Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

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.

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

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.

Software and Mobile Apps as a Strategy for Productivity Improvement in the Construction Industry

The construction industry, known for its low productivity, is increasingly utilising software and mobile apps to enhance efficiency. However, more comprehensive research is needed to understand the effectiveness of these technology applications. The PRISMA principles utilised a scoping review methodology to ascertain pertinent studies and extract significant findings. From 2013 onwards, articles containing data on mobile applications or software designed to enhance productivity in the construction sector were obtained from multiple databases, including Emerald Insight, Science Direct, IEEE Xplore, and Google Scholar. After evaluating 2604 articles, 30 were determined to be pertinent to the study and were subsequently analysed for the review. The review identified five key themes: effectiveness, benefits, successful implementation examples, obstacles and limitations, and a comprehensive list of software and mobile apps. In addition, 71 software and mobile apps have shown potentially how these technologies can improve communication, collaboration, project management, real-time collaboration, document management, and on-the-go project information and estimating processes in the construction industry, increasing efficiency and productivity. The findings highlight the potential of these technologies such as Automation, Radio-Frequency Identification (RFID), Building Information Modeling (BIM), Augmented Reality (AR), Virtual Reality (VR), and Internet of Things (IoT) to improve efficiency and communication in the construction industry. Despite challenges such as cost, lack of awareness, resistance to change, compatibility concerns, human resources, technological and security concerns and licensing issues, the study identifies specific mobile applications and software with the potential to enhance efficiency significantly, improve productivity and streamline workflows. The broader societal impacts of construction software and mobile app development include increased efficiency, job creation, and sustainability.

Time Parameter Based Low-Energy Data Encryption Method for Mobile Applications

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.

The Contribution of AI-Powered Mobile Apps to Smart City Ecosystems

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.

Health Behaviors and Outcomes of Mobile Health Apps and Patient Engagement in the USA

Mobile health applications, or mHealth apps, have gained popularity due to their practical functions and strengthening the connection between patients and healthcare professionals. These apps are designed for managing health and well-being on portable devices, allowing individuals to self-manage their health or healthcare practitioners to enhance patient care. Key features include personalized recommendations, data synchronization with other health devices, and connectivity with healthcare professionals. The research describes how mobile health applications support healthy behaviors, facilitate communication between patients and physicians, and empower individuals in the United States to take charge of their health. This study also examines how adults in the US use mobile health applications, or mHealth apps, on their tablets or smartphones for health-seeking purposes. The information was taken from Cycle 4 of the Health Information National Trends Survey (HINTS 4). The challenges regarding these mobile health apps have also been evaluated with possible remedies. Around 100 university students participated in a cross-sectional study by answering questions on their eating habits, physical activity, lifestyle choices related to health, and use of mobile health apps. The data was then analyzed and concluded as a result. Mobile health applications have brought about a significant shift in the way patients connect with their healthcare providers by providing them with convenient access to health services and information. By keeping track of health markers like diet, exercise, and medication compliance, patients may use these tools to help better manage their chronic conditions. Mobile health applications can improve patient outcomes and save healthcare costs by empowering patients to take charge of their health. Through the facilitation of communication between patients and healthcare professionals, mobile health apps also offer virtual consultations and remote monitoring.

A Literature Review: Potential Effects That Health Apps on Mobile Devices May Have on Patient Privacy and Confidentiality

Purpose: This research aims to evaluate the potential threats to patient privacy and confidentiality posed by mHealth applications on mobile devices. Methodology: A comprehensive literature review was conducted, selecting eighty-eight articles published over the past fifteen years. The study assessed data gathering and storage practices, regulatory adherence, legal structures, consent procedures, user education, and strategies to mitigate risks. Results: The findings reveal significant advancements in technologies designed to safeguard privacy and facilitate the widespread use of mHealth apps. However, persistent ethical issues related to privacy remain largely unchanged despite these technological strides.

Association between glucose levels of children with type 1 diabetes and parental economic status in mobile health application

BACKGROUND The glycemic control of children with type 1 diabetes(T1D)may be influenced by the economic status of their parents.AIM To investigate the association between parental economic status and blood glucose levels of children with T1D using a mobile health application.METHODS Data from children with T1D in China's largest T1D online community,Tang-TangQuan■.Blood glucose levels were uploaded every three months and parental economic status was evaluated based on annual household income.Children were divided into three groups:Low-income(<30000 Yuan),middle-income(30000-100000 Yuan),and high-income(>100000 yuan)(1 Yuan=0.145 United States Dollar approximately).Blood glucose levels were compared among the groups and associations were explored using Spearman’s correlation analysis and multivariable logistic regression.RESULTS From September 2015 to August 2022,1406 eligible children with T1D were included(779 female,55.4%).Median age was 8.1 years(Q1-Q3:4.6-11.6)and duration of T1D was 0.06 years(0.02-0.44).Participants were divided into three groups:Low-income(n=320),middle-income(n=724),and high-income(n=362).Baseline hemoglobin A1c(HbA1c)levels were comparable among the three groups(P=0.072).However,at month 36,the low-income group had the highest HbA1c levels(P=0.036).Within three years after registration,glucose levels increased significantly in the low-income group but not in the middle-income and high-income groups.Parental economic status was negatively correlated with pre-dinner glucose(r=-0.272,P=0.012).After adjustment for confounders,parental economic status remained a significant factor related to pre-dinner glucose levels(odds ratio=13.02,95%CI:1.99 to 126.05,P=0.002).CONCLUSION The blood glucose levels of children with T1D were negatively associated with parental economic status.It is suggested that parental economic status should be taken into consideration in the management of T1D for children.

Multilayer Satellite Network Collaborative Mobile Edge Caching:A GCN-Based Multi-Agent Approach

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.

Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

Quality of Service and Security on Cisco Network Devices, Coupled with the Development of a Mobile Application Prototype Software for Server Room Temperature Monitoring

In an era where digital technology is paramount, higher education institutions like the University of Zambia (UNZA) are employing advanced computer networks to enhance their operational capacity and offer cutting-edge services to their academic fraternity. Spanning across the Great East Road campus, UNZA has established one of the most extensive computer networks in Zambia, serving a burgeoning community of over 20,000 active users through a Metropolitan Area Network (MAN). However, as the digital landscape continues to evolve, it is besieged with burgeoning challenges that threaten the very fabric of network integrity—cyber security threats and the imperatives of maintaining high Quality of Service (QoS). In an effort to mitigate these threats and ensure network efficiency, the development of a mobile application to monitor temperatures in the server room was imperative. According to L. Wei, X. Zeng, and T. Shen, the use of wireless sensory networks to monitor the temperature of train switchgear contact points represents a cost-effective solution. The system is based on wireless communication technology and is detailed in their paper, “A wireless solution for train switchgear contact temperature monitoring and alarming system based on wireless communication technology”, published in the International Journal of Communications, Network and System Sciences, vol. 8, no. 4, pp. 79-87, 2015 [1]. Therefore, in this study, a mobile application technology was explored for monitoring of temperatures in the server room in order to aid Cisco device performance. Additionally, this paper also explores the hardening of Cisco device security and QoS which are the cornerstones of this study.

Application of Mobile Technology and Information Management in Emergency Pre- Examination and Triage

The primary objective of emergency pre-examination and triage is to provide the most appropriate clinical service to patients with acute and critical illnesses while ensuring the optimal utilization of limited medical resources.With the advancement of medical information technology,mobile technology,and information management,these features have been gradually incorporated into emergency pre-examination and triage and have shown promising outcomes.In this article,the benefits of implementing mobile technology and the current status of integrated information management to provide a reference for the future development and enhancement of emergency pre-examination and triage are reviewed.

Optimizing Spatial Crowdsourcing:A Quality-Aware Task Assignment Approach for Mobile Communication

The widespread use of advanced electronic devices has led to the emergence of spatial crowdsourcing,a method that taps into collective efforts to perform real-world tasks like environmental monitoring and traffic surveillance.Our research focuses on a specific type of spatial crowdsourcing that involves ongoing,collaborative efforts for continuous spatial data acquisition.However,due to limited budgets and workforce availability,the collected data often lacks completeness,posing a data deficiency problem.To address this,we propose a reciprocal framework to optimize task assignments by leveraging the mutual benefits of spatiotemporal subtask execution.We introduce an entropy-based quality metric to capture the combined effects of incomplete data acquisition and interpolation imprecision.Building on this,we explore a quality-aware task assignment method,corresponding to spatiotemporal assignment strategies.Since the assignment problem is NP-hard,we develop a polynomial-time algorithm with the guaranteed approximation ratio.Novel indexing and pruning techniques are proposed to further enhance performance.Extensive experiments conducted on datasets validate the effectiveness of our methods.

用户需求视角下医疗健康类APP适老化改造内容优先序研究

[目的/意义]了解用户对医疗健康类APP适老化改造的需求,探析改造内容的优先序,从用户需求视角优化功能设计,为医疗健康类APP适老化的改造提供参考。[方法/过程]在系统梳理相关文献的基础上,运用专家调研法、访谈法等方式提炼26项需求属性,并综合运用Kano模型、混合类分析以及Better-Worse系数分析对归纳的26项需求进行分类,识别各项需求属性的所属类型。[结果/结论]医疗健康类APP适老化改造的用户需求层次分明,分为8项必备型、7项期望型、4项魅力型和7项无差异型,并对此从保障必备型供给、提升期望型质量、扩大魅力型供给和调整无差异型内容4个方面有针对性地提出了对策建议,有效对接用户需求,分层次、有重点地进行医疗健康类APP适老化改造,帮助老年群体更好地融入现代社会。

基于用户体验的APP界面设计研究

目的 探讨符合用户体验的APP界面设计策略,为今后APP界面设计提供参考,更好地满足用户的需求。方法 对用户体验进行简要分析、了解之后,结合案例,并基于用户需求、用户情感体验、用户心理状态、用户使用习惯等对APP界面设计展开探究。结论 要使APP受到用户的青睐,必须要了解用户需求,把握用户心理,根据用户习惯来设计。

基于Gross理论的农村青年群体心理类APP交互设计研究

目的基于Gross理论解决农村青年大学生心理问题,以APP为载体与用户进行互动从而调节用户情绪。方法通过文献研究、问卷调查和用户访谈,对当代农村青年大学生心理问题进行深入分析和研究,进而从Gross情绪调节理论的角度,对农村青年大学生在不同情境下的情绪状态进行深入挖掘,从而进行需求分析,逐步转化为对应的功能点,并基于Gross理论和APP交互设计构建模型来输出设计方案。最后,运用李克特五分量表进行方案的可用性评估,并采用积极情绪与消极情绪量表(PANAS)进行用户积极情绪变化的验证。结论将Gross情绪调节理论引入心理类APP的交互设计中,创造出一款情绪调节的APP。经过用户测试,能够有效改善用户的情绪问题,帮助他们更好地管理情绪,同时也为其他同类APP的设计提供了参考和借鉴。另外,在研究过程中,验证了Gross理论的有效性和设计策略的合理性,为今后的进一步推广和理论应用提供了借鉴。

大数据赋能下移动App个性化用户报告技术特征的维度探索与量表开发

基于需求-示能性-特征理论,厘清移动App个性化用户报告情境下用户与品牌间产生情感联结的心理机制。采用定性与定量相结合的研究范式,通过扎根理论对技术特征的结构维度展开探索性研究,在此基础上开发并检验了测量量表,还实证检验了技术特征对用户心理的预测效用。研究表明:该情境的技术特征包括镜像性、客观性、社会性、趣味性、安全性5个维度;技术特征的测量量表由5个因子、21个题项构成,且信度和效度均达到理想水平;技术特征能够通过自我展示示能性对心理所有权进行正向预测,满足用户心理需求并促进用户与品牌的关系。

植物病害智能识别APP开发及实践教学应用

该文分析了传统植物病理实践教学存在的一些问题和弊端,利用卷积神经网络技术开发了植物病害症状和病原菌智能识别APP,并将之应用于实践教学,促进了学科交叉融合,丰富了教学内容,完善了实践教学评价体系。实践表明,植物病害智能识别APP在实践教学中效果显著,提高了学生的学习兴趣,便于学生个性化、精准化、自由化学习,有利于培养学生跨学科的创新思维和应用能力,为新农科复合型人才的培养提供了一种便利工具。

5G时代教育APP的发展机遇和实践路径

我国教育APP相关研究成果以及5G+智慧技术在教育APP中的应用前景:5G+云计算促进教学资源共享化;5G+大数据促进教学服务精准化;5G+AR/VR促进教学场景多元化;5G+AI促进教学交互智慧化。教育APP当前存在的问题:技术滞后,交互性不强,用户体验不佳,数据隐私泄露等。5G时代,教育APP的实践路径在于跨界合作,教育机构与互联网公司合作研发APP;内容为王,融合智慧技术,改善用户体验;技术向善,遵循数据伦理,保护数据安全。

心血管疾病患者心血管运动管理App的使用意愿及应用

目的 调查心血管疾病患者对心血管运动管理App的使用意愿,观察使用App对心血管不良事件的影响。方法 选取202例心血管疾病患者为研究对象,采用自行设计的调查问卷对患者运动需求、健康管理现状及影响患者选择心血管运动管理App的因素进行调查,根据调查结果将140例坚持使用心血管运动管理App的患者设为运动组,62例不使用心血管运动管理App的患者设为对照组,比较两组1年内的心血管不良事件发生率。结果 74.26%的调查对象认为需要合理运动,89.11%认为需要记录运动情况,84.16%日常生活中使用智能手机,81.68%认为使用心血管运动管理App方便,74.26%的患者关注自身健康、53.96%的患者认为健康可以被管理,74.75%的患者对体检报告关注并处理,当前有62.87%的患者在使用网上医疗App。影响心血管疾病患者使用心血管运动管理App的因素前三位分别为担心使用过程中收费(79.21%)、担心泄露个人信息(76.24%)、相似App太多选择困难(59.41%)。跟踪随访1年间,运动组的心血管不良事件发生率(4.28%)低于对照组(14.52%),差异有统计学意义(χ^(2)=6.542,P=0.011)。结论 心血管运动管理App的使用有助于降低心血管不良事件的发生,但担心使用过程中收费和泄露个人信息,限制了心血管疾病患者对App的使用意愿。