esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
However, in the actual system, after long-distance transmission to the receiving end of the signal, the laser beam power is weak, which will lead to a substantial deterioration in the signal-to-noise ratio. Thus, the position and angle detection accuracy of the direct detection method is reduced. On this basis, a DWS-based heterodyne coherent angle measurement technique was further proposed, which performs angle solving based on the signal phase. Compared with the traditional direct detection method, the heterodyne coherent angle measurement can obtain a higher accuracy and system signal-to-noise ratio [13; 14; 15]. The wavefront curvature of the measured light beam can be increased through the lens, significantly improving the detection sensitivity and is being well-applied to high-precision multi-degree-of-freedom interferometers [16]. For the phase angle conversion process, an angle measurement algorithm based on improved differential evolution was proposed, and a coherent laser angle measurement desktop experiment was constructed for verification,with a measurement error better than 5 \(\upmu\)rad [17]. Aiming at the problems of a low accuracy of direct detection technology and difficult integration with a high-speed coherent communication system, an interstellar laser communication angular displacement detection method based on coherent light was proposed. A laser communication link was built under laboratory conditions for testing and validation. The angular displacement detection accuracy was 0.6 \(\upmu\)rad (\(\upsigma\)) with a detection sensitivity of \(-\)43.93 dBm [18]. Based on the above analysis, this paper proposes a four-quadrant heterodyne coherent angle measurement technique with \(\upmu\)rad accuracy and nW detection sensitivity. Firstly, a set of heterodyne coherent angle measurement methods is proposed, a theoretical model established, a phase-locked loop was adopted as the core of the design, and the conversion relationship between the phase and angle was further deduced. Secondly, the Monte Carlo method was employed for the first time to simulate the whole optoelectronic process of the heterodyne coherent angle measurement and analyze the performance of angle measurement with the phase-locked loop model. Finally, an experimental system was built to compare the quantitative differences between the heterodyne coherence angle measurement and direct detection methods using the same four-quadrant detector (QD). The influence of parameters such as the power of the local oscillator laser beam and the loop bandwidth on the angle measurement performance was also tested and analyzed.
# A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges
## 5 Research Gaps and Future Direction
### Homogenous End Nodes  
Majority of the proposed ADR schemes consider homogenous end devices which transmit fixed payloads. In actual deployments, IoT networks are heterogenous, that send packets at different packet rates and varying payloads. Further study can include implementing ADR schemes in networks that are heterogenous and determining the power consumption in such networks.
## 3 Repair Materials
### Crack Behavior and Permeability Tests  
(1) Crack Behavior Test  
From each of the specimens completed as discussed in Section 4.1, the acrylic band (release prevention band of the water leakage repair materials) was removed, and a UTM was installed as shown in Figure 9 so that up and down movements could be repeatedly applied in the crack behavior test. During the crack behavior test, the crack behavior width was 2.5 mm for 1 minute per cycle, totaling 100 cycles. The temperature conditions were the same as the laboratory temperature conditions cited in Section 4.1. During the crack behavior duration of 100 cycles, not only the leaks, tears, cracks, and dents of the repair materials but also the detachment of the adhesive surface with the repair  
Figure 8: Inlet bar for injection Installation.  
Figure 10: Permeability test chamber (output).  
Figure 9: Universal testing machine (UTM).  
materials and the artificial crack surface were checked. In particular, if the adhesive surface with the repair materials and the surface of the artificial crack were detached (eliminated) in the middle of the crack behavior load, there was no responsiveness to the crack behavior, and the performance as a repair material was lost. Therefore, this was recorded as a \"failure.\"  
(2) Permeability Test  
After the completion of the crack behavior test, a permeability test was conducted by applying the water pressure of the OUTPUT method with the specimens that showed responsiveness to the crack behavior (the specimens in which the repair materials maintained their adhesiveness on the surface of the artificial crack) as the target (not including the specimens that failed to respond to the crack behavior due to the detachment of the adhesive surface from the artificial-crack specimen). For the permeability test, the specimen was installed in the air compressor and permeability test chamber, as shown in Figure 10, and the chamber was filled with water. The chamber was connected to the air compressor, and 0.3 N/mm\({}^{2}\) pressure (about 30-m-deep underground pressure) was applied to it, and then the point in time (minute) at which water leakage occurred was checked. If water leakage did not occur, the test results were recorded after allowing the specimen to stand for 1 hour. The temperature conditions were maintained at the laboratory temperature conditions cited in Section 4.1. In the permeability test, the main focus was on the existence of water leakage rather than on the calculation of the quantitative data on the amount of water leakage. This was because with regard to the water leaks in concrete structures, the mere existence of water leakage, regardless of the amount of water that is leaking out, is an important criterion for judgment as a defect. Accordingly, in this study, it was determined that if water leakage occurred, the water tightness performance of the repair materials was lost. Therefore, if water permeability occurred, it was recorded as \"permeable,\" and if it did not occur, it was recorded as \"not permeable\".
## 2 Datasets
### ETOPO1 Data  
ETOPO1 is a global elevation model that provides elevation data including land topography and ocean bathymetry with a spatial resolution of 1 arc. In this study, ETOPO1 data were used to distinguish between land and ocean. The ocean depth was extracted by interpolating the model data according to the InIRA image center. In preparing for collocations, only the data with water depths of less than \(-50\) m were used.
# Extension of DBSCAN in Online Clustering: An Approach Based on Three-Layer Granular Models
## 2 Related Work on DBSCAN Variants
### Incremental DBSCAN Variants  
Another problem in traditional DBSCAN clustering is the expansibility in online clustering. In today's big data era, the size of the historical dataset is large, so clustering on the whole dataset is a hard task. When new data are generated and added into the studied dataset continually, it is impossible to collect all data points before clustering. For this issue, a good solution is to divide the clustering process into a training part and testing part which aims at clustering new data online. However, since the results of most DBSCAN algorithms are non-parametric, DBSCAN is not applicable in the modeling process. For example, when new data comes, traditional DBSCAN algorithms have to re-cluster the whole dataset again, which certainly decreases its efficiency and wastes a large amount of computation time. Therefore, some extensions of DBSCAN algorithms based on incremental clustering were proposed in the literature, e.g., the incremental DBSCAN algorithm and the incremental G-DBSCAN algorithm [39; 40]. These algorithms utilized core points to direct the clustering of new data, and are widely applied to dynamic databases which are updated frequently, e.g., Data Warehouse, anomaly program behaviors detection [41; 42]. Compared to a traditional re-clustering approach, the incremental algorithm is verified to be more efficient, since it just needs to cluster new data. The other example was the incremental G-DBSCAN algorithm, which made use of the advantages of the G-DBSCAN model, and realized the clustering of updated data in [40]. Furthermore, considering that most incremental DBSCAN algorithms utilize core points in online clustering, an improved incremental DBSCAN algorithm was proposed based on partition methods in [43], which limit the search space to partitions for obtaining good efficiency.
## 1 Introduction
HECTOR has the following properties:  
* **Scalable:** Except the labeling steps which occurs at the bootstrap, to make a routing decision, a node has to be aware only of the location of itself, of its neighbors and of the final destination. Moreover, HECTOR is memoryless: no routing information has to be stored at the node and constant amount of information is embedded in the message along the path. * **Loop free:** HECTOR is loop-free since it is a greedy routing that always makes any sender node \(s\) on the path forward to a node closer to the destination (in our coordinate system) than the sender node. * **Guaranteed delivery:** HECTOR guarantees the delivery thanks to its set of labels derived from a tree. In the very worst case, HECTOR follows the tree that provides exactly one path between any pair of nodes. * **Energy efficient:** HECTOR selects the node that minimizes the cost over the progress towards the destination. Simulations show its superiority over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm. We then propose an extension of HECTOR based on multiple trees and theoretically prove the packet delivery. Simulations show that HECTOR provides fair performances regarding the energy efficiency and the path length. In addition, as far as we know, it is the first algorithm to propose a geographic routing protocol where nodes are not aware of their positions, which is both energy-efficient and guaranteed-delivery. Moreover, HECTOR does not rely on specific assumptions (e.g., Unit Disk Graph) or any radio propagation model. It may be applied in any general topology. For all these reasons, to our knowledge, HECTOR has no competing solutions. Indeed, classical routing protocols such as AODV [4] or DSR [11] trigger a flooding from each source while HECTOR provides a fixed amount of flooding (only at bootstrap) from all landmarks and tree root. Existing geographical protocols either need positioning system such as MFR [12] or GFG [2], do not guarantee delivery such as VCap [6] or VCost [9], or are not energy-aware like LTP [10]. The global analysis of HECTOR is performed by assuming that the network topology remains stable for at least the time needed to route a packet from its source to its final destination. This paper is organized as follows. We briefly cover related work in Section 2. In Section 3, we present the way of assigning the two sets of coordinates and introduce our model and assumptions. We describe HECTOR in Section 4. The HECTOR extension to multiple trees is motivated in Section 5. Then, we compare HECTOR's performances to existing methods in Section 6 by simulations and conclude in Section 7.
# Automated Generation of Daily Evacuation Paths in 4D BIM
###### Abstract  
Spatial movements of workers and equipment should be carefully planned according to project plans. In particular, it is crucial for workers' safety to prepare emergency evacuation paths according to changing construction site configurations and construction progress. However, creating evacuation paths for all crews for each day can be an extremely labor-intensive task if it is done manually. Consequently, in most construction projects, evacuation plans are not provided to managers and crews throughout the entire construction. Even state-of-the-art technologies do not suggest ways to generate evacuation paths according to changing progresses presented in 4-Dimensional Building Information Model (4D BIM). This research proposes a framework to automatically analyze, generate, and visualize the evacuation paths of multiple crews in 4D BIM, considering construction activities and site conditions at the specific project schedule. This research develops a prototype that enables users to define parameters for pathfinding, such as workspaces, material storage areas, and temporary structures to automatically identify the accessible evacuation paths. This prototype shows the secured evacuation paths in the 4D BIM environment and allows the users to organize the automatically generated evacuation paths. A case study using the BIM model of a real construction project involved in this paper demonstrates the potential of the proposed method.  
BIM; safety; path planning; A-Star Searching; evacuation +
Footnote †: journal: Applied Physics Letters  
_Article_  
Automated Generation of Daily Evacuation Paths in 4D BIM
# Antenna on Chip (AoC) Design Using Metasurface and SIW Technologies for THz Wireless Applications
## 2 Antenna on Chip Design
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Dimension** \\ \hline Area occupied area by copper patches & 400 \(\upmu\)m\({}^{2}\) \\ Area occupied by aluminium patches & 600 \(\times\) 600 \(\upmu\)m\({}^{2}\) \\ Number of slots on each copper patch & 7 \\ Thickness of the aluminium layer & 10 \(\upmu\)m \\ Thickness of copper patches & 10 \(\upmu\)m \\ Diameter of the slots & 7 \(\upmu\)m \\ Gap between slots & 26 \(\upmu\)m \\ Diameter of the metallic via & 7 \(\upmu\)m \\ Gap between metallic vias & 26 \(\upmu\)m \\ Width of gap between the patches & 10 \(\upmu\)m \\ Thickness of the GaAs layer & 100 \(\upmu\)m \\ Thickness of the ground-plane (GND) layer & 10 \(\upmu\)m \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Optimized structural parameters of the AoC. Figure 2: Reflection-coefficient response of the proposed AoC (i) without metamaterial slots, (ii) without metallic vias, and (iii) with metamaterial slots and metallic vias.
# Research and Application of Foam Filling Material in Soft Rock Roadways
## 5 Preparation of Filling Material and Determination of Foam Stabilizer Concentration  
The preparation process flow chart for the foaming material is shown in Figure 12. First, the foaming agent and foam stabilizer are mixed in proportion with water. They are then diluted and stirred to form a soaking system. Next, the mud to be prepared is created by mixing Portland cement, quick-setting cement, fly ash, and water in proportion to one another.  
To determine the concentration of the foaming agent, as shown in Figure 13, foaming agents with mass fractions of 0.5%, 0.6%, 0.7%, 0.8%, 0.9%, 1.0%, 1.1%, 1.2%, 1.3%, 1.4%, and 1.5% were fully stirred in 100 mL of water using a high-speed stirring method in order to measure the foam volume. As illustrated in Figure 14, the 5 min water secretion (the volume of foaming agent aqueous solution produced after foam destruction) was recorded. Five groups of experiments were conducted for each foaming agent, and the average value was calculated.  
Figure 12: Foaming material preparation process.  
Figure 13: Instant volume measurement after foaming.  
The experimental results are shown in Figure 15. From the perspective of water secretion, the difference between foam volume and water secretion gradually increases with the concentration. When the concentration of the foaming agent reaches 1.3%, the difference between the two is the largest.  
A single foaming agent often cannot meet the preparation requirements of foaming cement, and so a foam stabilizer is usually required at an appropriate concentration to enhance foam stability. Foam stabilizers with concentrations of 0.2%, 0.4%, 0.6%, 0.8%, 1.0%, 1.2%, 1.4%, 1.6%, 1.8%, and 2.0% were selected, and the above test was repeated; the experimental results are shown in Figure 16.  
Figure 14: Determination of water secretion after 5 min.  
Figure 15: Foam volume and 5 min water secretion of a single foaming agent.  
In the foaming system, as the concentration of the foam stabilizer increases, the five-minute water secretion fluctuates downward. When the concentration of the foam stabilizer is less than 0.6%, the five-minute water secretion of the foaming system changes little. However, when the concentration is in the range of 0.6% to 1.4%, water secretion begins to drop sharply. As the concentration of the foam stabilizer increases further, the five-minute water secretion of the foaming system does not decrease significantly.  
The concentration of foam stabilizer reaches a peak at 1.0%, with concentrations of 0.2% to 1.0% and 1.2% to 2.0% both showing a downward trend, indicating that 1.0% is the optimal concentration.
# Optimizing Lattice Basis Reduction Algorithm on ARM V8 Processors
###### Abstract  
The LLL (Lenstra-Lenstra-Lovasz) algorithm is an important method for lattice basis reduction and has broad applications in computer algebra, cryptography, number theory, and combinatorial optimization. However, current LLL algorithms face challenges such as inadequate adaptation to domestic supercomputers and low efficiency. To enhance the efficiency of the LLL algorithm in practical applications, this research focuses on parallel optimization of the LLL_FP (LLL double-precision floating-point type) algorithm from the NTL library on the domestic Tianhe supercomputer using the Phytium ARM V8 processor. The optimization begins with the vectorization of the Gram-Schmidt coefficient calculation and row transformation using the SIMD instruction set of the Phytium chip, which significantly improve computational efficiency. Further assembly-level optimization fully utilizes the low-level instructions of the Phytium processor, and this increases execution speed. In terms of memory access, data prefetch techniques were then employed to load necessary data in advance before computation. This will reduce cache misses and accelerate data processing. To further enhance performance, loop unrolling was applied to the core loop, which allows more operations per loop iteration. Experimental results show that the optimized LLL_FP algorithm achieves up to a 42% performance improvement, with a minimum improvement of 34% and an average improvement of 38% in single-core efficiency compared to the serial LLL_FP algorithm. This study provides a more efficient solution for large-scale lattice basis reduction and demonstrates the potential of the LLL algorithm in ARM V8 high-performance computing environments.  
lattice reduction; parallel optimization; Tianhe; ARM V8
## 6 Nanorobot Architecture
### Power Supply  
The use of CMOS for active telemetry and power supply is the most effective and secure way to ensure energy as long as necessary to keep the nanorobot in operation. The same technique is also appropriate for other purposes like digital bit encoded data transfer from inside a human body [88]. Thus, nanocircuits with resonant electric properties can operate as a chip, providing electromagnetic energy supplying 1.7 mAat 3.3V for power, which allows the operation of many tasks with few or no significant losses during transmission [65]. RF-based telemetry procedures have demonstrated good results in patient monitoring and power transmission through inductive coupling [66], using well established techniques already widely used in commercial applications of RFID. The energy received can also be saved in ranges of \(\sim\)1\(\upmu\)W while the nanorobot stays in inactive modes, just becoming active when signal patterns require it to do so. Some typical nanorobotic tasks may require the device only to spend low power amounts, once it has been strategically activated. For communication, sending RF signals \(\sim\)1 mW is required. Allied with the power source devices, the nanorobots need to perform precisely defined actions in the workspace, using available energy resources as efficiently as possible.  
A practical way to achieve easy implementation of this architecture should obtain both energy and data transfer capabilities for nanorobots by employing cell phones in such process [7]. The mobile phone can be uploaded with the control software that includes the communication and energy transfer protocols.
# Towards Understanding Driver Acceptance of C-ITS Services--A Multi-Use Case Field Study Approach
## 1 Introduction
### C-ITS Impact Areas  
C-ITS development and deployment projects require a methodology to assess the impact of technology use and related benefits. Consequently, the FESTA handbook [21] was written, where impact assessment is an integral part. The methodology is used in C-ROADS [22] to evaluate the impact of C-ITS seen from a traffic infrastructure perspective. It specifies the following impact areas.  
1. Functional evaluation: Validation of the real-world performance of the services and use cases in the vehicle (examples can be found in Table 1)
2. Safety: Validation of the safety improvements (e.g., reduced number of near-collision events)
3. Traffic efficiency: Validation of the traffic efficiency (e.g., reduction of lost time on a stretch of a road)
4. Environment: Validation of the environmental situation (e.g., reduction of fuel consumption)
5. Socio-economic: Validation of the cost-benefit ratio of the deployed services and use cases.
6. Use acceptance: According to the FESTA handbook, user acceptance is defined as the degree of approval of a technology by the users.  
To get as much positive impact as possible, the C-ITS services must be accepted by the users. The drivers of the vehicles on the road must trust and comply with the in-vehicle information provided by the road operator.
## 4 Experiment Setup and Results
### Measuring the Maximum Average Output Power  
Another interesting point is the cycle time of each pulse. As already mentioned, when sufficient energy is presented to the voltage booster, it emits a pulse of 3.3 V. With increasing distance, the intensity of the electromagnetic waves decreases. Consequently, this energy scarcity leads to a longer time in the pulse cycle production. This observation was noticed by measuring the length of each cycle of the pulse. On an average, 4 readings were taken in order to be more accurate, and the outcomes of this experiment is reported in Figure 8.