Compiler writers have developed various techniques, such as constant folding, subexpression elimination, loop transformation and vectorization, to help compilers in code optimization for performance improvement. Yet, they have been far less successful in developing techniques or cost models that compilers can rely on to simplify parallel programming and tune the performance of parallel applications automatically. This paper is the first of two-phase study to develop an analytical model that can be used to estimate the cost for sequential and parallel execution of array expressions on multicore architectures. While this paper discuss the possibility of developing a cost model to estimate the sequential execution of array expressions on a single CPU, the second part of the investigation shall focus on developing a model to estimate parallel execution of arrays on multicore platforms. The model presented in this paper is expected to be used by programming language compilers as complement component with the other model to estimate and subsequently decide whether to parallelize individual array expressions or not. The preliminary results which are presented here show that this model can give a satisfactory evaluation and high-precision estimation for the cost of executing a regular array expression on a single core processor.

The objectives of this study (baseline study, n = 20) were to implement Matlab procedures for quantifying selected static balance variables, establish baseline data of selected variables which characterize static balance activities in a population of healthy young adult males, and to examine any trial effects on these variables. The results indicated that the implementation of Matlab procedures for quantifying selected static balance variables was practical and enabled baseline data to be established for selected variables. There was no significant trial effect. Recommendations were made for suitable tests to be used in later studies. Specifically it was found that one foot-tiptoes tests either in static balance is too challenging for most participants in normal circumstances. A one foot-flat eyes open test was considered to be representative and challenging for static balance.

Abstract—this work reports on a high speed flexible automation system based on Cartesian multi-axis coordinate system linear step motor developed, in the target application as a multi-use robot system. The task of this work is to constructs an interactive multimedia page for study and researches the principle’s work of drive of direct action linear step motor, Development the mathematical model and implementation of a closed loop control, based MATLAB/SIMULINK, Study the static and dynamic characteristics of the motor movement which is restricted to the trajectories accessible through the given commands.

Abstract—This work reports on the steady-state analysis and control strategies of switched reluctance motors (SRMs). For this purpose, a theoretical background is introduced and a mathematical model is derived. A Matlab code has been written to determine the motor magnetic characteristics. The inductance profile has also been determined and from which the induced voltage constant, which is used to find the electromagnetic torque, is obtained. A low-performance voltage control strategy is applied to the motor. Simulation results are given to evaluate the overall system performance

Abstract

There is much discussion in the scientific literature and concern in the wider community about climate

change, recent climate analyses indicate that the magnitude of 21st Century warming is likely to have been the

largest of any century for the last 1000 years over the northern hemisphere. All the IPCC's four reports between

1990 and 2007 concluded that we cannot expect stable climate in the future and we should prepare scenarios

and strategies for the survival of humankind under the conditions of forthcoming global change. In this study,

the applicability of the statistical downscaling model (SDSM) in downscaling temperature in Misurata area -

Libya, was investigated. The investigation includes the calibration of the SDSM model by using large-scale

atmospheric variables encompassing NCEP reanalysis data, the validation of the model were measured daily

temperature data (1961-1990) using independent period of the NCEP reanalysis data and the general circulation

model (GCM) outputs of scenarios A2 and B2 of the HadCM3 model. The model is calibrated and applied at a

daily time series, even though the output is monthly and the prediction of the future regional maximum and

minimum temperature scenarios for three time windows: 2011-2040, 2041-2070 and 2071-2099. The results showed

that: The statistical downscaling model (SDSM) was able to describe the basic statistical properties of daily

minimum and maximum temperature in the period of record, suggesting that it could be used to predict future

trends. Trend analysis in the study area showed an increase in average annual and monthly temperature,

compared to the baseline period for both HadCM3A2a and HadCM3B2a scenarios in both the dry and wet

seasons. However, this increase is higher in dry months than wet months for all future time horizons and for

both HadCM3A2a and HadCM3B2a scenarios. Thus there is likely to be a significant warming in local surface

temperature, which is enough for a significant change on the energy balance and is likely to impact water

availability.

Key words: Statistical downscaling model SDSM Intergovernmental Panel on Climate Change

IPCC General circulation model GCM Special Report on the Emission Scenarios SERS

Maximum and minimum temperature Misurata area Libya

This study is aimed at investigating the interactive effect of reaction variables on the composition and octane number of reformat in catalytic naphtha reforming gasoline fuel. The relationship between aromatization activity and RON, with three reaction variables, namely temperature (480–510 °C), total pressure (10–30 bar) and space velocity LHSV (1.2–1.8 h⁻¹) were presented as empirical mathematical models. Experiments were performed based on the central composite rotatable design and analyzed using response surface methodology (RSM) and canonical analysis. First, the equation models are used to predict RON and aromatization activity as responses. Second, the regression analysis of RON and aromatization activity equations is obtained from the output of these developed models. Finally, the RSM is used to optimize these regression empirical models. R ² = 88.5 % for RON and 80.5 for the aromatization activity showed that RSM models fitted well with the observed data and considered to be accurate and available for predicting responses. The temperature and total pressure are the most effective variables as a linear (X 1 , X 2) terms and have a significant role in the responses. Numerical results also revealed that the maximum predicted RON of 105 was attained at optimum reaction temperature of 515 °C, operating pressure of 17 bar and LHSV of 2.0 h⁻¹.