esa-sceva/satcom-chunk-collection huggingface dataset:
# Research on Short-Term Prediction Methods for Small-Scale Three-Dimensional Wind Fields
## 2 WRF-CFD Coupled Small-Scale Wind Field Simulation
### CFD Model Settings
Nearest neighbour interpolation involves extracting the values of variables such as speed and temperature from the nearest grid points on the profiles obtained from the WRF model and directly assigning them to the grid points on the corresponding inflow boundary of the CFD model. Inverse distance weighted interpolation calculates the values of the grid points on the CFD inflow boundary by inversely weighting the variable values of the grid points on the aforementioned profiles from the WRF model based on their distances to the CFD grid points. The weight factors are inversely proportional to the distances between the grid points on the profiles obtained from the WRF model and the CFD grid points. In this study, the WRF model output information from nested domain d03 with an output interval of 10 min was firstly processed. Secondly, we saved the wind speed components of longitude, latitude, and vertical directions, denoted by \(u\), \(v\), and \(w\) respectively, and temperature \(tk\) into an ASCII file. Then, the boundary profile module of the CFD model used the wind speed and temperature as the inflow boundary conditions. Figure 3: Comparison of wind speed profiles simulated at different grid resolutions. The settings of the boundary conditions and solver parameters for the CFD model are listed in Table 2. The eastern, western, southern, and top boundaries of the model were set as the inflow boundaries. The speed and temperature variables from the three-dimensional field obtained from the WRF model were interpolated and assigned to the CFD grid points. We employed Fluent as the solver of the CFD. Fluent incorporates RANS and LES turbulence models. Although the LES module exhibited better performance than the RANS model in cases of complex turbulence [24], LES may incur more computational cost than RANS by over ten times. Therefore, the RANS turbulence model remains popular in wind field investigations using the CFD coupled with WRF method, considering both computational cost and simulation precision [4,5]. Furthermore, we used the realizable k-\(\varepsilon\) of RANS in the computation, following ref. [8] and ref. [25]. The northern boundary was set as the outflow boundary, which was specified as a pressure outlet boundary. The bottom boundary was classified into three types: sea surface, airport island, and Lantau Island, as shown in Figure 2a. The corresponding surface roughness values of 0.0005 m, 0.005 m, and 0.5 m were set for each type, respectively [26].
## 7 Conclusions  
In this paper, the target localization problems using RSS measurements in UWSN in both known and unknown transmit power cases are investigated. Firstly, an optimization problem for estimating target localization in both cases is presented. The derived objective function is then transformed into a GTRS framework. Efficient implementation methods are provided in both known and unknown target transmit power cases. The closed-form expressions of the CRLBs in both cases are derived. Computer simulation results confirm the effectiveness of the proposed methods in underwater acoustic environments.  
Figure 7: RMSE versus absorption coefficient \(\alpha_{f}\) when \(\sigma=4\) dB, \(N=10\), and \(\rho=0.8\).
# A Frequency-Domain Estimation Scheme for Frequency Offset with Large Range in OFDM Systems
## 4 Simulation Systems and Results
### The Frame Structure of 5G NR  
In 5G NR, one radio frame consists of ten subframes, each of which lasts 1 ms in the time domain and consists of \(2^{l}\) slots, where \(\mu\in\{0,1,2,3,4\}\) is called NR numerology. Each slot consists 14 OFDM symbols, as shown in Figure 4, when the normal CP is configured. In the frequency domain, the resource block (RB) consisting of 12 consecutive subcarriers is the basic schedulable resource unit by the NR base station. The number of available RBs varies with the configured SCS and bandwidth; for example, the maximum number of available RBs is 52, when \(\Delta f=15\) kHz (\(\mu=0\)) and bandwidth is 10 MHz [25].  
The 14 OFDM symbols in a PUSCH slot could be divided into data OFDM symbols and demodulation reference signal (DMRS) OFDM symbols, i.e., the pilot OFDM symbols used for demodulation at the receiver. As shown in Figure 4, the indices of DMRS OFDM symbols are configured as \(\{2,11\}\), where the index starts from zero in this paper. In the frequency domain, the DMRS symbols are distributed in a comb-like structure, i.e., there is one subcarrier gap between two adjacent DMRS symbols. It is noted that the middle subcarrier between two adjacent DMRS symbols could be configured to transmit a data symbol.  
\begin{table}
\begin{tabular}{l c} \hline
**Calculation Items** & **Complex-Multiplex Operation Numbers** \\ \hline Calculate \(\mathbf{H}_{0}(k)\) and \(\mathbf{H}_{1}(k)\) & \(2N_{\text{s}}\) \\ Calculate \(\alpha\) & \(N_{\text{s}}\) \\ Frequency offset compensation for & \(2 MN_{\text{s}}(L_{1}+L_{2}+1)\) \\ two pilot sequence & \(2N_{\text{s}}(L_{1}+L_{2}+1)\) \\ two pilot sequence & \(2N_{\text{s}}(L_{1}+L_{2}+1)\) \\ Total number & \(2N_{\text{s}}(M+1)(L_{1}+L_{2}+1)+3N_{\text{s}}\) \\ \hline \end{tabular}
\end{table}
Table 2: The number of complex-multiplex operations of Algorithm 1 with the simplified compensation.
## 7 Conclusions and Future Work  
This work proposed an interactive visualization system named VizCycSemantics for the exploration of cycling semantics, and the users of our system were mainly cyclists and urban planners. Based on large-scale GPS trajectories and road network data, the semantics studied in the paper were twofold, namely, the behavior semantics of cyclists and the moving semantics on road segments. Specifically, trajectories were converted into a street name corpus for cyclists and a moving feature corpus for road segments, respectively. Then, we used an LDA model to automatically extract the cyclists' behavior semantic (i.e., cycling topics of cyclists) and moving semantics (i.e., moving topics on roads). We further employed the k-means++ algorithm to capture the groups of similar cyclists and road segments in the city. At last, multiple user interfaces were implemented to visualize the various patterns of cycling semantics. To better demonstrate the practicality of the system in transportation planning, two case studies were shown within the Sixth Ring Road in Beijing. First, with specific cycling topics shown in our system, cyclists could find popular group trends and suitable routes of their own interest. Urban planners could also make corresponding traffic plans through different cycling topics. Secondly, with the moving topics on road segments, cyclists could choose routes with fast, stable and straight cycling. Urban planner could find out where the cycling infrastructures should be built/improved  
Figure 9: The grouping of moving attributes and the corresponding inference and suggestion.  
via the types of moving conditions in the area. Moreover, this system only employed some very basic information from the trajectory and road network data, thus it could be easily and safely generalized to other cities.  
In future work, we will broaden and deepen the cycling semantics exploration from more perspectives. For example, the visited points of interests (POIs) can be considered as words in the process of trajectory textualization, so as to import human activity semantics. Furthermore, social media data can be considered to enhance trajectory semantics and obtain a richer knowledge. It is also a good idea to make our own cycling trajectories with a camera, which can provide more contextual information to enrich cycling semantics. Additionally, we intend to refine the visualizations to further enhance the aesthetics of and interaction with the system, enabling users to do more diverse and personalized analysis and exploration.  
Conceptualization, X.G., C.L. and C.C.; methodology, X.G.; software, X.G.; supervision, C.C. and R.L.; visualization, X.G.; writing--original draft, X.G.; writing--review and editing, X.G., C.L. and C.C. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the National Natural Science Foundation of China (nos. 62172066 and 61872050). This work was sponsored by DiDi GAIA Research Collaboration Plan.  
Not applicable.  
Data availability Statement: Data is unavailable due to privacy.  
The authors declare no conflict of interest.
# Space-Efficient, Fast and Exact Routing in Time-Dependent Road Networks +
## 2 Materials and Methods
### Preliminaries
#### 2.1.2 Customizable Contraction Hierarchies  
_Customizable Contraction Hierarchies_ (CCH) [5] is a CH extension. It splits CH preprocessing into two phases where only the second uses weights. In the first phase, a separator decomposition and an associated nested dissection order [24; 25] are computed. This order determines the node ranks. Nodes in the top-level separators have the highest ranks, followed by the nodes of each cell, recursively ordered by the same method. Since all shortest paths between different cells have to use separator nodes, these nodes cover many shortest paths. Thus, a nested dissection order is a good CH order.  
Then, nodes are contracted iteratively ordered by ascending rank. Because weights are not considered in this phase, no witness search can be performed. All potential shortcuts between the higher ranked neighbors of the current node will be inserted. The upward neighbors become a clique. This phase is performed on the bidirected input graph with arcs \(A^{\prime}=A\cup\{uu:uv\in A\}\) where each arc exists in both directions.  
In the second phase called _customization_, arc weights are computed. Arcs in the augmented graph corresponding to an input graph arc are initialized with the corresponding weight. All other arc weights are set to \(\infty\). Then, all arcs are processed in ascending order of their lower ranked endpoint. To process an arc \(uv\), all _lower triangles_\([u,w,v]\), where \(w\) has lower rank than \(u\) and \(v\) are enumerated, checking if the path \([u,w,v]\) is shorter than \(uv\). If so, the weight of \(uv\) is set to the length of the \([u,w,v]\). We denote this as _lower triangle relaxation_.  
The result of this basic customization fulfills all necessary properties for the CH query algorithm to find correct shortest distances. However, it contains many unnecessary arcs. These can optionally be removed using the _perfect customization_ algorithm. Here, all arcs are processed in descending order of their higher ranked endpoint. For each arc \(uv\), upper and intermediate triangles are enumerated, i.e., the third node \(w\) has greater rank than either \(u\) or \(v\). The weight of \(uv\) will then be decreased if possible to the weight of the path \([u,w,v]\). Once all arcs have been processed, all arcs where the weight changed can be removed. The augmented graph is now as small as possible.  
The CH query algorithm can be reused without modifications. Another query algorithm is described in [5] which does not need priority queues. It is based on the _elimination tree_. A node's parent in the elimination tree is its lowest-ranked upward neighbor in the augmented graph. The ancestors of a node in the elimination tree are exactly the set of nodes that are reachable in a CH search from this node [24]. Thus, instead of exploring the search space through Dijkstra searches, the elimination tree query searches the same nodes by traversing the path to the root in the elimination tree.
# Reflection Propagation Law of Electromagnetic Waves in U-Shaped Roadway
## 6 Analyses of Simulation Experiments
### Analysis of the Relative Dielectric Constant of the Roadway Walls  
Figure 22 shows the variation in field strength with increasing distance between the relay node and the receiving point for the relative permittivity of the roadway wall as 4, 5, and 6. Let the transmitting frequency of the antenna be 0.3 GHz. The distance from the relay node to the plane \(m_{5}\) is \(w_{3}\) = 0.3 m, the distance from the receiving point to the plane \(m_{6}\) is \(w_{2}\) = 0.3 m, the height of both the relay node and the receiving point is 0.3 m, and the receiving point is moved in the same way as in Figure 20.  
From Figure 22, it can be seen that as the dielectric constant increases, the attenuation of the field strength at the receiving point becomes larger. This is because the larger the dielectric constant, the larger the reflection coefficient in the perpendicular direction, which makes the field strength at the receiving point smaller, in line with the conclusion of Figure 16. Therefore, the sensors should be placed in the U-shaped roadway with higher dielectric constants, which is conducive to reducing electromagnetic interference.
## 3 Problem Statement  
In the existing study, there have been many attempts at a QKDN based on trusted relay [7; 10; 32]. In order to improve the security of QKD networking, network protection schemes are also proposed, including shared protection schemes and dedicated protection schemes [10]. For the QKD networking based on the partially trusted relay, there is a cost optimization method in the deployment stage [33]. In that research, it is concluded that using the partially trusted relay scheme can lead to lower cost and higher security level. A QKD method which can work in a partially trusted QKDN is proposed [28]. In 2022, a partially trusted relay-based QKD method and routing of keys in different kinds of typical network topologies were described [34]. Security is a crucial problem. A key management and data scheduling scheme has been proposed [35].  
In large-scale or inter metropolitan quantum networks, the coexistence of multiple protocols is inevitable. The two users may communicate through trusted repeaters or exchange information through untrusted relays over a long distance. Nodes that follow the BB84 protocol and nodes that use the MDI-QKD protocol may appear in the same network topology. The QKDN link based on partially trusted relay is more complex, resulting in higher risk of failure. Since the channels used for QKD and data services are multiplexed in the common optical fiber, their protection against link failure can be considered separately. However, there is little research on the protection of QKD networking in a partially trusted relay situation. In order to reduce the impact of possible faults on QKD in a partially trusted relay scenario, the corresponding protection scheme is an important problem to be solved. For the sake of improving the security of QKD networking, we propose a protection scheme in a QKDN based on partially trusted relay. Protection refers to making a certain prediction before the fault occurs and reserving resources and paths for it. The proposed dedicated protection scheme transmits the key simultaneously on the working and protection paths to ensure security. The protection scheme mainly solves two sub-problems: (1) For the untrusted nodes that may appear in the network, different processing methods from the trusted nodes need to be considered. (2) A large number of protection paths can occupy the key resources in the link, resulting in a high blocking rate to the key distribution on working paths. Therefore, it is necessary to consider how to balance the resource allocation of secret keys on the working and protection paths.  
In order to solve these two sub-problems, a topology-abstraction-based protection scheme in a QKDN with partially trusted relay is proposed. When designing the protection strategy, the processing method of untrusted nodes was considered, which is different from trusted nodes. In addition, a key protection threshold was proposed to adjust the distribution of key resources.  
Topology-Abstraction-Based Protection Scheme in Quantum Key Distribution Networks with Partially Trusted Relay
# Fast Deployment of a UWB-Based IPS for Emergency Response Operations
## 2 State of the Art
### IPSs for ER Operations  
Delivering an accurate (\(\sim\)1 m) and sustainable-over-time (?-tens of minutes) real-time localization for ER operations in indoor environments is a long-sought technical feature [30] with a great potential to increase the efficiency and safety of ER operations such as firefighter interventions. Positioning information and walked paths of FRs offer a higher context awareness and a better common operational picture, which would allow an incident commander to evacuate or rescue at-risk or trapped FRs, identify personnel at key locations, notify FRs if they are in proximity to threats, and design escape routes [15].  
Unlike other IPS use cases, ER operations are highly conditioned by procedural and environmental constraints. On the first hand, any rescue mission has to cope with fully unpredictable real-life scenarios while following strict and hierarchical procedures. A suitable IPS should therefore adapt to existing ER processes and equipment, leaving little or no room for complex infrastructure deployments, system configurations, or positioning calibrations, which can become a burden during high-stress situations.  
On the other hand, ER environments are typically _unstructured_ or _unknown_, so that a running IPS has no prior information about the structure or the signal propagation conditions of the target building [31]. Moreover, hazardous working conditions (involving fire, floods, high temperature, darkness, or even a collapse) may affect not only a building's structure and power supply (hindering the operation of pre-existing IPS infrastructure), but also the security of FRs themselves and proper operation of the equipped electronic devices.  
Some commercial products already provide fine indoor positioning, but they either require pre-installation/calibration of reference devices in the building or the use of pre-existent building maps, which notably complicates their applicability in ER environments [31]. IPS market penetration is indeed much more consolidated in other activity sectors such as healthcare, industry, retail, hospitality, and transportation [32; 33; 34]. For its part, the scientific literature has also extensively addressed the issue of suiting current IPSs to the harsh conditions commonly found in ER operations. The result is a plethora of systems, with those based on RF, IMUs, and hybrid approaches predominating [35; 36; 37; 38; 39; 40; 41; 42; 30; 43; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42].
## 2 Materials and Methods
### Flux Data  
Carbon dioxide (CO\({}_{2}\)) and water vapor fluxes for the five sites were measured by an eddy flux system, while meteorological instruments are used for monitoring precipitation, temperature pressure, and wind speed. The measurements of Arou, Daman, and Sidaoqiao were collected from Heihe Watershed Allied Telemetry Experimental Research (HiWATER) [44]. These three sites are equipped with the instruments placed on a height of 3.15 m, including Campbell LI-COR 7500 for CO\({}_{2}\) flux, LI-COR Li7500 for latent heat flux and a Campbell CSAT3 for sensible heat flux. The meteorological tower is equipped with instrumentation including Campbell CS105 for pressure, Vaisala HMP45C for air temperature and relative humidity, Campbell TE525 for precipitation, MetOne for wind speed and wind direction, etc. In Xinier and Xitaizi, eddy covariance measurements were taken during our own experiments. The two sites have an eddy covariance system with the same equipment, which consists of a fast-response 3D sonic anemometer (CSAT3A, Campbell Scientific Instruments, Logan, UT, USA) for latent heat flux, a fast-response open-path infrared gas analyzer (EC150, Campbell Scientific Instruments) for CO\({}_{2}\) and water (H\({}_{2}\)O) flux, an air temperature and humidity sensor (HMP155A, Vaisala Inc., Woburn, MA, USA), and a micrologger (CR3000, Campbell Scientific Instruments).  
The half-hourly data are processed and quality controlled using the Eddypro software as per the method described in [PERSON] et al. [51]. The half-hourly EC data are processed using the REddyProc software [52; 53]. Data during the growing season are selected for ET partitioning and analysis. Growing season is defined using the logarithmic model, which is illustrated in Section 2.4.
# In-Motion, Non-Contact Detection of Ties and Ballasts on Railroad Tracks
## 2 Setup  
The experimental evaluation evaluated various methods and hardware implementations to achieve the study's goal of differentiation between ties and ballasts in motion. A remote-controlled track cart, shown in Figure 1, was constructed and used to house the required sensors and electronics [14]. A rail cart was selected due to its significant advantage over other potential solutions, such as aerial vehicles and legged robots, because of their poor performance in railroad environments and lack of ability to be tested over extensive distances. This rail cart can successfully replicate Hyrail vehicles and track geometry cars that are mainly used for track inspections. It is a stable platform that allows for continuous monitoring of track conditions as the cart moves.  
The cart is equipped with a traction-braking system and can run on various railroad tracks. The cart's frame is made of 80/20 extruded aluminum, offering flexibility in mounting multiple sensors and data acquisition units. Its flexibility allows efficient testing  
Figure 1: Railway Technologies Laboratory’s remotely controlled track cart used for in-motion differentiation of ties and ballasts.  
across diverse railroad environments, including branch lines and mainlines. This flexibility is crucial for the research objectives, as the cart can easily navigate various track conditions while ensuring that sensors maintain a stable orientation towards their targets for accurate data collection. Additionally, it features a \"kill switch\" to enable emergency braking if needed. Its tapered and flanged wheels provide a stable run up to 10 mph (~16 km/h) in both forward and reverse directions. Furthermore, the cart is designed to fit inside the bed of a pickup truck, facilitating easy transportation to various track locations.