In this paper, a completely new statistical based approach is developed for solving the system of nonlinear equations. The developed approach utilizes the characteristics of the normal distribution to search the solution space. The normal distribution is generally introduced by two parameters, i. e., mean and staNDArd deviation. In the developed algorithm, large values of staNDArd deviation enable the algorithm to escape from a local optimum, and small values of staNDArd deviation help the algorithm to , nd the global optimum. In the following, six benchmark tests and thirteen benchmark case problems are investigated to evaluate the performance of the Normal Distribution-based Algorithm (NDA). The obtained statistical results of NDA are compared with those of PSO, ICA, CS, and ACO. Based on the obtained results, NDA is the least time-consuming algorithm that gets high-quality solutions. Furthermore, few input parameters and simple structure introduce NDA as a user friendly and easy-to-understand algorithm.

Background: The aim of this study was to evaluate computer aided diagnosis (CAD) system with texture analysis (TA) to improve radiologists' accuracy in identification of thyroid nodules as malignant or benign.Methods: A total of 70 cases (26 benign and 44 malignant) were analyzed in this study. We extracted up to 270 statistical texture features as a descriptor for each selected region of interests (ROIs) in three normalization schemes (default, 3s and 1%-99%). Then features by the lowest probability of classification error and average correlation coefficients (POE+ACC), and Fisher coefficient (Fisher) eliminated to 10 best and most effective features. These features were analyzed under staNDArd and nonstaNDArd states. For TA of the thyroid nodules, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA) were applied. First Nearest-Neighbour (1-NN) classifier was performed for the features resulting from PCA and LDA. NDA features were classified by artificial neural network (A-NN). Receiver operating characteristic (ROC) curve analysis was used for examining the performance of TA methods.Results: The best results were driven in 1-99% normalization with features extracted by POE+ACC algorithm and analyzed by NDA with the area under the ROC curve (Az) of 0.9722 which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%.Conclusion: Our results indicate that TA is a reliable method, can provide useful information help radiologist in detection and classification of benign and malignant thyroid nodules.

Originating from Vygotsky’s Sociocultural Theory, dynamic assessment (DA) proposes a novel approach to second language acquisition (SLA) research according to which a dialectical relationship is envisaged between instruction and assessment. Although DA has been applied to some areas of SLA, there are areas, such as interlanguage pragmatics (ILP), that have been neglected. To address the issue, 40 university students of two proficiency levels were selected and assigned randomly to 1 of 4 groups consisting of two DA and two Non-DA groups. Each group received instruction concerning how to use appropriate request and apology strategies in the English language. However, following Lantolf and Poehner (2011), DA groups received ZPD-sensitive feedback whereas NDA groups received no more feedback but were assessed according to their independent performance. All participants completed a pretest, a posttest, and a delayed posttest of request and apology speech acts that were rated by two native speakers of English on a 6-point Likert scale. The findings revealed that DA groups outperformed NDA groups and that DA groups of both high and low proficiency levels differed significantly from pretest to posttest to delayed posttest. However, high NDA group didn’t show such a difference. The results also showed no interaction between proficiency and instruction indicating that instruction, but not proficiency, had a significant effect on posttest and delayed posttest performance of the students. The findings may be revealing in that they support DA and its applicability to ILP instruction.

In this study, the effect of importance factor (IF) on RC frames with and without infill walls, in both with and without opening conditions, is evaluated against progressive collapse. For this purpose, RC building with the intermediate moment frame system for three levels of importance factor that these levels are intermediate, high, and very high IF is designed. OpenSees program is utilized for modeling RC frames. For this aim, the accuracy of modeling of column removal and infill walls are compared with experimental researches. In the present study, nonlinear dynamic analysis (NDA) and push-down analysis (PDA) were used for evaluating RC frames against progressive collapse in each column removal scenario. Analysis results showed that the effect of the importance factors in NDA and PDA are reduced to less than 24% and 13% when the infill walls are modeled in the frames. In the frame without infill walls, the influence of the importance factor is increased up to 36.1%. Also, in this study, it was found that the role of importance factors depends on the place of the removed column, which the effect of middle column removal is relatively twice than the corner column removal due to more reduNDAncy. Other results about infill walls effects and opening in infill walls are presented in the paper. Finally, a proposed approach for column removal in NDA via OpenSees program is introduced, and its high accuracy is shown. This developed algorithm can remove any element of structure in different time intervals.

Feature extraction performs an important role in improving hyperspectral image classification. Compared with parametric methods، nonparametric feature extraction methods have better performance when classes have nonnormal distribution. Besides، these methods can extract more features than parametric feature extraction methods do. Nonparametric feature extraction methods use nonparametric scatter matrices to compute transformation matrix. Nonparametric Discriminant Analysis (NDA) is one of the nonparametric feature extraction methods in which، in order to form nonparametric scatter matrices، local means of samples and weight function are used. Local mean is calculated by k nearest neighbors of each sample and weight function emphasizes on bouNDAry samples in between class scatter matrix formation. In this paper، modified NDA (MNDA) is proposed to improve NDA. In MNDA، the number of neighboring samples، when measuring local mean، are determined considering position of each sample in feature space. MNDA uses new weight functions in scatter matrix formation. Suggested weight functions emphasizes on bouNDAry samples in between class scatter matrix formation and focus on samples close to class mean in within class scatter matrix formation. Moreover، within class scatter matrix is regularized to avoid singularity. Experimental results on Indian Pines and Salinas images show that MNDA has better performance compared to other parametric and nonparametric feature extraction methods. For Indian Pines data set، the maximum average classification accuracy is 80. 34%، which is obtained by 18 training samples، support vector machine (SVM) classifier and 10 extracted features achieved by MNDA method. For Salinas data set، the maximum average classification accuracy is 94. 31%، which is obtained by 18 training samples، SVM classifier and 9 extracted features achieved by MNDA method. Experiments show that using suggested weight functions and regularized within class scatter matrix، the proposed method obtained better results in hyperspectrl imag classification with limited training samples.

In the past decade design procedure changed to “performance-based design” from “force-based design”, by this mean many researchers focused on nonlinear static analysis (NSA) and the procedure named “PUSHOVER”. Advantages of this method are defining the inelastic behavior of structure without nonlinear dynamic analysis (NDA) effort and also defining plastic hinges formation in critical elements, and the order of formed plastic hinges. In spite of these good advantages NSA is limited to short and planar structures and application of that in tall and torsionaly asymmetric structures may yield unreliable results. In this study reliability of NSA is investigated by performing both nonlinear static and dynamic analysis on six 2D moment resisting concrete frames. Non linear dynamic analysis has been done by the suggested method in FEMA356 guideline called “Target Displacement Method”. A group of 4 different lateral increasing loads were used in pushover analysis and 3 different ground motions were applied in NDA. Results indicate that same respon ses can be obtained by performing NSA, but errors will be increased by frames height increment.

Pragmatics, which is one of the most eminent concepts in the world of language learning and teaching, has established itself in various academic fields. The teachability of pragmatics has been investigated in a plethora of studies (Derakhshan & Shakki, 2020; Shakki et al., 2020), though scant attention has been given to assessing and testing pragmatic features. It has been a long time that practitioners and teachers use traditional assessment to assess students, but with the emergence of new approaches in teaching, there should be new ways to test and assess learners. The present study is theoretically underpinned by Vygotsky’ s (1978) Socio-Cultural Theory (SCT), which postulates that a person’ cognition is mediated socially during the interaction, and it emphasizes a mediated relationship not a direct relationship which is the basis for Dynamic Assessment (DA). He believes that the development of a child consists of two levels, namely actual level and potential level of development. Activating the Zone of Proximal Developmnet (ZPD), which is the distance between the actual developmental level and the level of potential development, requires guidance and collaboration. Since assessing the speech acts of apology and request through DA has not been taken into account so far, the present study aimed to find out the effects of DA on the acquisition of Iranian intermediate EFL learners’ speech act of apology and request. To this end, 66 students, selected from Shokouh Language Institute in Kalaleh, Golestan Providence, Iran, participated in this study. Research Question: Does dynamic vs. non-dynamic assessments (NDA) have any effect on the acquisition of Iranian intermediate EFL learner’ s speech act of apology and request? Three groups of language learners whose language proficiency was determined by Oxford Quick Placement Test (OQPT), participated in the present study. The total number of the participants was 85 Iranian learners, from whom 66 were selected as intermediate level whose scores ranged from 24 to 30, according to OQPT. The gender of the students was both male and female, and learners aged from 15 to 19. Their native language was Persian, and they were studying English as a second language. After homogenizing learners, they were divided into three groups, one DA, one NDA, and one control group. Listening pragmatic comprehension test, devised and validated by Birjandi and Derakhshan (2014), was utilized as the pretest and posttest of the study. First, the participants were tested before the intervention; after teaching speech acts to learners (30 apology and request video vignettes that were taken from seasons and episodes of 13 Reasons Why and Suits), the learners were tested by the listening pragmatic comprehension test to compare the results. In this study, to have homogeneous learners for all three groups, the mean and staNDArd deviation of the proficiency test were calculated. To answer the research question, the scores taken from pretest and posttest were submitted to the Statistical Package of Social Sciences (SPSS). To find the effectiveness of the treatment, the means of control group, NDA group, and DA group were compared. In order to make sure whether or not the groups were statistically different, One-way ANOVA test and post hoc test of Tukey were run. Based on the mean scores for the pretest in one DA and two NDA groups, which are 58. 88, 55. 92, and 55. 67, it is shown that little difference exists among the three groups. However, in order to make sure whether or not the groups are similar statistically, One-way ANOVA test was conducted. The Sig. value is. 92 which demonstrates that since this is more than. 05, it can be concluded that there is not a statistically significant difference between the mean scores of the three groups. On the other hand, the mean scores for the posttest in one DA, NDA, and control group, respectively, were 117. 42, 72. 83, and 61. 58, showing that the groups are different. Furthermore, the Sig. value is 0. 00, which is smaller than. 05, so this means that the intervention which was implemented in the DA group was effective. Since the obtained value does not show where the significant difference exists, post hoc test of Tukey was used to find the statistical significance between the groups. The values corresponding with the comparison between the DA group and NDA groups are smaller than. 05. For this reason, it can be concluded that the difference between DA group and the other two groups is statistically significant. However, the comparison between the two NDA groups revealed that they are not significantly different from each other (p=. 392>. 05). The results of one-way ANOVA test indicated that there were statistically meaningful differences across groups, and the results of post hoc test of Tukey revealed that dynamic group outperformed both non-dynamic and control groups, but no meaningful difference was found between non-dynamic and control groups although nondynamic had a better mean score compared to that of control group. Considering the findings of the present study, it is suggested that harmonizing the instruction and testing provides opportunities for the learners, and learning should be individualized in order to have better outcomes. To put it in a nutshell, giving students contextually appropriate input has been a pivotal factor to increase learners’ pragmatic ability while understanding and performing the speech acts. In light of the gained results, the present study offers some implications for teachers, learners, and materials developers. It is suggested that teachers apply DA in their language classrooms to maximize interaction, mediation, and negotiation.