The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently.  Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ r

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

In this work, we construct projectively distinct (k,3)-arcs in the projective plane PG(2,9) by applying a geometrical method. The cubic curves have been been constructed by using the general equation of the cubic. We found that there are complete (13,3)-arcs, complete (15,3)-arcs and we found that the only (16,3)-arcs lead to maximum completeness

In this paper, a new technique is offered for solving three types of linear integral equations of the 2^nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree  and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those

In this paper, a new technique is offered for solving three types of linear integral equations of the 2nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree  and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those methods i

Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

   Reservoir characterization plays a crucial role in comprehending the distribution of formation properties and fluids within heterogeneous reservoirs. This knowledge is instrumental in constructing an accurate three-dimensional model of the reservoir, facilitating predictions regarding porosity, permeability, and fluid flow distribution. Among the various methods employed for reservoir characterization, the hydraulic flow unit stands out as a widely adopted approach. By effectively subdividing the reservoir into distinct zones, each characterized by unique petrophysical and geological properties, hydraulic flow units enable comprehensive reservoir analysis. The concept of the flow unit is closely tied to the flow zone indicator, a cr