Mobile Application Development Research Articles

Enhancing accessibility: Development and usability testing of mobile application mitigating sexual harassment for visually impaired masseurs

ABSTRACT This study aimed to assess the development and usability of the Visually Impaired Masseur Assistance Application (VIMAA) designed to respond to signs of danger or instances of sexual harassment experienced by Visually Impaired Masseurs (VIMs). It harmonizes Rapid Application Development (RAD) method and qualitative in-depth interviews. RAD was implemented with emphasis on four core stages: requirement identification, design workshop, construction, and implementation, while Qualitative in-depth interviews were conducted utilizing thematic analysis for usability testing. Functionality testing also verifies the effectiveness of VIMAA features while requesting help, notification, and feedback. Pre-test identified four themes, including traumatic experiences and the need for protection. Post-test revealed themes such as ease of requesting assistance and switching to speech mode. VIMs perceive that VIMAA as user-friendly, practical, and acceptable. The requesting help, notification, and feedback features also work well. This study presents the effectiveness of VIMAA in establishing a framework that is accessible by a diverse spectrum of VIMs. The insights derived from this research also furnish valuable perspectives on the preferences of users reliant on mobile applications designed for VIMs, thus providing significant impetus for future research and development endeavors in this domain.

Parking Assistant with the Simulation of Application

Smart Parking can be used for any city. It aims to improve the efficiency and sustainability of urban transportation systems by using technology to manage parking systems. This article provides an overview of the different components of smart parking systems. The increasing vehicular population in urban areas has led to significant challenges related to parking management, exacerbating traffic congestion, environmental impact, and user dissatisfaction. The app facilitates real- time information on available parking spaces, reservation capabilities, and payment integration, thereby enhancing user experience and operational efficiency. We summarize the methodologies applied in developing the app, which include sensor integration for dynamic parking space monitoring and mobile application development for user interaction. The article concludes with a consideration of the future of smart parking and its role in the overall development of smart cities. In conclusion, the findings serve as a basis for future advancements in intelligent parking systems, ensuring improved service delivery for urban commuters.

Nationwide Assessment of Solar PV Power Potential Using Geospatial Data and Collaborative Research with Higher Education Institutions: Case of the Philippines

Abstract. Geospatial technologies present a significant opportunity to assess solar photovoltaic (PV) power potential through remote sensing techniques and geospatial analysis. This aligns with the goal of ensuring access to affordable, reliable, and sustainable energy, one of the Sustainable Development Goals (SDG) that the Philippine National Economic and Development Authority (NEDA) aims to achieve. In support of the said SDG, a research project, called Project SINAG, has developed a method for estimating solar PV power resources utilizing high-temporal remotely-sensed data. The primary objectives of this study are twofold: first, to develop a webGIS platform for solar energy resource information access and decision support; second, to conduct information dissemination and capacitybuilding activities for various stakeholders in the solar energy sector. The localized assessment of solar PV power potential incorporates meteorological and geomorphological factors such as high temperature, dust deposition, and slope. Collaboration with academic institutions, government agencies, and the solar energy industry has been instrumental in providing capacity-building through training workshops, internships, and on-the-job training. Moreover, the project has produced information, education, and communication (IEC) materials, launched a webGIS portal, and supported data requests and student research. The webGIS platform serves as the primary information dissemination tool for the project, enabling rapid sharing of research outputs with end-users. To enhance the platform, future developments may include additional functionalities such as community forums, client feedback mechanisms, mobile application development, and the integration of real-time data for map layers and forecasting tools.

Optimizing Agricultural Labour: An Examination of On-Demand Workforce Solutions for Seasonal Demands

To address the growing challenges in managing on-demand Labour within the agricultural sector, we introduce Agro Finder, an innovative application developed using Figma for design and flutter for frontend development and firebase for backend. This research presents a comprehensive overview of the current state of Labour management in agriculture and proposes Agro Finder as a solution tailored to the sector's unique needs. The app leverages real-time data and sophisticated algorithms to streamline the connection between farmers and Labourers, optimizing Labour allocation based on geographic location, skills, and availability. Further analysis reveals that Agro Finder significantly enhances Labour utilization efficiency, reducing downtime in agricultural operations. The app's intuitive design, supported by Figma, ensures a user-friendly experience, while the fronted, powered by Flutter, provides reliable performance. The integration of these technologies facilitates efficient Labour management, leading to increased productivity and operational efficiency in agriculture. The research findings underscore the potential of applying modern development tools and methodologies to solve traditional problems in agriculture. By harnessing the power of Figma and Flutter, Agro Finder sets a new standard in on- demand Labour management, offering valuable insights and practical solutions. This study provides a solid foundation for future advancements in agricultural Labour management and highlights the importance of technological innovation in enhancing agricultural productivity. Key Words: on-demand Labour, agricultural management, mobile application development, Figma, Flutter, Labour allocation, real-time data processing, Firebase.

Bridging medical expertise in crisis: The development and implementation of a novel mobile application for Ukrainian physicians during wartime.

The full-scale invasion disrupted health care in Ukraine, leading to the displacement of physicians and affecting their access to subspecialist consultations. HealUA, a mobile application, was designed to provide secure and timely remote physician-to-physician consultations. We aimed to assess the implementation of the HealUA mobile application for peer-to-peer physician consultations in Ukraine during the Russian invasion. HealUA was developed in May 2022. Security measures included user verification, privacy policies, and legal disclaimers. The application allowed physicians to submit cases and receive remote consultations from physicians in Ukraine and worldwide. We assessed the implementation of the HealUA application using Proctor's implementation outcomes framework, specifically adoption and feasibility. Adoption was measured by user downloads, characteristics of registered physicians, and case submissions. Feasibility was evaluated through clinical case response times, translation services, and technical issues. From May 2022 to May 2024, 3861 physicians registered. The majority were from Ukraine (95%). Of 474 submitted cases, 97.3% received timely responses from other physicians. The application demonstrated prompt response times (84.6% within the first day), successful translation services, and effective resolution of technical issues. The HealUA application achieved broad adoption across medical specialties, fostering robust clinical information exchange during the ongoing conflict. Security standards were upheld and routine technical issues were satisfactorily addressed. Future efforts will focus on broader dissemination and assessing additional implementation outcomes.

The Influence of Digital Trading Applications on Financial Markets

The word "fintech" refers to a new technology that aims to make financial services better and more automated. Investment management, retail banking, artificial intelligence, block chains, mobile payments, stock trading, and other industries are increasingly included in the fintech sector. With today's high-tech electronic trading on the stock exchange, ordinary investors can purchase or sell shares in a matter of seconds, giving investors the opportunity to efficiently perform their research before investing in equities. This paper, thus, talks about the emergence of fintech, which has led to the development of various mobile trading applications like Zerodha, Grow, Upstox, Angel Broking, etc. These apps have become popular among young investors in recent years because of their low-cost broking services. In this study, both primary and secondary data have been used. Primary survey-based research has been used to know the experiences of people belonging to different age groups on trading apps, and secondary data for statistical figures and other factual points has been used from verified stock exchange data and websites of trading apps. This paper will also shed light on the various seamless services offered by such broking applications, which have drastically changed the way the market functions. Investors could easily browse through the available investments, order what they wanted, and manage their portfolio with a single tap from their phone, making adjustments right away. The paper will go on to explain how stock trading applications have affected the financial markets by encouraging an increasing number of people to participate in the process of constructing economies by trading in financial assets. The report can assist policymakers in determining the advantages and hazards of using these new technologies, as well as the repercussions of their use. It offers legislative recommendations that are meant to encourage the use of AI in finance while making sure that its application is consistent with fostering market integrity, financial stability, and competition while safeguarding financial consumers. To support and encourage the use of responsible AI, emerging dangers from the deployment of AI techniques need to be detected and mitigated.

Protocol for a Randomized Controlled Trial on the Development and Effectiveness of an Educational Mobile Application Using an Integrated Change Model to Prevent Atherosclerotic Cardiovascular Disease Risk Factors

Background: An effective approach to preventing cardiovascular issues is the use of mobile health applications to improve modifiable risk factors. This protocol for a randomized controlled trial aims to evaluate the development and effectiveness of an educational mobile app that employs an integrated change model to reduce risk factors for atherosclerotic cardiovascular disease (ASCVD) among individuals aged 20 to 69 years. Methods: This study will be a parallel, randomized, single-blind clinical trial utilizing the randomized block design involving 430 participants. The participants will be divided into a control group receiving standard clinical care and an intervention group receiving standard clinical care along with app-based education, over approximately 6 months. Conclusion: This application has been designed to enhance motivation, awareness, and positive habits to reduce risk factors in individuals at increased risk of ASCVD. Consequently, the results could improve cardiovascular health knowledge, manage biological risk factors, and modify cardiac behaviors through mobile applications. This research is expected to present a promising approach to utilizing mobile apps for managing cardiovascular health and contribute to the growing body of research on digital health interventions.

Development of a Deep Learning‐Assisted Mobile Application for the Identification of Nematodes Through Microscopic Images

ABSTRACTNematodes are microscopic metazoans, some species of which can be used as biological insecticides, while some other species annually damage 10.0%–20.0% of crops globally. Accurate identification of nematodes is crucial for their effective utilisation or control. Current methods of nematode identification are labour‐intensive, time‐consuming, and prone to false positives, thus necessitating the development of an intelligent system for their identification from microscopic images without technical assistance. In this study, a novel approach was investigated for the identification of nematodes from microscopic images. A novel lightweight convolutional neural network (CNN) was developed to identify the nematodes belonging to different trophic groups (Heterorhabditis indica, Meloidogyne incognita, Helicotylenchus, Anguina tritici, and Xiphinema). The CNN model was trained for 75 epochs using 70.0% of the nematode dataset, with validation on 20.0% of the dataset. To ensure unbiased evaluation, 30 images from each class were randomly selected from the remaining 10.0% of the dataset for testing the classification performance of the trained model. The trained models achieved an average classification accuracy, precision, recall, and F1‐score values of 98.52%, 95.66%, 95.56%, and 95.56%, respectively. The proposed CNN was found to be four times faster and five times lighter against a marginal (< 1.0%) decrease in accuracy when compared with the existing state‐of‐the‐art CNNs. The classification accuracy of the developed mobile application was validated by nematode specialists on freshly captured data and found to be greater than 98.0%. Hence, the developed mobile application can be effectively applied for the identification of targeted nematodes and eliminate the necessity of specialists.

Simultaneous generation of dual 16-QAM-modulated millimeter-wave signals enabled by precoding-based optical I/Q modulation and single photodetector detection

Integration of quadrature-amplitude-modulation (QAM) modulation and millimeter-wave (mm-wave) technology ensures a concise enhancement of transmission capacity and peak data rates in radio-over-fiber (RoF) systems. Nevertheless, with the continuous development of new-generation mobile applications, higher demands on access flexibility have also been formulated. We propose a novel, to the best of our knowledge, dual 16-QAM-modulated mm-wave signal generation scheme for the simultaneous generation and transmission of two independent 16-QAM signals with different carrier frequencies, enhancing the channel capacity, spectrum efficiency, and access flexibility of the RoF systems. In our proposed scheme, the generation of the optical dual 16-QAM-modulated mm-wave signals is implemented by a precoding-based optical in-phase/quadrature (I/Q) modulator operating at optical carrier suppression (OCS) mode, and their detection is implemented by a single photodetector (PD). At the transmitter side, two independent driving QAM vector radio-frequency (RF) signals with precoding, generated via digital signal process (DSP), are fed into two parallel Mach–Zehnder modulators (MZMs) of an I/Q modulator to implement OCS modulation. The I/Q modulator generates optical carriers carrying both information from different QAM signals simultaneously. After square-law detection in a single PD, we generate the desired dual 16-QAM-modulated mm-wave signals with photonic frequency-doubling and recover the original 16-QAM signals without information distortion. Based on our proposed scheme, we experimentally demonstrate the simultaneous generation and transmission of 2-Gbaud dual 16-QAM-modulated mm-wave signals with carrier frequencies of 26 GHz and 40 GHz, respectively. After transmission over 10-km single-mode fiber (SMF) link and 1.2-m wireless link, the dual 16-QAM signals can be successfully separated and demodulated by a common DSP. Bit-error ratios (BERs) of both recovered 16-QAM signals can reach the hard-decision forward-error-correction (HD-FEC) threshold of 3.8×10−3. Compared with the existing schemes, our scheme only requires one-half of the driving frequency to generate dual 16-QAM-modulated mm-wave signals with the same carrier frequency. The result indicates that our proposed scheme can lower bandwidth requirements for optoelectronics devices, along with implementing better spectral efficiency and receiver sensitivity, which is more applicable to the demands for increased system capacity and multi-frequency access flexibility in future systems.

Exploring the Impact of Mobile Devices in E-Learning: A case Study Evaluating its Effectiveness

Aim. The integration of mobile devices into educational environments has revolutionized the landscape of e-learning, presenting new opportunities and challenges. This research paper aims to examine the pivotal role of mobile devices in the e-learning environment and assess the effectiveness of mobile learning applications in enhancing the educational experience. Methodology. The study employs a mixed-methods approach, combining quantitative data through surveys and usage analytics with qualitative insights derived from interviews and focus group discussions. Results. By analyzing the perspectives of both educators and learners, the research investigates how mobile devices contribute to the flexibility and accessibility of e-learning content. Additionally, the paper evaluates the effectiveness of various mobile learning applications in promoting engagement, knowledge retention, and overall learning outcomes. It scrutinizes the features that contribute to the success of these applications, such as user interface design, interactivity, and adaptability to diverse learning styles. Furthermore, the research delves into the challenges associated with mobile learning, including issues related to device compatibility, connectivity, and user motivation. Strategies to overcome these challenges and optimize the benefits of mobile learning are explored. The findings of this study are expected to provide valuable insights for educators, curriculum designers, and developers of mobile learning applications. Conclusion. The research contributes to the ongoing discourse on the effective integration of mobile devices in e-learning environments and offers recommendations for optimizing the design and implementation of mobile learning strategies.

Structure and functions of talking book mobile applications: a comparative study of Google Play Books, Audible, LibriVox, Storytel and Loyal Books

PurposeTalking book mobile applications have introduced the concept of reading through listening. Though conventional reading methods are preferable, talking book mobile applications have the advantage that they treat every user equally. The purpose of this paper is to compare the five popular talking book mobile applications namely Google Play Books, Audible, LibriVox, Storytel and Loyal Books.Design/methodology/approachThis research compares and evaluates features and functionalities of five different talking book mobile applications using a checklist method. A structured checklist is prepared to compare the five popular talking book mobile applications comprising 261 dichotomous questions divided into 13 categories.FindingsAfter evaluating the features, an attempt was made to rate the selected applications. According to the evaluation, Audible application performed better than others. This study about the features and functions of talking book mobile applications considered a total number of 261 features from the selected five mobile applications. Audible is ranked first with 182 (69.7%) features and is rated “Above average”; Storytel (68.2%) is second with 178 features, also rated “Above average”; Google Play Books ranked third with 161 (61.7%) features, rated “Average”; LibriVox ranked fourth with 151 (57.9%) features and is rated “Below average”. Fifth is Loyal Books with 130 (49.8%) features, rated “Below average”.Research limitations/implicationsThe study covers only five talking book mobile applications. The checklist used in the study is generic covering limited features. Further, the perceptions of users were also not included while comparing the talking book mobile applications. The study does not comprehend whether the talking book mobile applications fulfil the information needs of the users.Practical implicationsUsers can use the findings of the study in choosing the suitable talking book mobile application suitable to their requirements. Instructors of information literacy programmes can use the checklist to train the users in using talking book mobile applications that can accelerate the usage of these mobile applications.Originality/valueThe study identifies the features that should be available in a model talking book mobile application. Features of the talking book mobile applications were evaluated after preparing the detailed checklist. Features were divided into 13 different categories. The checklist used in the study is original and the first of its kind. The findings of the study can be used by developers of talking book mobile applications to improve their functionalities.

Mobile Application Development for Prepaid Water Meter Based on LC Sensor

This study presents a novel low-cost and low-power prepaid water meter system that combines tokenization and LC sensors to monitor water consumption accurately with mobile application via Bluetooth Low Energy (BLE) connectivity compared to conventional meters. Water meters play a vital role in monitoring water usage in Indonesia. Postpaid billing methods that rely on manual data recording are a source of concern due to potential inaccuracies caused by human error. This study presents the development of a prepaid water meter system that integrates LC sensors, BLE connectivity, a tokenization mechanism, and a mobile application to address this issue. The system offers a cost-effective solution by utilizing BLE + Global System for Mobile (GSM) from the user’s mobile phone. Using the design thinking methodology, the mobile application for the prepaid water meter achieved a usability testing score of 80. The load testing results for the back-end server, conducted with a sample size of 515 users, revealed a back-end latency of 1.973 milliseconds and an error rate of 8.74%. Furthermore, the LC sensors integrated into the PWM device showed an average error rate of 1.33%. The power consumption during each work cycle was measured at 129 mA and each battery is expected to last six years. Overall, with simple LC sensors, this system can precisely measure water usage.

Enhancing University English Teaching through Mobile Interactive Applications from an Educational Technology Perspective

In the context of globalization and rapid advancements in information technology (IT), the application of educational technology in higher education has become increasingly prevalent. Particularly in university English teaching, mobile interactive applications have emerged as a significant teaching model. These applications transcend the constraints of time and space, providing students with a flexible learning environment that promotes interaction between teachers and students, thereby enhancing learning outcomes. However, existing research has primarily focused on the technological development and effectiveness evaluation of mobile interactive applications, neglecting the impact of student interaction and trust on learning outcomes. Additionally, there is a lack of dynamism and personalization in the recommendation of educational resources and study partners. This study constructs global and local dynamic trust models for mobile interactions, calculates trustworthiness based on mobile interactive behaviors, and integrates mobile interaction trust relationships and behaviors with a dynamic English recommendation algorithm, thereby providing a new theoretical framework and a practical approach for university English teaching, aiming to enhance the teaching effectiveness and improve students’ learning experiences.

Challenges Faced by Parents of Children With Selective Mutism in Accessing Medical Care Services.

Background Children with selective mutism (SM) typically exhibit SM symptoms in educational settings, which has led to extensive research on SM in such environments. However, SM symptoms also manifest in medical settings, where parents experience various challenges when seeking healthcare for their child with SM. Nevertheless, there is a lack of research on the specific challenges parents face when seeking medical care for their child with SM. In this study, we investigated the challenges faced by parents of children with SM when seeking healthcare services and explored strategies to reduce these challenges. Methodology In this study, we conducted an online questionnaire survey with 31 parents (mean age: 41.7 years) of children diagnosed with SM. Participants responded to open-ended questions about the difficulties they faced when seeking medical care for their child. The open-ended responses were qualitatively analyzed using the KJ method. Results Parents of children with SM reported the most challenges accessing medical services in pediatrics and dentistry. The analysis identified the following three main challenges parents face when seeking medical care for their child with SM: "Journey to Receiving Treatment," "Physicians' Inability to Accurately Capture the Child's Condition," and "Healthcare Providers' Responses." Conclusions These findings highlight the numerous challenges faced by parents of children with SM when seeking medical services for their child. The challenges faced by parents when bringing their child with SM to medical facilities may be alleviated through the implementation of telemedicine, the development of mobile health applications, multidisciplinary collaboration, and the introduction of SM-specific training programs for healthcare professionals.

The Acceptance of Mobile Applications for Government Services (MG- App): A Study From Users’ Perspective

Purpose: The objective of this study is to identify and analyze various factors that influence users' acceptance of mobile government applications (mG-Apps). Methodology: This study has constructed a research model grounded on the Unified Theory of Acceptance and Use of Technology (UTAUT). Further, information quality and trust, two vital constructs, have been added to the UTAUT to enhance the predictability of the model. Data collected from a sample size of 212 from Bangladesh has been used to test the model. Findings: We have employed the popular structural equation modeling (SEM) to assess the data. Our results suggest that the significant elements impacting users' acceptance of mG-Apps are performance expectancy, effort expectancy, facilitating conditions, information quality and trust. In contrast, social influence is identified as an insignificant predictor. Practical Implications: This research will assist different government agencies, policymakers, and practitioners in the creation of timely and effective policies to develop and promote myriad mG-Apps to render services to the citizens. Originality/Value: This research has offered an innovative framework to assess the acceptance of mG-apps by the citizens. This unique model has been constructed by expanding UTAUT with two key contextual constructs such as information quality and trust. We believe, this study will contribute to the extant body of theory surrounding the use of mobile government, e-government, and mobile applications development. Limitations: This study only looks at the opinions of people in Bangladesh, hence the researchers recommend that the proposed study model should be validated by using data collected from other similar countries.

Faceify- Human Face Sketch to Real

The Human Face Sketch to Real Image Application using deep learning presents the development of an innovative application designed to convert human face sketches into realistic image using advanced deep learning techniques. The primary objective of this research is to bridge the gap between manual sketching and digital realism, offering a powerful tool for artists, law enforcement, and digital content creators. The proposed system leverages generative adversarial networks (GANs), particularly a variant known as the Sketch-to-Image GAN (SI-GAN), which is optimizes for translating sparse and abstract sketch lines into high-fidelity facial representations. The architecture consists of a generator network that refines sketches into realistic images, and a discriminator network that distinguishes between generated images and real photographs, continuously enhancing the model’s output. To ensure high accuracy and detail preservation, the model is trained on a diverse dataset comprising thousands of paired sketch and real face images. Advanced techniques such as attention mechanisms and multi-scale feature extraction are incorporated to maintain the integrity of facial features and textures. Additionally, a user friendly interface has been developed, allowing users to input sketches and receive high-quality realistic images in real-time. Evaluation metrics, including structural similarity index (SSIM) and Frechet Inception Distance (FID), Indicate that the proposed model outperforms existing state-of-the-art methods in both quality and realism. Keywords: Image Translation, Conditional Generative Adversarial Networks (CGANs), Deep Learning, Mobile Application Development, Backend Integration, Face Sketch, Photorealistic Image.

Co-creation and evaluation of an algorithm for the development of a mobile application for wound care among new graduate nurses: A mixed methods study.

Chronic wounds are a growing concern due to aging populations, sedentary lifestyles and increasing rates of obesity and chronic diseases. The impact of such wounds is felt worldwide, posing a considerable clinical, environmental and socioeconomic challenge and impacting the quality of life. The increasing complexity of care requires a holistic approach, along with extensive knowledge and skills. The challenge experienced by health-care professionals is particularly significant for newly graduate nurses, who face a gap between theory and practice. Digital tools, such as mobile applications, can support wound care by facilitating more precise assessments, early treatment, complication prevention and better outcomes. They also aid in clinical decision-making and improve healthcare delivery in remote areas. Several mobile applications have emerged to enhance wound care. However, there are no applications dedicated to newly graduate nurses. The aim of this study was to co-create and evaluate an algorithm for the development of a wound care mobile application supporting clinical decisions for new graduate nurses. The development of this mobile application is envisioned to improve knowledge application and facilitate evidence-based practice. This study is part of a multiphase project that adopted a pragmatic epistemological approach, using the 'Knowledge-to-Action' conceptual model and Duchscher's Stages of Transition Theory. Following a scoping review, an expert consensus, and stakeholder meetings, this study was pursued through a sequential exploratory mixed methods design carried out in two phases. In the initial phase, 21 participants engaged in semi-structured focus groups to explore their needs regarding clinical decision support in wound care, explore their perceptions of the future mobile application's content and identify and categorize essential components. Through descriptive analysis, five overarching themes emerged, serving as guiding principles for conceptual data model development and refinement. These findings confirmed the significance of integrating a comprehensive glossary complemented by photos, ensuring compatibility between the mobile application and existing documentation systems, and providing quick access to information to avoid burdening work routines. Subsequently, the algorithm was created from the qualitative data collected. The second phase involved presenting an online SurveyMonkey® questionnaire to 34 participants who were not part of the initial phase to quantitatively measure the usability of this algorithm among future users. This phase revealed very positive feedback regarding the usability [score of 6.33 (±0.19) on a scale of 1-7], which reinforces its quality. The technology maturation process can now continue with the development of a prototype and subsequent validation in a laboratory setting.

E-commerce and Mobile Application Development in the Sports Industry

In order to achieve user recommendations that best match their current contextual needs, the author proposes a mobile service QoS (Quality of Service) hybrid recommendation model based on sports user situational awareness. Cluster the users and service items covered by mobile users based on their location contextual information according to the classification principle of autonomous systems, forming a collaborative filtering and recommendation mechanism for mobile user service items; In response to the cold start problem of new users and new projects in traditional QoS recommendation methods, prediction and recommendation of missing QoS attribute preference values are based on User based and Item based CF; In response to the problem of difficult determination of mixed recommendation weights caused by massive data and uneven distribution of service QoS attribute values in mobile network environments, MapReduce based ant colony neural network weight training is used for CF mixed recommendation. Experimental results have shown that the Hadoop sports industry has improved the operational efficiency of algorithms and reduced the time for global QoS preference prediction; And by comparing the operation results of the 10% and 100% sub datasets, it can also be seen that the acceleration ratio of the algorithm will continuously improve with the increase of data volume, thereby improving the operational efficiency of the recommendation algorithm. It has been proven that the MapReduce based ant colony neural network weight training method significantly reduces the global computation time of the algorithm and improves the operational efficiency of the recommendation system.

Requirements and Key Features of a Mobile Application for Adolescent Self-Care From a Stakeholders Perspective: A Qualitative Study.

Adolescence is characterized by many changes and these changes differentiate adolescents' self-care needs. The use of smartphones and tablets to provide healthcare services has expanded, and the user-centered design could help to create mobile applications based on users' needs. Therefore, the present study aimed to identify the data requirements and key features of mobile application for adolescent self-care from a stakeholder perspective. This study was conducted with a qualitative approach to identify the key features of mobile application for adolescent's self-care as well as educational content axes for five component of self-care using conventional and directed content analysis respectively. From 3 sub-groups 30 participants were selected based on purposive sampling with maximum variety and sampling was performed until data saturation. Data were collected through in-depth semi-structured interviews. Participants' informed consent was obtained before the interview. The interview lasted 20-40min and MAXQDA software version 10 was used for data analysis. In this study, four criteria of acceptability, reliability, transferability, and validity proposed by Guba and Lincoln were used to evaluate and validate the data. After conducting the interviews, 789 initial codes, 12 sub-categories, and 3 categories (app view, app content architecture, app self-care content) were emerged, which reflects the key features of a mobile application and the necessary educational content. The research findings could provide a guide for future mobile application development considering the viewpoints of health professionals, content, and software experts. Addressing the features and requirements in practice could lead to designing efficient and effective mobile applications.

The Development of Pusara Finder: Muslim Grave Finder Mobile Application

In Islam, visiting graves reflects and reminds us of death and life in the Barzakh. The cemeteries must be adequately cared for and maintained since they play a significant role in the community as an important location for remembering and lamenting. However, remembering or finding the specific grave can sometimes be challenging. Thus, this project aims to develop a mobile application in which users can track their loved one’s grave to help them locate, save, and share the grave’s location by utilising the GPS sensors on the mobile phone. It is easier for them to track their loved ones and build a community for the Muslim cemetery community. The objectives of this project are to identify user requirements and to design and develop Pusara Finder – Muslim Grave Finder Mobile Application. This project uses the Android platform, and the mobile application has been developed using Visual Studio or Android Studio. There is a novelty of this project in which Pusara Finder is anl app designed to simplify the process of locating and navigating to Muslim graves in Shah Alam. This apps offers a seamless and intuitive experience, making it easier to pay tribute to the loved ones. The user also can access the complete database of Muslim graves with ease. The target user of this project was Muslim Public Users or people who want to find their specific grave. The methodology used for this project will be the Mobile Application Development Life Cycle (MADLC) Model. This project, however, has been developed up until the testing phase only. The project has been developed, and it’s in a prototype. In order to develop the mobile application, Flutter and Firebase has been implemented in this project. There were 11 users who had been involved in testing the usability of the mobile application by using System Usability Scale method with the score of 76.59 which in adjective rating is good.