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The amount of power electronic interfaced generation (PEIG) is significantly proliferating in modern cyber-physical energy systems (CPESs). The limited capabilities (e.g. inertia, over-current) of PEIG, together with their location and technology-specific designed control systems, alter the dynamic properties of different types of stability phenomena, e.g. sub-synchronous oscillations (SSOs). A poorly damped SSO can emerge, within a sub-second time scale, through conflicting inter-actions between the controls of PEIG and the dynamic response of the surrounding electrical network. This paper focuses on the modelling and assessment of such interactions, with emphasis on the integration of large-size full converter (a.k.a. type-4) based wind power plants (WPPs). By combining different analysis tools, the implemented model supports sensitivity assessment of the occurrence and observability of a poorly damped SSO. State-space model based eigenanalysis is iteratively used to ascertain damping variability of a dominant SSO, excited by inappropriate controller settings of the WPP. Power spectral density (PSD) analysis is used to qualitatively estimate the degree of observability of the poorly damped SSO across different buses of a CEPS. Numerical tests are performed on a modified version of the IEEE-39 bus system by using DIgSILENT PowerFactory 2022 SP1. Suggestions are provided for the deployment of data generated from phasor measurement units (PMUs) in the monitoring and wide-area damping control of critical SSOs., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

Multi-agent networks are known for their scalability, robustness, flexibility, and are typically tasked with a variety of tasks such as target tracking, surveillance, traffic control, and environmental monitoring. Distributed Particle Filters (DPF) are often employed when the for non-linear parameter estimation with non-Gaussian noise. In this paper, we propose a novel distributed particle filter whose transmitted quantities are particles. The fusion process of particles is implemented in a distributed and iterative fashion. To reduce the communication overhead, we adopt the Gaussian process-enhanced resampling algorithm, which reduces the size of local particle set, while still ensures acceptable filtering performance. To determine the local particle set after the communication, we propose two solutions. Our first algorithm (GP-DPF) adopts a “scoring mechanism”, allowing local agents score the received particles and using the scores as the selection criterion. Our second proposed solution (FA-DPF) is a meta-heuristic approach, which uses the well known firefly algorithm as a selection method for particle-based distributed particle filtering. Our simulations demonstrate the superiority of our proposed algorithms under the condition of limited communication and computational resources against other state-of-the-art distributed particle filters., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Signal Processing Systems

Silicon Carbide (SiC) devices offer energy efficiency improvements over conventional silicon (Si) semiconductors. Through measurements and simulation results, this paper intends to quantify this efficiency improvement in a typical photovoltaic (PV) application. This allows designers and policy makers to better understand the benefits of SiC, enabling more informed decisions.

Machine learning methods in recent years have focused on multimodal input and cross-modal tasks, and they are used as approaches to problems in various domains. Associating comic texts and characters using these approaches is informative for commercial activities such as speech synthesis and automatic translation of texts. In this study, we address the task of associating a text with a speaker in comics. It is challenging to correspond between them because these are not self-evidently attached, and few studies have attempted. These previous studies have less considered the continuity of comics such as narrative flow or contextual information. We assume that considering the continuity of comics is effective for speaker estimation. This paper proposes algorithms for estimating the reading order of frames or texts, and it also proposes methods for estimating speakers based on these orders. As a result, our proposed method improves accuracy compared to previous methods. Consideration of the frame order is an effective clue to the comic speaker estimation.

News intentionally containing false information–known as "fake news"–is common on the Internet and often causes social disruption. In order to solve it, research on automatic detection of fake news using supervised learning has been active. Although the accuracy is improving, a major challenge for practical application remains: models can not work well for news in unknown fields (domains) due to domain biases. The goal of this study is to mitigate these domain biases and improve the accuracy of cross-domain fake news detection, which tests news from unknown domains. We firstly try to mitigate the bias by masking noun phrases which are considered a major source of domain bias. However, masking has not improved accuracy. Therefore, we point out that the dataset in this study has the property that it always contains pairs of fake and real news on the exact same topic. In this paper, we focus on this property of dataset and examine how it may affect domain bias and accuracy. Comparative experiments show that accuracy is higher when trained on a dataset with the property shown in this study. We suggest that a fake news dataset consisting of paired news could be effective for cross-domain detection.

Thermal management is one of the main concerns in three-dimensional integration due to difficulty of dissipating heat through the stack of the integrated circuit. In a 3D stack involving a data-path accelerator, a base processor and memory components, peak temperature reduction is targeted in this paper. A mapping algorithm has been devised in order to distribute operations of data flow graphs evenly over the processing elements of the target accelerator in two steps involving thermal-aware partitioning of input data flow graphs, and thermal-aware mapping of the partitions onto the processing elements. The efficiency of the proposed technique in reducing peak temperature is demonstrated throughout the experiments.

Robots are becoming more prevalent in industry and society as a whole. Alongside this growth their application domain is also broadening. Each application brings with it a host of potential uncertainties that the robots should be able to handle at runtime. To tackle this, the doctoral thesis outlined in this paper proposes to address three main problems. First, the current ad-hoc state of robotics software which impedes its evolution. Second, the inability to imagine every possible uncertainty at design time leading to unexpected scenarios at runtime. Third, unexpected scenarios resulting from the reality gap between the simulated environments in which robots are developed versus the real world. These unexpected scenarios may cause a system to violate its requirements, especially in our case non-functional requirements. In an attempt to solve these problems, we plan to implement a variety of self-adaptation strategies. These strategies allow systems to change their composition to handle the afore-mentioned unexpected events during operation autonomously. To accomplish this we will need to reason about how best to integrate these strategies into the software of existing robots, as well as how existing information available to designers regarding the robots can best be utilized to improve the strategies. Lastly, these strategies and the process through which they are integrated will be assessed in their impact across different robotic case studies. Preliminary results from the work towards the thesis are also presented, alongside a consideration of its potential industrial impact., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Robot Dynamics

The Multi-modal Information based Speech Processing (MISP) challenge aims to extend the application of signal processing technology in specific scenarios by promoting the research into wake-up words, speaker diarization, speech recognition, and other technologies. The MISP2022 challenge has two tracks: 1) audio-visual speaker diarization (AVSD), aiming to solve "who spoken when" using both audio and visual data; 2) a novel audio-visual diarization and recognition (AVDR) task that focuses on addressing "who spoken what when" with audio-visual speaker diarization results. Both tracks focus on the Chinese language, and use far-field audio and video in real home-tv scenarios: 2-6 people communicating each other with TV noise in the background. This paper introduces the dataset, track settings, and baselines of the MISP2022 challenge. Our analyses of experiments and examples indicate the good performance of AVDR baseline system, and the potential difficulties in this challenge due to, e.g., the far-field video quality, the presence of TV noise in the background, and the indistinguishable speakers., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Multimedia Computing

Spectral power distribution (SPD) is the radiation power intensity at different wavelengths, containing the most basic photometric and colorimetric performance of the illuminant, which is able to predict the lifetime of LEDs. This paper proposes an SPD model assisted by machine learning algorithms to detect the early failure of white LEDs. The SPD features of 3W high-power white LEDs were firstly extracted by the statistical models of Gaussian, Lorentz, and Asym2sig functions. An unsupervised learning method, principal component analysis (PCA), was then used to reduce the extracted features parameters’ dimensions. Next a K-nearest neighbor (KNN)-based method was used to detect LEDs’ anomalies by dividing the main cluster into groups, and estimating the distance from the center of mass of each cluster to the test point. The results showed the following: (1) for selected white LEDs, the Asym2sig function has a better fitting result than Gaussian and Lorentz functions; (2) machine learning methods can significantly assist in LED anomaly detection and can decrease the amount of anomaly detection time to 789.6 h, compared to the 1311 h when lumen maintenance degradation reaches 70% as required by IES TM21., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronic Components, Technology and Materials

This paper proposes a super-resolution harmonic retrieval method for uncorrelated strictly non-circular signals, whose covariance and pseudo-covariance present Toeplitz and Hankel structures, respectively. Accordingly, the augmented covariance matrix constructed by the covariance and pseudo-covariance matrices is not only low rank but also jointly Toeplitz-Hankel structured. To efficiently exploit such a desired structure for high estimation accuracy, we develop a low-rank Toeplitz-Hankel covariance reconstruction (LRTHCR) solution employed over the augmented covariance matrix. Further, we design a fitting error constraint to flexibly implement the LRTHCR algorithm without knowing the noise statistics. In addition, performance analysis is provided for the proposed LRTHCR in practical settings. Simulation results reveal that the LRTHCR outperforms the benchmark methods in terms of lower estimation errors., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Signal Processing Systems

This paper presents novel cascaded channel estimation techniques for an intelligent reflecting surface-aided multiple-input multiple-output system. Motivated by the channel angular sparsity at higher frequency bands, the channel estimation problem is formulated as a sparse vector recovery problem with an inherent Kronecker structure. We solve the problem using the sparse Bayesian learning framework which leads to a non-convex optimization problem. We offer two solution techniques to the problem based on alternating minimization and singular value decomposition. Our simulation results illustrate the superior performance of our methods in terms of accuracy and run time compared with the existing works., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Signal Processing Systems

Estimating tissue conductivity parameters from electrograms (EGMs) could be an important tool for diagnosing and treating heart rhythm disorders such as atrial fibrillation (AF). One of these parameters is the fibre direction, often assumed to be known in conductivity estimation methods. In this paper, a novel method to estimate the fibre direction from EGMs is presented. This method is based on local conduction slowness vectors of a propagating activation wave. These conduction slowness vectors follow an elliptical pattern that depends on the underlying conductivity parameters. The fibre direction and conductivity anisotropy ratio can therefore be estimated by fitting an ellipse to the conduction slowness vectors. Applying the presented method on simulated data shows that it can estimate the fibre direction more accurately than existing methods, and that its performance depends mostly on the range of wavefront directions present in the measurement area. The main advantage of the presented method is that it still functions relatively well in the presence of conduction blocks, as long as the surrounding tissue is approximately homogeneous., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Signal Processing Systems

In recent years, the large increase in connected devices and the data that are collected by these devices have caused a heightened interest in distributed processing. Many practical distributed networks are of heterogeneous nature, because different devices in the network can have different specifications. Because of this, it is highly desirable that algorithms operating within these networks can operate asynchronously, since in that case there is no need for clock synchronisation between the nodes, and the algorithm is not slowed down by the slowest device in the network. In this paper, we focus on the primal-dual method of multipliers (PDMM), which is a promising distributed optimisation algorithm that is suitable for distributed optimisation in heterogeneous networks. Most theoretical work that can be found in existing literature focuses on synchronous versions of PDMM. In this work, we prove the convergence of stochastic PDMM, which is a general framework that can model variations such as asynchronous PDMM and PDMM with transmission losses., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Signal Processing Systems

In this paper, we aim to design an automatic camera pose estimation pipeline for clinical spaces such as catheterization laboratories. Our proposed pipeline exploits Scaled-YOLOv4 to detect fixed objects. We adopt the self-supervised key-point detector SuperPoint in combination with SuperGlue, a keypoint matching technique based on graph neural networks. Thus, we match key-points on input images with annotated reference points. Reference points are chosen on fixed objects in the scene, such as corners of door posts or windows. The point-correspondences between the image coordinates and the 3D coordinates are applied to the Perspective-n-Point algorithm to estimate the pose of each camera. Compared with other camera pose estimation methods, the proposed pipeline does not require the construction of 3D point-cloud model of the scene or placing a polyhedron object in the scene before each required calibration. Using videos from real procedures, we show that the pipeline can estimate the camera pose with high accuracy., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Medical Instruments & Bio-Inspired Technology, Support Biomechanical Engineering, Signal Processing Systems

Nano-metal materials sintering has received increasing attention in recent years for its promising performance in the wide bandgap semiconductor packaging. In this paper, molecular dynamics (MD) simulation method were applied to simulate the nano-Cu sintering mechanism and the subsequent mechanical behavior. Hybrid sintering, comprising nanosphere (NS) and nanoflake (NF), was carried out at temperatures ranging from 500K to 650K. Furthermore, shearing simulations were conducted with constant strain rates on the sintered structure at multiple temperatures, and subsequently correlated the extracted mechanical properties with the sintering behavior. The results indicated that the mechanical properties of nano-Cu sintered structure were improved by tuning material composition and increasing the sintering temperature. We established a relationship between the sintered microstructure and mechanical response, the shear modulus and shear strength of the sintered structure with NF particles increased to 41.2GPa and 3.51GPa respectively. It offers valuable insights into the preparation phase of nano Cu paste for sintering technology., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronic Components, Technology and Materials

Current spatiotemporal learning methods for complex data exploit the graph structure as an inductive bias to restrict the function space and improve data and computation efficiency. However, these methods work principally on graphs with a fixed size, whereas in several applications there are expanding graphs where new nodes join the network; e.g., new sensors joining a sensor network or new users joining a recommender system. This paper focuses on the non-trivial extension of spatiotemporal methods to this setting, where now it is key to jointly capture both the topological and signal dynamics. Specifically, it considers a graph vector autoregressive (GVAR) model for multivariate time series. The GVAR is a multivariate linear model that leverages a bank of graph filters allowing scalability and data efficiency. To account for the dynamic nature of the graphs, the filters’s parameters are learned on-the-fly via adaptive gradient descent with provable sub-linear regret. Numerical results on both synthetic and real data corroborate the proposed method., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Multimedia Computing

The pursuit of battery charging technology for electric vehicle (EV) has led to extensive research on the inductive-based wireless power transfer (WPT) systems. In this paper, the compensation component (including coils) stresses will be studied in two commonly adopted compensation topologies, namely S-S and LCC-S compensations. Due to the peak voltage calculation inaccuracy for certain components based on conventional fundamental frequency analysis, an improved peak voltage calculation method is introduced in closed form, which is proved to be more accurate by both simulation and experiments., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., DC systems, Energy conversion & Storage

Industrial automation calls for precise tasks with cycle times reduced to the minimum. At the same time, when handling delicate products such as fruits and vegetables, accelerations must be kept low to keep interaction forces under a certain threshold to avoid damage. This trade-off hinders the penetration of automation in many relevant application fields. This paper investigates using soft technology to solve this challenge. We propose the FinFix gripper, a non-anthropomorphic soft gripper capable of handling delicate objects at high acceleration using a contact-reactive grasping approach. This gripper has two entirely passive sensorized fingers that establish contact and two active fingers that are actuated pneumatically through a rigid mechanism allowing for rapid closure. We provide exhaustive experimental validation by connecting the gripper to a delta robot. The system can reliably execute pick-and-place cycles in ∼1 s when the distance between the pick and the place locations is 400 mm, resulting in a peak speed of ∼10ms . None of the fragile objects used during the experiments showed any damage. The only information needed is a rough estimation of the object's position to be grasped and a contact event to trigger the reflex. The test results show that the gripper can hold fragile objects during lateral accelerations of 10g., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Learning & Autonomous Control, Medical Instruments & Bio-Inspired Technology

Nowcasting is an observation-based method that uses the current state of the atmosphere to forecast future weather conditions over several hours. Recent studies have shown the promising potential of using deep learning models for precipitation nowcasting. In this paper, novel deep generative models are proposed for precipitation nowcasting. These models are equipped with extreme-value losses to more reliably predict extreme precipitation events. The proposed deep generative model contains a Vector Quantization Generative Adversarial Network and a Transformer ("VQGAN + Transformer"). For enhanced modeling and forecasting of extreme events, Extreme Value Loss (EVL) is incorporated in the autore-gressive Transformer. The numerical results show that the proposed model achieves comparable performance with the state-of-the-art conventional nowcasting method PySTEPS for predicting nominal values. By incorporating an EVL, the proposed model yields more accurate nowcasting of extreme precipitation., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Signal Processing Systems, Water Resources

Fitting a polynomial to observed data is an ubiquitous task in many signal processing and machine learning tasks, such as interpolation and prediction. In that context, input and output pairs are available and the goal is to find the coefficients of the polynomial. However, in many applications, the input may be partially known or not known at all, rendering conventional regression approaches not applicable. In this paper, we formally state the (potentially partial) blind regression problem, illustrate some of its theoretical properties, and propose an algorithmic approach to solve it. As a case-study, we apply our methods to a jitter-correction problem and corroborate its performance., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Signal Processing Systems

In this paper, a novel interleaved high step-up (HSU) converter is presented. The proposed converter features a large voltage gain and common input-output grounding. In this interleaved HSU converter, by using only one zero voltage transition (ZVT) auxiliary circuit with one auxiliary switch and low number of elements, soft switching (SS) performance for all the semiconductors over a wide range of load variations is achieved. This leads to advantages of high efficiency and low complexity, expense, and size. The characteristics of the proposed converter are compared to similar state of the art converters, and to confirm its effectiveness, the simulation results of the proposed converter are presented., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronic Components, Technology and Materials

The electric vehicle (EV) market is expanding rapidly. However, the main barriers to EV adoption are high vehicle costs, range issues, and charging infrastructure. Meanwhile, energy storage systems (ESS) appear as a promising solution to preventing grid overload during charging and reducing infrastructure costs. In this paper, the integration of the battery energy storage system (BESS) in a 450 kW EV charger is designed and investigated via modeling and simulation mainly from the perspective of thermal management. To explore the heat dissipation and the temperature distribution across the pack, the thermal model based on the sub-modeling technique is developed via COMSOL, and a preliminary layout and cooling strategy are determined., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., DC systems, Energy conversion & Storage

A clear understanding of the spectral components of an irradiated beam, or captured optical emission, is essential to optimize an optical system and increase its performance. Logically, for this purpose a grating-based spectrometer could be the first choice. However, in the case of a wide range spectrum, and for radiation with one dominant wavelength, this option may not work well. In this paper, we present a technique based on an array of bandpass detectors to measure accurately the power of a number of beam-specific spectral components in a wide spectrum range: from soft X-ray to infrared. The main unique features of this technique are: customization for specific wavelengths of interest; vacuum compatibility; and high sensitivity to low-energy spectral components in the presence of one or more dominant highpower spectral components., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronic Instrumentation, EKL Processing, BUS/TNO STAFF

This paper investigates thermomigration (TM) and electromigration (EM) in SWEAT structure. Firstly, the distribution of temperature along SWEAT structure during EM is obtained by using finite element (FE) simulation. The FE simulation results show that the temperature is almost uniformly distributed in the most region of narrow line in SWEAT structure, but temperature decreases rapidly at both sides of conductor. Accordingly, the temperature gradient in the narrow line of SWEAT structures is calculated. Then, we apply the obtained temperature and temperature gradient in the governing equation of EM in terms of atomic concentration. The numerical results show that the TM caused by temperature gradient causes the material depletion near both ends of conductor. At the same time, atoms diffuse from the middle region of conductor to both sides driven by the atomic concentration, causing the voids in middle of conductor., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronic Components, Technology and Materials

Silicon carbide (SiC) epitaxial process is a key step in the fabrication of power devices, and the temperature field inside the reactor chamber plays an essential role in this process. In this paper, the temperature field in the horizontal chemical-vapor-deposition reactor chamber used for growing homo-epitaxial 4H-SiC material is studied using the finite-element method. A three-dimensional time-dependency model is built for the accuracy of simulation, and the effects of 11 relative coil locations (−50, −28, −18, −10, −4,0,4,10,18,28, and 50 mm) on heating efficiency and temperature uniformity of the substrate are analyzed. Results indicate that the suitable relative location between the center of coil and that of the substrate to achieve optimum temperature uniformity is −4 mm, and 18 mm to obtain the highest heating efficiency. To increase the heating efficiency and temperature uniformity of the substrate, the structure of the reactor was analyzed and optimized. It is observed that both heating efficiency and temperature uniformity can be effectively improved by adding a graphite pillar inside the down susceptor., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronic Components, Technology and Materials

Metamaterials are artificial structures with properties that are rare or non-existent in nature. These properties are created by the geometry and interconnection of the metamaterial unit cells. In active metamaterials, sensors and actuators are embedded in each unit cell to achieve greater design freedom and tunability of properties after the fabrication. While active metamaterials have been used in vibration control applications, the influence of applied control architectures on damping performance has not been thoroughly studied yet. This paper discusses the relationship between suitable control architectures for increased damping in finite active metamaterials and the number of damped modes. A metamaterial beam consisting of links with measured and actuated joints is considered. Optimal controllers for each of the considered scenarios are designed in the modal domain using linear-quadratic regulator (LQR). We show that, when all modes of a structure should be damped, the optimal solution can be reduced to a decentralised controller. When modes in a smaller range of frequencies are targeted, distributed controllers show better performance. The results are confirmed with experiments., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Mechatronic Systems Design

With the rise of the integration of renewable energy sources, the operating characteristics of existing electric power distribution systems are evolving and changing. As a result, the digitalisation of the distribution network is gaining attention for effective real-time monitoring and control. Cyber-Physical cosimulation is one of the options for implementing and testing novel concepts and ideas before actual implementation on the distribution network. Therefore, this paper presents some experiences on the cyber-physical testbed in the distribution network. Moreover, the methodology, possible challenges and mitigation techniques are also presented for a cyber-physical cosimulation testbed of optimal reactive power control in smarter distribution network (SDN). The cyber-physical co-simulation testbed is analysed using a Typhoon HIL 604 and OpenDSS on a CIGRE MV distribution., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

The (Ca, Sr) AlSiN₃:Eu²⁺(CSASN:Eu) red phosphor is widely used to improve color rendering of high-power phosphor-converted lighting diode (pc-WLED), but it is always unstable under high temperature and high humidity environments. Therefore, the studies on the temperature and humidity resistance of red phosphors and their aging mechanism have become essential to evaluate its reliability in harsh applications. In this paper, the pressure cooker test (PCT) and 85°C&85% RH aging test were carried out for the CSASN:Eu red phosphors. And, its hydrolysis reaction-driven degradation mechanism was simulated and analyzed based on first-principle calculation, in which the optimized adsorption of simplified CaAlSiN3(CASN) and H2 O was simulated based on Density Function Theory (DFT) and the specific aging process was analyzed by the charge density difference and ab initio molecular dynamics (AIMD). The experimental results showed that the photoluminescence performance of CSASN:Eu red phosphor dropped gradually and finally disappeared under PCT aging, and its temperature-dependent degradation kinetics followed the Arrhenius model well. Meanwhile, the simulation results indicate that the CASN, reacted with H2 O when the H atoms had a tendency to approach N atoms. Both the temperature and humidity could accelerate the hydrolysis reaction rate., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronic Components, Technology and Materials

Adhesive bonding is a key joining technology in many industrial applications, including automotive, aerospace industries, biomedical devices, and microelectronic components. Adhesive bonding is gaining more and more attention due to the increasing demand for joining similar or dissimilar components, mostly within the framework of designing lightweight structures. Silicone sealant is widely used in engineering application due to its thermal stability, excellent energy absorption, and good damping characteristics. In those applications, sealant usually exposed to various environment stress, such as, high temperature, mechanical stress, humidity, light radiation, and chemical attack. Long-term stability and durability of sealant is crucial to the performance of the associated application. The main degrading factors for silicone in microelectronic applications are temperature, humidity, alkali, and mechanical loading. The focus in the present paper is to understand different failure mechanisms in silicone sealants and adhesives and to study how different environmental, mechanical, and service-related stresses attribute to the kinetics and extent of degradation in silicone sealants and adhesives. The impact of different failure mechanisms on the lifetime and reliability of microelectronic devices will be methodically investigated., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Electronic Components, Technology and Materials

This paper presents EMGSense, a low-effort self-supervised domain adaptation framework for sensing applications based on Electromyography (EMG). EMGSense addresses one of the fundamental challenges in EMG cross-user sensing—the significant performance degradation caused by time-varying biological heterogeneity—in a low-effort (data-efficient and label-free) manner. To alleviate the burden of data collection and avoid labor-intensive data annotation, we propose two EMG-specific data augmentation methods to simulate the EMG signals generated in various conditions and scope the exploration in label-free scenarios. We model combating biological heterogeneity-caused performance degradation as a multi-source domain adaptation problem that can learn from the diversity among source users to eliminate EMG heterogeneous biological features. To relearn the target-user-specific biological features from the unlabeled data, we integrate advanced self-supervised techniques into a carefully designed deep neural network (DNN) structure. The DNN structure can seamlessly perform two training stages that complement each other to adapt to a new user with satisfactory performance. Comprehensive evaluations on two sizable datasets collected from 13 participants indicate that EMGSense achieves an average accuracy of 91.9% and 81.2% in gesture recognition and activity recognition, respectively. EMGSense outperforms the state-of-the-art EMG-oriented domain adaptation approaches by 12.5%-17.4% and achieves a comparable performance with the one trained in a supervised learning manner., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Embedded Systems

The paper presents the realization of an experimental setup used for testing energy harvesting and storage devices based on the use of lead-free bismuth sodium titanate-barium titanate (NBT-BT) in combination with polyvinylidene fluoride (PVDF) polymer. PVDF is a polymer matrix in which piezoelectric phase is dispersed and enables formation of flexible films by hot pressing method. The paper presents an electromechanical model of a typical PVDF module, generates a simulation model, and presents simulation results. The experimental setup is based on a mechanical excitation for generating pulses of an force of different amplitude and duration, applied on the aforementioned energy harvesting NBT-BT-PVDF devices, likewise, on an electronic assembly for measuring the pulses of electrical quantities (current and voltage), that are generated at the output electrodes. The research in this paper is predominantly experimental and it shows the obtained oscilloscope recordings of the excitation force and output voltage of energy harvesting modules at different modes and conditionsof mechanical excitation. After this, a comparison of the simulation and experimental results is made.

As diseases of the nervous system become more and more frequent, the research on instruments such as nerve stimulation is becoming more and more important. In this paper, the design of a neural stimulator based on MOS transistors is investigated. The basic principles of MOS transistor and neural stimulator are described in this paper. The structure, type, and application of different neurostimulator are described. The circuit of bipolar pulse neural stimulator based on MOS transistors is designed and analyzed. There is no doubt that through the research and explanation of this paper, more people will understand the neural stimulator, which is of great significance to the popularization and research of neural stimulator.

Retrofilling of an existing mineral oil-immersed transformer with ester oil is an alternative approach to extend the lifespan of transformers. This is associated with the excellent properties of ester oil that has high tolerance to moisture that promotes an advantage to prolong the life of paper insulation. However, the retrofilling process will mix the fresh ester oil with the remaining aged mineral oil in the transformer oil, and eventually affects the performance of the new ester oil. Therefore, it is essential to access the performance of mixed oil in order to detect any signs of oil degradation as a result of retrofilling, prior to transformer energization. In this paper, the total acid number (TAN) and Fourier Transform Infrared (FTIR) spectra were measured and analyzed to assess the condition of mixed aged mineral-synthetic ester oil (AMO/SE). Three different proportions of aged mineral oil (AMO), i.e. 3 %, 5 % and 7 % were prepared to simulate different amount of mineral oil residue in a transformer before being retrofilled with fresh synthetic ester oil. The AMO were prepared through thermally ageing of fresh mineral oil in a vacuum oven at 130°C for 150 hours. Based on the findings, it has been intriguingly discovered that the acid number of the AMO/SE oil has decreased as the percentage of AMO increased in fresh synthetic ester oil. In correlation with FTIR spectra, the present acid concentration of the degradation by-product of the retrofilled AMO/SE oils can be observed in carbonyl stretch region at the wavelength of 1700 – 1800 cm−1.

This paper focuses on the challenges and issues of detecting malware in to-day's world where cyberattacks continue to grow in number and complexity. The paper reviews current trends and technologies in malware detection and the limitations of existing detection methods such as signature-based detection and heuristic analysis. The emergence of new types of malware, such as file-less malware, is also discussed, along with the need for real-time detection and response. The research methodology used in this paper is presented, which includes a literature review of recent papers on the topic, keyword searches, and analysis and representation methods used in each study. In this paper, the authors aim to address the key issues and challenges in detecting malware today, the current trends and technologies in malware detection, and the limitations of existing methods. They also explore emerging threats and trends in malware attacks and highlight future directions for research and development in the field. To achieve this, the authors use a research methodology that involves a literature review of recent papers related to the topic. They focus on detecting and analyzing methods, as well as representation and extraction methods used in each study. Finally, they classify the literature re-view, and through reading and criticism, highlight future trends and problems in the field of malware detection.

Underwater surveillance using passive sonar and track-before-detect technology requires accurate models of the tracked signal and the background noise. However, in an underwater environment, the signal channel is time-varying and prior knowledge about the spatial distribution of the background noise is unavailable. In this paper, an autoregressive model that captures a time-varying signal level caused by multi-path propagation is presented. In addition, a multi-source model is proposed to describe spatially distributed background noise. The models are used in a Bernoulli filter track-before-detect framework and evaluated using both simulated and sea trial data. The simulations demonstrate clear improvements in terms of target loss and improved ability to discern the target from the noisy background. An evaluation of the track-before-detect algorithm on the sea trial data indicates a performance gain when incorporating the proposed models in underwater surveillance and tracking problems.

The surge in data generated by IoT sensors has increased the need for scalable and efficient data analysis methods, particularly for robust algorithms like quantile regression, which can be tailored to meet a variety of situations, including nonlinear relationships, distributions with heavy tails, and outliers. This paper presents a sub-gradient-based algorithm for distributed quantile regression with non-convex, and non-smooth sparse penalties such as the Minimax Concave Penalty (MCP) and Smoothly Clipped Absolute Deviation (SCAD). These penalties selectively shrink non-active coefficients towards zero, addressing the limitations of traditional penalties like the l(1)-penalty in sparse models. Existing quantile regression algorithms with non-convex penalties are designed for centralized cases, whereas our proposed method can be applied to distributed quantile regression using non-convex penalties, thereby improving estimation accuracy. We provide a convergence proof for our proposed algorithm and demonstrate through numerical simulations that it outperforms state-of-the-art algorithms in sparse and moderately sparse scenarios., Funding Agencies|Research Council of Norway

This paper proposes the modeling and analysis of multi-energy systems as multilayer networks. The aim is to assess the interdependence between different energy infrastructures. Multilayer network modeling enhances the one-dimensional graph-based approach employed to study the vulnerability and the topological characteristics of power grids. The centrality indices defined for one-dimensional networks are extended to multilayer networks, highlighting the differences emerging when interdependence is considered. The proposed multilayer framework is demonstrated on the 24-bus IEEE power grid coupled with a gas network with 7 nodes.

The QSAT problem, which asks to evaluate a quantified Boolean formula (QBF), is of fundamental interest in approximation, counting, decision, and probabilistic complexity and is also considered the prototypical PSPACE-complete problem. As such, it has previously been studied under various structural restrictions (parameters), most notably parameterizations of the primal graph representation of instances. Indeed, it is known that QSAT remains PSPACE-complete even when restricted to instances with constant treewidth of the primal graph, but the problem admits a double-exponential fixed-parameter algorithm parameterized by the vertex cover number (primal graph). However, prior works have left a gap in our understanding of the complexity of QSAT when viewed from the perspective of other natural representations of instances, most notably via incidence graphs. In this paper, we develop structure-aware reductions which allow us to obtain essentially tight lower bounds for highly restricted instances of QSAT, including instances whose incidence graphs have bounded treedepth or feedback vertex number. We complement these lower bounds with novel algorithms for QSAT which establish a nearly-complete picture of the problems complexity under standard graph-theoretic parameterizations. We also show implications for other natural graph representations, and obtain novel upper as well as lower bounds for QSAT under more fine-grained parameterizations of the primal graph., Funding Agencies|Austrian Science Fund (FWF) [J4656, P32830, Y1329]; Society for Research Funding Lower Austria (GFF) [ExzF-0004]; Vienna Science and Technology Fund (WWTF) [ICT19-060, ICT19-065]; ELLIIT - Swedish government

Hegselmann-Krause (HK) models exhibit complex behaviors which are not easily tractable through mathematical analysis. In this paper, a characterization of the steady-state behaviors of homogeneous HK models and sensitivity to confidence thresholds is discussed by commenting on existing and new numerical results. The typical decreasing of number of clusters and convergence time by increasing the confidence thresholds are discussed and motivations for the behavior of some counterexamples are provided. A tighter upper bound for the dependence of the number of clusters with respect to the confidence thresholds is proposed. Differences and analogies between the opinions evolution for symmetric and asymmetric HK models are commented.

The use of wildcard certificates and multi-domain certificates can impact how sensitive a certificate is to attacks and how many (sub)domains and machines may be impacted if a private key is compromised. Unfortunately, there are no globally agreed-upon best practices for these certificate types and the recommendations have changed many times over the years. In this paper, we present a 10-year longitudinal analysis of the usage of wildcard certificates and multi-domain certificates on the internet. Our analysis captures and highlights substantial differences in the heterogenous wildcard and multi-domain certificate practices. The results also show that there are several ways that CAs and domain owners have chosen to improve their practices, with many appearing to reduce the number of domains (and subdomains) for which each certificate is responsible., Funding Agencies|Swedish Foundation for Strategic Research (SSF); Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

Predicting pedestrian behavior when interacting with vehicles is one of the most critical challenges in the field of automated driving. Pedestrian crossing behavior is influenced by various interaction factors, including time to arrival, pedestrian waiting time, the presence of zebra crossing, and the properties and personality traits of both pedestrians and drivers. However, these factors have not been fully explored for use in predicting interaction outcomes. In this paper, we use machine learning to predict pedestrian crossing behavior including pedestrian crossing decision, crossing initiation time (CIT), and crossing duration (CD) when interacting with vehicles at unsignalized crossings. Distributed simulator data are utilized for predicting and analyzing the interaction factors. Compared with the logistic regression baseline model, our proposed neural network model improves the prediction accuracy and F1 score by 4.46% and 3.23%, respectively. Our model also reduces the root mean squared error (RMSE) for CIT and CD by 21.56% and 30.14% compared with the linear regression model. Additionally, we have analyzed the importance of interaction factors, and present the results of models using fewer factors. This provides information for model selection in different scenarios with limited input features., Funding Agencies|European research project "SHAPE-IT - Supporting the Interaction of Humans and Automated Vehicles: Preparing for the Environment of Tomorrow"; European Union [860410]

Recent studies of selective auditory attention have demonstrated that neural responses recorded with electroencephalogram (EEG) can be decoded to classify the attended talker in everyday multitalker cocktail-party environments. This is generally referred to as the auditory attention decoding (AAD) and could lead to a breakthrough for the next-generation of hearing aids (HAs) to have the ability to be cognitively controlled. The aim of this paper is to investigate whether cepstral analysis can be used as a more robust mapping between speech and EEG. Our preliminary analysis revealed an average AAD accuracy of 96%. Moreover, we observed a significant increase in auditory attention classification accuracies with our approach over the use of traditional AAD methods (7% absolute increase). Overall, our exploratory study could open a new avenue for developing new AAD methods to further advance hearing technology. We recognize that additional research is needed to elucidate the full potential of cepstral analysis for AAD.

This paper considers a communication system where a source sends time-sensitive information to its destination. We assume that both arrival and service processes of the messages are memoryless and the source has a single server with no buffer. Besides, we consider that the service is interrupted by an independent random process, which we model using an On-Off process. For this setup, we study the age of information for two queueing disciplines: 1) non-preemptive, where the messages arriving while the server is occupied are discarded, and 2) preemptive, where the in-service messages are replaced with newly arriving messages in the Off states. For these disciplines, we derive closed-form expressions for the mean peak age and mean age., Funding Agencies|US NSF [CNS-1814477, CNS-2225511]; Swedish Research Council (VR); ELLIIT; European Union (ETHER) [101096526]; Zenith

Extending the wireless power transfer range in miniaturized remotely powered micro-devices is a big challenge due to the very small effective area and low gain of the mm-sized antenna utilized in the micro-devices, which limits the harvested RF energy. This paper presents a method for increasing the separation distance between an external energy source antenna as a transmitter (TX) and micro device antenna as a receiver (RX) beyond 10 cm by utilizing various TX antennas, including a conventional loop antenna, multiple patch antennas, and a rectangular cavity antenna, and a 2-turn double-sided square loop RX antenna, sized 1.2mm x 1.2mm on FR4 substrate, which can be mounted on top of a CMOS SoC. The performance of the wireless power transfer system is evaluated and compared in different scenarios. At the 434 MHz ISM band, the results indicate that the highest peak power transfer efficiency of -20 dB and the highest harvested DC voltage of 4 V through an 8-stage Dickson RF-DC converter are obtained inside the rectangular hollow cavity sized 49.6cm x 49.6cm x 30.4cm, as TX, with an input TX power of 20 dBm. Furthermore, the multiple patch antennas have a power transfer efficiency of -39 dB and a harvested DC voltage of 2.5 V at a distance of 10 cm with an input TX power of 37 dBm. The specific absorption rate of both cases stays below the limits established by IEEE., Funding Agencies|Swedish Foundation for Strategic Research (SSF) [RMX18-0066]

An autonomous underwater vehicle (AUV) is a crewless robotic vehicle that dives into the water and performs without human assistance. This paper focuses on developing trajectory tracking control for bio-mimetic AUV system under uncertain environments. Therefore, a relatively new control technique called time delay-based estimation control is proposed for trajectory tracking under multiple uncertainties. This algorithm estimates the total disturbance in the system using immediate past information of input and output of feedback state and control variables. The benefit of this scheme is that it avoids assumptions about a priori upper bound information of disturbance. Further, the control structure is simple and does not require any high-frequency switching or high gain to nullify the effects of disturbance. The theoretical analysis of the proposed scheme guarantees the uniformly ultimate bounded stability of the closed-loop system. The numerical analysis is also carried out to validate the control performance of the given algorithm for lemniscate reference path tracking.

Automated vehicles connected through vehicle-tovehicle communications can use onboard sensor information from adjacent vehicles to provide higher traffic safety or passenger comfort. In particular, automated vehicles forming a platoon can enhance traffic safety by communicating before braking hard. It can also improve fuel efficiency by enabling reduced aerodynamic drag through short gaps. However, packet losses may increase the delay between periodic beacons, especially for the rear vehicles in a platoon. If the connected vehicles can forecast link quality, they can assign different performance levels in terms of intervehicle distances and also facilitate the designing of safer braking strategies. This paper proposes a strategy for incorporating machine learning algorithms into, e.g., the lead vehicle of a platoon to enable online training and real-time prediction of communication delays incurred by connected vehicles during runtime. The prediction accuracy and its suitability for making safety-critical decisions during, e.g., emergency braking have been evaluated through rigorous simulations.

The paper is devoted to the analysis of the TE-wave propagation in a planar waveguide with variable permittivity. The setting is reduced to a transmission eigenvalue problem for an ordinary differential equation where the spectral parameter is the wave propagation constant. For the computation of eigenvalues the shooting method is applied in the form specifically developed for this class of problems. The method allows one to calculate propagating, evanescent, and complex surface and leaky waves. A variety of numerical results illustrating the method is presented.

Accurate localization is essential for future wireless networks and perceptive mobile networks (PMNs) were proposed as a special type of integrated sensing and communication (ISAC) scheme, where the sensing functionality is integrated into current mobile networks. One exciting opportunity for PMNs is the collaborative sensing, where the perspectives of multiple base stations (BSs) are jointly utilized to sense the same target in a more effective way. In this paper, we will investigate the fundamental limits of collaborative sensing, which is not yet available in the literature. To this end, we derive the Cramér-Rao Bound (CRB) for the mean squared error (MSE) performance of the maximum likelihood estimator. Based on the evaluation results, we further investigate the effect of several important system parameters including the number of BSs, the number of antennas at each BS, and the relative location of the target and the BSs. The results are then utilized to propose a BS selection algorithm for achieving a good trade-off between localization accuracy and system complexity. Simulation results validate the accuracy of the performance evaluation results and illustrate the effectiveness of the proposed BS selection algorithm. © 2023 IEEE.

With the increasing attention and corresponding developments of data collection of underwater surveying/diving videos, a large number of underwater videos have been yielded for different purposes. However, it is time-consuming and requires the corresponding expertise to yield a hierarchical and comprehensive biological analysis report based on the collected underwater videos. The development of the underwater video analysis platform is an emergency and users of such a platform should not be limited to some specific groups (e.g., biological experts). The existing VIAME provides an intelligent solution for fishery and marine organism analysis with an installable platform. Differently, in this paper, we develop a novel cloud-based underwater video analysis platform, which focuses on more diverse marine species such as coral reefs and sea urchins. The proposed platform could provide hierarchical and comprehensive services for a wider user group. We aim to build a one-stop platform, which could allow every user to upload their surveying or diving videos and build a centralized database for more robust and accurate data analysis.

Intelligent reflecting surfaces (IRSs) are envisioned as a low-cost solution to achieve high spectral and energy efficiency in future communication systems due to their ability to customize wireless propagation environments. Although resource allocation design for IRS-assisted multiuser wireless communication systems has been exhaustively investigated in the literature, the optimal design and performance of such systems are still not well understood. To fill this gap, in this paper, we study optimal resource allocation for IRS-assisted multiuser multiple-input single-output (MISO) systems. In particular, we jointly optimize the beamforming at the base station (BS) and the discrete IRS phase shifts to minimize the total transmit power. For attaining the globally optimal solution of the formulated non-convex combinatorial optimization problem, we develop a resource allocation algorithm with guaranteed convergence based on Schur's complement and the generalized Bender's decomposition. Our numerical results reveal that the proposed algorithm can significantly reduce the BS transmit power compared to the state-of-the-art suboptimal alternating optimization-based approach, especially for moderate-to-large numbers of IRS elements.