esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Enabling Applications and Platforms for Cyber Physical Sensor Network
\begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{2}{c}{**WSN in a CPS Environment: Applications and Platforms**} \\ \hline \multirow{4}{*}{**Applications**} & \multicolumn{2}{c}{Physical Rehabilitation} \\  & Health Care & Telemedicine \\  & & Elder Assistance \\ \cline{2-3}  & \multirow{2}{*}{Security} & Transit Tracking \\  & & Emergency Navigation \\ \cline{2-3}  & \multirow{2}{*}{Social Networking} & Personal Interaction \\  & & Gaming & Grouping, Interaction \\ \cline{2-3}  & \multirow{2}{*}{Monitoring} & Traffic Lights \\  & & Parking \\  & & Route and Transit Planning \\ \hline \multirow{4}{*}{**Sensor Types**} & Pulse & ECG, EMG \\  & Movement & Accelerometer, Tilt Sensors \\  & \multirow{2}{*}{Imaging} & Video Camera \\  & & Light, Temperature Sensor \\  & Location & GPS, Compass, Magnetometer \\  & \multirow{2}{*}{Commodity} & Gas and Liquid Monitor \\  & Frequency & Ultrasonic’s \\ \hline \multirow{2}{*}{**Communication**} & Long Haul & GPRS, LTE, 3G, \\  & \multirow{2}{*}{**Platforms**} & Limited & Body Sensor Network \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Applications highlights of sensing plane in cyber physical sensor network.
# Design and Validation of a U-Net-Based Algorithm for Star Sensor Image Segmentation
## 3 Results
### BOSS Algorithm Tests  
In this section, examples of BOSS algorithm applications for stray light removal and ghost noise removal in night sky images are shown. The aim of a good segmentation in this case is to retrieve the point-like stars and streaks (RSOs) while removing background pixels that are often badly affected by several noise sources. By noise, we mean that part of the image signal that does not represent the target scene and must be filtered in a certain way. It corrupts the image actors, and if the ratio between the useful signal and noise is higher than but close enough to one, the useful signal could be filtered out as noise and lost for further processing. The image noise is due to several causes briefly divided into the following:  
Figure 5: Performance curves vs. \(p_{min}\) and models.  
Figure 6: Details of performance curves vs. \(p_{min}\) and models.  
* Inner noise: It is due to the sensor components, electronics and realization technique.
* External noise: It is due to planets, the Sun, the Moon, the Earth, hosting platform structures and camera baffle together with lenses non-uniform reflection.
## 1 Introduction
The most significant approaches for predicting wind speed include physical techniques like numerical weather forecasting (NWF), statistical techniques like the ARIMA model, intelligent models with artificial neural networks, and hybrid prediction models that combine multiple types of algorithms [20; 21]. While physical techniques are better at predicting wind speed over the long run, statistical and artificial intelligence models are useful at predicting wind speed in the short term. The majority of studies and wind speed forecasting techniques concentrate on very short-term forecasts. For turbine control applications, very short-term projections are relevant in the second range. As a result, the computational cost of models that will be employed in online applications is crucial. It has been claimed that multilayer perceptron (MLP) findings are more accurate when compared to wavelet-based networks and particle swarm optimization outcomes; however, this comes at a significant computational cost [22]. [PERSON] et al. [23] used fuzzy logic and an artificial neural network to forecast the wind speed. They pointed out that, in comparison to conventional models, the model offers a substantially smaller rule base and a greater level of anticipated wind speed accuracy. The experimental findings demonstrate the improved wind speed prediction and faster computation times of the suggested model. [PERSON] et al. [24] extracted the most energy possible from variable-speed wind power generation systems using an adaptive Takagi-Sugeno-Kang (TSK) fuzzy model. An integrated control approach was presented by [PERSON] et al. [25] for a wind farm to lessen frequency variations in a small power system. The least squares method was used to forecast the short-term forward wind speed in order to adjust the wind farm's output power command in response to the changing wind speed. The output power command of the wind farm is multiplied by the projected wind speed using fuzzy reasoning. The model was validated by the researchers using numerical simulations. ANFIS was utilized by [PERSON] et al. [26] for the wind speed profile and by [PERSON] et al. [27] for the prediction of wind power. The objectives of the present study were to determine the most suitable model by estimating the wind power with artificial neural networks and fuzzy logic methods using the wind speed values of the Velimese region. In order to predict the wind power, it was examined which of the different activation functions applied with different numbers of neurons in ANN gave better results. With the ANFIS method, tests were carried out using different membership functions, and it was investigated in which function the best predictive values were reached. It was examined how close the results obtained from these models were to the real values.
# Current Progress in Femtosecond Laser Ablation/Ionisation Time-of-Flight Mass Spectrometry
## 3 LIMS System: fs-Laser Ablation Ion Source and Time-of-Flight Mass Analyser
### Femtosecond Laser Radiation
#### 3.1.2 Generation of fs-Laser Radiation with Shorter Wavelength  
Higher harmonics of the output frequency can be obtained by using nonlinear quadratic crystals such as BBO (\(\beta\)-barium borate), LBO (lithium triborate), or KTP (KTiOPO\({}_{4}\)) [109; 110]. In a crystal medium, two incident fields at frequencies \(\omega_{1}\) and \(\omega_{2}\) can produce new radiation at \(\omega_{3}=\omega_{1}+\omega_{2}\) or \(\omega_{3}=\omega_{1}-\omega_{2}\). The output of the fs-laser can be used as a fundamental wave for second-harmonic generation, frequency mixing, and parametric amplification. The latter two methods are used to produce tunable infrared or visible fs-radiation (optical parametric generator, OPG, non-collinear optical parametric amplifier, NOPA) [111]. A simpler way to produce UV fs-radiation is by combining the output of the second-harmonic with the fundamental wave on a third-harmonic crystal (THG). The ideal crystal for this application must have a small group velocity difference between the fundamental and harmonic waves and a large nonlinearity and must exhibit no absorption at both the fundamental and the harmonic wavelengths. The crystal should also be transparent at twice the harmonic frequency to avoid two-photon absorption. A thin BBO crystal is typically used for the second-and third-harmonic generation and has 40-50% and up to 10% conversion efficiency, respectively [112; 113].
# Interface Design for Responsible Remote Driving: A Study on Technological Mediation
## 4 Interface Design Analysis
### Sight: Video Feedback
#### 4.1.3 Head-Mounted Displays for Virtual Reality  
Although interesting, the solutions considered so far do not seem to tackle the problem of detachment due to the feeling of an overly gamified experience. In this regard, one of the most innovative strategies to boost visual immersion is the adoption of Head-Mounted Displays (HMDs) for Virtual Reality (VR).  
Indeed, VR could offer a more immersive viewing experience by providing a 3D representation of vehicle surroundings with high degrees of precision, allowing operators to detect early signs of vehicle movements and anticipate road conditions with greater accuracy. Moreover, ROs' sense of presence would be enhanced, since HMDs would offer a wide FOV allowing them to look around as if they were physically sitting in the vehicle [46]. Offering ROs the possibility to exert some control on gaze direction might contribute to fostering safety and responsibility. A fixed viewpoint might hamper their ability to navigate effectively, especially during delicate maneuvers. In this sense, [41] explored the option of providing adjustable cameras but noted that they should be automatically returned to their original position after each shift; otherwise, ROs might become confused about their angle. Interestingly enough, then, amplifying remote vision by allowing gaze control in this way might lead to a reduction of spatial awareness due to its characteristic lack of embodiment. Precisely because of the sense of embodiment they mediate, HMDs would arguably help manage this last shortcoming.  
Research on HMDs for RD is still in its infancy, so that more studies are required to obtain a better picture of its technical feasibility, cost effectiveness, and actual impacts on driving performances. Currently, the evidence is mixed. For example, [48; 49] suggested that while HMDs do offer enhanced immersion, they may not necessarily lead to improved driving performance. Moreover, overreliance on visual feedback seems to characterize this strategy as well, so that related reductions might not find adequate countermeasures without posing risks of cognitive overload. In addition, the reduction of other sensory channels is so significant with HDM and VR that motion sickness and nausea might arise from the uncanny perception of disassociations between visual motion and vestibular inputs. Therefore, let us now consider other sensory feedback interfaces that might help cope with the reductions proper of visual HMIs.
# An Efficient Routing Protocol for Quantum Key Distribution Networks
## 2 The Proposed QOLSR Protocol
### The Proposed QOLSR Protocol
#### 2.3.2 Efficient Path Optimization for QKD Networks
Let \(Max_{(u,v)}\) represent the maximum threshold of the key pool on edge \((u,v)\) and \(\gamma_{(u,v)}(i)\) represent the quantum secure key recovery capability of edge \((u,v)\) at time \(i\). The formula to calculate \(\gamma_{(u,v)}(i)\) is:  
\[\gamma_{(u,v)}(i)=\frac{C_{(u,v)}-\sum\limits_{s\in V^{\prime},t \in V^{\prime}}\left(\omega_{(u,v)}^{s,t}(i)\cdot\kappa\right)}{Max_{(u,v)}- Cur_{(u,v)}(i)}. \tag{2}\]  
In addition, for a path that contains multiple links in the QKD network, the priority of the path can be expressed by the minimum value of the priority of all the links it contains. The formula is:  
\[\gamma_{path}(i)=\min\limits_{(u,v)\in path}\frac{C_{(u,v)}- \sum\limits_{s\in V^{\prime},t\in V^{\prime}}\left(\omega_{(u,v)}^{s,t}(i) \cdot\kappa\right)}{Max_{(u,v)}-Cur_{(u,v)}(i)}. \tag{3}\]  
Path optimization based on the quantum secure key recovery capability has a higher level of stability and is also good at coping with the link-state frequency changes in QKD networks. Therefore, quantum secure key utilization can be enhanced by selecting the optimal path.
## 2 Materials and Methods
### Antioxidant Activity  
The antioxidant activity was evaluated using two radicals (DPPH' and ABTS\({}^{+}\)) and a ferric-reducing ability (FRAP) assay. For the DPPH free radical scavenging ability, 100 uL of extract was combined with 100 uL of DPPH solution and then incubated in the dark for 30 min before the absorbance was measured at 517 nm. For the ABTS\({}^{+}\) radical scavenging ability, 160 uL of ABTS\({}^{+}\) solution, and 40 uL of extract were reacted in the dark for 6 min, after which the absorbance at 734 nm was measured. For the ferric-reducing ability, 30 uL of extract was mixed with 256 uL of FRAP reagent. This mixture was kept at room temperature for 30 min before the absorbance was measured at 593 nm. Vitamin E (VE) served as the positive control. The inhibitory concentration at 50% (IC\({}_{50}\)) reflected the antioxidant concentration of the tested samples needed to neutralize 50% of the initial concentration of free radicals.
# Coarsely Quantized Decoding and Construction of Polar Codes Using the Information Bottleneck Method
## 3 Polar Code Construction Using the Information Bottleneck Method
### Information Bottleneck vs. Tal and Vardy Construction
Lastly, the [PERSON] and Vardy method does not fully exploit the benefits of the discrete density evolution performed for code construction, i.e., the intermediate results could be used for decoding. The benefits of application of the information bottleneck method in polar codes go beyond the code construction. For each variable node \(v_{i,j}\), \(0\leq i<N\) and \(1\leq j\leq n\), in Figure 2, the distributions \(p(t_{ij}|\mathbf{y}_{i,j})\) and \(p(v_{ij}|t_{ij})\) are obtained. Here, \(\mathbf{y}_{i,j}\) represents the output of the virtual bit channel experienced by \(v_{i,j}\), and \(t_{ij}\) is the cluster index in which \(\mathbf{y}_{i,j}\) falls. With appropriate book keeping, we save all the hard work done during the discrete density evolution for computing these distributions and use them for coarsely quantized decoding as shown in the next section.
## 5 Results and Discussion
### Investigating Error Sources
#### 5.4.3 Model Generalisation  
The final potential error source was the quality of the 2.5D raster DSM, as the proposed methodology created this using 2D mapping and basic elevation information. The highest value of a building was chosen as the single elevation point. This was then applied to the entire 2D building polygon and in certain circumstances resulted in adding an area to each building's rooftop that did not exist. For example, in Figure 11c, the signal from one of the satellites has been flagged as 'obstructed' in theviewshed calculation by the LOD1 block used to create the LOD0 raster for the building on the right. A sloped roof, such as might be present in the same building represented at LOD2 on the left, would have allowed signals to reach the GNSS receiver. This is an unavoidable error source as this method is being proposed because it is an alternative to using high detail LOD2 or LOD3 models providing potential savings in terms of time and cost. However, the accuracy of the prediction around roof eaves or gable roofs will be reduced.
# Unravelling the Environmental Application of Biochar as Low-Cost Biosorbent: A Review
## 5 Limitation of Biochar Application  
In the production of biochar by thermochemical technologies the reduction in the waste volume is also possible, as well as the complete destruction of pathogens and parasites, immobilizing metalsand producing value-added bio-energy. However, the presence of impurities, mainly heavy metals, which are part of the wastes used as feedstock, may be a risk due to the heavy metals leaching during biochar application. Recently, a few papers have reported the behavior of heavy metals during the pyrolysis process, focusing on their distribution and mobility in the biochar [115]. [PERSON] et al. [116] studied the transformation behaviors of heavy metals in animal manure during pyrolysis at 300-700 \({}^{\circ}\)C. The results indicate that the characteristics of biochars (>500 \({}^{\circ}\)C) were relatively stable. Under this condition, the total percentages decreased from 16.98% to 9.43% for Cr, 85.60% to 65.55% for Mn, 57.26% to 10.61% for Cu, and 37.90% to 13.78% for Zn, respectively, determining that the bioavailability and toxicity of Cr, Mn, Cu and Zn in pig manure biochar were greatly reduced and the potential ecological risk index values significantly decreased after pyrolysis. Additionally, to reduce their possible adverse effects, one solution is the mixture of different kinds of biomass. Thus, co-pyrolysis of animal manure and biomass with lower heavy metals contents may lead to a decrease in the heavy metal contents in the obtained biochar compared to the single manure pyrolysis [117; 118]. By co-pyrolisis, it is possible to convert the more toxic heavy metals into stable fractions with a significant reduction in their bioavailability in biochar [119]. [PERSON] et al. [117] reported a minimal effect on the mobility of different heavy metals in biochar by the co-pyrolysis process of a mixture of sewage sludge with rice straw or sawdust at 50% mixture ratio. Similarly, [PERSON] et al. [120] detected the transformation of unstable metals into more stable fractions at a 50% mixture ratio of bamboo sawdust and sludge pyrolysis. Hence, the resultant biochars and their chemical composition depend on the kind of feedstock used and the controlling rate of pyrolysis temperature or the use of a mixture of feedstocks [121].
# Utilizing Mask R-CNN for Solid-Volume Food Instance Segmentation and Calorie Estimation
## 5 Experimental Results
### Comparison with the Other Algorithm  
The performance of the calorie estimation method with Mask R-CNN is evaluated by comparing its results with the results estimated by Faster R-CNN, as shown in Figure 11. The same test image is used for comparison, in order to minimize the effect of the parametric uncertainty. Five pieces of Gimbap are recognized as Gimbap1, and the calories are 113.3 kcal. Normally, the calories of five pieces of Gimbap are in the range of 175 kcal to 200 kcal. The calorie estimation result is much less than normal. After object detection using Faster R-CNN, only bounding box information is obtained, but no mask information. The unseen food shape cannot be considered. For the Gimbap1 label, based on Figure 7, there are two cases: (1) Gimbap is cut into pieces. The mask of the Gimbap is round. (2) Gimbap is cut into pieces and placed obliquely. The mask of the Gimbap is a rectangle. Since there is no mask information, it is hard to choose the right case. Therefore, the estimation result is wrong. In Figure 10(b2), the calorie estimation result is 194.57 kcal. It considered the unseen food and uses Mask R-CNN instance segmentation results to estimate the food's calories. Therefore, the result satisfied the standard.  
Figure 10: Calorie estimation results of test samples: (**a1**–**a3**) original images including Gimbap, (**b**) instance segmentation images. (**b1**) The Gimbap calorie of each detection is shown in the picture. The total calorie is 282.38 kcal. (**b2**), five pieces of Gimbap are recognized together as Gimbap1, and the calorie is 194.57 kcal. The calorie of the other two pieces of Gimbap is 35.07 kcal and 40.35 kcal, separately. The total calorie is 269.99 kcal. (**b3**), the calorie of the Gimbap is 390.84 kcal.
## 4 Discussion
### Comparison with Other RHEAs  
To understand the protection level, which was provided by CoO, we compared the mass gain values obtained after 1 h of oxidation at 1000 \({}^{\circ}\)C for the (HfCo)\({}_{90}\)(NbMo)\({}_{10}\) alloy and other RHEAs [9; 18; 19; 21; 23; 24; 31; 56; 57; 58; 59; 60] (Figure 6). This period of time was chosen to minimize the evaporation effects that accounted for misleading values of the mass gain and to cover a higher number of the alloys available in the literature. We found that the CoO-forming (HfCo)\({}_{90}\)(NbMo)\({}_{10}\) alloy showing 7.1 mg/cm\({}^{2}\) could not compete with RHEAs, the oxidation resistance of which relied on the rutile-type CrTaO\({}_{4}\), gaining only 0.2 mg/cm\({}^{2}\)[56]. Meantime, the (HfCo)\({}_{90}\)(NbMo)\({}_{10}\) alloy appeared to be more oxidation-resistant compared to RHEAs protected by another rutile-type CrNbO\({}_{4}\)[17] or AlTaO\({}_{4}\)[59] scales, or by layers composed of discontinuous complex (AlNbO\({}_{4}\), Ti\({}_{2}\)ZrO\({}_{6}\)) and simple (Al\({}_{2}\)O\({}_{3}\), Cr\({}_{2}\)O\({}_{3}\), ZrO\({}_{2}\), TiO\({}_{2}\)) oxides [23; 60] (Figure 6).  
The (HfCo)\({}_{90}\)(NbMo)\({}_{10}\) alloy also showed a better oxidation resistance compared to a commercial Nb alloy C103 [1], which is used only in a coated state in aerospace propulsion systems as thrust cones and high-temperature valves or in turbine engines as thrust augmenter flaps. Bearing in mind the promising mechanical properties [36], which can be improved by a proper heat treatment [40], excellent phase stability [40], and acceptable oxidation/spallation resistance in an uncoated state that provides some protectiveness in the case of coating failure, the (HfCo)\({}_{90}\)(NbMo)\({}_{10}\) alloy examined in the present work appears to be a potential candidate for high-temperature applications, for instance, as turbine blades, nozzles, and/or thrust augmenter flaps.
## 5 BACS Improvement Scenarios
### Energy Efficiency Improvements Package
#### 5.3.1 Case A  
Focusing on energy efficiency, it can be noted from the base case BACS assessment that the technical domains of heating, domestic hot water, cooling, lighting, and dynamic envelope all score relatively low (less than 40%) against energy efficiency compared to the rest of the domains. Because of the constraints, no changes are made to storage of domestic hot water or the dynamic envelope. Implementing changes with the goal of increasing the energy efficiency has led to the results in terms of points for each domain presented in Figure 12a. This is a very deep retrofit of the functionalities of the BACS aiming to enhance the level of energy efficiency in general. The mentioned upgrades for case A resulted in an increase in the energy efficiency of 50 points, while also increasing by 4 points in maintenance and fault prediction, 10 points in storage and 18 points in information to occupants. Given the estimation that 10 points increase in energy efficiency score would lead to 5% reduction in energy consumption, the resulting reduction in energy consumption for Case A would be around 25%. With the building's annual total energy consumption from the energy label report being approximately 440 MWh, this reduction corresponds to 110 MWh. Assuming an average electricity price of 1.60 DKK/kWh and a heating price of 550 DKK/MWh, it would be possible to achieve annual economic savings of approximately 10.45 k EUR.