esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Methodology
### User Spacecraft
#### 4.3.2 LANDSAT-9  
LANDSAT-9 is a satellite mission of the United States Geological Survey (USGS) in partnership with NASA. The LANDSAT-9 spacecraft was launched into space on 27 September 2021 from the Kennedy Space Center in Florida, USA. The spacecraft was placed in a polar low-Earth orbit with an altitude of about 705 km, an eccentricity of 0.00145, and an inclination of 98.2 degrees.  
The mission is designed to continue the LANDSAT program's legacy of providing critical information about the Earth's natural resources and environment. The mission's primary goal is to collect high-quality, multispectral images of the Earth's surface that can be used for a wide range of scientific and commercial applications [12].  
The FDF semi-annually performs proficiency DOWD OD analysis for the LANDSAT-9 spacecraft. Using an arc length equivalent to 17 LANDSAT-9 revolutions, the LANDSAT-9 orbit was reconstructed through 4 DOWD measurement passes received on 3 April 2022. TDRS-7, -10, -11, and -12 satellites were used during these passes.
# A Systematic Control Design Method with Active Damping Control in Voltage Source Converters
## 3 Design of the Control Gain Matrix
### Robustness Analysis
It is worth noting that, unlike the grid SCR, the PLL bandwidth is a known and, usually, fixed parameter; thus, the design procedure can be performed for the desired value of PLL bandwidth to guarantee the required stability margin and the optimal control gain calculation, as shown in Figure 7a,c. However, additional functionalities are recently suggested for VSCs to support power grids, e.g., transient stability enhancement, virtual inertia implementation, and fault ride-through capability. To obtain these objectives, the VSC may be equipped with a PLL designed with adaptive or gain scheduling techniques. In addition, it would be interesting to know how the PLL bandwidth can affect the system response under the proposed control method and the possibility of implementing a fast PLL. They can be considered reasons to provide Figure 7b. (3) The operational point variations on the system stability should also be investigated since the linearized model around the specific operating point is used to calculate the control gains. As shown in Figure 7c, the inverter power level under a weak grid condition (SCR = 1.5) affects the damping factor and frequency of oscillations; however, the system remains stable under different power levels and both control methods. Under the conventional control method, increasing the inverter power level reduces the stability margin due to higher coupling and interaction between different control loops, VSC, and the power grid. Moreover, the frequency of oscillation is higher at lower powers and vice versa. It can be supposed that the control system's high-frequency parts contribute to the critical mode at lower loading. Moreover, low-frequency control parts affect the critical mode at higher loading. Finally, note that the stability margin is linearly improved under the proposed control method by increasing the inverter power level from lower values to nominal. The reason is that the optimal control gain is calculated for the nominal power, and calculated control gain can provide the optimal performance under this condition. Therefore, we can expect stability to deteriorate as the power level moves away from the nominal value.
# Numerical Analysis of Reinforcing Effect for Scissors-Type Bridge with Strut Members
## 1 Introduction
These reinforcing elements should be designed to be lightweight so they can be installed without heavy machinery. The reinforcing techniques of the scissor structure before/after installation are discussed in a few research studies. For example, [PERSON] [31; 32] used a cable and [PERSON] [33; 34] used a combination of a cable and a strut member. The former study arranged the reinforcing cable starting from a central hinged point and zigzagged it through pulleys to each supporting strut before returning to the starting point. The latter research set the cable and the strut member between each hinge point. From the point of application on the bridge, the latter reinforcing method is expected to reduce the high sectional force in the scissors structure and increase the structural stiffness. Indeed, [PERSON] et al. performed a static loading test using a laboratory scale experimental bridge with cable reinforcement [35]. The experimental result based on the strain and displacement measurement shows the reinforcing effects in comparison with a nonreinforced bridge. In the authors' previous studies, the reinforcing effect of the MB was theoretically and numerically investigated using strut reinforcing members to resist both compressive and tensile forces [36; 37; 38]. However, considering the reinforcing situation was limited, it is not clear where and how much reinforcement should be introduced in the MB. In this paper, we make the reinforcing effect for the scissors structure with strut members through a theoretical and numerical approach clear. When the scissors structure is reinforced by the strut members, the rotation of the scissors member is constrained, and the sectional force distribution significantly changes compared to the nonreinforced state. However, the change in sectional force depends on the conditions, such as the deployment angle of the scissors structure and the cross section of the scissors and strut members. Hence, first, we evaluate the advantages of strut reinforcement by theoretically using a single scissors structure model with different reinforcing positions, focusing on the reduction of the bending moment which is the dominant sectional force. We found that the reinforcing effect indicates a nonlinear solution depending on the deployment angle and cross section of the scissors and strut members. Then, the applicability of the strut reinforcement to the MB with two and three scissors units was evaluated with a numerical simulation. We considered several reinforcing patterns, that is, additional horizontal, vertical, or a combination of horizontal and vertical reinforcing members, and tried to seek optimal reinforcing layout and its sectional area. These results implied that the scissors-type bridge, including the MB, can enhance its performance by using proper reinforcement of the strut members.
# A Resilient LoRa-Based Solution to Support Pervasive Sensing
## 5 Results
### Mesh Tests
#### 5.3.1 Straight Line  
In this experiment, the nodes were put along a (somewhat) straight line on a road, as seen in Figure 10. This configuration was chosen as it mimics that of street lights, as discussed in [17], where messages to control the state of each light (ON or OFF) could be sent from one node to the next one in line. While LoRaWAN could be used to cover this scenario, using it would require multiple gateway nodes to be present in order to connect all lampposts, increasing the number of devices needed to cover the same area and adding complexity.  
All nodes were about 100/150 m from each other and used a spreading factor of 7. Table 3 contains the data gathered from this test.  
This test showed that it could be possible to use the solution proposed in this paper to control street lighting in a smarter way instead of relying on hard-coded timers for the ON/OFF switch or light sensors that could provide unreliable results due to nearby light pollution.  
Figure 10: Positioning of nodes in straight line test.  
Figure 9: Throughput as a function of spreading factor.
## 4 Results and Discussion
### Results of Single Parameter Evaluation
#### 4.1.7 Hydraulic Conductivity  
The permeability of an aquifer is influenced by the type of aquifer medium, and the permeability coefficient partially reflects the lithological composition of the aquifer [44]. Generally, larger particle sizes or more voids in the aquifer medium indicate greater permeability, lower dilution capacity, and higher potential for pollution [45]. The aquifer's permeability coefficient is determined based on the type of aquifer medium, combined with empirical values, and adjusted using data obtained from field exploration and pumping tests (30 groups). The classification of aquifer medium types refers to the data source of aquifer thickness.  
In the plain area, the permeability coefficient was obtained by interpolating the collected drilling data using Kriging interpolation with software such as Golden Surfer. For mountain aquifers, the permeability coefficient is classified based on weathered fissure aquifers in metamorphic rocks, weathered fissure aquifers in igneous rocks, and karst fissure aquifers. The assignment of permeability coefficients is performed according to the aquifer types derived from pumping test results from hydrologic boreholes. GIS technology is utilized to overlay the mountain and plain areas, harmonize layer attributes, and assign values to each partition following evaluation guidelines.  
In the northern mountainous area of Tangshan City, the permeability coefficient mostly ranges from 0.5-5 m/d, with some areas reaching up to 10 m/d. In the southern coastal area, where silt is the predominant aquifer type, the permeability coefficient is relatively low, mostly below 12 m/d. The Shanqian area in central Tangshan exhibits higher permeability coefficients, with the lowest values observed in the north of Zunhua City, Qianxi County, and the northwest of Qian'an City. Conversely, the highest values are found in the east of Fengrun District, the south of Kaiping District, the south of Guye District, and the south of Luanzhou City. The assignment result for hydraulic conductivity in the DRASTIC parameter is presented in Figure 3g.
## 3 Results  
### pH, Water Activity, TBARS  
Table 2 presents the pH, water activity and TBARS values of the dry fermented sausages. At the beginning of the experiment (day 0), the pHs differed significantly between treatments and ranged from 5.98 \(\pm\) 0.02 to 6.04 \(\pm\) 0.02. The pH of the sausage sample with sea salt (S) was significantly (\(p\)\(\leq\) 0.05) higher compared to the sample with curing mixture (C) and sausage sample with sea salt, liquid acid whey and sodium ascorbate (SAWA). During the manufacturing process, significant differences between the samples C and S were also detected. However, data regarding processing time showed that the pH decreased significantly (\(p\)\(\leq\) 0.05) in all samples during ripening. The decrease in pH was significant after every 7 days of manufacturing process in samples C, S and SAW. In the case of the sample with ascorbic acid (SAWA), a decrease in pH value in the stuff and after 7 days was not significantly different (\(p\)\(\leq\) 0.05), but in next period time the changes were also significant. The addition of acid whey caused the greater acidification of fermented sausages at 7, 14 and 21 days compared to cured (C) and salted (S) sausages. During the manufacturing, water activity (a\({}_{w}\)) decreased significantly in all samples (Table 2). The highest changes in a\({}_{w}\) values were observed between stuff and after 7 days of manufacturing as well as between 14 th and 21 st day of processing. At 21 day water activity ranged from 0.867 \(\pm\) 0.002 in SAW sample to 0.875 \(\pm\) 0.003 in C and S samples. The differences in water activity in the samples with acid whey (SAW, SAWA) and other samples (C, S) were statistically significant at the end of production. Regarding the lipid oxidation, during the production of dry fermented sausages, no significant influence of the processing time on the TBARS value was observed (Table 2). However, acid whey and sodium ascorbate's combined addition resulted in significant changes of the TBARS value compared to acid whey separate addition or the treatment C and S. At 0, 7,14 and 21 days, samples with acid whey and ascorbic acid (SAWA) were characterized by significantly lower TBARS values compared to other samples. \begin{table}
# Evaluating the Impact of Optical Interconnects on a Multi-Chip Machine-Learning Architecture
###### Abstract  
Following trends that emphasize neural networks for machine learning, many studies regarding computing systems have focused on accelerating deep neural networks. These studies often propose utilizing the accelerator specialized in a neural network and the cluster architecture composed of interconnected accelerator chips. We observed that inter-accelerator communication within a cluster has a significant impact on the training time of the neural network. In this paper, we show the advantages of optical interconnects for multi-chip machine-learning architecture by demonstrating performance improvements through replacing electrical interconnects with optical ones in an existing multi-chip system. We propose to use highly practical optical interconnect implementation and devise an arithmetic performance model to fairly assess the impact of optical interconnects on a machine-learning accelerator platform. In our evaluation of nine Convolutional Neural Networks with various input sizes, 100 and 400 Gbps optical interconnects reduce the training time by an average of 20.6% and 35.6%, respectively, compared to the baseline system with 25.6 Gbps electrical ones.  
machine learning; accelerator; optical interconnect; multi-chip architecture; cluster; Convolutional Neural Network (CNN) +
Footnote †: journal: Electronics
## Results
### Switching Task Accuracy  
The omnibus analysis revealed no significant main effect for intervention type, however, there was a significant intervention x switch trial interaction (F(6270) = 4.1, \(p\) = 0.001), a trend towards significance for the intervention x task x session interaction (F(4320) = 2.18, \(p\) = 0.070) and a main effect of session (F(2320) = 3.63, \(p\) = 0.028). As shown in Figure 5a post hoc analysis revealed a trend towards significance whereby there was a reduction in accuracy for placebo between 2 h and 6 h (\(p\) = 0.050).  
As shown in Figure 5b post hoc analysis of the intervention x switch trial interaction revealed that for placebo there was a significant difference between S0 and S1 (\(p\) = 0.004), S2 (\(p\) = 0.027) and S3 (\(p\) = 0.012), however following the berry intervention there was only a significant difference between S0 and S3 (\(p\) = 0.016), and a weak trend between S0 and S1 (\(p\) = 0.084) indicating less evidence of a cognitive demand related switching cost (i.e., the difference between the S0 trial immediately following task switch and the following S1, S2, and S3 non-switch trials).  
Post-hoc analysis of the intervention x task x session interaction revealed no significant pairwise comparisons, however, for placebo, there was a trend for less accurate performance at 6 h in comparison to 4 h on the high/low task (\(p\) = 0.056) along with a weak trend for less accurate performance at 4 h in comparison to 2 h on the odd/even task (\(p\) = 0.092). For the berry treatment there was a weak trend for less accurate performance at 6 h in comparison to 2 h on the odd/even task (\(p\) = 0.094). A further trend was found for less accurate placebo performance in comparison to the berry treatment on the high/low task at 6 h (\(p\) = 0.078).
## 2 Technological Background and Related Work  
Though multi-core systems have high throughput, the performance increase depends on the placement of tasks and their data on nodes during runtime. Task placement affects contention between resources for the cache and cores, and data placement affects the memory access cost for a task. To utilize system resources more efficiently and increase performance, many studies [7; 8; 9; 10; 11; 12; 13; 14; 15] design specific placements of tasks and data to decrease resource contention, balance the loads in the cores, and reduce access to remote memory. The solutions focus on improving the performance of Symmetric Multi-processing (SMP) and Non-Uniform Memory Access (NUMA) [2] systems.  
However, the rises of multithreaded applications cause finding specific task placement or data placement to increase performance more complicated. Since threads in one multithreaded application commonly share memory address space, and if they run on cores that do not share or share fewer cache resources, tasks are placed less efficiently because of more cache misses. In terms of data placement, there are different memory access latencies for cores access memory on different nodes. It is more challenging to determine where to allocate the required memory for the requesting task on NUMA systems.  
This section first describes two types of multi-core systems and then reviews related work in Section 2.2. Section 2.3 introduces the kernel-based Memory-aware Load Balancing (kMLB) [4] mechanism and task selection policies proposed for improving inter-node migration.
# Study on the Time Domain Semi Analytical Method for Horizontal Vibration of Pile in Saturated Clay
###### Abstract  
Under the framework of Biot porous media theory, a fractional order Kelvin model is used to describe the rheological effects of soil skeletons, and a coupled vibration model of saturated clay and a pile foundation is constructed. The Laplace transform is used to derive the analytical solution of the control equation in the transformation domain, and then the time-domain solution is obtained through numerical inversion. By analyzing numerical examples, the displacement and internal force response of pile foundations under horizontal vibration loads, as well as the influence of parameters, are studied. The results show that the displacement and internal force response of pile foundation vibrations in saturated clay foundations have a delayed effect. The stronger the rheological properties of the foundation soil, the more obvious the delay, the lower the load frequency, and the more significant the influence of the rheological properties on the delayed effect. The stronger the rheological properties of the soil, the smaller the displacement amplitude of the pile foundation vibration, and the higher the load frequency, the greater the decrease in displacement amplitude. The stronger the rheological properties of the soil, the smaller the positive bending moment of the pile body, while the negative bending moment increases. Both positive and negative shear forces increase, but the shear force at the top of the pile is not affected. Therefore, when designing pile foundations in saturated clay foundations, it is necessary to appropriately increase the pile foundation or increase the reinforcement to meet the shear resistance of the pile foundation. The results of this study can provide a valuable reference for geotechnical and seismic engineers in pile foundation design.  
saturated clay; pile foundation; horizontal vibration; rheologic effect; Laplace transform +
Footnote †: journal: Applied Sciences
# Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform
###### Abstract
However, most conventional radars are basically designed to operate on the microwave frequency band between 300 MHz (1 m) and 300 GHz (1 mm). On the other hand, several chaos radar systems have been designed and implemented for various secure communications [7; 8; 9; 10]; they may employ coherent signal processing schemes either by matched filter or correlation to reduce the noise and eventually obtain the highest improvement in Signal-to-Noise Ratio (SNR) [7; 11]. Another issue in chaotic based radar systems (CBRS) is choosing the type of chaos synchronization between the transmitter and the receiver nodes. Conversely, traditional synchronization schemes such as Phase-Locked Loop (PLL) can be used in chaotic radars [4]. In fact, there are many studies on complete synchronization and feedback control [7; 8] in a radar system, but the limitation is raised due to its sensitivity to noise, and any tiny amounts of additive noise to the (echo) signal can degrade the synchronization quality, and the chaotic signals may not be synchronized [11]. Moreover, some CBRS systems have been widely studied, either with no modulation, such as pulse compression, or within a variety of modulation methods, such as continuous AM/FM/PM modulation where many CBRSs are utilized in microwave and UWB and laser applications [4; 12; 13]. One example was devoted to a microwave chaos signal practically generated through the Colpitts oscillator and directly transmitted through a wide-band antenna without modulation [7; 8]. In this paper, therefore, the key issue is how to design a robust chaotic radar system that can provide a complete- or quasi-synchronization in order to successfully recover the echo signal and then detect the target. To achieve this goal, we present a new robust indirect mono-static FM-based chaos radar using a time-delayed chaotic system under various levels of noise over the wireless channel. The design is simple and it does not need to use the complete self-synchronization or any complex projective synchronization schemes. Figure 2: A general principle of the simple monostatic continuous radar system. The following is a breakdown of the paper's structure: Section 2 introduces an overview of the frequency band design of radar systems and stealth counters. Section 3 explains the chaos radar challenges and the main contribution in this study. Section 4 addresses some related works on chaotic radars. The dynamical analysis of the mathematical model of the first-order time-delay chaotic system, as well as its dynamical properties such as the phase portrait chaotic attractor, equilibrium points, Nyquist plot, and bifurcation diagram, are presented in Section 5. Section 6 describes the chaotic signal based on FM modulation and how to modulate the chaotic signal with the voltage control oscillator (VCO) to generate continuous FM signals and then recover the reference signal with the PLL. Section 7 explains the comparative performance with the existing chaotic radars. Finally, Section 8 summarizes the conclusions and perspectives of this paper.