Basic Study on Elderly Tele-nursing Model for Emote Nursing by Smart Device

This study was carried out to examine the development of an “elderly tele-nursing model” for care provided in-home by family members and through remote nursing systems in a super-aging society. This model studied the travel time, cost, and means of transportation of care providers. The pre-survey results regarding elderly tele-nursing show that a son/daughter can visit a parent more than once a week. In the results, the time required for elderly tele-nursing was influenced by whether or not the visitor uses the shinkansen （bullet train of Japan）. In the main survey, based on 40 questionnaires, clear differences were observed according to whether visits were “every two weeks” or “once per month”. Furthermore, this result was also indicated by t-tests.

Access to smart devices and utilization of online health resources among older cardiac rehabilitation participants

BACKGROUND Newer models of cardiac rehabilitation(CR)delivery are promising but depend upon patient participation and ability to use technological media including Internet and smart devices.AIM To explore the availability of smart devices,current utilization and proficiency of use among older CR program attendees.METHODS Study participants were enrolled from four CR programs in Omaha,Nebraska United States and completed a questionnaire of 28 items.RESULTS Of 376 participants approached,169 responded(45%).Mean age was 71.1(SD±10)years.Demographics were 73.5%males,89.7%Caucasians,52%with college degree and 56.9%,with income of 40 K$or more.Smart device ownership was84.5%;desktop computer was the most preferred device.Average Internet use was 1.9 h/d(SD±1.7);54.3%of participants indicating for general usage but only18.4%pursued health-related purposes.Utilization of other health information modalities was low,29.8%used mobile health applications and 12.5%used wearable devices.Of all participants,72%reported no barriers to using Internet.Education and income were associated positively with measures of utilization and with less perceived barriers.CONCLUSIONAmong an older group of subjects attending CR,most have access to smart devices and do not perceive significant barriers to Internet use.Nonetheless,there was low utilization of health-related resources suggesting a need for targeted education in this patient population.

A Framework for Multi-Hop Ad-Hoc Networking over Wi-Fi Direct with Android Smart Devices

The wide diffusion of mobile devices that natively support ad hoc communication technologies has led to several protocols for enabling and optimizing Mobile Ad Hoc Networks (MANETs). Nevertheless, the actual utilization of MANETs in real life seems limited due to the lack of protocols for the automatic creation and evolution of ad hoc networks. Recently, a novel P2P protocol named Wi-Fi Direct has been proposed and standardized by the Wi-Fi Alliance to facilitate nearby devices’ interconnection. Wi-Fi Direct provides high-performance direct communication among devices, includes different energy management mechanisms, and is now available in most Android mobile devices. However, the current implementation of Wi-Fi Direct on Android has several limitations, making the Wi-Fi Direct network only be a one-hop ad-hoc network. This paper aims to develop a new framework for multi-hop ad hoc networking using Wi-Fi Direct in Android smart devices. The framework includes a connection establishment protocol and a group management protocol. Simulations validate the proposed framework on the OMNeT++ simulator. We analyzed the framework by varying transmission range, number of hops, and buffer size. The results indicate that the framework provides an eventual 100% packet delivery for different transmission ranges and hop count values. The buffer size has enough space for all packets. However, as buffer size decreases, the packet delivery decreases proportionally.

Conceivable Security Risks and Authentication Techniques for Smart Devices: A Comparative Evaluation of Security Practices

With the rapidly escalating use of smart devices and fraudulent transaction of users＇ data from their devices, efficient and reliable techniques for authentication of the smart devices have become an obligatory issue. This paper reviews the security risks for mobile devices and studies several authentication techniques available for smart devices. The results from field studies enable a comparative evaluation of user-preferred authentication mechanisms and their opinions about reliability, biometric authentication and visual authentication techniques.

MEACC: an energy-efficient framework for smart devices using cloud computing systems

Rapidly increasing capacities,decreasing costs,and improvements in computational power,storage,and communication technologies have led to the development of many applications that carry increasingly large amounts of traffic on the global networking infrastructure.Smart devices lead to emerging technologies and play a vital role in rapid evolution.Smart devices have become a primary 24/7 need in today’s information technology world and include a wide range of supporting processing-intensive applications.Extensive use of many applications on smart devices results in increasing complexity of mobile software applications and consumption of resources at a massive level,including smart device battery power,processor,and RAM,and hinders their normal operation.Appropriate resource utilization and energy efficiency are fundamental considerations for smart devices because limited resources are sporadic and make it more difficult for users to complete their tasks.In this study we propose the model of mobile energy augmentation using cloud computing(MEACC),a new framework to address the challenges of massive power consumption and inefficient resource utilization in smart devices.MEACC efficiently filters the applications to be executed on a smart device or offloaded to the cloud.Moreover,MEACC efficiently calculates the total execution cost on both the mobile and cloud sides including communication costs for any application to be offloaded.In addition,resources are monitored before making the decision to offload the application.MEACC is a promising model for load balancing and power consumption reduction in emerging mobile computing environments.

Thin film design for advanced thermochromic smart radiator devices

This paper describes the research on the materials and design methods for advanced smart radiator devices （SRDs） on large-area flexible substrates utilized on spacecraft. The functional material is thermochromic vanadium dioxide. The coating design of SRD is similar to the design of broadband filter coatings in a mid-infrared region. The multilayer coatings have complex structures. Coating materials must be highly transparent in a required spectrum region and also mechanically robust enough to endure the influence from the rigorous environments of outer space. The number of layers must be very small, suitable for the deposition on large-area flexible substrates. All the coatings are designed initially based on optical calculation and practical experience, and then optimized by the TFCALC software. Several designs are described and compared with each other. The results show that the emittance variability of the designed SRDs is great than 400%, more advanced than the reported ones.

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.

A Lightweight Anonymous Device Authentication Scheme for Information-Centric Distribution Feeder Microgrid

Distribution feeder microgrid(DFM)built based on existing distributed feeder(DF),is a promising solution for modern microgrid.DFM contains a large number of heterogeneous devices that generate heavy network traffice and require a low data delivery latency.The information-centric networking(ICN)paradigm has shown a great potential to address the communication requirements of smart grid.However,the integration of advanced information and communication technologies with DFM make it vulnerable to cyber attacks.Adequate authentication of grid devices is essential for preventing unauthorized accesses to the grid network and defending against cyber attacks.In this paper,we propose a new lightweight anonymous device authentication scheme for DFM supported by named data networking(NDN),a representative implementation of ICN.We perform a security analysis to show that the proposed scheme can provide security features such as mutual authentication,session key agreement,defending against various cyber attacks,anonymity,and resilience against device capture attack.The security of the proposed scheme is also formally verified using the popular AVISPA(Automated Validation of Internet Security Protocols and Applications)tool.The computational and communication costs of the proposed scheme are evaluated.Our results demonstrate that the proposed scheme achieves significantly lower computational,communication and energy costs than other state-of-the-art schemes.

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.

Convolutional Neural Network Model for Fire Detection in Real-Time Environment

Disasters such as conflagration,toxic smoke,harmful gas or chemical leakage,and many other catastrophes in the industrial environment caused by hazardous distance from the peril are frequent.The calamities are causing massive fiscal and human life casualties.However,Wireless Sensors Network-based adroit monitoring and early warning of these dangerous incidents will hamper fiscal and social fiasco.The authors have proposed an early fire detection system uses machine and/or deep learning algorithms.The article presents an Intelligent Industrial Monitoring System(IIMS)and introduces an Industrial Smart Social Agent(ISSA)in the Industrial SIoT(ISIoT)paradigm.The proffered ISSA empowers smart surveillance objects to communicate autonomously with other devices.Every Industrial IoT(IIoT)entity gets authorization from the ISSA to interact and work together to improve surveillance in any industrial context.The ISSA uses machine and deep learning algorithms for fire-related incident detection in the industrial environment.The authors have modeled a Convolutional Neural Network(CNN)and compared it with the four existing models named,FireNet,Deep FireNet,Deep FireNet V2,and Efficient Net for identifying the fire.To train our model,we used fire images and smoke sensor datasets.The image dataset contains fire,smoke,and no fire images.For evaluation,the proposed and existing models have been tested on the same.According to the comparative analysis,our CNN model outperforms other state-of-the-art models significantly.

Detection of Phishing in Internet-of-Things Using Hybrid Deep Belief Network

Increase in the use of internet of things owned devices is one of the reasonsforincreasednetworktraffic.Whileconnectingthesmartdeviceswith publicly available network many kinds of phishing attacks are able to enter into the mobile devices and corrupt the existing system.The Phishing is the slow and resilient attack stacking techniques probe the users.The proposed model is focused on detecting phishing attacks in internet of things enabled devices through a robust algorithm called Novel Watch and Trap Algorithm(NWAT).Though Predictive mapping,Predictive Validation and Predictive analysis mechanism is developed.For the test purpose Canadian Institute of cyber security(CIC)dataset is used for creating a robust prediction model.This attack generates a resilience corruption works that slowly gathers the credential information from the mobiles.The proposed Predictive analysis model(PAM)enabled NWAT algorithm is used to predict the phishing probes in the form of suspicious process happening in the IoT networks.The prediction system considers the peer-to-peer communication window open for the established communication,the suspicious process and its pattern is identified by the new approach.The proposed model is validated by finding thepredictionaccuracy,Precision,recallsF1score,errorrate,Mathew’sCorre-lationCoefficient(MCC)andBalancedDetectionRate(BDR).Thepresented approach is comparatively analyzed with the state-of-the-art approach of existing system related to various types of Phishing probes.

Metamaterial terahertz device with temperature regulation function that can achieve perfect absorption and complete reflection conversion of ultrawideband

The field of terahertz devices is important in terahertz technology.However,most of the current devices have limited functionality and poor performance.To improve device performance and achieve multifunctionality,we designed a terahertz device based on a combination of VO_(2)and metamaterials.This device can be tuned using the phase-transition characteristics of VO_(2),which is included in the triple-layer structure of the device,along with SiO_(2)and Au.The terahertz device exhibits various advantageous features,including broadband coverage,high absorption capability,dynamic tunability,simple structural design,polarization insensitivity,and incidentangle insensitivity.The simulation results showed that by controlling the temperature,the terahertz device achieved a thermal modulation range of spectral absorption from 0 to 0.99.At 313 K,the device exhibited complete reflection of terahertz waves.As the temperature increased,the absorption rate also increased.When the temperature reached 353 K,the device absorption rate exceeded 97.7%in the range of 5-8.55 THz.This study used the effective medium theory to elucidate the correlation between conductivity and temperature during the phase transition of VO_(2).Simultaneously,the variation in device performance was further elucidated by analyzing and depicting the intensity distribution of the electric field on the device surface at different temperatures.Furthermore,the impact of various structural parameters on device performance was examined,offering valuable insights and suggestions for selecting suitable parameter values in real-world applications.These characteristics render the device highly promising for applications in stealth technology,energy harvesting,modulation,and other related fields,thus showcasing its significant potential.

Higher ambient temperatures may worsen obstructive sleep apnea:A nationwide smartwatch-based analysis of 6.2 million person-days

Obstructive sleep apnea(OSA)is a serious type of sleep disorder that can lead to cardiometabolic and neurocognitive diseases.We utilized smart device-based photoplethysmography technology to collect sleep data from the Chinese population from 2019 to 2022.Distributed lag nonlinear models combined with a generalized nonlinear model or a linear mixed effects model were used to investigate the shortterm associations between daily temperature and indicators of OSA severity.We included a total of 6,232,056 d of sleep monitoring data from 51,842 participants with moderate to severe risk of OSA from 313 Chinese cities.The relationships between ambient temperature and OSA exacerbation,apneahypopnea index(AHI),and minimum oxygen saturation(MinSpO_(2))were almost linear and present only on the same day.Higher temperatures were associated with a greater risk of OSA exacerbation,with an 8.4%(95%confidence interval(CI):7.6%–9.3%)increase per 10℃increase in temperature.A 10℃increase in daily temperature corresponded to an AHI increase of 0.70 events/h(95%CI:0.65–0.76)and a MinSpO_(2)decrease of 0.18%(95%CI:0.16%–0.19%).Exposure to elevated temperatures during the night can also lead to adverse effects.The effects of higher temperatures on OSA severity were stronger among men,participants with a body mass index24 kg/m2,those aged 45 years and older,individuals with a history of hypertension and diabetes,and during the cold season.This large-scale,nationwide,longitudinal study provides robust evidence suggesting that higher ambient temperatures may immediately worsen OSA.

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.

Sensors and healthcare 5.0:transformative shift in virtual care through emerging digital health technologies

Emerging digital technologies continues to evolve posing unprecedented opportunities in health systems globally to improve healthcare services delivery.There has been significant progress in healthcare.However,the lack of emotive recognition coupled with a dearth of personalized and pervasive health applications and emotive smart devices calls for the integration of intelligent sensors health systems through emerging technologies.Although there has been significant progress in smart and connected health care,more research innovation,dissemination and technologies are needed to unbundle new opportunities and move towards healthcare 5.0.Healthcare is at the dawn of a paradigm change to reach the new era of smart disease control and detection,virtual care,smart health management,smart monitoring,and decision-making.Therefore,this study discusses the roles and capacities of sensors,their capabilities and other emerging technologies such as nanotechnology,5 G technologies,drone technology,blockchain,robotics,big data,internet of things,artificial intelligence,and cloud computing.Healthcare 5.0 provides healthcare services including patient remote monitoring.tracking and virtual clinics,emotive telemedicine,ambient assisted living,smart self-management,wellness monitoring and control,smart treatment reminders,compliance and adherence,and personalized and connected health care.However,building resilience and robust healthcare 5.0 is not immune to challenges.Organizational challenges,technological and infrastructural barriers,lack of legal and regulatory frameworks and e-health policies,individual perceptions,misalignment with hospitals'strategy,lack of funding,religious and cultural bariers are identified as potential barriers to the successful implementation of healthcare 5.0.Therefore,there is a need for building resilient technology-driven healthcare systems.To achieve this,there is a need for expanding technological infrastructure,provision of budgetary support based on sustainable business models,develop appropriate legal and e-health policies,standardization and synchronization of protocols,improving stakeholders'engagement and involvement and establishment of private and public partnerships and investments.

The Management of Digital Transformation in Higher Education:An Assessment Proposal

The impacts of the current digital era are growing more and more on the way in which higher education(HE)offers learning programs at every level.Smart learning(SL)represents the evolution of educational approaches and techniques that capitalizes on all the opportunities deriving from new digital ecosystems.This study argues that the usefulness of HE can benefit from rethinking the traditional active learning(AL)model to smart ones.Thus,this research aims at investigating how to adapt the performance evaluation when the operations of HE turn to digitalized models.Therefore,this paper designs a research approach that allows accounting for the effects that the adoption of some SL strategies and tools has on the engagement of students and the aggregate performance of HE programs that adopt AL.The results of this study would help academics and HE managers assess the effectiveness of SL initiatives they plan to adopt.

Lead zirconate(PbZrO_(3))embedded in natural rubber as electroactive elastomer composites

Perovskite lead zirconate(PbZrOz)was synthesized in an orthorhombic form at a temperature below the Curie temperature,Tc.The orthorhombic form is a noncentrosymmetric structure which is capable of spontaneous polarization.Fourier transform infrared(FTIR)spectra and X-ray diffraction(XRD)patterns confirm the siuccessful synthesis of the lead zirconate;and scanning electron microscopy(SEM)micrographs indicate that PbZrO_(3) particles are moderately dispersed in the natural rubber(NR)matrix.Without an electrical field,the particles merely act as a ferroelectric fller,which can absorb and store additional stress.Under an electrical field,particle induced dipole motents are generated,leading to interparticle interaction and a sub-stantial increase in the storage modulus.At a small amount of lead ziroonate part iculates present in the natural rubber matrix,at a volume fraction of 0.007306,the electrical conductivity increases dramatically by nearly two orders of magnitude at the electrical frequency of 500 kHz.

USB powered devices:A survey of side-channel threats and countermeasures

Recent technological innovations lead to the rise of a plethora of portable electronic devices such as smartphones,small household appliances,and other IoT devices.To power or recharge the battery of such devices,manufac-turers identified in the ubiquitous Universal Serial Bus(USB)standard a convenient solution,as it enables both communication and energy supply.Unfortunately,the default trust on USB ports has been exploited by hackers to extract highly sensitive user data on such devices.Despite the efforts by security experts and manufacturers to detect and block this threat,an even more stealthy approach to undermine users privacy relies on side-channel attacks on the USB interface,such as electromagnetic emissions and power consumption.In this paper,we present a comprehensive survey of the state-of-the-art of side-channel analysis on the security of USB-powered devices.Differently from other surveys on USB-based attacks via the communication interface only,this survey considers research works that aim to infer or extract private information from the energy supply,the device itself,or unintentionally available functionalities.In particular,we consider this emergent trend of security work that was not previously considered in other surveys,such as the energy consumption and electromagnetic emission analyses,as well as Juice Filming Charging(JFC)attacks.We first analyze the physical properties of the side-channels and technical characteristics of such research work,we then summarize the countermeasures proposed in the state-of-the-art.Finally,we also identify some possible future directions to foster further research in this field.

Advancing pathogen detection for airborne diseases

Airborne diseases including SARS,bird flu,and the ongoing Coronavirus Disease 2019(COVID-19)have stimulated the demand for developing novel bioassay methods competent for early-stage diagnosis and large-scale screening.Here,we briefly summarize the state-of-the-art methods for the detection of infectious pathogens and discuss key challenges.We highlight the trend for next-generation technologies benefiting from multidisciplinary advances in microfabrication,nanotechnology and synthetic biology,which allow sensitive,rapid yet inexpensive pathogen assays with portable intelligent device.

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.