esa-sceva/satcom-chunk-collection huggingface dataset:
# Geometric Spherical Surfaces Emulating the Geostationary Orbit at Any Latitude with Zenith Links
## 1 Satellite Constellations: Many Architectures and Many Problems
Therefore, each satellite can easily connect with its neighbors both in the same plane and in the adjacent planes. This orbital characteristic simplifies the networking design. However, to avoid satellites crashing at poles when all orbit planes meet, near polar orbits with inclination ranging from \(80^{\circ}\) to \(100^{\circ}\) are used to replace the perfect polar orbit at \(90^{\circ}\)[1]. Whatever solution is adopted for designing a satellite constellation, the complexity of a system composed of many satellites is large and refers to: launch of many satellites, distribution along the orbit with accurate positions, control and maintenance for all the lifespan, provision of the disposal at the end of life, and so on. The most challenging task is the control and maintenance of the constellation over a long time, which requires control of each satellite and of each satellite with respect to the others. After [14], in this paper, we propose to use the [PERSON] star constellation to emulate, for any latitude, the geostationary orbit with zenith paths. In other words, any transmitter/receiver, located at any latitude, can be linked to a satellite as if the site were at the equator and the satellite at its zenith. In other words, the distributed geostationary satellite concept, discussed in [14], will not be only in the equatorial plane, but in any plane parallel to the equatorial plane, from \(0^{\circ}\) latitude to \(90^{\circ}\) latitude, North or South, therefore covering also the poles, without an ad-hoc communication system [15]. The proposed constellation design can have most of the advantages of the current GEO, MEO and LEO constellations without having most of their drawbacks. Our aim is to put forth the main theoretical ideas about this design. The technological development necessary to make it practical should be addressed in many future studies. In the following, we refer to this design as to the geostationary surface (GeoSurf) constellation design. After this introduction, Section 2 sets the theory of the Walker star constellation used for the GeoSurf design. Section 3 shows some straight theoretical results concerning the number of satellites, service area dimension, available flight time for single satellites, and size of antennas. Section 4 discusses the overall theoretical results by comparing the GeoSurf constellation with the current constellations and draws some conclusions.
# Use of Binary Classification in Non-Invasive Load Monitoring
## 5 Classifiers Used for Identification
### Neural Classifier with a Decision Module  
The preclassification module of the neural classifier consisted of a set of neural networks (Figure 4), each of which was used to classify a device into one class--providing an answer to the following: Does the identification vector describe the device? The networks have an identical structure and consist of 5 neurons in the input layer, 15 in the hidden layer, and 1 in the output neuron. The number of neurons in the input layer is dictated by the length of the input vector, whereas the number of neurons in the input layer is the number of distinguishable classes. Owing to the lack of analytical methods for determining the number of hidden layer neurons [28], this selection was made experimentally (networks with 1 hidden layer and 2 hidden layers were tested). Similarly, a tangential transition function was selected for these layers, while the output layer neurons were fitted with a linear transition function. The Levenberg-Marquardt method, characterized by high efficiency and speed of learning, was used to teach the network [29].  
The decision block determines the final response of the system according to the following principle: if only one of the networks has indicated a device, then this device is recognized, and this response is given at the output of the system. If more than one network indicates that 'its' device is working, the decision module compares the response values and points to the one that has been most strongly indicated (the network response value is the highest), which can be described by the following relation:  
\[\forall j\
eq i:\left[Y_{j}\leq Y_{i}\right]\ \Leftrightarrow\ Decision=Y_{i} \tag{4}\]  
Figure 4: Schematic of a classifier based on artificial neural networks.  
where  
Decision--decision of the classifier;  
\(Y_{i}\)--the response of the i-th neural network.
## 3 Discussion  
In this study, we synthesized thirteen cyanopyridines and five pyrimidines and screened for antibacterial activity in eight strains. We found that cyanopyridine derivatives (**5a** and **5b**) have an antibacterial effect against _E. coli_ and _B. subtilis_. However, other synthesized molecules of the same family did not exhibit any antimicrobial effects against either bacteria or fungi at the tested concentrations [41; 42].  
A single pyrimidine derivative (6b) showed antibacterial activity, probably due to the nature of the heterocyclic. Our results are in agreement with other scientific findings [43] from studies on the antibacterial and antifungal effect of new pyrimidine derivatives based on benzothiazole by testing on bacterial strains (_S. aureus_, _E. coli_, _K. pneumoniae_, and _P. aeruginosa_) and on the fungal agent _C. albicans_. These studies revealed that the derivatives exert an antibacterial and antifungal effect, which varies from one molecule to another, and some of the derivatives were found to have antibacterial effects on all the strains tested, as well as an antifungal effect against _C. albicans_. This effect can be influenced by aromatic substituents, in particular, those with electron-donating properties.  
Several targets have been described for antibacterial agents, such as disruption of cell walls, membrane permeabilization, targeting of drug efflux pumps, targeting of R plasmids, and targeting quorum sensing, which plays an important role in regulating biofilms. Several studies showed that antibacterial agents tend to act more strongly on Gram-positive than on Gram-negative bacteria. This is probably due to the differences in cell wall composition and structure, as Gram-negative bacteria possess an outer membrane [44].
# Multi-Media and Multi-Band Based Adaptation Layer Techniques for Underwater Sensor Networks
## 5 Analyzing the Challenges and Advantages of Protocols in Underwater Communication
### Routing Layer Protocols
#### 5.2.1 Routing Protocols Including Localization Techniques  
SEANAR [35] was developed in 2010; it acts as a power efficient routing protocol for underwater communication. SEANAR shares topology information along with other information with the neighboring node. REBAR [36] was developed in 2008. In this approach, a cylindrical path is created between source and destination. This method is used for energy balancing in underwater routing techniques. Its major disadvantage is the difficulty of finding the position of the node due to node mobility. A Depth Adaptive Routing Protocol DARP [37] was developed in 2012; this approach is based on the depth of water and the speed of signal changes. The test proves that when the depth is under 1000 m, the signal strength is good, and communication is faster. The result shows that it will reduce the delay between end-to-end communication. Lifetime-Extended Vector-Based Forwarding (LE-VBF) [38] was developed in 2012. This approach is used for energy saving. The Mobicast [39] routing protocol, also known as mobile geocast, was developed in 2012. The data collection efficiency is solved by using this protocol. This approach comprises two phases: in the first phase, it collects the data inside the 3-D ZOR; in the second, the nodes in the 3-D ZOR are woken up. Because of this approach, power can be saved by activating the nodes only inside the 3-D ZOR. HH-VBF [40] was developed in 2008. This protocol is used to reduce the data load while routing through VBF. Computational complexity is the major issue associated with this approach. Vector-Based Void Avoidance (VBVA) [41] was developed in 2009. The vector shift routing strategy is used in this approach. One of its advantages is a high packet delivery rate; the major disadvantage is its high- power consumption and delays in data delivery.
## 3 System Design and Implementation
### Client Server Model
#### 3.4.3 Server-Side Application  
A TCP connection is a reliable one-to-one communication window that facilitates bi-directional talk between two terminals. However, in our case, as previously mentioned in Section 3.4, a server is required to send a response to all the queries sent by the clients at any given time. Since a single socket connection  
between a client and the server is exclusive, no other client can share this channel. For the communication to happen between the server and a client, while there is already an active communication channel, we have to rely on a concept called \"Concurrency\". Hardware exception handlers, processes, and Unix signal handlers are all familiar examples of Concurrency in a computer system. In this context, a concurrent server is one that creates a separate logic flow for each client. Nowadays, systems are equipped with multi-core processors that contain multiple CPUs to handle various tasks at once. Applications that run in such machines are faster and executed in parallel rather  
Figure 4: General-purpose input/output pins of Raspberry Pi model B+ [29].  
than being interleaved, as used in single-core systems. There can be three different approaches to dealing with concurrency in modern systems. These are:  
* **Processes:** The kernel schedules and maintains each logical control flow as a process. If processes need to exchange information with one another to complete a particular task, then they need to perform some kind of inter-process communication due to their individual virtual address space.
* **I/O multiplexing:** In this form of concurrency, a program is a single process where all logical flows share the same address space. The logical flows are modeled as state machines by the main program, which explicitly makes state-to-state transitions according to the data arriving on file descriptors.
* **Threads:** Threads are a hybrid of the two earlier approaches, and scheduled by the kernel as process flows, it shares the same virtual address space, like I/O multiplexing flows [31].  
In prototype application implementation, we used \"threads\" as a means to provide multi-tasking capability. This abstraction is provided by Python 2.7 in the form of a module called \"concurrent.futures\". This module provides a high-level interface for asynchronous execution of \"callables\" [32]. This execution can be carried out either by threads using a \"ThreadPoolExecutor\" or by processes using a \"ProcessPoolExecutor\". We chose the former, as it is generally preferred for I/O-bound applications.
# Review of GIS-Based Applications for Mining: Planning, Operation, and Environmental Management
## 2 Mine Development Phase  
Generally, the mine development phase consists of mine planning, construction, operation, and reclamation [9]. In the planning phase, the mineralized target is found through geophysical and geochemical exploration. In the construction and operation phases, infrastructure is built for mineral production, and ore materials are extracted using heavy equipment. Finally, in the reclamation phase, all undesirable materials, such as waste, tailings, and contaminated toposils, are removed from the mining area, and the underground area is properly filled with rock materials.  
To facilitate investment decisions, feasibility studies are performed by considering the technical, economic, and environmental aspects of mine development in the planning phase [10]. The scale and grade of mineral deposits are estimated using the results of computer-aided modeling. The appropriate mining method is selected, and the open-pit boundary is optimized to quantify the volume and amount of ore and waste. Additionally, the mine infrastructure is designed, and potential conflicts are identified to prevent political, legal, and environmental problems. Finally, ore resources and reserves, which refer to the amount and grade of the minable ore body, can be determined.  
When the mine development plan is approved, an open-pit or underground mine is constructed, and haulage roads, benches, and processing plants are built in the mining area. Various optimization techniques and decision-making systems are applied to optimize the mineral production and haulage operations. Furthermore, wireless communication systems can play a major role in tracking personnel and equipment and in monitoring the working environment from a remote office. Various management systems related to the underground ventilation network, safety management, and drainage system can be implemented to prevent disasters caused by noxious gases, dust, fires, or water; they can also alert workers about the need to escape, if necessary.  
The environmental impacts on the mining area should be monitored and controlled in both the mine operation and reclamation phases [11]. In the mine operation phase, dust, noise, and vibration mainly occurred as a result of drilling and blasting activities. Moreover, slope failure and erosion problems are a frequent occurrence in mining sites. After the mining operation, various mining-induced hazards, including subsidence, water pollution, soil contamination, and deforestation, can occur in mining areas [12]. Therefore, it is crucial to continuously monitor the movement of drainage flows, metal leaching, and sediments, and establish a database framework for effective hazard management. Furthermore, systematic mine rehabilitation planning may prevent and minimize risks to the mining environment and human health.
## 5 Influence of Major Factors on the Performance of Building Settlement Prediction  
The influence of the main factors on the effectiveness of building settlement prediction is discussed below, using the monitoring data of the enclosure construction condition as an example. These factors mainly include the soil layer parameters, monitoring point location, activation function, hyperparameters, and number of input points.
# Additive Manufacturing of Variable Density Lenses for Radio Frequency Communications in X-Band
## 4 Prototype Manufacturing  
### Additive Manufacturing  
The assembly of the horn antenna, the lens, and the support was additively manufactured. Different materials and technologies were used for each piece, depending on their characteristics.  
The designed RF feeding element, the X-band conical horn antenna, was manufactured using Vat Photopolymerization technology with curing by exposure to an ultraviolet laser beam with acrylic resin (VPP) with the printer Form 3 BL of Formlabs; resin Rigid10K was used, suitable for precise and rigid prints. The piece then underwent the process of sandblasting and metallization; the manufactured part is presented in Figure 10a, before metallization, and (b), after the metallization process.  
The three realizations of the lenses were manufactured with different materials, depending on their required dielectric constants provided by adjoint method optimization. Lens A was fabricated using Composite X resin due to its higher dielectric permittivity variation. Lens B was manufactured using Dental resin, selected for its dielectric constant, which is compatible with the design requirements, as well as its lower density compared to other acrylic-based resins. For the same reasons, Lens C was manufactured using Rigid 10K resin. All of them were printed using Vat Photopolymerization technology, with curing by exposure to an ultraviolet laser beam with acrylic resin (VPP). All of the prototypes are presented in Figure 9.  
Regarding the support, it was manufactured using two different powder materials: PA11, printed with Stratasys SAF 350 equipment, and UPP, printed with HP Multi Jet Fusion 5200 3D. These materials were chosen for their lightness, low permittivity, and good mechanical performance. In both cases, their mechanical and electromagnetic performances were similar. The assemblies using both PA11 and UPP mechanical support are presented in Figure 10c.
## 5 Numerical Results and Discussion
### Synchronous Networks
#### 5.2.2 Dual-Slot Networks  
For the dual-slot synchronous ISAL networks, as shown in Figure 10, we give the sensing SPEB of the step-by-step and the integrated schemes in the four networks with different topologies in Figure 8.  
Figure 10: SPEB comparison between the step-by-stepscheme and the integrated scheme in four dual-slot synchronous networks. (**a**) SPEB comparison in a dual-slot synchronous network (Figure 8a). (**b**) SPEB comparison in a dual-slot synchronous network (Figure 8b). (**c**) SPEB comparison in a dual-slot synchronous network (Figure 8c). (**d**) SPEB comparison in a dual-slot synchronous network (Figure 8d).  
According to Figure 10, we can draw the following conclusions. When the topologies of the partial networks used for target sensing in the two slots are similar, such as the topologies shown in Figure 8a,d, the energy allocation between the two time slots tends to be equal, as shown in Figure 10a,d. When there is a significant difference in the topologies of the partial networks used for target sensing in the two time slots, as shown in Figure 8b,c, more energy is allocated to the time slot corresponding to the sensing-resource-limited network, as shown in Figure 10b,c.
## 6 Experimental Results
### Conclusions on Performance Evaluation  
Table 2 presents time consumption and memory usage for each attack, respectively, for BMC algorithm and satisfiability testing. The table does not include protocols free of considered types of attacks.  
We have found the final results promising and would like to apply our approach further to validate more complex TSPs. Additionally, we aim to expand upon the algorithm presented in [34], which currently only considers a single lifetime value and does not account for system delays or the identification of time dependencies for when attacks occur. We plan to compare both approaches to assess their effectiveness.  
The experiments presented above demonstrate the outstanding scalability of the method, which is most evident when analysing memory usage and runtime results for the MobInfoSec protocol, the most complex protocol tested in these experiments. The scalability and efficiency of our method result from the fact that, unlike other approaches to time-based system verification, we do not model the entire protocol. Instead, we focus on modelling the executions of security protocols. This approach reduces the model size, allowing for faster identification of states in which an intruder may attack the protocol. The computational complexity of BMC using SMT for temporal interpreted systems is exponential concerning the bound k. It depends on the complexity of the theories used in SMT.  
It is known that the SMT problem is NP-hard since Boolean satisfiability is already NP-complete; moreover, the BMC-based verification process needs exponential time. However, the final stage of verification, which involves using an SMT solver, can often yield surprising results. Research indicates [59] that the choice of SMT solver also plays a significant role. It may be beneficial to experiment with various SMT solvers and select the one best suited to  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Protocol**} & \multicolumn{2}{c}{**BMC**} & \multicolumn{2}{c}{**SMT**} & \multirow{2}{*}{**Type of the Attack**} \\ \cline{2-2} \cline{4-6}  & **[s]** & **[MB]** & **[s]** & **[MB]** & \\ \hline NSPKT & 0.48 & 2.43 & 0.90 & 24.28 & MitM \\ \hline NSPKT & 0.49 & 1.61 & 2.40 & 30.80 & [PERSON]’s attack \\ \hline NSPKT\({}_{L}\) & 0.49 & 2.43 & 2.38 & 26.11 & MitM \\ \hline Denning-Sacco Protocol & 0.28 & 2.57 & 0.40 & 23.38 & MitM \\ \hline Woo Lam Pi Protocol & 0.40 & 2.54 & 0.70 & 29.11 & MitM \\ \hline Woo Lam Pi Protocol 1 & 0.54 & 2.61 & 1.26 & 32.54 & MitM \\ \hline Woo Lam Pi Protocol 3 & 0.54 & 2.61 & 1.44 & 32.19 & MitM \\ \hline Andrew Protocol & 1.80 & 2.69 & 12.90 & 48.93 & MitM 1 \\ \hline Andrew\({}_{L}\) Protocol & 0.98 & 2.75 & 3.15 & 40.44 & MitM \\ \hline MobInfoSec & 40.67 & 16.49 & 199.01 & 384.17 & MitM \\ \hline \hline \end{tabular}
\end{table}
Table 2: Sample experimental results for the protocols with the attacks.  
the specific problem, as the differences in runtime and memory usage can be substantial and depend on the solver's heuristics.
## 4 Applications of Multimodal Learning for Fault Detection Diagnosis
### Applications in Automotive Systems
#### 4.3.4 Integrating Multiple Data Sources for Automotive Fault Detection  
Combining data from various vehicle subsystems such as the engine, brakes, battery, and ADAS sensors creates a more comprehensive and accurate fault detection framework. This multimodal approach improves the vehicle's ability to detect faults early and ensures safe operation (See Table 3).  
However, integrating diverse data streams presents challenges as well. Differences in data format, frequency, and completeness can introduce inconsistencies. Preprocessing techniques such as normalization, interpolation, and outlier removal are essential to guarantee high-quality inputs for diagnostic models [78]. The use of integrated sensor data and advanced machine learning techniques in automotive systems especially for autonomous vehicles (AVs) and electric vehicles (EVs) enables accurate and proactive fault detection. These systems enhance vehicle safety, reduce maintenance costs, and contribute to a more reliable and enjoyable driving experience. Continued development in hybrid and multimodal learning techniques promises even greater capabilities in the future.
# Roasting Extraction of Lithium from Fly Ash: A Study of Influential Parameters and Mechanisms
## 3 Results and Discussion
### Roasting Effects  
#### 3.2.1 Sodium Carbonate Addition Ratio  
This study examined the leaching performance of the roasted products by mass R\({}_{\rm fs}\) during the roasting process. The results are shown in Figure 3. The roasting duration was set at 2.5 h, with a peak temperature of 850 \({}^{\circ}\)C. The leaching was conducted with a NaOH concentration of 4 mol/L, a solid-to-liquid ratio of 1 g:30 mL, a leaching temperature of 80 \({}^{\circ}\)C, and a leaching duration of 120 min. The R\({}_{\rm fs}\) was increased from 1:1 to 1:4. The leaching rate increased with the sodium carbonate addition ratio. The steepest increase occurred between 1:1 and 1:2, while the efficiency plateaued as the R\({}_{\rm fs}\) exceeded 1:2. At a R\({}_{\rm fs}\) of 1:4, the highest leaching rate of 89.32% was achieved, which was only 4.6% higher than that at a R\({}_{\rm fs}\) of 1:2 (84.72%). The main reason for the increase may be attributed to a complete reaction between the fly ash and sodium carbonate as the addition ratio increased. However, when the addition ratio exceeds 1:3, the contact between sodium carbonate and  
Figure 2: (**a**) EDX stratified images of raw fly ash and (**b**–**g**) EDX stratified images of each element.  
fly ash had been sufficiently uniform, and further addition of sodium carbonate no longer significantly enhanced the reaction. Considering the cost of sodium carbonate, the optimal R\({}_{\rm fs}\) of 1:2 was selected.
## 5 Discussion
### Ethical Considerations
#### 5.4.3 Misuse and Misinterpretation  
To minimize the risk of misuse, we provide clear documentation on the intended applications and limitations of our emotion detection models. The models were developed for research purposes in NLP and were not designed for applications involving surveillance or high-stakes decision-making. Additionally, we emphasize the importance of human oversight when deploying these models in real-world scenarios to prevent misinterpretation of emotional signals and unintended consequences.