Dynamic Performance of Fuel Cell Power Module for Mobility Applications

Fuel cell powered vehicles have been developed as another alternative to internal combustion engine powered vehicles for some applications including passenger cars, buses, trains, motorcycles, forklifts, electric wheelchairs, electric trolleybuses, medical carts, military engines, personal sports craft, mobility devices and other self propelled equipment. Up to now, many researches have focused on the development of the power module in the Fuel cell vehicles (FCVs) and the components of these systems such as membranes, bipolar plates, and electrodes. However, our work in this study focuses on operating the integrated fuel cell power module system efficiently for various operating conditions such as pressure, relative humidity and operating modes. In our validation we have utilized PEMFC single cell, with active area geometry 16 cm2 and of 120 cm2. Some results obtained in our study shown significant performance indicators for PEMFC stack (composed of 2 cells and 4 cells in a series) at different humidification levels.

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.

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.

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.

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.

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.

Validation of Peek Acuity application in pediatric screening programs in Paraguay

AIM： To validate the Peek Acuity mobile phone application in pediatric populations and compare its utility, both economic and diagnostic, against conventional screening methods using a pediatric ophthalmologist examination as the gold standard.METHODS： A cohort of 393 subjects from Fernando de la Mora, Paraguay（ages 6-16 y） were enrolled in the study. Subjects were randomly assigned a starting screening modality among： Peek Acuity, a single line of tumbling E optotypes set at 20/40, and Spot Vision Screener. Once completing the first screening modality, the subjects completed the two remaining techniques. Referral criteria were established based on the most current American Association of Pediatric Ophthalmology and Strabismus（AAPOS） recommendations： 20/40 for Peek Acuity and the tumbling E, and refractive error detection for the Spot Vision Screener. Subjects that failed to achieve the cutoff for any of the three screening techniques or subjects that passed the screening but were randomly selected to perform a comprehensive eye exam to determine the false negative rate, were evaluated by a pediatric ophthalmologist. This evaluation was considered the gold standard, and included vision assessment by a Snellen chart, strabismus evaluation, and cycloplegic refraction with dilated fundoscopy.RESULTS： We obtained 48% sensitivity, 83% specificity, 43% positive predictive value, and 86% negative predictive value for Peek Acuity＇s ability to refer compared to evaluation by a pediatric ophthalmologist, failing to achieve a desired sensitivity for implementation. Peek Acuity trended to overestimate the subject＇s visual acuity, providing a higher visual acuity that would not indicate referral for a comprehensive eye examination. However, its high specificity accurately predicted a significant number of children who did not need further evaluation. When comparing the three screening methods, no single screening modality outperformed the others. Peek Acuity represented a technology that was economically feasible compared to other screening modalities in low income settings, due to the prevalence of cell phone use.CONCLUSION： Peek Acuity represents an efficient tool that has potential for implementation in school screenings with different strategies aimed at pediatric populations due to its low cost and high specificity. An increase in sensitivity would improve detection of children with refractive errors.

Teaching Reform for HarmonyOS Mobile Application Development

In recent years,the IT industry in China has developed rapidly and made remarkable achievements.However,there is still a big gap between China and foreign countries in the core fields of information technology,such as system hardware and software platform.Currently,foreign countries have gradually raised the restrictions of information technology in China,and even added many domestic enterprises to the restricted list,which has rung the alarm to the information security of the country.Therefore,in order to break through the foreign technology blockade and find a unique way in independent software and hardware platform,it is urgent to carry out the curriculum construction and talent training mechanism on core software and hardware platform.HarmonyOS is a“future-oriented”distributed operating system developed by Huawei.It proposes a distributed concept based on the same system capability and adapts to a variety of terminal forms,and supports a variety of terminal devices such as mobile phones,watches and smart screens.Our course on HarmonyOS aims to increase the theoretical knowledge of the core independent software and hardware platform.In the course,we exploit our teaching reform experience in the course of“Mobile Application Development”,and investigate the teaching mechanism of HarmonyOS to contribute to the rapid development of information technology and ecological construction in China.

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.

A mobile application framework of the BIM-based facility management system under the cross-platform structure

The building information model/modeling （BIM） technology is currently applied in a broad range of applications and research for facility management, while the BIM-based mobile FM is difficult owing to various factors and environments. For example, the mobile applications usually require frequent cross-equipment compatibility. This paper proposes a reasonable BIM-based FM cross-platform framework and develops a mobile application on the basis of an existing BIM-based FM system. The developed mobile application is applied in a case study of a metro station project in Guangzhou to verify its effectiveness in FM practice. It helps maintenance staff in viewing BIMs, accessing related information, and updating maintenance records in a unique platform. The test results demonstrate that the proposed BIM-based cross-platform framework meet the FM application requirements and supports the extension of FM functions.

Moblie Application for Recognizing Pali Letters

Pali is considered as the language of the canon continued to be influenced by analysts and grammarians,and by the native languages of the countries like Sri Lanka,in which Therava da Buddhism became established over many years.The Pali language has been used to write many stone inscriptions in ancient times.For ordinary travelers the recognition of the content of ancient inscriptions and some other written material are not possible.This study has focused to find a solution with a mobile application to recognize Pali characters in a user-friendly User Interface.The character recognition in real time is the most essential part of the study.Machine learning and neural networks are trending technologies adapted for handwriting recognition in some languages.But for many languages this technology has not been developed yet.Pali is one of such languages that had survived until the eighteenth century.In this study the images of Pali letters are identified through a trained Convolution Neural Network(CNN).Python and Android Studio software were used for training process and identifying letters respectively with the developed mobile application.The limited capacity and the processing power of a mobile phone makes it more challenging to run the application.Tensor Flow Lite is end to end open source platform in machine learning.Therefore,Tensor Flow Lite was used in this study.Since the Android mobile is a common equipment which everybody has in modern societies,using this Off-line Pali character Recognition mobile application the archelogy researchers and travelers can use them conveniently to understand the content written in ancient documents.

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.

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.

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.

Online and Offline Android Based Mobile Application for Mapping Health Facilities Using Google Map API. Case Study: Tanzania and Kenya Borders

The evolution of technology in 1990s resulted in the enormous growth of smartphones and the propagation of mobile applications (App) that marked new opportunities for healthcare centers and medical education. Apps have altered health services from patient’s health monitoring to specialist’s appointments and consultations from specialized health facilities. It can be argued that a healthy society can bring forth sustainable economic development to its full potential while an unhealthy society cannot. However, a free movement of people, labour and right to residence which was built across East Africa (EA) borders enabled Tanzania and Kenya borders to have enormous interactions. Subsequently, increase the risk of highly communicable diseases such as Tuberculosis and Sexually transmitted infections in such a way that medical attention is unavoidable along the borders. Statistically, Android Operating System (OS) owns 83% of Africa’s mobile OS market. In addition, 25,794,560 internet users reported by Tanzania Communications Regulatory Authority (TCRA) together with the 22.86 million internet users provided by Kenya Digital which is equivalent to 46% and 43% of internet penetration in year 2020, disclose the need for Android mobile application for mapping health facilities both online and offline using Google map API, which will solve residents’ need to healthcare services on the presence or shortage of internet connections;using either Swahili or English language via Smartphone devices. The App incorporates Monitoring and Evaluation (M & E) tool for tracking application usage which will ease Admin’s task to generate daily and monthly reports in Excel and Comma-Separated Values (CSV) formats. The developed system received positive feedback from EA citizens and residents in the Arusha region and Namanga border crossing where 90.2% of the system evaluation conducted between Dec 2020 and Apr 2021 agreed upon App usage.

Instagram Mobile Application Digital Forensics

In this research,we developed a plugin for our automated digital forensics framework to extract and preserve the evidence from the Android and the IOS-based mobile phone application,Instagram.This plugin extracts personal details from Instagram users,e.g.,name,user name,mobile number,ID,direct text or audio,video,and picture messages exchanged between different Instagram users.While developing the plugin,we identified resources available in both Android and IOS-based devices holding key forensics artifacts.We highlighted the poor privacy scheme employed by Instagram.This work,has shown how the sensitive data posted in the Instagram mobile application can easily be reconstructed,and how the traces,as well as the URL links of visual messages,can be used to access the privacy of any Instagram user without any critical credential verification.We also employed the anti-forensics method on the Instagram Android’s application and were able to restore the application from the altered or corrupted database file,which any criminal mind can use to set up or trap someone else.The outcome of this research is a plugin for our digital forensics ready framework software which could be used by law enforcement and regulatory agencies to reconstruct the digital evidence available in the Instagram mobile application directories on both Android and IOS-based mobile phones.

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.

Teaching Reform for Mobile Application Development with Industrial Projects,Double Instructors,and Automatic Assessments

Mobile Application Development is a well-known undergraduate specialized course majoring in Computer Science and Software Engineering.Since it is a rapid developing technique and requires extensive project samples to help understand,current teaching mechanism has still limitations in rare real project examples,outdated course contents,and lack of automatic assessment platforms.In order to improve the teaching effects and cultivate students’practical ability,we employ this teaching reform with industrial projects,double instructors,and automatic assessment platform to allow students participating in every course process.We aim to improve students’practical and collaboration ability during conducting the project spontaneously,and cultivate their awareness of self-learning and lifelong learning.Our classroom feedback has demonstrated that this teaching reform is effective on improving students’practical abilities,learning initiatives and comprehensive qualities.

Reform of Human-Computer Interaction Course based on Mobile Application Interaction Design

With the popularity of new intelligent mobile devices in people’s lives,the development of mobile applications has paid increasing attention to the interactive experience of users.As the content of traditional Human-Computer Interaction(HCI)course and teaching material is out of date,it cannot meet the needs of mobile application interaction design and enterprises for students.Therefore,we need a new generation HCI course based on intelligent mobile devices to study the relationship between users and systems.The HCI course not only teaches students HCI theory and model,but also needs to cultivate students’interaction-oriented design practical ability.This paper proposes a set of HCI teaching material design and teaching methods for improving HCI class quality on mobile application interaction design,so as to make students more suitable for the employment requirements of enterprises.

Ideological and Political Education in Harmony OS Application Development Course

The emergence of the Harmony operating system independently developed by Huawei has provided new opportunities and challenges for the development of our country’s information industry.This paper mainly introduces how to combine ideological and political education with mobile devices software development via Harmony OS development courses,aiming to cultivate students’ability to develop applications under the Harmony OS operating system independently or in groups,as well as achieving the patriotism and national mission.