Graphics System Research Articles

“Us versus Them”: is the voice of the community heard when planning communication screening programmes for preschoolers?

ObjectivesCommunity consultation is necessary to ensure the uptake and use of community-based screening intervention to detect early childhood disabilities, as its absence can result in poor service acceptance and usage. To document stakeholders' perspectives regarding planning a community-based communication disorder (an impairment in the ability to receive, send, process and comprehend concepts or verbal, non-verbal and graphic symbol systems) screening programmes for pre-schoolers. Study designThis qualitative research design used purposive and random sampling to recruit 46 participants from eThekwini Municipality, South Africa. These stakeholders consisted of caregivers/parents of children who underwent screening for communication disorders, People who are Deaf, their parents, early childhood development practitioners, health professionals and government officials involved with children with disabilities. All participants were adults aged between 19 and 79 years, with an average age of 39.7 years. MethodsData was collected through focus group discussions and individual interviews, which were thematically analysed. ResultsThe four emergent themes were screening approaches, methods, location and personnel. Service users expected greater access to screening and reliable tests to identify problems by trained personnel at sites within the community. Service providers preferred a targeted approach to screening with parental input. Task shifting and sharing were seen as a solution to address staff shortages and provide services at health facilities, as resource constraints made it challenging to provide outreach services. ConclusionStakeholder engagement revealed diverging views between service users and providers, with implications for programme provision and uptake. There is a need for ongoing, inclusive discussion to ensure consensus during the planning stage, in order to render services that address issues of equity and accessibility for people with disabilities in marginalised communities.

Visual Lock - Enhancing Security with Visual Password

The prevailing method of user authentication commonly involves the submission of a text-based password along with a username. However, this approach has inherent drawbacks that have been widely acknowledged. A significant challenge is the difficulty users face in remembering passwords, leading to the adoption of short and simplistic ones, which in turn renders them susceptible to easy guessing or hacking. To address these concerns, this article introduces a novel financial graphical password authentication system. The operational details are elucidated through real-world examples, emphasizing key features of the system. In response to the limitations of conventional text-based password authentication, a groundbreaking financial graphical password method is proposed in this article. The prevailing issue of users resorting to short and easily guessable passwords due to memory constraints is addressed through this innovative approach. The article not only explains the functioning of the new system using real-world instances but also underscores its crucial features that enhance security in user authentication

On determining of the protograph features based on the graphic-orthographic systems of manuscripts

This article is concerned with the study of medieval manuscripts and the determining of the features of protographs based on the graphic and orthographic systems of their scribal copies. The study involves three manuscripts created in Nuremberg in the 15th century. The texts of the mentioned manuscripts are copies from the first two complete translations of one of the medieval treatises. Based on the study of the graphic and orthographic systems of these texts, as well as some of their morphological features, the author of the article makes an attempt to establish the relationship between the texts under study, as well as to restore some of the features of their protographs. The sources of influence on the formation of the graphic and orthographic portrait of the scribe were identified as a result of the study of the graphic and orthographic features of the texts. Among them the author identifies the written tradition of the scriptorium, features of the local dialect and dialect areas, as well as characteristic features of the protograph. A separate group includes such a source of variability as the individual preferences of the scribe. Analysis of the graphic and orthographic portrait of each of the scribes who participated in the creation of the texts under study allows us to determine the approximate time and place of creation of the protograph, as well as changes characteristic of each stage of conscious processing of the text. As a result of the study, a diagram was drawn up that clearly demonstrates the relationships between the texts under study.

Improving the Usability of Graphical Authentication Systems Using Subject-Based Images

Recognition based graphical authentication systems rely on a system user’s ability to recognize previously chosen images and use those images to gain access into a computing systems, devices or application. Recognition based systems that utilise several types of images have been developed and studied. The déjà vu scheme depends on the use of abstract (meaningless) images. Images in the déjà vu scheme have no exact meaning. This scheme has also been actively studied. This article presents a between user study conducted on two recognition-based schemes using system prototypes. The Abstract Based Graphical Authentication (ABGA) was designed to simulate the déjà vu scheme. The performance of this system was compared with the performance of a novel system developed for this research. The novel system, called Subject Based Graphical Authentication (SBGA), in which the system used images from the various disciplines of the research participants. The researcher conducted a lab-based study with 100 participants, 50 participants for each of the prototypes. The study investigated the impact of using subject based images to enhance the usability and security of recognition-based graphical passwords. Two graphical models were thus developed and presented to the 100 participants, which comprised of staff and students from the departments of Computer Science, Mathematics, and Engineering. In the experiments, participants selected their graphical passwords from sets of images representing their various disciplines. The researcher observed that the memorability rate for graphical passwords consisting of subject based images aligned with participants' disciplines surpassed the rate for passwords with purely abstract images. The results indicated 81.7% successful login rate and 18.3% failure rate for Subject Based Graphical Authentication (SBGA). In contrast, Abstract Based Graphical Authentication (ABGP) exhibited a 51.5% successful login rate and a 48.7% failure rate. The findings provide significant insights for graphical password designers and developers seeking to enhance system memorability. Balancing image familiarity with security considerations can lead to more user-friendly and effective recognition-based authentication systems. This study provides valuable insights into the benefits of incorporating familiar images in recognition-based graphical passwords, showcasing a significant improvement in memorability and user authentication success. The findings underscore the importance of considering the user’s familiarity with portfolio images in the design of graphical authentication systems.

New Test to Detect Clustered Graphical Passwords in Passpoints Based on the Perimeter of the Convex Hull

This research paper presents a new test based on a novel approach for identifying clustered graphical passwords within the Passpoints scenario. Clustered graphical passwords are considered a weakness of graphical authentication systems, introduced by users during the registration phase, and thus it is necessary to have methods for the detection and prevention of such weaknesses. Graphical authentication methods serve as a viable alternative to the conventional alphanumeric password-based authentication method, which is susceptible to known weaknesses arising from user-generated passwords of this nature. The test proposed in this study is based on estimating the distributions of the perimeter of the convex hull, based on the hypothesis that the perimeter of the convex hull of a set of five clustered points is smaller than the one formed by random points. This convex hull is computed based on the points that users select as passwords within an image measuring 1920 × 1080 pixels, using the built-in function convhull in Matlab R2018a relying on the Qhull algorithm. The test was formulated by choosing the optimal distribution that fits the data from a total of 54 distributions, evaluated using the Kolmogorov–Smirnov, Anderson–Darling, and Chi-squared tests, thus achieving the highest reliability. Evaluating the effectiveness of the proposed test involves estimating type I and II errors, for five levels of significance α∈{0.01,0.02,0.05,0.1,0.2}, by simulating datasets of random and clustered graphical passwords with different levels of clustering. In this study, we compare the effectiveness and efficiency of the proposed test with existing tests from the literature that can detect this type of pattern in Passpoints graphical passwords. Our findings indicate that the new test demonstrates a significant improvement in effectiveness compared to previously published tests. Furthermore, the joint application of the two tests also shows improvement. Depending on the significance level determined by the user or system, the enhancement results in a higher detection rate of clustered passwords, ranging from 0.1% to 8% compared to the most effective previous methods. This improvement leads to a decrease in the estimated probability of committing a type II error. In terms of efficiency, the proposed test outperforms several previous tests; however, it falls short of being the most efficient, using computation time measured in seconds as a metric. It can be concluded that the newly developed test demonstrates the highest effectiveness and the second-highest efficiency level compared to the other tests available in the existing literature for the same purpose. The test was designed to be implemented in graphical authentication systems to prevent users from selecting weak graphical passwords, enhance password strength, and improve system security.

Monge Surfaces. Generation, Discretisation and Application in Architecture

AbstractThis paper describes a revision of so-called Monge surfaces through using digital graphic tools, based on the synthetic conception exposed by Gaspard Monge in the 18th and 19th centuries, through their geometric relation with polar surface. As a starting point, we propose a graphical system that integrally solves the generation of these kind of surfaces, their rationalization and discretization, with the objective of their specific application in architecture. The geometric system described allows the generation of a type of surface in which the pair of curves -generatrix and directrix- give rise to the network of principal lines of curvature (LCP) of the final surface. In this way, we propose a process that follows a bottom-up generative system based on Monge surfaces, which offers wide possibilities of formal exploration, while imposing geometrical-constructive properties that are very useful in fabrication and assembly processes.

Advancements and Integration in Computer Vision and Graphics Systems

Advancements and Integration in Computer Vision and Graphics Systems

Graphical Arduino IDE system with wiring layout and flowchart functions for physical computing education

AbstractArduino, a widely used tool for physical computing, is favored for its affordability and easy availability. However, a drawback for beginners is the requirement of prior knowledge of C programming language and circuit theory for effectively utilizing Arduino. In this research, we address this issue by developing a Graphical Arduino IDE system that allows users to control Arduino without the need for prior knowledge of C language and circuit theory. Users can create node graph‐based scripts in the Wiring Tab of the Graphical Arduino IDE and develop flowchart‐based scripts in the Algorithm Tab. The scripts created in the Wiring Tab serve as guidelines for wiring, thus preventing users from making wiring mistakes. Additionally, users without knowledge of C language can control Arduino by creating flowchart‐based scripts in the Algorithm Tab. The finalized scripts are converted into Arduino code and uploaded to the Arduino board using the built‐in Code Upload feature. Finally, a paired t test was conducted between the Graphical Arduino IDE and Scratch for Arduino, confirming that the Graphical Arduino IDE required fewer user inputs.

Arctic tern-optimized weighted feature regression system for predicting bridge scour depth

This paper presents a pioneering artificial intelligence (AI) solution – the Arctic Tern-Optimized Weighted Feature Least Squares Support Vector Regression (ATO-WFLSSVR) system to aid civil engineers in accurately predicting scour depth at bridges. This prediction system amalgamates the strengths of hybrid models by uniting a metaheuristic optimization algorithm with weighted features and least squares support vector regression (WFLSSVR). The metaheuristic algorithm concurrently optimizes all hyperparameters of constituent WFLSSVR models, resulting in a highly effective system. Validation involves a comprehensive assessment using two case studies, which include datasets of scour depths across various complexities and pier foundation types. Comparative analyses against single AI models, conventional ensemble models, hybrid techniques, and empirical methods demonstrate that ATO-WFLSSVR's reliability outperforms others in performance evaluation metrics. Specifically, for the field dataset, ATO-WFLSSVR achieves MAPE and R values of 20.92% and 0.9435, respectively, and for scour depth data at complex pier foundations, it records MAPE and R values of 6.49% and 0.9384, respectively. The automated predictive analytics underscore the robustness, efficiency, and stability of ATO-WFLSSVR compared to existing methods. This study's notable contributions include the development of an innovative optimization algorithm named Arctic Terns Optimizer (ATO), proficiency in solving high-dimensional optimization problems, and the creation of a user-friendly graphical interface system, a promising tool for civil engineers to estimate scour depth at bridges. Further testing and evaluation of ATO-WFLSSVR across diverse datasets encompassing more complex scenarios are recommended. The data and source code for this study are currently accessible at https://www.researchgate.net/profile/Jui-Sheng-Chou/publications.

Iris: a multi-constraint graphic layout generation system

Iris: a multi-constraint graphic layout generation system

TRANSFORMASI DIGITAL : APLIKASI CANVA SEBAGAI MEDIA PEMBELAJARAN YANG INOVATIF DAN KOLABORATIF DALAM PENDIDIKAN SD/MI

ABSTRACT The digital transformation has brought comprehensive changes across variousdomains, one of which is the realm of education. One digital innovation that can be utilized inteaching is the Canva application, a graphic design system offering various features and templates that are use friendly for creating various type visual learning materialsto create different types of visual materials.The use of Canva in elementary (SD) and Islamic elementary schools (MI) can serve as an innovative and collaborative medium, thus enhancing the quality of education. The objective of this research is to explore the implementation of Canva in learning media in SD/MI and analyze its impact on student engagement an learning outcomes. Literature review is the method employd in this study, with the integration of Canva into the curriculum, aiming to create a more dynamic and enjoyable learning environment.

Creation of a visually graphical quality management system of the Etalon enterprise in the aviation industry

Creation of a visually graphical quality management system of the Etalon enterprise in the aviation industry

Multi-Factor Authentication: A User Experience Study

Usability issues prevent multi-factor authentication (MFA) systems from being widely used, despite the fact that they are essential for improving security measures. This study explores the problems with MFA systems' usability and suggests possible fixes to enhance the user experience. The study emphasizes the value of good design while highlighting the efficacy of graphical password systems as a user-friendly substitute for conventional MFA techniques. The report also makes recommendations for future research directions, such as assessing resilience against complex assaults, improving support for mobile applications, and weighing the benefits and drawbacks of image-based authentication systems. Comprehensive user research and assessments can yield important insights to improve the effectiveness and usability of different MFA approaches. Additionally, a two-way image-based mobile device authentication system devices is introduced in the article, demonstrating improved login success rates and security threat resistance. In order to further enhance the authentication process, future development will focus on scalability, user input surveys, and bolstering system security. Keywords: Multi-Factor Authentication (MFA), User Experience (UX), Security, Usability, Graphical Passwords, Biometric Authentication, Mobile Devices, Image- Based Authentication, Psychological Aspects, Resilience,Scalability, Advanced Security Features

Architecture of Graphics System with 3D Acceleration Support for Embedded Operating Systems

Architecture of Graphics System with 3D Acceleration Support for Embedded Operating Systems

Application of Cell Penetrating Peptides for Intracellular Delivery of Endostatin: A Computational Approach.

Endostatin is an antiangiogenic compound with anticancer activity. The poor stability and low half-life of endostatin are the main barriers to the clinical use of this protein. Cell-penetrating peptides (CPPs) are extensively applied as carrier in the delivery of drugs and different therapeutic agents. Therefore, they can be proper candidates to improve endostatin delivery to the target cells. In this study, we aim to computationally predict appropriate CPPs for the delivery of endostatin. Potential appropriate CPPs for protein delivery were selected based on the literature. The main parameters for detection of best CPP-endostatin fusions, including stability, hydrophobicity, antigenicity, and subcellular localization, were predicted using ProtParam, VaxiJen, and DeepLoc-1.0 servers, respectively. The 3D structures of the best CPP-Endostatin fusions were modeled by the I-TASSER server. The predicted models were validated using PROCHECK, ERRAT, Verify3D and ProSA-Web servers. The best models were visualized by the PyMol molecular graphics system. Considering the principal parameters in the selection of best CPPs for endostatin delivery, endostatin fusions with four CPPs, including Cyt c-ss-MAP, TP-biot1, MPGα, and DPV1047, high stability and hydrophobicity, no antigenicity and extracellular localization were predicted as the best potential fusions for endostatin delivery. Four CPPs, including Cyt c-ss-MAP, TP-biot1, MPGα, and DPV1047, were predicted as the best potential candidates to improve endostatin delivery. Application of these CPPs may overcome the limitation of endostatin therapeutic applications, including poor stability and low half-life. Subsequent experimental studies will contribute to verifying these computational results.

Introducing CASUX: A Standardized Scale for Measuring the User Experience of Artificial Intelligence Based Conversational Agents

Conversational agents are growing in popularity, and as such they must provide a good user experience and meet the needs of the users. Yet, how to measure the user experience in the conversational AI scenario remains an open and urgent question to be solved, which may hinder further empirical studies on human-agent interactions. In fact, there have been very few studies that explore how users perceive interacting with these conversational agents, which is important to ensure their sustainability. Accordingly, in this work, we used a subjective technique by following a measurement approach to develop a standardized measurement instrument/scale called the Conversational Agent Scale for User Experience. In terms of the methodology, we used a mixed-method approach involving an iterative process spanning across six different user studies (three qualitative and three quantitative) at different points of time for the purpose of dimension identification, item generation and subsequent item refinements. As a part of the qualitative studies we conducted a Systematic Literature Review, semi-structured interviews with users of conversational agents, and expert interviews. For the quantitative studies a lab-based experiment was performed for the pre-test, followed by two online surveys as a part of pilot testing and scale development. The qualitative studies initially identified a total of 13 distinct user experience dimensions and 418 measurement items. Finally, the Exploratory Factor Analysis as a part of the main survey resulted in 9 user experience dimensions (practicality perception, proficiency, humanness, sentiment, robustness, etiquette & mannerism, personality, anthropomorphism, and ease of use) and 34 measurement items. This was supplemented by conducting another Confirmatory Factor Analysis for establishing the reliability and validity of the proposed scale, together with checking the model-fit indices. All the 9 dimensions had sufficient validity, and a reasonable level of statistical reliability. Some of the user experience dimensions like humanness, personality, anthropomorphism, and etiquette & mannerism show the uniqueness of the conversational AI scenario from the traditional usage factors used commonly while evaluating graphical user interface-based systems. This work fills the gap of a lack of research on how to classify and measure the conversational experience of users and provides a reference for practitioners and designers in developing these agents and continuously improving the usage experience.

A Survey on Graphical Password Strategy Authentication

In an ever-evolving digital realm, ensuring the security and reliability of software applications has become increasingly crucial. The continuous advancement of technology also brings about more complex cyber threats, emphasizing the urgent need to identify and address vulnerabilities. In response to this growing imperative, we introduce "Graphical Password Authenticator: A Novel Approach to Secure User Authentication." The Graphical Password Authenticator reimagines the conventional user authentication process by utilizing graphical elements and innovative techniques. It provides a secure and user-friendly alternative to traditional text-based passwords, offering enhanced protection against unauthorized access. By incorporating graphical images, patterns, or other visual cues, users can create unique and memorable authentication credentials that are difficult for malicious actors to compromise. This approach offers a more intuitive and engaging way for users to access their accounts while significantly reducing the risk of password-related security breaches. The Graphical Password Authenticator system ensures robust security through a combination of graphical recognition and encryption technologies. It is designed to be resistant to common attack methods such as brute force and keyloggers, providing a higher level of protection for user accounts and sensitive information. This novel approach to user authentication fosters a secure and user-centric environment, making it a promising solution for the ever-evolving digital landscape. The Graphical Password Authenticator is a groundbreaking step at the intersection of user authentication and innovation. By redefining the way users prove their identity through memorable graphical elements, this approach empowers users with a more secure and intuitive means of accessing their digital resources. This paradigm shift in authentication methods showcases the potential of technology to enhance user security and create a safer digital future, ultimately bridging the gap between user convenience and robust cybersecurity. Keywords: Graphical Password Authenticator, User Authentication, Cybersecurity, Digital Security, Encryption Technologies, User-Centric Approach, Brute Force Resistance, Keyloggers Protection.

A Research on Graphical Password Strategy Authentication

In an ever-evolving digital realm, ensuring the security and reliability of software applications has become increasingly crucial. The continuous advancement of technology also brings about more complex cyber threats, emphasizing the urgent need to identify and address vulnerabilities. In response to this growing imperative, we introduce "Graphical Password Authenticator: A Novel Approach to Secure User Authentication." The Graphical Password Authenticator reimagines the conventional user authentication process by utilizing graphical elements and innovative techniques. It provides a secure and user-friendly alternative to traditional text-based passwords, offering enhanced protection against unauthorized access. By incorporating graphical images, patterns, or other visual cues, users can create unique and memorable authentication credentials that are difficult for malicious actors to compromise. This approach offers a more intuitive and engaging way for users to access their accounts while significantly reducing the risk of password-related security breaches. The Graphical Password Authenticator system ensures robust security through a combination of graphical recognition and encryption technologies. It is designed to be resistant to common attack methods such as brute force and keyloggers, providing a higher level of protection for user accounts and sensitive information. This novel approach to user authentication fosters a secure and user-centric environment, making it a promising solution for the ever-evolving digital landscape. The Graphical Password Authenticator is a groundbreaking step at the intersection of user authentication and innovation. By redefining the way users prove their identity through memorable graphical elements, this approach empowers users with a more secure and intuitive means of accessing their digital resources. This paradigm shift in authentication methods showcases the potential of technology to enhance user security and create a safer digital future, ultimately bridging the gap between user convenience and robust cybersecurity.

Differential privacy Kalman filtering for graphical dynamic systems: Performance improvement and privacy calibration

This paper investigates differential privacy Kalman filtering for graphical dynamic systems. An enhanced differential privacy Kalman filter is initially developed by leveraging the topology, a unique characteristic of graphical dynamic systems, to improve the filtering performance. And then upper and lower error bounds of the enhanced filter are established to evaluate the recipient's ability to infer sensitive data. Based on these error bounds, a privacy calibration guideline is provided to balance privacy and usability of sensitive data. A notable feature of the enhanced filter is that its Kalman gain matrix is a diagonal matrix, which facilitates the independent update of information at each node by reducing the coupling between nodes. This feature diminishes the accumulation of filtering errors, thereby improving the data availability for the recipient. Finally, the effectiveness of the proposed approach is verified through a simulation of epidemiological data analysis, and the results show that the enhanced filter performs well in systems with high privacy levels.

Design of Fast Radio Burst Signal Recognition System based on Deep Learning

In order to identify fast radio burst signals from the original observation data of FAST radio telescopes, this paper designs a fast radio burst signal recognition system based on deep learning object detection algorithm. The system uses the incoherent achromatization algorithm and the YOLO series target recognition algorithm to realize the recognition of fast radio burst signals, and provides users with a friendly graphical system interface. In view of the different performance of users' computers, the system has the function of selecting different algorithm models. Experiments have proved that the system achieves 86% recall and 83% accuracy in the FRB20201124A real-world data test set.