Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important a...Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.展开更多
BACKGROUND Children with critical acute abdominal conditions often undergo intestinal stoma surgery.AIM To explore the impact of a visual mobile terminal-based extended care model on caregiver competence for children ...BACKGROUND Children with critical acute abdominal conditions often undergo intestinal stoma surgery.AIM To explore the impact of a visual mobile terminal-based extended care model on caregiver competence for children with enterostomies.METHODS One hundred twenty children with enterostomies and their caregivers in a children's hospital in Beijing were divided into a control group and a study group.The control group(60 cases)received traditional telephone follow-up for continuity of care,while the study group(60 cases)used a visualization mobile terminal-based care model.The incidence of stoma-related complications,caregiver burden scale,and competence scores of children with stoma were compared between the two groups.RESULTS The primary caregiver burden score in the study group(37.22±3.17)was significantly lower than that in the control group(80.00±4.47),and the difference was statistically significant(P<0.05).Additionally,the caregiving ability score of the study group(172.08±3.49)was significantly higher than that of the control group(117.55±4.28;P<0.05).The total incidence of complications in the study group(11.7%,7/60)was significantly lower compared to the control group(33.3%,20/60;χ2=8.086,P=0.004).CONCLUSION The visual mobile terminal-based care model reduces caregiver burden,improves home care ability,lowers the incidence of complications and readmission rates,and supports successful second-stage reduction surgery for children with enterostomies.展开更多
Current you only look once(YOLO)-based algorithm model is facing the challenge of overwhelming parameters and calculation complexity under the printed circuit board(PCB)defect detection application scenario.In order t...Current you only look once(YOLO)-based algorithm model is facing the challenge of overwhelming parameters and calculation complexity under the printed circuit board(PCB)defect detection application scenario.In order to solve this problem,we propose a new method,which combined the lightweight network mobile vision transformer(Mobile Vi T)with the convolutional block attention module(CBAM)mechanism and the new regression loss function.This method needed less computation resources,making it more suitable for embedded edge detection devices.Meanwhile,the new loss function improved the positioning accuracy of the bounding box and enhanced the robustness of the model.In addition,experiments on public datasets demonstrate that the improved model achieves an average accuracy of 87.9%across six typical defect detection tasks,while reducing computational costs by nearly 90%.It significantly reduces the model's computational requirements while maintaining accuracy,ensuring reliable performance for edge deployment.展开更多
Objective:To systematically evaluate the effectiveness of mobile health(mHealth)interventions on self-management and blood pressure(BP)control in patients with hypertension and to provide recommendations for the clini...Objective:To systematically evaluate the effectiveness of mobile health(mHealth)interventions on self-management and blood pressure(BP)control in patients with hypertension and to provide recommendations for the clinic and future research.Methods:Databases including Embase,Cochrane Library,CINAHL,CNKI,SinoMed,Wanfang,and Weipu were searched to collect systematic reviews(SRs)and meta-analyses on mHealth interventions for hypertension management.Two researchers independently screened the articles and extracted data,and the Assessment of Multiple Systematic Reviews(AMSTAR 2)was used to evaluate the methodological quality of the included reviews.Results:A total of 11 SRs were included:1 review was rated as high quality,3 as low quality,and 7 as critically low quality.The mobile phone was the most common intervention type,followed by the internet.Seven reviews performed meta-analyses and showed that mHealth was associated with a significant reduction in systolic blood pressure(SBP),from 2.28 mmHg(95%CI-3.90 to-0.66;I^(2)=40%)to 14.77 mmHg(95%CI 11.76-17.77;I^(2)=89.7%),and diastolic blood pressure(DBP),from 1.50 mmHg(95%CI-2.20 to-0.08;I^(2)=62%)to 8.17 mmHg(95%CI 5.67-10.67;I^(2)=86%).Self-management behaviors included medication adherence(MA),diet,smoking,alcohol drinking,physical activity,and BP monitoring.There were inconsistent results on the effectiveness of mHealth interventions.Conclusions:mHealth interventions can improve BP control,MA,diet,and smoking in patients with hypertension,but the evidence for the efficacy of mHealth on physical activity and alcohol drinking improvement is limited.The methodological quality of existing SRs on the management of BP in patients with hypertension was relatively low,and more well-designed SRs or meta-analyses were needed to provide more evidence.mHealth interventions are useful for improving BP control of patients with hypertension.展开更多
Objectives:This study aimed to develop a mobile frailty management platform for Chinese communitydwelling older adults and evaluate its effectiveness,usability and safety.Methods:Based on literature research,the resea...Objectives:This study aimed to develop a mobile frailty management platform for Chinese communitydwelling older adults and evaluate its effectiveness,usability and safety.Methods:Based on literature research,the research team combined the frailty cycle and integration models,self-determination theory,and technology acceptance models and determined the frailty interventions through expert discussion,then transformed it into multimedia resources,finally,engineers developed the mobile management platform.A cluster sampling,parallel,single-blind,controlled quasiexperimental trial was conducted.Sixty older adults from two community health service centers were recruited from March to August 2023.The control group received routine community care,while the intervention group used the mobile frailty management platform.The incidence of frailty,scores of quality of life,depression,sleep quality,and grip strength within 12 weeks were compared between the two groups,and the availability and safety of the platform were assessed.Results:A total of 52 participants completed the study,27 in the intervention group and 25 in the control group.At 12 weeks after the intervention,the frailty state of the intervention group was reversed to prefrailty.There were no significant differences in the scores of quality of life,depression,sleep quality,and grip strength between the two groups before and 4 weeks after intervention.At 8 weeks and 12 weeks after the intervention,the quality of life,depression,and grip strength of the intervention group were improved with statistical significance(P<0.05).Sleep quality was statistically significant only 12 weeks after the intervention(P<0.05).System Usability Scale score for the platform was(87.96±5.88),indicating a highly satisfactory user experience.Throughout the intervention,no adverse events were reported among the older adults.Conclusions:The mobile frailty management platform effectively improved frailty status,depressive mood,sleep quality,grip strength,and quality of life for Chinese community-dwelling older adults.It holds clinical application value and is an effective tool for strengthening frailty management among Chinese community-dwelling older adults.展开更多
Background:This study evaluates the ability of mobile AI voice assistants(AI-VAs)to provide accurate medical advice for early knee osteoarthritis(KOA)and compares their performance with conventional web searches and h...Background:This study evaluates the ability of mobile AI voice assistants(AI-VAs)to provide accurate medical advice for early knee osteoarthritis(KOA)and compares their performance with conventional web searches and human clinicians.Methods:From September to October 2024,two AI-VAs(Apple’s Siri and Huawei’s Xiaoyi)were tested on 15 KOA-related questions in Chinese and English.The assessment focused on the accuracy of voice recognition,response capabilities,and medical advice.Siri was further tested in four international regions(USA,UK,Germany,Hong Kong)using localized languages.Results:In Chinese-language tests,Siri and Xiaoyi showed comparable voice recognition(recognition accuracy:95.6%vs.93.3%)and response ability(speech response:88.9%vs.85.7%).However,Siri provided significantly more accurate medical advice(medical advice:95.6%vs.53.3%;Z=2.762,P<0.001).External validation via Global Quality Score further confirmed Siri’s superiority(mean Global Quality Score=4.0 vs.Xiaoai=0.9).Siri outperformed Xiaoyi in English-language tests(53.3%vs.0%).While Siri’s medical advice accuracy(95.6%)surpassed non-specialist clinicians(Z=2.685,P=0.007),it primarily reflects filtered search results(Baidu/Google)rather than clinical synthesis.Claims of equivalence to junior surgeons(98.2%)must be interpreted cautiously,as AI-VAs lack diagnostic reasoning capabilities.This distinction is critical to avoid overstating their role in clinical decision-making.Conclusion:Current AI-VAs offer limited value in providing precise medical advice for KOA,primarily serving as intermediaries for web search results.Their performance varies across languages,regions,and search engines.展开更多
High-quality services in today’s mobile networks require stable delivery of bandwidth-intensive network content.Multipath QUIC(MPQUIC),as a multipath protocol that extends QUIC,can utilize multiple paths to support s...High-quality services in today’s mobile networks require stable delivery of bandwidth-intensive network content.Multipath QUIC(MPQUIC),as a multipath protocol that extends QUIC,can utilize multiple paths to support stable and efficient transmission.The standard coupled congestion control algorithm in MPQUIC synchronizes these paths to manage congestion,meeting fairness requirements and improving transmission efficiency.However,current algorithms’Congestion Window(CWND)reduction approach significantly decreases CWND upon packet loss,which lowers effective throughput,regardless of the congestion origin.Furthermore,the uncoupled Slow-Start(SS)in MPQUIC leads to independent exponential CWND growth on each path,potentially causing buffer overflow.To address these issues,we propose the CC-OLIA,which incorporates Packet Loss Classifcation(PLC)and Coupled Slow-Start(CSS).The PLC distinguishes between congestion-induced and random packet losses,adjusting CWND reduction accordingly to maintain throughput.Concurrently,the CSS module coordinates CWND growth during the SS,preventing abrupt increases.Implementation on MININET shows that CC-OLIA not only maintains fair performance but also enhances transmission efficiency across diverse network conditions.展开更多
Objectives:This study aimed to describe the development process of the peer precision-matching and health management mobile platform"Aspark"for people living with human immunodeficiency virus(HIV)(PLWH)and t...Objectives:This study aimed to describe the development process of the peer precision-matching and health management mobile platform"Aspark"for people living with human immunodeficiency virus(HIV)(PLWH)and to evaluate its usability.Methods:The study assembled a multidisciplinary research and development team comprising researchers,software engineers,art designers,clinical nursing specialists,HIV peer volunteers,and psychological counselors.The team employed an agile development model to iteratively build the platform.Using the social determinants of health framework and the interpersonal circumplex,we identified 14 matching variables for the mobile platform.A video production team was formed to create peer training videos on health management for PLWH.We integrated relevant tools to provide PLWH with various types of support,including informational,instrumental,emotional,affiliational,and appraisal assistance.From March to May 2024,the research team used convenience sampling to select 130 platform users.It administered an electronic questionnaire based on the System Usability Scale to evaluate the platform's overall usability.Results:The platform incorporates multiple functional modules,including"Precision Matching,""Drug Interaction Query,""Medication Reminder,""Health Management,""Mood Diary,""Community Discussion,"and"Activity Center,"achieving comprehensive coverage across informational,emotional,instrumental,social,and appraisal support.The precision matching module facilitates intelligent pairing between patients and peer volunteers;the health management module allows for the entry of test results and trend analysis;medication reminders and check-in features enhance medication adherence;the mood diary supports emotional recording and expressive writing;while the community module offers functions such as topic discussions,appointment scheduling,and organization of offline activities.Among the 130 valid questionnaires,more than 83%of users scored above 68 on the System Usability Scale,indicating that the platform demonstrates favourable usability.Conclusions:The"Aspark"platform offers a feasible and promising digital solution for precision matching in HIV peer support and health management,enabling healthcare providers to deliver personalized and continuous health support to patients through its functions.Well-designed clinical trials should be conducted in the future to evaluate the effectiveness of this tool.展开更多
The fast growth of mobile autonomous machines from traditional equipment to unmanned autonomous vehicles has fueled the demand for accurate and reliable localization solutions in diverse application domains.Ultra Wide...The fast growth of mobile autonomous machines from traditional equipment to unmanned autonomous vehicles has fueled the demand for accurate and reliable localization solutions in diverse application domains.Ultra Wide Band(UWB)technology has emerged as a promising candidate for addressing this need,offering high precision,immunity to multipath interference,and robust performance in challenging environments.In this comprehensive survey,we systematically explore UWB-based localization for mobile autonomous machines,spanning from fundamental principles to future trends.To the best of our knowledge,this review paper stands as the pioneer in systematically dissecting the algorithms of UWB-based localization for mobile autonomous machines,covering a spectrum from bottom-ranging schemes to advanced sensor fusion,error mitigation,and optimization techniques.By synthesizing existing knowledge,evaluating current methodologies,and highlighting future trends,this review aims to catalyze progress and innovation in the field,unlocking new opportunities for mobile autonomous machine applications across diverse industries and domains.Thus,it serves as a valuable resource for researchers,practitioners,and stakeholders interested in advancing the state-of-the-art UWB-based localization for mobile autonomous machines.展开更多
With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks e...With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks environment poses challenges,including frequent base station handoffs,which significantly degrade wireless network transmission performance.Improving transmission efficiency in high-speed mobile networks and optimizing spatiotemporal wireless resource allocation to enhance passengers’media experiences are key research priorities.To address these issues,we propose an Adaptive Cross-Layer Optimization Transmission Method with Environment Awareness(ACOTM-EA)tailored for high-speed rail streaming media.Within this framework,we develop a channel quality prediction model utilizing Kalman filtering and an algorithm to identify packet loss causes.Additionally,we introduce a proactive base station handoffstrategy to minimize handoffrelated disruptions and optimize resource distribution across adjacent base stations.Moreover,this study presents a wireless resource allocation approach based on an enhanced genetic algorithm,coupled with an adaptive bitrate selection mechanism,to maximize passenger Quality of Experience(QoE).To evaluate the proposed method,we designed a simulation experiment and compared ACOTM-EA with established algorithms.Results indicate that ACOTM-EA improves throughput by 11%and enhances passengers’media experience by 5%.展开更多
Background and Objective Social anxiety arising from intensive social media usage(SMU)among adolescents and youth has gained extensive attention in recent years due to its negative influence on mental health and acade...Background and Objective Social anxiety arising from intensive social media usage(SMU)among adolescents and youth has gained extensive attention in recent years due to its negative influence on mental health and academic performance.In spite of that,there is a dearth regarding the etiology of SMU-related social anxiety.This study aims to further clarify the influence of introversion personality on SMU-related social anxiety and the mechanism underlying such an association and provide a new perspective for developing effective intervention strategies for the highly prevailing SMU-related anxiety among Chinese college students.Methods A cohort of 979 college students(266 males and 713 females)aged 20.90±1.91 years was enrolled in this cross-sectional study.Four measures including the"extroversion"domain of Eysenck Personality Questionnaire Revised,Short Scale(EPQ-R-S E),Interaction Anxiousness Scale(IAS),Mobile Phone Addiction Index(MPAI),and Social Anxiety Scale for Social Media Users(SAS-SMU)were used to evaluate the influence of introversion personality on SMU-related social anxiety that was potentially mediated sequentially by interaction anxiousness and mobile phone addiction.Hayes PROCESS was used for correlation and mediation analysis.Results Interaction anxiousness(indirect effect=-1.331,95%CI:-1.559--1.122)partially mediated the association between introversion personality and SMU-related social anxiety.Besides,a sequential mediation of interaction anxiousness and mobile phone addiction in the link between introversion personality and SMU-related social anxiety was revealed(indirect effect=-0.308,95%CI:-0.404--0.220).No significant mediating effect was found with mobile phone addiction in the association between introversion personality and SMU-related social anxiety.Conclusion Targeting interaction anxiousness and mobile phone addiction may represent an efficient strategy alleviating SMU-related social anxiety among Chinese college students with introversion personality.展开更多
Self-management interventions for chronic obstructive pulmonary disease(COPD)patients using mobile health technology are beneficial for relieving disease symptoms,improving patients’adherence to rehabilitation self-m...Self-management interventions for chronic obstructive pulmonary disease(COPD)patients using mobile health technology are beneficial for relieving disease symptoms,improving patients’adherence to rehabilitation self-management,and improving quality of life.This paper reviews the application of mobile health technology in self-management of patients with chronic obstructive pulmonary disease,introduces the application form of mobile health technology in self-management of patients with chronic obstructive pulmonary disease,summarizes its application effect in self-management of patients with chronic obstructive pulmonary disease,analyzes the problems and proposes solutions in the process of research and implementation at this stage,with a view to providing a theory for the application of mobile health technology in pulmonary rehabilitation and management of patients with chronic obstructive pulmonary disease This study summarize the effect of its application in the self-management of patients with chronic obstructive pulmonary disease.展开更多
The correction of Light Detection and Ranging(LiDAR)intensity data is of great significance for enhancing its application value.However,traditional intensity correction methods based on Terrestrial Laser Scanning(TLS)...The correction of Light Detection and Ranging(LiDAR)intensity data is of great significance for enhancing its application value.However,traditional intensity correction methods based on Terrestrial Laser Scanning(TLS)technology rely on manual site setup to collect intensity training data at different distances and incidence angles,which is noisy and limited in sample quantity,restricting the improvement of model accuracy.To overcome this limitation,this study proposes a fine-grained intensity correction modeling method based on Mobile Laser Scanning(MLS)technology.The method utilizes the continuous scanning characteristics of MLS technology to obtain dense point cloud intensity data at various distances and incidence angles.Then,a fine-grained screening strategy is employed to accurately select distance-intensity and incidence angle-intensity modeling samples.Finally,based on these samples,a high-precision intensity correction model is established through polynomial fitting functions.To verify the effectiveness of the proposed method,comparative experiments were designed,and the MLS modeling method was validated against the traditional TLS modeling method on the same test set.The results show that on Test Set 1,where the distance values vary widely(i.e.,0.1–3 m),the intensity consistency after correction using the MLS modeling method reached 7.692 times the original intensity,while the traditional TLS modeling method only increased to 4.630 times the original intensity.On Test Set 2,where the incidence angle values vary widely(i.e.,0○–80○),the MLS modeling method,although with a relatively smaller advantage,still improved the intensity consistency to 3.937 times the original intensity,slightly better than the TLS modeling method’s 3.413 times.These results demonstrate the significant advantage of the modeling method proposed in this study in enhancing the accuracy of intensity correction models.展开更多
1.Introduction Mobile communications have catalyzed a new era of informa-tion technology revolution,significantly broadening and deepen-ing human-to-human,human-to-machine,and machine-to-machine connections.With their...1.Introduction Mobile communications have catalyzed a new era of informa-tion technology revolution,significantly broadening and deepen-ing human-to-human,human-to-machine,and machine-to-machine connections.With their incredible speed of development and wide-reaching impact,mobile communications serve as the cornerstone of the Internet of Everything,profoundly reshaping human cognitive abilities and ways of thinking.Furthermore,mobile communications are altering the patterns of production and life,driving leaps in productivity quality,and strongly promot-ing innovation within human civilization.展开更多
Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has b...Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has been constrained by high computational demands.Here,we developed GBiDC-PEST,a mobile application that incorporates an improved,lightweight detection algorithm based on the You Only Look Once(YOLO)series singlestage architecture,for real-time detection of four tiny pests(wheat mites,sugarcane aphids,wheat aphids,and rice planthoppers).GBiDC-PEST incorporates several innovative modules,including GhostNet for lightweight feature extraction and architecture optimization by reconstructing the backbone,the bi-directional feature pyramid network(BiFPN)for enhanced multiscale feature fusion,depthwise convolution(DWConv)layers to reduce computational load,and the convolutional block attention module(CBAM)to enable precise feature focus.The newly developed GBiDC-PEST was trained and validated using a multitarget agricultural tiny pest dataset(Tpest-3960)that covered various field environments.GBiDC-PEST(2.8 MB)significantly reduced the model size to only 20%of the original model size,offering a smaller size than the YOLO series(v5-v10),higher detection accuracy than YOLOv10n and v10s,and faster detection speed than v8s,v9c,v10m and v10b.In Android deployment experiments,GBiDCPEST demonstrated enhanced performance in detecting pests against complex backgrounds,and the accuracy for wheat mites and rice planthoppers was improved by 4.5-7.5%compared with the original model.The GBiDC-PEST optimization algorithm and its mobile deployment proposed in this study offer a robust technical framework for the rapid,onsite identification and localization of tiny pests.This advancement provides valuable insights for effective pest monitoring,counting,and control in various agricultural settings.展开更多
Background:Pneumonia remains a critical global health challenge,manifesting as a severe respiratory infection caused by viruses,bacteria,and fungi.Early detection is paramount for effective treatment,potentially reduc...Background:Pneumonia remains a critical global health challenge,manifesting as a severe respiratory infection caused by viruses,bacteria,and fungi.Early detection is paramount for effective treatment,potentially reducing mortality rates and optimizing healthcare resource allocation.Despite the importance of chest X-ray diagnosis,image analysis presents significant challenges,particularly in regions with limited medical expertise.This study addresses these challenges by proposing a computer-aided diagnosis system leveraging targeted image preprocessing and optimized deep learning techniques.Methods:We systematically evaluated contrast limited adaptive histogram equalization with varying clip limits for preprocessing chest X-ray images,demonstrating its effectiveness in enhancing feature visibility for diagnostic accuracy.Employing a comprehensive dataset of 5,863 X-ray images(1,583 pneumonia-negative,4,280 pneumonia-positive)collected from multiple healthcare facilities,we conducted a comparative analysis of transfer learning with pre-trained models including ResNet50v2,VGG-19,and MobileNetV2.Statistical validation was performed through 5-fold cross-validation.Results:Our results show that the contrast limited adaptive histogram equalization-enhanced approach with ResNet50v2 achieves 93.40%accuracy,outperforming VGG-19(84.90%)and MobileNetV2(89.70%).Statistical validation confirms the significance of these improvements(P<0.01).The development and optimization resulted in a lightweight mobile application(74 KB)providing rapid diagnostic support(1-2 s response time).Conclusion:The proposed approach demonstrates practical applicability in resource-constrained settings,balancing diagnostic accuracy with deployment efficiency,and offers a viable solution for computer-aided pneumonia diagnosis in areas with limited medical expertise.展开更多
The habitual use of smartphones during meals has become a common behavior,raising concerns about its potential impact on eating habits and metabolic health.The present narrative review investigates how using a smartph...The habitual use of smartphones during meals has become a common behavior,raising concerns about its potential impact on eating habits and metabolic health.The present narrative review investigates how using a smartphone or tablet during meals can cause distractions and negatively affect metabolic health.A comprehensive narrative review was conducted by synthesizing peer-reviewed studies on the interplay between smartphone use during meals,eating behaviors,and metabolic health.Relevant literature was identified through searches in electronic databases and organized thematically to highlight trends and research gaps.By synthesizing evidence from existing literature,this review highlights that smartphone use during meals is associated with increased caloric intake,altered food composition,and disruptions in postprandial metabolic responses.These effects are mediated by reduced meal awareness and psychological distractions,including multitasking.Variability in findings arises from differences in study designs and populations.This review identifies critical research gaps,including the lack of longitudinal studies and the need to explore mechanisms underlying these relationships.By summarizing trends and patterns,this narrative review offers valuable insights into the complex interplay between digital device use,eating habits,and metabolic health,providing a foundation for future research and interventions.展开更多
Patients with cardiovascular disease rely on medication to achieve favorable longterm clinical results.Poor adherence has been linked to a relative increase in mortality of 50%-80%as well as higher health care costs.T...Patients with cardiovascular disease rely on medication to achieve favorable longterm clinical results.Poor adherence has been linked to a relative increase in mortality of 50%-80%as well as higher health care costs.This scoping review thus aimed to explore the evidence of the effects of mobile health care apps on medication adherence in patients with cardiovascular diseases.A comprehensive data search and extraction was done in line with the updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews checklist.A total of 10 studies were included for the review.The mean pooled improvement in adherence was found to be 18%and the most effective tool was the digital therapeutics app discussed in Li et al’s study.Smartphones and apps enhance coronary artery disease management by promoting medication compliance.Challenges include data security and smartphone usage among the elderly.Tailored apps or voice assistants offer potential solutions.展开更多
With the advancement of globalization,South Korea has become a key destination for international students.However,these students often face challenges in adapting to daily life,particularly when using mobile banking a...With the advancement of globalization,South Korea has become a key destination for international students.However,these students often face challenges in adapting to daily life,particularly when using mobile banking applications,due to insufficient language support,cultural differences,and complex operational procedures.This study focuses on Chinese international students and analyzes the UI/UX design of mobile banking applications offered by Kookmin Bank and Hana Bank.Through literature reviews and surveys,the study identifies limitations in language adaptability,functionality layout,user interaction,and cultural adaptation,proposing concrete design improvements.The findings indicate that optimizing UI/UX design can significantly enhance international students’user experience and strengthen the global competitiveness of South Korean mobile banking services.This research provides reference material for designing for multicultural user groups and aims to promote research and practice in cross-cultural UI/UX design.展开更多
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2024-9/1).
文摘Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.
基金Supported by Project of the Health Bureau of the Logistics and Security Department of the Central Military Commission,No.145BHQ090003076XMilitary Family Planning Special Fund,No.21JSZ18.
文摘BACKGROUND Children with critical acute abdominal conditions often undergo intestinal stoma surgery.AIM To explore the impact of a visual mobile terminal-based extended care model on caregiver competence for children with enterostomies.METHODS One hundred twenty children with enterostomies and their caregivers in a children's hospital in Beijing were divided into a control group and a study group.The control group(60 cases)received traditional telephone follow-up for continuity of care,while the study group(60 cases)used a visualization mobile terminal-based care model.The incidence of stoma-related complications,caregiver burden scale,and competence scores of children with stoma were compared between the two groups.RESULTS The primary caregiver burden score in the study group(37.22±3.17)was significantly lower than that in the control group(80.00±4.47),and the difference was statistically significant(P<0.05).Additionally,the caregiving ability score of the study group(172.08±3.49)was significantly higher than that of the control group(117.55±4.28;P<0.05).The total incidence of complications in the study group(11.7%,7/60)was significantly lower compared to the control group(33.3%,20/60;χ2=8.086,P=0.004).CONCLUSION The visual mobile terminal-based care model reduces caregiver burden,improves home care ability,lowers the incidence of complications and readmission rates,and supports successful second-stage reduction surgery for children with enterostomies.
基金supported by the National Natural Science Foundation of China(Nos.62373215,62373219 and 62073193)the Natural Science Foundation of Shandong Province(No.ZR2023MF100)+1 种基金the Key Projects of the Ministry of Industry and Information Technology(No.TC220H057-2022)the Independently Developed Instrument Funds of Shandong University(No.zy20240201)。
文摘Current you only look once(YOLO)-based algorithm model is facing the challenge of overwhelming parameters and calculation complexity under the printed circuit board(PCB)defect detection application scenario.In order to solve this problem,we propose a new method,which combined the lightweight network mobile vision transformer(Mobile Vi T)with the convolutional block attention module(CBAM)mechanism and the new regression loss function.This method needed less computation resources,making it more suitable for embedded edge detection devices.Meanwhile,the new loss function improved the positioning accuracy of the bounding box and enhanced the robustness of the model.In addition,experiments on public datasets demonstrate that the improved model achieves an average accuracy of 87.9%across six typical defect detection tasks,while reducing computational costs by nearly 90%.It significantly reduces the model's computational requirements while maintaining accuracy,ensuring reliable performance for edge deployment.
基金supported by Chongqing Science and Technology Bureau Technology Innovation and Application Development Project(No.cstc2019jscx-msxmX0170)Chongqing Science and Health Joint Medical Research Project(No.2021MSXM208).
文摘Objective:To systematically evaluate the effectiveness of mobile health(mHealth)interventions on self-management and blood pressure(BP)control in patients with hypertension and to provide recommendations for the clinic and future research.Methods:Databases including Embase,Cochrane Library,CINAHL,CNKI,SinoMed,Wanfang,and Weipu were searched to collect systematic reviews(SRs)and meta-analyses on mHealth interventions for hypertension management.Two researchers independently screened the articles and extracted data,and the Assessment of Multiple Systematic Reviews(AMSTAR 2)was used to evaluate the methodological quality of the included reviews.Results:A total of 11 SRs were included:1 review was rated as high quality,3 as low quality,and 7 as critically low quality.The mobile phone was the most common intervention type,followed by the internet.Seven reviews performed meta-analyses and showed that mHealth was associated with a significant reduction in systolic blood pressure(SBP),from 2.28 mmHg(95%CI-3.90 to-0.66;I^(2)=40%)to 14.77 mmHg(95%CI 11.76-17.77;I^(2)=89.7%),and diastolic blood pressure(DBP),from 1.50 mmHg(95%CI-2.20 to-0.08;I^(2)=62%)to 8.17 mmHg(95%CI 5.67-10.67;I^(2)=86%).Self-management behaviors included medication adherence(MA),diet,smoking,alcohol drinking,physical activity,and BP monitoring.There were inconsistent results on the effectiveness of mHealth interventions.Conclusions:mHealth interventions can improve BP control,MA,diet,and smoking in patients with hypertension,but the evidence for the efficacy of mHealth on physical activity and alcohol drinking improvement is limited.The methodological quality of existing SRs on the management of BP in patients with hypertension was relatively low,and more well-designed SRs or meta-analyses were needed to provide more evidence.mHealth interventions are useful for improving BP control of patients with hypertension.
文摘Objectives:This study aimed to develop a mobile frailty management platform for Chinese communitydwelling older adults and evaluate its effectiveness,usability and safety.Methods:Based on literature research,the research team combined the frailty cycle and integration models,self-determination theory,and technology acceptance models and determined the frailty interventions through expert discussion,then transformed it into multimedia resources,finally,engineers developed the mobile management platform.A cluster sampling,parallel,single-blind,controlled quasiexperimental trial was conducted.Sixty older adults from two community health service centers were recruited from March to August 2023.The control group received routine community care,while the intervention group used the mobile frailty management platform.The incidence of frailty,scores of quality of life,depression,sleep quality,and grip strength within 12 weeks were compared between the two groups,and the availability and safety of the platform were assessed.Results:A total of 52 participants completed the study,27 in the intervention group and 25 in the control group.At 12 weeks after the intervention,the frailty state of the intervention group was reversed to prefrailty.There were no significant differences in the scores of quality of life,depression,sleep quality,and grip strength between the two groups before and 4 weeks after intervention.At 8 weeks and 12 weeks after the intervention,the quality of life,depression,and grip strength of the intervention group were improved with statistical significance(P<0.05).Sleep quality was statistically significant only 12 weeks after the intervention(P<0.05).System Usability Scale score for the platform was(87.96±5.88),indicating a highly satisfactory user experience.Throughout the intervention,no adverse events were reported among the older adults.Conclusions:The mobile frailty management platform effectively improved frailty status,depressive mood,sleep quality,grip strength,and quality of life for Chinese community-dwelling older adults.It holds clinical application value and is an effective tool for strengthening frailty management among Chinese community-dwelling older adults.
文摘Background:This study evaluates the ability of mobile AI voice assistants(AI-VAs)to provide accurate medical advice for early knee osteoarthritis(KOA)and compares their performance with conventional web searches and human clinicians.Methods:From September to October 2024,two AI-VAs(Apple’s Siri and Huawei’s Xiaoyi)were tested on 15 KOA-related questions in Chinese and English.The assessment focused on the accuracy of voice recognition,response capabilities,and medical advice.Siri was further tested in four international regions(USA,UK,Germany,Hong Kong)using localized languages.Results:In Chinese-language tests,Siri and Xiaoyi showed comparable voice recognition(recognition accuracy:95.6%vs.93.3%)and response ability(speech response:88.9%vs.85.7%).However,Siri provided significantly more accurate medical advice(medical advice:95.6%vs.53.3%;Z=2.762,P<0.001).External validation via Global Quality Score further confirmed Siri’s superiority(mean Global Quality Score=4.0 vs.Xiaoai=0.9).Siri outperformed Xiaoyi in English-language tests(53.3%vs.0%).While Siri’s medical advice accuracy(95.6%)surpassed non-specialist clinicians(Z=2.685,P=0.007),it primarily reflects filtered search results(Baidu/Google)rather than clinical synthesis.Claims of equivalence to junior surgeons(98.2%)must be interpreted cautiously,as AI-VAs lack diagnostic reasoning capabilities.This distinction is critical to avoid overstating their role in clinical decision-making.Conclusion:Current AI-VAs offer limited value in providing precise medical advice for KOA,primarily serving as intermediaries for web search results.Their performance varies across languages,regions,and search engines.
文摘High-quality services in today’s mobile networks require stable delivery of bandwidth-intensive network content.Multipath QUIC(MPQUIC),as a multipath protocol that extends QUIC,can utilize multiple paths to support stable and efficient transmission.The standard coupled congestion control algorithm in MPQUIC synchronizes these paths to manage congestion,meeting fairness requirements and improving transmission efficiency.However,current algorithms’Congestion Window(CWND)reduction approach significantly decreases CWND upon packet loss,which lowers effective throughput,regardless of the congestion origin.Furthermore,the uncoupled Slow-Start(SS)in MPQUIC leads to independent exponential CWND growth on each path,potentially causing buffer overflow.To address these issues,we propose the CC-OLIA,which incorporates Packet Loss Classifcation(PLC)and Coupled Slow-Start(CSS).The PLC distinguishes between congestion-induced and random packet losses,adjusting CWND reduction accordingly to maintain throughput.Concurrently,the CSS module coordinates CWND growth during the SS,preventing abrupt increases.Implementation on MININET shows that CC-OLIA not only maintains fair performance but also enhances transmission efficiency across diverse network conditions.
基金funded by the National Natural Science Foundation of China(72204006).
文摘Objectives:This study aimed to describe the development process of the peer precision-matching and health management mobile platform"Aspark"for people living with human immunodeficiency virus(HIV)(PLWH)and to evaluate its usability.Methods:The study assembled a multidisciplinary research and development team comprising researchers,software engineers,art designers,clinical nursing specialists,HIV peer volunteers,and psychological counselors.The team employed an agile development model to iteratively build the platform.Using the social determinants of health framework and the interpersonal circumplex,we identified 14 matching variables for the mobile platform.A video production team was formed to create peer training videos on health management for PLWH.We integrated relevant tools to provide PLWH with various types of support,including informational,instrumental,emotional,affiliational,and appraisal assistance.From March to May 2024,the research team used convenience sampling to select 130 platform users.It administered an electronic questionnaire based on the System Usability Scale to evaluate the platform's overall usability.Results:The platform incorporates multiple functional modules,including"Precision Matching,""Drug Interaction Query,""Medication Reminder,""Health Management,""Mood Diary,""Community Discussion,"and"Activity Center,"achieving comprehensive coverage across informational,emotional,instrumental,social,and appraisal support.The precision matching module facilitates intelligent pairing between patients and peer volunteers;the health management module allows for the entry of test results and trend analysis;medication reminders and check-in features enhance medication adherence;the mood diary supports emotional recording and expressive writing;while the community module offers functions such as topic discussions,appointment scheduling,and organization of offline activities.Among the 130 valid questionnaires,more than 83%of users scored above 68 on the System Usability Scale,indicating that the platform demonstrates favourable usability.Conclusions:The"Aspark"platform offers a feasible and promising digital solution for precision matching in HIV peer support and health management,enabling healthcare providers to deliver personalized and continuous health support to patients through its functions.Well-designed clinical trials should be conducted in the future to evaluate the effectiveness of this tool.
文摘The fast growth of mobile autonomous machines from traditional equipment to unmanned autonomous vehicles has fueled the demand for accurate and reliable localization solutions in diverse application domains.Ultra Wide Band(UWB)technology has emerged as a promising candidate for addressing this need,offering high precision,immunity to multipath interference,and robust performance in challenging environments.In this comprehensive survey,we systematically explore UWB-based localization for mobile autonomous machines,spanning from fundamental principles to future trends.To the best of our knowledge,this review paper stands as the pioneer in systematically dissecting the algorithms of UWB-based localization for mobile autonomous machines,covering a spectrum from bottom-ranging schemes to advanced sensor fusion,error mitigation,and optimization techniques.By synthesizing existing knowledge,evaluating current methodologies,and highlighting future trends,this review aims to catalyze progress and innovation in the field,unlocking new opportunities for mobile autonomous machine applications across diverse industries and domains.Thus,it serves as a valuable resource for researchers,practitioners,and stakeholders interested in advancing the state-of-the-art UWB-based localization for mobile autonomous machines.
基金substantially supported by the National Natural Science Foundation of China under Grant No.62002263in part by Tianjin Municipal Education Commission Research Program Project under 2022KJ012Tianjin Science and Technology Program Projects:24YDTPJC00630.
文摘With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks environment poses challenges,including frequent base station handoffs,which significantly degrade wireless network transmission performance.Improving transmission efficiency in high-speed mobile networks and optimizing spatiotemporal wireless resource allocation to enhance passengers’media experiences are key research priorities.To address these issues,we propose an Adaptive Cross-Layer Optimization Transmission Method with Environment Awareness(ACOTM-EA)tailored for high-speed rail streaming media.Within this framework,we develop a channel quality prediction model utilizing Kalman filtering and an algorithm to identify packet loss causes.Additionally,we introduce a proactive base station handoffstrategy to minimize handoffrelated disruptions and optimize resource distribution across adjacent base stations.Moreover,this study presents a wireless resource allocation approach based on an enhanced genetic algorithm,coupled with an adaptive bitrate selection mechanism,to maximize passenger Quality of Experience(QoE).To evaluate the proposed method,we designed a simulation experiment and compared ACOTM-EA with established algorithms.Results indicate that ACOTM-EA improves throughput by 11%and enhances passengers’media experience by 5%.
文摘Background and Objective Social anxiety arising from intensive social media usage(SMU)among adolescents and youth has gained extensive attention in recent years due to its negative influence on mental health and academic performance.In spite of that,there is a dearth regarding the etiology of SMU-related social anxiety.This study aims to further clarify the influence of introversion personality on SMU-related social anxiety and the mechanism underlying such an association and provide a new perspective for developing effective intervention strategies for the highly prevailing SMU-related anxiety among Chinese college students.Methods A cohort of 979 college students(266 males and 713 females)aged 20.90±1.91 years was enrolled in this cross-sectional study.Four measures including the"extroversion"domain of Eysenck Personality Questionnaire Revised,Short Scale(EPQ-R-S E),Interaction Anxiousness Scale(IAS),Mobile Phone Addiction Index(MPAI),and Social Anxiety Scale for Social Media Users(SAS-SMU)were used to evaluate the influence of introversion personality on SMU-related social anxiety that was potentially mediated sequentially by interaction anxiousness and mobile phone addiction.Hayes PROCESS was used for correlation and mediation analysis.Results Interaction anxiousness(indirect effect=-1.331,95%CI:-1.559--1.122)partially mediated the association between introversion personality and SMU-related social anxiety.Besides,a sequential mediation of interaction anxiousness and mobile phone addiction in the link between introversion personality and SMU-related social anxiety was revealed(indirect effect=-0.308,95%CI:-0.404--0.220).No significant mediating effect was found with mobile phone addiction in the association between introversion personality and SMU-related social anxiety.Conclusion Targeting interaction anxiousness and mobile phone addiction may represent an efficient strategy alleviating SMU-related social anxiety among Chinese college students with introversion personality.
基金supported by the 2025 Hangzhou Normal University Teaching Development and Reform Project(Project No.JG2025320)。
文摘Self-management interventions for chronic obstructive pulmonary disease(COPD)patients using mobile health technology are beneficial for relieving disease symptoms,improving patients’adherence to rehabilitation self-management,and improving quality of life.This paper reviews the application of mobile health technology in self-management of patients with chronic obstructive pulmonary disease,introduces the application form of mobile health technology in self-management of patients with chronic obstructive pulmonary disease,summarizes its application effect in self-management of patients with chronic obstructive pulmonary disease,analyzes the problems and proposes solutions in the process of research and implementation at this stage,with a view to providing a theory for the application of mobile health technology in pulmonary rehabilitation and management of patients with chronic obstructive pulmonary disease This study summarize the effect of its application in the self-management of patients with chronic obstructive pulmonary disease.
基金supported in part by the National Natural Science Foundation of China under grant number 31901239funded by Researchers Supporting Project Number(RSPD2025R947),King Saud University,Riyadh,Saudi Arabia.
文摘The correction of Light Detection and Ranging(LiDAR)intensity data is of great significance for enhancing its application value.However,traditional intensity correction methods based on Terrestrial Laser Scanning(TLS)technology rely on manual site setup to collect intensity training data at different distances and incidence angles,which is noisy and limited in sample quantity,restricting the improvement of model accuracy.To overcome this limitation,this study proposes a fine-grained intensity correction modeling method based on Mobile Laser Scanning(MLS)technology.The method utilizes the continuous scanning characteristics of MLS technology to obtain dense point cloud intensity data at various distances and incidence angles.Then,a fine-grained screening strategy is employed to accurately select distance-intensity and incidence angle-intensity modeling samples.Finally,based on these samples,a high-precision intensity correction model is established through polynomial fitting functions.To verify the effectiveness of the proposed method,comparative experiments were designed,and the MLS modeling method was validated against the traditional TLS modeling method on the same test set.The results show that on Test Set 1,where the distance values vary widely(i.e.,0.1–3 m),the intensity consistency after correction using the MLS modeling method reached 7.692 times the original intensity,while the traditional TLS modeling method only increased to 4.630 times the original intensity.On Test Set 2,where the incidence angle values vary widely(i.e.,0○–80○),the MLS modeling method,although with a relatively smaller advantage,still improved the intensity consistency to 3.937 times the original intensity,slightly better than the TLS modeling method’s 3.413 times.These results demonstrate the significant advantage of the modeling method proposed in this study in enhancing the accuracy of intensity correction models.
基金supported by the National Key Research and Develop-ment Program of China(2019YFB1803400).
文摘1.Introduction Mobile communications have catalyzed a new era of informa-tion technology revolution,significantly broadening and deepen-ing human-to-human,human-to-machine,and machine-to-machine connections.With their incredible speed of development and wide-reaching impact,mobile communications serve as the cornerstone of the Internet of Everything,profoundly reshaping human cognitive abilities and ways of thinking.Furthermore,mobile communications are altering the patterns of production and life,driving leaps in productivity quality,and strongly promot-ing innovation within human civilization.
基金support of the Natural Science Foundation of Jiangsu Province,China(BK20240977)the China Scholarship Council(201606850024)+1 种基金the National High Technology Research and Development Program of China(2016YFD0701003)the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(SJCX23_1488)。
文摘Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has been constrained by high computational demands.Here,we developed GBiDC-PEST,a mobile application that incorporates an improved,lightweight detection algorithm based on the You Only Look Once(YOLO)series singlestage architecture,for real-time detection of four tiny pests(wheat mites,sugarcane aphids,wheat aphids,and rice planthoppers).GBiDC-PEST incorporates several innovative modules,including GhostNet for lightweight feature extraction and architecture optimization by reconstructing the backbone,the bi-directional feature pyramid network(BiFPN)for enhanced multiscale feature fusion,depthwise convolution(DWConv)layers to reduce computational load,and the convolutional block attention module(CBAM)to enable precise feature focus.The newly developed GBiDC-PEST was trained and validated using a multitarget agricultural tiny pest dataset(Tpest-3960)that covered various field environments.GBiDC-PEST(2.8 MB)significantly reduced the model size to only 20%of the original model size,offering a smaller size than the YOLO series(v5-v10),higher detection accuracy than YOLOv10n and v10s,and faster detection speed than v8s,v9c,v10m and v10b.In Android deployment experiments,GBiDCPEST demonstrated enhanced performance in detecting pests against complex backgrounds,and the accuracy for wheat mites and rice planthoppers was improved by 4.5-7.5%compared with the original model.The GBiDC-PEST optimization algorithm and its mobile deployment proposed in this study offer a robust technical framework for the rapid,onsite identification and localization of tiny pests.This advancement provides valuable insights for effective pest monitoring,counting,and control in various agricultural settings.
文摘Background:Pneumonia remains a critical global health challenge,manifesting as a severe respiratory infection caused by viruses,bacteria,and fungi.Early detection is paramount for effective treatment,potentially reducing mortality rates and optimizing healthcare resource allocation.Despite the importance of chest X-ray diagnosis,image analysis presents significant challenges,particularly in regions with limited medical expertise.This study addresses these challenges by proposing a computer-aided diagnosis system leveraging targeted image preprocessing and optimized deep learning techniques.Methods:We systematically evaluated contrast limited adaptive histogram equalization with varying clip limits for preprocessing chest X-ray images,demonstrating its effectiveness in enhancing feature visibility for diagnostic accuracy.Employing a comprehensive dataset of 5,863 X-ray images(1,583 pneumonia-negative,4,280 pneumonia-positive)collected from multiple healthcare facilities,we conducted a comparative analysis of transfer learning with pre-trained models including ResNet50v2,VGG-19,and MobileNetV2.Statistical validation was performed through 5-fold cross-validation.Results:Our results show that the contrast limited adaptive histogram equalization-enhanced approach with ResNet50v2 achieves 93.40%accuracy,outperforming VGG-19(84.90%)and MobileNetV2(89.70%).Statistical validation confirms the significance of these improvements(P<0.01).The development and optimization resulted in a lightweight mobile application(74 KB)providing rapid diagnostic support(1-2 s response time).Conclusion:The proposed approach demonstrates practical applicability in resource-constrained settings,balancing diagnostic accuracy with deployment efficiency,and offers a viable solution for computer-aided pneumonia diagnosis in areas with limited medical expertise.
文摘The habitual use of smartphones during meals has become a common behavior,raising concerns about its potential impact on eating habits and metabolic health.The present narrative review investigates how using a smartphone or tablet during meals can cause distractions and negatively affect metabolic health.A comprehensive narrative review was conducted by synthesizing peer-reviewed studies on the interplay between smartphone use during meals,eating behaviors,and metabolic health.Relevant literature was identified through searches in electronic databases and organized thematically to highlight trends and research gaps.By synthesizing evidence from existing literature,this review highlights that smartphone use during meals is associated with increased caloric intake,altered food composition,and disruptions in postprandial metabolic responses.These effects are mediated by reduced meal awareness and psychological distractions,including multitasking.Variability in findings arises from differences in study designs and populations.This review identifies critical research gaps,including the lack of longitudinal studies and the need to explore mechanisms underlying these relationships.By summarizing trends and patterns,this narrative review offers valuable insights into the complex interplay between digital device use,eating habits,and metabolic health,providing a foundation for future research and interventions.
文摘Patients with cardiovascular disease rely on medication to achieve favorable longterm clinical results.Poor adherence has been linked to a relative increase in mortality of 50%-80%as well as higher health care costs.This scoping review thus aimed to explore the evidence of the effects of mobile health care apps on medication adherence in patients with cardiovascular diseases.A comprehensive data search and extraction was done in line with the updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews checklist.A total of 10 studies were included for the review.The mean pooled improvement in adherence was found to be 18%and the most effective tool was the digital therapeutics app discussed in Li et al’s study.Smartphones and apps enhance coronary artery disease management by promoting medication compliance.Challenges include data security and smartphone usage among the elderly.Tailored apps or voice assistants offer potential solutions.
文摘With the advancement of globalization,South Korea has become a key destination for international students.However,these students often face challenges in adapting to daily life,particularly when using mobile banking applications,due to insufficient language support,cultural differences,and complex operational procedures.This study focuses on Chinese international students and analyzes the UI/UX design of mobile banking applications offered by Kookmin Bank and Hana Bank.Through literature reviews and surveys,the study identifies limitations in language adaptability,functionality layout,user interaction,and cultural adaptation,proposing concrete design improvements.The findings indicate that optimizing UI/UX design can significantly enhance international students’user experience and strengthen the global competitiveness of South Korean mobile banking services.This research provides reference material for designing for multicultural user groups and aims to promote research and practice in cross-cultural UI/UX design.
