esa-sceva/satcom-chunk-collection huggingface dataset:
# An Overview of Indoor Positioning and Mapping Technology Standards
## 4 Our Research on IPMN Standards
### Seamless Cooperative Positioning Service Interface  
Based on the integrated hybrid indoor positioning system architecture (see Figure 3), the standard for indoor and outdoor multi-mode cooperative positioning service interface [103] can be used in some scenarios that applications need to get the device locations  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Code** & **Name** & **Symbol** \\ \hline A.2.5 & parking & \\ A.4.1.3 & ATM & \\ \hline \hline \end{tabular}
\end{table}
Table 1: _Cont._  
Figure 10: Multi-source fusion positioning data interface (From GB/T 38630-2020, [101]).  
from the data server. This standard specifies the basic service elements and service interfaces for seamless collaborative positioning, and designed according to the OGC Web Services Common Standard [104] and specifies five operations as in Figure 11.  
For a localization system or service, the service should retrieve adequate information for applications, including the service provider, coordinate reference system, quality information, positioning technology type, and potential service exceptions. The service metadata is also specified in this standard, as detailed in Figure 12.  
Similarly, applications can get indoor maps or entities through the OGC WMS [105] or WFS [106] standards.
## 5 Discussion
### Land Subsidence in the Wet and Dry Seasons
(**b**) Groundwater level changes at the three selected groundwater wells (see Figure 2, squares). It is believed that more groundwater extraction in the dry season caused a greater contribution of land subsidence in the five townships. The dry season contributed between 60% and 74% of the total subsidence (except Mailiao Township). The dry season contribution tended to increase with subsidence. For example, in Tuku, the cumulative subsidence was 49.67 mm in the dry season with a 73.75% contribution, compared to the cumulative subsidence of 28.07 mm in Baozhong that contributed 60.77% to the total subsidence. The percentages in Table 2 are consistent with a general impression that rainfall can slow down land subsidence due to increased surface water use and less groundwater extraction. One exception is Mailiao Township, where land subsidence in the wet season was larger than that in the dry season. Mailiao Township is a land reclamation area and it houses a large industrial zone. More data are needed to explain the different cumulative subsidence pattern in Mailiao. Except Mailiao Township, Yunlin consists of largely agricultural and aquacultural areas. This study showed that InSAR can detect short-term (monthly) variation of land subsidence, which also showed that different industries in Yunlin use groundwater in different ways. We recommend InSAR be used to monitor land subsidence in areas with different industries. Such InSAR results can be used along with monthly measurements from MLCWs [4] to understand the mechanism of land subsidence. This joint use of remote sensing and subsurface data can help to initiate effective rules to govern the use of groundwater and surface water to mitigate land subsidence.
# Fog Computing Enabling Industrial Internet of Things: State-of-the-Art and Research Challenges
## 2 Evolution and Enablers of Industrial Internet of Things
### Industry 4.0-Concept  
Increasing progress is witnessed in automation of industry using advancement in digitization, networking and new communication technologies, satisfying the market and consumer requirements [29]. Lenze SE, Corporate Communications Public Relations use idea of _machine modularization_. According to the demand of market/consumers, different modules are added or removed during the manufacturing process; machines are retooled smartly using smart communication technologies A cloud solution was given by Lenze, which is secure as no customer wants to share their demands and production details. Details about the customer's machine are saved in a cloud and he can investigate all the system details especially faults. This cloud solution is vulnerable to hackers, Lenze, along with another company, have provided a secure solution that is acceptable for today's industry [30].  
[PERSON] explained the idea of industry 4.0 using four terms, these are smart devices and smart production processes with horizontally and vertically integrated manufacturing systems. Smart devices result in the production of intelligent products, these products do self-monitoring, self-controlling and self-manufacturing, have a uniquely identifiable ID, know how to solve and achieve goals [31]. The intelligent production process comprises smart starting and ending of manufacturing processes. Vertical and horizontal integration means all the steps during the smart/intelligent production process are integrated throughout the life cycle i.e., from starting phase to ending phase [30].  
Industry 4.0 results in a faster manufacturing process, product development and improves the handling of complex environments inside an industry. The term first originated in Germany named as _Industrie 4.0;_ in United States term used for this fourth generation is _Smart Manufacturing_, Chinese researchers have used term _China 2020. Industrial Digitisation_ is the term used in Sweden for transformation of industry to automation [32]. It is believed that this industrial revolution will increase global competitiveness, preserve the domestic manufacturing industry and will have a huge impact on the business market as well. Now many countries around the globe have taken initiatives for automation in industries.
# Assimilation of Earth Observation Data Over Cropland and Grassland Sites into a Simple GPP Model
## 3 Methods
### Validation  
Simulated and observed daily GPP are temporally aggregated to 8-day MODIS temporal resolution. GPP data from 28 crop and 25 grassland EC sites are used in the validation. Simulation performances are assessed analyzing the simulated vs. observed GPP scatter plots in terms of: coefficient of determination (R\({}^{2}\)), root mean square error (RMSE), and mean bias error (MBE), slope and offset the ordinary-least-squared (OLS) regression model. All these metrics inform about the predictive power of the model as the GPP data were not used for model calibration. Finally, results were compared to those obtained with MODIS GPP product MOD17 that was used as benchmark model. Model performances in space (across sites) and time were further assessed by analyzing (1) the correlation between site averages of annual cumulative GPP observed and modeled, and (2) the ability of the models to track site-level inter-annual variability of GPP. The annual cumulative GPP value is computed summing GPP data over the calendar year (i.e., from 1 st of January to 31 st December).
# A Robust Hybrid Iterative Linear Detector for Massive MIMO Uplink Systems
###### Abstract  
Fifth-generation (5G) communications system is commercially introduced by several mobile operators where sub-6 GHz bands are the backbone of the 5G networks. A large-scale multiple-input multiple-output (MIMO), or massive MIMO (mMIMO), technology has a major impact to secure high data rate, high spectral efficiency, and quality of service (QoS). It could also have a major role in the beyond-5G systems. A massive number of antennas seek advanced signal processing to detect and equalize the signal. However, optimal detectors, such as the maximum likelihood (ML) and maximum posterior (MAP), are not desirable in implementation due to extremely high complexity. Therefore, sub-optimum solutions have been introduced to obtain and guarantee enough balance between the performance and the computational complexity. In this paper, a robust and joint low complexity detection algorithm is proposed based on the Jacobi (JA) and Gauss-Seidel (GS) methods. In such iterative methods, the performance, complexity, and convergence rate are highly dependent on the initial vector. In this paper, initial solution is proposed by exploiting the benefits of a stair matrix to obtain a fast convergence rate, high performance, and low complexity. Numerical results show that proposed algorithm achieves high accuracy and relieve the computational complexity even when the BS-to-user-antenna ratio (BUAR) is small.  
5G; Massive MIMO; iterative methods; stair matrix; Neumann series; successive overrelaxation; Gauss-Seidel; Jacobi +
Footnote †: journal:  
Article
## 4 Linear Regression Algorithm against Device Diversity Problem
### Pre-Processing of RSS Values  
In the typical WLAN localization scenario, the RSS values collected by the mobile device are subject to multiple sources of noise, such as multi-path fading and shadowing. To mitigate these RSS fluctuations, a large number of RSS measurements are collected from each AP at every location. Let \(\mathbf{RSS}_{li}=\{rss_{1},rss_{2},\ldots,rss_{p}\}\) be the set of RSS values collected at location \(l\) from the \(i\)-th AP. As shown in Figure 4, if we cannot receive any power from the AP, a value of \(-110\) dBm is used to denote the missing RSS value.  
\[rss_{li}=\left\{\begin{array}{ll}rss_{li},&\text{if }rss_{li}>-110\text{ dBm}\\ -110\text{ dBm},&\text{otherwise}\end{array}\right. \tag{7}\]  
In order to obtain the high localization accuracy, the first step in localization system is to stabilize the collected RSS values prior to the localization process. Aiming to overcome the fluctuations, the average of the collected RSS values is calculated. In the calculation of the average value, the filled RSS values of \(-110\) dBm could produce meaningless RSS values and will have a adverse impact. These filled RSS values could affect the localization process and produce erroneous location estimations. As a  
Figure 4: Linear correlation between RSS values for different devices.  
result, the average is calculated using the collected RSS values exclude the filled RSS values as the following equation:  
\[r_{li}=\frac{\sum\limits_{j=1}^{p}rss_{j}\mathbf{I}(rss_{j}\
eq-110\;\text{dBm}) }{\sum\limits_{j=1}^{p}\mathbf{I}(rss_{j}\
eq-110\;\text{dBm})} \tag{8}\]  
where \(\mathbf{I}(\bullet)\) is an indicator function.  
The average value \(r_{li}\) is used to build the radio map in offline training phase and estimate the current location in online localization phase.
## 3 Results and Discussion
### Influence of the Temperature  
The optimization of the process temperature is of great importance in enzymatic reactions. Concretely, in large-scale solvent-free systems, three main aspects must be considered when increasing temperature [37; 38]:It may cause enzyme denaturation;  
If not, it usually involves an improvement in reaction rate and a lower reaction media viscosity;  
Even if a biocatalyst's activity is incremented by temperature, the process energy consumption may not be cost-effective.  
The influence of the temperature in the synthesis of NPGDL with 7.5% (\(w\)/\(w\)) of Novozym(r) 40086 and 3.75% (\(w\)/\(w\)) of Novozym(r) 435 is represented in Figures 4a and 4b, respectively.  
According to the manufacturer, the optimum temperature range for working with Novozym(r) 40086 is from 30 to 50 \({}^{\circ}\)C [39] but considering the author's previous experience, temperatures from 50 to 80 \({}^{\circ}\)C were tried. As can be seen in Figure 4a, decreasing the temperature from 70 \({}^{\circ}\)C to 60 \({}^{\circ}\)C led to higher yields in shorter reaction times, and after 6 h the conversion was \(\sim\)80%, about 20 units more than the one obtained at 70 \({}^{\circ}\)C (although values \(\geq\) 90% where reached in both systems after 24 h). The negative effect of raising temperatures above 60 \({}^{\circ}\)C is confirmed when operating at 80 \({}^{\circ}\)C, as the reaction rate is dramatically reduced, and by the end of the assay, only a 46.1% of conversion was attained. On the other side, when the temperature is lowered to 50 \({}^{\circ}\)C, the reaction rate is not only slower than at 60 \({}^{\circ}\)C but also than at 70 \({}^{\circ}\)C, which suggests that the viscosity of the reaction medium should have been increased and so, mass transfer limitations should have been enhanced.  
On what concerns Novozym(r) 435, from Figure 4b it can be concluded that increasing the temperature has a positive impact on esterification. In fact, Novozymes affirms that this commercial lipase may work from 20 to 110 \({}^{\circ}\)C and different studies confirm its effectiveness at high temperatures, whether working with organic medium or in solvent-free systems [39; 40; 41]. This effect is less pronounced for the highest temperatures tested: for example, after 3 h of reaction, conversion is 1.8 times higher at 70 \({}^{\circ}\)C than at 60 \({}^{\circ}\)C but it is only increased by 1.3- and 1.1-fold when raising temperatures to 80 and 90 \({}^{\circ}\)C, respectively. Considering that conversion of \(\sim\)90% is attained in 6.5 h at 70 \({}^{\circ}\)C, but two hours before if the temperature is increased by 10 \({}^{\circ}\)C, 80 \({}^{\circ}\)C was selected as the optimum for operating with Novozym(r) 435.
# APT Detection via Hypergraph Attention Network with Community-Based Behavioral Mining
## 3 Preliminary
### Threat Model  
The threat model adopted in this paper is consistent with existing provenance graph-based APT detection research [1, 17, 18]. First, we assume the OS kernel and audit module maintain data integrity, ensuring provenance data provides a trustworthy foundation for analysis. Second, while attackers may use various strategies to execute APT attacks, their malicious activities are assumed to generate observable traces in audit logs.  
We further assume kernel-level APT behaviors exhibit statistical regularities and semantic correlations amenable to quantitative and semantic modeling. Specifically, as Figure 1 shows, entity interaction patterns in APTs, such as multi-level associations among processes, files, and network entities--reveal latent behavioral dependencies through semantic analysis. These dependencies are aggregated into behavioral units encoding high-order attack semantics, a premise validated by prior works, including T-Trace [9] and Hercule [8].
# High Performance Receiver Design for RX Carrier Aggregation
## 4 Conclusions  
The circuit was designed and simulated with TSMC 65 nm CMOS technology. Simulated performance of several LNA topologies within the context of a single-\(g_{m}\) receiver front-end was investigated and compared with a conventional SISO receiver. The single-\(g_{m}\) receiver architecture defers the voltage amplification to the TIA stage after the signal goes through the low-pass filtering operation. This property gives better linearity, especially for out-of-band blockers and jammers. Generic receiver architectures with CA support are introduced, and the proposed architectures support various CA scenarios in both inter-band and intra-band CA. Table 4 summarizes the performance metric for different LNTAs that are discussed in this article. Cascade shut-off topology shows promising results with the support of SIMO (CA) receiver. Simulation results exhibit \(<\)0.5 dB noise penalty in CA operation. Linearity performance (\(1 IP_{3}\)) is comparable to the legacy operation.  
**Acknowledgments:** This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MSIP) (No. 2016 RIC1B1012042).  
**Author Contributions:** [PERSON] is the the main author and was responsible for writing the paper. [PERSON] and [PERSON] contributed to the theoretical analysis and the design of the circuit. [PERSON] helped to review the proposed circuits and edit the paper. [PERSON] was responsible for revising and supervising the paper.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Gain (dB)** & **NF (dB)** & \(1 IP_{3}\) (dBm)** & \(I_{d}\) (mA) \\ \hline Reference (SISO) & 56.6 & 1.33 & \(-6.2\) & 7.4 \\ Three-Coil Balun, CA & 51.6 & 3.20 & \(-3.4\) & 7.6 \\ Two-Stage, CA & 57.5 & 1.5 & \(-16\) & 9.6 \\ Split-Cascode, CA (\(1\times I_{d}\)) & 51.9 & 2.55 & \(-4.8\) & 7.8 \\ Split-Cascode, CA (optimized) & 54.2 & 2.09 & \(-4.2\) & 19.8 \\ Cascade Shut-off, CA (\(2\times I_{d}\)) & 55.1 & 1.96 & \(-7.5\) & 16.4 \\ Cascade Shut-off, CA (optimized) & 57.1 & 1.76 & \(-6.7\) & 21.3 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Performance comparison with different LNTA architecture.  
Figure 9: Cascade shut-off LNTA.  
**Conflicts of Interest:** The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analysis, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.
# Calculation of Nonlimit Active Earth Pressure against Rigid Retaining Wall Rotating about Base
## 6 Parameter Sensitivity Analysis
### Friction Angle Effective Values at Different Angles of Rotation  
It can be inferred from Figure 8 that as the altitude of soil mass increased, the effective value of the friction angle increased and it exhibited a nonlinear relationship with depth. Until that soil reached its active limit, the friction angle was fully developed and its magnitude was a constant. As the angle of rotation increased, the height at which the friction angle reached a constant value decreased. The height at which the soil friction angle reached a constant value decreased by approximately 1/2H as the angle of rotation increased from 5 \(\times\) 10\({}^{-4}\) rad to 10 \(\times\) 10\({}^{-4}\) rad, the height at which the soil friction angle reached a constant value decreased by approximately 1/4H as the angle increased from 10 \(\times\) 10\({}^{-4}\) rad to 15 \(\times\) 10\({}^{-4}\) rad, and the height at which the soil friction angle reached a constant value decreased by approximately 1/8H as the angle increased from 15 \(\times\) 10\({}^{-4}\) rad to 20 \(\times\) 10\({}^{-4}\) rad. Evidently, the larger the angle of rotation, the sooner the soil friction angle reached a constant value.  
Figure 7: Combined earth pressure forces with varying rotation angles.
## 4 EDI Drive-by-Wire Car Demonstrator
### Safety Controller  
During the PRYSTINE project, this idea has been put to the test in the implemented prototype. The high-level perception system was based on the NVIDIA Drive PX2 platform, while Infineon's Aurix Lockstep processor carries out the functionality of the safety controller. Even though NVIDIA Drive PX2 supervises the system and has its own onboard safety features, the Auric controller has been used to monitor the state of the RADAR and LIDAR sensors and perform obstacle detection and crash prevention, i.e., perform ADAS.  
A simplified controller system architecture is shown in Figure 6, which gives a general overview of the interactions between the safety and the high-performance controllers and sensors. To respond to the obstacles detected by the RADAR, Auric uses Continental ARS408-21 RADAR's built-in functionality. This functionality enables a setup of certain collision regions, where if an object is detected, it generates an emergency message sent over the CAN bus.  
Figure 5: EDI perception system demonstrator. (**a**) EDI DbW car; (**b**) high-performance (NVIDIA PX2) and safety (Aurix TC3 xx) controllers; (**c**) SEKONIX SD3323 camera mounting; (**d**) emergency button for exiting automatic mode; (**e**) EDI V2X system.  
The other functionality of the safety controller is to process the data from the LIDAR sensor. In this particular case, the LIDAR perceives the environment by spinning 360\({}^{\circ}\) horizontally and firing 32 lasers simultaneously with a vertical angle ranging from \(-\)30.67\({}^{\circ}\) to 10.67\({}^{\circ}\). Each point \(\vec{p}_{s}=(d,v,h)\) from each laser is expressed in spherical coordinate system, where \(d\) is measured distance to an object, \(v\) and \(h\) are vertical and horizontal angles, respectively. Points are further broadcasted over the Ethernet using the UDP protocol, permitting multiple receivers. Safety controller first filters out received points \(\vec{p}_{s}\) outside of the region of interest by horizontal angle to reduce computational cost.  
Furthermore, in order for collision detection to ignore small objects, we filter them out. Computing the size of an object from one viewpoint is challenging, as only part of an object can be seen. We perform filtering by first dividing space into 25 \(\times\) 25 \(\times\) 25 regions or boxes and grouping points into each box. For every box, we compute variance along the axis and diagonals to measure the spread of points. If the points are spread out in any direction, we consider the object too large.  
Finally, for obstacle detection, we compute the intersection of each leftover point with an axis-aligned collision region defined by two points \(p_{min}^{-}=(x_{min},y_{min},z_{min})\) and \(p_{max}^{-}=(x_{max},y_{max},z_{max})\) in a vehicle-coordinate system. The collision region could be calculated once or recalculated on the fly depending on the environment circumstances or using other metrics such as speed. An example of testing the approach in pedestrian crossing use-case is shown in Figure 7.
# Ecological Suitability Evaluation for Conservation and Development in Bac Kan Province, Vietnam
## 3 Results
### Ecological Structural Resistance Assessment  
The final weights of four indicators for ecological structural resistance assessment include elevation, slope, geological hazard frequency, and distance to fracture zones (Figure 5) are 0.562, 0.227, 0.138, and 0.073, respectively (Table 11). The AHP provides an inconsistency value of 0.029, which is less than 0.10. This value indicates that no correction of judgments from experts is needed as suggested by [65]. In addition, the elevation is determined as the most important indicator of the ecological structural resistance, followed by slope and geological hazard frequency, whereas the distance to fracture zones is considered to be the least important indicator.  
The classification of ecological structural resistance for construction and development is displayed in Figure 6 and Table 12. The high ecological structural resistance indicates areas that are unsuitable for construction and development. As a result, the spatial pattern of ecological structural resistance for construction and development is considerably dominated by low and moderate classes that cover an area of about 2524 km\({}^{2}\) or 51.95% of the total area. In addition, the spatial pattern of the ecological structural resistance is considerably similar to elevation since it is affected by its weight under the SAW operation.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Indicators** & **Elevation** & **Slope** & **Geological Hazard Frequency** & **Distance to Fracture Zones** & **Weight** \\ \hline Elevation & 1 & 3.2 & 4.4 & 5.5 & 0.562 \\ Slope & 1 & 2 & 3.4 & 0.227 \\ Geological hazard & & 1 & 2.5 & 0.138 \\ frequency & & & 1 & 0.073 \\ Distance to fracture zones & & & & \\ \hline \end{tabular}
\end{table}
Table 11: Comparison matrix and weight for four indicators.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Resistance Class** & **Description** & **Resistance Value** & **Area (km\({}^{2}\))** & **Area (\%)** \\ \hline
1 & Very low & 1–1.817 & 898.219 & 18.49 \\
2 & Low & 1.817–2.363 & 1254.639 & 25.82 \\
3 & Moderate & 2.363–2.908 & 1269.600 & 26.13 \\
4 & High & 2.908–3.483 & 962.158 & 19.80 \\
5 & Very high & 3.483–4.861 & 473.998 & 9.76 \\ \hline \end{tabular}
\end{table}
Table 12: Area and percentage of ecological structural resistance for construction and development.  
Figure 5: Spatial distribution of ecological elements for ecological structural resistance assessment: (**a**) elevation, (**b**) slope, (**c**) geological hazard frequency, and (**d**) distance to fracture zones.