3D seismic and formation micro-imager (FMI) integrated study to delineate depositional pattern of Abu Madi (Upper Miocene) clastic reservoir rocks in El-Wastani gas field,onshore Nile Delta,Egypt

Ten wells (EW-4, EW-5, EW-6, EW-7, EW-8, EW-9, EW-10, EW-12, EW-13 and EW-15) were interpreted using the composite well logs, data of core analysis, gamma-ray logs, formation micro-imager logs (FMI), and 3D seismic data in SEGY format to understand the stratigraphy of the onshore, Nile Delta, Egypt.The amplitude analysis of 3-D seismic horizon slice of Lower Abu Madi rock unit together with the lithostratigraphic correlation through the study area depending on the gamma-ray log “HSGR” (left to right increasing), and the identification of type of bed geometry, nature of bed contacts, type of the sedimentary structures and the dominant formative paleocurrents by using some available borehole micro-resistivity images (FMI) and core photos. All of these techniques are used together to define the different depositional facies and depositional environment of the Messinian clastics (Lower Abu Madi rock unit), which is considered to be the main reservoir in the El-Wastani gas field, onshore Nile Delta, Egypt.The present study of depositional pattern of the Upper Miocene clastics reservoir (Lower Abu Madi rock unit) revealed that it is represented by high sinuous meandering channels or paleo-valley and three types of fluvial facies were defined; channel fill, channel margin, and floodplain basin.     

Implementing IoT/WSN based smart Saskatchewan Healthcare System

Wireless Networks - The Internet of Things (IoT) technology has recently experienced popularity and growth in every facet of life, and it has been applied to every industry in recent years. The...     

Optimization of flow in additively manufactured porous columns with graded permeability

Chemical engineering systems often involve a functional porous medium, such as in catalyzed reactive flows, fluid purifiers, and chromatographic separations. Ideally, the flow rates throughout the porous medium are uniform, and all portions of the medium contribute efficiently to its function. The permeability is a property of a porous medium that depends on pore geometry and relates flow rate to pressure drop. Additive manufacturing techniques raise the possibilities that permeability can be arbitrarily specified in three dimensions, and that a broader range of permeabilities can be achieved than by traditional manufacturing methods. Using numerical optimization methods, we show that designs with spatially varying permeability can achieve greater flow uniformity than designs with uniform permeability. We consider geometries involving hemispherical regions that distribute flow, as in many glass chromatography columns. By several measures, significant improvements in flow uniformity can be obtained by modifying permeability only near the inlet and outlet.     

Switched-capacitor high-speed emulator for real-time fault location in electrical power systems

This research presents a discrete-time transmission line model based on the propagation of travelling waves. In this approach, the transmission line is emulated by means of many interconnected unit delay cells implemented with switched-capacitor (SC) circuits. The accuracy and limitations of this method is compared to existing transconductance–capacitor solutions and is evaluated in the frame of a novel power network fault location method based on the electromagnetic time-reversal principle. The impact of the non-ideal effects associated to analog CMOS SC circuits, such as amplifier finite gain, offset and switch charge injection is evaluated in the same context. A possible application of the model for the simulation of interconnected or multi-conductor lines is also discussed. After an AMS 0.35 µm process implementation, it is shown that the present method allows a fault location within 1% resolution and is a hundred times faster than nowadays digital solutions. This speed improvement allows a fault location within 160 ms, making thus real-time applications realistic.     

EmotionMap: Visual Analysis of Video Emotional Content on a Map

Journal of Computer Science and Technology - Emotion plays a crucial role in gratifying users’ needs during their experience of movies and TV series, and may be underutilized as a framework...     

LPNN-based approach for LASSO problem via a sequence of regularized minimizations

In compressive sampling theory, the least absolute shrinkage and selection operator (LASSO) is a representative problem. Nevertheless, the non-differentiable constraint impedes the use of Lagrange programming neural networks (LPNNs). We present in this article the -LPNN model, a novel algorithm that tackles the LASSO minimization together with the underlying theory support. First, we design a sequence of smooth constrained optimization problems, by introducing a convenient differentiable approximation to the non-differentiable -norm constraint. Next, we prove that the optimal solutions of the regularized intermediate problems converge to the optimal sparse signal for the LASSO. Then, for every regularized problem from the sequence, the -LPNN dynamic model is derived, and the asymptotic stability of its equilibrium state is established as well. Finally, numerical simulations are carried out to compare the performance of the proposed -LPNN algorithm with both the LASSO-LPNN model and a standard digital method.     

A survey and taxonomy on virtual data center embedding

The Journal of Supercomputing - Data center network virtualization is being considered as a promising technology to provide a performance guarantee for cloud computing applications. One important...     

Energy management strategy in cloud computing: a perspective study

Optimizing energy consumption in cloud computing is yet a challenge despite the diversity of the proposed energy management strategies. Indeed, and during our related work study we have observed that the different elements or components which should be considered in order to be able to properly manage energy consumption in a cloud computing context are not well defined and/or discussed in terms of importance. This makes the proper classification and/or comparison of the different proposed strategies or techniques very difficult. Consequently, this paper aims, on the one hand, at defining and discussing properly such components in order to create a guideline and, on the other hand, to ease both the classification and the comparison of these proposed strategies and techniques. Second and after discussing some common weaknesses related to the current energy consumption optimization techniques and methods, this paper proposes energy-saving technique which uses a novel load detecting policy. This policy is based on the median absolute deviation method which uses the median and the standard deviation to calculate upper and lower thresholds which aim to classify hosts into either overloaded or under-loaded state. Simulation results have shown better results of the proposed technique compared to the existing ones especially in reducing energy consumption and the number of virtual machine migrations in addition to better active host time. Indeed, we found that the average of saved energy is around 40% compared to the built in techniques in cloudSim.