Enhancement in Physical Properties of Silver-Doped Fe–Ni Invar Nano-alloy Using Chemical Reduction Method

Journal of Superconductivity and Novel Magnetism - Silver-substituted Fe–Ni nano invar alloy is a new and innovative field of research due to their interesting invar, magnetic and electrical...     

Anomalous Behavior of 2D Janus Excitonic Layers under Extreme Pressures

Newly discovered 2D Janus transition metal dichalcogenides layers have gained much attention from a theory perspective owing to their unique atomic structure and exotic materials properties, but little to no experimental data are available on these materials. Here, experimental and theoretical studies establish the vibrational and optical behavior of 2D Janus S–W–Se and S–Mo–Se monolayers under high pressures for the first time. Chemical vapor deposition (CVD)-grown classical transition metal dichalcogenides (TMD) monolayers are first transferred onto van der Waals (vdW) mica substrates and converted to 2D Janus sheets by surface plasma technique, and then integrated into a 500 µm size diamond anvil cell for high-pressure studies. The results show that 2D Janus layers do not undergo phase transition up to 15 GPa, and in this pressure regime, their vibrational modes exhibit a nonmonotonic response to the applied pressures (dω/dP). Interestingly, these 2D Janus monolayers exhibit unique blueshift in photoluminescence (PL) upon compression, which is in contrast to many other traditional semiconductor materials. Overall theoretical simulations offer in-depth insights and reveal that the overall optical response is a result of competition between the ab-plane (blueshift) and c-axis (redshift) compression. The overall findings shed the very first light on how 2D Janus monolayers respond under extreme pressures and expand the fundamental understanding of these materials.     

Atmospheric deposition of arsenic and selenium across Canada using Sphagnum moss as a biomonitor

A biomonitoring study was made of the atmospheric deposition of arsenic and selenium across northern Canada utilizing Sphagnum fuscum moss. Intensive sampling was carried out adjacent to the smelter at Rouyn-Noranda, Quebec. An average background concentration of arsenic in the moss of 0.66 mg kg-1 was determined, while most selenium concentrations were below the detection limit of 0.2 mg kg-1. Elevated arsenic concentrations were found in the vicinity of the mining and smelting areas of Flin Flon, Manitoba, and Atikokan, Ontario. High concentrations of selenium were detected only near Rouyn-Noranda. Both arsenic and selenium occurred in moss at concentrations lower than found in Canadian soils.     

Ultra-Low Power 1 Volt Small Size 2.4 GHz CMOS RF Transceiver Design for Wireless Sensor Node

Ultra-low power transceiver design is proposed for wireless sensor node used in the wireless sensor network (WSN). Typically, each sensor node contains a transceiver so it is required that both hardware and software designs of WSN node must take care of energy consumption during all modes of operation including active/sleep modes so that the operational life of each node can be increased in order to increase the lifetime of network. The current declared size of the wireless sensor node is of millimeter order, excluding the power source and crystal oscillator. We have proposed a new 2.4 GHz transceiver that has five blocks namely XO, PLL, PA, LNA and IF. The proposed transceiver incorporates less number of low-drop outs (LDOs) regulators. The size of the transceiver is reduced by decreasing the area of beneficiary components up to 0.41 mm² of core area in such a way that some functions are optimally distributed among other components. The proposed design is smaller in size and consumes less power, <1 mW, compared to other transceivers. The operating voltage has also been reduced to 1 V. This transceiver is most efficient and will be fruitful for the wireless networks as it has been designed by considering modern requirements.     

Sub-millimeter-Wave Equivalent Circuit Model for External Parasitics in Double-Finger HEMT Topologies

We present a novel distributed equivalent circuit that incorporates a three-way-coupled transmission line to accurately capture the external parasitics of double-finger high electron mobility transistor (HEMT) topologies up to 750 GHz. A six-step systematic parameter extraction procedure is used to determine the equivalent circuit elements for a representative device layout. The accuracy of the proposed approach is validated in the 90–750 GHz band through comparisons between measured data (via non-contact probing) and full-wave simulations, as well as the equivalent circuit response. Subsequently, a semi-distributed active device model is incorporated into the proposed parasitic circuit to demonstrate that the three-way-coupled transmission line model effectively predicts the adverse effect of parasitic components on the sub-mmW performance in an amplifier setting.     

A Dynamic Spark-based Classification Framework for Imbalanced Big Data

Classification of imbalanced big data has assembled an extensive consideration by many researchers during the last decade. Standard classification methods poorly diagnosis the minority class samples. Several approaches have been introduced for solving the problem of class imbalance in big data to enhance the generalization in classification. However, most of these approaches neglect the effect of border samples on classification performance; the high impact border samples might expose to misclassification. In this paper, a Spark Based Mining Framework (SBMF) is proposed to address the imbalanced data problem. Two main modules are designed for this purpose. The first is the Border Handling Module (BHM) which under samples the low impact majority border instances and oversamples the minority class instances. The second module is the Selective Border Instances sampling (SBI) Module, which enhances the output of the BHM module. The performance of the SBMF framework is evaluated and compared with other recent systems. A number of experiments were performed using moderate and big datasets with different imbalanced ratio. The results obtained from SBMF framework, when compared to the recent works, show better performance for the different datasets and classifiers.     

A multi-layer perceptron neural network model for predicting the hydrate equilibrium conditions in multi-component hydrocarbon systems

Neural Computing and Applications - This work presents a model based on multilayer perceptron neural network (MLPNN) for the prediction of hydrate equilibrium conditions in hydrocarbon systems. The...     

Semantic similarity based approach for reducing Arabic texts dimensionality

An efficient method is introduced to represent large Arabic texts in comparatively smaller size without losing significant information. The proposed method uses the distributional semantics to build the word-context matrix representing the distribution of words across contexts and to transform the text into a vector space model (VSM) representation based on word semantic similarity. The linguistic features of the Arabic language, in addition to the semantic information extracted from different lexical-semantic resources such as Arabic WordNet and named entities’ gazetteers are used to improve the text representation and to create word clusters of similar and related words. Distributional similarity measures have been used to capture the words’ semantic similarity and to create clusters of similar words. The conducted experiments have shown that the proposed method significantly reduces the size of text representation by about 27 % compared with the stem-based VSM and by about 50 % compared with the traditional bag-of-words model. Their results have shown that the amount of dimension reduction depends on the size and shape of the windows of analysis as well as on the content of the text.     

Fractional variational iteration method for fractional initial-boundary value problems arising in the application of nonlinear science

In this paper, we suggest a fractional functional for the variational iteration method to solve the linear and nonlinear fractional order partial differential equations with fractional order initial and boundary conditions by using the modified Riemann-Liouville fractional derivative proposed by G. Jumarie. Fractional order Lagrange multiplier has been considered. Solution has been plotted for different values of α.