2. Lithic design space modelling and cognition inHomo floresiensis

2007 ◽  
pp. 11-33 ◽  
Author(s):  
Mark W. Moore
Keyword(s):  
Design Space

The Environmental Design Space: Modeling and Performance Updates

2021 ◽  
Author(s):  
Luis Salas Nunez ◽  
Jimmy C. Tai ◽  
Dimitri N. Mavris
Keyword(s):  
Design Space ◽  
Environmental Design ◽  
Space Modeling ◽  
And Performance

The impact of design space constraints on the noise and emissions from derivative engines for civil supersonic aircraft

2021 ◽  
Author(s):  
Laurens Voet ◽  
Prakash Prashanth ◽  
Raymond Speth ◽  
Jayant Sabnis ◽  
Choon Tan ◽  
...  
Keyword(s):  
Design Space ◽  
Supersonic Aircraft ◽  
The Impact

Proposal of an instrument to evaluate interaction spaces in a VLE

2019 ◽  
pp. 1-13
Author(s):  
Rubí Estela Morales-Salas ◽  
Daniel Montes-Ponce
Keyword(s):  
Learning Environment ◽  
Design Space ◽  
Collaborative Work ◽  
Virtual Learning ◽  
Interaction Space ◽  
Learning Objects ◽  
Traditional Education ◽  
Virtual Learning Environment ◽  
Discussion Forums ◽  
Exhibition Space

A virtual learning environment is conceived as an interaction space that ease the realization of mediated activities by technology, in this case the internet; besides using multimedia materials, learning objects, social networks, among others; which have changed imminently the traditional education. In this article an instrument is proposed in a checklist format, to evaluate any platform that has interaction spaces such as a Virtual Learning Environment, in this case responding to four spaces or general indicators: information Space, Mediation / Interaction Space, Instructional Design Space and Exhibition Space. Criteria are used according to the interactions and activities carried out by the consultant and virtual student. These, in turn, come up from the analysis and interaction of the advisers achieved in the discussion forums and portfolio activities through collaborative work. It was situated as a qualitative research, with a descriptive nature since it is not limited to data collection only, but also it refers and analyzes the interaction of the advisers achieved in the discussion forums and portfolio activities through the collaborative work of the workshop course "Virtual Learning Environments" developed in a virtual learning environment.

Optimization Study to Develop Once-a-day Controlled Release Formulation of Metoclopramide with Predictable Design Space

1970 ◽  
Vol 1 (1) ◽  
pp. 71-76
Author(s):  
Rajesh Dubey ◽  
Udaya K. Chowdary ◽  
Venkateswarlu V.
Keyword(s):  
Controlled Release ◽  
Drug Release ◽  
Design Space ◽  
Release Kinetics ◽  
Release Profile ◽  
Release Formulation ◽  
Linear Effect ◽  
Controlled Release Formulation ◽  
The Difference ◽  
Face Centered

A controlled release formulation of metoclopramide was developed using a combination of hypromellose (HPMC) and hydrogenated castor oil (HCO). Developed formulations released the drug over 20 hr with release kinetics following Higuchi model. Compared to HCO, HPMC showed significantly higher influence in controlling the drug release at initial as well as later phase. The difference in the influence can be explained by the different swelling and erosion behaviour of the polymers. Effect of the polymers on release was optimized using a face-centered central composite design to generate a predictable design space. Statistical analysis of the drug release at various levels indicated a linear effect of the polymers’ levels on the drug release. The release profile of formulations containing the polymer levels at extremes of their ranges in design space was found to be similar to the predicted release profile

Wireless Sensor Network in IoT and Performance Optimization

2020 ◽  
Vol 13 ◽  
Author(s):  
Sunita Gupta ◽  
Sakar Gupta ◽  
Dinesh Goyal
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Harvesting ◽  
Performance Optimization ◽  
Design Space ◽  
Life Time ◽  
Wireless Sensor ◽  
Topology Management ◽  
Management Application ◽  
Energy Latency

: A serious problem in Wireless Sensor Networks (WSNs) is to attain high-energy efficiency as battery is used to power and have limited stored energy. They can’t be suitably replaced or recharged. Appearance of renewable energy harvesting techniques and their combination with sensor devices gives Energy Harvesting Wireless Sensor Networks (EHWSNs). IoT is now becoming part of our lives, comforting simplifying our routines and work life. IoT is very popular . It connects together, computes, communicates and performs the required task. IoT is actually a network of physical devices or things that can interact with each other to share information. This paper gives an overview of WSN and IoT, related work, different ways of connecting WSN with internet, development of smart home, challenges for WSN etc. Next a Framework for performance optimization in IoT is given and QC-PC-MCSC heuristic is analyzed in terms of Energy Efficiency and Life Time of a sensor on Energy Latency Density Design Space, a topology management application that is power efficient. QC-PC-MCSC and QC-MCSC are compared for Energy Efficiency and Life Time of a sensor over energy latency density design space, a topology management application.

A Comprehensive Investigation of Ensembles of Gaussian-Based and Gradient-Based Transformed Reliability Analyses: When and How to Use Them

2016 ◽  
Author(s):  
Po Ting Lin ◽  
Wei-Hao Lu ◽  
Shu-Ping Lin
Keyword(s):  
Design Optimization ◽  
Design Space ◽  
Optimization Problems ◽  
Nonlinear Problems ◽  
Kernel Functions ◽  
Sensitivity Analyses ◽  
Normal Space ◽  
Highly Nonlinear ◽  
Standard Normal ◽  
Gradient Based

In the past few years, researchers have begun to investigate the existence of arbitrary uncertainties in the design optimization problems. Most traditional reliability-based design optimization (RBDO) methods transform the design space to the standard normal space for reliability analysis but may not work well when the random variables are arbitrarily distributed. It is because that the transformation to the standard normal space cannot be determined or the distribution type is unknown. The methods of Ensemble of Gaussian-based Reliability Analyses (EoGRA) and Ensemble of Gradient-based Transformed Reliability Analyses (EGTRA) have been developed to estimate the joint probability density function using the ensemble of kernel functions. EoGRA performs a series of Gaussian-based kernel reliability analyses and merged them together to compute the reliability of the design point. EGTRA transforms the design space to the single-variate design space toward the constraint gradient, where the kernel reliability analyses become much less costly. In this paper, a series of comprehensive investigations were performed to study the similarities and differences between EoGRA and EGTRA. The results showed that EGTRA performs accurate and effective reliability analyses for both linear and nonlinear problems. When the constraints are highly nonlinear, EGTRA may have little problem but still can be effective in terms of starting from deterministic optimal points. On the other hands, the sensitivity analyses of EoGRA may be ineffective when the random distribution is completely inside the feasible space or infeasible space. However, EoGRA can find acceptable design points when starting from deterministic optimal points. Moreover, EoGRA is capable of delivering estimated failure probability of each constraint during the optimization processes, which may be convenient for some applications.

Design Space Exploration of a 512KB STT-Assisted SOT MRAM Cache

2020 ◽  
Author(s):  
Adrian G. Caburnay ◽  
Jonathan Gabriel S.A. Reyes ◽  
Anastacia P. Ballesil-Alvarez ◽  
Maria Theresa G. de Leon ◽  
John Richard E. Hizon ◽  
...  
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration
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