When is a Proof-of-Concept (POC) not a POC? Pomaglumetad (LY2140023) as a Case Study for Antipsychotic Efficacy

2015 ◽  
Vol 21 (26) ◽  
pp. 3788-3796 ◽  
Author(s):  
Gerard Marek
Keyword(s):  
Proof Of Concept ◽  
Antipsychotic Efficacy

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.

Grid Business Process

2008 ◽  
pp. 257-297 ◽  
Author(s):  
Asif Akram ◽  
Rob Allen ◽  
Sanjay Chaudhary ◽  
Prateek Jain ◽  
Zakir Laliwala
Keyword(s):  
Web Services ◽  
Web Service ◽  
Business Process ◽  
Use Cases ◽  
Proof Of Concept ◽  
Service Standards

This chapter presents a ‘Case Study’ based on the distributed market. The requirements of this Grid Business Process are more demanding than any typical business process deployed within a single organization or enterprise. Recently different specifications built on top of Web service standards have originated from the Grid paradigm to address limitations of stateless Web services. These emerging specifications are evaluated in the first part of the chapter to capture requirements of a dynamic business process i.e. Business Process Grid. In second part of the chapter, a case study with different use cases is presented to simulate various scenarios. The abstract discussion and requirements of the case study is followed by the actual implementation. The implementation is meant for the proof-of-concept rather than fully functional application.

The Application of Swarm Intelligence to Collective Robots

2006 ◽  
pp. 157-185 ◽  
Author(s):  
Amanda J.C. Sharkey ◽  
Noel Sharkey
Keyword(s):  
Swarm Intelligence ◽  
Proof Of Concept ◽  
Practical Application ◽  
Predator Prey ◽  
Expected Benefits ◽  
Intelligent Approach ◽  
Intelligence Approach ◽  
Robotic Applications ◽  
Study Application

This chapter considers the application of swarm intelligence principles to collective robotics. Our aim is to identify the reasons for the growing interest in the intersection of these two areas, and to evaluate the progress that has been made to date. In the course of this chapter, we will discuss the implications of taking a swarm intelligent approach, and review recent research and applications. The area of “swarm robotics” offers considerable promise for practical application, although it is still in its infancy, and many of the tasks that have been achieved are better described as “proof-of-concept” examples, rather than full-blown applications. In the first part of the chapter, we will examine what taking a swarm intelligence approach to robotics implies, and outline its expected benefits. We shall then proceed to review recent swarm robotic applications, before concluding with a case study application of predator-prey robotics that illustrates some of the potential of the approach.

High Performance BLAST Over the Grid

2011 ◽  
pp. 121-148 ◽  
Author(s):  
Vincent Breton ◽  
Eddy Caron ◽  
Frederic Desprez ◽  
Gael Le Mahec
Keyword(s):  
Data Management ◽  
High Performance ◽  
Large Scale ◽  
Proof Of Concept ◽  
Experimental Platform ◽  
Complex Problems ◽  
Production Platform ◽  
And Storage

As grids become more and more attractive for solving complex problems with high computational and storage requirements, bioinformatics starts to be ported on large scale platforms. The BLAST kernel, one of the main cornerstone of high performance genomics, was one the first application ported on such platform. However, if a simple parallelization was enough for the first proof of concept, its use in production platform needed more optimized algorithms. In this chapter, we review existing parallelization and “gridification” approaches as well as related issues such as data management and replication, and a case study using the DIET middleware over the Grid’5000 experimental platform.

A Knowledge-Based Tool for the Selection of Design Options During the Competitive Tendering of Vehicle Systems

Volume 3 ◽  
2004 ◽  
Author(s):  
Clive I. Kerr ◽  
Rajkumar Roy ◽  
Peter J. Sackett
Keyword(s):  
Automotive Industry ◽  
Proof Of Concept ◽  
Competitive Tendering ◽  
Knowledge Based ◽  
Vehicle System ◽  
Tier 1 ◽  
Vehicle Systems ◽  
Design Options ◽  
Selection Of

In the automotive industry the activities of documenting the design options and generating the necessary request for quotations, for Tier 1 system suppliers to be awarded contracts for design and development, is complex and time-consuming since these activities are predominately manual and paper-based. Thus, a knowledge-based tool is being developed to aid the selection of the design options for vehicle systems during competitive tendering. The tool is based on ontologies in order to provide a common and shared definition for the options available for a given vehicle system. An overview of this approach is provided and, as a ‘proof of concept’, a case study involving seating systems is presented. This paper shows, through the seating system case study, how the functionalities and features of a vehicle system can be selected and documented in order to streamline the business process of contracting out product development through the supply chain.

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