CBA: multi source fusion model for fast and intelligent target intention identification

How to mine valuable information from massive multisource heterogeneous data and identify the intention of aerial targets is a major research focus at present. Aiming at the longterm dependence of air target intention recognition, this paper deeply explores the potential attribute features from the spatiotemporal sequence data of the target. First, we build an intelligent dynamic intention recognition framework, including a series of specific processes such as data source, data preprocessing,target space-time, convolutional neural networks-bidirectional gated recurrent unit-atteneion (CBA) model and intention recognition. Then, we analyze and reason the designed CBA model in detail. Finally, through comparison and analysis with other recognition model experiments, our proposed method can effectively improve the accuracy of air target intention recognition,and is of significance to the commanders’ operational command and situation prediction.

Improving innovation and entrepreneurship education in higher institutions: the impact of "Mass Entrepreneurship and Innovation" education on undergraduates' entrepreneurial intentions

The exploration of the way"mass entrepreneurship and innovation"(MEI)education influences students'aspirations to become entrepreneurs has grown into an important area of analysis in studies related to higher education.This research intends to examine the consequences of MEI education on students'tendency towards entrepreneurship,and to put forward methods for augmenting the teaching of innovation and entrepreneurship in private higher educational establishments.To achieve this objective,questionnaires and semi-structured interviews were employed in the study,which involved a total of 197 students and five education experts.The statistical analysis of the questionnaire data revealed that MEI education was positively related to students'entrepreneurial intentions,and that both entrepreneurial experience and family entrepreneurial background played moderating roles in this relationship.The interview findings indicated that private universities could enhance educational reforms by designing talent training programs,developing diversified curricula,and developing more professional entrepreneurial platforms to encourage students'entrepreneurial intentions.This study offers fresh insights for improving and perfecting the mechanism of innovation and entrepreneurship education in private universities.

KGTLIR:An Air Target Intention Recognition Model Based on Knowledge Graph and Deep Learning

As a core part of battlefield situational awareness,air target intention recognition plays an important role in modern air operations.Aiming at the problems of insufficient feature extraction and misclassification in intention recognition,this paper designs an air target intention recognition method(KGTLIR)based on Knowledge Graph and Deep Learning.Firstly,the intention recognition model based on Deep Learning is constructed to mine the temporal relationship of intention features using dilated causal convolution and the spatial relationship of intention features using a graph attention mechanism.Meanwhile,the accuracy,recall,and F1-score after iteration are introduced to dynamically adjust the sample weights to reduce the probability of misclassification.After that,an intention recognition model based on Knowledge Graph is constructed to predict the probability of the occurrence of different intentions of the target.Finally,the results of the two models are fused by evidence theory to obtain the target’s operational intention.Experiments show that the intention recognition accuracy of the KGTLIRmodel can reach 98.48%,which is not only better than most of the air target intention recognition methods,but also demonstrates better interpretability and trustworthiness.

Cardiovascular health awareness,risk perception,behavioural intention and INTERHEART risk stratification among middle-aged adults in Malaysia

Objective:To investigate the interrelationship between cardiovascular health awareness,risk perception,behavioural intention,and INTERHEART risk stratification in a middle-aged adult population in Malaysia.Methods:A cross-sectional survey with convenience sampling was conducted during November 2022 and January 2023.Participants completed validated questionnaires assessing cardiovascular health awareness,risk perception of cardiovascular diseases,behavioural intention towards adopting healthy habits,and INTERHEART risk stratification score(IHRS)based on established risk factors.A total of 602 respondents were included in the final analysis.Data were analysed with independent t-test/one-way ANOVA or Mann-Whitney/Kruskal-Wallis to test the differences,Pearson correlation or linear regression test to analyze the association of independent and dependent variables.Results:There was a significant positive correlation between medical knowledge related to cardiovascular disease(CVD)and knowledge related to CVD risk prevention,risk perception,behavioural intention and IHRS(P<0.05,Pearson correlation).Notably,individuals with higher IHRS tended to have lower knowledge related to CVD and CVD risk prevention,risk perception,and behavioural intention.Males,laborers,active/former smokers,individuals with lower household income and educational levels,those involved in occupations not related to the healthcare sector,and those who did not receive the CVD health brochure or are unaware of health self-assessment tools are likely to have lower levels of knowledge,risk perception,and poorer behavioural intention regarding cardiovascular health(P<0.05,one-way ANOVA).While educational level,smoking status,awareness about CVD poster,self-assessment tools were repeatedly significantly associated with knowledge related to CVD and CVD risk prevention,risk perception,behavioral intention and/or IHRS(P<0.05,linear regression).Conclusions:These findings underscore the importance of promoting cardiovascular health awareness and risk perception among middle-aged adults to foster positive BI and reduce CVD risk.Tailored interventions targeting specific risk factors identified by INTERHEART may enhance risk stratification accuracy and facilitate targeted preventive strategies.

Promoting sustainable consumption and circular economy:the intention of Vietnamese youth consumers to purchase products made from recycled plastics

Recycling is viewed as a key component in a circular economy and serves as an ideal solution for promoting sustainability.During the global plastic crisis,plastic recycling practices have been adopted worldwide,leading to the production of various products made from recycled plastics(PRP).Nevertheless,a gap persists between consumption and demand for such products,which is primarily attributed to a lack of comprehension from the consumer perspective.Given the pivotal role consumers play in the adoption of these products,this study explores consumers’intentions to purchase PRP.This is particularly significant in Vietnam,which is an emerging economy aspiring to achieve the objectives of a circular economy and sustainable development.Utilizing an integrated cognitive-emotional framework comprising the Valence Theory and the Norm Activation Model,data from 564 Vietnamese students were gathered and analyzed using structural equation modeling.The results show that awareness of consequences is a major driver of consumer purchase intentions,followed by perceived ease of application and monetary incentives.The results also indicate that health concerns have the strongest effect on purchase intention and in the negative side,meaning that the health-related risk is the primary concern for consumers during the decision-making process.This research holds substantial value for academics and managers,as it aids in the theoretical exploration and the formulation of strategies to improve consumer acceptance of PRP.

An Efficient Method for Identifying Lower Limb Behavior Intentions Based on Surface Electromyography

Surface electromyography(sEMG)is widely used for analyzing and controlling lower limb assisted exoskeleton robots.Behavior intention recognition based on sEMG is of great significance for achieving intelligent prosthetic and exoskeleton control.Achieving highly efficient recognition while improving performance has always been a significant challenge.To address this,we propose an sEMG-based method called Enhanced Residual Gate Network(ERGN)for lower-limb behavioral intention recognition.The proposed network combines an attention mechanism and a hard threshold function,while combining the advantages of residual structure,which maps sEMG of multiple acquisition channels to the lower limb motion states.Firstly,continuous wavelet transform(CWT)is used to extract signals features from the collected sEMG data.Then,a hard threshold function serves as the gate function to enhance signals quality,with an attention mechanism incorporated to improve the ERGN’s performance further.Experimental results demonstrate that the proposed ERGN achieves extremely high accuracy and efficiency,with an average recognition accuracy of 98.41%and an average recognition time of only 20 ms-outperforming the state-of-the-art research significantly.Our research provides support for the application of lower limb assisted exoskeleton robots.

What Drives Migrants Back to Set up Firms?Return-home Entrepreneurial Intention of Rural Migrant Workers in China

The extant literature on international immigrants has discussed migrants’entrepreneurial activities in the context of Western countries but has paid little attention to return-home entrepreneurial intention(RHEI).Rural migrant workers(RMWs)in China,who used to promote rural development by remittances and were characterized by similarities with early international migrants,have gradually returned to their hometowns to initiate entrepreneurial activities.Based on the structured questionnaire conducted in 2015 and 2020in Anhui Province,China,this article combines the concept of mixed embeddedness with the idea of double-layered embeddedness and analyzes the impacts of the social,economic and institutional context in RMWs’hometowns and migration destinations on RMWs’RHEI by using binary logistic regression.The article shows that the social,economic,and institutional environments of RMWs’hometowns and migration destinations have effects on their RHEI.The embeddedness in the economic and informal institutional context in RMWs’RHEI is even more important than personal characteristics.Compared with migration destinations,RMWs’hometowns exert a more influential effect on their RHEI.However,that does not mean that the role of migration destinations can be undervalued.Actually,the better the social,economic,and institutional environments of migration destinations RMWs moved into is,the higher entrepreneurial intention they will have after returning to their hometowns.The article proposes a modified framework in combination of mixed embeddedness with double-layer embeddedness and proves that it is suitable for analyzing RMWs’RHEI.The framework has important implications for strengthening China’s RMWs to return home to start their own businesses.

Withdrawal Intention of Farmers from Vacant Rural Homesteads and Its Influencing Mechanism in Northeast China: A Case Study of Jilin Province

The effective use of land in Northeast China is of great significance for ensuring national food security and regional rural revitalization.In this study,based on the survey data collected from Jilin Province,Northeast China,we analyzed the vacancy rates of rural homesteads in suburban,outer suburban,and remote villages,as well as the withdrawal intention of rural-settled farmers,urbansettled farmers,and farmers with urban and rural dual residency from vacant homesteads.From the perspective of farmers’perceptions,this study constructed a theoretical framework of the influence mechanism of their withdrawal intention and analyzed such mechanism by constructing a structural equation model.The results indicated that:1)rural homestead vacancy rates increased with distance from the village to the city.2)rural-settled farmers showed a low withdrawal intention for vacant rural homesteads,followed by urban and rural dual-residence farmers,and urban-settled farmers showed the highest withdrawal intention.3)the relative importance of the factors influencing withdrawal intention is in the following order:policy awareness>interest perception>living environment perception>family characteristics.Finally,this study discussed the reformation of the homestead system and rural homestead transition in Northeast China,which can provide policy support to increase the potential of cultivated land and promote sustainable rural development and urban-rural coordination.

The Impact of Saudi Nurses’ Happiness on Their Turnover Intentions

Highly happy nurses are more productive, engaged and loyal. If nurses are satisfied, then their intention to leave is low. Aim: to investigate the impact of Saudi nurses’ happiness on their intention to turnover in the Kingdom of Saudi Arabia. Research Hypothesis: H0. There is no relationship between the nurses’ happiness on their intention to turnover among Saudi nurses. H1. The happy Saudi nurses will have a lower turnover intention among Saudi nurses in the Medina region. Design: Quantitative, cross-sectional, and correlational study designs have been used. Setting: Big public hospital in Medina from June to October 2022. Sample: A quota, convenience sample of 281 Saudi nurses. Tools: A. Oxford happiness inventory to measure the nurses’ happiness. B. Turnover Intention Scale to evaluate the Saudi nurses’ intention to leave their current job. Results: More than half of the nurses had moderate happiness, but more than 75% of the Saudi nurses had a desire to leave. The relationship between happiness and turnover intentions is negative. Conclusion: Magnet-like work environments in Saudi Arabia are critical to recruit and retain nurses with critical nursing shortages. Recommendations: Encourage governmental policy-makers to formulate national policies and KPIs in order to make them happy and retain them. .

Two-Sided Stable Matching Decision-Making Method Considering Matching Intention under a Hesitant Fuzzy Environment

In this paper,a stable two-sided matching(TSM)method considering the matching intention of agents under a hesitant fuzzy environment is proposed.The method uses a hesitant fuzzy element(HFE)as its basis.First,the HFE preference matrix is transformed into the normalized HFE preference matrix.On this basis,the distance and the projection of the normalized HFEs on positive and negative ideal solutions are calculated.Then,the normalized HFEs are transformed into agent satisfactions.Considering the stable matching constraints,a multiobjective programming model with the objective of maximizing the satisfactions of two-sided agents is constructed.Based on the agent satisfaction matrix,the matching intention matrix of two-sided agents is built.According to the agent satisfaction matrix and matching intention matrix,the comprehensive satisfaction matrix is set up.Furthermore,the multiobjective programming model based on satisfactions is transformed into a multiobjective programming model based on comprehensive satisfactions.Using the G-S algorithm,the multiobjective programming model based on comprehensive satisfactions is solved,and then the best TSM scheme is obtained.Finally,a terminal distribution example is used to verify the feasibility and effectiveness of the proposed method.

Effect of Family Cohesion on Depression of Chinese College Students in the COVID-19 Pandemic: Chain Mediation Effect of Perceived Social Support and Intentional Self-Regulation

Individuals’perceptions,attitudes,and patterns of getting along with family members are important factors influencing Chinese people’s self-evaluation.The aim of this study was to investigate the effect of family cohesion on depression and the role of perceived social support and intentional self-regulation in this association.A hypothesized model of the association of family cohesion,perceived social support,intentional self-regulation,and depression was examined.A convenience sampling method was used to survey 1,180 college students in Yunnan Province using self-report.Data were collected using the Family Cohesion Scale,the Perceived Social Support Scale,the Intentional Self-Regulation Scale,and the Center for Epidemiological Studies Depression Scale.The findings revealed low to moderate correlation between the variables studied.College students’family cohesion was a negative predictor of their depression.This association was also mediated by the knock-on effect of perceived social support and intentional self-regulation.These findings show how family cohesion affects college students’depressive status.Specifically,these results help demonstrate the importance of family cohesion,perceived social support,and intentional self-regulation in optimizing students’depression,which in turn can promote better psychological states.

Extension of Goal-Directed Behavior Model for Post-Pandemic Korean Travel Intentions to Alternative Local Destinations: Perceived Risk and Knowledge

Since the outbreak of COVID-19,tourists have been increasingly concerned over various risks of international travel,while knowledge of the pandemic appears to vary significantly.In addition,as travel restrictions continue to impact adversely on international tourism,tourism efforts should be placed more on the domestic markets.Via structural equation modeling,this study unearthed different risk factors impacting Korean travelers’choices of alternative local destinations in the post-pandemic era.In addition,this study extended the goal-directed behavior framework with the acquisition of perceived risk and knowledge of COVID-19,which was proven to hold a sig-nificantly superior explanatory power of tourists’decisions of local alternatives over foreign countries during the COVID-19 pandemic.Furthermore,desire was found to play an imminent mediating role in the conceptual mod-el,maximizing the impact of perceived risk on travel intentions.Henceforth,this research offers meaningful the-oretical implication as thefirst empirical study to deepen the goal-directed behaviour framework with perceived risk and knowledge in the context of post-COVID-19 era.It also serves as insightful knowledge for Korean tour-ism authorities and practitioners to understand local tourists’decision-making processes and tailor effective recovery strategy for domestic tourism.

Workplace Wellness,Mental Health Literacy,and Usage Intention of E-Mental Health amongst Digital Workers during the COVID-19

The prevalence of mental health problems in both Malaysian and global workplaces has significantly increased due to the presence of the coronavirus disease(COVID-19)pandemic,globalization,technology advancement in Industry 4.0,and other contributing factors.The pervasiveness of the issue poses a huge challenge to improving the occupational safety and health(OSH)of workers in various industries,especially in the digital industry.The emergence of the innovative industry is evident mainly due to the rapid development of Industry 4.0 and the rele-vant demands of multiple businesses in the digital transformation.Nonetheless,limited studies and academic dis-cussions were conducted on the OSH topic of digital employees.Hence,the current study serves tofill the existing gap and provide academic contributions by scrutinising the perceptions of digital workers regarding their work-place well-being,mental health literacy,and the impression of employing e-mental health.The objectives of this study are:1)To examine the mental health literacy and workplace wellness of digital workers,2)to explore the e-mental health usage intention and actual e-mental health utilization,and 3)to identify digital workers’feedback on e-mental health.In the current context,e-mental health focuses on three dimensions,namely,1)“health in our hand(HIOH)”,2)“interacting for health(IFH)”,and 3)“data enabling health(DEH)”.The present study employed an online cross-sectional survey and received 326 digital workers’completed responses.Variables,such as“mental health literacy(MHL)”,“workplace wellness(WW)”,and e-mental health intention and usage were explicated by analysing the data through descriptive statistics.The study results indicated a moderate to a high level of the MHL and the WW.More than half of the workers possessed a high intention level to employ e-mental health,with the HIOH dimension being the most prevalent domain.Nevertheless,the actual e-mental health usage was very low,owing to the online resources being a new concept amongst digital employees.Numerous confounding factors also existed in affecting the low usage,such as privacy concerns,data security levels,and health verification issues.In addition,the mental health issue has not been openly and widely discussed in Malay-sian workplaces due to stigmatisation.As such,the currentfindings could provide additional insights into the OSH literature;it could serve as a guideline for the OSH decision-makers,employers,and eHealth developers when establishing a feasible framework for the practical adoption of e-mental health services by digital workers.

Behavioral Intention to Continue Using a Library Mobile App

To meet the needs of today’s library users,institutions are developing library mobile apps(LMAs),as their libraries are increasingly intelligent and rely on deep learning.This paper explores the influencing factors and differences in the perception of LMAs at different time points after a user has downloaded an LMA.A research model was constructed based on the technology acceptance model.A questionnaire was designed and distributed twice to LMA users with an interval of three months to collect dynamic data.The analysis was based on structural equation modeling.The empirical results show that the perceived ease of use,the perceived usefulness,the social influence,and the facilitating conditions affected the users’behavioral intention,but their impacts were different at different times.As the usage time increases,the technology acceptance model is still universal for understanding the user perception of LMA.In addition,two extended variables(social impact and convenience)also affect the user’s behavior intention.User behavior is dynamic and changed over time.This study is important both theoretically and practically,as the results could be used to improve the service quality of LMAs and reduce the loss rate of users.Its findings may help the designers and developers of LMAs to optimize them from the perspective of a user and improve the service experience by providing a deeper understanding of the adoption behavior of information systems by LMA users.

Integrating the valence theory and the norm activation theory to understand consumers’ e-waste recycling intention

Electrical and electronic waste(e-waste)is a growing challenge,matching the widespread boom in the use of information and communication technology.Opposite to an alarming increasing amount of e-waste,a low rate of consumer engagement in ensuring the proper disposal of such materials intensifies the pressure on the exist‐ing e-waste crisis.To deal with this thorny problem,it is of great interest to grasp consumers’disposal and re‐cycling behavioral intentions.Therefore,this study attempts to understand complementary perspectives around consumers’e-waste recycling intention based on the integration of the valence theory and the norm activation theory.Four data mining models using classification and prediction-based algorithms,namely Chi squared automatic interaction detector(CHAID),Neural network,Discriminant analysis,and Quick,unbiased,efficient statistical tree(QUEST),were employed to analyze a set of the 398 data collected in Vietnam.The re‐sults revealed that the social support value is by far the most critical predictor,followed by the utilitarian value,task difficulty,and monetary risk.It is also noteworthy that the awareness of consequences,education background,the ascription of responsibility,and age were also ranked as critical affecting factors.The lowest influential predictors found in this study were income and gender.In addition,a comparison was made in terms of the classification performance of the four utilized data mining techniques.Based on several evalua‐tion measurements(confusion matrix,accuracy,precision,recall,specificity,F-measure,ROC curve,and AUC),the aggregated results suggested that CHAID and Neural network performed the best.The findings of this research are expected to assist policymakers and future researchers in updating all information surround‐ing consumer behavioral intention-related topics focusing on e-waste.Furthermore,the adoption of data min‐ing algorithms for prediction is another insight of this study,which may shed the light on data mining applica‐tions in such environmental studies in the future.

Review and Comparison of Classical Entrepreneurial Intention Models

The study of entrepreneurial models carries significance in guiding the development of entrepreneurial activities.On the basis of a literature review,this paper reviews and analyzes six classic and widely influential entrepreneurial models:entrepreneurial event model(EEM),entrepreneurial intention model(EIM),revised EIM,theory of planned behavior(TPB),economic psychological model(EPM),and structural model of entrepreneurial intention(SMEI).This paper aims to discuss the similarities and differences of these entrepreneurial intention models and their applications in different contexts,which carries important theoretical and practical significance for further research on entrepreneurial behavior and intention.

Factors Affecting the Entrepreneurial Intention of Students at Tan Trao University

Entrepreneurship is one of the popular choices for students after graduation from higher education.The study focuses on proposing a model to identify the factors affecting the entrepreneurial intention of students at Tan Trao University by researching some typical models in the world.By quantitative research methods based on a survey of 391 students,the study has shown that there are 5 factors affecting the entrepreneurial intention of students at Tan Trao University,including opportunity,motivation,perception of behavioral control,skills and resources for entrepreneurship.Thereby,the study proposes a number of solutions for the students,the university and other related parties to promote students’entrepreneurial intentions.

征迁改造居民的“知情意”——风险感知、政府信任及焦虑情绪对政策支持意愿的影响

以人为核心、关注民情、尊重民意是推进新型城镇化征迁改造的核心理念。已有研究主要关注居民的多元理性认知对征迁改造意愿的影响,对于情绪在认知与意愿的关系中发挥何种作用仍缺乏解释。运用质性研究方法,开发涵盖生计风险、适应风险和利益风险3个维度的征迁改造风险感知多维构念,以焦虑情绪为中介,建立征迁改造风险感知和政府信任对政策支持意愿影响的“知-情-意”模型。通过对18个新型城镇化改造试点地区居民的大规模实证调查发现:焦虑情绪在征迁改造风险感知对支持意愿的负向影响路径中发挥部分中介作用;政府信任通过直接方式以及减弱焦虑情绪的间接方式正向影响支持意愿,且直接效应显著大于间接效应。将焦虑情绪这一重要中介因素纳入居民意愿形成的分析框架,从及时评估并缓解居民焦虑情绪、面向不同群体实施差异化征迁改造政策、打通民意的“最先和最后一公里”以及提升基层政府公信力等方面为推动新型城镇化建设、避免群体性事件提供政策启示。

生育意愿存在同群效应吗?——来自中国社区的经验证据

在人口出生率持续低迷的背景下,研究居民生育意愿的影响因素具有重要的现实意义。现有研究对生育意愿的各种影响因素展开了大量讨论并取得了丰硕的成果,但关于生育意愿的研究大多假设个体为一个“独立”的决策者,并未充分考虑周围群体的行为决策对个体产生的影响。而在“心理效应”以及“学习效应”的作用下,个体的生育意愿也可能会受到他人行为决策的影响,呈现出一定的同群效应。本文基于研究假说,使用中国家庭追踪调查(CFPS)2018年的微观数据对生育意愿的同群效应进行实证分析。实证结果显示社区平均生育水平会对个体的生育意愿产生显著的正向影响,即个体的生育意愿确实存在着明显的同群效应。在稳健性检验中,采用工具变量法、替换被解释变量、缩减样本范围以及更换模型的方式对实证结果进行重新估计后,核心解释变量的系数方向及显著性与基础模型基本一致,表明实证结论具有较强的稳健性。异质性分析结果表明生育意愿的同群效应在城乡归属、年龄阶段以及婚姻状态不同的群体之间存在显著差异。首先,从城乡差异来看,由于乡村地区的社区居住形式以及传统观念等方面的不同,使同群效应对乡村个体的生育意愿所带来的边际影响要明显高于城镇个体;其次,从年龄差异来看,受到性格特点以及所处人生阶段不同等方面的影响,年轻个体的生育意愿所表现出的同群效应要弱于年龄较大的个体;再次,从婚姻状态的差异来看,由于在婚个体考虑生育的可能性更高并且可能会面临更多的关于生育决策的社会舆论压力,因此其生育意愿所表现出来的同群效应也要明显强于未婚等其他婚姻状态的个体;最后,调节效应的分析结果表明个体的认知水平以及对信息获取渠道的倾向会对其生育意愿的同群效应产生明显的调节效应,即当个体的认知水平较高或者个体将互联网作为主要的信息获取渠道时,其生育意愿所表现出的同群效应会相对减弱。为提高居民的生育意愿,社区可以尝试建立社区内部的生育信息交流平台,同时政府也应建立关于生育的舆情追踪监测机制,及时把握和干预社会中有关婚育的舆情动态,充分发挥同群效应对生育意愿的正向影响作用。

基于强化学习的对抗意图识别

未来智能化战争复杂多变,敌我双方往往以对抗博弈情况出现,当我方作为攻击者时,如何有效隐藏我方意图实施有效打击,以及我方作为防御者时如何识别敌方意图实施有效防御,对战争局势的走向起到决定性作用。为把握战争局势,做到“知己知彼,百战不殆”,基于强化学习方法针对对抗意图识别问题提出了解决方案。仿真结果表明,基于强化学习被识别者可以有效地进行意图欺骗,而识别者可以通过意图识别设计方法有效地迫使被识别者暴露意图,从而采取攻防措施。