esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Datasets** & \multicolumn{4}{c}{**Performance Measures**} \\ \hline \multirow{6}{*}{**RIM-ONE**} & [PERSON] et al. (2016) [19] & [PERSON] et al. (2019) [22] & [PERSON] et al. (2019) [6] & \multirow{2}{*}{**Proposed method**} \\ \cline{2-3} \cline{5-5}  & \multirow{2}{*}{ACC = 81.32\%} & Sen = 87.01\% & ACC = 71.21\% & E(P1) & E(P2) \\ \cline{3-5}  & & Spe = 89.01\% & AUC = 85.75\% & ACC = 97.37\% & ACC = 92.11\% \\ \cline{3-5}  & & AUC = 94\% & AUC = 100\% & AUC = 99.04\% \\ \hline \multirow{6}{*}{**DRISTI-GSI**} & [PERSON] et al. (2017) [15] & [PERSON] et al. (2017) [23] & [PERSON] et al. (2019) [6] & \multirow{2}{*}{**Proposed method**} \\ \cline{2-3}  & \multirow{2}{*}{ACC = 76.77\% AUC = 78\%} & [PERSON] et al. (2017) [23] & [PERSON] et al. (2019) [6] & & \\ \cline{3-5}  & & (2017) [23] & [PERSON] et al. (2019) [6] & & \\ \cline{3-5}  & & (2017) [23] & [PERSON] et al. (2019) [6] & & \\ \cline{3-5}  & & (2017) [23] & [PERSON] et al. (2019) [6] & & \\ \hline \multirow{6}{*}{**ORIGA**} & [PERSON] et al. (2018) [20] & [PERSON] et al. (2019) [21] & \multirow{2}{*}{**Proposed method**} \\ \cline{3-5}  & & (2019) [21] & & E(P1) & E(P2) \\ \cline{3-5}  & & (2019) [21] & & E(P1) & E(P2) \\ \cline{3-5}  & & (2019) [21] & & ACC = 83.10\% & ACC = 83.59\% & ACC = 80.00\% \\ \cline{3-5}  & & (2019) [6] & & AUC = 88.86\% & AUC = 85.26\% \\ \hline \multirow{6}{*}{**ACRIMA**} & [PERSON] et al. (2019) [6] & \multirow{2}{*}{**Proposed method**} \\ \cline{3-5}  & & (2019) [21] & & E(P2) \\ \cline{3-5}  & & (2019) [21] & & ACC = 99.53\% & ACC = 96.23\% \\ \cline{3-5}  & & (2019) [21] & & AUC = 99.01\% \\ \hline \multirow{6}{*}{**REFUGE**} & [PERSON] et al. (2020) [5] & \multirow{2}{*}{**Proposed method**} \\ \cline{3-5}  & & (2019) [21] & & E(P1) & E(P2) \\ \cline{3-5}  & & (2019) [21] & & ACC = 95.59\% & ACC = 95.75\% \\ \cline{3-5}  & & (2019) [21] & & AUC = 94.32\% \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Performance of the proposed methods for glaucoma classification. screening system for all possible eye disease such as diabetic retinopathy, glaucoma, myopia, age related macular degeneration, vascularization, etc., which can be examined using retinal images.
## 7 Conclusions  
In this study, an innovative SAR payload design was proposed and investigated for the development of a new space-based 80 kg class X-band SAR microsatellite. The major design approaches, i.e., a flat-panel-type SAR payload integrated with a bus payload, were verified using an SAR performance analysis based on mathematical models. The proposed novel SAR payload can be applied to flat-panel-type microsatellites for Earth observation, communication, and internet service missions.  
Additionally, a study proposed the detailed design of the SAR system and its units, which are compatible with an 80 kg class microsatellite, by focusing on the SAR payload subsystem level. If this microsatellite SAR is deployed for a typical Earth observation at an altitude of 510 km, its SAR image performance can successfully satisfy the S-STEP mission requirements. Moreover, the MBSE design results for the SAR payload were presented using the Capella MBSE open-source SW, which facilitated rapid adaptation of the varying or updating mission requirements, improvement of consistency, and improved analysis of the system.  
Although the proposed design of the S-STEP SAR payload fulfilled the aims and objectives of applying an SAR on a single microsatellite of 80 kg mass, several facets of this research are required to be explored through dedicated future research. The S-STEP SAR payload will be developed through gradual performance improvements. In the future, the characteristics of the flat-panel-type shape, such as OrigamiSAT of Oxford Space Systems, Inc., can be utilized to expand and develop the S-STEP SAR into an advanced and innovative satellite concept.  
Figure 31: Azimuth ambiguity ratio vs. incidence angle of each antenna beam in (**a**) high-resolution and (**b**) wide-swath modes. AAR was lower than the required level of \(-17\) dB at an incidence angle of \(25^{\circ}\).  
**Author Contributions:** Investigations: S.K., S.-H.L. and H.-U.O.; writing--original draft preparation: S.K.; writing--reviewing and editing: S.K.; Visualization: S.K. and C.-M.S.; Supervision: S.-C.S. and H.-U.O. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was supported by the Challengeable Future Defense Technology Research and Development Program (912777601-9127776-04) of Agency for Defense Development (ADD) in 2022.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Materials and Methods  
### Sample Inclusion Criteria  
All the measurements in this work were performed in two study groups: diabetic patients, diagnosed with type 2 diabetes mellitus, and healthy subjects. Measurements were taken following a protocol approved by the Ethics Committee of the hospital where the measurements were taken, and each participant signed an informed consent form.  
Electrical impedance and punctual temperature: a group of 25 diabetic patients from the National Institute of Rehabilitation and 8 healthy subjects were selected for performing these studies, in an age range of 25 to 85 years, the sample of diabetic patients is composed by 60% female and 40% male, 40.9% were overweight, 36.36% were obese and 100% of the sample suffered from different types of macules on the legs and feet. The study of the maculae was performed in 19 diabetic patients without diabetic foot and with a variety of macules, which were namely vascular macules, petechiae, macules due to trophic changes and macules due to trauma; this classification was carried out by clinical observation. Temperature, impedance and macule measurements were performed in the period from January to August 2016. A group of 90 patients from a private clinic in the State of Mexico were selected to carry out this infrared thermography study, in an age range of 30 to 75 years; 32% were diabetic patients, 26% were patients diagnosed with diabetic foot and 26% were healthy subjects. A total of 16% of the patients who attended the study had arterial problems. The measurements with this system were repeated at different times with the supervision of medical personnel, recording the results obtained. Environmental parameters were also established, such as a humidity of 34.7% and temperature of 20.3 \({}^{\circ}\)C, with 15 min of acclimatization, before starting to take the images. Infrared measurements were performed in the period from August to September 2022. To visibly show temperature variations in healthy subjects and diabetic patients, a comparison was made between 6 healthy subjects and 6 diabetic patients from our sample.
# Design of a Compact Planar Magnetic Levitation System with Wrench-Current Decoupling Enhancement
###### Abstract  
Magnetic levitation technology has promising applications in modern manufacturing, especially for fine-motion stage and long-range omnidirectional planar motors. This paper presents the development of a compact planar magley prototype with the potential to achieve both applications to increase flexibility for the manufacturing system. The planar stator is designed by using optimized square coils arranged in the zigzag configuration, which provides a better uniform magnetic flux density compared with another configuration. The stator is a compact and portable module with built-in current amplifier units. The single-disc magnet mover is deployed with five controllable degrees of freedom. The cross-coupling effect is decoupled by a precomputed Lorentz force based wrench-current transformation matrix stored in the lookup table. A 2-D linear interpolation is implemented to enhance decoupling effectiveness which is offered via discrete lookup data. Experiments with motion-tracking cameras and a basic controller demonstrate the results of fine step motion of 10 and 20 \(\upmu\)m and rotation steps of 0.5 and 1.0 mrad. The potential for multidirectional material handling is represented by a total horizontal translation range of 20 mm by 20 mm with a maximum air gap of 26 mm and a total rotation range of 20 degrees for both roll and pitch.  
magnetic levitation; electromagnetic actuator; compact design; decoupling enhancement; interpolation; five degrees of freedom
# Numerical Analysis of the Cooling Performance in a 7.2 kW Integrated Bidirectional OBC/LDC Module
## 2 Development of the Numerical Model
### Numerical Procedures  
A numerical analysis was conducted using the above governing equations and boundary conditions together with the ANSYS Fluent 19.2 software package. During the analysis, the internal temperature variation over time and the internal temperature changes in each operating mode were assessed. Specifically, the cooling performance based on the size of the heat source in each mode was monitored and evaluated relative to the maximum temperature of each device. The convergence criterion for solving the continuity, momentum, and energy equations was 10.6. To evaluate the grid dependency, an analysis was conducted for grid sizes from 4,480,000 to 10,230,000, and it was determined that stable results could be achieved at a grid size of 7,840,000.
## 3 Problem Description
### Definition of Multi-Objective Parallel Machine Scheduling Problem  
In this section, we describe the multi-objective unrelated parallel machine scheduling problem. The objectives of this problem are to determine the assignment of jobs to some machines and the job processing order. This problem is subject to three constraints. The unrelated parallel machine scheduling problem has no specific restrictions on the processing time of each job. Additionally, the processing speed of each machine is different. It is more general than related parallel machine scheduling problems that the processing speed of each machine is the same.  
The following three constraints are given:  
* There is no idle time set for each machine.
* One machine can only handle one job at a time.
* Each job cannot be interrupted during processing. No preemption is allowed.  
In the scheduling problem, the obtained schedules are different depending on the objective function.
## 2 Doubly-Fed Induction Generator
With regard to (7), the rotor side electrical circuit is modelled by a three-phase voltage source of \(\overset{\rightarrow}{v}_{ro}^{r}\), the rotor resistance (\(R_{r}\)), and the transient inductance (\(\sigma L_{r}\)) during the fault condition. The level of rotor transient over-current will be changed with regard to the fault instant, the type of fault, and the voltage sag depth [14]. For instance, during a symmetrical grid fault, the open circuit rotor voltage (\(\overrightarrow{v}_{ro}^{r}\)) includes two expressions as follows:  
\[\overset{\rightarrow}{v}_{ro}^{r}=(1-p)V_{s}\frac{L_{m}}{L_{s}}se^{js\omega _{s}t}-\frac{L_{m}}{L_{s}}\left(\frac{1}{\tau_{s}}+j\omega_{r}\right)\frac{pV _{s}}{j\omega_{s}}e^{-j\omega_{s}t}e^{\frac{-t}{\tau_{s}}} \tag{8}\]  
whereby the pre-fault stator voltage magnitude, the voltage sag depth, and the slip are represented by \(V_{s}\), \(p\), and \(s\) during the symmetrical grid fault, respectively. Also, \(\tau_{s}\) decaying time constant is equal to \(L_{s}/R_{s}\). The schematic of control circuits for the rotor side converter and the grid side converter are presented in Figure 3B [15]. In both control systems, proportional-integral (PI) controllers are employed for regulation. In the rotor side converter, the reference active power (\(P_{\textit{ref}}\)) is computed in respect to maximum power point tracking and then the extracted active power (\(P_{\textit{extract}}\)), which depends on the wind speed, is compared to \(P_{\textit{ref}}\). Consequently, the \(d\)-axis reference current of the rotor is achieved. Meanwhile, the reference value for the reactive power of the stator (\(Q_{\textit{s-ref}}\)) is considered zero. Therefore, during the normal operation, the absorbed reactive power (\(Q_{s}\)) from the stator side of the DFIG will be equal to the reference value, and the required reactive power for the DFIG will be covered by the back-to-back converters. To maintain the DC-link voltage in constant value, the grid side converter provides the active power to the rotor side. Therefore, the \(d\)-axis reference current is obtained by comparing the DC-link voltage with the reference value (\(V_{DC-\textit{ref}}\)). Meanwhile, the reactive power (\(Q\)) in the GSC and the RSC is adjusted by the reference value of \(Q_{\textit{ref}}\).
## 4 Numerical Simulation of the Formation Effect of Grout Curtain in Ore-Rock Contact Zone
### Group-Hole Grouting Curtain Body Formation Effect
#### 4.3.3 Changes in Curtain Morphology for Different Cross-Sections  
Figures 12-14 illustrate the variations in the shape of the curtain body's cross-section at different positions. During the construction of the first sequence of holes, it is evident that the slurry spread at the working face will gradually form an almost elliptical stone body. Additionally, the slurry can also have a cementing effect on the two groups of rocks surrounding the base plate. However, at the end of the curtain body, due to the wide spacing of the grouting holes, only a small portion of the slurry spread will come into contact with the slurry from the adjacent grouting holes. As a result, a complete stone body fails to form, leading to poor grouting effectiveness. Upon construction of the second series of holes, it was observed that the spreading of the slurry both at the working face and at the end encountered the same issue. During the construction of the third sequence hole, it was observed that after the first two processes, the grouting holes were closely arranged at the working face. This resulted in the formation of a more complete curtain body. The grouting carried out by the two gangs also reinforced the top and bottom plates by filling the pores created during the first two construction processes. This further led to the formation of a complete and nearly rounded nodular body. The diagram in Figure 14c shows that the slurry diffusion at the two gangs forms a curtain that connects the top plate and the base plate. However, due to the disadvantage of insufficient slurry diffusion in the first two sequences of grouting holes with large spacing, a complete nodular body fails to form. Therefore, improvement measures need to be implemented in the subsequent stages to ensure that the bottom of the grouting holes forms a complete and dense curtain body, which will effectively plug water and provide waterproofing.  
Figure 11: The diffusion pattern of grouting slurry in multi-hole injection. (**a**) First sequence hole grouting; (**b**) Second sequence hole grouting; (**c**) Third sequence hole grouting.
# Information Fusion for Multi-Source Material Data: Progress and Challenges
## 3 Progress of Information Fusion for Multi-Source Material Data
### Unified Representation of Material Data  
The unified representation of material data is important to the integration of computational data, experimental data, test data, characterization data and service data in material science. Taking aluminum-based composite as an example, the whole process of processing, warehousing, database establishment and database storage is very important, and there are existing techniques of building an aluminum-based composite database platform that can be used continuously [19]. The machine-learning model of material data was applied to the qualitative and quantitative modeling of the full chain data of high-performance aluminum matrix composites. The service data of the aluminum matrix composite is added to the database, along with the simulation data. Descriptions of heterogeneous material data often use the predictive nonlinear multiscale model theory [2]. That is, the material data is normalized by constructing a multi-scale, multi-level data model. At present, the conceptual model is mainly used to describe the physical properties and the processing of material data [20]. Multi-source heterogeneous data is described with uniform tokens and views, all of which is described by a unified conceptual model.  
In order to cope with the complex characteristics of material data, several existing technologies in NoSQL databases [21] can be adopted to build a database platform for material data. These technologies include document databases, key-value databases, column databases, and graph databases. The document-oriented databases represented by MongoDB and CouchDB are mainly designed to store, acquire and manage the document-based data. The minimum unit of data storage in document databases is the document. The document attributes stored in the same table can be different. The data can be stored in various formats such as JSON and XML. The key-value storage databases represented by Redis and BerkeleyDB provide efficient storage for key-value pairs. They can efficiently retrieve values for a given key. The column databases represented by HBase store data by column family. The column databases offer the convenience of storing structured and semi-structured data, facilitating data compression, and reducing I/O (Input and Output) costs for queries toward certain columns. The graph databases represented by Neo4] and FlockDB are convenient to store graph-based relations among material data. The graph data structure is also helpful to construct knowledge graphs over integrated material data. In addition to the above NoSQL database technologies, in real applications it is also possible to use a variety of databases to store material data, resulting in a hybrid database that can store different types of material data.
# Traffic Aware Scheduler for Time-Slotted Channel-Hopping-Based IPv6 Wireless Sensor Networks
## 2 Background
### Tsch  
Frequently used MAC methods are time division multiple access (TDMA), random access protocols, or a combination of both. One of the most used random access protocols is carrier sense multiple access (CSMA). Nodes listen to the channel before transmitting. The back-off mechanism of CSMA is used in case more than one node tries to transmit at the same time. In TDMA, the nodes access a medium only in their allotted cell. Clocks of devices drift, and thus nodes need to periodically synchronize.  
TSCH is gaining popularity as a time-slotted MAC layer protocol. TSCH introduces multi-channel access to increase bandwidth, and channel hopping mechanism to tackle external interference and multipath effects. TSCH is responsible for granting access to the medium. It does so by organizing the medium in cells that are grouped in slotframes. These slotframes repeat periodically. A slotframe cell has as coordinates the time offset and channel offset. The absolute slot number (ASN) counts how many cells have passed since the start of the network, and a node uses it, together with the channel offset, for channel selection [6]. TSCH uses special control packets called enhanced beacons (EBs) to ensure that each node has its clock synchronized to the time source.  
Figure 1: Example of routing table created by the IPv6 routing protocol for low-power and lossy networks (RPL) in storing mode for node 3.
## 4 Results and Discussion
### Classification Threshold Adjustment  
Two popular evaluation metrics to estimate the model performance, accuracy, and AUC are for QCNN and QMLP models above 97%, indicating good performance. Following the procedure described in Section 3.4.2, for QCNN, the largest J statistic (0.947) is achieved using a threshold value of 0.939913, and for QMLP, the maximum J value (0.944) is for a threshold of 0.851953. However, this threshold value selection resulted in better FPR results but increased FNR value for both models, as seen in Table 8.  
On the other side, with the trial and error approach, using a threshold value of 0.1, FNR decreases to 0.02 for QCNN and to 0.03 for QMLP. Although the differences in achieved FNR are not high, it is important to remember that the volume of the data set on which the  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Model** & **acc** & **prec** & **rec** & **f1** & **AUC** & **fpr** & **fnr** \\ \hline QCNN & **0.9737** & **0.9790** & **0.9681** & **0.9736** & **0.9875** & **0.0207** & **0.0319** \\ QMLP & 0.9713 & 0.9782 & 0.9641 & 0.9711 & 0.9812 & 0.0215 & 0.0359 \\ \hline \hline \end{tabular}
\end{table}
Table 6: The results for the 2-bit quantized CNN and MLP models.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Settings** & **acc** & **prec** & **rec** & **f1** & **AUC** & **fpr** & **fnr** \\ \hline default & 0.9693 & 0.9731 & **0.9652** & 0.9691 & 0.9693 & 0.0267 & **0.0348** \\ optimized & **0.9694** & **0.9735** & **0.9652** & **0.9693** & **0.9694** & **0.0263** & **0.0348** \\ \hline \hline \end{tabular}
\end{table}
Table 7: The results of random forest classifier.  
model is intended to be used is very high, and even small differences in percent result in high absolute values. For example, for QCNN, the difference between the best achieved FNR and FNR obtained for the default threshold is 0.0119 (1.19%). Applied to a data set with just 1,000,000 samples, it ends with 11,900 additionally recognized EM clusters, and any of them could have a significant role in some new physical discovery. A comparison of results obtained using different thresholds is given in Table 8.  
Even though the obtained FNR (3.19% for QCNN and 3.59% for QMLP) and FPR (2.07% for QCNN and 2.15% for QMLP) are not high for the base quantized models with default threshold, using the thresholding technique they can be further optimized. It should be noted that the number of FPs increases by changing the threshold to decrease the FNs.  
It can be noticed there is no big difference in moving the threshold based on J-statistics or looking for minimization of FPR and FNR difference, but depending on needs, it is clear that it is possible to optimize targeted costs by choosing the appropriate threshold.