User Convenience Research Articles

Real-Time precision prehospital stroke diagnosis in weightlifting athletes using cutting-edge non-invasive sensors

This research paper presents an investigation into the efficacy of a novel diagnostic technology designed for the real-time monitoring of weightlifting athletes, focusing on precision, time efficiency, and user convenience compared to traditional diagnostic systems. The study introduces an advanced non-invasive sensor system, integrated into a cohesive Internet of Medical Things (IoMT) framework, which facilitates the immediate and accurate assessment of athletes' health parameters. To empirically test the benefits of this new technology, a pedagogical experiment was conducted involving two distinct groups: an experimental group that utilized the proposed technology for medical checkups, and a control group that continued with traditional diagnostic methods. Each group consisted of 30 athletes, and the outcomes were measured across three dimensions: the precision of diagnostic results, the time expended for medical checkups, and the user-reported convenience of the equipment. The findings indicate that the proposed technology not only significantly enhances the precision of health diagnostics but also reduces the time required for medical examinations, thereby increasing overall efficiency. Additionally, the higher convenience scores reported by the experimental group suggest improved user satisfaction and usability. These results demonstrate the potential of the proposed diagnostic system to transform athlete health monitoring by providing more accurate, efficient, and user-friendly medical assessments, suggesting a significant step forward in the application of advanced technologies in sports medicine.

Testing the effects of personalized recommendation service, filter bubble and big data attitude on continued use of TikTok

PurposeThis study attempts to identify the determinant factors for Chinese users’ intention of continuous use of TikTok.Design/methodology/approachDrawing on the theoretical background and previous literature, this study proposes the research model followed by research hypotheses. For the purpose of empirical analysis of this study, we conducted a questionnaire survey on current Chinese TikTok platform users. Factor analysis was conducted to verify the reliability and validity of the measurement variables; Confirmatory factor analysis was conducted to ensure that the structural dimensions of the measurement are effective; the analysis results of the structural equation model for hypothesis test.FindingsThe result of the study indicates that the core service traits (entertainment, informativeness and convenience of use) of TikTok all have a positive effect on user engagement and perceived usefulness. In addition, the study found that both personalized recommendation services and filter bubble, which are features of TikTok's service recommendation system, have a positive effect on user engagement and perceived usefulness of TikTok. In addition, it was found that both user engagement and perceived usefulness have a significant positive effect on continuous use intention. Finally, users’ attitude toward big data indicating privacy concern only had a positive moderating effect on the personalized recommendation service but not on filter bubble.Originality/valueAs consumers’ demand for services tailored to their needs and preferences fast increased, it calls for growing concern over the safety of personal data being used by the platforms. Although this paradox over increased user convenience versus privacy protection issue has been persistently recognized, no previous research empirically addressed this issue in the context of social media platforms.

Design and Development Model of a Web Accessibility Ecosystem

The article examines issues of web accessibility ecosystems for people with special needs. Methods, models, accessibility standards, and technologies related to the structure, design, and functionality of the web accessibility ecosystem are studied. The stages of developing an accessibility ecosystem are explored. The accessibility of the design, functionalities, structure, and content of a particular ecosystem are presented. Several themes for the design of the system with an emphasis on its accessibility for blind users are explored and analyzed. UX/UI design and the ontological model of accessibility, used in the implementation of the model of the ecosystem and its elements, are studied. A web accessibility ecosystem model has been developed, compliant with the Web Content Accessibility Guidelines and based on semantic technologies. Other qualities of this model are easy access to information resources on the topic of accessibility, convenience for users with different needs, and the possibility of expansion and enrichment in the future.

Personal Identity Proofing for E-Commerce: A Case Study of Online Service Users in the Republic of Korea

The rapid expansion of non-face-to-face e-commerce services in the Korea has significantly increased the importance of personal identity proofing (PIP) for verifying users in online transactions, such as payments, refunds, membership registrations, and access to age-restricted products. Currently, personal identity proofing agencies (PIPAs) indiscriminately provide all of a user’s personal information to internet service providers (ISPs), leading to substantial privacy concerns and preventing users from selectively disclosing only the necessary information. The objective of this paper is to enhance the safety, convenience, and security of PIP services by proposing a method that empowers users to control the personal information they disclose while enabling digital identity integration for both online and offline applications. To achieve this, an extensive overview and analysis of the current PIP systems in Korea is presented, including methods. The strengths and weaknesses of these systems are critically examined, revealing limitations in privacy protection, user convenience, and security. Based on this analysis, a new method is proposed that introduces differentiated levels of PIP means according to authentication strength, allowing for the minimal necessary disclosure of personal information. The proposed method aims to improve the stability and reliability of the PIP service environment by addressing current privacy concerns and enhancing user control over personal information. This approach can be applied to e-commerce services in Korea and other countries facing similar challenges, contributing to the development of safer and more reliable online services.

DESIGN AND FABRICATION OF SMART ENVIRO GUARDIAN

This project tackles the challenge of maintaining a comfortable and healthy indoor environment in the face of unpredictable weather conditions. The primary objective is to develop an automated weather monitoring system integrated with a humidifier, leveraging Internet of Things (IoT) technology and a suite of sensors including the DHT11 for temperature and humidity, a rain sensor, an LDR sensor, and a BMP180 barometric pressure sensor. The system aims to monitor real-time weather data and adjust indoor conditions accordingly, enhancing comfort and reducing health risks such as respiratory issues, allergies, and mold growth. Additionally, it provides remote monitoring and real-time alerts through IoT connectivity, improving user convenience and energy efficiency. The methodology includes detailed requirement analysis, hardware and software development, testing, and deployment. This project promises to significantly improve indoor environmental quality, especially in regions with erratic weather patterns, by providing a robust, adaptable solution. Keywords: Automated Weather Monitoring, Climate Control, IoT Technology, Humidifier, DHT11 Sensor, Rain Sensor, LDR Sensor, Energy Efficiency

Design and research of serial communication system based on virtual instrument technology

Abstract In the measurement and automation control system, serial communication has been connected between the acquisition hardware (lower computer) and the upper computer between the easiest to realize and the most economical way. In view of the traditional instrument itself is relatively bulky, inconvenient to carry, this paper adopts the virtual instrument development environment to realize the realization of serial communication, in order to complete the subsequent data acquisition. When compared with other software development environment, LabWindows/CVI platform comes with a function library to make the program writing simple and flexible. In this paper, we designed the realization method of serial communication based on virtual instrument Labwindows/CVI environment, completed the design and realization of serial communication between PC and lower computer (microcontroller) based on Labwindows/CVI environment, and applied it to the example of serial communication with microcontroller to realize the data communication function. Practical results prove that the serial communication system based on virtual instrument technology has the advantages of friendly user interface, high stability, convenience and reliability, and can reliably and accurately complete the communication, and provide strong technical support for the system to follow up data acquisition.

PROBLEMATIC ASPECTS OF DEVELOPING APPLICATIONS FOR GENERATING AND STORING USER PASSWORDS

In today’s digital world, the security of personal data is becoming an increasingly pressing issue. Apps for storing user passwords are an important tool in ensuring the security of online accounts, but their development is not without problematic aspects. This article discusses the key challenges developers face when building these applications. Particular attention is paid to storage security, authentication mechanisms, as well as usability and integration with other services. By analyzing these issues, you can identify the main challenges and find ways to solve them, contributing to the creation of more reliable and user- friendly applications for storing user passwords. This article provides an overview of the challenges that arise when developing applications to store user passwords and provides recommendations for solving them. The article discusses such important aspects as data protection, prevention of cyberattacks, compliance with security standards, and usability for the end user. Understanding these challenges and being able to solve them plays a key role in creating trustworthy and effective applications that can provide a high level of security and convenience for users in their everyday online experience. The article describes the practical development of an application for generating complex passwords, as well as their further secure storage in an encrypted database with subsequent integration with third-party applications for more secure storage. The article is of great practical significance. Keywords: generating passwords, storing passwords, cryptography, safety, encryption.

Enhancing cell phone security through finger vein biometric authentication systems

The growing demand for secure mobile devices has led to the widespread adoption of biometric technologies. While personal identification numbers (PINs), passwords, gridlock patterns to safeguard phones and facial recognition have become common, they have certain limitations in terms of security and user convenience. These conventional security measures are riddled with susceptibilities, such as password pilferage, memory lapses in authentication details, and user mistakes in grid pattern creation. Due to the rising occurrence of cell phone incursions and theft, there is an urgent requirement for a strong security system that not only defends data but also shields the device itself. This paper proposes a resilient finger vein biometric security system as a more effective substitute for knowledge-based and password-based authentication techniques. The implementation of finger vein biometrics as a novel approach to enhancing cell phone security. The method employs infrared (IR) light transmission to capture the vein patterns and shadows resulting from the different thicknesses of finger muscles, bones, and tissues. The unique vascular patterns in fingers are difficult to forge, offering a higher level of security compared to other biometric systems. The simulations we conducted indicate an identification accuracy rate of 93.82%, indicating that this technique provides a substantial enhancement in preventing unauthorized access and theft of cell phones. This study examines the technology behind finger vein biometrics, its integration into mobile devices, and the security advantages it offers.

RANCANG BANGUN USER INTERFACE DAN USER EXPERIENCE APLIKASI SEMBAKO BERBASIS WEB PADA TOKO G-STAR MENGGUNAKAN METODE HUMAN CENTERED DESIGN

The advancement of information and communication technology (ICT) has notably impacted various sectors, including trade. For grocery stores, effective User Interface (UI) and User Experience (UX) design are vital to ensure technology is user-friendly across different groups. This research applies the Human-Centered Design (HCD) method to develop the UI and UX for the G-Star grocery store web application, focusing on user needs, preferences, and contexts to create an intuitive interface. The research process includes stages such as user needs analysis, prototype design, usability testing, and iterative design based on feedback. Initially, user needs were identified through interviews and surveys, which guided the creation of application prototypes. These prototypes were then tested for usability, and feedback was used to refine and improve the design. The findings demonstrate that HCD principles enhance UI and UX, leading to higher customer satisfaction and loyalty. Implementing HCD improves user efficiency and convenience, contributing positively to the G-Star grocery store's performance. This research provides valuable insights for technology development in the grocery sector and offers practical guidance for designers and developers, encouraging the use of HCD in similar projects.

12-Lead Holter Integrated with Sleep Monitoring Module

ECG signals and sleep monitoring parameters complement each other and can be used for qualitative diagnosis of sleep apnea syndrome and cardio-related diseases. However, due to the limitations of the instrument volume and the detection environment, it is often challenging to integrate these two functions in practical applications. In this paper, a 12-lead dynamic electrocardiograph integrated with sleep monitoring is designed. The system's volume is reduced by combining the integrated ECG simulation front end with a miniature sensor. The system achieves the extraction, conditioning, and calculation of 12-lead ECG signals and sleep-related parameters and writes the data to a memory card in real time, which offers convenience for users and doctors in the diagnostic process.

딥러닝 기반의 주차 층수 탐지 애플리케이션의 개발

In this study, we develop an application to detect the number of indoor parking floors using deep-learning techniques. Previously, floor-number predictions relied solely on simple atmospheric pressure data. In this study, we expand this solution to create applications for both Android and iPhone platforms. This ensures that user experience is optimized for the unique characteristics of mobile applications on each platform. Our approach renders parking-space navigation more efficient and intuitive, thus significantly enhancing user convenience. Ultimately, this development contributes positively to environmental, social, and governance fields.

Deep learning techniques for hand vein biometrics: A comprehensive review

Biometric authentication has garnered significant attention as a secure and efficient method of identity verification. Among the various modalities, hand vein biometrics, including finger vein, palm vein, and dorsal hand vein recognition, offer unique advantages due to their high accuracy, low susceptibility to forgery, and non-intrusiveness. The vein patterns within the hand are highly complex and distinct for each individual, making them an ideal biometric identifier. Additionally, hand vein recognition is contactless, enhancing user convenience and hygiene compared to other modalities such as fingerprint or iris recognition. Furthermore, the veins are internally located, rendering them less susceptible to damage or alteration, thus enhancing the security and reliability of the biometric system. The combination of these factors makes hand vein biometrics a highly effective and secure method for identity verification.This review paper delves into the latest advancements in deep learning techniques applied to finger vein, palm vein, and dorsal hand vein recognition. It encompasses all essential fundamentals of hand vein biometrics, summarizes publicly available datasets, and discusses state-of-the-art metrics used for evaluating the three modes. Moreover, it provides a comprehensive overview of suggested approaches for finger, palm, dorsal, and multimodal vein techniques, offering insights into the best performance achieved, data augmentation techniques, and effective transfer learning methods, along with associated pretrained deep learning models. Additionally, the review addresses research challenges faced and outlines future directions and perspectives, encouraging researchers to enhance existing methods and propose innovative techniques.

Delusio - Plausible Deniability For Face Recognition

We developed an Android phone unlock mechanism utilizing facial recognition and specific mimics to access a specially secured portion of the device, designed for plausible deniability. The widespread adoption of biometric authentication methods, such as fingerprint and facial recognition, has revolutionized mobile device security, offering enhanced protection against shoulder-surfing attacks and improving user convenience compared to traditional passwords. However, a downside is the potential for third-party coercion to unlock the device. While text-based authentication allows users to reveal a hidden system by entering a special password, this is challenging with face authentication. We evaluated our approach in a role-playing user study involving 50 participants, with one participant acting as the attacker and the other as the suspect. Suspects successfully accessed the secured area, mostly without detection. They further expressed interest in this feature on their personal phones. We also discuss open challenges and opportunities in implementing such authentication mechanisms.

Diagnostics of viral infections using high-throughput genome sequencing data.

Plant viral infections cause significant economic losses, totalling $350 billion USD in 2021. With no treatment for virus-infected plants, accurate and efficient diagnosis is crucial to preventing and controlling these diseases. High-throughput sequencing (HTS) enables cost-efficient identification of known and unknown viruses. However, existing diagnostic pipelines face challenges. First, many methods depend on subjectively chosen parameter values, undermining their robustness across various data sources. Second, artifacts (e.g. false peaks) in the mapped sequence data can lead to incorrect diagnostic results. While some methods require manual or subjective verification to address these artifacts, others overlook them entirely, affecting the overall method performance and leading to imprecise or labour-intensive outcomes. To address these challenges, we introduce IIMI, a new automated analysis pipeline using machine learning to diagnose infections from 1583 plant viruses with HTS data. It adopts a data-driven approach for parameter selection, reducing subjectivity, and automatically filters out regions affected by artifacts, thus improving accuracy. Testing with in-house and published data shows IIMI's superiority over existing methods. Besides a prediction model, IIMI also provides resources on plant virus genomes, including annotations of regions prone to artifacts. The method is available as an R package (iimi) on CRAN and will integrate with the web application www.virtool.ca, enhancing accessibility and user convenience.

CardioGuard: AI-driven ECG authentication hybrid neural network for predictive health monitoring in telehealth systems

The increasing integration of telehealth systems underscores the importance of robust and secure methods for patient data management. Traditional authentication methods, such as passwords and PINs, are prone to breaches, underscoring the need for more secure alternatives. Therefore, there is a need for alternative approaches that provide enhanced security and user convenience. Biometric-based authentication systems uses individuals unique physical or behavioral characteristics for identification, have emerged as a promising solution. Specifically, Electrocardiogram (ECG) signals have gained attention among various biometric modalities due to their uniqueness, stability, and non-invasiveness. This paper presents CardioGaurd, a deep learning-based authentication system that leverages ECG signals—unique, stable, and non-invasive biometric markers. The proposed system uses a hybrid Convolution and Long short-term memory based model to obtain rich characteristics from the ECG signal and classify it as authentic or fake. CardioGaurd not only ensures secure access but also serves as a predictive tool by analyzing ECG patterns that could indicate early signs of cardiovascular abnormalities. This dual functionality enhances patient security and contributes to AI-driven disease prevention and early detection. Our results demonstrate that CardioGaurd offers superior performance in both security and potential predictive health insights compared to traditional models, thus supporting a shift towards more proactive and personalized telehealth solutions.

Promoting Consumers’ Adoption of Buy-Now-Pay-Later Feature while Using E-wallet Application: The Case of Gen Z in Vietnam

The Buy-Now-Pay-Later (BNPL) feature has emerged as a popular payment innovation, offering users convenience and flexibility in their purchasing behavior. However, consumers' adoption of BNPL is often limited due to the trust issue usually associated with electronic payment. Previous studies have highlighted personal traits that affect consumers’ trust in adopting BNPL, such as risky indebtedness behaviour or privacy concern. Adopting the Stimulus-Organism-Response framework, this study investigates environmental factors influencing consumers’ attitudes and perceptions of privacy risks and trust. The main objective of this study is to identify these factors, which can be valuable to practitioners in promoting consumers' intention to adopt BNPL. The model was tested based on data collected from 430 young Vietnamese consumers. Data analysis is conducted using SmartPLS 4.0. The study's findings, which are significant in consumer behavior, confirm that behavior intention to use BNPL results from attitude, trust, and perceived risk, which were influenced by perceived ease of use and subjective norms. These findings provide actionable insights for practitioners in the field, equipping them with the knowledge to promote BNPL adoption effectively. One notable result of the research is that perceived ease of use has a negative impact on privacy risk. This finding implies that users’ primary apprehension in using the E-wallet BNPL feature pertains to the risk of losing their privacy. It strongly recommends that developers create a more user-friendly and transparent BNPL experience to alleviate privacy concerns and enhance user trust, thereby promoting the adoption of BNPL.

An Evaluation of the Security of Bare Machine Computing (BMC) Systems against Cybersecurity Attacks

The Internet has become the primary vehicle for doing almost everything online, and smartphones are needed for almost everyone to live their daily lives. As a result, cybersecurity is a top priority in today’s world. As Internet usage has grown exponentially with billions of users and the proliferation of Internet of Things (IoT) devices, cybersecurity has become a cat-and-mouse game between attackers and defenders. Cyberattacks on systems are commonplace, and defense mechanisms are continually updated to prevent them. Based on a literature review of cybersecurity vulnerabilities, attacks, and preventive measures, we find that cybersecurity problems are rooted in computer system architectures, operating systems, network protocols, design options, heterogeneity, complexity, evolution, open systems, open-source software vulnerabilities, user convenience, ease of Internet access, global users, advertisements, business needs, and the global market. We investigate common cybersecurity vulnerabilities and find that the bare machine computing (BMC) paradigm is a possible solution to address and eliminate their root causes at many levels. We study 22 common cyberattacks, identify their root causes, and investigate preventive mechanisms currently used to address them. We compare conventional and bare machine characteristics and evaluate the BMC paradigm and its applications with respect to these attacks. Our study finds that BMC applications are resilient to most cyberattacks, except for a few physical attacks. We also find that BMC applications have inherent security at all computer and information system levels. Further research is needed to validate the security strengths of BMC systems and applications.

LINGPASS: An approach for multilingual passphrase generation by integrating English and Tamil

AbstractIn today's world of ever‐increasing cyber threats, safeguarding digital accounts is paramount. Traditional passwords are often vulnerable to brute force attacks and can be easily guessed, leading to a shift towards passphrases. However, using monolingual passphrases can pose several challenges, such as lack of diversity, predictability, memorability, and accessibility. To address this issue, this paper presents a model called LINGPASS, short for Language INtegrated Graph‐based PASSphrase, which generates multilingual passphrases by combining English and Tamil languages. The proposed approach is implemented as a web application for user convenience, and the entropy of the passphrase is evaluated using Shannon entropy. The LINGPASS model generates higher entropy passphrases than existing multilingual passphrase generators, increasing the security of digital accounts. By integrating two languages, LINGPASS increases the entropy of the passphrase by approximately 72%, making it less vulnerable to dictionary attacks. Additionally, the copy/paste functionality reduces typing errors, making it more user‐friendly.

A Comparative Analysis of Static and Dynamic Wireless Charging Systems for Electric Vehicles

The movement to electric vehicles (EVs) is central to sustainable transportation and necessitates improvements in effective and easy charging devices. This article compares static and dynamic wireless charging systems for electric vehicles, focusing on their operation, feasibility, and practical applications. Static charging involves inductive power transfer when the vehicle is parked, while dynamic charging allows power transfer while the vehicle is in motion. The paper explores efficiency, infrastructure needs, cost implications, and user convenience, highlighting potential benefits and challenges. The findings aim to inform stakeholders in the automotive and energy sectors about optimal wireless charging strategies for enhancing electric vehicle adoption.

Assessing and Enhancing Movement Quality Using Wearables and Consumer Technologies: Thematic Analysis of Expert Perspectives.

Improvements in movement quality (ie, how well an individual moves) facilitate increases in movement quantity, subsequently improving general health and quality of life. Wearable technology offers a convenient, affordable means of measuring and assessing movement quality for the general population, while technology more broadly can provide constructive feedback through various modalities. Considering the perspectives of professionals involved in the development and implementation of technology helps translate user needs into effective strategies for the optimal application of consumer technologies to enhance movement quality. This study aimed to obtain the opinions of wearable technology experts regarding the use of wearable devices to measure movement quality and provide feedback. A secondary objective was to determine potential strategies for integrating preferred assessment and feedback characteristics into a technology-based movement quality intervention for the general, recreationally active population. Semistructured interviews were conducted with 12 participants (age: mean 42, SD 9 years; 5 males) between August and September 2022 using a predetermined interview schedule. Participants were categorized based on their professional roles: commercial (n=4) and research and development (R&D; n=8). All participants had experience in the development or application of wearable technology for sports, exercise, and wellness. The verbatim interview transcripts were analyzed using reflexive thematic analysis in QSR NVivo (release 1.7), resulting in the identification of overarching themes and subthemes. Three main themes were generated as follows: (1) "Grab and Go," (2) "Adjust and Adapt," and (3) "Visualize and Feedback." Participants emphasized the importance of convenience to enhance user engagement when using wearables to collect movement data. However, it was suggested that users would tolerate minor inconveniences if the benefits were perceived as valuable. Simple, easily interpretable feedback was recommended to accommodate diverse audiences and aid understanding of their movement quality, while avoiding excessive detail was advised to prevent overload, which could deter users. Adaptability was endorsed to accommodate progressions in user movement quality, and customizable systems were advocated to offer variety, thereby increasing user interest and engagement. The findings indicate that visual feedback representative of the user (ie, an avatar) should be used, supplemented with concise text or audible instructions to form a comprehensive, multimodal feedback system. The study provides insights from wearable technology experts on the use of consumer technologies for enhancing movement quality. The findings recommend the prioritization of user convenience and simplistic, multimodal feedback centered around visualizations, and an adaptable system suitable for a diverse audience. Emphasizing individualized feedback and user-centric design, this study provides valuable findings around the use of wearables and other consumer technologies to enhance movement quality among the general population. These findings, in conjunction with those of future research into user perspectives, should be applied in practical settings to evaluate their effectiveness in enhancing movement quality.