With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy...With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy.However,efficient client selection and adaptive weight allocation in heterogeneous and non-IID environments remain challenging.To address these issues,we propose Federated Learning with Client Selection and Adaptive Weighting(FedCW),a novel algorithm that leverages adaptive client selection and dynamic weight allocation for optimizing model convergence in real-time vehicular networks.FedCW selects clients based on their Euclidean distance from the global model and dynamically adjusts aggregation weights to optimize both data diversity and model convergence.Experimental results show that FedCW significantly outperforms existing FL algorithms such as FedAvg,FedProx,and SCAFFOLD,particularly in non-IID settings,achieving faster convergence,higher accuracy,and reduced communication overhead.These findings demonstrate that FedCW provides an effective solution for enhancing the performance of FL in heterogeneous,edge-based computing environments.展开更多
At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown ...At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments,this paper proposes an Attention-Enhanced Dueling Deep Q-Network(ADDueling DQN),which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework.A multi-objective reward function,centered on energy efficiency,is designed to comprehensively consider path length,terrain slope,motion smoothness,and obstacle avoidance,enabling optimal low-energy trajectory generation in 3D space from the source.The incorporation of a multihead attention mechanism allows the model to dynamically focus on energy-critical state features—such as slope gradients and obstacle density—thereby significantly improving its ability to recognize and avoid energy-intensive paths.Additionally,the prioritized experience replay mechanism accelerates learning from key decision-making experiences,suppressing inefficient exploration and guiding the policy toward low-energy solutions more rapidly.The effectiveness of the proposed path planning algorithm is validated through simulation experiments conducted in multiple off-road scenarios.Results demonstrate that AD-Dueling DQN consistently achieves the lowest average energy consumption across all tested environments.Moreover,the proposed method exhibits faster convergence and greater training stability compared to baseline algorithms,highlighting its global optimization capability under energy-aware objectives in complex terrains.This study offers an efficient and scalable intelligent control strategy for the development of energy-conscious autonomous navigation systems.展开更多
Nowadays,as lightweight mobile clients become more powerful and widely used,more and more information is stored on lightweight mobile clients,user sensitive data privacy protection has become an urgent concern and pro...Nowadays,as lightweight mobile clients become more powerful and widely used,more and more information is stored on lightweight mobile clients,user sensitive data privacy protection has become an urgent concern and problem to be solved.There has been a corresponding rise of security solutions proposed by researchers,however,the current security mechanisms on lightweight mobile clients are proven to be fragile.Due to the fact that this research field is immature and still unexplored in-depth,with this paper,we aim to provide a structured and comprehensive study on privacy protection using trusted execution environment(TEE)for lightweight mobile clients.This paper presents a highly effective and secure lightweight mobile client privacy protection system that utilizes TEE to provide a new method for privacy protection.In particular,the prototype of Lightweight Mobile Clients Privacy Protection Using Trusted Execution Environments(LMCPTEE)is built using Intel software guard extensions(SGX)because SGX can guarantee the integrity,confidentiality,and authenticity of private data.By putting lightweight mobile client critical data on SGX,the security and privacy of client data can be greatly improved.We design the authentication mechanism and privacy protection strategy based on SGX to achieve hardware-enhanced data protection and make a trusted connection with the lightweight mobile clients,thus build the distributed trusted system architecture.The experiment demonstrates that without relying on the performance of the blockchain,the LMCPTEE is practical,feasible,low-performance overhead.It can guarantee the privacy and security of lightweight mobile client private data.展开更多
To solve the arrearage problem that puzzled most of the mobile corporations, we propose an approach to forecast and evaluate the credits for mobile clients, devising a method that is of the coalescence of genetic algo...To solve the arrearage problem that puzzled most of the mobile corporations, we propose an approach to forecast and evaluate the credits for mobile clients, devising a method that is of the coalescence of genetic algorithm and multidimensional distinguishing model. In the end of this paper, a result of a testing application in Zhuhai Branch, GMCC was provided. The precision of the forecasting and evaluation of the client’s credit is near 90%. This study is very significant to the mobile communication corporation at all levels. The popularization of the techniques and the result would produce great benefits of both society and economy.展开更多
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
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
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
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
Multiple quantum well(MQW) Ⅲ-nitride diodes that can simultaneously emit and detect light feature an overlapping region between their electroluminescence and responsivity spectra, which allows them to be simultaneous...Multiple quantum well(MQW) Ⅲ-nitride diodes that can simultaneously emit and detect light feature an overlapping region between their electroluminescence and responsivity spectra, which allows them to be simultaneously used as both a transmitter and a receiver in a wireless light communication system. Here, we demonstrate a mobile light communication system using a time-division multiplexing(TDM) scheme to achieve bidirectional data transmission via the same optical channel.Two identical blue MQW diodes are defined by software as a transmitter or a receiver. To address the light alignment issue, an image identification module integrated with a gimbal stabilizer is used to automatically detect the locations of moving targets;thus, underwater audio communication is realized via a mobile blue-light TDM communication mode. This approach not only uses a single link but also integrates mobile nodes in a practical network.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
1.Introduction It has been almost 60 years since the launch of Intelsat-I,the world’s first commercial satellite communications system.Over the past few decades,the development of satellite communications has been dr...1.Introduction It has been almost 60 years since the launch of Intelsat-I,the world’s first commercial satellite communications system.Over the past few decades,the development of satellite communications has been driven by both technological advancements and growing application demands,which have given rise to three primary services:broadcast,fixed satellite,and mobile satellite services[1].展开更多
Objective:The use of technology is growing rapidly.It can also be used in nursing interventions.A technology pack can support nursing interventions.An application called guided imagery in Indonesian(GIANESIA)has been ...Objective:The use of technology is growing rapidly.It can also be used in nursing interventions.A technology pack can support nursing interventions.An application called guided imagery in Indonesian(GIANESIA)has been developed to reduce anxiety in preoperative patients.Methods:A total of 42 participants joined this research.The respondents were those who would undergo surgery.We used the numeric visual analog anxiety scale(NVAAS)as the instrument to measure their anxiety levels.The participants were first given informed consent.Then,they open the application that has been installed.The process begins with participants choosing their initial anxiety score.Later,they start the therapy session,and immediately after finishing it,a pop-up bar prompts them to enter their final,posttherapy anxiety score.Results:This study shows the effectiveness of therapy given by GIANESIA in reducing anxiety in preoperative patients with p-value=0.000(a<0.05).Also,61.9%of the participants had decreased anxiety levels after therapy with GIANESIA.Conclusions:This study proves that providing therapy via a mobile application is effective in easing uncomfortable feelings,especially anxiety,in preoperative patients.Moving forward,the app can and should be expanded with new features and further developmental goals.展开更多
The proliferation of deep learning(DL)has amplified the demand for processing large and complex datasets for tasks such as modeling,classification,and identification.However,traditional DL methods compromise client pr...The proliferation of deep learning(DL)has amplified the demand for processing large and complex datasets for tasks such as modeling,classification,and identification.However,traditional DL methods compromise client privacy by collecting sensitive data,underscoring the necessity for privacy-preserving solutions like Federated Learning(FL).FL effectively addresses escalating privacy concerns by facilitating collaborative model training without necessitating the sharing of raw data.Given that FL clients autonomously manage training data,encouraging client engagement is pivotal for successful model training.To overcome challenges like unreliable communication and budget constraints,we present ENTIRE,a contract-based dynamic participation incentive mechanism for FL.ENTIRE ensures impartial model training by tailoring participation levels and payments to accommodate diverse client preferences.Our approach involves several key steps.Initially,we examine how random client participation impacts FL convergence in non-convex scenarios,establishing the correlation between client participation levels and model performance.Subsequently,we reframe model performance optimization as an optimal contract design challenge to guide the distribution of rewards among clients with varying participation costs.By balancing budget considerations with model effectiveness,we craft optimal contracts for different budgetary constraints,prompting clients to disclose their participation preferences and select suitable contracts for contributing to model training.Finally,we conduct a comprehensive experimental evaluation of ENTIRE using three real datasets.The results demonstrate a significant 12.9%enhancement in model performance,validating its adherence to anticipated economic properties.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
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
The mobile sound source localization system is a technology that can track and locate mobile sound sources in real time and has broad application prospects in many fields.This article first provides an overview of the...The mobile sound source localization system is a technology that can track and locate mobile sound sources in real time and has broad application prospects in many fields.This article first provides an overview of the mobile sound source localization system,introducing its concept and composition,as well as its design and application significance.It elaborates on the importance of the mobile sound source localization system from multiple aspects,such as safety,production,and daily life,and deeply explores its design and application strategies.The problems faced by the mobile sound source localization system and its future development direction were pointed out.展开更多
Mobile crowdsensing(MCS)has become an effective paradigm to facilitate urban sensing.However,mobile users participating in sensing tasks will face the risk of location privacy leakage when uploading their actual sensi...Mobile crowdsensing(MCS)has become an effective paradigm to facilitate urban sensing.However,mobile users participating in sensing tasks will face the risk of location privacy leakage when uploading their actual sensing location data.In the application of mobile crowdsensing,most location privacy protection studies do not consider the temporal correlations between locations,so they are vulnerable to various inference attacks,and there is the problem of low data availability.In order to solve the above problems,this paper proposes a dynamic differential location privacy data publishing framework(DDLP)that protects privacy while publishing locations continuously.Firstly,the corresponding Markov transition matrices are established according to different times of historical trajectories,and then the protection location set is generated based on the current location at each timestamp.Moreover,using the exponential mechanism in differential privacy perturbs the true location by designing the utility function.Finally,experiments on the real-world trajectory dataset show that our method not only provides strong privacy guarantees,but also outperforms existing methods in terms of data availability and computational efficiency.展开更多
文摘With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy.However,efficient client selection and adaptive weight allocation in heterogeneous and non-IID environments remain challenging.To address these issues,we propose Federated Learning with Client Selection and Adaptive Weighting(FedCW),a novel algorithm that leverages adaptive client selection and dynamic weight allocation for optimizing model convergence in real-time vehicular networks.FedCW selects clients based on their Euclidean distance from the global model and dynamically adjusts aggregation weights to optimize both data diversity and model convergence.Experimental results show that FedCW significantly outperforms existing FL algorithms such as FedAvg,FedProx,and SCAFFOLD,particularly in non-IID settings,achieving faster convergence,higher accuracy,and reduced communication overhead.These findings demonstrate that FedCW provides an effective solution for enhancing the performance of FL in heterogeneous,edge-based computing environments.
文摘At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments,this paper proposes an Attention-Enhanced Dueling Deep Q-Network(ADDueling DQN),which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework.A multi-objective reward function,centered on energy efficiency,is designed to comprehensively consider path length,terrain slope,motion smoothness,and obstacle avoidance,enabling optimal low-energy trajectory generation in 3D space from the source.The incorporation of a multihead attention mechanism allows the model to dynamically focus on energy-critical state features—such as slope gradients and obstacle density—thereby significantly improving its ability to recognize and avoid energy-intensive paths.Additionally,the prioritized experience replay mechanism accelerates learning from key decision-making experiences,suppressing inefficient exploration and guiding the policy toward low-energy solutions more rapidly.The effectiveness of the proposed path planning algorithm is validated through simulation experiments conducted in multiple off-road scenarios.Results demonstrate that AD-Dueling DQN consistently achieves the lowest average energy consumption across all tested environments.Moreover,the proposed method exhibits faster convergence and greater training stability compared to baseline algorithms,highlighting its global optimization capability under energy-aware objectives in complex terrains.This study offers an efficient and scalable intelligent control strategy for the development of energy-conscious autonomous navigation systems.
基金supported by the National Natural Science Foundation of China(Grant No.61762033)Hainan Provincial Natural Science Foundation of China(Grant Nos.2019RC041 and 2019RC098)+2 种基金Opening Project of Shanghai Trusted Industrial Control Platform(Grant No.TICPSH202003005-ZC)Ministry of Education Humanities and Social Sciences Research Program Fund Project(Grant No.19YJA710010)Zhejiang Public Welfare Technology Research(Grant No.LGF18F020019).
文摘Nowadays,as lightweight mobile clients become more powerful and widely used,more and more information is stored on lightweight mobile clients,user sensitive data privacy protection has become an urgent concern and problem to be solved.There has been a corresponding rise of security solutions proposed by researchers,however,the current security mechanisms on lightweight mobile clients are proven to be fragile.Due to the fact that this research field is immature and still unexplored in-depth,with this paper,we aim to provide a structured and comprehensive study on privacy protection using trusted execution environment(TEE)for lightweight mobile clients.This paper presents a highly effective and secure lightweight mobile client privacy protection system that utilizes TEE to provide a new method for privacy protection.In particular,the prototype of Lightweight Mobile Clients Privacy Protection Using Trusted Execution Environments(LMCPTEE)is built using Intel software guard extensions(SGX)because SGX can guarantee the integrity,confidentiality,and authenticity of private data.By putting lightweight mobile client critical data on SGX,the security and privacy of client data can be greatly improved.We design the authentication mechanism and privacy protection strategy based on SGX to achieve hardware-enhanced data protection and make a trusted connection with the lightweight mobile clients,thus build the distributed trusted system architecture.The experiment demonstrates that without relying on the performance of the blockchain,the LMCPTEE is practical,feasible,low-performance overhead.It can guarantee the privacy and security of lightweight mobile client private data.
基金Guangdong Mobile Communication Company Limited Key Item(2001 and 2002)
文摘To solve the arrearage problem that puzzled most of the mobile corporations, we propose an approach to forecast and evaluate the credits for mobile clients, devising a method that is of the coalescence of genetic algorithm and multidimensional distinguishing model. In the end of this paper, a result of a testing application in Zhuhai Branch, GMCC was provided. The precision of the forecasting and evaluation of the client’s credit is near 90%. This study is very significant to the mobile communication corporation at all levels. The popularization of the techniques and the result would produce great benefits of both society and economy.
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 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 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.
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jointly supported by the National Natural Science Foundation of China (U21A20495)Natural Science Foundation of Jiangsu Province (BG2024023)+1 种基金National Key Research and Development Program of China (2022YFE0112000)111 Project (D17018)。
文摘Multiple quantum well(MQW) Ⅲ-nitride diodes that can simultaneously emit and detect light feature an overlapping region between their electroluminescence and responsivity spectra, which allows them to be simultaneously used as both a transmitter and a receiver in a wireless light communication system. Here, we demonstrate a mobile light communication system using a time-division multiplexing(TDM) scheme to achieve bidirectional data transmission via the same optical channel.Two identical blue MQW diodes are defined by software as a transmitter or a receiver. To address the light alignment issue, an image identification module integrated with a gimbal stabilizer is used to automatically detect the locations of moving targets;thus, underwater audio communication is realized via a mobile blue-light TDM communication mode. This approach not only uses a single link but also integrates mobile nodes in a practical network.
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 in part by the National Key Research and Development Program of China(2023YFB2904703).
文摘1.Introduction It has been almost 60 years since the launch of Intelsat-I,the world’s first commercial satellite communications system.Over the past few decades,the development of satellite communications has been driven by both technological advancements and growing application demands,which have given rise to three primary services:broadcast,fixed satellite,and mobile satellite services[1].
基金supported by Ministry of Research and Technology/National Research and Innovation Agency Program scheme PDP(Research for Beginner Lecturers)2021(No.B/112/E3/RA.00/2021).
文摘Objective:The use of technology is growing rapidly.It can also be used in nursing interventions.A technology pack can support nursing interventions.An application called guided imagery in Indonesian(GIANESIA)has been developed to reduce anxiety in preoperative patients.Methods:A total of 42 participants joined this research.The respondents were those who would undergo surgery.We used the numeric visual analog anxiety scale(NVAAS)as the instrument to measure their anxiety levels.The participants were first given informed consent.Then,they open the application that has been installed.The process begins with participants choosing their initial anxiety score.Later,they start the therapy session,and immediately after finishing it,a pop-up bar prompts them to enter their final,posttherapy anxiety score.Results:This study shows the effectiveness of therapy given by GIANESIA in reducing anxiety in preoperative patients with p-value=0.000(a<0.05).Also,61.9%of the participants had decreased anxiety levels after therapy with GIANESIA.Conclusions:This study proves that providing therapy via a mobile application is effective in easing uncomfortable feelings,especially anxiety,in preoperative patients.Moving forward,the app can and should be expanded with new features and further developmental goals.
基金supported by the National Natural Science Foundation of China(Nos.62072411,62372343,62402352,62403500)the Key Research and Development Program of Hubei Province(No.2023BEB024)the Open Fund of Key Laboratory of Social Computing and Cognitive Intelligence(Dalian University of Technology),Ministry of Education(No.SCCI2024TB02).
文摘The proliferation of deep learning(DL)has amplified the demand for processing large and complex datasets for tasks such as modeling,classification,and identification.However,traditional DL methods compromise client privacy by collecting sensitive data,underscoring the necessity for privacy-preserving solutions like Federated Learning(FL).FL effectively addresses escalating privacy concerns by facilitating collaborative model training without necessitating the sharing of raw data.Given that FL clients autonomously manage training data,encouraging client engagement is pivotal for successful model training.To overcome challenges like unreliable communication and budget constraints,we present ENTIRE,a contract-based dynamic participation incentive mechanism for FL.ENTIRE ensures impartial model training by tailoring participation levels and payments to accommodate diverse client preferences.Our approach involves several key steps.Initially,we examine how random client participation impacts FL convergence in non-convex scenarios,establishing the correlation between client participation levels and model performance.Subsequently,we reframe model performance optimization as an optimal contract design challenge to guide the distribution of rewards among clients with varying participation costs.By balancing budget considerations with model effectiveness,we craft optimal contracts for different budgetary constraints,prompting clients to disclose their participation preferences and select suitable contracts for contributing to model training.Finally,we conduct a comprehensive experimental evaluation of ENTIRE using three real datasets.The results demonstrate a significant 12.9%enhancement in model performance,validating its adherence to anticipated economic properties.
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.
基金supported by the National Natural Science Foundation of China(U2013602).
文摘The mobile sound source localization system is a technology that can track and locate mobile sound sources in real time and has broad application prospects in many fields.This article first provides an overview of the mobile sound source localization system,introducing its concept and composition,as well as its design and application significance.It elaborates on the importance of the mobile sound source localization system from multiple aspects,such as safety,production,and daily life,and deeply explores its design and application strategies.The problems faced by the mobile sound source localization system and its future development direction were pointed out.
基金supported by the Inner Mongolia Natural Science Foundation(Grant No.2023MS06022)the University Youth Science and Technology Talent Development Project(Innovation Group Development Plan)of Inner Mongolia A.R.of China(Grant No.NMGIRT2318)+1 种基金the“Inner Mongolia Science and Technology Achievement Transfer and Transformation Demonstration Zone,University Collaborative Innovation Base,and University Entrepreneurship Training Base”Construction Project(Supercomputing Power Project)(Grant No.21300-231510)the Engineering Research Center of Ecological Big Data,Ministry of Education.
文摘Mobile crowdsensing(MCS)has become an effective paradigm to facilitate urban sensing.However,mobile users participating in sensing tasks will face the risk of location privacy leakage when uploading their actual sensing location data.In the application of mobile crowdsensing,most location privacy protection studies do not consider the temporal correlations between locations,so they are vulnerable to various inference attacks,and there is the problem of low data availability.In order to solve the above problems,this paper proposes a dynamic differential location privacy data publishing framework(DDLP)that protects privacy while publishing locations continuously.Firstly,the corresponding Markov transition matrices are established according to different times of historical trajectories,and then the protection location set is generated based on the current location at each timestamp.Moreover,using the exponential mechanism in differential privacy perturbs the true location by designing the utility function.Finally,experiments on the real-world trajectory dataset show that our method not only provides strong privacy guarantees,but also outperforms existing methods in terms of data availability and computational efficiency.
