Engineering Tools Research Articles

Transformação sustentável

The objective of the research was to apply composting techniques and social technology to treat food waste in a low -income condominium in southern Brazil, with the joint participation of university researchers and residents. The purpose was not only to reduce the environmental impact caused by waste, but also generate organic compounds of environmental and agronomic value. The project started with an observational visit to the condominium to identify appropriate spaces for the execution of the work. Then the researchers promoted the project through posters and direct conversations with the residents. After this interaction, training workshops were held for participating residents, totaling 40 families and 122 people. The workshops addressed topics such as the impacts of food waste, segregation at source, the composting process and social technology. Educational materials were distributed to assist in the learning process, and visual resources, such as workshops and educational videos, were used. Finally, the composting process was implemented. Social technology played a significant role throughout the process. During workshops and interactions with residents, participants became active learning agents, sharing traditional knowledge and integrating them with scientific knowledge. Educational materials have represented an important tool for social technology, providing information in an accessible and motivational way. The active participation of researchers and residents was also a positive aspect of this investigation, as it strengthened the condominium community, created social bonds and promoted awareness of environmental responsibility.

Crack Detection and Cost Analyzer Using AI

Crack Vision is an innovative AI-powered Android application developed to detect and analyze wall cracks, providing users with real-time, automated repair cost estimates. By leveraging advanced object detection models such as YOLOv7 and Mask R-CNN, Crack Vision enhances both the accuracy and efficiency of crack detection, enabling precise measurement of crack dimensions, severity assessment, and quick identification of structural issues. This application simplifies the inspection and budgeting process for wall repairs, making it an essential tool for homeowners, contractors, and structural engineers who seek to minimize reliance on manual inspection methods. The core functionality of Crack Vision combines high-resolution image processing with state-of-the-art machine learning algorithms, ensuring reliable detection across various wall types and crack textures. Using computer vision and deep learning techniques, the app can differentiate between structural and non-structural cracks, thereby offering a comprehensive solution for repair prioritization. Furthermore, Crack Vision integrates with a robust backend that stores user data, allowing users to track the condition of their walls over time. This feature aids in preventive maintenance by identifying trends in crack expansion and deterioration, potentially mitigating costly repairs. Additionally, the application provides a detailed breakdown of estimated repair costs based on crack size, depth, and type, empowering users to make informed decisions about necessary repairs. Crack Vision is designed with user-friendliness in mind, featuring an intuitive interface that guides users through the inspection process. The app also supports multilingual options and customizable settings to cater to diverse user needs. In sum, Crack Vision redefines wall crack inspection, offering a rapid, accurate, and accessible solution for both casual users and industry professionals, ultimately contributing to improved building safety and maintenance efficiency

Poly(norepinephrine)-Mediated Universal Surface Modification for Patterning Human Pluripotent Stem Cell Culture and Differentiation.

Maintaining undifferentiated states of human pluripotent stem cells (hPSCs) is key to accomplishing successful hPSC research. Specific culture conditions, including hPSC-compatible substrates, are required for the hPSC culture. Over the past two decades, substrates supporting hPSC self-renewal have evolved from undefined and xenogeneic protein components to chemically defined and xenogeneic-free materials. However, these synthetic substrates are often costly and complex to use, leading many laboratories to continue using simpler undefined extracellular matrix (ECM) protein mixtures. In this study, we present a method using poly(norepinephrine) (pNE) for surface modification to enhance the immobilization of ECM proteins on various substrates, including polydimethylsiloxane (PDMS) and ultralow attachment (ULA) hydrogels, thereby supporting hPSC culture and maintenance of pluripotency. The pNE-mediated surface modification enables spatial patterning of ECM proteins on nonadhesive ULA surfaces, facilitating tunable macroscopic cell patterning. This approach improves hPSC attachment and growth and allows for cell patterning to study the effects of anisotropic environments on the hPSC fate. Our findings demonstrate the versatility and simplicity of pNE-mediated surface modification for improving hPSC culture and spatially controlled differentiation into endothelial cells and cardiomyocytes on previously nonamenable substrates, providing a valuable tool for tissue engineering and regenerative medicine applications.

Development of a Real-Time Wearable Humming Detector Device

This study focuses on the development of a wearable real-time Humming Detector Device (HDD) aimed at enhancing the control of assistive devices through humming. As the need for portable user-friendly tools in assistive technology grows, the HDD offers a non-invasive solution to detect vocal cord vibrations. Vibrations, detected thanks to an accelerometer worn on the neck, are processed in real time using a Fast Fourier Transform (FFT) to identify specific humming frequencies, which are then translated into commands for controlling assistive devices via Bluetooth Low Energy (BLE) transmission. The device was tested with 13 healthy subjects to validate its potential and determine the optimal number of distinct commands that users can achieve. The HDD’s portability and precision make it a promising alternative to traditional voice recognition systems, particularly for individuals with speech impairments.

Charting a way forward for the use of data science in competition enforcement and platform regulation

ABSTRACT Competition authorities and other regulators already rely on data science to monitor markets and check compliance with applicable rules. The Digital Markets Act and the Digital Services Act have made the use of data science by regulators even more relevant, given the scale and complexity of the oversight required. The existing use of data science shows that regulators are able to adapt their organizations and processes to realize the potential of using technology tools in their activities. At the same time, the use of data science poses challenges in terms of data reliability and individual privacy. Beyond involvement in specific investigations, data science also has the potential to reform the work of regulators by moving towards a more proactive form of enforcement. The sharing of data science expertise and tools between regulators deserves to be further facilitated to increase collaboration and share resources in monitoring the platform economy.

Comparative Computer-Aided Analysis of Three-Dimensional Carpal Alignment in Scapholunate Advanced Collapse and Healthy Wrists.

Scapholunate dissociation frequently results in malalignment and scapholunate advanced collapse (SLAC). Previous analyses have relied on visual observations of carpal angles among the scaphoid, lunate, and capitate on lateral radiographs. However, the 3-dimensional carpal alignment during SLAC progression remains unclear. The purpose of this study was to analyze 3-dimensional carpal malalignment in SLAC wrists. Using computer-aided cone-beam computed tomography analysis software based on segmentation and numerical modeling, we defined three-dimensional carpal axes and examined alignment and carpal height ratio in 18 SLAC wrists along the radial coordinate (positive in palmar and ulnar directions). These results were compared with previously reported normal alignment values obtained from 121 healthy wrists. In the sagittal plane, mean scapholunate, lunotriquetral, lunocapitate, and capitometacarpal angles were -100° (SD, 11°); 20° (SD, 11°); 7° (SD, 12°); and 18° (SD, 8°); respectively, whereas the angles were -58° (SD, 9°); 12° (SD, 8°); -17°(SD, 11°); and 8° (SD, 6°); respectively, in healthy wrists. The sagittal scapholunate angle exhibited the highest area under the receiver operating characteristic curve (0.999), with a threshold value of ≤-76°, indicating pathology. In the coronal plane, the carpal alignment of SLAC wrists remained unchanged, excluding a minimal ulnar tilt of the capitate. Carpal malalignment in SLAC wrists not only affects the radio- and midcarpal joints, but also extends to the third carpometacarpal joint, with malalignment evident in both the sagittal and coronal planes. In SLAC wrists, the sagittal lunotriquetral angle increases in the positive direction, due to the lunate angulating more than the triquetrum. These findings have potential to contribute to the development of computer-aided diagnostic tools for 3-dimensional imaging technology. In the future, such tools could highlight abnormal values and minimize diagnostic errors in clinical practice.

Model-Based Assessment of Energy Efficiency in Industrial Pump Systems: A Case Study Approach

Outdated, oversized variable speed pump drives (VSDPs) in industry lead to sub-optimal energy efficiency and considerable energy losses. This paper proposes methods to develop 2D efficiency maps for motors, converters, and pumps using polynomial surface fitting, which enables efficiency evaluation in a wide operating range. The method was applied to an oversized VSDP in an industrial chilled water supply system, comparing the original system with five alternative VSDP combinations with high-efficiency motors and pumps. The five VSDP variants demonstrated average energy savings of around 30%, with the synchronous reluctance motor (SRM) configurations outperforming the induction motor (IM) configurations by up to 7 percentage points, particularly at low loads. The high-efficiency SRM-based 252-IE5 variant delivered the best overall energy performance, highlighting the benefits of optimised system sizing and motor selection for energy savings. The proposed method can be used in both industrial and residential applications and offers great advantages in process systems that require variable flow and pressure of water or other fluids during operation, such as HVAC, water supply and wastewater treatment, district heating, etc. The development of a VSDP drive with efficient energy optimisation is an interdisciplinary problem of mechanical and electrical engineering, and without the interaction of engineers from both fields the result will not be optimal. We try to present our method so that it can be a reliable tool for mechanical, electrical, and other engineers or researchers to assist them in finding possible energy savings, performing energy audits, and selecting the most suitable components when modernising existing or developing new systems.

Teledentistry as a Tool for Health Care Transformation

Teledentistry is a valuable technology tool that supports dental professionals in improving access to oral health care. Technological infrastructure, workforce availability, staff readiness, reimbursement, and patient population served must all be considered when implementing teledentistry.

NIGERIA’S SECURITY DYNAMICS AND THE FIGHT AGAINST CRIME

This review paper delves into the 'security dynamics in Nigeria, and the fight against crime', elucidating the current state of criminal activities in Nigeria, which have reached unprecedented levels, particularly with the emergence of social media and other sophisticated technological tools. Nevertheless, the paper aims to leverage these advanced technological resources for intelligence gathering to combat crime effectively. It correlates the nature of criminal activities and their evolution with the intergenerational differences present in our society today, highlighting how these differences have also impacted the capabilities of law enforcement agencies in addressing crime in Nigeria. The recommendations put forth in this paper emphasize the significance of inter-agency cooperation, advocating for the integration of advanced intelligence-gathering mechanisms into the operational frameworks of security agencies to expedite crime prevention. Additionally, the discussion on recommendations entails investing in community policing, enhancing security protocols, and enacting reforms, among other proposals.

STUDENTS’ AND TEACHERS’ PERCEPTION ON USING VIDEO STREAMING PLATFORM TO ENHANCE LISTENING SKILLS

This study investigates the influence of video streaming platforms on effective listening proficiency among English teachers and secondary school students in SMKA Tun Ahmadshah, Kota Kinabalu, Sabah. The research utilized a qualitative approach, interviewing 5 experienced English teachers and five students from Form 3 to Form 5. Among the reasons, the integration of modern technological tools was provided in the school. The theories of cognitivism and content-based learning (CBL) within the book are employed. The research focuses on these theories to explore cognitive and instructional merits of using video streaming platforms. Based on the findings, the content of video streaming platforms significantly sustains students’ engagement and motivation. At the same time, teachers comment on the content being interesting, relevant, and in multimedia format. It combines visual and auditory sense for their engagement. Among the challenges for the students was that they rely on subtitles on the video. The issue of buffering was not mentioned by the students, but it is likely to reduce their engagement. Teachers suggested that the platform content is authentic similar to that on social media, and students can receive other messages beside the expected ones. For effective teaching, the use of some features could be of help considering that buffering poses a major challenge, and some students rely on subtitles. Nevertheless, they could make the process simpler and with motivation by their utilization on the students’ part. The medium is significantly used in distance learning where it is effective since students rely on the authentic content and are engaged. Thus, the platform should be used for effective proficiency in listening with assistance from its video features. They require the employing of the platform features and adequate motivation from the participants. Keyword(s): Listening Skills, Content Based Learning (CBL), Video Streaming Platform, Cognitivism.

Integrating Multimodal Generative AI Technologies in Postgraduate Marketing Education

While industry practices evolve rapidly, marketing education in Australia and New Zealand faces challenges in keeping pace, particularly regarding the adoption of current marketing technologies (Harrigan et al., 2022). Generative AI, exemplified by systems like ChatGPT and DALL·E, has demonstrated benefits for learning (Baidoo-Anu & Ansah, 2023). However, despite its potential, there remains a dearth of practical guidance on effectively incorporating these technologies into marketing courses. This gap persists even as general frameworks for responsible and ethical AI use, such as the Australian Framework for Generative AI in Schools (2023), emerge. As the demand for graduates with generative AI skills grows in the job market, educators must explore innovative pedagogical approaches to bridge this gap. This academic poster presents an innovative application of generative artificial intelligence (GenAI) in the context of teaching digital marketing at the postgraduate level. Its purpose is to bridge the gap between academic theory and industry practice by encouraging educators to integrate AI tools into their curriculum through experiential learning pedagogy (Kolb, 2014), characterized by a learning process whereby knowledge is created through hands-on experiences. The poster exemplifies how various types of GenAI technologies — specifically text-based, image-based, and video-based — can enhance teaching content, tutorial exercises, and assessments within the digital marketing course. The poster showcases examples of how these GenAI tools are integrated in the course content, to guide students in generating innovative ideas for using AI in marketing to gain a competitive edge: Text-based GenAI: Tools like ChatGPT and Gemini can automatically generate search keywords for search engine marketing. By integrating text-based GenAI tools with established marketing technology (MarTech) tools such as Google Ads and Google Ads Keyword Planner, students engage in practical exercises that combine AI-generated initial ideas (e.g., search keywords) with further analysis (e.g., search volume, click-through rates, and bidding costs) using established MarTech tools. This hands-on approach enhances their learning experience and prepares them for real-world applications. Image-based GenAI: Platforms such as DALL·E, Midjourney, and Stable Diffusion enable the creation of custom images for display advertising, enhancing visual communication in marketing materials. Through experiential learning activities, students can explore ideas, seek unusual combinations, and inspire creativity faster with image-based GenAI tools, resulting in a greater variety of display ad materials. Video-based GenAI: Applications like Sora and Synthesia facilitate the production of short video clips suitable for social media marketing (e.g., YouTube Shorts, TikTok). By engaging in dynamic content creation exercises, students learn to streamline content creation, reduce manual work, and save both time and budget, thereby gaining practical skills in social media marketing. By incorporating these GenAI technologies through experiential learning pedagogy, educators can enrich the learning experience, foster critical thinking, and prepare students for the evolving landscape of digital marketing. Future research can study the use of GenAI in marketing education using theoretical frameworks such as the Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2016).

3D WCSPH modelling of landslide-water dynamics during 1963 Vajont disaster.

This study illustrates the full-scale 3D numerical simulation of the coupled water-landslide dynamics of the 1963 Vajont catastrophic event. The focus is given to the early phase of the event when about 270million cubic meters of rock fell into the reservoir within an estimated runout time of about 25s. A complex surge wave system developed throughout the basin in the first 40-55s, producing maximum run-up of 270m above the dam crowning. The mesh-free Lagrangian Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) method is adopted to discretize and solve the coupled system of governing equations for the landslide and water dynamics. The adopted model, which is based on SPHERA v.9.0.0 (Amicarelli et al. Comput Phys Commun, 2020), has been derived by introducing relevant modifications in the research code SPHERA (RSE SpA). The derived model is validated and the influence of water saturated soil on prediction of surge wave run-up is analysed. The average values from technical literature are assigned to mechanical parameters without tuning or calibration. The maximum flooding on the opposite side of the valley and the peak flow rate of the discharge hydrograph through the dam section show good agreement with reference data and improvements with respect to published results. The validated derived model proves to be a promising engineering tool for quantifying the level of risk in analogous applications.

INTEGRATION OF DIGITAL TECHNOLOGIES INTO THE PERSONNEL DEVELOPMENT MANAGEMENT MECHANISM IN HEALTHCARE INSTITUTIONS

This article explores the integration of digital technologies into the personnel management mechanisms of healthcare institutions in Ukraine. In an era marked by rapid digital transformation, the healthcare sector is increasingly recognizing the importance of utilizing modern technological tools to enhance operational efficiency, improve patient care, and streamline administrative processes. The study begins by examining the current state of personnel management in Ukrainian healthcare institutions, identifying key challenges such as workforce shortages, inefficient communication channels, and inadequate training programs. The research further delves into the various digital solutions available, including human resource management systems (HRMS), telemedicine platforms, and data analytics tools. These technologies are evaluated for their potential to optimize recruitment processes, enhance employee performance tracking, and facilitate continuous professional development. The article also highlights case studies from healthcare institutions that have successfully implemented digital technologies, showcasing tangible improvements in staff engagement, patient outcomes, and overall institutional effectiveness. Additionally, the paper discusses the critical role of digital literacy among healthcare professionals, emphasizing the need for targeted training initiatives to ensure that staff can effectively utilize new technologies. It concludes by proposing a strategic framework for integrating digital tools into personnel management practices, advocating for a holistic approach that encompasses technological adoption, staff training, and organizational culture change. Ultimately, the article aims to provide valuable insights and practical recommendations for healthcare leaders seeking to navigate the complexities of digital integration in personnel management. It has been determined that further research can significantly contribute to the development of effective personnel management strategies in healthcare institutions, which will not only enhance the quality of medical services but also promote the sustainable development of the healthcare system in Ukraine.

Optimal Periodic Control of Unmanned Aerial Vehicles Based on Fourier Integral Pseudospectral and Edge-Detection Methods

The endurance of unmanned aerial vehicles (UAVs) is a critical factor in expanding the scope of their applications. Extended flight times enable UAVs to undertake longer missions, cover larger areas and perform tasks such as persistent surveillance, data collection and search and rescue operations. Optimal trajectory planning is a cost-effective method to significantly enhance UAV endurance and performance by minimizing fuel consumption. This study introduces a novel numerical optimization framework to maximize UAV endurance. Specifically, we address the problem of determining optimal thrust and cruise angle of attack for a UAV in 2D space under specific initial, periodic and boundary conditions. By normalizing the free final time optimal control problem and employing Fourier collocation and quadrature, we transform it into a nonlinear programming problem. A key contribution of this work is accurately detecting and reconstructing the thrust history, including jump discontinuities, directly from Fourier pseudospectral data without smoothing techniques. The proposed method outperforms existing approaches in solving the periodic energy-optimal path planning problem for UAVs, as it effectively reconstructs the bang-bang thrust profile, facilitating rapid and efficient thrust adjustments essential for various flight maneuvers. Furthermore, the algorithm aligns with the UAV model, ensuring seamless integration into real-world control systems. The method’s independence from prediction horizon length, due to the use of Fourier collocation on the normalized interval [Formula: see text], is a notable advantage. This characteristic offers potential for future applications in various fields involving nonsmooth optimal control problems. This research generally provides a valuable tool for researchers and engineers working on UAV design and operation, paving the way for more efficient and effective UAV systems.

Optimizing cancer treatment: the synergistic potential of CAR-T cell therapy and CRISPR/Cas9

Optimizing cancer treatment has become a pivotal goal in modern oncology, with advancements in immunotherapy and genetic engineering offering promising avenues. CAR-T cell therapy, a revolutionary approach that harnesses the body’s own immune cells to target and destroy cancer cells, has shown remarkable success, particularly in treating acute lymphoblastic leukemia (ALL), and in treating other hematologic malignancies. While CAR-T cell therapy has shown promise, challenges such as high cost and manufacturing complexity remain. However, its efficacy in solid tumors remains limited. The integration of CRISPR/Cas9 technology, a powerful and precise genome-editing tool, also raises safety concerns regarding unintended edits and off-target effects, offers a synergistic potential to overcome these limitations. CRISPR/Cas9 can enhance CAR-T cell therapy by improving the specificity and persistence of CAR-T cells, reducing off-target effects, and engineering resistance to tumor-induced immunosuppression. This combination can also facilitate the knockout of immune checkpoint inhibitors, boosting the anti-tumor activity of CAR-T cells. Recent studies have demonstrated that CRISPR/Cas9-edited CAR-T cells can target previously untreatable cancer types, offering new hope for patients with refractory cancers. This synergistic approach not only enhances the efficacy of cancer treatment but also paves the way for personalized therapies tailored to individual genetic profiles. This review highlights the ongoing research efforts to refine this approach and explores its potential to revolutionize cancer treatment across a broader range of malignancies. As research progresses, the integration of CAR-T cell therapy and CRISPR/Cas9 holds the promise of transforming cancer treatment, making it more effective and accessible. This review explores the current advancements, challenges, and future prospects of this innovative therapeutic strategy.

FORMATIVE ASSESSMENT: STRATEGIES TO PROMOTE CONTINUOUS LEARNING

This research addressed the issue of the effectiveness of formative assessment in the teaching and learning process, with the aim of analyzing how this practice impacts student motivation and performance. The methodology used was a bibliographic review, in which articles, books and academic documents on the subject were examined. The results indicated that formative assessment, when applied appropriately, promoted significant learning, allowing students to become autonomous and engaged in their educational trajectories. In addition, the analysis revealed that educators' resistance and the lack of continuous training were barriers to the implementation of formative assessment. It was observed that teacher training and the use of digital technologies facilitated the application of this approach, providing dynamic monitoring of learning. The final considerations emphasized the importance of teacher training and the integration of technological tools in assessment practices. The research concluded that formative assessment is a strategy that contributes to improving the quality of education. However, the need for future research to deepen the discussion on formative assessment in different educational contexts was highlighted.

How Online Learning Has Changed the Accessibility of Higher Education

It has become more accessible, flexible, and affordable than ever before as it completely does away with geographical and time barriers as have persisted in traditional education. This aspect accelerated not just in presence but also with identifying strengths and weaknesses in online learning during the pandemic. An advantage of online education has been low cost, based on reduced physical infrastructure. Another is flexibility in learning that learners enjoy as it balances personal responsibilities with their educational needs. Additionally, access for disabled students exists through assistive technologies. Many institutions have embraced this hybrid model where both the traditional learning experience and the online learning experience can give personalized educational experiences. On the other hand, it has posed such problems as the digital divide: students from lower-income backgrounds and those residing in rural areas often cannot access the internet and its other technological tools, which remain inaccessible to a high number of students with disabilities. This contributes to the isolation and disengagement of the online learners, who feel much more at home within the face-to-face learning setting. A further drawback relates to the issue of academic integrity in an online virtual learning environment, where there are no guarantees that students would be self-regulatory.The study examines how these challenges affect the accessibility of higher education and explores gaps in current research, such as the digital divide, inclusion of marginalized students, and the emotional and social impact of online learning. Online education has broadened access to higher education, but there is a need to ensure that all barriers are addressed so that equitable, high-quality learning opportunities are offered to all students.

Conceptualising a data analytics framework to support targeted teacher professional development

ABSTRACT This paper proposes a conceptual framework enabling the development and adoption of descriptive, diagnostic, predictive and recommendatory data analytics in teacher professional learning by harnessing some of the affordances of digital technologies to convert data into actionable insights. The paper argues for a technology-enhanced approach that uses data to support teachers in selecting appropriate professional development (PD) options to improve their professional practice. The ultimate goal is to lay the foundations for a robust and adaptable data analytics framework that could offer tailored PD recommendations based on the developmental trajectories of individual teachers. The paper analyses data-supported personalised professional learning as meaning-making and the appropriation of cultural artefacts within the ‘mobile complex’ - consisting of structures, agency, and the dynamic interplay between cultural and technological tools and practices. This study undertakes a comprehensive literature review to identify key concepts, gaps, and theoretical insights, informing the development of a data analytics framework. The resultant framework integrates personalisation, teacher agency and autonomy, contextual relevance, and ethical safeguards into PD process, aiming to foster a responsive, collaborative, and context-aware data-supported PD.

The development of supplemental multimedia learning modules and their impact on student learning in food biotechnology courses.

The rapid growth of online education has created opportunities to integrate multimedia learning tools into complex scientific disciplines like food biotechnology. This study aimed to develop and evaluate supplementary online course modules on gene expression analysis, protein engineering tools, and fermentation genomics for undergraduate food biotechnology education. Based on cognitive load theory and multimedia learning principles, the modules incorporated focused visual media and interactive knowledge checks. The study involved 85 students in an introductory food microbiology course and 25 students in an upper-level food biochemistry elective at a large public university. Module implementation included tracking student usage through learning management system analytics, collecting qualitative feedback, and assessing learning outcomes via exam performance. Results showed that 73%-76% of students voluntarily accessed the modules, with average engagement times of 5-8 min per module. Student feedback highlighted the modules' effectiveness in clarifying textbook content through replayable examples and real-world scenarios. Comparison of exam scores revealed a 6%-10% improvement in performance on module-related items compared to overall exam averages. Qualitative feedback indicated that students found the visual representations and interactive elements helpful for clarifying complex concepts. This study demonstrates the potential of well-designed multimedia modules to support student learning in food biotechnology education, providing a model for expanding such resources in food science curricula.

Analyze the physical interaction between the user and the furniture design to optimize comfort and functionality

The physical interaction between users and furniture is pivotal in determining comfort and functionality, particularly in environments where individuals spend extended periods, such as offices, homes, and public spaces. This study aims to analyze how different furniture designs impact user comfort, postural stability, and long-term usability. By employing a hybrid research framework combining observational studies, simulations, and advanced technological tools such as motion tracking, pressure mapping, and biomechanical sensors, the research provides a comprehensive evaluation of user-furniture interaction. The study involved 178 participants with diverse demographic backgrounds, allowing for a broad range of body types, ages, and activity levels to be examined. Key findings indicate that ergonomic features such as adjustable seat height, lumbar support, and reclining mechanisms significantly enhance comfort, particularly when customized to the user’s anthropometric profile. For example, adjustable seat height reduced pressure on the thighs, improving comfort by 8.5% over prolonged periods. Additionally, lumbar support was the most compelling feature in alleviating muscle strain, improving overall comfort by 9.0%. The analysis of long-term comfort revealed that postures supporting dynamic movements, such as using a standing desk, maintained higher comfort levels over time compared to static postures like leaning forward, which showed a marked increase in muscle fatigue. Postural stability analysis showed that sitting at a 90° angle provided the best balance of stability and long-term comfort, with a usability rating 8.4. In contrast, leaning forward exhibited the lowest postural stability and the highest discomfort, making it unsuitable for prolonged tasks.