Effect Of Redundancy Research Articles

Evaluation on Redundancy-Induced Rigidity Enhancement of a Parallel Manipulator

Abstract Redundantly actuated parallel manipulator (RAPM) has been proved to have comparative advantages of higher rigidity and higher payload over other parallel manipulators. This paper is to quantitatively reveal the effect of redundancy on rigidity enhancement of a previously invented 2UPR&1RPS&1RPU RAPM. For this purpose, three critical issues are clarified, i.e., establishing a sufficient accurate stiffness model, constructing a reasonable index frame for evaluating rigidity performance, and quantifying the effect of redundancy on the rigidity enhancement. First, drawing on the screw theory, a hierarchical method is presented to establish a semi-analytic stiffness model at the joint level for the proposed RAPM. Subsequently, based on the stiffness matrix, a set of local and global stiffness indices are constructed to evaluate the rigidity of parallel manipulators. Finally, the stiffness indices of the 2UPR&1RPS&1RPU RAPM and its non-redundantly actuated forms are predicted and compared to reveal the effort of redundancy. The present work is expected to provide a useful frame for quantitatively assessing redundancy-induced rigidity enhancement in redundantly actuated parallel manipulators.

Species α-diversity promotes but β-diversity restricts aboveground biomass in tropical forests, depending on stand structure and environmental factors

Forest plays a vital role in the global biogeochemical cycles through a high rate of carbon sequestration and harboring biodiversity. However, local species diversity is declining while also becoming increasingly homogenized across communities. Although effects of local biotic processes (e.g., species α-diversity and stand structural heterogeneity) and environmental factors on aboveground biomass (AGB) have been widely tested, there is a huge knowledge gap for the effect of regional biotic processes (i.e., taxonomic and functional β-diversity) in forests. Here, we hypothesized that regional and local environmental factors along with biotic processes jointly regulate AGB through species shifts in tropical forests. Using piecewise structural equation modeling (pSEM), we linked climatic water availability, soil fertility, stand structural heterogeneity (either tree DBH inequality, height inequality, or stand density), species α-diversity, taxonomic or functional β-diversity (and its two components; β-turnover and β-richness), and AGB across 189 inventory plots in tropical forests of Sri Lanka. Soil fertility and climatic water availability shaped local and regional biotic processes. Stand structural heterogeneity promoted species α-diversity but declined β-diversity (but increased β-taxonomic turnover). Species α-diversity and stand structural heterogeneity promoted AGB whereas taxonomic and functional β-diversity declined (but β-taxonomic turnover increased) AGB. The relationships of AGB with species α-diversity and β-diversity varied from significant to nonsignificant positive depending on the specific combinations of stand structural heterogeneity metrics used. This study shows that local biotic processes could increase AGB due to the local and regional niche complementarity effect whereas the regional biotic processes could restrict AGB due to the regional selection or functional redundancy effect under favorable environmental conditions. We argue that biotic homogenization, as well as drought conditions, may have strong divergent impacts on forest functions and that the impacts of tree diversity loss may greatly reduce carbon sequestration.

Why leading is (almost) as important as winning

Competitions in sports, business, or politics often provide perceivers with cumulative standings over time. Recent research suggests that people fail to accurately update their impressions from cumulative observations as they are influenced by previous standings. This cumulative redundancy bias (CRB) implies that competitors that are leading during a competition will receive more favorable evaluations, over and beyond their eventual success or failure. While the CRB has far-reaching implications, its underlying mechanisms are not fully understood. We present data from four experiments in which we modified the standard CRB task by adding a step-by-step procedure to track the dynamics of perceivers' impressions during the competition. We also manipulated the length of the competition and tested different possible explanations for the CRB. Results suggest that the CRB is a robust phenomenon that constitutes an actual bias and that is best explained by an additive effect of cumulative redundancy.

Redundancy and Synergy of an Entangling Cloner in Continuous-Variable Quantum Communication

We address minimization of information leakage from continuous-variable quantum channels. It is known, that regime of minimum leakage can be accessible for the modulated signal states with variance equivalent to a shot noise, i.e., vacuum fluctuations, in the case of collective attacks. Here we derive the same condition for the individual attacks and analytically study the properties of the mutual information quantities in and out of this regime. We show that in such regime a joint measurement on the modes of a two-mode entangling cloner, being the optimal individual eavesdropping attack in a noisy Gaussian channel, is no more effective that independent measurements on the modes. Varying variance of the signal out of this regime, we observe the nontrivial statistical effects of either redundancy or synergy between the measurements of two modes of the entangling cloner. The result reveals the non-optimality of entangling cloner individual attack for sub-shot-noise modulated signals. Considering the communication between the cloner modes, we show the advantage of knowing the residual noise after its interaction with the cloner and extend the result to a two-cloner scheme.

Optimization of Worked Example-Problem Solving Pair to Increase Learning Independence and Reduce Cognitive Load

This study aims to show what kinds of problems are able to optimize worked examples to increase student learning independence and reduce cognitive load for VIIB grade junior high school students in algebraic forms material. The data in this study were in the form of learning independence data, cognitive load, and implementation of learning obtained through questionnaires and observation sheets, as well as learning achievement data obtained with test instruments that have been tested to be valid and reliable according to experts and statistical test results. The results showed that the addition of the deep isomorphism problem type with insufficient guidance in the worked example-problem solving pair increased learning independence and reduced cognitive load, accompanied by an increase in student achievement. The increase is indicated by: (1) the average student's learning independence is in the "high" category, (2) the average cognitive load reaches the "low" category, and (3) obtained 75% of students with learning achievements that pass the minimum pass criteria, i.e. 65, and (4) implementation of learning with worked example-problem solving pair 80%. It is really recommended for the next researcher to make student worksheets as attractive as possible to avoid redundancy effect, present varied types of problems, provide guidance as clear as possible but not excessive, and serve the student worksheets to students individually.

Multi-Label Feature Selection with Conditional Mutual Information.

Feature selection is an important way to optimize the efficiency and accuracy of classifiers. However, traditional feature selection methods cannot work with many kinds of data in the real world, such as multi-label data. To overcome this challenge, multi-label feature selection is developed. Multi-label feature selection plays an irreplaceable role in pattern recognition and data mining. This process can improve the efficiency and accuracy of multi-label classification. However, traditional multi-label feature selection based on mutual information does not fully consider the effect of redundancy among labels. The deficiency may lead to repeated computing of mutual information and leave room to enhance the accuracy of multi-label feature selection. To deal with this challenge, this paper proposed a multi-label feature selection based on conditional mutual information among labels (CRMIL). Firstly, we analyze how to reduce the redundancy among features based on existing papers. Secondly, we propose a new approach to diminish the redundancy among labels. This method takes label sets as conditions to calculate the relevance between features and labels. This approach can weaken the impact of the redundancy among labels on feature selection results. Finally, we analyze this algorithm and balance the effects of relevance and redundancy on the evaluation function. For testing CRMIL, we compare it with the other eight multi-label feature selection algorithms on ten datasets and use four evaluation criteria to examine the results. Experimental results illustrate that CRMIL performs better than other existing algorithms.

Infant selective attention to native and non-native audiovisual speech

The current study utilized eye-tracking to investigate the effects of intersensory redundancy and language on infant visual attention and detection of a change in prosody in audiovisual speech. Twelve-month-old monolingual English-learning infants viewed either synchronous (redundant) or asynchronous (non-redundant) presentations of a woman speaking in native or non-native speech. Halfway through each trial, the speaker changed prosody from infant-directed speech (IDS) to adult-directed speech (ADS) or vice versa. Infants focused more on the mouth of the speaker on IDS trials compared to ADS trials regardless of language or intersensory redundancy. Additionally, infants demonstrated greater detection of prosody changes from IDS speech to ADS speech in native speech. Planned comparisons indicated that infants detected prosody changes across a broader range of conditions during redundant stimulus presentations. These findings shed light on the influence of language and prosody on infant attention and highlight the complexity of audiovisual speech processing in infancy.

Diabetic Foot in Algeria Illustration V – Case Report

This article is a sequel to other previous articles entitled “Diabetic foot in Algeria” in which the technique is extensively described. To avoid the redundancy effect, we invite you to refer to them. In addition, in this article, we share our experience concerning a precise lesion localization of the diabetic foot.

Target reliability for new road bridges in South Africa

Currently, there are no recommendations of target reliability for new-build road bridges tailored to developing countries. Target reliabilities in existing international literature reflect the economic and social circumstances associated with developed countries and may not be economically or societally acceptable for South Africa. This research determines target reliability for new-build road bridges specifically for a South African context. Economic cost optimisation and a societal risk approach are considered. Cost optimisation considers the cost of safety and consequences of failure. The life quality index methodology is used to consider limits on target reliability from a societal risk perspective. Additionally, the effect of structural redundancy on target reliability in bridges is investigated. Target reliabilities from cost optimisation are shown to be slightly higher than those from SANS 10160-1 and correspond with those from ISO 2394:2015. Recommendations of annual target reliability for new-build road bridges in South Africa are proposed - a typical value of β = 4.2 is recommended. Societal limits on target reliability correspond with target reliability from cost optimisation for bridges with minor consequences of failure and do not govern new-build bridges in South Africa. Target reliability reduces with increasing measures of bridge redundancy; a means by which to consider the effect of structural redundancy on target reliability is also proposed.

The manufacturing adaptive capabilities of firms: the role of technology, market and management systems-related adaptive capabilities

PurposeThis study investigates the roles of market, technology, and management system-related adaptive capability variables on a firm’s manufacturing adaptive capability. In addition, the study examines the effects of a firm’s manufacturing adaptive capability on its effectiveness. Further, this study tests the moderating role of organizational redundancy on the relationship between the market, technology, and management system-related adaptive capabilities and the overall manufacturing adaptive capability of a firm.Design/methodology/approachThis study utilizes questionnaire-based research to test the suggested hypotheses by gathering related data from 59 manufacturing firms.FindingsThis study determined that a firm’s technology and management system-related adaptive capability positively relates to firm's manufacturing adaptive capability. Further, market adaptive capability influences manufacturing adaptive capability via the levels of technology and management system-related adaptive capabilities. Manufacturing adaptive capability is also found to be positively associated with organizational effectiveness, and resource redundancy positively moderates the relationship between management systems adaptive capability and manufacturing adaptive capability. Conversely, resource redundancy negatively moderates the relationship between technology adaptive capability and manufacturing adaptive capability. Finally, this study demonstrates that information redundancy does not moderate the desired relationship between all the adaptive capability-related variables for firms.Research limitations/implicationsThis study has some limitations inherent in survey design, mainly for both convenient sampling and country context.Practical implicationsThis study suggests that management should improve firm’s manufacturing adaptive capability to enhance firm's overall effectiveness. For that purpose, managers should consider the interrelationships between the market and a firm’s technology, management system, and manufacturing-related adaptive capabilities. Management should also consider the importance of using resource-related redundancy to leverage the relationship between a firm’s management adaptive capability and manufacturing adaptive capability. At the same time, management should be aware of certain reverse effects of resource redundancy on both technology adaptive capability and the manufacturing adaptive capability linkage of a firm.Originality/valueThis study expands the understanding of the adaptive capability of firms by examining how manufacturing adaptive capability can be further enhanced. The study also offers a model for the potential relationships that develop between different aspects of organizational adaptive capability by applying the contingency role of organizational redundancy variables.

Redundancy and complementarity between ERAP1 and ERAP2 revealed by their effects on the Behçet’s disease-associated HLA-B*51 peptidome

The endoplasmic reticulum aminopeptidases (ERAP)1 and ERAP2 trim peptides to be loaded onto the HLA class I molecules, including the main risk factor for Behçet’s disease HLA-B*51. The low activity ERAP1 variant is also a risk factor for this disease among HLA-B*51-positive individuals, whereas no association is known with ERAP2. This study aimed at defining the mutual relationships between both enzymes in the processing of an HLA-bound peptidome and at gaining insight into their differential association with Behçet’s disease. CRISPR/Cas9 was used to generate knock outs of ERAP1, ERAP2 or both enzymes from transfectant 721.221-HLA-B*51:01 cells. The surface expression of HLA-B*51 was reduced in all cases. The effects of depleting each or both enzymes on the B*51:01 peptidome was analyzed by quantitative label-free mass spectrometry. Substantial quantitative alterations of peptide length, subpeptidome balance, N-terminal residue usage, affinity and presentation of non-canonical li-gands were observed. These effects were often different in the presence or absence of the other enzyme, revealing their mutual dependency. In the absence of ERAP1, ERAP2 showed significant processing of B*51:01 ligands, indicating functional redundancy. A high overlap between the peptidomes of wildtype and double KO cells was observed, indicating that a large majority of B*51:01 ligands are present in the ER without the need of N-terminal processing, while ERAP1 and ERAP2 shape the peptidomes by altering the quantities of available peptides to be presented by the HLA molecule. These results indicate that both enzymes have distinct, but complementary and partially redundant effects on the B*51:01 pep-tidome, leading to its optimization and maximal surface expression. The distinct effects of both enzymes on the HLA-B*51 peptidome provide a basis for their differential association with Behçet’s disease and suggest a pathogenetic role of the B*51:01 peptidome.

Reinsurance And The Determinants Of The Ceding Decision Of Life Insurance Companies In Nigeria: An Empirical Analysis

Purpose: This paper is an empirical analysis of Nigeria's determinants of the ceding decision of life insurance companies. It is birthed from the notion that reinsurance, though highly beneficial to the insurance industry, is rarely undertaken by life insurers. Thus, this study aims at expounding on the determinants of reinsurance decisions of life insurance companies in Nigeria and the relationship of each determinant with ceded reinsurance. Methodology: An ex-post facto research design was adopted, and a sample size of seven (7) core life insurance companies in Nigeria was selected using the purposive sampling technique. Data were sourced from the Nigerian Insurers Digest and the websites of the select insurance companies covering the years 2011 to 2019. Descriptive analysis and unit root tests were conducted on the data to justify its suitability. Data were further analyzed using the panel data regression, and a decision was arrived at using the Hausman and redundant fixed effect tests. Results/Findings: The analysis showed a significant relationship between leverage and ceded reinsurance, firm size and ceded reinsurance, as well as return on assets and ceded reinsurance, while underwriting risk and reinsurance price had insignificant relationships with ceded reinsurance. All the explanatory variables also had positive relationships with the ratio of ceded reinsurance. Thus, it was concluded that leverage, firm size and return on assets are major determinants of the ceding decision of these companies, while underwriting risk and reinsurance price are not. Originality and Practical Implications:This study is an original work of the authors. It practically shows the relationship between the factors considered by life insurers in deciding to cede their risks and ceded reinsurance. With previous studies on reinsurance and its benefit to the insurance industry, this study brings factors that impede the life insurer from deriving these benefits. Therefore, it was recommended that to encourage life insurers to cede more risks, policymakers and regulators should align specific regulations on leverage, firm size and return on assets of life insurers in Nigeria.

How Do Emotional Speech Affect Second Language Comprehension: Examining Learners’ Eye Movements

Reading-while-listening has been proved to be helpful in second language reading comprehension under certain circumstances, while limited research has addressed whether the emotional auditory input effect reading comprehension, so the aim of this study was to identify this effect. In this study, second language learners were asked to read short passages while their eye movements were monitored. We found no significant effect on reading comprehension between two modes and we also found that reading-while-listening mode slower the reading speed. Moreover, there was a redundancy effect among participants.

Multiscale partial information decomposition of dynamic processes with short and long-range correlations: theory and application to cardiovascular control

Objective. In this work, an analytical framework for the multiscale analysis of multivariate Gaussian processes is presented, whereby the computation of Partial Information Decomposition measures is achieved accounting for the simultaneous presence of short-term dynamics and long-range correlations. Approach. We consider physiological time series mapping the activity of the cardiac, vascular and respiratory systems in the field of Network Physiology. In this context, the multiscale representation of transfer entropy within the network of interactions among Systolic arterial pressure (S), respiration (R) and heart period (H), as well as the decomposition into unique, redundant and synergistic contributions, is obtained using a Vector AutoRegressive Fractionally Integrated (VARFI) framework for Gaussian processes. This novel approach allows to quantify the directed information flow accounting for the simultaneous presence of short-term dynamics and long-range correlations among the analyzed processes. Additionally, it provides analytical expressions for the computation of the information measures, by exploiting the theory of state space models. The approach is first illustrated in simulated VARFI processes and then applied to H, S and R time series measured in healthy subjects monitored at rest and during mental and postural stress. Main Results. We demonstrate the ability of the VARFI modeling approach to account for the coexistence of short-term and long-range correlations in the study of multivariate processes. Physiologically, we show that postural stress induces larger redundant and synergistic effects from S and R to H at short time scales, while mental stress induces larger information transfer from S to H at longer time scales, thus evidencing the different nature of the two stressors. Significance. The proposed methodology allows to extract useful information about the dependence of the information transfer on the balance between short-term and long-range correlations in coupled dynamical systems, which cannot be observed using standard methods that do not consider long-range correlations.

Effect of Label Redundancy in Crowdsourcing for Training Machine Learning Models

Crowdsourcing is widely utilized for collecting labeled examples to train supervised machine learning models, but the labels obtained from workers are considerably noisier than those from expert annotators. To address the noisy label issue, most researchers adopt the repeated labeling strategy, where multiple (redundant) labels are collected for each example and then aggregated. Although this improves the annotation quality, it decreases the amount of training data when the budget for crowdsourcing is limited, which is a negative factor in terms of the accuracy of the machine learning model to be trained. This paper empirically examines the extent to which repeated labeling contributes to the accuracy of machine learning models for image classification, named entity recognition and sentiment analysis under various conditions of budget and worker quality. We experimentally examined four hypotheses related to the effect of budget, worker quality, task difficulty, and redundancy on crowdsourcing. The results on image classification and named entity recognition supported all four hypotheses and suggested that repeated labeling almost always has a negative impact on machine learning when it comes to accuracy. Somewhat surprisingly, the results on sentiment analysis using pretrained models did not support the hypothesis which shows the possibility of remaining utilization of multiple-labeling.

Relationship between diversity and stability of a karst plant community.

The relationships among species diversity, functional diversity, functional redundancy, and community stability are central to community and ecosystem ecology. In this paper, a “space substitution for time” approach is used to study the plant communities at different stages of the natural recovery process of degraded karst vegetation on the karst plateau of Guizhou. These restoration stages include the herbaceous stage, herbaceous and shrub transition stage, shrub stage, tree and shrub transition stage, and tree stage. We calculated the functional diversity and functional redundancy of the community based on functional characteristics and mediated the relationship between functional diversity, functional redundancy, and stability of the plant community through changes in functional diversity and functional redundancy. This study aims to reveal the mechanisms of changes in species diversity and community stability and thus further reveals the intrinsic reasons for maintaining the stability of karst plant communities. The most important results include the following: (1) Species diversity, functional redundancy, and stability gradually increased with restoration, and there were significant differences among the different stages; functional diversity increased at first and then decreased, and reached the highest level at the tree and shrub transition stage; (2) Plant height and specific leaf area were functional traits that influenced the diversity and stability of the plant community, with plant height being positively correlated with plant community diversity and stability, and specific leaf area being negatively correlated with plant community diversity and stability; (3) During the community's recovery, functional diversity and functional redundancy interacted to maintain stability. In the early and late stages of recovery, the effect of functional redundancy on stability was greater than that of functional diversity, but it was the opposite in the middle stages; (4) The tree and shrub transition stage is the likely point at which the functional diversity of plant communities in karst areas reaches saturation, and the growth rate of functional redundancy after functional diversity saturation is greater than that before saturation. Overall, community stability increased with species diversity; habitat heterogeneity increased functional diversity in the early stages of recovery; and habitat homogeneity increased functional redundancy.

Cognitive-based methods to facilitate learning of software applications via E-learning systems

E-learning systems, which are used for teaching complex software, can facilitate learning if they provide an appropriate teaching approach that decreases learners’ cognitive load in addition to providing practical knowledge. We believe there is lack of cognitively guided educational recommendations on how to effectively and efficiently design such learning platforms. We thus provide an integrative review paper that overviews relevant literature to cognitive load theory to provide practical solutions and an empirically validated framework to decrease learners’ cognitive load and improve the learning of complex software through E-learning systems. The solutions (which contain practical examples) are proposed based on different concepts of cognitive load theory including using analogies, worked examples and infographics to facilitate schema acquisition; keeping learners’ concentration on the target tools by preventing split-attention and redundancy effects and applying the training wheel method; using interactive videos based on embodied cognition theory and finally considering the modality and transient information effects in designing E-learning systems. These solutions are related to adapting the learning platform to human cognitive structures and can lead to increased learning performance by preventing working memory from being overwhelmed, thus facilitating the formation of schemas and resulting in more efficient and reliable learning with less effort.

No selective integration required: A race model explains responses to audiovisual motion-in-depth

Looming motion is an ecologically salient signal that often signifies danger. In both audition and vision, humans show behavioral biases in response to perceiving looming motion, which is suggested to indicate an adaptation for survival. However, it is an open question whether such biases occur also in the combined processing of multisensory signals. Towards this aim, Cappe, Thut, Romei, and Murraya (2009) found that responses to audiovisual signals were faster for congruent looming motion compared to receding motion or incongruent combinations. They considered this as evidence for selective integration of multisensory looming signals. To test this proposal, here, we successfully replicate the behavioral results by Cappe et al. (2009). We then show that the redundant signals effect (RSE - a speedup of multisensory compared to unisensory responses) is not distinct for congruent looming motion. Instead, as predicted by a simple probability summation rule, the RSE is primarily modulated by the looming bias in audition, which suggests that multisensory processing inherits a unisensory effect. Finally, we compare a large set of so-called race models that implement probability summation, but that allow for interference between auditory and visual processing. The best-fitting model, selected by the Akaike Information Criterion (AIC), virtually perfectly explained the RSE across conditions with interference parameters that were either constant or varied only with auditory motion. In the absence of effects jointly caused by auditory and visual motion, we conclude that selective integration is not required to explain the behavioral benefits that occur with audiovisual looming motion.

A sparse and spectral smooth regularized low-rank tensor decomposition method for hyperspectral target detection

ABSTRACT In recent years, hyperspectral target detection methods have been widely used in military or civilian fields. Many high-performance hyperspectral target detection methods have been proposed, and tensor decomposition-based methods have attracted the attention of researchers. However, the non-uniqueness of tensor rank and the interference of noise will reduce the effect of target detection. In order to solve these problems, a sparse and spectral smooth regularized low-rank tensor decomposition method for hyperspectral target detection is proposed in this paper. The proposed method adds the low-rank regularization to the factor matrix of the tensor decomposition framework, which can reduce the adverse effect of information redundancy on the detection effect of the algorithm. Furthermore, the spectral smooth regularization is added to the spectral factor matrix to suppress noise and the sparse regularization is added to the core tensor to solve the problems of non-uniqueness of the Tucker tensor decomposition, which can improve the effect of target detection. On this basis, it simplifies the calculation process and reduces the complexity of the algorithm by using the conjugate gradient algorithm and the tensor Kronecker product. In this paper, the algorithm is tested on four real hyperspectral data sets and compared with six state-of-the-art algorithms. The experimental results show that targets detected by the proposed method are more obvious and the background is more pure.

Phasic Alertness and Multisensory Integration Contribute to Visual Awareness of Weak Visual Targets in Audio-Visual Stimulation under Continuous Flash Suppression

Multisensory stimulation is associated with behavioural benefits, including faster processing speed, higher detection accuracy, and increased subjective awareness. These effects are most likely explained by multisensory integration, alertness, or a combination of the two. To examine changes in subjective awareness under multisensory stimulation, we conducted three experiments in which we used Continuous Flash Suppression to mask subthreshold visual targets for healthy observers. Using the Perceptual Awareness Scale, participants reported their level of awareness of the visual target on a trial-by-trial basis. The first experiment had an audio-visual Redundant Signal Effect paradigm, in which we found faster reaction times in the audio-visual condition compared to responses to auditory or visual signals alone. In two following experiments, we separated the auditory and visual signals, first spatially (experiment 2) and then temporally (experiment 3), to test whether the behavioural benefits in our multisensory stimulation paradigm could best be explained by multisensory integration or increased phasic alerting. Based on the findings, we conclude that the largest contributing factor to increased awareness of visual stimuli accompanied by auditory tones is a rise in phasic alertness and a reduction in temporal uncertainty with a small but significant contribution of multisensory integration.