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.

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.

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.

Password-Authenticated Multiple Key Exchange Protocol for Mobile Applications

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.

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.

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.

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.

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.

Comparative Analysis of Mobile Application Stores in Different Charging Modes

This paper describes the platformisation of the mobile services domain,which in recent years has become a successful strategy for some hardware manufacturers and software companies.While having different platform strategies and business models,they have succeeded in creating a demand for mobile software and content with end-users.This paper proposes a way to determine the optimum platform-charging mode that an operator should adopt to play a meaningful role in the mobile service domain and with respect to content with end-users.Four charging modes employed by mobile application stores are studied in this paper,namely the one-sided paid-by-users charging mode,the one-sided paid-by-advertisers charging mode,the two-sided differential paid charging mode and the two-sided paid and free access charging mode.Furthermore,a comparative analysis of the four modes is also presented.

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.

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.

EPIDEM: A Mobile Application to Contain Coronavirus Disease 2019

With the spread of COVID-19 across the globe, almost 33 million people became sick and almost 1 million have died (WHO). The government of the Philippines, along with the government of other countries declared movement restrictions or lockdown in the attempt to contain the virus. This resulted in loss of job and economic breakdown. The Philippines, in particular, experienced the longest and strictest lockdown. As a down side, a lot of people have lost their jobs and the country is currently facing economic recession. With the aim of containing the virus to reopen the economy, a team of experts developed a mobile application called EPIDEM. The application is available for both Android and Apple smartphones. With the use of EPIDEM, lay people can monitor their infection risk for COVID-19 and isolate themselves or get themselves tested when infection risk is high. Users can also monitor the health risk of other people that they come in contact with, so they can decide if meeting them is safe or risky. Further, the application provides a monitoring map that shows the area that is safe from COVID-19 and area where a possible outbreak might occur. The monitoring map will be helpful to both lay people, so they would know the places to avoid and to government officials, so they can quickly respond to outbreak. The teams of developers are recommending the nationwide implementation of EPIDEM to help contain the COVID-19 outbreak in the country. The application is not a new strategy of containment. Instead, it’s a better wheel that utilizes advanced technology to execute the manual containment strategies that are already being implemented in the country.

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.

Optical Character Recognition Functionality Introduction in Mobile Application for Car Diary

The purpose of the paper is to develop a mobile Android application--＂Car Log＂ that gives to users the ability to track all the costs for a vehicle and the ability to add fuel cost data by taking a photo of the cash receipt from the respective gas station where the charging was performed. OCR （optical character recognition） is the conversion of images of typed, handwritten or printed text into machine-encoded text. Once we have the text machine-encoded we can further use it in machine processes, like translation, or extracted, meaning text-to-speech transformed, helping people in simple everyday tasks. Users of the application will be able to enter other completely different costs grouped into categories and other charges. Car Log application quickly and easily can visualize, edit and add different costs for a ear. It also supports the ability to add multiple profiles, by entering data for all ears in a single family, for example, or a small business. The test results are positive thus we intend to further develop a cloud ready application.

Mobile Application for Research Knowledge Sharing and Dissemination: The Case of Nm-Aist Univeristy Tanzania

The utilization of mobile and web applications has surpassed all other platforms in terms of disseminating researchers’ knowledge among diverse communities throughout the world. The current method of disseminating researchers’ knowledge to the communities in the Arusha region in Tanzania is through meetings, workshops, and focus group discussions held by researchers, agricultural extension officers and community members after every three months or during field study. Yet the strategy is inefficient and ineffective in practice. The purpose of this study was to determine the most efficient and successful method of disseminating knowledge in communities. The study began with a qualitative phase, utilizing an interpretive technique and a qualitative multiple case study research design. The Arusha region in Tanzania was selected as a case study where different social activities were undertaken, including farming, livestock keeping, tourism activities and fishing. Individual participants were interviewed by using a semi-structured questionnaire. In addition, focus group discussions were conducted to gather more information regarding the needs of the mobile application. Through the implementation of the application, the second phase of the study led to the development of a mobile application that includes community members, agricultural extension officers, and researchers that will enable anyone to install the application on their mobile phones to access knowledge regarding activities undertaken in Arusha. According to the findings of the first phase of the research, a substantial percentage of community members own mobile phones, and hence a mobile application would be sufficient. The research also found that most researcher-community interactions occur at the data collection and intervention assessment (field trials) stages. Hence, the mobile application will benefit community members, district agricultural, irrigation, and cooperative officers (DAICO), and researchers.

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.

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.