Characterization of the Ion Beam Current Density of the RF Ion Source with Flat and Convex Extraction Systems

Silicon - The characterization of ion beam current density distribution and beam uniformity is crucial for improving broad-beam ion source technologies. The design of the broad ion beam extraction...     

Oil Families and Their Potential Sources in the Southern Gulf of Suez, Egypt

Four oil families are identified in the southern Gulf of Suez, through high-resolution geochemical studies including gas chromatography, gas chromatography-mass spectrometry, and carbon isotope analyses. Biological features characterize oils in family 1a, suggesting tertiary carbonate source rocks for these oils, rich in type II organic matter and deposited under anoxic depositional environment. Family 1b oil shows minor variations in the source of organic matter and the depositional environment, as it was derived from carbonate source rock with more algal and bacterial contribution and minor input of terrestrial organic sources, deposited under less saline condition compared to family 1a oil. Family 2 oil, although genetically related to family 1a oil, has some distinctive features, such as diasterane to sterane and pristane to phytane ratios, which suggest clay-rich source rocks and a more oxic depositional environment. Also, the lack of oleanane indicates pre-tertiary source rocks for this oil. In contrast, family 3 oil is of mixed sources (marine and non-marine), generated from low sulfur and clay-rich source rock of tertiary and/or younger age. Family 4 oil seems to be mixed from family 1b and family 3 oils, sourced mainly from carbonate source rocks rich in clay minerals with algal and bacterial contributions. Family 4 oil is highly mature, family 1b oil lies within equilibrium values (peak oil generation stage), while the other families are more or less near equilibrium.     

Influence of Ni Interlayers on the Mechanical Properties of Ti6Al4V/(WC-Co) Friction Welds

Ni interlayers were introduced prior to dissimilar friction welding of Ti6Al4V base material to three cemented carbide substrates. The fracture strength of Ti6Al4V/(WC-6 wt% Co) welds were poor and were markedly improved when 20-µm thick Ni interlayers were introduced prior to dissimilar friction welding. These results were only produced when the (WC-6 wt% Co) cermet was electroplated prior to friction welding. When the Ti6Al4V alloy was electroplated prior to friction welding, fractured WC particles and cracking were observed in the (WC-Co) carbide substrate. The fracture strengths of Ti6Al4V/(WC-11 wt% Co) and Ti6Al4V/(WC-24 wt% Co) welds were not improved when 20-µm thick Ni interlayers were introduced prior to friction welding. During mechanical testing, the Ni layer retained at the dissimilar joint interface created a region of weakness.     

Statistical analysis of fiber-optic CDMA communication systems. I. Device modeling

In this paper, we present a new methodology for analysis of all-optical fiber-optic code-division multiple-access (FO-CDMA) networks. In this analysis, we propose statistical models, based on photon-counting techniques, for some basic elements of the network, such as splitters, combiners, star couplers, and FO-CDMA passive encoders/decoders. By following the statistical variation of the photon-count of the string of pulses that constitutes the address sequence in an FO-CDMA network, we will be able to reveal the quantum-limited optical signal-to-noise ratio (OSNR) required at the transmitter output to meet the performance limits. Moreover, considering receiver thermal noise and source extinction ratio, we explore the role of using an optical preamplifier before the detector and the dependence of the performance on the transmitted power and the weight of the employed optical orthogonal codes (OOCs).     

Electro-optical characteristics of indium tin oxide (ITO) films: effect of thermal annealing

The effect of thermal annealing on the electrical and optical characteristics of ITO films prepared by reactive sputtering and thermal evaporation have been studied. The effect of the thermal annealing is to improve the conductivity and the optical transmission in the shorter wavelength region. The conductivity of the films increases with annealing temperature, this behaviour is associated with grain growth in the film.     

Novel hybrid DNN approaches for speaker verification in emotional and stressful talking environments

Neural Computing and Applications - In this work, we conducted an empirical comparative study of the performance of text-independent speaker verification in emotional and stressful environments....     

Low‐velocity impact of nanocomposite and polymer plates

Nanocomposites are more widely studied today because of higher stiffness, decreased permeability, thermal stability, and many other properties superior to those of regular polymers. However, manufacturers are concerned about implementing nanocomposites because of their lower impact properties with respect to the base polymer. This study focused on low‐velocity impact tests of a thermoplastic olefin by itself and with 5 wt % nanoclay. The impact tests were conducted at ?40, 23.9, and 65.6°C until the polymer and nanocomposite plates experienced complete striker penetration. The force–time and force–deflection responses obtained from the impact testing provided a means of comparing the impact performances of the two materials. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 2309–2315, 2005     

Employing both gender and emotion cues to enhance speaker identification performance in emotional talking environments

Speaker recognition performance in emotional talking environments is not as high as it is in neutral talking environments. This work focuses on proposing, implementing, and evaluating a new approach to enhance the performance in emotional talking environments. The new proposed approach is based on identifying the unknown speaker using both his/her gender and emotion cues. Both Hidden Markov Models (HMMs) and Suprasegmental Hidden Markov Models (SPHMMs) have been used as classifiers in this work. This approach has been tested on our collected emotional speech database which is composed of six emotions. The results of this work show that speaker identification performance based on using both gender and emotion cues is higher than that based on using gender cues only, emotion cues only, and neither gender nor emotion cues by 7.22 %, 4.45 %, and 19.56 %, respectively. This work also shows that the optimum speaker identification performance takes place when the classifiers are completely biased towards suprasegmental models and no impact of acoustic models in the emotional talking environments. The achieved average speaker identification performance based on the new proposed approach falls within 2.35 % of that obtained in subjective evaluation by human judges.     

Modulation Based Combination of High Level Features Generated from SCCF & Contourlet Transforms for CBIR Applications

The need for suitable and cost-effective technologies rise with the growth of the internet of things (IoT) applications. These aim at handling voluminous data transmission in addition to minimum energy and latency cost constraints. LoRa networks are recommended for applications in confined spaces, long ranges, and less battery consumption requirements. However, the end devices in these networks communicate to all gateways in their ranges, thereby expediting energy unproductively in redundant transmissions. In our article, we explore the possibilities of whether LoRa networks could employ the advantages of clustering and propose two algorithms, path-based and data-centric, for such networks. We suggest that LoRaWAN technology with clustering can be apt for long-range, low power consumption IoT applications in the future. We study the impact of network density, node range, and cluster range on the energy consumption in data transmissions. The algorithms are compared with the inherent star-based communication of LoRa networks based on energy consumed, and our results show that, for dense deployments, clustering becomes advantageous.

     

Dynamic estimation of the modeling error statistics in Diffuse Optical Tomography

Diffuse Optical Tomography (DOT) is a non-invasive imaging technique that suffers from a typical large-scale and ill-posed inverse problem with low spatial resolution. In DOT, the inverse problem is computationally intensive and decreasing the computation complexity and making it well-posed is the one of the most challenging research areas. More precisely, one of the well-known complexity reduction techniques is defined as applying modelling error originated from discretization of forward problem. Applying the discretization error in Bayesian inference has already been discussed; the method in which the likelihood is modified by an off-line prior density estimation. This paper implements a new method to enhance the modelling error approach using an iterative scheme to update statistical parameters of modelling discrepancy in DOT. The algorithm is very similar to Ensemble Kalman Filter. Moreover, the reconstruction process in the applied method is conducted by a small sample size rather than off-line method. Hence, the computation complexity is decreased and the algorithm converges in few iterations. The efficiency of the proposed method is illustrated by simulations.