Different parameters of double pipe helical coil were investigation experimentally. Four coils were used; three with a curvature ratio (0.037, 0.031, and 0.028) and 11mm diameter of the inner tube while the fourth with 0.033 curvature ratio and 13 mm diameter of the inner tube. The hot water flow in the inner tube whereas the cold water flows in the annulus. The inlet temperatures of hot and cold water are 50 ⁰C and 18 ⁰C respectively. The inner mass flow rate ranges from 0.0167 to 0.0583 kg/s. The results show the Nusselt number increase with increase curvature ratio. The Nusselt number of the coil with 0.037 curvature ratio increases by approximately 12.3 % as compare with 0.028 curvature ratio. The results also r

The current research aims to provide a conceptual and applied frame  on the subject of multi- level analysis in the research of business administration. The research tries to address some of the problems that befall the preparation of research and studies at the Arab level and local level, where the unity of theory and measurement and analysis, as well as clarify  the various types of conceptual constructs and give researchers the ability to  distinguish different models related to the level of analysis. On the other hand, this research  provides an example of 

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

Investigating the thermal and electrical gains and efficiencies influence the designed photovoltaic thermal hybrid collector (PVT) under different weather conditions. The designed system was manufactured by attaching a fabricated cooling system made of serpentine tubes to a single PV panel and connecting it to an automatic controlling system for measuring, monitoring, and simultaneously collecting the required data. A removable glass cover had been used to study the effects of glazed and unglazed PVT panel situations. The research was conducted in February (winter) and July (summer), and March for daily solar radiation effects on efficiencies. The results indicated that electrical and thermal gains increased by the incre