esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experiment
### Experiments in Indoor Real-World Scenarios
The algorithm estimated the pose of each test sample, and the relocalization accuracy and robustness were assessed using the same evaluation metrics as ORB-SLAM3, namely Absolute Trajectory Error (ATE) and Relative Pose Error (RPE). In Figure 13, the dashed line represents the ground-truth trajectory of the test set, while the solid line denotes the trajectory estimated by the proposed method. Figure 12: Comparison between test trajectory and map trajectory. Figure 13: Relocalization trajectory in different scenes. To quantitatively assess the localization accuracy and robustness of the proposed algorithm, Absolute Trajectory Error (ATE) and Relative Pose Error (RPE) are employed as evaluation metrics. By comparing the ground-truth trajectory of the test set with the trajectory estimated by the algorithm, the quantitative results presented in Table 6 are obtained. The results indicate that the algorithm achieves high localization accuracy in indoor environments, with both the mean and root mean square errors of RPE and ATE remaining low. This demonstrates that the proposed method is capable of performing accurate relocalization even under complex indoor conditions.
# Interpretability Study of Gradient Information in Individual Travel Prediction
## 4 Experiment
### Feature Impact Analysis
#### 4.4.2 Comparison of Multi-Feature Masking Policies
The distribution range of JS divergence values under this strategy is relatively large, possibly because the proportion of important features and non-important features masked under the random strategy is different. This shows that when features are randomly selected for masking, the model can adjust other unmasked features to maintain a certain level of prediction performance, indicating that the model has a certain degree of robustness. In summary, we can draw the following conclusions: In individual travel prediction models, there is a significant difference in the contribution of features to model predictions. Features with larger gradient values have a more noticeable impact on model prediction performance, but this impact is not a simple linear relationship. The feature with the maximum gradient value has the greatest impact on model performance, causing a decline of about 30%; apart from the feature at the maximum gradient position, the impact of other features on model performance shows an upward and downward fluctuation and gradually decreases. This fluctuation may reflect the interactions between features and their complex impact on model predictions. A single feature cannot be a strong factor affecting the model, but specific feature combinations, especially those with larger gradient values, can have a significant impact on the model with a small feature masking subset. Additionally, the experimental results show that in the ascending order arrangement, the smallest feature masking subset (about 25% of the features) has a very limited impact on model predictions, with a decline in prediction accuracy of less than 20%. The subway travel prediction model has a certain degree of robustness and can resist the impact of feature loss to a certain extent; features with smaller gradient values have a relatively low contribution to the model. This means that when conducting feature selection or model optimization, it is possible to consider reducing the dependence on these features, thereby simplifying the model and improving efficiency.
# Extended Geometry and Probability Model for GNSS+ Constellation Performance Evaluation
###### Abstract  
We proposed an extended geometry and probability model (EGAPM) to analyze the performance of various kinds of (Global Navigation Satellite System) GNSS+ constellation design scenarios in terms of satellite visibility and dilution of precision (DOP) et al. on global and regional scales. Different from conventional methods, requiring real or simulated satellite ephemerides, this new model only uses some basic parameters of one satellite constellation. Verified by the reference values derived from precise satellite ephemerides, the accuracy of visible satellite visibility estimation using EGAPM gets an accuracy better than 0.11 on average. Applying the EGAPM to evaluate the geometry distribution quality of the hybrid GNSS+ constellation, where highly eccentric orbits (HEO), quasi-zenith orbit (QZO), inclined geosynchronous orbit (IGSO), geostationary earth orbit (GEO), medium earth orbit (MEO), and also low earth orbit (LEO) satellites included, we analyze the overall performance quantities of different constellation configurations. Results show that QZO satellites perform slightly better in the Northern Hemisphere than IGSO satellites. HEO satellites can significantly improve constellation geometry distribution quality in the high latitude regions. With 5 HEO satellites included in the third-generation BeiDou navigation satellite system (BDS-3), the average VDOP (vertical DOP) of the 30\({}^{\circ}\) N-90\({}^{\circ}\) N region can be decreased by 16.65%, meanwhile satellite visibility can be increased by 38.76%. What is more, the inclusion of the polar LEO constellation can significantly improve GNSS service performance. When including with 288 LEO satellites, the overall DOPs (GDOP (geometric DOP), HDOP (horizontal DOP), PDOP (position DOP), TDOP (time DOP), and VDOP) are decreased by about 40%, and the satellite visibility can be increased by 183.99% relative to the Global Positioning System (GPS) constellation.  
GNSS+ constellations; highly eccentric orbit; low earth orbit; quasi-zenith orbit; dilution of precision; geometry and probability model +
Footnote †: journal: Remote Sensing, 2020, 12, 2560
# An Efficient Framework for Securing the Smart City Communication Networks
## 4 Simulation Network and Setup
### Simulation Evaluation
After 20 mins, the amount of traffic received in packets per second rapidly decreased until it reached only 2 packets per second. The control center, on the other hand, has received traffic from 20 smart meters, but according to the smart grid communication system's design, the smart meter can only accept traffic from the control center server. Because it deals with twenty smart meters, the control center has received significantly more traffic packets per second in both scenarios, especially in the scenario with authentication and session key exchange schemes, which required a secure two-way communication channel from each smart meter to the control center. In this situation, the control center receives many more packets per second than in the other scenario, which does not use authentication or key exchange systems.
###### Abstract  
To improve the efficiency and accuracy of microseismic event extraction from time-series data and enhance the detection of anomalous events, this paper proposes a Multi-scale Fusion Convolution and Dilated Convolution Autoencoder (MDCAE) combined with a Constraint Shape-Based Distance algorithm incorporating volatility (CSBD-Vol). MDCAE extracts low-dimensional features from waveform signals through multi-scale fusion and dilated convolutions while introducing the concept of waveform volatility (Vol) to capture variations in microseismic waveforms. An improved Shape-Based Distance (SBD) algorithm is then employed to measure the similarity of these features. Experimental results on a microseismic dataset from the 802 working faces of a mining site demonstrate that the CSBD-Vol algorithm significantly outperforms SBD, Shape-Based Distance with volatility (SBD-Vol), and Constraint Shape-Based Distance (CSBD) in classification accuracy, verifying the effectiveness of constrained time windows and volatility in enhancing performance. The proposed clustering algorithm reduces time complexity from \(O(n^{2})\) to \(O(n\log n)\), achieving substantial improvements in computational efficiency. Furthermore, the MDCAE-CSBD-Vol approach achieves 87% accuracy in microseismic time-series waveform classification. These findings highlight that MDCAE-CSBD-Vol offers a novel, precise, and efficient solution for detecting anomalous events in microseismic systems, providing valuable support for accurate and high-efficiency monitoring in mining and related applications.  
microseismic event time series; multi-scale fusion convolution; feature extraction; volatility; shape similarity algorithm; unsupervised clustering
## 3 Analytical Model of the HIL Equipment  
### The Mechanical Impedance of the Subject and the Operator  
The physical model of the HIL equipment is depicted in Figure 4. The interaction with the operator who handles the device is taken into account by a viscoelastic impedance (\(k_{1}\) and \(\beta_{1}\)) connecting the AP to the fixed frame. The human subject can be also assumed as a second mechanical impedance (\(M_{2}\), \(k_{2}\) and \(\beta_{2}\)), thus emulating only the passive response of the human body. The mechanical characteristics of the end striker, combined with the properties of tissues in the contact area, are represented by constants \(k_{3}\) and \(\beta_{3}\), which have been defined with a Kelvin-Voigt model. \(M_{1}\) and \(m\) are, respectively, the masses of perturbator's body and of piston + rod. \(G_{1}\) and \(G_{2}\) are the air flow rates entering the cylinder's chambers, regulated by three-ways flow proportional valves \(V_{1}\) and \(V_{2}\). All parameters used in the HIL equipment model are listed in the nomenclature of Table 2.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Symbol** & **Description** & **Unit** \\ \hline \(d_{\rm s}\) & Diameter of the piston rod & mm \\ \(d_{\rm c}\) & Diameter of the cylinder & mm \\ \(m\) & Mass of the piston and rod & kg \\ \(M_{1}\) & Mass of the cylinder body & kg \\ \(M_{2}\) & Mass of the subject & kg \\ \(x_{0}\) & Half of the stroke of the rod & mm \\ \(x_{\rm m}\) & Dead band of the chamber & mm \\ \(P_{\rm i}\) & Initial pressure in the chamber & bar \\ \(T_{1}\) & Initial temperature in the chamber & K \\ \(n\) & Polytropic coefficient of air & \\ \(\gamma\) & Viscous coefficient of air & N-s/m \\ \(P_{\rm s}\) & Supply pressure & bar \\ \(F_{\rm fr}\) & Friction force on the piston rod & N \\ \(C_{\rm max}\) & Max conductance of the valve & L/(s-bar) \\ \(V_{\rm max}\) & Max command voltage of the valve & V \\ \(K_{\rm v}\) & Static flow gain of the valve & L/(s-bar-V) \\ \(\tau\) & Valve response time & ms \\ \(k_{1}\) & Elastic constant of the operator & N/m \\ \(\beta_{1}\) & Damping coefficient of the operator & N-s/m \\ \(k_{2}\) & Elastic constant of the subject & N/m \\ \(\beta_{2}\) & Damping coefficient of the subject & N-s/m \\ \(k_{3}\) & Elastic constant of the buffer & N/m \\ \(\beta_{3}\) & Damping coefficient of the buffer & N-s/m \\ \hline \hline \end{tabular}
\end{table}
Table 2: Nomenclature of parameters of HIL equipment model.  
Figure 4: Sketch of the HIL equipment model.
# Mechanical Properties of Concrete with Bamboo Chips
## 3 Experimental Results and Discussion
### Compressive Properties
#### 3.2.1 Compressive Strength  
The compressive strength of the bamboo-free plain concrete specimen was 18 and 31 MPa at 7 and 28 days, respectively. As BCC increased, the strength and stiffness decreased, regardless of the bamboo-chip type. Figure 4 shows the compressive strength of 7-day- and 28-day-cured concrete with bamboo chips.  
At 28 days, the strength of the concretewith 30% of dried bamboo chip was about 10% of that of plain concrete. The chip became swollen after absorbing some water for hydration. This resulted in micro cracks and weak bonds between the mortar and the aggregates, leading to low strength when dried bamboo was used for the natural coarse aggregate. Figure 5 shows the cutting plane of the specimen with different bamboo chips. During cutting, some of the dried and coated bamboo chips were removed, owing to the weakness of the interface. In contrast, the natural aggregates (NA in Figure 5) and wetted bamboo chips (BA in Figure 5) were characterized by a relatively strong cemented interface between the aggregate and the mortar.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**TEST ID** & **Compressive Strength (MPa)** & **Strain at Peak Stress (\%)** & **Elastic Modulus (\(\times\)10\({}^{4}\) MPa)** & **Compressive** & **Splitting Tensile** \\ \hline NB-7 & 18.00 & 0.22 & 1.87 & 0.26 & 1.89 \\ DB10-7 & 9.40 & 0.30 & 0.55 & 0.34 & 1.15 \\ DB20-7 & 4.28 & 0.33 & 0.38 & 0.68 & 0.82 \\ DB30-7 & 2.37 & 0.35 & 0.20 & 0.59 & 0.37 \\ CB10-7 & 9.84 & 0.28 & 1.26 & 0.45 & 1.39 \\ CB20-7 & 7.94 & 0.35 & 0.81 & 0.51 & 1.11 \\ CB30-7 & 7.33 & 0.33 & 0.29 & 0.44 & 0.74 \\ WB10-7 & 12.52 & 0.27 & 1.48 & 0.73 & 1.63 \\ WB20-7 & 11.26 & 0.30 & 0.97 & 0.71 & 1.52 \\ WB30-7 & 9.51 & 0.29 & 0.78 & 0.58 & 1.35 \\ NB-28 & 30.77 & 0.22 & 2.20 & 0.17 & 2.38 \\ DB10-28 & 13.55 & 0.20 & 1.35 & 0.30 & 1.59 \\ DB20-28 & 5.76 & 0.27 & 0.50 & 0.66 & 0.83 \\ DB30-28 & 3.13 & 0.35 & 0.32 & 0.65 & 0.38 \\ CB10-28 & 15.01 & 0.26 & 1.63 & 0.61 & 1.74 \\ CB20-28 & 14.15 & 0.25 & 0.98 & 0.61 & 1.13 \\ CB30-28 & 8.99 & 0.20 & 0.51 & 0.63 & 0.84 \\ WB10-28 & 23.73 & 0.25 & 1.89 & 0.50 & 2.21 \\ WB20-28 & 19.04 & 0.28 & 1.22 & 0.55 & 1.79 \\ WB30-28 & 17.75 & 0.23 & 1.03 & 0.57 & 1.61 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Experimental results.  
Figure 4: Comparison of the compressive strength.  
As expected, the compressive strength of concrete with and without bamboo chip increased with increasing curing age. The strength of plain concrete was increased by71% when the curing age increased from 7 to 28 days. The compressive strength of the concrete with 10%, 20%, and 30% of the dried (coated and wetted) bamboo chip increased by 44% (53% and 90%), 35% (78% and 69%), and 32% (23% and 87%), respectively, when the curing age increased from 7 to 28 days. The greatest increase in strength occurred for the concrete with wetted chips. Moreover, the rate of increase induced by curing decreased with increasing BCC, and for a BCC of 30%, the treatment of the bamboo influenced the overall strength.
## 2 Materials and Methods
### Data and Preprocessing
#### 2.1.3 Data Filtering  
All the daily data were preprocessed to remove invalid records before the analyses. The procedure can be summarized as follows: First, the data before 2000 were excluded due to the unavailability of remote sensing data. Second, only the daily data with GPP aggregated from at least 50% of valid hourly samples within one day were used. Third, only the data periods with NDVI larger than 0.2 were selected to avoid the impact of non-growth season data [35].
## 1 Introduction
The proposed CIMS scheme resolves the problem of condensing the document indexes and performing secure data search at the same time. The contributions of the paper can be summarized in three folds. * The sizes of document indexes are significantly reduced, with only a commensurate loss on search precision. * A searchable encryption scheme which enables multi-keyword search is seamlessly integrated with the condensed document indexes. Data security and user privacy are protected in the popular cloud computing environment. * A real-world dataset is collected to evaluate the performance of the proposed scheme. The results show that the proposed scheme significantly improves the search efficiency in terms of time and space. The paper is organized as follows. Section 2 describes the related work for a secure keyword search on the cloud. Section 3 addresses the system model and illustrates the problem. The proposed scheme for condensing the document index and performing secure search on the cloud is presented in Section 4. Section 5 shows the simulation results for the performance of the proposed scheme. The paper concludes in Section 6.
## 1 Introduction  
With roughly 16.5 gigatons of carbon dioxide equivalent (GtCO2e) annually out of a total of 54 GtCO2e, food systems represent one-third of global anthropogenic greenhouse (GHG) gas emissions, making them a significant environmental impact driver [1]. Furthermore, according to the United Nations, the world's population, currently at 8.2 billion, is projected to grow steadily over the next six decades, and peak at approximately 10.3 billion by the mid-2080s [2]. Agriculture represents 9.91% of GDP [3], yet many countries prioritize it as a \"national security\" concern, given the essential role these products play in their survival.  
Agricultural production is currently facing one of humanity's biggest challenges: how to meet the food needs of a growing global population while minimizing reliance on chemical inputs. By 2050, global food production must increase by 70%, which calls for a transition to more sustainable farming methods [4]. Achieving this goal will require a significant boost in agricultural output despite limited resources and increasingly degraded soils. The challenge is further exacerbated by the escalating impacts of climate change, such as more frequent droughts, extreme weather events, and the spread of new pests and diseases, all of which place considerable stress on crops and food systems [5].  
The extensive use of agrochemicals, including fertilizers and pesticides, has greatly increased agricultural productivity, supporting the growth of the global population. However, excessive use has resulted in significant environmental and health issues [6]. These problems include soil and water contamination, a decline in biodiversity, and the accumulation of harmful residues in food chains, posing a threat to ecosystems and human health [7]. To address these concerns, initiatives like the European Green Deal, led by the European Union, aim to transition toward more sustainable agricultural practices. Through the Farm to Fork Strategy, the plan targets a 50% reduction in pesticide use and a 20% decrease in chemical fertilizers by 2030 [8].  
With the expansion of insect farming, the growing availability of insect excrement presents new opportunities for agricultural applications. It is estimated that grass production in Europe already exceeds several thousand tons per year and could reach 1.5 million tons annually by 2025 [9]. This review explores its potential as a novel agricultural input, focusing on how it can help alleviate both abiotic and biotic stresses. Additionally, the discussion analyzes the viability of grass as a sustainable substitute for synthetic agrochemicals and its contribution to promoting eco-friendly farming practices, along with a thorough evaluation of its future prospects. The possible negative effects resulting from its application, such as the spread of plant pathogens, the inhibition of local plant defense mechanisms, or even an increase in pest populations, will also be discussed.
## 3 Chirped Microwave Pulse Generation and Compression  
Chirped microwave waveforms are of interest for applications in instrumentation, imaging, and communications. For example, they can be compressed to increase the detection distance and improve the measurement resolution for radar systems. Recently, [PERSON] et al. demonstrated the use of generating and compressing chirped microwave waveforms as a means for performing high resolution and real-time interrogation of an LCFBG sensor [7]. In this section, we describe how this approach can be extended for simultaneous interrogation of multiple LCFBG temperature sensors.
## 3 Results and Discussion
### Spatiotemporal Variation of Evaporranspiration  
The annual ET ranged between 12-1344 mm during 2000-2008, which showed significant spatial heterogeneity (Figure 4). It is very low in most part of the study area, where it generally ranged between 32-100 mm, and it is only high in the oases, East Juyanhai Lake and the regions along Heihe River. The highest ET was generally found in the forests, water body and irrigated croplands, while the lowest ET was found in the desert area and Gobi area. In particular, the highest ET in 2005 and 2008 occurred in the water body of East Juyanhai Lake, which reappeared in 2003. By comparison, ET was generally below 50 mm in the desert area, where the land surface is mainly covered by bare rock with sparse vegetation. There were widespread sandy land and Gobi desert in most part of the study area, where both the vegetation coverage rate and the water availability was very low. While the high-coverage vegetation such as the cultivated land and forests was generally distributed in the oases and the regions along the main stream of Heihe River, where there was high water availability. Besides, the annual ET first increased during the first half of the period (2000-2005), and then decreased after that, but the overall increase was significant in the entire study period. In addition, there was also obvious variation of the monthly ET, which was generally high during the growing season (from April to  
Figure 3: The annual potential soil loss (SSp), annual soil conservation amount (SC) (Unit: t) and soil conservation rate (SCR) in 2000, 2005 and 2008.  
October) and low during the non-growing season (Figure 3). It is noticeable that there was obvious temporal inconsistency between the ET and the soil conservation amount (Figure 2). Most part of the ET occurred in the summer and autumn, while most part of the soil conservation amount concentrated in the spring, indicating only a part of the ET was used to provide the soil conservation service. What is more, since the precipitation of the study area is very limited (approximately 37 mm), it has very limited impacts on the change of ET, other factors such as the water diversion of Heihe River and land use and land cover change may have played a key role in influencing the spatiotemporal variation of ET.
## 2 Theory and Simulation of Five-Frame Variable Phase-Shifting Method for SD-OCT  
### Theory  
Figure 1 shows a homemade full-range spectral domain optical coherence tomography system, including a super luminescent diode (SLD) light source, Michelson Interferometer, and a spectrometer, etc. The graded index (GRIN) fiber collimator makes the light output of a SLD (850 nm) into collimated light and a cube beam splitter divided the light into two equal-power beams. One light went to the piezoelectric ceramic transducer (PZT) translating reference mirror and the second one went into the sample arm. The data acquisition (DAQ) card was used to control the moving of the PZT translating reference mirror. The optical path difference between reference and sample arm will be changed if the reference mirror moves. We could obtain five frames of the interference signal of the sample with a phase difference of \(\pi/2\).  
In SD-OCT system, the light source from SLD passing through the reference beam of Michelson Interferometer finally captured by the detector could be expressed as:  
\[E_{R}(k,z)=A_{R}(k,z)exp(-j2 kz_{r}) \tag{1}\]  
Figure 1: Schematic of full-range spectral domain optical coherence tomography system. SLD Super Luminescence Diode (Exalos), FC Graded Index (GRIN) Fiber Collimator (Thorlabs), Obj Objective Lenses (Thorlabs), BS Cube Beam Splitter (Thorlabs), PZT Piezoelectric Ceramic Transducer (Thorlabs), DAQ Card Data Acquisition Card (NI), PC Personal Computer, Cyl Cylindrical Lens (Thorlabs), Col Collection Lens (Thorlabs), Gra Optical Grating (Thorlabs), CCD CCD camera.  
\[tan[\varphi(k)]=\frac{2(I_{2}-I_{4})}{2I_{3}-I_{1}-I_{5}} \tag{12}\]  
In fact, the Equations (11) and (12) are the special cases of Equations (9) and (10) when \(\varnothing(k)\) is equal to an invariant phase shift of \(\pi/2\). After calculating the intensity \(A_{nr}(k)\) and phase \(\varphi(k)\), the reconstructed complex conjugate interferometric signal \(I_{c}(k)\) is given by:  
\[I_{c}(k)=A_{nr}(k)cos[\varphi(k)]+jA_{nr}(k)sin[\varphi(k)]. \tag{13}\]  
By doing fast Fourier transform (FFT) for Equation (13), we could obtain the depth information of the sample.