Improve User Experience Research Articles

Stochastic Modeling of a Base Station in 5G Wireless Networks for Energy Efficiency

ABSTRACTThe potential benefits of 5G networks, such as faster data speeds and improved user experiences, come with a critical challenge—efficiently preserving energy in base stations (BSs). Addressing this challenge is crucial, necessitating a focus on maximizing the energy efficiency of these stations. BSs play a vital role in providing coverage and capacity by using different frequency bands adapting to diverse communication needs. The choice of a specific frequency band can impact network performance, data rates, coverage range, and signal propagation. This study emphasizes the crucial challenge of preserving energy in 5G BSs and underscores the significance of strategic frequency band selection for optimizing energy efficiency and network performance. For this, stochastic models are introduced for BSs, specifically the Markov and semi‐Markov models, which help choose frequency bands based on system traffic. Closed‐form solutions for steady‐state system size probabilities in these models are derived. A sensitivity analysis is conducted to assess power consumption in various scenarios. Furthermore, a comparison between analytical findings and simulation outcomes regarding power consumption is presented. The convergence of results in both methodologies emphasizes a significant level of agreement; that is, the introduced stochastic models provide insights and are validated by a close alignment between analytical and discrete‐event simulation outcomes. We have shown the behavior of power consumption with respect to three different distributions named deterministic, exponential, and hypo‐exponential. This research highlights the importance of strategic frequency band selection for 5G BSs to optimize energy efficiency and meet the demands of evolving communication networks.

Contact lens adoption and associated knowledge among the general population of South Gujarat, India

: Contact lenses have emerged as a popular alternative to spectacles, offering users enhanced vision correction, cosmetic appeal, and improved quality of life. However, awareness of contact lens care, hygiene, and complications remains a concern, particularly in regions with limited access to proper education on lens use. This study aimed to assess the level of knowledge, awareness, and practices related to contact lens use among the general population of South Gujarat, India.: A cross-sectional study was conducted using a structured online questionnaire administered to 1,500 participants. The questionnaire covered demographics, awareness of contact lens types, usage patterns, hygiene practices, and knowledge of potential complications. Data were analyzed using SPSS software, with chi-square tests used to determine statistical significance.: The study revealed that 60% of participants had some awareness of contact lenses, but only 30% demonstrated "extreme" awareness. Most participants used contact lenses for vision correction (65%), followed by cosmetics (30%). Adherence to recommended hygiene practices was variable, with only 56% consistently using contact lens solutions. Furthermore, 21% of users experienced discomfort while wearing lenses, and the dropout rate within the first six months was 28%.: There are significant gaps in knowledge and adherence to contact lens care, especially among younger users. Educational interventions focusing on hygiene practices, replacement schedules, and proper lens care are crucial to reducing complications and improving user experience.

FunCoup 6: advancing functional association networks across species with directed links and improved user experience.

FunCoup 6 (https://funcoup.org) represents a significant advancement in global functional association networks, aiming to provide researchers with a comprehensive view of the functional coupling interactome. This update introduces novel methodologies and integrated tools for improved network inference and analysis. Major new developments in FunCoup 6 include vastly expanding the coverage of gene regulatory links, a new framework for bin-free Bayesian training and a new website. FunCoup 6 integrates a new tool for disease and drug target module identification using the TOPAS algorithm. To expand the utility of the resource for biomedical research, it incorporates pathway enrichment analysis using the ANUBIX and EASE algorithms. The unique comparative interactomics analysis in FunCoup provides insights of network conservation, now allowing users to align orthologs only or query each species network independently. Bin-free training was applied to 23 primary species, and in addition, networks were generated for all remaining 618 species in InParanoiDB 9. Accompanying these advancements, FunCoup 6 features a new redesigned website, together with updated API functionalities, and represents a pivotal step forward in functional genomics research, offering unique capabilities for exploring the complex landscape of protein interactions.

Analisis Kepuasan Pengguna Website Zahira Media Publisher Menggunakan Metode End User Computing Satisfaction (EUCS)

This study aims to analyze user satisfaction with the website of Zahira Media Publisher, a publishing company that has been operating since 2012. Using a descriptive analysis method and a quantitative approach, this study collected data through a questionnaire designed based on the End User Computing Satisfaction (EUCS) model. The five main variables analyzed include content, accuracy, format, ease of use, and timeliness of information. The results showed that the quality of content and the accuracy of information greatly influenced user satisfaction. In addition, the ease of use of the website is also an important factor that improves user experience. that improves user experience. Although the Zahira Media Publisher website offers a wide range of publishing services, there are some obstacles, especially in the process of registering new user accounts, which can hinder access to key features. This research provides recommendations for improvements in website design and functionality to increase user satisfaction and customer loyalty.

A New Research Model for Artificial Intelligence-Based Well-Being Chatbot Engagement: Survey Study.

Artificial intelligence (AI)-based chatbots have emerged as potential tools to assist individuals in reducing anxiety and supporting well-being. This study aimed to identify the factors that impact individuals' intention to engage and their engagement behavior with AI-based well-being chatbots by using a novel research model to enhance service levels, thereby improving user experience and mental health intervention effectiveness. We conducted a web-based questionnaire survey of adult users of well-being chatbots in China via social media. Our survey collected demographic data, as well as a range of measures to assess relevant theoretical factors. Finally, 256 valid responses were obtained. The newly applied model was validated through the partial least squares structural equation modeling approach. The model explained 62.8% (R2) of the variance in intention to engage and 74% (R2) of the variance in engagement behavior. Affect (β=.201; P=.002), social factors (β=.184; P=.007), and compatibility (β=.149; P=.03) were statistically significant for the intention to engage. Habit (β=.154; P=.01), trust (β=.253; P<.001), and intention to engage (β=.464; P<.001) were statistically significant for engagement behavior. The new extended model provides a theoretical basis for studying users' AI-based chatbot engagement behavior. This study highlights practical points for developers of AI-based well-being chatbots. It also highlights the importance of AI-based well-being chatbots to create an emotional connection with the users.

Rfam 15: RNA families database in 2025.

The Rfam database, a widely used repository of non-coding RNA families, has undergone significant updates in release 15.0. This paper introduces major improvements, including the expansion of Rfamseq to 26 106 genomes, a 76% increase, incorporating the latest UniProt reference proteomes and additional viral genomes. Sixty-five RNA families were enhanced using experimentally determined 3D structures, improving the accuracy of consensus secondary structures and annotations. R-scape covariation analysis was used to refine structural predictions in 26 families. Gene Ontology (GO) and Sequence Ontology annotations were comprehensively updated, increasing GO term coverage to 75% of families. The release adds 14 new Hepatitis C Virus RNA families and completes microRNA family synchronization with miRBase, resulting in 1603 microRNA families. New data types, including FULL alignments, have been implemented. Integration with APICURON for improved curator attribution and multiple website enhancements further improve user experience. These updates significantly expand Rfam's coverage and improve annotation quality, reinforcing its critical role in RNA research, genome annotation and the development of machine learning models. Rfam is freely available at https://rfam.org.

The Future of Smart Home Security: Generative AI and LLMs for Intelligent Event Detection and Personalized Notifications

Abstract—Smart home security cameras are becoming more common, but their usefulness can be diminished by notification fatigue from too many alerts about minor incidents. This paper examines the gaps of existing event detection and notification systems in security cameras and then recommends using Generative AI and Large Language Models (LLMs) to add intelligence which would improve user experience. Generative AI can be leveraged to classify events more accurately and assist with anomaly detection. LLMs can further be used to create notifications that are tailored to the context and personalized to users behavior, helping to reduce notification fatigue and provide meaningful user alerts. The paper also looks into wider applications of these technologies to add intelligence and improve other related experiences like automated video summarization, proactive security measures, and improved privacy controls. The integration of Generative AI and LLMs with smart home security camera systems advances the smart cameras capabilities and offers enhanced security, personalized user experiences. Keywords—Smart home security, Generative AI, Large Language Models (LLMs), Event detection, Anomaly detection, Notification fatigue, Context-aware notifications, Personalized security, Reinforcement Learning from Human Feedback (RLHF), Internet of Things (IoT).

Application of Large Language Model Based on Knowledge Graph in Speech Dialogue System

Abstract. This paper comprehensively discusses the development status and future direction of AI-driven voice interaction systems, focusing on key technologies such as automatic speech recognition (ASR), natural language processing (NLP), and text-to-speech (TTS). With the continuous advancement of deep learning technology, voice interaction systems have achieved significant improvements in accuracy, naturalness, and user experience. However, these systems still face challenges such as accent recognition, background noise processing, complex query comprehension, and emotional expression. By analyzing the existing research results, this paper proposes that the research should focus on developing more robust models to achieve generalization across languages and dialects, and improve the system's ability to handle complex interactions.

Practical implications for design professionals: integrating emerging patterns into new media interface design

ABSTRACT In the new media era, visual communication design (VCD) in interface design (ID) relies on critical design patterns—layout, color, typography, and interactive elements—that are essential for user engagement. This study investigates these design patterns in ID, drawing on responses from 760 professionals, including UI and UX designers, researchers, and industry experts. Data analysis with SPSS revealed key trends, common practices, and areas for innovation, informing strategies for improved user experiences in new media interfaces. By highlighting emerging patterns and addressing literature gaps, the study offers valuable insights into design preferences and challenges faced by professionals, with implications for educational curricula, tool development, cross-disciplinary collaboration, and user-centric guidelines.

The Evolution of Identity and Access Management: Integrating Biometric and Behavioral Authentication

This article explores the transformative role of biometric and behavioral authentication in the evolving landscape of Identity and Access Management (IAM). As traditional password-based systems increasingly fail to meet the challenges posed by sophisticated cyber threats, these advanced authentication methods offer a promising solution. The article provides a comprehensive overview of physical and behavioral biometrics, examining their integration into multi-factor authentication systems and their capacity for continuous, passive user verification. It delves into the significant security benefits these technologies offer, including enhanced resistance to phishing, social engineering, and insider threats, while also highlighting the improvements in user experience and convenience. The article critically analyzes the challenges and considerations associated with implementing biometric and behavioral authentication, including privacy concerns, data security, accuracy issues, and scalability. Furthermore, it explores future directions and research opportunities in the field, such as advancements in biometric technologies, the application of machine learning and AI in behavioral analysis, and the development of context-aware authentication systems. By synthesizing current research and industry trends, this article provides valuable insights for cybersecurity professionals, IT decision-makers, and researchers interested in the future of secure and user-friendly authentication methods. It underscores the potential of biometric and behavioral authentication to significantly enhance organizational security postures while improving user satisfaction in an increasingly digital world.

Mixed reality strategies for piano education

Head-mounted mixed reality interfaces, in which a user perceives a seamless blend of real, virtual or remote content, have great potential in a wide range of educational contexts. In this paper, we explore the use of mixed reality (MR) in piano education. We begin with a review of previous examples of virtual and mixed reality for piano teaching and learning, identifying four major categories of functionality: remote teaching, learning to read musical notation, providing alternative notation systems to Western musical notation, and enhancing users’ understanding and experience of music. Following this review, we present an application designed to demonstrate the use of MR for facilitating remote student-teacher piano lessons. Additionally, hand-tracking enables real-time, bi-directional visualization of both the student’s and teacher’s hand movements while playing, which is a crucial communication channel in piano instruction. We also present the Piano Theory Hub, an interactive area for independent learning and practice designed to compliment remote instructions. The Piano Theory Hub uses MR to provide spatial in situ explanations and exercises on notes, intervals, scales, and chords. User studies were conducted to evaluate both remote and solo aspects of the application. The first study with 10 participants revealed a strong sense of immersion and co-presence with the teacher during remote lessons. Trials also revealed that, in addition to virtual hands, visual highlighting of key-presses was found to improve visualisation of the remote users’ play. The second study, with 15 participants found the Piano Theory Hub to be helpful for beginners and some intermediate players, with feedback suggesting improvements in user experience and highlighting the limitations of replacing traditional piano teachers. Our experiments demonstrate that MR can be successfully employed for the following strategies for piano education: hand interaction coaching, flexible virtual hand and piano visibility, augmented feedback including key highlighting, gamified learning elements, and flexible teacher positioning options. Overall, the findings suggest that mixed reality holds promise as an effective tool for remote piano learning and music education, offering immersive and engaging learning experiences.

Using Ecosystem Design to Help Projects Thrive—Cultivating Systemic Project Success

Emphasizing ethical considerations, community well‐being, and sustainability, designers are challenged to create product solutions that are technically effective while being socially responsible and inclusive.Substantial improvements in business efficiency and user experience can be achieved by employing ecosystem design. The challenge is creating solutions that are technically effective, socially responsible, and inclusive.

Chinese Consumers' Satisfaction with Online Shopping Platforms

With the rapid development of Internet technology, China's online shopping industry is also expanding rapidly, becoming an important part of global e-commerce. This article investigates Chinese consumers' satisfaction levels with Taobao, Jingdong (JD.com), and Pinduoduo, three of the country's most popular e-commerce sites. The article reviews the historical development of these platforms, their market positioning, and some of the unique spending habits of Chinese consumers. This paper analyzes several key factors that affect consumer satisfaction, including delivery accuracy, price, information quality, payment convenience, and security. The way that these aspects are handled by each platform greatly affects the buying experience of users. Technological innovations on platforms such as Taobao, such as AI-driven recommendations, have dramatically improved user experience and satisfaction. Jingdong has improved its delivery efficiency and customer satisfaction by building its own logistics system, and Pinduoduo's logistics are both slightly inadequate in comparison. However, Jingdong's logistics during peak hours still needs to be improved. The paper also points out that while price is a very important factor for consumers when choosing a platform, Pinduoduo still needs to find a balance between low price and service quality. Lastly, future studies can explore how cross-border e-commerce and the behavioral inclinations of various user groups could impact the platform's subsequent development stage. These findings suggest that continued attention to these factors can provide online shopping platforms with strategies to increase consumer satisfaction and improve service quality, as well as provide new ideas for academic research.

Research on Personalized Cultural Learning Platform Based on Collaborative Filtering and Popularity Recommendation

With the rapid progress of information technology, it has become the demand of the times to use the power of the Internet to inherit and develop Chinese traditional culture. Given the challenge of users searching for learning content in massive online resources, personalized recommendation systems have become the key to improving user experience. This paper focuses on building a personalized Chinese traditional culture learning platform based on collaborative filtering and popularity recommendation, aiming to stimulate users’ interest in learning traditional culture through intelligent algorithms. In terms of technical implementation, this study relies on the Django framework and MySQL database to build a feature-rich and user-friendly traditional cultural learning platform, supporting users’ diverse learning needs, and providing flexible learning paths and abundant learning resources. Experimental evaluation shows that the hybrid algorithm of collaborative filtering and popularity recommendation proposed in this paper has improved recommendation performance compared to existing methods, effectively enhancing user satisfaction and platform activity. This platform not only promotes the digital dissemination of traditional culture, but also provides users with a highly autonomous and personalized learning experience, meeting the contemporary society’s pursuit of diversified and personalized cultural learning.

Robust embedded access control system based on face and encrypted QR with RPi4

&lt;p&gt;&lt;span&gt;Facial-based recognition systems are commonly used for building access control, with the accuracy and computing requirements still being improved. On the other hand, QR codes are gaining rising attention as an input interface to many embedded applications. This paper proposes an embedded access control system that customises both previous techniques to be implemented on the CPU of a low-cost Raspberry Pi 4 computer. The achieved system works smoothly with a frame rate of 8.27 FPS, increasing the accessing control's robustness compared to a system based on face recognition only. It also offers the ability to control the access of unknown faces. In tandem with integration, this strengthens security measures, improves user experience, and outperforms conventional access control approaches, creating an attractive offer for many businesses.&lt;/span&gt;&lt;/p&gt;

Smart Attendance Management System with QR Code Authentication

Abstract: This paper presents the development of a Smart Attendance Management System (SAMS) designed to automate and streamline the process of tracking attendance in educational institutions and workplaces. The proposed system utilizes advanced technologies such as facial recognition and QR code to accurately and efficiently monitor attendance. By eliminating the need for manual entry, the system reduces human error, saves time, and enhances data accuracy. The SAMS also integrates with databases and analytics tools to provide real-time reporting and insights, helping institutions make data-driven decisions. The study outlines the system's architecture, implementation, and potential impact, demonstrating its ability to enhance operational efficiency and improve user experience in diverse environments

Empowering sports facilities and sports physiotherapy performance with Integrated Management Information System (IMIS): Enhanced user experience and service quality

This study investigates the development of Integrated Management Information Systems (IMIS) to improve user experience and service quality in sports facilities. This research conducts a systematic review (2018-2023) of 7 articles from Scopus, Google Scholar, and Semantic Scholar to explore how IMIS can address evolving industry needs. The system facilitates user access to information, online transactions, and feedback mechanisms while enabling personalization and recommendations. However, the review also highlights the potential of IMIS to revolutionize sports physiotherapy through enhanced athlete care, data-driven treatment plans, and streamlined operations. Successful IMIS implementation requires careful planning, stakeholder involvement, and continuous adaptation to emerging technologies like AI and IoT. By overcoming challenges and embracing opportunities, IMIS can usher in a new era of personalized, effective, and efficient athlete care. IMIS implementation involves evaluating facility needs, staff training, and introducing the system to users. Data security and privacy are paramount. Future integration of AI, IoT, and mobile applications holds promise for further enhancing IMIS effectiveness. Overall, IMIS implementation has demonstrably improved user experience and service quality. By prioritizing user experience and adapting to technological advancements, sports facilities can remain competitive in a digital age.

Technological transformation of transactions with the rise of FINTECH

In recent years, the entire financial landscape has experienced a significant transformation due to the rise of financial technology simply called Fintech, which has redefined the transaction processes and democratized the access to financial services. This review focuses on how fintech is transforming transactions by enhancing efficiency, increasing security, providing transparency, and creating accessibility for consumers and businesses alike. Key technologies such as blockchain, artificial intelligence, smart contracts, digital wallets, and mobile applications are transforming transactions, reducing costs, and improving user experiences. The integration of fintech solutions with the above mentioned key technologies is creating a more secure and interconnected ecosystem, reshaping and transforming the transactions. This article examines the impact of fintech on customer experiences through digital platforms and real-time transactions, as well as its potential to drive innovation and promote sustainability in payment services. It explores benefits, challenges. It also discusses regulatory considerations, collaboration opportunities between traditional banks and fintech startups, and emerging banking models. Overall, the review highlights fintech's transformative potential in revolutionizing energy payments and shaping the future of transactions.

Navigating the digital tax landscape: The impact of service quality factors on E-filing adoption among individual taxpayers in Jakarta

Tax administration digitization improves taxpayer experience through e-filing, supported by service quality, trust, and information technology. This study integrates electronic service quality to understand the decision to use E-filing, offering a comprehensive approach with the E-Filling model to create digital records that are easily accessible. This study analyzes the effect of quality factors on the use of E-filing, with mediation from perceived ease of use and perceived usefulness. The study design uses an explanatory with a causal approach to confirm the relationship between variables related to the use of e-filing by taxpayers in Jakarta. Samples were taken from 10,580,475 taxpayers, with 150 respondents based on certain criteria. Primary data were collected through an online survey using a Likert scale. The measurement model was tested for validity and reliability, as well as structural analysis to assess the relationship between variables using path coefficients and bootstrapping analysis for significance. The coefficient of determination (R²) and path analysis were also conducted to measure the impact of mediating variables. The study shows that of the various service quality factors, only responsiveness has a significant effect on the perception of e-filing usefulness with a T-statistic of 3.253 and a P value of 0.001. Meanwhile, the informativeness, reliability, and system availability factors do not show a significant effect on the perception of ease and usefulness, indicating the need for improvement in information delivery and system reliability. High responsiveness is very important in supporting positive perceptions of the usefulness of the e-filing system. Path analysis shows that neither perceived ease of use nor perceived usefulness affect the actual use of e-filing, with R Square only explaining 2.6% of the variation in use. Although the research model shows an adequate fit with an NFI of 0.786, improvements are still needed to increase e-filing adoption. Thus, focusing on improving responsiveness and optimizing other factors is needed to improve user experience. It is necessary to improve the responsiveness of the e-filing system and improve informativeness, reliability, and system availability to improve user perception. Future research is suggested to develop interventions for service factors that are not yet significant and explore other elements that influence e-filing adoption.

The Impact of Video Game Dimensions on Brand Love: A Guide for the Gaming Industry 2023-2024

This research paper investigates the factors contributing to brand love among gamers, with the aim of enhancing user experience and optimizing marketing strategies within the gaming industry. The study explores how specific gameplay elements and sensory triggers—such as rewards, personalization, music, and storytelling—affect emotional connections and foster brand loyalty. Additionally, it examines the application of neuromarketing techniques to gain a deeper understanding of consumer behavior and to promote stronger emotional engagement with gaming products, while also highlighting the importance of addressing ethical considerations and cultural differences in these strategies. Despite the growing popularity of video games, there is a notable lack of comprehensive research on the factors that elicit brand love, which limits developers' and marketers' ability to create engaging experiences that drive loyalty. Utilizing qualitative analysis involving professional gamers, developers, and bloggers, the study provides valuable insights for stakeholders aiming to develop more engaging and intuitive gaming experiences. It contributes to the academic literature on brand love and consumer behavior by identifying key dimensions of video games that evoke brand love. Specifically, the research focuses on: (1) analyzing how gameplay and sensory triggers enhance emotional connections, (2) exploring the impact of neuromarketing techniques on emotional responses, and (3) offering actionable recommendations for improving user experience and boosting customer loyalty. The major research question investigates which video game dimensions can trigger brand love, with subsidiary questions examining the effects of game and sensory triggers, and the potential role of neuromarketing in this context.