Perceptual Abilities Research Articles

A multi-stage approach for desired part grasping under complex backgrounds in human-robot collaborative assembly

Human-robot collaborative assembly can leverage the unique capabilities of humans and robots to provide a flexible and efficient way for complex tasks. In this context, robots are expected to be endowed with the perception ability to collaborate with humans. For flexible processes, robotic grasping for a desired assembly part from variable multi-parts is essential but remains challenging, especially in situations of complex backgrounds including disordered placement, occlusion, similarity, and large-scale differences in size. To improve the perception and decision-making abilities of robots in collaborative assembly, firstly, a multi-stage approach integrating 2D part recognition and 6D pose estimation with perspective-focusing is proposed for desired part grasping under complex backgrounds. Secondly, to efficiently and accurately recognize a desired part from variable multi-parts under complex backgrounds, based on RGB data, an enhanced detector is adopted, which lays the foundation for the subsequent pose estimation. Thirdly, based on point cloud data, a pose estimation method based on perspective-focusing is proposed to enhance the success rate and efficiency of pose acquisition. Additionally, a modular autonomous robotic grasping system is designed. Finally, taking decelerator assembly as a case, the proposed approaches are comprehensively validated and compared on a real collaborative robot platform. Under complex backgrounds with occlusion, our approach shows stable performance with an average grasping success rate of 90.0 % and an average cycle time of 6.4175 s. Our work is expected to improve robots’ perception and decision-making capabilities while further reducing the cycle time of collaborative assembly tasks.

Musical Sophistication and Multilingualism: Effects on Arcuate Fasciculus Characteristics.

The processing of auditory stimuli which are structured in time is thought to involve the arcuate fasciculus, the white matter tract which connects the temporal cortex and the inferior frontal gyrus. Research has indicated effects of both musical and language experience on the structural characteristics of the arcuate fasciculus. Here, we investigated in a sample of n = 84 young adults whether continuous conceptualizations of musical and multilingual experience related to structural characteristics of the arcuate fasciculus, measured using diffusion tensor imaging. Probabilistic tractography was used to identify the dorsal and ventral parts of the white matter tract. Linear regressions indicated that different aspects of musical sophistication related to the arcuate fasciculus' volume (emotional engagement with music), volumetric asymmetry (musical training and music perceptual abilities), and fractional anisotropy (music perceptual abilities). Our conceptualization of multilingual experience, accounting for participants' proficiency in reading, writing, understanding, and speaking different languages, was not related to the structural characteristics of the arcuate fasciculus. We discuss our results in the context of other research on hemispheric specializations and a dual-stream model of auditory processing.

Musical Expertise Influences the Processing of Short and Long Auditory Time Intervals: An Electroencephalography Study.

Musical expertise has been proven to be beneficial for time perception abilities, with musicians outperforming nonmusicians in several explicit timing tasks. However, it is unclear how musical expertise impacts implicit time perception. Twenty nonmusicians and 15 expert musicians participated in an EEG recording during a passive auditory oddball paradigm with 0.8- and 1.6-sec standard time intervals and deviant intervals that were either played earlier or delayed relative to the standard interval. We first confirmed that, as was the case for nonmusicians, musicians use different neurofunctional processes to support the perception of short (below 1.2 sec) and long (above 1.2 sec) time intervals: Whereas deviance detection for long intervals elicited a N1 component, P2 was associated with deviance detection for short time intervals. Interestingly, musicians did not elicit a contingent negative variation (CNV) for longer intervals but show additional components of deviance detection such as (i) an attention-related N1 component, even for deviants occurring during short intervals; (ii) a N2 component for above and below 1.2-sec deviance detection, and (iii) a P2 component for above 1.2-sec deviance detection. We propose that the N2 component is a marker of explicit deviance detection and acts as an inhibitory/conflict monitoring of the deviance. This hypothesis was supported by a positive correlation between CNV and N2 amplitudes: The CNV reflects the temporal accumulator and can predict explicit detection of the deviance. In expert musicians, a N2 component is observable without CNV, suggesting that deviance detection is optimized and does not require the temporal accumulator. Overall, this study suggests that musical expertise is associated with optimized implicit time perception.

Biomimetic Hydrodynamic Sensor with Whisker Array Architecture and Multidirectional Perception Ability.

The rapid development of ocean exploration and underwater robot technology has put forward new requirements for underwater sensing methods, which can be used for hydrodynamic characteristics perception, underwater target tracking, and even underwater cluster communication. Here, inspired by the specialized undulated surface structure of the seal whisker and its ability to suppress vortex-induced vibration, a multidirectional hydrodynamic sensor based on biomimetic whisker array structure and magnetic 3D self-decoupling theory is introduced. The magnetic-based sensing method enables wireless connectivity between the magnetic functional structures and electronics, simplifying device design and endowing complete watertightness. The 3D self-decoupling capability enables the sensor, like a seal or other organisms, to perceive arbitrary whisker motions caused by the action of water flow without complex calibration and additional sensing units. The whisker sensor is capable of detecting a variety of hydrodynamic information, including the velocity (RMSE<0.061ms-1) and direction of the steady flow field, the frequency (error<0.05Hz) of the dynamic vortex wake, and the orientation (error<7°) of the vortex wake source, demonstrating its extensive potential for underwater environmental perception and communication, especially in deep sea conditions.

Evaluating Effectiveness and Challenges in B.Ed. Student Teacher Internships

The B.Ed. internship program is essential for teacher preparation, but its effectiveness in preparing future educators for diverse classrooms requires ongoing evaluation. The school internship programme in teacher education is changing from a pre-specified practice-teaching approach to a more comprehensive approach, as emphasized by the NCTE Regulations, 2009 and 2014 respectively. The 2009 regulations expanded the scope of practice-teaching by emphasizing the importance of student-teachers experiencing all school activities and programs. The 2014 regulations further strengthened the component of ‘Field Engagement’ by prescribing a longer duration of 15 weeks. In the present paper researchers has made an attempt to examines the effectiveness and challenges of B.Ed. student teacher internships, focusing on skill development, support structures, and resource availability. It also investigates the program’s impact on student teachers’ confidence in managing diverse classrooms and fostering student success with varying needs and abilities perception of student teachers about the engagement of 15weeks (15+2 weeks) with the field in B.Ed. 3 rd. semester. Internship Programme as per the curriculum of Guru Nanak Dev University Amritsar Punjab. The present study aims to evaluate the effectiveness and challenges faced by student teachers during their internship. The sample consisted of 180 student-teachers selected from B.Ed. colleges of Amritsar district through random sampling. The study, utilizing an open-ended questionnaire, revealed that student-teachers encountered numerous challenges during their internship in the 3rd semester of B.Ed., highlighting the challenges faced by both students and educators.

Intrinsic interpersonal emotion regulation strategy use and effectiveness across adulthood: The role of interaction partner age.

One way older adults may be able to maintain emotional well-being despite declining in cognitive ability is through leveraging social resources for intrinsic interpersonal emotion regulation. Additionally, given their increased life experience, older adults might also be particularly well-suited to regulate the emotions of others. To examine age difference in use and effectiveness of intrinsic interpersonal emotion regulation, community adults (N = 290, aged 25-85 years) were prompted 6×/day for 10 days to report their emotional experience, use of intrinsic emotion regulation strategies (including capitalization, social sharing, co-reappraisal, and reminiscing), and interaction partner age. Older age was associated with being less likely to engage in social sharing of negative emotions, and this effect was stable when controlling for negative emotion experience. Otherwise, there were no age differences in how often or how effectively people use intrinsic interpersonal emotion regulation. In terms of interaction partner age, older partner age was only associated with greater likelihood of using co-reappraisal and higher reports of negative emotion after social sharing. In summary, there was no strong evidence for the idea that interpersonal emotion regulation becomes more (or less) common or effective with age. However, though people may be less likely to share negative emotions and be seen as less effective partners for sharing these emotions later in life, older adults are preferable social partners for co-reappraisal potentially due to their life experience. Future work should explore motivational (i.e., attitudes toward negative emotions) and cultural (i.e., perceptions of roles and emotional abilities) mechanisms. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A Multi-Scale Feature Fusion Based Lightweight Vehicle Target Detection Network on Aerial Optical Images

Vehicle detection with optical remote sensing images has become widely applied in recent years. However, the following challenges have remained unsolved during remote sensing vehicle target detection. These challenges include the dense and arbitrary angles at which vehicles are distributed and which make it difficult to detect them; the extensive model parameter (Param) that blocks real-time detection; the large differences between larger vehicles in terms of their features, which lead to a reduced detection precision; and the way in which the distribution in vehicle datasets is unbalanced and thus not conducive to training. First, this paper constructs a small dataset of vehicles, MiVehicle. This dataset includes 3000 corresponding infrared and visible image pairs, offering a more balanced distribution. In the infrared part of the dataset, the proportions of different vehicle types are as follows: cars, 48%; buses, 19%; trucks, 15%; freight, cars 10%; and vans, 8%. Second, we choose the rotated box mechanism for detection with the model and we build a new vehicle detector, ML-Det, with a novel multi-scale feature fusion triple cross-criss FPN (TCFPN), which can effectively capture the vehicle features in three different positions with an mAP improvement of 1.97%. Moreover, we propose LKC–INVO, which allows involution to couple the structure of multiple large kernel convolutions, resulting in an mAP increase of 2.86%. We also introduce a novel C2F_ContextGuided module with global context perception, which enhances the perception ability of the model in the global scope and minimizes model Params. Eventually, we propose an assemble–disperse attention module to aggregate local features so as to improve the performance. Overall, ML-Det achieved a 3.22% improvement in accuracy while keeping Params almost unchanged. In the self-built small MiVehicle dataset, we achieved 70.44% on visible images and 79.12% on infrared images with 20.1 GFLOPS, 78.8 FPS, and 7.91 M. Additionally, we trained and tested our model on the following public datasets: UAS-AOD and DOTA. ML-Det was found to be ahead of many other advanced target detection algorithms.

Study of the Effect of ChatGpt on the Development of Research Capacity of Higher Education Students

As a relatively mature generative AI technology, ChatGPT's application in education and scientific research has attracted wide attention. This paper investigates the current situation of ChatGPT use among college students and the impact of ChatGPT on their scientific research capabilities and analyzes that the current application effect of ChatGPT in learning is relatively positive, but there are still problems such as inaccurate and insufficient quality of the generated text. At the same time, ChatGPT is of great help to college students in terms of perception ability, language comprehension ability, language expression ability, data collection ability, and knowledge construction ability, but it is not significantly helpful for the improvement of students' teamwork ability, problem discovery ability, innovative thinking ability, and innovative practice ability. Given the current problems in the use of ChatGPT and the challenges it brings to the development of students' scientific research ability, this article provides corresponding countermeasures and suggestions from multiple perspectives.

Communication Skills in Toddlers Exposed to Maternal SARS-CoV-2 during Pregnancy.

Studies about the effects of SARS-CoV-2 on pregnant women and children born to positive women are controversial with regard to possible inner ear-related damage but most of them do not detect the involvement of this virus in auditory function. However, only a few studies on long-term effects on language development are currently available because of the recent onset of the pandemic. The aim of this study was to investigate the impact of SARS-CoV-2 infection on perceptual and expressive abilities and the emerging development of communication in young children. To this purpose, the MacArthur-Bates Communicative Development Inventory-Words and Gestures form (CDI-WG), was administered to parents. In total, 115 children whose mother was infected by SARS-CoV-2 during pregnancy were enrolled in the study and evaluated at the Audiology Service of the Modena University Hospital. All children underwent Otoacoustic Emissions (OAE) at birth: 114/115 had a "pass" result bilaterally, while 1 case had a unilateral "refer" result. Overall, 110/115 newborns (95.65%) underwent audiological evaluation between 10-18 months of age. In 5/110 patients (3.6%), the Pure Tone Average (PTA) result was equal to 35 dB; one case had a hearing threshold of around 50 dB due to a bilateral effusive otitis media. A notable finding was the percentage of children with tubal dysfunction in both evaluations, within 2 months of age and around 12 months of age. Most children revealed normal hearing. The CDI-WG was completed by 56/115 families. The rate of children below the fifth percentile was 8.9% for sentences understood, 12.5% for words understood, and 5.4% for words produced. Concerning CDI-Gestures, only 2 children (3.6%) were below the fifth percentile. A structured audiological follow-up in association with the evaluation of communication skills of children appears fundamental, particularly in the years of maximum neuroplasticity. Long-term studies are still necessary to evaluate the possible consequences of the pandemic.

Study on correlation between Chinese medicine syndromes in stroke and neurological deficits during recovery phase: Perspective.

Stroke is a leading cause of long-term disability and mortality worldwide, necessitating effective rehabilitation strategies for successful recovery. Traditional Chinese medicine (TCM) has gained recognition as a complementary and alternative approach in stroke rehabilitation, owing to its unique syndromes that offer valuable insights for personalized treatment plans. This study aims to elucidate the correlation between TCM syndromes observed during the recovery phase of stroke and the associated neurological deficits. Syndromes such as Blood stasis, Phlegm-dampness, Qi deficiency, and Yin deficiency were systematically examined, while standardized neurological assessments, encompassing motor function, sensory perception, and cognitive abilities, were employed to evaluate the extent of neurological impairment. Rigorous statistical analyses were conducted to discern potential correlations between TCM syndromes and the severity of neurological deficits. The results revealed statistically significant positive associations between certain TCM syndromes, particularly Blood stasis and Phlegm-dampness, and heightened neurological deficits during the recovery phase post-stroke. These findings suggest that these syndromes may serve as indicators of more severe brain injury post-stroke, thereby guiding the development of tailored rehabilitation strategies. By establishing robust connections between TCM syndromes and neurological deficits, this study contributes to advancing our understanding of stroke recovery through an integrated approach that incorporates TCM principles. Moreover, it underscores the potential benefits of integrating TCM into conventional rehabilitation protocols, offering valuable insights for healthcare professionals and potentially improving patient outcomes.

Image Quality Difference Perception Ability: A BIQA model effectiveness metric based on model falsification method

Blind Image Quality Assessment (BIQA) methods refer to algorithms that predict image quality scores without reference images. This challenging area is crucial for preprocessing and optimizing visual tasks. Since BIQA is a small-sample task, it has become a common practice to apply transfer learning by using models pre-trained on other visual tasks, such as semantic recognition, to BIQA. This paper is interested in whether a backbone that performs better in semantic recognition also improves predictive accuracy in BIQA tasks. Comparative experiments showed that different semantic backbones with varying precision exhibit minimal differences in PLCC (Pearson Linear Correlation Coefficient) and SRCC (Spearman Rank Order Correlation Coefficient). However, further comparison shows that the semantic backbone does enhance the model’s IQA abilities, which traditional metrics fail to capture due to their oversight of quality differences between images. We term this ability as Image Quality Difference Perception Ability (IQDP Ability). Based on this, we propose an IQDP comparison method and a new metric, which can effectively compare and measure a model’s IQDP Ability, supplementing traditional metrics and providing an effective means of identifying superior models.

Real-time assessment of ship collision risk using image processing techniques

The poor quality or the miss of Automatic Identification System (AIS) data may cause erroneous judgement of the potential navigational risk. Therefore, this study proposes a real-time framework for assessing ship collision risk using onboard video data in order to improve the risk perception ability of navigators. Firstly, the Squeeze-and-Excitation (SE) attention mechanism and the K-means algorithm are simultaneously utilized for the framework to enhance the multi-scale ship detection capability. The Deep-SORT is employed to complete multi-ship feature matching. Secondly, the distances between two ships and their speeds are measured using the pinhole imaging principle based on the ship visual feature extraction results. Moreover, the ship distance-speed correction method is designed to improve the reliability of estimated results. Finally, the effectiveness of the framework is validated using naturalistic driving data from the “He Hua Hai” ship. The results show that the proposed framework could demonstrate an excellent performance in assessing ship collision risk using the onboard video data. The proposed framework could help precisely detect and promptly provide warnings about potential ship collision risks. This could help prevent catastrophic accidents that pose a threat to oceans and coasts, particularly in situations when AIS data proves to be unreliable or ineffective.

Firefighting Robot Extinguishment Decision‐Making Based on Visual Guidance: A Novel Attention and Scale U‐Net Model and Genetic Algorithm

ABSTRACTAt present, rescue firefighting relies mainly on firefighting robots, and robots with perception and decision‐making functions are the key elements for achieving intelligent firefighting. However, traditional firefighting robots often lack the ability for autonomous perception and decision‐making when extinguishing multiple fire sources, leading to low rescue efficiency and increased risk for rescue personnel, especially when making firefighting decisions in extreme fire scenes, which poses a challenge. To effectively handle firefighting tasks and ensure operational efficiency, a robot firefighting decision‐making method based on drone visual guidance is proposed. First, we introduce a novel Attention and Scale U‐Net (ASUNet) model to accurately capture crucial target information, including fire location and size, in a fire scene. The ASUNet model adopts an effective multiscale fusion strategy and attention mechanism to enhance the model's performance. Subsequently, based on the results of the ASUNet model, through pixel segmentation clustering and a genetic optimization algorithm, we obtain the robot's firefighting decision results, thereby guiding the robot to carry out firefighting operations systematically. Finally, through numerical experiments, it is verified that the proposed ASUNet model is superior and effective, as the model can perceive important information in a fire scene and extract it well. The use of improved genetic optimization can further accelerate algorithm convergence. To our knowledge, this study is the first to use drone‐based monocular vision guidance for firefighting decision‐making, providing significant engineering value.

High-accuracy direction measurement and high-resolution computational spectral reconstruction based on photonic crystal array

Portable and wearable miniaturized spectrometers play a crucial role in various fields. In this paper, we present a method for simultaneously realizing high-accuracy direction measurement and high-resolution computational spectral reconstruction based on the angle sensitivity of conventional photonic crystals (PCs), wherein an optical filter array is composed of multiple one-dimensional PCs. The high-angle sensitivity of PCs results in angle-dependent optical spectra. When these spectra with different angles are used to reconstruct the target spectra in an unknown direction and the interval between adjacent angles is sufficiently small, the accurate direction of the target can be automatically identified. Moreover, the computational spectra still have high resolution over a wide range of incidences. The computational spectra under arbitrary polarizations can also be recognized based on the polarization dependence of the PCs at an oblique incidence. Our research results are significant for engineering a new miniaturized comprehensive computational spectrometer with target-direction perception and omnidirectional spectral reconstruction abilities.

Faktor-Faktor Yang Mempengaruhi Kepuasan Jamaah Umroh Dan Haji Dengan Persepsi Kesehatan Sebagai Variabel Moderating

Background – Indonesia is the country with the largest Muslim population in the world. This creates a lot of interest and demand for Hajj and Umrah in Indonesia. Hajj and Umrah are worship activities carried out by visiting Mecca and Medina and carried out in accordance with religious law. Since the city of Mecca reopened for Umrah pilgrims after Covid-19, thousands of people have visited various travel services that provide Umrah services. Various types of travel offers ranging from cheap prices, good aircraft facilities, and hotels close to the Kaaba. This offering strategy is carried out to get the attention of prospective Umrah pilgrims. Aim – In this study, the purpose of the study is to test whether service quality, price perception, trust, empathy and health perception influence customer satisfaction and whether health perception is able to moderate all these factors. Design / methodology / approach – This type of research is quantitative research, namely analyzing data in the form of numbers. The data used in this research is primary data which is data directly obtained from the first data source. Data was obtained from the results of a questionnaire distributed to respondents, namely Hikmah Travel pilgrims and Umrah pilgrims. The method used is multiple linear regression analysis with moderator effects. Findings – The results of this research are that the service quality variable (X1) has no effect on consumer satisfaction (Y), the price perception variable (X2) has no effect on consumer satisfaction (Y), the trust variable (X3) has no effect on consumer satisfaction (Y), the empathy variable (X4) has a significant effect on consumer satisfaction (Y), healthy perception (Z) moderates the influence of service quality (X1) on consumer satisfaction (Y), healthy perception (Z) is unable to moderate the influence of price (X2) on consumer satisfaction (Y), healthy perception (Z) is able to moderate the influence of trust (X3) on consumer satisfaction (Y), healthy perception (Z) is unable to moderate the influence of empathy (X4) on consumer satisfaction (Y). Conclusion - The ability of health perception to moderate consumer satisfaction is seen from the quality of service, price perception, trust is good, so this needs to be a concern for hajj and umrah services. However, the absence of health perception will actually result in compromised customer satisfaction. Research implication – Empathy has a significant effect on consumer satisfaction, so travel agencies should pay attention to the empathy factor so that it can increase consumer satisfaction and can be used to attract Hajj pilgrims to use their travel services. Apart from the empathy factor, healthy perceptions are able to moderate the factors of service quality and trust in customer satisfaction, so travel agencies must also pay attention to these factors to get potential customers. Limitations – The population in this research is Hajj and Umrah travel services in East Java, while the sample from this research is Umrah and Hajj pilgrims at Hikmah Travel.

The effects of cognition and visual perception on activities daily living in the elderly

This study aimed to investigate the influence of cognition and visual perception on activities of daily living (ADL) among community-dwelling elderly individuals. Cognition was assessed using the Korean version of Montreal Cognitive Assessment, visual perception was assessed using the Motor Free Visual Perception Test -3, and ADL were assessed using the Modified Barthel Index. The results indicated that cognition, visual perception, and ADL were all positively correlated. Additionally, both cognition and visual perception were found to impact the ADL in the elderly. This study provides evidence that can be used to develop welfare and rehabilitation programs for the elderly, focusing on managing cognitive and visual perception abilities to support independent ADL and enhance quality of life.

Objective Determination of Site-of-Lesion in Auditory Neuropathy.

Auditory neuropathy (AN), a complex hearing disorder, presents challenges in diagnosis and management due to limitations of current diagnostic assessment. This study aims to determine whether diffusion-weighted magnetic resonance imaging (MRI) can be used to identify the site and severity of lesions in individuals with AN. This case-control study included 10 individuals with AN of different etiologies, 7 individuals with neurofibromatosis type 1 (NF1), 5 individuals with cochlear hearing loss, and 37 control participants. Participants were recruited through the University of Melbourne's Neuroaudiology Clinic and the Murdoch Children's Research Institute specialist outpatient clinics. Diffusion-weighted MRI data were collected for all participants and the auditory pathways were evaluated using the fixel-based analysis metric of apparent fiber density. Data on each participant's auditory function were also collected including hearing thresholds, otoacoustic emissions, auditory evoked potentials, and speech-in-noise perceptual ability. Analysis of diffusion-weighted MRI showed abnormal white matter fiber density in distinct locations within the auditory system depending on etiology. Compared with controls, individuals with AN due to perinatal oxygen deprivation showed no white matter abnormalities ( p > 0.05), those with a neurodegenerative conditions known/predicted to cause VIII cranial nerve axonopathy showed significantly lower white matter fiber density in the vestibulocochlear nerve ( p < 0.001), while participants with NF1 showed lower white matter fiber density in the auditory brainstem tracts ( p = 0.003). In addition, auditory behavioral measures of speech perception in noise and gap detection were correlated with fiber density results of the VIII nerve. Diffusion-weighted MRI reveals different patterns of anatomical abnormality within the auditory system depending on etiology. This technique has the potential to guide management recommendations for individuals with peripheral and central auditory pathway abnormality.

Face naming and recollection represent key memory deficits in developmental prosopagnosia

Previous studies have found that face perception deficits do not fully account for the severity of face recognition deficits in developmental prosopagnosia (DP). Researchers have begun identifying deficient memory mechanisms such as impaired face recollection, but these findings require replication, and further characterization of additional memory deficits is necessary. Our goals were to replicate prior findings of face recollection impairment in DP and extend these findings to assess different types of face associative memory. We had 69 DPs and 99 controls perform a face perception battery as well as three face memory tasks: 1) Old/New task with confidence ratings to calculate recollection and familiarity using ROC analysis, 2) Face/Scene task to examine remember-know judgments and contextual memory for faces, and 3) Face-Name/Occupation task to assess the ability to learn semantic associations with faces. Compared to controls, DPs showed poorer recollection and familiarity across both Old/New and Face/Scene tasks as well as reduced scene accuracy for correct faces. Of these differences, only Old/New recollection remained significant after controlling for group differences in face perception abilities. In the Face-Name/Occupation task, after controlling for face perception, DPs showed poorer recall of names than controls but performed similarly in recalling occupations. Finally, we found that DPs with major, mild, and no face perception deficits showed consistent impairments in Old/New recollection and face-naming, and larger perceptual deficits were associated with larger memory deficits. Together, these results provide several mechanistic insights into the nature of memory deficits in DPs and have diagnostic and treatment implications.

A Multi-Mechanism Fusion Method for Robust State of Charge Estimation via Bidirectional Long Short-Term Memory Model with Mixture Kernel Mean p-Power Error Loss Optimized by Golden Jackal Optimization Algorithm

Abstract Accurate state of charge (SOC) estimation is crucial for effective battery management in various applications. The bidirectional long short-term memory (BiLSTM) as an outstanding nonlinear regression model can be used for SOC estimation. This work develops a novel multi-mechanism fusion method based on BiLSTM to further enhance its estimation performance for SOC, in which the convolutional neural network (CNN), attention mechanism, and mixture kernel mean p-power error (MKMPE) loss are introduced into the BiLSTM framework for addressing different issues. First, the introduction of CNN components aims to extract essential features from battery data, enhancing the model's comprehension of complex information. Then, the attention mechanism is used to further refine the model's perceptual ability and a robust MKMPE loss is introduced into the BiLSTM framework to replace its original mean squared error loss, and a novel robust model is developed to suppress non-Gaussian noise interference. Finally, some key hyperparameters of the proposed model are fine-tuned using the golden jackal optimization algorithm, resulting in improved estimation performance. Comparative numerical experiments are meticulously conducted in various cases to evaluate the performance of the proposed method, and the experiment results demonstrate that it can perform outstanding effectiveness in handling non-Gaussian noise scenarios.

Four Cases of Children With Phonological Impairment and Precocious Vocabulary: Making Sense of a Clinical Conundrum.

The purpose of this study was to describe the speech production, speech perception, vocabulary, and word learning abilities of lexically precocious 4-year-old children with phonological impairment, in an effort to better understand the underlying nature of phonological impairment in children. Using a case series approach, we identified four children with phonological impairment and precocious vocabulary abilities. Each child completed routine speech production and vocabulary assessments, as well as experimental speech perception and word learning tasks. The results from these tasks were then used to create profiles of each child's individual strengths and needs across the abilities assessed. Although all four children presented with phonological impairment and lexically precocious receptive and expressive vocabulary, they differed in their specific speech errors. One child presented with phonological speech errors only, while the other three children presented with an interdental lisp alongside their phonological errors. Three children presented with average speech perception abilities, and one child presented with poorer speech perception. The same three children also showed some learning of novel nonwords 1 week post-initial exposure, while the other child showed no evidence of word learning 1 week post-initial exposure. The clinical profiles of lexically precocious children with phonological impairment offered different insights into the nature of the problem. Although one child appeared to present with underspecified underlying representations of words, the other three children appeared to present with well-specified underlying representations. Of the three children with well-specified underlying representations, two appeared to have difficulty abstracting particular rules of the ambient phonological system. Further research is needed to improve our understanding of the underlying nature of phonological impairment. https://doi.org/10.23641/asha.26307640.