Case study: Proof of concept trial with sample size re-estimation

2014 ◽  
pp. 383-390
Keyword(s):  
Sample Size ◽  
Proof Of Concept

Sample size and informetric model goodness-of-fit outcomes: a search engine log case study

2006 ◽  
Vol 32 (3) ◽  
pp. 212-222 ◽  
Author(s):  
Isola Ajiferuke ◽  
Dietmar Wolfram ◽  
Felix Famoye
Keyword(s):  
Sample Size ◽  
Search Engine ◽  
Goodness Of Fit

scholarly journals Knowledge Organization and Representation under the AI Lens

2020 ◽  
Vol 5 (1) ◽  
pp. 3-17
Author(s):  
Jian Qin
Keyword(s):  
Linked Data ◽  
Information Science ◽  
Knowledge Organization ◽  
Library And Information Science ◽  
Proof Of Concept ◽  
Primary Method ◽  
Methods And Techniques ◽  
Preliminary Research ◽  
Practical Implications

AbstractPurposeThis paper compares the paradigmatic differences between knowledge organization (KO) in library and information science and knowledge representation (KR) in AI to show the convergence in KO and KR methods and applications.MethodologyThe literature review and comparative analysis of KO and KR paradigms is the primary method used in this paper.FindingsA key difference between KO and KR lays in the purpose of KO is to organize knowledge into certain structure for standardizing and/or normalizing the vocabulary of concepts and relations, while KR is problem-solving oriented. Differences between KO and KR are discussed based on the goal, methods, and functions.Research limitationsThis is only a preliminary research with a case study as proof of concept.Practical implicationsThe paper articulates on the opportunities in applying KR and other AI methods and techniques to enhance the functions of KO.Originality/value:Ontologies and linked data as the evidence of the convergence of KO and KR paradigms provide theoretical and methodological support to innovate KO in the AI era.

scholarly journals THE DIGITAL RESTITUTION OF LOT 3317: USING UNDERWATER IMAGE BASED MODELLING TO GENERATE VALUE IN VIRTUAL HERITAGE EXPERIENCES

2019 ◽  
Vol XLII-2/W15 ◽  
pp. 1163-1170
Author(s):  
K. T. D. Tousant ◽  
S. Fai
Keyword(s):  
Cultural Values ◽  
Spatial Dynamics ◽  
Cultural Value ◽  
Proof Of Concept ◽  
Cultural Resource ◽  
Head Mounted Display ◽  
Virtual Heritage ◽  
Underwater Image ◽  
History Of

<p><strong>Abstract.</strong> The intent of this paper is to demonstrate the cultural value that Virtual Heritage experiences can generate. As a proof of concept, game resolution assets were optimized from high polygon image based models (IBMs) and rendered in real-time, within a Head Mounted Display (HMD). The case study of lot 3317 was chosen to facilitate heuristic explorations pertinent to the history of the St. Lawrence Seaway, Canada. This case study explores methods in creating and validating heritage values, while valourizing assets as a cultural resource for use in the future. While at the same time, challenging the current spatial dynamics by conceptually reducing the distance between the viewer and the flooded landscape. In addition to demonstrating the cultural values generated through the veneration of lot 3317, the paper aims to provide a model for optimizing and post processing meshes produced through Under-Water Image-Base Modelling.</p>

scholarly journals Uncertainty modeling process for semantic technology

2016 ◽  
Vol 2 ◽  
pp. e77 ◽  
Author(s):  
Rommel N. Carvalho ◽  
Kathryn B. Laskey ◽  
Paulo C.G. Da Costa
Keyword(s):  
Knowledge Engineering ◽  
Uncertainty Modeling ◽  
Domain Model ◽  
Proof Of Concept ◽  
Semantic Technology ◽  
Modeling Process ◽  
Ontology Language ◽  
Domain Semantics ◽  
Probabilistic Ontology

The ubiquity of uncertainty across application domains generates a need for principled support for uncertainty management in semantically aware systems. A probabilistic ontology provides constructs for representing uncertainty in domain ontologies. While the literature has been growing on formalisms for representing uncertainty in ontologies, there remains little guidance in the knowledge engineering literature for how to design probabilistic ontologies. To address the gap, this paper presents the Uncertainty Modeling Process for Semantic Technology (UMP-ST), a new methodology for modeling probabilistic ontologies. To explain how the methodology works and to verify that it can be applied to different scenarios, this paper describes step-by-step the construction of a proof-of-concept probabilistic ontology. The resulting domain model can be used to support identification of fraud in public procurements in Brazil. While the case study illustrates the development of a probabilistic ontology in the PR-OWL probabilistic ontology language, the methodology is applicable to any ontology formalism that properly integrates uncertainty with domain semantics.

scholarly journals Multi-Perspective Modeling of Healthcare Systems

2017 ◽  
Vol 5 (2) ◽  
pp. 1-20 ◽  
Author(s):  
Ignace Djitog ◽  
Hamzat Olanrewaju Aliyu ◽  
Mamadou Kaba Traoré
Keyword(s):  
Specific Problem ◽  
Discrete Event ◽  
Healthcare Systems ◽  
Proof Of Concept ◽  
System Specification ◽  
Disease Propagation ◽  
Dynamic Update ◽  
Event System ◽  
Simulation Based

This paper presents a multi-perspective approach to Modeling and Simulation (M&S) of Healthcare Systems (HS) such that different perspectives are defined and integrated together. The interactions between the isolated perspectives are done through dynamic update of models output-to-parameter integration during concurrent simulations. Most often, simulation-based studies of HS in the literature focus on specific problem like allocation of resources, disease propagation, and population dynamics that are studied with constant parameters from their respective experimental frames throughout the simulation. The proposed idea provides a closer representation of the real situation and helps to capture the interactions between seemingly independent concerns - and the effects of such interactions - in simulation results. The article provides a DEVS (Discrete Event System Specification)-based formalization of the loose integration of the different perspectives, an Object-Oriented framework for its realization and a case study as illustration and proof of concept.

scholarly journals A complete Greenwich degree in a personal learning space

2014 ◽  
Vol 3 (6) ◽  
Author(s):  
Geoff Rebbeck
Keyword(s):  
Proof Of Concept ◽  
Basic Form ◽  
Learning Space ◽  
Personal Learning ◽  
University Degree ◽  
Personal Devices

This Case study shows and explains the issues and value of placing a whole Greenwich first degree completed in Jan. 2007 into an e-portfolio. The purpose is to show proof of concept that it is possible and how it looks in basic form, when done retrospectively (6 years later).The completed portfolio was the presentation made at the APT Conference July 2013, audience members also able to access and explore it on personal devices in the session.The Case Study considers whether a degree can be presented inside a portfolio, what the issues are in creating a degree portfolio like this, what limitations may be encountered in the process.It then evaluates the value of this approach, and what might be done with a Greenwich University degree in this form.

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