esa-sceva/satcom-chunk-collection huggingface dataset:
# Non-Probabilistic Reliability Analysis of Slopes Based on Fuzzy Set Theory
###### Abstract  
Aimed at the problem of fuzzy uncertainty of geotechnical parameters in slope stability analysis, a non-probabilistic reliability analysis method for slopes based on fuzzy set theory is proposed. Geotechnical parameters are described as fuzzy numbers, which are transformed into interval numbers at different cut set levels by taking fuzzy sets. The corresponding non-probabilistic reliability indexes and failure degrees of the slope are calculated by the non-probabilistic reliability analysis method based on the ellipsoidal model, and then the overall failure degree of the slope is obtained by weighted average to judge the stability state of the slope. The feasibility of the method was verified by a case analysis. The results show that the type and shape parameters of the fuzzy affiliation function of geotechnical parameters have a great influence on the non-probabilistic reliability of the slope. The slope failure degrees obtained from trapezoidal fuzzy numbers were larger, the slope failure degrees obtained from triangular fuzzy numbers and normal fuzzy numbers were medium, and the slope failure degrees obtained from lognormal fuzzy numbers were smaller. When considering soil parameters as triangular fuzzy numbers, normal fuzzy numbers, or lognormal fuzzy numbers, with the reduction of the shape parameters, the non-probabilistic reliability indexes of the slope increased while the failure degrees decreased. Additionally, adopting the overall failure degree to evaluate the stability of the slope can effectively solve the problem where the calculation results are too conservative (if the non-probabilistic reliability index is greater than 1) to judge the stability state of the slope in the traditional non-probabilistic reliability method.  
slope; non-probabilistic reliability; fuzzy set; ellipsoidal model; failure degree
# Reconfiguration Decision-Making of IoT based Reconfigurable Manufacturing Systems
## 5 Decision-Making System
### Decision-Making Process
#### 5.1.2 Decision-Making Factors  
When a situation for reconfiguration occurs, it is necessary to build a reconfiguration plan that includes the outcome and timing of reconfiguration. First, it is necessary to decide which machine is to be reconfigured and the outcome of reconfiguration. Then, the time schedule of each machine's reconfiguration needs to be decided. This is scheduled in consideration of a reconfiguration time, the unavailable time of machines, and the current production plan. During reconfiguration, connected machines have to stop. Therefore, it greatly influences a production plan. In this study, a reconfiguration time was set based on the assumption that reconfiguration is possible after stopping related machines in the entire manufacturing line.  
Through reconfiguration, a manufacturing system is modified to meet given goals such as a productivity level and a regulation change. As the current manufacturing system has a change through reconfiguration, it is natural to apply existing production policies such as a scheduling rule and an objective function to the reconfigured system. The result drawn by reconfiguration is operated and evaluated according to these policies. The dispatching rules for production scheduling generally applied include FIFO (first in first out), SPT (shortest processing time), and EDD (earliest due date). There are various target objective functions such as a due date and a level of productivity.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Category** & \multicolumn{2}{c}{**Situation**} \\ \hline External & Change of product mix & Introduction of new products changes in product combinations \\  & Introduction of additional processes due to environmental regulation or additional features \\ \hline Internal & Lack of productivity & Reconfiguration for enhancing the productivity of a production line \\  & Breakdown & Replacement due to sudden failure of the machine and reconfiguration \\  & Preventive maintenance & Preventive maintenance and reconfiguration \\  & & according to tool life and internal condition \\ \hline \hline \end{tabular}
\end{table}
Table 2: An example of reconfiguration situations.  
Figure 4: Reconfiguration process of the RMS.  
Before reconfiguration decision-making, it is required to determine the reconfiguration targets. For efficient reconfiguration, reconfiguration targets have to include both reconfigured modules and their related modules. The algorithm proposed in this study considers all modules as reconfiguration targets in reconfiguration planning and takes into account every available reconfiguration starting time.
# Predicting C/N0 as a Key Parameter for Network RTK Integrity Prediction in Urban Environments
## 2 Experiment  
A kinematic experiment was conducted on 29 July 2021, in which four different RTK receivers, namely Leica GS18 T, Trimble R12i, Septentrio Altus NR3 and an integrated antenna with a u-blox ZED-F9P receiver, were used (Figure 1b). In addition to the RTK receivers, one navigation-grade IMU (iMAR iNAT-RQT-4003) (Figure 1c) was installed inside the vehicle to compute a precise reference trajectory [32]. GNSS RTK receivers have internal GSM modems and are capable of connecting to World Wide Web to receive the differential corrections from a reference station or a network of reference stations (N-RTK) in an Ntrip format [33]. In this experiment, the Network RTK correction stream is acquired by the VRS mount-point of SAPOS(r) service delivering GPS and GLONASS corrections in the time of experiment in Hannover, supported by the Lower Savony State office for Geoinformation and surveying (LGLN) [34]. When referring to real data in the remainder of this paper, we are using here exemplarily the real data from the Septentrio Altus NR3 (Figure 1, the receiver on the far right in Figure 1b). An eight-shaped trajectory (Figure 1a) was driven for twelve rounds divided into two sections of six rounds separated by two hours in order to cover various satellite sky distributions. Each round of the eight-shaped trajectory was almost 1 km long and took approximately 5 min to drive. The GNSS receivers log data in 10 Hz sample rate and the rate for IMU is 400 Hz.
###### Abstract  
Recently, the development of a rapid detection approach for glaucoma has been widely proposed to assist medical personnel in detecting glaucoma disease thanks to the outstanding performance of artificial intelligence. In several glaucoma detectors, cup-to-disc ratio (CDR) and disc damage likelihood scale (DDLS) play roles as the major objects that are used to analyze glaucoma. However, using CDR and DDLS is quite difficult since every person has different characteristics (shape, size, etc.) of the optic disc and optic cup. To overcome this issue, we proposed an alternative way to detect glaucoma disease by analyzing the damage to the retinal nerve fiber layer (RNFL). Our proposed method is divided into two processes: (1) the pre-treatment process and (2) the glaucoma classification process. We started the pre-treatment process by removing unnecessary parts, such as the optic disc and blood vessels. Both parts are considered for removal since they might be obstacles during the analysis process. For the classification stages, we used nine deep-learning architectures. We evaluated our proposed method in the ORIGA dataset and achieved the highest accuracy of 92.88% with an AUC of 89.34%. This result is improved by more than 15% from the previous research work. Finally, it is expected that our model could help improve eye disease diagnosis and assessment.  
disease classification; deep learning; glaucoma; retinal nerve fiber layer; eye assessment Article
# A Study of Eye-Tracking Gaze Point Classification and Application Based on Conditional Random Field
## 4 Experimental Results and Analysis
### Real Scene Image Gaze Points Classification and Application  
Through the previously mention research on the classification of gaze points, the eye-tracking technology is used to control the servo platform and perform the visual aiming of the servo platform. Specifically, the experimenters wear on the eye-tracking device, and gaze at the targets on the display (the image transmitted by the scene camera on the servo platform) are verified. In addition, the original gaze point and the gaze point after classification are compared. **Part 1** shows the gaze at real images experiment. **Part 2** further shows the real-time servo platform visual aiming. **Part 1:** experimenters gaze at the \"person\" (as for target) in the school and select six scenes to illustrate. Figure 16 presents the comparison of gaze points during the real images gazing. Figure 16: Comparison of gaze points during the real scene images. (1)–(6) is the number of the images, these number where be used in Table 6.  
In Figure 16, (1) the target of gaze is not specified, and the gaze points are widely distributed; (2) and (3) the gaze target is the person on the right; (4) the gaze target is designated as the second person; (5) the gaze target is the person on the right side of the step; (6) the gaze target is the person on the steps. In each image, the first row presents the gaze image, the second row presents the original gaze points, and the third row presents the classified gaze points. It can be clearly seen that the proposed method classifies the gaze points associated with the target \"person\". Table 6 presents the comparison of real images gaze test evaluation results. The proposed method can classify real scene images gaze points, the _Co_ is the lowest, the _Ra_ is better than other methods result, and the _Precision_, _Recall_ and _We_ all is better than others result. These further show our method have a well classification result based on visual characteristics, and in gazing process gaze target long time that with different attention distribution. So, when we manipulate servo platform accuracy aiming visual, need understanding the meaning of gaze point to use. **Part 2:** experimenter gaze the center of target, as shown in Figure 17. Figure 17a is gaze target. During the gazing process, interference to the target Figure 17b and the target Figure 17c will appear from different positions to the target. The position of the \"+\" in the
# An Efficient Person Search Method Using Spatio-Temporal Features for Surveillance Videos +
## 4 Experiments and Results
### Experimental Design  
In the surveillance video database, the RGB frames of video clips were employed as the inputs for the proposed person search method. A pretrained Yolov5 network [45] was used to detect the bounding boxes of persons in each frame, and an ImageNet-pretrained Resnet-50 model [42] was used to extract the spatial features of persons. After that, GRU and average pooling layer were added to the network and finetuned together with the Resnet-50 model. Finally, to ensure search efficiency, LSH was used to organize all the 256-dimensional spatio-temporal features in the video database.  
To verify the spatio-temporal features and evaluate the search performance, our proposed method was compared with Region Convolutional Neural Network (RCNN) [8], which is widely used in person search methods, and the proposed method was also compared with the Progressive Propagation Person Search (PPPS) method [34]. The comparisons included: (i) the accuracy comparison between spatio-temporal features and spatial features, (ii) the accuracy comparison between our method and RCNN using spatio-temporal features, (iii) the accuracy comparison between GRU and LSTM with different pooling methods, (iv) the accuracy comparison between our method and the RCNN method with different numbers of video clips, (v) the accuracy comparison between our method and the PPPS method with different numbers of video clips, (vi) the efficiency comparison between our method, the RCNN method and the PPPS method with different numbers of video clips. All the methods were performed on machines with an Intel Xeon E5-1620 3.5 GHz processor, 256 GB of RAM, and NVIDIA Geforce GTX 1080 Ti GPU. All the experiments are implemented based on PyTorch [46].  
Figure 3: Examples of the surveillance video database.
## 4 Conclusions  
This paper studied the anti-wrinkle performance of glycosyl polyaldehyde finishing agents (OFr, OSu, OTr, ORa, OSt), glycosyl polyuronic acid finishing agents (openSu, openTr, openRa and openSt) on finished cotton fabrics. Among them, OTr-, Ora-, openTr- and openRa- finished fabrics showed excellent an anti-wrinkle property, the TS of the finished fabric was above 68%, and the WI was above 70. The molecular radius of the glycosyl polyaldehyde finishing agents and the glycosyl polyuronic acid finishing agents were calculated using the MM2 method; the smaller the molecular volume of the finishing agent was, the easier it was to diffuse into the cotton fiber, and the higher the amount of finishing agent was inside the cotton fiber, which was conducive to the effective cross-linking of the finishing agent with the cotton fiber. The number of reactive groups, the number of reactive sites, and the RBN value of the finishing agent affected the crosslinking reaction with cellulose. The more reactive the groups and sites were, the greater the RBN value was, which was more conducive to the occurrence of the crosslinking reaction. The cross-linking radius range of glycosyl formaldehyde-free finishing agent was analyzed using a molecular simulation. The most suitable cross-linking radius range was 3.5-6.0 A; within this range, the anti-wrinkle finishing agent was easily diffused to the inside of the cellulose. This study provides a reference for the design of new formaldehyde-free anti-wrinkle finishing agents with new molecular structures.  
Conceptualization, X.F.; Software and writing--original draft preparation, J.L.; Writing--review and editing, D.W. and J.Y. All authors have read and agreed to the published version of the manuscript.  
This work was financially supported by the National Key R&D Program of China (2017 YFB0309202) and Postgraduate Research & Practice Innovation Program of Jiangsu Provence (1062050205198056).  
Not applicable.  
The authors declare no conflict of interest.
# Feature Integration Strategies for Neural Speaker Diarization in Conversational Telephone Speech
## 2 Methodology
### Adaptation Methodology  
The adaptation phase bridges the gap between our simulated training conversations and real-world telephone speech. Although our training data incorporates noise and reverberation augmentations, real CallHome conversations present unique challenges including spontaneous speaking patterns and telephone channel effects. Our methodology employs targeted strategies to address these domain differences:
# Electrical Conductivity Evidence for the Existence of a Mantle Plume Benath Tarim Basin
## 3 Results  
We apply the ISA method to the one-dimensional inversion of measured geomagnetic depth sounding data from four stations around the Tarim area [40]. The above-mentioned stations are located inland at low latitudes. Therefore, their C-responses should not be affected by aurora and ocean effects [41] and thus can be directly inverted [32]. During the inversion, according to the law that the conductivity of the deep mantle jumps with the phase transition of the main minerals [42], nine layers above the core are divided [20]. The possible range for the conductivity of each layer is estimated based on the results of the Semenov inversion [22]. The control parameters of simulated annealing inversion are as follows: \(M=3000\); \(L=10\); \(T_{0}=0.01\). The control parameter \(RMS^{\rm max}\) is given in Figure 6. The variation range of the conductivity parameter is indicated by the shading in Figure 7. The final ISA inversion results in a smooth C-response curve with the same variation trend as the original data. At the same time, the RMS value is given in the Figure.  
Figure 7 shows the final conductivity model beneath Tarim area. Above 410 km, the conductivity values below the four stations are similar. Within the sensitive depth range of geomagnetic depth sounding, there is no obvious conductivity jump under the HOQ and WEQ stations on the 410 km discontinuity, which is consistent with the conductivity characteristics of the continental transition zone obtained by [PERSON] [43]. On the same discontinuity surface, the conductivity values below WUS and WMQ stations have greatly increased. We speculate that the transition zone is affected by the mantle plume beneath Tarim. From 520-660 km, the conductivity below the WMQ station in the lower layer of the transition zone is much higher than at the other three stations. At 660-900 km, compared with the lower layer of the transition zone, the conductivity of the top of the lower mantle below the four stations is significantly increased and the value is at the same order of magnitude. The noise test of the theoretical data shows that when the data contain noise, the true value of the conductivity is included in the reliable interval of the conductivity obtained by the inversion. Therefore, we believe that the inversion result of this paper is reasonable.  
Figure 5: The log-normal distribution histogram of the \(\sigma_{4}\) samples in the SA inversion. The inset is the P-P graph of the lognormal probability distribution of the \(\sigma_{4}\) samples. The abscissa of the subgraph is the measured cumulative probability density, and the ordinate is the expected cumulative probability density.  
Figure 6: The ISA inversion fitting of the C-response over WMQ **(a)**, WUS **(b)**, WEQ **(c)**, and HOQ **(d)** stations.  
Figure 7: Conductivity depth profiles beneath HOQ, WEQ, WUS, and WMQ stations obtained by ISA inversion. The shaded zone is the parameter variation range; the dashed line indicates the reliability intervals estimated after inversion.
## 3 Simulation and Results
In Figure 10, the dashed and solid lines in pink, light blue, blue, and green, respectively, represent the BER of the all-optical OFDM systems with \(2^{4-7}\) subcarriers based on the Sinc-shaped filter and the Gauss-shaped filter at different accumulated dispersions, and it can be seen from the overall change trend of the eight curves that, although the modulation format of each subcarrier was different from the PAM4 in Figure 10, the overall change trend was almost the same. When the accumulated dispersion was 1000 ps/nm, the BER of an all-optical OFDM system based on a Sinc-shaped filter with \(2^{4-7}\) subcarriers was higher than \(5\times 10^{-2}\), where the number of subcarriers was 16, BER = 7.081 \(\times\)\(10^{-2}\). The BER of the Gauss-shaped filter-based system was less than \(5\times 10^{-2}\), BER = 3.113 \(\times\)\(10^{-2}\) when the number of subcarriers was 16, and BER = 3.956 \(\times\)\(10^{-2}\) when the number of subcarriers was 128. As can be seen from Figures 9 and 10, when the Gauss-shaped filter replaced the Sinc-shaped filter, the BER of the system was greatly reduced under the influence of different accumulated dispersions. However, the reduction was not large enough, and it was necessary to carry out frequency domain sparsening treatment on the subcarrier, which could also be said to insert CP into the all-optical OFDM system to reduce the crosstalk caused by the insufficient orthogonality of the subcarrier generated by the Gauss-shaped filter, and further highlighted its anti-dispersion ability. Figure 11 shows two all-optical OFDM systems with a subcarrier power of \(-13\) dBm, modulation format of 16 QAM, and 32 orthogonal subcarriers, and the BER varied with transmission distance after inserting CP = 0 and CP with a size of 0.33. In the modulation format 16 QAM of the system in Figure 12, for the all-optical OFDM system with a Sinc filter before inserting CP, BER = 8.545 \(\times\) 10\({}^{-2}\) after 60 km transmission; after inserting CP of size 0.33, BER = 1.925 \(\times\) 10\({}^{-2}\); and after replacing the Sinc filter with a Gaussian filter, BER = 1.596 \(\times\) 10\({}^{-3}\). The two constellations in Figure 12 more clearly reflect the difference between the use of a Sinc filter and a Gaussian filter in the AO-OFDM system, and the change in the AO-OFDM signal transmission quality before and after CP insertion. Figure 10: BER of two all-optical OFDM systems based on different filters with 16 QAM subcarrier modulation format after being affected by accumulated dispersion of different sizes when CP is not inserted. Figure 9: BER of two all-optical OFDM systems based on different filters with PAM\(-4\) subcarrier modulation format after being affected by accumulated dispersion of different sizes when CP is not inserted.
## 4 Discussion
Beyond that, some studies have shown that the application of FA could enhance enzyme activity and increase crop yield [5; 28; 29; 31]. Our analysis results of the oxidation-reduction system also revealed that FA decreased the accumulation of O\({}^{2\cdots}\), H\({}_{2}\)O\({}_{2}\) and MDA induced by Ca(NO\({}_{3}\))\({}_{2}\) stress, but enhanced the activities of SOD, POD, APX and CAT in Chinese flowering cabbage, which finally relieved the oxidative stress induced by calcium nitrate. All the results suggested that FA can alleviate Ca(NO\({}_{3}\))\({}_{2}\) stress in Chinese cabbage seedlings by improving the antioxidative capacity against oxidative damage. Figure 7: The mechanistic model of Chinese flowering cabbage in the alleviation of nitrate stress by FA. The growth depression of Chinese flowering cabbage induced by Ca(NO\({}_{3}\))\({}_{2}\) was alleviated by FA. FA could promote photosynthetic capacity by increasing Pn, Tr, Gs and Ci. In addition, the activity of reductases including SOD, POD, APX and CAT was increased, but the accumulations of H\({}_{2}\)O\({}_{2}\), O\({}^{2}\) and MDA were decreased by FA under Ca(NO\({}_{3}\))\({}_{2}\) stress. Moreover, FA inhibited the expressions of _BCNRT.1_ and _BCNRT.5_, which suppressed the uptake and translocation of Ca(NO\({}_{3}\))\({}_{2}\). In conclusion, the possible reasons for the alleviation of nitrate stress by FA in Chinese flowering cabbage seedlings were explored in this study through analyses of the photosystem, oxidation-reduction system and nitrate accumulation. NRT1.1 is involved in nitrate absorption, and NRT1.5 and NRT1.8 are identified as two transporters for root-to-shoot nitrate translocation [32; 33; 34]. In the nitrate content experiment, we observed that FA could reduce nitrate accumulation in roots (Figure 6a), which was in accord with the transcription level of _BcNRT1.1_ (Figure 6c).Meanwhile, FA could also decrease nitrate translocation (Figure 6b), which was in accord with the gene expression of _BcNRT1.5_ (Figure 6d). _NRT1.8_ could not be detected in Chinese flowering cabbage seedlings in our study. Overall, we speculated that FA-mediated amelioration of nitrate stress may result from its inhibitory effect on nitrate absorption and translocation in Chinese cabbage flowering seedlings.