Atomistic NEGF Simulations of Carbon Nano-Ribbons in Magnetic Fields

The non-equilibrium Green’s function (NEGF) approach has been employed in the simulation of Carbon Nano Ribbon (CNR) structures in magnetic fields (B) within the ballistic regime. Both the armchair edge (ACNR) and the zigzag edge (ZCNR) have been considered. The electronic structure is represented by the atomistic nearest-neighbor tight-binding Hamiltonian with a single pz orbital basis. The magnetic field is included in the tight-binding Hamiltonian through Peierls substitution, t exp (i(2p e / h)∫ A.dl ) . Two numerical methods have been employed in the calculation of contact self-energies: (a) the conventional surface Green’s function technique and (b) the Sancho-Rubio algorithm [1]. We used the recursive Green’s function (RGF) algorithm [2] which relaxes the memory constraints while simulating realistically extended structures on the order of tens of nanometers. Use of large dimensions in the simulation is crucial in order to capture the experimentally observed quantum Hall effect in realistic magnetic fields within 10– 20T

Unit selection for Malay text-to-speech system using segmental context and simulated annealing

Unit selection method has become the main approach in speech synthesis. The increasing size of recorded speech has resulted in better synthesis speech quality but at the same time also resulted in more expensive computational effort. Therefore, this paper proposes a combination of segmental context matching procedure and Simulated Annealing (SA) in unit selection to improve the quality of synthetic speech and reduce the computational time. The process of unit selection is based on minimization of two costs: target cost and join cost. The segmental context (target cost), the first stage of unit selection matching procedure used to narrow down the search space, followed by an optimization method which is SA to find the units sequence with minimum join cost. Result shows that the synthesis words produced by the proposed system are 15.48% better compared to previous version of corpus-based Malay Text-to-Speech system. Future works may focus on combining SA with other heuristic methods to further enhancing the performance of unit selection

Leader green behavior as an outcome of followers' critical thinking and active engagement: the moderating role of pro-environmental behavior

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI linkPurpose The purpose of this study is to investigate the role of followership dimensions of active engagement (AE) and independent critical thinking (ICT) in leader green behavior (LGB), and how followers' pro-environmental behavior (FPEB) moderates between the proposed relationship. Design/methodology/approach The data was collected from 381 employees working in different small and medium enterprises (SMEs) of Pakistan, through a structured questionnaire with five points Likert scale. The proposed hypotheses were tested by using Smart-partial least square (PLS).V.3. Findings Results showed a significant positive impact of followership dimensions on LGB. Moreover, the findings of the study substantiated the moderating role of FPEB between the direct relationship of ICT and LGB, but no significant moderation of FPEB in case of the relationship between AE and LGB was observed. Practical implications This paper argues that organizational effective green leadership can be enhanced by followership dimensions of AE and ICT, and by participation of followers in pro-environmental behavior. This has been largely overlooked in the past studies. Originality/value The study attempted to empirically test the “Reversing the Lens” perspective by Shamir (2007) in the context of green human resource management (HRM). This study extends a distinct theoretical contribution to the social exchange theory (SET) by focusing on the fact that follower's role is equally as important as that of a leader in the effective leadership process

Artifact removal from single-trial ERPs using non-Gaussian stochastic volatility models and particle filter

This paper considers improved modeling of artifactual noise for denoising of single-trial event-related potentials (ERPs) by state-space approach. Instead of the inadequate constant variance models used in existing studies, we propose to use stochastic volatility (SV) models to better describe the time-varying volatility in real ERP noise sources. We further propose a class of non-Gaussian SV models to capture the abrupt volatility changes typically present in impulsive noise, to improve artifact removal from ERPs. Two specifications are considered: (1) volatility driven by a heavy-tailed component and (2) transformation of volatility. Both result in volatility processes with heavy-tailed transition densities which can predict the impulsive noise volatility dynamics, more accurately than the Gaussian models. These SV noise models are incorporated in an autoregressive (AR) state-space ERP dynamic model. Parameter estimation is done using a Rao-Blackwellized particle filter (RBPF). Evaluation on simulated auditory brainstem responses (ABRs), corrupted by real eye-blink artifacts, shows that the non-Gaussian models can accurately detect the artifact-induced abrupt volatility spikes, and able to uncover the underlying inter-trial dynamics. Among them, the log-SV model performs the best. The results on real data demonstrate significant artifact suppression

Design and dimensional analysis of interdigital sensor for blood glucose measurement through non-invasive method

Diabetes has shown to be a chronic disease world over, mainly caused due to reduced physical activity and increased obesity. World health organization statistics show diabetes as a leading cause of disability universally. To avoid extreme medical conditions of subjects, regular monitoring of their glucose levels has been suggested. The most common method that has been in use is the pinprick method for glucose monitoring which carries the risk of contamination as well as irritation. One possible approach called noninvasive technique can be adopted to avoid this major concern. This paper presents designing Inter-Digital-Sensor (IDS) for non-invasive sensing of the glucose level. The sensor-based chip once mounted onto the upper arm or pinkie finger of diabetes subject, is able to sense different glucose levels concentration as impedance plots. A set of several simulation results has been obtained using COMSOL for getting optimized dimensions of the sensor digits. This research has presented the generation of an electric field and intensity by using electrode of known length with element spacing varying from 250µm to 600µm developed over 15mm x 20mm sensor area. An IDS of 475µm width spacing with ten (10) digits producing 2.33 pF of capacitance value with impedance resonating at 13 GHz of frequency is reported in this paper