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161.
    
ABSTRACT

The field of cognition and emotion has grown considerably over the past 30 years, with an increased emphasis on the relationships between emotional and motivational components and how they contribute to basic perceptual, cognitive, and neural processes. For instance, research has revealed that emotion often influences these processes via emotion’s relationship with motivational dimensions, as when positive emotions low versus high in approach motivational intensity have different influences on attentional and other cognitive processes. Research has also revealed that motivational direction (approach vs. withdrawal) and affective valence (positive vs. negative) are not as closely related as once was theorised; that is, positive affect is not inevitably associated with approach motivation and negative affect is not inevitably associated with withdrawal motivation. These and other lines of research with anger have suggested that the field needs to move beyond a focus on affective valence and it needs to consider an integration of dimensional and discrete models of emotion. The article also includes some suggestions for improving methods of measuring and inducing emotions and some recommendations for future researchers.  相似文献   
162.
    
The development in the interface of smart devices has lead to voice interactive systems. An additional step in this direction is to enable the devices to recognize the speaker. But this is a challenging task because the interaction involves short duration speech utterances. The traditional Gaussian mixture models (GMM) based systems have achieved satisfactory results for speaker recognition only when the speech lengths are sufficiently long. The current state-of-the-art method utilizes i-vector based approach using a GMM based universal background model (GMM-UBM). It prepares an i-vector speaker model from a speaker’s enrollment data and uses it to recognize any new test speech. In this work, we propose a multi-model i-vector system for short speech lengths. We use an open database THUYG-20 for the analysis and development of short speech speaker verification and identification system. By using an optimum set of mel-frequency cepstrum coefficients (MFCC) based features we are able to achieve an equal error rate (EER) of 3.21% as compared to the previous benchmark score of EER 4.01% on the THUYG-20 database. Experiments are conducted for speech lengths as short as 0.25 s and the results are presented. The proposed method shows improvement as compared to the current i-vector based approach for shorter speech lengths. We are able to achieve improvement of around 28% even for 0.25 s speech samples. We also prepared and tested the proposed approach on our own database with 2500 speech recordings in English language consisting of actual short speech commands used in any voice interactive system.  相似文献   
163.
    
This study compared the ability of seven statistical models to distinguish between linked and unlinked crimes. The seven models utilised geographical, temporal, and modus operandi information relating to residential burglaries (n = 180), commercial robberies, (n = 118), and car thefts (n = 376). Model performance was assessed using receiver operating characteristic analysis and by examining the success with which the seven models could successfully prioritise linked over unlinked crimes. The regression‐based and probabilistic models achieved comparable accuracy and were generally more accurate than the tree‐based models tested in this study. The Logistic algorithm achieved the highest area under the curve (AUC) for residential burglary (AUC = 0.903) and commercial robbery (AUC = 0.830) and the SimpleLogistic algorithm achieving the highest for car theft (AUC = 0.820). The findings also indicated that discrimination accuracy is maximised (in some situations) if behavioural domains are utilised rather than individual crime scene behaviours and that the AUC should not be used as the sole measure of accuracy in behavioural crime linkage research.  相似文献   
164.
    
Blended Cognitive Behaviour Therapy (bCBT) is a new form of treatment, mixing internet-based modules and face-to-face therapist sessions. How participants rate the therapeutic alliance in bCBT has not yet been thoroughly explored, and neither is it clear whether therapist- and patient-rated alliances are predictors of change in depression during treatment. Depression and alliance ratings from 73 participants in a treatment study on bCBT (part of the E-COMPARED project) were analysed using growth curve models. Alliance, as rated by both patients and therapists, was high. The therapist-rated working alliance was predictive of subsequent changes in depression scores during treatment, whereas the patient-rated alliance was not. A therapeutic alliance can be established in bCBT. The role of the therapist-rated alliance seems to be of particular importance and should be carefully considered when collecting data in future studies on bCBT.  相似文献   
165.
    
ABSTRACT

Each individual possesses character strengths, the most significant of which are classified as signature strengths. With a sample of 164 individuals who were employed at least part-time in a variety of industries, we examined application of signature strengths and well-being both between-persons (global) and within-persons (daily). Global application of signature strengths was associated with global job satisfaction and strain; however, no significant mediation effects on intent to turnover were found. We also found that daily variations in application of signature strengths were related to daily job satisfaction and strain. Common method bias associated with trait positive and negative affect differed by level of analysis: At the between-person (global) level, trait affect produced substantial inflation of estimates, but at the within-person (daily) level, inflation was negligible. The results suggest the importance of daily opportunities to apply signature strengths and of accounting for variance attributable to trait affect in between-person analyses.  相似文献   
166.
Personality development in emerging adults who do not attend college after high school has been largely overlooked so far. In this study, we investigated personality development in emerging German adults (NT1 = 1,886, MageT1 = 18.01 years, 29% female) undergoing vocational education and training (VET). The trainees were assessed at the start of VET, 1.5 years later, and another 1.5 years after that, just before graduation. Longitudinal latent change score analyses were applied. Bivariate analyses investigated life satisfaction and job strain as social and work‐related aspects that are potentially reciprocally related to personality development. Mean‐level personality changes included increases in neuroticism and decreases in agreeableness and conscientiousness in the first interval. In the second interval, neuroticism decreased and conscientiousness increased. Simultaneously, trainees reported a gradual decrease in extraversion and openness across the 3‐year time span. Personality, especially agreeableness and conscientiousness, emerged as a stronger predictor of changes in job strain and life satisfaction than vice versa. For example, more agreeable and more conscientious trainees subsequently showed increases in life satisfaction. Trainees reporting higher job strain subsequently showed decreases in agreeableness. Trajectories of personality development partly support the maturity principle that has been established in many college student samples.  相似文献   
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168.
    
Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance.  相似文献   
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170.
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