Interface Platform Research Articles

Enhancing Online Learning in Architectural Education: A Virtual Reality Enabled Experiment with Arkio

This study examines the role of Arkio, a Virtual Reality (VR) platform, in facilitating design critiques during online learning in first-year architectural design studios. This research, which was conducted in the wake of the COVID-19 pandemic and a severe earthquake that required a return to remote education, is based on the experiences of instructors who had previously adapted to online teaching during the pandemic. Arkio provides an innovative solution for the preservation of the quality of architectural education by offering an immersive, real-time environment for design feedback, which is essential in the absence of in-person studio sessions. Using a mixed-methods approach that incorporates surveys and qualitative feedback from students, the study investigates the impact of Arkio on students' understanding of architectural principles, participation in design critiques, and overall learning experience. The results suggest that Arkio was generally well-received for its ability to facilitate critiques and enhance spatial understanding. However, students encountered difficulties with the platform's interface, 3D modeling tools, and file integration. The significance of user-friendly design in educational technologies is underscored by the strong correlation between the perceived educational value of Arkio and its usability, as revealed by cross-analysis. The study identifies critical areas for improvement, despite the fact that Arkio has the potential to significantly transform the critique process in architectural education, particularly in an online setting that is influenced by external disruptions. These insights are essential for the continuous adaptation of VR-driven tools in architectural education, particularly as institutions navigate the complexities of post-pandemic and disaster-responsive teaching environments.

Optimized energy efficient reactive distillation for octane upgrading with economic and environmental considerations

Advancing fuel efficiency and production technologies can significantly reduce “Well to Wheels” and “Octane on Demand” emissions. This has been accomplished by integrating intensified technologies in fuel refineries. However, maintaining low energy consumption and high octane number while considering the impact of operating conditions under uncertainty on the process feasibility remains a challenge. Therefore, this article proposes a novel absorption heat pump reactive distillation (AHPRD). Aiming to maximize the economic potential of the AHPRD, an optimization framework that considers operating conditions under uncertainty (i.e. temperature (T), pressure (P), reflux ratio (RR), and feed stage (FS)) is developed. The optimization framework synchronizes Monte Carlo simulation and particle swarm optimization (PSO) to maximize the net present value (NPV). The framework used a hybrid Python-DWSim interface platform. The AHPRD was further investigated and compared against existing processes, namely, a conventional process refinery (CP) and reactive distillation (RD), to improve energy saving, increase financial return, and cut CO2 emissions. Attractively, the AHPRD outperforms existing processes, both economically and environmentally, doubling profit values and avoiding 52.2% − 77.4% of CO2 emissions. This study believes that the future direction will be to build an artificial intelligence model for process optimization and economic prediction.

Research On the Design of Public Transit Services for The Elderly in China

As China enters an aging society, the elderly in China are increasingly becoming an important user group of public transportation. This study uses service design thinking to optimize the inclusiveness of Chinese elderly people's travel by bus and subway, and explores the feasibility of applying service design thinking to the field of public transportation. This paper adopts the observation method, with Guangzhou and Beijing as the research areas. The researchers conduct service design research based on the entire process of elderly travel, summarize the travel needs and pain points of elderly passengers, optimize the station guidance system, intelligent interface and service platform, make the public transportation service environment more friendly, and thus make the public transportation service environment more inclusive. Analyze the passenger flow, contact points, and stakeholders of the station, draw character portraits and journey maps, and output service design strategies to improve the travel experience of Chinese elderly passengers. In summary, this study aims to improve the convenience of Chinese elderly passengers taking public transportation and provide theoretical support for the transformation and optimization of China's public transportation services.

Magnetically Integrated Tumor-Vascular Interface System to Mimic Pro-angiogenic Endothelial Dysregulations for On-Chip Drug Testing.

The tumor-vascular interface is a critical component of the tumor microenvironment that regulates all of the dynamic interactions between a growing tumor and the endothelial lining of the surrounding vasculature. In this paper, we report the design and development of a custom-engineered tumor-vascular interface system for investigating the early stage tumor-mediated pro-angiogenic dysfunctional behavior of the endothelium. Using representative endothelial cells and triple negative breast cancer cell lines, we established a biomimetic interface between a three-dimensional tumor tissue across a mature, functional endothelial barrier using a magnetically hybrid-integrated tumor-vascular interface system, wherein vasculature-like features containing a monolayer of endothelial cell culture on porous microfluidic channel surfaces were magnetically attached to tumor spheroids generated on a composite polymer-hydrogel microwell plate and embedded in a collagen matrix. Tumor-mediated endothelial microdynamics were characterized by their hallmark behavior such as loss of endothelial adherens junctions, increased cell density, proliferation, and changes in cell spreading and corroborated with endothelial YAP/TAZ nuclear translocation. We further confirm the feasibility of drug-mediated reversal of this pro-angiogenic endothelial organization through two different signaling mechanisms, namely, inhibition of the vascular endothelial growth factor pathway and the Notch signaling pathway, thereby demonstrating the utility of the tumor-vascular interface platform for rapid, early stage prediction of antiangiogenic drug efficacy. Overall, our work emphasizes the importance of our strategic engineering approach for identifying some unique, physiologically relevant aspects of the tumor-vascular interface, which are otherwise difficult to implement using standard in vitro approaches.

New Sustainable Fintech Business Models Created by Open Application Programming Interface Technology: A Case Study of Korea’s Open Banking Application Programming Interface Platform

Fintech facilitates financial inclusion by introducing new sustainable and accessible business models in developing countries. Open banking API technology is used by various fintech businesses in both developing and developed countries, with varying effects on financial markets. It changes the financial market distribution structure by separating financial product manufacturing and distribution and intensifying competition between traditional financial institutions and fintech companies. Fintech companies innovate by using this tool to create new business models. In December 2019, Korea established a standardized “open banking API platform”, sharing an interbank payment network with fintech companies. It has since shown explosive growth, surpassing the trading volume of the UK, the country that introduced open banking APIs for the first time. This study analyzes new business models fintech companies created using this API technology. Based on existing literature, statistics from the platform operator (the Korea Financial Telecommunications and Clearings Institute), and investigations of 30 Korean fintech mobile applications, this study analyzes new fintech business models that provide financial services using this platform. These companies create sustainable business models by combining multiple APIs. Four representative business models (simple funds transfer, simple payment, cross-border remittance, and asset management) are analyzed to reveal how fintech companies create business models with open APIs.

Prediction of RC T-Beams Shear Strength Based on Machine Learning

The contribution of shear resisted by flanges of T-beams is usually ignored in the shear design models even though it was proven by many experimental studies that the shear strength of T-beams is higher than that of equivalent rectangular cross-sections. Ignoring such a contribution result in a very conservative and uneconomical design. Therefore, the aim of this research is to investigate the capability of machine learning (ML) techniques to predict the shear capacity of reinforced concrete T-beams (RCTBs) by incorporating the contribution of the flange. Five machine learning (ML) techniques, which are the Decision Tree (DT), Random Forest (RF), Gradient Boosting Regression Tree (GBRT), Light Gradient Boosting Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), are trained and tested using 360 sets of data collected from experimental studies. Among the various machine learning models evaluated, the XGBoost model demonstrated exceptional reliability and precision, achieving an R-squared value of 99.10%. The SHapley Additive exPlanations (SHAP) approach is utilized to identify the most influential input features affecting the predicted shear capacity of RCTBs. The SHAP results indicate that the shear span-to-depth ratio (a/d) has the most significant effect on the shear capacity of RCTBs, followed by the ratio of shear reinforcement multiplied by the yield strength of shear reinforcement (ρvfyv\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\rho }_{{\ ext{v}}}{f}_{{\ ext{yv}}}$$\\end{document}), flange thickness (hf\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${h}_{{\ ext{f}}}$$\\end{document}), and flange width (bf\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${b}_{{\ ext{f}}}$$\\end{document}). The accuracy of the XGBoost model in predicting the shear capacity of RCTBs is compared with established codes of practice (ACI 318-19, BS 8110-1:1997, EN 1992-1-2, CSA23.3-04) and existing formulas from researchers. This comparison reinforces the superior reliability and accuracy of the machine learning approach compared to traditional methods. Furthermore, a user-friendly interface platform is developed, effectively simplifying the implementation of the proposed machine-learning model. The reliability analysis is performed to determine the value of the resistance reduction factor (ϕ) that will achieve a target reliability index (βT\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\beta }_{T}$$\\end{document}= 3.5).

Process of Acquisition to Destination – A Bang on Economic Prudence with Reference to Indian Logistics Industry

The study explores the significance of the logistics industry in the Indian economy and examines its sector-wise impact on economic well-being. It emphasizes how the presence or absence of transport infrastructure significantly influences economic growth and global competitiveness. With globalization expanding its scope, the study addresses the challenges of global logistics, such as trade laws, cultural differences, and the necessity for efficient cross-border transportation networks. Moreover, the research delves into factors driving the growth of the Indian logistics industry. Innovations and developments are seen as pivotal to economic progress, with intelligent logistics and smart transportation playing crucial roles. The Logistics Performance Index (LPI), a benchmarking tool by the World Bank, ranks countries based on logistics performance. In the 2023 report, India achieved an LPI rating of 3.4, securing the 38th position among 139 countries. The study substantiates the factors fueling the logistics industry with statistical evidence, highlighting technological advancements and the integration of IoT-enabled facilities as key drivers. Furthermore, the study discusses strategic initiatives aimed at enhancing India's logistics infrastructure. The PM Gati Shakti initiative seeks to streamline infrastructure development by promoting integrated planning and coordinated implementation across government departments. Concurrently, the National Logistics Policy (NLP) provides a comprehensive framework for the industry's development. Additionally, the Unified Logistics Interface Platform (ULIP) facilitates real-time information exchange among stakeholders, thereby simplifying logistics planning.

Enhancing Informal Education with Robotic Process Automation

Robotic Process Automation (RPA) is a cutting-edge technology that empowers software robots to perform repetitive digital tasks based on predefined rules. Traditionally, these tasks are carried out by humans interacting with various software applications through mouse and keyboard actions. RPA robots excel at emulating human actions with exceptional precision, speed, and consistency. RPA has gained widespread popularity across industries for its capacity to streamline business processes, increase productivity, and reduce operational costs. In educational settings, RPA is becoming an integral part of broader digital transformations. The related work discussed in this paper highlights that RPA is commonly utilized to automate administrative tasks for university staff, teachers, and occasionally students, while its potential applications in the learning process remain largely unexplored. Addressing this research gap, we introduce an innovative approach to leverage RPA in informal learning. Our method focuses on automating the course search process on e-learning platforms. The proposed algorithm includes interaction with platform interface, extraction of essential course details, storing retrieved data, and generating structured reports, all while communicating with various systems. Subsequently, we present a solution developed based on this approach, along with its outcomes, evaluation, and discussion of findings.

At the Heart of the Mothercrystal: Final Fantasy XIV’s Approach to Localization and Lore as a Virtual Contact Zone

<p>Virtual worlds by nature of their persistence and ability to have multiple simultaneous users in the same space can act as contact zones, defined by Mary Louse Pratt as a "social space where disparate cultures meet, clash, and grapple with each other, often in highly asymmetrical relations of domination and subordination," (1991, p. 34). One affordance of virtual worlds in constructing the contact zone is the ability for the developer to use localization to bridge language gaps between a user and the virtual world and, to some extent, between players who have a shared understanding of the virtual world. This understanding extends to the properties of objects and locations and any narrative lore or background in the world. However, localization can be a double-edged sword, with choices in translation and localization leading to confusion among virtual world users and conflict between users and developers. </p><p>Language impacts two aspects of the virtual contact zone. For one, players communicate using languages they are proficient in, using whatever affordances are available in the interface and paratextual platforms, such as the official forums and social mediaplatforms like Reddit and Tumblr. For another, the world itself is awash in language. That text manifests itself in gameplay elements from user abilities and item names to more narrative elements such as character names, dialogue, and written story and worldbuilding elements. These textual and narrative components, called "lore," are essential in contextualizing virtual spaces. Lore helps build the virtual world beyond the actual mechanics and interactions within a virtual space. Lore gives users a sense of not just place but of geography, not just time, but of history, and not just context for players but their place within the story of the virtual world. Lore offers players motivation for playing in addition to traditional gameplay motivators such as exploration, achieving, socializing, and defeating enemies or other players (Yee, 2006; Bartle, 1996) to interact with the world. </p><p>This paper focuses on the case of Final Fantasy XIV: A Realm Reborn (FFXIV), an MMORPG initially released in 2013, its production, approaches to localization,and how it contributes to building a "virtual contact zone." In looking at specific instances where controversies in translation and localization led to confusion and conflict among the participants and developers of the game, this case study illustrates the role of localization in games beyond translation and acculturation. Localization not only serves as the linguistic bridge among members of the contact zone but, in the case of online games where world-building and narrative are important aspects for immersion and play, creates shared experiences and understandings of that virtual world among all members of the virtual contact zone.</p>

Video Summarization for Marathi Language

The Video Summarization Platform using Python Flask is a comprehensive tool designed to summarize Marathi and English videos while providing summaries in Hindi, Marathi, and English languages. Leveraging machine learning and natural language processing (NLP) techniques, this platform offers a sophisticated solution for efficiently extracting key information from videos. The platform begins by transcribing the audio content of the video into text using automatic speech recognition (ASR) technology. This transcription process ensures that the platform can accurately analyze and summarize the video's content. Next, the text is translated into the target languages, namely Hindi, Marathi, and English, enabling users from diverse linguistic backgrounds to access the summarized content. To generate concise and informative summaries, advanced NLP algorithm is applied. This algorithm analyze the transcribed text to identify the most significant phrases, sentences, and concepts. By considering factors such as keyword frequency, semantic relevance, and context, the platform effectively distils the video's content into digestible summaries. Additionally, machine learning models are employed to classify the type of video content. These models are trained on diverse datasets encompassing various video genres and topics. By recognizing patterns and features within the video content, the platform can accurately categorize videos into distinct types, such as news, interviews, tutorials, or entertainment. The platform's user interface, powered by Python Flask, offers a seamless experience for users to upload videos, select their preferred language for summarization, and receive concise summaries in their chosen languages. The intuitive design ensures accessibility and ease of use, catering to both novice and advanced users. Overall, the Video Summarization Platform serves as a valuable resource for individuals seeking efficient ways to consume multimedia content. Whether for educational, informational, or entertainment purposes, this platform empowers users to access summarized video content in multiple languages, facilitated by cutting-edge machine learning and NLP technologies. Key Words: Transcription, Marathi-speaking users, Marathi YouTube videos, video content, transcription, summary, translation, Natural Language Toolkit (NLTK), content comprehension, user interaction data, past summaries, recommendation

Flexible Peripheral Nerve Interfacing Electrode for Joint Position Control in Closed-Loop Neuromuscular Stimulation.

Addressing peripheral nerve disorders with electronic medicine poses significant challenges, especially in replicating the dynamic mechanical properties of nerves and understanding their functionality. In the field of electronic medicine, it is crucial to design a system that thoroughly understands the functions of the nervous system and ensures a stable interface with nervous tissue, facilitating autonomous neural adaptation. Herein, we present a novel neural interface platform that modulates the peripheral nervous system using flexible nerve electrodes and advanced neuromodulation techniques. Specifically, we have developed a surface-based inverse recruitment model for effective joint position control via direct electrical nerve stimulation. Utilizing barycentric coordinates, this model constructs a three-dimensional framework that accurately interpolates inverse isometric recruitment values across various joint positions, thereby enhancing control stability during stimulation. Experimental results from rabbit ankle joint control trials demonstrate our model's effectiveness. In combination with a proportional-integral-derivative (PID) controller, it shows superior performance by achieving reduced settling time (less than 1.63 s), faster rising time (less than 0.39 s), and smaller steady-state error (less than 3 degrees) compared to the legacy model. Moreover, the model's compatibility with recent advances in flexible interfacing technologies and its integration into a closed-loop controlled functional neuromuscular stimulation (FNS) system highlight its potential for precise neuroprosthetic applications in joint position control. This approach marks a significant advancement in the management of neurological disorders with advanced neuroprosthetic solutions.

Legitimizing video-sharing practices on local and global platforms: A multimodal analysis of menu design, folk genres and taxonomy

There have been extensive public and academic debates on the role platform algorithms play in shaping social media (sub)cultures. Little attention, however, has been paid to how platform (sub)cultures are discursively constructed by the design of the platform interface. This study examines Bilibili, a leading Chinese video platform, and investigates how it discursively frames video-sharing culture through platform menu design. We developed a three-level analytical framework that includes: 1) a multimodal social semiotic analysis of Bilibili’s menu design; 2) a contrastive analysis of YouTube’s video menu, and 3) a focused analysis of guichu or kichiku videos (as a linguistic phenomenon, a transcultural practice and a multimodal semiotic artefact). Our findings reveal that Bilibili discursively frames and legitimizes video-sharing practices by establishing a folk taxonomy of video genres and integrating subculture into its menu design. Furthermore, Bilibili controls access to cultural knowledge through explicit (gatekeeping) and implicit (semiotic) measures, in contrast to YouTube’s visual and superficial taxonomy. This study unveils different discursive strategies platforms use to shape unique online video cultures.

Synergistic Interface Platforms: Designing Superhydrophilic Conductive Nanoparticle‐Decorated Nanofibrous Membranes

AbstractIn today's technological landscape, advancing methods for producing conductive membranes that simplify and streamline the development of advanced interface materials is crucial. This study introduces a versatile and innovative method for fabricating superhydrophilic, conductive nanofibrous membranes based on the in situ synthesis of polypyrrole nanoparticles on poly(vinylidene fluoride‐co‐hexafluoropropylene) (PVDF‐HFP) electrospun fibers. The composite membranes morphologically exhibit a particle‐decorated nanofibrous configuration, with polypyrrole nanoparticles distributed along the individual fibers' surface. The nanoparticle‐nanofiber configuration shows distinctive properties; electrochemically, the electrospun mats demonstrate excellent inherent electrical conductivity, good cyclic and high electrochemical stability, and low resistance. Furthermore, the amphiphilic and superhydrophilic behavior, achieved through nanotopography, porosity and interactions between the intrinsically conductive polymer and the PVDF‐HFP fibers, enables efficient uptake of polar and nonpolar analytes. The membranes also demonstrate good in vitro cell viability of both murine and human fibroblasts. Given its efficient interaction with liquids and omnidirectional 360‐degree conductivity, this material emerges as an excellent candidate for use as a biocompatible, multifunctional interface layer. The produced nanoparticle‐nanofibrous membrane materials offer a promising platform for interface applications, featuring enhanced spatiotemporal configurations and wide‐ranging applicability.

Data Processing Engine (DPE): data analysis tool for particle tracking and mixed radiation field characterization with pixel detectors Timepix

Hybrid semiconductor pixelated detectors from the Timepix family are advanced detectors for online particle tracking, offering energy measurement and precise time stamping capabilities for particles of various types and energies. This inherent capability makes them highly suitable for various applications, including imaging, medical fields such as radiotherapy and particle therapy, space-based applications aboard satellites and the International Space Station, and industrial applications. The data generated by these detectors is complex, necessitating the development and deployment of various analytical techniques to extract essential information.For this purpose, and to aid the Timepix user community, it was designed and developed the“Data Processing Engine” (DPE) as an advanced tool for data processing designed explicitly for Timepix detectors. The functionality of the DPE is structured into three distinct processing levels: i) Pre-processing: this phase involves clusterization and the application of necessary calibrations and corrections. ii) Processing: this stage includes particle classification, employing machine learning algorithms, and the recognition of radiation fields. iii) Post-processing: involves various analyses, such as directional analysis, coincidence analysis, frame analysis, Compton directional analysis, and the generation of physics products, are performed. The core of the DPE is supported by an extensive experimental database containing calibrations and referential radiation fields of typical environments, including protons, ions, electrons, gamma rays and X rays, as well as thermal and fast neutrons. To enhance accessibility, the DPE is implemented into various user interface platforms such as a command-line tool, an application programming interface, and as a graphical user interface in the form of a web portal. The DPE's broad utility is exemplified through its integration into various applications and developments.

A Post-processing Computational Fluid Dynamics System for Turbomachinery

Computational fluid dynamics applied to the turbomachinery domain require specialized post-processing functionality. For computational fluid dynamics turbomachinery, we have developed a lightweight post-processing software. We have developed a system utilizing the Visualization Toolkit (VTK) for rendering and the Qt toolkit as the cross-platform graphical user interface platform. The system is lightweight, which implements the fundamental postprocessing functions such as iso-surface and cut plane visualization and determines the meridional plane and the constant blade/van height plane. We designed and evaluated two different methods to determine the meridional plane and the constant blade/van height plane and used VTK filters in VTK to obtain necessary scene information. Finally, we visualized these planes by using the VTK visualization pipeline.

A Reversible, Versatile Skin‐Attached Haptic Interface Platform with Bioinspired Interconnection Architectures Capable of Resisting Sweat and Vibration (Adv. Funct. Mater. 17/2024)

A Reversible, Versatile Skin‐Attached Haptic Interface Platform with Bioinspired Interconnection Architectures Capable of Resisting Sweat and Vibration (Adv. Funct. Mater. 17/2024)

A new propulsion system GUI based control amenable model development for high‐power rockets

SummaryThis paper proposes a new algorithm to model and characterize an autonomous high‐power rocket using an indigenously developed graphical user interface (GUI) platform. This platform features a newly devised app, termed as THIEC Rocketry App which embeds the simulation based analysis to determine the design parameters of the rocket, required for a vertical flight. A solid propellant using potassium nitrate and sucrose, also known as rocket‐candy, is considered for the GUI development. The GUI facilitates the designer to specify the desired flight parameters for the rocket propulsion system. Various characteristic plots for visualization and analysis are made available in GUI. The obtained parameters from the GUI are then utilized in computer‐aided designing (CAD) for further identification of geometrical parameters like inertia tensor, center of gravity (CG) and center of pressure (CP). The mathematical control amenable model of the rocket is then developed using first principles so as to achieve an altitude up to 3 km. The overall system represents a complex nonlinear multi‐input multi‐output (MIMO) dynamics, having six degrees of freedom. The Newton‐Euler formulation is employed to develop the equations of motion. The attitude control using canards is analyzed via simulations for the complete flight path ‐ the boost and coast flights. Finally, the developed GUI based model is validated by practically manufacturing the components of the propulsion system for the small‐scale high‐power rocket. The proposed model will create the pathway for the development of some robust model‐based control schemes for such autonomous rockets in future.

Understanding the user perception of digital nudging in platform interface design

AbstractGiven the nascent understanding of user perceptions toward digital nudges in e-commerce, our study examines key factors: perceived usefulness, ease of use, trust, and privacy risks. Via an online experiment of 273 participants, we examined the influence of digital nudging interventions – social norms, defaults, and scarcity warnings – against a control group. Employing descriptive and inferential statistics, notable trust variations were found between default and scarcity warning groups versus controls. To assess these findings, we interviewed 11 information systems and psychology experts. This research enriches our understanding of digital nudges in e-commerce and provides design insights. Theoretical implications span from providing propositions in order to enhance user involvement, conducting narrative accompanying research, analyzing diverse time points of nudging. Practical implications focus on emphasizing to users their choice autonomy and the highlighting that defaults and scarcity warnings are designed to mitigate inherent heuristics and biases for combining nudging with boosting elements.

Online education in design disciplines: factors influencing the interactive experience of group learning

There has been much previous research into online group learning, but they have not been aware of or focused on the challenges that design disciplines encounter in terms of interaction when moving to online delivery. This qualitative study comprised 3 participatory design workshops and 22 one-to-one interviews that included a total of 34 teachers and students from the School of Design at the University of Leeds. Participants reported the challenges and feelings they encountered in online group learning during the COVID-19 pandemic. The study found that the interactive experience of group learning is mainly influenced by the size of the group, the layout of the platform interface, the teacher’s management style and the conflict within the group, with more far-reaching discussions providing specific questions and subtle suggestions. The article’s findings can inform future strategies for online group learning for students and teachers of design disciplines in design higher education institutions.

Enhancing Coal Mining Efficiency

Coal is a prominent energy resource for several countries. Of late, exploring the automatic management and control of coal mining has been a significant task. This article presents a framework for a mine-wide integrated automation management and control platform with the goal of advancing coal mining through unified data, models, platforms, and plans. Utilizing cutting-edge technologies, the platform offers resource management, real-time monitoring, remote control, statistical analysis, and intelligent alarm systems. Data access design ensures standardized data collection and exchange, fostering interoperability. A big data storage center manages heterogeneous data sources. The platform interface design emphasizes flexibility and scalability through containerized applications and microservices frameworks, streamlining deployment. The functional design encompasses subsystem configuration access, real-time monitoring, remote access, etc. A detailed evaluation is presented to demonstrate the significance of the proposed platform in terms of functionality, performance, and scalability.