esa-sceva/satcom-chunk-collection huggingface dataset:
# Determination of the Equivalent Thickness of a Taiko Wafer Using ANSYS Finite Element Analysis
## 7 Conclusions  
In conclusion, we have determined analytically, in a linear approximation, the dependence of the slope of the curvature vs. stress curve, of an FSM taiko wafer as a function  
Figure 8: Slope in the linear case of a taiko wafer reported as a function of the substrate thickness in \(\upmu\)m and its comparison with the slope provided by the Stoney equation.  
Figure 9: Equivalent thickness of an FSM-taiko wafer as a function of the substrate thickness.  
of the thickness of the substrate. From this we derived the equation of the equivalent thickness of an FSM taiko wafer. In parallel, we developed an FEM ANSYS mechanical model of the same system and investigated the warpage as a function of the stress of the metal layer, for different values of substrate thickness. From these data we calculated the slope as a function of the thickness, as well as the values of the equivalent thickness and pursued a comparison with the analytical results.  
The comparison of the two approaches reveals that the analytical solution provides the right order of magnitude of the slope and a value which agrees with the ANSYS simulations experiments. Moreover, the trend of the mitigation of the curvature due to the structure of the taiko wafer, by thinning the substrate, can be reproduced, also showing a good match with the finite element model devised with the ANSYS simulation tools. Hence, by exploiting simulations, it is proven that the FSM-taiko wafer behaves as an equivalent flat wafer whose thickness is higher than the substrate thickness in the central region of the taiko wafer. All these findings indicate that the theory explains well the physics which is behind the mitigation of the warpage of a taiko wafer. On the other hand, since the results obtained with ANSYS have been validated, we can rely on these simulation experiments to explore further properties of an FSM taiko wafer. Lastly the obtained results can also be extended to investigate other wide band gap semiconductors such as silicon carbide and gallium nitride.  
V.V. Conceptualization of the work, analytical model elaboration, conceptualization of the ANSYS(r) simulation experiments, data elaboration, paper drafting, editing, and writing. G.L.M. ANSYS(r) system design, optimization and simulations. A.L. first validation of the approach, M.R. sponsorship, funding, validation. All authors have read and agreed to the published version of the manuscript.  
This research was partially funded by the H2020-ECSEL Joint Undertaking under grant agreement n783158, REACTION (first and euRopEAn siC eigTh Inches piOct liNe) Project, the Important Project of Common European Interest (IPCEI-ME) and by the European Union (NextGeneration EU), through the MUR-PNRR project SAMOTHRACE (ECS00000022).  
All data underlying the results are available as part of the article and no additional source data are required.  
The authors declare no conflict of interest.
# High Precision Indoor Positioning System for Mobile Asset Management and Safety +
### Techniques of Indoor Positioning  
Several techniques can be implemented to locate the object in an indoor environments, such as:  
* **RSS**: This technique is purely dependent on the signal strength of the system. The transmitter 1 transmits the radio signal received by the receiver, which provides the approximation of an object. However, this technique is not suitable where high accuracy is required.
* **TOF**: This system focuses on radio signal propagation sent from the transmitter for the flight time to the receiver. This appropriate method works smoothly because the speed of radio waves in the air is known.
* **TDOA**: In TDOA, three or more anchors are placed on known locations, and these anchors are time-synchronized, as shown in Figure 1.
### Related Work
However, as explained there, using a log-frequency spectrogram inevitably results in a loss in frequency resolution which in this case needs to be mitigated via heavy preprocessing. Moreover, phase information is lost completely. Therefore, if given the choice, we argue that a linear-frequency representation should be preferred. Due to the general success of deep neural networks, it is not surprising that they have also been applied to audio source separation problems. In fact, when it comes to supervisedseparation (with labeled training data), they dominate the state of the art [21, 22, 23, 24, 25]. While supervised training is the \"classical\" way in which neural networks are used, it was demonstrated by [PERSON] el al. with the _deep image prior_ (DIP) approach [26] that the structure of (convolutional) neural networks is inherently useful for representing natural images. This technique was used for image decomposition by [PERSON] et al. via the _double-DIP_ algorithm [27]. Given this success, it was natural to also apply this method to audio data, leading to the _deep audio prior_ approach by [PERSON] et al. [28]. Based on this, [PERSON] et al. [29] used _generative adversarial networks_ (GANs) trained on unlabeled training data as priors, further improving the quality of the output signals. The problem with all the previously presented separation algorithms based on unsupervised training of neural networks is that they make the assumption that the separated signals are stochastically independent. This case is often referred to as the _cocktail party problem_, but it is different from polyphonic music, in which the tones are usually both rhythmically and harmonically aligned. Therefore, rather than relying on general stastistical properties of the signals, we use deep neural networks in conjunction with a parametric model. _Policy gradients_ were pioneered within reinforcement learning with the _REINFORCE_ algorithm [30], which is designed to train a neural network to predict a discrete variable. While reinforcement learning has progressed towards _actor-critic_ methods, cf. [2], and, famously, the _AlphaG Zero_[31], _AlphaZero_[32], and _MuZero_[33] algorithms based on _Monte Carlo tree search_ (MCTS), we stay relatively close to the original approach, but we extend the formulation by adding deterministic values, combining policy gradients with backpropagation gradients.
# High-Speed GaN-Based Superluminescent Diode for 4.57 Gbps Visible Light Communication
## 3 Results
### Data Communication Performance  
We firstly use a network analyzer to observe the frequency response of the SLD-based VLC system, and the result is shown in Figure 5. When the injection current exceeds 80 mA, there is a significant increase in modulation, suggesting that the SLD operating in the amplified spontaneous emission regime has a better frequency response characteristic. The device shows a \(-\)10 dB and \(-\)20 dB bandwidth beyond 700 MHz and 1.3 GHz, respectively.  
Figure 3: The measured light output current–voltage (L-I-V) relations of the SLD.  
In the data communication experiment where SLD is used as the transmitter, the driving current and the amplitude of the signal should be optimized for communication applications. Thus, we perform a series of measurements to find the optimal working condition of the SLD transmitter for achieving a high data rate. We test the average QAM order under a bias current from 180 mA to 320 mA, with a step of 10 mA, and under the peak-to-peak voltage (V\({}_{\text{pp}}\)) generated by the AWG, from 350 mV to 650 mV, with a step of 50 mV. As shown in Figure 6, to attain the highest QAM order, the V\({}_{\text{pp}}\) is set at 500 mV, and the driving current of 290 mA is set for the DC bias of the SLD. According to the device characterization results, the corresponding operating voltage is \(\sim\)6.98 V, the emission peak is \(\sim\)442 nm, and the FWHM is \(\sim\)12 nm at 290 mA. The \(-\)3 dB and \(-\)20 dB bandwidth of the VLC system are 110 MHz and 1.4 GHz, respectively.  
The gain control voltage of the amplifier is set as 1 V, and an attenuation of 5 dB is set by the attenuator. To reduce the spontaneous emission component of the beam, an iris is placed in front of the Rx. The utilized bandwidth is adjusted to achieve a higher data rate in the experimental system. We test the transmission rate using a modulation bandwidth from 1 GHz to 1.425 GHz, with a step of 250 MHz. When testing the data rate, the BER is strictly controlled under the forward error correction (FEC) threshold 3.8 \(\times\) 10\({}^{-3}\). As is shown in Figure 7a, the optimized bandwidth is tested as 1.35 GHz. The SNR and allocated bits for each subcarrier are demonstrated in Figure 7b. The constellation diagrams for different QAM orders in this experiment are also included. From the constellation diagrams, we  
Figure 4: (**a**) Spectra of SLD under different injection currents ranging from 20 mA to 320 mA; (**b**) the changes in peak position and FWHM versus injection current.  
Figure 5: The frequency response of the blue SLD-based VLC system.  
can observe a clear separation of constellation points, which indicates a relatively good SNR. In the SLD-based VLC data link, the highest QAM order reaches six. At a data rate of 4.57 Gbps, the BER is \(\sim\)3.5 \(\times\) 10\({}^{-3}\), which satisfied the forward error correction (FEC) standard of 3.8 \(\times\) 10\({}^{-3}\).
## 2 Noncontact Mechanical Property Testing Methods
### Photothermal (PT) Techniques
A  
Figure 8: Schematic of lock-in photo-thermo-mechanical radiometry (PTMR) testing with a single-point detector and a confocal radiation collection system, redrawn based on [100]. Figure 7: Schematic of a lock-in photothermal technique for stress-strain evaluation, redrawn based on [97]. Figure 9: Composite thermal parameter \(\kappa\) as a function of strain that shows good analogy with a typical engineering stress-strain curve, reproduced from [100] with permission from Elsevier © 2016.  
linear dependence of thermal diffusivities on the load level was found within the elastic regime and only a minimal 0.6% diffusivity change occurred the in nano-coated samples. Based on these reports, the PTMR research was extended to a number of complex materials and structures with different elasticity. Mechanical properties of intact, defective and multi-structured samples were evaluated by studying the stability of thermo-mechanical parameters under loading. Photothermal techniques have advantages over other methods in characterizing stress-strain relations. Compared with PA, PTMR detection usually evaluates mechanical performance through diffusivity changes. Coupling between thermoelastic properties can be completely separated and the mechanical stress-strain relation can be represented by a single parameter. In addition, dynamic PT techniques generate thermal-wave fields inside a sample where the effective thermal diffusion length can be controlled by the modulation frequency or the delay time of the photothermal source which can be made to impinge on specific locations and thus can be more sensitive to regionally distributed stresses. The use of continuous wave lasers and thermal infrared detectors and cameras makes the PTMR methodology totally non-contact. Nevertheless, PT techniques analyze the thermophysical properties by sensing thermal-wave field changes and thus are time consuming and optimally performing when confocal optical systems are used which can be complicated and expensive.
# Predictive Distillation Method of Anchor-Free Object Detection Model for Continual Learning
## 1 Introduction
* The object detection CL model proposed in this study is an algorithm for distilling the teacher model prediction (t-pred) and delivering it to the next learning model. This can be distinguished from the models described in prior studies in the following ways:
* Instead of the simple layer distillation KD technique, we propose a method for generating the GT' that combines t-pred with the ground truth (GT), which transforms t-pred into the same form as the GT. * Two problems of t-pred, the prediction result of the t-model, are solved as follows: 1. Not all results of t-pred are correct; to delete the error results, prediction information is only used when the prediction score of t-pred is greater than or equal to the threshold value. 2. Objects included in the GT only have information about new classes, but the t-model only interprets new images as past class lists; as a result, t-pred can misclassify new class objects into past classes. To solve this problem, the IoU scores of the object of the GT and the object of t-pred are compared to prevent misclassification by using only objects below the threshold. * Among the objects included in the new learning image target, the number of objects related to the previous class was small. Considering this problem, KD can be performed for entire output layers to distill all the information related to the class, size, and size correction values of the object. * In our study, old data and old class labels are not reused in the learning process of the s-model. The dataset is used separately in learning as shown in Figure 1. In this process, when the existing loss function of the CenterNet model is used as it is, information on the existing class cannot be learned in the new class learning process. It means there is a problem in that the weight associated with the existing class is changed. We suggest that the loss function associated with the existing class is modified among the loss functions. The s-model first learns new classes at the GT and then learns information from the previous class and new class information together at the GT' to reduce the occurrence of catastrophic forgetting about existing classes when learning new classes. The rest of this paper is organized as follows. Section 2 examines existing studies on CL and object detection. Section 3 deals with the database scenario and proposes a CL model by applying KD to the anchor-free model and distilling the predictions of the t-model. Section 4 describes how the experimental environment and comparison verification targets are organized to perform the experiment and compare the results. Finally, Section 5 presents the conclusions of the present study and directions for future research.
# Chloride Resistance of Assembled Bridge Piers Reinforced with Epoxy-Coated Steel Bars
## 4 Service Life Prediction
### Determination of \(D_{\text{NSSD}}\)
#### 4.1.2 The Correction of Diffusion Coefficient  
In concrete, chloride ions exist as free and bound chloride ions. It is primarily the free chloride ion that causes corrosion of steel bars. During the transport process of free chloride ions within the concrete, physical adsorption and chemical binding occur, partially converting them into bound chloride ions. To account for the effects of adsorption and  
Figure 18: Corrosion morphology of bar in joint 2.  
binding, scholars have proposed a modification of the chloride ion diffusion coefficient according to Equation (6) [30]:  
\[D_{\rm c}=\frac{D}{1+\frac{1}{\omega_{\rm c}}\frac{\alpha_{\rm b}}{\omega_{\rm c }}} \tag{6}\]  
where \(D_{\rm c}\) represents the modified chloride ion diffusion coefficient accounting for adsorption and binding effects; \(D\) is the unmodified chloride ion diffusion coefficient; \(\omega_{\rm e}\) is the volume ratio of evaporable pore water to concrete, typically assumed to be 8% [31]; \(C_{\rm b}\) denotes the content of bound chloride ions; and \(C_{\rm f}\) represents the content of free chloride ions.  
Under specified conditions of temperature and chloride ion concentration range, the relationship between the content of bound chloride ions (\(C_{\rm b}\)) and the content of free chloride ions (\(C_{\rm f}\)) is known as the chloride binding isotherm. Currently, commonly used models of chloride binding isotherms [32] include the Linear Binding Isotherm (Equation (7)), the Langmuir Isotherm (Equation (8)), and the Freundlich Isotherm (Equation (9)).  
\[C_{\rm b}=\alpha C_{\rm f} \tag{7}\]  
\[C_{\rm b}=\frac{\alpha C_{\rm f}}{(1+\beta C_{\rm f})} \tag{8}\]  
\[C_{\rm b}=\alpha C_{\rm f}^{\beta} \tag{9}\]  
Among these, the Freundlich isotherm has been shown to fit the data best [32]. However, the Linear Binding Isotherm is often used in numerical simulations to reduce the workload of modeling and improve computational efficiency [33]. In this chapter, the Linear Binding Isotherm is adopted, referencing the isotherm used in the studies by [PERSON] et al. under similar water-to-cement ratios and environmental chloride ion concentration conditions [33]. Using \(\alpha=0.2\), Equation (7) is substituted into Equation (6) to derive the modified chloride ion diffusion coefficient considering the effects of chloride ion adsorption and binding, as shown in Equation (10):  
\[D_{\rm c}=0.28571D \tag{10}\]  
Thus, by using Equations (5) and (10) and incorporating the \(D_{\rm nssm}\) values for various materials and interfaces, the value of \(D_{\rm nsSD}\) can be obtained, which is one of the most crucial parameters for numerical simulations of the chloride ion diffusion process, as shown in Equation (11):  
\[D_{\rm nsSD}=0.14286D_{\rm nssm} \tag{11}\]
# A Distance-Encoded Bloom Filter for Fast NDN Name Lookup
###### Abstract  
A shared data networking (NDN) is a content-centric network architecture that requires efficient name lookup to forward packets based on hierarchical content names. Whereas IP lookup operates on fixed-length addresses, NDN name lookup must identify the longest matching prefix (LMP) from a variable-length name space, making it computationally challenging. Hash table-based approaches provide \(O\) (1) search complexity but often require multiple accesses due to the unknown LMP length. To mitigate excessive off-chip memory accesses, Bloom filter-assisted pre-checking is commonly employed. However, conventional Bloom filter-based approaches can only perform membership tests and do not provide information about the next search range, which limits their ability to effectively reduce Bloom filter accesses. This paper proposes a distance-encoded Bloom filter to improve name lookup efficiency. It encodes two distance values into the Bloom filter, enabling a more refined search range compared to binary search-based methods. By utilizing these encoded distances, the proposed scheme not only reduces the number of Bloom filter queries but also ensures that only prefix nodes need to be stored in the hash table. This helps reduce hash collisions and minimize off-chip memory accesses. Experimental evaluation using large-scale FIB datasets shows that the proposed approach reduces both Bloom filter accesses and hash table lookups, which contributes to improving overall lookup performance.  
a _Applied Sciences_  
Academic Editor: [PERSON]  
Received: 28 February 2025  
Revised: 30 March 2025  
Accepted: 7 April 2025  
Published: 10 April 2025  
**Citation:** [PERSON]; [PERSON]-C. A Distance-Encoded Bloom Filter for Fast NDN Name Lookup. _Appl. Sci._**2025**, 154163. [[https://doi.org/10.3390/appl/15084163](https://doi.org/10.3390/appl/15084163)]([https://doi.org/10.3390/appl/15084163](https://doi.org/10.3390/appl/15084163))  
**Copyright:** 62 2025 by the authors.  
Luoense MDPL, Basel, Switzerland.  
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license  
([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))).
## 3 Results and Discussion
### Responsive Carrier Release Mechanism  
Figure 11 illustrates the release behavior of responsive carriers in aqueous solutions. Three sets of conductivity measurements were conducted: with the blank solution, with the  
Figure 10: Schematic diagram of vegetation growth in eco-soil at different curing ages.  
Figure 9: Vegetation height evolution in eco-soil over time.  
solution with encapsulated carriers, and with the solution with non-encapsulated carriers (NSZ group), using 70 \({}^{\circ}\)C heating for 15 min to activate the response. As shown in the figure, prior to thermal stimulation (0-15 min), the conductivity of both the encapsulated and blank groups remained stable within 20-30 \(\upmu\)S/cm, indicating that the encapsulation coating effectively restricted ion migration at ambient temperature, maintaining electrochemical inertness. In contrast, the NSZ group was directly exposed to the solution because the carrier loaded with APS was not encapsulated, and its initial conductivity was higher and reached 150 \(\upmu\)S/cm. Upon thermal triggering, the encapsulation coating underwent phase transition and dissociation, enabling directional carrier release. The conductivity of the encapsulated group surged to 120 \(\upmu\)S/cm within 5 min, approaching the dynamic equilibrium level of the NSZ group (140 \(\upmu\)S/cm). This abrupt transition confirms the feasibility of thermally responsive encapsulation technology in precisely regulating carrier release kinetics.  
Figure 12 demonstrates the release behavior of responsive carriers in a hydrogel system. Specimens were thermally triggered using a 500 W power source for 15 min. As shown in the figure, prior to thermal activation (0-60 min), the viscosity of both the encapsulated (ZT-package) and blank groups remained stable within 0-5 mPa-s, exhibiting rheological properties similar to conventional curing slurries. This confirms that the encapsulation coating technology effectively delays contact between active hydrogel components and crosslinkers through physical isolation, ensuring normal fluidity during storage and construction. In contrast, the ZT-unpackage group (with unencapsulated carriers) showed immediate crosslinker release upon mixing, triggering rapid reactions with precursor solutions. This resulted in an initial viscosity exceeding 35 mPa-s, indicating significant pre-crosslinking tendencies. Upon thermal triggering (60 min), the ZT-package group exhibited rapid dissociation of the encapsulation layer under heat, followed by directional release of active components. This initiated crosslinking reactions, driving viscosity to surge beyond 30 mPa-s within 30 min--demonstrating pronounced thermo-responsive behavior.  
Figure 11: Controlled release of responsive carriers in aqueous solution.