In this work gold nanoparticles (AuNPs), were prepared. Chemical method (Seed-Growth) was used to prepare it, then doping AuNPs with porous silicon (PS), used silicon wafer p-type to produce (PS) the processes doping achieved by electrochemical etching, the solution etching consist of HF, ethanol and AuNPs suspension, the result UV-visible absorption for AuNPs suspension showed the single peak located at ~(530 – 521) nm that related to SPR, the single peak is confirmed that the NPs present in the suspension is spherical shape and non-aggregated. X-ray diffraction analysis indicated growth AuNPs with PS. compare the PS layer without AuNPs and with AuNPs doped for electrical properties and sensitivity properties we found AuNPs:PS is more

This work focuses on the preparation of pure nanocrystalline SnO2 and SnO2:Cu thin films on cleaned glass substrates utilizing a sol-gel spin coating and chemical bath deposition (CBD) procedures. The primary aim of this study is to investigate the possible use of these thin films in the context of gas sensor applications. The films underwent annealing in an air environment at a temperature of 500 ^◦C for duration of 60 minutes. The thickness of the film that was deposited may be estimated to be around 300 nm. The investigation included an examination of the structural, optical, electrical, and sensing characteristics, which were explored across various preparation circumstances, specifically focusing on varied

This project sought to fabricate a flexible gas sensor based on a short functionalized multi-walled carbon nanotubes (f-MWCNTs) network for nitrogen dioxide gas detection. The network was prepared by filtration from the suspension (FFS) method and modified by coating with a layer of polypyrrole conductive polymer (PPy) prepared by the oxidative chemical polymerization to improve the properties of the network. The structural, optical, and morphological properties of the f-MWCNTs and f-MWCNTs/PPy network were studied using X-ray diffraction (XRD), Fourie-transform infrared (FTIR), with an AFM (atomic force microscopy). XRD proved that the structure of f-MWCNTs is unaffected by the synthesis procedure. The FTIR spectra verified the existence o

Target tracking is a significant application of wireless sensor networks (WSNs) in which deployment of self-organizing and energy efficient algorithms is required. The tracking accuracy increases as more sensor nodes are activated around the target but more energy is consumed. Thus, in this study, we focus on limiting the number of sensors by forming an ad-hoc network that operates autonomously. This will reduce the energy consumption and prolong the sensor network lifetime. In this paper, we propose a fully distributed algorithm, an Endocrine inspired Sensor Activation Mechanism for multi target-tracking (ESAM) which reflecting the properties of real life sensor activation system based on the information circulating principle in the endocr

Knowing the distribution of the mechanical rock properties and the far field stresses for the field of interest is an important task for many applications concerning reservoir geomechanics, including wellbore instability analysis, hydraulic fracturing, sand production, reservoir compaction, and subsidence. A major challenge with determining the rock's mechanical properties is that they cannot be directly measured at the borehole. Furthermore, the recovered carbonate core samples for performing measurements are limited and they provide discrete data for specific depths.

   The purpose of this study is to build 2D and 3D geomechanical models of the Khasib reservoir in the East Baghdad oil field/ Central area. TECHLOG.2015.3 softwa

Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In

Energy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit

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

A chemical optical fiber sensor based on surface plasmon resonance (SPR) was developed and implemented using multimode plastic optical fiber. The sensor is used to detect and measure the refractive index and concentration of various chemical materials (Urea, Ammonia, Formaldehyde and Sulfuric acid) as well as to evaluate the performance parameters such as sensitivity, signal to noise ratio, resolution and figure of merit. It  was noticed that the value of the sensitivity of the optical fiber-based SPR sensor, with 60nm and 10 mm long, Aluminum(Al) and Gold (Au) metals film exposed sensing region, was 4.4 μm, while the SNR was 0.20, figure of merit was 20 and resolution 0.00045. In this work a multimode