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

Background: Multifactor affect the pathogenesis of thrombosis in solid malignancy; however, a significant role is attributed to the cancer cells ability to interact with and activate the host hemostatic system. [1] 

Hemostasis is highly correlated to tumor growth, angiogenesis and metastasis, modulation of these pathways reflects interesting and promising treatment options in the future. [1]

Most patients with cancer frequently suffer from chronic compensated DIC and have abnormal laboratory coagulation tests without clinical manifestations of thrombosis, which is a subclinical hypercoagulable state that can be detected by varying degrees of activation of blood clotting. The results of laboratory tests in th

Biodiesel is an environmentally friendly fuel and a good substitution for the fossil fuel. However, the purity of this fuel is a major concern that challenges researchers. In this study, a calcium oxide based catalyst has been prepared from local waste eggshells by the calcination method and tested in production biodiesel. The eggshells were powdered and calcined at different temperatures (700, 750, 800, 850 and 900 °C) and periods of time (1, 2, 3, 4 and 5 hr.). The effect of calcination temperature and calcination time on the structure and activity of the solid catalyst were examined by X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Brunaure-Emmett-Teller (BET). The optimum catalyst performance was obtained at 900 °C

Solar tracking systems used are to increase the efficiency of the solar cells have attracted the attention of researchers recently due to the fact that the attention has been directed to the renewable energy sources. Solar tracking systems are of two types, Maximum Power Point Tracking (MPPT) and sun path tracking. Both types are studied briefly in this paper and a simple low cost sun path tracking system is designed using simple commercially available component. Measurements have been made for comparison between fixed and tracking system. The results have shown that the trackin

Process capability provides a quantitative measure for gasoline production conformance to specifications.It was measured throughout four consecutive months of the last quarter of 2011. Results revealed high percentages (up to 44%) of non conforming gasoline blends to Iraqi marketing specifications for petroleum products (2000) by inspecting 122 different samples of Iraqi regular gasoline (RON 85).
Quality cost analysis as an important financial control tool was carried out to evaluate Cost of Quality (COQ) which was large due to non conforming gasoline reached up to (722.8 M.ID) in October. In this research COQ was investigated in order to identify the opportunities of gasoline quality improvements through production process. Also cus

Target costing is one of the modern techniques in strategic Management accounting, Is has shown active adoption to changes in current business environments, In addition, is has seen a growth in strategic approach, The goal of using target costing is to build and strengthen competition abilities of economic units through introducing appropriate ways to decrease cost values while maintaining and improving quality of product, So this study is aim to show how can  economic units use target costing to achieve competitive advantages .

Solar tracking systems used are to increase the efficiency of the solar cells have attracted the attention of
researchers recently due to the fact that the attention has been directed to the renewable energy sources. Solar tracking systems are of two types, Maximum Power Point Tracking (MPPT) and sun path tracking. Both types are studied briefly in this paper and a simple low cost sun path tracking system is designed using simple commercially available component. Measurements have been made for comparison between fixed and tracking system. The results have shown that the tracking system is effective in the sense of relatively high output power increase and low cost.

In the present study the performance of drying process of dffirent solid materials by batch fluidized bed drying
under vacuum conditions was investigated. Three, different solid materials, namely; ion exchange resin-8528,
aspirin and paracetamol were used. The behavior of the drying curves as well as the rate of drying of these
materials had been studied. The experiments were caried out in a 0.0381 m column diameter fluidized by hot
air under yacuum conditions. Four variables affecting on the rate of drying were studied' these variables are
vacuum pressure (100 - 500 mm Hg), air temperature (303-323 K), particle size (0.3-0.8 mm) and initial
moisture content (0.35-0.55 g/g solid)-for resin and (0.1-0.2 g/g soltid) for a

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation