Teerapong Poltue, Chao Zhang, Frédéric Demoly
et al.
Active composite (AC) plates, composed of active and passive materials, can undergo complex shape transformations when stimulated. Leveraging 4D printing—which combines additive manufacturing with stimuli‐responsive materials—digitally encoded design patterns offer flexibility in shape morphing. However, performing inverse design, i.e., determining the pattern to achieve a desired shape, remains challenging due to the vast design space. Recently, machine learning (ML) has been applied to inverse design tasks with promising results. Nevertheless, these approaches require large datasets, and even then, inverse design remains difficult, often demanding multiple strategies and trials to obtain optimal results. To address these challenges, this work introduces an iterative data curation strategy combined with transfer learning. This method ensures that newly curated data is nonredundant and distinct from existing datasets, reducing the required training data by a factor of eight while maintaining performance. Additionally, ML models are integrated with a genetic algorithm (ML‐GA) to further fine‐tune the generated design patterns. The results show that ML‐GA enhances accuracy in achieving the desired shape while reducing computational effort. This framework offers an efficient and scalable approach for inverse design, reducing data needs and improving performance, making it a valuable tool for AC plate design and 4D printing.
Computer engineering. Computer hardware, Control engineering systems. Automatic machinery (General)
Steerable catheters offer significant advantages over conventional catheters, including enhanced control, stability, and accessibility, which reduce operational complexity, fluoroscopy time, and radiation exposure, positioning them as a promising advancement for vascular interventional procedures. Herein, a novel steerable catheter is presented, featuring a hydraulically actuated, soft, steerable tip that allows for real‐time visualization in X‐ray imaging. To optimize performance, several silicone materials were evaluated for their mechanical properties, resulting in a soft tip design with a diameter of 2.6 mm. The tip incorporates an internal tool channel and supports a large bending angle of 180°. The tip demonstrates an average response time of 1.141 s (±0.750 s), a maximum output force of 0.145 N (±0.001 N), and a maximum radial expansion of 1.121 (±0.006). A steering kinematic model of the catheter tip is developed to simulate its movement. The catheter tip's real‐time shape and position information are obtained through intelligent segmentation and neighborhood‐based endpoint detection methods, assisting the surgeon during superselective procedures. The catheter's visibility and flexibility are validated in a live porcine model, demonstrating its potential for future use in interventional procedures.
Computer engineering. Computer hardware, Control engineering systems. Automatic machinery (General)
Abstract Knock-In event prediction is one of the most crucial tasks in Equity-Linked Securities (ELS) investment. Simply relying on the contract terms is insufficient for reliable predictions. To address this limitation, this study integrates macroeconomic features from the Federal Reserve Economic Data Monthly Database (FRED-MD) and the Quarterly Database (FRED-QD) with contract terms, thereby capturing broader economic influences. Furthermore, to refine the work on these macroeconomic signals, we introduce a Time-Feature Blender (TFBlender). Built on attention mechanisms, the TFBlender operates along two paths: time and features. On the time-step token path, it captures both short- and long-term patterns in data, while on the feature token path, multi-head attention analyzes interactions among diverse features. TFBlender achieves a Knock-In F1 of 0.896 and an AUROC of 0.908, accurately detecting Knock-In events while minimizing false alarms. This predictive capability provides investors with early insights into potential ELS risks, enabling more proactive decision making. Additionally, applying SHAP reveals the macroeconomic factors that drive TFBlender’s predictions, helping practitioners focus on key inputs and optimizing resources for more efficient modeling. By comprehensively integrating economic features with specialized attention mechanisms, the proposed framework enhances detection reliability, representing a significant advance in ELS risk management.
Computer engineering. Computer hardware, Information technology
Carbon Capture, Utilization and Storage (CCUS) is a topic of interest for its relevance in decreasing the emissions to the atmosphere of CO2, a powerful greenhouse gas, related to the industrial production and power generation by fossil fuels. Aqueous amine solutions can be used as chemical solvents for this aim, though the high energy consumption and the related operating costs, their toxicity and the corrosion issues related to their use do not favor their application on the large scale.
The research on novel solvents for CO2 removal, that could overcome the disadvantages of the traditional solvents, requires the analysis of phase equilibria of systems for which physical-chemical properties cannot be found in detail in the literature. In particular, the solubility of gases, mainly CO2, in the mixture to be considered, is fundamental to understand the suitability of a new species as solvent for chemical or physical absorption.
With the aim of overcoming the issues due to the lack of experimental data on novel systems, an experimental unit has been installed at the Process Thermodynamics laboratory (PT lab) of Politecnico di Milano aimed at collecting data of solubility and diffusivity of gases into low volatile liquids that could be used as solvents for CO2 capture. A detailed specific experimental procedure has been defined and the unit has been firstly operated for validation, by collection of solubility data of CO2 into a 30% wt. MonoEthanolAmine (MEA) solvent, one of the most developed solvents already industrially used. Both the conditions of the absorption section and of the regeneration section, operating at different temperatures, have been considered. Then, the description of the equilibrium attained in the experimental unit has been carried out, taking into account different thermodynamic models and selecting the one best describing the system.
Chemical engineering, Computer engineering. Computer hardware
The purpose of the research is to evaluate the accuracy and reliability of methods for measuring the impedance of a biological material and to develop recommendations for improving algorithms for the development of software and hardware complexes in the field of biomedical diagnostics. Considerable attention is paid to the analysis of data obtained in Vivo.Methods. 400 measurements were performed on a group of 20 volunteers using electrical thermal effects to obtain amplitude-phase frequency characteristics of the impedance of biological tissues. During the experiment, the Cole method was used to determine coefficients reflecting the key parameters of the test tissue and its impedance characteristics. To generate the test signals, sequences of single-frequency sinusoidal signals were used, controlled by software on the E20-10 platform, specially designed for digitizing data and analyzing transients in living tissues.Results. Based on the E20-10 data acquisition system manufactured by L-Card CJSC, a complex for receiving and processing impedance data was developed, including software implemented in the Delphi language designed to generate and process test signals. The in Vivo results showed average discrepancies within 4% between the measured and expected values, which confirms the high accuracy and reliability of the proposed approach to measuring the resonance of biological tissues.Conclusion. The implementation of software for measuring biomaterial impedance using the developed algorithms and applied amplitude-phase frequency characteristics provides a more accurate assessment of the dissipative properties of biological tissues. Data analysis has shown the possibilities and prospects of developing high-precision classifiers for a decision support system for early diagnosis of medical risks. These classifiers can be especially useful for identifying predisposition to lung diseases such as pneumonia and tuberculosis. Further research in this field can lead to significant progress in the creation of effective software and hardware complexes for biomedical diagnostics, contributing to the improvement of the prevention and treatment of various pathologies, taking into account the individual characteristics of the patien
Andrew J. Moodie, Eric Barefoot, Eric Hutton
et al.
Abstract. Geomorphologists have more data and computational resources available than ever before. Collaboration between researchers specializing in different modes of inquiry (e.g., numerical, experimental, and field-based) often accelerates impactful scientific insights, but tools to facilitate these collaborations are lacking. In this article, we present four challenges to collaboration in the geomorphology community, and provide a framework that addresses these challenges to enable research utilizing the full extent of data and computational resources available today. We report a component of this framework, a newly developed specification for a shareable data schema called sandsuet. The schema is designed to accommodate most kinds of rasterized geomorphology data, and makes it easy to package, publish, and share those data. Finally, we present possibilities for community development of resources to address other challenges to collaboration in geomorphology.
This article explores how phased antenna arrays can enhance Low Earth Orbit (LEO) satellite reception systems, while
addressing cybersecurity challenges in wireless communications. A conceptual design is proposed to tackle the variable
dynamics of LEO satellites and meet the increasing demands of satellite communication systems for future wireless
applications. The study highlights the advantages of this approach over traditional beamsteering methods. Integrating
advanced artificial intelligence (AI), digital signal processing (DSP), and software-defined radio (SDR) is
identified as a transformative strategy, improving adaptability and optimization for phased antenna arrays,
particularly in mitigating RF threats. Beamforming evaluations demonstrate how adjusting the phases and amplitudes
of feeding signals significantly impacts radiation patterns, enhancing the quality of received signals. The
paper's main contribution lies in its comprehensive analysis of key challenges in LEO satellite communications,
emphasizing the role of phased antenna arrays alongside AI and SDR. As cyber threats rise, the findings underscore
the urgent need for further research into RF protection to secure communication systems in the rapidly evolving
landscape of IoT and satellite technologies.
Bernardo Patella, Sonia Carbone, Luigi Roberto Oliveri
et al.
Green hydrogen is a real alternative to change the current energy system. Electrochemical water splitting is considered an attractive solution to convert and store the surplus of renewable energy sources. However, hydrogen production by water electrolysis is not economically sustainable due to the use of high noble metals as catalysts (generally platinum or palladium). In order to reduce costs, in this work we have synthesized a ternary alloy of nickel, iron and sulfur and used it as the cathode in an alkaline electrolyzer to produce hydrogen from water.
Furthermore, to increase the features of the proposed alloy, this material was synthesized into the pore of a polycarbonate membrane to obtain a nanostructured electrode that exposes a very high surface area to the solution and consequently a large number of electrocatalytic active sites. The electrode fabrication was carried out by potential-controlled pulsed electrochemical deposition where the potential switch from -0.45 V to -1.3 V vs. SCE for 60 cycles. The electrode was characterized by SEM and EDS showing the nanostructured nature and the composition of the electrode. Then it was tested as the cathode in an alkaline electrolyzer (30% KOH) at room temperature. Preliminary results show that the addition of sulfur to the alloy permits to increase in the electrode features compared to the binary alloy of nickel and iron.
Chemical engineering, Computer engineering. Computer hardware
This paper provides necessary properties to algorithmically secure firstorder maskings in scalar micro-architectures. The security notions of threshold implementations are adapted following micro-processor leakage effects which are known to the literature. The resulting notions, which are based on the placement of shares, are applied to a two-share randomness-free PRESENT cipher and Keccak-f. The assembly implementations are put on a RISC-V and an ARM Cortex-M4 core. All designs are validated in the glitch and transition extended probing model and their implementations via practical lab analysis.
Computer engineering. Computer hardware, Information technology
Daniela Manrique, David Troncoso, Agustina Buccella
et al.
Data analysis is a widely researched field, where innumerable applications allow to discover domain particularities that are specially useful. In this paper, we introduce the data analysis process that we applied to two different systems storing information about statements and testimonies of crimes against Humanity. We describe the activities, design decisions and lessons learned from implementing a specific goal, which involves transforming text data into georeferenced information.
This paper presents a constant-time implementation of Classic McEliece for ARM Cortex-M4. Specifically, our target platform is stm32f4-Discovery, a development board on which the amount of SRAM is not even large enough to hold the public key of the smallest parameter sets of Classic McEliece. Fortunately, the flash memory is large enough, so we use it to store the public key. For the level-1 parameter sets mceliece348864 and mceliece348864f, our implementation takes 582 199 cycles for encapsulation and 2 706 681 cycles for decapsulation. Compared to the level-1 parameter set of FrodoKEM, our encapsulation time is more than 80 times faster, and our decapsulation time is more than 17 times faster. For the level-3 parameter sets mceliece460896 and mceliece460896f, our implementation takes 1 081 335 cycles for encapsulation and 6 535 186 cycles for decapsulation. In addition, our implementation is also able to carry out key generation for the level-1 parameter sets and decapsulation for level-5 parameter sets on the board.
Computer engineering. Computer hardware, Information technology
In the field of object detection in remote sensing images, most of the existing object detection algorithms perform poorly for small objects.This paper proposes an algorithm that fuses multi-scale features for object detection in remote sensing images.The features are first extracted by using the basic network of the SSD algorithm to form a feature map pyramid.Then the feature map fusion module is designed to fuse the position information of the shallow feature map and the semantic information of the deep feature map, retaining rich context information.Finally, a module to remove redundant information is designed, and the features in the feature map are further extracted through the convolution operation.The feature information is also screened to reduce the aliasing effect brought by the fusion of the feature maps.The experimental results on NWPU VHR-10, a dataset of remote sensing images, show that the proposed algorithm achieves an average detection accuracy of 93.9%, demonstrating that it outperforms Faster R-CNN, SSD and other algorithms in detection of small objects in remote sensing images.
ABSTRACT The process of modern photogrammetry converts images and/or LiDAR data into usable 2D/3D/4D products. The photogrammetric industry offers engineering-grade hardware and software components for various applications. While some components of the data processing pipeline work already automatically, there is still substantial manual involvement required in order to obtain reliable and high-quality results. The recent development of machine learning techniques has attracted a great attention in its potential to address complex tasks that traditionally require manual inputs. It is therefore worth revisiting the role and existing efforts of machine learning techniques in the field of photogrammetry, as well as its neighboring field computer vision. This paper provides an overview of the state-of-the-art efforts in machine learning in bringing the automated and ‘intelligent’ component to photogrammetry, computer vision and (to a lesser degree) to remote sensing. We will primarily cover the relevant efforts following a typical 3D photogrammetric processing pipeline: (1) data acquisition (2) geo-referencing/interest point matching (3) Digital Surface Model generation (4) semantic interpretations, followed by conclusions and our insights.
Contribution: Portable learning instrumentation has become common in university classrooms and laboratories, but few publications assess the effects of these technologies on student retention. This paper addresses this under-researched connection between the use of portable learning technologies, incorporated into an Introduction to Computer Engineering course, and student retention. Background: The desire for active learning experiences has promoted the use of portable, hands-on technologies in classrooms and laboratories. However, published results from such efforts do not often assess the impact of such tools on student retention. In Fall 2015, the Kansas State University Department of Electrical and Computer Engineering overhauled an introductory computer engineering course, incorporating portable learning tools with the aims to increase student retention, where a secondary focus related to helping students understand the limitations of portable hardware platforms. Intended Outcomes: The goal was to improve student confidence and the retention of first- and second-year students who took the course. Application Design: Laboratory exercises used portable technologies and focused on hardware limitations. Summative surveys helped to quantify the impact of the new course structure on student confidence. The retention of first- and second-year students who took the course was also investigated. Findings: Survey results indicated that the course transformation positively affected student confidence (measured directly and indirectly). Retention of second-year students who took the course improved to a two-year average of 51%, from a 40% average for the three prior years.
Gonzalo Farias, E. Fabregas, Emmanuel Peralta
et al.
The use of mobile robots for teaching automatic control is becoming more popular in engineering curricula. Currently, many robot simulators with high-graphical capabilities can be easily used by instructors to teach control engineering. However, the use of real robots is not as straightforward as simulations. There are many hardware and software details that must be considered before applying control. This paper presents the development of an easy-to-use platform for teaching control of mobile robots. The laboratory has been carefully designed to conceal all technical issues, such as communications or the localization that do not address the fundamental concepts of control engineering. To this end, a position sensor based on computer vision has been developed to provide the positions of the robots on the platform in real time. The Khepera IV robot has been selected for this platform because of its flexibility and advanced built-in sensors but the laboratory could be easily adapted for similar robots. The platform offers the opportunity to perform laboratory practices to test many different control strategies within a real experimental multi-agent environment. A methodology for using the platform in the lab is also provided.
This study aimed to analyse the winter indoor thermal environment of double-story commercial and residential building in herdsmen settlements of China Northwest mountain grassland area. The method of research is ?eld testing and data calculation analysis; include indoor air temperature and humidity, outdoor air temperature and humidity, outdoor wind speed, thermal comfort index. The result shows the relationship between indoor thermal environment, envelope materials, heating methods, location of rooms and building type. In addition, the in?uence was quanti?ed in 0~6.9 °C in winter. Finally, put forward three strategies to enhance the winter double-story commercial and residential building indoor environment.
Chemical engineering, Computer engineering. Computer hardware
Siti Suhaili Shahlan, Kamarizan Kidam, Ljiljana Medic-Pejic
et al.
Hydrogen can store and deliver usable energy, but it does not typically exist by itself in nature and must be produced from compounds that contain it such as biomass. Hydrogen can be used as fuel which produce from gasification process that used renewable sources as feedstock. Large amount of empty fruit bunch (EFB) has been produced in Malaysia and yet has no specific used in large quantity and it is being incinerated or used as landfill material dumped in the plantation. These situations have led to increased CO2 and other greenhouse gas (GHG) emissions in the atmosphere. During preliminary study, it shows that there are very limited studies being done in the process design development of the hydrogen production by using EFB from oil palm. Despite of tremendous experimental studies done on the effectiveness of using EFB for production of hydrogen, the process implementation in industry is still discouraging. This is due to lack of proven technology and high capital cost of investment. In this study, the drying, gasification and purification unit operations were modelled in Aspen Plus simulator for production of pure hydrogen gas and char was removed significantly after several gas cleaning processes. The final product for purified hydrogen gas is 12.3 t/h which is 16.3 % of hydrogen gas produced from the total EFB feedstock. Based on the result, the optimum temperature and pressure for gasification process is 850 °C and 1 atm respectively. Since, there is not much research have been carried out on process design of hydrogen production process by using EFB as feedstock, the understanding towards this topic can be prolonged.
Chemical engineering, Computer engineering. Computer hardware