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1.
A considerable percentage of depressed patients do not respond to antidepressive treatment. Early indicators of prognosis are needed. The aims of this study are to examine (a) whether the interpersonal behavior of patients and psychiatrist, as assessed by means of direct observation of behavior during a baseline clinical interview, might have predictive value with respect to therapeutic outcome and (b) which predictive potency measures of psychomotor activation, as assessed by less refined methods, such as global clinical judgment, might have. In the analysis used, speech-pause behavior was taken as the basic structure of the interaction. The relations of other behaviors such as looking and hand and head movement with this structure were determined. Evidence is presented that in a group of 31 depressives, improvement after a period of 10 weeks was related to observed behaviors during a baseline interview. The behaviors of the patients are interpreted as relational or nonrelational. The relational behaviors (i.e., looking yesnodding, gesturing) occur less in patients who will improve, whereas the nonrelational behaviors (i.e., intensive body touching, head movements) occur more in these patients. The nonrelational behaviors are presumed to be indicative of the state of arousal. The predictive potency of these variables could not be explained by their relationship with the baseline severity of depression, which in itself also predicted improvement. Moreover, global clinical assessment of psychomotor activation (i.e., retardation and agitation) could not be related to outcome.  相似文献   
2.
The development of the ability to anticipate—as manifested by preparatory actions and neural activation related to the expectation of an upcoming stimulus—may play a key role in the ontogeny of cognitive skills more broadly. This preregistered study examined anticipatory brain potentials and behavioral responses (reaction time; RT) to anticipated target stimuli in relation to individual differences in the ability to use goals to direct action (as indexed by measures of executive function; EF). A cross-sectional investigation was conducted in 40 adults (aged 18–25 years) and 40 children (aged 6–8 years) to examine the association of changes in the amplitude of modality-specific alpha-range rhythms in the electroencephalogram (EEG) during anticipation of lateralized visual, tactile, or auditory stimuli with inter- and intraindividual variation in RT and EF. Children and adults exhibited contralateral anticipatory reductions in the mu rhythm and the visual alpha rhythm for tactile and visual anticipation, respectively, indicating modality and spatially specific attention allocation. Variability in within-subject anticipatory alpha lateralization (the difference between contralateral and ipsilateral alpha power) was related to single-trial RT. This relation was more prominent in adults than in children, and was not apparent for auditory stimuli. Multilevel models indicated that interindividual differences in anticipatory mu rhythm lateralization contributed to the significant association with variability in EF, but this was not the case for visual or auditory alpha rhythms. Exploratory microstate analyses were undertaken to cluster global field power (GFP) into a distribution-free temporal analysis examining developmental differences across samples and in relation to RT and EF. Anticipation is suggested as a developmental bridge construct connecting neuroscience, behavior, and cognition, with anticipatory EEG oscillations being discussed as quantifiable and potentially malleable indicators of stimulus prediction.  相似文献   
3.
Im Anfang des 20.Jahrhunderts unterzog eine Reihe von jungen, später berühmt gewordenen Philosophen den Marxismus einer tiefen Kritik. Ihnen ist es gelungen, wichtige Defekte der revolutionären Doktrinen aufzudecken und ihre verhängnivsollen Konsequenzen vorwegzunehmen. Diese Kritik ist auch für die gegenwärtige geistig-politische Situation aktuell.  相似文献   
4.
This essay proposes to extend the model of apocalyptic argument developedin my recent book Arguing the Apocalypse (OLeary, 1994) beyond the study ofreligious discourse, by applying this model to the debate over awell-publicized earthquake prediction that caused a widespread panic in theAmerican midwest in December, 1990. The first section of the essay willsummarize the essential elements of apocalyptic argument as I have earlierdefined them; the second section will apply the model to the case of the NewMadrid, Missouri, earthquake prediction, in order to demonstrate thatcertain patterns of reasoning characteristic of religious apocalyptic arepresent in the discourse over an anticipated local disaster. My ultimatepurpose is to show that predictions of global and local catastrophe mayserve as extreme cases that will illuminate the dynamics of predictiveargument in general. Thus my argument will seek to undercut Daniel Bellsdistinction between prophecy and prediction (Bell, 1973) by establishingthat these discourses share identifiable formal and substantivecharacteristics, and depend for their rhetorical effect on anxiety, hope,far, and excitement as modes of temporal anticipation.  相似文献   
5.
Three skills which characterize cognitive functioning in human infants in the middle of the first year of life—habituation, novelty responsiveness, and cross-modal transfer—predict mental ability in later childhood. Antecedents of each skill at 5 months postnatal were examined in a short-term prospective longitudinal study of infant ability and maternal intelligence and interaction style. Infant perceptuocognitive performance at 2 months, maternal intelligence, and maternal responsiveness at 5 months relate to the expression of the three infant cognitive skills, but in different ways. Variation in infant information-processing abilities can be explained by specific child and maternal factors that are evident soon after birth.  相似文献   
6.
Based on the test theory model for ordinal measurements proposed by Schulman and Haden, the present paper considers correlations between tests, attenuation, regressions involving true and observed scores, and prediction of test reliability.The population correlation between tests is shown to be related to the expected sample correlation for samples of sizen 1 andn 2. Errors of estimation, measurement and prediction are found to be similar to their counterparts in interval test theory, while attenuation is identical to its counterpart. The bias in estimating population reliability from sample data is compared for Kendall's tau and Spearman's rho.The author wishes to thank the referees for their helpful comments on an earlier draft of this paper, and in particular, for the suggested alternative methods of establishing some of the presented results.  相似文献   
7.
Older adults are more likely to get severely injured or die in vehicle crashes. Advanced driver-assistance systems (ADAS) can reduce their risk of crashes; however, due to the lack of knowledge and training, usage rate of these systems among older drivers is limited. The objective of this study was to evaluate the impact of two ADAS training approaches (i.e., video-based and demonstration-based training) on older drivers’ subjective and objective measures of mental workload, knowledge and trust considering drivers’ demographic information. Twenty older adults, balanced by gender, participated in a driving simulation study. Results indicated that the video-based training might be more effective for females in reducing their mental workload while driving, whereas the demonstration-based training could be more beneficial for males. There was no significant difference between the video-based and demonstration-based trainings in terms of drivers’ trust and knowledge of automation. The findings suggested that ADAS training protocols can potentially be more effective if they are tailored to specific driver demographics.  相似文献   
8.
Securing appropriate driver responses to conflicts is essential in automation that is not perfect (because the driver is needed as a fall-back for system limitations and failures). However, this is recognized as a major challenge in the human factors literature. Moreover, in-depth knowledge is lacking regarding mechanisms affecting the driver response process. The first aim of this study was to investigate how driver conflict response while using highly reliable (but not perfect) supervised automation differ for drivers that (a) crash or avoid a conflict object and (b) report high trust or low trust in automation to avoid the conflict object. The second aim was to understand the influence on the driver conflict response of two specific factors: a hands-on-wheel requirement (with vs. without), and the conflict object type (garbage bag vs. stationary vehicle). Seventy-six participants drove with highly reliable but supervised automation for 30 min on a test track. Thereafter they needed to avoid a static object that was revealed by a lead-vehicle cut-out. The driver conflict response was assessed through the response process: timepoints for driver surprise reaction, hands-on-wheel, driver steering, and driver braking. Crashers generally responded later in all actions of the response process compared to non-crashers. In fact, some crashers collided with the conflict object without even putting their hands on the wheel. Driver conflict response was independent of the hands-on-wheel requirement. High-trust drivers generally responded later than the low-trust drivers or not at all, and only high trust drivers crashed. The larger stationary vehicle triggered an earlier surprise reaction compared to the garbage bag, while hands-on-wheel and steering response were similar for the two conflict object types. To conclude, crashing is associated with a delay in all actions of the response process. In addition, driver conflict response does not change with a hands-on-wheel requirement but changes with trust-level and conflict object type. Simply holding the hands on the wheel is not sufficient to prevent collisions or elicit earlier responses. High trust in automation is associated with late response and crashing, whereas low trust is associated with appropriate driver response. A larger conflict object trigger earlier surprise reactions.  相似文献   
9.
Autonomous Vehicle (AV) research has focused on public acceptance of and intention to use AVs, with trust emerging as important to these variables. Research on AV trust has centered on trust in vehicle performance. However, trust evaluation may include AV manufacturers and developers, and regulation pertaining to AVs; thus, we expand our measurement of trust to include beliefs based on manufacturers and regulation. In this experiment, we manipulate information regarding manufacturer focus (i.e., an emphasis on standards, regulations, and research (SRR) versus speed to market) to determine its effect on trust. When information focused on SRR, we found higher levels of trust in AV performance and in manufacturers, compared to when it focused on speed to market. In addition, information regarding passenger control (i.e., the ability to take over for the vehicle and to determine privacy settings) was manipulated to yield either high or low passenger control conditions. Behavioral Intention (BI) to use AVs was lowest when speed to market was emphasized and when passenger control was low. Furthermore, trust was tested as a mediator between perceived risk and BI. Trust in AV performance partially mediated the relationship between perceived AV performance risk and BI. In addition, trust in AV regulation partially mediated the relationship between AV privacy/security risk and BI. Researchers should continue to examine trust beyond the AV itself to encompass trust in manufacturers and regulations. Those designing and marketing AVs should carefully consider decisions that influence manufacturer/developer reputation and passenger control due to their effect on intention to use AVs.  相似文献   
10.
随着高等教育规模的扩大,学业表现不良逐渐成为一个不容忽视的现象,对学业表现不良的学生进行预测并提早给予干预可降低退学率并减少教育资源的损失。由于导致学业表现不良的因素众多且关系复杂,传统的基于相关分析的研究方法很难建立早期预测模型并进行应用。本研究旨在利用机器学习算法,对数据进行挖掘,并建立学业表现预测模型。研究对653名大一新生的心理健康状况、应对方式、人格、内外控倾向和相关人口统计学信息进行了收集,并在一年后采集了其学业成绩,利用随机森林(RF)、K邻近(KNN)、支持向量机(SVM)、决策树(DT)、朴素贝叶斯(NB)等机器学习算法建立了分类模型。结果显示,随机森林算法在识别学业表现不良学生时有最好的表现,其中准确率95.86%, 召回率91.83%,f1分数为93.80%。特征重要性分析显示,前10个对模型有最高贡献度的特征包括:年龄、性别、是否为独生子、内外控倾向、神经质倾向、积极应对倾向、宜人性倾向、一般症状指数、开放性倾向和焦虑水平。为避免过度拟合问题,本研究在一年后收集的166名新生样本中进行了模型验证,结果显示模型在新数据集上有较好的泛化表现,其中f1分数90.90%,准确率92.60%,召回率89.26%。研究提示基于人口统计学和心理测评信息,机器学习算法有助于及早识别学业表现不良学生并为开展早期干预提供启示。  相似文献   
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