Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital Twins and AI in Smart Motion Control Applications

Recently, smart system integration was identified as a key competence for optimizing machines and robots. However, when one wants to ’tune’ the entire production process a step further is necessary. We should evaluate performance indicators (e.g. energy and material consumption) over the whole machine life cycle in order to align the production with circular economy principles. To reach that target MBSE (model-based system engineering) should be covered by advanced digital twin approaches which allow continuous monitoring of machine performance, predict the failures and maintenance. Moreover, artificial intelligence and machine learning must be used to process big data sets gathered from the production lines. This paper identifies a common set of technologies and building blocks suitable to solve above mentioned problems for a large variety of industrial domains (semiconductor production, health-care robotics, CNC1 machining, high-speed packaging and others). It presents the first results of the large-scale IMOCO4.E2 project and shows the pathways for application of the technology on specific machines (so-called pilots). The authors believe the ideas presented could be inspiring also in other domains.
A brief overview of the interplay between nonlinearity and transverse Anderson localization

This article presents a brief overview of the interplay between nonlinearity and Anderson localization of light, primarily in the context of transverse Anderson localization. The focus is on whether Anderson localization is preserved, enhanced, weakened, or destroyed in the presence of nonlinearity. Several recent experimental and theoretical results are highlighted and reviewed.
Emotion recognition based on EEG directed functional connectivity using deep learning algorithm

Numerous features have been extracted from multichannel electroencephalography (EEG) signals, however, the directed functional connectivity derived from EEG signals for emotion recognition using deep learning algorithm remains unexplored. The present work aimed to exploit emotion recognition based on directed functional connectivity with a deep learning (DL) algorithm. First, this paper reviews the current trends of DL implementation for emotion recognition using EEG and identify their limitations and future directions. Second, the directed functional connectivity was extracted from EEG and was used as input to long short-term memory-recurrent neural network (LSTM-RNN). The performance of the proposed framework was validated using DEAP dataset. Results suggest that the LSTM-RNN is suitable for classifying emotional valence (low vs. high) and arousal (low vs. high) with accuracy of 95.28% and 96.17%, respectively. This study provide preliminary evidence of EEG-based directed functional connectivity and DL method for recognizing emotion.
Towards Developing High Performance RISC-V Processors Using Agile Methodology

While research has shown that the agile chip design methodology is promising to sustain the scaling of computing performance in a more efficient way, it is still of limited usage in actual applications due to two major obstacles: 1) Lack of tool-chain and developing framework supporting agile chip design, especially for large-scale modern processors. 2) The conventional verification methods are less agile and become a major bottleneck of the entire process. To tackle both issues, we propose MINJIE, an open-source platform supporting agile processor development flow. MINJIE integrates a broad set of tools for logic design, functional verification, performance modelling, pre-silicon validation and debugging for better development efficiency of state-of-the-art processor designs. We demonstrate the usage and effectiveness of MINJIE by building two generations of an open-source superscalar out-of-order RISC-V processor code-named XIANGSHAN using agile methodologies. We quantify the performance of XIANGSHAN using SPEC CPU2006 benchmarks and demonstrate that XIANGSHAN achieves industry-competitive performance.
Dynamics and Bifurcations

This study presents ideas and examples about the geometry of dynamics and bifurcations of ordinary differential equations. The subject of differential and difference equations is an old and much-honoured chapter in science. In recent years, due primarily to the proliferation of computers, dynamical systems have returned to their roots in applications. It is the aim of this book to provide a modest foundation of knowledge for undergraduate and beginning graduate students in mathematics or science and engineering. Equations in dimension one and two constitute the majority of the text. It is demonstrated in particular that the basic notion of stability and bifurcations of vector fields are easily explained for scalar autonomous equations. Proceeding, the authors investigate the dynamics of planar autonomous equations where new dynamical behaviour, such as periodic and homoclinic orbits, appears.
Deployment of a broadband test fixture for characterization of high-volume TO-housed devices

We present an automated system for characterization of mid-infrared (mid-IR) photodetectors in a wide frequency range. It is composed of a vector network analyzer (VNA) and a dedicated test fixture for matching the pin geometry of transistor outline (TO) canned device under test (DUT) to the VNA ports. The fixture enables a mixed-signal analysis of the DUT’s impedance, yet it introduces systematic errors into collected measurements due to fixture leakage, losses and dispersion. Thus, in this work we apply a novel calibration technique (SOLR16) to determine the four port S-matrix of the fixture and then use it for the de-embedding photodiode’s mixed-mode characteristics. We utilize the differential impedance to determine parameters of the photodiode’s small-signal equivalent-circuit by fitting its impedance to the de-embedded one. These parameters can be easily attributed to the interconnects of TO-can and to the mid-IR photodiode junction depending on the DUT’s voltage bias. Such a model applied to SPICE enables one to quickly evaluate how the junction and package parasitics affect the response of receiver optical sub-assemblies (ROSAs) and thus, elevate effectiveness of their manufacturing. This approach can be easily adapted to other microwave devices encapsulated in TO-can packages.
COS-burst: Observations of the Impact of Starburst-driven Winds on the Properties of the Circum-galactic Medium

We report on observations made with the Cosmic Origins Spectrograph (COS) on the Hubble Space Telescope (HST) using background quasi-stellar objects to probe the circum-galactic medium (CGM) around 17 low-redshift galaxies that are undergoing or have recently undergone a strong starburst (the COS-Burst program). The sightlines extend out to roughly the virial radius of the galaxy halo. We construct control samples of normal star-forming low-redshift galaxies from the COS/HST archive that match the starbursts in terms of galaxy stellar mass and impact parameter. We find clear evidence that the CGM around the starbursts differs systematically compared to the control galaxies. The Lyα, Si iii, C iv, and possibly O vi absorption lines are stronger as a function of impact parameter, and the ratios of the equivalent widths of C iv/Lyα and Si iii/Lyα are both higher than in normal star-forming galaxies. We also find that the widths and the velocity offsets (relative to vsys) of the Lyα absorption lines are significantly larger in the CGM of the starbursts, implying velocities of the absorbing material that are roughly twice the halo virial velocity. We show that these properties can be understood as a consequence of the interaction between a starburst-driven wind and the preexisting CGM. These results underscore the importance of winds driven from intensely star-forming galaxies in helping drive the evolution of galaxies and the intergalactic medium. They also offer a new probe of the properties of starburst-driven winds and of the CGM itself.
Low-Complexity Vision-Sensing Directivity Control for Planar Phased Array in 24-GHz-Band Wireless Power Transfer

A low-complexity vision-sensing directivity control scheme is described for a massive planar phased array in an on-vehicle quasi-millimeter-wave power transfer system. Horizontal and vertical directivity control variables are derived from an equidistance-projected target coordinate inherent in a fish-eye lens. The computationally efficient scheme that we have proposed provides the same beam directivity that can be obtained with a conventional polar conversion scheme. Our simulation results demonstrated that when the receive antenna height was not the same as the array center height, the newly derived low-complexity beam steering scheme significantly reduced the loss of received energy that would otherwise be stored, compared to horizontal-only beam steering.
Causes of Low Mathematics Achievement in Uganda and Exploiting ICT -based Tools in Response

This study focuses on mathematics education by using cognitive linguistics and developmental psychology to identify the causes of low levels of mathematics achievement in Sub-Sahara African countries. It also develops and adapts tools to directly investigate the causes in detail. Drawing on these perspectives, we suggested the following hypotheses: The real world and the mathematical concepts are disconnected because of the lack of appropriate metaphors, and the underdevelopment of the mental number line is an impediment to learning outcomes. The mental number line is considered the foundation of the quantity concept and basis of calculation skills. A survey was conducted to elucidate the hypotheses by using a questionnaire involving addition and subtraction with negative numbers and a number line task that can measure the development of a mental number line. We found that our hypotheses were generally correct. At the same time, we created application that automatically calculate the indicator of mental number line and the self-learning tool with AR. In the survey, we investigated whether using this tablet program is be accepted by Sub-Sahara African pupils.
The Helium Abundance of NGC 6791 from Modeling of Stellar Oscillations

The helium abundance of stars is a strong driver of evolutionary timescales; however, it is difficult to measure in cool stars. We conduct an asteroseismic analysis of NGC 6791, an old, metal-rich open cluster that previous studies have indicated also has a high helium abundance. The cluster was observed by Kepler and has unprecedented light curves for many of the red giant branch stars in the cluster. Previous asteroseismic studies with Kepler data have constrained the age through grid-based modeling of the global asteroseismic parameters ( and ). However, with the precision of Kepler data, it is possible to do detailed asteroseismology of individual mode frequencies to better constrain the stellar parameters, something that has not been done for these cluster stars as yet. In this work, we use the observed mode frequencies in 27 hydrogen shell burning red giants to better constrain initial helium abundance (Y0) and age of the cluster. The distributions of helium abundance and age for each individual red giant are combined to create a final probability distribution for age and helium abundance of the entire cluster. We find a helium abundance of Y0 = 0.297 ± 0.003 and a corresponding age of 8.2 ± 0.3 Gyr.
An Enhanced Visual SLAM Supported by the Integration of Plane Features for the Indoor Environment

This paper presents an enhanced indoor RGB-D simultaneously localisation and mapping (SLAM) system based on the integration of plane and point features. A new method was proposed to register each point feature to a corresponding plane feature and then modify its position accordingly. The plane features are parallelly extracted from depth data sources and used jointly to solve the camera pose with point features. Both point and plane features are stored on the map and used for backend optimisation, where the weights associated with features can be dynamically updated. At the same time, the on-plane feature points are fixed during the optimisation. The proposed method has been tested with open-source benchmarks, including the scenarios with or without a structured environment. Experiment results demonstrated that the proposed algorithm performs better than other widely cited visual SLAM systems in some structured environments, in which the point features form plane features without introducing excessive errors.
DIFFERENT ORIGINS OR DIFFERENT EVOLUTIONS? DECODING THE SPECTRAL DIVERSITY AMONG C-TYPE ASTEROIDS

Anhydrous pyroxene-rich interplanetary dust particles (IDPs) have been proposed as surface analogs for about two-thirds of all C-complex asteroids. However, this suggestion appears to be inconsistent with the presence of hydrated silicates on the surfaces of some of these asteroids, including Ceres. Here, we report the presence of enstatite (pyroxene) on the surface of two C-type asteroids (Ceres and Eugenia) based on their spectral properties in the mid-infrared range. The presence of this component is particularly unexpected in the case of Ceres, because most thermal evolution models predict a surface consisting of hydrated compounds only. The most plausible scenario is that Ceres’ surface has been partially contaminated by exogenous enstatite-rich material, possibly coming from the Beagle asteroid family. This scenario questions a similar origin for Ceres and the remaining C-types, and it possibly supports recent results obtained by the Dawn mission (NASA) that Ceres may have formed in the very outer solar system. Concerning the smaller D ∼ 200 km C-types such as Eugenia, both their derived surface composition (enstatite and amorphous silicates) and low density (<1.5 g cm−3) suggest that these bodies accreted from the same building blocks, namely chondritic porous, pyroxene-rich IDPs and volatiles (mostly water ice), and that a significant volume fraction of these bodies has remained unaffected by hydrothermal activity likely implying a late accretion. In addition, their current heliocentric distance may best explain the presence or absence of water ice at their surfaces. Finally, we raise the possibility that CI chondrites, Tagish-Lake-like material, or hydrated IDPs may be representative samples of the cores of these bodies.
The Clustering of High-redshift (2.9 ≤ z ≤ 5.1) Quasars in SDSS Stripe 82

We present a measurement of the two-point autocorrelation function of photometrically selected high-z quasars over ∼100 deg2 on the Sloan Digital Sky Survey Stripe 82 field. Selection is performed using three machine-learning algorithms in a six-dimensional optical/mid-infrared color space. Optical data from the Sloan Digital Sky Survey are combined with overlapping deep mid-infrared data from the Spitzer IRAC Equatorial Survey and the Spitzer-HETDEX Exploratory Large-Area survey. Our selection algorithms are trained on the colors of known high-z quasars. The selected quasar sample consists of 1378 objects and contains both spectroscopically confirmed quasars and photometrically selected quasar candidates. These objects span a redshift range of 2.9 ≤ z ≤ 5.1 and are generally fainter than i = 20.2, a regime that has lacked sufficient number density to perform autocorrelation function measurements of photometrically classified quasars. We compute the angular correlation function of these data, marginally detecting quasar clustering. We fit a single power law with an index of δ = 1.39 ± 0.618 and amplitude of θ0 = 0. ′71 ± 0. ′546 . A dark matter model is fit to the angular correlation function to estimate the linear bias. At the average redshift of our survey ( ), the bias is b = 6.78 ± 1.79. Using this bias, we calculate a characteristic dark matter halo mass of 1.70–9.83 . Our bias estimate suggests that quasar feedback intermittently shuts down the accretion of gas onto the central supermassive black hole at early times. If confirmed, these results hint at a level of luminosity dependence in the clustering of quasars at high-z.
High Bandwidth and Low Phase Noise Architecture for Multi-Mode 60/77GHz FMCW Radars

Higher chirp bandwidth in FMCW radar provides better range resolution but comes with higher phase noise and design complexity. This paper presents a multi-mode FMCW synthesizer and radar architecture, to simultaneously achieve low phase noise performance for longer-range applications, and higher range resolution performance in near-range/imaging applications. It uses two low phase noise VCOs with overlapping frequency bands, and a digital combining architecture, addressing static as well as moving scenarios. The paper concludes with silicon results from a two-VCO 60GHz radar and a two-VCO 77GHz radar, achieving 6.8GHz and 5GHz chirp bandwidths, respectively.
Cryptocurrency Price Prediction using Bi-GRU Model with English and Malay News Sentiment Features

The effect of sentiment from news sources on cryptocurrency prices has garnered significant interest from the financial community including researchers. However, current findings reporting the usefulness of sentiment features in cryptocurrency price prediction is still mixed. This paper aims to explore various feature combinations encompassing cryptocurrency historical prices and sentiment scores of the current day aggregated from English and Malay news sources to predict the closing price of the next day. Each news headline related to Bitcoin and Ethereum within the duration of one year is first manually annotated and then aggregated on a daily basis to generate the sentiment features. A Bi-GRU deep learning model is implemented to predict the cryptocurrency closing price of the next day given a combination of historical price and sentiment features of the current day. Our findings evidently show sentiment features when combined with the closing price of the current day contribute significantly to improve the model's performance. Our study is also the first attempt to examine the effect of Malay news sentiment on cryptocurrency prices and we have demonstrated that cryptocurrency price prediction models leveraging Malay news sentiment features for Bitcoin and Ethereum are able to yield performance that is at par with models using English news sentiment features.
Modeling Coronal Response in Decaying Active Regions with Magnetic Flux Transport and Steady Heating

We present new measurements of the dependence of the extreme ultraviolet (EUV) radiance on the total magnetic flux in active regions as obtained from the Atmospheric Imaging Assembly (AIA) and the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. Using observations of nine active regions tracked along different stages of evolution, we extend the known radiance—magnetic flux power-law relationship ( I ∝ Φ α ) to the AIA 335 Å passband, and the Fe xviii 93.93 Å spectral line in the 94 Å passband. We find that the total unsigned magnetic flux divided by the polarity separation ( Φ / D ) is a better indicator of radiance for the Fe xviii line with a slope of α = 3.22 ± 0.03 . We then use these results to test our current understanding of magnetic flux evolution and coronal heating. We use magnetograms from the simulated decay of these active regions produced by the Advective Flux Transport model as boundary conditions for potential extrapolations of the magnetic field in the corona. We then model the hydrodynamics of each individual field line with the Enthalpy-based Thermal Evolution of Loops model with steady heating scaled as the ratio of the average field strength and the length ( B ¯ / L ) and render the Fe xviii and 335 Å emission. We find that steady heating is able to partially reproduce the magnitudes and slopes of the EUV radiance—magnetic flux relationships and discuss how impulsive heating can help reconcile the discrepancies. This study demonstrates that combined models of magnetic flux transport, magnetic topology, and heating can yield realistic estimates for the decay of active region radiances with time.
Octave-Band Three-Beam Scalable Antenna Array Fed by Broadband 4 × 4 Butler Matrix

A novel concept of a three-beam antenna array operating over a one-octave frequency range is proposed in this paper. The antenna array allows stable beams’ direction and beamwidths. To achieve constant radiation patterns, the antenna elements are appropriately spaced and fed by a network consisting of a broadband Butler matrix to which outputs directional filters are connected. The radiating elements are placed in such a way that two similar subarrays can be distinguished, one for the lower and another for the higher end of the desired frequency range. Signal switching between the subarrays and differential phase between pairs of radiating elements is ensured by directional filters and Butler matrix, respectively. The concept has been verified by measurements of the antenna array operating in a 2–4 GHz frequency range.
Thermal Pressure in Diffuse H2 Gas Measured by Herschel Emission and FUSE UV H2 Absorption

UV absorption studies with the Far Ultraviolet Spectroscopic Explorer (FUSE) satellite have made important observations of H2 molecular gas in Galactic interstellar translucent and diffuse clouds. Observations of the 158 μm [C ii] fine-structure line with Herschel trace the same H2 molecular gas in emission. We present [C ii] observations along 27 lines of sight (LOSs) toward target stars of which 25 have FUSE H2 UV absorption. Two stars have only HST STIS C ii λ2325 absorption data. We detect [C ii] 158 μm emission features in all but one target LOS. For three target LOSs that are close to the Galactic plane, 1°, we also present position–velocity maps of [C ii] emission observed by Herschel Heterodyne Instrument in the Far Infrared (HIFI) in on-the-fly spectral-line mapping. We use the velocity-resolved [C ii] spectra observed by the HIFI instrument toward the target LOSs observed by FUSE to identify [C ii] velocity components associated with the H2 clouds. We analyze the observed velocity integrated [C ii] spectral-line intensities in terms of the densities and thermal pressures in the H2 gas using the H2 column densities and temperatures measured by the UV absorption data. We present the H2 gas densities and thermal pressures for 26 target LOSs and from the [C ii] intensities derive a mean thermal pressure in the range of ∼6100–7700 K cm−3 in diffuse H2 clouds. We discuss the thermal pressures and densities toward 14 targets, comparing them to results obtained using the UV absorption data for two other tracers C i and CO. Our results demonstrate the richness of the far-IR [C ii] spectral data which is a valuable complement to the UV H2 absorption data for studying diffuse H2 molecular clouds. While the UV absorption is restricted to the directions of the target star, far-IR [C ii] line emission offers an opportunity to employ velocity-resolved spectral-line mapping capability to study in detail the clouds’ spatial and velocity structures.
Digital Twin proposal using the Matlab-Stateflow model and Docker containers

The core of the contribution is a proposal for the implementation of Digital Twin (DT) of a real production line in a laboratory environment. The source of data is the physical production line – Festo AFB factory. The functional logic of the physical Programmable Logic Controllers (PLC) is simulated as a block within a Stateflow object in MATLAB. As a virtualization hosting system, an open-source containerization platform, known as DOCKER, including the simulation of communication infrastructure, is proposed. Thanks to connection between real and virtual process, it is possible to transfer of real process values online to virtualized DT. In addition, the proposed DT can be connected to the existing Manufacturing Execution System (MES) and implement control of the entire line in a virtualized form. The advantage of such a solution is the possibility of using the data of the MES data historian server for the simulation of fault states within the DT environment.