Marcia K. Johnson: 2006 Award for Distinguished Scientific Contributions.

Presents the citation to Marcia K. Johnson, who received the Award for Distinguished Scientific Contributions "for raising and illuminating fundamental questions about the cognitive and neural processes that constitute the subjective experience of mental life." A brief profile and a selected bibliography, as well as Johnson's award address, entitled Memory and Reality (see record 2006-21079-028), accompany the citation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

La capacité d'imitation à la naissance: Elle existe, mais que signifie-t-elle?

Much of the research on early imitations is restricted to the problem of their existence, without trying to describe them. The aim of this research is to analyze the principal characteristics of neonatal imitations in order to differentiate them from the later imitations. The behaviours of 16 neonates were filmed. A facial and a manual model were used. A detailed analysis of newborn behaviour revealed several features of early imitations: They were selective, quite exact, integrated, and occurred with short-time latencies. These results are interpreted within a cognitive framework. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Using what we know: Consequences of intentionally retrieving gist versus item-specific information.

The effect of a prior gist-based versus item-specific retrieval orientation on recognition of objects and words was examined. Prior item-specific retrieval increased item-specific recognition of episodically related but not previously tested objects relative to both conceptual- and perceptual-gist retrieval. An item-specific retrieval advantage also was found when the stimuli were words (synonyms) rather than objects but not when participants overtly named objects during gist-based recognition testing, which suggests that they did not always label objects under general gist-retrieval instructions. Unlike verbal overshadowing, labeling objects during recognition attenuated (but did not eliminate) test- and interference-related forgetting. A full understanding of how retrieval affects subsequent memory, even for events or facts that are not themselves retrieved, must take into account the specificity with which that retrieval occurs. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Waveform design and high-resolution imaging of cognitive radar based on compressive sensing

We introduce the compressive sensing(CS) theory for waveform design of cognitive radar,and then propose an algorithm for the high-resolution radar signal waveform and its corresponding imaging method based on the sparse orthogonal frequency division multiplexing-linear frequency modulation(OFDM-LFM) signal.We first present the principle of spectrum synthesis and high-resolution imaging based on OFDM-LFM signals.Then,we propose the spectrum-sparse waveform design criterion and the reconstruction algorithm for a highresolution range profile(HRRP) based on CS.Based on this,we analyze in detail the relationship between the scattering characteristics of the target and the parameters of the designed signal,and we construct the feedback of the target characteristics on the waveforms.Therefore,the "cognitive" function of radar can be achieved by adaptively adjusting the waveform with the target characteristics.Simulations are given to validate the effectiveness of the proposed algorithm.     

高校信息公开与保密工作的创新思考

随着高校推行信息公开,如何管理涉密信息成为信息公开的一个重要环节。因此,怎样正确处理好高校信息公开与保密的关系,既全面推行信息公开,又保障国家秘密是高校当前的一个十分紧迫而重要的两难问题。     

认知定位系统的自适应精度研究

为了能够实现定位精度的自适应,本文分析了认知无线电定位系统(cognitive positioning systems,CPS)的原理。该系统利用频谱及环境感知等模块中的传感器单元来获取所需的定位参数,并将其与到达时间(time of arrival,TOA)定位估计算法相结合,以克拉美罗下界(Cramer-Rao lower bound,CRLB)为准则分析最大似然(maximum likelihood,ML)定位精度自适应算法。本文还对单径和多径环境条件下定位精度自适应性能进行了比较。仿真结果表明,该算法能够实现定位精度的自适应,并能通过改善系统可用的频带带宽、分散频谱的数目、信号的调制方式等因素来提高定位精度。     

认知无线电技术在ZigBee中的应用研究

目前多种无线通信技术共享2．4GHzISM频段,它们之间的相互干扰以及频谱重叠现象已成为人们非常关注的一个问题。文中将认知无线电技术应用到ZigBee网络通信中,针对2．4GHz频段,利用认知无线电的频谱感知功能,对信道状态进行检测,搜寻频谱空穴,并且对频谱进行长期感知和统计,使ZigBee用户选择最可能空闲的频段作为传输信道,同时提出了一个2．4GHz无线环境感知模型。该方法提高了ISM频段的频谱利用率,并且减少了同频段其他多种无线通信技术对ZigBee产生的干扰,保证了ZigBee信号的有效传输。     

A novel method for the classification of Alzheimer's disease from normal controls using magnetic resonance imaging

Alzheimer's disease (AD) is the most prevalent form of dementia. Although fewer people, who suffer from AD are correctly and promptly diagnosed, due to a lack of knowledge of its cause and unavailability of treatment, AD is more manageable if the symptoms of mild cognitive impairment (MCI) are in an early stage. In recent years, computer‐aided diagnosis has been widely used for the diagnosis of AD. The main motive of this paper is to improve the classification and prediction accuracy of AD. In this paper, a novel approach is developed to classify MCI, normal control (NC), and AD using structural magnetic resonance imaging (sMRI) from the Alzheimer's disease Neuroimaging Initiative (ADNI) dataset (50 AD, 50 NC, 50 MCI subjects). FreeSurfer is used to process these MRI data and obtain cortical features such as volume, surface area, thickness, white matter (WM), and intrinsic curvature of the brain regions. These features are modified by normalizing each cortical region's features using the absolute maximum value of that region's features from all subjects in each group of MCI, NC, and AD independently. A total of 420 features are obtained. To address the curse of dimensionality, the obtained features are reduced to 30 features using a sequential feature selection technique. Three classifiers, namely the twin support vector machine (TSVM), least squares TSVM (LSTSVM), and robust energy‐based least squares TSVM (RELS‐TSVM), are used to evaluate the classification accuracy from the obtained features. Five‐fold and 10‐fold cross‐validation are used to validate the proposed method. Experimental results show an accuracy of 100% for the studied database. The proposed approach is innovative due to its higher classification accuracy compared to methods in the existing literature.     

Micro-persistence and difficulty in a game-based learning environment for computational thinking acquisition

Persistence has been identified as a crucial quality of learning. However, it is hard to attain in online game-based environments as the drive to progress in the game may influence the ability to achieve the learning goals. This study aimed to examine the associations between micro-persistence, that is, the tendency to complete an individual task successfully, and task difficulty while acquiring computational thinking (CT). We further explored whether contextual or personal attributes better explain micro-persistence. We analysed data of 111 school students who used the CodeMonkey platform. We took a learning analytics approach for analysing the platform's log files. We found that micro-persistence is associated with task difficulty and that students who demonstrated an aptitude to learn new material are motivated to achieve the best solution. We also found that contextual variables better-explained micro-persistence than personal attributes. Encouraging micro-persistence can improve CT acquisition and the learning processes involved.