esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Methods
### Accuracy Assessment

Table 3: Verification measures, acronyms and equations derived from contingency table from Table 2.  
lower resolution burned area products (300 m and 500 m, for PROBA-V and MODIS, respectively). This proportion was used to weigh the contingency table data. For example, if an AQM-PROBA burned pixel has 70% of its area considered as burned in the reference data, this pixel has a hit of 0.7 and a commission error of 0.3. On the other hand, if the burned area in the reference data corresponds to 30% of an AQM-PROBA pixel, none of which is captured by AQM-PROBA, this pixel will have an omission error of 0.3. The proportions were used as weights to calculate the contingency table, which results from the summation of all weighted values for each error or hit. The analysis takes into account the extent to which the lower resolution information diverges from the higher resolution reference. This approach has been used for validating burned area maps derived from low-spatial resolution data against reference data of higher spatial resolution, since it is more appropriate than the traditional contingency table for the comparison of datasets with different spatial resolutions [7; 50; 64]. Moreover, a confidence interval was calculated for each verification measure using AQM-PROBA and MDC64A1 burn maps, by means of the Z-test. The confidence interval means that by repeating the analysis with independent samples, the results will be within the upper and lower bounds of the interval with a pre-defined probability, in our case 95%. In the second approach, grid-based, we compared AQM-PROBA, MCD64A1, and the Landsat reference data over 10 \(\times\) 10 km grids for each L8 reference scene. The Kendall rank coefficient [65] was used to assess the correlation between the BA products within the 10 \(\times\) 10 km grid. The advantage of grid correlation analysis is that it quantifies regionally the overall agreement between burned area estimation and the reference, and has been widely used to study the relationship between burned area estimates at different spatial resolutions [15]. The Mann-Kendall test was used in order to check the null hypothesis (H0) of no correlation between reference maps and the developed maps (\(\tau\leq\) 0). The alternative hypothesis (H1) indicates that there is a correlation between both reference and developed maps (\(\tau>\) 0), at a significance level of 0.05. Finally, we also evaluated classification errors according to the distribution of fire-scars size by number and by area for each Landsat scene. Thus, the reference, AQM-PROBA and MCD64A1 maps scars were categorized into four classes according to the fire-scar area: (1) very small (0-25 ha); (2) small (25-100 ha); (3) medium (100-1000 ha) and (4) large (>1000 ha).
# Development Status of Key Technologies for Optoelectronic Integrated Circuit Manufacturing
## 4 Packaging of Optoelectronic Integrated Circuits  
The packaging of optoelectronic integrated circuits is the system integration of optoelectronic devices, electronic components, and functional application materials [73]. With the continuous development of optoelectronic integrated circuit technology, requirements for transmission speed, performance index, form factor, and packaging cost in terms of packaging have become stringent. Thus, promoting the progress and innovation of packaging technology is essential for the packaging technology to experience double-inline insertion, butterfly packaging, coaxial packaging, Mini-DL packaging, small form factor packaging, chip on board (COB), tape automated bonding (TAB), and flip-chip (FC) [74; 75]. Based on the packaging form, packaging can be categorized into monolithic packaging and optoelectronic co-package (photoelectric hybrid packaging). Among these, optoelectronic co-packaging is a mixing package of microelectronic technology and photonic technology, which can not only give full play to the advantages of fast optical interconnection speed, large bandwidth, anti-interference, high density, and low power consumption, but also use the mature microelectronics technology, high-density integration, high yield, low cost, and other advantages, which is a critical topic of research.
## 2 Mathematical Preliminaries
### Gramian-Based Model Reduction  
Gramian-based model reduction approximates the input-output behavior of a system by removing the least controllable _and_ observable state components. To this end, the system is transformed to a representation in which controllability and observability are balanced. Given a controllability Gramian \(W_{\mathsf{C}}\) (Section 3.1.1) and observability Gramian \(W_{\mathsf{O}}\) (Section 3.1.2) to an input-output system,a balancing transformation [4] is computable; here in the variant from [40], utilizing the singular value decomposition (SVD):  
\[W_{C} \stackrel{{\text{SVD}}}{{=}}U_{C}D_{C}U_{C}^{\intercal},\] \[W_{O} \stackrel{{\text{SVD}}}{{=}}U_{O}D_{O}U_{O}^{\intercal}\] \[\to U_{C}D_{C}^{\frac{1}{2}}U_{C}^{\intercal}U_{O}D_{O}^{\frac{1} {2}}U_{O}^{\intercal}=W_{C}^{\frac{1}{2}}W_{O}^{\frac{1}{2}}\stackrel{{ \text{SVD}}}{{=}}UDV^{\intercal}.\]  
Partitioning the columns of \(U\) and \(V\) based on the Hankel singular values (HSV) in \(D\), \(D_{ii}=\sigma_{i}>\sigma_{i+1}\), which indicate the balanced state's relevance to the system's input-output behavior, into \(U_{1}\in\mathbb{R}^{N\times n}\), \(V_{1}\in\mathbb{R}^{N\times n}\) related to the large HSV and \(U_{2}\in\mathbb{R}^{N\times N-n}\), \(V_{2}\in\mathbb{R}^{N\times N-n}\) associated to the small HSV,  
\[U =\left(U_{1}\quad U_{2}\right),\] \[V =\left(V_{1}\quad V_{2}\right),\]  
then discarding the partitions associated to small singular values \(\sigma_{n+1}\ll\sigma_{n}\), corresponds to the balanced truncation method [4; 41].  
A cross Gramian \(W_{X}\) (Section 3.1.4) encodes both controllability and observability in a single linear operator. For a symmetric system, a balancing transformation can then be obtained from an eigenvalue decomposition (EVD) of the cross Gramian [42; 43]:  
\[W_{X} \stackrel{{\text{EVD}}}{{=}}UDV^{\intercal}.\]  
Alternatively, an approximate balancing transformation is obtained from an SVD of the cross Gramian [11; 44]:  
\[W_{X} \stackrel{{\text{SVD}}}{{=}}UDV^{\intercal}.\]  
The truncated projections, \(U_{1}\) and \(V_{1}\), are obtained in the same way as for balanced truncation. Using only the left or only the right singular vectors of \(W_{X}\) for the (truncated) projections of the state-space, and their transpose as reverse transformation, results in orthogonal (Galerkin) projections [45]. This approach is called direct truncation method [11; 27], i.e., \(V:=U^{\intercal}\).  
Similarly, the parameter projection can be based on associated covariance matrices. A transformation aligning the parameters along their principal axes, resulting from an SVD of such a parameter covariance matrix \(\omega\)[11; 46; 47]:  
\[\omega \stackrel{{\text{SVD}}}{{=}}\Pi\Delta\Lambda,\]  
yields truncatable projections given by the singular vectors, with partitioning of \(\Pi\) and \(\Lambda\) based on the singular values in \(\Delta\).
## 4 Early Warning of Rockburst Based on Microseismic Indices
### Commonly Used Microseismic Indices
#### 4.1.4 b Value  
[PERSON] and [PERSON] [61] observed that there is a negative correlation between the moment magnitude and the frequency of earthquakes, and proposed the famous Gutenberg-Richter model.  
\[\log N(M)=a-bM \tag{8}\]  
where \(N(M)\) is the cumulative number of microseismic events with a greater magnitude than \(M\); \(a\) and \(b\) are constants; and \(b\) value is the linear slope obtained by fitting the moment magnitude-frequency relationship in the region.  
Laboratory studies, field observations, and numerical simulations have shown that the slope of the distribution curve is related to the stress condition and reflects the degree of microfracture activity in the rock mass. In the process of surrounding rock excavation and unloading, when the large-scale fracture in the rock mass increases gradually, the \(b\) value evidently decreases [47; 60]. Because it can directly reflect the stability of a surrounding rock, the \(b\) value is often considered an important early warning index for rockbursts. However, its applicability is limited: (1) the \(b\) value is often insensitive to the weakening of the microseismicity; (2) in some strong rockburst caves, high-magnitude events are often accompanied by a large number of low-magnitude events, and there are almost no intermediate magnitude events, showing the characteristics of a typical bimodal model. In this scenario, the moment magnitude-frequency distribution relationship is no longer subject to the Gutenberg-Richter model; therefore, the \(b\) value becomes inapplicable.
# Search and Rescue in a Maze-like Environment with Ant and Dijkstra Algorithms
## 3 Search and Rescue in Maze-like Environments
### Modeling the Problem
#### 3.1.2 The Physical Accessibility  
Mazes as a concept are rich with historical connotations, but abstractly speaking can be seen as environments with obstacles, commonly oriented such that elongated hallways or paths are created. In contrast to a labyrinth, mazes have branching points; that is, there are locations where the next step (which does not reverse the previous step, i.e., going back) can be in more than one direction. This gives rise to the most commonly known property of mazes, namely that the finding of a specific location, or retracing one's steps to return to the entry point, can be challenging. While there are many variations on this theme, in the simplest form (and, as it turns out, a sufficiently general description) a maze is a collection of locations combined with a accessibility relation that determines, for any two locations, whether they are directly connected. Due to this, mazes can be represented as graphs [104].
## 4 Discussion and Conclusions  
In this study, physical property parameters of rock mass, such as density and water absorption, were obtained. Physical and mechanical experiments of rock mass were carried out in the laboratory, and mechanical parameters of rock mass were obtained, such as elastic modulus, Poisson's ratio, internal friction angle, and cohesion. The main conclusions of this study are as follows:  
1. By carrying out physical and mechanical experiments of rock, the elastic modulus, Poisson's ratio, internal friction angle, and cohesion of coal and rock are obtained. The experimental results show that the compressive strength of the sample is in the order of medium sandstone > fine sandstone > mudstone.  
Figure 14: The relations between unknown parameters and confining pressure strength.  
Figure 13: The relations between confining pressure strength and residual strength.  
2. The mechanical equation of fine sandstone under triaxial stress is established. On the basis of statistical damage mechanics, this chapter fully considers the influence of hydrostatic pressure in the experimental process, takes hydrostatic pressure as a part of the equation, and establishes a stress-strain equation based on confining pressure, which can describe the mechanical failure characteristics of rock under triaxial stress.
3. There is little difference in the cohesion and internal friction angle of the three rocks, among which mudstone has the lowest cohesion value under triaxial compression, indicating that the triaxial compression shear strength of the three rocks is similar. The cohesion of coal rock is the lowest, indicating that coal rock is easy to be destroyed by shear.  
Methodology, Y.T., H.D., R.Z., J.F. and Z.D.; writing--original draft, H.D.; writing--review and editing, R.Z., J.F. and Z.D. All authors have read and agreed to the published version of the manuscript.  
This work was financially supported by the National Key Research and Development Plan (Grant No. 2018 YFC1504902), the National Natural Science Foundation of China (Grant No. 52079068,52090081), the Key Research and Development Plan of Ningxia Hui Autonomous Region (Grant No. 2018 BCG01003), the State Key Laboratory of Hydroscience and Engineering (Grant No. 2021-KY-04), and National Natural Science Foundation of China (No. 12102230).  
Not applicable.  
The data used to support the findings of this study are available from the corresponding author upon request.  
The authors would like to thank the editor and the reviewers for their contributions.  
The authors declare that they have no conflict of interest.
# An Evaluation of Image Slicing and YOLO Architectures for Object Detection in UAV Images
## 3 Materials and Methods
### Object Detection Model
#### 3.3.1 YOLOv7  
The YOLOv7 algorithm combines multiple computational modules into a single module in the inference phase when updating the parameters of the model. With this method, during training, YOLOv7 splits a module into multiple branches of the same or different modules, and during inference, it integrates multiple branched modules into a completely equivalent module [6]. YOLOv7 architecture is a deep learning model inspired by previous versions (Scaled YOLOv4, YOLOv4, and YOLO-R). To improve the performance of the network, it is designed by taking into account factors such as input/output (I/O) channel ratio, activation functions, gradient path, and memory access cost. The E-ELAN structure represents an important computational block in the YOLOv7 architecture.  
Figure 4: The network structure of the YOLO algorithm.  
The YOLOv7 architecture differs from previous versions by adopting the composite model scaling approach. This approach scales depth and width consistently, enabling its use in join-based models [6]. The E-ELAN structure uses mixing, expansion, and merging cardinality to increase the learning capacity of the network, as well as adapting depth and width consistently with this scaling approach. In this way, YOLOv7 architecture provides a more effective learning ability by providing optimal scaling in both depth and width dimensions. The general structure of the YOLOv7 algorithm can be seen in Figure 5.
## 2 Experimental Section
### Synthesis of Ni\({}_{3}\)Se\({}_{4}\)-MoSe\({}_{2}\) Composites  
In a typical procedure, 0.2 mmol Se powder dissolved in 10 mL of OAm and dodecanethiol (9:1, vol%) was placed in a three-neck flask at room temperature. The suspension was first maintained at 120 \({}^{\circ}\)C for around 10 min with moderate stirring. To obtain the highly active Se precursor, the mixture was then heated up to 200 \({}^{\circ}\)C and aged for an additional 0.5 h. After it cooled down to room temperature, as-obtained Ni\({}_{3}\)Se\({}_{4}\) nanosheets (0.05, 0.1, and 0.2 mmol) mixed with 0.1 mmol of Mo(CO)\({}_{6}\) were added into 5 mL OAm and 15 mL ODE and then sufficiently mixed before injecting into the flask (the ratios of Ni\({}_{3}\)Se\({}_{4}\) to MoSe\({}_{2}\) were fixed at 1:2, 1:1, and 2:1, respectively). The products were then held at 250 \({}^{\circ}\)C for 0.5 h before being cooled to room temperature. Subsequently, the black powders were thoroughly washed alternately by hexane and ethanol and separated from solution by centrifugation. Further, an acid-picking process was applied to remove the organic molecules and improve the hydrophilic property of the products by dissolving them in acetic acid and maintaining them at 85 \({}^{\circ}\)C with vigorous magnetic stirring for 12 h. The final products were washed with alcohol, centrifuged, and dried for further characterization. Pristine MoSe\({}_{2}\) nanosheets were synthesized under the same conditions except adding Ni\({}_{3}\)Se\({}_{4}\) nanosheets. The Ni\({}_{3}\)Se\({}_{4}\)-MoSe\({}_{2}\) composites with ratios of 1:2, 1:1, and 2:1 weighed 31.2, 52.4, and 96.8 mg, and are denoted as Sample 1, 2, and 3 in the following discussion, respectively
# Changes in the Stress Tolerance of Dwarf Rabbits in Animal-Assisted Interventions
## 1 Introduction
### Studies Made with Rabbits: Previous Research Results  
In the spring of 2014, the University of Kaposvar, Erdligeti Primary School, Korosi Cosoma Sandor Primary School in Erd and Bobita Kindergarten in Torokbalint started a 6-week-long animal-assisted pilot study involving 11 dwarf rabbits. The rabbits had not received any prior therapy training. The animals were in the kindergarten for 6 weeks, and human approach tests were recorded every second week. The relationship of the individuals with humans was tested with three different groups: children (twice a week), teachers (they were the animals' owners) and strangers (with whom the rabbits had had no prior contact). The study aimed to determine how the animals' attachment to the owner and the other persons changed over the animal-assisted therapy process. At the end of the project, the dwarf rabbits were subjected to a major stress effect when groups of 6-9 children handled them for 7-10 min. The conclusion of the study was that the carrier cages were a major stressor for the animals, so their confidentiality level decreased significantly. The strong stress effect deteriorated the previously established relationship, so the interoperability of the rabbits might have been replaced by fear, indifference or perhaps even aggression. Based on the research study, it was suggested that rabbits should receive handling for 2-3 weeks before starting therapy [30].  
In another study, school-starting stress was examined using rabbits. This research involved 51 children in a regular and in an inclusive primary school. The effect of rabbits on first-formers (six- and seven-year-old children) was examined under classroom conditions. Animal-assisted development had a substantial effect on children's anxiety levels: anxiety levels decreased during the periods of the development sessions. The higher the anxiety level at the beginning, the greater the effect the animal-assisted activity had. The presence of the rabbit reduced children's anxiety levels by 9.48% in the inclusive schools and by 7.24% in the regular school. At the same time, however, the research did not provide any findings connected to the behaviour of the animals and their stress levels [11].  
The objective of our present result was to analyse the behaviour and stress tolerance of dwarf rabbits in a classroom-like animal-assisted environment with the purpose of providing new results on the other participant in the therapeutic work, the rabbit. These results may be important for animal welfare reasons and also to facilitate animal-assisted work.
# Node-Based QoS-Aware Security Framework for Sinkhole Attacks in Mobile Ad-Hoc Networks
## 2 Related Literature
### Cross-Layer Scheme  
The authors in [5] proposed a novel cross-layer cooperative scheme for detecting blackhole attacks targeting the QoS of OLSR in VANETs. They implement this using QoS-OLSR, a protocol that relies mainly on MPRs that are responsible for all routing in the network. Blackhole attacks target MPRs where packets are intentionally dropped to cause DoS. The authors proposed two mechanisms that allow the exchange of information between layers. The first scheme utilized information among network and physical layers while the second scheme was linked with the physical, MAC, and network layers to enable reliable and efficient detection of packets in transit. In the physical layer, the detection technique assigned each legitimate user a signature that is multiplied by the message, and each node used a maximum likelihood approach to detect the legitimacy of the message.  
In the MAC layer, the detection technique monitored the number of RTS/CTS (request to send/clear to send) requests among neighbor nodes. The cooperative watchdog technique is implemented at the network layer to monitor the packets exchanged among neighbors. The cross-layer technique gave enhanced detection results and minimized the false alarm rate as compared to other state-of-the-art detection schemes. The proposed scheme was implemented for blackhole attacks and there is no evidence of its effectiveness on other attacks in MANETs. Thus, this paper implements an intruder detection system that includes a pathrater and a watchdog between MAC and network layers. At the application layer, the AES algorithm is implemented as an additional security measure.
## 2 Materials and Methods  
### Dataset  
Voice recordings were performed in a double-walled, sound-attenuated room at the Policlinico Tor Vergata (PTV), an affiliate institution of the University of Tor Vergata (Rome-Italy). A digital audio recorder (ZOOM H5) was connected to a headset dynamic microphone (model WH20, by Shure Inc., Chicago, IL, USA) positioned 2-3 cm away from the mouth of the speaker, in a quiet environment with no significant room echo (measurable reverberation), no machinery noises, and/or any kind of static background, and there were no other speakers. Voice signals were sampled at 44.1 kHz, 16 bit resolution.  
PD participants were a group of 51 PD patients (38 men and 13 women with an average age of 65 years), and a control group of 51 healthy subjects (HSs) (12 men and 39 womenwith an average age of 63.7). ASD participants included 60 patients affected by ASD (9 men and 51 women with an average age 60.44 and 64.69 years, respectively), and a group of 60 age- and sex-matched HSs (15 men and 45 women with an average age of 60.73 and 57.76 years, respectively).  
Each participant was asked to perform sustained emission of the vowel/e/ and to read loudly one selected Italian sentence (\"Nella casa in riva al mare [PERSON] vide tre cani bianchi e neri\"). Vowel and sentence were repeated three times each, by applying a pitch considered as \"normal\" for each participant, i.e., without effort. The Italian sentence was chosen for its ability to activate the oral cavity while being uttered due to the presence and alternation of plosive and fricative consonant sounds.