Miracle-dz/UniFAR-FTUs huggingface dataset:
Widely Linear Complex-Valued Spline-Based Algorithm for Nonlinear Filtering

Over the past decade, spline adaptive filtering (SAF) has attracted much attention in nonlinear signal processing. In this paper, we investigate the WL complex-valued SAF (WL-CSAF) algorithm in the complex domain based on the cascaded architecture combining a widely linear (WL) model and a nonlinear lookup table (LUT), which is capable of exploiting the full second-order information of signals. Moreover, the steady-state mean square error (MSE) is analyzed to provide insights into the theoretical behavior of the WL-CSAF algorithm. Simulations of nonlinear system identification scenarios demonstrate the superiority of WL-CSAF against known algorithms, and validate the accuracy of the theoretical predictions.
A Teflon-Filled Open-Ended Circular Waveguide Focal-Plane-Array Used for Sway Compensation in W-band 50dB-Gain Backhaul Reflector Antennas

The paper introduces a novel focal plane array (FPA) design aimed at enhancing the reliability of millimeter-wave backhaul communication links by compensating for the impact of antenna mounting structures’ sways. This FPA is analyzed for an offset parabolic reflector antenna with the 40-cm aperture diameter at W-band frequencies (92-96 GHz). The FPA-fed reflector antenna generates multiple closely-overlapping beams to compensate for the expected antenna tilt range, equivalent to seven beamwidths. This study addresses major challenges associated with FPA design implementation at these high frequencies, including (i) the need for a small ($\leq 0.75 \lambda$) inter-element spacing for the required beam overlap, and (ii) manufacturing complexities of an array element ensuring optimal reflector illumination and impedance matching in the presence of mutual coupling effects. An analytical approach to the FPA pattern shaping for optimal reflector illumination is proposed and successfully validated via numerical optimization and measurements. Furthermore, our analysis of the total reflector-FPA system shows promising results, i.e. 56 – 68% antenna aperture efficiency (49 – 50 dBi directivity) for all beams with compliance to the radiation emission constraints (ETSI class 3) within ±89°.
Actuation of Ferrobots in a Plane for Independent and Swarm Motion Using a Grid of Electromagnets

We present a robotic platform in which multiple ferromagnetic bots can be moved independently on a plane above a grid of iron-core solenoid electromagnets. Our magnetic robots are iron balls fitted with custom-designed mounts, which we call ferrobots. We chose ferromagnets because when several of them are close together, they can still be separated by turning off the nearest solenoids. A solenoid influences only the ferrobots near it, thus enabling different specified forces applied on them. A significant challenge addressed in this work is calculating the forces on the ferromagnets. This is because the magnetic force on a ferro object is a function of its magnetization and the external field. Analytical calculation of the magnetization in the presence of non-uniform external fields is difficult. Furthermore, large computation is involved if finite element analysis is used. So, in this work, we present an approximate but quick method for calculating the force on a ferromagnetic ball due to a general magnetic field. By assuming that the field inside a ferromagnetic ball can be expressed as a linear combination of Legendre and other polynomials, we show that the magnetization of the ferromagnetic ball is also a polynomial. Furthermore, we express the polynomial coefficients of magnetization in terms of those of the magnetic field. The ferromagnetic force then turns out to be an easily computable analytical expression. The developed force model is used to calculate the current in the solenoids for required forces. The results of our semi-analytical method are compared with finite element analysis with better than 4% error. To further validate our calculation, we developed a two-axis force sensor using an XY-decoupled compliant stage to measure magnetic forces of lower magnitudes in our setup. During the motion of a ferrobots towards a coil, it would build up momentum due to increased force, causing it to overshoot and oscillate at the endpoint. Therefore, we have developed a braking mechanism on the ferrobots mount that responds to the downward magnetic force from the coil that decelerates the ferrobots. We show a reduced overshoot, no oscillation, and fast travel times because of the responsive braking mechanism. Using our platform and force-modelling, we demonstrate the motion of a ferrobots along bespoke trajectories by applying forces as needed. We also demonstrate the swarm motion of multiple ferromagnets and their ability to change the shape of an enclosing elastic band. Together they function as a shape-changing robot that can navigate the workspace, changing shape as required and thereby grasp and manipulate other objects.
Structured DFT Development Approach for Chisel-Based High Performance RISC-V Processors

Research has shown that agile language Chisel and related agile design methodology is promising to sustain the scaling computing performance in a more efficient way. Design For Test, as an economical and effective method for chip production testing, must be integrated into the agile development system to meet the requirements of mass production. Due to the lack of support for the traditional EDA toolchain, chip development through Chisel has not been widely accepted in the industry. This paper is based on the research of XiangShan, an open-source project for RISC-V high-performance processor. XiangShan establishes a structured DFT(degisn for test) development approach and Chisel-based DFT agile design flow. XiangShan develops a flexible chisel-based XS-shared bus mbist interface to improve design PPA and proposes the MarchSLD algorithm to enhance defect detection in the FinFet process node. XiangShan’s DFT development Approach is moving towards hierarchical, flexible, and reliable in two generations of processors. Experimental results show that the optimized Chisel-based DFT design flow can support agile development requirements and achieve industry-competitive performance.
Ambient IoT: Transmit Power Minimization for NOMA-Enabled BackCom

Ambient internet-of-things networks are just emerging to support sixth-generation wireless goals. We thus investigate a symbiotic radio (SR) system for a single-user primary network and a backscatter communication network that supports non-orthogonal multiple access. The primary base station (BS) concurrently supports the primary user and multiple tags, which modulate and reflect their data using the primary BS signal. The user decodes its data and the tags’ data using the successive interference cancellation technique. We propose a novel optimization framework to accommodate the requirements of both the primary user and the tags while also improving SR network performance. By constructing the beamforming vectors to support both primary and backscatter networks, we develop a BS transmit power minimization problem. The problem formulation ensures the various quality-of-service demands of the user and the tags and the tag energy harvesting requirements. Because of the non-convexity of the problem, we employ semi-definite relaxation techniques to obtain a sub-optimal solution. We evaluate the computational complexity of the proposed algorithm. Finally, we present extensive numerical results and simulations that establish the validity and performance gains of the proposed optimization scheme without modifying the fundamental passive tag architecture.
Supervised Change-Point Detection with Dimension Reduction

This paper presents an automated approach for calibrating change point detection algorithms for high-dimensional time series. Our method leverages partial annotations provided by experts to learn a diagonal Mahalanobis metric, combined with a detection algorithm to replicate the expert's segmentation strategy on new signals. Our approach includes sparsity-inducing regularization to improve accuracy, which performs dimension selection and adapts to partial annotations. Our experiments on audio signals and physiological time series signals demonstrate that supervised learning improves detection accuracy significantly.
THz Spectroscopic Electron Paramagnetic Resonance of the Fe3+ Defect in GaN

We present a recently developed method for electron paramagnetic resonance (EPR) measurements in the THz spectral range. The method is based on spectroscopic ellipsometry and thus requires no cavity, unlike conventional EPR. This permits us to scan the frequency parameters in addition to the magnetic field parameters. To showcase this, both frequency and magnetic field scans are performed on Fe-doped GaN, and the results are compared to previous work that used conventional EPR to study the same defect.
Application of Minimum Vertex Cover Problem in Functional Brain Connectivity Graphs

Brain connectivity networks play a crucial role in understanding the organization and functioning of the human brain. In this regard, graph theoretical models may provide a powerful way for the analysis of brain connectivity networks. The vertex cover (VC) problem, a well-established computational problem in graph theory, may reveal the underlying properties of the brain networks when it is modeled as a graph representation. In the context of brain connectivity, the VC problem aims to identify a minimal set of brain regions that can adequately represent the entire network. To explore the changes in this property by age, a functional magnetic resonance imaging (fMRI) study is conducted with two groups of healthy adults. The characteristics of functional connectivity networks of the young and elderly groups are scrutinized with the minimum vertex cover problem. The results show that in the young participants the vertex cover of brain network includes almost all regions of the brain which indicates that the connections have been distributed homogeneously between the regions so that to cover all edges almost all regions should be added to the minimum VC. However, in the elderly participants the minimum VC sets cover 75% up to 93.75% percent of nodes which indicates in the elderly participants some regions of the brain considerably have more connections than some other parts that can be the sign of weakened connections among some regions.
Stable and Broadband Extraction of Permittivity and Permeability of Low-loss Dielectric Material using Rectangular Waveguide System

Electric permittivity and magnetic permeability are the two main parameters used to describe the electromagnetic properties of materials. Determination of these complex constitutive parameters is imperative for many applications (radar, acoustic, EM interference, automotive, microwave circuit design, etc) [1]. Several experimental techniques and algorithms have been developed over the years to measure and extract the EM properties of the materials. The rectangular waveguide system is one of the most commonly used systems. The material under test (MUT) is placed inside the waveguide, and the S-parameters are measured. However, an accurate determination of the permittivity and permeability from this measurement is more delicate. The Nicolson Ross Weir (NRW) algorithm has been proposed in the literature for this purpose [2]. This technique is known to suffer from divergence, resulting from phase ambiguities, when the thickness of the sample is an integer multiple of the half-guided wavelength [3]. A new stable algorithm to correct the divergence is proposed in this paper. To validate the approach, two different and known samples of polystyrene based materials of different densities and carbon-loaded concentrations were tested. The thickness of the samples is 9.6 mm.
Historical account of monitoring the Fault at the Ismetpasa latest findings North Anatolian segment and the

North Anatolian Fault (NAF) is the largest and longest earthquake producing fault of Turkey which extends from its Iranian border in the east to Marmara Sea in the west with a length of 1200km. It separates the Eurasian Plate and the Anatolian Plate and has similar features to the San Andreas Fault in California in USA in that both faults have a right-lateral strike slip faulting mechanism, similar lengths and linearity as far as their poles of rotation are concerned. NAF is considered to be one of the longest and most active fault systems in the world, and thus has been the stage of 11 major earthquakes (Mw >6.7) since 1939. Two of these major earthquakes occurred in the Ismetpasa segment of the fault, located 350 km east of Istanbul at the intersection of Karabuk and Cankiri provinces in north-central Anatolia, the Asia Minor, and 100km north of Ankara, the capital of Turkey. The Ismetpasa segment of NAF stands out with its aseismic fault slip feature, also referred to as creeping, as the rare occurrence in the world. The Ismetpasa first drew attention by a gradually enlarging crack on the wall of State Highway Maintenance Station built in 1957 and its aseismic slip movement that caused an offset in the wall was first reported in 1969 by Ambraseys. Since then, many researchers have investigated the creep by conducting various measurement methods from conventional surveying techniques to modern techniques such as GPS, LIDAR, InSAR. This paper documents the studies carried on NAF at Ismetpasa segment in a chronological perspective, and also gives the latest findings obtained by different research groups in the last decade.
Free Non-Linear Vibrations of a Fractionally Damped Cylindrical Shell Subjected to the Two-to-One Internal Resonance

In the present paper, free nonlinear vibrations of a thin cylindrical shell embedded in a viscoelastic medium, the rheological features of which are described by the fractional derivative Kelvin-Voigt model, are investigated when the shell is subjected to the condition of the internal resonance. Resolving equations are obtained for the case of the two-to-one internal resonance for determining nonlinear amplitudes and phases using the generalized method of multiple time scales involving the fractional derivative expansion. Numerical solution has been found via the fourth-order Runge-Kutta algorithm, which is implemented in GNU Octave software. The influence of viscosity on the energy exchange mechanism between interacting modes has been analyzed. The results obtained indicate that the order of the fractional derivatives have a notable impact on the intensity of the energy exchange mechanism between interacting modes.
Dual-Stage Control Strategy for a Three-Level Neutral Point Clamped Converter with Selective Harmonic Mitigation PWM

Grid-connected converters must meet the requirements imposed by grid codes, such as harmonic emission limits and grid voltage support during voltage dips. Selective harmonic mitigation pulsewidth modulation (SHMPWM) is a very interesting technique for high power converters to meet the maximum harmonic emission levels, while keeping a low switching frequency. However, the combination of this modulation with a proportional integral (PI) controller requires slow dynamics, which makes it difficult to comply with the dynamic response requirements of grid codes. As an alternative, model predictive control (MPC) offers a very fast dynamic response, but a wide spread harmonic spectrum in steady state. Thus, the combination of MPC with a PI controller with SHMPWM is advantageous. In this work, a dual-stage control strategy is implemented. During transients, finite control set MPC (FCS-MPC) is activated to rapidly drive the current to the desired reference, while in steady state, the PI controller with SHMPWM is used. Therefore, the dual-stage control strategy allows to comply with the two requirements of grid codes, becoming a suitable strategy for grid-connected converters.
A Simplified Model for the Secular Dynamics of a Parametrically-Excited Magnetic Micro-Particle

Magnetic micro-particles find numerous applications as the end-effectors in micro-manipulation technologies. A recent micro-manipulation technology proposed the use of micro-ring actuators and parametric excitation to trap magnetic particles in three-dimensions (3-D). Here, a simplified linear time-invariant system model is proposed to describe the secular dynamics of such particles. First, the exact dynamic equations are obtained for the case of a particle oriented upwards and the procedure to obtain their approximate solution is described. The obtained approximate response is employed to subsequently propose a simple linear time-invariant system model for the secular dynamics of the particle. Next, the same approach is extended for the case of a magnetic particle with arbitrary orientation. In both cases the results of the simplified model are compared with numerical solutions of the exact system equations. The two are found to match with an accuracy of over 99.6%.
Fine-tuning Wav2Vec2 for Classification of Turkish Broadcast News and Advertisement Jingles

The accurate classification of news and commercial jingles is essential for the automated generation of broadcast flow. Currently, in press companies, editors manually label the start and end times of news and advertisements, which incurs both cost and time loss. Although the method of extracting fingerprints of news and commercial jingles has been employed to detect jingles on a channel basis and automatically classify news and commercial music, this approach falls short when it comes to classifying new jingles produced by channels. In this study, we created a new dataset by extracting segments of commercial and news jingles from TV channels in Turkey. We analyzed the most effective second interval for classifying news or commercials, resulting in an impressive accuracy score of 98.18%. By leveraging this dataset and conducting extensive analysis, we have made significant progress in accurately classifying news and commercial jingles. This research can potentially save press companies costs and time by automating the classification process.
Cyber Deception under Strategic and Irrationality Considerations

This paper presents a novel cyber deception technique that can employ fake nodes to deceive attackers. To devise such a technique, the paper uses game theory to model strategic interactions between a defender and an attacker, and prospect theory to model their possible cognitive biases, while diligently accounting for cost factors associated with attack-defense strategies. Nash Equilibrium (NE)-based strategies for deploying our devised deception tactics when the defender and the attacker are fully rational in nature as well as when they may exhibit behavioral irrationalities have been analytically characterized in the paper. Among others, our results delineate how vulnerabilities of conventional defense resources can influence adoption of deception-based defenses. Numerous simulation results have been presented that provide important insights into our developed deception-based defense strategies.
Equivalent Circuit Based Design Approach of Axial-Flux Induction Generator for Wind Turbines

In this study, an equivalent circuit based systematic design approach was proposed for an axial-flux induction generator (AFIG). As initial step, analytical design equations were derived based on equivalent circuit parameters. An AFIG with 12 poles, 3-kW, 132. 79V/60 Hz is designed using the proposed approximation. Finite element based 3D transient magnetic modeling was used to validate calculated analytical design parameters. By comparing the finite element analysis (FEA) with results from the analytical approach, the consistency of the approach was demonstrated. In order to minimize the computational time, an analytical approach that is significantly faster than FEA-based tools was developed.
Functional Clustering of Continuous Cardiovascular and Brain Oxygenation Signals During an Active Stand Test in The Irish Longitudinal Study on Ageing (TILDA)

In this study, we performed K-shape functional clustering of two non-invasive continuous cardiovascular (systolic Blood Pressure: sBP) and brain oxygenation (left frontal lobe Tissue Saturation Index: TSI) times series signals, simultaneously collected 20 seconds before to 40 seconds after an active stand (AS) test in 2158 participants of The Irish Longitudinal Study on Ageing. Both signals were normalised and adjoined prior to clustering, and the gap statistic method was used to determine the optimum number of clusters. Eight clusters were obtained and characterised. Cluster 5 (n=287) and Cluster 1 (n=173) were independently predictive of not reporting dizziness post-AS or falls after 8 years, and were characterised by complete (Cluster 5) or near-complete (Cluster 1) sBP recovery and a moderate/transient (Cluster 5) or large/sustained (Cluster 1) TSI overshoot. Cluster 3 (n=304) and Cluster 6 (n=326) were independently predictive of post-AS dizziness and had large sBP recovery deficit/lack of TSI overshoot (Cluster 3) or moderate sBP recovery deficit/TSI overshoot (Cluster 6). Cluster 8 (n=289) was the most multimorbid and showed both sBP and TSI recovery deficits. This data-driven approach produced clinically meaningful results and may help clinicians recognise combined neurovascular signatures of orthostatic regulation in older people, both in health and disease.
Data-Driven Regression Modeling for Measuring the Influence of Infodemic over Social Media

The infodemic, which encompasses rumors, fake news, disinformation, and misinformation, has resulted in significant collateral damage alongside epidemics. However, the main factors and impact of the infodemic on epidemics remain unresolved. This study systematically reviews the concept and influence mechanism of the infodemic on social media based on previous literature and external influencing factors. Empirical data is collected through questionnaires from 1125 individuals. By employing ordered logistic regression modeling, this paper analyzes the factors influencing respondents' awareness of the infodemic from four perspectives: the extent of social media usage, media preference, rational information processing, and personal factors such as education level and age. The findings suggest that individuals who are more influenced by social media exhibit higher preference for its usage and employ more rational information processing. Additionally, it is observed that those with lower levels of education and older age tend to have relatively higher levels of information cognition.