Users Face Research Articles

Survey Analysis on Secured user Authentication through Biometric Recognition

Secured user authentication is the process of verifying the user authenticity. Biometric authentication is the human identification system employed to match the biometric characteristics of user for verifying the authenticity. Biometric identifiers are exclusive, making it harder to hack accounts using them. Common types of biometrics comprise the fingerprint scanning verifies authentication based on a user's fingerprints Face recognition and voice recognition are employed in real-time application for improving the security level in different application scenarios. Face recognition is a method of identifying or verifying the individual identity using their face expression. Voice recognition is the ability of machine to receive and interpret the dictation to understand. Many researchers carried out their research on different face and voice recognition methods. But, recognition accuracy was not improved with minimum time consumption by existing biometric recognition method. In this research, different recognition methods are reviewed using biometric recognition method for user authentication. The recognition methods are efficiently on human faces dataset with respect to performance metrics like recognition accuracy, error rate, and recognition time.

AppleGo: React Js (Web Application)

Abstract: In today's digital landscape, users face the inconvenience of visiting multiple platforms to hunt for the best prices on Apple devices. However, "AppleGo" aims to be the solution to this problem. This innovative platform consolidates listings of nearby shops on a single platform, enabling users to effortlessly compare and discover the most favorable prices for their desired devices. "AppleGo" is a groundbreaking online platform designed to revolutionize the way users find Apple devices from nearby shops. It eliminates the need for physically searching multiple stores by offering a comprehensive list of available devices, complete with the best discounts. Users can conveniently identify the ideal option without the hassle of in-person visits. This platform also empowers local Apple shop owners, facilitating easy registration and the showcasing of services and packages to potential customers. By enhancing visibility and expanding their customer reach, "AppleGo" aids shop owners in growing their businesses. In essence, the platform bridges the gap between users and shop owners, creating a win-win solution that saves time and effort for users and boosts business prospects for local shops.

USABILITY EVALUATION OF SATUSEHAT APPLICATION USING USABILITY TESTING METHOD

SatuSehat is an application created and developed by the government of the Republic of Indonesia with the aim of controlling and tracking the spread of Coronavirus Disease (Covid-19). SatuSehat application has a main feature, namely location tracking, which requires community participation as users to report each other's locations when they travel. This aims to track the location and history of contact with people with Covid-19. However, in its use and implementation, users face various problems such as slow and difficult to understand application responses, unclear information, and frequent application problems that suddenly close. This research was conducted to evaluate the usability value of the SatuSehat application. The research method used was the SUS method by giving a questionnaire consisting of 10 questions related to the SatuSehat application to 38 respondents in the initial study. Based on this research, 7 improvement recommendations were obtained which were then implemented in the SatuSehat application. The final result shows an average value of 61.7 (Grade D). After calculating the usability value of each respondent, the final result is 61.7 (Grade D).

USER EXPERIENCE ANALYSIS OF THE CANVA APPLICATION USING THE SYSTEM USABILITY SCALE (SUS) METHOD.

The Canva Design application has gained popularity among users seeking to design graphics and visual content. However, users face challenges such as difficulty finding features, slow performance, unclear user interface, and functional issues. This research aims to identify and analyze these problems through User Experience and System Usability Scale (SUS) analysis. The findings provide valuable insights to Canva's development team to address weaknesses and improve usability. This research serves as a foundation for enhancing the quality and user-friendliness of the Canva application to meet the evolving needs and expectations of users.

The political use of encrypted messaging applications: Evidence from southeast Asia and its implications for the global public sphere

Global Internet users face rising challenges with well-organized disinformation and propaganda campaigns. Scholars have studied this challenge by examining political communication over social media platforms including Facebook, YouTube, and X (formerly Twitter). Much less work has examined the manipulative political role of encrypted messaging applications (EMAs), despite their massive popularity around the world. Our research examines EMAs as elements of the global public sphere through 16 qualitative interviews with people who design and track propaganda campaigns online in three ASEAN nations: Indonesia, Myanmar, and the Philippines. Interviewees report that: 1) politicians and political groups harness EMAs in coordinated efforts to inorganically amplify their own agendas; 2) disinformation proliferates on EMAs, but civil society works to address this; and, 3) while citizens see the encrypted aspect of EMAs as powerful for civic engagement, they also feel it presents unique barriers to addressing what has become a serious problem with disinformation on EMAs.

SAS-HRM: Secure Authentication System for Human Resource Management

To guarantee data confidentiality and information sensitivity, human resource management requires secure systems. In the field of authorization and dependability in recognizing and identifying persons, facial recognition has grown in importance. In this research, a secure authentication system is proposed based on biometric aspects of the user's face and identifying it using the CNN classification model is provided to give access to human resource management and update data. The system is divided into four major stages: First, set up the system environment, beginning with smart cards, card readers, Arduino, and so on. Second, after undergoing pre-treatment steps, the facial characteristics are extracted using LDA. Third, create a high-accuracy CNN model to recognize and classify the user's face among the system's users. Finally, the user is allowed to enter the system and update his information. When compared to the accuracy of classification using machine learning techniques with a CNN proposed model, the accuracy of the model with LDA was up to 100%. K-NN has 91%, while TD has 94%.

Investigating Security Folklore: A Case Study on the Tor over VPN Phenomenon

Users face security folklore in their daily lives in the form of security advice, myths, and word-of-mouth stories. Using a VPN to access the Tor network, i.e., Tor over VPN, is an interesting example of security folklore because of its inconclusive security benefits and its occurrence in pop-culture media. Following the Theory of Reasoned Action, we investigated the phenomenon with three studies: (1) we quantified the behavior on real-world Tor traffic and measured a prevalence of 6.23%; (2) we surveyed users' intentions and beliefs, discovering that they try to protect themselves from the Tor network or increase their general security; and (3) we analyzed online information sources, suggesting that perceived norms and ease-of-use play a significant role while behavioral beliefs about the purpose and effect are less crucial in spreading security folklore. We discuss how to communicate security advice effectively and combat security misinformation and misconceptions.

YouTube online videos as a source for patient education of cervical spondylosis—a reliability and quality analysis

BackgroundGiven a prolonged course of Cervical spondylosis (CS) could cause irreversible neurological deficits, it is crucial to disseminate CS-related health information to the public to promote early diagnosis and treatment. YouTube has been widely used to search for medical information. However, the reliability and quality of videos on YouTube vary greatly. Thus, this study aimed to assess the reliability and educational quality of YouTube videos concerning CS and further explore strategies for optimization of patient education.MethodsWe searched YouTube online library for the keywords “cervical spondylosis”, “cervical radiculopathy” and “cervical myelopathy” on January 15, 2023. Ranked by “relevance”, the first 50 videos of each string were recorded. After exclusions, a total of 108 videos were included. All videos were extracted for characteristics and classified based on different sources or contents. Two raters independently evaluated the videos using Journal of American Medical Association (JAMA) benchmark criteria, Modified DISCERN (mDISCERN) tool, Global Quality Scale (GQS) and Cervical-Spondylosis-Specific Scale (CSSS), followed by statistical analyses. All continuous data were described as median (interquartile range).ResultsAll videos had median values for JAMA, mDISCERN, GQS and CSSS scores of were 3.00 (1.00), 3.00 (2.00), 2.00 (1.00) and 7.00 (8.88), respectively. There were significant differences in VPI (P = 0.009) and JAMA (P = 0.001), mDISCERN (P < 0.001), GQS (P < 0.001) and CSSS (P < 0.001) scores among different sources. Videos from academic source had advantages in reliability and quality scores than other sources. VPI (P < 0.001), mDISCERN (P = 0.001), GQS (P < 0.001) and CSSS (P = 0.001) scores also significantly differed among videos of various contents. Spearman correlation analysis indicated VPI was not correlated with either reliability or quality. Multiple linear regression analysis showed a longer duration and an academic source were independent predictors of higher reliability and quality, while a clinical source also led to the higher video quality.ConclusionsThe reliability and educational quality of current CS-related videos on YouTube are unsatisfactory. Users face a high risk of encountering inaccurate and misleading information when searching for CS on YouTube. Longer duration, source of academic or clinician were closely correlated to higher video reliability and quality. Improving the holistic reliability and quality of online information requires the concerted effort from multiple parties, including uploaders, the platform and viewers.

Why do people use telecentres in the age of mobile technologies? Answers from Malawi

AbstractTelecentres provide access to Information and Communication Technonology (ICT) services to disadvantaged communities. With the coming of mobile technologies such as smartphones, some services that telecentres provide such as internet can easily be accessed through mobile technologies. This, therefore, questions the relevance of telecentres in the age of mobile technologies. Two main questions exist: are telecentres still relevant? If yes, why do people still use telecentres in the age of mobile technologies? This paper aims at answering these questions. It also discusses the challenges that users face in using telecentres. Qualitative data were collected from telecentre users and managers of two telecentres in Malawi through focus groups and interviews. Gioia methodology was used to analyze the data. The study reveals four main reasons why people still patronize telecentres: (i) to socialize with fellow users; and (ii) that it is cheaper to access services in the telecentre as compared to using smartphones for the same services; (iii) telecentres provide services compatible with users' needs such as library services and computers; (iv) and to attain ICT skills some of which are applied in using smartphones. However, users face numerous challenges such as limited space within telecentres and unreliable power. The study is valuable as it provides insights into why governments should continue investing in telecentres. It also comes at a right time when the government of Malawi plans to abandon the community telecentre model to adopt the school managed model that may limit the number of users thereby limiting the benefits of telecentres in the presence of mobile technologies.

Accessible exercise for wheelchair users: comparing the usability of two adapted exercise machines

Introduction Exercise is an important occupation for wheelchair users. Limited access to adapted aerobic exercise equipment in the community and lack of knowledge on how to exercise are barriers to exercise participation among wheelchair users. To address these barriers, the adapted rower (aROW) and adapted skier (aSKI) exercise machines and educational materials were created. Purpose 1) To compare wheelchair users’ perspectives of the effectiveness and usability of the aROW and aSKI. 2) To explore perceptions of educational materials to support use of the machines. Materials and Methods A sequential, mixed-methods study design was used. Six wheelchair users trialled the machines, and completed an interview and two usability questionnaires. Qualitative data were analysed using thematic and conventional content analysis. Usability scores of both machines were compared using the Wilcoxon Signed Ranks Test. Results Data show high usability of the aROW and aSKI. More set up challenges were reported for the aROW than the aSKI. Participants perceived both machines provided effective cardiovascular workouts, and each met their exercise goals differently. Participants preferred the instructional videos over instructional sheets and provided suggestions for improving both. The Wilcoxon Signed Ranks Test showed no statistically significant difference in usability between the aROW and aSKI. Conclusion Implementing the aROW and aSKI in the community may address some equity issues that wheelchair users face by providing more aerobic exercise options. Results will inform educational material revisions to support use of the machines.

Analysis of the Inventory Management System Towards Enhanced University Service Delivery

Inventory management is an essential component of business operations including academic institutions. Using a quantitative descriptive research design, this study analyzed the processes involved in the use of the University of Baguio Requisition, Procurement, and Inventory System (UBRPIS), a software that automates inventory management by streamlining the operations required to efficiently maintain inventory and manage recording and updating records. The paper specifically determined the employees’ familiarity of the inventory management, identified the system limitations and proposed necessary adjustments and modifications. The majority of respondents are familiar with the various processes involved in the use of UBRPIS, such as the request for non-consumable items, the use of barcodes, accountability transfer, the withdrawal of condemned non-consumable items, and physical inventory of accounted non-consumable items. On the other hand, nearly half of the respondents identified limitations in the process itself, while 38.60% and 46.50% identified the location of the barcodes and the lack of non-consumable items as the primary issues, respectively. Despite respondents’ familiarity with the system, users face challenges in the processes involved in system use. It is therefore recommended that the University invests in inventory management system technology that best meets the requirements of all system users. Periodic staff training on the use of UBRPIS is likewise recommended.

Lightweight and Anonymous Group Authentication Scheme Based on PUF in the Smart Grid

&lt;p&gt;As a new generation of electricity system, smart grid significantly improves electricity services&amp;rsquo; efficiency, reliability, and sustainability. The smart meters, which are the essential terminals, help establish two-way communication between users and electricity providers. While enjoying the convenience of smart meters, users face many challenges. On the one hand, malicious adversaries could attack the smart meters and thus steal the users&amp;rsquo; privacy. On the other hand, the computational overhead of electricity data verification is high for lightweight smart meters. To address above issues, a lightweight authentication and group key management scheme is proposed. In the proposed scheme, the physical properties of the Physical Unclonable Function (PUF) are exploited to defend against external attacks from adversaries. Moreover, the Chinese Remainder Theorem (CRT) is used to broadcast the updated group keys for the legitimate smart meters in the community. In addition, the aggregated signature is utilized to reduce the overhead of the data verification. Finally, the Random Oracle Model (ROM) is used to demonstrate that the proposed scheme meets many security requirements. Performance analysis shows that the proposed scheme is more suitable for smart grid compared to previous schemes.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

The Effect of Privacy Fatigue on Privacy Decision-Making Behavior

With the rapid growth of information communication technology, internet users face constantly demands to manage privacy setting and make decisions on whether to disclose privacy data in the digital environment. Such privacy-related decisions and actions are heavily influenced by users’ level of trust, privacy concerns, perceived risks, and perceived benefits. One recently recognized factor that may impair privacy behaviors is privacy fatigue. This study will employ a within-subjects design with eye-tracking devices in which participants complete the same online decision-making task. Additionally, potential covariates, including privacy concern and digital privacy literacy, will be controlled for. We expect that higher level of baseline privacy fatigue will reveal poorer privacy decision-making outcomes, which will be represented by more frequent acceptance of online cookies. Moreover, we predict that participants’ pupil dilation, a physiological index of cognitive effort, will decrease, and privacy fatigue levels will increase over the course of the online decision-making task.

IMPLEMENTATION OF FACE RECOGNITION AND LIVENESS DETECTION SYSTEM USING TENSORFLOW.JS

Facial recognition is a popular biometric security system used to authenticate individuals based on their unique facial structure. However, this system is vulnerable to spoofing attacks where the attacker can bypass the system using fake representations of the user's face such as photos, statues or videos. Liveness detection is a method used to address this issue by verifying that the user is a real person and not a representation. This journal article focuses on the life sign method of liveness detection, which utilizes facial movements to confirm the user's existence. We implement the latest technology of artificial intelligence from TensorFlow.js using face-api.js and compare it with the GLCM algorithm. However, even with the life sign detection method, there is still a chance of bypassing the system if an attacker uses a video recording. To mitigate this, we propose the addition of an object detection system to detect the hardware used to show video recordings with ml5.js. Our face recognition and expression detection system, using the pre-trained model face-api.js, achieved an accuracy of 85% and 82.5%, respectively, and the object detection system built with ml5.js has high accuracy and is very effective for liveness detection. Our results indicate that face-api.js outperformed GLCM algorithm in detecting spoofing attempts.

NeuroBridge ontology: computable provenance metadata to give the long tail of neuroimaging data a FAIR chance for secondary use.

Despite the efforts of the neuroscience community, there are many published neuroimaging studies with data that are still not findable or accessible. Users face significant challenges in reusing neuroimaging data due to the lack of provenance metadata, such as experimental protocols, study instruments, and details about the study participants, which is also required for interoperability. To implement the FAIR guidelines for neuroimaging data, we have developed an iterative ontology engineering process and used it to create the NeuroBridge ontology. The NeuroBridge ontology is a computable model of provenance terms to implement FAIR principles and together with an international effort to annotate full text articles with ontology terms, the ontology enables users to locate relevant neuroimaging datasets. Building on our previous work in metadata modeling, and in concert with an initial annotation of a representative corpus, we modeled diagnosis terms (e.g., schizophrenia, alcohol usage disorder), magnetic resonance imaging (MRI) scan types (T1-weighted, task-based, etc.), clinical symptom assessments (PANSS, AUDIT), and a variety of other assessments. We used the feedback of the annotation team to identify missing metadata terms, which were added to the NeuroBridge ontology, and we restructured the ontology to support both the final annotation of the corpus of neuroimaging articles by a second, independent set of annotators, as well as the functionalities of the NeuroBridge search portal for neuroimaging datasets. The NeuroBridge ontology consists of 660 classes with 49 properties with 3,200 axioms. The ontology includes mappings to existing ontologies, enabling the NeuroBridge ontology to be interoperable with other domain specific terminological systems. Using the ontology, we annotated 186 neuroimaging full-text articles describing the participant types, scanning, clinical and cognitive assessments. The NeuroBridge ontology is the first computable metadata model that represents the types of data available in recent neuroimaging studies in schizophrenia and substance use disorders research; it can be extended to include more granular terms as needed. This metadata ontology is expected to form the computational foundation to help both investigators to make their data FAIR compliant and support users to conduct reproducible neuroimaging research.

The correlation between smartphone use and musculoskeletal symptom

Several issues arise from using smartphones while sitting and lying down, such as poor posture and physical discomfort. Therefore, this research aims to assess the ergonomic risk level of smartphone users and determine the correlation between self-reported musculoskeletal disorders (MSDs) and ergonomic risk level. Data were collected from 90 participants, aged 18 to 24, through video recording while seated and using a smartphone. MSDs were measured using the Modified Standardised Nordic Questionnaires (SNQ) and the Numerical Rating Scale (NRS). Rapid Upper Limb Assessment (RULA) was used to evaluate ergonomic risks in the posture of smartphone users. Furthermore, the correlation between MSDs and the ergonomic risk levels was evaluated using Chi-Square and Fisher's exact tests. Most smartphone users had RULA scores between 6 and 7 for both the left and right sides, suggesting a need for immediate investigation and improvement. The results showed a strong correlation between the right sided RULA total score and MSDs in the neck and upper back. Other results showed there was a significant correlation between RULA B and RULA D scores with neck MSDs, as well as between the RULA score of the right upper arm and MSDs in the right shoulder, and between the RULA score of the neck and MSDs in the neck. The trunk RULA score also had a significant correlation with upper back MSDs. The research showed that smartphone users face significant ergonomic risks.

얼굴추적 기술을 활용한 자동 거리 조절 스마트장치 거치대 개발

To make the use of smart devices convenient to users such as patients confined to hospital beds and persons with disabilities, a smart device cradle that can recognize the user's movement and automatically adjust the distance of the smart device is needed. In this study, we proposed to develop a cradle that can automatically adjust the position of the smart device and its distance from the user. A face tracking technology recognizing the user's face and utilizing facial features and a reservation function to automatically move the cradle as required were applied to the development. The developed and manufactured smart device cradle was able to maintain suitable distance based on the position of the user's face and move automatically for the user to easily see the smart device.

Smart Eye Tracker Control System

Abstract: Many people are physically injured or paralyzed as a result of an accident, making it impossible for them to engage in daily activities like watching TV or browsing the internet. Even after becoming paralyzed, individuals can instinctively move their eyes and use it. The primary goal of this is to address the issue of any physically challenged individuals who wish to operate freely on a computer system, without depending on any of the person for the daily activities. It is a system that is accessible for free that uses open-source software and a webcam to take pictures of the user's face and pupil before doing actions in response to their movements.

Accessibility barriers of wheelchair users in public spaces

Background: Wheelchair users encounter many barriers when traveling in public spaces. This research aims to explore the experiences wheelchair users have when facing physical and non-physical barriers in public areas. Methods: This study used qualitative research methods. Data were collected through observation and semi-structured in-depth interviews with six wheelchair users using purposive sampling. First, the data were analyzed using thematic analysis, and then the trustworthiness of the data was checked using triangulation of data sources and member checking. Results: Three themes were found. The first theme: accessibility barriers, includes two subthemes: Physical barriers; Non-physical barriers. The second theme: accessibility barrier strategies, consists of two subthemes: Physical barrier strategies; Non-physical barrier strategies. The third theme: the ability level of wheelchair users, consists of two subthemes: Level of independence; Level of incapacity. In this study, wheelchair users face accessibility when accessing public spaces. The emergence of barriers makes wheelchair users create strategies to deal with them to make public spaces more accessible for wheelchair users.

Exploring nonintrusive measurements of spatio‐temporal portrait of microservices

AbstractAs cloud native technology advances, the scale and complexity of applications built on microservice architecture continue to expand, leading to increasingly intricate differences between software within the same application. Microservice applications, offering high flexibility, are deployed in data centers as black boxes from the users' perspective, leaving them with no insight into the orchestration of cloud service providers. Consequently, users face challenges in promptly recognizing performance imbalances within their deployed applications. Meanwhile, cloud service providers may cut costs by offering a mix of qualified and unqualified services, potentially deceiving users. To enhance the understanding of microservice application organization, we propose a non‐intrusive measurement framework, termed NMPI. NMPI facilitates rapid identification of microservice application defects, offering insights into cloud services and detecting fraudulent behavior in microservice‐based applications. We model microservice applications using a queue analysis‐based approach and filter the dominant frequency components of average response time signals by employing k‐means on the fast fourier transform (FFT). Our model constructs a library of performance portraits for various software, with these portraits resembling human fingerprints that carry and mark the software's internal information. Utilizing a two‐tier microservices‐based application incorporating a database as a case study allows us to demonstrate the effectiveness of NMPI. Our experimental results show that NMPI can produce differentiable profiles of data service performance portraits across a diverse and extensive range of workloads, enabling the identification of software types and the analysis of performance conditions.