The Marketing Factors Affecting Customer Decision-Making of Xiaomi Smart Wearable Devices in Guangxi,China

From an empirical point of view,this paper proposes research hypotheses and models based on the market situation of Xiaomi smart wearable devices in Guangxi,as well as the research status of consumers’purchasing decisions,combined with the empirical research of some researchers.This paper designs questionnaires and scales.The sampling survey method is used to investigate and analyze the influencing factors of Guangxi consumers’decision to purchase Xiaomi smart wearable devices.Questionnaires were distributed through Questionnaire Star,and 385 valid questionnaires were collected for descriptive statistics and correlation analysis.Conclusions are as follow:(1)Consumers in Guangxi who purchase Xiaomi smart wearable devices are between 19 and 32 years old,and most of them have a bachelor’s degree.Among the five factors of demographic characteristics,only income and marketing mix satisfaction have a positive correlation,indicating that customers are sensitive to Xiaomi smart wearable products.And among the customers of Xiaomi smart wearable products,the monthly income of less than 5,000 yuan accounted for 30.91%of the total number of surveys;the monthly income was 5,000-7,000 yuan,accounting for 34.29%.(2)The satisfaction of the marketing mix is positively correlated with the satisfaction of customer decision-making.The satisfaction of the marketing mix varies with the age,gender,education,income,and working years of each population,and only the income is positively correlated with the satisfaction of the marketing mix.Relationships,age,gender,education,and years of employment were not associated with marketing mix satisfaction.According to the above conclusions,relevant and reasonable product development and marketing suggestions are put forward for the enterprise,which provides a reference for the enterprise’s brand building and market development.Therefore,on the basis of comparing with other scholars at home and abroad,through the 7P marketing theory and purchasing decision theory and the research on the current situation of influencing factors for customers to purchase Xiaomi smart wearable devices in Guangxi,this paper compiled a questionnaire for 385 private colleges and universities in Guangxi.A questionnaire survey was carried out with customers,and the current situation of customers’purchasing decision-making behavior was obtained and analyzed and the following suggestions were put forward:continuously innovating products,targeting target customers,reasonably setting product prices,improving marketing mix.

Recent Progress for Gallium-Based Liquid Metal in Smart Wearable Textiles

The development of smart textiles has presentend new requirements for integrated devices that can be compatible with both conductivity and deformation.At room temperature,liquid metal presents both metallic properties and flexible properties,as well as low toxicity and biocompatible,which makes it more and more popular on the research of liquid metal based electronic devices.This review summarizes the basic physical properties,and the key points to be fabricated into fibers and fabrics including oxides and wettability.Meantime,the application in the field of textiles is presented.Liquid metal based electrical conductive fibers and flexible sensors can be fabricated mainly by injection and printing,as well as direct-writing for smart fabrics.Liquid metal can be integrated as functional components for smart wearable devices in the future by assembling the as-prepared fibers and fabrics with textile technology,such as twisting,sewing,knitting,and embroidering.

A Double-Compensation-Based Federated Learning Scheme for Data Privacy Protection in a Social IoT Scenario

Nowadays,smart wearable devices are used widely in the Social Internet of Things(IoT),which record human physiological data in real time.To protect the data privacy of smart devices,researchers pay more attention to federated learning.Although the data leakage problem is somewhat solved,a new challenge has emerged.Asynchronous federated learning shortens the convergence time,while it has time delay and data heterogeneity problems.Both of the two problems harm the accuracy.To overcome these issues,we propose an asynchronous federated learning scheme based on double compensation to solve the problem of time delay and data heterogeneity problems.The scheme improves the Delay Compensated Asynchronous Stochastic Gradient Descent(DC-ASGD)algorithm based on the second-order Taylor expansion as the delay compensation.It adds the FedProx operator to the objective function as the heterogeneity compensation.Besides,the proposed scheme motivates the federated learning process by adjusting the importance of the participants and the central server.We conduct multiple sets of experiments in both conventional and heterogeneous scenarios.The experimental results show that our scheme improves the accuracy by about 5%while keeping the complexity constant.We can find that our scheme converges more smoothly during training and adapts better in heterogeneous environments through numerical experiments.The proposed double-compensation-based federated learning scheme is highly accurate,flexible in terms of participants and smooth the training process.Hence it is deemed suitable for data privacy protection of smart wearable devices.

Wearable and humidity-resistant biomaterials-based triboelectric nanogenerator for high entropy energy harvesting and self-powered sensing

Triboelectric nanogenerator(TENG)provides a new solution to the energy supply by harvesting high entropy energy.However,wearable electronic devices have high requirements for flexible,humidity-resistant,and low-cost TENG.Here,environmentfriendly and multi-functional wheat starch TENG(S-TENG)was made by a simple and green method.The open-circuit voltage and short-circuit current of S-TENG are 151.4 V and 47.1μA,respectively.S-TENG can be used not only to drive and intelligently control electronic equipment,but also to effectively harvest energy from body movements and wind.In addition,the output of S-TENG was not negatively affected with the increase in environmental humidity,but increased abnormally.In the range of 20%RH–80%RH,S-TENG can be potentially used as a sensitive self-powered humidity sensor.The S-TENG paves the way for large-scale preparation of multi-functional biomaterials-based TENG,and practical application of self-powered sensing and wearable devices.