Adaptive Interface Research Articles

Технология сквозной разработки мобильных приложений для людей с ограниченными интеллектуальными возможностями

The features of developing mobile applications for users with intellectual disabilities are examined. A technology for developing mobile applications is proposed, utilizing a template multi-module architecture that allows for the selection of ready-made functional solutions from a module repository. A method for developing an adaptable mobile applica-tion interface is described, including the creation of screen templates with interface elements, categorizing template elements into mandatory and optional, and matching each element with sets of possible images. A web system is out-lined that supports the stages of creating and operating mobile applications with an adaptable interface. Examples of developed mobile applications demonstrate their effectiveness for users with intellectual disabilities. A method is pro-posed for adapting the mobile application interface using a configuration panel, which supports the life cycle of mobile applications for this user category. An ontology was selected as a formal model for representing knowledge, enabling the extraction of knowledge for developing mobile applications with an adaptable interface and applying it to create applications accessible to people with intellectual disabilities.

Knowledge-based approach to adaptive XR interface design for non-programmers

Knowledge-based approach to adaptive XR interface design for non-programmers

Instant interaction driven adaptive gaze control interface

Gaze estimation is long been recognised as having potential as the basis for human-computer interaction (HCI) systems, but usability and robustness of performance remain challenging . This work focuses on systems in which there is a live video stream showing enough of the subjects face to track eye movements and some means to infer gaze location from detected eye features. Currently, systems generally require some form of calibration or set-up procedure at the start of each user session. Here we explore some simple strategies for enabling gaze based HCI to operate immediately and robustly without any explicit set-up tasks. We explore different choices of coordinate origin for combining extracted features from multiple subjects and the replacement of subject specific calibration by system initiation based on prior models. Results show that referencing all extracted features to local coordinate origins determined by subject start position enables robust immediate operation. Combining this approach with an adaptive gaze estimation model using an interactive user interface enables continuous operation with the 75th percentile gaze errors of 0.7∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ $$\\end{document}, and maximum gaze errors of 1.7∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ $$\\end{document} during prospective testing. There constitute state-of-the-art results and have the potential to enable a new generation of reliable gaze based HCI systems.

A Comparative Evaluation of the Share-VDE Search System

The Share-VDE search system (https://svde.org) shifts the library discovery paradigm from record-based indexing and retrieval to that of linked data entity exploration. This paper reports the results of iterative testing of multiple versions of the Share-VDE interface. The testing included remote user experience (UX) interviews with a total of twenty participants across four rounds of tests spanning 2 years. The comparison among participants encompassed catalogers, students of all levels, and faculty. Synthesizing IFLA Library Reference Model user tasks with interface evaluation methods supported the qualitative inquiry into how linked data systems in general, and BIBFRAME specifically, can support search system objectives.

Robust and durable superlubricity enabled by carboxylated graphene quantum dots in lubricated steel contacts

Achieving macroscale superlubricity on engineering steel by utilizing aqueous green lubricants has gained growing interest, given its substantial potential to reduce energy consumption and carbon footprint. However, maintaining superlubricity under diverse sliding conditions over a prolonged duration is a major obstacle for real-scale applications. Herein, we report that a robust and durable tribofilm enabled by a unique lubrication mechanism based on carboxylated graphene quantum dots (CGQDs) in aqueous glycerol triggers macroscale superlubricity in self-mated steel contacts. A dedicated intermittent test was designed to show the superlubricity's robustness and the ability of the tribofilm to adapt to a variety of relevant sliding conditions. Moreover, the boundary film provides an average coefficient of friction of around 0.007 and up to 69 % wear reduction (compared to the base lubricant), resulting in the maintenance of superlubricity at a real final contact pressure of 123 MPa, which increases the upper limit of the contact pressure compared to current aqueous-lubricated steel contacts. The new superlubricity mechanism was enabled by the chemical adsorption of the CGQDs onto the worn metal surface, coupled with the tribo-induced structural degradation and transformation of the CGQDs into layered graphitic structures that generate an adaptable low-shear interface. This work provides new insights into the role of chemical adsorption and structural transformation of CGQDs in achieving superlubricity and is an important step forward for implementing energy-efficient and green lubrication technologies for industrial applications.

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.

Research on Intelligent Application Design Based on Artificial Intelligence and Adaptive Interface

Research on Intelligent Application Design Based on Artificial Intelligence and Adaptive Interface

When Do Users Prefer Voice Control Systems in Vehicles? A Survey of Chinese Drivers

Voice control systems (VCSs) are becoming increasingly common in modern vehicles, but concerns are still expressed by drivers about adopting them in smart cockpits. Previous research on privacy and recognition accuracy may not fully address users’ needs with regard to VCSs. In addition, studies on the safety impacts of different interaction modalities may not reveal drivers’ preference for interaction modalities, given that driver choice may not be solely based on interaction safety. Thus, to better understand and optimize VCSs design, an online survey was conducted in China to investigate drivers’ choices between VCSs and manual interaction. In total, we analyzed 168 drivers’ preferred interaction modality (i.e., either VCSs or manual interaction) in different scenarios defined by passenger presence (i.e., present versus absent), traffic complexity (i.e., low versus high traffic density), roadway type (i.e., urban road versus highway), and task characteristics (i.e., six in-vehicle interaction tasks). Compared with manual interactions, drivers preferred VCSs when driving alone, driving on highways, and driving in complex traffic. Further, drivers preferred VCSs when in-vehicle tasks were more distracting and time-demanding (e.g., compiling a text message). The preference for interaction modalities could also be affected by the characteristics of drivers: those with lower driving frequencies and higher VCSs familiarity and those who perceived higher VCSs usability tended to choose VCSs as an interaction modality for in-vehicle interaction tasks. These findings offer insights for adaptive interface design and future optimization of VCSs.

Performance analysis of a gas turbine engine via intercooling and regeneration- Part 2

Abstract The current study aims to amplify the predictive ability of the numerical model developed for a gas turbine engine-based power plants by process of regeneration and intercooling. Artificial neural networks (ANN) and adaptive neuro-fuzzy interface systems (ANFIS) are the two techniques mainly concentrated in this study which were not properly implemented previously. The performance parameters namely, specific power (SP), thermal efficiency (η), and enthalpy based specific fuel consumption (EBSFC) of a Turboprop engine were predicted using thermodynamic parameters namely, pressure ratio (PR), nozzle pressure ratio (NPR), turbine inlet temperature (TIT), for constant regeneration (R), and intercooling (E) efficiencies. The results showed that a high regression result R 2 of 0.9831 and 0.9899 was found for the ANFIS model for η for training and testing, respectively. Also, the ANFIS model resulted in best performance of the performance characteristics when compared to ANN.

AirMouse and AirWrite Intuitive Digital Interaction

The primary purpose of this project is to redefine the way people will interact with their systems more easily, and this will be achieved by eliminating the touchpads and keyboards to connect to the computer. This cutting-edge system eliminates the need for a regular mouse or a keyboard, allowing for easier device user-interface adaptation. The implementation of the latest gesture recognition technology lets the system not only pick up and decipher the movements of users' hands but also translate them into wider operations that are similar to those of a mouse and keyboard. Central to the design of the metaphoric system is the "virtual mouse," which enables the cursor movement and the performance of various mouse buttons without touching anything physically. So, it is a virtual mouse with an on-the-screen cursor that reacts to hand gestures in real-time. The system utilizes certain hand gestures enough to enable the effortless execution of actions commonly associated with a traditional mouse including left-clicking, right-clicking, and dragging across the screen. The virtual mouse feature is enhanced by the air writing technique, commonly acknowledged as a milestone in input development. This capability precisely reads and decodes the movements developed in the space by the fingertips while conveying them to the screen as written words. The air writing system would predict the characters from the user's gestures, creating a fresh, secure, and user-friendly method that favors the option of air typing rather than relying on a physical keyboard. This project brings innovation in human-computer interaction when implemented using powerful computer vision and machine learning techniques and promotes accessibility and usability of the system where the traditional inputs become inapplicable. On the other hand, its feasible justifications range from medical uses to pioneering in virtual reality, gaming, and education that drives brilliantly the new options in interaction across various fields.

Design and application of a new type of switchable semi-closed sputum suction device for transfer

Sputum suction is a necessary measure to remove respiratory secretions and collect sputum specimens, and the traditional sputum suction device includes open and closed methods. However, the open sputum suction device can easily cause sputum splashing during operation, polluting the operator and the surrounding environment. The closed sputum suction device is more expensive than the open sputum suction device. Although it can be used repeatedly, the friction between the protective sleeve and the wall of the suction tube increases after repeated uses, which in turn affects the operation. In addition, the two sputum suction methods need to be connected to a sputum collector when the sputum specimen is collected. This process can easily lead to leakage and contamination of specimens, and at the same time increase the infection risk for patients. In order to overcome the above problems, the medical staff from the department of critical care medicine of the First Affiliated Hospital of Dalian Medical University invented a new type of switchable semi-closed sputum suction device, and obtained the National Utility Model Patent of China (ZL 2020 2 1564712.3). The device is composed of a suction device connection port, a sliding negative pressure switch, an adapter interface, a pipe body, a transparent film protective sleeve, a clip-on connection joint, and a sputum collector. The sliding negative pressure switch at the connection port of the suction device can realize one-person one-handed operation. The sputum collector is connected with the sputum suction device to ensure that the specimen is not exposed. The transparent film protective sleeve covers the sputum suction tube body to ensure that the whole process of sputum suction operation is pollution-free. The clip-on connection joint is connected with the artificial airway interface to avoid sputum splashing during sputum suction, and it is clamped immediately after operation to reduce environmental pollution. Compared with the existing sputum suction device, the new switchable semi-closed sputum suction device has a more reasonable design and lower cost, which is worthy of clinical promotion.

Chatbot Based Online Shopping Web Application

This study presents an innovative chatbot system aimed at transforming product recommendation and customization. It integrates feature-based input analysis and user-driven updates to provide tailored product recommendations. Users can input specific product features, leading to personalized suggestions that align precisely with their preferences. Utilizing a dynamic customization framework, the chatbot consistently refines recommendations based on user interests, ensuring a personalized and evolving user experience. The project seeks to reshape the realm of product recommendation systems by providing a seamless and adaptable interface, enhancing the exploration and acquisition of products that precisely match individual needs and preferences.

Mobile User Interface Adaptation Based on Usability Reward Model and Multi-Agent Reinforcement Learning

Today, reinforcement learning is one of the most effective machine learning approaches in the tasks of automatically adapting computer systems to user needs. However, implementing this technology into a digital product requires addressing a key challenge: determining the reward model in the digital environment. This paper proposes a usability reward model in multi-agent reinforcement learning. Well-known mathematical formulas used for measuring usability metrics were analyzed in detail and incorporated into the usability reward model. In the usability reward model, any neural network-based multi-agent reinforcement learning algorithm can be used as the underlying learning algorithm. This paper presents a study using independent and actor-critic reinforcement learning algorithms to investigate their impact on the usability metrics of a mobile user interface. Computational experiments and usability tests were conducted in a specially designed multi-agent environment for mobile user interfaces, enabling the implementation of various usage scenarios and real-time adaptations.

Experimentation at the WTO lab: towards a better ‘Interface’ to accommodate State-owned enterprises

Abstract This article advocates for a more inclusive and adaptable interface mechanism at the World Trade Organization (WTO), specifically tailored to address the nuanced dynamics of State-Owned Enterprises (SOEs). It revisits the foundational ‘Interface Theory’ by John H. Jackson, a cornerstone in shaping initial WTO rules for non-market economies. Drawing upon the critiques of David Kennedy, this article identifies three key limitations inherent in the existing interface theory. It then delves into a critical examination of the regulations pertaining to SOEs within the frameworks of the Trans-Pacific Partnership / the Comprehensive and Progressive Agreement for Trans-Pacific Partnership, arguing that these models inadequately address the complexity of state participation in the economy, with a particular focus on non-market economies like China. This article suggests leveraging the WTO as a global policy laboratory, a forum for the exploration and discussion of varied national strategies concerning SOE management. It posits China’s mixed-ownership reform as an exemplary starting point for such experimental endeavours.

Prediction of colour strength in environmentally‐friendly dyeing of polyester fabric with madder using supercritical carbon dioxide

AbstractThe textile industry is one of the significant reasons for global water pollution, with dyeing processes being particularly environmentally detrimental. Researchers have explored alternative approaches to address this issue, such as using natural dyes, supercritical fluids and so forth. In addition to environment‐friendly approaches, reducing the number of experiments in studies, accurate production straightaway and using artificial intelligence (AI), one of the technologies of the present and the future that will provide significant support. Reaching clearer results with AI technology will not necessarily contribute to environment‐friendly technologies. However, AI techniques, including artificial neural networks (ANNs) and adaptive neuro fuzzy interface system (ANFIS) were employed to predict the colour strength (K/S) of the dyed fabric based on process parameters. A comprehensive experimental design involving pressure, temperature, and time variations was conducted, and the results were analysed using multi‐factor analysis of variance (MANOVA). The study demonstrates that supercritical carbon dioxide (scCO2) dyeing with madder on polyester fabric is a promising and environmentally friendly approach. Additionally, the optimised ANN and ANFIS models, aided by genetic algorithms (GAs), exhibit high predictive accuracy (less than 3%), providing insights into the impact of process parameters on colour strength. This research underscores the potential of AI‐driven automation in textile dyeing, offering solutions for dye formula prediction, colour matching, and defect detection, reducing the need for human intervention in these processes.

Simplifying Multimodal Clinical Research Data Management: Introducing an Integrated and User-friendly Database Concept.

Clinical research, particularly in scientific data, grapples with the efficient management of multimodal and longitudinal clinical data. Especially in neuroscience, the volume of heterogeneous longitudinal data challenges researchers. While current research data management systems offer rich functionality, they suffer from architectural complexity that makes them difficult to install and maintain and require extensive user training. The focus is the development and presentation of a data management approach specifically tailored for clinical researchers involved in active patient care, especially in the neuroscientific environment of German university hospitals. Our design considers the implementation of FAIR (Findable, Accessible, Interoperable, and Reusable) principles and the secure handling of sensitive data in compliance with the General Data Protection Regulation. We introduce a streamlined database concept, featuring an intuitive graphical interface built on Hypertext Markup Language revision 5 (HTML5)/Cascading Style Sheets (CSS) technology. The system can be effortlessly deployed within local networks, that is, in Microsoft Windows 10 environments. Our design incorporates FAIR principles for effective data management. Moreover, we have streamlined data interchange through established standards like HL7 Clinical Document Architecture (CDA). To ensure data integrity, we have integrated real-time validation mechanisms that cover data type, plausibility, and Clinical Quality Language logic during data import and entry. We have developed and evaluated our concept with clinicians using a sample dataset of subjects who visited our memory clinic over a 3-year period and collected several multimodal clinical parameters. A notable advantage is the unified data matrix, which simplifies data aggregation, anonymization, and export. THIS STREAMLINES DATA EXCHANGE AND ENHANCES DATABASE INTEGRATION WITH PLATFORMS LIKE KONSTANZ INFORMATION MINER (KNIME): . Our approach offers a significant advancement for capturing and managing clinical research data, specifically tailored for small-scale initiatives operating within limited information technology (IT) infrastructures. It is designed for immediate, hassle-free deployment by clinicians and researchers.The database template and precompiled versions of the user interface are available at: https://github.com/stebro01/research_database_sqlite_i2b2.git.

Using Eye-Tracking for Adaptive Human-Machine Interfaces for Pilots: A Literature Review and Sample Cases

This paper explores the potential of eye-tracking technology in adaptive human-machine interfaces for pilots in aviation. We argue that an interface able to adjust its layout and elements based on pilots’ real-time eye-tracking data can prevent errors and enhance their performance. The study presents a literature review on the use of eye-tracking for various pilot cases, including flight simulator games, drone pilots, and cockpit pilots. Results in most cases showed that eye-tracking has been employed to improve interactions, enhance spatial awareness, guide pilots’ gaze to relevant areas, and provide insights into pilots’ information processing and task load. The paper discusses two sample cases demonstrating the potential of eye-tracking in adaptive human-machine interfaces. In the first case, during challenging drone simulations, eye-tracking identified areas where an adaptive human-machine interface could aid navigation and reduce cognitive load. In the second one, based on real drone flights, when signal loss incidents occurred, eye-tracking data showed that the interface should adapt to pilots’ needs by providing critical information to help them to improve situational awareness. The paper concludes that eye-tracking technology has significant potential in adaptive human-machine interfaces for aviation, emphasising the importance of refining these technologies to meet pilots’ specific needs and enhance flight safety.

Influence of Bioceramic Cements on the Quality of Obturation of the Immature Tooth: An In Vitro Microscopic and Tomographic Study.

The present in vitro study focuses on the filling ability of three different bioceramic cements with or without the addition of a bioceramic sealer in an open apex model on the marginal apical adaptation, tubule infiltrations, and void distributions as well as the interface between the cement and the sealer materials. To this end, sixty mandibular premolars were used. MTA-Biorep (BR), Biodentine (BD), and Well-Root Putty (WR) were used to obturate the open apex model with or without the addition of a bioceramic sealer, namely TotalFill® BC sealer™ (TF). A digital optical microscope and scanning electron microscope (SEM) were used to investigate the cement-dentin interface, marginal apical adaptation, and the material infiltration into the dentinal tubules. Micro-computed X-ray tomography and digital optical microscopy were used to investigate the cement-sealer interface. The results were analyzed by using the Kruskal-Wallis test. No significant difference was found between the groups for the marginal apical adaptation quality (p > 0.05). Good adaptation of the dentin-cement interface was found for all tested groups and the sealer was placed between the cement material and dentinal walls. All the groups demonstrated some infiltrations into the dentinal tubules at the coronal part except for the BR group. A good internal interface was found between the cement and the sealer with the presence of voids at the external interface. A larger number of voids were found in the case of the BD-TF group compared to each of the other two groups (p < 0.05). Within the limitations of the present in vitro study, all the groups demonstrated good marginal apical adaptation. The use of a sealer in an open apex does not guarantee good filling and, in addition, creates voids at the external interfaces with the dental walls when the premixed sealer is used with powder-liquid cement systems. The use of a premixed bioceramic cement could offer fewer complications than when a powder-liquid cement system is used.

Development of Online NAS Application User Guide Website using NextJS 13 and REST API to Enhance User Understanding

This research focuses on developing a user guide for the Nusantara Certification Application System (NAS) through an online platform, utilizing NextJS 13 technology and REST API to enhance comprehensive understanding and optimal utilization of NAS features. The implementation of NextJS 13 ensures a responsive and adaptive interface, while the REST API optimizes speed and smooth access to required data. Through a combination of structured video tutorials and information sources in PDF format, the objective of this guide is to provide comprehensive insight into each feature offered within the NAS application. Research findings confirm the success of integrating NextJS 13 technology and REST API, significantly enhancing understanding and efficiency in NAS application use. The primary role of this implementation lies in aiding users to deeply comprehend and optimize the benefits of the NAS application while expediting access to necessary information. In conclusion, the utilization of cutting-edge technology in user guide development has proven to have a positive impact by broadening user insights into the application and enhancing productivity and efficiency in its use. This underscores the significance of employing advanced technology in delivering information to modern application users.

An ASER AI/ML expert panel formative user research study for an interpretable interactive splenic AAST grading graphical user interface prototype.

The AAST Organ Injury Scale is widely adopted for splenic injury severity but suffers from only moderate inter-rater agreement. This work assesses SpleenPro, a prototype interactive explainable artificial intelligence/machine learning (AI/ML) diagnostic aid to support AAST grading, for effects on radiologist dwell time, agreement, clinical utility, and user acceptance. Two trauma radiology ad hoc expert panelists independently performed timed AAST grading on 76 admission CT studies with blunt splenic injury, first without AI/ML assistance, and after a 2-month washout period and randomization, with AI/ML assistance. To evaluate user acceptance, three versions of the SpleenPro user interface with increasing explainability were presented to four independent expert panelists with four example cases each. A structured interview consisting of Likert scales and free responses was conducted, with specific questions regarding dimensions of diagnostic utility (DU); mental support (MS); effort, workload, and frustration (EWF); trust and reliability (TR); and likelihood of future use (LFU). SpleenPro significantly decreased interpretation times for both raters. Weighted Cohen's kappa increased from 0.53 to 0.70 with AI/ML assistance. During user acceptance interviews, increasing explainability was associated with improvement in Likert scores for MS, EWF, TR, and LFU. Expert panelists indicated the need for a combined early notification and grading functionality, PACS integration, and report autopopulation to improve DU. SpleenPro was useful for improving objectivity of AAST grading and increasing mental support. Formative user research identified generalizable concepts including the need for a combined detection and grading pipeline and integration with the clinical workflow.