NITCO: an intelligent agent technique for optimising of resource utilisation in cloud

AbstractAs we enter a chronic phase of the SARS-CoV-2 pandemic, with uncontrolled infection rates in many places, relative regional susceptibilities are a critical unknown for policy planning. Tests for SARS-CoV-2 infection or antibodies are indicative but unreliable measures of exposure. Here instead, for four highly-affected countries, we determine population susceptibilities by directly comparing country-wide observed epidemic dynamics data with that of their main metropolitan regions. We find significant susceptibility reductions in the metropolitan regions as a result of earlier seeding, with a relatively longer phase of exponential growth before the introduction of public health interventions. During the post-growth phase, the lower susceptibility of these regions contributed to the decline in cases, independent of intervention effects. Forward projections indicate that non-metropolitan regions will be more affected during recurrent epidemic waves compared with the initially heavier-hit metropolitan regions. Our findings have consequences for disease forecasts and resource utilisation.

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Black-Box-Based Mathematical Modelling of Machine Intelligence Measuring

Mathematics ◽

10.3390/math9060681 ◽

2021 ◽

Vol 9 (6) ◽

pp. 681

Author(s):

László Barna Iantovics

Keyword(s):

Problem Solving ◽

Scientific Literature ◽

Real Life ◽

Intelligent Agent ◽

Difficult Problem ◽

Black Box ◽

Machine Intelligence ◽

Agent Based ◽

Np Hard Problem ◽

Box Method

Current machine intelligence metrics rely on a different philosophy, hindering their effective comparison. There is no standardization of what is machine intelligence and what should be measured to quantify it. In this study, we investigate the measurement of intelligence from the viewpoint of real-life difficult-problem-solving abilities, and we highlight the importance of being able to make accurate and robust comparisons between multiple cooperative multiagent systems (CMASs) using a novel metric. A recent metric presented in the scientific literature, called MetrIntPair, is capable of comparing the intelligence of only two CMASs at an application. In this paper, we propose a generalization of that metric called MetrIntPairII. MetrIntPairII is based on pairwise problem-solving intelligence comparisons (for the same problem, the problem-solving intelligence of the studied CMASs is evaluated experimentally in pairs). The pairwise intelligence comparison is proposed to decrease the necessary number of experimental intelligence measurements. MetrIntPairII has the same properties as MetrIntPair, with the main advantage that it can be applied to any number of CMASs conserving the accuracy of the comparison, while it exhibits enhanced robustness. An important property of the proposed metric is the universality, as it can be applied as a black-box method to intelligent agent-based systems (IABSs) generally, not depending on the aspect of IABS architecture. To demonstrate the effectiveness of the MetrIntPairII metric, we provide a representative experimental study, comparing the intelligence of several CMASs composed of agents specialized in solving an NP-hard problem.

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In-situ resource utilisation manufacturing of optically transparent glass from lunar regolith simulant

Journal of Materials Science ◽

10.1007/s10853-021-06059-x ◽

2021 ◽

Author(s):

Juergen Schleppi ◽

Geoffrey Bromiley ◽

Nic Odling ◽

Nick S. Bennett

Keyword(s):

Lunar Regolith ◽

Resource Utilisation ◽

Transparent Glass ◽

Optically Transparent ◽

Lunar Regolith Simulant

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Impact of neovascular age-related macular degeneration: burden of patients receiving therapies in Japan

Scientific Reports ◽

10.1038/s41598-021-92567-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Shigeru Honda ◽

Yasuo Yanagi ◽

Hideki Koizumi ◽

Yirong Chen ◽

Satoru Tanaka ◽

...

Keyword(s):

Macular Degeneration ◽

Productivity Loss ◽

Work Productivity ◽

The Elderly ◽

Developed Countries ◽

Age Related Macular Degeneration ◽

Resource Utilisation ◽

Total Work ◽

Healthcare Resource Utilisation ◽

Age Related

AbstractThe chronic eye disorder, neovascular age-related macular degeneration (nAMD), is a common cause of permanent vision impairment and blindness among the elderly in developed countries, including Japan. This study aimed to investigate the disease burden of nAMD patients under treatment, using data from the Japan National Health and Wellness surveys 2009–2014. Out of 147,272 respondents, 100 nAMD patients reported currently receiving treatment. Controls without nAMD were selected by 1:4 propensity score matching. Healthcare Resource Utilisation (HRU), Health-Related Quality of Life (HRQoL), and work productivity loss were compared between the groups. Regarding HRU, nAMD patients had significantly increased number of visits to any healthcare provider (HCP) (13.8 vs. 8.2), ophthalmologist (5.6 vs. 0.8), and other HCP (9.5 vs. 7.1) compared to controls after adjusting for confounding factors. Additionally, nAMD patients had reduced HRQoL and work productivity, i.e., reduced physical component summary (PCS) score (46.3 vs. 47.9), increased absenteeism (18.14% vs. 0.24%), presenteeism (23.89% vs. 12.44%), and total work productivity impairment (33.57% vs. 16.24%). The increased number of ophthalmologist visits were associated with decreased PCS score, increased presenteeism and total work productivity impairment. The current study highlighted substantial burden for nAMD patients, requiring further attention for future healthcare planning and treatment development.

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