esa-sceva/satcom-chunk-collection huggingface dataset:
# Physical Properties of _Jatropha curcas_ L. Fruits and Seeds with Respect to Their Maturity Stage
## 3 Results and Discussion
### Geometric Characteristics of _J. curcas_ fruits and Seeds
#### 3.2.2 Seeds  
The moisture content of \"yellow\" seeds was significantly higher than for \"black\" seeds, while the unit mass was lower at \(p<0.05\). Only \"black\" seeds were suitable for oil extraction, since the proper moisture content of _J. curcas_ seeds for the process should be below 10% [26; 27]. Based on these findings, an overview of the moisture and oil content of _J. curcas_ seeds has been established to maximize the oil yield. Moreover, the lower moisture content of \"black\" seeds could result in a longer shelf life and higher resistance against mold, fungi, and other contaminants. On the other hand, the dimensions of \"black\" seeds, such as length, width, thickness, arithmetic diameter, geometric diameter, volume, and surface area were generally larger than for \"yellow\" seeds. With increasing maturity of the fruits, the size of the seeds increased and the moisture content decreased [18]. As the seeds were maturing, the unit mass increased from 0.4 to 0.6 g, the surface area increased from 467.6 to 503.3 mm\({}^{2}\), and the specific surface area dropped from 4.5 to 4.1 cm\({}^{2}\)/cm\({}^{3}\). Only the specific surface area of \"black\" seeds was slightly lower than for \"yellow\" seeds. Therefore, these results indicated that \"yellow\" seeds were not mature enough for harvest and could cause low oil yield during mechanical oil extraction due to their high moisture and low oil content. Due to its sphericity, the shape of _J. curcas_ seeds was identified as ellipsoid [14]. It can also be seen that \"yellow\" seeds had a higher proportion of shells (61.9%) than \"black\" seeds (45.8%).  
The unit mass and the geometric characteristics of \"yellow\" and \"black\" seeds were lower than in _J. curcas_ seeds from Thailand [24], but similar to _J. curcas_ seeds from India [14]. Moreover, the moisture content of \"black\" seeds seemed in good agreement with the _J. curcas_ seeds from India.
## 4 Discussion
### Environmental Sustainability Evaluation by DEXi-met
[15] indicated that a simpler component structure has a greater influence on the overall sustainability, whereas a higher number of variables, that individually could have no significant impact, become more sensitive if they are considered together. In our study, the _DEXi-met_ produced both the \"microorganism preservation\" and the \"macrofauna preservation\" attributes as the most influential variables of our sensitivity analysis. This last result was due to the difference in the systems analyzed. In particular, it is a consequence of using agro-ecological practices, especially in the ECO system. Except for \"strip cultivation with agro-ecological functions\", all the other basic attributes in the nodal aggregate \"biodiversity conservation\" showed the SI higher than 0.2, indicating the positive influence of the systems on the environmental sustainability [40]. The basic attributes \"fertilizer C/N\" (within the \"resources preservation\" nodal attribute), the \"insets and pests diseases\", \"weeds\", and \"productionquantity\" (within the \"production capacity\"), and \"soil erosion control\" (within the \"soil and water preservation\") reached the highest values. According to [PERSON] et al. [15], when the SI is high, the effect of each variable on the overall sustainability is more relevant. The detailed analysis of the _Dexi-met_ model structure through the distribution of frequencies in the overall sustainability and the nodal attributes (showed by the Monte Carlo analysis) revealed that the model adequately represents the diversity of the systems evaluated. In fact, the frequencies obtained in the \"overall sustainability\" showed the highest value for the \"medium\" modality, following a normal Gaussian pattern. This behavior is due to the use of till to seven qualitative classes at the \"overall sustainability\" level, allowing to distinguish the different scenarios. However, the number of the qualitative classes (from \"very low\" to \"very high\") was not so large to generate unnecessary complications in the use of the model, and to reduce its ability to distinguish differences between systems. Besides, to avoid further complications, in agreement with [PERSON] et al. [24], the aggregate attributes were composed by five qualitative classes (from \"low\" to \"high\") and the basic attributes were composed by only three classes (\"high\", \"medium\", and \"low\").
# Inferring Long-Term Demand of Newly Established Stations for Expansion Areas in Bike Sharing System
## 5 Discussion of the Results  
In this research, we are facing the demand prediction problem of real-world bike-sharing systems. In the previous experiments, we can observe that two important factors in LDA settings are worth discussing, considering real-world applications. One is batch deployment. Another is the prediction time period. These two factors are mutually high-correlated.  
**Discussion of batch deployment**: In the past, existing works usually aimed to predict human flows for each individual station in a short time, such as next hour, next day, and next 1-3 days. However, in real-world applications, we claim that predicting long-term demands for station deployment is also critical for urban planning and construction. Therefore, we propose an LDA framework, which can help governments or transportation companies to make decisions for deploying bike-sharing services in a smart city. We have observed that the real-world bike stations are mainly built-in batches for expansion areas in modern cities. That is, we can use only the historical demand data from previously deployed areas for prediction. The batch consideration in the LDA framework confirms that our work is the first to address the long-term demand of new stations for future batch  
Figure 14: Random prediction for rental/drop-off.  
Figure 13: Different periods of prediction for Drop-off.  
stations, providing the government with a tool to pre-evaluate the bike flow of new stations before deployment. LDA can avoid wasting resources such as personnel expense or budget.  
**Discussion of prediction periods:** In Section 4.2.4, our experiment shows that the six months' prediction has the best performance. The reason is we observe that in the New York Citi bike sharing system there are some new stations built surrounding the existing stations after six months so that the demands of some stations in a certain batch were influenced by new stations. However, we believe our proposed LDA framework is also helpful for making decisions using the prediction results of periods that are more than six months since the prediction error is mainly from the crawled future data. To conclude, our LDA framework can work as a web service to assess the effectiveness of new bike stations for expansion areas in different cities.
# Relative Pose Estimation between Image Object and ShapeNet CAD Model for Automatic 4-DoF Annotation
## 5 Discussion  
The goal of the proposed pipeline is to estimate the 3D pose of a real object in a single image only with the 4-DoF annotation parameters to a matching CAD model. To achieve the goal, the proposed pipeline detects objects of various classes in RGB images, retrieves CAD candidates with the same shape, estimate the rotational pose of the objects, and performs the similarity measurement to find the base matching 3D model. The rotational pose is represented only with 3-DoF parameters and the focal length of the camera for alignment of the model to the object is represented only with 1-DoF parameter. Thus total 4-DoF pose parameters are enough to annotate the pose of the CAD model relatively with the object area in an RGB image.  
In this study, ten CAD models were arbitrarily selected for each class of the object, and the similarity between the rendered image of the rotated CAD model and the RGB image was measured to determine the optimal CAD model. DetectoRS was trained to detect the object and its class, and PoseContrast was used for rotation among the detected object pose information. The similarity between the rendered images of the 10 candidate CAD models with the same class as the class of the detected object was measured by matching the DELF feature to minimize the domain gap problem.  
From experiments, we find that only 4-DoF pose annotation parameters are enough to project the CAD model to the image space to align the shape of the model with the object region. The proposed pose estimation framework can be used to several graphic-to-image fusion applications such as Augmented or Extended Reality.  
Conceptualization, S.-Y.P.; methodology, software, validation, formal analysis, C.-M.S., W.-J.J. and S.P.; investigation, S.-Y.P., C.-M.S., W.-J.J. and S.P.; writing--original draft preparation, S.-Y.P.; writing--review and editing, S.-Y.P.; supervision, S.-Y.P.; project administration, S.-Y.P.; funding acquisition, S.-Y.P. All authors have read and agreed to the published version of the manuscript.  
This research was by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2021-0-00320, Manipulation and Augmentation for XR in the Real-World Environment).  
Figure 10: The matched CAD model is projected to the 2D image plane with the 4-DoF pose information. 4-DoF pose of the Clock and Car objects are very closely matched with the real objects. The Bench model projection is not perfectly matched with real object area due to a small pose error. The projection error of the Bag object CAD is caused by the shape mismatch between the real object and the CAD model.
# 3D In Situ Stress Estimation by Inverse Analysis of Tectonic Strains
## 2 Inverse Analysis for In Situ Stress Determination
### Tectonic Stress-Based Approach
The shear stress along axes Y can be, respectively, considered as Equations (9) and (10):  
\[\sigma_{\mathbf{n}}\ =\ \mathbf{a_{0}}+\mathbf{a_{1}}\times\mathbf{y}+\mathbf{a_{2}}\times\mathbf{z} \tag{8}\]  
\[\sigma_{\tau\mathrm{Y}}\  
meet the force equilibrium applied on boundaries for whole model, in inverse analysis, the stress boundary is usually simply dealt with as the follows: the normal and shear stress conditions are applied to the boundaries BCDE and ABEF, the boundaries AOCF and OCDG are normally constrained, and the bottom ones are fixed. Mostly, multiple regression approach is utilized to solve the best-fit boundary, especially the linear regression approach [17].  
It can be seen that for linear expressions of stress boundary mode in 3-D calculating model, there are seven variables on each boundary BCDE and ABEF, and in total, 14 variables need to be solved by linear regression approach, however, more variables will appear in complex expressions for stress boundary mode.  
In order to obtain a reasonable in situ stress field, the best-fit stress boundary condition must be determined by using the optimization algorithm, such as the simplex method, neural network, genetic algorithm [22], and surrogate model accelerated random search [17]. Generally, the objective function needs to be established based on the measured values and calculated values, as Equation (12). For the optimization algorithm, if the variables are less than 10, the simplex algorithm can be available to obtain the rational results, or else the global optimization algorithm should be more effective than the simplex algorithm:  
\[F\ =\ \min\sum_{j\ =\ 1}^{m}\sum_{k\ =\ 1}^{6}\left\|\sigma_{jk}-\hat{\sigma }_{jk}\right\|_{2} \tag{12}\]  
where \(m\) is the number of measured points in the field test, for Figure 2, \(m=6\). \(\left\|\ \right\|_{2}\) is the 2-norm of stress tensor, \(\hat{\sigma}_{jk}\) stands for the k component of the measured stress tensor at point \(j\), and \(\sigma_{jk}\) is the corresponding calculated value at point j. For a stress-based approach, the key problem is to select the stress boundary mode, and different boundary modes determine different in situ stress fields. It needs to be noted that a more complicated expression of stress boundary mode does not necessarily lead to a better estimation of an in situ stress field. However, in an optimization algorithm, more variables require exponentially increased computational effort.
# Impact of Die Radius in a Streamlined Die during Wire Drawing
## 4 Results
### Comparison of Temperature and Drawing Force  
It is important to calculate the temperature distribution of the wire during wire drawing because the microstructures and mechanical properties depend on the temperature during the forming process [41]. Figure 10 shows the temperature contour and profile with the die radius. During the wire drawing process, the temperature rise originates from two factors, as shown in Figure 2: the frictional stress at the wire-die interface and the heat generation stemming from the plastic deformation of the wire [1]. Thus, the surface area of the wire had a higher temperature compared to the center area regardless of the die radius because of the surface heating of the wire stemming from the frictional stress at the wire-die interface. The center temperature increased in a parabolic manner during the drawing process (Figure 10b). Meanwhile, the behavior of the temperature rise showed a complex relationship with the die radius. The temperature rise of the wire was high when dies with a low radius were used, and it was also high when dies with a high radius were used. For example, the minimum temperature rise among the streamlined dies occurred in the wire manufactured by the die with a radius of 64. Interestingly, the temperature rise was lowest in the wire by the conventional die as shown in Figure 10c.  
Figure 11 compares the drawing force with the die radius. It was observed that the drawing force had a similar pattern to the temperature rise with the die radius. The wire manufactured by the die with a radius of 128 exhibited the maximum drawing force owing  
Figure 10: Comparison of (**a**) temperature contour, (**b**) history of center temperature along the drawing direction, and (**c**) the steady-state center temperature and the maximum temperature of the wire with the die radius.  
to the greater contact length of the wire and die, and the conventional die had the minimum drawing force.
# Study of Coded ALOHA with Multi-User Detection under Heavy-Tailed and Correlated Arrivals
## 4 Numerical Experiments
### Impact of the Marginal Distribution of the Arrival Process
#### 4.1.2 Frame Asynchronous Coded-Slotted ALOHA
If instead we set as arrivals two discrete Pareto with different variances, i.e., \(\sigma^{2}=1.1\mu^{2}\) and \(\sigma^{2}=4\mu^{2}\), then we observe (Figure 11) the same shapes for the \(\mathsf{PLR}\) and average delays, with the only expected difference that performance is worse as the second moment \(\sigma^{2}\) increases.
# A Multimode Fusion-Based Aviation Communication System
## 3 Hardware Design
### ADS-B Broadcasting Communication Module  
The ADS-B broadcast communication module is an automatic broadcasting system that transmits vital information about the aircraft, including its type, aviation code, position, speed, altitude, and route, in an omnidirectional manner, as depicted in Figure 9. This  
Figure 8: RDSS module composition block diagram.  
Figure 7: Schematic diagram of the BeiDou satellite communication link.  
module has the potential to offer safer and more efficient air traffic monitoring methods; widen the coverage of monitoring; and enhance air traffic safety levels, airspace capacity, and operational efficiency. The primary communication functions of this module are as follows:  
1. The ADS-B communication module receives real-time messages from other aircraft broadcasts. These messages can be of various types, which will then be assembled into mode state (MS) reports following the RTCA/DO-260B standard [36]. The reports will then be sent to the flight control computer for analysis and processing. At the same time, the data will be transmitted down to the ground control center through dedicated ad hoc network links and public network links. The current air situation of the aircraft will be analyzed and displayed based on this data.
2. The ADS-B broadcast communication module receives navigation information such as longitude, latitude, altitude, and speed from the flight control computer. After inserting ME fields in DF18 format, multiple 1090 ES data links are assembled to transmit various types of ADS-B messages. These messages are then broadcast through omnidirectional antennas. At the same time, the data are transmitted to the ground control center through dedicated ad hoc network links and public network links. Finally, the current situation of the aircraft is analyzed and displayed.  
The composition diagram of the ADS-B module is shown in Figure 10.  
Figure 10: ADS-B module composition block diagram.  
Figure 9: ADS-B broadcast communication diagram.  
The ADS-B module is a compact design that combines an ARM+FPGA+RF transceiver, saving space and enhancing the system capacity. The digital processing is accomplished using Xilinx's Z7 series FPGA chip XC7Z020. The RF processing includes a reception channel and a transmission channel. The received signal is converted into a 70 MHz intermediate frequency signal through low-noise amplification, filtering, and mixing and then sent to the digital processing section. The transmission channel generates a 1090 MHz CW signal through VCO. The high-speed RF switch is controlled by FPGA to complete 2 ASK modulation of the baseband signal and the local oscillator signal. The standby power consumption of the ADS-B module is approximately 25 W, and the signal transmitting power is about 33 W.
# Influence of Cryogenic Grinding on the Nutritional and Antinutritional Components of Rapeseed Cake
## 3 Results and Discussion
### Influence of the Grinding on the Particle Size Distribution

Table 3: Particle size distribution parameters determined for the rapeseed cake (RC = sample before additional grinding; RT = room temperature; CC = cryogenic cooling). Span and specific surface area of powders affect the flow and caking properties of powders [44]. The samples without cooling (RT) had a larger distribution span, ranging from 2.6 to 3.3 and increasing significantly with increasing grinding time. This was an indication that while longer grinding time resulted in a smaller median particle size, it also resulted in particles with different particle diameters and a larger spread from the median diameter. Powders with larger spans often exhibit poor flow properties that are difficult to control [41]. The effect of increasing the span was not as pronounced at CC. The span of the initial sample before grinding (1.9) was comparable to the values obtained after grinding for two minutes with cryogenic cooling, with a slight increase in span for sample 12 CC (2.2). The specific surface area increased from 0.010 m\({}^{2}\)/g to 0.031 m\({}^{2}\)/g without cooling and to 0.071 m\({}^{2}\)/g with cooling. Again, the positive effect of cooling is particularly pronounced, as the specific surface area increases sevenfold, whereas without cooling it increases only threefold. As with the median particle size, the same increase in specific surface area was obtained with 12 min of RT grinding as with only 2 min of CC grinding. The smaller particle size of rapeseed cake and distribution span of particle size, as well as the increase in specific surface area of samples grinded under cryogenic conditions, are in accordance with the results of previous research [13; 14; 15]. Pre-cooling rapeseed cake with liquid nitrogen solidifies the oil since the melting point of rapeseed oil ranges from \(-\)20 to \(-\)10 \({}^{\circ}\)C [40]. In addition, cooling the system during the grinding absorbs the heat generated during the grinding operation and maintains the desired low temperature [13]. This embrittles the material, which allows finer grinding and a more uniform particle size.
# FusionTrack: Multiple Object Tracking with Enhanced Information Utilization
## 3 Methodology
### Score Guided Multi-Level Query Fuser  
To better extract appearance information from queries and fuse the appearance features across frames, we propose the score-guided multi-level query fuser. It takes the input and intermediate results of the joint track-detection decoder and extracts target appearance information from multi-level and historical features.  
In a decoder using an iterative refinement framework, the output features of the final layer are only supervised by classification and bounding box offset based on previous output. Such features may not represent the target's appearance information needed for tracking well. To obtain richer appearance information, we fully utilize the intermediate queries from different levels that may potentially focus on different aspects of the target during the iterative refinement process. This module also incorporates the query input from the previous frame to fuse historical appearance features between frames. Since the accuracy of detection also affects the importance of historical information during fusion, we use the classification scores of each target as a basic hint for querying the required appearance information from these features.  
As shown in Figure 4, the features we need to fuse come from the current frame's track queries \(q_{t}\), which contains historical information about the tracked targets, and the intermediate queries \(q^{\prime}_{t1},q^{\prime}_{t2},\ldots,q^{\prime}_{tL}\) obtained by each layer of the decoder, which contains information about the targets in the current frame. Sinusoidal embedding followed by a single-layer network is used to embed the targets' classification scores to obtain a score embedding of the same feature dimension as the query. We concatenate it with the aforementioned features to obtain a feature vector of \((L+2)\times B\times Q\times D\). This vector is treated as a batched token of length \((L+2)\). After adding sinusoidal position encoding to the tokens, the tokens are sent into multiple layers of transformer encoder-like structure for feature fusion. In this structure, we utilize self-attention as a fusion module, where different queries are fused using attention weights. It is similar to a combination of self-attention between queries and cross-attention between queries and score embedding. The final appearance feature is obtained by selecting the output token that is derived from score embedding.  
Considering the difference in form between the object query and track query, we use two separate score-guided multi-level query fusers to obtain their respective appearances \(a_{det}\) and \(a_{track}\) in FusionTrack.
# Efficient LDPC Encoder Design for IoT-Type Devices
## 5 LDPC Encoder Design for a Microcontroller Implementation  
The application of dual-diagonal QC-LDPC codes with Richardson-Urbanke encoding can be an attractive option for the transmission system under consideration. In this section, we present a developed implementation of an efficient QC-LDPC encoder for a computational core of a typical microcontroller device.  
Similarly to the majority of embedded software solutions, the experimental application is implemented in the C language using the GCC (GNU compiler collection) compiler delivered with an IDE (independent development environment) from STMicroelectronics, version for STM32-9-2020-q2-update. The encoder is compiled for Cortex-M4 core, with optimization for size (-Os flag), which increases the possible size of applicable parity check matrices. All drivers for HAL (hardware abstraction level) were delivered by ST company. The experimental hardware is based on the STM32L476 microcontroller; however, the proposed solution can be adapted for other devices from numerous vendors. The device utilized for experiments has 1 MB of flash memory and 128 KB of static RAM, operating with an 80 MHz clock frequency.