Graphical User Interface Design Research Articles

A Developed Graphical User Interface-Based on Different Generative Pre-trained Transformers Models

Objective: The article investigates the integration of advanced Generative Pretrained Transformers (GPT) models into a user-friendly Graphical User Interface (GUI). The primary objective of this work is to simplify access to complex Natural Language Processing (NLP) tasks for a diverse range of users, including those with limited technical background. Method: The development process of the GUI was comprehensive and systematic: Needs Assessment: This stage involved understanding the requirements and expectations of potential users to ensure the GUI effectively addresses their needs. Preliminary Design and Development: The initial designs were created and developed into a functional GUI, emphasizing the integration of features supporting various NLP tasks like text summarization, translation, and question-answering. Iterative Refinement: Continuous improvements were made based on user feedback, focusing on enhancing user experience, ease of navigation, and customization capabilities. Results: The developed GUI successfully integrated GPT models, including GPT-4 Turbo and GPT-3.5, resulting in an intuitive and adaptable interface. It demonstrated efficiency in performing various NLP tasks, thereby making these advanced language processing tools accessible to a broader audience. The GUI's design, emphasizing user-friendliness and adaptability, was particularly noted for its ability to cater to both technical and non-technical users. Conclusion: In conclusion, the article illustrates the significant impact of combining advanced GPT models with a Graphical User Interface to democratize the use of NLP tools. This integration not only makes complex language processing more accessible but also marks a pivotal step in the inclusive application of AI technology across various domains. The successful implementation of the GUI highlights the potential of AI in enhancing user interaction and broadening the scope of technology usage in everyday tasks.

The influence of Graphical User Interfaces on human-computer interaction and the impact of organizing software on decision-making process

The necessity for effective information management has grown crucial due to the widespread availability and utilization of electronic devices and software systems. Organizational software provides a solution by enhancing efficiency and reducing cognitive burden. Graphical User Interfaces (GUIs) play a crucial role in facilitating the interaction between humans and computers in the domain of software design. This study employs a comprehensive literature review to examine the fundamental concepts underlying efficient GUI design and the current trends in organizing software interfaces. The text presents a GUI concept that has been designed for the purpose of organizing software in order to address complex decision-making scenarios. The model offers a graphical representation of a framework that may be used to analyze various elements influencing decision-making. This study sheds light on the potential of Organizing Software to enhance cognitive processes. However, there is a need for additional enhancements in integrating user connectivity and intelligent algorithms. In general, the study emphasizes the significance of user-centric GUI design in improving the effectiveness of Organizing Software.

Simplistic Graphic User Interface Design for Rendering Blockchain Data (A Case Study of Educational Administrative Domain)

Blockchain data is characterized by encryption which is usually aimed at securing the data itself from getting into wrong hands. However, this limits the readability of the data when there is a need to. Clarity and understanding are essential indicators of a usable system as a complex but functioning system is of no value to the user if the data are not presented in a simple readable format. A Graphic User Interface (GUI) with a simplistic design is presented to solve this problem by rendering only necessary blockchain data while considering supplementary details that are usually hidden. 5 blockchain scenarios are created for this purpose. The activities and potential data involved are clearly stated. The raw blockchain data on a high level are recorded in form of JavaScript Object Notification (JSON). Attention is given to supplementary details from the raw blockchain data while translating them into graphical form. Results were presented in three different forms (raw blockchain data, complex GUI, and the simplistic GUI) to different categories of users and their comments were compared and analyzed. Since human computer interaction is an essential factor in user’s readability, the GUI rendered in this work is an enhancement to the blockchain technology as seen in the result which shows the simplistic GUI as the best understood interface even by a novice among the three.

Investigating the effects of nudges to promote knowledge-sharing behaviours on MOOC forums: a mixed method design

ABSTRACT Knowledge-sharing in forums is an integral part of many MOOCs (Massive Open Online Courses). However, forum usage for knowledge-sharing in MOOCs is often inadequate. This study adopts a mixed-methods approach to investigate problems behind MOOC learners’ problematic forum participation and propose real-time sharing-quality-monitoring mechanisms to mitigate the problems. We explore different designs and implementation of computerised nudges to enhance knowledge contribution, considering challenges such as vast data, user aversion to AI monitoring, and complex user interactions. Through testing graphical (Model A), numerical (Model B), and textual message (Model C) interface designs, we found that graphical and numerical designs were most effective in improving performance. However, Model C received conflicting judgments, with some users feeling controlled by the AI while others found algorithmic guidance valuable. Our findings shed light on leveraging computerised nudges for meaningful contributions and address concerns related to AI monitoring. The complex nature of user interactions, behaviours, and the abundance of data present significant challenges that require innovative approaches. This study contributes to understanding the issues in MOOC forum participation and provides insights into effective computerised nudges. We discuss directions for refining the current design, emphasising the need for more design science research in this domain.

ONE HUNDRED NAZI SCREENS: INTERFACES AND THE STRUCTURE OF U.S. WHITE NATIONALIST DIGITAL NETWORKS ON TELEGRAM

The “Alt-Right,” a white nationalist online coalition, has collapsed amidst a revolution in digital governance termed the “regulatory turn.” Nevertheless, the regulatory turn remains incomplete because white nationalists utilize graphical user interface (GUI) design to subvert public stewardship. Why have some former Alt-Right platforms collapsed while others have grown despite increased scrutiny? The field’s account is currently limited to social media networks and rooted in positivist methods, lending a static conception of white nationalist networks that is slow to recognize cultural shifts. This paper fills the gap by comparatively critiquing the interfacing affordances of Telegram, an instant messaging app that functions as an "ideological safe harbor" for U.S. white nationalists with content aggregation, blogging, and activist use-cases. I apply interface critique to index how the manipulation of graphical user interfaces allows white nationalists to frame their browsing as a technology of mastery over and against the regulatory turn. I argue that Telegram networks coopt the enclave public, exploiting an ideology of decentralization to mystify the leverage held by white nationalist developers over their users. This occlusion redirects white masculine anxieties against publicity to justify an intensified racist fanaticism and the exportation of violence against racial, religious, and gendered outsiders. White interfacing frames GUI design as a capitalist technology that weaponizes the racist and sexist logic of the “average user” to secure the reproduction of reactionary platforms. This project furthers Internet research by developing a theory of the interface as an ideological mirror of production.

An Improved Algorithm for Optical Character Recognition using Graphical User Interface Design

An Improved Algorithm for Optical Character Recognition using Graphical User Interface Design

Interaction Design and Research for User Interfaces of Central Bank Digital Currency: An Empirical Study

There is already a consensus among central banks to accelerate the development of Central Bank Digital Currencies (CBDC). To facilitate a smooth money transfer process, the interactive experience of the CBDC user interface design is very important. However, much of the current research has focused on the technical feasibility of the CBDCs, and no scientific research has yet attempted to design an effective CBDC user interface. In this study, a series of CBDC user interfaces were designed to help study the interaction process of CBDCs in a simulated payment transaction context with a focus on the user interface and interactive experience of the CBDCs. The experiment in this study was a 2 (graphical metaphor) × 3 (gesture type) × 2 (visual feedback) mixed factorial design in which a total of 12 CBDC prototypes were created and evaluated based on users’ task performance and a series of subjective evaluations. The results of our empirical study revealed that graphical metaphor user interface design can improve the interface usability and subjective evaluation of CBDCs, and may also trigger the user’s sense of experience with traditional banknotes. Specifically, the use of animated cues for currency movement on the CBDC user interface may help evoke the user’s experience of using cash. In addition, we found that the wave type gesture may cause users to spend more time completing the CBDC operational tasks. Moreover, the animated cue of money moving may have faster performance and a higher degree of rationality. The above-mentioned results may provide an important design reference for CBDC developers to create easy-to-use CBDC services.

A novel code generator for graphical user interfaces

Graphical user interfaces (GUIs) are widely used in human–computer interaction, providing a convenient interface for operation. Automating the conversion of GUI design images into source code can significantly reduce the coding workload for front-end developers. Detecting elements in GUI images is a key challenge in achieving automatic GUI code generation and is crucial for tasks such as GUI automation and testing. However, current state-of-the-art methods do not fully consider the unique characteristics of GUI images and elements, and they lack the required high localization accuracy, resulting in low detection accuracy for GUI element boxes. In this paper, we propose GUICG, an automatic GUI code generator that combines deep neural networks with image processing techniques to efficiently detect GUI elements from GUI images and generate front-end code. We empirically investigate various deep learning approaches and image processing methods for GUI component detection. Based on a comprehensive understanding of their performance and characteristics, we design GUICG by fusing image processing with a deep learning-based target detection model, achieving state-of-the-art performance. GUICG outperforms existing methods in accuracy and F1 score for component detection tasks, while producing human-readable code with a logical structure. Furthermore, we conduct an ablation study to quantitatively assess the impact of each key element in GUICG.

Users’ Visual Experience During Temporal Navigation in Forecast Weather Maps on Mobile Devices

This study investigated the impact of graphical user interface (GUI) design on the efficiency and effectiveness of map-based tasks on mobile devices, using time-based weather data as a case study. Three different GUI designs (button-type, circle-type, and slidebar) were tested in a between-subjects design, with 50 participants completing a set of map-based tasks on each GUI design. The results showed that GUI design significantly affected the effectiveness of map-based tasks. Participants performed better at tasks involving the search for the highest and lowest temperature amplitudes on the button-type GUI whereas the circle-type GUI showed lower effectiveness for tasks involving the search for day temperatures. Analysis of the visual attention distribution based on fixation count revealed that different GUI designs led to different patterns of visual attention. The study highlights the importance of considering GUI design in the development of mobile map applications, particularly for map-based tasks involving time-based data. The study shows that separating the date from the time navigation panel reduces necessary visual focus on the GUI itself and is a valuable insight for future GUI design.

Investigating the rendering capability of embedded devices for graphical-user-interfaces in mobile machines

Abstract This paper focuses on the alignment of Graphical-User-Interface (GUI) applications and embedded devices. The main contribution is a benchmark approach that enables measuring and comparing the GUI rendering capability of embedded devices and provides a performance-oriented GUI design recommendation for an embedded device. The benchmark is tailored to common GUI applications and resource-limited devices, which are usually mounted in mobile machines. GUI applications can only be rendered smoothly if these devices have sufficient performance. A general benchmark concept is described and modeled in Unified Modeling Language (UML) at first, followed by a prototypical implementation and evaluation. It is demonstrated that the benchmark approach is applicable to GUI applications with different levels of complexity as well as embedded devices of different performance classes.

User-centered design in mobile human-robot cooperation: consideration of usability and situation awareness in GUI design for mobile robots at assembly workplaces

Abstract Mobile cobots can increase the potential for assembly work in industry. For human-friendly automation of cooperative assembly work, user-centered interfaces are necessary. The design process regarding user interfaces for mobile human-robot cooperation (HRC) shows large research gaps. In this article an exemplary approach is shown to design a graphical user interface (GUI) for mobile HRC at assembly workplaces. The design is based on a wireframe developed to support situation awareness. An interactive mockup is designed and evaluated. This is done in two iterations. In the first iteration, a user analysis is carried out using a quantitative survey with n = 31 participants to identify preferred input modalities and a qualitative survey with n = 11 participants that addresses touch interfaces. The interactive mockup is developed by implementing design recommendations of the usability standards ISO 9241 – 110, 112 and 13. A heuristic evaluation is conducted with n = 5 usability experts and the measurement of situation awareness with n = 30 end users. In the second iteration, findings from the preceding iteration are implemented in the GUI and a usability test with n = 20 end users is conducted. The process demonstrates a combination of methods that leads to high usability and situation awareness in mobile HRC.

MINIMALISM IN DESIGN: A TREND OF SIMPLICITY IN COMPLEXITY

Minimal design is an approach to communicate a concept in a simple manner. The goal of the minimalist design is to remove unnecessary components from an image. With the intention of grabbing consumers attention, minimizing clutter and seeming elegant, this type of visual design emphasizes on having just the most significant components of the design effortlessly prominent. Minimalism seeks to understand the core of things, emphasizing on a simple way of dealing with complexity. This paper offers a conceptual foundation for the minimalism design trend and elaborates on the creative philosophy that underlies it, as well as its influences, applications, implications, and multiple perspectives. The influence of minimalism on graphic design, user interface and web design are also discussed in the paper.

TriSigEM: Un modelo semiótico para la evaluación de interfaces gráficas de usuario de apps

The percentage of user acceptance and adoption of some apps needs to be improved. The reasons for this issue are multifactorial. This research observed usability problems in implementing the Graphical User Interface (GUI) Design Patterns. As a result, we design and implement TriSigEM (Peirce’s Triad of Signs Evaluation Model), a hierarchical model capable of guiding an evaluator in observing the GUI’s signs: Index, Icon, and Symbol. TriSigEM can help us improve GUI’s implementation and, even- tually, the app’s functionalities. Also, we made a comparative analysis of TriSigEM with related works reported in the literature. This analysis shows that TriSigEM surpasses other models. Moreover, we highlighted that the analyzed GUI patterns need specifications on the Triad of Signs.

Hybrid machine learning-based model for predicting chloride ion concentration in coral aggregate concrete and its ethically aligned graphical user interface design

The chloride ion concentration distribution in coral aggregate concrete (CAC-CC) holds significant importance for evaluating CAC performance, assessing rebar corrosion, and understanding chloride ion diffusion. Thus, this study employs hybrid machine learning algorithms to establish predictive models for CAC-CC under three environmental conditions (salt spray zone, tidal zone, and underwater zone) and evaluates the accuracy and generalization ability of these models. The results demonstrate that the genetic algorithm-optimized support vector regression (GA-SVR) model provides predictions closer to the actual values, exhibiting smoother error fluctuations. The GA-SVR model also exhibits smaller mean and standard deviation in the residual distribution. Furthermore, the GA-SVR model excels in five performance evaluation metrics, with R2, MAE, MAPE, MSE, and RMSE values of 0.986, 1.25e-2, 3.24e-2, 0.276e-3, and 1.66e-2, respectively. Hence, the GA-SVR model emerges as the optimal choice for CAC-CC prediction. Additionally, this work utilizes Shapley Additive Explanations (SHAP) to assess the contribution of eight features. The analysis reveals that the water-binder ratio and the pre-wetted water to total water ratio are the two most critical features. Moreover, an increase in the pre-wetted water to total water ratio and a decrease in the water-cement ratio hinder chloride ion diffusion. Mechanistic analysis of the feature contribution to CAC-CC is further explored in this study. Based on the GA-SVR model, a graphical user interface for CAC-CC has been developed, enabling visualization of CAC-CC predictions. This research introduces a novel approach to optimize CAC performance and predict chloride ion concentration, laying the foundation for CAC application in reef construction.

The effect of lightness, chroma, and hue on depth perception

AbstractColor coding of the graphical user interface (GUI) is effective in cognitive tasks, especially searching and identifying target stimuli from a crowded GUI. The perceived color depth on a flat GUI is a critical feature in mapping the stratification of information. In color science, the visual phenomena of advancing and receding colors provide the perceived depth needed for GUI design. The experiment used a series of color pairs as experimental samples to observe the phenomenon of depth perception caused by colors and obtain the judgment of the perception of color depth. This study developed a best‐fit regression model to predict the perceived color depth. The study found that the higher the lightness, the higher the chroma, and the closer the hue is to 33° (reddish color), the colors tend to be the advancing colors; the lower the lightness, the lower the chroma, and the closer the hue is to 213° (blue‐greenish color), the colors tend to be the receding colors.

Engaging Multidisciplinary Clinical Users in the Design of an Artificial Intelligence-Powered Graphical User Interface for Intensive Care Unit Instability Decision Support.

Critical instability forecast and treatment can be optimized by artificial intelligence (AI)-enabled clinical decision support. It is important that the user-facing display of AI output facilitates clinical thinking and workflow for all disciplines involved in bedside care. Our objective is to engage multidisciplinary users (physicians, nurse practitioners, physician assistants) in the development of a graphical user interface (GUI) to present an AI-derived risk score. Intensive care unit (ICU) clinicians participated in focus groups seeking input on instability risk forecast presented in a prototype GUI. Two stratified rounds (three focus groups [only nurses, only providers, then combined]) were moderated by a focus group methodologist. After round 1, GUI design changes were made and presented in round 2. Focus groups were recorded, transcribed, and deidentified transcripts independently coded by three researchers. Codes were coalesced into emerging themes. Twenty-three ICU clinicians participated (11 nurses, 12 medical providers [3 mid-level and 9 physicians]). Six themes emerged: (1) analytics transparency, (2) graphical interpretability, (3) impact on practice, (4) value of trend synthesis of dynamic patient data, (5) decisional weight (weighing AI output during decision-making), and (6) display location (usability, concerns for patient/family GUI view). Nurses emphasized having GUI objective information to support communication and optimal GUI location. While providers emphasized need for recommendation interpretability and concern for impairing trainee critical thinking. All disciplines valued synthesized views of vital signs, interventions, and risk trends but were skeptical of placing decisional weight on AI output until proven trustworthy. Gaining input from all clinical users is important to consider when designing AI-derived GUIs. Results highlight that health care intelligent decisional support systems technologies need to be transparent on how they work, easy to read and interpret, cause little disruption to current workflow, as well as decisional support components need to be used as an adjunct to human decision-making.

GUILGET: GUI Layout GEneration with Transformer

Sketching out Graphical User Interface (GUI) layout is part of the pipeline of designing a GUI and a crucial task for the success of a software application. Arranging all components inside a GUI layout manually is a time-consuming task. In order to assist designers, we developed a method named GUILGET to automatically generate GUI layouts from positional constraints represented as GUI arrangement graphs (GUIAGs). The goal is to support the initial step of GUI design by producing realistic and diverse GUI layouts. The existing image layout generation techniques often cannot incorporate GUI design constraints. Thus, GUILGET needs to adapt existing techniques to generate GUI layouts that obey to constraints specific to GUI designs. GUILGET is based on transformers in order to capture the semantic in relationships between elements from GUI-AG. Moreover, the model learns constraints through the minimization of losses responsible for placing each component inside its parent layout, for not letting components overlap if they are inside the same parent, and for component alignment. Our experiments, which are conducted on the CLAY dataset, reveal that our model has the best understanding of relationships from GUI-AG and has the best performances in most of evaluation metrics. Therefore, our work contributes to improved GUI layout generation by proposing a novel method that effectively accounts for the constraints on GUI elements and paves the road for a more efficient GUI design pipeline.

Analysis and Comparison of Weibull Parameters for Wind Energy Potential Using Different Estimation Methods: A Case Study of Isparta Province in Turkey

In this study, the success of the numerical methods and a metaheuristic algorithm in parameter estimation of Weibull distribution, which is frequently used in wind energy applications, are compared. Numerical methods are Justus empirical method, moment method, graphical method, energy pattern factor method (EPM), energy trend method, maximum likelihood estimation method (MLE). The metaheuristic algorithm is manta ray foraging optimization method (MRFO). The wind data used in the study were recorded hourly in the Isparta region in the southwest of Turkey. A graphical user interface design has been made to easily perform the calculations in this study. The success of the methods was tested with four different statistical error analysis methods. According to the results of the analysis, the MRFO method was by far the most successful method. EPM and MLE methods were the most unsuccessful methods.

Graphical user interface design to improve understanding of the patient-reported outcome symptom response.

Symptom monitoring application (SMA) has clinical benefits to cancer patients but patients experience difficulties in using it. Few studies have identified which types of graphical user interface (GUI) are preferred by cancer patients for using the SMA. This is a cross-sectional study aimed to identify preferred GUI among cancer patients to use SMA. Total of 199 patients were asked to evaluate 8 types of GUIs combining text, icon, illustration, and colors using mixed-methods. Subgroup analyses were performed according to age and gender. The mean age of the patients was 57 and 42.5% was male. The most preferred GUI was "Text + Icon + Color" (mean = 4.43), followed by "Text + Icon" (mean = 4.39). Older patients (≥ 60 years) preferred "Text + Icon" than younger patients (p for interaction < 0.01). Simple and intuitive text and icons were the most useful GUI for cancer patients to use the SMA. Simple and intuitive text and icons were the most useful GUI for cancer patients to use the SMA. Researchers need to be careful when applying realistic face drawings to cancer symptom monitoring applications because they can recall negative images of cancer.

Design and Development of a Macro to Compare Sections of Planes to Parts Using Programming with Visual Basic for Applications in CATIA

This article presents an application for educational purposes in the field of engineering graphics, which corrects the dihedral projections of the sections of a plane for a part by comparing the solution provided by the student with that obtained through 3D CAD modelling software. Said application is generated as a macro in CATIA (Computer-Aided Three-Dimensional Interactive Application), which is included as a tool in the ‘Part Design’ module. The code of this macro is written in the CATVBA language, utilizes the CATIA internal editor, and takes advantage of the capabilities offered by Visual Basic for Applications (VBA) in the design of Graphical User Interfaces (GUI). The operation of the macro consists of obtaining the section in the 3D CAD model, projecting it onto three dihedral projections of the part (elevation, plan, and profile), and calculating the visible and hidden lines by means of a numerical process based on dividing the lines into discrete sections. Likewise, to obtain numerical results, the section obtained in CATIA (reference section) is compared with the section provided by the student (section that needed to be corrected) by means of a spreadsheet (Microsoft Excel). The data of the coordinates of the points of the reference section are exported to said spreadsheet as is the data of the coordinates of the section that needed to be corrected, which is contained in a file with a dxf format (Drawing eXchange Format). From these data, by programming the appropriate formulae in the cells of the spreadsheet, the numerical values of the errors are obtained, thereby locating said errors in the dihedral projections of the section which needed to be corrected. Likewise, the application can be programmed to compare the central symmetry of both of the sections.