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In this article we apply a folk linguistic listening task to examine how the Tver' Karelians in Russia recognise a sample of their own dialect and a sample of Border Karelian (spoken in Finland), both recorded about 60 years ago. Tver' Karelian and Border Karelian have a shared origin in Proto-Karelian but have been diverging from each other since the seventeenth century; the former has had strong influence from Russian and the latter from Finnish. The study investigates the Tver' Karelians' awareness of and observations about the Karelian language and shows that they easily recognise their own dialect, whereas the Border Karelian sample is harder to recognise and describe. However, the respondents observed and described lexical and phonetic features of this sample, and two thirds of them located the sample in the republic of Karelia or in Finland, mostly based on the 'accent' of the speaker. [ABSTRACT FROM AUTHOR]

Emotional facial expressions are a crucial non-verbal communication skill for humans’ interactions. The current study assessed the impact of sex on emotional face recognition. A total of 125 individuals performed an online emotional face recognition task. The stimuli were created recutting male and female Saudi volunteers. Results showed that, except of the male participants having faster responses compared to fe-males in general, no main significant differences between the sex group in accuracy nor any significant in-teraction between participant sex and the sex of the faces. Our findings suggests that the effect of sex on emotional face recognition needs further investigation with well calibrated stimuli. Limitations and the di-rection of future research in this area were discussed. [ABSTRACT FROM AUTHOR]

Human faces convey a range of emotions and psychobiological signals that support social interactions. Multiple factors potentially mediate the facial expressions of emotions across cultures. To further determine the mechanisms underlying human emotion recognition in a complex and ecological environment, we hypothesized that both behavioral and neurophysiological measures would be influenced by stimuli ethnicity (Japanese, Caucasian) in the context of ambiguous emotional expressions (mid-happy, angry). We assessed the neurophysiological and behavioral responses of neurotypical Japanese adults (N = 27, 13 males) involved in a facial expression recognition task. Results uncover an interaction between universal and culturally-driven mechanisms. No differences in behavioral responses are found between male and female participants, male and female faces, and neutral Japanese versus Caucasian faces. However, Caucasian ambiguous emotional expressions which require more energy-consuming processing, as highlighted by neurophysiological results of the Arousal Index, were judged more accurately than Japanese ones. Additionally, a differential Frontal Asymmetry Index in neuronal activation, the signature of an approach versus avoidance response, is found in male participants according to the gender and emotional valence of the stimuli.

Developmental aspects of auditory cognition were investigated in 5‐to‐10‐year‐old children (n = 100). Musical and verbal short‐term memory (STM) were assessed by means of delayed matching‐to‐sample tasks (DMST) (comparison of two four‐item sequences separated by a silent retention delay), with two levels of difficulty. For musical and verbal materials, children's performance increased from 5 years to about 7 years of age, then remained stable up to 10 years of age, with performance remaining inferior to performance of young adults. Children and adults performed better with verbal material than with musical material. To investigate auditory cognition beyond STM, we assessed speech‐in‐noise perception with a four‐alternative forced‐choice task with two conditions of phonological difficulty and two levels of cocktail‐party noise intensity. Partial correlations, factoring out the effect of age, showed a significant link between musical STM and speech‐in‐noise perception in the condition with increased noise intensity. Our findings reveal that auditory STM improves over development with a critical phase around 6–7 years of age, yet these abilities appear to be still immature at 10 years. Musical and verbal STM might in particular share procedural and serial order processes. Furthermore, musical STM and the ability to perceive relevant speech signals in cocktail‐party noise might rely on shared cognitive resources, possibly related to pitch encoding. To the best of our knowledge, this is the first time that auditory STM is assessed with the same paradigm for musical and verbal material during childhood, providing perspectives regarding diagnosis and remediation in developmental learning disorders. [ABSTRACT FROM AUTHOR]

In this study, the authors are interested in building a unified deep learning framework to solve the recognition problem of both single‐line and double‐line car license plates. Most existing methods are designed for single‐line license plate recognition. For double‐line cases, detection and segmentation are usually adopted firstly to locate each line of characters. These methods are usually environmentally sensitive and will bring propagation of error between segmentation and recognition. To solve the problems, the authors propose a unified method that can recognise both single‐line and double‐line license plates in an end‐to‐end way without line segmentation and character segmentation. Specifically, an improved lightweight convolutional neural network is used to extract features efficiently. Then, the multi‐task learning strategy is used to simultaneously perform license plate classification and character recognition. Finally, recognition task is treated as sequence labelling problems, which are solved by connectionist temporal classification directly. Experimental results indicate that the proposed method significantly outperforms the previous state‐of‐the‐art methods on both public datasets and the synthetic dataset. [ABSTRACT FROM AUTHOR]

For the past 140 years, numerous studies have been conducted to examine minimum durations of samples needed for the recognition of acoustic parameters such as pitch, timbre or vocal phonemes. Recent studies in this field are often based on short clips (plinks) of popular songs, using target variables such as titles and interpreters. These studies provide strong evidence that a wide range of intra- and extramusical information can be identified above chance level for stimuli lasting much shorter than a second. Nevertheless, a review of precedent studies revealed a heterogeneity in stimulus generation processes that could have influenced overall recognition rates. As a piece of music unfolds in time, its timbral structure is subject to a variety of changes. We assume that the position of stimulus extraction, therefore, could influence the outcomes of a subsequent recognition task, for instance. In this study, we offer a systematic and objective stimulus extraction procedure that might help to control for (a) a possible confounding of stimulus duration and timbre (caused by the extraction of stimulus sets of various length from different song positions), (b) possible confoundings of song section and timbre (caused by the comparison of stimulus sets from divergent song sections), and (c) the suspected influence of subjective criteria on extract selection (caused by the non-randomized selection of extract positions). As an alternative approach, the suggested Matryoshka principle produces randomized sets of nested stimuli controlled for song position and objective selection. Each set represents an individual section and consists of five short excerpts, cut from each other in decreasing duration. Correlation analyses confirmed that these sets prove to be stable in terms of their mel-frequency cepstrum coefficients, the so-called "psycho-acoustic fingerprint" of a sound. Based on the software Random Plink Generator, the suggested procedure can help to contribute to an objective selection of stimuli in future plink research. [ABSTRACT FROM AUTHOR]

Segmentation of handwritten words into isolated characters and their recognition are challenging due to the presence of high variability and cursiveness in Indian scripts. The complex shapes and availability of numerous atomic character classes, compound characters, modifiers, ascendants, and descendants make the recognition task even more difficult. A holistic approach effectively tackles such issues by avoiding the character‐level segmentation and the earlier holistic methods have been mostly developed using multi‐stage machine learning architecture. In this study, a deep convolutional neural network‐based holistic method termed 'H‐WordNet' is proposed for handwritten word recognition. The H‐WordNet model includes merely four convolutional layers and one fully connected layer to effectively classify the word images', which lead to a significant reduction in parameters. The efficacy of different pooling operations with the proposed model is investigated. The main purpose of this study is to avoid the need for handcrafted feature extraction and obtain a more stable and generalised system for word recognition. The proposed model is evaluated using a standard handwritten Bangla word database (CMATERdb2.1.2), which contains 18000 Bangla word images of 120 different categories and it obtained a higher recognition accuracy of 96.17% when compared to recent state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

Automatic targets recognition (ATR) for synthetic aperture radar (SAR) image is very important. ATR can be used in traffic management, national frontier safety, and so on. Traditional algorithms for SAR ATR is composed of extraction features and training classifier. The features are essential for the classification accuracy. However, choosing good features by hand is a hard task. The deep convolutional neural networks (CNNs) which can learn features automatically have got a great performance in natural images. However, the CNNs have many parameters and need a lot of data to train such networks. The remote-sensing data of SAR is limited. Then, the authors need a simple network which needs not much data and easy to train. The principal component analysis network (PCANet) is a shallow network that performs well in the recognition task and needs no hand features choosing. Though this network has produced a wide application in the natural images, it is rarely used in the SAR images. The experimental result of the moving and stationary target acquisition and recognition (MSTAR) dataset shows that the PCANet can achieve over 99% accuracy on ten-class targets. This result is better than traditional algorithms and is very close to the results of deep-learning methods.

Automatic targets recognition (ATR) for synthetic aperture radar (SAR) image is very important. ATR can be used in traffic management, national frontier safety, and so on. Traditional algorithms for SAR ATR is composed of extraction features and training classifier. The features are essential for the classification accuracy. However, choosing good features by hand is a hard task. The deep convolutional neural networks (CNNs) which can learn features automatically have got a great performance in natural images. However, the CNNs have many parameters and need a lot of data to train such networks. The remote-sensing data of SAR is limited. Then, the authors need a simple network which needs not much data and easy to train. The principal component analysis network (PCANet) is a shallow network that performs well in the recognition task and needs no hand features choosing. Though this network has produced a wide application in the natural images, it is rarely used in the SAR images. The experimental result of the moving and stationary target acquisition and recognition (MSTAR) dataset shows that the PCANet can achieve over 99% accuracy on ten-class targets. This result is better than traditional algorithms and is very close to the results of deep-learning methods. [ABSTRACT FROM AUTHOR]

In this paper, we propose a regularized point-to-manifold distance metric to measure the distance between the unknown query object and object-specific manifolds for the task multi-view multi-manifold learning. Our metric determine the class of query object based on the class of objects that have smallest average geodesic distance from it. To do this, we propose our proposed method with the two features: 1. We automatically discover the object-specific manifolds. In this section, we focus on the fundamental problem of efficiently selecting a uniform class-consistent neighbors from all available poses for graph-based multi-manifold learning methods in a supervised manner. Also, we extract the most distinctive exemplars from the manifold of each object that cover the possible variations on pose angles. To make a distinction between some object-specific pose-inconsistent and object-inconsistent pose-consistent that may be very close, we utilize the total variation regularized least squares problem to representing each object in a weighted sum of its class-consistent neighbors under different poses. 2. We use the information of k objects to decide about the class of query object. We measure the distance between the unknown object and k exemplars of each object-specific manifold to find the closest manifold as the class of query object. Numerical experiments on several benchmark multi-view datasets are reported, which provide excellent support to the proposed methods. In the mean, our neighborhood graph can improve the SH-NGC and UTDTV, as new supervised multi-manifold learning and unsupervised multi-view multi-manifold learning methods, more than 2.6 and 7%, respectively. Also, in object recognition, our proposed method achieves more than 5% better results respect to the best result of state-of-the-art graph-based manifold learning methods. [ABSTRACT FROM AUTHOR]

The task of face recognition in real‐world scenarios is still a challenging one. There exist many techniques for the recognition of faces in videos. The recognition task may be computationally easier, but is susceptible to pose variations, lighting conditions etc. This paper focuses on recognition of faces from multi‐view videos using the combination of particle filtering with Immune Genetic Algorithm (IGA) and HSH, which is insensitive to pose variations. Particle filtering along with the IGA efficiently track the target using immune system mechanism and then the recognition phases are carried out using HSH. For recognition of video, the ensemble feature similarity calculated which can be measured with the limiting Bhattacharyya distance of features in the Reproducing Kernel Hilbert space. The proposed system with HSH provides better performance than using Spherical Harmonics (SH) for recognising the face of the target and the performance are analysed with existing techniques for recognition of face. [ABSTRACT FROM AUTHOR]

Challenges in the development of a multi-level memory (MM) device for multinary arithmetic computers have posed an obstacle to low-power, ultra-high-speed operation. For the effective transfer of a huge amount of data between arithmetic and storage devices, optical communication technology represents a compelling solution. Here, by replicating a floating gate architecture with CdSe/ZnS type-I core/shell quantum dots (QDs), a 2D-0D hybrid optical multi-level memory (OMM) device operated is demonstrated by laser pulses. In the device, laser pulses create linear optically trapped currents with MM characteristics, while conversely, voltage pulses reset all the trapped currents at once. Assuming electron transfer via the energy band alignment between MoS 2 and CdSe, the study also establishes the mechanism of the OMM effect. Analysis of the designed device led to a new hypothesis that charge transfer is difficult for laterally adjacent QDs facing a double ZnS shell, which is tested by separately stimulating different positions on the 2D-0D hybrid structure with finely focused laser pulses. Results indicate that each laser pulse induced independent MM characteristics in the 2D-0D hybrid architecture. Based on this phenomenon, we propose a MM inverter to produce MM effects, such as programming and erasing, solely through the use of laser pulses. Finally, the feasibility of a fully optically-controlled intelligent system based on the proposed OMM inverters is evaluated through a CIFAR-10 pattern recognition task using a convolutional neural network., (© 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH.)

Images, audio, and videos have been used by researchers for a long time to develop several tasks regarding human facial recognition and emotion detection. Most of the available datasets usually focus on either static expression, a short video of changing emotion from neutral to peak emotion, or difference in sounds to detect the current emotion of a person. Moreover, the common datasets were collected and processed in the United States (US) or Europe, and only several datasets were originated from Asia. In this paper, we present our effort to create a unique dataset that can fill in the gap by currently available datasets. At the time of writing, our datasets contain 10 full HD (1920)1080) video clips with annotated JSON file, which is in total 100 minutes of duration and the total size of 13 GB. We believe this dataset will be useful as a training and benchmark data for a variety of research topics regarding human facial and emotion recognition. [ABSTRACT FROM AUTHOR]

Differences in pupil dilation are observed for studied compared to new items in recognition memory. According to cognitive load theory, this effect reflects the greater cognitive demands of retrieving contextual information from study phase. Pupil dilation can also occur when new items conceptually related to old ones are erroneously recognized as old, but the aspects of similarity that modulate false memory and related pupil responses remain unclear. We investigated this issue by manipulating the degree of featural similarity between new (unstudied) and old (studied) concepts in an old/new recognition task. We found that new concepts with high similarity were mistakenly identified as old and had greater pupil dilation than those with low similarity, suggesting that pupil dilation reflects the strength of evidence on which recognition judgments are based and, importantly, greater locus coeruleus and prefrontal activity determined by the higher degree of retrieval monitoring involved in recognizing these items. [ABSTRACT FROM AUTHOR]

Many different human spatial memory tasks were developed in the last two decades. Virtual reality based tasks make possible developing different scenarios and situations to assess spatial orientation but sometimes these tasks are complex for specific populations like children and older-adults. A new spatial task with a very limited technological requirement was developed in this study. It demanded the use of spatial memory for an accurate solution. It also proved to be sensitive to gender differences, with men outperforming women under high specific difficulty levels. Thanks to its simplicity it could be applied as a screening test and is easy to combine with EEG and fMRI studies. [ABSTRACT FROM AUTHOR]

Objective To examine the effects of an acute bout of exercise on attentional bias, mood, and memory in young adult females who differ in anxiety. Methods Sixty-four participants between the ages of 18–34 years completed two experiments involving tests of attentional bias, mood, and memory before and after a cycling protocol or seated rest control condition. Participants were categorized into low-trait anxious (n = 29) or high-trait anxious (n = 35) groups and randomly allocated to experimental conditions. For both experiments, participants completed the assessments before and following 20 min of moderate intensity exercise or seated rest. Experiment 1 examined word-based attentional bias, while Experiment 2 utilized picture-based attentional bias tests. Results Acute moderate exercise did not alter word-based attentional bias. Exercise decreased picture-based attentional bias, but failed to reach statistical significance (p = 0.057). Enhancements in participants' mood post-exercise were observed; effects of exercise on memory were inconsistent. Conclusion The effects of acute exercise on attentional bias seems to depend on stimulus type. Results suggest that exercise has a greater impact on picture-based attentional bias pre- to post-exercise (Experiment 2) compared to word-based attentional bias (Experiment 1). Moderate intensity exercise improves measures of total mood disturbance, anger, confusion, state anxiety, vigor and tension. This suggests that exercise may have a greater impact on subjective mood measures compared to the attentional processes associated with anxiety. [ABSTRACT FROM AUTHOR]

Embodied approaches of cognition argue that retrieval involves the re-enactment of both sensory and motor components of the desired remembering. In this study, we investigated the effect of motor action performed to produce the response in a recognition task when this action is compatible with the affordance of the objects that have to be recognised. In our experiment, participants were first asked to learn a list of words referring to graspable objects, and then told to make recognition judgements on pictures. The pictures represented objects where the graspable part was either pointing to the same or to the opposite side of the 'Yes' response key. Results show a robust effect of compatibility between objects affordance and response hand. Moreover, this compatibility improves participants' ability of discrimination, suggesting that motor components are relevant cue for memory judgement at the stage of retrieval in a recognition task. More broadly, our data highlight that memory judgements are a function of motor components mappings at the stage of retrieval. [ABSTRACT FROM AUTHOR]

The validity of learning styles needs supports of additional objective evidence. The identification of learning styles using subjective evidence from VARK questionnaires (where V is visual, A is auditory, R is read/write, and K is kinesthetic) combined with objective evidence from visual event-related potential (vERP) studies has never been investigated. It is questionable whether picture superiority effects exist in V learners and R learners. Thus, the present study aimed to investigate whether vERP could show the relationship between vERP components and VARK learning styles and to identify the existence of picture superiority effects in V learners and R learners. Thirty medical students (15 V learners and 15 R learners) performed recognition tasks with vERP and an intermediate-term memory (ITM) test. The results of within-group comparisons showed that pictures elicited larger P200 amplitudes than words at the occipital 2 site (P < 0.05) in V learners and at the occipital 1 and 2 sites (P < 0.05) in R learners. The between-groups comparison showed that P200 amplitudes elicited by pictures in V learners were larger than those of R learners at the parietal 4 site (P < 0.05). The ITM test result showed that a picture set showed distinctively more correct responses than that of a word set for both V learners (P < 0.001) and R learners (P < 0.01). In conclusion, the result indicated that the P200 amplitude at the parietal 4 site could be used to objectively distinguish V learners from R learners. A lateralization existed to the right brain (occipital 2 site) in V learners. The ITM test demonstrated the existence of picture superiority effects in both learners. The results revealed the first objective electrophysiological evidence partially supporting the validity of the subjective psychological VARK questionnaire study. [ABSTRACT FROM AUTHOR]

Objective: To examine whether a 2-week attribution modification training (AMT) changes symptom severity, emotional evaluation of health-threatening stimuli, and cognitive biases in pathological health anxiety. Method: We randomized 85 patients with pathological health anxiety into an electronic diary-based AMT group (AMTG; n = 42) and a control group without AMT (CG; n = 43). Self-report symptom measures, emotional evaluation, attentional bias, and memory bias toward symptom and illness words were assessed with an emotional Stroop task, a recognition task, and an emotional rating task for valence and arousal. Results: After the 2-week period, the AMTG compared with the CG reported lower symptoms of pathological health anxiety, F(l, 82) = 10.94, p < .01, ηp²= .12, rated symptom, f(1, 82) = 5.56, p = .02, ηp² = .06, and illness words, F(1, 82) = 4.13, p = .045, ηp² = .05, as less arousing, and revealed a smaller memory response bias toward symptom words in the recognition task F(1, 82) = 12.32, p < .01, ηp² = .13. However, no specific AMT effect was observed for the attentional bias. Conclusion: The results support the efficacy of a comparatively short cognitive intervention in pathological health anxiety as a possible add-on intervention to existing treatment approaches to reduce symptom severity, as well as abnormalities in health-related emotional evaluation and memory processes. [ABSTRACT FROM AUTHOR]

The present study aimed to clarify the role played by the eye/brow and mouth areas in the recognition of the six basic emotions. In Experiment 1, accuracy was examined while participants viewed partial and full facial expressions; in Experiment 2, participants viewed full facial expressions while their eye movements were recorded. Recognition rates were consistent with previous research: happiness was highest and fear was lowest. The mouth and eye/brow areas were not equally important for the recognition of all emotions. More precisely, while the mouth was revealed to be important in the recognition of happiness and the eye/brow area of sadness, results are not as consistent for the other emotions. In Experiment 2, consistent with previous studies, the eyes/brows were fixated for longer periods than the mouth for all emotions. Again, variations occurred as a function of the emotions, the mouth having an important role in happiness and the eyes/brows in sadness. The general pattern of results for the other four emotions was inconsistent between the experiments as well as across different measures. The complexity of the results suggests that the recognition process of emotional facial expressions cannot be reduced to a simple feature processing or holistic processing for all emotions. [ABSTRACT FROM AUTHOR]

The production effect refers to a memory advantage for items studied aloud over items studied silently. Ozubko and MacLeod (2010) used a list-discrimination task to support a distinctiveness account of the production effect over a strength account. We report new findings in this task--including negative production effects--that better fit with an attributional account of this task. According to the attributional account, list judgments are influenced by recognition memory, knowledge of the composition of the 2 lists, and a bias to attribute non-recognized items to the 1st list. Using a recognition task to eliminate these attributional influences revealed production effects consistent with either a distinctiveness or strength account. In our discussion, we consider whether the absence of production effects on implicit-memory tests and in between-group designs provides unequivocal support for a distinctiveness account over a strength account. [ABSTRACT FROM AUTHOR]

Tests of the theory of morphic resonance have tended to confirm the theory''s predictions but are difficult to evaluate since they are typically reported in popular accounts rather than more detailed peer-reviewed journal papers. We replicated earlier work using word-based stimuli in a study that also looked at the effects of transliminality on performance. Sixty participants were exposed to five genuine Chinese characters and five false characters. Subsequently, participants identified the characters they could recognize among a sheet consisting of those originally presented intermixed with 10 decoys. As predicted, participants accurately recognized more of the genuine than false characters, t(59)= 2.40, P = .020, but also were more likely to report false memories for genuine than false characters, t(59)= 3.805, P < .001. Transliminality scores were related to performance with presented characters (r = .38; P = .003) but not with decoy characters (r = .14, P = .28). [Copyright &y& Elsevier]

Chess experts store domain-specific representations in their long-term memory; due to the activation of such representations, they perform with high accuracy in tasks that require the maintenance of previously seen information. Chunk-based theories of expertise (chunking theory: Chase & Simon, 1973; template theory: Gobet & Simon, 1996) state that expertise is acquired mainly by the acquisition and storage in long-term memory of familiar chunks that allow quick recognition. This study tested some predictions of these theories by using fMRI while chessplayers performed a recognition memory task. These theories predict that chessplayers access long-term memory chunks of domain-specific information, which are presumably stored in the temporal lobes. It was also predicted that the recognition memory tasks would activate working memory areas in the frontal and parietal lobes. These predictions were supported by the data. [ABSTRACT FROM AUTHOR]

Abstract: Implicit and explicit memory processes for panic-relevant and neutral word stimuli were examined in 16 panic patients and 16 healthy participants matched for sex, age, and education, using behavioral and electrophysiological measures. In the study phase, panic-relevant and neutral words were presented and the level of processing was varied by requiring either shallow (orthographic) or deeper (syntactic) processing. Implicit memory was tested with a lexical decision task, explicit memory with a recognition task. Panic patients and healthy participants did not differ in behavioral (response time) or event-related brain potential (ERP) measures of implicit memory. However, panic patients deviated from healthy participants in the recognition test, an explicit memory test. Although recognition of panic words was overall worse compared to neutral words, panic patients compared to healthy participants exhibited enhanced discrimination scores and faster reaction times for panic words. The level of processing manipulation had comparable effects on patients and healthy participants. While neither behavioral nor electrophysiological measures provided evidence for an implicit memory bias in panic patients, behavioral measures confirmed an explicit memory bias in panic patients for panic-relevant stimuli. [Copyright &y& Elsevier]

• Novel tactile recognition is a vibrissae dependent activity • High-fat diet impairs tactile recognition memory in mice • High-fat diet does not impair whisker sensitivity in mice Research on the impact of diet and memory has garnered considerable attention while exploring the link between obesity and cognitive impairment. High-fat diet (HFD) rodent models recapitulate the obesity phenotype and subsequent cognitive impairments. While it is known that HFD is associated with sensory impairment, little attention has been given to the potential role these sensory deficits may play in recognition memory testing, one of the most commonly used cognitive tests. Because mice utilize their facial whiskers as their primary sensory apparatus, we modified a common recognition test, the novel object recognition task, by replacing objects with sandpaper grits at ground level, herein referred to as the novel tactile recognition task (NTR). First, we tested whisker-manipulated mice in this task to determine its reliance on intact whiskers. Then, we tested the HFD mouse in the NTR. Finally, to ensure that deficits in the NTR are due to cognitive impairment and not HFD-induced sensory deficiencies, we tested the whisker sensitivity of HFD mice via the corner test. Our results indicate that the NTR is a whisker dependent task, and that HFD mice exhibit tactile recognition memory impairment, not accompanied by whisker sensory deficits. [ABSTRACT FROM AUTHOR]