esa-sceva/satcom-chunk-collection huggingface dataset:
# Computation of Optimized Electrode Arrays for 3-D Electrical Resistivity Tomography Surveys
###### Abstract  
The present study explores the applicability and effectiveness of an optimization technique applied to electrical resistivity tomography data. The procedure is based on the Jacobian matrix, where the most sensitive measurements are selected from a comprehensive data set to enhance the least resolvable parameters of the reconstructed model. Two existing inversion programs in two and three dimensions are modified to incorporate this new approach. Both of them are selecting the optimum data from an initial comprehensive data set which is comprised of merged conventional arrays. With the two-dimensional (2-D) optimization approach, the most sensitive measurements are selected from a 2-D survey profile and then a clone of the resulting optimum profile reproduces a three-dimensional (3-D) optimum data set composed of equally spaced parallel lines. In a different approach, with the 3-D optimization technique, the optimum data are selected from a 3-D data set of equally spaced individual parallel lines. Both approaches are compared with [PERSON]'s optimization technique which is based on the resolution matrix. The Jacobian optimization approach has the advantage of selecting the optimum data set without the need for the solution of the inversion problem since the Jacobian matrix is calculated as part of the forward resistivity problem, thus being faster from previous published approached based on the calculation of the sensitivity matrix. Synthetic 3-D data based on the extension of previous published works for the 2-D optimization case and field data from two case studies in Greece are tested, thus verifying the validity of the present study, where fewer measurements from the initial data set (about 15-50%) are able to reconstruct a model similar with the one produced from the original comprehensive data set.  
Keywords:ERT; optimization; Jacobian; 3-D +
Footnote †: journal: Applied Sciences
# GNSS Based Low-Cost Magnetometer Calibration
## 3 Experimental Verification  
### Data Acquisition Module  
We needed data for experimental verification. We developed a device for logging data from multiple sensors. The data acquisition unit used the MPU 9250 module for experimental measurements, which combines a three-axis _MEMS_ gyroscope, a three-axis MEMS accelerometer, and a three-axis magnetometer. The built-in magnetometer, according to the MPU-9250 datasheet [23]: is a \"3-axis silicon monolithic Hall-effect magnetic sensor with magnetic concentrator with an output data resolution of 14 bit (0.6 \(\mu\)T/LSB) and 8 Hz repetition rate\". The GNSS receiver used: Ublux Neo 6P supporting GPS and SBAS: EGNOS (with the capability of other SBAS services which are not suitable for use in the central European area) with velocity accuracy: 0.1 m/s and heading accuracy: 0.5\({}^{\circ}\)[24]. The data are stored in the module memory, and after the drive, they are downloaded for processing. The module contains an ESP32 microcontroller, thanks to which it can be connected to a Wi-Fi network, then the module may send the measured data to an FTP server. The module has the option of connecting an OGN (Open Glider Network) transmitter for usage in small aircraft. The data acquisition unit is shown in Figure 3. The module was placed on the dashboard of a passenger car.  
Figure 3: Data acquisition unit.
## 3 Results and Discussion  
The ASIC was manufactured, glued, and bonded to a prototype 4-chip hybrid, as shown in Figure 9. Although the figure shows the SALT already bonded to the silicon sensor, the first measurements were performed without it. Similar results were obtained for several chips, so the paper presents only the results for a representative one. Although these results verify the performance of the chip, they are not sufficient to qualify a complete detector system. Detailed measurements of the complete detector setup quantifying chip parameters on different hybrids will be presented in future publications.  
The test setup, as shown in Figure 10, partially mimics the expected readout in the LHCb experiment by using the final hybrid together with adapter boards acting as substitutes for the final detector parts. The hybrid, made in Flexible Printed Circuit Board (FPCB) technology with a ceramic stiffener, is connected to a Versatile Link Demo Board (VLDB) [38], through a passive interconnect adapter, which supports the hybrid mechanically and accounts for connectors and pinout differences. The VLDB delivers clock, TFC commands, I\({}^{2}\)C, receives data via e-links, and communicates through optical links with the next component in the test chain, the MiniDAQ [39]. The VLDB encompasses the elements chosen to be a common communication platform for the new generation of readouts for several LHC experiments. It was developed in cooperation of many groups focused around LHC to improve and standardise the testing of readout ASICs. On the contrary, the MiniDAQ is specific merely to LHCb experiment. It emulates the planned DAQ system on a small scale, integrating all of the key components packed inside a single Field-Programmable Gate Array (FPGA) [39]. The VLDB, and consequently the hybrid, are then connected to an Agilent Technologies N6705B DC Power Analyzer to monitor the current draw of the SALT and its correct behaviour depending on the registers' configuration. The high speed SLVS signals, together with the I\({}^{2}\)C, are monitored at multiple points along the readout via an SDA80 SZi-A 8 GHz Serial Data Analyzer to ensure the required signal integrity and bit-error rate (BER) are achieved. The overall setup is then positioned in a humidity, temperature, and particulate controlled clean room to guarantee consistency between different measurement sessions. All the tests described in this article were conducted in a standard temperature environment and then validated at the lower temperatures at which SALT is expected to operate.  
Figure 9: SALT mounted on the hybrid and connected to the sensor.
## 1 Introduction
However, the non-uniform bulk material distribution has been rarely considered for optimal speed control. In the previous study [48], we presented a noncontact measurement system and a bulk material flow calculation method using laser scanning technology. It could contribute to establishing a mechanical model of a loaded belt based on more accurate bulk material flow data. Considering the previous discussion, the main purpose of this paper is to propose a high-precision dynamic model intended to determine the dynamic characteristics of a conveyor belt under non-uniform bulk material distribution. In addition, a method for measuring the actual bulk material distribution using laser scanning technology is presented. In this paper, an experimental facility for bulk material distribution measurement based on laser scanning technology is designed and constructed firstly. After acquiring the bulk material cross-sections in real-time, a non-uniform bulk material distribution model is proposed. Due to the bulk material on the conveyor belt is discretized into a series of micro-units, this distribution model can describe the actual load distribution on a conveyor belt. Based on this, a high-precision longitudinal dynamic model to investigate the dynamic behavior of a belt conveyor is investigated. We represent the experimental verification results for the non-uniform bulk material distribution model and establish the discrete simulation model of the belt conveyor system using MATLAB software. Then, we present a simulation test on the different belt tensions, accelerations and tensioning device displacements at the head and tail of the belt conveyor system. The discussion on the influence of the non-uniform bulk material distribution and starting time on the dynamic characteristics of the belt conveyor is proposed,which contribute to the establishment of speed control constraints for developing a control strategy for practical application. The layout of the rest of the paper is as follows: Section 2 introduces the laser scanner on-line measurement system and describes the theoretical determination of the non-uniform bulk material distribution on the conveyor belt with the data collected by the laser scanner online measurement system, and then formulates an improved mathematical model considering the non-uniform bulk material distribution to determine the dynamic characteristics of the conveyor belt in Section 3. Section 4 presents the numerical simulation study of a belt conveyor dynamic behavior with non-uniform bulk material distribution, and Section 5 discusses the results. Section 6 concludes the paper.
## 5 Conclusions
Compare the schemes after and before optimization; the maximum angle variation induced by temperature change dropped from 117.74\" to 10.72\" through the ground temperature deviation and prism calibration test by heating the satellite temperature hauled up under the ambient temperature of 20 \({}^{\circ}\)C in the ground atmosphere backdrop. Under the condition of maximum temperature pull-up, the maximum angle variation is 0.1532 mrad, close to the requirement of 0.16 mrad, which further proves the effectiveness of the optimized design. The on-orbit alignment test confirms that the required capture time of 30 s is met. After launch, by 27 July, 14 bidirectional captures had been completed after the first chain establishment, with 10 of those taking place in under 30 s (71.4%). The four capture times that were longer than 30 s all occurred early in the test, and after the test's full completion on 23 July all capture times were within the required range of 30 s. The in-orbit acquisition time test results demonstrate that the uncertain region of the satellite satisfies the design specifications and that the thermal deformation stability between the satellite star sensor and laser communication load satisfies the specifications. Conceptualization, Y.S. and S.C.; methodology, Y.S. and Y.W. ; software, Y.S. and M.Y. ; validation, Y.S. ; torsional analysis, Y.S. ; investigation, Y.S. ; resources, S.C.; data curation, Y.S. and M.Y. ; writing--original draft preparation, Y.S. ; writing--review and editing, S.C. and J.Y. ; visualization, Y.S. ; supervision, S.C. and L.Z. ; project administration, L.Z. ; funding acquisition, L.Z. All authors have read and agreed to the published version of the manuscript. This research was funded by the Jilin Province Science and Technology Development Plan Project of China, Grant No.20210509052 RQ. Not applicable. The authors declare no conflict of interest.
# NESO-Based Path Following Control for
## 2 Preliminaries and Problem Formulation  
### Preliminaries  
In this subsection, some definitions and lemmas are presented to facilitate the analysis and design of control strategies for underactuated hovercrafts.  
**Definition 1**.: _(Definition 2.1 in [12]) A function \(V:\Re^{n}\to\Re\) is called homogeneous of degree \(\gamma\) with respect to weight \(\alpha_{i}>0(i=1,\cdots,n)\) such that_  
\[V(\chi^{\alpha_{1}}x_{1},\chi^{\alpha_{2}}x_{2},\cdots,\chi^{\alpha_{n}}x_{n} )=\chi^{\gamma}V(x_{1},x_{2},\cdots,x_{n}) \tag{1}\]  
_for \(\chi>0\) and all \((x_{1},x_{2},\cdots,x_{n})\in\Re^{n}\)._  
**Remark 1**.: _If the function \(V\) is differentiable with respect to \(x_{n}\) and satisfies Definition 1, then the partial derivative of \(V\) respect to \(x_{n}\) such that_  
\[\chi^{\alpha_{n}}\frac{\partial}{\partial x_{n}}V(\chi^{\alpha_{1}}x_{1},\chi ^{\alpha_{2}}x_{2},\cdots,\chi^{\alpha_{n}}x_{n})=\chi^{\gamma}\frac{\partial }{\partial x_{n}}V(x_{1},x_{2},\cdots,x_{n}) \tag{2}\]  
**Definition 2**.: _(Definition 2.1 in [12]) A vector field \(G:\mathbb{R}^{n}\rightarrow\mathbb{R}^{n}\) is said to be homogeneous of degree \(\gamma\) with respect to weight \(\alpha_{i}>0(i=1,\cdots,n)\) such that_  
\[G_{i}(\chi^{\alpha_{1}}x_{1},\chi^{\alpha_{2}}x_{2},\cdots,\chi^{\alpha_{n}}x_ {n})=\chi^{\gamma+\alpha_{i}}G_{i}(x_{1},x_{2},\cdots,x_{n}) \tag{3}\]  
_for all \((x_{1},x_{2},\cdots,x_{n})\in\mathbb{R}^{n}\) and \(\chi>0\), where \(G_{i}\) represents the \(i\)-th component of \(G\)._  
**Lemma 1**.: _(Theorem 2 in [27]) If \(f\) is a homogeneous function satisfies \(f\in C(\mathbb{R}^{n},\mathbb{R}^{n})\), initial state \(f(0)=0\) and the equilibrium point \(x=0\) of system \(\dot{x}=f(x)\) is locally asymptotically stable. Let \(k\) be a real number and \(p\) be a positive integer such that \(k>p\cdot\max\{\alpha_{i}(i=1,2,\cdots,n)\}\), then there exists a function \(V:\mathbb{R}^{n}\rightarrow\mathbb{R}\) such that (1) \(V\in C^{p}(\mathbb{R}^{n},\mathbb{R})\cap C^{\infty}(\mathbb{R}\backslash \{0\},\mathbb{R})\), (2) \(V(0)=0\), \(V(x)>0\) for all \(x\
eq 0\) and \(V(x)\rightarrow+\infty\) as \(\|x\|\rightarrow+\infty\), (3) \(V\) is homogeneous, (4) \(\
abla V(x)f(x)<0\), for \(\forall x\
eq 0\)._  
**Lemma 2**.: _(Lemma 4.2 in [28]) Let \(V(x)\) and \(W(x)\) be continuous real-valued function on \(\mathbb{R}^{n}\) and homogeneous with respect to \(\gamma\) of degree \(h_{1}>0\) and \(h_{2}>0\), respectively, and \(V\) is positive definite. Then, for every \(x\in\mathbb{R}^{n}\) such that_  
\[\min\{W(s)\}_{|s:W(s)=1}[V(x)]^{\frac{h_{2}}{h_{1}}}\leq W(x)\leq\max\{W(s)\}_ {|s:W(s)=1}[V(x)]^{\frac{h_{2}}{h_{1}}} \tag{4}\]  
**Lemma 3**.: _(Lemma 4.2 in [29]) Let the system \(\dot{x}=f(x)\) and the equilibrium point \(x=0\), a continuous positive, radially unbounded function \(V:\mathbb{R}^{n}\rightarrow\mathbb{R}\) such that \(\dot{V}(x)<0\), \(\forall x\
eq 0\), then the equilibrium point \(x=0\) is globally asymptotically stable._
## 2 Materials and Methods
### Choice of Models  
We have chosen RF, SVM and ANN as the basic models for our comparison, each with different underlying principles. SVMs, as linear models, define a boundary through linear algebra, while RFs, as ensemble learning models, generate multiple decision trees during training and combine these decisions to make predictions, providing valuable insight into the origins of their output. On the other hand, ANNs, due to their non-linear nature, are able to capture intricate relationships between data points, potentially offering superior performance in dealing with the inherently ill-posed and non-linear problem of identifying conductive enclosures, particularly tumours in our context. Detailed explanations of these models are given in the following sections.  
Figure 3: Visualization of the glandular tissue structure with a tumor visible in yellow.
## 4 Implementation
### Server Side
#### 4.3.3 Model Performance  
To evaluate the inference performance of our model with different threshold levels, we calculated the precision, recall and F1 score for each object class in the image: bus, car and truck. Then we also calculated the mean average precision (mAP) for different threshold levels. Table 3 presents those calculation results.  
Figure 9: Inference speed based on RPN score thresholds and DSSIM thresholds.  
As shown in Table 3, the precision, recall, F1 score, and mAP values decreased as the higher DSSIM threshold was applied. These results were obtained using a Faster R-CNN model provided by TorchVision 0.22 (accessed on 29 December 2024) [25], establishing a performance baseline against which we can demonstrate the enhancements achieved through our object-clarification method described in the following sections. When the threshold was greater than 0.3, the F1 scores for three object classes appeared quite different to one another. Especially the recall and F1 score of 'car' class was affected more than those of bus and truck classes as the threshold increased. We can analyze that it is because the strong filtering with high threshold values damaged some of each object area in the image and the smaller class, such as car, was suffered more than the other classes.
## 3 Results
### Organization of the WBCT Workflow: Proposal for a Classification of Recent Innovations  
A critical analysis of the 50 studies included enabled the authors to classify recent innovative techniques brought about by WBCT in the foot and ankle into categories. These categories are based on the nature of the innovations and on their positioning within the patient or image processing workflows. Some of these are identified in italic fonts below as hypotheses from the authors, based on the literature that was excluded from this specific work because it did not directly apply to our object, but which could in theory be applied to the foot and ankle field. For clarity, we included these in the classification, as well as pre-processing techniques in the initial exhaustive screening of the literature summarized and referenced hereunder.  
* Techniques for image acquisition
* Dynamic/augmented stress techniques
* Ankle instability
* Shod auto-varus [43]
* Angled jigs/wedges [43]
* Syndesmotic instability
* Torque stress
* Coleman block test [19]
* Static techniques
* Combination with pedagraphy [44]
* Computerized techniques for image processing
* Pre-processing (processing of the raw data before image rendering)
* _Metal artifact reduction_
* _Movement Artifact reduction_  
* 3D biometric techniques without segmentation
* Linear HU assessment of joint space width [25]
* Middle subtalar facet uncoverage [45]  
* Foot-ankle offset [19; 44; 46; 47; 48]
* Segmentation techniques
* Statistical shape modelling (SSM) [49]
* Mimics (materialization) [27; 50; 51]
* CurvebeamAI [52]
* Disior/Paragon [16; 53; 54; 26; 55; 56]
* Advanced techniques issued from segmentation (semi-automatic or fully automatic)
* 3D bone absolute and relative relationships reporting [16; 52; 53; 54; 21; 22; 26; 55; 56; 57; 58; 59; 60; 61; 62; 63; 64]
* 3D Joint space width (3D-JSW) mapping: distance mapping [65; 66; 67; 68; 69]
* Coverage mapping [70]
* Surface measurements
* Syndesmosis [17]
* Lisfranc [71]
* Volumetric measurements
* Syndesmosis [49; 72; 73; 74]
* Lisfranc [71]
* Center of rotation assessment [75]
* Advanced clinical applications derived from computerized techniques
* Customized/patient specific surgical jigs [76]
* Supra malleolar osteotomy [18]
* Total ankle replacement [77]
* _Robotic surgical protocols_
* Personalized risk assessment [47]  
Following this exhaustive screening of the literature, the authors proposed a systematic classification of the WBCT computerized workflow to illustrate the role of each advanced technique associated with its development (Figure 4).  
Figure 4: Proposed simplified classification of WBCT advanced technique workflow.
## 4 Simulation Study on Strata Movement Characteristics in UCG
### Simulation Results
#### 4.2.3 Vertical Stress Distribution of Surrounding Rock in Combustion Cavity  
As shown in Figure 6, the vertical stress distribution pattern inside the strata is similar under different conditions. The farther away from the combustion cavity, the smaller the stress is until the original rock stress is restored. In the vertical direction, the closer to the combustion cavity, the smaller the vertical stress is. Moreover, the farther away from the combustion cavity, the greater the stress is until the original rock stress is restored. However, the extreme stress varies greatly under different conditions, with a maximum value of \(-\)13.8 MPa when the surrounding rock is subjected to both thermal stress and coal-rock burnt, the same stress when the rock is subjected to high-temperature burnt only, a minimum value of \(-\)10.9 MPa when there is no thermal effect, and a slight increase in vertical stress of \(-\)11.5 MPa when the surrounding rock is subjected to thermal stress only. From the above analysis, both the high-temperature thermal stress and surrounding rock burnt affect the redistribution of stresses within the combustion cavity. However, the coal-rock burnt has the most significant effect, whereas thermal stress has a smaller effect.  
From the numerical simulation results, the main controlling factor that changes the movement and deformation characteristics of the UCG combustion cavity surrounding rocks is the change in the physical and mechanical properties of the coal-rock caused by the high-temperature burnt. Moreover, the high-temperature thermal stress generated in the underground gasification process has less influence on the rock movement and overburden deformation.  
Figure 5: Displacements of rock strata in various conditions (m). (**a**) norm mining. (**b**) thermal stress. (**c**) rock burnt. (**d**) synergistic effect.
## 3 DT Technologies
### Cloud Computing  
Cloud computing is a technology that enables the delivery of hosted services via the internet, providing an efficient means of storing, managing, and accessing data [19]. This modern approach to computing offers various benefits, such as data computing and cloud data storage technology, which are particularly useful for applications like Digital Twin (DT).  
DT, known for its ability to handle substantial volumes of data, greatly benefits from cloud computing. The integration of cloud computing with DT technology allows for the storage of massive amounts of data in a virtual cloud environment. This not only leads to a significant reduction in computation time but also facilitates easy access to crucial information from any location [25].  
Beyond just processing vast volumes of data generated by the Internet of Things (IoT), cloud computing enables real-time analytics and new knowledge discovery. This computational power enhances decision-making processes and allows for immediate action based on the data insights. By leveraging cloud computing, DT can effortlessly store, process, and analyze data, making the technology more efficient, scalable, and versatile. This seamless integration between DT and cloud computing paves the way for improved data management, increased reliability, and better overall performance. As a result, organizations can optimize their operations and make more informed decisions thanks to the powerful combination of these two groundbreaking technologies [26].  
[PERSON] et al. explore the promising advantages of implementing Digital Twin (DT) concepts in healthcare, presenting a case study on CloudDTH, a cloud-based framework designed for the healthcare sector. This framework is particularly geared toward aiding the self-management of elderly individuals. CloudDTH not only provides real-time monitoring capabilities but also facilitates personalized healthcare interventions [27]. In summary, cloud-based DTs have immense potential to support real-time monitoring and personalized healthcare, making them invaluable tools in modern healthcare systems.
# Improved Retinex-Theory-Based Low-Light Image Enhancement Algorithm
###### Abstract  
Researchers working on image processing have had a hard time handling low-light images due to their low contrast, noise, and brightness. This paper presents an improved method that uses the Retinex theory to enhance low-light images, with a network model mainly composed of a Decom-Net and an Enhance-Net. Residual connectivity is fully utilized in both the Decom-Net and Enhance-Net to reduce the possible loss of image details. Additionally, Enhance-Net introduces a positional pixel attention mechanism that directly incorporates the global information of the image. Specifically, Decom-Net serves to decompose the low-light image into illumination and reflection maps, and Enhance-Net serves to increase the brightness of the illumination map. Finally, via adaptive image fusion, the reflectance map and the enhanced illuminance map are fused to obtain the final enhanced image. Experiments show better results in terms of both subjective visual aspects and objective evaluation indicators. Compared to RetinexNet, the proposed method shows improvements in the full-reference evaluation metrics, including a 4.6% improvement in PSNR, a 1.8% improvement in SSIM, and a 10.8% improvement in LPIPS. Additionally, it achieved an average improvement of 17.3% in the no-reference evaluation metric NIQE.  
image processing; low-light image enhancement; Retinex theory; low/normal-light image