The development of Traditional Chinese Medicine(TCM)in Thailand can be traced back to the Sukhothai Kingdom period in the 13th century,which was introduced by immigrants.In 1995,the Ministry of Public Health in Thaila...The development of Traditional Chinese Medicine(TCM)in Thailand can be traced back to the Sukhothai Kingdom period in the 13th century,which was introduced by immigrants.In 1995,the Ministry of Public Health in Thailand established the Thai-Chinese Medicine Exchange Center to specifically support the development of TCM.In 1997,the health departments of Thailand and China signed a Memorandum of Understanding regarding cooperation in the fields of health sciences and pharmaceuticals.展开更多
Recently, use of mobile communicational devices in field data collection is increasing such as smart phones and cellular phones due to emergence of embedded Global Position System GPS and Wi-Fi Internet access. Accura...Recently, use of mobile communicational devices in field data collection is increasing such as smart phones and cellular phones due to emergence of embedded Global Position System GPS and Wi-Fi Internet access. Accurate timely and handy field data collection is required for disaster management and emergency quick responses. In this article, we introduce web-based GIS system to collect the field data by personal mobile phone through Post Office Protocol POP3 mail server. The main objective of this work is to demonstrate real-time field data collection method to the students using their mobile phone to collect field data by timely and handy manners, either individual or group survey in local or global scale research.展开更多
This paper proposes a personalized headrelated transfer function(HRTF)prediction method based on Light GBM using anthropometric data.Considering the overfitting problems of the current training-based prediction method...This paper proposes a personalized headrelated transfer function(HRTF)prediction method based on Light GBM using anthropometric data.Considering the overfitting problems of the current training-based prediction methods,we use Light GBM and a specific network structure to prevent over-fitting and enhance the prediction performance.By decomposing and combining the data to be predicted,we set up 90 Light GBM models to separately predict the 90instants of HRTF in log domain.At the same time,the method of 10-fold cross-validation is used to score the accuracy of the model.For models with scores below 80 points,Bayesian optimization is used to adjust model hyperparameters to obtain a better model structure.The results obtained by Light GBM are evaluated with spectral distortion(SD)which can show the fitting error between the prediction and the original data.The mean SD values of both ears on the whole test set are 2.32 d B and 2.28 d B respectively.Compared with the non-linear regression method and the latest method,SD value of Light GBM-based method relatively decreases by 83.8%and 48.5%.展开更多
With the rapid development of artificial intelligence and Internet of Things technologies,video action recognition technology is widely applied in various scenarios,such as personal life and industrial production.Howe...With the rapid development of artificial intelligence and Internet of Things technologies,video action recognition technology is widely applied in various scenarios,such as personal life and industrial production.However,while enjoying the convenience brought by this technology,it is crucial to effectively protect the privacy of users’video data.Therefore,this paper proposes a video action recognition method based on personalized federated learning and spatiotemporal features.Under the framework of federated learning,a video action recognition method leveraging spatiotemporal features is designed.For the local spatiotemporal features of the video,a new differential information extraction scheme is proposed to extract differential features with a single RGB frame as the center,and a spatialtemporal module based on local information is designed to improve the effectiveness of local feature extraction;for the global temporal features,a method of extracting action rhythm features using differential technology is proposed,and a timemodule based on global information is designed.Different translational strides are used in the module to obtain bidirectional differential features under different action rhythms.Additionally,to address user data privacy issues,the method divides model parameters into local private parameters and public parameters based on the structure of the video action recognition model.This approach enhancesmodel training performance and ensures the security of video data.The experimental results show that under personalized federated learning conditions,an average accuracy of 97.792%was achieved on the UCF-101 dataset,which is non-independent and identically distributed(non-IID).This research provides technical support for privacy protection in video action recognition.展开更多
Personalized medicine is the development of “tailored” therapies that reflect traditional medical approaches with the incorporation of the patient’s unique genetic profile and the environmental basis of the disease...Personalized medicine is the development of “tailored” therapies that reflect traditional medical approaches with the incorporation of the patient’s unique genetic profile and the environmental basis of the disease. These individualized strategies encompass disease prevention and diagnosis, as well as treatment strategies. Today’s healthcare workforce is faced with the availability of massive amounts of patient- and disease-related data. When mined effectively, these data will help produce more efficient and effective diagnoses and treatment, leading to better prognoses for patients at both the individual and population level. Designing preventive and therapeutic interventions for those patients who will benefit most while minimizing side effects and controlling healthcare costs requires bringing diverse data sources together in an analytic paradigm. A resource to clinicians in the development and application of personalized medicine is largely facilitated, perhaps even driven, by the analysis of “big data”. For example, the availability of clinical data warehouses is a significant resource for clinicians in practicing personalized medicine. These “big data” repositories can be queried by clinicians, using specific questions, with data used to gain an understanding of challenges in patient care and treatment. Health informaticians are critical partners to data analytics including the use of technological infrastructures and predictive data mining strategies to access data from multiple sources, assisting clinicians’ interpretation of data and development of personalized, targeted therapy recommendations. In this paper, we look at the concept of personalized medicine, offering perspectives in four important, influencing topics: 1) the availability of “big data” and the role of biomedical informatics in personalized medicine, 2) the need for interdisciplinary teams in the development and evaluation of personalized therapeutic approaches, and 3) the impact of electronic medical record systems and clinical data warehouses on the field of personalized medicine. In closing, we present our fourth perspective, an overview to some of the ethical concerns related to personalized medicine and health equity.展开更多
The advent of the big data era has opened up unprecedented quantifiable dimensions for all walks of life,while also presented many opportunities and challenges.The widespread application of big data in the field of ed...The advent of the big data era has opened up unprecedented quantifiable dimensions for all walks of life,while also presented many opportunities and challenges.The widespread application of big data in the field of education will inevitably promote the innovation and transformation of the higher education in colleges and universities which introduce new opportunities and challenges to personalized education in colleges and universities.How to promote the indepth integration of big data and higher education to meet the needs of students’personalized development is one of the hot topics in the theoretical field today.In view of this,this article starts with explaining the connotation of personalized education in colleges and universities,analyzes the opportunities and challenges faced by personalized education in colleges and universities under the context of big data,and proposes the ideas of innovating personalized education in colleges and universities under the context of big data.展开更多
Although the existing legal norms and judicial practic-es can provide basic guidance for the right to personal data portabili-ty, it can be concluded that there are obstacles to the realization of this right through e...Although the existing legal norms and judicial practic-es can provide basic guidance for the right to personal data portabili-ty, it can be concluded that there are obstacles to the realization of this right through empirical research of the privacy policies of 66 mobile apps, such as whether they have stipulations on the right to personal data portability, whether they are able to derive copies of personal in-formation automatically, whether there are textual examples, whether ID verification is required, whether the copied documents are encrypt-ed, and whether the scope of personal information involved is consis-tent. This gap in practice, on the one hand, reflects the misunderstand-ing of the right to personal data portability, and on the other hand, is a result of the negative externalities, practical costs and technical lim-itations of the right to personal data portability. Based on rethinking the right to data portability, we can somehow solve practical problems concerning the right to personal data portability through multiple measures such as promoting the fulfillment of this right by legislation, optimizing technology-oriented operations, refining response process mechanisms, and enhancing system interoperability.展开更多
The purpose of this study is to investigate the sleep habits, cervical health status, and the demand and preference for pillow products of different populations through data analysis. A total of 780 valid responses we...The purpose of this study is to investigate the sleep habits, cervical health status, and the demand and preference for pillow products of different populations through data analysis. A total of 780 valid responses were gathered via an online questionnaire to explore the sleep habits, cervical health conditions, and pillow product preferences of modern individuals. The study found that sleeping late and staying up late are common, and the use of electronic devices and caffeine consumption have a negative impact on sleep. Most respondents have cervical discomfort and have varying satisfaction with pillows, which shows their demand for personalized pillows. The machine learning model for predicting the demand of latex pillow was constructed and optimized to provide personalized pillow recommendation, aiming to improve sleep quality and provide market data for sleep product developers.展开更多
This paper deals with personal data use by firms in the e-business environment from the viewpoint of business administration and information ethics. Whereas the tremendous development of information and communication ...This paper deals with personal data use by firms in the e-business environment from the viewpoint of business administration and information ethics. Whereas the tremendous development of information and communication technology (ICT) has made it easier for firms to acquire, store, share, and utilise personal data on their customers, firms that use personal data are exposed to risks related to privacy issues. Since individuals fear the invasion of their privacy, the failure of a firm to appear or remain trustworthy would make it difficult for it to maintain accurate, up-to-date databases and to construct desirable business processes, which would affect the bottom line. Therefore, modern firms should do what they can to ensure that their customers trust them. For them, one promising way to remain trustworthy is to behave as a moral agent. Although it is difficult for any firm to meet the conditions necessary to be a moral agent, competence in behaving as a moral agent is a hard-to-imitate capability af firms for which personal data use is vital for enjoying the benefits of business relationships in the e-business environment.展开更多
The right to the protection of personal data is an important human right in the era of big data and a constitutional right based on the national protection obligation and the theory of human dignity,making it of speci...The right to the protection of personal data is an important human right in the era of big data and a constitutional right based on the national protection obligation and the theory of human dignity,making it of special significance for the realization of citizenship in a digital society.It can be seen from an examination of the constitutional texts of various countries in the world that the right to the protection of personal data as a constitutional right has rich normative connotations,and the key legal link to realize this right lies in the national legislature actively fulfilling its obligation to shape and specify the protection of personal data in accordance with the entrustment of the constitutional norms.Given the constitutional principles of fundamental rights protection,i.e.,realizing the constitutional status of the right to the protection of personal data as a basic right by means of institutional guarantees,the legislature should first adhere to the constitutionality principle of data protection legislation.Second,a multi-level data protection legal system centered on the right to the protection of personal data should be established.Finally,the institutional guarantee mechanism for the protection of personal data should be continuously improved through constitutional interpretation.展开更多
Mobile operators face the challenge of how to best design a service-centric network that can effectively process the rapidly increasing number of bandwidth-intensive user requests while providing a higher quality of e...Mobile operators face the challenge of how to best design a service-centric network that can effectively process the rapidly increasing number of bandwidth-intensive user requests while providing a higher quality of experience(QoE). Existing content distribution networks(CDN) and mobile content distribution networks(mCDN) have both latency and throughput limitations due to being multiple network hops away from end-users. Here, we first propose a new Personalized Edge Caching System(PECS) architecture that employs big data analytics and mobile edge caching to provide personalized service access at the edge of the mobile network. Based on the proposed system architecture, the edge caching strategy based on user behavior and trajectory is analyzed. Employing our proposed PECS strategies, we use data mining algorithms to analyze the personalized trajectory and service usage patterns. Our findings provide guidance on how key technologies of PECS can be employed for current and future networks. Finally, we highlight the challenges associated with realizing such a system in 5G and beyond.展开更多
The exercise recommendation system is emerging as a promising application in online learning scenarios,providing personalized recommendations to assist students with explicit learning directions.Existing solutions gen...The exercise recommendation system is emerging as a promising application in online learning scenarios,providing personalized recommendations to assist students with explicit learning directions.Existing solutions generally follow a collaborative filtering paradigm,while the implicit connections between students(exercises)have been largely ignored.In this study,we aim to propose an exercise recommendation paradigm that can reveal the latent connections between student-student(exercise-exercise).Specifically,a new framework was proposed,namely personalized exercise recommendation with student and exercise portraits(PERP).It consists of three sequential and interdependent modules:Collaborative student exercise graph(CSEG)construction,joint random walk,and recommendation list optimization.Technically,CSEG is created as a unified heterogeneous graph with students’response behaviors and student(exercise)relationships.Then,a joint random walk to take full advantage of the spectral properties of nearly uncoupled Markov chains is performed on CSEG,which allows for full exploration of both similar exercises that students have finished and connections between students(exercises)with similar portraits.Finally,we propose to optimize the recommendation list to obtain different exercise suggestions.After analyses of two public datasets,the results demonstrated that PERP can satisfy novelty,accuracy,and diversity.展开更多
Advancing the application of safety and health(S&H)technologies is likely to remain a value in the mining industry.However,any information that technologies generate must be translated from the organization to the...Advancing the application of safety and health(S&H)technologies is likely to remain a value in the mining industry.However,any information that technologies generate must be translated from the organization to the workforce in a targeted way to result in sustainable change.Using a case study approach with continuous personal dust monitors(CPDMs),this paper argues for an organizational focus on technology integration.Although CPDMs provide mineworkers with near real-time feedback about their respirable coal dust exposure,they do not ensure that workers or the organization will continuously use the information to learn about and reduce exposure sources.This study used self-determination theory(SDT)to help three mines manage and communicate about information learned from the CPDM technology.Specifically,35 mineworkers participated in two mixed-method data collection efforts to discuss why they do or do not use CPDMs to engage in dust-reducing practices.Subsequently,the data was analyzed to better understand how organizations can improve the integration of technology through their management systems.Results indicate that using the CPDM to reduce sources of dust exposure is consistent with mineworkers’self-values to protect their health and not necessarily because of compliance to a manager or mine.展开更多
This comprehensive study investigates the multifaceted impact of AI-powered personalization on strategic communications, delving deeply into its opportunities, challenges, and future directions. Employing a rigorous m...This comprehensive study investigates the multifaceted impact of AI-powered personalization on strategic communications, delving deeply into its opportunities, challenges, and future directions. Employing a rigorous mixed-methods approach, we conduct an in-depth analysis of the effects of AI-driven personalization on audience engagement, brand perception, and conversion rates across various industries and communication channels. Our findings reveal that while AI-powered personalization significantly enhances communication effectiveness and offers unprecedented opportunities for audience connection, it also raises critical ethical considerations and implementation challenges. The study contributes substantially to the growing body of literature on AI in communications, offering both theoretical insights and practical guidelines for professionals navigating this rapidly evolving landscape. Furthermore, we propose a novel framework for ethical AI implementation in strategic communications and outline a robust agenda for future research in this dynamic field.展开更多
Personal health record （PHR） enables patients to manage their own electronic medical records （EMR） in a centralized way, and it is oRen outsourced to be stored in a third-party server. In this paper we propose a n...Personal health record （PHR） enables patients to manage their own electronic medical records （EMR） in a centralized way, and it is oRen outsourced to be stored in a third-party server. In this paper we propose a novel secure and scalable system for sharing PHRs. We focus on the multiple data owner scenario, and divide the users in the system into multiple security domains that greatly reduce the key management complexity for owners and users. A high degree of patient privacy is guaranteed by exploiting hierarchical and multi- authority attribute-sets based encryption （HM- ASBE）. Our system not only supports compound attributes due to flexible attribute sets combinations, but also achieves fine-grained access control. Our scheme supports efficient on-demand user/attribute revocation and break-glass access under emergency scenarios.展开更多
Before the implementation of product data management (PDM) system, person model and enterprise process model (EPM) must be firstly established. For the convenience of project management, all the related users must be ...Before the implementation of product data management (PDM) system, person model and enterprise process model (EPM) must be firstly established. For the convenience of project management, all the related users must be allocated to the “Person User Role Group” net. Based on the person model and the direction of information flow, the EPM is established subsequently. The EPM consists of several release levels, in which the access controls are defined. The EPM procedure shows the blueprint of the workflow process structure. The establishment of person model and EPM in an enterprise has been instanced at the end of this paper.展开更多
Personal credit risk assessment is an important part of the development of financial enterprises. Big data credit investigation is an inevitable trend of personal credit risk assessment, but some data are missing and ...Personal credit risk assessment is an important part of the development of financial enterprises. Big data credit investigation is an inevitable trend of personal credit risk assessment, but some data are missing and the amount of data is small, so it is difficult to train. At the same time, for different financial platforms, we need to use different models to train according to the characteristics of the current samples, which is time-consuming. <span style="font-family:Verdana;">In view of</span><span style="font-family:Verdana;"> these two problems, this paper uses the idea of transfer learning to build a transferable personal credit risk model based on Instance-based Transfer Learning (Instance-based TL). The model balances the weight of the samples in the source domain, and migrates the existing large dataset samples to the target domain of small samples, and finds out the commonness between them. At the same time, we have done a lot of experiments on the selection of base learners, including traditional machine learning algorithms and ensemble learning algorithms, such as decision tree, logistic regression, </span><span style="font-family:Verdana;">xgboost</span> <span style="font-family:Verdana;">and</span><span style="font-family:Verdana;"> so on. The datasets are from P2P platform and bank, the results show that the AUC value of Instance-based TL is 24% higher than that of the traditional machine learning model, which fully proves that the model in this paper has good application value. The model’s evaluation uses AUC, prediction, recall, F1. These criteria prove that this model has good application value from many aspects. At present, we are trying to apply this model to more fields to improve the robustness and applicability of the model;on the other hand, we are trying to do more in-depth research on domain adaptation to enrich the model.</span>展开更多
The formation of personality comes from people’s choices and pursuit of self-realization,which is influenced by objective factors but not determined by them,so personality does not belong to the domain of objectivity...The formation of personality comes from people’s choices and pursuit of self-realization,which is influenced by objective factors but not determined by them,so personality does not belong to the domain of objectivity.The concept of general personality rights in the German Constitution was initially premised on the objective determinability in the field of personality,but in constitutional jurisprudence,it gradually shifted to something with individual autonomy as the core and personal self-realization as the goal,and the scope of relevant rights expanded accordingly,so that they could not be clearly distinguished from general freedom of action and thus became the general principle of constitutional rights.The protection of constitutional personality rights in the United States and Japan can also confirm this process,providing evidence for the constitutional nature of personality rights.Deeper research shows that constitutional personality rights actually manifest the highest value of modern constitutions—human dignity.In contrast,the theoretical justification of personality rights in civil law just lies in the objectivity and defensive nature of personality elements.展开更多
It is necessary to confirm the personal data factors and the rules of verification before conducting personal data detection. So that the detection method can be written in the subsequent implementation of the automat...It is necessary to confirm the personal data factors and the rules of verification before conducting personal data detection. So that the detection method can be written in the subsequent implementation of the automatic detection tool. This paper will conduct experiments on common personal data factor rules, including domestic personal identity numbers and credit card numbers with checksums. We use ChatGPT to test the accuracy of identifying personal information like ID card identification numbers or credit card numbers. And then use personal data correlation to reduce the time for personal data identification. Although the number of personal information factors found has decreased, it has had a better effect on the actual manual personal data identification. The result shows that it saves about 45% of the calculation time, and the execution efficiency of the accuracy is also improved with the original method by about 22%, which is about 2.2 times higher than the general method. Therefore, the method proposed in this paper can accurately and effectively find out the leftover personal information in the enterprise. .展开更多
文摘The development of Traditional Chinese Medicine(TCM)in Thailand can be traced back to the Sukhothai Kingdom period in the 13th century,which was introduced by immigrants.In 1995,the Ministry of Public Health in Thailand established the Thai-Chinese Medicine Exchange Center to specifically support the development of TCM.In 1997,the health departments of Thailand and China signed a Memorandum of Understanding regarding cooperation in the fields of health sciences and pharmaceuticals.
文摘Recently, use of mobile communicational devices in field data collection is increasing such as smart phones and cellular phones due to emergence of embedded Global Position System GPS and Wi-Fi Internet access. Accurate timely and handy field data collection is required for disaster management and emergency quick responses. In this article, we introduce web-based GIS system to collect the field data by personal mobile phone through Post Office Protocol POP3 mail server. The main objective of this work is to demonstrate real-time field data collection method to the students using their mobile phone to collect field data by timely and handy manners, either individual or group survey in local or global scale research.
基金supported by the cooperation between BIT and Ericssonpartially supported by the National Natural Science Foundation of China under Grants No.62071039。
文摘This paper proposes a personalized headrelated transfer function(HRTF)prediction method based on Light GBM using anthropometric data.Considering the overfitting problems of the current training-based prediction methods,we use Light GBM and a specific network structure to prevent over-fitting and enhance the prediction performance.By decomposing and combining the data to be predicted,we set up 90 Light GBM models to separately predict the 90instants of HRTF in log domain.At the same time,the method of 10-fold cross-validation is used to score the accuracy of the model.For models with scores below 80 points,Bayesian optimization is used to adjust model hyperparameters to obtain a better model structure.The results obtained by Light GBM are evaluated with spectral distortion(SD)which can show the fitting error between the prediction and the original data.The mean SD values of both ears on the whole test set are 2.32 d B and 2.28 d B respectively.Compared with the non-linear regression method and the latest method,SD value of Light GBM-based method relatively decreases by 83.8%and 48.5%.
基金supported by National Natural Science Foundation of China(Grant No.62071098)Sichuan Science and Technology Program(Grants 2022YFG0319,2023YFG0301 and 2023YFG0018).
文摘With the rapid development of artificial intelligence and Internet of Things technologies,video action recognition technology is widely applied in various scenarios,such as personal life and industrial production.However,while enjoying the convenience brought by this technology,it is crucial to effectively protect the privacy of users’video data.Therefore,this paper proposes a video action recognition method based on personalized federated learning and spatiotemporal features.Under the framework of federated learning,a video action recognition method leveraging spatiotemporal features is designed.For the local spatiotemporal features of the video,a new differential information extraction scheme is proposed to extract differential features with a single RGB frame as the center,and a spatialtemporal module based on local information is designed to improve the effectiveness of local feature extraction;for the global temporal features,a method of extracting action rhythm features using differential technology is proposed,and a timemodule based on global information is designed.Different translational strides are used in the module to obtain bidirectional differential features under different action rhythms.Additionally,to address user data privacy issues,the method divides model parameters into local private parameters and public parameters based on the structure of the video action recognition model.This approach enhancesmodel training performance and ensures the security of video data.The experimental results show that under personalized federated learning conditions,an average accuracy of 97.792%was achieved on the UCF-101 dataset,which is non-independent and identically distributed(non-IID).This research provides technical support for privacy protection in video action recognition.
文摘Personalized medicine is the development of “tailored” therapies that reflect traditional medical approaches with the incorporation of the patient’s unique genetic profile and the environmental basis of the disease. These individualized strategies encompass disease prevention and diagnosis, as well as treatment strategies. Today’s healthcare workforce is faced with the availability of massive amounts of patient- and disease-related data. When mined effectively, these data will help produce more efficient and effective diagnoses and treatment, leading to better prognoses for patients at both the individual and population level. Designing preventive and therapeutic interventions for those patients who will benefit most while minimizing side effects and controlling healthcare costs requires bringing diverse data sources together in an analytic paradigm. A resource to clinicians in the development and application of personalized medicine is largely facilitated, perhaps even driven, by the analysis of “big data”. For example, the availability of clinical data warehouses is a significant resource for clinicians in practicing personalized medicine. These “big data” repositories can be queried by clinicians, using specific questions, with data used to gain an understanding of challenges in patient care and treatment. Health informaticians are critical partners to data analytics including the use of technological infrastructures and predictive data mining strategies to access data from multiple sources, assisting clinicians’ interpretation of data and development of personalized, targeted therapy recommendations. In this paper, we look at the concept of personalized medicine, offering perspectives in four important, influencing topics: 1) the availability of “big data” and the role of biomedical informatics in personalized medicine, 2) the need for interdisciplinary teams in the development and evaluation of personalized therapeutic approaches, and 3) the impact of electronic medical record systems and clinical data warehouses on the field of personalized medicine. In closing, we present our fourth perspective, an overview to some of the ethical concerns related to personalized medicine and health equity.
文摘The advent of the big data era has opened up unprecedented quantifiable dimensions for all walks of life,while also presented many opportunities and challenges.The widespread application of big data in the field of education will inevitably promote the innovation and transformation of the higher education in colleges and universities which introduce new opportunities and challenges to personalized education in colleges and universities.How to promote the indepth integration of big data and higher education to meet the needs of students’personalized development is one of the hot topics in the theoretical field today.In view of this,this article starts with explaining the connotation of personalized education in colleges and universities,analyzes the opportunities and challenges faced by personalized education in colleges and universities under the context of big data,and proposes the ideas of innovating personalized education in colleges and universities under the context of big data.
基金the current result of the “research on the basic category system of contemporary Chinese digital law” (23&ZD154), a major project of the National Social Science Fund of China.
文摘Although the existing legal norms and judicial practic-es can provide basic guidance for the right to personal data portabili-ty, it can be concluded that there are obstacles to the realization of this right through empirical research of the privacy policies of 66 mobile apps, such as whether they have stipulations on the right to personal data portability, whether they are able to derive copies of personal in-formation automatically, whether there are textual examples, whether ID verification is required, whether the copied documents are encrypt-ed, and whether the scope of personal information involved is consis-tent. This gap in practice, on the one hand, reflects the misunderstand-ing of the right to personal data portability, and on the other hand, is a result of the negative externalities, practical costs and technical lim-itations of the right to personal data portability. Based on rethinking the right to data portability, we can somehow solve practical problems concerning the right to personal data portability through multiple measures such as promoting the fulfillment of this right by legislation, optimizing technology-oriented operations, refining response process mechanisms, and enhancing system interoperability.
文摘The purpose of this study is to investigate the sleep habits, cervical health status, and the demand and preference for pillow products of different populations through data analysis. A total of 780 valid responses were gathered via an online questionnaire to explore the sleep habits, cervical health conditions, and pillow product preferences of modern individuals. The study found that sleeping late and staying up late are common, and the use of electronic devices and caffeine consumption have a negative impact on sleep. Most respondents have cervical discomfort and have varying satisfaction with pillows, which shows their demand for personalized pillows. The machine learning model for predicting the demand of latex pillow was constructed and optimized to provide personalized pillow recommendation, aiming to improve sleep quality and provide market data for sleep product developers.
基金Supported by the MEXT Research Project "Global Business and IT Management: Global eSCM" at the Research Institute of Commerce, Meiji University.
文摘This paper deals with personal data use by firms in the e-business environment from the viewpoint of business administration and information ethics. Whereas the tremendous development of information and communication technology (ICT) has made it easier for firms to acquire, store, share, and utilise personal data on their customers, firms that use personal data are exposed to risks related to privacy issues. Since individuals fear the invasion of their privacy, the failure of a firm to appear or remain trustworthy would make it difficult for it to maintain accurate, up-to-date databases and to construct desirable business processes, which would affect the bottom line. Therefore, modern firms should do what they can to ensure that their customers trust them. For them, one promising way to remain trustworthy is to behave as a moral agent. Although it is difficult for any firm to meet the conditions necessary to be a moral agent, competence in behaving as a moral agent is a hard-to-imitate capability af firms for which personal data use is vital for enjoying the benefits of business relationships in the e-business environment.
基金the provincial key academic project Research of the Grassroots Negotiation and Governance Modernization Viewing from the Angle of State Governance(2019-GDXK-0005)
文摘The right to the protection of personal data is an important human right in the era of big data and a constitutional right based on the national protection obligation and the theory of human dignity,making it of special significance for the realization of citizenship in a digital society.It can be seen from an examination of the constitutional texts of various countries in the world that the right to the protection of personal data as a constitutional right has rich normative connotations,and the key legal link to realize this right lies in the national legislature actively fulfilling its obligation to shape and specify the protection of personal data in accordance with the entrustment of the constitutional norms.Given the constitutional principles of fundamental rights protection,i.e.,realizing the constitutional status of the right to the protection of personal data as a basic right by means of institutional guarantees,the legislature should first adhere to the constitutionality principle of data protection legislation.Second,a multi-level data protection legal system centered on the right to the protection of personal data should be established.Finally,the institutional guarantee mechanism for the protection of personal data should be continuously improved through constitutional interpretation.
基金supported in part by the Fundamental Research Funds for the Central Universities of China (No. 2018CUCTJ078, CUC18A002-2)
文摘Mobile operators face the challenge of how to best design a service-centric network that can effectively process the rapidly increasing number of bandwidth-intensive user requests while providing a higher quality of experience(QoE). Existing content distribution networks(CDN) and mobile content distribution networks(mCDN) have both latency and throughput limitations due to being multiple network hops away from end-users. Here, we first propose a new Personalized Edge Caching System(PECS) architecture that employs big data analytics and mobile edge caching to provide personalized service access at the edge of the mobile network. Based on the proposed system architecture, the edge caching strategy based on user behavior and trajectory is analyzed. Employing our proposed PECS strategies, we use data mining algorithms to analyze the personalized trajectory and service usage patterns. Our findings provide guidance on how key technologies of PECS can be employed for current and future networks. Finally, we highlight the challenges associated with realizing such a system in 5G and beyond.
基金supported by the Industrial Support Project of Gansu Colleges under Grant No.2022CYZC-11Gansu Natural Science Foundation Project under Grant No.21JR7RA114+1 种基金National Natural Science Foundation of China under Grants No.622760736,No.1762078,and No.61363058Northwest Normal University Teachers Research Capacity Promotion Plan under Grant No.NWNU-LKQN2019-2.
文摘The exercise recommendation system is emerging as a promising application in online learning scenarios,providing personalized recommendations to assist students with explicit learning directions.Existing solutions generally follow a collaborative filtering paradigm,while the implicit connections between students(exercises)have been largely ignored.In this study,we aim to propose an exercise recommendation paradigm that can reveal the latent connections between student-student(exercise-exercise).Specifically,a new framework was proposed,namely personalized exercise recommendation with student and exercise portraits(PERP).It consists of three sequential and interdependent modules:Collaborative student exercise graph(CSEG)construction,joint random walk,and recommendation list optimization.Technically,CSEG is created as a unified heterogeneous graph with students’response behaviors and student(exercise)relationships.Then,a joint random walk to take full advantage of the spectral properties of nearly uncoupled Markov chains is performed on CSEG,which allows for full exploration of both similar exercises that students have finished and connections between students(exercises)with similar portraits.Finally,we propose to optimize the recommendation list to obtain different exercise suggestions.After analyses of two public datasets,the results demonstrated that PERP can satisfy novelty,accuracy,and diversity.
文摘Advancing the application of safety and health(S&H)technologies is likely to remain a value in the mining industry.However,any information that technologies generate must be translated from the organization to the workforce in a targeted way to result in sustainable change.Using a case study approach with continuous personal dust monitors(CPDMs),this paper argues for an organizational focus on technology integration.Although CPDMs provide mineworkers with near real-time feedback about their respirable coal dust exposure,they do not ensure that workers or the organization will continuously use the information to learn about and reduce exposure sources.This study used self-determination theory(SDT)to help three mines manage and communicate about information learned from the CPDM technology.Specifically,35 mineworkers participated in two mixed-method data collection efforts to discuss why they do or do not use CPDMs to engage in dust-reducing practices.Subsequently,the data was analyzed to better understand how organizations can improve the integration of technology through their management systems.Results indicate that using the CPDM to reduce sources of dust exposure is consistent with mineworkers’self-values to protect their health and not necessarily because of compliance to a manager or mine.
文摘This comprehensive study investigates the multifaceted impact of AI-powered personalization on strategic communications, delving deeply into its opportunities, challenges, and future directions. Employing a rigorous mixed-methods approach, we conduct an in-depth analysis of the effects of AI-driven personalization on audience engagement, brand perception, and conversion rates across various industries and communication channels. Our findings reveal that while AI-powered personalization significantly enhances communication effectiveness and offers unprecedented opportunities for audience connection, it also raises critical ethical considerations and implementation challenges. The study contributes substantially to the growing body of literature on AI in communications, offering both theoretical insights and practical guidelines for professionals navigating this rapidly evolving landscape. Furthermore, we propose a novel framework for ethical AI implementation in strategic communications and outline a robust agenda for future research in this dynamic field.
基金the National Natural Science Foundation of China under contract NO 61271235 and No.60973146,and the Fundamental Research Funds for the Central Universities under Grant No.BUPT2013RC0308
文摘Personal health record （PHR） enables patients to manage their own electronic medical records （EMR） in a centralized way, and it is oRen outsourced to be stored in a third-party server. In this paper we propose a novel secure and scalable system for sharing PHRs. We focus on the multiple data owner scenario, and divide the users in the system into multiple security domains that greatly reduce the key management complexity for owners and users. A high degree of patient privacy is guaranteed by exploiting hierarchical and multi- authority attribute-sets based encryption （HM- ASBE）. Our system not only supports compound attributes due to flexible attribute sets combinations, but also achieves fine-grained access control. Our scheme supports efficient on-demand user/attribute revocation and break-glass access under emergency scenarios.
文摘Before the implementation of product data management (PDM) system, person model and enterprise process model (EPM) must be firstly established. For the convenience of project management, all the related users must be allocated to the “Person User Role Group” net. Based on the person model and the direction of information flow, the EPM is established subsequently. The EPM consists of several release levels, in which the access controls are defined. The EPM procedure shows the blueprint of the workflow process structure. The establishment of person model and EPM in an enterprise has been instanced at the end of this paper.
文摘Personal credit risk assessment is an important part of the development of financial enterprises. Big data credit investigation is an inevitable trend of personal credit risk assessment, but some data are missing and the amount of data is small, so it is difficult to train. At the same time, for different financial platforms, we need to use different models to train according to the characteristics of the current samples, which is time-consuming. <span style="font-family:Verdana;">In view of</span><span style="font-family:Verdana;"> these two problems, this paper uses the idea of transfer learning to build a transferable personal credit risk model based on Instance-based Transfer Learning (Instance-based TL). The model balances the weight of the samples in the source domain, and migrates the existing large dataset samples to the target domain of small samples, and finds out the commonness between them. At the same time, we have done a lot of experiments on the selection of base learners, including traditional machine learning algorithms and ensemble learning algorithms, such as decision tree, logistic regression, </span><span style="font-family:Verdana;">xgboost</span> <span style="font-family:Verdana;">and</span><span style="font-family:Verdana;"> so on. The datasets are from P2P platform and bank, the results show that the AUC value of Instance-based TL is 24% higher than that of the traditional machine learning model, which fully proves that the model in this paper has good application value. The model’s evaluation uses AUC, prediction, recall, F1. These criteria prove that this model has good application value from many aspects. At present, we are trying to apply this model to more fields to improve the robustness and applicability of the model;on the other hand, we are trying to do more in-depth research on domain adaptation to enrich the model.</span>
文摘The formation of personality comes from people’s choices and pursuit of self-realization,which is influenced by objective factors but not determined by them,so personality does not belong to the domain of objectivity.The concept of general personality rights in the German Constitution was initially premised on the objective determinability in the field of personality,but in constitutional jurisprudence,it gradually shifted to something with individual autonomy as the core and personal self-realization as the goal,and the scope of relevant rights expanded accordingly,so that they could not be clearly distinguished from general freedom of action and thus became the general principle of constitutional rights.The protection of constitutional personality rights in the United States and Japan can also confirm this process,providing evidence for the constitutional nature of personality rights.Deeper research shows that constitutional personality rights actually manifest the highest value of modern constitutions—human dignity.In contrast,the theoretical justification of personality rights in civil law just lies in the objectivity and defensive nature of personality elements.
文摘It is necessary to confirm the personal data factors and the rules of verification before conducting personal data detection. So that the detection method can be written in the subsequent implementation of the automatic detection tool. This paper will conduct experiments on common personal data factor rules, including domestic personal identity numbers and credit card numbers with checksums. We use ChatGPT to test the accuracy of identifying personal information like ID card identification numbers or credit card numbers. And then use personal data correlation to reduce the time for personal data identification. Although the number of personal information factors found has decreased, it has had a better effect on the actual manual personal data identification. The result shows that it saves about 45% of the calculation time, and the execution efficiency of the accuracy is also improved with the original method by about 22%, which is about 2.2 times higher than the general method. Therefore, the method proposed in this paper can accurately and effectively find out the leftover personal information in the enterprise. .
