Mobile Edge Computing to Assist the Online Ideological and Political Education

With the rapid development of mobile Internet technology, mobile network data traffic presents an explosive growth trend. Especially, the proportion of mobile video business has become a large proportion in mobile Internet business. Mobile video business is considered as a typical business in the 5G network, such as in online education. The growth of video traffic poses a great challenge to mobile network. In order to provide users with better quality of experience (QoE), it requires mobile network to provide higher data transmission rate and lower network delay. This paper adopts a combined optimization to minimize total cost and maximize QoE simultaneously. The optimization problem is solved by ant colony algorithm. The effectiveness is verified on experiment.

Information disclosing willingness in mobile internet contexts

Purpose This paper aims to learn about consumers’ information disclosing patterns in the mobile internet context by investigating how demographic, geographic and psychological factors influence their information disclosing willingness (IDW).Design/methodology/approach Drawing on self-disclosure theory, the authors carried out simple linear regression analyses on a Chinese sample of 10,000 participants.Findings The results revealed that significant gender differences exist between males and females in their IDW in mobile internet context, and females have higher IDW than males do. And the authors also found that first-tier (third tier) citizens have the lowest (highest) IDW in their mobile internet usage.Originality/value This study offers three implications. First, this paper captures the insight of IDW within the mobile internet context, while previous studies mostly focus on the desktop internet context. Second, the results show that females have higher willingness to disclose than males do in the context of mobile internet, which is different from the findings of prior studies that females have higher privacy concerns and lower disclosing willingness in the context of desktop internet. Thirdly, this research introduces city tiers as a new approach to the study of IDW, which is one of the first studies exploring the geographical effect on information privacy.

Application and Feasibility Study of Integrated Nursing Information Construction in Nephrology Nursing

With the continuous deepening of medical reforms and the continuous attempts and explorations of various management models, the traditional health care model is undergoing tremendous changes, and patients’ needs for medical institutions are becoming more and more comprehensive. Medical institutions are meeting the needs of providing medical services to patients at the same time. It is even more necessary to change our thinking and enhance the service concept. This article is based on case-based deep learning hospital nursing business process reengineering and the application and feasibility study of integrated nursing information construction in nephrology nursing. This article uses the literature analysis method, the social survey method, and other methods to discuss the construction of integrated nursing information. On the one hand, the content of this article uses the concept of process reengineering to analyze the current development status and existing problems of the hospital care industry and find countermeasures to solve problems. On the other hand, the main research content of this article is the construction of integrated nursing information and its analysis of the application and feasibility of nursing in the nephrology department. At the same time, under the background of the rapid development of the mobile Internet, we will carry out extended thinking on the continuous transformation of the construction of nursing information. According to the survey results, 87.5% of patients in the nephrology department are dissatisfied with the current hospital’s work efficiency, and 85.7% of the nursing staff in the nephrology department are generally satisfied with the information management of the current department. After the implementation of the hospital information integration system, patient satisfaction is as high as 98.2%, and the satisfaction of medical staff reached 94.2%. The construction of integrated nursing information has played a great role in the application of nephrology nursing.

Evaluation Index of School Sports Resources Based on Artificial Intelligence and Edge Computing

As the demand for education continues to increase, the relative lack of physical resources has become a bottleneck hindering the development of school physical education to a certain extent. This research mainly discusses the evaluation index system of school sports resources based on artificial intelligence and edge computing. Human resources, financial resources, and material resources in school sports resources are the three major resources in resource science. University sports stadium information publicity uses Internet technology to establish a sports information management platform and mobile Internet terminals to optimize university sports resources and stadium information management services. It uses artificial intelligence technology to improve venue information management. It establishes a comprehensive platform for venue management information, collects multidimensional information, provides information resources and accurate information push, and links venue information with public fitness needs. Using edge computing to realize nearby cloud processing of video data, reduce the phenomenon of black screen jams during live broadcast, improve data computing capabilities, and reduce users’ dependence on the performance of terminal devices, build a smart sports resource platform, combine artificial intelligence (AI) to create smart communities, smart venues, and realize intelligent operations such as event service operations and safety prevention and control in important event venues. During the live broadcast of the student sports league, the nearby cloud processing of video data is realized in the form of edge computing, which improves the data computing ability and reduces the performance dependence on the user terminal equipment itself. In the academic survey of college physical education teachers, undergraduates accounted for 26.99%, masters accounted for 60.3%, and doctoral degrees accounted for 12.8%. This research will help the reasonable allocation of school sports resources.

Principle of 6G Wireless Networks: Vision, Challenges and Applications

The 5G mobile communication has now become commercially available. Furthermore, research across the globe has begun to improve the system beyond 5G and it is anticipated that 6G will deliver higher quality services and energy efficiency than 5G. The mobile network architecture needs to be redesigned to meet the requirements of the future. In the wake of the commercial rollout of the 5G model, both users and developers have realized the limitations of the system when compared to the system's original premise of being able to support the vast applications of connected devices. The article discusses the related technologies that can contribute to a robust and seamless network service. An upheaval in the use of vast mobile applications, especially those powered and managed by AI, has opened the doors to discussion on how mobile communication will evolve in the future. 6G is expected to go beyond being merely a mobile internet service provider to support the omnipresent AI services that will form the rock bed of end-to-end connected network-based devices. Moreover, the technologies that support 6G services and comprehensive research that enables this level of technical prowess have also been identified here. This paper presents a collective wide-angle vision that will facilitate a better understanding of the features of the 6G system.

Knowledge Graph Construction for Intelligent Media Based on Mobile Internet

Mobile Internet-based intelligent media has become a popular academic topic. This study uses the CiteSpace visualisation tool and Scientific Citation Index Expanded database to comb the existing research in the field of intelligent media from a quantitative perspective. A total of 7248 English papers were published on the topic of “intelligent media” from 2012 to 2021, and 145 highly cited papers refined were analysed. Scientific knowledge graphs were analysed from six dimensions: annual publication quantity, country of publication, institution of publication, author, keywords, and cited references. In the last 10 years, the research literature on intelligent media has been found to increase annually. Presently, the People’s Republic of China and the United States of America have a high proportion of documents in this field. Chinese universities and institutions have achieved significantly in terms of the quantity and quality of documents. From the perspective of the whole intelligent media discipline, the high-yield author group has not been formed, and there is minimal cooperation amongst authors. Popular intelligent media topics include film, social media, machine learning, swarming motility, data mining, and artificial intelligence. Subject words of the main research directions are event recognition, fake news, Cable News Network model, reconfigurable intelligent surface, comprehensive survey, microblog message, strain sensor, and traffic event. Combined with popular topics and time zone maps, the future research frontier in the field of smart media is identified.

Design of E-commerce Data Scalable Storage System Based on Mobile Internet Communication Technology

The traditional encrypted storage system is inefficient when it encrypts the data of the Internet of Things, and there are few IOT data nodes that can be encrypted in a short time. In order to solve the above problems, a new Internet of Things data effective information encryption storage system is proposed. The hardware and software of the system are mainly designed. The chip selected for the collector is TTSAD251, which can expand the collection range. The processor is set with multiple cores to reduce the system power consumption. The memory uses SPRTAN-2 chip as the structure chip. The software work consists of three parts: collecting effective information of Internet of Things big data, establishing encrypted documents and storing effective information of big data of Internet of Things. In order to detect the working effect of the system, the experimental comparison with the traditional system shows that the proposed encryption storage system can improve the storage range of big data effective information of the Internet of Things by 20.58%, and the work efficiency by 5.64%. Compared with the traditional system, the designed system also has obvious advantages in the number of big data node secrets. In different files, the average number of big data information node encryption in this system is about 166,700. The experimental data show that the designed system has ideal application performance and provides a reliable basis for related fields.

Effect of Mobile Internet on Attitude and Self-Efficacy of Patients with Coronary Heart Disease Diagnosed by 12-Lead Holter ECG

Objective. To explore the effect of mobile Internet on attitude and self-efficacy of patients with coronary heart disease (CHD) diagnosed by 12-lead Holter ECG. Methods. The clinical data of 62 patients with CHD who underwent routine ECG examination (control group I) and 12-lead dynamic electrocardiogram (control group II) in our hospital (June 2017–December 2020) were retrospectively analyzed, and the clinical data of another 62 patients with CHD who received 12-lead Holter ECG examination combined with mobile Internet in our hospital at the same time (study group) were retrospectively analyzed. The clinical observation indexes of the three groups were compared. Results. No obvious difference in general data among groups ( P > 0.05 ). Compared with the control group I, the positive detection rate (PDR) of the study group and the control group II was obviously higher ( P < 0.05 ), and the PDR of the study group was obviously higher than that of the control group II, without remarkable difference between both groups ( P > 0.05 ). Compared with the control group, the scores of CAS-R of the study group were obviously higher ( P < 0.05 ), and self-efficacy of daily life, health behaviors, medication compliance, and compliance behavior of the study group was obviously better ( P < 0.05 ). The diagnostic efficacy was derived by ROC curve analysis, 12-lead Holter ECG combined with mobile Internet + routine ECG > 12-lead Holter ECG combined with mobile Internet > 12-lead Holter ECG > routine ECG. Conclusion. Compared with the routine ECG, the sensitivity of 12-lead Holter ECG in the diagnosis of CHD is conspicuously higher. Meanwhile, 12-lead Holter ECG combined with mobile Internet can enhance the diagnostic efficiency and improve patients’ perceived control attitude and self-efficacy.

Joint Multi-domain Resource Allocation and Trajectory Optimization in UAV-assisted M-IoT Networks

<div>The integration of Maritime Internet of Things (M-IoT) technology and unmanned aerial/surface vehicles (UAVs/USVs) has been emerging as a promising navigational information technique in intelligent ocean systems. With the unprecedented increase of computation-intensive yet latency sensitive marine mobile Internet services, mobile edge computing (MEC) and non-orthogonal multiple access (NOMA) have been envisioned as promising approaches to providing with the low-latency as well as reliable computing services and ultra-dense connectivity. In this paper, we investigate the energy consumption minimization based energy-efficient MEC via cooperative NOMA for the UAV-assisted M-IoT networks. We consider that USVs offload their computation-workload to the UAV equipped with the edge-computing server subject to the UAV mobility. To improve the energy efficiency of offloading transmission and workload computation, we focus on minimizing the total energy consumption by jointly optimizing the USVs’ offloaded workload, transmit power, computation resource allocation as well as the UAV trajectory subject to the USVs’ latency requirements. Despite the nature of mixed discrete and non-convex programming of the formulated problem, we exploit the vertical decomposition and propose a two-layered algorithm for solving it efficiently. Specifically, the top-layered algorithm is proposed to solve the problem of optimizing the UAV trajectory based on the idea of Deep Reinforcement Learning (DRL), and the underlying algorithm is proposed to optimize the underlying multi-domain resource allocation problem based on the idea of the Lagrangian multiplier method. Numerical results are provided to validate the effectiveness of our proposed algorithms as well as the performance advantage of NOMA-enabled computation offloading in terms of overall energy consumption.</div>

Joint Multi-domain Resource Allocation and Trajectory Optimization in UAV-assisted M-IoT Networks

<div>The integration of Maritime Internet of Things (M-IoT) technology and unmanned aerial/surface vehicles (UAVs/USVs) has been emerging as a promising navigational information technique in intelligent ocean systems. With the unprecedented increase of computation-intensive yet latency sensitive marine mobile Internet services, mobile edge computing (MEC) and non-orthogonal multiple access (NOMA) have been envisioned as promising approaches to providing with the low-latency as well as reliable computing services and ultra-dense connectivity. In this paper, we investigate the energy consumption minimization based energy-efficient MEC via cooperative NOMA for the UAV-assisted M-IoT networks. We consider that USVs offload their computation-workload to the UAV equipped with the edge-computing server subject to the UAV mobility. To improve the energy efficiency of offloading transmission and workload computation, we focus on minimizing the total energy consumption by jointly optimizing the USVs’ offloaded workload, transmit power, computation resource allocation as well as the UAV trajectory subject to the USVs’ latency requirements. Despite the nature of mixed discrete and non-convex programming of the formulated problem, we exploit the vertical decomposition and propose a two-layered algorithm for solving it efficiently. Specifically, the top-layered algorithm is proposed to solve the problem of optimizing the UAV trajectory based on the idea of Deep Reinforcement Learning (DRL), and the underlying algorithm is proposed to optimize the underlying multi-domain resource allocation problem based on the idea of the Lagrangian multiplier method. Numerical results are provided to validate the effectiveness of our proposed algorithms as well as the performance advantage of NOMA-enabled computation offloading in terms of overall energy consumption.</div>