Non-invasive Thermal Modeling Techniques Using Ambient Sensors for Greening Data Centers

2010 ◽  
Author(s):  
Michael Jonas ◽  
Georgios Varsamopoulos ◽  
Sandeep K. S. Gupta
Keyword(s):  
Data Centers ◽  
Thermal Modeling ◽  
Non Invasive ◽  
Modeling Techniques

Effects of diffusion signal modeling and segmentation approaches on subthalamic nucleus parcellation

2021 ◽  
Author(s):  
Demetrio Milardi ◽  
Gianpaolo Antonio Basile ◽  
Joshua Faskowitz ◽  
Salvatore Bertino ◽  
Angelo Quartarone ◽  
...  
Keyword(s):  
Subthalamic Nucleus ◽  
Healthy Subjects ◽  
Fine Tuning ◽  
Signal Modeling ◽  
Fiber Density ◽  
Non Invasive ◽  
Human Connectome Project ◽  
Modeling Techniques ◽  
Winner Takes All

AbstractThe subthalamic nucleus (STN) is commonly used as a surgical target for deep brain stimulation in movement disorders such as Parkinson’s Disease. Tractography-derived connectivity-based parcellation (CBP) has been recently proposed as a suitable tool for non-invasive in vivo identification and pre-operative targeting of specific functional territories within the human STN. However, a well-established, accurate and reproducible protocol for STN parcellation is still lacking. The present work aims at testing the effects of different tractography-based approaches for the reconstruction of STN functional territories.We reconstructed functional territories of the STN on the high-quality dataset of 100 unrelated healthy subjects and on the test-retest dataset of the Human Connectome Project (HCP) repository. Connectivity-based parcellation was performed with a hypothesis-driven approach according to cortico-subthalamic connectivity, after dividing cortical areas into three groups: associative, limbic and sensorimotor. Four parcellation pipelines were compared, combining different signal modeling techniques (single-fiber vs multi-fiber) and different parcellation approaches (winner takes all parcellation vs fiber density thresholding). We tested these procedures on STN regions of interest obtained from three different, commonly employed, subcortical atlases. We evaluated the pipelines both in terms of between-subject similarity, assessed on the cohort of 100 unrelated healthy subjects, and of within-subject similarity, using a second cohort of 44 subjects with available test-retest data. We found that each parcellation provides converging results in terms of location of the identified parcels, but with significative variations in size and shape. Higher between-subject similarity was found with multi-fiber signal modeling techniques combined with fiber density thresholding. All the pipelines obtained very high within-subject similarity, with tensor-based approaches outperforming multi-fiber pipelines. We suggest that a fine-tuning of tractography-based parcellation may lead to higher reproducibility and aid the development of an optimized surgical targeting protocol.

Dynamic Thermal Modeling of Data Centers

2014 ◽  
pp. 97-154
Author(s):  
Bahgat Sammakia ◽  
Yogendra Joshi ◽  
Dereje Agonafer ◽  
Emad Samadiani ◽  
Avram Bar-Cohen
Keyword(s):  
Data Centers ◽  
Thermal Modeling

Load, Speed and Inflation Pressure Effects on Rolling Loss Distribution in Automobile Tires

1988 ◽  
Vol 16 (2) ◽  
pp. 78-95 ◽  
Author(s):  
J. D. Clark ◽  
D. J. Schuring
Keyword(s):  
Thermal Model ◽  
Thermal Modeling ◽  
Infrared Camera ◽  
Pressure Effects ◽  
Direct Result ◽  
Laboratory Measurements ◽  
Inflation Pressure ◽  
Camera System ◽  
Temperature Distributions ◽  
Modeling Techniques

Abstract The effect of tire load, speed, and cold inflation pressure on the rolling loss contribution of any tire region is determined by numerical calculations involving both laboratory measurements and thermal modeling techniques. Laboratory measurements include tire surface temperature distributions obtained from an infrared camera system; thermal modeling is based on finite-difference procedures. Results are presented in two formats: (1) plots of rolling loss distributions from bead to bead and (2) contributions of tread, shoulder, sidewall, and bead regions. The first format is a direct result of the thermal model; the second is derived from multiple-regression operations. Both formats are given as functions of load, cold inflation pressure, and speed. Beahvior in the tread region is shown to be unique.

A Data-Centric Approach for Integrated Data Center Management

2011 ◽  
Author(s):  
Christopher Hoover
Keyword(s):  
Control Systems ◽  
Data Model ◽  
Data Center ◽  
Data Centers ◽  
Loose Coupling ◽  
Cross Domain ◽  
Model Combining ◽  
Modeling Techniques ◽  
Logical Modeling ◽  
Domain Management

In this paper, we present the Daffy data model and messaging framework for data centers. The model is a hybrid model, combining physical, structural, geometrical, and logical modeling techniques. The messaging scheme has excellent performance and allows for the loose coupling of the various framework components. The framework bridges the gap between facilities and IT domains and enables the holistic, cross-domain management of data centers. The framework supports rich visualization, cross-domain queries and sophisticated cross-domain autonomic control systems.

Thermal Modeling of Data Centers for Control and Energy Usage Optimization

2018 ◽  
pp. 123-186 ◽  
Author(s):  
Jayati Athavale ◽  
Minami Yoda ◽  
Yogendra Joshi
Keyword(s):  
Data Centers ◽  
Thermal Modeling ◽  
Energy Usage

Thermal Modeling and Management of Storage Systems in Data Centers

2015 ◽  
pp. 915-943 ◽  
Author(s):  
Xunfei Jiang ◽  
Ji Zhang ◽  
Xiao Qin ◽  
Meikang Qiu ◽  
Minghua Jiang ◽  
...  
Keyword(s):  
Data Centers ◽  
Storage Systems ◽  
Thermal Modeling
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