Use Of Mobile Devices Research Articles

Impact of Mobile Health Interventions on HIV Testing Rates among At-Risk Youths: A Review

HIV remains a significant global public health challenge, particularly among at-risk youths aged 15–24, who accounted for over 30% of new infections in 2022. Barriers such as stigma, socioeconomic disparities, and limited access to healthcare contribute to low HIV testing rates within this demographic. Mobile health (mHealth) interventions, which leverage the widespread use of mobile devices, offer innovative solutions to address these barriers by providing confidential, accessible platforms for HIV testing and care. This review explored the impact of various mHealth interventions, such as SMS-based reminders, mobile apps, and telehealth platforms, on HIV testing rates among at-risk youths in different regions. Several studies demonstrate significant increases in testing rates, with mHealth tools reducing barriers related to confidentiality, stigma, and geographical access. However, challenges remain, including digital access disparities, privacy concerns, and the sustainability of interventions. A comprehensive literature review of studies on mHealth interventions targeting at-risk youth populations were utilized in compiling this educating paper. Future research should focus on refining mHealth strategies, incorporating emerging technologies like AI, and ensuring interventions are tailored to specific cultural and geographical contexts. mHealth has the potential to play a crucial role in combating the HIV epidemic by empowering at-risk youths to access testing and care. Keywords: Mobile health (mHealth), HIV testing, At-risk youths, Digital health interventions. HIV prevention.

Towards Understanding Nomophobia: A Systematic Review of Its Prevalence, Causes, and Effects in Educational Settings

This article analyzes the causes and consequences of excessive mobile device use among university students and its impact on mental health and academic performance through a review of studies published between 2018 and 2023. Articles were selected from Scopus and Web of Science databases that included "nomophobia" and "education" in the title, abstract, or keywords, and that were open access. The final analysis included 30 articles organized into 14 thematic categories. The most addressed topics were consequences, causes, levels, and factors that determine nomophobia. It was found that excessive mobile device use is mainly due to the constant need to stay connected and the fear of missing out on social media information. This technological dependence manifests in symptoms such as anxiety, stress, nervousness, and physical health problems, such as thumb and wrist pain, visual fatigue, and sleep disturbances. Nomophobia negatively impacts academic performance by interfering with the attention and concentration necessary for learning. Although educational technology does not seem to be a risk factor, it is crucial to promote a balanced use of mobile devices. Family intervention and education on the risks of excessive mobile use are essential to mitigate these effects and foster healthy technology use. Received: 2 August 2024 / Accepted: 30 October 2024 / Published: 05 November 2024

The Role of Technophilia and User Goals in the Intention to Use a Mobility Management Travel App

The ubiquitous use of mobile devices along with the amount of traffic, transportation services, and travel pattern data available has led to the emergence and deployment of smartphone applications for providing information about personal travel management. Several of these travel apps are aimed at voluntary travel behavior change (VTBC) to support and increase sustainable mobility, and have led to the development of research to investigate their influence on travel behavior. Here, the aim is to study the role of technophilia and goal-framing theory in the intention to adopt and situationally use a prospective VTBC travel app. A Structural Equation Model is developed with the aim of empirically testing a sample of 971 respondents collected in two suburban corridors in the Lisbon Metropolitan Area. The results support that goal-framing theory is important for explaining the adoption of VTBC travel apps. Gain and normative motives are more relevant than hedonic motives, pointing to the importance of their tangible benefits. Frequent car users may benefit from VTBC travel apps in terms of encouraging behavioral changes, supporting sustainable mobility management solutions. The results also outline the importance of technophilia and the current use of travel apps in influencing the intention to use VTBC apps.

Supporting equitable access to learning via SMS in Kenya: Impact on engagement and learning outcomes

AbstractThe use of SMS messaging for education has grown in recent years, with particular attention recently during the Covid‐19 pandemic. Mobile phones often have high levels of ownership in low‐income contexts compared to computers, and lower connectivity requirements, which arguably make this a more equitable medium than data‐heavy online instruction, for example. However, given that gender can be a factor to influence mobile device access and use, it is also important to consider educational applications through a gender lens, to avoid further exacerbating digital divides. In this paper, we present an analysis of server log and evaluation data in relation to a literacy‐focused initiative for primary‐aged learners carried out in Kenya as part of the Tusome programme and through the SMS‐based M‐Shule education platform, which does not require an Internet connection or smartphone to run. The extent of engagement with the platform varies according to gender and location within the country. The data also demonstrate a positive impact on learning outcomes regardless of learners' gender and location. Furthermore, the learning gains are shown to be relatively cost‐effective in comparison with educational technology interventions in similar contexts. The findings show that this low‐connectivity adaptive model has a positive impact on learning outcomes. It is a scalable approach to support a range of learners in Kenya, providing more support to learners who need it, and leading to increased foundational learning outcomes overall. As such, the findings will also be of highly relevant to other low‐connectivity contexts. Practitioner notesWhat is already known about this topic Mobile phones can be used as a means to support learning, through mobile learning and SMS, particularly in low‐connectivity contexts, although there is a lack of rigorous evidence of impact upon learning outcomes. Mobile phone device ownership tends to be higher than computer or wired Internet connections in many low‐income contexts. Software applications which adapt to the learners' level have shown good potential for gender‐equitable learning outcomes in low‐income contexts; however, these often require an Internet connection in addition to computers or tablets to be run on. What this paper adds There is a lack of contextually relevant evidence of the impact of SMS‐based mobile learning applications in low‐resource and low‐connectivity contexts upon learning outcomes. Through analysis of data generated via an experimental design, this study provides evidence that literacy materials delivered through an SMS‐based educational platform—M‐Shule—can have a positive impact upon learning outcomes. Furthermore, gains are equitable in terms of learners' gender, and location, within Kenya. Implications for practice and/or policy Mobile phones can be an effective way of reaching learners to provide additional educational support as part of existing education programmes in low‐connectivity environments. Learning gains using M‐Shule are evidenced as significant and relatively cost‐effective. Existing high‐quality learning materials developed in other media can be effectively adapted to SMS to reach learners particularly who are out‐of‐school or during periods of educational disruption.

Comprehensive Review and Future Research Directions on ICT Standardisation

Standardisation has become imperative to retaining order and development in modern society. The simplest actions, such as train timings and the width of the railroad, would be very difficult to achieve without Standardisation. Standardisation also solves problems, such as the use of mobile devices, which requires travel abroad when out of range. We perform a large-scale quantitative analysis for papers dealing with (1) standards and (2) Information and communications technology (ICT) data in three important databases, namely Web of Science, IEEE Explore, and ACM digital library, in this paper. These three databases presented 216 articles that were divided into five categories: standard-related review and survey studies, information management across hardware and software standards, energy management standards, machine learning model classification performance, privacy-aware software system standards, and health information and communications technology standards. This paper discusses how Standardisation facilitates the planning of the entire research and innovation process by encouraging discussions regarding the specific outputs the research aims to achieve. The paper further illustrates that references related to standardisation within the call topics act as a crucial motivating factor in the decision to adopt standardisation. In conclusion, our contribution provides a better understanding of standards in peer-reviewed publications and an essential foundation for future research. In addition, we demonstrate that standards play an important role in innovation.

PERFECT: Personalized Exercise Recommendation Framework and architECTure

Background : The health benefits of regular physical activity (PA) are well-established and widely acknowledged. Through the integration of wearable trackers, the Internet of Things (IoT)—a network of interconnected devices capable of collecting and exchanging data—coupled with mobile health (mHealth), which refers to the use of mobile devices to support medical and public health practices, it is now feasible to systematically gather and present individual exercise behaviors. This advanced approach enables the precise correlation of users’ physiological data and daily activities with their specific fitness needs, offering a personalized pathway to improving health outcomes. Objective : This study aims to enhance PA levels among individuals by developing a personalized exercise recommendation system. Utilizing reinforcement learning, the system proposes tailored exercise plans based on biomarkers and the user’s specific context. Methods : In this study, we developed applications for smartphones and smartwatches designed to gather, monitor, and recommend exercise routines through the application of a contextual multi-arm bandit algorithm. To evaluate the efficacy of this mHealth exercise regimen, we enlisted the participation of twenty female college students. Results : The outcomes of our investigation revealed a significant enhancement in the average daily duration of exercise (P \({\lt}\) . 001). Participants expressed high levels of satisfaction with both the walking program and the recommendation system, achieving average ratings of 4.31 (SD \(=\) 0.60) and 3.69 (SD \(=\) 0.95), respectively, on a 5-point scale. Furthermore, the average scores for participants’ confidence in safely performing the recommended walking exercises, as well as their perception of the study’s effectiveness in meeting their PA needs, were both above 4, indicating a positive reception and confidence in the program’s design and implementation. Conclusions : The evolution of the IoT and wearable technology has marked the beginning of a new era for mHealth systems, particularly in the personalization of health interventions. Such advancements enable the precise personalization of PA recommendations, potentially enhancing user engagement and performance outcomes. This paper introduces a novel exercise recommendation system that utilizes reinforcement learning to personalize walking exercises based on the user’s biomarkers and context, aiming to improve the user’s aerobic capacity significantly.

An enhanced whale optimization algorithm for task scheduling in edge computing environments.

The widespread use of mobile devices and compute-intensive applications has increased the connection of smart devices to networks, generating significant data. Real-time execution faces challenges due to limited resources and demanding applications in edge computing environments. To address these challenges, an enhanced whale optimization algorithm (EWOA) was proposed for task scheduling. A multi-objective model based on CPU, memory, time, and resource utilization was developed. The model was transformed into a whale optimization problem, incorporating chaotic mapping to initialize populations and prevent premature convergence. A nonlinear convergence factor was introduced to balance local and global search. The algorithm's performance was evaluated in an experimental edge computing environment and compared with ODTS, WOA, HWACO, and CATSA algorithms. Experimental results demonstrated that EWOA reduced costs by 29.22%, decreased completion time by 17.04%, and improved node resource utilization by 9.5%. While EWOA offers significant advantages, limitations include the lack of consideration for potential network delays and user mobility. Future research will focus on fault-tolerant scheduling techniques to address dynamic user needs and improve service robustness and quality.

Influence of maternal and infant technology use and other family factors on infant development

BackgroundDigital technology is ubiquitous in the lives of many children and parents. To better understand any influence of technology use by infants, and mothers, on child development, technology use should be considered within the broader family system context in which children develop. This study aimed to investigate associations between infant and maternal technology use and infant 12-month development, taking into consideration other family factors.MethodsThis cross-sectional study used data from ORIGINS participants, collected at 12-months of age: maternal and child technology use (TechU-Q), sociodemographic factors (e.g. child sex, household income), parental mental health (DASS-21), and child development (Ages and Stages Questionnaire). Linear regression was used for analyses.ResultsWhen family factors were considered, higher infant mobile touchscreen device (MTSD) use was associated with poorer infant development for gross motor, problem-solving, and total ASQ-3 scores. In contrast there were no associations between infant television (TV) watching or maternal technology use and total ASQ-3 scores. Higher maternal technology use was associated with higher infant technology use. Poorer maternal and paternal mental health were associated with poorer infant development. Poorer maternal mental health was also associated with higher infant TV watching and higher maternal MTSD use.ConclusionThere is a complex relationship between technology use, parental mental health and other family factors that together influence infant development. To improve infant development outcomes, less focus should be on infant or maternal technology use, and more on supporting the family as a whole, and parental mental health in particular.

Unravelling the sleep crisis: insomnia among medical students in government and private medical college students in Mysuru district

Background: Insomnia, a prevalent sleep disorder, significantly impacts medical students due to the high levels of stress and demanding academic schedules. The educational environment of medical students, marked by intense competition and high expectations, often contributes to chronic stress, a known precursor to sleep disturbances. This study aimed to compare the prevalence of insomnia among medical students in government and private medical colleges and assess the factors contributing to insomnia in these groups. Methods: The cross-sectional study was conducted among 490 medical students from government and private medical colleges over three months (April to June 2024). Systematic sampling was used to select participants, and data were collected via a self-administered questionnaire, including sociodemographic information and the Athens insomnia scale. Data were analysed using SPSS Version 26.0, with chi-square tests for qualitative data and Mann-Whitney U tests for insomnia comparisons. Results: The study revealed a significantly higher prevalence of insomnia in private medical college students (40.8%) compared to government college students (11.8%). Significant associations were found between insomnia and insufficient sleep, stress, and depression in both groups. Additionally, the use of mobile devices at night and irregular sleep patterns during exams were linked to higher insomnia rates. The median insomnia score was higher in private medical college students compared to government college students, indicating a statistically significant difference (p value <0.05). Conclusions: Targeted interventions to improve sleep quality and mental health support are crucial for this population. Regular assessments and feedback mechanisms should be implemented to enhance the effectiveness of these interventions.

Research on Mobile Learning (M-Learning) in Higher Education: A Systematic Review (2016 to 2023)

This study investigates the evolution of mobile learning (M-Learning) applications in higher education between 2016 and 2023. This period marks an era of significant technological innovations and the profound impacts of the COVID-19 pandemic on education. The purpose of this research is to delineate how M-Learning applications are represented in the academic literature during this time and to identify research trends within this field. The research is based on a systematic review of 161 academic articles related to M-Learning, published between 2016 and 2023 in the Scopus and Web of Science databases. The study utilizes the TCCM (Theory, Context, Characteristics, Methodology) framework to conduct an in-depth analysis of theoretical approaches, research contexts, learning characteristics, and methodological strategies in the literature. The findings reveal that M-Learning positively impacts areas such as collaboration, skill development, and self-assessment among students. The effective use of mobile devices as educational tools by instructors and students is identified as crucial for the success of M-Learning applications. Moreover, the success of M-Learning is closely linked to users' attitudes toward technology and the integration of technological and pedagogical supports into the learning processes. This systematic review provides significant insights into how M-Learning can transform learning and teaching practices in higher education. It suggests strategic planning and further research for educators, policymakers, and researchers on integrating mobile technologies into learning processes. Specifically, there is a need to explore the long-term effects of M-Learning on student achievement and its applicability in various learning contexts.

RISC-V Leads the Future: Evolution and Outlook of CPU Architecture

This essay mainly talked the development of CPU and some instruction set architecture based on RISCV. CPU is known as the Central Processing Unit, the main appliment is RISCV, Also the ARM architecture is characterized by a focus on the balance between low power consumption and high performance. Then X86, its significant advantage is its complex instruction set and excellent performance, so it can handle complex computational tasks. We also explore the Pipeline technology, it is a widely used parallel processing technology today. The design principle is to divide complex, multilevel combinational logic circuits into multiple levels. Then, we find some experiment data to explore our conclusion. We find that each has its own advantages and is better suited to different scenarios. In terms of performance, x86 offers superior capabilities but consumes more power, making it ideal for high-performance computing and server applications. ARM, on the other hand, excels in power efficiency and finds its primary use in mobile devices and embedded systems. RISC-V, known for its flexibility, allows for a balance between performance and power consumption based on specific requirements, making it suitable for highly customizable applications, IoT devices, and emerging high-performance computing markets. The advantages of each architecture in different fields depend on the specific application environment and demands placed on them.

Quantifying Parental Perceptions of Their Experiences With Their Young Children's Use of Power Mobility Devices.

To quantify and explore parental perceptions of their experiences with their child's use of the Explorer Mini (EM) and a modified ride-on car (mROC) in young children with cerebral palsy. Data were gathered throughout a multisite, randomized, counterbalanced AB crossover 16-week clinical trial, wherein all participants used device A (EM) and device B (mROC) for 8-weeks each. Semistructured parent interviews were conducted at baseline (T0), post-intervention period 1 (T1), and post-intervention period 2 (T2). The Linguistic Inquiry and Word Count program was used to objectively analyze the transcribed interviews. Twenty-four child-parent dyads participated in the study. Parental perceptions were related to children's gross motor abilities, cognitive development scores, and device use order (EM-mROC or mROC-EM). Parents were positive about a potential means of helping their children. While most preferred the EM, opinions were contingent on the PM device, device use order, and child-centered factors.

Technoference in infant feeding: the impact of maternal digital media use during breastfeeding on maternal attention and mother-infant interactions

IntroductionParents' sensitivity and responsiveness to their infants may be affected by the widespread availability and use of mobile devices. The present study examined the impact of maternal digital media use on maternal attention and the quality of mother-infant interaction during breastfeeding.MethodsMothers and infants (n = 25 dyads) participated in a within-subject experiment. Mothers breastfed their infants under one experimental and one control condition, counterbalanced across two laboratory visits. During the Digital Media condition, mothers watched a television show on a tablet. During the Control condition, mothers listened to classical music at ambient levels. Video records were later coded to assess maternal attention to the infant, tablet, or elsewhere and evaluate the quality of mother-infant interaction.ResultsThere were more disruptions in maternal attention to the infant during the Digital Media (M = 3.7, S.E. = 0.2 per minute) vs. Control condition (M = 1.7, S.E. = 0.2 per minute, p < 0.001). The proportion of the meal duration mothers spent focused on their infant was significantly lower during the Digital Media (M = 52.5%, S.E. = 3.9) vs. Control condition (M = 83.9%, S.E. = 4.0%, p < 0.001). Lower maternal attention to the infant was associated with lower maternal sensitivity to cues (p = 0.03) and cognitive growth fostering (p = 0.002), as well as lower infant clarity of cues (p = 0.001). Lower maternal attention was also associated with less socioemotional growth fostering (p < 0.001) and lower infant responsiveness to the mother (p < 0.001) regardless of whether digital media was present or absent, but during the Digital Media condition, mothers engaged in more socioemotional growth fostering (p = 0.004) and infants were more responsive to mothers (p = 0.03).DiscussionThe presence of digital media during infant feeding led to more interruptions to mothers' attention to their infants and the time mothers spent focused on digital media displaced time spent focused on their infants. The degree to which mothers were attentive to their infants vs. digital media was a more important predictor of most aspects of interaction quality than the mere presence of digital media.

Use of Remote Focus Groups to Improve Inclusive Design Practice

This study examines the use of remote focus groups to obtain wheeled mobility device user’s ideas regarding Shared Autonomous Vehicles (SAVs). Given the global increase in the aging population and disabled people, inclusive design is essential for accessible transportation. Using remote focus groups, this research collected statements from nine wheeled mobility device users about their design preferences, needs, and challenges with SAVs. Participants attended four virtual sessions featured with presentations and videos of SAVs. Discussions were video recorded in Zoom, with transcripts reviewed for accuracy. Data analysis included cleaning, coding, and assessing interrater reliability using the ICC. The findings not reported here highlighted the diverse needs and preferences of participants, emphasizing the importance of collecting information from this group early in the design process. This study shows well-planned remote focus groups can be an effective tool to gather human factors system design information from user populations that face transportation barriers.

Exploring Normalization for High Convergence on Federated Learning for Drones

The usage of mobile devices like drones has been increasing in various fields, ranging from package delivery to emergency services and environmental monitoring. Intelligent services increasingly use the processing power of these devices in conjunction with techniques such as Federated Learning (FL), which allows machine learning to be carried out in a decentralized way using data accessed by clients or devices. However, in normal operations, the data accessed by clients is distributed heterogeneously among themselves, negatively impacting learning results. This article discusses the normalization in Federated Learning local training to mitigate results obtained in heterogeneous distributions. In this context, we propose Federated Learning with Weight Standardization on Convolutional Neural Networks (FedWS) and evaluate it with Batch Normalization, Layer Normalization, and Group Normalization in experiments with heterogeneous data distributions. The experiments demonstrated that FedWS achieved higher accuracy results ranging from 3% to 6% and reduced the computational and communication costs between 25% and 40%, being more suitable for use in devices with computational resource limitations.

An Instrumental Analysis of the Triad Association Between Sugar-Sweetened Beverages, Screen Time, and Dental Caries in Adolescents

Background: Previous studies reported screen time in association with unhealthy dietary behaviors, such as excessive intake of sugar-sweetened beverages leading to dental caries. Thus, we aimed to explore the association between screen time on mobile devices and dental caries experience in adolescents, as well as whether sugar-sweetened beverages would mediate the association. Methods: We analyzed 24,374 junior and senior high school students of age 12 to 17 years from the 2021 “Surveillance for common diseases and health risk factors among students” Project in Jiangsu Province of China. Dental caries experience was determined by the designated dentists. Screen time and consumption of sugar-sweetened beverages were self-reported and treated as a priori risk. We employed an instrumental variable (IV) approach for the current cross-sectional setting. We used the lasso technique to shortlist covariates from a range of confounding factors. Binary logistic regression or ordered logistic regression was performed where appropriate to explore the associations of screen time on mobile devices with dental caries and sugar-sweetened beverages. Results: The prevalence rate of dental caries was 38.4% in the study population. In comparison with <2 h/d screen time on mobile devices, extended screen time (≥2 h/d) was associated with higher dental caries risk (coefficient: 1.27, 95%; confidence interval: 0.80–1.75). Mediation analysis suggested that sugar-sweetened beverage intake might be an independent risk factor for dental caries, instead of the mediator between screen time on mobile devices and dental caries. None of the interaction terms under investigation was statistically significant. Conclusions: Exposure to mobile device screens and sugar-sweetened beverages was associated with dental caries in adolescents. These findings highlighted the importance of increasing awareness of potential risks owing to mobile device usage and sugar-sweetened beverages and the necessity to develop appropriate intervention strategies for school-aged adolescents.

The Use of Automatic AI-based Notes and Transcription Services in Qualitative Research: Ethical and Methodological Concerns

The rise of online interviewing using videoconferencing platforms has impacted the way qualitative researchers conduct their data collection. Previous studies have investigated the use of Zoom Meetings for online data collection (Archibald et al., 2019; Lobe et al., 2020), yet other studies also have outlined ethical challenges when collecting data remotely (Bamdad et al., 2022; Lim & Kaveri, 2024). In LIS studies, researchers have examined ethical considerations for qualitative research methods in a virtual setting (Newman et al., 2021), although the discussion surrounding the advancement of AI-based technology in online data collection has been limited. With the growing interest in the use of transcription features in Zoom Meetings to support data analysis (Handler et al., 2022), issues surrounding automatic AI-based notes and transcription services integrated with this platform may have been overlooked. This study reflected ethical and methodological concerns when collecting data on student mothers’ use of mobile devices via Zoom Meetings synced with Otter.ai services. Ten participants were involved in online interviews from February to May 2023, resulting in nine transcripts from Zoom Meetings and Otter.ai services each. Ethical and methodological concerns surrounding AI-based meeting assistants’ use were outlined, including data ownership and intellectual property management, data repository and flow strategies, real-time nature of interactions, implicit speech bias, and decision-making accountability. The study contributes to broadening the understanding of the ethical and methodological concerns for qualitative researchers when using AI meeting assistants and further calls for specific LIS guidelines in online research using AI technology.

The Use of Automatic AI-based Notes and Transcription Services in Qualitative Research: Ethical and Methodological Concerns

The rise of online interviewing using videoconferencing platforms has impacted the way qualitative researchers conduct their data collection. Previous studies have investigated the use of Zoom Meetings for online data collection (Archibald et al., 2019; Lobe et al., 2020), yet other studies also have outlined ethical challenges when collecting data remotely (Bamdad et al., 2022; Lim & Kaveri, 2024). In LIS studies, researchers have examined ethical considerations for qualitative research methods in a virtual setting (Newman et al., 2021), although the discussion surrounding the advancement of AI-based technology in online data collection has been limited. With the growing interest in the use of transcription features in Zoom Meetings to support data analysis (Handler et al., 2022), issues surrounding automatic AI-based notes and transcription services integrated with this platform may have been overlooked. This study reflected ethical and methodological concerns when collecting data on student mothers’ use of mobile devices via Zoom Meetings synced with Otter.ai services. Ten participants were involved in online interviews from February to May 2023, resulting in nine transcripts from Zoom Meetings and Otter.ai services each. Ethical and methodological concerns surrounding AI-based meeting assistants' use were outlined, including data ownership and intellectual property management, data repository and flow strategies, real-time nature of interactions, implicit speech bias, and decision-making accountability. The study contributes to broadening the understanding of the ethical and methodological concerns for qualitative researchers when using AI meeting assistants and further calls for specific LIS guidelines in online research using AI technology.

APPLICATION FOR ANALYZING WATER QUALITY FOR TILAPIA FISH FARMING IN NET TANK

With the ability to provide food and income for the planet, fish farming and fishing, which are already widely practiced activities around the world, continue to grow across the globe. Water quality is essential for this type of activity. Controlling the chemical and physical factors of the water can ensure the success or failure of the farming. There are many ways to analyze water quality, but not all of them are simple or easy to use. The growing use of mobile devices has sought to facilitate this task, increasingly contributing to these and other activities. Aiming to support this evolution, the “Water Quality Monitor” application was modeled and developed, with the objective of providing, in a simple, easy and accessible way, relevant information on water quality scenarios for raising Nile tilapia fish in a cage-net farming environment. The application development methodology was based on the Rational Unified Process, focused on objects within programming and structured by UML diagrams. The final modeling proved capable of supporting the construction of an application to meet the expected requirements for assessing water quality, which during its use, allowed the control of chemical and physical factors of the water, ensuring the success of the creation, or indicating mitigating solutions for the corrections necessary for the process, being later validated in a case study.

The Role of Electronic Notification in Accelerating the Litigation Proceedings in Civil Lawsuits: (A Comparative Study)

Objective: The purpose of the article research of the topic is represented in showing the role of E-notification in accelerating the litigation proceedings in civil lawsuits, as it saves time, effort, and expense, as well as addressing the problems of traditional notification, and propose recommendations to complete the legal system concerned. Method: In the current research, which is based on the analysis of legal texts, the analytical approach and the comparative approach were adopted. A comparison was made among the" Iraqi Civil Procedure Law No. (83) of 1969 amended by Law No. (10) of 2016", and the UAE Federal Civil Procedure Law No. (11). ) for the year 1992 amended by Law No. (15) for the year 2021 and its bylaw No." (57) for the year 2018 amended by Law No. (75) for the year 2021". Results: Some valuable findings have been revealed such as The electronic notification is an effective way to accelerate the judicial proceedings because it prevents the recurrence of notification, and reduces the objection to the judgments in absentia due to the certainty of informing the defendant in addition to the ease of the notification process, regardless of the location of the defendants. Conclusion: The research employs theories that Electronic notification is a result of the advancement of current communication techniques as well as the pervasive use of mobile devices and the Internet across a variety of aspects of economic and social life. Despite this development, the Iraqi legislator still maintains the same traditional means that he put in place when enacting the Civil Procedure Code. He excluded the electronic means from all judicial proceedings from the scope of the electronic signature law, including proceedings related to the judicial notification. On the contrary, the UAE legislator adopted electronic judicial notification in order to accelerate such civil litigation proceedings.