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
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 Mobile element variants(MEVs)have a significant and complex impact on genomic diversity and phe-notypic traits.However,the quantity,distribution,and relationship with gene expression and complex traits of M...Background Mobile element variants(MEVs)have a significant and complex impact on genomic diversity and phe-notypic traits.However,the quantity,distribution,and relationship with gene expression and complex traits of MEVs in the pig genome remain poorly understood.Results We constructed the most comprehensive porcine MEV library based on high-depth whole genome sequencing(WGS)data from 747 pigs across 59 breeds worldwide.This database identified a total of 147,993 poly-morphic MEVs,including 121,099 short interspersed nuclear elements(SINEs),26,053 long interspersed nuclear elements(LINEs),802 long terminal repeats(LTRs),and 39 other transposons,among which 54%are newly discovered.We found that MEVs are unevenly distributed across the genome and are strongly influenced by negative selec-tion effects.Importantly,we identified 514,530,and 584 candidate MEVs associated with population differentiation,domestication,and breed formation,respectively.For example,a significantly differentiated MEV is located in the ATRX intron between Asian and European pigs,whereas ATRX is also differentially expressed between Asian and European pigs in muscle tissue.In addition,we identified 4,169 expressed MEVs(eMEVs)significantly associated with gene expression and 6,914 splicing MEVs(sMEVs)associated with gene splicing based on RNA-seq data from 266 porcine liver tissues.These eMEVs and sMEVs explain 6.24%and 9.47%,respectively,of the observed cis-heritability and high-light the important role of MEVs in the regulation of gene expression.Finally,we provide a high-quality SNP–MEV reference haplotype panel to impute MEV genotypes from genome-wide SNPs.Notably,we identified a candidate MEV significantly associated with total teat number,demonstrating the functionality of this reference panel.Conclusions The present investigation demonstrated the importance of MEVs in pigs in terms of population diversity,gene expression and phenotypic traits,which may provide useful resources and theoretical support for pig genetics and breeding.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
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
By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-grow...By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this article.The proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for UEs.Firstly,we introduce the AGC-MEC architecture and elaborate three typical use cases.Then,we discuss four main challenges in the AGC-MEC as well as their potential solutions.Next,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement strategy.Finally,we highlight several potential research directions of the AGC-MEC.展开更多
In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mo...In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.展开更多
In the groundbreaking study “The Contribution of AI-powered Mobile Apps to Smart City Ecosystems,” authored by Zaki Ali Bayashot, the transformative role of artificial intelligence (AI) in urban development is metic...In the groundbreaking study “The Contribution of AI-powered Mobile Apps to Smart City Ecosystems,” authored by Zaki Ali Bayashot, the transformative role of artificial intelligence (AI) in urban development is meticulously examined. This comprehensive research delineates the multifaceted ways in which AI-powered mobile applications can significantly enhance the efficiency, sustainability, and livability of urban environments, marking a pivotal step towards the realization of smart cities globally. Bayashot meticulously outlines the critical areas where AI-powered apps offer unprecedented advantages, including urban mobility, public safety, energy management, and environmental monitoring. By leveraging AI’s capabilities, these applications not only streamline city operations but also foster a more sustainable interaction between city dwellers and their environment. The paper emphasizes the importance of data-driven decision-making in urban planning, showcasing how AI analytics can predict and mitigate traffic congestion, optimize energy consumption, and enhance emergency response strategies. The author also explores the social implications of AI in urban settings, highlighting the potential for these technologies to bridge the gap between government entities and citizens. Through engaging case studies, Bayashot demonstrates how participatory governance models, enabled by AI apps, can promote transparency, accountability, and citizen engagement in urban management. A significant contribution of this research is its focus on the challenges and opportunities presented by the integration of AI into smart city ecosystems. Bayashot discusses the technical, ethical, and privacy concerns associated with AI applications, advocating for a balanced approach that ensures technological advancements do not come at the expense of civil liberties. The study calls for robust regulatory frameworks to govern the use of AI in public spaces, emphasizing the need for ethical AI practices that respect privacy and promote inclusivity. Furthermore, Bayashot’s research underscores the necessity of cross-disciplinary collaboration in the development and implementation of AI technologies in urban contexts. By bringing together experts from information technology, urban planning, environmental science, and social sciences, the author argues for a holistic approach to smart city development. This interdisciplinary strategy ensures that AI applications are not only technologically sound but also socially and environmentally responsible. The paper concludes with a visionary outlook on the future of smart cities, posited on the seamless integration of AI technologies. Bayashot envisions a world where AI-powered mobile apps not only facilitate smoother urban operations but also empower citizens to actively participate in the shaping of their urban environments. This research serves as a critical call to action for policymakers, technologists, and urban planners to embrace AI as a tool for creating more sustainable, efficient, and inclusive cities. By presenting a detailed analysis of the current state of AI in urban development, coupled with practical insights and forward-looking recommendations, “The Contribution of AI-powered Mobile Apps to Smart City Ecosystems” stands as a seminal work that is poised to inspire and guide the evolution of urban landscapes worldwide. Its comprehensive exploration of the subject matter, combined with its impactful conclusions, make it a must-read for anyone involved in the field of smart city development, AI technology, or urban policy-making.展开更多
Existing mobile robots mostly use graph search algorithms for path planning,which suffer from relatively low planning efficiency owing to high redundancy and large computational complexity.Due to the limitations of th...Existing mobile robots mostly use graph search algorithms for path planning,which suffer from relatively low planning efficiency owing to high redundancy and large computational complexity.Due to the limitations of the neighborhood search strategy,the robots could hardly obtain the most optimal global path.A global path planning algorithm,denoted as EDG*,is proposed by expanding nodes using a well-designed expanding disconnected graph operator(EDG)in this paper.Firstly,all obstacles are marked and their corners are located through the map pre-processing.Then,the EDG operator is designed to find points in non-obstruction areas to complete the rapid expansion of disconnected nodes.Finally,the EDG*heuristic iterative algorithm is proposed.It selects the candidate node through a specific valuation function and realizes the node expansion while avoiding collision with a minimum offset.Path planning experiments were conducted in a typical indoor environment and on the public dataset CSM.The result shows that the proposed EDG*reduced the planning time by more than 90%and total length of paths reduced by more than 4.6%.Compared to A*,Dijkstra and JPS,EDG*does not show an exponential explosion effect in map size.The EDG*showed better performance in terms of path smoothness,and collision avoidance.This shows that the EDG*algorithm proposed in this paper can improve the efficiency of path planning and enhance path quality.展开更多
How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is pro...How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.展开更多
The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-base...The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.展开更多
This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. ...This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.展开更多
With the explosive growth of highdefinition video streaming data,a substantial increase in network traffic has ensued.The emergency of mobile edge caching(MEC)can not only alleviate the burden on core network,but also...With the explosive growth of highdefinition video streaming data,a substantial increase in network traffic has ensued.The emergency of mobile edge caching(MEC)can not only alleviate the burden on core network,but also significantly improve user experience.Integrating with the MEC and satellite networks,the network is empowered popular content ubiquitously and seamlessly.Addressing the research gap between multilayer satellite networks and MEC,we study the caching placement problem in this paper.Initially,we introduce a three-layer distributed network caching management architecture designed for efficient and flexible handling of large-scale networks.Considering the constraint on satellite capacity and content propagation delay,the cache placement problem is then formulated and transformed into a markov decision process(MDP),where the content coded caching mechanism is utilized to promote the efficiency of content delivery.Furthermore,a new generic metric,content delivery cost,is proposed to elaborate the performance of caching decision in large-scale networks.Then,we introduce a graph convolutional network(GCN)-based multi-agent advantage actor-critic(A2C)algorithm to optimize the caching decision.Finally,extensive simulations are conducted to evaluate the proposed algorithm in terms of content delivery cost and transferability.展开更多
Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground infrastructure.Mitigating this has greatly developed the applicat...Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground infrastructure.Mitigating this has greatly developed the application and integration of UAV and Mobile Edge Computing(MEC)to the Internet of Things(loT).However,problems such as multi-user and huge data flow in large areas,which contradict the reality that a single UAV is constrained by limited computing power,still exist.Due to allowing UAV collaboration to accomplish complex tasks,cooperative task offloading between multiple UAVs must meet the interdependence of tasks and realize parallel processing,which reduces the computing power consumption and endurance pressure of terminals.Considering the computing requirements of the user terminal,delay constraint of a computing task,energy constraint,and safe distance of UAV,we constructed a UAV-Assisted cooperative offloading energy efficiency system for mobile edge computing to minimize user terminal energy consumption.However,the resulting optimization problem is originally nonconvex and thus,difficult to solve optimally.To tackle this problem,we developed an energy efficiency optimization algorithm using Block Coordinate Descent(BCD)that decomposes the problem into three convex subproblems.Furthermore,we jointly optimized the number of local computing tasks,number of computing offloaded tasks,trajectories of UAV,and offloading matching relationship between multi-UAVs and multiuser terminals.Simulation results show that the proposed approach is suitable for different channel conditions and significantly saves the user terminal energy consumption compared with other benchmark schemes.展开更多
Tight gas reservoirs with mobile water exhibit multi-phase flow and high stress sensitivity.Accurately analyzing the reservoir and well parameters using conventional single-phase rate transient analysis methods proves...Tight gas reservoirs with mobile water exhibit multi-phase flow and high stress sensitivity.Accurately analyzing the reservoir and well parameters using conventional single-phase rate transient analysis methods proves challenging.This study introduces novel rate transient analysis methods incorporating evaluation processes based on the conventional flowing material balance method and the Blasingame type-curve method to examine fractured gas wells producing water.By positing a gas-water two-phase equivalent homogenous phase that considers characteristics of mobile water,gas,and high stress sensitivity,the conventional single-phase rate transient analysis methods can be applied by integrating the phase's characteristics and defining the phase's normalized parameters and material balance pseudotime.The rate transient analysis methods based on the equivalent homogenous phase can be used to quantitatively assess the parameters of wells and gas reservoirs,such as original gas-in-place,fracture half-length,reservoir permeability,and well drainage radius.This facilitates the analysis of production dynamics of fractured wells and well-controlled areas,subsequently aiding in locating residual gas and guiding the configuration of well patterns.The specific evaluation processes are detailed.Additionally,a numerical simulation mechanism model was constructed to verify the reliability of the developed methods.The methods introduced have been successfully implemented in field water-producing gas wells within tight gas reservoirs containing mobile water.展开更多
In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of ...In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of UAV,the transmitting beamforming of users,and the phase shift matrix of IRS.The original problem is strong non-convex and difficult to solve.We first propose two basic modes of the proactive eavesdropper,and obtain the closed-form solution for the boundary conditions of the two modes.Then we transform the original problem into an equivalent one and propose an alternating optimization(AO)based method to obtain a local optimal solution.The convergence of the algorithm is illustrated by numerical results.Further,we propose a zero forcing(ZF)based method as sub-optimal solution,and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes.展开更多
Various mobile devices and applications are now used in daily life.These devices require high-speed data processing,low energy consumption,low communication latency,and secure data transmission,especially in 5G and 6G...Various mobile devices and applications are now used in daily life.These devices require high-speed data processing,low energy consumption,low communication latency,and secure data transmission,especially in 5G and 6G mobile networks.High-security cryptography guarantees that essential data can be transmitted securely;however,it increases energy consumption and reduces data processing speed.Therefore,this study proposes a low-energy data encryption(LEDE)algorithm based on the Advanced Encryption Standard(AES)for improving data transmission security and reducing the energy consumption of encryption in Internet-of-Things(IoT)devices.In the proposed LEDE algorithm,the system time parameter is employed to create a dynamic S-Box to replace the static S-Box of AES.Tests indicated that six-round LEDE encryption achieves the same security level as 10-round conventional AES encryption.This reduction in encryption time results in the LEDE algorithm having a 67.4%lower energy consumption and 43.9%shorter encryption time than conventional AES;thus,the proposed LEDE algorithm can improve the performance and the energy consumption of IoT edge devices.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 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.
基金National Key Research and Development Program of China(2022YFF1000103)Postdoctoral Fellowship Program of CPSF under Grant Number GZC20240620.
文摘Background Mobile element variants(MEVs)have a significant and complex impact on genomic diversity and phe-notypic traits.However,the quantity,distribution,and relationship with gene expression and complex traits of MEVs in the pig genome remain poorly understood.Results We constructed the most comprehensive porcine MEV library based on high-depth whole genome sequencing(WGS)data from 747 pigs across 59 breeds worldwide.This database identified a total of 147,993 poly-morphic MEVs,including 121,099 short interspersed nuclear elements(SINEs),26,053 long interspersed nuclear elements(LINEs),802 long terminal repeats(LTRs),and 39 other transposons,among which 54%are newly discovered.We found that MEVs are unevenly distributed across the genome and are strongly influenced by negative selec-tion effects.Importantly,we identified 514,530,and 584 candidate MEVs associated with population differentiation,domestication,and breed formation,respectively.For example,a significantly differentiated MEV is located in the ATRX intron between Asian and European pigs,whereas ATRX is also differentially expressed between Asian and European pigs in muscle tissue.In addition,we identified 4,169 expressed MEVs(eMEVs)significantly associated with gene expression and 6,914 splicing MEVs(sMEVs)associated with gene splicing based on RNA-seq data from 266 porcine liver tissues.These eMEVs and sMEVs explain 6.24%and 9.47%,respectively,of the observed cis-heritability and high-light the important role of MEVs in the regulation of gene expression.Finally,we provide a high-quality SNP–MEV reference haplotype panel to impute MEV genotypes from genome-wide SNPs.Notably,we identified a candidate MEV significantly associated with total teat number,demonstrating the functionality of this reference panel.Conclusions The present investigation demonstrated the importance of MEVs in pigs in terms of population diversity,gene expression and phenotypic traits,which may provide useful resources and theoretical support for pig genetics and breeding.
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.
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.
基金supported in part by the National Natural Science Foundation of China under Grant 62171465,62072303,62272223,U22A2031。
文摘By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this article.The proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for UEs.Firstly,we introduce the AGC-MEC architecture and elaborate three typical use cases.Then,we discuss four main challenges in the AGC-MEC as well as their potential solutions.Next,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement strategy.Finally,we highlight several potential research directions of the AGC-MEC.
文摘In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.
文摘In the groundbreaking study “The Contribution of AI-powered Mobile Apps to Smart City Ecosystems,” authored by Zaki Ali Bayashot, the transformative role of artificial intelligence (AI) in urban development is meticulously examined. This comprehensive research delineates the multifaceted ways in which AI-powered mobile applications can significantly enhance the efficiency, sustainability, and livability of urban environments, marking a pivotal step towards the realization of smart cities globally. Bayashot meticulously outlines the critical areas where AI-powered apps offer unprecedented advantages, including urban mobility, public safety, energy management, and environmental monitoring. By leveraging AI’s capabilities, these applications not only streamline city operations but also foster a more sustainable interaction between city dwellers and their environment. The paper emphasizes the importance of data-driven decision-making in urban planning, showcasing how AI analytics can predict and mitigate traffic congestion, optimize energy consumption, and enhance emergency response strategies. The author also explores the social implications of AI in urban settings, highlighting the potential for these technologies to bridge the gap between government entities and citizens. Through engaging case studies, Bayashot demonstrates how participatory governance models, enabled by AI apps, can promote transparency, accountability, and citizen engagement in urban management. A significant contribution of this research is its focus on the challenges and opportunities presented by the integration of AI into smart city ecosystems. Bayashot discusses the technical, ethical, and privacy concerns associated with AI applications, advocating for a balanced approach that ensures technological advancements do not come at the expense of civil liberties. The study calls for robust regulatory frameworks to govern the use of AI in public spaces, emphasizing the need for ethical AI practices that respect privacy and promote inclusivity. Furthermore, Bayashot’s research underscores the necessity of cross-disciplinary collaboration in the development and implementation of AI technologies in urban contexts. By bringing together experts from information technology, urban planning, environmental science, and social sciences, the author argues for a holistic approach to smart city development. This interdisciplinary strategy ensures that AI applications are not only technologically sound but also socially and environmentally responsible. The paper concludes with a visionary outlook on the future of smart cities, posited on the seamless integration of AI technologies. Bayashot envisions a world where AI-powered mobile apps not only facilitate smoother urban operations but also empower citizens to actively participate in the shaping of their urban environments. This research serves as a critical call to action for policymakers, technologists, and urban planners to embrace AI as a tool for creating more sustainable, efficient, and inclusive cities. By presenting a detailed analysis of the current state of AI in urban development, coupled with practical insights and forward-looking recommendations, “The Contribution of AI-powered Mobile Apps to Smart City Ecosystems” stands as a seminal work that is poised to inspire and guide the evolution of urban landscapes worldwide. Its comprehensive exploration of the subject matter, combined with its impactful conclusions, make it a must-read for anyone involved in the field of smart city development, AI technology, or urban policy-making.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFB4700402).
文摘Existing mobile robots mostly use graph search algorithms for path planning,which suffer from relatively low planning efficiency owing to high redundancy and large computational complexity.Due to the limitations of the neighborhood search strategy,the robots could hardly obtain the most optimal global path.A global path planning algorithm,denoted as EDG*,is proposed by expanding nodes using a well-designed expanding disconnected graph operator(EDG)in this paper.Firstly,all obstacles are marked and their corners are located through the map pre-processing.Then,the EDG operator is designed to find points in non-obstruction areas to complete the rapid expansion of disconnected nodes.Finally,the EDG*heuristic iterative algorithm is proposed.It selects the candidate node through a specific valuation function and realizes the node expansion while avoiding collision with a minimum offset.Path planning experiments were conducted in a typical indoor environment and on the public dataset CSM.The result shows that the proposed EDG*reduced the planning time by more than 90%and total length of paths reduced by more than 4.6%.Compared to A*,Dijkstra and JPS,EDG*does not show an exponential explosion effect in map size.The EDG*showed better performance in terms of path smoothness,and collision avoidance.This shows that the EDG*algorithm proposed in this paper can improve the efficiency of path planning and enhance path quality.
文摘How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.
基金the China Scholarship Council(202106690037)the Natural Science Foundation of Anhui Province(19080885QE194)。
文摘The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.
基金the National Natural Science Foundation of China under Grant U22A2043.
文摘This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.
基金supported by the National Key Research and Development Program of China under Grant 2020YFB1807700the National Natural Science Foundation of China(NSFC)under Grant(No.62201414,62201432)+2 种基金the Qinchuangyuan Project(OCYRCXM-2022-362)the Fundamental Research Funds for the Central Universities and the Innovation Fund of Xidian University under Grant YJSJ24017the Guangzhou Science and Technology Program under Grant 202201011732。
文摘With the explosive growth of highdefinition video streaming data,a substantial increase in network traffic has ensued.The emergency of mobile edge caching(MEC)can not only alleviate the burden on core network,but also significantly improve user experience.Integrating with the MEC and satellite networks,the network is empowered popular content ubiquitously and seamlessly.Addressing the research gap between multilayer satellite networks and MEC,we study the caching placement problem in this paper.Initially,we introduce a three-layer distributed network caching management architecture designed for efficient and flexible handling of large-scale networks.Considering the constraint on satellite capacity and content propagation delay,the cache placement problem is then formulated and transformed into a markov decision process(MDP),where the content coded caching mechanism is utilized to promote the efficiency of content delivery.Furthermore,a new generic metric,content delivery cost,is proposed to elaborate the performance of caching decision in large-scale networks.Then,we introduce a graph convolutional network(GCN)-based multi-agent advantage actor-critic(A2C)algorithm to optimize the caching decision.Finally,extensive simulations are conducted to evaluate the proposed algorithm in terms of content delivery cost and transferability.
基金supported by the Jiangsu Provincial Key Research and Development Program(No.BE2020084-4)the National Natural Science Foundation of China(No.92067201)+2 种基金the National Natural Science Foundation of China(61871446)the Open Research Fund of Jiangsu Key Laboratory of Wireless Communications(710020017002)the Natural Science Foundation of Nanjing University of Posts and telecommunications(NY220047).
文摘Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground infrastructure.Mitigating this has greatly developed the application and integration of UAV and Mobile Edge Computing(MEC)to the Internet of Things(loT).However,problems such as multi-user and huge data flow in large areas,which contradict the reality that a single UAV is constrained by limited computing power,still exist.Due to allowing UAV collaboration to accomplish complex tasks,cooperative task offloading between multiple UAVs must meet the interdependence of tasks and realize parallel processing,which reduces the computing power consumption and endurance pressure of terminals.Considering the computing requirements of the user terminal,delay constraint of a computing task,energy constraint,and safe distance of UAV,we constructed a UAV-Assisted cooperative offloading energy efficiency system for mobile edge computing to minimize user terminal energy consumption.However,the resulting optimization problem is originally nonconvex and thus,difficult to solve optimally.To tackle this problem,we developed an energy efficiency optimization algorithm using Block Coordinate Descent(BCD)that decomposes the problem into three convex subproblems.Furthermore,we jointly optimized the number of local computing tasks,number of computing offloaded tasks,trajectories of UAV,and offloading matching relationship between multi-UAVs and multiuser terminals.Simulation results show that the proposed approach is suitable for different channel conditions and significantly saves the user terminal energy consumption compared with other benchmark schemes.
文摘Tight gas reservoirs with mobile water exhibit multi-phase flow and high stress sensitivity.Accurately analyzing the reservoir and well parameters using conventional single-phase rate transient analysis methods proves challenging.This study introduces novel rate transient analysis methods incorporating evaluation processes based on the conventional flowing material balance method and the Blasingame type-curve method to examine fractured gas wells producing water.By positing a gas-water two-phase equivalent homogenous phase that considers characteristics of mobile water,gas,and high stress sensitivity,the conventional single-phase rate transient analysis methods can be applied by integrating the phase's characteristics and defining the phase's normalized parameters and material balance pseudotime.The rate transient analysis methods based on the equivalent homogenous phase can be used to quantitatively assess the parameters of wells and gas reservoirs,such as original gas-in-place,fracture half-length,reservoir permeability,and well drainage radius.This facilitates the analysis of production dynamics of fractured wells and well-controlled areas,subsequently aiding in locating residual gas and guiding the configuration of well patterns.The specific evaluation processes are detailed.Additionally,a numerical simulation mechanism model was constructed to verify the reliability of the developed methods.The methods introduced have been successfully implemented in field water-producing gas wells within tight gas reservoirs containing mobile water.
基金This work was supported by the Key Scientific and Technological Project of Henan Province(Grant Number 222102210212)Doctoral Research Start Project of Henan Institute of Technology(Grant Number KQ2005)Key Research Projects of Colleges and Universities in Henan Province(Grant Number 23B510006).
文摘In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of UAV,the transmitting beamforming of users,and the phase shift matrix of IRS.The original problem is strong non-convex and difficult to solve.We first propose two basic modes of the proactive eavesdropper,and obtain the closed-form solution for the boundary conditions of the two modes.Then we transform the original problem into an equivalent one and propose an alternating optimization(AO)based method to obtain a local optimal solution.The convergence of the algorithm is illustrated by numerical results.Further,we propose a zero forcing(ZF)based method as sub-optimal solution,and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes.
基金This work was supported by the National Science and Technology Council,Taiwan,under Project NSTC 112-2221-E-029-015.
文摘Various mobile devices and applications are now used in daily life.These devices require high-speed data processing,low energy consumption,low communication latency,and secure data transmission,especially in 5G and 6G mobile networks.High-security cryptography guarantees that essential data can be transmitted securely;however,it increases energy consumption and reduces data processing speed.Therefore,this study proposes a low-energy data encryption(LEDE)algorithm based on the Advanced Encryption Standard(AES)for improving data transmission security and reducing the energy consumption of encryption in Internet-of-Things(IoT)devices.In the proposed LEDE algorithm,the system time parameter is employed to create a dynamic S-Box to replace the static S-Box of AES.Tests indicated that six-round LEDE encryption achieves the same security level as 10-round conventional AES encryption.This reduction in encryption time results in the LEDE algorithm having a 67.4%lower energy consumption and 43.9%shorter encryption time than conventional AES;thus,the proposed LEDE algorithm can improve the performance and the energy consumption of IoT edge devices.
