esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Therefore, for the autonomous operation of agricultural machinery, the proposed algorithm generates waypoints based on the absolute position using the geodetic coordinates of field boundary points measured with positioning sensors such as GNSS. The main contributions of this paper are as follows: (1) propose a path-generation algorithm for crawler-type agricultural machinery rather than wheeled agricultural machinery such as tractors; (2) generate an autonomous driving path covering the entire field using a simple mathematical method using only the coordinates of the field boundary points and the sizes of the robot and implement; and (3) generate waypoints step by step based on the defined autonomous driving ridge-forming operation scenario. The structure of this paper is as follows. Section 2 introduces the proposed algorithm that generates an autonomous driving path for a ridge-forming robot by defining field boundaries, generating working line segments according to the field boundaries, and generating waypoints using the working line segments according to autonomous driving operation scenarios. Section 3 presents the test results of the proposed algorithm. Section 4 describes the discussion and conclusions.
# Wearable 256-Element MUX-Based Linear Array Transducer for Monitoring of Deep Abdominal Muscles
## 3 Results  
### System Characterization  
#### 3.1.1 Multiplexer Characterization  
The functional cells (transmission gates, LNA, serial shift register) were first produced and characterized separately. The transmission gates used in the multiplexer were characterized: An open switch should attenuate the signal by at least 60 dB, while the closed switch should have minimal attenuation. Also, the crosstalk between adjacent channels should be better than 60 dB. Due to the capacitive coupling of cables in the measurement system, the actual attenuation and crosstalk could not be measured, but it could be shown that the target of 60 dB could be met. When measuring the LNA, the gain-bandwidth product was the critical parameter to qualify the different circuits, partly using CMOS or bipolar transistors and different phase compensation for stability. The combination of MUX and LNA was characterized using a test PCB with CW signals of different frequencies (from a waveform generator) fed into the ASIC. The characterization of the response is shown in Figure 5F, with an attenuation larger than 60 dB for frequencies below 4 MHz and between 50 and 60 dB for the relevant spectral range between 4 and 10 MHz. On the other hand, with open MUX and active LNA, the gain is between 0 and 4 dB for frequencies between 200 kHz and 9 MHz (\(-\)0.1 dB attenuation for a frequency of 10 MHz). The power consumption of the ASIC-MUX was measured as 17 mW (current of 5 mA at the driving voltage of 3.3 V), which is negligible in comparison to the overall power consumption of the system. The switching speed of the MUX is defined by the half-period of the system clock of 50 MHz, which means it can theoretically switch within 10 ns, which is much faster than needed for the application. In the chosen beamforming scheme, a switching of MUX settings is performed between consecutive transmission events such that the requirements for switching speed are defined by the system PRF and the acoustic time of flight (e.g., 65 \(\upmu\)s for 5 cm image depth).
# An Improved Detail-Enhancement CycleGAN Using AdaLIN for Facial Style Transfer
## 3 The Proposed Method
### Algorithm  
Based on the above model and loss function, the algorithm flow of this paper is shown in Algorithm 1.  
**Input:** Gallery \(X\), gallery \(Y\), generator \(G\) and its corresponding parameter \(\theta_{G}\), discriminator \(D_{Y}\) and its corresponding parameter \(\omega_{Y}\), generator \(F\) and its corresponding parameter \(\theta_{F}\), discriminator \(D_{X}\) and its corresponding parameter \(\omega_{X}\), weight factor \(\lambda\), maximum number of cycles \(N_{epoch}\), number of rounds to start reducing the learning rate \(N_{offset}\), current number of iterations \(t\), generator initial learning rate \(\eta_{g}\) and discriminator initial learning rate \(\eta_{d}\).  
**Output:** Stylized photo  
_step 1_**:** Initialization: \(\theta_{G}\), \(\omega_{Y}\), \(\theta_{F}\) and \(\omega_{X}\).  
_step 2_**:** Updating: \(t=t+1\).  
_step 3_**:** Sample images from \(X\) and \(Y\), generate corresponding outputs, and label real as 1 and generated as 0.  
_step 4_**:** Input generated samples to generators \(G\) and \(F\) to obtain reconstructed images and calculate reconstruction losses.  
_step 5_**:** Input generated and real samples to discriminators \(D_{X}\) and \(D_{Y}\). Compute and minimize the discriminator objective function. Update discriminator weights using back-propagation and improved Adam optimization.  
_step 6_**:** Minimize generator objective function and update weights of generators \(G\) and \(F\) using back-propagation and improved Adam optimization.  
_step 7_**:** Adjust learning rate based on current iteration count \(t\) and \(N_{offset}\).  
_step 8_**:** Repeat steps 3-7 until maximum iterations are reached.  
**Algorithm 1** CycleGAN Algorithm Flow
# Implementing and Testing a U-Space System: Lessons Learnt
## 1 Introduction  
A safe use of drones sharing the airspace, same as with crewed aviation, requires a management of the separation. This separation cannot always rely on the skills of the pilots, since many of the operations are expected to be beyond the visual line of sight (BVLOS), with pilots having limited information of the airspace and context. Moreover, the use of human air traffic controllers does not fit well with the particularities of the small drones and the city environment. A better option is to automate an Unmanned Traffic Management (UTM) system. To harmonize such UTM systems in Europe, under the European Union's (EU) Horizon 2020 research and innovation program, the project CORUS (Concept of Operations for EuRopean UTM Systems) developed and published the U-space concept of operations (ConOps), which would be regulated and adopted in April 2021 as the EU's UTM ConOps, entering into force on January 2023. The constant research and projects focused on developing and implementing different aspects in the ConOps since the first version was published, have contributed to its refinement, extension and improvement and today version 4 is available [1], addressing new topics like Urban Air Mobility (UAM).  
U-space does not only address drone traffic management, but also other relevant aspects like safety, privacy, security, social acceptance or co-existence of all Very Low-Level airspace operations, and its architecture is aimed at facilitating the proliferation of anentire industry around the offer of services provided by and for unmanned aerial vehicles (UAVs). This is permitted by its modular architectural design, which can be seen as a system of systems. Part of these systems are called services, and represent specialized functionalities like calculations or data provision. Services can be dependent on or could make use of other services. For a single U-space, the services can be provided by different companies or institutions and therefore run in different infrastructures; hence, the need for the harmonization for a compatible market.
## 4 Experimental Results
### Hyper-Heuristics Analysis  
Utilization of Low-Level Meta-Heuristics  
In this section, we address the following issue: how much a single LLH is chosen by a particular hyper-heuristics. Figure 1 graphically presents this usage: for MOABHH, it represents the percentage of participation in generating offspring along with the search. On the other hand, for HHRL, HHLA, and HHCF, the figure presents the percentage of times that each LLH was chosen. The data consider all problem instances, each of them running 30 times.  
The particular behavior of each HH may be found by analyzing Figure 1. For example, if we consider problem P03, one may notice that MOABHH has chosen more times GDE3 (blue) and SPEA2 (red), while HHLA chose more often SPEA2. On the other hand, HHRL and HHCF have chosen LLHs more uniformly. Table 7 presents a summarized evaluation of this analysis, where we classified HHs'c behavior into four classes: (i) _One Elitist_: problems  
Figure 1: Utilization rate for the four hyper-heuristics.  
where one LLH is clearly selected more times than any other, i.e. more than 50%; (ii) _Two Elitist_: problems where two LLHs are privileged, i.e. each LLH selected more than 40% ; (iii) _Three Elitist_: problems where three LLHs are selected more times than others, i.e., each LLH selected more than 30%; (iv) _Not Elitist_: when there is no clear LLH preference.  
We can identify HHLA and HHCF with more problems classified as _One Elitist_, while MOABHH and HHRL had more problems in _Two Elitist_ category. For _Three Elitist_, HHLA, HHCF, and HHRL had four problems classified while MOABHH had three. Considering all elitist classified problems (_One Elitist + Two Elitist + Three Elitist_), we can identify all HH behaving in a similar way.
# Impact of Soil on the Penetration of Prefabricated Spherical Fragments and Its Protective Effect
###### Abstract  
As a natural environmental medium, soil has a wide range of sources and is often used as a material for building houses. It can also be used to construct simple protective structures in actual battlefield environments. In order to study the protective effect of sand on prefabricated fragments in practical situations, the authors conducted experiments on spherical tungsten alloy prefabricated fragments penetrating into sand using sand as the target medium. Natural sand (naturally generated rock particles with a particle size less than 4.75 mm) was selected as the sand, and the initial velocities of the fragments were 689 m/s-1761 m/s (fragment diameter 6 mm) and 596 m/s-1325 m/s (fragment diameter 11 mm), respectively. Based on the residual velocity of fragments and experimental phenomena in experimental data, the authors used LS-DYNA software to numerically simulate and compare the residual velocity of fragments and obtained a numerical model for sandy soil media and a calculation formula for the residual velocity of spherical fragments. Based on modeling equivalence in practical environments, the authors studied the impact of different attack angles on fragment trajectory deviation and found that fragments have the highest deviation values at 20\({}^{\circ}\) and 70\({}^{\circ}\) attack angles. They also analyzed the soil boundary effect within a small scale range, and the effect was significant when the vertical distance was less than 40 mm. The penetration resistance of different thicknesses of soil was calculated, and the maximum soil thickness under prefabricated fragment penetration at different speeds was obtained. The effective protective size of the soil under actual conditions was about 550 mm. This experiment provides a reference for the construction parameters of simple soil defense structures in actual environments.  
soil; prefabricated fragments; protective fortifications; residual speed +
Footnote †: journal: Applied Sciences
# Towards Trust and Friendliness Approaches in the Social Internet of Things
## 3 Trust and Friendliness in the Social IoT
### Current State of the ART in Peer-To-Peer and Client/Server Networks  
The underlying ideas of friendliness are trust and using local information about an object, finding another object for a specific service in a distributed way [14]. There are only a few studies about trust in the IoT and the social IoT. A recent study [34] addressed the link selection method in the social IoT. In this method, objects make friendliness-based connections to other objects by using links. The first step in this study was to analyze network navigation by using a simulation. They tried to find service discovery among objects, aiming to find the number of connections on the basis of the available number of hubs in the network. A similar effort was made in an attempt to find a way towards an exchange of information between members with feasibility based on trust [1]. Those authors proposed subjective and objective approaches to address the problem. Both of these approaches provide a future for both P2P and social networks. In objective-based trustworthiness, information regarding the network is centric. The trustworthiness value is stored in a special type of table called a distributed hash table (DHT). The network information is managed by a distinctive type of object, referred to as a pretrusted object (PTO). Subjective trustworthiness is local because it is accessed and updated on its own or by friends [1]. The difficulty in this study is choosing a static or a fixed topology. This means that trust cannot dynamically adapt to change [34]. A similar type of study suggested a trust-based model based mainly on fuzzy logic that is only suitable for IoT-based systems [24]. Here, quality of service was considered, including delivery ratio, measurement of packet ratio (forward and delivery), and consumed energy between sensors, which allowed people to compute the trust level among social networks and boost the level of social relationships among owners and devices [24]. [PERSON] et al. [35] suggested a scheme that is fully based on security. This scheme works as a shield against attacks. They provided context-aware and multiservice-based features for the IoT. However, their method was based on only centralized servers. These servers are used for gathering and dissemination of trust data [34] among peers. This type of feature is not available in the IoT environment. The integration of QoS and social trust was described by [PERSON] and [PERSON] [36]. In their study, two recommendation systems including direct and indirect trust were proposed. Both of these are used to update the trust value. The trust evaluation and response in the case of dynamically changing conditions was a real challenge in this investigation. Moreover, dealing with misbehaving nodes in a dynamic network and increasing the performance of trust-based applications were not addressed.
## 1 Introduction
[11] developed a test bench in which an axial load was applied statically with a cylinder made of CoCr to a horizontally moving plate made of PE, resulting in a rolling movement of the rotating cylinder on the plate. After stopping the CoCr cylinder, a sliding movement occurs due to the continuous movement of the PE plate in a tempered test fluid [11]. As this test chamber is not sealed, there is a risk of contamination by foreign particles. In another rolling-sliding test bench, an axial sinusoidal load is applied to a plate made of PE by means of a CoCr cylinder [14]. The rolling-sliding movement results from the horizontal movement of the test chamber. These test rigs represent an appropriate mixture of screening and simulator tests and are designed for wear and endurance testing. However, none of them replicate the dynamically acting load conditions in the human knee joint. To address this, [PERSON] et al. developed a rolling-sliding test bench (RST) [7]. Comparable to the test benches of [PERSON] [14] and [PERSON] et al. [11], the force is applied to a flat sample of PE using CoCr cylinders. The rolling-sliding movement is caused by the coupled movement of a lifting arm. With this test bench, the forces acting on the knee during normal gait can be dynamically and variably applied to the sample during the roll-slide movement [7]. Furthermore, it is possible to simulate the roll-slide movement of a femoral component made of CoCr under wear conditions that are as close as possible to physiological conditions [7]. However, this test bench has some limitations. [PERSON] et al. used the same force, according to ISO 14243-1 [15], that is used for the testing of total endoprostheses in knee wear simulators, although only one knee condyle was simulated on the test bench. Furthermore, the test bench had only one station, resulting in time-consuming sample screening [7]. In the present study, the test bench was optimized, and the forces were adapted to the physiological contact pressure in the knee joint using the available geometric parameters. In this study, a knee spacer, which is a unicompartmental interpositional implant, was developed with the aim to postpone the implantation of a unicondylar or bicondylar knee endoprosthesis. For this purpose, we adapted the test bench and test conditions described by [PERSON] et al. [7] to simulate the contact conditions of an osteoarthritis femoral conodyle on the spacer material. Furthermore, a second station was added to the rolling-sliding test bench. The joint reaction force according to ISO 14243-1 [15] was adjusted to the load situation at the unicompartmental implant surface, and different bearing material pairs were compared.
## 3 Energy Harvesting Techniques
### Thermal Energy Harvesting  
Thermal energy harvesting converts heat gradients into electrical power using thermoelectric generators (TEGs) [63; 64]. These generators exploit the Seebeck effect, where a temperature difference across a material generates a voltage. The electrical power generated by a TEG can be expressed as follows:  
\[P=\frac{S^{2}\cdot\Delta T^{2}}{R_{\text{load}}+R_{\text{int}}} \tag{2}\]  
where \(P\) is the electrical power output (in watts), \(S\) is the Seebeck coefficient of the material (in volts per kelvin), \(\Delta T\) is the temperature gradient across the TEG (in kelvin), \(R_{\text{load}}\) is the load resistance (in ohms), and \(R_{\text{int}}\) is the internal resistance of the TEG (in ohms). The **advantages** of thermal energy harvesting are as follows:  
* Continuous Operation: Can operate as long as there is a temperature gradient, which can be constant in many environments.
* Compact Design: TEGs are generally small and can be integrated into various devices. The **limitations** of thermal energy harvesting are as follows:
* Low Efficiency: TEGs typically have low conversion efficiency, making them suitable for low-power applications.
* Temperature Gradient Requirement: Requires a consistent temperature difference to generate power effectively.  
Figure 3 depicts a thermal energy harvesting setup, including the thermoelectric generator, heat source, and energy storage unit.  
Figure 2: Solar energy harvesting system.
###### Abstract  
This study aimed to investigate the relationships between the modified \(\mathrm{t-}\)agility test (MAT) time and muscular strength and power of lower limb extensors, adductors (AD), and adductors (AB). Nineteen male basketball players performed: linear sprint tests at 5 m and 20 m, MAT, countermovement (CMJ) and drop jump (DJ), leg press exercise, AD and AB hip maximum isometric strength measurements. All of them were left leg dominant. The correlation analysis showed a significant, moderate to very large negative relationship between MAT test time initiated to the left and height of CMJ and DJ (\(\tau=-0.69\) and \(-0.54;p<0.01\), both), left (\(\tau=-0.56;p<0.01\)) and right leg (\(\tau=-0.41;p<0.05\)) AD, left leg AB (\(\tau=-0.48;p<0.05\)) maximum isometric strength, left (\(\tau=-0.72;p<0.01\)) and right (\(\tau=-0.64;p<0.01\)) leg power output in leg press. In the case of the MAT test initiated on the right side first, the correlations were found between CMJ height (\(\tau=-0.46;p<0.05\)), AD and AB maximum isometric strength of left (\(\tau=-0.58\) and \(-0.84;p<0.01\), both) and right leg (\(\tau=-0.58\) and \(-0.79;p<0.01\), both), and both legs power output in leg press (\(\tau=-0.66\) for left and \(\tau=-0.59\) for right; \(p<0.01\), both). The regression analyses showed that the prediction model of left leg press peak power, left leg AD maximum isometric strength, and CMJ height could explain up to 93% of the MAT test time initiated to the left first. The model, including left leg AB and AD maximum isometric strength, could explain up to 83% of the MAT test time initiated to the right side first. Findings from this study demonstrate that AB and AD maximum isometric muscle strength are highly related to MAT test performance, which is particularly important when the first turn is performed in the non\(-\)dominant direction in this test.  
team sports; change of direction; hip abductors; hip adductors; maximal isometric strength Article
## 4 Numerical Simulation
### Pile Foundation Deformation and Internal Force Analysis  
The subsidence cloud charts of the pile foundations of the culvert after the shield excavation in the reinforced and unreinforced conditions are shown in Figure 22. Before reinforcement, tunnel excavation leads to a decrease in soil pressure along the pile, affecting the soil-friction effect. Moreover, it might result in pile foundation sinking, with a maximum subsidence of 43.69 mm and a minimum subsidence of 20.28 mm. After reinforcement based on the MJS method, the subsidence of the pile foundation was controlled to more than 3.14 mm and less than 8.51 mm. The maximum subsidence was reduced by 80%. Moreover, the subsidence difference of the pile foundation was reduced from 23.41 mm to 5.37 mm, which could effectively avoid the cracked upper structure caused by the excessively large subsidence difference of the pile foundation.  
The horizontal displacement cloud charts of the pile foundations of the culvert in the X direction after shield excavation in the reinforced and unreinforced conditions are shown in Figure 23. According to the cloud chart, the displacement of the pile foundation in the X direction occurs at the bottom of the pile, moving towards the shield tunnel. This is because the loss of the upper stratum is caused by the shield-tunnel excavation, and the soil mass above the tunnel is unloaded. Before reinforcement, the maximum horizontal displacement of the pile foundation was 26.6 mm. After reinforcement, the maximum horizontal displacement was only 4.2 mm, which was a reduction of 84.2%.  
A pile foundation closest to the shield tunnel at the 13 th excavation step of the left tunnel was selected, as shown in Figure 24. The curve shows the changes in the bending moment of the pile foundation before and after the shield construction. In the unreinforced condition, the negative bending moment of the pile foundation was increased by more  
Figure 23: Cloud diagram of horizontal displacement of bridge and culvert pile foundation: (**a**) not reinforced; (**b**) reinforced.  
Figure 22: Settlement cloud image of bridge and culvert pile foundation: (**a**) not reinforced; (**b**) reinforced.  
than 150 kN-m, and the positive bending moment was increased by more than 50 kN-m after the shield construction. Conversely, in the reinforced condition, the bending moment curves of the pile foundation before and after shield excavation nearly overlapped; that is, the additional bending moment could be ignored. This shows that the piles reinforced by the MJS method can \"offset\" the soil pressure generated by the shield excavations.