esa-sceva/satcom-chunk-collection huggingface dataset:
# Correlations between SSQ Scores and ECG Data during Virtual Reality Walking by Display Type
## 2 Research Methods  
### Experimental Design  
Eleven men in their 20s (age 23.7 \(\pm\) 2.5, height 176.5 \(\pm\) 5.5 cm, weight 74.6 \(\pm\) 12 kg) participated in this study. The protocol for the research project was approved by the Institutional Review Committee of Konkuk University, where this study was performed, and conforms to the provisions of the Declaration of Helsinki (IRB number: 7001355-202307-HR-675).  
In the experiments, Unity 3D (Unity Technologies, San Francisco, CA, USA) was used to present the subjects with a virtual straight walking path (Figure 1), and they walked continuously on a treadmill (DRAX, RX9200, Anyang, Gyeonggi-do, Republic of Korea). The virtual scene was presented to the subjects via a screen (160 cm \(\times\) 120 cm) and an HMD (Oculus Quest 2, Meta, weight: 503 g) (Figure 2).  
The experiment was conducted under two conditions: screen walking, where participants walked on a treadmill while looking at a screen (160 cm \(\times\) 120 cm), and VR walking, where participants walked on a treadmill while wearing a Head-Mounted Display (HMD). In both conditions, the screen moved in sync with the participant's walking speed on the treadmill. The experimental design for both conditions was identical, as shown in Figure 3. The baseline segment involved participants standing still and looking at the screen for 1 min in a rest state. During the walking segment, participants performed a total of 15 min of walking on a straight pathway, with the walking speed fixed at 3.6 km/h. The rest segment was a break period, during which participants were instructed to stand still and look at the screen to return to a rested state. The experiment was conducted randomly, with a 30 min rest period after the walking experiment of one condition before performing the walking experiment of the other condition. Each condition was performed once, without repetition.  
Figure 1: Virtual environment presented in the study (straight walking path).
# LDPC Coded Massive MIMO Systems
## 5 Numerical Results
### Performance Comparison without Complexity Constraint  
We next considered the JDD without constraint on the amount of computational complexity. We investigated the threshold and BER obtained with different values of \(N_{dec}\), where the case of \(N_{dec}=1\) corresponded to the reference system using GIO JDD. In Table 3, we list optimal degree distributions of LDPC codes and resultant thresholds for some values of \(R\), \(N_{dec}\) and \(d_{v,\max}\) with \(n_{T}=n_{R}=16\). It was observed that the proposed JDD strategy and the GIO JDD resulted in the same threshold for given \(d_{v,\max}\) and \(R\). In Figure 7, we plot BER performances of coded massive MIMO systems with \(N=\) 64,000 over \(16\times 16\) channel for some values of \(N_{dec}\) and sufficiently large \(N_{g}\). The degree distributions listed in Table 3 corresponding to \(d_{v,\max}=24\) and \(d_{v,\max}=20\) for \(R=0.5\) and \(R=0.75\), respectively, were used for generating LDPC codes. We used \(N_{g}=200\) and \(N_{g}=85\) for \(N_{dec}=1\) and \(N_{dec}=15\), respectively, when \(R=0.5\) and we used \(N_{g}=100\) and \(N_{g}=90\) for \(N_{dec}=1\) and \(N_{dec}=5\), respectively, when \(R=0.75\). It was observed that the proposed JDD strategy and GIO JDD showed similar BER performances if a sufficiently high amount of computational complexity was allowed. This result agreed with the threshold analysis presented in Figure 6 and Table 3.  
Figure 6: The threshold of the LDPC coded massive MIMO system with the proposed JDD strategy and with the GIO JDD obtained by the density evolution algorithm given in Algorithm 3, where \(R=0.5\) and \(R=0.75\) were considered with \(n_{T}=n_{R}=16\). corresponding to \(d_{v,\text{max}}=3\) and \(d_{v,\text{max}}=20\) for GIO JDD and the proposed JDD strategy, respectively. In Figure 8, we plot BER performances of the LDPC coded massive MIMO system equipped with the proposed JDD strategy and with GIO JDD over \(16\times 16\) channel. It was observed that using the proposed JDD strategy resulted in a lower BER than using GIO JDD. This result agreed with the threshold analysis presented in Tables 4 and 5. Consequently, the jointly designed LDPC codes and JDD strategy could result in the lower BER of coded massive MIMO system by using the equivalent amount of computational complexity. As shown in Figures 9 and 10, we compared BER performances of the proposed LDPC coded massive MIMO system and the conventional system with various numbers of antennas, where the conventional system was equipped with the conventional LDPC codes and GIO JDD [38]. As the proposed system, we constructed the rate-0.5 LDPC codes with \(N=4096\) using the degree distribution corresponding to \(d_{v,\text{max}}=24\) in Table 4 and the rate-0.75 LDPC codes with \(N=2048\) using the degree distribution corresponding to \(d_{v,\text{max}}=3\) in Table 5. It was observed (Figures 9 and 10) that the coding gain of the proposed system over the conventional one at the BER of \(10^{-5}\) over \(16\times 16\) channel was about 2.3 dB and 1.4 dB for \(R=0.5\) and \(R=0.75\), respectively.
## 3 Error Correction Framework
### Stage 2: Realtime (Dynamic) Error Correction
Sensor Tracking enables the robot controller to change the position in case of error. It helps to change the current robot position whilst the robot is moving. It helps to run the dynamic error correction in realtime [18]. iii. Communication Interface passes the information from the controller to the requested module and also receives the requests from the modules. 4. **Communication through the Network:** The NRTEC system is based on the concept of communication, which is performed through the network. TCP/IP is used as a protocol to perform this communication. Web services are used to communicate to the outside world system, such as FLEXA [20] (FP7 project, 2010-2012). 5. **Metrology System:** The metrology system is needed to determine the current position of the robot. Its feedback is crucial to determine the robot kinematical error. The Leica Tracker was chosen as the device for metrology work because of its proven accuracy. 6. **Database:** The database is used to store the steps performed by the system on each stage. It stores the robot position, metrology measurements, calculated errors and noise. All of this information is stored along with the timestamp details. Figure 6 details the algorithm for the error correction and compensation side in the NRTEC system. The main error correction and compensation is run through the Compact RIO project. The MPC is implemented to control the complete process along with a Kalman filter. The system starts with the trajectory calculation for the robot path. The system provides the path to the robot and the robot start moving along the trajectory. The system then starts the concurrent process of running the error correction and compensation mechanism while the robot is moving. There is a concurrent loop inside the system in the Compact RIO, which handles the timesteps for error correction phases. These timesteps can be increased or decreased according to the requirement of the application. The system asks the measurement device to provide the measurement based on the timestep. The system then performs the calculations to transform the measurement into the robot coordinate system. Once the measurement is in the robot, the coordinate system for the forward kinematics is performed to determine the TCP/IP value, which is then compared with the robot controller's TCP (tool centre point) values. If there is a difference between values, then inverse kinematics is calculated to make certain the robot is aligned to the measured position. The inverse kinematics provides the robot join angles that are provided to the robot controller through sensor tracking, which makes certain that offsets are applied while the robot is moving. The output is also supplied to the neural network, which helps tolearn the system and its errors. Once the system learns its errors, the offset drops and there is no need to take measurements for the trained path.
# A Method to Reduce Non-Nominal Troposphere Error
## 4 VPL under Non-Nominal troposphere  
In the development of the Radio Technical Commission for Aeronautics (RTCA), Federal Aviation Administration (FAA), and International Civil Aviation Organization standards, the following assumptions were made: all non-zero mean components could be mathematically removed from the differential corrections before broadcasting to the aircraft, and the pseudorange error (thermal noise, multipath, ionospheric error, troposphere error and interference) obeys a zero-mean Gaussian distribution [10]. However, it is not practical to completely remove all non-zero mean components in the pseudorange corrections because of realistic factors (i.e., GBAS site selection, ground station reference receiver antenna calibration and meteorological factors). Given these inherent difficulties, it was decided that where the removal of non-zero mean errors is not possible, the error sources must be overbounded.  
Figure 9: Relationship between the non-nominal troposphere error and satellite elevation.  
VPL is an important indicator for assessing GBAS performance. This parameter provides a confidence boundary to bind the positioning error with a large probability (defined by an integrity risk of less than \(2\times 10^{-7}\)) [14].  
In 2004, [PERSON] proposed an alternate VPL methodology to bind the conspiring error [10]. This alternate VPL-C consists of the component that arises from only the pseudorange error that obeys a zero-mean Gaussian distribution and the component that arises from conspiring biases.
## 2 Interval Iterative Otsu Method Based on Region Growing
### Interval Iterative Otsu Method Based on Region Growing
#### 2.2.2 The Final Stage  
According to the final thresholds (\(T_{1}\), \(T_{2}\),..., \(T_{k-1}\), \(T_{k}\)) obtained by region growing methods, the pixels of the original image are divided into \(K+1\) categories, and the mean of each category is recorded as \(\mu_{1,I}\) (\(i\) = 1,..., \(K+1\)). Pixels whose gray value \(p_{i}\leq\mu_{1,1}\) are divided into class \(C_{1}\), while pixels whose gray value \(p_{i}\geq\mu_{1,K+1}\) are divided into class \(C_{K+1}\). The remaining pixels are divided into \(K\) intervals [\(\mu_{1,1}\), \(\mu_{1,2}\)], [\(\mu_{1,2}\), \(\mu_{1,3}\)],..., [\(\mu_{1,K-1}\), \(\mu_{1,K}\)], and [\(\mu_{1,K}\), \(\mu_{1,K+1}\)]. Figure 3 depicts an example of interval iteration. Figure 3a shows the grayscale interval, and Figure 3b shows the updated grayscale interval after the first interval iteration. In Figure 3a, the intervals filled with different colors are to be iterated continuously next.  
Next, Otsu single-threshold segmentation is performed in intervals [\(\mu_{1,1}\), \(\mu_{1,2}\)], [\(\mu_{1,2}\),..., [\(\mu_{1,K-1}\), \(\mu_{1,K}\)], and [\(\mu_{1,K}\), \(\mu_{1,K+1}\)], respectively, to obtain the thresholds \(T_{2,i}\) (\(i\) = 1,..., \(K\)) and the corresponding class means \(\mu_{2,2i-1}\), \(\mu_{2,2i}\) (\(i\) = 1,..., \(K\)). Pixels whose gray value is located in the interval [\(\mu_{2,i}\), \(\mu_{2,i+1}\)] (\(i\) = 2,..., \(2K-2\)) are divided into \(C_{j}\)(\(j\) = 2,..., \(K\)), as shown in Figure 3b.  
Figure 2: Final thresholds obtained by region growing.  
Repeat the above process in class \(C_{j}\) (\(j=2,\,\ldots,\,K\)) to obtain the threshold and class mean, and re-divide \(C_{j}\) (\(j=2,\,\ldots,\,K\)) until the threshold is satisfied \(\left|T_{h,r}-T_{h-1,r}\right|<\delta\), (where \(\delta>0\)). The final obtained \(T_{h,r}\) (\(r=1,\,\ldots,\,K\)) is the optimal threshold \(T_{r}^{\prime}\) (\(r=1,\,\ldots,\,K\)). Figure 4 shows all the optimal thresholds obtained by RGIIM.
## 3 Test Results and Discussion
### Load-Concrete Strain Relationships for All Specimens  
The developed concrete compressive strains were measured using strain gauges positioned 115 mm above the deck overhang's upper surface and at the barrier wall's front face at three distinct locations, as illustrated in Figure 8c. Figure 13 presents the load-concrete strain relationships for all tested specimens. The average concrete compressive strains at the point of failure were recorded as 818, 868, 688, 1045, 893, and 701 \(\upmu\epsilon\) for specimens B-1, B-2, B-3, B-4, B-5, and B-6, respectively. These values are significantly lower than the ultimate concrete compressive strain at failure, which is 3500 \(\upmu\epsilon\). The observed low strain values can be attributed to the failure of the barrier-deck junction consistently occurring at locations distant from the measurement points.  
Figure 13: Load–concrete strain relationships for all specimens.  
Strain data indicated that neither concrete nor GFRP bars reached their ultimate strain capacities prior to failure. Maximum concrete compressive strains remained well below 3500 \(\mu\epsilon\), and GFRP bar tensile strains were below the 1.67% rupture threshold. These findings confirm that failure occurred due to concrete cracking or GFRP bar pullout, not GFRP bar rupture. In overhang systems, diagonal tension cracks controlled failure, while in thick deck slabs, pullout failure dominated.
###### Abstract  
Microcapsules are employed extensively in various applications; however, most are composed of synthetic plastics. Thus, substitution of their component materials is essential to prevent environmental problems associated with primary microplastics. Herein, we report the synthesis of eco-friendly silica core-shell microcapsules for fragrance retention. The silica shell was prepared via oil/water emulsion template synthesis using tetraethyl orthosilicate (TEOS), which was added to the immature silica microcapsules prior to complete formation of primary silica shells to promote seeded growth for further reaction of silica. The thickness of the silica shell increased from 42.29 to 70.03 nm, while the Brunauer-Emmett-Teller surface area and internal pore area decreased from 155.16 and 30.08 m\({}^{2}\)/g to 92.28 and 5.36 m\({}^{2}\)/g, respectively. The silica microcapsules with lower surface areas retained fragrance for more than 80 days, even in a harsh environment of 15% sodium dodecyl sulfate at 60 \({}^{\circ}\)C, whereas the fragrance compound in those without additional TEOS treatment was completely released within seven days. Practical qualitative evaluation of fragrance was also performed for application in fragrance delivery because of the enhanced long-term fragrance retention ability. Our findings show the widespread potential of microcapsules synthesized from eco-friendly materials in industrial applications.  
microcapsules; silica shell; fragrance retention; seeded growth; oil/water emulsion template; microplastics alternatives +
Footnote †: journal: Applied Sciences
# Study on New Bolted T-Stub Connection with Inserted Plates under Axial and Cyclic Loads
## 4 Test Observations, Results and Analysis
### Cyclic Test
#### 4.3.2 Energy Dissipation Capacity  
In order to further probe into the influence of existent plates and their widths, as well as the length of flange on the energy dissipation capacity of specimens, energy dissipated in each cycle was estimated by determining the area surrounding each loop, as illustrated in Figure 11.  
Figure 11: Energy dissipated by specimens at each cycle represent specimens from groups (**a**) TC, (**b**) WA and (**c**) WB.  
According to Figure 11a, the average energies consumed by specimens TC-P-50-38-H, TC-P-50-40-H and TC-P-50-42-H were about 1.35, 1.5 and 1.65 times as much as specimen TC-N-50-0-H, further confirming that the addition of plates can effectively strengthen the energy dissipation capacity, mainly thanks to the deformation space available under compression. As a plate's width grows from 38 to 42 mm, the energy consumed increases steadily. For every 2-mm increase in width, the energy consumption rises by about 10%. With reference to specimen TC-P-50-40-H and specimen TC-P-60-40-H, the 10-mm growth in length of flange resulted in an increase of about 16% in energy dissipation capacity. Therefore, an increase of flange length by 10 mm was more effective than a 2-mm plate width when comparing average energy dissipation among specimens TC-P-50-40-H, TC-P-60-40-H and TC-P-50-42-H.  
Figure 11b demonstrates that the average energy dissipated by specimen WA-P-50-40-H was about 14% larger than that consumed by specimen TC-P-50-40-H; namely, under the same conditions, the overall energy dissipation performance of welded specimens was better than that of rolled specimens. This result aligns with the previous analyses of tension-displacement, compression-displacement and hysteretic curves in which the better elastic-plastic performance of welded specimens was verified.  
When the width of plates rose from 40 to 46 mm, the energy dissipation capacity of specimens presented an average growth of about 23% and 38% in groups WA and WB, respectively (see Figure 11b,c). When it continued to rise to 52 mm, the growth of energy consumption capacity was been guaranteed, but declined by about 3% as a whole. It is shown that unduly wide plates seriously degrade energy dissipation performance. In addition, it should be noted that due to the excessive wide plates and too-thick T-stub flange and web, the two bolts of specimen WB-P-50-52 showed a shank necking action in the late period of cyclic loading, and failed to go through as many cycles as the other specimens did (see Figure 11c).
# A Review on Applications of Fuzzy Logic Control for Refrigeration Systems
## 4 Conclusions  
In this review, the application of the fuzzy controllers to the RACs is proposed. This review also includes the implementation and design of these systems as well as the results obtained from the different types of implementations. Detailed information about the application of the fuzzy controllers in the RACs is also presented. In the same sense, the input and output variables, the inference methods, and the different shapes for the membership function are explained looking for possible energy savings in these systems:  
* It was shown that the use of fuzzy controllers in the RACs has allowed the obtaining of a better thermal efficiency than that of classic controllers, such as the ON/OFF and the PID. Additionally, it is possible to improve the results when the controller is integrated with artificial neural networks or genetic algorithms;
* Computer simulations and experimental validation have shown that the use of fuzzy controllers can reduce energy consumption. Furthermore, the implementation using different control strategies, such as fuzzy-PID or the fuzzy neuro-controllers has allowed better energy savings than using only one type of control.  
Conceptualization, J.M.B.-F. and D.A.R.-V.; methodology and writing of the paper, J.M.B.-F.; analysis of the information, investigation, and writing of the paper, D.M.P.-C., J.J.G.-P., S.L., D.H.; review and editing, J.M.B.-F. and D.A.R.-V.; All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
We acknowledge the University of Guanajuato for their sponsorship in the realization of this work.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Authors** & **Control Application** & **Simulation** & **Experimental Study** & **Energy Saving** \\ \hline [PERSON] et al. [26] & Chiller & X & & 1\% \\ [PERSON] et al. [31] & Industrial plant & & X & 13\% \\ [PERSON] et al. [28] & Chiller & & X & 17\% \\ [PERSON] et al. [76] & Chiller & X & & \(-\)3.15\% \\ [PERSON] et al. [41] & Air conditioning & & X & 5.27\% \\ [PERSON] et al. [44] & Air conditioning & & X & 35.59\% daily \\ [PERSON] [59] & Air conditioning & & X & 36\% annual \\ [PERSON] et al. [60] & Air conditioning & & X & 39.14\% to 64.35\% \\ [PERSON] [63] & Domestic & & X & 12\% \\ [PERSON] et al. [66] & refrigerator & X & & 3\% \\  & Domestic & X & & 0.3957 W \\ [PERSON] et al. [67] & Domestic & & X & 3\% \\  & refrigerator & & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Reduction in energy consumption due to the use of fuzzy control.
IV-SSIM--The Structural Similarity Metric for Immersive Video Applications--IV-SSIM. The proposed IV-SSIM metric is an evolution of our previous work--IV-PSNR (immersive video peak signal-to-noise ratio)--which became a commonly used metric in research and ISO/IEC MPEG standardization activities on immersive video. IV-SSIM combines the advantages of IV-PSNR and metrics based on the structural similarity of images, being able to properly mimic the subjective quality perception of immersive video with its characteristic distortions induced by the reprojection of pixels between multiple views. The effectiveness of IV-SSIM was compared with 16 state-of-the-art quality metrics (including other metrics designed for immersive video). Tested metrics were evaluated in an immersive video coding scenario and against a commonly used image quality database--TID2013--showing their performance in both immersive and typical, non-immersive use cases. As presented, the proposed IV-SSIM metric clearly outperforms other metrics in immersive video applications, while also being highly competitive for 2D image quality assessment. The authors of this paper have provided a publicly accessible, efficient implementation of the proposed IV-SSIM metric, which is used by ISO/IEC MPEG video coding experts in the development of the forthcoming second edition of the MPEG immersive video (MIV) coding standard.  
image quality; immersive video; video compression; view rendering; structural similarity
# Preliminary Validation of Surface Reflections from Fengyun-3C Radio Occultation Data
###### Abstract  
Fengyun-3C (FY-3C) is a Global Navigation Satellite Systems (GNSS) Radio Occultation (RO) mission founded which was by China on 23 September 2013. In this study, under a specific temporal and spatial domain, we systematically compare FY-3C refractivity profiles with Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) refractivity profiles for the year 2015. The COSMIC profiles used in this study contain reflections, as identified in the Radio Occultation Meteorology Satellite Application Facility (ROM SAF) flag database. From 0 to 25 km altitude, the mean biases and relative standard deviations of the comparisons between FY-3C and COSMIC are less than 1% and 2% when COSMIC profiles present reflected signals. Radio holographic analysis is used to visualize and identify the spectra of FY-3C-reflected signals in the time-frequency domain. It is confirmed that the reflected signals in the lower troposphere and near the surface can be tracked by an FY-3C receiver. Further, most of the FY-3C events that matched with COSMIC reflected events show reflection patterns at a lower height, especially above the ocean's surface. Under Bouguer's rule and spherical symmetry assumptions, we reconstructed the reflected bending angle models by Abel transformation, which are valuable for reducing N-bias in the ducting layer. Three examples of FY-3C events show that the reflected bending branch is near the surface. Overall, the reflected signal of FY-3C could be used as a supplementary data portion for FY-3C atmospheric products.  
Fengyun-3C; radio occultation; quality analysis; reflection Article Preliminary Validation of Surface Reflections from Fengyun-3C  
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