Increased cognitive demands boost the spatial interference effect in bimanual pointing

Peer reviewed

COGNITIVE AND LINGUISTIC FACTORS OF READING ARABIC: THE ROLE OF MORPHOLOGICAL AWARENESS IN READING

Scientific reading research has produced substantial evidence linking specific reading components to a range of constructs including phonological awareness (PA), morphological awareness, orthographic processing (OP), rapid automatized naming, working memory and vocabulary. There is a paucity of research on Arabic, although 420 million people around the world (Gordon, 2005) speak Arabic. As a Semitic language, Arabic differs in many ways from Indo-European languages. Over the past three decades, literacy research has begun to elucidate the importance of morphological awareness (MA) in reading. Morphology is a salient aspect of Arabic word structure. This study was designed to (a) examine the dimensions underlying MA in Arabic; (b) determine how well MA predicts reading; (c) investigate the role of the standard predictors in different reading outcomes; and (d) investigate the construct of reading in Arabic. This study was undertaken in two phases. In Phase I, 10 MA measures and two reading measures were developed, and tested in a sample of 102 Grade 3 Arabic-speaking children. Factor analysis of the 10 MA tasks yielded one predominant factor supporting the construct validity of MA in Arabic. Hierarchical regression analyses, controlling for age and gender, indicated that the MA factor solution accounted for 41– 43% of the variance in reading. In Phase II, the widely studied predictor measures were developed for PA and OP in addition to one additional measure of MA (root awareness), and three reading measures In Phase II, all measures were administered to another sample of 201 Grade 3 Arabic-speaking children. The construct of reading in Arabic was examined using factor analysis. The joint and unique effects of all standard predictors were examined using different sets of hierarchical regression analyses. Results of Phase II showed that: (a) all five reading measures loaded on one factor; (b) MA consistently accounted for unique variance in reading, particularly in comprehension, above and beyond the standard predictors; and (c) the standard predictors had differential contributions. These findings underscore the contribution of MA to all components of Arabic reading. The need for more emphasis on including morphology in Arabic reading instruction and assessment is discussed.

Telenovela’s orality: from medium to a linguistic-discursive construction

Telenovela’s orality: from medium to a linguistic-discursive construction. Studies about telenovelas usually highlight their "orality". However, a literature review, specifically for Latin American telenovelas, shows that the term "orality" has been used with varying senses. In contrast with those devoted to telenovelas, literary studies have addressed the question by conceptualizing it as fictional orality. This paper takes fictional orality as a key concept to explain telenovela’s discursive peculiarities, and on that base, it distinguishes several dimensions of linguistic and discursive variation, in which such orality is being portrayed.

Beamforming and interference cancellation in D2D communication underlaying cellular networks

This paper presents an analytical performance investigation of both beamforming (BF) and interference cancellation (IC) strategies for a device-to-device (D2D) communication system underlaying a cellular network with an M-antenna base station (BS). We first derive new closed-form expressions for the ergodic achievable rate for BF and IC precoding strategies with quantized channel state information (CSI), as well as, perfect CSI. Then, novel lower and upper bounds are derived which apply for an arbitrary number of antennas and are shown to be sufficiently tight to the Monte-Carlo results. Based on these results, we examine in detail three important special cases including: high signal-to-noise ratio (SNR), weak interference between cellular link and D2D link, and BS equipped with a large number of antennas. We also derive asymptotic expressions for the ergodic achievable rate for these scenarios. Based on these results, we obtain valuable insights into the impact of the system parameters, such as the number of antennas, SNR and the interference for each link. In particular, we show that an irreducible saturation point exists in the high SNR regime, while the ergodic rate under IC strategy is verified to be always better than that under BF strategy. We also reveal that the ergodic achievable rate under perfect CSI scales as log2M, whilst it reaches a ceiling with quantized CSI.

Beamforming and interference cancellation schemes for D2D communications

We investigate device-to-device (D2D) communication underlaying cellular networks with M-antenna base stations. We consider both beamforming (BF) and interference cancellation (IC) strategies under quantized channel state information (CSI), as well as, perfect CSI. We derive tight closed-form approximations of the ergodic achievable rate which hold for arbitrary transmit power, location of users and number of antennas. Based on these approximations, we derive insightful asymptotic expressions for three special cases namely high signal-to-noise (SNR), weak interference, and large M. In particular, we show that in the high SNR regime a ceiling effect exists which depends on the received signal-to-interference ratio and the number of antennas. Moreover, the achievable rate scales logarithmically with M. The ergodic achievable rate is shown to scale logarithmically with SNR and the antenna number in the weak interference case. When the BS is equipped with large number of antennas, we find that the ergodic achievable rate under quantized CSI reaches a saturated value, whilst it scales as log2M under perfect CSI.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Secure Multiple Amplify-and-Forward Relaying with Co-Channel Interference

We investigate the impact of co-channel interference on the security performance of multiple amplify-and-forward (AF) relaying networks, where N intermediate AF relays assist the data transmission from the source to the destination. The relays are corrupted by multiple co-channel interferers, and the information transmitted from the relays to destination can be overheard by the eavesdropper. In order to deal with the interference and wiretap, the best out of N relays is selected for security enhancement. To this end, we derive a novel lower bound on the secrecy outage probability (SOP), which is then utilized to present two best relay selection criteria, based on the instantaneous and statistical channel information of the interfering links. For these criteria and the conventional maxmin criterion, we quantify the impact of co-channel interference and relay selection by deriving the lower bound on the SOP. Furthermore, we derive the asymptotic SOP for each criterion, to explicitly reveal the impact of transmit power allocation among interferers on the secrecy performance, which offers valuable insights into practical design. We demonstrate that all selection criteria achieve full secrecy diversity order N, while the proposed in this paper two criteria outperform the conventional max-min scheme. 

An Efficient Precoder Design for Multiuser MIMO Cognitive Radio Networks with Interference Constraints

We consider a linear precoder design for an underlay cognitive radio multiple-input multiple-output broadcast channel, where the secondary system consisting of a secondary base-station (BS) and a group of secondary users (SUs) is allowed to share the same spectrum with the primary system. All the transceivers are equipped with multiple antennas, each of which has its own maximum power constraint. Assuming zero-forcing method to eliminate the multiuser interference, we study the sum rate maximization problem for the secondary system subject to both per-antenna power constraints at the secondary BS and the interference power constraints at the primary users. The problem of interest differs from the ones studied previously that often assumed a sum power constraint and/or single antenna employed at either both the primary and secondary receivers or the primary receivers. To develop an efficient numerical algorithm, we first invoke the rank relaxation method to transform the considered problem into a convex-concave problem based on a downlink-uplink result. We then propose a barrier interior-point method to solve the resulting saddle point problem. In particular, in each iteration of the proposed method we find the Newton step by solving a system of discrete-time Sylvester equations, which help reduce the complexity significantly, compared to the conventional method. Simulation results are provided to demonstrate fast convergence and effectiveness of the proposed algorithm. 

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Epistemic Modality in Linguistic and Literature Essays in English : A comparative corpus-based study of modal verbs in student claims

This study is a corpus-based comparison between student essays written in the subject areas of English linguistics and literature at undergraduate level. They are 200 Bachelor degree theses submitted at a variety of university departments (such as English, Language and Literature, Humanities, Social and Intercultural Studies) in Sweden. The comparison concerns frequencies of core modal verbs and how often they occur together with the I, we and it subject pronouns and in the structures this/the [essay, study, project, thesis] when students attempt to communicate their personal claims. Quantitative and qualitative analyses of the essays show few similarities in the ways that core modal verbs appear in both disciplines. The results indicate mainly distinct differences, especially in relation to clusters and variation of performative verbs. Specific patterns in the ways that students use core modal verbs as hedges have also been identified.