esa-sceva/satcom-chunk-collection huggingface dataset:
# Integration of the Adaptive Approach in HVAC System Operation: A Case Study
## 4 Conclusions  
The integration of adaptive algorithms based on thermal adaptive behavior is a feasible solution for buildings. Although further studies on thermal comfort and preference are necessary when these guidelines are applied within a building, this study highlights that the percentage of HVAC system usage is low due to a declared preference that differs from the natural behavior of the building or as a result of adjustments through other adaptive measures.  
The present work carried out a field study in an office room for a year, collecting the operational mode of said room and carrying out a survey regarding the thermal preference of the users, although they were required to use the HVAC with a previously defined adaptive setpoint. As for the main conclusions of the work, they are exposed below.  
The analysis of 2859 working hours and 1320 records of thermal preference showed statistically significant TPV responses, with a low percentage of discomfort situations in a Mediterranean climate. The hourly evolution of thermal preference during a working period over a year reveals that in 93.5% of the hours, users are in a neutral or unexpressed thermal acceptability situation. A rate of 86.7% of evaluations correspond to thermal acceptability situations without the need for using the HVAC system (slightly cooler or warmer conditions). Only 10% represent significant thermal preferences requiring the HVAC system as an adaptive measure where the integration of an adaptive law as a setpoint allows for proper building operation, aligning with supporting future proposals for the integration of adaptive setpoints in mixed-function buildings.  
The results obtained reflect a model with a good balance between precision (92.96%) and F1-Score (87.43%), indicating the model's ability to correctly identify thermal comfort in most cases while minimizing incorrect predictions. Although recall (82.52%) and accuracy (77.81%) are slightly lower, the model demonstrates an overall acceptable performance, suggesting that it is suitable for assessing and ensuring the perceived thermal comfort of occupants. These results highlight its potential to optimize both user experience and energy savings, ensuring an accurate representation of the thermal comfort range in real conditions. Additionally, it would be interesting to develop future individual or group learning proposals that could refine the results and further improve the model's capacity to adapt to the specific needs of occupants and changing environmental conditions.
## 5 Results and Discussion
### Calibration of Under-Sampled SAR Data
The squint angle on the x-axis is defined in the antenna reference frame as in (6) and, for this particular response, the zero Doppler frequency corresponds to a squint of \(-4^{\circ}\).
# Systematic Error Correction for Geo-Location of Airborne Optoelectronic Platforms
## 3 Results
### Flight Experiments and Results
#### 3.2.2 Systematic Error Solving
But through simulation and flight experiment, it is recommended that the UAV flies on the left side and right side of the target, and take sample during the azimuth angle near 45, 135, 225 and 325 deg, respectively. (2) Solving the azimuth and heading angle errors  
It can be seen from the systematic error iterative graph in Figure 8 that the roll angle, pitch angle installation error of the POS system and pitch angle error of the platform generally achieved stable results after about 50 measurements. However, the POS heading angle, the installation error and the azimuth angle of the platform require about 200 measurements to obtain stable values. This is because when the platform's installation errors are small, the azimuth angle and the heading angle have the same axis, so there will be coupling when solving. The sum of the errors of the two axes will stay at a fixed value, as shown in Figure 10. Calculations show that if the sum of the two errors remains at a fixed value, the final geo-location accuracy will not be affected.
# Plasma-Sprayed Flexible Strain Sensor and Its Applications in Boxing Glove
###### Abstract  
The most common and easy approach to fabricating flexible strain sensors is based on the deposition principle. To improve the design of the sensing layer pattern, the reproducibility of the process and the sensitivity of the sensor, a controllable low-temperature-plasma spraying method for conducting nanoparticles was proposed. A flexible strain sensor was developed with multiwalled carbon nanotubes as the sensing layer and silica gel films as the substrate. The effects of plasma treatment on the cyclic stability and sensitivity of the sensor were examined and compared. The changes in the sensitivity of the sensor with the pattern parameters were also studied. The sensitivity of the sensor treated with low-temperature plasma was greatly improved (from 3.9 to 11.5) compared to that of an untreated sensor. In addition, pattern parameters significantly affected the rate of change in the resistance. A portable smart boxing glove prototype was developed using the prepared sensor and was then tested. The results showed that the smart glove could transmit and monitor a striking force of 49-490 N in real time with a sampling time, resolution, response time, and recovery time of 100 ms, up to 1.05 kg, 8 ms, and 150 ms, respectively.  
flexible sensor; two-dimensional-plane controllable spraying technology; smart boxing gloves; portable; wireless data transmission +
Footnote †: journal: Medical Imaging and Biomedicine
## 5 Material Parameter Calibration
The calculated crater parameters for screen #9 have values quite close to the experimental values (see Table 2). By increasing the thickness of screen #9 by 1.4 mm compared to screen #2, the depth of the crater decreased while its diameter increased. On a semi-infinite screen, the crater's shape would become hemispherical. Let us examine a two-layer screen composed of aluminum alloy plates on the front and stainless steel on the back (screen #3). The stainless steel 316L plate is 3 mm thick, while the aluminum alloy A356 plate is 4.5 mm thick. In this case, the calculated crater parameters have several high errors: the depth exceeds the experimental depth by 12.5%, the diameter is smaller by 16.4%, and the volume of the crater exceeds the experimental volume by only 5.8%. Figure 8 shows a comparison of the crater cross-sections. In the calculation, the steel plate sustained significantly more damage compared to the experiment, while the  
Figure 6: Comparison of the crater shapes in the 316L steel screen #1: (a) simulation results; (b) optical micrograph of the impact plane in cross-section [18]. Figure 7: Comparison of the crater shapes in screen #2 of the aluminum alloy A356: (a) simulation results; (b) optical micrograph of the impact plane in cross-section [18]. aluminum plate suffered damage and fracture similar to the experimental sample. The only difference is that the plate has a larger diameter but slightly less thickness. It can be concluded that this is the upper limit of the process parameters for material fracture of the screen. For screen #4, made up of the A356 alloy plates and 316L steel, the calculated crater depth is 5.6% less than the experimental one, and the diameter is 12% smaller, but the volume of the crater is almost the same as the experimental one, with only a 2.1% deviation. There are no chips in the steel, nor are there any separate particles torn from the back surface. The calculated crater's distinctive feature is its almost cylindrical shape, which is due to the fragile aluminum alloy being crushed on the steel plate, as shown in Figure 9.  
Thus, methodological calibration calculations were carried out using the physical and mechanical properties from [44; 45; 46] and experimental data from [18], giving the fracture parameters of homogeneous materials summarized in Table 3.  
Figure 8: Comparison of the crater shapes in screen #3—two-layer protection 316L + A356: (**a**) Simulation results; (**b**) Optical micrograph of the impact plane in cross-section [18]. Figure 9: Comparison of the crater shapes in screen #4—two-layer protection A356 + 316L: (**a**) simulation results; (**b**) optical micrograph of the impact plane in cross-section [18].
# Simple Ultrasonic-Based Localization System for Mobile Robots
###### Abstract  
This paper presents the development and validation of a cost-efficient and uncomplicated real-time localization system (RTLS) for use in mobile robotics, specifically within indoor and storage environments. By harnessing ultrasonic waves to measure distances from three beacons, the system provides stable and reliable localization. This method utilizes the time-of-flight (TOF) principle, allowing for accurate distance calculations with simple microcontrollers. The system is designed to update the robot's position at a frequency of at least 10 times per second, ensuring smooth navigation. Our trilateration-based approach allows for the precise determination of the robot's position with a notable standard deviation accuracy of up to 15 mm. The aim was to design a simple yet sufficiently accurate system and verify its precision through experimental measurements. The experimental results demonstrate the system's efficacy and lay a solid foundation for advancing this technology. Furthermore, the cost for the components required to build this indoor localization system (ILS) with three beacons and one tag is remarkably low, under EUR 80.  
indoor localization; ultrasonic; mobile robot +
Footnote †: journal: Applied Physics Letters
# Quantum Circuit Synthesis Using Fuzzy-Logic-Assisted Genetic Algorithms
## 4 Materials and Methods
### Crossover  
In the proposed method, we utilized three different types of crossover operations. In the first crossover operation, complete layers from each chromosome are selected uniformly at random [69] to produce an offspring, as shown in Figure 6a. In the second crossover operation, individual gates from each chromosome are selected uniformly at random, as shown in Figure 6b. We refer to these crossover operations as _coarse-grained crossover_ and _fine-grained crossover_, respectively. Finally, for the third crossover operation, the input and output qubit mappings are swapped, as shown in Figure 6c. Further, each of these crossover operations act on two parents and yield two offspring. At runtime, a random crossover operation is chosen out of the three and applied between two parents.  
During the crossover step, the parents can be selected based on fitness relative to others in the population in order to pass on their genes. If only chromosomes with the best fitness are chosen as parents, then high _selection pressure_[70] is created. A high selection pressure can speed up convergence by only promoting the best solutions to move forward. However, it can also lead to premature convergence [70; 71]. On the other hand, low selection pressure is created when chromosomes with both inferior and superior fitness have similar chances of being chosen as parents. In this case, the genetic exploration is better compared to the high selection pressure scenario since more diverse individuals can participate in reproduction, reducing the risk of premature convergence. However, low selection pressure can slow down convergence. To ensure diversity and steady convergence, we use _tournament selection_[70; 72] for parent selection, as described in Algorithm A1 in Appendix B.1. In this technique, _tournament size_ number of chromosomes are randomly chosen to compete and the chromosome with the best fitness among the selected cohort is selected to be a parent. This process is repeated until the desired number of parents have been obtained. It is worth noting that selection pressure is directly correlated with tournament size. Smaller tournament sizes result in lower selection pressure due to increased randomness in cohort selection, while larger tournament sizes lead to higher selection pressure, as they increase the likelihood of selecting only the highest-fitness individuals in the cohort.  
Tournament selection is a proven selection mechanism that provides a broader selection net while allowing control over the influence of fitness (rank) by adjusting the tournament size. In contrast, purely rank-based selection, where parents are chosen exclu  
Figure 5: Chromosome encoding scheme, including initial and final qubit mapping.  
sively based on fitness, often leads to repeated selection of a limited number of high-ranking chromosomes, resulting in a saturated population with low diversity. Therefore, tournament selection promotes higher diversity compared to purely rank-based methods. In our tests, we use a tournament size of 2.
# DNN-Based FES Control for Gait Rehabilitation of Hemiplegic Patients
## 2 Methods
### Control of the FES Based on Reference EMG
#### 2.2.2 Generation of FES Signal According to Gait Phase  
To generate cyclic gait motion, it is essential to apply the FES signals to the target muscles at a correct time, considering the walking speed. The walking speed can be represented by the time difference of heel strikes (TDH), which is the difference between the times of heel-ground contact of the two feet, measured by FSR sensors. Based on the estimated TDH, the profiles of the reference EMG envelopes were determined and fed to the soleus and TA.  
Along with the measurement from FSR sensors, the finite state machine (FSM) is commonly used to determine the state in the gait cycle [38; 39]. In this study, a threshold-based FSM with FSR sensors was used to determine the gait phase because it is highly accurate for both indoor and outdoor environments with a low computational demand [40].  
Figure 6 illustrates that the FSM-based control algorithm modulates the amplitude and duration of the FES for the soleus and TA. In one gait cycle, there are three states, and the gait state is determined by the on/off signals from the four FSR sensors on the two feet. Depending on the gait state, different control laws were applied to produce FES signals to the soleus and TA.  
State 1 starts at the heel strike on the paretic side. As state 1 starts, a new gait cycle is initiated, and the TDH is updated. In state 1, the reference EMG for the soleus was updated based on the newly updated TDH, while that of the TA was identical to the previous gait cycle. The reference EMG data were fed into the DNN model to yield the joint torque. Subsequently, the FES signals proportional to the positive and negative joint torques were applied to the soleus and TA, respectively.  
State 2 starts at the toe strike on the paretic side. The reference EMG for the TA is updated based on the current TDH, whereas the FES signal for the TA was set to zero. In state 2, the FES signal was applied to the soleus only, based on the reference EMG for the soleus.  
State 3 is the swing phase and starts at toe-off on the paretic side. In state 3, the FES for the soleus was set to zero, and the FES signal was applied to the TA only, based on the reference EMG for the TA.  
When the FSR sensors detect the loss of foot-ground contact for both feet, the control algorithm enters the emergency stop state and sets the FES for the soleus and TA to zero.  
Figure 5: Datasets from the estimation progress of CNN–MLP model at 1 km/h. (**a**) foot-ground contact information on paretic side, (**b**) reference EMG envelope of the soleus and TA, (**c**) estimated joint torque.
## 1 Introduction
Based on current research results, the relevant studies have mainly focused on an analysis of the influence of the excavation unloading process on rock mechanical prop-erties. The common unloading mechanical test idea is as follows. First, the rock sample is loaded to a certain three-way stress state, and then the stress adjustment in the excavation process is simulated. Various stress paths are adopted to unload the rock sample until it is damaged. The deformation and failure characteristics-tics of the rock during the unloading process are analyzed closely. In general, previous studies on the mechanical characteristics of excavation and the unloading of various rocks have been systematic,providing a solid theoretical basis for the stability control of roadways. However, a large number of engineering practices have shown that the damaged rock mass under un-loading is the main bearing structure when the roadway is put into use. At present, the length of the conventional support forms of the mine anchors and cables is difficult to anchor into the original stressed rock mass. Whether it is the end anchor or the whole anchor, its anchoring section is in the damaged rock mass under unloading. Therefore, it is extremely valuable to study the following two aspects to strengthen the effect of sup-porting structures: (1) the mechanical properties and reloading failure mechanism of damaged rock masses with different degrees of pre-peak unloading; and (2) the collabo-rative bearing mechanism of supporting structures and damaged rock masses under pre-peak unloading. On this basis, this pa-per closely focuses on the mechanical properties of damaged rock masses with differ-ent degrees of pre-peak unloading along with the reloading failure mechanism. First, the red sandstone samples are loaded to the state of hydrostatic pressure. Next, the triaxial unloading test is used to prepare the unloadingdamaged samples with differ-ent unloading quantities, and the uniaxial loading test is then carried out. The me-chanical properties and failure mechanism of unloading-damaged rock masses under reloading are analyzed.
## 5 Conclusions  
The paper compares performances of commonly used stochastic inverse and deterministic regularized total least squares (RTLS) methods for simultaneous retrievals of O\({}_{3}\) profile and surface temperature using simulated data. To gain confidence in our approach, ozonesonde data were used to represent highly dynamic and realistic atmospheric states. We reaffirm that RTLS is one of the most effective inverse methods applicable for highly non-linear satellite inverse problems in conjunction with our earlier publications. Interestingly, OEM solution is highly regularized for O\({}_{3}\) retrievals when exact error covariances are used, which is contradictory to our previous study on H\({}_{2}\)O profile retrievals where the problem was very lightly regularized for the same setup. The paper also clearly demonstrates that OEM produces contradictory results across different sensors and various tweaking conditions. This study, based on consistent RTLS solutions and inconsistent OEM solutions between two sensors, confirms that the prevalent inverse method in operation is the primary cause for inconsistent retrievals for same gas profile from different sensors.  
RTLS performances are compared using two different stabilizers, namely LFDO and LSDO and LSDO is outperform than that of LFDO. RTLS retrievals are characterized using subspace analysis. It is found that inherent regularization scheme of RTLS can prevent noise propagation from measurement space to state space holding the information content more than 0.8 along the altitudinal grids. One of the major findings is that RTLS can extract information from the measurement optimally and \(\sim\)50% \"information gain\" is possible from tropospheric O\({}_{3}\) retrieval from CrIS or TES measurement. On the contrary, OEM often yields more errors than are present in the a priori, which leads to loss of information. In this era of advanced hyperspectral measurements from satellites, we emphasize that RTLS-based methods are capable of unambiguously converting \"data to information\" and should be further explored to improve present day retrievals.  
The lead author, [PERSON], undertook all work, conceived and designed the experiments, derived the method, collected and generated data, developed the software, produced results, analyzed and interpreted the data and results, wrote the manuscript, and [PERSON] contributed to the discussions and the writing to improve the quality of the manuscript.  
This work was funded under NASA Grant number 80 NSSC18K0705.  
The authors thank [PERSON], NOAA and [PERSON], UMD for helpful discussions. [PERSON] would like to thank [PERSON], Dalhousie University, Canada, for the insightful discussions and inspiration to build up a paradigm shift idea in the satellite inverse problem when he was working with him.  
There is no conflict of interest. The views, opinions, and findings contained in this report are those of the authors and should not be construed as an official NOAA or US Government position, policy, or decision.
## 1 Introduction
Further examples of its employment are shown by the authors of [27], creating a unique 3D tiling method for a 3D puzzle, and a photominoes synthesizer, detailed in study [28], which applied digital images to the creation of polyomino pieces for a jigsaw. Although numerous research work has been done towards development and application of Polyomino tiling theories, they are largely limited to gaming and graphics domains. Besides, none of the previous works involving tiling theory has been applied to a robotic system towards solving area coverage problem, which opens much opportunity for research and development. In this paper, we present a novel application of Tromino tiling theory, a class of Polyomino with three cells in the context of a reconfigurable floor cleaning robot, hTromo. The developed robot platform is able to automatically generate a global tiling set required to cover a defined space while leveraging on the Tromino tiling theory. The main challenges in the proposed approach include the design of the reconfiguring mechanism, the inclusion of cleaning features and the non-trivial process of implementing theoretical Tromino tiling designs generated analytically into physical mechanisms. All these aspects are detailed in this paper, concluding with experimental results using the prototype hTromo robot that validates the proposed approach. The application of Tromino tiling theory herein presented is a critical effort towards designing a self-reconfigurable robot that is capable of autonomously generating global tiling set for any given space, identifying associated local and global optimal trajectories and generating appropriate motor primitives based on inverse kinematics and dynamics model. Rest of this article is organized as follows: Section \"Polyomino Tiling Theory\" introduces the concept of polyominoes and the specific Tromino tiling theorems implemented in this paper. Section \"hTromo: Robot Architecture\" presents a discussion on the realization of a Tromino inspired floor cleaning robot. This Section covers details on the core component modules of the developed robot namely the reconfigurable base, mobility unit, cleaning module and Android application interface. Section \"Experiments and Results\" details the experimental design involving our hTromo robot and application of Tromino tiling theory, test setup, and analysis of the results. Finally, the Section \"Conclusion\" concludes this study and discusses future work.
# Validating CYGNSS Wind Speeds with Surface-Based Observations and Triple Collocation Analysis
## 3 Results
### Surface-Based Analysis
#### 3.1.2 Extreme Events
(**a–c**) are the Australian dataset and (**d–f**) for the Pacific, comparing FDS, Merged and NOAA respectively with anemometer. 24 h before storm (grey), storm events (blue), 24 h after storm (red). Pacific for all three products--the opposite of what was observed for all wind speeds (Figure 2), suggesting that CYGNSS was more sensitive to 1 min sustained gusts in storm events than the hourly average wind-speed.