Efficient and Scalable Collection of Dynamic Metrics Using MapReduce

2015 ◽  
Author(s):  
Shallu Sarvari ◽  
Paramvir Singh ◽  
Geeta Sikka
Keyword(s):  
Dynamic Metrics

scholarly journals Dynamic Daylight Metrics for Electricity Savings in Offices: Window Size and Climate Smart Lighting Management

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3143 ◽  
Author(s):  
Ignacio Acosta ◽  
Miguel Ángel Campano ◽  
Samuel Domínguez-Amarillo ◽  
Carmen Muñoz
Keyword(s):  
Energy Efficiency ◽  
Net Present Value ◽  
Energy Savings ◽  
Performance Metrics ◽  
Control Strategies ◽  
Window Size ◽  
Weather Conditions ◽  
Worst Case ◽  
Daylight Performance ◽  
Dynamic Metrics

Daylight performance metrics provide a promising approach for the design and optimization of lighting strategies in buildings and their management. Smart controls for electric lighting can reduce power consumption and promote visual comfort using different control strategies, based on affordable technologies and low building impact. The aim of this research is to assess the energy efficiency of these smart controls by means of dynamic daylight performance metrics, to determine suitable solutions based on the geometry of the architecture and the weather conditions. The analysis considers different room dimensions, with variable window size and two mean surface reflectance values. DaySim 3.1 lighting software provides the simulations for the study, determining the necessary quantification of dynamic metrics to evaluate the usefulness of the proposed smart controls and their impact on energy efficiency. The validation of dynamic metrics is carried out by monitoring a mesh of illuminance-meters in test cells throughout one year. The results showed that, for most rooms more than 3.00 m deep, smart controls achieve worthwhile energy savings and a low payback period, regardless of weather conditions and for worst-case situations. It is also concluded that dimming systems provide a higher net present value and allow the use of smaller window size than other control solutions.

Dynamic metrics to differentiate booster performance

2021 ◽  
Vol 22 (7) ◽  
pp. 530-535
Author(s):  
Kathleen D. Klinich ◽  
Miriam A. Manary ◽  
Kyle J. Boyle ◽  
Nichole R. Orton
Keyword(s):  
Dynamic Metrics

scholarly journals Correction: Dynamic metrics-based biomarkers to predict responders to anti-PD-1 immunotherapy

2019 ◽  
Vol 120 (7) ◽  
pp. 772-772
Author(s):  
Can Liu ◽  
Hua He ◽  
Xiaobing Li ◽  
Maureen A. Su ◽  
Yanguang Cao
Keyword(s):  
Dynamic Metrics

scholarly journals Comparing Static and Dynamic Weighted Software Coupling Metrics

Computers ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 24 ◽  
Author(s):  
Henning Schnoor ◽  
Wilhelm Hasselbring
Keyword(s):  
Software Quality ◽  
Object Oriented ◽  
Software System ◽  
Dynamic Coupling ◽  
Commercial Software ◽  
Dynamic Case ◽  
Compiled Code ◽  
Software Coupling ◽  
Dynamic Metrics ◽  
Production Dynamic

Coupling metrics that count the number of inter-module connections in a software system are an established way to measure internal software quality with respect to modularity. In addition to static metrics, which are obtained from the source or compiled code of a program, dynamic metrics use runtime data gathered, e.g., by monitoring a system in production. Dynamic metrics have been used to improve the accuracy of static metrics for object-oriented software. We study weighted dynamic coupling that takes into account how often a connection (e.g., a method call) is executed during a system’s run. We investigate the correlation between dynamic weighted metrics and their static counterparts. To compare the different metrics, we use data collected from four different experiments, each monitoring production use of a commercial software system over a period of four weeks. We observe an unexpected level of correlation between the static and the weighted dynamic case as well as revealing differences between class- and package-level analyses.

Numerical study on structures formed by the deposition and solidification of a single molten droplet

2020 ◽  
Vol 98 (10) ◽  
pp. 907-916
Author(s):  
Wenbin Li ◽  
Ying Zhang ◽  
Yue Chen ◽  
Peisheng Li ◽  
Chunhong Ma
Keyword(s):  
Cooling Rate ◽  
Numerical Study ◽  
Deposition Process ◽  
Droplet Deformation ◽  
Molten Droplet ◽  
Front Tracking Method ◽  
Parametric Studies ◽  
Dynamic Metrics ◽  
Formed Structure

The formed structure is of importance in determining the surface quality of a component made by droplet-based 3D printing. In the present work, the molten droplet solicitation process was simulated under an axisymmetric system where the smallest length scale and time scale were fully resolved. Evolutions of sharp droplet interfaces were captured through the front tracking method. Parametric studies have been carried out to explore how the dynamic metrics, which include the Ohnesorge number (Oh) and Weber number (We), can affect the structure of depositing droplet. The effect of the superheat parameter on the cooling rate was also investigated in the final section. Numerical results show that the inertial resisting force is critical dynamics in the variation of horizontal dimensionless length at the early deposition process. Three levels of Oh numbers and stages of We numbers were classified according to the deformation behavior. Flattening degree under different Oh number and We number cases were both fitted well by the exponential function. This paper also reveals that the variation law of the cooling rate and solidification time is affected by the superheat parameter, resulting in a feasible and promising method to predict droplet deformation time through the fully resolved numerical simulations during the manufacturing process.

scholarly journals Augmenting static source views in IDEs with dynamic metrics

2009 ◽  
Author(s):  
David Rothlisberger ◽  
Marcel Harry ◽  
Alex Villazon ◽  
Danilo Ansaloni ◽  
Walter Binder ◽  
...  
Keyword(s):  
Static Source ◽  
Dynamic Metrics

Minimum Daylight Autonomy: A New Concept to Link Daylight Dynamic Metrics with Daylight Factors

2019 ◽  
Vol 15 (4) ◽  
pp. 251-269 ◽  
Author(s):  
Ignacio Acosta ◽  
Miguel Ángel Campano ◽  
Samuel Domínguez ◽  
Jessica Fernández-Agüera
Keyword(s):  
Dynamic Metrics
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