the Open System for Energy Services (OS4ES) project is to provide a solution that closes the current information, communication and cooperation gap between DERs and energy market actors. To this end, the OS4ES project delivers an innovative Open Service System that enables dynamic cooperation between these two parties. A Distributed Registry for DERs offers to involved actors the opportunity to reserve the aggregated flexibility of DERs as a grid management service in order to improve Smart Grid robustness and reliability. OS4ES will be based on standardized and interoperable communication interfaces, as well as generic interfaces among components producing, consuming or storing electrical energy.The OS4ES Open Service System includes laboratory and field tests under different service scenarios such as congestion management, energy trading, imbalance risk reduction and Volt/VAR optimization. An OS4ES User Group has been established to allow interested parties to gain a broader insight in the project and to actively contribute to the work packages of interest. Besides, standardization proposals will be prepared and submitted to the respective standardization committees.

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