esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Related Work
### SIN Concept and Its Features  
Researchers have presented various interpretations for SIN [7; 8; 9; 10; 11; 12]. Combined with the main research plan of the National Nature and Science Fund of China, \"Space information networks-based theory and key technology [6]\", we define the concept of SIN as follows.  
**Definition 1 (SIN)**.: _SIN is an integrated information network system and network infrastructure that is carried by space platforms. It is composed of a GEO (Geostationary Earth Orbit) satellite system, a MEO (Medium Earth Orbit)/LEO (Low Earth Orbit) satellite system, other information systems (such as HABs (Hot Air Balloons) or UAVs (Unmanned Aerial Vehicles) in near-space), and ground terminals (which are mainly responsible for control). It can support real-time data acquisition, transmission, and the processing of mass data, and achieve systematic information service application through integrated network interconnecting. It provides integrated investigation, navigation, communications, and other services, and realizes battlefield situational awareness (such as communication broadcasting; investigation and surveillance; intelligence detection; navigation and positioning; missile warning; and weather, hydrology, and terrain)._  
Combining the concept and functional requirements, we design the composition and architecture of SIN as shown in Figure 1.  
Figure 1: Composition and architecture of the Space Information Network (SIN) (adopted from [PERSON] et al. [13]).  
As shown in Figure 1 above, we designed the four-layer structure of the SIN. By analyzing the structure of its backbone network and other supporting facilities, we determined the specific components of the SIN. According to its function and Definition 1, the SIN should be mainly composed of four layers: the GEO layer satellite system, the MEO/LEO layer satellite system, the near-space layer information system, and the ground layer terminals. Meanwhile, the basic design ideas are building space-based backbone networks--including GEO and MEO/LEO layer satellite systems to solve global coverage issues--building a near-space backbone network, including the near-space layer information system to solve regional strengthening issues, and building ground layer terminals to achieve command and control.  
Compared with other network systems, the SIN has both similar basic features and some typical features, and those typical features are the key focus and critical links of the research on the SIN. As shown in Table 1, we divide and categorize some typical features of the SIN.  
As shown in Table 1, the emergence of the above characteristics has led to many difficulties in the study of the SIN, such as the difficulty in system design, information acquisition, dealing with the satellite, routing on the satellite and network management, etc.
# Neural Network-Based Analysis and Its Application to Spectroscopy for Mango
## 2 Equipment and Method
### Machine Learning Model
#### 2.2.3 Optimization by Simulated Annealing Algorithm  
In consideration of the linear regression curve derived from the BP-PLS model and a thorough literature review, the propensity for overfitting during the BP neural network training phase is elucidated, often accompanied by uncertain network topology. To address these challenges, the study introduces the Simulated Annealing Algorithm (SAA) [21]. The simulated annealing algorithm is initiated by drawing parallels between the annealing process in solid matter physics and general combinatorial optimization problems. The algorithm's flowchart is depicted in Figure 3. Commencing from a designated high temperature T and progressively decreasing temperature parameters, the algorithm facilitates a probabilistic transition towards the global optimal solution of the objective function by evading local optima. This approach helps in mitigating errors arising from local optima entrapment and overfitting during the search process, thereby enhancing the optimization of the neural network's weight thresholds. Consequently, the study leverages the simulated annealing algorithm to optimize the neural network and enhance its overall performance.
## 1 Introduction
On the other hand, such an approach is resistant to cycle-slips, and may be beneficial for better assessing the established and compared positioning scenarios. To present a comprehensive study, in the following section we start with the analysis of code and phase signals noise, with special attention paid to E14 & E18 satellites. Such analysis may be beneficial for establishing, e.g., an advanced stochastic model of positioning [42]. The characteristic of stochastic properties is followed by presentation of the observation model of multi-constellation relative kinematic positioning. Furthermore, the performance of the instantaneous multi-station medium-range positioning is assessed using single-system or combined GPS + Galileo dual-frequency data. The computations were performed using GNSS data processing software developed at the University of Warmia and Mazury in Olsztyn. In the last section, a summary and conclusions are provided.
# A Noncontact Method for Calibrating the Angle and Position of the Composite Module Array
## 3 Calibration Method
### Influence of Array Placement Error on Calibration
#### 3.2.2 Influence of Array Placement Error on Position Calibration  
It is known from Section 3.2.1 that in each placement error angle of the composite module array, \(\gamma\) is the main factor affecting the calibration accuracy. Since the essence of the calibration system is angle measurement, the effect of \(\gamma\) on the calibration of the position is analyzed as follows.  
Assume that the relative position between the composite module \(i\) and the reference composite module when the array is placed along the X direction of the machine tool is \(\left(x,y\right)^{T}\). When the placement error angle of the composite module array around the Z-axis is \(\gamma\), the relative position between the composite module at this time \(\left(x^{\prime},y^{\prime}\right)^{T}\) is  
\[\left(\begin{array}{c}x^{\prime}\\ y^{\prime}\end{array}\right)=\left(\begin{array}{cc}\cos\gamma&-\sin\gamma\\ \sin\gamma&\cos\gamma\end{array}\right)\left(\begin{array}{c}x\\ y\end{array}\right)=\left(\begin{array}{c}x\cos\gamma-y\sin\gamma\\ x\sin\gamma+y\cos\gamma\end{array}\right) \tag{29}\]  
The introduced position calibration error is  
\[\Delta x=(1-\cos\gamma)x+y\sin\gamma \tag{30}\]  
Figure 7: The composite module array base.  
\begin{table}
\begin{tabular}{c c c} \hline \(\gamma\)**/arcsec** & \(\theta_{xi}\)**=\(\theta_{yi}\)**/arcsec** & \(\Delta_{x}\)**/arcsec** \\ \hline
720 & 50 & 6.10 \(\times 10^{-5}\) \\
720 & 100 & 3.08 \(\times 10^{-4}\) \\
720 & 150 & 6.03 \(\times 10^{-5}\) \\
720 & 200 & 9.51 \(\times 10^{-4}\) \\
720 & 300 & 1.28 \(\times 10^{-3}\) \\
720 & 500 & 3.46 \(\times 10^{-3}\) \\
720 & 800 & 5.94 \(\times 10^{-3}\) \\ \hline \end{tabular}
\end{table}
Table 9: Angle calibration error when \(\alpha\) is 720\({}^{\prime\prime}\).
# Double-Shot Transfer Learning for Breast Cancer Classification from X-Ray Images
## 2 Materials and Methods
### Dataset Description
#### 2.1.2 MIAS Dataset  
The mammographic image analysis society (MIAS) is an organization of UK research groups interested in the understanding of mammograms. MIAS has created a database of digital mammograms taken from the UK National Breast Screening Programme. The database contains 322 digitized films and is available on 2.3 GB 8 mm (ExaByte) tape. In total, 114 images out of the total images are abnormal images, where 63 images are benign and 51 images are malignant. It also includes radiologists' annotation on the locations of cancers. The abnormality is divided into six classes of masses namely calcification, well-defined/circumscribed, speculated, ill-defined, architectural distortion, and asymmetry. The database images have been decreased to a 200 micron pixel edge and padded/clipped, making all the images 1024 \(\times\) 1024. Mammographic images can be accessed from the Pilot European Image Processing Archive at the University of Essex [19; 20]. The total images of benign and malignant cases before applying the augmentation methods are 63 and 51 respectively.
## 3 Problem Formulation, Assumptions, and Notations
### Properties of Throughput  
The properties of the throughput function \(f(\mathbf{b})\) can be exploited to accelerate the solution process of the BAP, as stated in [4; 10; 11; 12; 29]. [PERSON] and [PERSON] [4] performed an extensive study to show that the throughput function has the following properties:  
* Continuity. \(f(\mathbf{b})\) is a continuous differentiable function with respect to each buffer capacity \(b_{i}\), \(i=1,\ldots,K-1\). A small change in any \(b_{i}\) leads to a small change in the throughput.
* Monotonicity. \(f(\mathbf{b})\) is a monotonically increasing function with respect to \(b_{i}\), \(i=1,\ldots,K-1\).
* Concavity. \(f(\mathbf{b})\) is a concave function with respect to \(b_{i}\), \(i=1,\ldots,K-1\).  
Figure 1: A \(K\)-machine production line.  
Based on the above properties, the BAP can be considered as a concave optimization problem, and thus gradient techniques can be applied to enhance computational efficiency.
# Stability Conditions in Lignite Open Pits from Romania, Case Study: Olteu Open Pit
## 3 Results and Discussion
### Determination of the Stable Geometry of the Working Front and Lateral Slopes  
To ensure the stability conditions of the slopes, several geometries of the working steps and the lateral slopes were analyzed, determining their height and inclination for an imposed value of the stability factor.  
In order not to affect in an unjustified manner the excavator's efficiency indicators, the dimensioning took into account the fact that the working slopes have a short lifetime, so a stability reserve of 5-10% can be considered sufficient, and in the case of side slopes, which remain in place from a few months up to a year, a stability reserve of 20-25% was considered sufficient.
## 12 Sustainability of Self-Healing Concrete
In the US, the cost for reconstructing bridges is estimated to be in the range of USD 20 to 200 billion [157], wherein the average maintenance costs for these bridges per year is about USD 5.2 billion. Detailed analyses of the life cycle clearly indicated that the indirect expenditure due to traffic jam and related low output is 10 times higher than the direct one spent for their maintenance and repairs [158]. The Netherlands spent about one-third of their annual budget on the inspection, monitoring, maintenance, up-gradation, and repair of the outsized civil engineering construction works. The repairing and maintenance cost of the construction in the United Kingdom is more than 45% of their annual spending [159; 160]. The department for environment, food, and rural affairs (DEFRA) reports showed that nearly half of CO2 emissions in the UK were due to poor-quality building structures. For instance, the manufacturing of 1 tons of OPC is responsible for the emission of 1 tons of CO2 because of the calcination and fuel combustion process [161; 162]. Worldwide, approximately \(2.35\times 10^{9}\) tons of cement is manufactured per year, which results in major emissions of CO2, nearly 5-7% of the total CO2 emissions in the world. The rapid expansion of the economy of China and India caused the largest consumption of cement, which is anticipated to amplify if the present technologies that are used to manufacture cement remains unaltered. Enhancement of the durability and reduction of the repair costs of the building infrastructures can certainly lessen the negative impact of cement and related pollution due to greenhouse gases emission, thus, improving our activities and stabilizing the biosphere. In this view, it is necessary to perform more studies and look for promising solutions for the future sustainable development. In-depth understanding of the negative impact of the construction materials on our environment is expected to benefit several stakeholders concerned with the construction industries, improving the quality of social life and service life span of the concrete structures, thereby meeting the sustainable goals. Traditionally, concrete structures have been designed to fulfill the desired specifications in the beginning of its service life. Then, the durability of such structures has been monitored via the maintenance plans. Lately, material scientists have adopted some new strategies by considering the adaptability or self-healing properties of the materials over the service life span of the construction materials. This inspiration of using new functional and smart materials in the construction industries has appeared from nature via the bio-mimicry of diverse living organisms. Motivated by the feasibility of achieving self-healing concrete structures, some of the pioneering research has focused on both natural capacity of hydrates to heal cracks over a certain period, as well as artificial ways to repair cracks using adhesive reservoirs embedment into the concrete network matrix.
# Fault Diagnosis of Rolling Bearings Based on Improved Kurtogram in Varying Speed Conditions
## 2 Theoretical Background
### Procedure of the Proposed Method
The outer race fault characteristic order \(FCO_{o}\), the inner race fault characteristic order \(FCO_{i}\) and the rolling element fault characteristic order \(FCO_{b}\) are formulated as follows:  
\[FCO_{o}=\frac{Z}{2}\bigg{(}1-\frac{d}{D}\cos\alpha\bigg{)} \tag{10}\]  
\[FCO_{i}=\frac{Z}{2}\bigg{(}1+\frac{d}{D}\cos\alpha\bigg{)} \tag{11}\]  
\[FCO_{b}=\frac{Z}{2d}\bigg{(}1-(\frac{d}{D})^{2}\cos^{2}\alpha\bigg{)} \tag{12}\]  
where \(Z\) is the number of rolling elements, \(\alpha\) is the contact angle, and \(d\) and \(D\) are the diameter of the rolling element and pitch diameter, respectively.
## 2 Materials and Methods
### Feature Reduction and Main Clustering
#### 2.2.4 HdbSCAN  
As the distance between vector representations of the input light spectra within the two-dimensional, maximally reduced embedded space are no longer meaningful after the application of the UMAP algorithm, the choice of clustering algorithms suitable for this kind of data is limited to density-based approaches that do not rely on the distance between individual data points. Due to its robustness against noise, the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) [42] algorithm has been chosen for this work. In contrast to other density-based cluster approaches, such as the quite popular DBSCAN [55] algorithm, it performs much better on detecting variable density clusters without increasing computational run-time. Compared to DBSCAN, it further eliminates the need for manually selecting and fine-tuning distance scale parameters. As can be seen from Figure 3, HDBSCAN clusters the dense regions of the embedded space from UMAP and leaves the rest as noise. In preparation of the following sub-clustering process, all light spectra independent of whether they were assigned to a cluster or identified as noise were labelled accordingly.
# Recoil Control of Deepwater-Drilling Riser with Optimal Guaranteed Cost \(H_{\infty}\) Control
## 5 Conclusions  
The recoil control issue of the deepwater-drilling riser system has been studied in this paper. First, an incremental model of the riser system has been established by considering the heave motion, linear tension force, and drilling mud discharge model. Then, an optimal guaranteed cost \(H_{\infty}\) recoil control scheme has been presented for the riser system, and the sufficient conditions for the asymptotic stability of the closed-loop system have been derived based on Lyapunov stability theory. In addition, under the designed recoil controller, the \(H_{\infty}\) performance index and the minimum upper bound of the quadratic performance index of the riser can be guaranteed.  
Simulation results show that the designed optimal guaranteed cost \(H_{\infty}\) recoil controller is more efficient than the exiting quadratic optimal recoil controller to refrain the recoil movements of the riser. In fact, the quadratic performance index of the riser with the former  
Figure 11: The elongation of springs under case I.  
Figure 12: The elongation of springs under case II.  
is smaller than that with the latter. It is also found that under the designed recoil controller, the compression of the riser has been avoided, and the safety of the riser has been ensured.  
This paper provides an active recoil control scheme for the riser system in the event of emergency disconnection; however, there are still important issues regarding recoil analysis and control topics to be investigated in the future. It is important to further explore and understand the recoil mechanism of the riser, to provide an in-depth development potential and reasonable active-recoil control schemes.  
Conceptualization and methodology, B.-L.Z.; software, B.-L.Z. and Y.-T.S.; validation, Y.-D.Z., W.Z. and H.S.; formal analysis and investigation, Y.-T.S.; resources, Y.-D.Z., W.Z. and H.S.; writing--original draft preparation, Y.-T.S.; writing--review and editing, B.-L.Z.; visualization, W.Z. and H.S.; supervision, B.-L.Z. and W.Z.; project administration and funding acquisition, B.-L.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China under Grant 61773356.  
Not applicable.  
All data presented in this paper are freely available upon request.  
The authors declare no conflict of interest.
## 3 Threat Model
### Selective Dropping (Deceitful Behaviour)  
A misbehaving node can act deceitfully in order to conserve its energy. It periodically participates in route discovery processes by forwarding control packets for other nodes. This is because control packets are smaller in size than data packets and consume a low amount of energy during transmission. Whenever a data packet is presented to this node for onward transmission, the data packet is dropped. Nodes that forward data packets to this node perceive the link as broken when they do not receive acknowledgements for the first set of data sent. The connection to this node is then deleted from their route entries, but after a given period, the connection is later re-added when the deceitful node participates in the route discovery process again.
# Detection and Localization of Overlapped Fruits Application in an Apple Harvesting Robot
## 4 Overlapped Circles Localization  
Since the outline of the apple can be regarded as a quasi-circular edge, the apple can be effectively positioned with some circle fitting methods. To the problem of overlapped circles, there are many solutions, such as curvature, Hough transform, and least square method, etc. But each method has flaws. This paper presents a method based on extremum. Namely, obtain a distance function which shows the minimum distance from each internal contour point to the edge, and then obtain the center by finding the maxima of the distance function. Finally, by means of rotating vectors, the radii can be got.
###### Abstract  
A new surface profilometry technique is proposed for profiling a wafer surface with both diffuse and specular reflective properties. Most moire projection scanning techniques using triangulation principle work effectively on diffuse reflective surfaces, on which the reflected light beams are assumed to be well captured by optical sensors. In reality, this assumption is no longer valid when measuring a semiconductor wafer surface having both diffuse and specular reflectivities. To resolve the above problem, the proposed technique uses a dual optical sensing configuration by engaging two optical sensors at two different viewing angles, with one acquiring diffuse reflective light and the other detecting at the same time specular surface light for achieving simultaneous full-field surface profilometry. The deformed fringes measured by both sensors could be further transformed into a 3-D profile and merged seamlessly for full-field surface reconstruction. Several calibration targets and industrial parts were measured to evaluate the feasibility and accuracy of the developed technique. Experimental results showed that the technique can effectively detect diffuse and specular light with repeatability of one standard deviation below 0.3 \(\upmu\)m on a specular surface and 2.0 \(\upmu\)m on a diffuse wafer surface when the vertical measuring range reaches 1.0 mm. The present findings indicate that the proposed technique is effective for 3-D microscale surface profilometry in in-situ semiconductor automated optical inspection (AOI).  
semiconductor; surface profilometry; moire projection; 3-D measurement; automated optical inspection (AOI) +
Footnote †: journal: Applied Physics Letters
# A Novel Inductor-Based Non-Dissipative Equalizer
## 2 Proposed Equalizer Scheme  
### Structure of the Proposed Equalizer  
The equalization circuit proposed in [11] is shown in Figure 3a. The proposed NIBNDE replaces the even-numbered inductors in [11] with MOSFETs, which can almost reduce half of the inductors. Because the volume of a MOSFET is much smaller than an inductor, the NIBNDE can greatly reduce the volume of the equalization circuit.  
As shown in Figure 3b, the number of batteries is assumed to be \(n\). If \(n\) is an even number, the equalizer consists of \(n/2\) inductors, \((n-2)/2\) bidirectional MOSFET switches and \(n\) MOSFET switches \(S_{1}-S_{n}\). The inductors \(L_{1},L_{3}-L_{n-1}\) have odd-numbered subscripts, while the bidirectional switches have even-numbered subscripts, which are respectively named \((S_{2u},\ S_{2b})-\left(S_{(n-2)a^{\prime}},S_{(n-2)b}\right)\).  
If \(n\) is an even number, the last set of series MOSFETs is replaced by an inductor to ensure the circuit can operate functionally. Therefore, the required elements are \((n+1)/2\) inductors, \((n-3)/2\) bidirectional MOSFET switches and \(n\) MOSFET switches \(S_{1}-S_{n}\).