Miracle-dz/UniFAR-FTUs huggingface dataset:
Synchrosqueezing Transform and Non-Negative Matrix Factorization based Feature Extraction from EEG Signals for Motor Imagery Classification

Motor imagery (MI) refers to the mental representation of movement without any motor action. Effective classification of MI tasks is promising for patients with motor disabilities. However, achieving a reliable MI task classification by electroencephalography (EEG) is challenging. The purpose of the study is to improve classification performance by providing discriminative features of intent in MI tasks. In this study, a matrix decomposition technique, namely Non-Negative Matrix Factorization (NMF) is adopted for feature extraction from time-frequency distributions (TFD) obtained by the Waveletbased Synchrosqueezing Transform (WSST). EEG signals were meticulously cleared of noise by Independent Component Analysis (ICA) before performing NMF. Then, the various features such as skewness, kurtosis, discontinuity, standard deviation and sparsity were extracted from NMF vectors in order to train five different classifiers, namely Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Decision Tree (DT), Random Forest (RF) and AdaBoost. WSST provides energy distributions with highly localization capability in TFD, using the reassignment technique. TFDs showed distinctive energy spikes for right-and left-hand MI tasks. The experimental results revealed that the proposed method approaches outstanding accuracy (>95%), kappa (>0.90), and F1 score (0.99) by using KNN, RF, DT and AdaBoost. The study results also show that WSST-based NMF features are promising for MI task classification.
Design and Fabrication of a Sensorized Soft Actuator via Embedded 3D Printing

The application of soft sensors significantly enhances the functionality of soft robotics. However, most sensorized soft robots need to be fabricated by multi-step manual methods, which are cumbersome and time-consuming. Here, we design a sensorized pneumatic actuator and print it entirely without any molds or sacrificial support structures using multi-material embedded 3D (EMB3D) printing. This effective and economic strategy achieves the integrated manufacturing of the network of actuators and sensors and simplifies the design and fabrication process of soft robotics. The finite element analysis (FEA) simulations of actuator bending behaviors are conducted and the comparisons between simulations and experiments verify the effectiveness of EMB3D printing. The soft strain sensor integrated on the top surface can detect the bending angle of the actuator with good linearity and sensitivity. Furthermore, a sensorized soft gripper assembled with two printed actuators is used to grasp objects of different sizes. The integrated sensor can estimate the grasping state and estimate the size of the object potentially, which is essential for closed-loop feedback control.
Radar Cross Section Modeling of Complex Objects. Application to a Target Over Sea Surface

The work presented here involves studying the interaction of electromagnetic (EM) waves with complex targets observed in bistatic and monostatic configuration. So, an efficient approach for calculating Radar Cross Section (RCS) of an arbitrary target which is modeled with a sum of triangular facets. The proposed model uses the Physical Optics (PO) to compute the first order reflection (direct scattering (SR)), and Geometrical Optics GO) to track the path of reflected ray and PO to compute the second order reflection (DR). The proposed model is validated by comparing the theoretical results with the FEKO simulation results, which are then applied to the ocean scene by considering both sea surface and marine target as a single complex target.
Capitalizing on a Small Dataset to Refine a Mixed Methods Study

Learning to use computational tools is a critical aspect of many first-year engineering courses. Students in these courses can have varying degrees of prior exposure to computational tools and often exhibit a wide range of intrinsic motivation for learning these skills. Interviews with first-year engineering students were conducted to study the degree to which motivation correlated with intended major within engineering. The pilot round of interviews was conducted in the spring of 2021. This pilot study used the same data set of 8 interviews to progressively refine both the survey and interview collection in the 2021 – 2022 academic year. This paper will review the results of the pilot study and detail the process used to develop and use the finalized protocol and coding schemes for a planned series of 20 interviews in Summer 2022. While this technique developed because of limited data collection during the COVID-19 pandemic, it has been beneficial to the researcher and may provide guidance for future researchers.
A Novel Predictor with Optimized Sampling Method for Hardware-aware NAS

Designing suitable neural networks in resource-constrained scenarios is a very challenging problem. It means the network architecture must not only have excellent performance on the target task but also meet the requirements of the deployment platform. In previous works, hardware-aware neural architecture search is proposed to automatically search for such architectures by integrating hardware attributes into the neural architecture search (NAS) process. However, hardware-aware NAS methods suffer from the difficulty of architecture evaluation and multi-objective optimization. Using a predictor to directly output the defined evaluation score of the architecture is a good solution, which is both efficient and accurate.In this work, we design a novel multi-objective predictor framework, which better reflects the differences in multi-objective optimization and is more suitable for hardware-aware NAS. We transfer the knowledge of single-objective predictors from different perspectives to the designed multi-objective predictor structure and define the decoding rule with the specific multi-objective score. In addition, higher-performance architecture sampling (HPAS) is proposed to selectively collect training samples from the search space instead of simple random sampling. Because for NAS, the status of architectures is unequal, and high-performance architectures are more important than low-performance architectures. By increasing the proportion of the former in the training dataset, we can obtain better performance under the same actual measurements. Experimental results in multiple scenarios based on NAS-BENCH-201 and HW-NAS-BENCH prove the effectiveness of our methods. This work can also be applied to other hardware platforms, such as control chips in specific fields.
Dissipational Galaxy Formation. I. Effects of Gasdynamics

Numerical simulations of hierarchical galaxy formation including gasdynamics are presented. These simulations are conducted using a new, general-purpose programs for evolving self-gravitating systems in three dimensions. The gravitational forces are calculated with a hierarchical tree algorithm, while the gasdynamic properties are determined by an approach known as smoothed particle hydrodynamics. In this method the complete thermodynamic state of the gas is known everywhere, so dissipational effects can be included by allowing the gas to cool radiatively. We use standard cooling curves that include Compton, as well as radiative, cooling
ColorWater: A Diverse Dataset and Benchmark for Semantic Water Surface Understanding

Intelligent water environment monitoring has received global attention. Providing researchers with a water surface dataset with sufficient data and diversity is an important support for training and evaluating the water surface understanding model. However, current water surface datasets lack high-quality and rich annotations of various floating objects on real-world water surfaces, resulting in a partial understanding of the water surface by existing intelligent monitoring methods of the water environment. To address this, we present ColorWater, a diverse semantic segmentation dataset tailored for comprehensively understanding the complex water surface. ColorWater contains 1279 complex water images and pixel-level annotations consisting of 9 categories and 10942 objects and stuff. Our effort exceeds previous datasets in terms of annotation richness and scene complexity. In ColorWater, there exists scale diversity in which the small objects are the majority. Thus, we propose a new global evaluation metric, SWIoU (Scale Weight IoU), to improve the sensitivity of the global metric for the segmentation of differentscale objects and reasonably evaluate the global performance of semantic water surface segmentation models. We further provide an in-depth analysis of annotation inconsistency and dataset’s characteristics. Moreover, we also build a benchmark evaluation of semantic segmentation methods in the ColorWater. Our dataset is publicly available at https://github.com/L-cuixiao/ColorWater.
Biological Activity of Pumpkin Byproducts: Antimicrobial and Antioxidant Properties

Pumpkin fruits are widely appreciated and consumed worldwide. In addition to their balanced nutritional profile, pumpkin species also present valuable bioactive compounds that confer biological and pharmacological properties to them. However, the seeds, peels, and fibrous strands resulting from pumpkin processing are still poorly explored by the food industry. The current study used those fruit components from the genotypes of pumpkin that are economically significant in Portugal and Algeria to produce bioactive extracts. In order to support their usage as preservatives, their phenolic content (HPLC-DAD-ESI/MS) and antioxidant (OxHLIA and TBARS) and antimicrobial properties (against eight bacterial and two fungal strains) were assessed. In terms of phenolic profile, the peel of the Portuguese ‘Common Pumpkin’ showed the most diversified profile and also the highest concentration of total phenolic compounds, with considerable concentrations of (-)-epicatechin. Regarding the antioxidant capacity, the seeds of ‘Butternut Squash’ from both countries stood out, while the fibrous strands of Portuguese ‘Butternut Squash’ and the seeds of Algerian ‘Gold Nugget Pumpkin’ revealed the strongest antimicrobial activity. The bioactive compounds identified in the pumpkin byproducts may validate their enormous potential as a source of bio-based preservatives that may enhance consumers’ health and promote a circular economy.
Exploring Professional Identity Development Research on Displaced Higher Education Students

In university, students develop professionally in ways that affect their ability to find and retain jobs after graduation. Outlined curriculum goals ensure students gain conceptual understanding and practical skills, but throughout their enrollment, students also develop their professional identities in ways that are less understood. Positively formed professional identities gain students’ entrances into a professional community, making the transition to work more seamless [1], [2], however, scholars concernedly note that a large population of students face violence, natural disasters, and pandemics that disrupt their education and development [3]. This makes displaced students who are facing forced migration particularly vulnerable to an incomplete professional identity formation.Researchers have begun to study the challenges displaced students face as they develop professionally and personally towards gainful employment in resettlement contexts [4], [5], finding that displaced students negotiate and renegotiate both personal and professional identities [6], [7], [8] upon migration. This negotiation and competition of identity happens in ways that are socially embedded [9] and can impinge on students’ development.These issues may be particularly challenging for engineering students, where tightly structured curricula make disruptions even more problematic and where a sense of belonging and connection to peer groups are crucial to success [10]. However, we do not yet have a clear comparative understanding of displaced student experiences in engineering, nor do we understand how displacement contexts impact displaced student professional development broadly. To that end, this scoping literature review and research full paper seeks to summarize and characterize current research on the influences on professional identity development in displaced university students broadly, laying the groundwork for future discipline-specific research. The study describes the contextual barriers to displaced students’ professional identity development in multiple disciplines, and then focuses on engineering-specific issues and complementary supports. Preliminary findings indicate that engineering-specific nuances exist in professional identity development for displaced students based on discipline-specific values, attitudes, conventions, and approaches. Uncovering these nuances helps ensure educators better facilitate positive professional identity development in displaced engineering students across disciplines, which is aligned with the achievement of the sustainable development goals.
Line Art Colorization of Fakemon using Generative Adversarial Neural Networks

This work proposes a complete methodology to colorize images of Fakemon, anime-style monster-like creatures. In addition, we propose algorithms to extract the line art from colorized images as well as to extract color hints. Our work is the first in the literature to use automatic color hint extraction, to train the networks specifically with anime-styled creatures and to combine the Pix2Pix and CycleGAN approaches, two different generative adversarial networks that create a single final result. Visual results of the colorizations are feasible but there is still room for improvement.
Elimination before imagination: How children’s early understanding of scientists may limit aspirations for broader STEM careers

This research full paper presents a study that examines emerging understanding of science careers among very young children (aged 5-7) and seeks to identify the factors that influence their understanding. Knowing that early interest in science is a strong predictor for future engineering pathways, and that children begin eliminating careers as incompatible with their future self at a very young age, the results are interpreted in the context of what this means for engineering education. Grounded theory approaches were applied to qualitative data collected through focus groups and used to sort and categorize data and identify themes. The study finds that despite science being a core subject in elementary schooling in the UK, young children’s awareness of scientists and science careers remains low. Four categories to describe the patterns of children’s understanding were identified: undeveloped, introductory, stereotypical, and diversifying. For most children, their perceptions of scientists remained either under-developed or confined to ideas with clear labels, such as stereotypes. Young children’s understanding of engineers may be even more restricted due to engineering not being a taught subject within elementary education in the UK. The factors identified as influencing young children’s understanding of scientists differ somewhat from those presented in studies with slightly older children. Young children did not commonly relate science learning in school with scientists or to a broader spectrum of science-related jobs. Children within the diversifying group highlight the value of personal experiences with science and STEM professionals. By identifying the potential of careers-related learning to shape young children’s understanding of engineering and engineering careers as distinct from that of science and mathematics, these findings have implications for future engineering education practices.
Pore-scale investigation of immiscible displacement process in porous media under high-frequency sound waves

Although experimental and theoretical studies have been performed to identify the effects of elastic waves on multi-phase flow in porous structures, the literature lacks finely tuned experiments at the micro-scale. This paper reports observations and critical analysis of immiscible displacement in micro-scale porous media under ultrasonic energy. A number of experiments are performed on homogeneous and heterogeneous micromodels for varying wave frequency and power, initial water saturation, wettability and injection rates. We show that ultrasonic radiation influences the displacement pattern and yields lower residual non-wetting phase (oil) behind when low injection rates are applied. Higher wave frequency results in faster recovery of oil, but the ultimate recovery is controlled mainly by wave intensity. The presence of initial water saturation has a positive effect on the displacement, especially in an oil-wet medium. Of the possible mechanisms suggested for recovery enhancement under ultrasonic radiation, deformation of pore walls and change in fluid properties due to heating are not an issue in these experiments but other mechanisms including coalescence of oil droplets under oscillation, reduction of wetting films, adherence to grains and the peristaltic movement of fluids due to mechanical vibration were observed to be effective and are discussed in the analysis of the visual observations.
Freshmen Orientation Program Using Minecraft: Designed by Students for Students during the Covid-19 Pandemic

This Innovative Practice Full Paper presents experiences in designing a student-led virtual freshmen orientation program that uses a Minecraft environment. We describe the planning process, roles of the organizing committee members, and how the game was constructed for participants to learn and interact with one another. The student organizers not only created a virtual environment that scales the college map where more than a hundred freshmen (participants) could have an immersive experience of the campus, but also ensured the branding and marketing, logistics, and safety/well-being aspects of the event. In this paper, we present students’ experience of this program from both the designers’ as well as the participants’ perspectives. We conducted surveys with the organizing committee members and interviewed the participants to gain insights on their perception of this event. Our analysis showed that student organizers had the autonomy to brainstorm, suggest creative ideas, develop novel games, and procure materials. They also felt that they developed authentic programming and leadership skills. On the other hand, participants felt engaged as the event was well-organized, had clear delivery of information, introduced them to new technology, made them more familiar with the campus, provided a conducive environment to hone their soft skills such as communication and teamwork even before they officially enrolled as undergraduate students in an engineering program, and helped them establish social networks to support them throughout their undergraduate education journey.
Graphene Biosensor for Carbon monoxide Monitoring

carbon monoxide asphyxiation is responsible for the loss of many human lives every year in Algeria, and this is increasing every year, the exposure to this gas leads to harmful consequences for the organism which leads to death. For this purpose, the initial step is to detect these gases with miniature structure and solid progressed estimation methods using a simulation software tool. In this work, we are going to present an electromagnetic (EM) wireless graphene-kapton (polyimide film) sensor device able to detect and recognize carbon monoxide toxic gas.
Measurement and Operation Based Condition Monitoring Methodology for High Voltage Circuit Breakers

High voltage circuit breakers (HVCBs) are essential components for reliability and resiliency of the power system, and it is crucial to optimize principles of condition monitoring for maintenance of this equipment. In this paper a novel methodology based on combination of HVCB’s overall health index and expected aging curve is presented to provide an optimal scheduling of HVCB’s maintenance. The overall health index of HVCB is acquired by conventional measurements, e.g. contacts dynamic resistance, drive motor current, etc. The methodology has been verified based on experimental tests that are implemented on a 110 kV HVCB. Based on the obtained results, the proposed method would increase the accuracy of HVCB’s condition based maintenance scheduling, which will improve system reliability, ensure personnel safety, reduce the unplanned down time, and decrease the overall maintenance cost.
Transfer function method of measuring in‐duct acoustic properties. II. Experiment

This paper is the second of two papers describing the transfer function method of measuring in‐duct acoustic properties. In the previous paper the theoretical formulae were developed. In this paper experimental results are presented to demonstrate the accuracy and the general utility of the method. Test results of the complex reflection coefficient, the complex acoustic impedance, and the transmission loss are found to agree well with theoretical predictions. The sound absorption coefficient was evaluated with both the new method and the conventional Standing‐Wave‐Ratio (SWR) method and the accuracy of the two results are found to be comparable. The new method, however, is about 40 times faster than the SWR method. Also included are experimental verifications of two methods for improving the transfer function estimate, namely the use of sensor switching for automatic system calibration and the use of coherence functions for signal enhancement.
Optical bistability and Fano-like resonance transmission in a ring cavity-coupled Michelson interferometer

This paper presents theoretical investigations on a new ring cavity-coupled scheme of a Michelson interferometer with a linear loop mirror, which has the attraction of low loss and high stability due to the closed geometry. The optical transmission response is modeled using a scattering matrix approach and analytical expressions are derived. This single ring cavity-coupled system exhibits optical Fano resonance features and significantly enhances the switching sensitivity to the cavity detuning required for a large ON/OFF contrast ratio. The evolution of Fano-like interference and the effect of ring cavity confinement on the Fano-like resonance are studied numerically. Furthermore, optical bistability and multi-bistability are demonstrated by introducing Kerr nonlinearity inside the ring cavity. The shape and polarity of hysteresis loops are easily controllable by adjusting the phase compensation of the direct channel, while the switching thresholds are affected remarkably by the linear phase shift of the ring cavity. The simple structure of the single cavity-coupled interferometer will be important for practical applications in optical sensors, all-optical switches and logic function elements.
Crystalline structure and squeeze-out dissipation of liquid solvation layers observed by small-amplitude dynamic AFM

Using frequency-modulation atomic force microscopy (FM-AFM) at sub-nanometer vibration amplitudes, we find in the system $n$-dodecanol/graphite that solvation layers may extend for several nanometers into the bulk liquid. These layers maintain crystalline order which can be imaged using FM-AFM. The energy dissipation of the vibrating tip can peak sharply upon penetration of molecular layers. The tip shape appears critical for this effect.