An Enhanced Searching Strategy for Multi-Agent Mobile Applications

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.

A Two-Stage Algorithm of High Resolution Image Alignment for Mobile Applications

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.

Assessment and Prediction of Software Reliability in Mobile Applications

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.

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.

Impact of mobile health and medical applications on clinical practice in gastroenterology

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.

Opportunities and challenges of smart mobile applications in transportation

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.

Reverse Engineering of Mobile Banking Applications

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.

Mobile Cloud Computing and Applications

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.

A Case Study of Mobile Health Applications:The OWASP Risk of Insufficient Cryptography

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.

Usability-Driven Mobile Application Development

Recently,a specific interest is being taken in the development of mobile application(app)via Model-Based User Interface Development(MBUID)approach.MBUID allows the generation of mobile apps in the target platform(s)from conceptual models.As such it simplified the development process of mobile app.However,the interest is only focused on the functional aspects of the mobile app while neglecting the non-functional aspects,such as usability.The latter is largely considered as the main factor leading to the success or failure of any software system.This paper aims at addressing non-functional aspects of mobile apps generated using MBUID approach.As such,we propose a usability-driven approach for the development of mobile apps.The main stages of the proposed approach are defined in a generic way so that they can be integrated with any MBUID method.A case study is presented,in the paper,with the aim of illustrating the feasibility of this approach.

Effectiveness of Mobile-Assisted Language Learning in Enhancing the English Proficiency

In response to the significant impact of the widespread use of digital devices and mobile technologies on language teaching and learning in this time of Internet information technology,this study aims to investigate the effectiveness of Mobile-Assisted Language Learning(MALL)in enhancing the English proficiency of students,while exploring the potential advantages of mobile devices for assisted learning in the English learning environment in China and the potential for mobile applications to assist English learning to foster learner autonomy.Anchored with the design thinking approach,the researchers used the empirical analysis methodology in developing an efficient mobile-assisted language learning model.Usability testing was conducted using a case study of two mobile applications,WeLearn and Flipped English,in Heilongjiang University of Finance and Economics to measure the extent of usability and acceptability of MALL on English language acquisition among college students identified through surveys,interviews,and quantitative assessments.Mobile technology is a perfect tool for every student that enhances their experience and increases their joy while improving their English language skills.It adds new value and brings new opportunities for both English learners and the language education industry.Indeed,MALL is English learners’new ally.

Construction of apricot variety search engine based on deep learning

Apricot has a long history of cultivation and has many varieties and types. The traditional variety identification methods are timeconsuming and labor-consuming, posing grand challenges to apricot resource management. Tool development in this regard will help researchers quickly identify variety information. This study photographed apricot fruits outdoors and indoors and constructed a dataset that can precisely classify the fruits using a U-net model (F-score:99%), which helps to obtain the fruit's size, shape, and color features. Meanwhile, a variety search engine was constructed, which can search and identify variety from the database according to the above features. Besides, a mobile and web application (ApricotView) was developed, and the construction mode can be also applied to other varieties of fruit trees.Additionally, we have collected four difficult-to-identify seed datasets and used the VGG16 model for training, with an accuracy of 97%, which provided an important basis for ApricotView. To address the difficulties in data collection bottlenecking apricot phenomics research, we developed the first apricot database platform of its kind (ApricotDIAP, http://apricotdiap.com/) to accumulate, manage, and publicize scientific data of apricot.

Analysis of Key Attributes Influencing the User Satisfaction towards Applications

This research aims to find out the key attributes influencing the user trust towards applications on the mobile application store. In this research, both the experimental data set and the evaluation results of analysis are described. The analysis results include the test results of analysis of variance （ANOVA） and correlation analysis. In ANOVA, the attributes affecting user rating are derived and applied to the correlation analysis to evaluate the degree of correlation towards user rating, and in the last stage the positive or negative relationship with user satisfaction is figured out.

Development of Comment Correlation Matrix for Mobile Application Recommendation

As the evolution of mobile technology, mobile devices have become an essential tool in people＇s daily life. Moreover, with the rapid growth of Internet and mobile networks, people can easily access various services provided by mobile platforms. Many services can be executed on the mobile devices with various mobile applications launched to mobile platforms. People can choose what they like to install in their mobile devices and hence make their life more convenient, entertaining, and productive. However, there are too many mobile applications for users to choose. The goal of this research is to propose a methodology which can recommend top-N lists for mobile applications. A comment correlation matrix is proposed. Furthermore, a recommendation algorithm for mobile applications based on user comments and key attributes is built. With the proposed method, it outperforms Google play and is closer to user real feelings.

A systematic review of the effect of mobile health on cardiac rehabilitation among coronary heart disease patients

Objective： Mobile health （mHealth） provides an innovative and effective approach to promote prevention and management of coronary heart disease. However, the magnitude of its effects is unclear. The aim of this systematic review was to examine the impact of mHealth-based cardiac rehabilitation outcomes among coronary heart disease patients. Methods： Medline, CINAHL, Embase, PubMed, Google Scholar, NICE, and Cochrane library were searched for randomized controlled trials published between January 2002 and March 2017 which compared mHealth with conventional cardiac rehabilitation programs among coronary heart disease patients. Results： Eight articles were included in this review. The impact of mHealth interventions on physical activity, medicine adherence, smoking cessation, level of anxiety, and quality of life was inconsistent among the articles. Conclusions： Further research is needed to conclusively determine the impact of mHealth interventions on cardiac rehabilitation outcomes. The limitations of the included studies （e.g., inadequate sample size, failure to address the core components of cardiac rehabilitation programs, and lack of theory-based design） should be taken into account when designing future studies.

Design of Intelligent Window Automatic Monitoring System Based on Microcontroller Control

To ensure the safety of residents’lives and property by using automatic opening and closing of ordinary windows,this article designs an intelligent window automatic monitoring system.The article proposes a software and hardware design scheme for the system,which comprises a microcontroller control module,temperature and humidity detection module,harmful gas detection module,rainfall detection module,human thermal radiation induction module,Organic Light-Emitting Diode(OLED)display module,stepper motor drive module,Wi-Fi communication module,etc.Users use this system to monitor environmental data such as temperature,humidity,rainfall,harmful gas concentrations,and human health.Users can control the opening and closing of windows through manual,microcontroller,and mobile application(app)remote methods,providing users with a more convenient,comfortable,and safe living environment.

Managing Traumatic Stress Using a Mental Health Care Mobile App: A Pilot Study

This study aims to contribute to improving mental health services and establishing a direction for disaster survivors by verifying the effectiveness of the TLS(Training for Life Skills)app,a mental health management mobile application.Altogether,22 disaster survivors received access to the app(with guidance)for eight weeks;we analyzed its effectiveness by examining each participant’s electroencephalography data,which were collected while they were utilizing the app.The results of this study show that the use of the TLS app had a significant positive effect on emotional quotient,basic rhythm quotient(left brain,right brain),alpha blocking rate(left brain,right brain),and brain quotient of disaster survivors.The TLS mobile app is expected to not only provide psychological first aid to disaster survivors but also to improve their life skills,which may allow them to gain information about their emotions;hence,it may provide the appropriate conditions needed to enable effective self-control and health management for disaster survivors.

An Expert System Oriented towards the Detection of Influenza and Dengue Developed on Mobile Platforms

Nowadays, mobile technology makes it possible for us to realize processes in a relatively short amount of time, showing the user friendly and efficient interfaces that any person is capable of adapting to. Continuing this trend, we develop a mobile application that aids in giving an early diagnosis of Influenza and Dengue, two diseases that affect approximately 5% of the world population (in the case of Dengue) and 5% - 15% of the northern hemisphere (in the case of influenza). Our application consists of an expert system based on fuzzy logic that analyzes symptoms introduced by the user and formulates a diagnosis in approximately 2 - 4 minutes. This system considerably reduced the diagnostic time, improving the recuperation process from these diseases due to their early detection.