Katherine M. Collins, Ilia Sucholutsky, Umang Bhatt
et al.
What do we want from machine intelligence? We envision machines that are not just tools for thought but partners in thought: reasonable, insightful, knowledgeable, reliable and trustworthy systems that think with us. Current artificial intelligence systems satisfy some of these criteria, some of the time. In this Perspective, we show how the science of collaborative cognition can be put to work to engineer systems that really can be called ‘thought partners’, systems built to meet our expectations and complement our limitations. We lay out several modes of collaborative thought in which humans and artificial intelligence thought partners can engage, and we propose desiderata for human-compatible thought partnerships. Drawing on motifs from computational cognitive science, we motivate an alternative scaling path for the design of thought partners and ecosystems around their use through a Bayesian lens, whereby the partners we construct actively build and reason over models of the human and world. In this Perspective, the authors advance a view for the science of collaborative cognition to engineer systems that can be considered thought partners, systems built to meet our expectations and complement our limitations.
Heavy-haul railways are important for bulk freight transport, and improving their transport capacity is essential for railway operators to enhance operational efficiency. This study develops an integer linear programming model for train formation planning that maximizes transport capacity, incorporating key practical constraints such as section headway, station capacity, and locomotive matching. This study makes two main contributions: (1) explicit formulation of transport-capacity maximization as the primary objective; and (2) incorporation of specific train formation rules through linear resource-flow coefficients that characterize the combination and decomposition operations. The model is applied to the Shuozhou–Huanghua Railway in a case study. Experimental results show that the optimized train formation plan increases total freight volume from 2810.4 thousand tons to 3080.0 thousand tons, representing a capacity improvement of approximately 9.6%. This result is achieved by adjusting the mix of train tonnage levels, increasing combination operations for medium-capacity trains, and reallocating locomotive types in accordance with traction requirements. The study demonstrates that a capacity-oriented optimization framework can effectively support train-formation plan decisions under practical operational constraints, providing railway operators with a systematic tool to enhance line utilization without expanding infrastructure.
Mechanical engineering and machinery, Machine design and drawing
Engine oil degradation critically influences the performance, efficiency, and longevity of internal combustion engines. Conventional mileage or time-based replacement schedules often result in premature oil changes or delayed servicing, both of which compromise engine health and increase costs. This review examines recent advances in real-time oil condition monitoring and evaluates the feasibility of a low-cost microcontroller-based system that integrates physical sensors with machine learning models for continuous on-board oil health assessment. Drawing on established techniques from industrial lubrication monitoring, we propose an experimental framework that leverages electrical engineering principles, including sensor interface, analog front-end design, signal acquisition, and embedded AI deployment to enable accurate, affordable, and scalable oil health diagnostics. The review highlights opportunities for innovation in embedded systems and electrical engineering design, positioning AI-driven monitoring as a practical solution for predictive automotive maintenance.
Fale Martin, Knez Matjaž, Klimecka-Tatar Dorota
et al.
The implementation of the EU Taxonomy represents a key challenge for organisations operating in production and logistics systems, as it requires not only regulatory compliance but also the development of specific skills and knowledge. While existing research has addressed legal and financial aspects of the taxonomy, limited attention has been given to the competencies required for its practical application. This study aims to determine whether the legislative framework can be used as a structured database for identifying the skills and knowledge necessary to implement the EU Taxonomy and to assess the potential of Do No Significant Harm (DNSH) analysis as a learning and educational tool. The research adopts a qualitative case study approach, using Slovenia as an illustrative example. An analysis of European and national legislative acts was conducted and treated as a structured source of competency requirements. In total, 182 legal acts were reviewed and categorised according to EU Taxonomy environmental objectives. Based on this analysis, a set of 26 competencies was identified, including 11 general and 15 specific skills and knowledge areas relevant to production and logistics activities within organisational contexts. In addition, three DNSH analyses were developed to demonstrate the interdependencies between economic activities and environmental objectives. The results confirm that the legislative framework can serve as a comprehensive basis for identifying taxonomyrelated competencies. Furthermore, DNSH analysis was used to demonstrate its potential as an educational and analytical tool for translating regulatory complexity into actionable and educational insights. The findings contribute to the understanding of capacity-building for EU Taxonomy implementation and provide a transferable foundation for developing education and training programmes across different European contexts.
Machine design and drawing, Engineering machinery, tools, and implements
Federated learning (FL)–a distributed machine learning that offers collaborative training of global models across multiple clients. FL has been considered for the design and development of many FL systems in various domains. Hence, we present a comprehensive survey and analysis of existing FL systems, drawing insights from more than 250 articles published in 2019-2024. Our review elucidates the functioning of FL systems, particularly in comparison with alternative distributed learning approaches. Considering the healthcare domain as an example, we define the building blocks of a typical FL healthcare system, including system architecture, federation scale, data partitioning, open-source frameworks, ML models, and aggregation algorithms. Furthermore, we identify and discuss key challenges associated with the design and implementation of FL systems within the healthcare sector while outlining the directions of future research. In general, through systematic categorization and analysis of existing FL systems, we offer insights to design efficient, accurate, and privacy-preserving healthcare applications using cutting-edge FL techniques.
Federico Ricci, Mario Picerno, Massimiliano Avana
et al.
In order to determine thermally safe driving parameters of ignition coils for hydrogen internal combustion engines (ICE), a reliable estimation of internal power losses is essential. These losses include resistive winding losses, magnetic core losses due to hysteresis and eddy currents, dielectric losses in the insulation, and electronic switching losses. Direct experimental assessment is difficult because the components are inaccessible, while conventional computer-aided engineering (CAE) approaches face challenges such as the need for accurate input data, the need for detailed 3D models, long computation times, and uncertainties in loss prediction for complex structures. To address these limitations, we propose an artificial intelligence (AI)-based framework for estimating internal losses from external temperature measurements. The method relies on an artificial neural network (ANN), trained to capture the relationship between external coil temperatures and internal power losses. The trained model is then employed within an optimization process to identify losses corresponding to experimental temperature values. Validation is performed by introducing the identified power losses into a CAE thermal model to compare predicted and experimental temperatures. The results show excellent agreement, with errors below 3% across the −30 °C to 125 °C range. This demonstrates that the proposed hybrid ANN–CAE approach achieves high accuracy while reducing experimental effort and computational demand. Furthermore, the methodology allows for a straightforward determination of the coil safe operating area (SOA). Starting from estimates derived from fitted linear trends, the SOA limits can be efficiently refined through iterative verification with the CAE model. Overall, the ANN–CAE framework provides a robust and practical tool to accelerate thermal analysis and support coil development for hydrogen ICE applications.
Mechanical engineering and machinery, Machine design and drawing
Fawzan Salem, Immanuel Kelekwang, Muzi Siphilangani Ndlangamandla
et al.
This paper presents a fault-tolerant control strategy that dynamically reconfigures the proposed system, and the inverter leg with a fault is isolated through a MOSFET-based clamping branch. With the use of a modified Vector Control (VC) and Pulse-Width Modulation (PWM) technique, the remaining two phases can continue operating. MATLAB/Simulink is used to create a thorough simulation model that examines various fault scenarios and evaluates how well the control process adjusts to each one. The obtained findings demonstrate that, in the event of a fault, the system can maintain accurate speed regulation, maintain a tolerable current balance, and deliver steady torque. The obtained findings demonstrate that, in the event of a fault, the system can maintain accurate speed regulation, maintain a reasonable current balance, and deliver steady torque. In contrast to traditional methods that rely on hardware redundancy, this software-driven technique maintains the electric vehicle’s functionality even when a malfunction arises. In just a few milliseconds, normal operation is restored without the need for more sensors or additional expenses. Because of these characteristics, the suggested approach is a sensible option for actual EV applications.
Mechanical engineering and machinery, Machine design and drawing
This study investigates the knowledge, perception and trust in Advanced Driver Assistance Systems (ADAS) among drivers in Eastern Sicily, a Mediterranean region characterized by infrastructural and socio-economic differences. A structured survey (N = 961) was conducted to assess user attitudes towards eight key ADAS technologies using two validated indices: the Knowledge Index (KI) and the Importance Index (II). To capture user consistency, a normalized product (z(KI) × z(II)) was calculated for each technology. This composite metric enabled the identification of three latent dimensions through exploratory factor analysis: Emergency-Triggered Systems, Adaptive and Reactive Systems and Driver Vigilance and Stability Systems. The results show a clear discrepancy between perceived importance (56.6%) and actual knowledge (35.1%). Multivariate analyses show that direct experience with ADAS-equipped vehicles significantly increases both awareness and confidence. Age is inversely correlated with knowledge, while gender has only a marginal influence. The results are consistent with established acceptance models such as TAM and UTAUT, which emphasize the role of perceived usefulness and trust. The study presents an innovative integration of psychometric metrics and behavioral theory that provides a robust and scalable framework for assessing user readiness in evolving mobility contexts, particularly in regions facing infrastructural heterogeneity and cultural changes in travel behavior.
Mechanical engineering and machinery, Machine design and drawing
For vertical takeoff and landing (VTOL) control of distributed-propulsion, fixed-wing UAVs exhibiting strong nonlinearity and aerodynamic/propulsive coupling, traditional linearization methods incur significant modeling errors in pitch–roll coupling and vortex interference scenarios due to neglected high-order nonlinearities, leading to inherent control law limitations. This study focuses on a non-tilting, distributed-propulsion VTOL UAV featuring integrated airframe-propulsion design. Each of its four propulsion units contains six ducted rotors, arranged in tandem wing configuration on both fuselage sides. A revised propulsion–aerodynamic coupling model was established and validated through bench tests and CFD data, enabling the design of an Incremental Nonlinear Dynamic Inversion (INDI) control architecture. The UAV dynamics model was constructed in Matlab/Simulink incorporating this revised model. An INDI-based attitude control law was developed with cascade controllers (angular rate inner-loop/attitude outer-loop) for VTOL mode, integrated with propulsion-system and control-surface allocation strategies. Digital simulations validated the controller’s effectiveness and robustness. Finally, tethered flight tests with physical prototypes confirmed the method’s applicability for high-precision control of strongly nonlinear distributed-propulsion UAVs.
Mechanical engineering and machinery, Machine design and drawing
Michael A. Bekos, Giordano Da Lozzo, Fabrizio Frati
et al.
A well-known result by Kant [Algorithmica, 1996] implies that n-vertex outerplane graphs admit embedding-preserving planar straight-line grid drawings where the internal faces are convex polygons in $O(n^2)$ area. In this paper, we present an algorithm to compute such drawings in $O(n^{1.5})$ area. We also consider outerplanar drawings in which the internal faces are required to be strictly-convex polygons. In this setting, we consider outerplanar graphs whose weak dual is a path and give a drawing algorithm that achieves $Θ(nk^2)$ area, where $k$ is the maximum size of an internal facial cycle.
Erwin Sitompul, Raden Hilary Ardanta Yoga, Mia Galina
Technology continues to develop, especially in the world of manufacturing. Processes done manually by humans are replaced gradually by machines through automation. This paper proposes a batik drawing machine with Arduino-based computer numerical control (CNC). The intention is to reduce the production of small-sized batik products by eliminating the sketching process of the batik design on the fabric. Besides, the expertise in using canting, a pen-like tool, to apply the liquid wax on the fabric will not be required. A prototype of a batik drawing machine was designed and constructed using main components such as Arduino Mega 2560, NEMA17 HS4401 stepper motor, and RAMPS 1.4 controller board. The batik design data is to be prepared by using a graphic editor, computer-aided design (CAD), and computer-aided manufacturing (CAM) software. After several trials, the best setting for the canting temperature was found to be 112 °C with a drawing speed of 25 steps/mm and a 3 mm distance between the cloth and the tip of the canting. Three batik designs with different difficulty levels were tested for fabric printing. The fabrics were colored to obtain the final results. The batik products with a diameter of up to 450 mm can be finished satisfactorily
Why do security cameras, sensors, and siri use cloud servers instead of on-board computation? The lack of very-low-power, high-performance chips greatly limits the ability to field untethered edge devices. We present the NV-1, a new low-power ASIC AI processor that greatly accelerates parallel processing (> 10X) with dramatic reduction in energy consumption (> 100X), via many parallel combined processor-memory units, i.e., a drastically non-von-Neumann architecture, allowing very large numbers of independent processing streams without bottlenecks due to typical monolithic memory. The current initial prototype fab arises from a successful co-development effort between algorithm- and software-driven architectural design and VLSI design realities. An innovative communication protocol minimizes power usage, and data transport costs among nodes were vastly reduced by eliminating the address bus, through local target address matching. Throughout the development process, the software and architecture teams were able to innovate alongside the circuit design team's implementation effort. A digital twin of the proposed hardware was developed early on to ensure that the technical implementation met the architectural specifications, and indeed the predicted performance metrics have now been thoroughly verified in real hardware test data. The resulting device is currently being used in a fielded edge sensor application; additional proofs of principle are in progress demonstrating the proof on the ground of this new real-world extremely low-power high-performance ASIC device.
In order to solve the problem that digging lotus roots manually was high in labor intensity, low in efficiency and easy to damage lotus roots, and, in view of the defects of the high cost of existing digging lotus roots equipment and the cumbersome operating process needing a certain experience in technology, a jetting spin type digging lotus root machine is designed. Combined with the mechanism of hydraulic digging lotus root, a rotation pipeline is designed, so as to simplify the whole machine structure and increase the digging width. It takes only manpower or vehicles to push forward to perform digging lotus root work, with simple operation and low manufacturing cost. Pro/Engineer 3D design software and CAD 2D drawing software are used to design key working parts such as rotation pipeline, spray-head, nozzle, etc. In addition, key parameters of nozzle structure are designed. Through validation, the intensity of jet flow impact force produced by the diameter 17 mm nozzle to lotus root surface is 97.22 N, and the pressure is 0.20 MPa, which produces no damage to lotus root. By means of a mechanical analysis method, combined with CFD flow field analysis and fluid dynamics analysis, the rotational speed mathematical model of rotation pipeline in water is established through MATLAB software solving and calculating. In addition, the influence of nozzle structural parameters on rotational speed of rotation pipeline is made clear. By using the kinematic analysis method, the rotational speed mathematical model of rotation pipeline associated with the jetting impact frequency of single point and the time of each impact is established, and from which the restricting factors of the working speed of jetting spin type digging lotus root machine is obtained, so as to improve the efficiency of digging lotus roots machine under the premise of ensuring the digging depth and the quality of lotus roots. Through the CFD flow field analysis and dynamic analysis, the mathematical model of loss power of rotating pipeline is established. Through comprehensive analysis, the mathematical model of working speed associated with digging time and speed of rotary pipe and effective range radius of jet impact for digging lotus root machine is obtained, which provides a theoretical basis for adjustment of working parameters of digging lotus root machine.
Daniel S. Fowler, Carsten Maple, Gregory Epiphaniou
We provide a practical implementation of a free space optical quantum key distribution (FSO-QKD) system within a vehicle-to-infrastructure (V2I) application developed under the Innovate UK AirQKD project. The FSO-QKD system provides the quantum secure encryption keys that serve as the foundation for secure communications throughout the V2I application to address known concerns over V2I security. This document includes summaries of the quantum key generation process and the deployed V2I technology. Subsequently, a high-level view of the system design, the practical experiment, and its execution are presented. Multiple AirQKD project partners developed technologies ranging from semiconductors and hardware to security protocols and software, to enable the QKD-secured V2I system. The developed technology includes a novel zero-trust security protocol used to protect the V2I communications, ensuring that spoofed V2I messages from a compromised device are not accepted by the system.
Mechanical engineering and machinery, Machine design and drawing
Oswin Aichholzer, Birgit Vogtenhuber, Alexandra Weinberger
Simple drawings are drawings of graphs in which any two edges intersect at most once (either at a common endpoint or a proper crossing), and no edge intersects itself. We analyze several characteristics of simple drawings of complete multipartite graphs: which pairs of edges cross, in which order they cross, and the cyclic order around vertices and crossings, respectively. We consider all possible combinations of how two drawings can share some characteristics and determine which other characteristics they imply and which they do not imply. Our main results are that for simple drawings of complete multipartite graphs, the orders in which edges cross determine all other considered characteristics. Further, if all partition classes have at least three vertices, then the pairs of edges that cross determine the rotation system and the rotation around the crossings determine the extended rotation system. We also show that most other implications -- including the ones that hold for complete graphs -- do not hold for complete multipartite graphs. Using this analysis, we establish which types of isomorphisms are meaningful for simple drawings of complete multipartite graphs.
We study methods to manipulate weights in stress-graph embeddings to improve convex straight-line planar drawings of 3-connected planar graphs. Stress-graph embeddings are weighted versions of Tutte embeddings, where solving a linear system places vertices at a minimum-energy configuration for a system of springs. A major drawback of the unweighted Tutte embedding is that it often results in drawings with exponential area. We present a number of approaches for choosing better weights. One approach constructs weights (in linear time) that uniformly spread all vertices in a chosen direction, such as parallel to the $x$- or $y$-axis. A second approach morphs $x$- and $y$-spread drawings to produce a more aesthetically pleasing and uncluttered drawing. We further explore a "kaleidoscope" paradigm for this $xy$-morph approach, where we rotate the coordinate axes so as to find the best spreads and morphs. A third approach chooses the weight of each edge according to its depth in a spanning tree rooted at the outer vertices, such as a Schnyder wood or BFS tree, in order to pull vertices closer to the boundary.
We define some Schnyder-type combinatorial structures on a class of planar triangulations of the pentagon which are closely related to 5-connected triangulations. The combinatorial structures have three incarnations defined in terms of orientations, corner-labelings, and woods respectively. The wood incarnation consists in 5 spanning trees crossing each other in an orderly fashion. Similarly as for Schnyder woods on triangulations, it induces, for each vertex, a partition of the inner triangles into face-connected regions (5~regions here). We show that the induced barycentric vertex-placement, where each vertex is at the barycenter of the 5 outer vertices with weights given by the number of faces in each region, yields a planar straight-line drawing.
It is shown that every $n$-vertex graph that admits a 2-bend RAC drawing in the plane, where the edges are polylines with two bends per edge and any pair of edges can only cross at a right angle, has at most $20n-24$ edges for $n\geq 3$. This improves upon the previous upper bound of $74.2n$; this is the first improvement in more than 12 years. A crucial ingredient of the proof is an upper bound on the size of plane multigraphs with polyline edges in which the first and last segments are either parallel or orthogonal.
ABSTRACT The development of artificial intelligence (AI) made human feel the pressure of machine competition. The architectural industry focuses on whether the AI will replace manpower. This study is an exploratory one. The problems that AI will have in the practice of architectural design are discussed through semi-structured interviews with architects, draftsmen, drawing reviewers, construction company owners, and professors of architecture. This study proposes an extended robotic architectural technology acceptance model with five facets and ten elements. This model highlights two dimensions, namely, specialised field diversity and controllable flexibility. This study provides new three implications in the future, namely, development direction, theoretical framework, and industry guidance, in the architectural design with artificial intelligence. Diversity and flexibility are important research directions for the development of AI robotic architects, just as fluctuations phenomenon in human capabilities can lead to a mutation effect in the design. Human beings need to contribute their own emotional intelligence, and replace competitive relationship with complementary mode of extended intelligence. Similar to any new technology, AI may create many jobs no less than it replaces.