scholarly journals Enhanced Situational Awareness through a Decision Support Service for Optimal Allocation of Resources and Response Capacity

2017 ◽  
Vol 32 (S1) ◽  
pp. S229
Author(s):  
Irene Christodoulou ◽  
George M. Milis ◽  
Panayiotis Kolios ◽  
Christos Panayiotou ◽  
Marios Polycarpou ◽  
...  
Keyword(s):  
Decision Support ◽  
Optimal Allocation ◽  
Situational Awareness ◽  
Support Service ◽  
Allocation Of Resources ◽  
Response Capacity

Context-Driven Proactive Decision Support for Hybrid Teams

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 41-57
Author(s):  
Manisha Mishra ◽  
Pujitha Mannaru ◽  
David Sidoti ◽  
Adam Bienkowski ◽  
Lingyi Zhang ◽  
...  
Keyword(s):  
Decision Support ◽  
Situational Awareness ◽  
Feature Space ◽  
Human Interaction ◽  
Superior Performance ◽  
Uncertain Environments ◽  
Cognitive States ◽  
Contextual Elements ◽  
Human Operators ◽  
Smart Machine

A synergy between AI and the Internet of Things (IoT) will significantly improve sense-making, situational awareness, proactivity, and collaboration. However, the key challenge is to identify the underlying context within which humans interact with smart machines. Knowledge of the context facilitates proactive allocation among members of a human–smart machine (agent) collective that balances auto­nomy with human interaction, without displacing humans from their supervisory role of ensuring that the system goals are achievable. In this article, we address four research questions as a means of advancing toward proactive autonomy: how to represent the interdependencies among the key elements of a hybrid team; how to rapidly identify and characterize critical contextual elements that require adaptation over time; how to allocate system tasks among machines and agents for superior performance; and how to enhance the performance of machine counterparts to provide intelligent and proactive courses of action while considering the cognitive states of human operators. The answers to these four questions help us to illustrate the integration of AI and IoT applied to the maritime domain, where we define context as an evolving multidimensional feature space for heterogeneous search, routing, and resource allocation in uncertain environments via proactive decision support systems.

scholarly journals More for less: predicting and maximizing genomic variant discovery via Bayesian nonparametrics

Biometrika ◽  
2021 ◽  
Author(s):  
Lorenzo Masoero ◽  
Federico Camerlenghi ◽  
Stefano Favaro ◽  
Tamara Broderick
Keyword(s):  
Optimal Allocation ◽  
Bayesian Nonparametrics ◽  
Allocation Of Resources ◽  
Experimental Conditions ◽  
Follow Up Study ◽  
Variant Discovery ◽  
Fixed Budget ◽  
The Cost ◽  
Genomic Variant

Abstract While the cost of sequencing genomes has decreased dramatically in recent years, this expense often remains non-trivial. Under a fixed budget, scientists face a natural trade-off between quantity and quality: spending resources to sequence a greater number of genomes or spending resources to sequence genomes with increased accuracy. Our goal is to find the optimal allocation of resources between quantity and quality. Optimizing resource allocation promises to reveal as many new variations in the genome as possible. In this paper, we introduce a Bayesian nonparametric methodology to predict the number of new variants in a follow-up study based on a pilot study. When experimental conditions are kept constant between the pilot and follow-up, we find that our prediction is competitive with the best existing methods. Unlike current methods, though, our new method allows practitioners to change experimental conditions between the pilot and the follow-up. We demonstrate how this distinction allows our method to be used for more realistic predictions and for optimal allocation of a fixed budget between quality and quantity.

scholarly journals Assessing a Decision Support Tool for SOC Analysts

2021 ◽  
Author(s):  
Jassim Happa ◽  
Ioannis Agrafiotis ◽  
Martin Helmhout ◽  
Thomas Bashford-Rogers ◽  
Michael Goldsmith ◽  
...  
Keyword(s):  
Decision Support ◽  
Mixed Method ◽  
User Study ◽  
Situational Awareness ◽  
Decision Support Tool ◽  
Lessons Learned ◽  
Visualization Tool ◽  
Support Tool ◽  
Response Strategies ◽  
Method Approach

In recent years, many tools have been developed to understand attacks that make use of visualization, but few examples aims to predict real-world consequences. We have developed a visualization tool that aims to improve decision support during attacks. Our tool visualizes propagation of risks from IDS and AV-alert data by relating sensor alerts to Business Process (BP) tasks and machine assets: an important capability gap present in many Security Operation Centres (SOCs) today. In this paper we present a user study in which we evaluate the tool's usability and ability to deliver situational awareness to the analyst. Ten analysts from seven SOCs performed carefully designed tasks related to understanding risks and prioritising recovery decisions. The study was conducted in laboratory conditions, with simulated attacks, and used a mixed-method approach to collect data from questionnaires, eyetracking and voice-recorded interviews. The findings suggest that providing analysts with situational awareness relating to business priorities can help them prioritise response strategies. Finally, we provide an in-depth discussion on the wider questions related to user studies in similar conditions as well as lessons learned from our user study and developing a visualization tool of this type.

Morphometric Registration of Cytotoxic Changes of Epithelial Cells In Vitro: A Methodological Study

1990 ◽  
Vol 17 (3) ◽  
pp. 174-176
Author(s):  
Lis Andersen ◽  
Dorthe Arenholt-Bindslev
Keyword(s):  
Culture System ◽  
Optimal Allocation ◽  
Volume Density ◽  
Cell Culture System ◽  
Allocation Of Resources ◽  
Methodological Study ◽  
Epithelial Cell Culture ◽  
Coefficients Of Variation ◽  
And Control

Quantification of toxicity-induced cytomorphological effects in an epithelial cell culture system is described. Estimates of volume density and star volume of mitochondria and lysosomes are given. Mean volumes (n = 5) and coefficients of variation of these parameters were equal in experimental (TPA-treatment) and control cultures. An optimal allocation of resources for estimating cytomorphometric parameters would be to increase the number of culture flasks.

scholarly journals REMUNERATIONS AND LABOUR PRODUCTIVITY IN AGRICULTURE AGAINST A BACKGROUND OF OTHER ECONOMY SECTORS

2018 ◽  
Vol 17 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Justyna Góral ◽  
Włodzimierz Rembisz
Keyword(s):  
Agricultural Sector ◽  
Optimal Allocation ◽  
Labour Force ◽  
Empirical Studies ◽  
Labour Productivity ◽  
Allocation Of Resources ◽  
Economic Activities ◽  
Agricultural Producers ◽  
The Sustainable Development ◽  
Economic Growth Model

The optimal allocation of resources in various sectors results in the sustainable development of the whole economy (the theory of optimum allocation of resources by Kantonowicz and Koopmans). According to Tinbergen’s studies, the excessive labour force in one of them gives rise to all types of social and economic problems. The objective of theoretical considerations and empirical studies of this publication is to analyse the ratio of the remuneration for labour to its productivity in various economy sectors with particular attention paid to the agricultural sector. The authors also refer to the theory by Lewis and Schultz, who had analysed the problems of agriculture in developing countries, as well as to the Solow economic growth model with the Cobb–Douglas production function. In the light of the empirical data presented in the paper, we can conclude that in section A of Statistical Classification of Economic Activities this ratio is seriously disturbed and distorted. The remuneration is overvalued in relation to the labour productivity. Such a ratio is not a positive testimony to the reasonableness of management in the sense of agricultural producers’ equilibria.

Optimal allocation of resources to nodes of parallel and series systems

1992 ◽  
Vol 24 (4) ◽  
pp. 894-914 ◽  
Author(s):  
Moshe Shaked ◽  
J. George Shanthikumar
Keyword(s):  
Optimal Allocation ◽  
Allocation Of Resources ◽  
Series Systems ◽  
Total Resource

In this paper we consider parallel and series systems, the components of which can be ‘improved'. The ‘improvement' consists of supplying the components with cold or hot standby spares or by allotting to them fixed budgets for minimal repairs. A fixed total resource of spares or minimal repairs is available. We find the optimal allocation of the resource items in several commonly encountered settings.

Decision support for the optimal allocation of security controls

2018 ◽  
Vol 115 ◽  
pp. 92-104 ◽  
Author(s):  
He Zhang ◽  
Kaushal Chari ◽  
Manish Agrawal
Keyword(s):  
Decision Support ◽  
Optimal Allocation ◽  
Security Controls

scholarly journals Conducting Non-Adaptive Experiments in a Live Setting: A Bayesian Approach to Determining Optimal Sample Size

2019 ◽  
Author(s):  
Nandan Sudarsanam ◽  
Ramya Chandran ◽  
Daniel D. Frey
Keyword(s):  
Statistical Learning ◽  
Optimal Allocation ◽  
Analytical Techniques ◽  
Optimal Level ◽  
Base Case ◽  
Allocation Of Resources ◽  
Worst Case ◽  
Optimal Sample Size ◽  
Optimal Sample ◽  
Theoretical Results

Abstract This research studies the use of predetermined experimental plans in a live setting with a finite implementation horizon. In this context, we seek to determine the optimal experimental budget in different environments using a Bayesian framework. We derive theoretical results on the optimal allocation of resources to treatments with the objective of minimizing cumulative regret, a metric commonly used in online statistical learning. Our base case studies a setting with two treatments assuming Gaussian priors for the treatment means and noise distributions. We extend our study through analytical and semi-analytical techniques which explore worst-case bounds and the generalization to k treatments. We determine theoretical limits for the experimental budget across all possible scenarios. The optimal level of experimentation that is recommended by this study varies extensively and depends on the experimental environment as well as the number of available units. This highlights the importance of such an approach which incorporates these factors to determine the budget.

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