esa-sceva/satcom-chunk-collection huggingface dataset:
# Enhanced Joint and Separable Reversible Data Hiding in Encrypted Images with High Payload
## 1 Introduction
In addition, we consider the actual value of pixels in preference to an estimated value, and exploit the absolute difference between neighboring pixels, rather than prediction error, to calculate fluctuation for both joint and separable method. By avoiding block division and prediction error, we fully use the spatial correlation property of a natural image, which helps to reduce the bit error rate (BER). For this reason, performance of the proposed system is superior to the performance of other systems. Additionally, before hiding the data, we encrypt the information bits to further increase the security of the system. The rest of this paper is organized as follows. Related work is described in Section 2. Then, the proposed joint and separable data hiding systems are discussed in Sections 3 and 4, respectively. After that, the experimental results are presented in Section 5. Finally, the conclusion is in Section 6.
# Tightly-Coupled Data Compression for Efficient Face Alignment
## 5 Results
### The Choice of \(Q\)  
In this section, the face alignment accuracy was evaluated according to the average distance between the detected landmarks and the ground truth, normalized by the inter-ocular distance as proposed in [46]. The number of bits used for each element in \(\mathbf{AQ}_{d}\) was varied and their corresponding normalized mean error loss against standard SDM algorithm [6] was calculated. Figure 7 shows the result.  
From the above figure it can be concluded that if each element in \(\mathbf{AQ}_{d}\) used more than 6 bits, the loss was small and reduced smoothly. However, if each element was represented with less than 6 bits, the error loss increased rapidly. In this paper we chose 6 bits, considering the balance between the error loss and compression efficiency. This means \(Q=2^{6}=64\).  
In this paper, HoG features were utilized and 68 feature points were detected. The number of regression steps was 6. The dimensions of \(\mathbf{AQ}_{d}\) and \(\mathbf{A}_{d}\) were both 136 \(\times\) 27,200, as mentioned before. The dimension of bias vector \(\mathbf{b}_{d}\) was 136. For standard SDM, all the elements were represented by 32-bit single precision floating point numbers. Therefore, the total space needed for the training model was  
\[(136\times 27,200+136)\times 4\times 6=88,784,064\text{~{}Bytes}\]  
With our proposed method, we needed to store 64 single precision floating point numbers for quantized values, 136 \(\times\) 27,200 6-bit matrix \(\mathbf{AQ}_{d}\) and 136-dimensional single precision floating point vector \(\mathbf{b}_{d}\) for each regression step. Therefore, our storage consumption for the whole training data was  
\[(64\times 4+136\times 27,200\times 6/8+136\times 4)\times 6=16,651,200\text{~{}Bytes}\]  
Our model size was only about 18.75% of the standard one, which means the compression rate of our proposed method was about 5.3X. Furthermore, when entropy coding [25] was applied to our proposed compressed data, about 10% more compression power was usually obtained.  
Figure 7: Normalized mean error loss against the standard SDM.
# Coverage and Rate Analysis for Location-Aware Cross-Tier Cooperation in Two-Tier HetNets
## 1 Introduction
### Related Work
The non-uniform deployment of small cells is caused by the fact that the coverage area of a small cell in the vicinity of the MBS shrinks, resulting in a poor offloading effect from its MBS [14], which was not considered in [23]. To further investigate this non-uniform small-cell deployment model, the authors in [33] analyzed load balancing (i.e., CRE) and its effect on the network. In [34], the authors also derived the coverage probability and rate coverage of a typical user in non-uniform HetNets. It is shown in [14; 32] that the coverage and capacity of the network will be improved when the small cells are kept apart from MBSs. However, these works did not jointly discuss load balancing and CoMP transmission to tackle the excessive cross-tier interference suffered by offloaded users.
# Spoofing Traction Strategy Based on the Generation of Traction Code
## 5 Conclusions  
The correlation peak superposition of conventional strategies rendersthe observations of the receiver unstable. The receiver only needs to perform mathematical statistics on the observations of the receiver to detect spoofing, such as TOA and power detection. Weassumed that we can design spoofing that can form an optimal correlation peak at the receiver to avoid the instability of the received results.  
From the analysis of the desired ideal correlation peak, we determined that pseudo-code used in modulation could be replaced by a traction code, and this traction code was derived. The simulation and experimental results proved the feasibility of the traction code. Compared to conventional traction strategies, the proposed strategy has the following advantages:  
1. The change in the phase discriminator output is small, and the code loop, carrier frequency, and baseband signal power are ensured to be stable. The observations' RMSE percentage change in the proposed strategy is significantly better than those of Strategies 1 and 2. The Ratio Test metric values prove that this strategy can bypass the SQM detection. Therefore, the proposed strategy can resist TOA and power detection.
2. Under the condition of a high or low C/N0, the proposed spoofing traction strategy also exhibits an optimal good performance; hence, it is still effective when the GNSS signal is enhanced in the battlefield or when the signal quality is poor owing to the low elevation.
3. This strategy expands the range of traction speeds and has the potential to quickly and covertly accomplish traction.
4. The proposed strategy can also be applied to narrow- and pulse-aperture correlators.  
**Author Contributions:** Conceptualization, N.J.; methodology, N.J. and Y.R.; software, N.J., X.C. and Y.G.; validation, N.J. and Y.R.; formal analysis, X.W. and N.J.; investigation, N.J.; resources, N.J., Y.R., X.W., D.Z. and X.C.; data curation, N.J. and Y.G.; writing--original draft preparation, N.J.; writing--review and editing, Y.R., X.W., D.Z., X.C. and Y.G.; visualization, N.J.; supervision, Y.R., X.W. and D.Z.; project administration, Y.R. and D.Z.; funding acquisition, Y.R., X.W. and D.Z. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This study received no external funding.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 6 Simulation Results and Discussions  
NSFNET topology with 14 nodes and 21 links was adopted for simulation to evaluate the performance of the proposed multi-dimensional RWTA algorithm. Our work focuses on short distance QKD-ON scenario. NSFNET topology's nodes and links were taken into this simulation and the maximum distance between any two nodes was less than the distance that can carry out point-to-point quantum key distribution process. Meanwhile, we assumed that the key generation rate of all links is constant. Forty wavelengths are considered in each fiber link according to the commercial systems. Multiplexing QKD and classical flows at different spectral windows (e.g., O-band, C-band) could be an option to overcome the contamination associated with Raman scattering. In future work, relevant research will be considered. Four wavelengths (200 GHz spectrum grid) are reserved as theguard band between QKCh and the other two channels to avoid four-wave-mixing effects as mentioned before [24]. The number of wavelengths reserved for MBCh is assumed to be the same as QKCh. Service requests are randomly generated among all node pairs following Poisson distribution. To the best of our knowledge, for the RWTA problem in QKD-ONs, Ref. [21] has proposed the RWTA algorithm considering three types of channels and different security levels of services which is a basic work. This paper considers how to improve the wavelength utilization under the fixed updating period scenario based on the theoretical model proposed in Ref. [21]. Therefore, we chose the first-fit (FF) based RWTA strategy in Ref. [21] for comparison in our paper. In addition, for learning more about the performance of our proposed algorithm, we also took the random-fit (RF) based RWTA strategy as comparison. The simulation is composed of three parts: (1) the performance of TW-SO strategy for provisioning of multi-security-level services is verified; (2) the performance of ReLoss-TCC-based RWTA strategy in different scenarios is demonstrated; (3) the performance of multi-dimensional RWTA algorithm for three different kinds of channels under different wavelength assignment scenarios are explored.
# Practical Work of Three-Phased Induction Motor Modeling in a Classical Spreadsheet Software
## 2 Three-Phased Induction Motor
### Power Balance  
The power balance is rather the same, whether the machine is operating as a motor or as a generator. The only thing to take care of is the losses. They are always deduced from the original power in the balance, whatever the direction of conversion. The detailed explanation of the power balance is given for the scheme presented in Figure 4, describing the motor operation.  
To model the induction motor operating as a motor, the following notations were used: \(P_{abs}\) is the absorbed electrical power supplied to the induction motor. Since the stator windings are composed of conductors, \(P_{ls}\) are the Joule effect losses in the stator windings. The alternating currents induce iron losses in the stator and are represented by \(P_{ls}\). The remaining power \(P_{tr}\) is transmitted to the rotor, in which the currents dissipate rotor Joule losses \(P_{lr}\). The low rotor current frequency allows us to neglect the rotor iron losses \(P_{lr}\). The remaining power at this stage is called total mechanical power \(P_{M}\), from which the mechanical power losses of the motor \(P_{m}\), which are mainly proportional to its rotational speed \(\Omega_{r}\), must be subtracted to finally obtain the useful mechanical power.  
The major elements of the model of an induction motor are given in the power balance presented in Figure 4, where \(U\) stands for the RMS (Root Mean Square) voltage value between two terminals of the three-phase induction motor, \(V\) is the RMS value at the terminals of a winding, \(I\) is the RMS value of a line current, \(J\) is the RMS value in a winding, \(R\) is the resistance measured between two terminals of the three-phase induction motor, \(r\) is the resistance of a winding, \(T_{em}\) is the electromagnetic torque moment, \(T_{u}\) is the useful torque moment, and \(T_{p}\) is the torque due to losses.
# Automated Control of the Fresh State of Industrial Concrete Behaviour by Rheometer Test Adjustment
## 8 Conclusions  
This study aims to develop a rheometer prototype and to define a procedure to adjust its configuration and the testing protocols to enable the automated control of the concrete fresh state. This was developed using a highly flowable concrete mix that was characterised at various testing times (ranging from 10 to 30 min from the water-to-cement contact).  
The rheometer prototype designed works in relative units. This, although it limits its comparability with other devices, simplifies the process. It was also concluded that,the most suitable rheological test is the FCT, as it provides information regarding both the yield stress and plastic viscosity of the concrete. Taking these two issues into account, the rheometer prototype was compared to a commercial rheometer, concluding that it is equally efficient in capturing the trends of fresh concrete behaviour.  
A flow chart was designed that suggests an iterative protocol that enables industrial users to select the FCT profile (breakdown period and rotational speed) and impeller-type with a reduced number of iterations. This protocol considers the torque at the end of the breakdown period, torque reduction during the breakdown period, possibility of segregation, and possible negative values of the yield stress in relative units.  
Finally, it can be concluded that a new calibrated device has been developed and a flow chart has been designed suggesting a protocol to adjust the procedure for the assessment of the fresh state behaviour of concrete automatically, thereby requiring minimal operator input.  
Conceptualization, B.G.-F. and D.C.-L.; methodology, B.G.-F. and G.R.-L.; validation, B.G.-F., G.R.-L. and D.C.-L.; formal analysis, B.G.-F., G.R.-L. and D.C.-L.; data curation, G.R.-L.; writing--original draft preparation, G.R.-L. and D.C.-L.; writing--review and editing, B.G.-F. and D.C.-L.; supervision, B.G.-F. and F.M.-A.; funding acquisition, B.G.-F. and F.M.-A. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Spanish Ministerio de Ciencia e Innovacion--Agencia Estatal de Investigacion through three research projects entitled: \"Design of sustainable concrete for 3D printing based on rheology and on the control of very early properties (Eco3 DConcrete)--PID2020-115433 RB-I00\", \"Design of concrete precast elements incorporating sustainable strategies for self-healing to increase their service life (PREHEALING)--PDC2021-121660-I00\" and \"Exploiting the synergic effects between 3D printing and self-healing technologies to design sustainable and durable concrete (3 DHealConcrete)--TED2021-129757B-I00\".  
Not applicable.  
Data availability Statement: Data will be made available on request.  
We would like to thank Grupo Puentes S.A. for the support of this study.  
The authors declare that they have no known competing financial interest or personal relationships that could have appeared to influence the work reported in this paper.
# Power Autonomy Estimation of Low-Power Sensor for Long-Term ECG Monitoring
## 4 Power Consumption Models
### Active Mode Power Consumption Model  
In the active mode, the ECG sensor connects to the controlling device, such as a mobile phone, and starts sampling and streaming the ECG signal. The average power consumed during the active mode \(\overline{P}_{conn}\) is the sum of all energy consumed in active mode divided by the time period \(T\) which we are measuring the average power consumption for. The total energy consumed consists of the energy consumed in connection events \(E_{conn}\), ECG sampling events \(E_{sample}\), system tick events \(E_{tick}\), and sleep mode \(P_{sleep\_active}\times T_{sleep}\). We can calculate the total sleep time \(T_{sleep}\) as the difference between the total time period \(T\) and the sum of time spent in all other events.  
The proposed analytical model for the power consumption in active mode is presented with Equation (5), where \(e_{conn}\) is the energy consumed during one connection event, \(e_{msg}\) is the energy consumed during one message-processing event, \(e_{sample}\) is the energy consumed during an ECG sampling event, \(e_{tick}\) is the energy consumed during one system tick event, \(tp_{comm}\) is the connection interval, \(tp_{msg}=14\times tp_{sample}\) is the message-processing interval that happens at every 14 th ECG sampling event (assuming that each ECG packet contains 14 ECG samples), \(tp_{sample}\) is the ECG sampling interval, and \(tp_{tick}\) is the system tick interval. \(t_{conn}\), \(t_{msg}\), \(t_{sample}\), and \(t_{tick}\) are the duration of the connection event, the message-processing event, the ECG sampling event, and the system tick event, respectively. Entering actual connection parameters into Equation (5) gives an estimation of the power consumption in an active mode, which is the basis for the sensor autonomy estimation.  
\[\begin{split}\overline{P}_{conn}&=\frac{1}{T}\Big{(}E_{conn} +E_{sample}+E_{tick}\Big{)}+\frac{1}{T}P_{sleep\_active}T_{sleep}\\ &=\frac{1}{T}\Bigg{(}\frac{T}{tp_{conn}}e_{conn}+\frac{T}{tp_{msg }}e_{msg}+\frac{T}{tp_{sample}}e_{sample}+\frac{T}{tp_{tick}}e_{tick}\Bigg{)}\\ &+\frac{1}{T}P_{sleep\_active}T\Bigg{(}1-\frac{t_{conn}}{tp_{ comm}}-\frac{t_{msg}}{tp_{msg}}-\frac{t_{sample}}{tp_{sample}}-\frac{t_{tick}}{tp_{tick}} \Bigg{)}\\ &=\frac{e_{conn}}{tp_{conn}}+\frac{e_{msg}}{tp_{msg}}+\frac{e_{ sample}}{tp_{sample}}+\frac{e_{tick}}{tp_{tick}}+P_{sleep\_active}\Bigg{(}1-\frac{t_{ comm}}{tp_{conn}}-\frac{t_{msg}}{tp_{msg}}-\frac{t_{sample}}{tp_{sample}}-\frac{t_{tick}}{tp_{tick}} \Bigg{)}\end{split} \tag{5}\]
# An Unambiguous Delay-And-Multiply Acquisition Scheme for GPS L1C Signals
###### Abstract  
The GPS provides positioning information almost anytime and anywhere on Earth, regardless of the weather conditions, and has become an essential technology for positioning and navigation. As a modernization program, the fourth civil GPS signal, denoted as L1C, will be transmitted from Block III satellites. One distinction of the L1C signal from the former signals is the use of binary offset carrier (BOC) modulation, which is necessary for compatibility and the reduction of interference between the legacy L1 signal and L1C signal, despite their use of the same carrier frequency. One drawback of using BOC modulation is the ambiguity problem, which comes from the multiple peaks in the correlation function and causes difficulties finding the code phase in the acquisition process. In this paper we suggest two delay-and-multiply (DM) methods for the L1C signal to solve the ambiguity problem. For the DM acquisition schemes we suggest the optimal delay time for the delay signal, and prove that the correlation function of the received DM signal and the generated DM signal has a triangular shape, as seen in the legacy GPS L1 signal. The noise characteristics of the decision variable are obtained and the performance of the DM acquisition scheme is given in terms of the probability of detection, and compared with that of the conventional method. We provide the procedure to find the Doppler frequency after obtaining the code phase through the proposed DM method.  
GPS; L1C signal acquisition; delay-and-multiply approach; ambiguity problem +
Footnote †: journal: Sensors
# Temperature Load Mode of Bridge in Permafrost Region of Qinghai-Tibet Railway
## 7 Conclusions  
In order to study the temperature load mode of a railway bridge in the permafrost region of the Qinghai-Tibet railway, long-term experimental research and finite element simulation analysis were carried out in this paper. The main conclusions are as follows:  
1. The daily temperature difference of a concrete two-piece T-beam bridge in the Qinghai-Tibet railway area presents a large value from November to March of the next year, which is mainly related to the ground's effective radiation and surface reflectivity.
2. The maximum daily temperature difference of the beam body in the Za'gya Zangbo region is 17.8 \({}^{\circ}\)C, exceeding the 15 \({}^{\circ}\)C specified in _Code for Design of Railway Continuously Welded Rail_. It is suggested that when designing bridges in plateau areas, the beam's temperature difference should be increased as appropriate to ensure the durability requirements of bridge in operation. In addition, observation and analysis should be further strengthened to provide important data support for revising and perfecting the codes.
3. Through long-term field test and simulation calculation, it is found that under the conditions of strong radiation and large daily temperature difference in the Qinghai-Tibet railway area, the bridge frequently produces telescopic displacement, which can easily lead to the attenuation of the performance of rail fasteners and bridge bearings and has an adverse impact on the safety of track structure. It is suggested that the maintenance of the bridge structure be strengthened and that performance index of bearing in this area be improved.
4. Based on the measured data and heat transfer simulation analysis, the temperature difference load mode suitable for concrete two-piece T-beams in typical areas of the  
Figure 16: Stress and displacement of CWR on bridge. (**a**) Rail expansion force. (**b**) Bridge and rail displacement.  
Qinghai-Tibet railway was proposed. This study overcomes the deficiency of regional limitations in the existing research, and makes up for the deficiency that the relevant codes do not consider the plateau's special climatic conditions, which can provide a reference for the design of CWR on a bridge in the plateau. Furthermore, the temperature load modes of other types of bridges need to be further studied.  
Conceptualization, B.Y.; methodology B.Y. and X.Z.; software, B.Y., R.C., H.X. and X.Z.; validation, R.C., H.X. and X.Z.; formal analysis, R.C., H.X. and X.Z.; writing--original draft preparation, R.C. and X.Z.; writing--review and editing, B.Y. and R.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key R&D Program of China (grant number 2017 YFB1201204) and the Project of Science and Technology Research and Development Program of China National Railway Group (grant number K2021G026).  
Not applicable.  
All data, models, and code generated or used during the study appear in the submitted article.  
The authors declare no conflict of interest.
## 3 System Architecture and Data Collection Protocol  
EIT is a non-invasive technique that operates on the principle of injecting micro-ampere alternating current (AC) electrical signals into a target region through surface electrodes. By measuring the resulting boundary voltages (BVs) between pairs of electrodes, EIT reconstructs the impedance maps of the cross-section of the region under study, such as the forearm in our case. These impedance maps provide valuable insights into the spatial distribution of the electrical properties within the tissue.  
The EIT system architecture used in this study, presented in Figure 1, integrates a compact hardware configuration that includes an AD9834 direct Digital Synthesis Module (DDS) that generates a 150 uA AC. This excitation signal module is a precise current source that maintains consistent amplitude across variable impedance loads while conforming to medical safety standards (EN60601). The DDS module employs a 10-bit high-impedance DAC to generate a 40 kHz, 150 uA sinusoidal current signal with zero-phase initialisation. The experimental EIT system uses a CD74 HC4067 high-speed analogue multiplexer to manage the eight-electrode configuration. An adjacent-driven measurement pattern is implemented where the current is sequentially injected and rotated across the electrodes, with each rotation generating 40 boundary voltage measurements. This multiplexer-controlled approach enables precise electrode switching and effectively managing current injection and voltage extraction. The last part of the EIT system uses a differential amplifier circuit designed to improve the accuracy of signal acquisition for low-voltage measurements. The circuit incorporates DC offset voltage compensation and strategic resistor calibration to deal with the minimal voltage differences resulting from milliamp current injections.  
The entire system is consolidated onto a single circuit board and interfaced with an Arduino Uno microcontroller [24]. Using a four-pole, adjacent electrode sensing method, the system systematically injects the current through an adjacent pair of electrodes and sequentially measures BVs across the remaining electrode pairs. The experimental protocol includes 36 different ASL signs as shown in Figure 2, with each sign characterised by 40 boundary voltage measurements, derived from 10 peak-to-peak averages per measurement. The dataset is collected from 10 healthy subjects performing each sign ten times. To minimise the forearm muscle fatigue, a 2-s interval is maintained between gesture repetitions. Additionally, a 5-min rest period is provided after every nine gestures to ensure that the fatigue parameter does not influence the measurements.  
Figure 1: EIT data collection and measurement system.  
Figure 2: ASL set of gestures.