esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Optimal Cluster Head Distance  
In an end-to-end multi-hop transmission considering an equal hexagonal cell, the best route between the source and the sink node is the direct line between them, where intermediate nodes are properly deployed (the nodes exists whenever needed). As shown in Figure 1, the data packet is transmitted from the source to the sink node, where \(L\) is the distance between them. Assuming that the distance between each CH is \(D\), \(m\) is the number of CHs and is derived as:  
\(R=\sqrt{13}\cdot r\), \(D=\sqrt{3}\cdot r\),  
\[m=\frac{L}{D}=\frac{L}{\sqrt{3}\cdot r} \tag{7}\]In this paper, we consider static traffic in the network. Network is considered to have static traffic when the traffic rate following along the network is constant. In the hexagonal cluster model, \(r\) represents the side of the hexagon and the optimal CH distance, while \(R\) is the maximum transmission range of a node and the range should be such that two nodes located anywhere in adjacent cluster should be able to transmit and receive data. The energy consumed for the end-to-end multi-hop transmission based on the energy consumption model discussed earlier is:  
\[E_{i}= E_{t}+E_{r}+E_{l} \tag{8}\] \[= (e_{e}+e_{a}R^{\upbeta})N+(e_{e})N+e_{e}d_{R}(1-\frac{N}{d_{R}})\] \[= (2e_{e}+e_{a}R^{\upbeta}_{i})N\] \[E_{t}= m\cdot E_{i}\] (9) \[= \frac{L}{\sqrt{3}r}\left[2e_{e}+e_{a}\left(\sqrt{13}r\right)^{ \upbeta}\right]N\]  
In order to find the minimum energy consumption, we take the first derivative of \(E_{t}\) with respect to the optimal CH distance, \(r\), and let: \(\frac{d}{dr}\left(E_{t}\right)=0\)  
\[\frac{d}{dr}\left(E_{t}\right)=\frac{L}{\sqrt{3}}\left(e_{a}N(\sqrt{13})^{ \upbeta}(\upbeta-1)r^{\upbeta-2}-\frac{2e_{e}N}{r^{2}}\right) \tag{10}\]  
From Equation (10), we can derive the value for \(r\), the optimal CH distance, as:  
\[r= \frac{1}{\sqrt{13}}\left(\frac{2e_{e}}{(\upbeta-1)e_{a}}\right)^{ 1/\upbeta} \tag{11}\] \[= \frac{1}{\sqrt{13}}\left(\frac{2e_{e}\lambda^{2}d_{R}}{(\upbeta- 1)p_{thr}(4\pi)^{2}}\right)^{1/\upbeta}\]  
By using correct transceiver parameters, Equation (11) shows the optimal CH location \(r\), which depends on the propagation loss factor \(\upbeta\) with values ranging from two to four and with the network traffic, and the relationship between propagation loss factor \(\upbeta\) and \(r\) is shown in Figure 2. In Figure 2,  
Figure 1: Cluster-based end-end multihop transmission in a hexagonal structure.  
the optimal CH distance and the side of the cell decrease when the propagation loss factor \(\beta\) increases, while network traffic \(N\) is constant. Furthermore, there is a trade-off between the number of CHs and the energy consumed in each CH. Based on Equation (8), when the number of CHs increases, the length of the side of the hexagonal cluster decreases, then energy consumption is dominated by the fixed energy consumption of each CH. When the number of CHs decreases, the length of the side of the hexagonal cluster increases, and energy consumption is dominated by the CH, because the energy consumed in the transmitter amplifier of each CH increases quickly.
# Design and Implementation of a Multi-Function Hydrophone for Underwater Acoustic Application
## Abbreviations  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} ADC & Analog-to-Digital Converter \\ ASK & Amplitude Shift Keying \\ AUV & Autonomous Underwater Vehicle \\ BER & Bit Error Rate \\ CE-DEF & Channel Estimation based Decision Feedback Equalizer \\ CPU & Central Processing Unit \\ DA-DEF & Direct Adaptive Decision Feedback Equalizer \\ DMIPS & Drnyrstone Million Instructions Per Second \\ DSP & Digital Signal Processor \\ DSSS & Direct Sequence Spread Spectrum \\ DMA & Direct Memory Access \\ FPU & Floating Point Unit \\ FTP & File Transfer Protocol \\ GPIO & General Purpose Input Output \\ GUI & Graphical User Interface \\ kSPS & Kilo-Symbols Per Second \\ LDPC & Low-density Parity-check \\ LFM & Linear Frequency Modulation \\ MCASP & Multichannel Audio Serial Port \\ MCU & Micro-controller Unit \\ OFDM & Orthogonal Frequency Division Multiplexing \\ OOK & On-off Keying \\ OSDM & Orthogonal Signal Division Multiplexing \\ PN & Pseudo Noise \\ QPSK & Quadrature Phase Shift Keying \\ RTC & Real-time Clock \\ SD & Secure Digital \\ SNR & Signal to Noise Ratio \\ SPI & Serial Peripheral Interface \\ SSP & Sound Speed Profile \\ ST & STMicroelectronics \\ TCP/IP & Transmission Control Protocol/Internet Protocol \\ UDP & User Datagram Protocol \\ USART & Universal Synchronous/Asynchronous Receiver/Transmitter \\ UUV & Unmanned Underwater Vehicle \\ WAV & Waveform \\ \end{tabular}  
Notes1 This picture is from Acoustic and Navigation Laboratory (ANL) in Haifa University, Israel.
## 3 Results and Discussion
### Sensitivity Analysis  
A sensitivity analysis of the Merredin WA mining sector considering different parameters such as RE sources (RESs) size, annual cost escalation, load demand, solar panel degradation and battery efficiency are measured. As illustrated in Figure 15, cost savings of the studied mining site is significantly affected by the considered parameters. It indicates that cost savings can be changed from USD $5.41 to USD $11.92 when varied the relevant factors.
## 5 Performance Evaluation
### Results
#### 5.3.2 Acceptance Ratio  
Long simulation runs have been carried out to evaluate the studied schemes in terms of the acceptance ratio over small and large scale networks, while the ILP-A has not been evaluated in the large scale networks due to its large execution time. The acceptance ratios of ILP-P in all scenarios are better than the acceptance ratios of  
Unlike the ILP-P, the DcPSM maps virtual paths to the shorter or equal physical paths, where the possibility of finding similar path identification is lower in small-scale. Therefore, the proposed DcPSM shows lower acceptance ratio in Simple-Small and Multiple-Small compared to the other schemes, while it shows higher acceptance ratio compared to the DSBM especially in Simple-Large and Multiple-Large.  
As expected, the increase of virtual links and paths has a high impact on the acceptance ratio compared to the increase of nodes. Figure 8 shows that the low acceptance ratios are distributed over the nodes axis and over edges axis for both DSBM and DcPSM. However, the low acceptance ratios are concentrating on the service requests with a high number of edges and paths as shown in Figure 8.
## 1 Introduction
This interconnected 6G ecosystem enables Immersive Communications across worlds, supports real-time control for responsive applications, and achieves cyber-physical twinning for advanced simulations and monitoring. depicted in Figure 1, Edge computing ensures the efficient processing of IoT data, since it allows the offloading of the data gathered by different devices (e.g., sensors, machines, robots, and cameras) to be processed outside these devices in order to create useful information for the user. This implies not only reduced latency and improved response times but also a simplification of devices, which has an impact on their fabrication costs. In addition, Edge computing also filters data locally before sending only the necessary insights to the Cloud, thereby reducing bandwidth usage and ensuring quicker decision-making [8]. Throughout the literature, there are many Edge computing architecture proposals to implement real-time Digital Twins or support the testing of future applications for research purposes. However, few of them are implemented in private 5G networks and deployed in real logistics and industrial scenarios. To address this gap, the proposed solution involves designing and implementing a hyper-distributed IoT-Edge-Cloud computing platform that is automatically managed for real-time Digital Twins in logistics and industrial environments. This platform is intended as a living lab and testbed for future 6G applications, developed to meet the requirements of end users and designed in close collaboration with them. The design integrates the latest advancements in AI-driven analytics, machine learning-based automation, and cross-domain interoperability. The system's hyper-distributed nature ensures that computation and decision-making occur at the optimal point--whether at the Edge, in the Cloud, or within the IoT device itself--depending on the application's specific requirements. This document is organized as follows: Section 2 provides a comprehensive overview of the state of the art in Digital Twin technologies, Edge computing, and IoT integration. Section 3 delves into the detailed design and development of the proposed hyper-distributed platform, highlighting its key components and functionalities, such as AI-driven orchestration. Section 4 presents the experimental platform setup, comprising two sites, including the frameworks used for the validation of the platform and early results on the 5G core and RAN performance. The validation also includes the implementation of a Digital Twin application prototype featuring immersive remote driving, where the QoS offered by the platform is demonstrated via an extensive QoE evaluation of the application. Section 5 discusses open challenges and potential future research directions, while Section 6 summarizes the key findings and contributions of this work.
# A Constrained Coding-Aware Routing Scheme in Wireless Ad-Hoc Networks
## 5 Conclusions  
In this paper, we reviewed the shortcomings of coding-aware routing in multi-flows and multi-rate networks and proposed a constrained coding-aware opportunistic routing (CCAR) to increase the performance of the multi-flow and multi-rate networks. The proposed mechanism consists of three components:  
1. It contains the constrained coding conditions to avoid the hotspot and solve the re-encoded problem.
2. To suit the constrained coding conditions, we added some routing information (such as Flow_nm, Neig_id and Code_f) in the RREP messages and simplified the process of routing and coding discovery.
3. In the EXQL metric, the novel coding benefit function introduces a weight factor that consists of queue length to resolve the rate matching problem and reduce the network delay.  
The simulation results for the grid topology demonstrated that the constrained coding conditions and the EXQL metric can improve the success ratio of decoded packets and trade off coding opportunities. In the random topology, the proposed CCAR scheme can significantly improve performance in terms of the network throughput and the average end-to-end delay compared with the existing DCAR and AODV + COPE schemes.  
In future work, we will further consider a more harsh scenario with a higher packet loss rate, node mobility, and the limitations of buffer size.  
Conceptualization, Y.Z.; data curation, L.L.; formal analysis, Y.Z., H.G., and L.L.; funding acquisition, S.X.; investigation, Y.Z.; methodology, Y.Z.; project administration, Y.Z.; resources, Y.Z.; software, H.G.; supervision, S.X.; validation, L.X.; visualization, L.X.; writing, original draft, Y.Z.; writing, review and editing, H.G., L.L., and L.X.  
This work was supported by the National Natural Science Foundation of China (NSFC No. 61372069), National Defense Pre-research Foundation, the SRF for ROCS, SEM (JY0600090102), the \"111\" project of China (No. B08038), the Chongqing Municipal Education Commission (No. KJ1501105), Chongqing Yongchuan Science and Technology Commission (No. Ycstc,2015 nc2001), and the Fundamental Research Funds for the Central Universities.  
We would like to appreciate the anonymous reviewers for their constructive comments which greatly improve the quality of the paper.  
The authors declare no conflict of interest.
# A Real-Time Semi-Supervised Log Anomaly Detection Framework for ALICE O\({}^{2}\) Facilities
## 2 Literature Review
### Non-Negative Matrix Factorization (NMF)  
Non-negative matrix factorization (NMF) [22] is a dimensionality reduction and clustering technique widely applied to text data for uncovering latent features and patterns. By approximating a non-negative data matrix as the product of two lower-dimensional matrices, NMF can extract meaningful topics or clusters from textual datasets. This property has made NMF particularly effective for log anomaly detection, where the sparse nature of log data aligns well with the method's non-negativity constraint. Its ability to decompose log data into interpretable components allows for identifying anomalous patterns and behaviors in structured datasets.  
Although there are no direct applications of NMF specifically targeting log message analysis, its use in related domains highlights its potential for anomaly detection. For example, [PERSON] et al. [32] utilized NMF to detect anomalies in profiling a program and user behavior by identifying deviations from typical patterns in user commands. Similarly, [PERSON] et al. [33] applied NMF to outlier detection in wireless sensor networks, showcasing its capability to manage large-scale and distributed systems. These studies demonstrate NMF's relevance for tasks that share similarities with log anomaly detection.  
Recent advancements in NMF methodologies focus on enhancing its robustness to noise and sparsity in text data. [PERSON] et al. [34] introduced an anomaly-aware symmetric NMF for short text clustering. This approach demonstrates the adaptability of NMF for anomaly detection in which one could consider short text as a log message.  
The primary strength of NMF lies in its ability to uncover hidden patterns in log data while maintaining interpretability by decomposing the data into meaningful matrices. However, NMF is highly sensitive to the initialization of the factor matrices. Poor initialization can lead to local optima instead of the global solution [35]. Additionally, NMF is computationally expensive. An alternative approach employs an alternating minimization cost function, which enhances its efficiency and scalability for large datasets [36].
# Dual Enhancement Network for Infrared Small Target Detection
## 3 The Proposed Dual Enhancement Network
### Residual Sparse Enhancement Module
For A, we use pixel-wise matrix multiplication along with the softmax function for normalization. We adjust the high-resolution salient features according to the affinity matrix. Following the same operation as the previous work [29] mentioned, we employ the residual structure in Equation (3). The low-resolution salient features are added to the adjusted high-resolution salient features to obtain the final \(f_{l-1}(\hat{p})^{r}\). We calculate the high-semantic sampled pixels through pixel-wise affinity according to the semantic similarity on the low-semantic sampled pixels, which can diminish the interference of redundant background information in the infrared scene. Finally, we scatter \(f_{l-1}^{r}\) into \(F_{l-1}\) according to the salient indexes \(I_{s}\) and obtain the refined feature \(F_{l-1}^{r}\). Since the substitution is based on the salient index, only useful salient information is propagated from top to bottom. The sparse correlation modelling for the high-resolution salient feature \(f_{l}(\hat{p})\) and the low-resolution salient feature \(f_{l-1}(\hat{p})\) also results in less interference from background noise when adjusting \(f_{l}(\hat{p})\) using the affinity matrix. Compared with the original features generated from the encoder, these refined features gain more salient information about small targets and less redundant information about complex backgrounds. Considering the importance of capturing contextual information, we additionally insert the pyramid pooling module (PPM) [30] into the top layer between the encoder and the RSE module. Finally, the enhanced feature with less background noise, precise location information, and rich semantic information can be obtained by combining these refined features in an additive way.
# Geotechnical Property Modeling and Construction Safety Zoning Based on GIS and BIM Integration
## 1 Introduction
### Scope of Work  
The main scope of this paper is to integrate BIM and GIS for the modeling of geotechnical parameters and use this model for safe construction planning. The GIS technology has been used in this study to spatially interpolate the values and provide geotechnical information along the whole region instead of only boring points as the borehole information provides one-dimensional information about soil condition along the depth having the spatial uncertainty [59]. BIM is integrated with the GIS to facilitate the visualization, details about each subsurface layer, append extra information, and calculate the volume of each soil layer available. The geotechnical investigation data from the in-situ and laboratory tests are used in this study since these tests provide information about the soil properties such as standard penetration test (SPT), cone penetration test (CPT), compressive strength, shear strength, etc., [14; 59]. The proposed BIM and GIS integration method is applied to the borehole dataset of the Peshawar region. The application of the proposed BIM and GIS integration provides geotechnical information for the whole region in great detail such as layers type with color code, their distribution, extra semantic properties such as laboratory test parameters information, and the thickness of each layer. Even though the proposed methodology and the results of the geotechnical property modeling can be applied for many purposes, however, the application in the scope of this paper was limited to identify a safe and proper construction type and place for the excavation design according to the OSHA soil classification.
###### Abstract  
This paper describes the simulation of the S (scattering)-parameters and absorbed energy for polymeric nanocomposites with metallic insertions (iron and aluminum, with two particle dimensions). The considered frequency domain, 0.1-3 GHz, is specific for a wide range of applications in microwave technologies. The actual limitations of electromagnetic simulations are described, along with an application related to the Nicolson-Ross-Weir procedure in infinite media, which opens new perspectives in nanocomposite electromagnetic modeling. It was demonstrated that, due to a higher conductivity, nanocomposites with Al particles can absorb a larger amount of energy compared to Fe particles within composite materials, at both insertion dimensions. At higher frequencies, the power loss density increases for both metals. The significant reduction in transmission, linked to a minimal reflection, verifies that for composites with added metallic powder, microwave energy is extensively absorbed by the materials, particularly at frequencies above 1.5 GHz, confirming their potential functionality as hot melts for advanced reversible bonding technologies.  
microwave domain; Nicolson-Ross-Weir procedure in infinite media; S-parameters; absorbed energy; polymeric nanocomposites; metallic insertions Article
# A Survey on Approximation in Parameterized Complexity: Hardness and Algorithms
## 4 Algorithms
### Clustering
#### 4.3.1 General Metric Space
Otherwise, recall that \(S_{i}=\{s_{1},\ldots,s_{t}\}\) where each \(s_{j}\) is an independent and uniform sample from \(P_{i}\) with weight \(w:=|P_{i}|/t\). For \(j=1,\ldots,t\), let \(X_{j}:=w\cdot\rho(C,s_{j})\). Note that \(\operatorname{cost}(S_{i},C)=\sum_{j}X_{j}\) and \(\operatorname{cost}(P_{i},C)=t\cdot\mathbb{E}[X_{j}]=\mathbb{E}[\operatorname {cost}(S_{i},C)]\). A crucial observation is that that \(|\rho(C,p_{j})-\rho(C,p_{j^{\prime}})|\leq\operatorname{diam}(P_{i})\) for any \(j,j^{\prime}\in[|P_{i}|]\), so that \(|X_{j}-X_{j^{\prime}}|\leq w\cdot\operatorname{diam}(P_{i})\) for any \(j,j^{\prime}\in[t]\). If we let \(X_{\min}:=\min_{j\in[|P_{i}|]}(w\rho(C,p_{j}))\) and \(Y_{j}:=(X_{j}-X_{\min})/(w\cdot\operatorname{diam}(P_{i}))\), \(Y_{j}\)'s are \(t\) i.i.d. random variables that are supported in \([0,1]\). The standard Chernoff-Hoeffding inequality gives  
\[\Pr\left[|\sum_{j}X_{j}-t\mathbb{E}[X_{j}]|>\varepsilon|P_{i}|\operatorname{ diam}(P_{i})\right]=\Pr\left[|\sum_{j}Y_{j}-t\mathbb{E}[Y_{j}]|>\varepsilon t \right]\leq\exp(O(\varepsilon^{2}t))\leq o(1/(\ell\cdot n^{k})),\]  
proving (1) for \(t=\widetilde{O}(k\log n)\) and finishing the proof. A precise version of this argument was stated in Haussler [163].
## 3 Proposed Design
### Application Traffic Patterns Identification
#### 3.1.4 Pulse Oximeter  
A pulse oximeter is helpful for measuring the heart rate, oxygen saturation levels (SpO2) and blood volume that is related with the cardiac cycle. It can be placed on an earlobe or finger and it is composed of the infra-red light-emitting diodes (LEDs) and a photodetector which is useful to measure oxygenated hemoglobin to deoxygenated hemoglobin. From Table 1, considering sampling rate 100 Hz and the sampling resolution 12 bits, we have SIT = 10 ms; MPDS = 150 bytes/s; DNS after 10 ms including minimum header size = 132 bits; Total data rate required by Pulse oximeter packet = 13.2 Kbps.
# Train-Induced Vibration Analysis and Isolation Trench Measures in Metro Depot Structures
## 2 Environmental Vibration Model of Metro Depot
### Over-Track Platform and Building of the Metro Depot  
In this study, a metro depot is used as an example for simulation analysis. The metro depot adopts an integrated structure combining the over-track platform and the building. As shown in Figure 2, the model focuses on the section near the depot gate in the operation depot. The over-track platform is a reinforced concrete frame structure. The first floor is used as the operation depot, with a floor height of 11.3 m. The second floor is used as a vehicle garage, with a floor height of 5.1 m. The platform spans four bays longitudinally along the track direction, with each bay measuring 12 m, resulting in a total length of 48 m.  
Transversely, the platform spans five bays, with each bay measuring 6.8 m, resulting in a total width of 34 m. A nine-story residential building is constructed above the platform. The building adopts a reinforced concrete frame structure. The first floor of the building has a floor height of 5.1 m, while the remaining standard floors have a uniform floor height of 3.1 m. The structural layout of a standard floor is shown in Figure 3, and the numbering of the standard floor slabs is presented in Figure 4.  
The floor slabs and filling walls in the over-track platform and building structure are simulated using shell elements. Structural beams and columns are simulated using beam elements. The element size ranges from 0.5 to 1 m. The shell elements consist of two types: S3R and S4R. A total of 360 S3R elements and 11,030 S4R elements are used. The beam elements are of type B31, with a total of 5635 elements. The material parameters for the structural components of the building are listed in Table 1.  
Figure 4: Floor slab number.  
Figure 3: Standard floor structure.  
Figure 2: Over-track platform and building structure.  
The Rayleigh damping model is used to simulate the attenuation of train-induced vibrations during propagation. The damping ratio of structural component materials is set to 0.05. The lower and upper limits of the vibration frequency range of interest for structural components are set to 1 Hz and 80 Hz, respectively.