Lexical Priming and Sound-to-Spelling Contingency Effects in Nonword Spelling

1988 ◽  
Vol 40 (1) ◽  
pp. 5-40 ◽  
Author(s):  
Christopher Barry ◽  
Philip H. K. Seymour
Keyword(s):  
Priming Effect ◽  
Experimental Task ◽  
Lexical Priming ◽  
Spelling Pattern ◽  
Priming Task ◽  
Proposed Model ◽  
Selection Of

Campbell (1983) demonstrated that nonword spelling may be influenced by the spelling patterns of previously heard, rhyming words (“lexical priming”). We report an experiment that compares two nonword spelling tasks: an experimental (“priming”) task, in which nonwords were preceded by rhyming words of different spellings (as in Campbell's task), and a free-spelling task in which only nonwords are presented. The frequency of production of critical spelling patterns was significantly greater in the experimental task than in the free-spelling task (a lexical priming effect). However, there were, and equally for both tasks, significant and substantial effects of sound-to-spelling contingency (i.e. the frequency with which spelling patterns represent vowel phonemes in words): subjects produced more high-contingency (i.e. common) spelling patterns of vowels than low-contingency (rare) spellings. Further, within high-contingency spelling patterns, subjects more frequently produced the most common spelling correspondence of vowels than the second most common spelling. The results are interpreted within a proposed model of assembled spelling, in which it is suggested that there exist a set of probabilistic sound-to-spelling mappings that relate vowel phonemes to weighted lists of alternative spelling patterns ordered by sound-to-spelling contingency, but that the selection of a spelling pattern from such lists is open to lexical influence.

Bioluminescent proteins prediction with voting strategy.

2020 ◽  
Vol 15 ◽  
Author(s):  
Shulin Zhao ◽  
Ying Ju ◽  
Xiucai Ye ◽  
Jun Zhang ◽  
Shuguang Han
Keyword(s):  
Amino Acid ◽  
Model Building ◽  
Prediction Method ◽  
Pair Composition ◽  
Proposed Model ◽  
Counting Rules ◽  
Significant Phenomenon ◽  
Voting Strategy ◽  
Improved Accuracy ◽  
Selection Of

Background: Bioluminescence is a unique and significant phenomenon in nature. Bioluminescence is important for the lifecycle of some organisms and is valuable in biomedical research, including for gene expression analysis and bioluminescence imaging technology.In recent years, researchers have identified a number of methods for predicting bioluminescent proteins (BLPs), which have increased in accuracy, but could be further improved. Method: In this paper, we propose a new bioluminescent proteins prediction method based on a voting algorithm. We used four methods of feature extraction based on the amino acid sequence. We extracted 314 dimensional features in total from amino acid composition, physicochemical properties and k-spacer amino acid pair composition. In order to obtain the highest MCC value to establish the optimal prediction model, then used a voting algorithm to build the model.To create the best performing model, we discuss the selection of base classifiers and vote counting rules. Results: Our proposed model achieved 93.4% accuracy, 93.4% sensitivity and 91.7% specificity in the test set, which was better than any other method. We also improved a previous prediction of bioluminescent proteins in three lineages using our model building method, resulting in greatly improved accuracy.

Automated Image Denoising Model: Contribution Towards Optimized Internal and External Basis

2021 ◽  
pp. 2150051
Author(s):  
S. Elavaar Kuzhali ◽  
D. S. Suresh
Keyword(s):  
Image Denoising ◽  
Image Patch ◽  
The Past ◽  
Local Means ◽  
Hybrid Optimization Algorithm ◽  
Proposed Model ◽  
Processing Step ◽  
Non Local ◽  
Chicken Swarm Optimization ◽  
Selection Of

For handling digital images for various applications, image denoising is considered as a fundamental pre-processing step. Diverse image denoising algorithms have been introduced in the past few decades. The main intent of this proposal is to develop an effective image denoising model on the basis of internal and external patches. This model adopts Non-local means (NLM) for performing the denoising, which uses redundant information of the image in pixel or spatial domain to reduce the noise. While performing the image denoising using NLM, “denoising an image patch using the other noisy patches within the noisy image is done for internal denoising and denoising a patch using the external clean natural patches is done for external denoising”. Here, the selection of optimal block from the entire datasets including internal noisy images and external clean natural images is decided by a new hybrid optimization algorithm. The two renowned optimization algorithms Chicken Swarm Optimization (CSO), and Dragon Fly Algorithm (DA) are merged, and the new hybrid algorithm Rooster-based Levy Updated DA (RLU-DA) is adopted. The experimental results in terms of some relevant performance measures show the promising results of the proposed model with remarkable stability and high accuracy.

The cross-modal affective priming effect: Effects of the valence and arousal of primes

2021 ◽  
Vol 49 (12) ◽  
pp. 1-11
Author(s):  
Cheng Kang ◽  
Nan Ye ◽  
Fangwen Zhang ◽  
Yanwen Wu ◽  
Guichun Jin ◽  
...  
Keyword(s):  
Priming Effect ◽  
Affective Priming ◽  
Negative Valence ◽  
Priming Task ◽  
The Cross ◽  
Visual Targets ◽  
Positive And Negative Valence ◽  
Valence And Arousal ◽  
Affective Information

Although studies have investigated the influence of the emotionality of primes on the cross-modal affective priming effect, it is unclear whether this effect is due to the contribution of the arousal or the valence of primes. We explored how the valence and arousal of primes influenced the cross-modal affective priming effect. In Experiment 1 we manipulated the valence of primes (positive and negative) that were matched by arousal. In Experiments 2 and 3 we manipulated the arousal of primes under the conditions of positive and negative valence, respectively. Affective words were used as auditory primes and affective faces were used as visual targets in a priming task. The results suggest that the valence of primes modulated the cross-modal affective priming effect but that the arousal of primes did not influence the priming effect. Only when the priming stimuli were positive did the cross-modal affective priming effect occur, but negative primes did not produce a priming effect. In addition, for positive but not negative primes, the arousal of primes facilitated the processing of subsequent targets. Our findings have great significance for understanding the interaction of different modal affective information.

scholarly journals A Proposed Heuristic Optimization Algorithm for Detecting Network Attacks

2019 ◽  
Vol 2 (4) ◽  
pp. 530
Author(s):  
Amr Hassan Yassin ◽  
Hany Hamdy Hussien
Keyword(s):  
Neural Network ◽  
Heuristic Algorithms ◽  
Feed Forward Neural Network ◽  
Data Set ◽  
Network Attacks ◽  
Security Issues ◽  
Proposed Model ◽  
Network Intrusions ◽  
Attack Patterns ◽  
Selection Of

Due to the exponential growth of E-Business and computing capabilities over the web for a pay-for-use groundwork, the risk factors regarding security issues also increase rapidly. As the usage increases, it becomes very difficult to identify malicious attacks since the attack patterns change. Therefore, host machines in the network must continually be monitored for intrusions since they are the final endpoint of any network. The purpose of this work is to introduce a generalized neural network model that has the ability to detect network intrusions. Two recent heuristic algorithms inspired by the behavior of natural phenomena, namely, the particle swarm optimization (PSO) and gravitational search (GSA) algorithms are introduced. These algorithms are combined together to train a feed forward neural network (FNN) for the purpose of utilizing the effectiveness of these algorithms to reduce the problems of getting stuck in local minima and the time-consuming convergence rate. Dimension reduction focuses on using information obtained from NSL-KDD Cup 99 data set for the selection of some features to discover the type of attacks. Detecting the network attacks and the performance of the proposed model are evaluated under different patterns of network data.

Organizing inter-firm project governance – a contextual model for empirical investigation

2018 ◽  
Vol 11 (1) ◽  
pp. 144-157 ◽  
Author(s):  
Simon von Danwitz
Keyword(s):  
Organization Theory ◽  
Contextual Factors ◽  
Project Performance ◽  
Future Research ◽  
Content Type ◽  
Project Governance ◽  
Proposed Model ◽  
Key Characteristics ◽  
Conceptual Paper ◽  
Selection Of

Purpose The management of major inter-firm projects requires a coherent, holistic governance framework to be effective. However, most existing models of project governance are limited to a narrow selection of contractual, structural or procedural aspects, and further neglect contextual factors, such as key characteristics of a project and its partners. The paper aims to discuss these issues. Design/methodology/approach This conceptual paper proposes an integrative analytical model of inter-firm project governance, building upon contingency theory and drawing from established constructs rooted in organization theory. Findings The paper aims to integrate two largely distinct streams of research and synthesize the respective constitutive dimensions of project governance into a coherent conceptual model. Further, interrelationships with contextual factors, such as project-related and partner-related characteristics, and project performance are discussed. Originality/value The proposed model purposefully merges two complementary streams of project governance research. As the model further provides clear contextual factors, it strengthens an emerging stream of project research by systematically examining external influences of project organizing. Future research may utilize this model and the suggested operationalization for each of the constructs as a basis to empirically investigate the design and effectiveness of governance regimes of major projects.

An Integrated Methodology for Evaluation of Electric Vehicles Under Sustainable Automotive Environment

2019 ◽  
pp. 41-62 ◽  
Author(s):  
Tapas Kumar Biswas ◽  
Željko Stević ◽  
Prasenjit Chatterjee ◽  
Morteza Yazdani
Keyword(s):  
Electric Vehicles ◽  
Sustainability Assessment ◽  
Model Performance ◽  
Compromise Solution ◽  
Holistic Model ◽  
Proposed Model ◽  
Criteria Importance ◽  
Assessment Problems ◽  
Selection Of

In this chapter, a holistic model based on a newly developed combined compromise solution (CoCoSo) and criteria importance through intercriteria correlation (CRITIC) method for selection of battery-operated electric vehicles (BEVs) has been propounded. A sensitivity analysis has been performed to verify the robustness of the proposed model. Performance of the proposed model has also been compared with some of the popular MCDM methods. It is observed that the model has the competency of precisely ranking the BEV alternatives for the considered case study and can be applied to other sustainability assessment problems.

A Hybrid AHP-ELECTRE I Multicriteria Model for Performance Assessment and Team Selection

2017 ◽  
pp. 115-127
Author(s):  
Ikram Khatrouch ◽  
Lyes Kermad ◽  
Abderrahman el Mhamedi ◽  
Younes Boujelbene
Keyword(s):  
Human Resources ◽  
Decision Maker ◽  
Human Resources Management ◽  
Real Data ◽  
Assessment Model ◽  
Team Selection ◽  
Proposed Model ◽  
Electre I ◽  
Multicriteria Model ◽  
Selection Of

Human resources management is essential to any health care system. This paper proposes an assessment model to help the decision maker in the selection of an optimal team. In the proposed model, AHP method is applied to identify the weights of each criterion in the decision model. ELECTRE I method is used to obtain the best team that satisfies most of the decision maker preferences. We test the effectiveness of the model on the real data collected from the ‘Habib Bourguiba' Hospital in Tunisia.

Development of a new empirical method for Tunnel Squeezing Classification (TSC)

2020 ◽  
Vol 53 (4) ◽  
pp. 655-660 ◽  
Author(s):  
Hadi Farhadian ◽  
Arash Nikvar-Hassani
Keyword(s):  
Quality Index ◽  
Empirical Method ◽  
Point Of View ◽  
Geological Hazard ◽  
Case Histories ◽  
Proposed Model ◽  
Two Parameters ◽  
Classification Tool ◽  
Selection Of

The characterization of squeezing phenomena as a geological hazard is of great importance because squeezing has a crucial role in the selection of the route and type of tunnels and in the characteristics of the excavation device. Tunnel squeezing is also the basis for the designation and construction of tunnelling-related structures. We present a new tunnel squeezing classification tool to predict tunnel squeezing based on two parameters: Q, the tunnelling quality index; and H, the depth of the tunnel. We used data collected from published papers to train the model; these data included 225 case histories from different countries, including Andorra, India, Iran, Japan, Nepal, Spain, Turkey and Venezuela. Validation of the model indicated that our tunnel squeezing classification tool is more accurate than the speculative and analytical methods currently in use. The proposed model will help tunnelling experts to classify tunnelling media from the point of view of squeezing hazards.

An Accurate Full Car Ride Model Using Model Reducing Techniques

2002 ◽  
Vol 124 (4) ◽  
pp. 697-705 ◽  
Author(s):  
Chul Kim ◽  
Paul I. Ro
Keyword(s):  
Model Complexity ◽  
Ride Quality ◽  
Singular Perturbation Method ◽  
Suspension Systems ◽  
Proposed Model ◽  
Model Size ◽  
Improved Performance ◽  
Accurate Matching ◽  
Multibody Dynamics Model ◽  
Selection Of

In this study, an approach to obtain an accurate yet simple model for full-vehicle ride analysis is proposed. The approach involves linearization of a full car MBD (multibody dynamics) model to obtain a large-order vehicle model. The states of the model are divided into two groups depending on their effects on the ride quality and handling performance. Singular perturbation method is then applied to reduce the model size. Comparing the responses of the proposed model and the original MBD model shows an accurate matching between the two systems. A set of identified parameters that makes the well-known seven degree-of-freedom model very close to the full car MBD model is obtained. Finally, the benefits of the approach are illustrated through design of an active suspension system. The identified model exhibits improved performance over the nominal models in the sense that the accurate model leads to the appropriate selection of control gains. This study also provides an analytical method to investigate the effects of model complexity on model accuracy for vehicle suspension systems.

scholarly journals Sustainable Location Selection of Data Centers: Developing a Multi-Criteria Set-Covering Decision-Making Methodology

2020 ◽  
Vol 19 (03) ◽  
pp. 741-773
Author(s):  
Siamak Kheybari ◽  
Mansoor Davoodi Monfared ◽  
Hadis Farazmand ◽  
Jafar Rezaei
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Social Economic ◽  
Set Covering ◽  
Online Questionnaire ◽  
Location Selection ◽  
Sustainability Criteria ◽  
Proposed Model ◽  
Covering Model ◽  
Selection Of

In this paper, a multi-criteria set-covering methodology is proposed to select suitable locations for a set of data centers. First, a framework of criteria, with social, economic and environmental dimensions, is presented. The framework is used to calculate the suitability of potential data center locations in Iran. To that end, a sample of specialists in Iran was asked to take part in an online questionnaire, based on best–worst method (BWM), to determine the weight of the criteria included in the proposed framework, after which a number of potential locations are evaluated on the basis of the criteria. The proposed model is evaluated under a number of settings. Using the proposed multi-criteria set-covering model, not only the utility of candidate places is evaluated by sustainability criteria but also all service applicants are covered by at least one data center with a specific coverage radius.

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