Reflective writing is a core component of teacher education, especially during practical internships. However, providing high-quality feedback on reflections is resource-intensive. This study examines descriptively observable associations between an early dual-feedback approach combining basic (automated) and elaborate (human-generated) feedback and structural features of preservice physics teachers’ reflective writing, prior to the widespread adoption of generative AI in education. Using an exploratory, non-equivalent, non-concurrent cohort design, we analyzed participant-level aggregates of written reflections from a non-intervention cohort (<i>N</i> = 22) and an intervention cohort (<i>N</i> = 32), applying a validated reflection-supporting model to assess structural composition and discursive elements of reflective writing. In the intervention, basic feedback was generated by a previously validated BERT-based machine learning model focusing on structural reflection elements, while elaborate feedback addressed content-related and pedagogical depth. In this study, the automated model was employed as an analytic measurement instrument drawing on validation work demonstrating its transferability across comparable reflection contexts. Quantitative analyses did not reveal systematic longitudinal growth in indicators of reflective writing quality in either cohort. Across comparable measurement points, descriptively different structural reflection profiles were observed between cohorts, without permitting causal or developmental interpretations. Feedback acceptance was high overall, although structural AI feedback was perceived as less personalized and less useful. These findings highlight the descriptive value of early, non-generative AI-based approaches for scalable structural diagnostics of reflective writing, while underscoring the continued importance of human-generated, content-focused feedback. The study establishes an empirical baseline for evaluating contemporary generative AI–based feedback systems in teacher education.
Yuto Fukao, Tatsuro Terakawa, Takahiro Endo
et al.
Abstract In this paper, we propose a distributed controller for the cooperative transportation of an object with a nonholonomic constraint by a swarm robot. Because an object with passive wheels fixed to it does not slide along the axle direction, its velocity constraint is nonholonomic. We set the center of rotation of the object as a control point of the entire system. To derive the control point of an object with passive fixed wheels, we analyze dynamics of the object. Then we design a distributed cooperative transportation controller considering the nonholonomic constraint of an object with passive fixed wheels based on a kinematic model. We divide the distributed controller into two steps. In the first step, each robot derives the desired velocity and angular velocity of the object to achieve its desired position and orientation. In the second step, each robot calculates its desired velocity to achieve the object’s desired velocity and angular velocity. Each robot moves and pushes the object using the distributed controller, and can transport it to the desired position and orientation. We verify the effectiveness of the proposed controller in dynamic simulations and real robot experiments.
This study presents the development of an open-source Driver-in-the-Loop simulation platform, specifically designed to test and analyze advanced automated driving functions. We emphasize the creation of a versatile system architecture that ensures seamless integration and interchangeability of components, supporting diverse research needs. Central to the simulator’s configuration is a hexapod motion platform with six degrees of freedom, chosen through a detailed benchmarking process to ensure dynamic accuracy and fidelity. The simulator employs a half-vehicle cabin, providing an immersive environment where drivers can interact with authentic human–machine interfaces such as pedals, steering, and gear shifters. By projecting complex driving scenarios onto a curved screen, drivers engage with critical maneuvers in a controlled virtual environment. Key innovations include the integration of a motion cueing algorithm and an adaptable, cost-effective open-source framework, facilitating collaboration among researchers and industry experts. The platform enables standardized testing and offers a robust solution for the iterative development and validation of automated driving technologies. Functionality and effectiveness were validated through testing with the ISO lane change maneuver, affirming the simulator’s capabilities.
Mechanical engineering and machinery, Machine design and drawing
Manuel García-Troya, Miguel Sánchez-Lozano, David Abellán-López
A quasi-static FEM framework for wheel–rail contact is presented, aimed at large parametric analyses including independently rotating wheel (IRW) configurations. Unlike half-space formulations such as CONTACT, the FEM approach resolves global deformations and strongly non-Hertzian geometries while remaining computationally tractable through three key features: (i) a tailored mesh transition around the contact patch, (ii) solver settings optimized for frictional contact convergence, and (iii) an integrated post-processing pipeline for creep forces, micro-slip, and wear. The model is verified against CONTACT, an established surface-discretization reference based on the Boundary Element Method (BEM), demonstrating close agreement in contact pressure, shear stress, and stick–slip patterns across the Manchester Contact Benchmark cases. Accuracy is quantified using error metrics (MAE, RMSE), with discrepancies analyzed in high-yaw, near-flange conditions. Compared with prior FEM-based contact models, the main contributions are: (i) a rigid–flexible domain partition, which reduces 3D computational cost without compromising local contact accuracy; (ii) a frictionless preconditioning step followed by friction restoration, eliminating artificial shear-induced deformation at first contact and accelerating convergence; (iii) an automated selection of the elastic slip tolerance (slto) based on frictional-energy consistency, ensuring numerical robustness; and (iv) an IRW-oriented parametrization of toe angle, camber, and wheel spacing. The proposed framework provides a robust basis for large-scale studies and can be extended to transient or elastoplastic analyses relevant to dynamic loading, curved tracks, and wheel defects.
Mechanical engineering and machinery, Machine design and drawing
This survey article assesses and compares existing critiques of current fairness-enhancing technical interventions in machine learning (ML) that draw from a range of non-computing disciplines, including philosophy, feminist studies, critical race and ethnic studies, legal studies, anthropology, and science and technology studies. It bridges epistemic divides in order to offer an interdisciplinary understanding of the possibilities and limits of hegemonic computational approaches to ML fairness for producing just outcomes for society’s most marginalized. The article is organized according to nine major themes of critique wherein these different fields intersect: 1) how "fairness" in AI fairness research gets defined; 2) how problems for AI systems to address get formulated; 3) the impacts of abstraction on how AI tools function and its propensity to lead to technological solutionism; 4) how racial classification operates within AI fairness research; 5) the use of AI fairness measures to avoid regulation and engage in ethics washing; 6) an absence of participatory design and democratic deliberation in AI fairness considerations; 7) data collection practices that entrench “bias,” are non-consensual, and lack transparency; 8) the predatory inclusion of marginalized groups into AI systems; and 9) a lack of engagement with AI’s long-term social and ethical outcomes. Drawing from these critiques, the article concludes by imagining future ML fairness research directions that actively disrupt entrenched power dynamics and structural injustices in society.
Die in der Literatur beschriebenen Untersuchungen hinsichtlich der Wirkung von geometrischen Parametern auf den Zugkraftbedarf von Grubberwerkzeugen sind oftmals nur auf den getesteten Bodentyp und die zu dem Zeitpunkt herrschenden Witterungsverhältnisse anwendbar. In einem Forschungsprojekt soll festgestellt werden, ob über eine Echtzeitverstellung der Werkzeuggeometrie auf den Zugkraftbedarf Einfluss genommen werden kann. Die Grundlage für eine Optimierungsentwicklung und Gegenstand dieses Berichts ist die Kennfeldanalyse eines Grubberwerkzeuges mit variabler Geometrie in Labor- und Feldversuchen. In den Laborversuchen zeigte sich eine starke Abhängigkeit der Scharwölbung auf den Zugkraftbedarf. Die Ergebnisse der Feldversuche sind erwartungsgemäß heterogener. Hier zeigte sich eine Abhängigkeit des Anstellwinkels. Hinsichtlich möglicher Optimierungsstrategien wird das Kennfeld variabel und ortsabhängig angenommen. Entsprechend ist eine kraftoptimierte Geometrie situationsabhängig einzustellen.
Step-ratio automatic transmission upshift performance can be improved by modulating the off-going (OFG) clutch during the inertia phase. In this paper, a static powertrain performance model is derived and applied for the purpose of numerically efficient, multi-objective shift control parameter optimization for the inertia phase. The optimization is aimed at finding the optimal node parameters for simplified, piecewise linear, open-loop profiles of oncoming (ONC) clutch, OFG clutch, and engine torque reduction control variables. The performance indices, i.e., the optimization objectives, include shift comfort, clutch thermal loss, and shift time. The optimization results in 3D Pareto optimal frontiers, which are then analyzed and compared with those obtained by using the previously developed, nonlinear model-based, genetic algorithm optimization tool. The derived method is employed in order to develop a static model-based predictive control (S-MPC) strategy, which commands ONC clutch torque control input while retaining open-loop controls for engine and OFG clutch control inputs. The S-MPC strategy aims at providing the prespecified shift time, while the shift time accuracy is relaxed to some extent by using a control input dead zone element to avoid chattering effect. The S-MPC system performance is verified through simulation and compared with the genetic algorithm benchmark. The simulation results demonstrate that the S-MPC strategy approaches the benchmark performance.
Mechanical engineering and machinery, Machine design and drawing
Integration, testing, and release of complex Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) is one of the main challenges in the field of automated driving. In order for the systems to be accepted by customers and to compete in the market, they have to feature functional, comfortable, safe, efficient, and natural driving behavior. The calibration process acquires increasing importance in the achievement of this objective. Complex ADAS/ADS require the optimization of interacting calibration parameters in a large number of different scenarios—a task that can hardly be performed with feasible effort and cost using conventional calibration methods. Virtual calibration in simulation enables reproducible and automated testing of different data sets of calibration parameters in various scenarios. These capabilities facilitate different use cases to extend the conventional calibration process of ADAS/ADS through virtual testing. This paper discusses the different use cases of virtual calibration and methods to achieve the desired objectives. A special focus is on a multi-scenario-level method that can be used to iteratively calibrate ADAS/ADS for optimal behavior in a variety of scenarios, resulting in a more comfortable, safe, and natural behavior of the system and still a feasible number of test cases. The presented methods are implemented for the virtual calibration of an Adaptive Cruise Control model for evaluation.
Mechanical engineering and machinery, Machine design and drawing
Autonomous ground vehicles (AGVs) operating in complex environments face the challenge of accurately following desired paths while accounting for uncertainties, external disturbances, and initial conditions, necessitating robust and adaptive control strategies. This paper addresses the critical path-tracking task in AGVs through a novel control framework for multilevel speed AGVs, considering both structured and unstructured uncertainties. The control system introduced in this study utilizes a nonlinear adaptive approach by integrating integral backstepping with terminal sliding mode control (IBTSMC). By incorporating integral action, IBTSMC continuously adjusts the control input to minimize tracking errors, improving tracking performance. The hybridization of the terminal sliding mode method enables finite time convergence, robustness, and a chatter-free response with reduced sensitivity to initial conditions. Furthermore, adaptive control compensators are developed to ensure robustness against unknown but bounded external disturbances. The Lyapunov stability theorem is employed to guarantee the global asymptotic stability of the closed-loop system and the convergence of tracking errors to the origin within finite time. To validate the effectiveness of the proposed control scheme, high-fidelity cosimulations are conducted using CarSim and MATLAB. Comparative analysis is performed with other methods reported in the literature. The results confirm that the proposed controller demonstrates competitive effectiveness in path-tracking tasks and exhibits strong efficiency under various road conditions, parametric uncertainties, and unknown disturbances.
Mechanical engineering and machinery, Machine design and drawing
Markus Pöllänen, Heikki Liimatainen, Erika Kallionpää
et al.
Transport automation is increasingly being studied from different perspectives; however, the perceptions of road haulage companies have received less attention. This study explores the views of representatives of small- and medium-sized road haulage companies on transport automation in Finland. We conducted an online survey to gather perceptions of automation, which received 254 responses from representatives of a range of different transport industries. The respondents’ views towards automation were generally negative. The overall view was that automation may not be possible for heavy vehicles in Finland due to the adverse weather and driving conditions. The perception was that road haulage automation is unlikely to occur before 2050 in Finland. The results provide valuable insight for vehicle manufacturers, technology developers, policy makers, and haulage companies. As the road haulage industry is dominated by small- and medium-sized companies, hauliers should be supported in actively implementing new technologies.
Mechanical engineering and machinery, Machine design and drawing
The ISO 9000 series of standards are among the best-known standards developed by the International Organisation for Standardisation ISO. They provide guidance and guidelines for companies and organisations that want their products and services to satisfy customer requirements and their quality to be continuously improved. However, the need for recertification of the Quality Management System (QMS) based on ISO 9001 is increasingly being discussed by managers. The questions asked are: is it necessary to have such a certificate in order to maintain high product quality and customer satisfaction? What is the balance of benefits and losses for maintaining a certificate of this standard? The authors of the paper will try to answer these questions based on the experience of a medium-sized metal manufacturing company.
Machine design and drawing, Engineering machinery, tools, and implements
A number of factors determine the mechanical, but also physical and chemical properties. One of the most important are the steel microstructure and its working conditions. A few corrosion processes in crevices and awkward corners can be avoided at the design stage (low roughness parameters, round-section and other). But still the construction material is exposed to corrosion. These steels often come into contact with an aggressive environment based on nitric acid. Stainless steel is more and more often used in many sectors of industry.
Machine design and drawing, Engineering machinery, tools, and implements
Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common mental disorders affecting children. Because the etiology of ADHD is complex and its symptoms are not specific, there is a lack of feasible quantitative diagnostic methods. Pursuing objective and non-invasive detection methods and standards is of great practical significance to prevent the development of the disease. In this study, we aim to address one specific concern about the objectivity and quantification of ADHD diagnosis. Over a year, we iteratively designed and tested WeDA, a scale-driven wearable diagnostic assessment system. This system contains an Android computer machine with a large touchscreen, a suite of 3D printed interactive devices, and six wearable motion sensors. We implement ten diagnostic tasks drawing on the symptoms of ADHD based on DSM-5. The experimental results of classifying children with ADHD and typically developing children and subjective evaluations from doctors, parents, and children validate the effectiveness and acceptability of WeDA.
ABSTRACT This article responds to technofeminist calls to unpack the gendered politics of technologies and create critical crossover between their representation and design. I analyze feminized artificial intelligence (Siri, Alexa, Cortana) in light of two science-fiction narratives: Tomorrow’s Eve, a Victorian novel; and Her, a postmillennial film. Each story exemplifies a pivotal moment in media history: Eve the transition from symbolic to technical media; Her the transition from technical to computational media. Both stories depict a man falling in love with an artificially intelligent, feminized version of the communication media du jour. Whereas Eve and Her operate on our imaginary, Siri, Alexa, and Cortana are by our side every day, naturalizing contingent gender divisions. I address three questions: what is the cultural work accomplished by feminized AI? Which boundaries are coming down or built up? What gendered relations are (re)produced? Drawing on media archaeology, critical theory, gender studies, and media theory, this article argues the association of femininity with technology sustains differences across three dimensions: docile labour, replaceable embodiment, and artificial intelligence. This triadic framework weaves together analytic threads that often remain separate to develop a nuanced critique of femininity as a mode for domesticating new technology and technology as materializing gender relations. The discussion extends the framework to a more generalized analysis of AI as a problematic prescription for how we become machine-shaped. I advance an entangled reinterpretation of the Turing Test and suggest ethics, aesthetics, and performativity as key sites of intervention in rethinking AI design to include rather than exclude multiple forms of difference. The conclusion offers the framework as a novel heuristic for intersectional, nonreductive critiques of technology and difference.
Ren Komatsu, Hiromitsu Fujii, Yusuke Tamura
et al.
Abstract In robot teleoperation, a lack of depth information often results in collisions between the robots and obstacles in its path or surroundings. To address this issue, free viewpoint images can greatly benefit the operators in terms of collision avoidance as the operators are able to view the robot’s surrounding from the images at arbitrary points, giving them a better depth information. In this paper, a novel free viewpoint image generation system is proposed. One approach to generate free viewpoint images is to use multiple cameras and Light Detection and Ranging (LiDAR). Instead of using the expensive LiDAR, this study utilizes a cost-effective laser rangefinder (LRF) and a characteristic of man-made environments. In other words, we install multiple fisheye cameras and an LRF on a robot. Free viewpoint images are generated under the assumption that walls are perpendicular to the floor. Furthermore, an easy calibration for estimating the poses of the multiple fisheye cameras, the LRF, and the robot model is proposed. Experimental results show that the proposed method can generate free viewpoint images using cameras and an LRF. Finally, the proposed method is primarily implemented using OpenGL Shading Language to utilize a graphics processing unit computation to achieve a real-time processing of the multiple high-resolution images. Supplementary videos and our source code are available at our project page ( https://matsuren.github.io/fvp ).
Neural interfaces are the core of prosthetic devices, such as implantable stimulating electrodes or brain–machine interfaces, and are increasingly designed for assisting rehabilitation and for promoting neural plasticity. Thus, beyond the classical neuroprosthetic concept of stimulating and/or recording devices, modern technology is pursuing toward ideal bio/electrode interfaces with improved adaptability to the brain tissue. Advances in material research are crucial in these efforts and new developments are drawing from engineering and neural interface technologies. Here, a microporous, self‐standing, 3D interface made of polydimethylsiloxane (PDMS) implemented at the interfacing surfaces with novel conductive nanotopographies (carbon nanotubes) is exploited. The scaffold porosity is characterized by 3D X‐ray microtomography. These structures are used to interface axons regenerated from cultured spinal explants and it is shown that engineering PDMS 3D interfaces with carbon nanotubes effectively changes the efficacy of regenerating fibers to target and reconnect segregated explant pairs. An improved electrophysiological performance is shown when the spinal tissue is interfaced to PDMS enriched by carbon nanotubes that may favor the use of our substrates as regenerative interfaces. The materials are implanted in the rat brain and a limited tissue reaction surrounding the implants at 2, 4, and 8 weeks from surgery is reported.
High-strength steels are used in various civilian and military products. The initial cost of the raw materials for these products is very high. The surface roughness of these products is extremely important during the finishing pass to be accepted during the final inspection. The surface roughness should conform to the required values stated on the design drawing. The paper presents the results of experiments in turning of high-strength steel featuring three factors—cutting speed V, feed rate f, and depth of cut t—on five levels (125 specimens). These were divided into 25 groups. Each of the five groups was subjected to one common machining speed. Each group was machined using five levels of cutting depth. Each depth was processed using five levels of feed rate. Tessa was used for examination of surface roughness. There is little modern research on machining high-strength steel. The high cost of this material compels us to look for the optimum turning conditions to provide for the specified roughness of surface Ra and the minimum machining time of unit volume Tm. As a result of our study, an artificial neural network was designed in Matlab on the basis of the MLP 3-10-1 multilayer perceptron that allows us to predict Ra of the workpiece with ±2.14% accuracy within the range of the experimental cutting speed, depth of cut, and feed rate values. For the first time, a Pareto frontier was obtained for Ra and Tm of the finished workpiece from high-strength steel using the artificial neural network model that was later used to determine the optimum cutting conditions. It is possible to integrate the suggested optimization algorithms into computer-aided manufacturing using Matlab.