Research on the Service Industry Mobile Marketing under the Mobile Internet Background

In this paper, we conduct research on the service industry mobile marketing under the mobile Internet background. Marketing activities from scratch, never valued to the cherished, the Marketing Department in from scratch, from the production of auxiliary department to the enterprise leading department of course have made indelible contribution to the development of the enterprise. Services marketing is not justfor external customers, at the same time also want to take a marketing gimmick to internal customers. External marketing is a pointer to a series of services provided by the customer, including all preferential foreign propaganda and sales promotion action plan, including personnel and more than the personnel communication skills, as well as the services provided by all service equipment. This paper analyzes this issue from theunique perspective that is meaningful.

Impact of Sharing Marketing on Marketing Willingness of Employees in Internet Decoration Industry

With the development of information technology,sharing marketing,as an innovative marketing method,plays an important role in promoting the marketing willingness and enthusiasm of employees in the Internet decoration industry.Based on the data obtained from the ques-tionnaire survey,this paper makes an empirical analysis of the impact of the economic value,social value,perceived ease of use,perceived convenience,enabling conditions and subjective norms of sharing marketing on the marketing willingness of employees in the Internet decoration industry.The results showed that the questionnaire had good internal consistency and construct validity.Through empirical analysis,it can be found that the economic value,social value,perceived ease of use,perceived convenience,enabling conditions and subjective norms of sharing marketing have a significant positive impact on employees'marketing willingness.

A Double-Timescale Reinforcement Learning Based Cloud-Edge Collaborative Framework for Decomposable Intelligent Services in Industrial Internet of Things

With the proportion of intelligent services in the industrial internet of things(IIoT)rising rapidly,its data dependency and decomposability increase the difficulty of scheduling computing resources.In this paper,we propose an intelligent service computing framework.In the framework,we take the long-term rewards of its important participants,edge service providers,as the optimization goal,which is related to service delay and computing cost.Considering the different update frequencies of data deployment and service offloading,double-timescale reinforcement learning is utilized in the framework.In the small-scale strategy,the frequent concurrency of services and the difference in service time lead to the fuzzy relationship between reward and action.To solve the fuzzy reward problem,a reward mapping-based reinforcement learning(RMRL)algorithm is proposed,which enables the agent to learn the relationship between reward and action more clearly.The large time scale strategy adopts the improved Monte Carlo tree search(MCTS)algorithm to improve the learning speed.The simulation results show that the strategy is superior to popular reinforcement learning algorithms such as double Q-learning(DDQN)and dueling Q-learning(dueling-DQN)in learning speed,and the reward is also increased by 14%.

Core competencies and perceived training needs of nurses in the background of Internet plus nursing service:a qualitative descriptive study

Background:The Internet plus nursing service program is being piloted in China,which has become a new home nursing service model led by nurses.To enable safe and effective homecare service delivery,nurses working in the program need a high level of competency.However,the content of these core competencies and the training needs of nurses for Internet plus nursing services are still unknown.Aim:To describe nurses’perceptions of core competencies and training needs to work in the Internet plus nursing service program,thereby providing a reference for the development of training programs.Methods:A qualitative descriptive study using semi-structured interviews was conducted on 15 nurses with experience of working in the Internet plus nursing service program.Interviews were audio-recorded and transcribed verbatim,and the data were analyzed using thematic analysis.Results:Core competencies involved comprehensive assessment competence,direct care practice competence,health education and consulting competence,risk estimation and response competence,and communication competence.Training needs involved complex operational items,knowledge of chronic disease management,professional communication,risk identification and response,nursing standards,norms,and procedures,and utilization of information technology.Conclusions:The training system may be developed based on nurses’core competencies and their training needs to promote professional development of the Internet plus nursing service.

Analysis of the Current Situation of“Internet Plus Nursing Service”

In the era of“Internet Plus,”technologies like big data,the Internet of Things,and cloud computing have revitalized nursing services in China,leading to the emergence of the“Internet Plus Nursing Services”model.This model facilitates on-site nursing care for discharged patients and special groups with mobility challenges,further advancing the construction of a Healthy China and enabling more people to access high-quality and continuous nursing services.Governments at all levels should actively improve the systems related to“Internet Plus Nursing Services”and simplify the appointment and operation processes.It is also essential to standardize the medical waste disposal process to ensure the quality of on-site nursing services,protect the legitimate rights and interests of both caregivers and patients and safeguard patient privacy and security.Additionally,building a robust“Internet Plus”platform to promote“online appointment of nurses”services,integrate nursing resources,and foster the healthy development of“Internet Plus Nursing Services”is crucial.

Analysis of Service Marketing Strategies in the Senior Study Travel Tour Market

Senior study travel,as an emerging form of tourism,combines the dual characteristics of educational learning and leisure travel.It not only meets the elderly’s desire for spiritual and cultural life and self-fulfillment but also promotes the construction of a healthy aging society.This study comprehensively uses methods such as literature analysis,interviews,and case studies to analyze the current status and existing problems of the senior study travel market.Based on the 7Ps service marketing model,it explores service marketing strategies for the senior study travel market,aiming to provide reference and guidance for related tourism enterprises to supply more attractive senior study travel services.

From Inside Out:Internal Marketing as an Engine for Service Promotion-A Secondary Publication

Focusing on“from inside out”means understanding that the driving force behind a successful service promotion campaign lies in a deep connection with the internal team,turning it into the engine that propels a positive brand perception.The University of Panama faces challenges in the effective implementation of strategies involving its internal staff,impacting the coherence and strength of its promotional messages.The research aimed to determine internal marketing strategies as an engine for service promotion at the Central Campus and CRUSAM.The applied study was descriptive,non-experimental field research,and cross-sectional.The sample consisted of 80 individuals using a quota sampling method to measure and quantify the expression of a construct or variable that is not directly observable.A selfadministered questionnaire was used to collect information,measuring variables in their various dimensions.Content validity of the questionnaire was ensured through the evaluation of three experts,and the reliability of the Likert-type instrument was assessed using Cronbach’s α coefficient,which was found to be very high(0.918).The results led to the conclusion that establishing internal marketing strategies is necessary for the transformation and innovation process in the university through service promotion.

Mechanisms for the Application of Health Services Marketing Policies in Algeria

In this paper, we tried to give health services marketing mix and raise patients＇ interest in health services with the contribution to highlighting the possible application mechanisms of different marketing policies on health services in Algeria. Because we see that, health foundations in Algeria like other foundations live in an environment marked with constantly economic, social, politic, and cultural changes. And to respond to change requirements, especially with the appearance of health services market liberation signs, these foundations are obliged to adapt to ensure their existence and development by giving best services to meet the patients＇ needs in order to gain their satisfaction and loyalty. These ones, who became more conscious about the quality of services they are given quantitatively, qualitatively, and timely.

Effect of Internet+continuous midwifery service model on psychological mood and pregnancy outcomes for women with highrisk pregnancies

BACKGROUND There are many drawbacks to the traditional midwifery service management model,which can no longer meet the needs of the new era.The Internet+continuous midwifery service management model extends maternal management from prenatal to postpartum,in-hospital to out-of-hospital,and offline to online,thereby improving maternal and infant outcomes.Applying the Internet+continuous midwifery service management model to manage women with highrisk pregnancies(HRP)can improve their psycho-emotional opinion and,in turn,minimize the risk of adverse maternal and/or fetal outcomes.AIM To explore the effectiveness of a midwife-led Internet+continuous midwifery service model for women with HRP.METHODS We retrospectively analyzed the clinical data of 439 women with HRP who underwent prenatal examination and delivered at Shanghai Sixth People's Hospital(affiliated to the Shanghai Jiao Tong University School of Medicine)from April to December 2022.Among them,239 pregnant women underwent routine obstetric management,and 200 pregnant women underwent Internet+continuous midwifery service mode management.We used the State-Trait Anxiety Inventory,Edinburgh Postnatal Depression Scale,and analysis of delivery outcomes to compare psychological mood and the incidence of adverse delivery outcomes between the two groups.RESULTS The data showed that in early pregnancy,the anxiety and depression levels of the two groups were similar;the levels gradually decreased as pregnancy progressed,and the decrease in the continuous group was more significant[31.00(29.00,34.00)vs 34.00(32.00,37.00),8.00(6.00,9.00)vs 12.00(10.00,13.00),P<0.05].The maternal self-efficacy level and strategy for weight gain management were better in the continuous group than in the traditional group,and the effective rate of midwifery service intervention in the continuous group was significantly higher than in the control group[267.50(242.25,284.75)vs 256.00(233.00,278.00),74.00(69.00,78.00)vs 71.00(63.00,78.00),P<0.05].The incidence of adverse delivery outcomes in pregnant women and newborns and fear of maternal childbirth were lower in the continuous group than in the traditional group,and nursing satisfaction was higher[10.50%vs 18.83%,8.50%vs 15.90%,24.00%vs 42.68%,89.50%vs 76.15%,P<0.05].CONCLUSION The Internet+continuous midwifery service model promotes innovation through integration and is of great significance for improving and promoting maternal and child health in HRP.

Growing Market Demand for After-Sales Service Management

With the background of the current economic globalization and informatization,how to improve the quality of after-sales services and meet the diversified needs of consumers has become an important issue that the industry has had to face and solve.Recently,the“report on 2022-2028 after-sales service management industry market competition analysis and development strategic planning assessment forecast”(hereinafter referred to as the“Report”)released by CICC Consulting pointed out that the high penetration rate of electronic information products.

Current Status and Trend of Internet and E-Commerce Market in Korea

After the remarkable increase of Internet users and broadband Internet subscribers at the end of the 20th century, the size of Korean Internet and e-commerce market steadily increased but the growth rate has been either stagnant or decreased. Trends of Korean Internet and e-commerce market are summarized in this paper the trends on Internet usage are introduced. Trends of online games, blogs and wireless Internet are introduced. The trends of Korean Internet market may have implications for China and Japan.

Evaluation method for assessing the auxiliary service transaction mechanism in regional power markets

Accurate and seamless auxiliary services in the power market can guarantee smooth and continuous power system operation. China’s new round of power system reform has entered a critical period, and reform implementation requires comprehensive improvements in the maturity of the supporting auxiliary service market. This study reviews the development status and evolution path of the European unified power market and the US regional power market, provides experience for the development of China’s regional power market, then identifies the key influencing factors of auxiliary service trading mechanism design in regional power markets. To analyze the rationality of the auxiliary service trading evaluation index, this paper established an evaluation model for assessing regional power markets. Using combined weight optimization, the gray correlation TOPSIS method was applied to comprehensively evaluate auxiliary service trading in the regional power market. Finally, the application of the proposed evaluation method was briefly analyzed to examine four regional power markets in China and evaluate the effectiveness of current market construction in different regions and provide suggestions for future market construction.

Internet big data and capital markets:a literature review

Background:Research in various academic disciplines has undergone tremendous changes in the era of big data.Everyone is talking about big data nowadays,but how exactly is it being applied in research on financial studies?Results:This study summarizes the sources of Internet big data for research related to capital markets and the analytical methods that have been used in the literature.In addition,it presents a review of the research findings based on Internet big data in the field of capital markets and proposes suggestions for future studies in which big data can be applied to examine issues related to capital markets.Conclusion:(1)Internet big data sources related to present capital market research can be categorized into forum-type data,microblog-type data and search class data.(2)As for research about investors’sentiments on the basis of Internet big data,the main methods of sentiment analysis include building an inventory of lexical categories,using dictionaries for analysis of lexical categories,and machine learning.(3)Many studies address whether Internet big data can predict capital markets.However,they reach no consistent conclusions,which could be due to limitations of sample and analysis method used.(4)Data collection technique and analysis methods require further improvements.

Strategic Thinking of the Internet of Things and M2M Services

Editor＇s Desk：The Internet of Things is an important part of the emerging high-tech industry and has been recognized as one of the important technologies for addressing global financial crisis and revitalizing the economy. Therefore, at the beginning of the new year, we are honored to have invited Mr. Samuel Qi （Qi Qingzhong）, a famous Chinese communication technology expert and GM of Shanghai Symphony Telecommunications Co., Ltd., to give his views on the development strategy of the Internet of Things and Machine to Machine （M2M） Communications.

Length matters:Scalable fast encrypted internet traffic service classification based on multiple protocol data unit length sequence with composite deep learning

As an essential function of encrypted Internet traffic analysis,encrypted traffic service classification can support both coarse-grained network service traffic management and security supervision.However,the traditional plaintext-based Deep Packet Inspection(DPI)method cannot be applied to such a classification.Moreover,machine learning-based existing methods encounter two problems during feature selection:complex feature overcost processing and Transport Layer Security(TLS)version discrepancy.In this paper,we consider differences between encryption network protocol stacks and propose a composite deep learning-based method in multiprotocol environments using a sliding multiple Protocol Data Unit(multiPDU)length sequence as features by fully utilizing the Markov property in a multiPDU length sequence and maintaining suitability with a TLS-1.3 environment.Control experiments show that both Length-Sensitive(LS)composite deep learning model using a capsule neural network and LS-long short time memory achieve satisfactory effectiveness in F1-score and performance.Owing to faster feature extraction,our method is suitable for actual network environments and superior to state-of-the-art methods.

Design and Implementation of Novel Precision Internet Marketing Patterns under the Big Data and Cloud Environment

Nowadays most of the cloud applications process large amount of data to provide the desired results. The Internet environment, the enterprise network advertising, network marketing plan, need partner sites selected as carrier and publishers. Website through static pages, dynamic pages, floating window, AD links, take the initiative to push a variety of ways to show the user enterprise marketing solutions, when the user access to web pages, use eye effect and concentration effect, attract users through reading web pages or click the page again, let the user detailed comprehensive understanding of the marketing plan, which affects the user＇ s real purchase decisions. Therefore, we combine the cloud environment with search engine optimization technique, the result shows that our method outperforms compared with other approaches.

A framework for Internet service evolution based on active object

The wide use of Internet Service in distributed computing and e-business has made the evolution of Internet Service to be one of the most prevalent research fields in software development domain. Traditional methods for software development cannot adapt to the challenge of Internet Service oriented software development. In this paper, we propose a new paradigm for the evolution of Internet Service with active objects from the characteristics of Intemet Service and principles of active objects. The paradigm uses an automatic monitoring mechanism of active object to detect and process evolution requirement in system based on Internet Service.

Regulation Issues for the Internet Market

Regulation of Internet market attracts more and more scholars and governments＇ attention as the Internet＇s commercial potential is displayed worldwide. Key characteristics of Internet market prove there are also market failures in Internet market, so regulation is an avoidable issue for the Internet market. Policy approaches relating to competition, intellectual property, and information privacy are three key areas of regulation that the paper emphasizes. The paper also analyzes the current regulation practices carried by some developed countries and calls for countries to cooperate and coordinate thus build a legal and fair environment for the Internet market.

Performance Analysis of Wavelength Division Multiplexing Asynchronous Internet Router Employing Space Priority Mechanism under Self-Similar Traffic Input—Multi-Server Queueing System with Markovian Input and Erlang-k Services

In this paper, we analyze the queueing behaviour of wavelength division multiplexing (WDM) Internet router employing partial buffer sharing (PBS) mechanism with self-similar traffic input. In view of WDM technology in networking, each output port of the router is modelled as multi-server queueing system. To guarantee the quality of service (QoS) in Broadband integrated services digital network (B-ISDN), PBS mechanism is a promising one. As Markov modulated Poisson process (MMPP) emulates self-similar Internet traffic, we can use MMPP as input process of queueing system to investigate queueing behaviour of the router. In general, as network traffic is asynchronous (unslotted) and of variable packet lengths, service times (packet lengths) are assumed to follow Erlang-k distribution. Since, the said distribution is relatively general compared to deterministic and exponential. Hence, specific output port of the router is modelled as MMPP/Ek/s/C queueing system. The long-term performance measures namely high priority and low priority packet loss probabilities and the short-term performance measures namely mean lengths of critical and non-critical periods against the system parameters and traffic parameters are computed by means of matrix-geometric methods and approximate Markovian model. This kind of analysis is useful in dimensioning the router under self-similar traffic input employing PBS mechanism to provide differentiated services (DiffServ) and QoS guarantee.

A Machine Learning-Based Distributed Denial of Service Detection Approach for Early Warning in Internet Exchange Points

The Internet service provider(ISP)is the heart of any country’s Internet infrastructure and plays an important role in connecting to theWorld WideWeb.Internet exchange point(IXP)allows the interconnection of two or more separate network infrastructures.All Internet traffic entering a country should pass through its IXP.Thus,it is an ideal location for performing malicious traffic analysis.Distributed denial of service(DDoS)attacks are becoming a more serious daily threat.Malicious actors in DDoS attacks control numerous infected machines known as botnets.Botnets are used to send numerous fake requests to overwhelm the resources of victims and make them unavailable for some periods.To date,such attacks present a major devastating security threat on the Internet.This paper proposes an effective and efficient machine learning(ML)-based DDoS detection approach for the early warning and protection of the Saudi Arabia Internet exchange point(SAIXP)platform.The effectiveness and efficiency of the proposed approach are verified by selecting an accurate ML method with a small number of input features.A chi-square method is used for feature selection because it is easier to compute than other methods,and it does not require any assumption about feature distribution values.Several ML methods are assessed using holdout and 10-fold tests on a public large-size dataset.The experiments showed that the performance of the decision tree(DT)classifier achieved a high accuracy result(99.98%)with a small number of features(10 features).The experimental results confirmthe applicability of using DT and chi-square for DDoS detection and early warning in SAIXP.