esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 FTN Signal Processing Based on the UEP Algorithm
### Reordering According to Priority Settings  
Figure 7 shows the composition of the encoded bits, according to their priority. As explained in Section 3.1, we reordered the LDPC-coded bits, from high priority to low priority, from the right part of Figure 6 to the left part. For example, the 26 th bit node group of the 360 coded bits were firstly rearranged in the form of Figure 7.  
\(N_{p}\) is the number of different FTN interference rates, used to perform the UEP setups by applying a priority algorithm for the \(G_{N_{p}}\) groups. For example, N = 64,800 LDPC coded bits, supposing \(N_{p}=4\), and each group, \(G_{i}\), has 16,200 coded data.  
Figure 6: The order of the bit node group, with or without the UEP algorithm.  
Figure 7: Composition of the code word by priority.  
For high-priority bit groups, the FTN interference ratio needs to be set to low, as this can enhance the performance, because the number of repetitions between the bit node and check node updating processes is high during decoding. For low-priority bit groups, the FTN interference ratio needs to be set to high, because the number of bit node and check node updating repetitions is relatively small. High and low priorities indicate the level of importance of the transmitted signals, and each group of transmitted signals have different FTN interference ratios, based on the priority. A transmitting signal is generated by setting the FTN interference rate in each group differently. The average of \(\boldsymbol{\tau^{\prime}}_{1},\boldsymbol{\tau^{\prime}}_{2},\cdots,\boldsymbol {\tau^{\prime}}_{N_{p}}\Big{(}\boldsymbol{\tau^{\prime}}_{1}\leq\boldsymbol{ \tau^{\prime}}_{2}\leq\cdots\leq\boldsymbol{\tau^{\prime}}_{N_{p}}\Big{)}\) for different interference ratios is set to be the same as that in the conventional FTN transmission methods. Thus, the algorithm enhances the performance, while maintaining or improving the transmission efficiency of the conventional FTN transmission method.
# A Low-Cost Electronic System for Human-Body Communication
## 3 System Description  
This section presents a description of the proposed low-cost electronic system for human-body communication. We based our system on galvanic coupling, which was once a method for injecting an electrical communication signal into the body. The body acts as the communication medium, and the injected signal is transmitted primarily through the skin. The signal is completely injected within the human body, and the performance is not affected by the surrounding environment in terms of interference [18].  
The proposed system comprises two main components: (i) differential current driver and (ii) sensing amplifier. Figure 1 presents the block diagram for the differential current driver component, whereas Figure 2 shows the block diagram for the sensing amplifier component. Figures are detailed next. The first diagram illustrates two electrodes (A and B), inverters, converters, and the current flow. The second diagram also shows the electrodes and all the steps to amplify the signal as the instrumentation amplifier, DC suppression, main amplifier, and low-pass filter. The following subsections detail the preliminaries and the two main components.  
Figure 1: Differential current driver block. Data bits written at the inputs (IN and ON-OFF) converted into current pulses at the electrodes A and B.  
Figure 2: Sensing amplifier block diagram. Electrodes collect the differential voltage together with noise and interference and a third is linked to the active common-mode rejection circuit.
# A Human-Inspired Control Strategy for Improving Seamless Robot-To-Human Handovers
## 2 Design of the Robotic Human-Inspired Control Strategy for HRH  
### Background of Human-Human Handower Strategy  
It is crucial to understand the kinematics and dynamics of HHH behaviour to design a conceptual guideline for a robotic human-like controller for robust, behaviour-based, HRH. Consequently, a set of HHH tests was initially conducted as fully detailed in our previous journal article [32]. It can be summarized that the experimental results of HHH intensively addressed (1) investigation of the human handover strategies of the givers and receivers (2) examination of the interactive forces and the transfer locations between the couple and (3) clarification of the mathematical model of the giver's arm, which leads to a better understanding how the giver regulates the bilateral force before releasing the object to be transferred to the receiver.  
The tests give the behavioural explanation of HHH in which the HHH process can be interpreted as three distinct phases consisting of (1) sending, (2) transferring and (3) receiving. In the sending session, the giver starts grasping and holding an object and moves to the receiver, who is in the field of the giver's view. Once the handler recognizes a receiver and his/her position, the giver subsequently computes and estimates a suitable object transfer point based on human-relevant parameters. In the meantime, the giver is then moving to the transfer point facing the receiver before naturally handling the object. The handover locations \(y\) (height from the ground) is formulated as Equation (1), where \(x_{1}\) and \(x_{2}\) are the giver's and receiver's heights, respectively. Contrastingly, the transfer distance (in the x-axis) along the facing direction was approximately 0.85 m.  
\[y=8.23+0.243x_{1}-9.592x_{2}-1.626{x_{1}}^{2}+1.441{x_{2}}^{2}+3.189x_{1}x_{2} \tag{1}\]  
In the transferring phase, the giver's decision is based on the amount of threshold (interactive) force (\(f_{tsh}\)), which was significantly proportional to the object mass. The relationship between the \(f_{tsh}\) as a function of object mass (\(\vartheta_{m}\)) can be exposed in Equation (2).  
\[f_{tsh}=-85{\vartheta_{m}}^{3}+100.75{\vartheta_{m}}^{2}-35.78\vartheta_{m}+6.75 \tag{2}\]  
The handover time was approximately 0.46 s. Moreover, to gain more understanding of how the giver regulates the interactive force, the transfer function (\(T_{G}\)) of the giver's hand can be expressed as the following equation:  
\[T_{G}=\frac{-2.63\times 10^{-4}S+5211}{S^{2}-20.255+51.76} \tag{3}\]  
These findings disclose the human characteristics of the haptic handover interaction and for the aim of obtaining a conceptual guideline for a robotic human-like control strategy in HRH.
###### Abstract  
This study presents a simulation procedure for the wear of metallic materials exposed to long-term cumulative contact forces and introduces a numerical analysis procedure using the discrete element method (DEM) to predict the wear damage. Since the DEM can calculate the motion and contact load of each particle and the interaction between particles for each dynamic collision of particles, it was possible to analyze the motion of the particles causing metal wear. A method to reflect particle size, material properties, and long-term cumulative friction distance required by the DEM was proposed so that the collision and friction load between particles can be predicted practically. Considering the feature of wear suggested by [PERSON], it was shown that the wear amount can be predicted efficiently by converting the long-term load into an equivalent material constant. In addition, it was suggested that it is reasonable to determine the size of the particles in consideration of the size of the surface mesh of the metal surface. The accuracy of the analysis results obtained using the procedure proposed in this study was compared with that of the wear test results of metal material specimens presented by former studies. The numerical analysis was also performed in the reference study, but inaccurate results were derived compared to the analysis results. The reason for the inaccuracy of the numerical model performed in the previous study was found to be environmental factors that cannot be considered in a numerical analysis. In this study, it was determined that it was because the behavior of particles and the load transferred to the specimen were not well simulated, which remains a problem for future research. As a result, it was confirmed that it is possible to compute a worn shape similar to the measured shape of experiments. Thereafter, the change in the contact load predicted by simulation is discussed in terms of wear shape and cross-sectional area loss ratio.  
discrete element method (DEM); wear simulation; long-term wear; Archard's wear law; contact friction force +
Footnote †: journal: Applied Sciences
## 1 Introduction
### Challenges  
There are currently two major challenges for the practical implementation of the suggested measurement and quantification procedure. The first one stems from the fact that there is currently no unified method for the precise definition of the ramp rate itself. For instance, there is a plethora of specifications with respect to \(\Delta t\) in (1). The TSOs in Puerto Rico [13], Ireland [13; 14; 15], China [32; 41], or in England and Wales NGC [32], specify various \(\Delta t\) in the range of 2 s, 1-min, 5-min or 10-min. Such differences are documented in reviews like [28; 32]. In the same context belongs the lack of specifications with respect to \(\Delta P_{\text{el}}(t)\) in (1). It is not clear what is actually meant with \(P_{\text{el}}(t)\): is it the instantaneous 3-phase active power measured at instant \(t\), or is it the active power averaged over some period and, in such a case, what is that period? Such details seriously affect the way powers and subsequently, the ramp rates are measured and quantified. The second challenge stems from the lack of a unified approach with respect to the measuring devices that will be used to measure the quantities in (3) or (5). All these quantities are currently measured within the respective converters; however, the aim of the measurement is the control of the converters and not the measurement and quantification of power and energy [25]. Even if it is assumed that the DSOs or TSOs trust such measurements, the different measurement accuracies among the various DRES, prohibit the use of the converter-based measurements, because they will be finally translated in financial remuneration.
## 4 Materials And Methods
### Optical Methods  
Optical performance was measured as follows: Spectroscopic ellipsometry permitted us to extract the refractive index of the coatings; reflectance in the visible-to-near IR range leads to the reflection coefficient evidencing anti-reflection in some cases; mid-IR provided us with the transmittance of the samples.  
The variable angles spectroscopic ellipsometer we used was a HORIBA Jobin Yvon UVISEL working here in the 250-1300 nm range and we analysed eight angles in the range 55-75\({}^{\circ}\). We worked only on the thinnest grade of nanoparticles (4 nm) as the material made out of the largest ones scatters too much light.  
The reflection measurements were performed at 'normal' incidence with basic bench-top equipment from Avantes. The sample was illuminated via the same co-axial fibre, from which the light emerging from the sample is also collected (Avantes reference FCR-7 UVIR400-2-BX/ME). Neither the illumination nor the collection are actually at perfect normal incidence: The illumination fibre is not collimated (numerical aperture 0.22). The lamp shines at the spectral range of 200-2500 nm, but due to the two detectors we use, there is an unfortunate detection gap around 800-1000 nm.  
Transmission in the mid-IR range was measured on a specific system, namely fast infrared imaging spectroscopy (FIIST [33; 34]), which permits us to image the optical transmission in the range of 2-6 \(\upmu\)m.  
Figure 9: Sketch of the \(\upmu\)-pervaporation technique leading to micro-structured deposits: A poly(dimethyl siloxane) (PDMS) mould (**left**) is designed with channels initially filled with a dilute dispersion; solvent spontaneously permeates across the elastomer, concentrates the nanoparticles, and leads to a solid material out of the dispersion upon removal of the mould (**right**).
## 1 Introduction
It is therefore imperative to investigate the optimal design of transport routes in order to maximize production transport efficiency, while allowing for potential route conflicts and ensuring compliance with the relevant engineering transport laws. This paper discusses the problems of an intelligent scheduling system for trackless transport on slope roads, with a view to addressing the issues of the low utilization of trackless transport passes in underground mines, the conflict and blockage of transport routes due to the unscientific planning of transport routes, low transport efficiency, and so on. The principal findings of the research are as follows: 1. An improved genetic algorithm is proposed, which introduces the constraints of the law of vehicle transport in underground mines in the calculation of adaptability in a novel manner. 2. In the proposed improved genetic algorithm, a coding method is proposed which is more applicable to trackless transport in underground mines. 3. The principle of fuzzy logic is applied, and the interval positioning method is used to divide the road sections and locate the vehicles. This approach reduces the spatial complexity of the algorithm and improves its response speed. 4. The proposed improved genetic algorithm is used to carry out simulation experiments on the trackless transport of underground mines. The results of the experiments demonstrate that the algorithm is effective in improving the efficiency of the trackless transport of underground mines and in enhancing economic benefits. Section 2 provides a comprehensive description of the initial scheduling model for underground metal mine trackless transport. This includes an in-depth analysis of the technical characteristics of the model, interval fuzzy positioning, the generation of transport task sequences, the construction of mathematical models, cost calculation, and the constraints of the scheduling model. Section 3 proposes an optimization method based on an improved genetic algorithm, which enhances the coding method and innovates the adaptation calculation to align with the transport scheduling requirements of underground mines. Section 4 validates the efficacy of the proposed algorithm in enhancing transport efficiency, reducing costs and congestion through computer simulation experiments, demonstrating a notable improvement before and after the optimization.
## A Distributed Geo-Routing Algorithm for Wireless Sensor Networks  
**[PERSON] and [PERSON]*  
Department of Information and Communication Engineering, Yeungnam University, Gyeongsang  
buk-do 712-749, Korea; E-Mail: [EMAIL_ADDRESS]  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +82-53-810-2483; Fax: +82-53-810-4742  
_Received: 24 April 2009; in revised form: 21 May 2009/ Accepted: 25 May 2009 / Published: 27 May 2009_  
**Abstract:** Geographic wireless sensor networks use position information for greedy routing. Greedy routing works well in dense networks, whereas in sparse networks it may fail and require a recovery algorithm. Recovery algorithms help the packet to get out of the communication void. However, these algorithms are generally costly for resource constrained position-based wireless sensor networks (WSNs). In this paper, we propose a void avoidance algorithm (VAA), a novel idea based on upgrading virtual distance. VAA allows wireless sensor nodes to remove all stuck nodes by transforming the routing graph and forwarding packets using only greedy routing. In VAA, the stuck node upgrades distance unless it finds a next hop node that is closer to the destination than it is. VAA guarantees packet delivery if there is a topologically valid path. Further, it is completely distributed, immediately responds to node failure or topology changes and does not require planarization of the network. NS-2 is used to evaluate the performance and correctness of VAA and we compare its performance to other protocols. Simulations show our proposed algorithm consumes less energy, has an efficient path and substantially less control overheads.  
**Keywords:** geo-routing; communication void; greedy routing; wireless sensor networks
# GNSS Accuracy Under White Gaussian Noise Jamming +
## 4 Comparison of Theoretical and Measured Results  
In this Section, the results of the comparison of the theory versus the measurements are provided. First, the measured impact of the jammer on the \(C/N_{0}\) is compared to the predicted impact based on Equation (3). Next, the impact on the DLL tracking accuracy is compared to the measured standard deviations of the detrended pseudo-range measurements.
## 5 Conclusions  
In this study, a FE model of a timber frame with straight mortise-tenon joints is built and verified. The stress state of the model subjected to the lateral cyclic loading is then analyzed. Three damage types of the mortise-tenon joint are proposed and included in the FE model to study the influence of these damages on the cyclic performance of the timber frame. The conclusions are as follows.  
1. The vertical compressive stress at the contact surface of the mortise-tenon joint is a reasonable variable that can represent the reaction force of the whole model. Larger value of this stress corresponds to more demand for the lateral loadings exerted on the columns.
2. The gap between the mortise and the tenon can reduce the stiffness of the timber frame because of the lack of contact between the external surface of the column and the vertical surface of the beam, while the dissipated energy remains almost unchanged. When the gap reaches a certain value, 20 mm in this study, the stiffness will become stable.
3. The damage in the top of the tenon can lead to the reduction in the maximum force and stiffness of the model followed by a sudden increase when some lateral displacement is reached. This certain lateral displacement can be derived from both the stiffness curves and the vertical compressive stresses at the contact surfaces.
4. Damage in the end of the tenon has two types of influences on the stiffness and dissipated energy of the model according to the length of the cutoff part. When the length is small, the stiffness and dissipated energy decrease slowly with the increase of the length. When this length is larger than 100 mm in this study, the stiffness and dissipated energy will decrease dramatically.  
All the authors discussed and agreed upon the idea and made scientific contributions. [PERSON] did the mathematical modeling, performed the simulations, and contributed to the writing. [PERSON], [PERSON] contributed to the revisions and discussion of the results. Conceptualization, B.S.; formal analysis, B.S.; methodology, B.S.; supervision, H.W., A.L.; writing--original draft, B.S.; writing--review & editing, H.W., A.L.  
This research was funded by the National Natural Science Foundation of China, grant number 51978033.  
The authors declare no conflict of interest.
## 7 Observations and Recommendations
### Recommendations and Research Challenges  
#### Practical Evaluation  
The resource constraints of IWSNs are one of their most critical limiting factors as discussed in the previous section. The literature survey revealed that very few of the proposed schemes' feasibilities were adequately evaluated in this context. Future work should address this overlooked aspect in order for the field to evolve from being primarily concept-based, to one that is practically viable. Practical considerations are also more than just the resource constraints, in order to enhance their practical feasibility these schemes also have to include protocols that govern how they would work in a practical setup. Considerations of aspects such as the underlying network architecture, topology and protocols are paramount in determining a scheme's viability in practice. Very few schemes found in the literature considered this and most were primarily evaluated using popular datasets such as those found on the University of California, Irvine (UCI) machine learning repository [80]. While this is adequate to evaluate the accuracy of the proposed schemes, it neglects the challenges inherent within the IWSN application environment.
# Variable Speed Limit and Ramp Metering for Mixed Traffic Flows: A Review and Open Questions
## 2 Application of VSL and RM Control in HDV Traffic Flows  
The VSL control system application with timely and appropriate speed limits can control the incoming flow of the vehicles approaching the bottleneck by adjusting it to a lower level, i.e., to the amount of capacity of the bottleneck [6]. This prevents the capacity from dropping further and allows the congestion to be resolved more quickly and achieve traffic flow values less than or equal to the maximum capacity in the bottleneck area. The preventive effect of VSL is manifested in delaying the occurrence of the capacity drop, which prevents the activation of bottlenecks by timely control of the incoming traffic flow. The application of VSL leads to smaller speed deviations between vehicles and lanes, thus reducing the risk of accidents [27; 28; 29; 30].  
RM systems control the inflow of on-ramp motorway vehicles. For this purpose, the feedback system detectors required for operation are usually placed downstream of the on-ramp where vehicle merging takes place [31]. The most common RM algorithm, ALINEA [32], uses the output of the previous control step interval as input for the current iteration. Thus, the ALINEA inputs used are the previous control step interval metering rate and downstream occupancy. Some of the extensions to ALINEA that have been developed to improve performance are FL-ALINEA, UP-ALINEA, UF-ALINEA, AD-ALINEA, X-ALINEA/Q, and PI-ALINEA [19].  
In the following subsections, the VSL and RM algorithms for HDV flows are analyzed, and grouped by the applied processing methods (rule-based, open-loop, feedback loop, and RL). Different metrics have been used as indicators of algorithm performance in different simulation scenarios. Thus, it is difficult to say which is the best method without in-depth simulation analysis using the same scenario, which is out of the scope of this paper--especially since each of them has a different optimization objective, such as minimizing emissions, improving safety, and improving chosen macroscopic traffic parameters. Thus, only a comment about the effectiveness of the respective method group is given using the metric results published in the surveyed literature.
## 4 Results and Discussion
### Stock Price Prediction Results
The inferior performance of the Random Forest and SVM might be attributed to their inability to capture long-term dependencies in time series data effectively. Deep learning models, especially those based on the Transformer architecture, due to their layered structure and self-attention mechanisms, can decipher complex patterns in time series data more adeptly. In summary, the results signify that for intricate time series prediction tasks such as stock price prediction, deep learning methodologies, particularly those based on Transformer, offer distinct advantages. The proposed model, amalgamating multiple techniques such as  
Figure 7: Ground truth and the predicted values by proposed method. the Memory module and Long-Distance Loss, demonstrates an especially commendable performance in this task.