Multichannel Approach Research Articles

Global feedforward active noise control using a linearly constrained loudspeaker beamformer and a sensor interpolation approach

The key issue of three-dimensional active noise control (3D ANC) problems is that global control is generally difficult, given limited number of discrete sensors. In this paper, feedforward multi-channel ANC approach is proposed to circumvent this difficulty. In view of the model-matching principle and multiple secondary sources, an underdetermined multi-channel inverse filtering (UMIF) system is formulated. With this UMIF system as a design constraint, a cost function is introduced to minimize the noise energy at a large number of control points. This linearly constrained minimum variance (LCMV) proves effective in broadening the controlled area in a 3D space. Optimal deployment of control points and the regularization terms of LCMV approach are also examined. To implement the proposed ANC system in a non-freefield environment, sensor interpolation can be used to find the frequency response between control points and loudspeakers, with plane wave decomposition and some room response measurements. The proposed ANC system has been implemented on a six-element linear loudspeaker array. Simulation and experiment results have demonstrated that the propose approach has yielded significant noise reduction performance in a large control area.

A Multi-Channel Convolutional Neural Network approach to automate the citation screening process

The systematic literature review (SLR) process is separated into several steps to increase rigor and reproducibility. The selection of primary studies (i.e., citation screening) is an important step in the SLR process. The citation screening process aims to identify the relevant primary studies fairly and with high rigor using selection criteria. Through the study selection criteria, reviewers determine whether an article should be included or excluded from the SLR. However, the screening process is highly time-consuming and error-prone as the researchers must read each title and possibly hundreds to thousands of abstracts and full-text documents. This study aims to automate the citation screening process using Deep Learning algorithms. With this, it is aimed to reduce the time and costs of the citation screening process and increase the precision and recall of the relevant primary studies. A Multi-Channel Convolutional Neural Network (CNN) is proposed, which can automatically classify a given set of citations. As the architecture uses the title and abstract as features, our end-to-end pipeline is domain-independent. We have performed six experiments to assess the performance of Multi-Channel CNNs across 20 publicly available systematic literature review datasets. It was shown that for 18 out of 20 review datasets, the proposed method achieved significant workload savings of at least 10%, while in several cases, our model yielded a statistically significantly better performance over two benchmark review datasets. We conclude that Multi-Channel CNNs are effective for the citation screening process in SLRs. Multi-Channel CNNs perform best on large datasets of over 2500 samples with few abstracts missing.

Framework for Smart City Model Composition

This paper is a reflective overview of the knowledge on online conversion of services in the perspective of urban planning. It points that traditional planning aimed at building optimal spatial relationships between particular functions in urban environment. Appropriate decision-making rules had been introduced, contributing to a hierarchical land-use structure. This conventional approach has been recently challenged by the rapid ICT development which added a lively, virtual, non-spatial dimension of urban economy. The well-established foundations of urban planning started to shake, calling for a new paradigm. This paper looks for an alternative to traditional planning which would be able to develop policies for omnichannel services (i.e., enterprises that use both online and offline channels for communicating and distributing their products). The advantages of ‘e-planning' in managing omnichannel services are outlined and a conclusion is drawn that only a multi-channel approach can bring appropriate answers to contemporary developments in services sector.

A multi-channel approach for automatic microseismic event association using RANSAC-based Arrival Time Event Clustering (RATEC)

In the presence of background noise, arrival times picked from a surface microseismic data set usually include a number of false picks that can lead to uncertainty in location estimation. To eliminate false picks and improve the accuracy of location estimates, we develop an association algorithm termed RANSAC-based Arrival Time Event Clustering (RATEC) that clusters picked arrival times into event groups based on random sampling and fitting moveout curves that approximate hyperbolas. Arrival times far from the fitted hyperbolas are classified as false picks and removed from the data set prior to location estimation. Simulations of synthetic data for a 1-D linear array show that RATEC is robust under different noise conditions and generally applicable to various types of subsurface structures. By generalizing the underlying moveout model, RATEC is extended to the case of a 2-D surface monitoring array. The effectiveness of event location for the 2-D case is demonstrated using a data set collected by the 5200-element dense Long Beach array. The obtained results suggest that RATEC is effective in removing false picks and hence can be used for phase association before location estimates.

Characteristics of Tc-MEP Waveforms in Spine Surgery for Patients with Severe Obesity.

Prospective multicenter study. The aim of this study was to evaluate transcranial motor evoked potential (Tc-MEP) waveform monitoring in spinal surgery for patients with severe obesity. Spine surgeries in obese patients are associated with increased morbidity and mortality. Intraoperative Tc-MEP monitoring can identify neurologic deterioration during surgery, but has not been examined for obese patients. The subjects were 3560 patients who underwent Tc-MEP monitoring during spine surgery at 16 centers. Tc-MEPs were recorded from multiple muscles via needle or disc electrodes. A decrease in Tc-MEP amplitude of ≥70% from baseline was used as an alarm during surgery. Preoperative muscle weakness with manual muscle test (MMT) grade ≤4 was defined as a motor deficit, and a reduction of one or more MMT grade postoperatively was defined as deterioration. The 3560 patients (1698 males, 47.7%) had a mean age of 60.0 ± 20.3 years. Patients with body mass index >35 kg/m2 (n = 60, 1.7%) were defined as severely obese. Compared with all other patients (controls), the rates of preoperative motor deficit (41.0% vs. 29.6%, P < 0.05) and undetectable baseline waveforms in all muscles were significantly higher in the severely obese group (20.0% vs. 1.7%, P < 0.01). Postoperative motor deterioration did not differ significantly between the groups. The sensitivity and specificity of the alarm criterion for prediction of postoperative neurologic complications were 75.0% and 83.9% in severely obese patients and 76.4% and 89.6% in controls, with no significant difference between the groups. Tc-MEPs can be used in spine surgery for severely obese cases to predict postoperative motor deficits, but the rate of undetectable waveforms is significantly higher in such cases. Use of a multichannel waveform approach or multiple modalities may facilitate safe completion of surgery. Waveforms should be carefully evaluated and an appropriate rescue procedure is required if the alarm criterion occurs.Level of Evidence: 3.

Distributed optimal congestion control and channel assignment in wireless mesh networks

Wireless mesh networks have numerous advantages in terms of connectivity as well as reliability. Traditionally the nodes in wireless mesh networks are equipped with single radio, but the limitations are lower throughput and limited use of the available wireless channel. In order to overcome this, the recent advances in wireless mesh networks are based on multi-channel multi-radio approach. Channel assignment is a technique that selects the best channel for a node or to the entire network just to increase the network capacity. To maximize the throughput and the capacity of the network, multiple channels with multiple radios were introduced in these networks. In the proposed system, algorithms are developed to improve throughput, minimise delay, reduce average energy consumption and increase the residual energy for multi radio multi-channel wireless mesh networks. In literature, the existing channel assignment algorithms fail to consider both interflow and intra flow interferences. The limitations are inaccurate bandwidth estimation, throughput degradation under heavy traffic and unwanted energy consumption during low traffic and increase in delay. In order to improve the performance of the network distributed optimal congestion control and channel assignment algorithm (DOCCA) is proposed. In this algorithm, if congestion is identified, the information is given to previous node. According to the congestion level, the node adjusts itself to minimise congestion.

Accurate Ballistocardiogram Based Heart Rate Estimation Using an Array of Load Cells in a Hospital Bed.

The ballistocardiogram (BCG), a cardiac vibration signal, has been widely investigated for continuous monitoring of heart rate (HR). Among BCG sensing modalities, a hospital bed with multi-channel load-cells could provide robust HR estimation in hospital setups. In this work, we present a novel array processing technique to improve the existing HR estimation algorithm by optimizing the fusion of information from multiple channels. The array processing includes a Gaussian curve to weight the joint probability according to the reference value obtained from the previous inter-beat-interval (IBI) estimations. Additionally, the probability density functions were selected and combined according to their reliability measured by q-values. We demonstrate that this array processing significantly reduces the HR estimation error compared to state-of-the-art multi-channel heartbeat detection algorithms in the existing literature. In the best case, the average mean absolute error (MAE) of 1.76 bpm in the supine position was achieved compared to 2.68 bpm and 1.91 bpm for two state-of-the-art methods from the existing literature. Moreover, the lowest error was found in the supine posture (1.76 bpm) and the highest in the lateral posture (3.03 bpm), thus elucidating the postural effects on HR estimation. The IBI estimation capability was also evaluated, with a MAE of 16.66 ms and confidence interval (95%) of 38.98 ms. The results demonstrate that improved HR estimation can be obtained for a bed-based BCG system with the multi-channel data acquisition and processing approach described in this work.

Final-state-resolved mutual neutralization of Na+ and D−

The present paper reports on a merged-beam experiment on mutual neutralization between ${\mathrm{Na}}^{+}$ and ${\mathrm{D}}^{\ensuremath{-}}$. For this experiment, we have used the DESIREE ion-beams storage-ring facility. The reaction products are detected using a position- and time-sensitive detector, which ideally allows for determination of the population of each individual quantum state in the final atomic systems. Here, the $4s, 3d$, and $4p$ final states in Na are observed and in all cases the D atom is in its ground state $1s ^{2}S$. The respective branching fractions of the states populated in Na are determined by fitting results from a Monte Carlo simulation of the experiment to the measured data. The center-of-mass collision energy is controlled using a set of biased drift tubes, and the branching fractions are measured for energies between 80 meV and 393 meV. The resulting branching fractions are found to agree qualitatively with the only available theoretical calculations for this particular system, which are based on a multichannel Landau-Zener approach using dynamic couplings determined with a linear combination of atomic orbitals model.

A dynamic three-path authenticating model for anti-counterfeiting in a single host of CaAl2Si2O8

Luminescent materials are one of the most fascinating candidates for the field of data communication and information security because of their special optical characteristics. Unfortunately, unimodal output of luminescent performance reaches unsatisfied security of anti-counterfeiting. Hence, achieving multicolor, multitemporal, and multimodal luminescence performance simultaneously is still a fascinating target, especially in a single host. Here, multi-model optical output is realized for the multiple emission centers of CaAl2Si2O8 doped with Eu3+/Eu2+ ions. Moreover, a successive defect structure is constructed via the introduction of Nd3+ ions, which enables the thermo-/photon- responded luminescence properties. Herein, an efficient three-path authenticating model that performs a dynamic multiple color response and stimulated-sources dependent emission is accomplished in the CaAl2Si2O8 host matrix. The explored multichannel approach offers a unique insight for designing advanced anti-counterfeiting technology.

Improving text comprehension in ESL learners: a multichannel approach

ABSTRACT Purpose This paper is a proposal for improving ESL text comprehension by merging a multimodal perspective on language (Kress et al. [2005]. Urban Classrooms, Subject English: Multimodal Perspectives on Teaching and Learning. London: Routledge Falmer.) with an integrated psychological (or ‘metacognitive’) approach to language learning and awareness (Fairclough [1992]. Critical Language Awareness. London: Longman, 1) . Design A multichannel approach is presented, based on two strategies: a main ‘multichannel’ strategy for reading the text, which focuses on the assessment of the visual, auditory, cognitive and kinaesthetic/emotional channels and relative functions, and a corollary one, specifically dedicated to implementing the cognitive function. Methodology/approach The approach has been extensively applied in university-level English classes (Reggio Emilia, Parma, Bologna University) using a ‘multichannel test’ based on students’ feedback to explore the effectiveness of the method. In this paper, a case study is offered: data have been collected with specific reference to the University of Bologna, A. Y. 2017/18 and 2018/2019. Originality/value Evidence suggests that further and diversified applications promise an empowerment of the approach and of its impact on ELT as well as on students’ awareness and satisfaction.

Digital touchpoints and multichannel segmentation approach in the life insurance industry

PurposeDigital technology is revolutionizing insurance distribution allowing the insurer companies to reach customers via multichannel. The aim of this study is to segment potential customers of life insurance based on their information search, purchasing channels and personal characteristics in the digital environment.Design/methodology/approachThe study uses cross-sectional research survey. In total, 422 questionnaires were collected through a convenience sample of the Romanian population. The data was segmented based on consumer information touchpoints (online vs offline), purchase channel preference (offline by a professional vs online by a standardized platform) and personal characteristics (age, marital status and children).FindingsThe channel segmentation analysis revealed that information channel preferences are the most important clustering variables, followed by purchase channel preferences, marital status, having children and age. Four distinct segments were identified: young fully offliners (23.7%), mature fully offliners (31.5%), committed online searchers (23.2%) and cross-channel onliners (21.6%).Practical implicationsInsurance companies should adapt their communication and distribution strategy based on multichannel segmentation and should focus on digital touchpoints with costumers.Originality/valueFirstly, the paper reveals multichannel and hybrid segmentation for life insurance. Secondly, it extends the already studied retail channels with search engines and companies' websites. Thirdly, it extends the behavioural variables for channel segmentation with technology acceptance behaviour, attitude towards life insurance, knowledge about life insurance, attitude towards personal selling and quality appraisal of online information sources.

Comparison of conventional versus single port laparoscopy for surgical treatment of gynecological diseases: a pilot study.

IntroductionMany recent studies have conducted laparoscopic single-site surgery (LESS) using single-port laparoscopy (SPL), which combines conventional laparoscopy (CL) with a novel multichannel port. However, to implement SPL, several obstacles must be overcome.AimTo study the clinical value of SPL in the surgical treatment of gynecological diseases.Material and methodsTwenty-five patients with ectopic pregnancy (EP) and 11 with uterine leiomyoma (UL) were randomly assigned to undergo either LESS by SPL or CL. The CL was performed routinely, while the SPL was performed through a single port using a self-made, multi-channel laparoscopic approach based on CL. The following parameters were compared between the SPL and CL groups: intraoperative conditions (operation time and blood loss), postoperative conditions (exhaustion and hospital stay time), and visual analog scale. Patients with EP and those with UL were analyzed separately in this regard. In patients with UL, hemoglobin changes, complications, and long-term physical recovery within 6 months of surgery were also compared.ResultsThe operation time was significantly longer in the SPL group than in the CL group (p < 0.001). However, blood loss, postoperative exhaustion, and hospital stay time were significantly lower (p < 0.05 in all cases). In patients with UL, intraoperative and postoperative conditions did not differ significantly between the groups. At the follow-up within 6 months, patients with UL in the SPL group had recovered, with better cosmetic effects and more satisfaction. No cases of umbilical incisional hernia occurred in the SPL group.ConclusionsSPL showed clinical efficacy, with minimal invasion, rapid recovery, and cost-effectiveness in patients with EP or UL.

Transient recovery problem in acoustics: A multichannel model-based deconvolution approach.

Critical acoustical systems operating in complex environments contaminated with disturbances and noise offer an extreme challenge when excited by out-of-the-ordinary, impulsive, transient events that can be undetected and seriously affect their overall performance. Transient impulse excitations must be detected, extracted, and evaluated to determine any potential system damage that could have been imposed; therefore, the problem of recovering the excitation in an uncertain measurement environment becomes one of multichannel deconvolution. Recovering a transient and its initial energy has not been solved satisfactorily, especially when the measurement has been truncated and only a small segment of response data is available. The development of multichannel deconvolution techniques for both complete and incomplete excitation data is discussed, employing a model-based approach based on the state-space representation of an identified acoustical system coupled to a forward modeling solution and a Kalman-type processor for enhancement and extraction. Synthesized data are utilized to assess the feasibility of the various approaches, demonstrating that reasonable performance can be achieved even in noisy environments.

Multichannel dual protein sensing using amphiphilic supramolecular assemblies.

Protein sensing strategies have implications in detection of many human pathologies. Here, a supramolecular strategy for sensing two different proteins using a multichannel readout approach is outlined. Protein-ligand binding or enzymatic cleavage can both be programmed to induce supramolecular disassembly, which leads to fluorescence enhancement via aggregation-induced emission (AIE), protein-induced fluorescence enhancement (PIFE), or disassembly-induced fluorescence enhancement (DIFE). The accompanying signal change from two different fluorophores and their patterns are then used for specific protein sensing.

Multi-Channel Multi-Frame ADL-MVDR for Target Speech Separation

Many purely neural network based speech separation approaches have been proposed to improve objective assessment scores, but they often introduce nonlinear distortions that are harmful to modern automatic speech recognition (ASR) systems. Minimum variance distortionless response (MVDR) filters are often adopted to remove nonlinear distortions, however, conventional neural mask-based MVDR systems still result in relatively high levels of residual noise. Moreover, the matrix inverse involved in the MVDR solution is sometimes numerically unstable during joint training with neural networks. In this study, we propose a multi-channel multi-frame (MCMF) all deep learning (ADL)-MVDR approach for target speech separation, which extends our preliminary multi-channel ADL-MVDR approach. The proposed MCMF ADL-MVDR system addresses linear and nonlinear distortions. Spatio-temporal cross correlations are also fully utilized in the proposed approach. The proposed systems are evaluated using a Mandarin audio-visual corpus and are compared with several state-of-the-art approaches. Experimental results demonstrate the superiority of our proposed systems under different scenarios and across several objective evaluation metrics, including ASR performance.

Inertial focusing and zeta potential measurements of single-nanoparticles using octet-nanochannels.

Capture-to-translocation dynamics control is an important issue for single-particle and -molecule analyses by resistive pulse waveforms. Here, we report on regulated motions for accurate zeta-potential assessments of single nanoscale objects passing through an octet-nanochannel. We observed ionic spike signals consisting of eight consecutive sub-pulses signifying the ion blockage at the eight sensing zones in series upon electrophoretic translocation of individual nanoparticles. We find an exponential decrease to saturation of the channel-to-channel translocation duration as a nanobead moves forward, reflecting the more restricted radial motion degrees of freedom via inertial effects at the downstream side of the octet channel. This finding enabled a protocol for single-nanoparticle zeta potential estimation impervious to the uncertainty stemming from the stochastic nature of the translocation dynamics. The multi-channel approach presented in this study may be used as a useful tool for analyzing particles and molecules of variable sizes.

Recent experimental activity on heavy-ion induced reactions within the NUMEN project

The possibility to use a special class of heavy-ion induced direct reactions, such as double charge exchange reactions, is discussed in view of their application to extract information that may be helpful to determinate the nuclear matrix elements entering in the expression of neutrinoless double beta decay half-life. The strategies adopted in the experimental campaigns performed at INFN - Laboratori Nazionali del Sud are briefly described, emphasizing the advantages of the multi-channel approach to nuclear reaction data analysis.

Inelastic processes in copper–hydrogen collisions including fine-structure effects

Abstract Inelastic processes in low-energy Cu + H and Cu+ + H− collisions, 306 partial processes in total, are investigated taking fine-structure effects into account. We use the asymptotic approach to model the adiabatic potentials and adapt a recently proposed method to include the copper fine structure. The nuclear dynamics is performed by the multichannel analytical approach and the Landau–Zener model. The rate coefficients are calculated for the temperature range of 1000–10 000 K. The largest rate coefficient is obtained for the mutual neutralization process Cu+ + H− → Cu(3d105s 2S1/2) + H with a value of $3.81 \times 10^{-8}\, {\rm cm}^3\,{\rm s^{-1}}$ at a temperature of 6000 K . It is shown that the practice to redistribute LS-coupling rate coefficients among fine-structure sublevels can give rates that deviate significantly from those calculated in the JJ-coupling scheme, that is with account for the fine-structure effects.

How to Include Omnichannel Services in Land-Use Policy?

This paper is a reflective overview of the knowledge on online conversion of services in the perspective of urban planning. It points that traditional planning aimed at building optimal spatial relationships between particular functions in urban environment. Particular decision-making rules have been introduced, contributing to a hierarchical land-use structure. This traditional approach has been recently challenged by the rapid ICT development which added a lively, virtual, and non-spatial dimension of urban economy. The well-established foundations of urban planning started to shake, calling for a new paradigm. This paper looks for an alternative to conventional planning which would be able to develop policies for omnichannel services (i.e., enterprises that use both online and offline channels for communicating and distributing their products). The advantages of ‘e-planning' in managing omnichannel services sector are outlined and a conclusion is drawn that only a multi-channel approach can bring appropriate answers to contemporary developments in services sector.

Introduction of a sEMG Sensor System for Autonomous Use by Inexperienced Users

Wearable devices play an increasing role in the rehabilitation of patients with movement disorders. Although information about muscular activation is highly interesting, no approach exists that allows reliable collection of this information when the sensor is applied autonomously by the patient. This paper aims to demonstrate the proof-of-principle of an innovative sEMG sensor system, which can be used intuitively by patients while detecting their muscular activation with sufficient accuracy. The sEMG sensor system utilizes a multichannel approach based on 16 sEMG leads arranged circularly around the limb. Its design enables a stable contact between the skin surface and the system’s dry electrodes, fulfills the SENIAM recommendations regarding the electrode size and inter-electrode distance and facilitates a high temporal resolution. The proof-of-principle was demonstrated by elbow flexion/extension movements of 10 subjects, proving that it has root mean square values and a signal-to-noise ratio comparable to commercial systems based on pre-gelled electrodes. Furthermore, it can be easily placed and removed by patients with reduced arm function and without detailed knowledge about the exact positioning of the sEMG electrodes. With its features, the demonstration of the sEMG sensor system’s proof-of-principle positions it as a wearable device that has the potential to monitor muscular activation in home and community settings.