esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Difference Between LCA of Buildings and LCA of Neighborhoods  
### LCA of Buildings  
The research of LCA at the individual building scale involves analyzing the components of a building without considering its interaction with the surrounding built environment [1].  
Several reviews [5; 8; 13; 16] have categorized LCA studies based on their analytical scale. Some studies have focused on the environmental impacts of different building materials [9; 17], while others have examined the differences among renovation, demolition, and the potential of recycling [18; 19; 20; 21]. Additionally, many articles and case studies have concentrated on a life cycle energy analysis (LCEA) and the assessment of carbon dioxide emissions [22; 23; 24; 25]. LCEA studies are crucial as they assess the energy consumption impacts within a building, including operational and embodied energy. Carbon dioxide assessment studies focus on the greenhouse gas emissions of the building, aiding in evaluating its carbon footprint. Other information gathered from LCA studies includes building morphology differences, energy characteristics (passive or active heating and cooling systems, the integration of renewable energy, etc.), and social impacts, such as user behavior [26].  
The ongoing efforts by researchers and designers to minimize the environmental impacts of buildings and the construction sector have been successful, particularly in terms of improving the energy efficiency of buildings, leading to High Energy Performance Buildings (HEPs). This progress is evident in the evolution from constructing low-energy buildings to passive buildings, zero-energy buildings (ZEBs), and eventually positive energy buildings (PEBs). Additionally, there is continuous research on autonomous buildings, which are not connected to an energy distribution grid [27]. A previous study by [28] focused on the LCA of a smart building, the ESTP Campus building. This study will focus on the LCA of neighborhoods, as described in the following section.
## 4 Studied Settings  
### Simulation Models  
In our simulation study, we examine six distinct sinusoidal time series models, allowing for a detailed analysis of their behaviors under a consistent upward trend (\(\beta\) = 0.75). The model settings are as follows:  
* Model 1: Constant amplitude with trend, using a fixed amplitude of 5 units, representing a stable cyclic pattern.
* Model 2: Varying amplitude with trend, starting with an amplitude of 3 units, increasing linearly by 0.05 units per month, simulating intensifying seasonal effects.
* Model 3: Mixed frequency with trend, combining a primary cycle amplitude of 5 units with a secondary cycle amplitude of 3 units, capturing overlapping periodic patterns.
* Model 4: Phase shift with trend, initially set to zero for simplicity, but adaptable to simulate shifts in periodic events.
* Model 5: Nonlinear modulation with trend, incorporating a modulation depth of 0.5 to reflect additional cyclical influences.
* Model 6: Noise variability with trend, using a fixed amplitude of 5 units with stochastic noise modulation, modeling fluctuations in predictability over time.  
Across all models, the angular frequency is set to \(2\pi/12\) to reflect a yearly cycle in monthly measurements. The mean level remains at 10 units, ensuring a standardized basis for comparison.
# Network Defense Strategy Selection with Reinforcement Learning and Pareto Optimization
## 1 Introduction
There has been a growing body of research towards game-theoretic approach on network security problems [24]. [PERSON] et al. [26] and [PERSON] et al. [4] have conducted comprehensive surveys of the field showing that game theory serves as an excellent tool for modeling security in computer networks, since securing a computer network involves an administrator trying to defend the network while an attacker tries to harm the network. [PERSON] categorized game-theoretic network security models into six groups [26]. They are (1) the perfect information game--all the players are aware of the events that have already taken place; (2) the complete information game--all the players know the strategies and payoffs of the other players; (3) the Bayesian game--where strategies and payoffs of others are unknown and Bayesian probability is used to predict them; (4) the static game--a one-shot game where all of the players play at once; (5) the dynamic game--a game with more than one stage in which players consider the subsequent stages; and (6) the stochastic game--games involving a probabilistic transition of stages. [PERSON] [27] has proposed a stochastic approach to study vulnerabilities and system's security and dependability in certain environments. The model provides real-time assessment. Unlike our model the proposed model is more inclined toward security risk assessment, dependability, and trustworthiness of the system. In addition to that, their model assumes vulnerabilities are unknown, whereas in our work the possible attack and defense scenarios are known to both agents. [PERSON] et al. [28] analyzed interaction between attacking and defending nodes in ad-hoc wireless networks using a Bayesian game to approach. The proposed hybrid Bayesian-approach Intrusion Detection System (IDS) saves significant energy while reducing the damage inflicted by the attacker. In this model, the stage games are considered Bayesian static since the defender's belief update requires constant observation of the attacker's action at each stage. [PERSON] et al. [29] have proposed a similar model that uses collaborative method for IDS. The dynamic nature of this multi-stage game is similar to our model. In contrast to their model, we analyze the best defense strategy for a defender in heterogeneous network. In this paper, we study the behavior of an agent (defender) who tries to maximize three goals: the cost difference, the number of uncompromised data nodes, and network availability. The agents iteratively play the game and stage transition uses a probability function. Thus, in this article, we focus on stochastic game with multiple objectives. In multi-objective mathematical programming there is no single optimal solutions [30]. Since all objective functions are simultaneously optimized, the decision maker searches for the most preferable solution, instead of the most optimal solution [31].
# A Novel Low-Complexity and Parallel Algorithm for DCT IV Transform and Its GPU Implementation
## 4 Implementation  
The implementation of the mathematical relation, previously presented, will be shown in this section of this study, starting with a brief description of the development boards used in all tests together with the analysis carried out in this study, followed by a general overview of CUDA cores placed on these development boards.  
We choose to present the performance of the algorithm on two different Nvidia CUDA architectures so that the reader can have a clear and global picture of its performance compared to the classical implementation of the DCT algorithm. The increase in performance obtained with the new parallel algorithm presented in this study depends on the architecture on which it will run. The architectures on which we will analyze the performances of the parallel algorithm are Volta and Ampere.
## 2 The Development of Typical Rotating Motion Mechanisms
### Linkage Mechanism
#### Four-Bar Linkage
Figure 45: A neutral and stable four-bar linkage mechanism (orange schematic) consists of a rigid linkage (black) and a helical shell joint (grey). These joints are preloaded to move within a constant torque range. At the bottom, top views of some equilibrium positions are displayed. The crank rocker mechanism has a simple structure, high reliability, and strong load capacity. It is widely used in internal combustion engines, stamping machines, and biomimetic machinery through the conversion of rotation and swing. However, its motion is discontinuous, high speed vibration is prone to occur, and it occupies a large amount of space, which limits its application in high precision and high speed scenarios. The hyperbolic handle mechanism (hyperbolic handle mechanism) can achieve full rotation of the hyperbolic handle, with constant input speed and variable output speed, suitable for bidirectional rotation or variable speed transmission scenarios. However, the speed fluctuation of the driven shaft is significant, and the stability is limited. The elastic inner connecting rod achieves high stiffness, an extensive range of motion, and a low driving force through a spiral shell preloading design, which is suitable for precision instruments and flexible joints, but its performance depends on the preloading optimisation of the snail shell structure; The double spherical 6R linkage mechanism is based on super constraint design, with multiple degrees of freedom and deformation capability, strong scalability, and suitability for biomimetic structures and robotic arms, but the high complexity of design and manufacturing raises costs. Overall, various linkage mechanisms complement each other in simple transmission, variable speed requirements, precision control, and spatial deformation and require comprehensive selection based on motion characteristics, load conditions, and costs. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Types** & **Advantages** & **Disadvantages** & **Applications** \\ \hline Crank-rocker mechanism & Simple structure, high reliability, strong load capacity & High speed is prone to vibration and occupies ample space & Internal combustion engine, stamping press, biomimetic machinery \\ Hyperbolic handle mechanism [103; 104] & Full rotation, uniform input, variable output & The speed of the driven crankshaft is unstable & Scenarios of bidirectional rotation or variable speed transmission \\ Elastic inside link [105] & High stiffness, wide range of motion, and low driving force & Dependency on the preloading design of the snail shell & Precision instruments, flexible joints \\ Double spherical 6R linkage [106] & Deformable, with multiple degrees of freedom & High design complexity and manufacturing cost & Expandable structure, biomimetic structure, robotic arm \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Comparison of different types of linkage mechanisms. Figure 46: Double spherical 6R connecting rod.
# An Efficient On-Chip Data Storage and Exchange Engine for Spaceborne SAR System
## 2 Analysis of Storage and Exchange Efficiency for SAR Data
### Analysis of Existing Data Exchange Solutions  
The newer data exchange methods in spaceborne SAR imaging systems are currently studied as matrix block three-dimensional cross-mapping. This method allows for an efficient balance between the range and azimuth data access and is pipelined with two off-chip DDR3s to improve efficiency. This method has a data write bandwidth of 8.45 GB/s and a data read bandwidth of 10.24 GB/s. Therefore, the data access bandwidth of the method is still limited. A brief analysis of the key technologies in this method is presented below.
# A Wireless EEG System for Neurofeedback Training
## 4 Materials and Methods
### NF-EEG Brain Locations  
The 40-channel EEG placement was according to the standard 10-20 and 10-10 systems [31, 32] and separated sensors for the ground, sensors placed on the forehead, and reference sensors in both mastoid processes (Table 3 and Figure 4). The stretch cap held the 40 embedded sensors that were prepositioned in the international montages, which minimized electrode placement errors through measurements (10% and 20% as well as 10% and 5%) of the distances between the skull landmarks along the midline from the nasion (Nz) to the inion (Iz) and from the left to the right pre-auricular points (A1 and A2, respectively) correctly aligned in the horizontal and vertical planes with placement Cz. The EEG sensors (10-20: Fz, Cz, Pz, O1-O2, and Oz; 10-10: FT9-FT10, TP7-TP8, PO7-PO8) for \begin{table}
\begin{tabular}{c c c} \hline \hline
**Characteristics** & **Spring-Loaded Sensors** & **Foam Sensors** \\ \hline Impedance & 200–500 K\(\Omega\) & 200–500 K\(\Omega\) \\ Size (mm) & \(15\times 15\times 14\) & \(15\times 15\times 14\) \\ Weight & 1.8 g & 0.8 g \\ Position & Hairy area & No hair area \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Specifications of the dry sensors in the wireless EEG acquisition system. Figure 3: The dry sensors used in the system: (**A**) a spring-loaded sensor and (**B**) a foam sensor applied as the ground and reference electrodes with a clip on each earlobe. The easy-to-handle dry electrodes can be quite helpful in fostering the practical application of EEG in schools while minimizing variances related to measurement errors (e.g., crosstalk between electrodes due to excessive amounts of gel application). the NF experiment are underlined in Table 3. Their choice was according to the functional connectivity studies [6; 7] of the typically developed children. We hypothesized that qEEG z-NF may lead to a functional reorganization in DD children that consists of a reduced interhemispheric low-frequency theta band and an increased alpha band in the regions involved in the reading network in the temporal lobe, occipital cortex, and those which intervene in the articulation and gesticulation of words as frontal and precentral cortices.
# Two-Way Linear Probing Revisited
## 7 Conclusions  
In this research, we designed efficient open addressing hashing schemes that improve the worst-case performance of classical linear probing. We proposed two-way linear probing hashing schemes that use two independent linear probe sequences and accomplish \(\Theta(\log\log n)\) worst-case insertion and search times, w.h.p. The common idea of these schemes is the successful marriage between the two-way linear probing concept and the blocking technique where the hash table is partitioned into equal-sized blocks. Simulation and comparison results supported our theoretical analyses of all algorithms discussed in this research and illustrated that the worst-case and average performances of such schemes are practically plausible. Thus, we conclude that two-way linear probing hashing with blocking has several advantages over other proposed hashing methods as it reduces the worst-case behavior of hashing, it requires only two hash functions, it is easy to parallelize, it is pointer-free and easy to implement, and it does not require any rearrangement of keys or rehashing. Its maximum cluster size is \(O(\log\log n)\), and its average-case performance can be at most twice the classical linear probing as shown in the simulation results.  
Furthermore, we also showed that not every two-way linear probing algorithm has a good worst-case performance. We proved that, if the two-way linear probing algorithm always inserts any key upon arrival into the empty cell of its two initial cells whenever one of them is empty, then, w.h.p., a cluster of size \(\Omega(\log n)\) emerges in the hash table.  
Our results suggest that two-way linear probing may be a more promising open addressing hashing scheme than classical linear probing for many applications, including, e.g., mobile networks [94; 95].  
It would be interesting to extend the result of Theorem 10 to any constant load factor \(\alpha\in(0,1)\)--as is suggested by the simulation results--and to investigate its applications to other problems in computer science.  
Conceptualization and methodology, L.D. and E.M.; validation and formal analysis, K.D., L.D. and E.M.; writing--original draft preparation, E.M.; writing--review and editing, K.D. and L.D.; supervision and project administration, L.D. All authors have read and agreed to the published version of the manuscript.  
This research was funded by NSERC Grant A3456.  
The authors declare no conflicts of interest.
# Lightweight Transformer with Adaptive Rotational Convolutions for Aerial Object Detection
## 3 Proposed Methodology
### Pseudo-Label Guided Learning
#### 3.3.2 Rotation-Aware Adaptive Weighting (RAW) Loss  
Given that the pseudo-labels may contain noise, particularly in terms of the orientation of the predicted bounding boxes, we introduce the RAW Loss. The RAW Loss dynamically adjusts the impact of each pseudo-label based on the orientation difference between the teacher and student models. This ensures that pseudo-labels with more accurate orientations contribute more to the learning process. \(\theta_{T}\) and \(\theta_{S}\) are the orientations of the bounding box predicted by the teacher and student models, respectively. The orientation difference \(\Delta\theta\) is defined as:  
\[\Delta\theta= |\theta_{T}-\theta_{S}|, \tag{17}\]  
The RAW Loss introduces a modulating factor \(\omega_{rot}\) based on this orientation difference:  
\[\omega_{rot}(\Delta\theta)=(1+\alpha\cdot\frac{\Delta\theta}{\pi}), \tag{18}\]  
where \(\alpha\) is a hyperparameter that controls the sensitivity to orientation differences. The unsupervised loss \(\mathcal{L}_{u}\) is then weighted by \(\omega_{rot}\) :  
\[\mathcal{L}_{u}=\sum_{i=1}^{N_{p}}\omega_{rot}(\Delta\theta_{i})\cdot\mathcal{L }_{u}(\kappa_{i},\hat{y}_{i}), \tag{19}\]  
where \(N_{p}\) is the number of pseudo-labeled samples. This dynamic weighting mechanism allows the student model to focus more on pseudo-labels with accurate orientations, improving the robustness of the learning process.
# Remote Sensing of Snow Cover Using Spaceborne SAR: A Review
## 5 Discussion
### Overall Trajectory of Spaceborne SAR-Based SCE Detection and Future Possibilities
Finally, in the application aspect, as previous studies did not fully utilize the benefit that SAR can distinguish wet and dry SCE, but only regard the wet SCE as total SCE during snow melting season [140], the information of wet SCE which cannot be derived from conventional optical-based approach (can only detect total SCE) should be further utilized. Consequently, based on the trajectory and the recent developments of SAR sensors and snow detection algorithms, it can be expected that in the near future once the SAR-based SCE detection approach (1) achieves daily temporal resolution by fusing different SAR sensors' information (2) reaches satisfactory classification accuracy and global transferability as proved by [PERSON] et al. [143]; SAR-based monitoring approach would replace the conventional optical-sensor-based SCE detection approach as more snowpack information can be inferred (such as wet or dry and surface roughness) and can fundamentally solve the cloud coverage and polar darkness issues.
## 4 Empirical Propagation Models
### Close-in Model (CI)  
This path loss model is referenced as the Free Space Path Loss (\(FSPL\)) provided in the equation and parameterized by the model parameter \"\(n\)\", also known as the Path Loss Exponent (PLE) [41]. In this model, the PLE is modeled through MMSE [40], aiming to minimize the standard deviation (\(\sigma\)) between the Path Loss and the measured data. This model has been used for frequencies on the order of gigahertz (GHz), and it is based on the fundamental principles of propagation, linked to the Friis and Bullington formulas related to Free Space Path Loss (\(FSPL\)) [38]. While the FI model uses constants based on curve fitting, the CI model has the \(FSPL\) as a physical anchor, ensuring a fixed and continuous relationship between transmitted power and distance. Its equation is given in (5):  
\[PL^{CI}(f,d)=FSPL(f,d_{0})+10 nlog_{10}\left(\frac{d}{d_{0}}\right)+X_{\sigma} ^{CI} \tag{5}\]  
In which \(d\) is the distance between the antennas in meters, \(n\) is the path loss exponent, which typically has values less than 2 in indoor environments with line-of-sight, and \(X_{\sigma}\) represents large-scale shadowing. The \(FSPL(f,d_{0})\) is defined as follows:  
\[FSPL(f,d)=10 nlog_{10}\left(\frac{4\pi d_{0}}{\lambda}\right)^{2} \tag{6}\]where \(\lambda\) is the wavelength, and the distance \(d_{0}\) is equal to 1 m, as it is a reference adopted in various models capable of providing a standardized modeling approach.
## 3 Results and Discussion
### Effect of Heating Rate  
Tests of the effect of different heating rate tests were carried out; the results are shown in Figure 5. Since the crystallization water in scandium chloride is removed under the protection of inert gases flow, there are strict requirements on the heating speed. The purpose is to make the crystal water rapidly gasify while the water vapor is quickly taken away by the inert gas--and to minimize the probability of water vapor hydrolyzing with scandium chloride.  
When the heating rate was less than 12 \({}^{\circ}\)C/min, increasing the heating rate was conducive to reducing the hydrolysis rate of scandium. The rate of heating was 12 \({}^{\circ}\)C/min and the hydrolysis rate of scandium decreased to the minimum value of 1.86% and scandium content of 27.46% in anhydrous scandium chloride. When the heating rate increased to 16 \({}^{\circ}\)C/min, the hydrolysis rate of scandium increased to 2.34% instead. This was related to the factors such as the slow sublimation rate of the crystal water and the long action time of the water vapor and scandium chloride. Therefore, anhydrous scandium chloride with scandium content of 27.46% was produced and the hydrolysis rate of scandium was 1.86% under the condition used a heating rate of 12 \({}^{\circ}\)C/min.  
Figure 4: Effect of holding time on scandium content of anhydrous scandium chloride and hydrolysis rate of scandium.