Optimal placement of excitations and sensors by simulated annealing

The optimal placement of discrete actuators and sensors is posed as a combinatorial optimization problem. Two examples for truss structures were used for illustration; the first dealt with the optimal placement of passive dampers along existing truss members, and the second dealt with the optimal placement of a combination of a set of actuators and a set of sensors. Except for the simplest problems, an exact solution by enumeration involves a very large number of function evaluations, and is therefore computationally intractable. By contrast, the simulated annealing heuristic involves far fewer evaluations and is best suited for the class of problems considered. As an optimization tool, the effectiveness of the algorithm is enhanced by introducing a number of rules that incorporate knowledge about the physical behavior of the problem. Some of the suggested rules are necessarily problem dependent

Fuzzy-rough set and fuzzy ID3 decision approaches to knowledge discovery in datasets

Fuzzy rough sets are the generalization of traditional rough sets to deal with both fuzziness and vagueness in data. The existing researches on fuzzy rough sets mainly concentrate on the construction of approximation operators. Less effort has been put on the knowledge discovery in datasets with fuzzy rough sets. This paper mainly focuses on knowledge discovery in datasets with fuzzy rough sets. After analyzing the previous works on knowledge discovery with fuzzy rough sets, we introduce formal concepts of attribute reduction with fuzzy rough sets and completely study the structure of attribute reduction

The Rule of Artificial Neural Network Algorithm in Geomagnetic Storms Prediction

While relativistic electrons can completely destroy a spacecraft when the solar wind-magnetospheric interactions are enhanced, the Dst index is considered to be an indicator of any geomagnetic storm. The more negative the Dst index values, the stronger the magnetic storm.   Every relativistic electron event was associated with a magnetic storm, but, magnetic storms could occur without appreciable enhancement of the relativistic electron fluxes. The problem thus arises, which one should be predicted:  the Dst index or relativistic electron enhancements (REE), in order to be more logic? and which is more effective for prediction: the use of statistical relationships or Artificial Neural Networks? Reproduction (or simulation) of the Dst index using a neural network algorithm would solve the problem. An Artificial Neural Network Algorithm was adopted in the present study for the reproduction of the Dst index of geomagnetic storms having the training concept “Train to Gain” in mind.  The ANN was well trained using a data set of 37 storms of different intensities as input to the network. A well trained ANN would yield an extremely good correlation between the measured Dst and the predicted Dst. The applied ANN algorithm in the present study shows an excellent performance. About 97% of the Dst have been reproduced, at least, for both the main and recovery phases. Efficient forecast of the oncoming relativistic electron flux enhancements (REE) can thus - under certain conditions - be issued. Keywords: Geomagnetic storms, Geosynchronous orbit, Solar cycle-23, Dst index, Relativistic Electron Enhancement, Artificial Neural Network

Relativistic Electron Enhancement (REE) Behavior during the Recovery Phase of Solar Cycle 23

To quantify the relationship between geomagnetic storms and relativistic electron enhancement (REE) at geosynchronous orbit and magnetic storms, a full solar cycle (1996–2006) of data has been examined.  The relativistic electron fluxes of the earth’s outer belt are subjected to strong temporal variations.  The most prominent changes are initiated by the fast solar wind streams which often also caused enhanced substorm activity and magnetic storms.  We considered the weak, moderate and intense geomagnetic storms using the index for 313 storms that occurred during Solar Cycle 23 (in the interval from January 1996 to December 2006).  The relativistic electron fluence data were based on fluxes observed by the GOES geosynchronous satellites. In the present study, we analyzed 313 Intense, Moderate and Weak storms observed at three different latitudes. A statistical study has been performed to quantify the REE behavior before and after the recovery phase of magnetic storms.  Every relativistic electron event was associated with a magnetic storm, but, magnetic storms could occur without appreciable enhancement of the relativistic electron fluxes.  More input parameters such as; solar wind velocity, dynamic pressure, and density, were thus used to make a cross-correlation analysis to determine what parameters might influence the flux of relativistic electrons. Keywords: Geomagnetic storms, Geosynchronous orbit, Dst index, Relativistic Electron Enhancement

The role of mega projects in redefining housing development in Gulf cities

Since the end of the 1990s large scale mega projects have been initiated in Gulf cities to enable an unprecedented urban growth and the expansion of new economic sectors. In this respect, mega projects have played a key role in redefining housing developments in Gulf cities. This paper explores the newly emerging housing typologies and their distinctive roles in defining new urban environments. The selected case studies are located in the Jumeirah District in Dubai, which can be seen as the first prototype of a large cohesive development area that has been built of nine rather differing mega projects including the iconic Palm project and one of the largest residential high-rise agglomerations in the Middle East. The paper is based on the evaluation of official planning data from each project and field observations. Conclusions are drawn to highlight key implications while identifying housing development tendencies

Ending Neglect of older people in the response to Humanitarian Emergencies

Older people make up a significant and growing number of those affected by humanitarian crises, yet they are often not sought out or prioritised within the humanitarian response. Humanitarian agencies, donors, and international bodies neglect older people's health and nutrition. The gaps in knowledge and research about the needs of older people in emergencies are considerable. Older people are not monitored in emergencies and they are not prioritised despite evidence of disproportionate mortality and morbidity in this group. We call for policy changes by humanitarian agencies and donors to ensure that the needs of this vulnerable group are met