Objective:To evaluate mobile applications available for patients undergoing assisted reproduction and assess the extent of their clinical validation.Methods:A systematic search was conducted in the Apple App Store and...Objective:To evaluate mobile applications available for patients undergoing assisted reproduction and assess the extent of their clinical validation.Methods:A systematic search was conducted in the Apple App Store and Google Play between September 1,2023 and September 30,2023 to identify mobile applications related to assisted reproduction.Apps were evaluated using the mobile app rating scale(MARS).In parallel,a literature search of PubMed,Scopus,Embase,and Web of Science was performed to identify clinical studies related to mobile applications in assisted reproduction.Clinical validation status and MARS scores were recorded,and findings were synthesized to highlight the gap between commercially available apps and research-based evidence.Results:From 1143 apps screened,11 met the inclusion criteria.Mean MARS score across apps was 3.63,with Leeaf scoring the highest(4.60).However,only one application(Embie)was supported by published research.The literature research identified 13 relevant studies,mostly randomized controlled trials,cohort studies,or usability studies.While research-based apps demonstrated clinical utility(e.g.,MediEmo,PreLiFe,Patient Journey App),most were unavailable on app stores.This revealed a disconnect between research-backed applications and those accessible to patients.Conclusions:Although several mobile apps for assisted reproduction demonstrate high usability and quality,few are clinically validated.The lack of integration between research and practice highlights the need for stronger collaboration between researchers,developers,and policymakers to ensure that patients access safe and effective tools.展开更多
To achieve privacy and authentication sinmltaneously in mobile applications, various Three-party Password-authenticated key exchange （3PAKE） protocols have been proposed. However, some of these protocols are vulnera...To achieve privacy and authentication sinmltaneously in mobile applications, various Three-party Password-authenticated key exchange （3PAKE） protocols have been proposed. However, some of these protocols are vulnerable to conventional attacks or have low efficiency so that they cannot be applied to mobile applications. In this paper, we proposed a password-authenticated multiple key exchange protocol for mobile applications using elliptic curve cryptosystem. The proposed protocol can achieve efficiency, reliability, flexibility and scalability at the same time. Compared with related works, the proposed protocol is more suitable and practical for mobile applications.展开更多
Multi-agent mobile applications play an essential role in mobile applications and have attracted more and more researchers’attention.Previous work has always focused on multi-agent applications with perfect informati...Multi-agent mobile applications play an essential role in mobile applications and have attracted more and more researchers’attention.Previous work has always focused on multi-agent applications with perfect information.Researchers are usually based on human-designed rules to provide decision-making searching services.However,existing methods for solving perfect-information mobile applications cannot be directly applied to imperfect-information mobile applications.Here,we take the Contact Bridge,a multi-agent application with imperfect information,for the case study.We propose an enhanced searching strategy to deal with multi-agent applications with imperfect information.We design a self-training bidding system model and apply a Recurrent Neural Network(RNN)to model the bidding process.The bridge system model consists of two parts,a bidding prediction system based on imitation learning to get a contract quickly and a visualization system for hands understanding to realize regular communication between players.Then,to dynamically analyze the impact of other players’unknown hands on our final reward,we design a Monte Carlo sampling algorithm based on the bidding system model(BSM)to deal with imperfect information.At the same time,a double-dummy analysis model is designed to efficiently evaluate the results of sampling.Experimental results indicate that our searching strategy outperforms the top rule-based mobile applications.展开更多
Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilizatio...Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilization). However, in some mobile devices applications (e.g. image sequence panoramic stitching), the high resolution is necessary to obtain satisfactory quality of panoramic image. However, the computational cost will become too expensive to be suitable for the low power consumption requirement of mobile device. The full search algorithm can obtain the global minimum with extremely computational cost, while the typical fast algorithms may suffer from the local minimum problem. This paper proposed a fast algorithm to deal with 2560 × 1920 high-resolution (HR) image sequences. The proposed method estimates the motion vector by a two-level coarse-to-fine scheme which only exploits sparse reference blocks (25 blocks in this paper) in each level to determine the global motion vector, thus the computational costs are significantly decreased. In order to increase the effective search range and robustness, the predictive motion vector (PMV) technique is used in this work. By the comparisons of computational complexity, the proposed algorithm costs less addition operations than the typical Three-Step Search algorithm (TSS) for estimating the global motion of the HR images without the local minimum problem. The quantitative evaluations show that our method is comparable to the full search algorithm (FSA) which is considered to be the golden baseline.展开更多
<div style="text-align:justify;"> <span style="font-family:Verdana;">Software reliability is an important quality attribute, and software reliability models are frequently used to measu...<div style="text-align:justify;"> <span style="font-family:Verdana;">Software reliability is an important quality attribute, and software reliability models are frequently used to measure and predict software maturity. The nature of mobile environments differs from that of PC and server environments due to many factors, such as the network, energy, battery, and compatibility. Evaluating and predicting mobile application reliability are real challenges because of the diversity of the mobile environments in which the applications are used, and the lack of publicly available defect data. In addition, bug reports are optionally submitted by end-users. In this paper, we propose assessing and predicting the reliability of a mobile application using known software reliability growth models (SRGMs). Four software reliability models are used to evaluate the reliability of an open-source mobile application through analyzing bug reports. Our experiment proves it is possible to use SRGMs with defect data acquired from bug reports to assess and predict the software reliability in mobile applications. The results of our work enable software developers and testers to assess and predict the reliability of mobile software applications.</span> </div>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
Patients with cardiovascular disease rely on medication to achieve favorable longterm clinical results.Poor adherence has been linked to a relative increase in mortality of 50%-80%as well as higher health care costs.T...Patients with cardiovascular disease rely on medication to achieve favorable longterm clinical results.Poor adherence has been linked to a relative increase in mortality of 50%-80%as well as higher health care costs.This scoping review thus aimed to explore the evidence of the effects of mobile health care apps on medication adherence in patients with cardiovascular diseases.A comprehensive data search and extraction was done in line with the updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews checklist.A total of 10 studies were included for the review.The mean pooled improvement in adherence was found to be 18%and the most effective tool was the digital therapeutics app discussed in Li et al’s study.Smartphones and apps enhance coronary artery disease management by promoting medication compliance.Challenges include data security and smartphone usage among the elderly.Tailored apps or voice assistants offer potential solutions.展开更多
Mobile health apps (MHAs) and medical apps (MAs) are becoming increasinglypopular as digital interventions in a wide range of health-related applications inalmost all sectors of healthcare. The surge in demand for dig...Mobile health apps (MHAs) and medical apps (MAs) are becoming increasinglypopular as digital interventions in a wide range of health-related applications inalmost all sectors of healthcare. The surge in demand for digital medical solutionshas been accelerated by the need for new diagnostic and therapeutic methods inthe current coronavirus disease 2019 pandemic. This also applies to clinicalpractice in gastroenterology, which has, in many respects, undergone a recentdigital transformation with numerous consequences that will impact patients andhealth care professionals in the near future. MHAs and MAs are considered tohave great potential, especially for chronic diseases, as they can support the selfmanagementof patients in many ways. Despite the great potential associated withthe application of MHAs and MAs in gastroenterology and health care in general,there are numerous challenges to be met in the future, including both the ethicaland legal aspects of applying this technology. The aim of this article is to providean overview of the current status of MHA and MA use in the field ofgastroenterology, describe the future perspectives in this field and point out someof the challenges that need to be addressed.展开更多
Due to the rapid rise of mobile phones around the globe, many consumers, researchers, clinicians, and health services are starting to see their utility in health. As well as a health informatics role in improving the ...Due to the rapid rise of mobile phones around the globe, many consumers, researchers, clinicians, and health services are starting to see their utility in health. As well as a health informatics role in improving the uptake and efficiency of current health services, mobile communication-assisted health care （m-health） also opens opportunities for services that are strikingly new and curative, in particular delivering personal health behaviour change programmes. Herein, we report the preliminary findings of a health-promotion survey titled ＂Mobile Apps User Trend Analysis of Turkish People＂. The survey examines the information needs and media preferences of women and men who research health information and use mobile apps for their healthcare in everyday life. Also this study tries to recover the behaviour of people and what applications they are downloading with respect to health, wellness, and medical mobile applicaitons. In looking the data, it appears that adoption of mHealth is growing at a furious pace. In this context, improvements to health communication have the potential to make a significant role to a promising new medium for health education and communication.展开更多
Smart mobile applications are software applications that are designed to run on smart phones, tablets, and other mobile electronic devices. In this era of rapid technological advances, these applications have become o...Smart mobile applications are software applications that are designed to run on smart phones, tablets, and other mobile electronic devices. In this era of rapid technological advances, these applications have become one of the primary tools we use daily both in our personal and professional lives. The applications play key roles in facilitating many applications that are pivotal in our today＇s society including communication, education, business, entertainment, medical, finance, travel, utilities, social, and transportation. This paper reviewed the opportunities and challenges of the applications related to transportation. The opportunities revealed include route planning, ridesharing/carpooling, traffic safety, parking information, transportation data collection, fuel emissions and consumption, and travel information. The potential users of these applications in the field of transportation include （I） transportation agencies for travel data collection, travel information, ridesharing/carpooling, and traffic safety, （2） engineering students for field data collection such as travel speed, travel time, and vehicle count, and （3） general traveling public for route planning, ridesharing/carpooling, parking, traffic safety, and travel information. Significant usage of smart mobile applications can be potentially very beneficial, particularly in automobile travel mode to reduce travel time, cost, and vehicle emissions. In the end this would make travel safer and living environments greener and healthier. However, road users＇ interactions with these applications could manually, visually, and cognitively divert their attention from the primary task of driving or walking. Distracted road users expose themselves and others to unsafe behavior than undistracted. Road safety education and awareness programs are vital to discourage the use of applications that stimulate unsafe driving/walking behaviors. Educating the traveling public about the dangers of unsafe driving/walking behavior could have significant safety benefits to all road users. Future research needs to compare accuracies of the applications and provide guidelines for selecting them for certain transportation related applications.展开更多
Objectives:In recent years,the use of mobile health applications(mHealth apps)to deliver care for patients with breast cancer has increased exponentially.This study aimed to summarize the available evidence on develop...Objectives:In recent years,the use of mobile health applications(mHealth apps)to deliver care for patients with breast cancer has increased exponentially.This study aimed to summarize the available evidence on developing mHealth apps to care for patients with breast cancer and identify the need for systematic efforts.Methods:A scoping review was performed according to Arksey and O’Malley’s framework,aiming to identify eligible research studies in PubMed,CINAHL,and Web of Science between January 2010 and December 2020.All identified studies were screened,extracted,and analyzed independently by two reviewers.Results:A total of 676 studies were retrieved,and eight eligible studies were finally included.Four themes emerged:the involvement of patients and health professionals in the phases of design and development,patients’preferences,the characteristics of patients,and the motivators to use mHealth apps.The results indicated promising prospects for using mHealth apps to care for patients with breast cancer and identified the need for systematic efforts to develop and validate relevant apps.Conclusions:The attributes of patient characteristics,needs,and patient-reported outcomes data are vital components for developing mHealth apps for patients with breast cancer.Additionally,collaborative efforts,including patients,nurses,and other significant health professionals,should develop mHealth apps for breast cancer care.Additional research focusing on the design and development of mHealth apps for patients with breast cancer is warranted.展开更多
Software reverse engineering is the process of analyzing a software system to extract the design and implementation details.Reverse engineering provides the source code of an application,the insight view of the archit...Software reverse engineering is the process of analyzing a software system to extract the design and implementation details.Reverse engineering provides the source code of an application,the insight view of the architecture and the third-party dependencies.From a security perspective,it is mostly used for finding vulnerabilities and attacking or cracking an application.The process is carried out either by obtaining the code in plaintext or reading it through the binaries or mnemonics.Nowadays,reverse engineering is widely used for mobile applications and is considered a security risk.The Open Web Application Security Project(OWASP),a leading security research forum,has included reverse engineering in its top 10 list of mobile application vulnerabilities.Mobile applications are used in many sectors,e.g.,banking,education,health.In particular,the banking applications are critical in terms of security as they are used for financial transactions.A security breach of such applications can result in huge financial losses for the customers as well as the banks.There exist various tools for reverse engineering of mobile applications,however,they have deficiencies,e.g.,complex configurations,lack of detailed analysis reports.In this research work,we perform an analysis of the available tools for reverse engineering of mobile applications.Our dataset consists of the mobile banking applications of the banks providing services in Pakistan.Our results indicate that none of the existing tools can carry out the complete reverse engineering process as a standalone tool.In addition,we observe significant differences in terms of the execution time and the number of files generated by each tool for the same file.展开更多
In 2010, cloud computing gained momentum. Cloud computing is a model for real-time, on-demand, pay-for-use network access to a shared pool of configurable computing and storage resources. It has matured from a promisi...In 2010, cloud computing gained momentum. Cloud computing is a model for real-time, on-demand, pay-for-use network access to a shared pool of configurable computing and storage resources. It has matured from a promising business concept to a working reality in both the private and public IT sectors. The U.S. government, for example, has requested all its agencies to evaluate cloud computing alternatives as part of their budget submissions for new IT investment.展开更多
Mobile devices are being deployed rapidly for both private and professional reasons.One area of that has been growing is in releasing healthcare applications into the mobile marketplaces for health management.These ap...Mobile devices are being deployed rapidly for both private and professional reasons.One area of that has been growing is in releasing healthcare applications into the mobile marketplaces for health management.These applications help individuals track their own biorhythms and contain sensitive information.This case study examines the source code of mobile applications released to GitHub for the Risk of Insufficient Cryptography in the Top Ten Mobile Open Web Application Security Project risks.We first develop and justify a mobile OWASP Cryptographic knowledge-graph for detecting security weaknesses specific to mobile applications which can be extended to other domains involving cryptography.We then analyze the source code of 203 open source healthcare mobile applications and report on their usage of cryptography in the applications.Our findings show that none of the open source healthcare applications correctly applied cryptography in all elements of their applications.As humans adopt healthcare applications for managing their health routines,it is essential that they consider the privacy and security risks they are accepting when sharing their data.Furthermore,many open source applications and developers have certain environmental parameters which do not mandate adherence to regulations.In addition to creating new free tools for security risk identifications during software development such as standalone or compiler-embedded,the article suggests awareness and training modules for developers prior to marketplace software release.展开更多
Background:Pneumonia remains a critical global health challenge,manifesting as a severe respiratory infection caused by viruses,bacteria,and fungi.Early detection is paramount for effective treatment,potentially reduc...Background:Pneumonia remains a critical global health challenge,manifesting as a severe respiratory infection caused by viruses,bacteria,and fungi.Early detection is paramount for effective treatment,potentially reducing mortality rates and optimizing healthcare resource allocation.Despite the importance of chest X-ray diagnosis,image analysis presents significant challenges,particularly in regions with limited medical expertise.This study addresses these challenges by proposing a computer-aided diagnosis system leveraging targeted image preprocessing and optimized deep learning techniques.Methods:We systematically evaluated contrast limited adaptive histogram equalization with varying clip limits for preprocessing chest X-ray images,demonstrating its effectiveness in enhancing feature visibility for diagnostic accuracy.Employing a comprehensive dataset of 5,863 X-ray images(1,583 pneumonia-negative,4,280 pneumonia-positive)collected from multiple healthcare facilities,we conducted a comparative analysis of transfer learning with pre-trained models including ResNet50v2,VGG-19,and MobileNetV2.Statistical validation was performed through 5-fold cross-validation.Results:Our results show that the contrast limited adaptive histogram equalization-enhanced approach with ResNet50v2 achieves 93.40%accuracy,outperforming VGG-19(84.90%)and MobileNetV2(89.70%).Statistical validation confirms the significance of these improvements(P<0.01).The development and optimization resulted in a lightweight mobile application(74 KB)providing rapid diagnostic support(1-2 s response time).Conclusion:The proposed approach demonstrates practical applicability in resource-constrained settings,balancing diagnostic accuracy with deployment efficiency,and offers a viable solution for computer-aided pneumonia diagnosis in areas with limited medical expertise.展开更多
Objective:This study aims to evaluate the effects of a symptom management intervention(SMI)based on symptom management group sessions combined with a mobile health(mHealth)application(app)on the knowledge of symptom m...Objective:This study aims to evaluate the effects of a symptom management intervention(SMI)based on symptom management group sessions combined with a mobile health(mHealth)application(app)on the knowledge of symptom management,the certainty of symptom self-management,symptom severity,symptom distress,medication adherence,social support,and quality of life among persons living with HIV(PLWH)in China.Methods:A parallel randomized controlled trial with 61 PLWH was conducted in Shanghai,China.The participants in the control group(n¼30)downloaded the Symptom Management(SM)app according to their needs and preferences,and received routine follow-ups.The participants in the intervention group(n¼31)were guided to download and use the SM app,and received four tailored weekly group sessions at routine follow-ups.Each group session lasted for approximately 2 h and targeted one of the major modules of the SM app.All the outcomes were assessed at baseline and post-intervention.The study was registered with the Chinese Clinical Trial Registry(ChiCTR1900024821).Results:The symptom management knowledge and certainty of symptom self-management were significantly improved after the intervention(all P<0.01).Compared with the control group,the scores of symptoms reasons knowledge score improved 11.47 points(95%CI:3.41,19.53)and scores of symptoms self-management knowledge score improved 12.80 points(95%CI:4.55,21.05)in the intervention group after controlling for covariates.However,other outcomes did not show statistically significant differences between the intervention group and the control group(P>0.05).Conclusion:The SMI could improve PLWH’s symptom management knowledge and certainty of symptom self-management.Multi-center studies with larger sample sizes and longer follow-ups are needed to further understand the effects of SM app on ameliorating symptom severity and symptom distress.More innovative strategies are also needed to promote and maintain the sustainability of the SM app.展开更多
Purpose:This study aimed to explore whether the attitudes of nursing students toward the use of mobile learning are positive or negative and to identify the factors influencing their attitudes by reviewing the literat...Purpose:This study aimed to explore whether the attitudes of nursing students toward the use of mobile learning are positive or negative and to identify the factors influencing their attitudes by reviewing the literature.Methods:Electronic search of six databases,including PubMed,the Cumulative Index of Nursing and Allied Health Literature,ProQuest,Web of Science,EMBASE,and Cochrane Library,was conducted,and relevant references within articles were manually searched.Retrieval time was from inception to October 21,2020.The literature review was conducted in accordance with the PRISMA guidelines and the integrative review method.The Mixed Method Appraisal Tool(MMAT)was used for quality assessment.Results:A total of 316 articles were identified,and 18 English-language studies were finally included by reviewing titles,abstracts,and full text.Six quantitative,five qualitative,and seven mixed-method articles related to nursing students’attitudes toward the use of mobile learning were identified.The results showed that most nursing students had positive attitudes toward mobile learning.Although students expressed strong intentions for mobile learning,the actual usage rate in practical settings was low.Several advantageous factors included usefulness,convenience,and ease of use,whereas disadvantageous factors included hardware facility,updated content,and software stability.Conclusion:Most nursing students have positive attitudes and willingness to mobile learning,but the actual use rate remains low.Advantageous and disadvantageous factors coexist.Further studies are needed to assess how mobile learning improves nursing students’clinical knowledge and improves patient care.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
Objective:The purpose of this study was to determine the effectiveness of Mobile-Stroke Risk Scale and Life Style Guidance(M-SRSguide)in promoting a healthy lifestyle and reducing stroke risk factors in atrisk persons...Objective:The purpose of this study was to determine the effectiveness of Mobile-Stroke Risk Scale and Life Style Guidance(M-SRSguide)in promoting a healthy lifestyle and reducing stroke risk factors in atrisk persons.Methods:This research was an clinical trial with a pre-test and post-test control group design.The accessible population is persons at risk of stroke in the community(West and East Kalimantan Province,Indonesia).Thirty-two participants in the intervention group and 32 participants in the control group participated in this study.The sampling method was systematic random sampling.We allocate the sample into the intervention and control groups using a randomized block design.The intervention group used the M-SRSguide.The control group used manual book for a self-assessment of stroke risk.The measurement of a healthy lifestyle and the stroke risk factors was performed before and six months after the intervention.Results:There are no significant differences in healthy lifestyle and stroke risk factors between the two groups after the intervention(P>0.05).Analysis of healthy lifestyle behavior assessment items in the intervention group showed an increase in healthy diets,activity patterns,and stress control after the use of the M-SRSguide(P<0.01).Conclusion:The use of M-SRSguide is effective in promoting a healthy lifestyle.展开更多
基金funded by Vietnam National University Ho Chi Minh City(VNU-HCM)under grant number NCM2020-28-01.
文摘Objective:To evaluate mobile applications available for patients undergoing assisted reproduction and assess the extent of their clinical validation.Methods:A systematic search was conducted in the Apple App Store and Google Play between September 1,2023 and September 30,2023 to identify mobile applications related to assisted reproduction.Apps were evaluated using the mobile app rating scale(MARS).In parallel,a literature search of PubMed,Scopus,Embase,and Web of Science was performed to identify clinical studies related to mobile applications in assisted reproduction.Clinical validation status and MARS scores were recorded,and findings were synthesized to highlight the gap between commercially available apps and research-based evidence.Results:From 1143 apps screened,11 met the inclusion criteria.Mean MARS score across apps was 3.63,with Leeaf scoring the highest(4.60).However,only one application(Embie)was supported by published research.The literature research identified 13 relevant studies,mostly randomized controlled trials,cohort studies,or usability studies.While research-based apps demonstrated clinical utility(e.g.,MediEmo,PreLiFe,Patient Journey App),most were unavailable on app stores.This revealed a disconnect between research-backed applications and those accessible to patients.Conclusions:Although several mobile apps for assisted reproduction demonstrate high usability and quality,few are clinically validated.The lack of integration between research and practice highlights the need for stronger collaboration between researchers,developers,and policymakers to ensure that patients access safe and effective tools.
基金Acknowledgements This work was supported by the National Natural ScienceFoundation of China under Grants No. 60873191, No. 60903152, No. 60821001, and the Beijing Natural Science Foundation under Grant No. 4072020.
文摘To achieve privacy and authentication sinmltaneously in mobile applications, various Three-party Password-authenticated key exchange （3PAKE） protocols have been proposed. However, some of these protocols are vulnerable to conventional attacks or have low efficiency so that they cannot be applied to mobile applications. In this paper, we proposed a password-authenticated multiple key exchange protocol for mobile applications using elliptic curve cryptosystem. The proposed protocol can achieve efficiency, reliability, flexibility and scalability at the same time. Compared with related works, the proposed protocol is more suitable and practical for mobile applications.
基金supported by the Funds for Creative Research Groups of China under No.61921003 and Snyrey Bridge Company.
文摘Multi-agent mobile applications play an essential role in mobile applications and have attracted more and more researchers’attention.Previous work has always focused on multi-agent applications with perfect information.Researchers are usually based on human-designed rules to provide decision-making searching services.However,existing methods for solving perfect-information mobile applications cannot be directly applied to imperfect-information mobile applications.Here,we take the Contact Bridge,a multi-agent application with imperfect information,for the case study.We propose an enhanced searching strategy to deal with multi-agent applications with imperfect information.We design a self-training bidding system model and apply a Recurrent Neural Network(RNN)to model the bidding process.The bridge system model consists of two parts,a bidding prediction system based on imitation learning to get a contract quickly and a visualization system for hands understanding to realize regular communication between players.Then,to dynamically analyze the impact of other players’unknown hands on our final reward,we design a Monte Carlo sampling algorithm based on the bidding system model(BSM)to deal with imperfect information.At the same time,a double-dummy analysis model is designed to efficiently evaluate the results of sampling.Experimental results indicate that our searching strategy outperforms the top rule-based mobile applications.
文摘Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilization). However, in some mobile devices applications (e.g. image sequence panoramic stitching), the high resolution is necessary to obtain satisfactory quality of panoramic image. However, the computational cost will become too expensive to be suitable for the low power consumption requirement of mobile device. The full search algorithm can obtain the global minimum with extremely computational cost, while the typical fast algorithms may suffer from the local minimum problem. This paper proposed a fast algorithm to deal with 2560 × 1920 high-resolution (HR) image sequences. The proposed method estimates the motion vector by a two-level coarse-to-fine scheme which only exploits sparse reference blocks (25 blocks in this paper) in each level to determine the global motion vector, thus the computational costs are significantly decreased. In order to increase the effective search range and robustness, the predictive motion vector (PMV) technique is used in this work. By the comparisons of computational complexity, the proposed algorithm costs less addition operations than the typical Three-Step Search algorithm (TSS) for estimating the global motion of the HR images without the local minimum problem. The quantitative evaluations show that our method is comparable to the full search algorithm (FSA) which is considered to be the golden baseline.
文摘<div style="text-align:justify;"> <span style="font-family:Verdana;">Software reliability is an important quality attribute, and software reliability models are frequently used to measure and predict software maturity. The nature of mobile environments differs from that of PC and server environments due to many factors, such as the network, energy, battery, and compatibility. Evaluating and predicting mobile application reliability are real challenges because of the diversity of the mobile environments in which the applications are used, and the lack of publicly available defect data. In addition, bug reports are optionally submitted by end-users. In this paper, we propose assessing and predicting the reliability of a mobile application using known software reliability growth models (SRGMs). Four software reliability models are used to evaluate the reliability of an open-source mobile application through analyzing bug reports. Our experiment proves it is possible to use SRGMs with defect data acquired from bug reports to assess and predict the software reliability in mobile applications. The results of our work enable software developers and testers to assess and predict the reliability of mobile software applications.</span> </div>
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.
文摘Patients with cardiovascular disease rely on medication to achieve favorable longterm clinical results.Poor adherence has been linked to a relative increase in mortality of 50%-80%as well as higher health care costs.This scoping review thus aimed to explore the evidence of the effects of mobile health care apps on medication adherence in patients with cardiovascular diseases.A comprehensive data search and extraction was done in line with the updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews checklist.A total of 10 studies were included for the review.The mean pooled improvement in adherence was found to be 18%and the most effective tool was the digital therapeutics app discussed in Li et al’s study.Smartphones and apps enhance coronary artery disease management by promoting medication compliance.Challenges include data security and smartphone usage among the elderly.Tailored apps or voice assistants offer potential solutions.
文摘Mobile health apps (MHAs) and medical apps (MAs) are becoming increasinglypopular as digital interventions in a wide range of health-related applications inalmost all sectors of healthcare. The surge in demand for digital medical solutionshas been accelerated by the need for new diagnostic and therapeutic methods inthe current coronavirus disease 2019 pandemic. This also applies to clinicalpractice in gastroenterology, which has, in many respects, undergone a recentdigital transformation with numerous consequences that will impact patients andhealth care professionals in the near future. MHAs and MAs are considered tohave great potential, especially for chronic diseases, as they can support the selfmanagementof patients in many ways. Despite the great potential associated withthe application of MHAs and MAs in gastroenterology and health care in general,there are numerous challenges to be met in the future, including both the ethicaland legal aspects of applying this technology. The aim of this article is to providean overview of the current status of MHA and MA use in the field ofgastroenterology, describe the future perspectives in this field and point out someof the challenges that need to be addressed.
文摘Due to the rapid rise of mobile phones around the globe, many consumers, researchers, clinicians, and health services are starting to see their utility in health. As well as a health informatics role in improving the uptake and efficiency of current health services, mobile communication-assisted health care （m-health） also opens opportunities for services that are strikingly new and curative, in particular delivering personal health behaviour change programmes. Herein, we report the preliminary findings of a health-promotion survey titled ＂Mobile Apps User Trend Analysis of Turkish People＂. The survey examines the information needs and media preferences of women and men who research health information and use mobile apps for their healthcare in everyday life. Also this study tries to recover the behaviour of people and what applications they are downloading with respect to health, wellness, and medical mobile applicaitons. In looking the data, it appears that adoption of mHealth is growing at a furious pace. In this context, improvements to health communication have the potential to make a significant role to a promising new medium for health education and communication.
文摘Smart mobile applications are software applications that are designed to run on smart phones, tablets, and other mobile electronic devices. In this era of rapid technological advances, these applications have become one of the primary tools we use daily both in our personal and professional lives. The applications play key roles in facilitating many applications that are pivotal in our today＇s society including communication, education, business, entertainment, medical, finance, travel, utilities, social, and transportation. This paper reviewed the opportunities and challenges of the applications related to transportation. The opportunities revealed include route planning, ridesharing/carpooling, traffic safety, parking information, transportation data collection, fuel emissions and consumption, and travel information. The potential users of these applications in the field of transportation include （I） transportation agencies for travel data collection, travel information, ridesharing/carpooling, and traffic safety, （2） engineering students for field data collection such as travel speed, travel time, and vehicle count, and （3） general traveling public for route planning, ridesharing/carpooling, parking, traffic safety, and travel information. Significant usage of smart mobile applications can be potentially very beneficial, particularly in automobile travel mode to reduce travel time, cost, and vehicle emissions. In the end this would make travel safer and living environments greener and healthier. However, road users＇ interactions with these applications could manually, visually, and cognitively divert their attention from the primary task of driving or walking. Distracted road users expose themselves and others to unsafe behavior than undistracted. Road safety education and awareness programs are vital to discourage the use of applications that stimulate unsafe driving/walking behaviors. Educating the traveling public about the dangers of unsafe driving/walking behavior could have significant safety benefits to all road users. Future research needs to compare accuracies of the applications and provide guidelines for selecting them for certain transportation related applications.
基金This study was supported by the Natural Science Foundation of China(71874032)the Natural Science Foundation of China(72074054).
文摘Objectives:In recent years,the use of mobile health applications(mHealth apps)to deliver care for patients with breast cancer has increased exponentially.This study aimed to summarize the available evidence on developing mHealth apps to care for patients with breast cancer and identify the need for systematic efforts.Methods:A scoping review was performed according to Arksey and O’Malley’s framework,aiming to identify eligible research studies in PubMed,CINAHL,and Web of Science between January 2010 and December 2020.All identified studies were screened,extracted,and analyzed independently by two reviewers.Results:A total of 676 studies were retrieved,and eight eligible studies were finally included.Four themes emerged:the involvement of patients and health professionals in the phases of design and development,patients’preferences,the characteristics of patients,and the motivators to use mHealth apps.The results indicated promising prospects for using mHealth apps to care for patients with breast cancer and identified the need for systematic efforts to develop and validate relevant apps.Conclusions:The attributes of patient characteristics,needs,and patient-reported outcomes data are vital components for developing mHealth apps for patients with breast cancer.Additionally,collaborative efforts,including patients,nurses,and other significant health professionals,should develop mHealth apps for breast cancer care.Additional research focusing on the design and development of mHealth apps for patients with breast cancer is warranted.
基金The authors acknowledge the support of Security Testing-Innovative Secured Systems Lab(ISSL)established at University of Engineering&Technology,Peshawar,Pakistan under the Higher Education Commission initiative of National Center for Cyber Security(Grant No.2(1078)/HEC/M&E/2018/707).
文摘Software reverse engineering is the process of analyzing a software system to extract the design and implementation details.Reverse engineering provides the source code of an application,the insight view of the architecture and the third-party dependencies.From a security perspective,it is mostly used for finding vulnerabilities and attacking or cracking an application.The process is carried out either by obtaining the code in plaintext or reading it through the binaries or mnemonics.Nowadays,reverse engineering is widely used for mobile applications and is considered a security risk.The Open Web Application Security Project(OWASP),a leading security research forum,has included reverse engineering in its top 10 list of mobile application vulnerabilities.Mobile applications are used in many sectors,e.g.,banking,education,health.In particular,the banking applications are critical in terms of security as they are used for financial transactions.A security breach of such applications can result in huge financial losses for the customers as well as the banks.There exist various tools for reverse engineering of mobile applications,however,they have deficiencies,e.g.,complex configurations,lack of detailed analysis reports.In this research work,we perform an analysis of the available tools for reverse engineering of mobile applications.Our dataset consists of the mobile banking applications of the banks providing services in Pakistan.Our results indicate that none of the existing tools can carry out the complete reverse engineering process as a standalone tool.In addition,we observe significant differences in terms of the execution time and the number of files generated by each tool for the same file.
文摘In 2010, cloud computing gained momentum. Cloud computing is a model for real-time, on-demand, pay-for-use network access to a shared pool of configurable computing and storage resources. It has matured from a promising business concept to a working reality in both the private and public IT sectors. The U.S. government, for example, has requested all its agencies to evaluate cloud computing alternatives as part of their budget submissions for new IT investment.
文摘Mobile devices are being deployed rapidly for both private and professional reasons.One area of that has been growing is in releasing healthcare applications into the mobile marketplaces for health management.These applications help individuals track their own biorhythms and contain sensitive information.This case study examines the source code of mobile applications released to GitHub for the Risk of Insufficient Cryptography in the Top Ten Mobile Open Web Application Security Project risks.We first develop and justify a mobile OWASP Cryptographic knowledge-graph for detecting security weaknesses specific to mobile applications which can be extended to other domains involving cryptography.We then analyze the source code of 203 open source healthcare mobile applications and report on their usage of cryptography in the applications.Our findings show that none of the open source healthcare applications correctly applied cryptography in all elements of their applications.As humans adopt healthcare applications for managing their health routines,it is essential that they consider the privacy and security risks they are accepting when sharing their data.Furthermore,many open source applications and developers have certain environmental parameters which do not mandate adherence to regulations.In addition to creating new free tools for security risk identifications during software development such as standalone or compiler-embedded,the article suggests awareness and training modules for developers prior to marketplace software release.
文摘Background:Pneumonia remains a critical global health challenge,manifesting as a severe respiratory infection caused by viruses,bacteria,and fungi.Early detection is paramount for effective treatment,potentially reducing mortality rates and optimizing healthcare resource allocation.Despite the importance of chest X-ray diagnosis,image analysis presents significant challenges,particularly in regions with limited medical expertise.This study addresses these challenges by proposing a computer-aided diagnosis system leveraging targeted image preprocessing and optimized deep learning techniques.Methods:We systematically evaluated contrast limited adaptive histogram equalization with varying clip limits for preprocessing chest X-ray images,demonstrating its effectiveness in enhancing feature visibility for diagnostic accuracy.Employing a comprehensive dataset of 5,863 X-ray images(1,583 pneumonia-negative,4,280 pneumonia-positive)collected from multiple healthcare facilities,we conducted a comparative analysis of transfer learning with pre-trained models including ResNet50v2,VGG-19,and MobileNetV2.Statistical validation was performed through 5-fold cross-validation.Results:Our results show that the contrast limited adaptive histogram equalization-enhanced approach with ResNet50v2 achieves 93.40%accuracy,outperforming VGG-19(84.90%)and MobileNetV2(89.70%).Statistical validation confirms the significance of these improvements(P<0.01).The development and optimization resulted in a lightweight mobile application(74 KB)providing rapid diagnostic support(1-2 s response time).Conclusion:The proposed approach demonstrates practical applicability in resource-constrained settings,balancing diagnostic accuracy with deployment efficiency,and offers a viable solution for computer-aided pneumonia diagnosis in areas with limited medical expertise.
基金part of a project funded by the National Natural Science Foundation of China(Grant Number 71673057)the China Scholarship Council(No.201906100135).
文摘Objective:This study aims to evaluate the effects of a symptom management intervention(SMI)based on symptom management group sessions combined with a mobile health(mHealth)application(app)on the knowledge of symptom management,the certainty of symptom self-management,symptom severity,symptom distress,medication adherence,social support,and quality of life among persons living with HIV(PLWH)in China.Methods:A parallel randomized controlled trial with 61 PLWH was conducted in Shanghai,China.The participants in the control group(n¼30)downloaded the Symptom Management(SM)app according to their needs and preferences,and received routine follow-ups.The participants in the intervention group(n¼31)were guided to download and use the SM app,and received four tailored weekly group sessions at routine follow-ups.Each group session lasted for approximately 2 h and targeted one of the major modules of the SM app.All the outcomes were assessed at baseline and post-intervention.The study was registered with the Chinese Clinical Trial Registry(ChiCTR1900024821).Results:The symptom management knowledge and certainty of symptom self-management were significantly improved after the intervention(all P<0.01).Compared with the control group,the scores of symptoms reasons knowledge score improved 11.47 points(95%CI:3.41,19.53)and scores of symptoms self-management knowledge score improved 12.80 points(95%CI:4.55,21.05)in the intervention group after controlling for covariates.However,other outcomes did not show statistically significant differences between the intervention group and the control group(P>0.05).Conclusion:The SMI could improve PLWH’s symptom management knowledge and certainty of symptom self-management.Multi-center studies with larger sample sizes and longer follow-ups are needed to further understand the effects of SM app on ameliorating symptom severity and symptom distress.More innovative strategies are also needed to promote and maintain the sustainability of the SM app.
文摘Purpose:This study aimed to explore whether the attitudes of nursing students toward the use of mobile learning are positive or negative and to identify the factors influencing their attitudes by reviewing the literature.Methods:Electronic search of six databases,including PubMed,the Cumulative Index of Nursing and Allied Health Literature,ProQuest,Web of Science,EMBASE,and Cochrane Library,was conducted,and relevant references within articles were manually searched.Retrieval time was from inception to October 21,2020.The literature review was conducted in accordance with the PRISMA guidelines and the integrative review method.The Mixed Method Appraisal Tool(MMAT)was used for quality assessment.Results:A total of 316 articles were identified,and 18 English-language studies were finally included by reviewing titles,abstracts,and full text.Six quantitative,five qualitative,and seven mixed-method articles related to nursing students’attitudes toward the use of mobile learning were identified.The results showed that most nursing students had positive attitudes toward mobile learning.Although students expressed strong intentions for mobile learning,the actual usage rate in practical settings was low.Several advantageous factors included usefulness,convenience,and ease of use,whereas disadvantageous factors included hardware facility,updated content,and software stability.Conclusion:Most nursing students have positive attitudes and willingness to mobile learning,but the actual use rate remains low.Advantageous and disadvantageous factors coexist.Further studies are needed to assess how mobile learning improves nursing students’clinical knowledge and improves patient care.
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We thank the Politeknik Kesehatan Kementerian Kesehatan Indonesia,LB.01.01/I.1/2657/2019 for funding this study,the respondents for participating in this study,and Marshall Godwin for granting permission to use the Simple Lifestyle Indicator Questionnaire(SLIQ).
文摘Objective:The purpose of this study was to determine the effectiveness of Mobile-Stroke Risk Scale and Life Style Guidance(M-SRSguide)in promoting a healthy lifestyle and reducing stroke risk factors in atrisk persons.Methods:This research was an clinical trial with a pre-test and post-test control group design.The accessible population is persons at risk of stroke in the community(West and East Kalimantan Province,Indonesia).Thirty-two participants in the intervention group and 32 participants in the control group participated in this study.The sampling method was systematic random sampling.We allocate the sample into the intervention and control groups using a randomized block design.The intervention group used the M-SRSguide.The control group used manual book for a self-assessment of stroke risk.The measurement of a healthy lifestyle and the stroke risk factors was performed before and six months after the intervention.Results:There are no significant differences in healthy lifestyle and stroke risk factors between the two groups after the intervention(P>0.05).Analysis of healthy lifestyle behavior assessment items in the intervention group showed an increase in healthy diets,activity patterns,and stress control after the use of the M-SRSguide(P<0.01).Conclusion:The use of M-SRSguide is effective in promoting a healthy lifestyle.
