esa-sceva/satcom-chunk-collection huggingface dataset:
# A New Prediction Model of Annular Pressure Buildup for Offshore Wells
## 4 Multi-String Annular Pressure Buildup Model  
The annulus pressure buildup is the increase in fluid expansion pressure in the sealed annulus between each layer of casing due to temperature rise. The typical calculation model is as follows:  
\[\Delta p=(\frac{\partial p}{\partial T})_{m,V}\cdot\Delta T+\left(\frac{ \partial p}{\partial V_{ann}}\right)_{m,T}\cdot\Delta V_{ann}+(\frac{\partial p }{\partial m})_{V,T}\cdot\Delta m \tag{17}\]  
The first term on the right side of the equation represents the pressure due to the thermal expansion effect, and the second term represents the pressure due to the annular deformation caused by the thermal effect or load of the casing. The third term is the pressure due to annular fluid leakage or reservoir fluid overflow into the annulus.  
In the typical three-annulus well structure, the tubing and production casing form the A annulus, the production casing and intermediate casing form the B annulus, and the intermediate casing and surface casing form the C annulus. When the production parameters of oil and gas wells and the annular drilling fluid system are determined, according to the calculation formula of annular pressure buildup, the main factor affecting annular pressure buildup is the change of annular volume. The annular pressure buildup is affected by the pressure of the adjacent annulus; therefore, the casing annulus pressure buildup values are solved as a system.  
Taking the A annulus as an example, the changes of annulus volume mainly include the following: 1 radial deformation of tubing; 2 the radial deformation of the casing-free section (related to the B annulus pressure); 3 the radial deformation of the casing sealing section.  
The volume change caused by the radial deformation of the tubing is as follows:  
\[\Delta V_{1}=\int_{0}^{L_{t}}\pi\Big{(}(r_{T0}+u_{c}(r_{T0}))^{2}-r_{T0}^{2} \Big{)}dx \tag{18}\]  
The volume change caused by the radial deformation of the casing-free section (related to the B annulus pressure) is as follows:  
\[\Delta V_{2}=\int_{0}^{L_{ps}}\pi\Big{(}(r_{p1i}+u_{s}(r_{p1i}))^{2}-r_{p1i}^{ 2}\Big{)}dx \tag{19}\]The volume change caused by the radial deformation of the casing sealing section is as follows:  
\[\Delta V_{3}=\int_{0}^{L_{p_{c}}}\pi\Big{(}\big{(}r_{p1i}+u_{c}(r_{p1i})\big{)}^ {2}-r_{p1i}^{2}\Big{)}dx \tag{20}\]  
In the process of calculating the change of the A annulus volume, the influence of the B annular pressure on the A annulus volume needs to be considered.  
The deformation of annulus B and C can be obtained using the same method. The change of the B annulus volume is affected by the pressure of annulus A and C, and the change of the C annulus volume is affected by the B annulus pressure.
# Improving Water Efficiency in a Municipal Indoor Swimming-Pool Complex: A Case Study
###### Abstract  
This study aimed to determine the water demand of a municipal swimming pool complex to propose water use efficiency measures. Concomitantly, the possibility of recycling and reusing the water from filter backwashing was evaluated. The pools consumed 25.6% of water, the filter backwashing 24.5%, and the showers 34.7%. Despite the current impossibility of reducing water consumption in pools and filter backwashing, it is feasible to promote more efficient use of water through reducing water consumption by adopting simple water-saving initiatives for showers, taps, and flushing cisterns. These were organized into three distinct scenarios: (a) flushing cistern volume adjustment and the replacement of washbasin and kitchen taps; (b) flushing cistern volume adjustment and shower replacement and (c) flushing cistern volume adjustment, shower, washbasin, and kitchen taps replacement. Under scenarios 1, 2, and 3, the water consumption reduction was 8.0, 13.2, and 20.4%, respectively. The initial investment for scenario 1 was $2290.5, $6859.0 for scenario 2 and $3149.5 for scenario 3; the annual water bill reduction was $7115.4, $11,518.1, and $17,655.9, respectively. Therefore, the turnover of the investment was four (scenario 1), one (scenario 2), and three months (scenario 3). The filter washings attained the required standard for irrigation after being subjected to 15 h of sedimentation.  
water efficiency; indoor municipal swimming pools; economic viability; filter washings reuse +
Footnote †: journal: Applied Sciences
## 3 Experiment Result and Discussion  
### Experimental Setup  
The proposed approach was tested on experimental thermogram sequences. The experimental setup for square pulse thermography is shown in Figure 3. Two Phillips QVF137 halogen lamps with a rated power of 1000 W were used to generate square pulse thermal waves. The temperature distribution of the metallic surface was captured using a SAY-HY6850 infrared imager with a thermal sensitivity of 80 mK and a resolution of 320 \(\times\) 240. Both the lamps and the infrared thermal imager were located on the same side with respect to the inspection surface of the specimen. The vertical distance between the inspection surface and the lamps is 0.4 m, while that between the inspection surface and the infrared thermal imager is 0.9 m. With these arrangements, one pixel represented about 1.47 mm in thermograms. The incidence angle of square pulse thermal waves was about 45\({}^{\circ}\). In order to verify the efficiency of the proposed approach for blurry defects, the lamps were mounted such that their centers were 5 mm higher than the horizontal center line of the specimen. As a result, less heating flux was obtained by defects in the bottom row. Due to this non-uniform heating, indications of the bottom row defects were greatly weakened in the captured thermograms.  
Experiments were performed on a Q235 steel plate (320 \(\times\) 320 \(\times\) 6 mm\({}^{3}\)). The plate was placed in a moist environment for about three months without any corrosion prevention. Then, the surface of the plate was completely covered by corrosion material. Nine flat-bottom blind holes with the same diameter of 15 mm but with different depths (from D1 to D9: 0.55, 0.50, 0.65, 0.8, 0.65, 0.75, 0.70, 0.7, 1.0 mm) were machined, and detailed information of these defects is shown in Figure 4. If the surface  
Figure 3: Photograph of the experimental setup.  
of the specimen had not been corroded and had been processed by black matt painting, indications of these defects would be very distinct in thermograms. However, due to the effect of the corrosion material, the indications of defects were weakened significantly in the real test. Under this condition, the performance of the proposed approach for blurry defects can be tested precisely.  
In order to verify the repeatability of the proposed approach, the specimen was tested four times, and the specimen was rotated for 90\({}^{\circ}\) in each testing. During each testing, the specimen was heated for 8 s, and thermograms were recorded for 16 s with a sampling frequency of 25 Hz.
## Case Study
### The Combination of EWOSM and SQP Method  
As the proposed method EWOSM is based on the analysis and comparison of large amount of historical data, in practical applications, some historical data may be missing and some historical control schemes are not optimized, which will lead to that the result of EWOSM is more like a suboptimal feasible solution rather than a global solution. In practical scenarios that the global optimal solution is necessary, EWOSM can be used in combination with GA method, neighborhood search method, SQP method and other existing methods to speed up the convergence and ensure the global optimization.  
In this case, comparison of objective function values, computation time and convergence algebra of three different methods is designed to prove the effectiveness of the proposed hybrid method, in which the result of EWOSM is treated as an initial solution of SQP method. The computation time and results of EWOSM, the hybrid method and SQP method are shown in Table 7.  
It can be seen from Table 7 that the objective function of the three methods is almost the same, which proves the validity of the hybrid method proposed. From the view of computation time, the time of hybrid method is 7.41 s, which is reduced by 62% than SQP method. Besides, from the view of convergent rate, the hybrid method converges in the ninth iteration, which is much less than the forty-second iteration of SQP method. The comparison result illustrates that the effect of the proposed hybrid method in speeding up the convergence and reducing the computation time is remarkable.
# A Lightweight Uav Swarm Detection Method Integrated Attention Mechanism
###### Abstract  
Aiming at the problems of low detection accuracy and large computing resource consumption of existing Unmanned Aerial Vehicle (UAV) detection algorithms for anti-UAV, this paper proposes a lightweight UAV swarm detection method based on You Only Look Once Version X (YOLOX). This method uses depthwise separable convolution to simplify and optimize the network, and greatly simplifies the total parameters, while the accuracy is only partially reduced. Meanwhile, a Squeeze-and-Extraction (SE) module is introduced into the backbone to improve the model's ability to extract features; the introduction of a Convolutional Block Attention Module (CBAM) in the feature fusion network makes the network pay more attention to important features and suppress unnecessary features. Furthermore, Distance-IoU (DIoU) is used to replace Intersection over Union (IoU) to calculate the regression loss for model optimization, and data augmentation technology is used to expand the dataset to achieve a better detection effect. The experimental results show that the mean Average Precision (mAP) of the proposed method reaches 82.32%, approximately 2% higher than the baseline model, while the number of parameters is only about 1/10 th of that of YOLOX-S, with the size of 3.85 MB. The proposed approach is, thus, a lightweight model with high detection accuracy and suitable for various edge computing devices.  
object detection; Unmanned Aerial Vehicle (UAV) swarm; lightweight model; attention mechanism; data augment +
Footnote †: journal: Advances in Neural Information Processing Systems
# An Adaptive UI Based on User-Satisfaction Prediction in Mixed Reality
## 5 Conclusions and Future Works  
In this paper, we proposed the adaptive UI based on user-satisfaction prediction in MR. The proposed method predicts user satisfaction based on interaction information, and provides adaptive UI based on the prediction results. In this paper, two experiments were performed for the proposed method: the experiment for the implementation of proposed method and the experiment for the evaluation of the proposed method. In the experiment for the implementation of the proposed method, SVR and MLP were used to predict user satisfaction based on interaction information. As a result of the experiment, it was confirmed that the prediction performance of MLP (MAE = 0.531) was higher than SVR (MAE = 0.654). In the experiment for evaluation of the proposed method, user satisfaction with and without proposed method was compared. As a result of the experiment, user satisfaction for selecting and moving tasks was increased by 8.793% and 10.725%, respectively, with the proposed method (selecting: 4.714, moving: 4.381) compared to without the proposed method (selecting: 4.333, moving: 3.952), and through this, it was confirmed that the proposed adaptive UI was effective in improving satisfaction. From the results, we expect that proposed adaptive UI based on user-satisfaction prediction to improve user satisfaction in MR environments. For example, it can contribute to higher user satisfaction when combined with scenarios such as in our previous study of predicting gestures. In addition, it can contribute to providing a real-time corrected UI based on each user's satisfaction in applications with various target users, such as adults and children, without additional manipulation. In this study, we proposed an adaptive UI that corrects only one element (UI position), and in the future, we intend to extend our method which uses various correction elements including position, size, color, etc. Additionally, the study results were obtained from a small number of subjects. Thus, one of the future works may include extensions into a larger number of subjects.  
Conceptualization, Y.C. and Y.S.K.; methodology, Y.C. and Y.S.K.; software, Y.C.; validation, Y.C.; formal analysis, Y.C.; investigation, Y.S.K.; resources, Y.S.K.; data curation, Y.C.; writing--original draft preparation, Y.C. and Y.S.K.; writing--review and editing, Y.S.K.; visualization, Y.C.; supervision, Y.S.K.; project administration, Y.S.K.; funding acquisition, Y.S.K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board of KOREATECH (approval on 26 May 2021).  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
This work was supported by Electronics and Telecommunications Research Institute(ETRI) grant funded by ICT R&D program of MSIT/IITP [2020-0-00537].  
The authors declare no conflict of interest.
## 1 Introduction
Moreover, the availability of a sample of several pattern measurements for each individual opens up the unique opportunity to use statistical inference and apply potent statistical tests of hypothesis to measure similarity between class data and, consequently, determine the class of membership of a measurement or observation [14]. Such effective tests would not be applicable otherwise. In this study, we investigate a Kohonen neural network generalized to encode data in the form of samples, which we apply to knee OA pathology categorization using knee kinematic data samples. Datasets of knee kinematic measurements are generally small, containing samples from typically fewer than one hundred subjects, each sample composed of about a dozen kinematic curves as described earlier. Kohonen neural networks, which are potent classifiers [15; 16; 17; 18; 19; 20], are particularly apposite for such small-sized training data sets because they are associative memories that represent classes each by several patterns which training determines, and do so such that neighboring representations correspond to neighboring classes. Sample similarity evaluation, which underlies both training, to determine this spatially organized layout of representation patterns, and classification, to assign a category to observations, is done using the two-sample Hotelling \(T^{2}\) statistic. This will be explained further when we the describe the sample-encoding generalization of the Kohonen network in greater detail subsequently. This sample-based Kohonen neural network outperformed other classifiers in knee OA experimentation to distinguish between two types of knee osteoarthritis pathologies, namely femero-rotulian (FR) and femero-tibilal (FT). The remainder of this paper is organized as follows: Section 2.1 describes the knee kinematic data and its collection. Section 2.2 explains the sample-encoding Kohonen associative memory, expounding its structure, the Hotelling \(T^{2}\) statistic and its use to measure similarity between pattern samples, training, and classification role. Section 3 describes the experimental results to classify FR knee pathology versus FT, as well as three-class problems involving classes FR and FT as well as class FR-FT representing the joint occurrence of pathologies FR and FT in the same individual. Finally, Section 4 contains a discussion of the results and the last Section contains a conclusion.
Remote Sens._**2014**, \(6\), 10966-10985; doi:10.3390/rs61110966  
_remote sensing_ ISSN 2072-4292  
www.mdpi.com/journal/remotesensing  
_Article_  
A Synergistic Methodology for Soil Moisture Estimation in an Alpine Prairie Using Radar and Optical Satellite Data  
**[PERSON] *, [PERSON] and [PERSON]**  
School of Resources and Environment, University of Electronic Science and Technology of China,  
No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, China;  
E-Mails: [EMAIL_ADDRESS] (M.X.); [EMAIL_ADDRESS] (X.B.)  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +86-28-6183-1571.  
External Editors: [PERSON] and [PERSON]  
_Received: 22 June 2014; in revised form: 18 September 2014 / Accepted: 29 September 2014 / Published: 10 November 2014_  
This paper presents a microwave/optical synergistic methodology to retrieve soil moisture in an alpine prairie. The methodology adequately represents the scattering behavior of the vegetation-covered area by defining the scattering of the vegetation and the soil below. The Integral Equation Method (IEM) was employed to determine the backscattering of the underlying soil. The modified Water Cloud Model (WCM) was used to reduce the effect of vegetation. Vegetation coverage, which can be easily derived from optical data, was incorporated in this method to account for the vegetation gap information. Then, an inversion scheme of soil moisture was developed that made use of the dual polarizations (HH and VV) available from the quad polarization Radarsat-2 data. The method developed in this study was assessed by comparing the reproduction of the backscattering, which was calculated from an area with full vegetation cover to that with relatively sparse cover. The accuracy and sources of error in this soil moisture retrieval method were evaluated. The results showed a good correlation between the measured and estimated soil moisture (\(R^{2}=0.71\), RMSE = 3.32 vol.%, \(p<0.01\)). Therefore, this method has operational potential for estimating soil moisture under the vegetated area of an alpine prairie.  
soil moisture; remote sensing; microwave/optical synergistic methodology; vegetated area; Integral Equation Method (IEM); Water Cloud Model (WCM)
## 6 Computational Results
### Lower Bounds for Datasets B and X
#### 6.5.3 Dual Bounds with Partial Scenario Decomposition  
Table 11 compares the dual bounds for datasets B and X using \(LB(5)\) and \(LB\) formulations with LP+cuts computations varying \(M\) the maximal number of scenarios in each sub-problem.  
Like in Table 6, the impact of partial scenario decomposition is significant in Table 11, but not so important to close the gap to the optimal dual bounds. The distribution of stochastic scenarios illustrated in Figure 1 holds also for datasets B and X, and this is related to the industrial application. Badly partitioning the scenarios in Proposition 5 also induces few differences from the scenario decomposition with \(M=1\). The gap improvements with \(M\) increasing are significant, and it shows the interest of Algorithm 1.  
Figure 2: Comparison of dual bound convergence using MILP computation of \(LB\) and \(LB(5)\) formulations for instance B6 (relatively easy) and for difficult instance B7.
## 5 Discussion
### Generalizability of the Proposed Method  
This method is developed for circular underground workings with flexible sealing layers. However, it can be extended to other cases:  
(1) The proposed method is also applicable to non-circular geometries, such as horseshoe or elliptical tunnels. These shapes often perform better under high internal pressure. By adjusting the ratio between the major and minor axes of the cross-section, the stress distribution can be better aligned with the in situ stress field. This allows the structure to more effectively utilize the surrounding rock's confinement. As a result, applying this method to such geometries would be conservative and structurally safe.  
(2) In practice, storage involves cyclic loading. The surrounding rock may accumulate residual deformation. This may enlarge seam openings and cause retractable joint failure. Future work should study joint behavior under repeated loading and damaged conditions.  
(3) The design fits well with prefabricated rubber sealing layers. These materials offer high tensile strength and good deformation capacity. As long as they resist leakage and aging, they are suitable for use in underground workings with segmented linings for CAES.
## 5 Conclusions  
Orientation information of space debris is important to improve the orbital prediction accuracy for mitigation or elimination of a significant threat to not only human space activities but also operational satellites. The ELPW records the scattering signals from the space target surface and thus reflects the target shape in the direction of laser beam propagation. The new method based on the ELPW analysis was proposed to achieve the orientation information of space debris because it has no measurement constraints, unlike the photometry, AO and SLR technologies. This paper discussed the feasibility of using ELPW for the orientation determination of space debris by numerical simulations for a defunct satellite and a rocket body. By assuming that the reflected surface consists of small grids, the mathematical model was derived to generate the ELPW and also took into account the temporal beam broadening and spatial spreading due to the atmospheric turbulence. The beam broadening is so significant only in the femtosecond regime; it is negligible in the numerical simulation using the nanosecond pulse laser. Gaussian decomposition based on a genetic algorithm was employed to the ELPWs in order to analyze the orientation features. In particular, Gaussian functions obtained from the Gaussian decomposition were able to characterize the orientation features in more detail for a defunct  
Figure 12: The (**a**) reflected surface, (**b**) orientation of rocket body, and (**c**) the echo waveform and 7 Gaussian functions obtained from the Gaussian decomposition for 45\({}^{\circ}\) rotation about the y-axis w.r.t. Figure 2b.  
Figure 13: The (**a**) reflected surface, (**b**) orientation of rocket body, and (**c**) the echo waveform and 7 Gaussian functions obtained from the Gaussian decomposition for \(-90^{\circ}\) rotation about the y-axis w.r.t. Figure 2b.  
satellite with a simpler configuration than a rocket body. It was demonstrated from the numerical simulations that the ELPW had a distinctive shape corresponding to the orientation of space debris, and therefore it could be considered as a feasible method to provide orientation information. Future works will focus on machine learning as a powerful tool to identify the orientation based on waveform shape recognition.  
Conceptualization, H.-C.L.; formal analysis, Z.-P.Z. and S.K.; software, K.-P.S.; writing--original draft, H.-C.L.; writing--review and editing, J.U.P. and C.-S.C.; project administration, M.C. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
This work was supported by the Korea Astronomy and Space Science Institute through the project of \"Operation of Ground Based Laser Ranging System\" funded by the Ministry of Science and ICT (MSIT) of the Korean government. The authors thank NASA for the 3D models of space objects.  
The authors declare no conflict of interest.