esa-sceva/satcom-chunk-collection huggingface dataset:
# Build Orientation Optimization Based on Weighted Analysis of Local Surface Region Curvature
## 6 Conclusions  
Although the multi-object optimization is a hot issue, there are lots of restrictions even paradox among the parameters to be optimized. It is difficult to find the balance to get the best quality and efficiency. If we adopt a comprise plan, we have to sacrifice part of quality or efficiency. Therefore, the surface quality is only concerned especially for the models with free-form surface in this paper. The geometry shape of the model has an important influence on the dynamic performance. A useful method is proposed to provide an optimal build orientation for the parts that needs high surface quality especially in the aircraft industry. The developed algorithm is capable of analyzing the key position using the curvature shift strategy. All those regions which have high obvious curvature changes are considered more by distributing a bigger weight factor in determining the orientation. The optimal orientation can ensure the key regions have the higher accuracy when printed. The analysis of local surface region curvature is challenging in this paper. Curvature shift strategy is proposed to cluster the original points and surface reconstruction is applied in estimating the curvature of each point. The novelty of the proposed algorithm is the analysis of local surface region curvature and the key region of the model is considered more to guarantee surface quality such as sharp regions and thin regions.  
This article does not involve the actual application scenarios of the model, but only analyzes and verifies it from the theoretical method. This is the limitation of this paper. Although the algorithm proposed can significantly improve the surface quality of the regions with obvious curvature changes of the model, there are still conflicting regions that make the weight distribution counterbalance each other and weaken the effectiveness  
Figure 14: The comparison results of local amplification regions measured by TR200 roughness meter (the left, medium and right figure in turn are the orientation determined by default, EWO and method proposed, respectively).  
of the algorithm. Therefore, the next article will attempt to solve this problem through multi-directional optimization.  
Methodology, H.G.; validation, H.G.; writing--original draft preparation, H.G.; resources, G.Y.; visualization, J.X.; supervision, S.Z.; funding acquisition, J.X. and S.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China (No. 51775494; 51821093), Zhejiang key research and development project (No. 2019C01141), National key research and development project of China (No. 2018 YFB1700701).  
Not applicable.  
The authors declare no conflict of interest.
## 4 Bearing with Longitudinal Microgrooves
### Modeling Circumferential Flows in End Regions  
Circumferential flows can affect the reduction in load-bearing capacity and increase compliance in the end regions. Obviously, this influence will be smaller since the width of the end regions is usually smaller and, at the exit from the bearing gap, the pressure is constant and equal to the ambient pressure. At the same time, it is of interest to study the effect of the width of the end regions and eccentricity in order to assess at what width the circumferential flows have little effect on the bearing capacity.  
We divide the segment [0, \(L_{1}\)] into \(n\) parts and the arc [0, \(\pi\)] into \(m\) parts. The basic finite-difference equations (56) will be slightly modified, where \(x=j-1\), \(y=j+1\). Due to the symmetry of the air pressure at \(\varphi=0\) and \(\varphi=\pi\), we assume \(x=1\), if \(x=-1\), and \(\text{y}=m-1\), if \(\text{y}=m+1\). Taking this into account, iterative Formula (56) takes the form  
\[\left\{\Psi_{i}^{y}\right\}_{\alpha+1}=-\frac{1}{c_{0}}\Big{\{}\big{(}b_{0}+a _{0}U_{j}\big{)}\Psi_{i}^{y}+\big{(}b_{0}-a_{0}U_{j}\big{)}\Psi_{i}^{x}+\Psi_{ i+1}^{j}+\Psi_{i-1}^{j}\Big{\}}_{\alpha^{\prime}}\]  
where \(j=0\), \(1\),..., \(m\); \(i=1\), \(2\),..., \(n-1\), \(\alpha\) is the iteration number.  
Figure 6: Dependences of the bearing capacity \(W\) of the sectors on their length \(L\) for various numbers of microgrooves \(n_{g}\).  
The boundary conditions for \(Z=L_{1}\) correspond to the conditions in (48). The boundary conditions in (66) will be used on the pressurization line \(Z=0\).  
For comparison, let us find the bearing capacity of an ideal model in which there are no circumferential flows. In this case, the solution to the boundary value problem is the function  
\[\Psi(Z,\varphi)=[\Pi(\varphi)-1]\frac{L_{1}-Z}{L_{1}}+1.\]  
The bearing load capacity can be determined numerically by the formula  
\[W=\frac{2}{\pi}\int\limits_{0}^{\pi}\int\limits_{0}^{L_{1}}\left(\sqrt{\Psi}- 1\right)\cos\varphi dZd\varphi.\]  
The results of modeling circumferential flows on the end zones are shown in Figure 7. Graphs of the dependence of the bearing capacity \(W\) on the width \(L_{1}\) of the end zone are plotted for various values of the eccentricity \(\varepsilon\). Solid lines show the dependences obtained by the iterative method. The dashed lines correspond to the ideal airflow model, where there are no circumferential flows.  
It can be seen from the graphs that circumferential flows affect the decrease in the bearing capacity only at \(L_{1}>0.4\). Such a significant width is not typical for the location of the pressurization lines; therefore, at \(L_{1}\leq 0.4\), we can assume that there are no circumferential flows in the end regions.
## 3 Formal and Legal Conditions  
The buildings analyzed in the article were implemented by the developer. The contract between the developer and the buyer of an apartment, in accordance with Polish law, is governed by the Act on Protection of Buyers of Apartments or Single-Family Houses [4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27]. According to the Act, the transfer of ownership to the purchaser is preceded by acceptance in the presence of the customer or his proxy (notarial power of attorney is required). Before taking over the residential unit, the developer is obliged to notify the buyer of this fact. Based on the legal status, as well as court decisions, the authors have prepared a graph depicting the moment of commencement of the warranty period in the case of developer investments (Figure 1).  
The buildings analyzed in the paper were executed by a developer. According to the law, the transfer of ownership to the buyer is preceded by acceptance in the presence of the customer. During the acceptance meeting, the client or the company supporting the acceptance inspects the apartment, after which an acceptance protocol is to be prepared, to which the buyer or their proxy may report any defects or faults found during the acceptance meeting. The customer, as the receiving party, has the right to decide which defects will be included in the acceptance protocol. He or she has the right to report all objections to the apartment, even the least important ones, such as dirt on the handles.  
After the possible identification of minor defects and preparing the acceptance report, the apartment is handed over to the client. Before handing over the apartment, minor assembly work is usually done. In case of detecting significant defects and faults, the apartment is not handed over to the client, and the developer is obliged to repair the defects. At the time of acceptance, the customer agrees to the condition of the apartment. This means that if the customer has not noticed any defects during acceptance, or he or she has not decided to put a defect noticed in the acceptance report, the customer has no right to demand its repair. If the defect was, for example, hidden or a result from the operation of the building, the buyer of the apartment can take advantage of a 5-year warranty for construction works because, during this time, the developer is obliged to maintain the so-called \"acceptance status\" of the flat.  
Figure 1: Diagram showing the start of the warranty after acceptance.  
To a large extent, the results presented in this paper form a continuation of the research on defects occurring at the acceptance stage [3; 27]. The research results presented here involve the case of a couple of buildings, one of which had a statistical analysis of defects performed at the acceptance stage.
# Practical Performance Analysis of Interference in DSS System
###### Abstract
Reference [22] provides a comprehensive summary of crucial future DSS trends, regulatory reform initiatives, and research challenges; references [23; 24] focus on the management of spectrum sharing; references [25; 26; 27; 28] study the improvement of the spectrum sharing technique; references [29; 30] focus on the service level of spectrum sharing. DSS is able to low-frequency overlapping deployments of LTE and NR, but the problem of intra-frequency interference in inter-system networks cannot be ignored. Interference has always been a key concern of NR networks. Reference [31] focuses on time division duplexing (TDD) cross-link interference; references [32; 33] focus on interference coordination; references [34; 35] focus on interference management. In 4G and 5G dynamic spectrum sharing, the physical layer share channels carrying user-plane services can be flexibly scheduled to achieve time division or frequency division multiplexing of spectrum resources, without generating 4G and 5G interference conflicts. However, the physical layer control channel cannot be flexibly scheduled and needs to be statically configured to avoid interference. The allocation method of the time-frequency resources of the physical layer is the key to solving the conflict of the control channel in the dynamic spectrum sharing [36]. Compared with 4G, 5G physical layer control channel configuration is more flexible. It is possible to avoid interference conflicts by configuring the physical layer control channel of the 5G network. However, there are few studies on the interference principles and corresponding solutions for 4G and 5G DSS.
## 3 Snake Robot in SAR
### Snake Robot in Rescue Team and Its Communication  
Robots are seen as part of the rescue team due to their capabilities to explore unknown and hazardous terrains and gather important data using their sensors to then send it back to the control centre to perform effective SAR. Further, these robots can be involved in different stages of operation'search and reconnaissance', 'excavation of rubble piles', 'capture victim bodies', and'send emergency medicine' [46]. Similarly, snake robots can be used to 'localise and identify', 'locomotion and grasping', 'transportation' (first aid, oxygen, water, etc.), 'deploy or collect objects' (radioactive materials, explosives), etc. Several works included robots in rescue organisation frameworks at several SAR operations like in the World Trade Center (WTC) disaster where robots deployed to traverse in confined space and explored the terrain [77, 78, 79, 80].  
Communication with any robot in a confined place is critical and having several issues with both wired and wireless communication. In 2003, [PERSON] et al. studied the human-robot interaction in SAR response at WTC [77]. A task force organisation was introduced which includes robot teams and robot-assisted tasks such as 'confined space search and inspection','monitoring', and 'victim extraction'. During the operation, several communication issues in the organisation like a skill gap between the human operators, task assignment, collaboration between the rescue roles, and communication between the robot and control centre are discussed. Most of the robotic SAR operations are performed using teleoperation [46, 78, 79], a general robot-operator communication framework is mentioned in [46]. From various studies, tethered communication is found to be not reliable and susceptible to tangling, and breakage. The robot can use wireless communication but there is a possibility of a loose connection with the operator as it encounters thick blocks or walls. Further, the robot and data transfer channels can be unencrypted and used by an external agency which leads to privacy issues [78, 81].
## 1 Introduction  
Landslides caused by either earthquakes or rainfall have caused the destruction of public facilities, economic loss, and loss of life and property in Taiwan over the past few decades [1; 2]. One of the severest slope disasters in Taiwan took place during Typhoon Morakot, which affected Taiwan from 8-10 August 2009. That disaster left nearly 700 persons dead or missing and caused about 3.3 billion USD in economic loss [2; 3]. The unexpected heavy rainfall caused thousands of landslides and debris flows in southern Taiwan, including the giant Hsiaolin landslide and the Taimali landslide [2]. In particular, significantly more landslides with larger disturbed areas occurred during Typhoon Morakot in 2009 than during previous typhoon events. These giant landslides, known as large-scale landslides (LSLs), are defined as the landslides with areas of larger than 10\({}^{5}\) m\({}^{2}\), volumes of more than 10\({}^{6}\) m\({}^{3}\), or depths greater than 10 m [4]. After Typhoon Morakot, the study of LSLs became one of the most important issues related to slope disasters in Taiwan. The features of LSLs include spontaneity, fast movement, and destruction; hence, landslide processes are a hard-to-observe natural phenomenon [5], and it is difficult to mitigate landslide disasters with traditional study methods.  
A few studies have reported that block sliding processes on the slope would generate ground motions that can be recorded by seismic stations [6; 7; 8]. The landslide-generated ground motions contain low-frequency (<1 Hz) and high-frequency (>1 Hz) waves. The high-frequency waves are produced by the unloading and reloading cycle of the sliding materials [7], and the high-frequency waves result from the complex impacts between the sliding debris [8]. In the frequency domain,the landslide-induced seismic ground motions are mainly distributed below 10 Hz, and the energy signature in the spectrogram shows a triangular pattern from accumulation to dissipation due to the high-frequency constituents over time. The triangular signature in the spectrogram is a distinctive property enabling the differentiation of the landslide-induced signals from those generated by earthquakes and other ambient noise. If such ground motion is recorded by seismic stations, the timing of large landslides can be extracted, and the seismic interpretation can be used as precious information to calibrate numerical simulations [9]. Furthermore, waveform inversion techniques allow us to reconstruct sliding processes (e.g., sliding velocity, direction, and runout distance), so they are appropriate methods for research on the dynamic processes of landslides. After nearly a decade of development, different waveform inversion approaches have been proposed, and each has distinguishing features and advantages. Reviewing the achievements of different kinds of waveform inversion methods for large-scale landslides is vital for further application. In this study, a waveform inversion method was applied to the large-scale Taimali landslide.
# A Distributed Storage and Access Approach for Massive Remote Sensing Data in MongoDB
## 5 Results and Analysis
### Metadata
#### 5.1.1 Storage  
The storage experiments are conducted by inserting different amounts of metadata into the MongoDB database. The storage mode of the remote sensing metadata is described in detail in Section 3.2. In order to make the experimental results more intuitive and reliable, we have chosen the insert speed under different shard key strategies for comparison in this experiment. The experimental result is shown in Figure 5.  
As can be seen from the above figure, storage performance is affected by the number of metadata records. When choosing \"_id_hashed\" and \"TopLeftLatitude\" as shard keys, the two curves exhibit a similar changing trend, where the insert speed levels off after going through a process of growth. For the shard key named \"_id_hashed\", the data are stored randomly and evenly, which guarantees the load balancing among the shard nodes in the MongoDB cluster. While for \"TopLeftLatitude\" whose values range from \(-90\) to \(90\), the new inserted data can be routed to various chunks, and when viewing the data distribution on the shard nodes at this time, we find that the image data is distributed evenly among the nodes. However, strictly speaking, the data storage with \"TopLeftLatitude\" does not achieve an absolute random and even distribution compared with the \"_id_hashed\" shard key, which yields better storage performance with the latter.  
Figure 5: The comparison of the metadata storage time with different shard keys.  
In addition, when the number of metadata records inserted are less than 5000, the insert speed of the two sharding strategies keeps rising because the metadata are not partitioned at that moment, and there are sufficient resources that can be utilized in the MongoDB cluster.
## 3 Mathematical Model for Optimal Trajectory Planning
### Objective Function Design
#### 3.2.2 Flight Risk Estimation (FRE)  
Some physical limitations need to be overcome during flight time as those limitations make the UAV vulnerable to harsh weather conditions during the surveillance, like rain, strong winds or snow, etc. \(A\)dditionally, flying at high altitudes can be another big risk as higher altitudes pose stronger winds, which may increase the risk or uncertainty of being accidentally destroyed. Based on the above scenario, we define two kinds of flight risks:  
* Environmental Risk  
The environment consists of a wide range of random characteristics variables which makes it difficult to build a model that precisely measures the environmental risk. Therefore, for removing complexity, we randomly generated an environmental risk value for each waypoint. That is, environmental risk, \(r_{i,i+1}^{\sigma}\), between the \(i\)th waypoint and (\(i+1\))th waypoint is defined as the sum of their environmental values.  
High altitude risk is an absolute difference in flying altitude between the two waypoints. High altitude risk, \(r_{i,i+1}^{har}\), can be formulated as,  
\[r_{i,i+1}^{har}=\ \eta*(z_{i+1}-z_{i}) \tag{11}\]  
where \(\eta\) represents a constant parameter control.  
Since the flying risk a location-dependent parameter, it changes accordingly to the environment depending only on the weather conditions and flying altitude during the flight time. Therefore, flight risk estimation can be formulated as from Equations (12)-(14),  
\[F_{FRE}=\frac{\sum_{i=1}^{N_{w}-1}FRE_{i}}{maxFRE} \tag{12}\]  
\[FRE_{i}=\varphi_{ER}r_{i,i+1}^{er}+\varphi_{HAR}r_{i,i+1}^{har} \tag{13}\]  
where \(FRE_{i}\) is the flight risk estimation from the \(i\)th waypoint to the \((i+1)\)th waypoint, \(\varphi_{HAR}\) is the total high altitude risk, and \(\varphi_{ER}\) is total environmental risk. We normalized the flight risk estimation and formulated it as, \(max\)\(FRE\):  
\[maxFRE=(N_{w}-1)*[\varphi_{HAR}*Z+\varphi_{ER}*(2*max^{er})] \tag{14}\]  
where \(max^{er}\) represents the maximal environmental risk.
# Compositional Modeling of Dimethyl Ether-CO2 Mixed Solvent for Enhanced Oil Recovery
## 2 Materials and Methods
### Minimum Miscible Pressure  
The MMP is the minimum pressure at which the injected gas and oil can be mixed under a specific reservoir temperature condition. If the reservoir pressure is less than the MMP, the immiscible flooding process is applied. Conversely, if the reservoir pressure is greater than the MMP, the miscible flooding process is applied. Though the main mechanism of the effect of oil expansion and oil viscosity reduction in immiscible flooding and miscible flooding is similar, the effect is greater in miscible flooding [39]. In addition, in the case of miscible flooding, the displacement efficiency increases because of the decrease in IFT between gas and oil [40]. In this study, the MMP between oil and gas according to DME addition was investigated. The slim tube test is recognized to be the most accurate experimental method for determining MMP. However, the slim tube test is expensive and takes a long time to measure MMP [41]. To overcome the limitations, slim tube test simulation has been widely used. Since slim tube test simulation is a cost-effective method providing an accurate prediction [42]. Therefore, we used slim tube simulation in this study.  
\begin{table}
\begin{tabular}{c c} \hline
**Properties** & **Values** \\ \hline Initial Pressure (kPa) & 13,789 \\ Initial oil saturation & 0.88 \\ Porosity (\%) & 30 \\ Permeability (m\({}^{2}\)) & \(4.9\times 10^{-14}\) \\ Producing pressure (kPa) & 11,031 \\ Total injection (PV) & 1.5 \\ \hline \end{tabular}
\end{table}
Table 5: Reservoir initial conditions and operating conditions.
## 4 Experimental Results and Discussion
### Experimental Results in Case 2  
The experiments have were applied in various experimental environments (test environment I, II, and III) to carry out every use case with its specific SQL command and collected data set. Similarly, for all of the experiments in Case 2, the response with a query for In-memory Cache was always within 5 s, and for In-disk Cache, the response was between 5 and 10 s. Therefore, the following experimental results were given by the other methods. As a result, the averaged execution time for the experiment of each use case with test environment I, II, and III are shown in Figures 30-32, respectively.  
Similarly, the performance comparison and performance index for Case 2 have been done in the same way as Case 1. Table 13 gives the performance comparison among the methods presented in this paper. Furthermore, the normalized performance indexes in two different test environments among the methods were evaluated as indicated in Table 14. Table 15 shows the performance index for Case 2 between the tool selection and the other alternatives.  
Figure 30: Execution time of each use case in test environment I.
# Landslide Displacement Prediction Method Based on GA-Elman Model
## 3 Application Research and Method Comparison
### Landslide Monitoring Data  
Four crack displacement monitoring points are set in the deformation area of the main cracks of the landslide, and the landslide monitoring data are accurately and reliably obtained by LoRa wireless ad hoc network communication. The low power frequency conversion mode and acquisition trigger mode are set, respectively. When the low power frequency conversion mode is used, the main frequency of the microprocessor is reduced from 16 MHz to 65 KHz and the device function module uploads the monitoring data regularly. When the trigger mode is collected, the microprocessor opens the real-time monitoring mode to monitor the change of cracks in real time. Once the preset threshold is exceeded, the data communication interface can start to upload the displacement monitoring data.  
In this study, the monitoring data from 6 July 2020 to 30 October 2020 were selected for data analysis. The initial working mode of the system is set as periodic return interval of 1 h, data collection port trigger return mode is enabled, rainfall trigger return threshold is set as 0.2 mm and displacement trigger return threshold is set as 20 mm. Affected by rainfall factors, EI19003 began to change its displacement from 6 July 2020. The analysis of rainfall and crack displacement is shown in Figure 4. In order to explore the response relationship between rainfall and landslide crack displacement change, the displacement change during the rainfall cycle is used as the data research sample. The training set and the test set are constructed to predict the displacement change under the condition of rainfall and without rainfall, respectively.  
Figure 3: Schematic diagram of monitoring equipment deployment.