esa-sceva/satcom-chunk-collection huggingface dataset:
# Augmented Reality for PCB Component Identification and Localization
## 4 Materials and Methods
### Experiment 1-Methods
#### 4.2.1 Technical Setup  
The augmented reality (AR) system was developed using the Unity(tm) game engine, widely recognized for supporting complex 3D modeling and real-time AR interactions [21]. A digital twin of the printed circuit board (PCB) was created using a high-resolution image of its front face, overlaid with dynamically rendered 3D markers. These markers were synchronized in real-time with the PCB's rotation and position, enabling accurate alignment as the user shifted their perspective [13].  
The Microsoft(tm) HoloLens(tm) 2 served as the optical see-through head-mounted display (HMD-OST), showing only a red marker in the AR interface to guide component identification. This marker updates dynamically to maintain alignment with the physical PCB (Figure 2).  
To enable marker-based tracking, the Vuforia(tm) engine was employed by treating the PCB image as a pattern target. This markerless approach supported lightweight deployment, but its effectiveness depended on the visual distinctiveness of the PCB's textures. In regions with dense or miniaturized components, reduced feature contrast led to tracking instability, particularly at oblique viewing angles. Prior research has demonstrated that marker detection stability is influenced by factors such as marker size, position, and orientation [22; 23].  
The digital twin in this study comprised only the 2D PCB image and the overlaid markers. The system exchanged only rotation and position data between the digital and physical boards, ensuring persistent spatial alignment [13].  
The user interface (UI), developed using Unity(tm) and the Mixed Reality Toolkit (MRTK), was designed to minimize distractions and enhance operational efficiency during PCB component identification. It integrated gesture recognition, spatial mapping, and pre-built MRTK components to support intuitive interaction [19]. Users could search for components, toggle marker visibility, and reposition interface panels within their field of view. Visual cues indicated successful board recognition, while markers were placed  
Figure 2: A red 3D marker for a component rendered on the PCB.  
based on precise coordinates from the pick-and-place file to ensure alignment with the physical PCB.  
The interface emphasized clarity, minimal visual clutter, and task continuity, aligning with best practices in AR information presentation [7]. These design choices contributed to effective task performance, particularly for non-expert users, by reducing cognitive load and maintaining user engagement.  
Together, Unity(tm), Vufforia(tm), and MRTK provided a cohesive framework for developing the AR system, enabling a precise, task-specific interaction in electronics manufacturing contexts. Figure 3 shows the texture-mapped digital twin and 3D markers rendered in the Unity(tm) environment.
# Digital Pre-Distortion of Carrier Frequency Offset for Reliable Wi-Fi Enabled IoTs
## 4 Related Work  
Many studies have been done to provide reliable communication links to users in IEEE 802.11 standards [15; 16; 17; 18]. In the conventional wireless devices, a CFO is estimated by a unit of a packetusing a preamble located at a header of a data packet transmitted through a wireless channel in an OFDM wireless communication system [17; 18]. The conventional wireless systems compensate the CFO by estimating the CFO based on the received frames at the receiver. Furthermore, data is restored by compensating for the estimated CFO when a signal field and a data field of the data packet are restored. An OFDM communication system transmits and receives a massive amount of data through multi-subcarriers. In the OFDM communication system, each subcarrier of a wireless channel has an orthogonal property that transmits and receives multi-subcarriers. In order to improve the data transmission rate of a limited wireless channel, the OFDM communication system determines the channel state of a wireless channel and controls the transmitting and receiving of data based on the determined channel state of the wireless channel.  
The OFDM communication system estimates a CFO using a unit of a packet; it then restores the transmitted data packet by compensating for the estimated CFO. However, it is difficult to accurately estimate a CFO when the wireless channel state is very poor due to noise, interference or channel effects, for example when the signal to interference and noise ratio (SINR) of a wireless channel is smaller than a predetermined threshold value. When the transmitted data packet is restored by compensating for an inaccurately compensated CFO, the packet error rate increases and throughput drops. Particularly, if the mobile terminal in the OFDM communication system is in a dense network, channel variation and interference are further and more seriously generated and the wireless channel state abruptly varies. Accordingly, inaccurate estimation of the CFO and the data packet error are further and frequently generated. As a result, the data transmission rate significantly deteriorates and overall system performance also rapidly drops.  
Therefore, there have been demands for the development of a data transmitting/receiving method to minimize errors generated while restoring data packets and improving data transmission rate by accurately estimating the CFO of data packets transmitted through wireless channels in wireless communication systems such as the OFDM communication system. When a CFO estimation error is generated due to a poor wireless channel state such as low SINR in a dense network, an error is generated while restoring the information included in a signal field, such as the data packet length and the data transmit rate. Accordingly, an error is generated in the next data packet or data packet transmission is delayed because the end of the data packet is determined inaccurately. As a result, system performance deteriorates.
## 3 Preliminary Methodology  
The complete virtual commissioning process is based on a methodical approach that includes three basic phases: analysis, design, and implementation [72]. This systematic approach enables the detailed development and verification of the assembly system in a digital environment before its physical implementation, thus reducing potential errors and optimizing the production process [73].  
This section outlines the methodology for integrating a CPS into a DT for real-time data collection, processing, and evaluation. The goal is to establish seamless interoperability between the physical system and its digital counterpart through an effective communication and control framework.  
The MPS(r) 203 I4.0 (Festo Didactic GmbH & Co. KG., Denkendorf, Germany) [74] was selected as the CPS model, serving as a platform to test digital twin integration in manufacturing. A crucial aspect of this research is the choice of a suitable software tool for 3D visualization, system behaviour modelling, and standardized communication protocol support.  
The system relies on Siemens PLC as the primary control unit, with a focus on its efficient integration with the digital replica in a simulated environment. The selected solution has to ensure control signal generation, behavioural modelling, and real-time communication, enabling a functional and responsive digital twin.
# Video Streaming Adaptive QoS Routing with Resource Reservation (VQoSRR) Model for SDN Networks
## 3 The Proposed VQoSRR Framework  
In this part, we describe the proposed VQoSRR framework. Section 3.1 explains the network model architecture, Section 3.2 describes the QoS routing mechanism, and Section 3.3 describes the VQoSRR reservation method.
## 4 Classification Based on Taxonomy and Design Drivers
### Similarity Search
In the query probing phase there can be the two following possible cases:  
* Case 1: \(I_{T}\) is non-empty and \(v_{s}^{t_{i}}\) is the most similar local data in \(I_{T}\). * Sub-case 1: If \(v_{s}^{t_{i}}\) is larger than \(v_{q}\), then all data in \(I_{T-i}\) must be even greater than \(v_{q}\). But in \(I_{T-i}\) there may be a \(v_{s}^{t_{T-1}}\) that is closer to \(v_{q}\). * Sub-case 2: If \(v_{s}^{t_{i}}\) is smaller than \(v_{q}\), then all data in \(I_{T-i}\) must not be more similar to \(v_{q}\) than \(v_{s}^{t_{i}}\) is. But in \(I_{T+i}\) there may be a \(v_{s}^{t_{i}\cdot}\) that is closer to \(v_{q}\). * Case 2: \(I_{T}\) is empty (_i.e._, no data stored). \(v_{q}\) has to be sent to both neighbors (_i.e._, \(I_{T-i}\) and \(I_{T+i}\)) of \(I_{T}\) to find the most similar data. In SSA, three functions are proposed referred as backward probing, forward probing and bi-directional probing where backward probing and forward probing are used to deal with Case 1 and bi-directional probing is used for Case 2.
# A Survey on Congestion Control for RPL-Based Wireless Sensor Networks
## 4 Congestion Control Schemes for RPL
### Schemes Exploiting Path Diversity
#### 4.2.4 RPL using the Heuristic Load Distribution Algorithm  
[PERSON] et al. propose a multipath routing mechanism based on RPL and a load distribution mechanism to equalize traffic load between nodes of the same level in a DODAG using the heuristic load distribution algorithm (HeLD) [36]. To construct a multipath DODAG, a node \(i\) maintains a parent set \(P_{i}\) using DIO messages received from more than one neighbor node with the minimum hop count. Node \(i\) computes its rank \(R(i)\) as follows.  
\[C_{ij}=R(j)+c_{ij} \tag{17}\]  
\[w_{j}(i)=1-\frac{C_{ij}}{\sum_{j\in P_{i}}C_{ij}} \tag{18}\]  
\[R(i)=\sum_{j\in P_{i}}w_{j}(i)C_{ij} \tag{19}\]  
where \(c_{ij}\) denotes the cost of link \((i,j)\), \(C_{ij}\) the route cost from node \(i\) to the sink through node \(j\), \(w_{j}(i)\) parent \(j\)'s share of node \(i\)'s output traffic rate. The share \(w_{j}(i)\) is initialized as shown in Equation (18), but adaptively updated by their load distribution algorithm. The authors used ETX as the main routing metric (i.e., \(c_{ij}\)). Since the rank must increase monotonically, any parent with a greater rank is removed from the parent set and the rank is recomputed.  
The authors formulate the cost-efficient load distribution optimization problem as a network flow problem. To approximately solve the problem using local information only, they propose the heuristic load distribution (HeLD) algorithm. In HeLD, each node compares the input traffic rates of its parents in a pairwise manner. If the input traffic rates are not close enough between two parents, the traffic shares are gradually adjusted to be equalized between the parents, i.e., the nodes of an equal depth from the sink. In this way, HeLD tries to equalize energy consumption rates between the nodes of an equal depth from the sink while minimizing the total transmission cost. To this end, each node must obtain its parent nodes' incoming traffic rates through feedback messages such as 'hello' or 'ACK'.  
For performance evaluation, the authors compared this scheme to the standard single-path RPL and a node-disjoint multipath routing algorithm via simulation using OMNET++ and MATLAB. At the data link layer, unslotted CSMA-CA over IEEE802.15.4 was used. Simulation results show that this scheme enhanced the network lifetime and throughput compared to the other schemes, but caused more link drops due to utilization of less reliable links.
# Application of Reinforcement Learning in Decision Systems: Lift Control Case Study
## 2 Description of the Problem and Concept of the Solution
### Problem Definition  
The task presented to the lift system controller can be defined as follows: for \(N\) passengers wishing to travel from the starting floor \(s_{i}\) to the destination floor \(d_{i}\), denoted as \((s_{1},d_{1}),(s_{2},d_{2}),\ \ldots,(s_{N},d_{N})\), the goal is to determine a sequence of visited floors \(p_{1},p_{2},\ \ldots,p_{k}\) in such a way that, for each passenger, their starting floor \(s_{i}\) precedes their destination floor \(d_{i}\). Moreover, if the task includes finding a sequence of minimal length, the problem becomes \(\mathcal{NP}\)-complete due to a reduction from the problem of cyclic vertex cover, as demonstrated by [PERSON] and [PERSON] [2] in 1999. Similarly, the problem addressed in this work may share similarities with variants of the Traveling Salesman Problem or the Routing Problem, but none of them fully models it. This is because the cost of travel depends not only on the order in which passengers are serviced but also on how they are grouped. Additionally, these aforementioned problems operate in static environments and assume full knowledge of them, while in lift control systems, passengers appear dynamically, and the complete system state is unknown. Hence, heuristic algorithms for real-time lift system control have been developed. Below, we outline those that can be used in a single-lift system, as described by [PERSON] and [PERSON] [3].
# Electromagnetic Characteristics Analysis of a Tubular Moving Magnet Linear Generator System
## 3 Electromagnetic Analysis  
### Finite Element Model  
To analyze the characteristics and evaluate the performance of the linear generator designed in the last section, a three-dimensional finite element model (FEM) is created and a transient computing method with a motion solver is used. Compared to the simplified two-dimensional finite element model, the three-dimensional finite element model is more accurate; the end effect of the coil and the magnetic flux leakage in the stator core are considered and the eddy losses in the PM ring, the shell, and the shaft are also considered by the model. Commercial electromagnetic field analysis software was used to carry out the finite element analysis (FEA) of the model.  
As shown in Figure 4, the finite element model is 1/12 of the designed linear generator for reducing the computation time. The two cut surfaces of the FEM model are set as the flux tangential boundary. The model is meshed by triangular finite elements. To display the internal structure, the magnetic field in the coil and the air box of the calculation region are hidden. The mover moves along the x axis, as shown in the figure. The mover is in the start of the stroke, and it is defined as the original point. The magnetic field is mainly distributed in ferromagnetic materials. The leakage flux in the shell and the shaft is relatively small but also induces a certain amount of eddy current loss.
# Fuzzy-Logic Dijkstra-Based Energy-Efficient Algorithm for Data Transmission in WSNs
## 4 Proposed Fuzzy Logic Dijkstra-based Routing Algorithm
### Network Deployment Phase  
This is the initial phase, wherein the network management control messages are exchanged between the BS and sensor nodes. The BS broadcasts the initialization request message (\(M_{IRQ}\)) to all the sensor nodes in the network field. Once the \(M_{IRQ}\) message is received by a sensor node, it responds with an initialization reply message (\(M_{IRP}\)). This exchange of messages occurs to know the current location and residual energy of the nodes in the deployment area [31].
## 2 Theoretical Background
### The Virtual Knowledge Graph Framework  
In scholarly literature, the _Virtual Knowledge Graph_ (VKG) framework is also called _Ontology-based Data Access_ (ODBA) [36], and its paradigms refer to an integrated data approach and data access to diverse data sources, either internal or external [4]. As a result of VKG, the rigid structure of tables in relational databases and data model structures is replaced by the flexibility of graphs that are kept virtual and are effective in encapsulating domain and contextual knowledge. The data-driven landscape requires integrating data and providing seamless access to end users that is time-consuming, cost-effective, and rigorous [29]. Various data integration tools are available [8], enabling users to integrate data from other sources using the standard relational model, which is inflexible [4]. Moreover, only a few vendors integrate data without moving or transforming data sources [29], such as Denodo [37], Dremio [38], and Teiid [39].  
As a result of the VKG, three essential parameters are incorporated: First, _Data Virtualization_ (DV) is a technique that assists end users by providing them with global schemas of relevant domain-oriented data, contextual knowledge, and dispersed data sources rather than individual physical data sources like _Local-As-View_ (LAV) [4]. Although the federated global perspective [38; 40] may still need to be fully achieved, DV enables query data without incurring storage, data movement, and retrieval time cost factors [4; 29].  
Secondly, the data are subsequently represented as a graph (G), where domain objects and data values serve as nodes and object characteristics as edges [4; 41]. Thirdly, _Domain Knowledge_ (DK) and _Contextual Knowledge_ (CK) enhance the network, supporting the data by organizing concepts [4], property hierarchies, inter-domain properties, and essential attributes [40; 42]. The VKG technique [4], or OBDA [43], has been extensively studied in the formal context of ontologies. Virtualization in OBDA is achieved by defining mappings between disparate data sources, models, and the domain ontology (_federated ontology_) [36].  
Additionally, mapping assertions include information on how to construct identifiers for objects within the ontology, such as those that appear in replies to user queries based on the values obtained from the sources, such as _Uniform Resource Identifiers_ (URIs) or _International Resource Identifiers_ (IRIs) [29].
## 1 Introduction
In our study, the evaluations were performed using the Thurstone method with ties (TH), the analytic hierarchy process with logarithmic least squares method (AL) and the RankNet (RN) neural network. During our analysis, we also investigated the effect of the weighting factor of international matches. The resulting rankings were compared to each other and also to the UEFA coefficient rankings. Additionally, we also made comparisons with data from Transfermark [35] that contained the financial values of the teams. Furthermore, we also compared the entire national leagues to each other and determined the rankings of the national championships. Summarizing the methods and results related to this research, the contributions of this article are as follows: (1) The unified ranking of the teams playing in the five strongest European football leagues was determined based on _incomplete comparisons_. For this purpose, the results of all matches played in the national championships and the results of matches played between the same teams in international leagues were considered. (2) The methods used allowed teams that did not play international matches to be included in the rankings. (3) The ranking capabilities of the Thurstone method, the analytic hierarchy process with logarithmic least squares method, and RankNet were compared in a ranking task based on incomplete comparisons. (4) Finally, based on the experimental results, the main characteristics of the investigated methods were also highlighted. The structure of the paper is as follows: In Section 2, we briefly present the research papers connected to the evaluation of football championships. Then, in Section 3, the methods applied for evaluation in the current study are briefly presented, namely the Thurstone method with maximum likelihood estimation, the analytic hierarchy process with logarithmic least squares method, and the RankNet method. Section 4 presents the research methodology. In Section 5, the evaluation results are presented and discussed. Section 5.1 contains the evaluation of match results in the Premier League by all three methods. Section 5.2 comprises the unified rankings of the teams in the five above-mentioned championships. Section 5.3 presents the correlations between the resulting rankings and the financial value of the teams, while Section 5.4 contains the rank correlations between the presented rankings and the UEFA club coefficient rankings in the case of those teams that played matches in international cups during the 2020/2021 season. In Section 5.5, the national leagues are compared to each other. Then, in Section 6, we summarize the properties of the applied evaluation methods. Finally, some conclusions are drawn in Section 7.
# Improving Multi-Label Learning by Correlation Embedding
## 4 Experiment
### Evaluation Metrics
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Data**} & \multicolumn{8}{c}{**Example-Based F1 \(\uparrow\)**} \\ \cline{2-7}  & **MLLCE** & **NL-MLLCE** & **ML-LSS** & **JFSC** & **BR** & **Glocal** & **MLL-FLSDR** \\ \hline rcv1 subset1 & 0.262 \(\pm\) 0.007 & 0.265 \(\pm\) 0.008 & **0.306**\(\pm\) 0.007 & 0.271 \(\pm\) 0.010 & 0.244 \(\pm\) 0.008 & 0.301 \(\pm\) 0.007 & 0.279 \(\pm\) 0.011 \\ rcv1 subset2 & 0.265 \(\pm\) 0.007 & 0.262 \(\pm\) 0.004 & **0.338**\(\pm\) 0.013 & 0.323 \(\pm\) 0.011 & 0.284 \(\pm\) 0.014 & 0.325 \(\pm\) 0.007 & 0.277 \(\pm\) 0.020 \\ enron & **0.486**\(\pm\) 0.011 & 0.504 \(\pm\) 0.021 & 0.500 \(\pm\) 0.020 & 0.534 \(\pm\) 0.013 & 0.555 \(\pm\) 0.007 & 0.523 \(\pm\) 0.013 & **0.563**\(\pm\) 0.018 \\ recreation & **0.299**\(\pm\) 0.010 & 0.274 \(\pm\) 0.010 & 0.278 \(\pm\) 0.012 & 0.265 \(\pm\) 0.013 & 0.243 \(\pm\) 0.009 & 0.037 \(\pm\) 0.008 & 0.275 \(\pm\) 0.015 \\ stackex-coffee  
ranking loss and AUC. We can note that the performance of MLLCE is not so sensitive to the value of \(d_{1}\).
## 1 Introduction
[13] examined the effects of additive manufacturing on 316L, revealing the formation of voids due to air gaps between rasters, which adversely affect mechanical properties. [PERSON] et al. [8] emphasized the relationship between porosity distribution, build orientation, and printing strategy, noting that increasing nozzle diameter reduces porosity and improves mechanical performance, whereas decreasing nozzle diameter enhances geometric accuracy at the cost of mechanical strength. [PERSON] et al. [14] found that catalytic and thermal binder removal processes did not impact the mechanical properties in 316L additive manufacturing and also highlighted the cost-effectiveness of using metal filament in this process. [PERSON] et al. [15] focused on nozzle temperature, recommending a range of 195-205 \({}^{\circ}\)C for optimal mechanical properties, with a correlation found between relative density, microstructures, and hardness. [PERSON] et al. [16] applied warm isostatic pressure (WIP) and observed a 2.5-fold increase in the tensile strength of 316L samples produced by additive manufacturing. Lastly, [PERSON] et al. [17] employed artificial intelligence to optimize parameters in lattice structuresmade of 316L, achieving significant improvements in mechanical properties across various lattice configurations. The objective of this research is to examine whether it is possible to produce high-performance and durable structures using 316L stainless steel filament through additive manufacturing. The mechanical and physical properties of parts produced using FDM technology were evaluated. The study aims to reveal the potential of metal-based additive manufacturing technologies in medical and industrial applications. By encouraging the development of additive manufacturing technologies and the use of high-performance materials like 316L stainless steel, this research seeks to contribute to making future production processes more efficient and flexible. Additionally, the literature indicates variations in the debinding and sintering processes applied to 316L stainless steel, resulting in significant changes in product quality. It has also been observed that layer thickness significantly affects tensile strength [8]. This study investigates the effects of debinding parameters and layer thickness on the properties of 316L parts produced using FDM.