In the intelligent transportation system, the license information can be automatically recognized by the computer and the vehicle can be tracked. Red light running, illegal change of lanes, vehicle retrograde, and other illegal driving events are reasonably recorded. This is undoubtedly an effective help for the traffic police to relieve the huge work pressure. However, in China, a considerable number of vehicle tracking methods have certain limitations in resisting complex external environmental influences. The external environmental factors include but not limited (...) to variable factors such as camera movement, jitter, and severe rain and snow. These factors cannot be controlled well, so the tracking accuracy is greatly reduced. In regard to this, this paper proposes an optimization method for moving vehicle tracking based on SPF. First, according to the size of the overlapping area of the motion area between the two images, the researcher can construct and simplify the vertex adjacency matrix that reflects the characteristics of the undirected bipartite graph. Then according to the corresponding relationship between the vertex adjacency matrix and the regional behavior and vehicle behavior, the researcher completes the regional behavior analysis and vehicle behavior analysis. On this basis, a particle filter vehicle tracking algorithm based on segmentation compensation is introduced, and the vector sum of the tracked segmentation area is used as the final position of the target vehicle. In this way, as many scattered particles fall on the target area as possible, which will greatly improve the efficiency of particle utilization, enhance tracking accuracy, and avoid the problem of tracking failure caused by too fast vehicle movement. Through experimental simulation, it can be seen that the method proposed in this paper can greatly enhance the vehicle tracking ability when tracking vehicles in “complex environments.”. (shrink)

The COVID-19 pandemic cropping up at the end of 2019 started to pose a threat to millions of people’s health and life after a few weeks. Nevertheless, the COVID-19 pandemic gave rise to social and economic problems that have changed the progress steps of individuals and the whole nation. In this study, the work conditions for employees from Taiwan, Malaysia, and the Chinese mainland are explored and compared, and the relationship between support mechanisms and innovation behaviors is evaluated with a (...) view of the social cognitive career theory. This study adopts the cross-sectional survey and purposive sampling to collect questionnaires. A total of 623 copies of a questionnaire from Taiwanese, 440 copies from Malaysians, and 513 copies from mainlanders were collected in this study to compare the three groups in developing employees’ IBs. Smart-partial least squares for partial least squares structural equation modeling was applied in the structural model to conduct a verification of the hypotheses and comparative analysis in this study. According to the findings, compared with employees from the Chinese mainland, the Taiwanese and Malaysian samples show more significant paths regarding employee employability, IB, prior knowledge, perceived organizational support, self-efficacy, and job performance. Our results will offer more insights and advice concerning theories of human resource. (shrink)

Many scholars have investigated education management. Scholars in the education field have made significant achievements in contributing to multiple educational reform policies, while other scholars discuss teacher-related issues from the perspective of organizational behavior. The teaching innovation of high school teachers plays a critical role in students’ learning attitude and motivation, especially in the context of the COVID-19 pandemic. Teachers need to utilize more diversified teaching methods to enable students to carry out effective learning. In order to examine teachers’ teaching (...) innovation, this study explores teaching innovation intentions and performance from the perspective of individual and social factors in combination with goal-oriented behavior and social identity theory. This study conducts questionnaires with a sample of Chinese coastal high school teachers, and obtains a total of 475 responses. The research results show that innovation attitude, positive anticipated emotion, group norms and social identity positively affect teachers’ teaching innovation intention; furthermore, teachers’ teaching innovation intention also positively affects their teaching innovation performance. Based on the comprehensive research findings, this research proposes corresponding theoretical and practical implications. (shrink)

Research shows that entrepreneurial activities significantly promote economic development, which enhances the importance of the innovative entrepreneurial potential of college students. This study analyzes the effect of entrepreneurship education on entrepreneurial intention from the perspective of planned behavior theory. By examining the significant role of entrepreneurship education at colleges and universities on economic and social development, we established a conceptual model. To understand the relationship between entrepreneurship education and entrepreneurial intention, the hypotheses propose the intermediary role of entrepreneurial ability, and (...) the study provides evidence from China the relationship between entrepreneurship education and entrepreneurial intention. Improving entrepreneurial intention and encouraging college students to establish businesses through entrepreneurship education in universities is crucial. This study proposes a hypothetical model of the relationship between entrepreneurial competence and entrepreneurial intention in entrepreneurship education at universities. Using a questionnaire survey of college students with practical experience in the Yangtze River Delta of China, the bootstrap method in the SPSS macro program process software verifies the hypotheses. The results show that entrepreneurial teaching, business plan competition, and entrepreneurial practice support positively affect entrepreneurial competence. In addition, entrepreneurial competence plays an intermediary role in the relationship between entrepreneurial teaching, business plan competition, entrepreneurship practice support, and entrepreneurial intention. Entrepreneurship education improves the ability to establish a business in the present and in entrepreneurial activities in the future. Entrepreneurial competence obtained through entrepreneurship education continuously affects entrepreneurial intention. (shrink)

The convenience of big data processing technology has played a great advantage in many scenarios, and its deep learning can effectively mine different types of data in data sets. Applying this method to mining psychological prediction data set of legal anomie behavior can effectively prevent the occurrence of illegal behavior. The effective analysis of its psychological characteristics and the changes of psychological emotions will have hidden dangers, so it is necessary to extract this kind of data in such cases. Therefore, (...) the forest algorithm under deep learning uses weight factors, simple sampling, and other ideas to build the intervention mechanism, which will improve psychological quality to prevent anomie. The experimental results of this paper are as follows: In the case of testing psychological fluctuation by three algorithms, the forest algorithm calculates the psychological change area steadily, with the increase of the number of samples. In the data sample extraction of different dimensions, the test value increases with the increase of dimensions, and it is stable at 12 dimensions. Preventive intervention is extremely important to construct the mechanism before the anomie behavior occurs, and the longest running time of the roll neural network is as much as 950 s. The data mining technology for constructing the intervention mechanism accounts for 15.4% of counseling, which also shows that the auxiliary measures for preventing behavior are particularly important. (shrink)

Previous studies have shown that adolescents are experiencing growing pains due to their unbalanced physical and mental development. Their life satisfaction showed a steady downward trend with age. Altruism may be an effective way to improve their life satisfaction. Against this background, the current study carried out school altruistic group games for the first time to explore the role of altruistic group activities in the school context in improving adolescents’ life satisfaction. There were 176 adolescents in the study, including 90 (...) in the experimental group and 86 in the control group, who were enrolled from a junior high school in East China. A 10-week school altruism group game was carried out for the experimental group. The participants in the control group participated in activities that were not related to altruism. Participants in both groups reported their life satisfaction and emotions before and after the games. The findings of this study were as follows: SAGGs can effectively improve adolescents’ life satisfaction, especially school satisfaction; SAGGs can significantly improve adolescents’ emotional state; that is, SAGGs can enhance positive emotions and reduce negative emotions; and SAGGs have different effects on the life satisfaction of adolescents with different initial emotional states. The results of this study not only enrich the existing literature but also provide enlightenment and a reference for schools to improve adolescents’ life satisfaction. (shrink)

Mathematically gifted students are precious human resources, educators of which make a great difference in helping them realize their potential. The retention of qualified teachers of mathematically gifted students is an issue worthy of in-depth exploration. In China, mathematics competitions are an important part of mathematics gifted education, and the teaching of the Mathematical Olympiad is a challenging profession with a high attrition rate. This qualitative study takes four seasoned and outstanding Chinese teachers as cases, collects data through individual semi-structured (...) interviews, and uses the thematic analysis method based on Herzberg’s two-factor theory to analyze why they can persist in the field of Mathematical Olympiad teaching for more than 20 years. The results show that the motivation factors affecting retention are recognition, achievement, possibility of growth, work itself, and responsibility, and the hygiene factors are policy and interpersonal relationships. Motivation factors are the main reason for their long-term persistence, while hygiene factors are conducive to their persistence as a whole. Finally, enlightenment to educational policy and school management and suggestions for retention and development of teachers of the mathematically gifted are provided. (shrink)

The grey system model with time power, which is often called the GM, appeals considerable interest of research due to its effectiveness in time series forecasting. Aimed to improve further the GM model, this paper introduces a new whitening equation with variable coefficient into the original whitening equation which extends applicable scope; as a result, an improved grey model with time power, namely, OGM, is proposed. Firstly, the time response function of the novel model and the restored values of original (...) series are deduced through grey modelling techniques. Secondly, the variable coefficient in the whitening equation and the time power are determined by particle swarm optimization algorithm. Two empirical examples are then used to verify the validity of the novel model. Finally, the novel model is applied to predict the oil consumption of China from 2004 to 2018. Results show the novel model outperforms other commonly-used competitive models, which can well serve a benchmark model for scholars and decision-makers. (shrink)

To identify relationships among entities in natural language texts, extraction of entity relationships technically provides a fundamental support for knowledge graph, intelligent information retrieval, and semantic analysis, promotes the construction of knowledge bases, and improves efficiency of searching and semantic analysis. Traditional methods of relationship extraction, either those proposed at the earlier times or those based on traditional machine learning and deep learning, have focused on keeping relationships and entities in their own silos: extracting relationships and entities are conducted in (...) steps before obtaining the mappings. To address this problem, a novel Chinese relationship extraction method is proposed in this paper. Firstly, the triple is treated as an entity relation chain and can identify the entity before the relationship and predict its corresponding relationship and the entity after the relationship. Secondly, the Joint Extraction of Entity Mentions and Relations model is based on the Bidirectional Long Short-Term Memory and Maximum Entropy Markov Model. Experimental results indicate that the proposed model can achieve a precision of 79.2% which is much higher than that of traditional models. (shrink)

The main idea of S-curve diagram is to assign different angle values to different nucleotide acid residues or to different protein amino acids, and then according to cos α j and sin α j, the values are accumulated to construct an S-curve diagram, which is in strict one-to-one correspondence with the biological sequence. In addition, the S-curve diagram proves to be without the degeneracy phenomenon, so that both the degeneracy problem represented by diagrams and the problem of visualization for biological (...) sequence data are solved. Meanwhile, a new approach to differentiate the similarity of biological sequences—the degree of similarity—is put forward on the basis of the S-curve diagram. To put it in detail, the least square approach is first adopted to obtain a straight line equation according to the S-curve diagram, then according to the distance formula of the point to the straight line, the average ratio of square sum for the distance between the S-curve and the straight line is calculated, and finally, the similarity of the biological sequences is presented by the new standard—the degree of similarity. As is shown by the experimental results, the S-curve diagram can better represent biological sequences within Cartesian coordinate system, and the mutation point of biological sequence. Thus, it turns out that the new standard—the degree of similarity is of obviously great advantage. (shrink)

Adolescents have gradually become a vital group of interacting with social media recommendation algorithms. Although numerous studies have been conducted to investigate negative reactions that the dark side of recommendation algorithms brings to social media users, little is known about the resistance intention and behavior based on their agency in the daily process of encountering algorithms. Focusing on the concept of algorithm resistance, this study used a two-path model to investigate the algorithmic resistance of rural Chinese adolescents in their daily (...) use of short video apps. The findings revealed that the perceived threat to freedom, algorithmic literacy, and peer influence were positively associated with the resistance willingness and intention; while the independent psychology on algorithmic recommendations significantly weakened resistance willingness and intention. Furthermore, this study verified the mediating role of resistance willingness and intention between the above independent variables and resistance behavior. Additionally, the positive impact of resistance willingness on resistance intention was confirmed. In conclusion, this study offers a comprehensive approach to further understanding adolescents’ algorithmic resistance awareness and behavior by combining psychological factors, personal competency, and interpersonal influences, as well as two types of resistance reactions. (shrink)

In the present paper, we introduce the notions of quasi-Boolean algebras as the generalization of Boolean algebras. First we discuss the related properties of quasi-Boolean algebras. Second we define filters of quasi-Boolean algebras and investigate some properties of filters in quasi-Boolean algebras. We also show that there is a one-to-one correspondence between the set of filters and the set of filter congruences on a quasi-Boolean algebra. Then we investigate the prime filters and maximal filters of quasi-Boolean algebras, showing that the (...) prime filters of a quasi-Boolean algebra are precisely the maximal filters and the prime spectrum of a quasi-Boolean algebra is a compact Hausdorff topological space. Finally, we define and study the reticulation of a quasi-Boolean algebra. (shrink)

Discourse connection is a challenging aspect of writing in a second language. This study seeks to investigate the effects of two classroom instructions on discourse connection in writing for EFL college students, focusing on their argumentative writing. Three classes were exposed to different pre-task conditions: receiving reading materials that provide content support for the writing, receiving planning instructions on effective outlining, and receiving no resources. The results showed that the instructions helped students attain better overall coherence in writing. However, noticeable (...) differences between the two experimental groups emerged in terms of cohesion features. The reading group was found to employ more lexical cohesion devices in writing than the outline group, which indicated a heightened genre awareness. This inquiry helped us identify the reading group’s alignment with content support materials, particularly the change in stance as a factor that contributes to a higher level of lexical cohesion in writing. (shrink)

The outbreak of the coronavirus disease 2019 has resulted in widespread university lockdown. However, impacts of the university lockdown on the learning and academic development of university students have not been thoroughly investigated. The current study examined college students’ changes of learning outcomes during the COVID-19 lockdown period and clarified what might explain individual differences in students’ learning outcomes after they had learned from home for a whole semester when universities were physically closed due to the COVID-19 pandemic. Data were (...) derived from a longitudinal study examining the development of college students including students’ academic achievement and critical thinking before and after the university lockdown. We observed significant decreases in critical thinking skills and dispositions from pre- to post-lockdown. Both perceived academic achievement and critical thinking exhibited greater variability after the lockdown. In addition, students’ readiness for online learning, especially their self-management skills, consistently predicted post-lockdown learning outcomes after controlling for pre-lockdown outcomes and family socioeconomic status. Those who have assumed more responsibilities at home, or who were more vulnerable to emotional distress during the pandemic, performed less well in post-lockdown learning outcomes. These findings call for better management of student learning and development when major changes are required in higher education practices for responding to the ongoing COVID-19 crisis as well as other potential situations. (shrink)

China set the goal of expanding early childhood education in 2018, by encouraging the development of public interest kindergartens to provide high-quality, low-cost preschool services to the general public. This is in response to the challenges of accessibility, affordability, and accountability besetting China’s current ECE system. However, the transition toward PIK has been slow due to various complex problems, including the lackluster willingness of ECE providers to become PIK. To better understand the challenges leading to low participation, this study explores (...) the external pressures affecting ECE providers and evaluates the external factors that influence their level of social responsibility. A stratified-random sampling questionnaire survey solicited responses from 832 ECE personnel representing 261 kindergartens from across China. Our findings suggest that institutional pressure has a positive effect on social responsibility and inclusive participation. We also found that institution visibility positively regulates the relationship between institutional pressure and social responsibility. At the same time, the level of environmental perception positively governs the relationship between social responsibility and participation willingness. Kindergartens should have certain social values, including assuming certain behaviors and participating in social activities in the spirit of social service and ensure multiple subjects’ synergetic governance. (shrink)

Patients with chronic obstructive pulmonary disease are characterized by attenuated pulmonary function and are frequently reported with cognitive impairments, especially memory impairments. The mechanism underlying the memory impairments still remains unclear. We applied resting-state functional magnetic resonance imaging to compare the brain local activities with static and dynamic amplitude of low-frequency fluctuations among patients with COPD and healthy controls. Compared with HC, COPD patients exhibited decreased sALFF in the right basal ganglia and increased dALFF in the bilateral parahippocampal/hippocampal gyrus. The (...) reduced the left basal ganglia was associated with lower oxygen partial pressure. Besides, the increased dALFF in the left hippocampal/parahippocampal cortex was associated with poor semantic-memory performance and the increased dALFF in the left hippocampal/parahippocampal cortex was associated the forced vital capacity. The present study revealed the abnormal static and dynamic local-neural activities in the basal ganglia and parahippocampal/hippocampal cortex in COPD patient and its relationship with poor lung function and semantic-memory impairments. (shrink)

There are three main problems in track fastener defect detection based on image: The number of abnormal fastener pictures is scarce, and supervised learning detection model is difficult to establish. The potential data features obtained by different feature extraction methods are different. Some methods focus on edge features, and some methods focus on texture features. Different features have different detection capabilities, and these features are not effectively fused and utilized. The detection of the track fastener clip will be interfered by (...) the track fastener bolt subimage. Aiming at the above three problems, a method for track fastener defects detection based on Local Deep Feature Fusion Network is proposed. Firstly, the track fastener image segmentation method is used to obtain the track fastener clip subimage, which can effectively reduce the interference of bolt subimage features on the track fastener clip detection. Secondly, the edge features and texture features of track fastener clip subimages are extracted by Autoencoder and Restricted Boltzmann Machine, and the features are fused. Finally, the similarity measurement method Mahalanobis Distance is used to detect defects in track fasteners. The effectiveness of the proposed method is verified by real Pandrol track fastener images. (shrink)

Dynamic vision sensor is a kind of bioinspired sensor. It has the characteristics of fast response, large dynamic range, and asynchronous output event stream. These characteristics make it have advantages that traditional image sensors do not have in the field of tracking. The output form of the dynamic vision sensor is asynchronous event stream, and the object information needs to be provided by the relevant event cluster. This article proposes a method based on the event correlation index to obtain the (...) object’s position, contour, and other information and is compatible with traditional tracking methods. Experiments show that this method can obtain the position information of the moving object and its continuous motion trajectory and analyze the influence of the parameters on the tracking effect. This method will have broad application prospects in security, transportation, etc. (shrink)

Research in second language pragmatics has paid increasing attention to learners’ individual differences, but few studies have examined the relationship between learners’ willingness to communicate in L2 and their pragmatic competence. To this end, this study investigates the association between WTC and pragmatic awareness and comprehension of Chinese as a second language learners. A total of 80 CSL learners studying abroad in three universities in China participated in this study. Data were collected through a WTC questionnaire, a self-perceived communication competence (...) questionnaire, a pragmatic awareness judgment task, and a multiple-choice test for pragmatic comprehension. Statistical analyses were conducted to explore the relationship between the learners’ pragmatic awareness and pragmatic comprehension on the one hand and their WTC and SPCC in L2 on the other. The findings indicated that SPCC correlated positively with the learners’ L2 pragmatic comprehension, but not with their L2 pragmatic awareness. No correlation was found between WTC and pragmatic awareness and comprehension. The results suggest that SPCC may contribute to learners’ L2 pragmatic comprehension; some implications for teaching and future research directions are also discussed. (shrink)

Business Ethics, the Environment &Responsibility, Volume 31, Issue 4, Page 1040-1052, October 2022.

The self-organizing model and expectation-maximization method are two traditional identification methods for switching models. They interactively update the parameters and model identities based on offline algorithms. In this paper, we propose a flexible recursive least squares algorithm which constructs the cost function based on two kinds of errors: the neighboring two-parameter estimation errors and the output estimation errors. Such an algorithm has several advantages over the two traditional identification algorithms: it can estimate the parameters of all the sub-models without prior (...) knowledge of the model identities; has less computational efforts; and can update the parameters with newly arrived data. The convergence properties and simulation examples are provided to illustrate the efficiency of the algorithm. (shrink)

In the recent years, gesture recognition based on the surface electromyography (sEMG) signals has been extensively studied. However, the accuracy and stability of gesture recognition through traditional machine learning algorithms are still insufficient to some actual application scenarios. To enhance this situation, this paper proposed a method combining feature selection and ensemble extreme learning machine (EELM) to improve the recognition performance based on sEMG signals. First, the input sEMG signals are preprocessed and 16 features are then extracted from each channel. (...) Next, features that mostly contribute to the gesture recognition are selected from the extracted features using the recursive feature elimination (RFE) algorithm. Then, several independent ELM base classifiers are established using the selected features. Finally, the recognition results are determined by integrating the results obtained by ELM base classifiers using the majority voting method. The Ninapro DB5 dataset containing 52 different hand movements captured from 10 able-bodied subjects was used to evaluate the performance of the proposed method. The results showed that the proposed method could perform the best (overall average accuracy 77.9%) compared with decision tree (DT), ELM, and random forest (RF) methods. (shrink)

In order to improve the impact resistance and mechanical performance of anchor rods and satisfy the requirements for supporting rockburst roadways, the energy balance equation of the energy-absorbing support and roadway surrounding rock system is established. Moreover, to effectively prevent rockburst disasters, the energy criterion for roadway instability is derived. From the perspective of an energy-absorbing support, a yield-absorbing anti-shock anchor composed of a rod body, tray, constant resistance energy-absorbing device, and special-shaped nut is designed and developed; compared with ordinary (...) anchor rods, this rod has stronger mechanical properties for resisting impact. Theoretical and numerical simulation studies show that the energy-absorbing device has a repeatable deformation failure mode and a constant yield force. The paper also presents the principle involved in the design of anti-shock bolt supports. The energy-absorbing support not only effectively guides and controls the release and conversion of impact energy but also consumes the impact energy in the buffering process of the anchor to ensure the stability of surrounding rock and support protection system. This study aims to provide reference for roadway support design and to improve rock bolts used in rockburst roadways. (shrink)

Deficits in gestures act as early signs of impairment in social interaction and communication in children with autism spectrum disorder. However, the pieces of literature on atypical gesture patterns in ASD children are contradictory. This investigation aimed to explore the atypical gesture pattern of ASD children from the dimensions of quantity, communicative function, and integration ability; and its relationship with social ability and adaptive behavior. We used a semi-structured interactive play to evaluate gestures of 33 ASD children and 24 typically (...) developing children. And we evaluated the social ability, adaptive behavior, and productive language of ASD and TD children by using the Adaptive Behavior Assessment System version II and Chinese Communication Development Inventory. No matter the total score of CCDI was corrected or not, the relative frequency of total gestures, behavior regulation gestures, SI gestures, and joint attention gestures of ASD children were lower than that of TD children, as well as the proportion of JA gestures. However, there was no significant group difference in the proportion of BR and SI gestures. Before adjusting for the total score of CCDI, the relative frequency of gestures without vocalization/verbalization integration and vocalization/verbalization-integrated gestures in ASD children was lower than that in TD children. However, after matching the total score of CCDI, only the relative frequency of gestures without vocalization/verbalization integration was lower. Regardless of the fact that the total score of CCDI was corrected or not, the relative frequency and the proportion of eye-gaze-integrated gestures in ASD children were lower than that in TD children. And the proportion of gestures without eye-gaze integration in ASD children was higher than that in TD children. For ASD children, the social skills score in ABAS-II was positively correlated with the relative frequency of SI gesture and eye-gaze-integrated gestures; the total score of ABAS-II was positively correlated with the relative frequency of total gestures and eye-gaze-integrated gestures. In conclusion, ASD children produce fewer gestures and have deficits in JA gestures. The deficiency of integrating eye gaze and gesture is the core deficit of ASD children’s gesture communication. Relatively, ASD children might be capable of integrating vocalization/verbalization into gestures. SI gestures and the ability to integrate gesture and eye gaze are related to social ability. The quantity of gestures and the ability to integrate gesture with eye gaze are related to adaptive behavior.Clinical Trial Registration:www.ClinicalTrials.gov, identifier ChiCTR1800019679. (shrink)

This study examined the relationship between maternal sense of parenting efficacy and parental stress in children with autism and the moderating effect of family interaction. A total of 263 mothers of children with autism were investigated with the Parenting Ability Scale, Family Interaction Scale, and Parental Stress Scale. The results showed that maternal sense of parenting efficacy significantly predicted parental stress in children with autism; and family interaction significantly moderated the relationship between maternal sense of parenting efficacy and parental stress (...) in children with autism, that is, when family interaction was lower than −1.54 standard deviation, the sense of parenting efficacy did not significantly predict parental stress. When family interaction was higher than −1.54 SD, parenting efficacy had a significant negative predictive effect on parenting stress. (shrink)