In this commentary,we respond to Zhao et al’s recent paper which focuses on mechanisms underlying insomnia sufferers’engagement with acupuncture.Insomnia,a prevalent condition characterized by difficulty falling asl...In this commentary,we respond to Zhao et al’s recent paper which focuses on mechanisms underlying insomnia sufferers’engagement with acupuncture.Insomnia,a prevalent condition characterized by difficulty falling asleep and poor sleep quality,is associated with increased risk of cardiovascular disease,diabetes,and psychiatric illness.Acupuncture,a method involving the therapeutic placement of needles,has been widely accepted as a treatment for insomnia with minimal side effects.In fact,clinical trials suggest auricular acupuncture may improve sleep duration more than cognitive behavioral therapy.However,responses to acupuncture vary.Some patients find it extremely beneficial,while others view it as a routine treatment—or avoid it altogether due to needle phobia.Patient engagement is influenced by cultural beliefs,encouragement,motivation,prior experiences,and recommendations from peers or clinicians.Trust in the physician and testimonials from recovered patients are particularly important facilitators.Looking ahead,a holistic approach-integrating acupuncture with meditation,pranayama,yoga,and other restorative practices-may enhance treatment effectiveness and help patients achieve restorative sleep.展开更多
Ransomware is malware that encrypts data without permission,demanding payment for access.Detecting ransomware on Android platforms is challenging due to evolving malicious techniques and diverse application behaviors....Ransomware is malware that encrypts data without permission,demanding payment for access.Detecting ransomware on Android platforms is challenging due to evolving malicious techniques and diverse application behaviors.Traditional methods,such as static and dynamic analysis,suffer from polymorphism,code obfuscation,and high resource demands.This paper introduces a multi-stage approach to enhance behavioral analysis for Android ransomware detection,focusing on a reduced set of distinguishing features.The approach includes ransomware app collection,behavioral profile generation,dataset creation,feature identification,reduction,and classification.Experiments were conducted on∼3300 Android-based ransomware samples,despite the challenges posed by their evolving nature and complexity.The feature reduction strategy successfully reduced features by 80%,with only a marginal loss of detection accuracy(0.59%).Different machine learning algorithms are employed for classification and achieve 96.71%detection accuracy.Additionally,10-fold cross-validation demonstrated robustness,yielding an AUC-ROC of 99.3%.Importantly,latency and memory evaluations revealed that models using the reduced feature set achieved up to a 99%reduction in inference time and significant memory savings across classifiers.The proposed approach outperforms existing techniques by achieving high detection accuracy with a minimal feature set,also suitable for deployment in resource-constrained environments.Future work may extend datasets and include iOS-based ransomware applications.展开更多
The advent of the digital era has provided unprecedented opportunities for businesses to collect and analyze customer behavior data. Precision marketing, as a key means to improve marketing efficiency, highly depends ...The advent of the digital era has provided unprecedented opportunities for businesses to collect and analyze customer behavior data. Precision marketing, as a key means to improve marketing efficiency, highly depends on a deep understanding of customer behavior. This study proposes a theoretical framework for multi-dimensional customer behavior analysis, aiming to comprehensively capture customer behavioral characteristics in the digital environment. This framework integrates concepts of multi-source data including transaction history, browsing trajectories, social media interactions, and location information, constructing a theoretically more comprehensive customer profile. The research discusses the potential applications of this theoretical framework in precision marketing scenarios such as personalized recommendations, cross-selling, and customer churn prevention. Through analysis, the study points out that multi-dimensional analysis may significantly improve the targeting and theoretical conversion rates of marketing activities. However, the research also explores theoretical challenges that may be faced in the application process, such as data privacy and information overload, and proposes corresponding conceptual coping strategies. This study provides a new theoretical perspective on how businesses can optimize marketing decisions using big data thinking while respecting customer privacy, laying a foundation for future empirical research.展开更多
Background:Amid the global rise in adolescent sedentary behavior and psychological distress,extant research has largely focused on variable-level associations,neglecting symptom-level interactions.This study applies n...Background:Amid the global rise in adolescent sedentary behavior and psychological distress,extant research has largely focused on variable-level associations,neglecting symptom-level interactions.This study applies network analysis,aims to delineate the interconnections among sedentary time,social support,social exclusion,and psychological distress in Chinese students,and to identify core and bridge symptoms to inform targeted interventions.Methods:This study employed a cross-sectional design to investigate the complex relationships among sedentary behavior,social support,social exclusion,and psychological distress among Chinese students.The research involved 459 high school and university students,using network analysis and mediation models to examine these relationships.Results:Network analysis revealed that the network had a density of 58.33%and an average edge weight of 0.11.In terms of centrality,stress had the highest expected influence(EI=1.135),acting as the core amplifier in the network.Sedentary behavior demonstrated the highest bridging expected influence,functioning as a critical bridge for cross-community transmission.Conversely,friend support showed the lowest bridging EI with a negative value,indicating its effectiveness in blocking cross-community diffusion and alleviating symptoms.Conclusion:With stress acting as the most influential“core engine”within the symptom network and sedentary behavior serving as the key“bridge”for cross-community transmission,interventions should first target stress to weaken the overall symptom cascade,followed by reducing sedentary behavior or enhancing friend support to disrupt cross-community pathways,thereby achieving a core-bridge dual blockade.展开更多
We explored the relationship between Internet altruistic behavior(IAB)and subjective well-being(SWB)to estimate the effects and directionality of that predictive relationship between the two.Employing cross-lagged mod...We explored the relationship between Internet altruistic behavior(IAB)and subjective well-being(SWB)to estimate the effects and directionality of that predictive relationship between the two.Employing cross-lagged models we examined the interaction between IAB and SWB,among 339 college students(females=53.10%,mean age=19.02 years,SD=1.56 years).The students were tracked twice in a period of 5 months.Results showed that college students’IAB increased significantly,while their SWB remained relatively stable during the two measurement periods.IAB and SWB had significant simultaneous and sequential correlations.SWB at Time 1 positively predicted IAB at Time 2,however,IAB at Time 1 did not significantly predict SWB at Time 2.Moreover,there was cross-gender invariance in the cross-lagged effect between IAB and SWB.Research topics in the current environment exhibit remarkable practical significance.展开更多
With the rapid development of the Internet and e-commerce,e-commerce platforms have accumulated huge amounts of user behavior data.The emergence of big data technology provides a powerful means for in-depth analysis o...With the rapid development of the Internet and e-commerce,e-commerce platforms have accumulated huge amounts of user behavior data.The emergence of big data technology provides a powerful means for in-depth analysis of these data and insight into user behavior patterns and preferences.This paper elaborates on the application of big data technology in the analysis of user behavior on e-commerce platforms,including the technical methods of data collection,storage,processing and analysis,as well as the specific applications in the construction of user profiles,precision marketing,personalized recommendation,user retention and churn analysis,etc.,and discusses the challenges and countermeasures faced in the application.Through the study of actual cases,it demonstrates the remarkable effectiveness of big data technology in enhancing the competitiveness of e-commerce platforms and user experience.展开更多
Advancements in animal behavior quantification methods have driven the development of computational ethology,enabling fully automated behavior analysis.Existing multianimal pose estimation workflows rely on tracking-b...Advancements in animal behavior quantification methods have driven the development of computational ethology,enabling fully automated behavior analysis.Existing multianimal pose estimation workflows rely on tracking-bydetection frameworks for either bottom-up or top-down approaches,requiring retraining to accommodate diverse animal appearances.This study introduces InteBOMB,an integrated workflow that enhances top-down approaches by incorporating generic object tracking,eliminating the need for prior knowledge of target animals while maintaining broad generalizability.InteBOMB includes two key strategies for tracking and segmentation in laboratory environments and two techniques for pose estimation in natural settings.The“background enhancement”strategy optimizesforeground-backgroundcontrastiveloss,generating more discriminative correlation maps.The“online proofreading”strategy stores human-in-the-loop long-term memory and dynamic short-term memory,enabling adaptive updates to object visual features.The“automated labeling suggestion”technique reuses the visual features saved during tracking to identify representative frames for training set labeling.Additionally,the“joint behavior analysis”technique integrates these features with multimodal data,expanding the latent space for behavior classification and clustering.To evaluate the framework,six datasets of mice and six datasets of nonhuman primates were compiled,covering laboratory and natural scenes.Benchmarking results demonstrated a24%improvement in zero-shot generic tracking and a 21%enhancement in joint latent space performance across datasets,highlighting the effectiveness of this approach in robust,generalizable behavior analysis.展开更多
With a Critical Discourse Analysis approach, this essay reveals four types of discourses: discourse of examination, instruction, technology and regulation. Based on the analysis of power relation among those discourse...With a Critical Discourse Analysis approach, this essay reveals four types of discourses: discourse of examination, instruction, technology and regulation. Based on the analysis of power relation among those discourses, a vivid picture of teachers' identity at training-school has been clearly sketched. That is, teacher at training-school is a puppet acting as not only the transmitter of specific knowledge, but also the supervisor of rules and spokesman of institution.展开更多
This paper provided full and accurate material for Taibai Mountain eco-tourism and forecasted its potential market through investigating on the visitors of Taibai Mountain Nature Reserve and the surrounding forest par...This paper provided full and accurate material for Taibai Mountain eco-tourism and forecasted its potential market through investigating on the visitors of Taibai Mountain Nature Reserve and the surrounding forest parks eco-tourism tourist.By using Excel and mapping method,this study described the sample characteristics and tourist behavior.In addition,this paper also carried on descriptive statistics factorial analysis by using SPSS statistics software,analyzed the potential market according to tourists' characteristics of Taibai Mountain.The survey results showed that visitors of Taibai Mountain Nature Reserve mainly were middle-income young people,and the majority of tourists were with higher education.With the purpose of enjoying the scenery and relaxing,tourists were interested in natural ecological landscape of Taibai Mountain Nature Reserve.Tourists mainly came from Shaanxi Province and preferred to day trip,the travel route was single.There were a small number of tourists travelling for business,conference and medical treatment in Taibai Mountain Nature Reserve.According to the analysis,related countermeasures were given in this paper as the following:① Promoting activities should be focused on the big or medium cities in Shaanxi Province,such as Xi'an,Xianyang,Baoji,etc..Meanwhile,various means should be adopted to expand its influence and raise awareness around the provincial cities for attracting tourists.② Strengthening the infrastructure construction and improving comprehensive tourist reception capacity with the pursuit of the diversity of tourism resources,and create a good environment for the tourism market;③ Focusing on tourism product development;④ Protecting the ecological resources and developing ecotourism.展开更多
In this work, a set of GTN （Gurson-Tvergaard-Needleman） parameters of the Alloy52M dissimilar metal welded joint （DMWJ） have been calibrated, and a micromechanical analysis of in-plane constraint effects on the lo...In this work, a set of GTN （Gurson-Tvergaard-Needleman） parameters of the Alloy52M dissimilar metal welded joint （DMWJ） have been calibrated, and a micromechanical analysis of in-plane constraint effects on the local fracture behavior of two cracks, which located in the weakest regions of the DMWJ, has been investigated by the local approach based on the GTN damage model. The results show that the partition of the material and the variation of the q2 parameter make the J-resistance curves obtained by numerical simulations close to the experimental values. The numerical J-resistance curves and crack growth paths are consistent with the experiment results, which show that the GTN damage model can incorporate the in-plane constraint effect. Furthermore, after the stress, strain and damage fields at the crack tip during the crack propagation process have been calculated, and the change of the J-resistance curves, crack growth paths and fracture mechanism with in-plane constraint have been analyzed.展开更多
The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related in...The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related information of an employee are introduced, and methods for deletion of false data are presented. Next, the three-layer model(User, Subject, Keyword) is proposed for analysis of user behavior. Then, the proposed keyword selection algorithm based on a greedy approach, and the influence and propagation of an e-mail subject are defined. Finally, the e-mail user behavior is analyzed for the Enron organization. This study has considerable significance in subject recommendation and character recognition.展开更多
To clarify the solidification behavior of Re- and Ru-containing Ni-based single-crystal superalloys, four experimental alloys with varied contents of Re and Ru were investigated by differential scanning calorimetry （...To clarify the solidification behavior of Re- and Ru-containing Ni-based single-crystal superalloys, four experimental alloys with varied contents of Re and Ru were investigated by differential scanning calorimetry （DSC） and metallographic techniques. To obtain the - solvus temperatures, the stepwise solution and aging heat treatments were used. DSC analysis shows that Re leads to the increase in freezing range and γ-solvus temperature. On the contrast, Ru only has negligible influence on the freezing range, but leads to the lower γ-solvus temperature. In comparison with Ru, Re leads to more severe segregation and higher eutectic fractions in as-cast microstructures. Furthermore, the castability and phase stability of Ni-based superalloys were analyzed by the results of DSC and metallographic analysis, such as freezing range, critical nucleation temperature, γ-solvus temperature and eutectic fractions. It shows that Re leads to the wider freezing range and lower critical nucleation temperature, indicating the worse castability of Re-con- taining Ni-based single-crystal superalloys.展开更多
An FE model was developed to study thermal behavior during the rod and wire hot continuous rolling process. The FE code MSC. Marc was used in the simulation using implicit static arithmetic. The whole rolling process ...An FE model was developed to study thermal behavior during the rod and wire hot continuous rolling process. The FE code MSC. Marc was used in the simulation using implicit static arithmetic. The whole rolling process of 30 passes was separated and simulated with several continuous 3D elastic-plastic FE models. A rigid pushing body and a data transfer technique were introduced into this model. The on-line experiments were conducted on 304 stainless steel and GCr15 steel hot continuous rolling process to prove the results of simulation by implicit static FEM. The results show that the temperature results of finite element simulations are in good agreement with experiments, which indicate that the FE model developed in this study is effective and efficient.展开更多
This paper presents a simulation model based on the finite element method. The method is used to analyze the motion response and mooring line tension of the flatfish cage system in waves. The cage system consists of t...This paper presents a simulation model based on the finite element method. The method is used to analyze the motion response and mooring line tension of the flatfish cage system in waves. The cage system consists of top frames, netting, mooring lines, bottom frames, and floats. A series of scaled physical model tests in regular waves are conducted to verify the numerical model. The comparison results show that the simulated and the experimental results agree well under the wave conditions, and the maximum pitch of the bottom frame with two orientations is about 12o. The motion process of the whole cage system in the wave can be described with the computer visualized technology. Then, the mooring line tensions and the motion of the bottom frame with three kinds of weight are calculated under different wave conditions. According to the numerical results, the differences in mooring line tensions of flatfish cages with three weight modes are indistinct. The maximum pitch of the bottom frame decreases with the increase of the bottom weight.展开更多
This paper presents an innovative investigation on prototyping a digital twin(DT)as the platform for human-robot interactive welding and welder behavior analysis.This humanrobot interaction(HRI)working style helps to ...This paper presents an innovative investigation on prototyping a digital twin(DT)as the platform for human-robot interactive welding and welder behavior analysis.This humanrobot interaction(HRI)working style helps to enhance human users'operational productivity and comfort;while data-driven welder behavior analysis benefits to further novice welder training.This HRI system includes three modules:1)a human user who demonstrates the welding operations offsite with her/his operations recorded by the motion-tracked handles;2)a robot that executes the demonstrated welding operations to complete the physical welding tasks onsite;3)a DT system that is developed based on virtual reality(VR)as a digital replica of the physical human-robot interactive welding environment.The DT system bridges a human user and robot through a bi-directional information flow:a)transmitting demonstrated welding operations in VR to the robot in the physical environment;b)displaying the physical welding scenes to human users in VR.Compared to existing DT systems reported in the literatures,the developed one provides better capability in engaging human users in interacting with welding scenes,through an augmented VR.To verify the effectiveness,six welders,skilled with certain manual welding training and unskilled without any training,tested the system by completing the same welding job;three skilled welders produce satisfied welded workpieces,while the other three unskilled do not.A data-driven approach as a combination of fast Fourier transform(FFT),principal component analysis(PCA),and support vector machine(SVM)is developed to analyze their behaviors.Given an operation sequence,i.e.,motion speed sequence of the welding torch,frequency features are firstly extracted by FFT and then reduced in dimension through PCA,which are finally routed into SVM for classification.The trained model demonstrates a 94.44%classification accuracy in the testing dataset.The successful pattern recognition in skilled welder operations should benefit to accelerate novice welder training.展开更多
The main objective of this study is to analyze work travel-related behavior through a set of variables relative to socio-economic class, urban environment and travel characteristics. The Principal Component Analysis w...The main objective of this study is to analyze work travel-related behavior through a set of variables relative to socio-economic class, urban environment and travel characteristics. The Principal Component Analysis was applied in a sample consisting of workers of the S?o Paulo Metropolitan Area, based on the origin-destination home interview survey, carried out in 1997, in order to: 1) examine the interdependence between travel patterns and a set of socioeconomic and urban environment variables;2) determine if the original database can be synthetized on components. The results enabled to observe relations between the individual’s socio-economic class and car usage, characteristics of urban environment and destination choices, as well as age and non-motorized travel mode choice. It is then concluded that the database can be adequately summarized in three components for subsequent analysis: 1) urban environment;2) socio-economic class;and 3) family structure.展开更多
In order to reduce economic and life losses due to terrorism or accidental explosion threats, reinforced concrete （RC） slabs of buildings need to he designed or retrofitted to resist blast loading. In this paper the...In order to reduce economic and life losses due to terrorism or accidental explosion threats, reinforced concrete （RC） slabs of buildings need to he designed or retrofitted to resist blast loading. In this paper the dynamic behavior of RC slabs under blast loading and its influencing factors are studied. The numerical model of an RC slab subjected to blast loading is established using the explicit dynamic analysis software. Both the strain rate effect and the damage accumulation are taken into account in the material model. The dynamic responses of the RC slab subjected to blast loading are analyzed, and the influence of concrete strength, thickness and reinforcement ratio on the behavior of the RC slab under blast loading is numerically investigated. Based on the numerical results, some principles for blast-resistant design and retrofitting are proposed to improve the behavior of the RC slab subjected to blast loading.展开更多
Due to the increasing demand for security, the development of intelligent surveillance systems has attracted considerable attention in recent years. This study aims to develop a system that is able to identify whether...Due to the increasing demand for security, the development of intelligent surveillance systems has attracted considerable attention in recent years. This study aims to develop a system that is able to identify whether or not the people need help in a public place. Different from previous work, our work considers not only the behaviors of the target person but also the interaction between him and nearby people. In the paper, we propose an event alarm system which can detect the human behaviors and recognize the happening event through integrating the results generated from the single and group behavior analysis. Several new effective features are proposed in the study. Besides, a mechanism capable of extracting one-to-one and multiple-to-one relations is also developed. Experimental results show that the proposed approach can correctly detect human behaviors and provide the alarm messages when emergency events occur.展开更多
文摘In this commentary,we respond to Zhao et al’s recent paper which focuses on mechanisms underlying insomnia sufferers’engagement with acupuncture.Insomnia,a prevalent condition characterized by difficulty falling asleep and poor sleep quality,is associated with increased risk of cardiovascular disease,diabetes,and psychiatric illness.Acupuncture,a method involving the therapeutic placement of needles,has been widely accepted as a treatment for insomnia with minimal side effects.In fact,clinical trials suggest auricular acupuncture may improve sleep duration more than cognitive behavioral therapy.However,responses to acupuncture vary.Some patients find it extremely beneficial,while others view it as a routine treatment—or avoid it altogether due to needle phobia.Patient engagement is influenced by cultural beliefs,encouragement,motivation,prior experiences,and recommendations from peers or clinicians.Trust in the physician and testimonials from recovered patients are particularly important facilitators.Looking ahead,a holistic approach-integrating acupuncture with meditation,pranayama,yoga,and other restorative practices-may enhance treatment effectiveness and help patients achieve restorative sleep.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2021R1I1A3049788).
文摘Ransomware is malware that encrypts data without permission,demanding payment for access.Detecting ransomware on Android platforms is challenging due to evolving malicious techniques and diverse application behaviors.Traditional methods,such as static and dynamic analysis,suffer from polymorphism,code obfuscation,and high resource demands.This paper introduces a multi-stage approach to enhance behavioral analysis for Android ransomware detection,focusing on a reduced set of distinguishing features.The approach includes ransomware app collection,behavioral profile generation,dataset creation,feature identification,reduction,and classification.Experiments were conducted on∼3300 Android-based ransomware samples,despite the challenges posed by their evolving nature and complexity.The feature reduction strategy successfully reduced features by 80%,with only a marginal loss of detection accuracy(0.59%).Different machine learning algorithms are employed for classification and achieve 96.71%detection accuracy.Additionally,10-fold cross-validation demonstrated robustness,yielding an AUC-ROC of 99.3%.Importantly,latency and memory evaluations revealed that models using the reduced feature set achieved up to a 99%reduction in inference time and significant memory savings across classifiers.The proposed approach outperforms existing techniques by achieving high detection accuracy with a minimal feature set,also suitable for deployment in resource-constrained environments.Future work may extend datasets and include iOS-based ransomware applications.
文摘The advent of the digital era has provided unprecedented opportunities for businesses to collect and analyze customer behavior data. Precision marketing, as a key means to improve marketing efficiency, highly depends on a deep understanding of customer behavior. This study proposes a theoretical framework for multi-dimensional customer behavior analysis, aiming to comprehensively capture customer behavioral characteristics in the digital environment. This framework integrates concepts of multi-source data including transaction history, browsing trajectories, social media interactions, and location information, constructing a theoretically more comprehensive customer profile. The research discusses the potential applications of this theoretical framework in precision marketing scenarios such as personalized recommendations, cross-selling, and customer churn prevention. Through analysis, the study points out that multi-dimensional analysis may significantly improve the targeting and theoretical conversion rates of marketing activities. However, the research also explores theoretical challenges that may be faced in the application process, such as data privacy and information overload, and proposes corresponding conceptual coping strategies. This study provides a new theoretical perspective on how businesses can optimize marketing decisions using big data thinking while respecting customer privacy, laying a foundation for future empirical research.
文摘Background:Amid the global rise in adolescent sedentary behavior and psychological distress,extant research has largely focused on variable-level associations,neglecting symptom-level interactions.This study applies network analysis,aims to delineate the interconnections among sedentary time,social support,social exclusion,and psychological distress in Chinese students,and to identify core and bridge symptoms to inform targeted interventions.Methods:This study employed a cross-sectional design to investigate the complex relationships among sedentary behavior,social support,social exclusion,and psychological distress among Chinese students.The research involved 459 high school and university students,using network analysis and mediation models to examine these relationships.Results:Network analysis revealed that the network had a density of 58.33%and an average edge weight of 0.11.In terms of centrality,stress had the highest expected influence(EI=1.135),acting as the core amplifier in the network.Sedentary behavior demonstrated the highest bridging expected influence,functioning as a critical bridge for cross-community transmission.Conversely,friend support showed the lowest bridging EI with a negative value,indicating its effectiveness in blocking cross-community diffusion and alleviating symptoms.Conclusion:With stress acting as the most influential“core engine”within the symptom network and sedentary behavior serving as the key“bridge”for cross-community transmission,interventions should first target stress to weaken the overall symptom cascade,followed by reducing sedentary behavior or enhancing friend support to disrupt cross-community pathways,thereby achieving a core-bridge dual blockade.
基金supported by the Yizhou Organization Management Research Fund and the Hainan Province Graduate Student Innovation Research Project(grant no.Qhyb2024-135).
文摘We explored the relationship between Internet altruistic behavior(IAB)and subjective well-being(SWB)to estimate the effects and directionality of that predictive relationship between the two.Employing cross-lagged models we examined the interaction between IAB and SWB,among 339 college students(females=53.10%,mean age=19.02 years,SD=1.56 years).The students were tracked twice in a period of 5 months.Results showed that college students’IAB increased significantly,while their SWB remained relatively stable during the two measurement periods.IAB and SWB had significant simultaneous and sequential correlations.SWB at Time 1 positively predicted IAB at Time 2,however,IAB at Time 1 did not significantly predict SWB at Time 2.Moreover,there was cross-gender invariance in the cross-lagged effect between IAB and SWB.Research topics in the current environment exhibit remarkable practical significance.
文摘With the rapid development of the Internet and e-commerce,e-commerce platforms have accumulated huge amounts of user behavior data.The emergence of big data technology provides a powerful means for in-depth analysis of these data and insight into user behavior patterns and preferences.This paper elaborates on the application of big data technology in the analysis of user behavior on e-commerce platforms,including the technical methods of data collection,storage,processing and analysis,as well as the specific applications in the construction of user profiles,precision marketing,personalized recommendation,user retention and churn analysis,etc.,and discusses the challenges and countermeasures faced in the application.Through the study of actual cases,it demonstrates the remarkable effectiveness of big data technology in enhancing the competitiveness of e-commerce platforms and user experience.
基金supported by the STI 2030-Major Projects(2022ZD0211900,2022ZD0211902)STI 2030-Major Projects(2021ZD0204500,2021ZD0204503)+1 种基金National Natural Science Foundation of China(32171461)National Key Research and Development Program of China(2023YFC3208303)。
文摘Advancements in animal behavior quantification methods have driven the development of computational ethology,enabling fully automated behavior analysis.Existing multianimal pose estimation workflows rely on tracking-bydetection frameworks for either bottom-up or top-down approaches,requiring retraining to accommodate diverse animal appearances.This study introduces InteBOMB,an integrated workflow that enhances top-down approaches by incorporating generic object tracking,eliminating the need for prior knowledge of target animals while maintaining broad generalizability.InteBOMB includes two key strategies for tracking and segmentation in laboratory environments and two techniques for pose estimation in natural settings.The“background enhancement”strategy optimizesforeground-backgroundcontrastiveloss,generating more discriminative correlation maps.The“online proofreading”strategy stores human-in-the-loop long-term memory and dynamic short-term memory,enabling adaptive updates to object visual features.The“automated labeling suggestion”technique reuses the visual features saved during tracking to identify representative frames for training set labeling.Additionally,the“joint behavior analysis”technique integrates these features with multimodal data,expanding the latent space for behavior classification and clustering.To evaluate the framework,six datasets of mice and six datasets of nonhuman primates were compiled,covering laboratory and natural scenes.Benchmarking results demonstrated a24%improvement in zero-shot generic tracking and a 21%enhancement in joint latent space performance across datasets,highlighting the effectiveness of this approach in robust,generalizable behavior analysis.
文摘With a Critical Discourse Analysis approach, this essay reveals four types of discourses: discourse of examination, instruction, technology and regulation. Based on the analysis of power relation among those discourses, a vivid picture of teachers' identity at training-school has been clearly sketched. That is, teacher at training-school is a puppet acting as not only the transmitter of specific knowledge, but also the supervisor of rules and spokesman of institution.
文摘This paper provided full and accurate material for Taibai Mountain eco-tourism and forecasted its potential market through investigating on the visitors of Taibai Mountain Nature Reserve and the surrounding forest parks eco-tourism tourist.By using Excel and mapping method,this study described the sample characteristics and tourist behavior.In addition,this paper also carried on descriptive statistics factorial analysis by using SPSS statistics software,analyzed the potential market according to tourists' characteristics of Taibai Mountain.The survey results showed that visitors of Taibai Mountain Nature Reserve mainly were middle-income young people,and the majority of tourists were with higher education.With the purpose of enjoying the scenery and relaxing,tourists were interested in natural ecological landscape of Taibai Mountain Nature Reserve.Tourists mainly came from Shaanxi Province and preferred to day trip,the travel route was single.There were a small number of tourists travelling for business,conference and medical treatment in Taibai Mountain Nature Reserve.According to the analysis,related countermeasures were given in this paper as the following:① Promoting activities should be focused on the big or medium cities in Shaanxi Province,such as Xi'an,Xianyang,Baoji,etc..Meanwhile,various means should be adopted to expand its influence and raise awareness around the provincial cities for attracting tourists.② Strengthening the infrastructure construction and improving comprehensive tourist reception capacity with the pursuit of the diversity of tourism resources,and create a good environment for the tourism market;③ Focusing on tourism product development;④ Protecting the ecological resources and developing ecotourism.
基金supported by the National Natural Science Foundation of China(Grant No.51605292)the Natural Science Foundation of Shanghai(Grant No.15ZR1429000)the Youth Foundation of Shanghai(Grant No.ZZslg15013)
文摘In this work, a set of GTN （Gurson-Tvergaard-Needleman） parameters of the Alloy52M dissimilar metal welded joint （DMWJ） have been calibrated, and a micromechanical analysis of in-plane constraint effects on the local fracture behavior of two cracks, which located in the weakest regions of the DMWJ, has been investigated by the local approach based on the GTN damage model. The results show that the partition of the material and the variation of the q2 parameter make the J-resistance curves obtained by numerical simulations close to the experimental values. The numerical J-resistance curves and crack growth paths are consistent with the experiment results, which show that the GTN damage model can incorporate the in-plane constraint effect. Furthermore, after the stress, strain and damage fields at the crack tip during the crack propagation process have been calculated, and the change of the J-resistance curves, crack growth paths and fracture mechanism with in-plane constraint have been analyzed.
基金sponsored by the National Natural Science Foundation of China under grant number No.61100008,61201084the China Postdoctoral Science Foundation under Grant No.2013M541346+3 种基金Heilongiiang Postdoctoral Special Fund(Postdoctoral Youth Talent Program)under Grant No.LBH-TZ0504Heilongjiang Postdoctoral Fund under Grant No.LBH-Z13058the Natural Science Foundation of Heilongjiang Province of China under Grant No.QC2015076The Fundamental Research Funds for the Central Universities of China under grant number HEUCF100602
文摘The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related information of an employee are introduced, and methods for deletion of false data are presented. Next, the three-layer model(User, Subject, Keyword) is proposed for analysis of user behavior. Then, the proposed keyword selection algorithm based on a greedy approach, and the influence and propagation of an e-mail subject are defined. Finally, the e-mail user behavior is analyzed for the Enron organization. This study has considerable significance in subject recommendation and character recognition.
基金financially supported by the National High Technology Research and Development Program of China (No. 2012AA03A511)the National Natural Science Foundation of China (Nos. 51171151 and 51331005)+2 种基金the State Key Laboratory of Solidification Processing in Northwestern Polytechnical University (No. SKLSP201310)the Science and Technology Program of Shaanxi Province(No.2013JQ6003)the Research Foundation of Education Bureau of Shaanxi Province (No. 2013JK0898)
文摘To clarify the solidification behavior of Re- and Ru-containing Ni-based single-crystal superalloys, four experimental alloys with varied contents of Re and Ru were investigated by differential scanning calorimetry （DSC） and metallographic techniques. To obtain the - solvus temperatures, the stepwise solution and aging heat treatments were used. DSC analysis shows that Re leads to the increase in freezing range and γ-solvus temperature. On the contrast, Ru only has negligible influence on the freezing range, but leads to the lower γ-solvus temperature. In comparison with Ru, Re leads to more severe segregation and higher eutectic fractions in as-cast microstructures. Furthermore, the castability and phase stability of Ni-based superalloys were analyzed by the results of DSC and metallographic analysis, such as freezing range, critical nucleation temperature, γ-solvus temperature and eutectic fractions. It shows that Re leads to the wider freezing range and lower critical nucleation temperature, indicating the worse castability of Re-con- taining Ni-based single-crystal superalloys.
基金Item Sponsored by Youth Science Technology Elitist Foundation of Dalian Local Government (2001-122)
文摘An FE model was developed to study thermal behavior during the rod and wire hot continuous rolling process. The FE code MSC. Marc was used in the simulation using implicit static arithmetic. The whole rolling process of 30 passes was separated and simulated with several continuous 3D elastic-plastic FE models. A rigid pushing body and a data transfer technique were introduced into this model. The on-line experiments were conducted on 304 stainless steel and GCr15 steel hot continuous rolling process to prove the results of simulation by implicit static FEM. The results show that the temperature results of finite element simulations are in good agreement with experiments, which indicate that the FE model developed in this study is effective and efficient.
基金financially supported by the Earmarked Fund for Modern Agro-industry Technology Research System(Grant No.CARS-50-G05)the National Natural Science Foundation of China(Grant Nos.31101938+1 种基金30972256 and 51239002)Science and Technology Development Project of Shandong Province(Grant No.2009GG10005005)
文摘This paper presents a simulation model based on the finite element method. The method is used to analyze the motion response and mooring line tension of the flatfish cage system in waves. The cage system consists of top frames, netting, mooring lines, bottom frames, and floats. A series of scaled physical model tests in regular waves are conducted to verify the numerical model. The comparison results show that the simulated and the experimental results agree well under the wave conditions, and the maximum pitch of the bottom frame with two orientations is about 12o. The motion process of the whole cage system in the wave can be described with the computer visualized technology. Then, the mooring line tensions and the motion of the bottom frame with three kinds of weight are calculated under different wave conditions. According to the numerical results, the differences in mooring line tensions of flatfish cages with three weight modes are indistinct. The maximum pitch of the bottom frame decreases with the increase of the bottom weight.
文摘This paper presents an innovative investigation on prototyping a digital twin(DT)as the platform for human-robot interactive welding and welder behavior analysis.This humanrobot interaction(HRI)working style helps to enhance human users'operational productivity and comfort;while data-driven welder behavior analysis benefits to further novice welder training.This HRI system includes three modules:1)a human user who demonstrates the welding operations offsite with her/his operations recorded by the motion-tracked handles;2)a robot that executes the demonstrated welding operations to complete the physical welding tasks onsite;3)a DT system that is developed based on virtual reality(VR)as a digital replica of the physical human-robot interactive welding environment.The DT system bridges a human user and robot through a bi-directional information flow:a)transmitting demonstrated welding operations in VR to the robot in the physical environment;b)displaying the physical welding scenes to human users in VR.Compared to existing DT systems reported in the literatures,the developed one provides better capability in engaging human users in interacting with welding scenes,through an augmented VR.To verify the effectiveness,six welders,skilled with certain manual welding training and unskilled without any training,tested the system by completing the same welding job;three skilled welders produce satisfied welded workpieces,while the other three unskilled do not.A data-driven approach as a combination of fast Fourier transform(FFT),principal component analysis(PCA),and support vector machine(SVM)is developed to analyze their behaviors.Given an operation sequence,i.e.,motion speed sequence of the welding torch,frequency features are firstly extracted by FFT and then reduced in dimension through PCA,which are finally routed into SVM for classification.The trained model demonstrates a 94.44%classification accuracy in the testing dataset.The successful pattern recognition in skilled welder operations should benefit to accelerate novice welder training.
文摘The main objective of this study is to analyze work travel-related behavior through a set of variables relative to socio-economic class, urban environment and travel characteristics. The Principal Component Analysis was applied in a sample consisting of workers of the S?o Paulo Metropolitan Area, based on the origin-destination home interview survey, carried out in 1997, in order to: 1) examine the interdependence between travel patterns and a set of socioeconomic and urban environment variables;2) determine if the original database can be synthetized on components. The results enabled to observe relations between the individual’s socio-economic class and car usage, characteristics of urban environment and destination choices, as well as age and non-motorized travel mode choice. It is then concluded that the database can be adequately summarized in three components for subsequent analysis: 1) urban environment;2) socio-economic class;and 3) family structure.
基金Supported by National Natural Science Foundation of China (No. 50638030)National Key Technologies R&D Program of China (No. 2006BAJ13B02).
文摘In order to reduce economic and life losses due to terrorism or accidental explosion threats, reinforced concrete （RC） slabs of buildings need to he designed or retrofitted to resist blast loading. In this paper the dynamic behavior of RC slabs under blast loading and its influencing factors are studied. The numerical model of an RC slab subjected to blast loading is established using the explicit dynamic analysis software. Both the strain rate effect and the damage accumulation are taken into account in the material model. The dynamic responses of the RC slab subjected to blast loading are analyzed, and the influence of concrete strength, thickness and reinforcement ratio on the behavior of the RC slab under blast loading is numerically investigated. Based on the numerical results, some principles for blast-resistant design and retrofitting are proposed to improve the behavior of the RC slab subjected to blast loading.
基金supported by the“MOST”under Grant No.104-2221-E-259-024-MY2
文摘Due to the increasing demand for security, the development of intelligent surveillance systems has attracted considerable attention in recent years. This study aims to develop a system that is able to identify whether or not the people need help in a public place. Different from previous work, our work considers not only the behaviors of the target person but also the interaction between him and nearby people. In the paper, we propose an event alarm system which can detect the human behaviors and recognize the happening event through integrating the results generated from the single and group behavior analysis. Several new effective features are proposed in the study. Besides, a mechanism capable of extracting one-to-one and multiple-to-one relations is also developed. Experimental results show that the proposed approach can correctly detect human behaviors and provide the alarm messages when emergency events occur.
