esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
In this paper, an object localization and tracking system is implemented with an ultrasonic sensing technique and improved algorithms. The system is composed of one ultrasonic transmitter and five receivers, which uses the principle of ultrasonic ranging measurement to locate the target object. This system has several stages of locating and tracking the target object. First, a simple voice activity detection (VAD) algorithm is used to detect the ultrasonic echo signal of each receiving channel, and then a demodulation method with a low-pass filter is used to extract the signal envelope. The time-of-flight (TOF) estimation algorithm is then applied to the signal envelope for range measurement. Due to the variations of position, direction, material, size, and other factors of the detected object and the signal attenuation during the ultrasonic propagation process, the shape of the echo waveform is easily distorted, and TOF estimation is often inaccurate and unstable. In order to improve the accuracy and stability of TOF estimation, a new method of TOF estimation by fitting the general (GN) model and the double exponential (DE) model on the suitable envelope region using Newton-Raphson (NR) optimization with Levenberg-Marquardt (LM) modification (NRLM) is proposed. The final stage is the object localization and tracking. An extended Kalman filter (EKF) is designed, which inherently considers the interference and outlier problems of range measurement, and effectively reduces the interference to target localization under critical measurement conditions. The performance of the proposed system is evaluated by the experimental evaluation of conditions, such as stationary pen localization, stationary finger localization, and moving finger tracking. The experimental results verify the performance of the system and show that the system has a considerable degree of accuracy and stability for object localization and tracking.  
object localization; tracking; time-of-flight (TOF); ultrasonic; ultrasound; range measurement; extended Kalman filter; Newton-Raphson optimization Article
## 3 Energy Harvesting Techniques
### RF Energy Harvesting  
RF energy harvesting captures energy from radio frequency signals, such as those emitted by cellular towers [68; 69; 70], Wi-Fi routers [69; 71; 72], or other RF sources. This  
Figure 4: Kinetic energy harvesting system.  
Figure 3: Thermal energy harvesting system.  
technique uses RF antennas and rectifiers to convert electromagnetic waves into electrical power. The power harvested from RF signals can be expressed as follows:  
\[P=\eta\cdot P_{\text{RF}}\cdot G\cdot\left(\frac{\lambda}{4\pi d}\right)^{2} \tag{4}\]  
where \(P\) is the electrical power output (in watts), \(\eta\) is the conversion efficiency of the rectifier, \(P_{\text{RF}}\) is the transmitted RF power (in watts), \(G\) is the antenna gain (dimensionless), \(\lambda\) is the wavelength of the RF signal (in meters), and \(d\) is the distance between the RF source and the antenna (in meters). The **advantages** of RF energy harvesting are as follows:  
* Non-Intrusive: Can capture energy from existing RF sources without additional infrastructure.
* Can be deployed in various environments with prevalent RF signals. The **limitations** of RF energy harvesting are as follows:
* Low Power Density: RF energy is typically low in power density, making it suitable for low-power applications.
* Distance Dependent: Efficiency decreases with increasing distance from the RF source.  
Figure 5 illustrates an RF energy harvesting system, showing the RF antenna, rectifier circuit, and energy storage component.
## 4 Results and Discussion
### Study on High-Reputation Products and Their Related Ingredient Characteristics  
#### 4.2.1 Distribution of Consumer Sentiments on Five Topics  
To better define consumer perceptions of product reputation, this study first analyzed the distribution of consumer sentiments across five topics: price, taste, ingredient, delivery, and pack. Of the 58,186 reviews collected, 44,176 showed sentiment inclination in at least one of these topics. The largest proportions of sentiment-based reviews concerned ingredients and taste, accounting for 47.4% and 47.3%, respectively--more than double those for delivery (23.2%), pack (16.0%), and price (15.0%) (Figure 5A). Additionally, 23,338 reviews expressed opinions on at least one of the topics of price, pack, and delivery, representing 40.1% of the total. These findings suggest that while users place significant emphasis on ingredient-related factors when expressing satisfaction, non-formula elements also play a notable role in overall consumer satisfaction.  
Consumer sentiment scores for the five topics generally form a relatively symmetrical peaked distribution (Figure 5B-F). The median score for each topic is above zero, indicating that most customers lean positively in their evaluations of breakfast products. However, an overall positive rating does not necessarily mean a product outperforms similar offerings and could even place it below average. Among the five topics, price has the highest median sentiment score (0.39), followed by taste (0.33) and ingredient (0.31), suggesting users are more sensitive in these three areas and thus require higher evaluations to surpass comparable products. The median score for price also highlights the need to decouple non-formula factors. Consequently, in this study, a consumer's evaluation of a topic is deemed \"approved\" only if the sentiment score for that topic exceeds its median value.
## 2 Materials and Methods
### Accuracy Evaluation  
ALS data were employed as the reference benchmark to validate CASAL-derived ground elevation and canopy height estimates. Model performance was quantified using four statistical metrics against ALS reference data, including the coefficient of determination (\(R^{2}\)), \(Bias\), root mean square error (\(RMSE\)), and median absolute deviation (\(MAD\)) (Equations (5)-(8)). Positive Bias values denote systematic overestimation, whereas negative values indicate underestimation relative to ALS measurements. Lower RMSE values, asymptotically approaching zero, correspond to enhanced prediction accuracy. The \(MAD\) provided an outlier-resistant validation of CASAL accuracy [34], complementing the traditional error metric.  
\[R^{2}=1-\frac{\sum_{i=1}^{n}{(x_{i}-y_{i})^{2}}}{\sum_{i=1}^{n}{(x_{i}-\overline {y})^{2}}} \tag{5}\]  
\[Bias=\frac{\sum_{i=1}^{n}{(y_{i}-x_{i})}}{n} \tag{6}\]  
\[RMSE=\sqrt{\frac{\sum_{i=1}^{n}{(x_{i}-y_{i})^{2}}}{n-1}} \tag{7}\]  
\[MAD=1.4826\times median_{j}\big{(}\big{|}\triangle h_{j}-m_{\triangle h}\big{|} \big{)} \tag{8}\]  
where \(x_{i}\) is the ALS parameter metric, \(y_{i}\) is the height metric computed by CASAL, \(n\) is the number of CASAL footprints, \(\hat{y}\) is the average of the ALS parameter metrics, \(\triangle h_{j}\) is the difference between \(x_{i}\) and \(y_{i}\), and \(m_{\triangle h}\) is the median of these differences.
# Improving Convolutional Neural Networks' Accuracy in Noisy Environments Using k-Nearest Neighbors
## 3 Experiments
### Statistical Significance Tests  
The previous section has presented the evaluation results, which serve to analyze the general trend of our proposal. However, in this section, statistical tests are performed for comparing the results objectively [35]. Specifically, Wilcoxon signed-rank tests are used, which allow a pairwise comparison of the methods.  
We did 4 tests, corresponding to the comparison between CNN + softmax and kNN, between CNN + kNN and CNN + softmax, between CNN + \(\ell_{2}\) + kNN and CNN + softmax and between CNN + \(\ell_{2}\) + kNN and CNN + kNN. The first one is done to verify that, even in the cases with greater noise, the selected CNN are good predictors. The second and third tests are those that verify the goodness of the proposal of this work: the use of a kNN algorithm instead of the softmax of the network. Finally, the last test is focused on measuring the statistical improvement when using \(\ell_{2}\) normalization.  
Table 4 reports the results of such tests, with significance established at a \(p\)-value \(<\) 0.05. The symbol \(\checkmark\) states that the test is significantly accepted, whereas \(\checkmark\) states that the test is accepted in the other way. No symbol is depicted otherwise.  
These tests reflect that CNN + softmax significantly outperforms kNN for all noise levels, as may be expected. Furthermore, the statistical test only recommends using CNN + softmax instead of the hybrid model without normalization in one case (label noise level of 40%), yet it never does when normalization is considered. Consequently, adding \(\ell_{2}\) is always statistically beneficial with respect to the original neural codes.
# Provenance and Paleo-Environment of the Late Carboniferous Bauxite Formations in Southern Shanxi
## 1 Introduction
The Jinyu and Jinshi profiles, investigated in this study, are located in the Pinglu bauxite concentration area. The bauxite-bearing strata in the Carboniferous Benzi Formation mainly consist of clastic rocks rich in iron, aluminum, and coal. However, there is ambiguity in the sedimentological markers that indicate the depositional environment and facies, and the \"iron-aluminum-coal\" depositional system has few primary sedimentary structures. Recent research has involved U-Pb dating and Hf isotope analysis of detrital zircons, in addition to trace element analysis of detrital rutile in the Shanxi bauxite [25; 26]. These studies indicate that the igneous rocks from the North Qinling orogenic belt, arc granites along the northern margin of the NCC, and regional metamorphic rocks could be important sources of the metallogenic materials for bauxite [6; 7; 13]. This indicates the complex and diverse origins of metallogenic materials for the Late Carboniferous bauxite in North China. Shanxi Province is a large coal province in China, and the lithium-rich aluminum-bearing rock system is symbiotic/associated with coal-bearing strata (such as Benzi Formation, Taiyuan Formation and Shanxi Formation). The provenance and sedimentary environment of aluminum-bearing rock strata in south Shanxi Province are controversial. Therefore, this paper takes the aluminum-bearing rock strata of Benzi Formation in Pinglu area of southern Shanxi Province as the research object and carries out a series of research work (Figure 1). This study aims to ascertain the mineralogical, petrographic, and geochemical characteristics of aluminum-bearing strata, explore their metallogenic sourcesand paleo-depositional environments, and offer theoretical insights for further clarifying the metallogenic model. This will aid in the development and utilization of bauxite and underlying coal-based aluminum resources in the region.
## 3 Control System Design
### Upper Controller  
#### 3.2.1 Theoretical Basis of High-Order Sliding Mode Control  
The sliding mode algorithm has a low sensitivity to internal and external disturbances in the system, and can be used for the high-precision control of dynamic systems under given constraints. Theoretically, it can realize control switching in an infinite frequency domain [16; 17].  
The biggest flaw of the sliding mode control algorithm is that high-frequency chattering effects may occur near the sliding mode surface. This chattering is characterized by an infinitely small amplitude near the sliding mode surface (in the state space) and near the first-order sliding mode surface. The amplitude is limited [18]. The core idea to solve the chattering problem is to change the dynamic characteristics of the small area of the discontinuous sliding mode surface in order to avoid discontinuities and ensure the main characteristics of the entire system [19].
# Collision Frequency and Energy Transfer Rate in e-He Scattering
## 3 Results and Discussion
### Effective Collision Frequency and Energy Transfer Rate
In our case, the increase in the magnitude of the energy transfer rate is driven solely by the electron temperature itself (see Equation (17)), while the collision frequency decreases, thereby slowing this growth. Figure 7 illustrates the energy transfer between an electron and a helium atom over time for an electron temperature of \(T_{e}=5\) eV and a gas atom temperature of \(T_{He}=5\) eV. At this temperature, the energy transfer remains relatively stable over time, indicating that the collision frequency reaches an optimal value. This results in a consistent energy exchange, which can be beneficial for maintaining equilibrium conditions in plasma. At a higher electron temperature of \(T_{e}=20\) eV, as seen in Figure 8, the energy transfer exhibits a significant difference compared to the lower temperature cases (see Figure 7). This behavior is primarily due to a decrease in the effective collision frequency as the electron energy surpasses the previously observed maximum. While [PERSON] model predicts higher values for the effective collision frequency in this region, our calculations show a decline in collision frequency, indicating less frequent interactions between electrons and helium atoms. As a result, the absolute value of the energy transfer in our results is notably lower than that predicted by [PERSON] model. These results indicate that at higher electron temperatures, the efficiency of energy transfer decreases, which has important implications for plasma behavior in high-temperature environments, such as those found in fusion reactors. Figure 6: Energy transfer rate between an electron and a helium atom at \(T_{He}=5\) eV. [PERSON] data were derived using his formula as referenced in [22] and computed using Equation (17) from this study.
# Sulfate Resistance in Cements Bearing Bottom Ash from Biomass-Fired Electric Power Plants
## Materials and Methods  
### Materials  
The biomass ash (BA) used in this study was sourced from a Spanish electric power plant fired with non-woody + woody (eucalyptus, fruit tree, pine, etc.) biomass. The waste was collected randomly in situ at three representative heights in the airtight containers in which it was stored. At the laboratory the samples were pre-conditioned (dried and ground) and analyzed for their chemical,physical and mineralogical characteristics, as reported in earlier papers [24; 25]. The specific surface was also determined and found to be 6.63 m\({}^{2}\)/g.  
The X-ray fluorescence-determined chemical composition of the BA wafer revealed that it contained \(\sim\)66 wt% CaO + MgO + SiO\({}_{2}\), \(\sim\)13 wt% K\({}_{2}\)O, and \(\sim\)5 wt% Al\({}_{2}\)O\({}_{3}\) + Fe\({}_{2}\)O\({}_{3}\). According to the [PERSON] et al. [26] diagram, these values are indicative of type S, subtype medium acid (MA) biomass. A net 28.2% of the silica content was found to be reactive.  
The X-ray diffraction findings, in turn, showed that this material had an amorphous hump across (2 \(\theta\)) angles 20\({}^{\circ}\) to 35\({}^{\circ}\), attributable in all likelihood to amorphous silica, in addition to reflections characteristic of cristobalite and quartz. Other crystalline phases detected included sylvite (KCl), calcite (CaCO\({}_{3}\)), multhe (Al\({}_{6}\)Si\({}_{2}\)O\({}_{13}\)), hematite (Fe\({}_{2}\)O\({}_{3}\)), and microcline or orthoclase-like (KAlSi\({}_{3}\)O\({}_{8}\)) alkaline feldspars.  
The EN 197-1 [27]-compliant CEM I 42.5 R Portland cement (OPC) used was supplied by a Lafarge Group plant at Villaluenga de la Sagra in the Spanish province of Toledo.
## 4 Conclusions  
This study was focused on the characteristics of EMPs generated from the plasma associated with the laser filament-excited aluminum alloy target in air. We measured the time and frequency domain characteristics of the EMP. It was found that its main characteristic frequency was at 0.19 GHz, and a theoretical explanation for this observation was provided. The intensity of EMPs generated from the plasma associated with the ultrashort laser filament-excited aluminum alloy target in air was tens of times higher than that generated from the plasma associated only with ultrashort laser filaments. Besides, the angular distribution and the effect of detection distance were also measured. The measured power of EMPs did not show the expected decreasing trend with increasing detection distance (15-40 cm), and the EMP signals were mainly emitted toward the 70\({}^{\circ}\) direction. In addition, the effects of laser pulse duration and laser energy on EMPs were also investigated. As the laser pulse duration increased, the intensity of EMPs was found to decrease following a weak linear trend. Moreover, the intensity of EMPs was observed to be positively correlated with the laser energy, with the rate of increase slowing down at approximately 600 mJ. Obviously, more experiments regarding the influence of laser parameters and the type of target material on the temporal characteristics of EMPs are required to fully understand the EMP emission mechanism, especially for EMPs that are generated from the plasma associated with ultrashort laser filament-excited solid material.  
Conceptualization, Y.T.; Formal analysis, R.Q. and C.Z.; Funding acquisition, C.Z., Y.L. and Y.T.; Investigation, R.Q., C.Z., D.Z., X.Y. and J.G.; Methodology, L.S.; Supervision, Y.L., Y.T. and R.L.; Visualization, R.Q. and C.Z.; Writing--original draft, R.Q.; Writing--review & editing, C.Z. and Y.T. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work has received funding from the National Natural Science Foundation of China (grants No. 11922412, 11874372), Young Talents Support Project of China Association for Science and Technology, Shanghai Pilot Program for Basic Research--Chinese Academy of Science, Shanghai Branch. Key Research Program of Frontier Sciences, Chinese Academy of Science and Youth Innovation Promotion Association of Chinese Academy of Sciences.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data that support the findings of this study are available from the corresponding author upon reasonable request.  
**Acknowledgments:** The authors gratefully acknowledge fruitful discussions with [PERSON].  
**Conflicts of Interest:** The authors declare no conflict of interest.
# A Systematic Review of the Trends and Advances in IFC Schema Extensions for BIM Interoperability
## 6 Discussion
### Summary of the Results and Suggestions for Future Work
#### 6.1.1 Main IFC Extension Areas Developed and Extension Approaches Used  
Within the architecture domain, the main focus was on process representations, employing 'entity and property extension' techniques to represent essential concepts and processes for data management and analysis in areas such as structural analysis and module design. While there was some emphasis on product representations, especially in integrating emerging technologies, the primary emphasis remained on processes, given that comprehensive building element definitions were already defined in earlier IFC schema versions.  
In contrast, the infrastructure domain extensively employed 'entity and property extension' methods for both product and process representations. Product-focused efforts sought to define elements absent from the standard schema, while process representations were geared towards concepts crucial for alignment representation and asset management. Interestingly, the following sectoral differences were evident: the bridge sector leaned towards process representation, whereas the tunnel sector prioritized product representation, underlining the distinct structural and component disparities between the two.
## 3 Results and Discussion
### Characterisation of Microstructure  
The microstructure of cross-sections of 7 YSZ TBC coatings deposited on samples I-IV with four different bond coat roughness treatments is presented in Figure 6. Analysing Figure 6a-d, it was observed that with the reduction in the bond coat roughness, the columnar structures of the 7 YSZ top coat become more uniform, and the growth direction is more consistent, perpendicular to the bond coat. Meanwhile, the columnar gaps become smaller, and the linear density of the columns increases. This indicates that the columnar structure is correlated with the roughness of the bond coat surface. This leads to the conclusion that TBCs prepared on smoother bond coats exhibit a more uniform columnar structure. Therefore, the initial treatment of the bond coat roughness is more beneficial for the nucleation and growth of perpendicular, uniform columns.  
Figure 5: Surface profiles of (**a**) sample I as-coated bond coat with Ra of 1.065 \(\upmu\)m; (**b**) sample I top coat with Ra of 1.118 \(\upmu\)m; (**c**) sample VI rough-grinded bond coat with Ra of 0.475 \(\upmu\)m; (**d**) sample VI top coat with Ra of 0.521 \(\upmu\)m; (**e**) sample VII grinded bond coat with Ra of 0.287 \(\upmu\)m; (**f**) sample VII top coat with Ra of 0.437 \(\upmu\)m; (**g**) sample IV polished bond coat with Ra of 0.018 \(\upmu\)m; and (**h**) sample IV top coat with Ra of 0.385 \(\upmu\)m.  
Figure 6: SEM cross-sectional morphologies of the 7 YSZ top coat deposited on (**a**) sample I as-coated bond coat; (**b**) sample II rough-grinded bond coat; (**c**) sample III grinded bond coat; (**d**) sample IV polished bond coat. Figures (**e–h**) show higher-magnification images of the coating microstructure presented in (**a–d**).  
Figure 6e-h illustrate the cross-sectional morphology of the coating at higher magnification. It was observed that the columnar crystals growing on the polished bond coat appear to be denser and that the columnar gaps between the columns are narrower compared to those of the rougher bond coat. The columnar crystals growing on the as-coated bond coat surface exhibit uneven and irregular growth, and the columnar gaps seem to be quite large. There is also a noticeable lack of perpendicularity of the columnar crystals to the substrate. In summary, surface preparation has a significant impact on the microstructure of TBC coatings, and to improve their quality, the bond coat should be polished prior to the deposition of the 7 YSZ top coat in the EB-PVD process.
# Face Recognition Using Popular Deep Net Architectures: A Brief Comparative Study
## 2 Materials and Methods
### CNN Variants Used  
While there are easily dozens, if not hundreds, of image classification variations explored in the literature [17; 22], the specific CNN variants in our proposed study have shown themselves to be particularly adept at the task of pattern recognition, especially in the realm of image classification [23; 24]. The variants that are used in our study consist of eight Deep Nets: AlexNet, Xception, and then two versions each of the following: Inception, ResNet, and VGG. A comparison of each of these different CNN variants can be found in the following pages (Table 1), and a brief description of each of these CNN models can be found in Section 3.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**CNN Model** & **Established** & **Total Layers** & **Conv Layers** & **Trainable Params** & **Unique Feature** \\ \hline AlexNet & 2012 & 8 & 5 & 62,378,344 & ReLU activation \\ \hline Xception & 2016 & 71 & 36 & 22,855,952 & Depth-Seperable Convs \\ \hline Inception v2 & 2014 & 48 & 22 & 55,813,192 & Wider-Parellel Kernels \\ \hline Inception v3 & 2014 & 48 & 22 & 23,817,352 & Wider-Parellel Kernels \\ \hline ResNet50 & 2015 & 50 & 48 & 25,583,592 & Simpler Mapping \\ \hline ResNet101 & 2015 & 101 & 99 & 44,601,832 & Simpler Mapping \\ \hline VGG16 & 2014 & 16 & 13 & 138,357,544 & Fixed-size Kernels \\ \hline VGG19 & 2014 & 19 & 16 & 143,667,240 & Fixed-size Kernels \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of different CNN Models used in our study.