中央执行注意资源在消极和积极特征捆绑中的作用

鉴于以往研究未明确视觉工作记忆中特征捆绑是否需要注意资源,以及未考察积极加工条件下的特征捆绑等问题,本研究运用双任务干扰范式,通过两个实验分别在消极加工和积极加工条件下考察了联结客体的特征加工和特征捆绑,以及中央执行注意资源在特征捆绑中的作用。结果表明：联结客体的特征加工不但存在双重存储机制,还存在双重操作机制,这一结果拓展了Wheeler和Treisman（2002）的特征捆绑理论;联结客体的特征捆绑可分为消极特征捆绑和积极特征捆绑两种类型,消极特征捆绑不需要中央执行注意资源的参与,而积极特征捆绑则需要中央执行注意资源的参与。     

场景在价值驱动注意捕获中的作用

本研究采用训练-测试范式考察场景信息在价值驱动注意捕获中的作用。实验1训练阶段将唯一性的场景信息与奖励建立联结,测试阶段发现只有当分心刺激出现在高奖励场景中才能捕获注意;实验2训练阶段将场景和颜色信息联合但分别独立预测奖励,结果发现高奖励颜色出现在任何场景中都能捕获注意。研究结果表明:(1)场景-价值联结能够引发注意捕获效应;(2)与场景相比,颜色特征在价值驱动的注意捕获中具有优势效应。     

Application of multi-feature fusion and random forests to the automated detection of myocardial infarction

Myocardial infarction (MI) was one of the most threatening cardiovascular diseases due to its suddenness and high mortality. Electrocardiography (ECG) reflected the electrophysiological activity of the heart which was widely used for the diagnosis of MI. The aim of the paper was to provide a novel method to detect MI leveraging ECG. Firstly, data enhancement technology was employed to extend the database and prevent overfitting. Then, principal component analysis (PCA) features, statistical features, and entropy features were computed as the representation of first layer features for each lead. Furthermore, the second layer features for each lead were extracted by using random forests (RF), and the feature extraction results were quantified as a classification data set. Finally, in order to evaluate the proposed method, two schemes for the intra-patient and inter-patient were employed. The accuracy, sensitivity, specificity and F1 values in the intra-patient scheme were 99.71%, 99.7%, 99.73%, and 99.71%, respectively, and 85.82%, 73.91%, 97.73%, and 83.9% in the inter-patient scheme. Meanwhile, compared with different methods including support vector machine (SVM), back propagation neural network (BPNN), and k-nearest neighbor (KNN), RF displayed the best performance.     

乐观偏差研究概况

乐观偏差指个体倾向于认为自己更可能经历积极事件而他人更可能遭遇消极事件的现象。对乐观偏差的测量主要有直接比较和间接比较两种方式。事件特征和个体因素是乐观偏差的主要影响因素。产生乐观偏差的心理机制主要有自我中心主义和聚焦主义。乐观偏差对个体既有积极作用也有消极影响。未来研究主要包括:开发科学可行的测量工具;加强对个体水平乐观偏差的研究;把乐观偏差和悲观偏差结合起来进行研究;对乐观偏差进行认知神经心理机制的探讨。     

自然概念语义特征提取的范畴效应

本研究采用概念特征自由列举实验范式,考察三类范畴(动物、自然食物、人造物)自然概念的语义特征提取反应时间的范畴效应。结果表明,⑴语义特征提取的反应时间存在范畴效应:提取动物特征的时间显著短于提取自然食物特征的时间,提取自然食物特征的时间显著短于提取人造物特征的时间;⑵三类范畴的特征提取时间模式表现出相同的规律:先是显著降低(第1到第2个特征),然后持续升高(第2到第10个特征)。语义特征提取的范畴效应反映了语义记忆组织的范畴特异性,有必要进一步分析特征提取时间与特征类型、关联特征、独有特征之间的关系,以深入揭示语义特征提取范畴效应的产生机制。     

视觉工作记忆中的储存单位--特征还是客体?

视觉工作记忆中存储的基本单位是客体还是特征,目前尚无定论。本实验试图进一步探索这一问题。被试为30名大学生。实验1的条件是:颜色特征数不同,客体总数相同。实验2的条件是:颜色特征数相同,客体总数不同。结果表明:在记忆由同一属性的特征组成的客体时,视觉工作记忆存储的基本单位是特征。     

视觉特征捆绑的认知机制研究

以大学生为被试,探讨视觉特征捆绑的认知机制。实验采用空间提示范式,要求被试完成字母形状和颜色的辨别任务,考察集中注意和分散注意条件下的IC差异。结果表明,注意在视觉特征捆绑中起重要作用,集中注意能有效地减少IC的出现。同时注意对特征捆绑的调节作用表现出距离效应,即近距离比远距离的IC错误多,提示了注意的作用机制有可能与空间距离信息有关。     

The effects on classifier performance of 2D discrete wavelet transform analysis and whale optimization algorithm for recognition of power quality disturbances

Power Quality (PQ) is becoming more and more important day by day in the electric network. Signal processing, pattern recognition and machine learning are increasingly being studied for the automatic recognition of any disturbances that may occur during the generation, transmission, and distribution of electricity. There are three main steps to identify the PQ disturbances. These include the use of signal processing methods to calculate the features representing the disturbances, the selection of those that are more useful than these feature sets to prevent the creation of a complex classification model, the creating a classification model that recognizes multiple classes using the selected feature subsets. In this study, one-dimensional (1D) PQ disturbances signals are transformed into two-dimensional (2D) signals, 2D discrete wavelet transforms (2D-DWT) are used to extract the features. The features are extracted by using the wavelet families such as Daubechies, Biorthogonal, Symlets, Coiflets and Fejer-Korovkin in 2D-DWT to analyze PQ disturbances. Whale Optimization Algorithm (WOA) and k-nearest neighbor (KNN) classifier determine the feature subsets. Then, WOA and k nearest neighbor (KNN) classifier are used to determine the feature group. By using KNN and Support Vector Machines (SVM) classification methods, Classifier models that distinguish PQ disturbances are formed. The main aim of the study is to determine the features derived from 2D wavelet coefficients for different wavelet families and to determine which of them has a better classification performance to distinguish PQ disturbances signals. At the same time, different classification methods are simulated and a model which can classify PQ disturbances signals with high performance is created. Also, the generated models are analysed for their performance in terms of different noise levels (40 dB, 30 dB, 20 dB). The result of this simulation study shows that the model developed to classify PQ disturbances is superior to conventional models and other 2D signal processing methods in the literature. In addition, it was concluded that the proposed method can cope better with noisy signals by low computational complexity and higher classification rate.     

幼儿在等级图形知觉中的整体优先现象

研究采用Navon的干涉实验范式和等级图形刺激模式研究4-6岁幼儿的整体优先现象。实验中所用刺激的结构关系有一致、无关、矛盾。实验1研究自由注意条件下,不同年龄儿童自发形成整体或局部反应策略的比率,发现被试自发形成对整体特征反应策略的比例较大,且该比例是随年龄而增长的;实验2比较注意整体和注意局部两种实验条件下,不同年龄儿童对整体或局部的反应正确率。结果发现在注意整体和注意局部的条件下,4-6岁幼儿的整体／局部干涉效应呈相互影响到相互独立再到整体优势的发展过程。这表明幼儿对整体特征的注意选择可能是随着年龄增长和视觉经验的积累而逐渐成型的。     

大学新生应对方式特点的研究

目的:探讨大学新生应对方式特点。方法:采用应对方式问卷对563名大学新生进行测量。结果:大学新生以使用成熟的应对方式(解决问题、求助)为主;在幻想因子上,性别和专业的主效应显著,女生得分比男生高,文科学生得分高于理科学生得分;在自责因子上,专业主效应显著,文科学生得分高于艺术体育类学生;在求助因子上,生源地的主效应显著,城市大学新生得分高于农村学生。结论:大学新生更多地使用成熟的应对方式;女生比男生更多地使用幻想的应对方式;文科学生比艺术体育类学生更多地使用自责的应对方式;文科学生比理科生更多地使用幻想的应对方式;农村学生比城市学生更少使用求助的应对方式。