esa-sceva/satcom-chunk-collection huggingface dataset:
# An Accurate Probabilistic Model for TVWS Identification
## 5 Experimental Results and Discussion
### Data Characteristics
These curves have enough information to reveal the behaviour of the spectrum. Figure 13: Each Panel contains a plot of the pdf of the signals sensed, from (**a**–**j**) pdf of the \(W(f)\) and \(X(f)\) taken in Points 1–10. It is important to note that each reading provides valuable information to determine the state of the spectrum in that specific location at an instant of time \(t_{i}\). To obtain a global view of the proposed method and its applicability, it is necessary to compare all the obtained curves together to find a usable relationship, if any. Figure 15a plots the ROC curves (\(P_{fa}\) vs \(P_{d}\)) of the ten analyzed locations. It is quite clear that each location has its own characteristics which differ from others. Figure 15b depicts the same ROC curves shown in Figure 15a but focusing on a \(P_{fa}\) a range of 0% to 4%. Additionally, the dotted vertical lines represent the adaptive \(T\) in red, the \(T\) obtained with a \(M=5\) dBm in blue, \(M=7\) dBm in green, and \(M=10\) dBm in brown, respectively. The Y-coordinate value of the intersection of a particular \(T\) and the ROC curve of a location represents \(P_{d}\). For example in P3, for a \(P_{fa}\) of 3%, it corresponds to a 48.4% of \(P_{d}\) according to the vertical-axis scale of the ROC plot, and it means a 96.8% of the \(P_{dmax}\). Figure 14: ROC that represents the relation of \(P_{fa}\) vs. \(P_{d}\). Panels (**a-j**) ROC curves of the signal sensed in Points 1 to 10. To visualize the accuracy of the model that proposes an adaptive \(T\), the curve of the \(P_{fa}\) vs \(P_{d}\) is obtained by calculating the average of 36,176 readings or 4,051,712 samples. By using Equations (5), (9), (15), and (16), the \(P_{famax}\) is obtained and it corresponds to 4%. Figure 16 illustrates the average curve, the \(P_{famax}\), the adaptive \(T\), and the values for \(T\) using a margin \(M\) of 5, 7, and 10 dB. Considering that \(P_{famax}\) defines the \(P_{dmax}\) which becomes 99.999% of the signals that are possible to be detected, then the values of the Y-axis were re-calculated according to the new \(P_{dmax}\) scale. In gray color it can be observed the recommended operation area, defined by the \(P_{famax}\), \(P_{famax}\), \(P_{dmax}\), and \(P_{dmin}\), and on the left side of the plot, are the new re-calculated values for \(P_{d}\).
## 2 Method  
The process of the proposed method to extract buildings from PolSAR images is described in this section. The main steps are shown in Figure 1. Firstly, we extract the PauliRGB three-channel data, which can characterize the polarization information of the PolSAR data. The G\({}^{0}\) statistical texture parameter that can characterize the statistical information of PolSAR is also extracted. They are then combined into a feature set, and samples are collected and selected as input to the convolutional neural network for training. Subsequently, the preliminary result of polarimetric SAR buildings is obtained. For misclassification problems in the initial extracted building, superpixel constraints are applied to the preliminary results to reduce them. After obtaining the superpixel area and the preliminary extraction area of the building, we will modify the building area with the superpixel constraint. Finally, obtain a final building extraction result.
# Mycelium-Based Thermal Insulation for Domestic Cooling Footprint Reduction: A Review
###### Abstract  
Domestic cooling demands in arid and hot climate regions, including Qatar, induce a significant challenge to reduce the area's cooling energy consumption and carbon footprint, primarily due to the heavy reliance on electricity-intensive air conditioning systems. The inadequacy and inefficiency of conventional construction and insulation materials and their improper implementation further exacerbate this issue. Considering such challenges, this research comprehensively evaluates an unconventional and innovative solution recently proposed for this purpose: mycelium-based thermal insulation. Mycelium is the vegetative, thread-like structure of fungi, consisting of a network of branching hyphae that facilitate nutrient absorption and environmental interactions. This review paper analyses mycelium-based composites, focusing on their mechanical, physical, and chemical characterization. It also explores the potential of mycelium as a sustainable solution for indoor temperature regulation, particulate matter absorption, and bioremediation. Moreover, this review examines various available insulation materials and highlights the unique advantages offered by mycelium-based composites. As a result, the literature review indicates that mycelium exhibits exceptional thermal and acoustic insulation properties owing to its low thermal conductivity, favorable water absorption coefficient, porous structure, and considerable mechanical strength. This porous architecture facilitates efficient air purification, improving indoor air quality. Additionally, mycelium shows promise in actively degrading pollutants such as hydrocarbons, heavy metals, and pesticides in soil and water.  
mycelium; thermal insulation; indoor temperature regulation; particulate matter absorption; bioremediation; carbon footprint
## 3 Parameters and Existing Model  
### Model Parameters  
Studies [20,25] indicate that incorporating multiple ground motion parameters can effectively reduce model error. However, [PERSON] et al. [33] noted that further increasing the parameters does not necessarily enhance model accuracy and may reduce its applicability. Consequently, model accuracy primarily depends on its parameters and configuration.  
Arias intensity (\(I_{a}\)) [34] is a key parameter representing the energy level of seismic waves (Equation (1)), with its value determined by recorded acceleration \(a(t)\) over the duration of the event. Higher \(I_{a}\) corresponds to greater seismic energy at a site, increasing the likelihood of inducing significant permanent slope displacement. Many studies [22,24,33] have explored the relationship between \(I_{a}\) and the permanent displacement of seismic slopes, applying this parameter in \(EM\).  
\[I_{a}=\frac{\pi}{2g}\int_{0}^{T}a^{2}(t)dt \tag{1}\]  
Here, \(g\) is gravity acceleration.  
Similarly to \(I_{a}\), peak ground acceleration (\(PGA\)) also reflects the energy magnitude of seismic waves. However, \(PGA\) better captures the peak seismic force, making it a critical parameter in fitting [11,14,20,25]. Additionally, \(PGA\) is often associated with yield acceleration (\(a_{y}\)), and the yield acceleration ratio (\(a_{y}/PGA\)) is often employed in the \(EM\). Yield acceleration represents the acceleration necessary for a slope to reach its limit equilibrium. When the yield acceleration ratio exceeds 1, all points on the slope remain stable during an earthquake, resulting in zero permanent displacement. As the ratio decreases below  
Figure 1: The distribution of ground motion parameters in the database. (**a**) Magnitude; (**b**) duration; (**c**) peak ground acceleration; (**d**) arias intensity.  
1, slope stability under seismic conditions diminishes, leading to slide. When \(a_{y}/PGA\) approaches 0, the permanent displacement of landslide theoretically approaches infinity.
# RFID Based Embedded System for Sustainable Food Management in an IoT Network Paradigm
## 3 RFID Food Management System
### Database  
The RFID Food Management system stores rich information related to common ingredients, such as energy (kcal), proteins (g), carbohydrates (g), and fat (g), contained in 100 g. This nutritional information has been directly extracted from an international food composition database [15]. RFM app users request data through an API REST (Representational State Transfer), which is a web service that provides interoperability among computer systems on the Internet. In order to build a simple REST service, we used the _deployed_[16] tool. This open source tool allows one to design, build, and scale REST services for web applications in minutes. It provides a user model with methods to open and close sessions, and a control panel to configure a database. The database implemented in _deployed_ is the open source tool _MongoDB_[17], based on the NoSQL paradigm, its architecture relies on collections and documents. One advantage of using a non relational database, is that it optimizes queries that involve huge amounts of registers. Table 3 shows the four collections of data created in the database. Table 3 presents the list of parameters from the generated collections: Product, Recipe, User, and Offer. Note that each item created from each collection will be identified uniquely. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Sector** & **Block** & **Bytes** & **Information** \\ \hline
15 & 0–2 & 0–15 & Product name \\ \hline
14 & 2 & 0–4 & Product identifier \\ \hline
14 & 2 & 5–6 & Group product belongs to \\ \hline
14 & 2 & 7–10 & Energy in 100 g (kcals) \\ \hline
14 & 2 & 11–15 & Quanty of product \\ \hline
14 & 1 & 0–2 & Fat in 100 g (grams) \\ \hline
14 & 1 & 3–5 & Carbohydrates in 100 g (grams) \\ \hline
14 & 1 & 6–8 & Proteins in 100 g (grams) \\ \hline
14 & 1 & 9 & Contains gluten. \\ \hline
14 & 1 & 10 & Contains egg \\ \hline
14 & 1 & 11 & Contains milk \\ \hline
14 & 1 & 12 & Contains soy \\ \hline
14 & 1 & 13 & Contains peanuts \\ \hline
14 & 1 & 14 & Contains nuts \\ \hline
14 & 1 & 15 & Contains fish \\ \hline
14 & 0 & 0 & Contains shellfish \\ \hline
14 & 0 & 1 & Contains celery \\ \hline
14 & 0 & 2 & Contains sesame \\ \hline
14 & 0 & 3 & Contains mustard \\ \hline
14 & 0 & 4 & Is it fresh? \\ \hline
14 & 0 & 5–6 & Expiration/issue day \\ \hline
14 & 0 & 7–8 & Expiration/issue month \\ \hline
14 & 0 & 9–12 & Expiration/issue year \\ \hline
14 & 0 & 13–14 & Units \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Bytes used to locate product information.
## 2 Model Constructions and Hypothesis
### Critical Analysis of Theoretical Constructs
#### 2.1.1 Performance Expectancy  
Performance expectancy (PE) is a critical determinant of the UTAUT framework. Performance expectancy is the degree to which people believe that using a system will enhance their job performance [35].  
The construct of performance expectancy is based on [31], where the item PE1 originated from the \"Perceived usefulness\" [37; 38]; the items PE2 and PE3 originated from the \"Relative Advantage\" [39]; and the item PE4 originated from the \"Outcome Expectations-Performance\" [40; 41].  
Perceived usefulness has been widely used in robot acceptance models as an independent variable that has a relationship with the intention to use [7; 27; 28]. In related robot acceptance studies that used the UTAUT model, performance expectancy had a relationship with the intention to use [5; 8; 9; 10; 11; 12; 13; 14; 42].  
Therefore, the following hypothesis was proposed:  
**H1**: _There is a significant relationship between performance expectancy (PE) and behavior intention (BI) to use the robot as a co-worker._
# Effect of Thermal via Design on Heat Dissipation of High-Lead QFN Packages Mounted on PCB
## 3 Simulation Results  
In this paper, we have primarily embraced fundamental steady-state thermal analysis and static structural analysis methodologies to comprehensively assess the heat dissipation capabilities and thermal stress characteristics of the QFN package. Our analytical framework begins by elucidating the simulated outcomes pertaining to the high-lead QFN package under varied thermal via parameters. Subsequently, building upon this foundation, we undertake an in-depth exploration encompassing the conventional QFN, dual-row QFN, and high-lead QFN packages, with the overarching objective of pinpointing the QFN  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Material**} & **Thermal Conductivity** & **Thermal Expansion** & **Young’s Modulus** \\  & **(W/m °C)** & **(ppm/°C)** & **(GPa)** \\ \hline Silicon & 148 & 2.8 & 131 \\ EMC & 2.1 & 13.8 & 14.21 \\ Copper & 385 & 17.6 & 121 \\ Silver Paste & 5 & 31 & 2.3 \\ FR-4 & 0.3 & 18 & 22 \\ SAC305 & 64 & 19.1 & 37.4 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Material properties of QFN package.  
Figure 3: Mesh simulation model for the high-lead QFN package.  
package that exhibits optimal thermal performance alongside its corresponding optimal thermal via parameters.
## 3 Design and Implementation
### Sensor Data Synchronization  
The CNC information includes tool coordinates by tool position and peripheral information (e.g., feed rate, spindle RPM, G code, etc.). However, due to the absence of additional information on machining status, it is hard to estimate tool wear (breakage) and chatter exactly. For the diagnosis of machining conditions, sensors should be selected collected data should be synchronized to CNC information. For the diagnosis of tool wear, a CNC load meter can be adopted. However, it is hard to diagnose overload or micro-load during machining using a face cutter or a small-size tool (3\(\phi\) or less in diameter). It is very difficult to diagnose a chatter with CNC information only. To check if there is any problem during machining, diagnosing current machining conditions by synchronizing sensor data is needed. Therefore, this study collected data through the SENSOR and IO packages of MDT4 DE and stored them in a database through the model.  
Figure 6: A package diagram of the MDT4 DE.
# Experimental Study on Multi-Cell Counting Using an Inertial Microfluidic Device
## 3 Results and Discussion
### Counting Under Diseased Conditions (Ratio 2)  
Figure 9a,b illustrates the particle counting for the 8-\(\upmu\)m and Figure 9c,d for the 15-\(\upmu\)m particles under diseased conditions (ratio of 400:1). The graphs indicate that the particle counts were significantly higher at lower flow rates in all channel sizes due to the prolonged interaction time with the detection mechanisms.  
* Influence of Channel Size and Flow Rates: The 150 \(\upmu\)m channel size remained the most effective in maintaining high counting efficiency at low flow rates. However, as the flow rate increased, the particles misaligned and lost their equilibrium position, resulting in a disruption to the counting efficiency, especially in wider channels (250 \(\upmu\)m).  
The above results indicate a decrease in counting efficiency due to the channel design and imaging process, especially when dealing with wider channels and higher flow rates. The main issue is that the imaging system's lens has limitations when used with wider channels, as it focuses more on the central region. The reference counts of particles in Figures 6 and 7 by hemocytometer are shown by the dotted line for the 8 \(\upmu\)m and 15 \(\upmu\)m particles of 6.45 \(\times\) 10\({}^{7}\) cells/mL and 1.10 \(\times\) 10\({}^{7}\) cells/mL respectively.  
The smallest percentage error of 1.8% for the 8 \(\upmu\)m microparticles and 1.1% for the 15 \(\upmu\)m ones indicates the optimal parameters for cell counting using the microfluidic device that presented the smallest channel, measuring 150 \(\upmu\)m by 150 \(\upmu\)m, and the lowest flow rate of 1 \(\upmu\)L/min. These results were validated by counting the same suspension solution of both ratios through the commercially used hemocytometer microparticle counting device [23]. This configuration allowed for a more controlled flow and interaction of the  
Figure 9: Channel size vs. 8-\(\upmu\)m and 15-\(\upmu\)m count (cells/mL) at different flow rates in Ratio 2. (**a**) Under observation of Bioimager fluorescent microscope. (**b**) Inverted microscope. (**c**) Under observation of Bioimager fluorescent microscope. (**d**) Inverted microscope.  
particles within the detection zones, ensuring that the microparticles were adequately focused and accounted for during the imaging process. These findings highlight that the system's reliability depends significantly on maintaining the optimal flow and channel conditions. Although the current setup is less integrated than commercial counters, it provides an efficient, flexible, and easily customizable platform for experimental cell counting applications. This is especially beneficial in resource-limited or research environments where adaptability and accuracy are prioritized.
# A Voxel-Based Watermarking Scheme for Additive Manufacturing
## 4 Discussion and Analysis
### Encryption Using Distance Fields  
During the watermarking process, our encoder encrypts the digital model by transforming it into a distance field. To attack the watermark, the attackers must obtain full knowledge about this encryption procedure. Otherwise, they are not able to comprehend the volume data and be aware of the digital model. Thus, our method offers an extra layer of security against malicious accesses.  
Conventional G-code generators cannot translate encrypted models into G-code programs. Thus, encrypted models must be decoded before being processed. After the decryption, the input models are not protected and may be illegally copied and distributed. Hence, encryption was not favored in protecting digital models in AM [4; 5]. On the other hand, our slicer is capable of directly converting encrypted and watermarked voxel models into G-code programs, as shown in the experiments. Therefore, encryption using distance field is pragmatic and increases the strength of watermarking.
## 18 Uni-Planar MIMO Antenna for Sub-6 GHz 5G Mobile Phone Applications  
[PERSON] et al. [17] proposed the uni-planar MIMO antenna system for sub-6 GHz 5G-enabled mobile phones. The MIMO antenna consists of four loop-shaped radiators placed at each corner of the mobile phone board. Each single antenna resonates at 3.5 GHz, and the matching bandwidth is from 3 GHz to 4.28 GHz, and from 3.18 GHz to 3.9 GHz. A peak gain of the single antenna is 3.64 dBi. It is confirmed that the isolation between each antenna is more than 10 dB. The proposed antenna provides sufficient radiation coverage, which is an important feature for the future 5G application. In addition, the authors investigate the effect of human hands and head on MIMO antenna performances.
# Solution-Based Synthesis and Processing of Metal Chalcogenides for Thermoelectric Applications
## 2 Solution-Based Approaches for Synthesis of Metal Chalcogenides
### Chemical Reduction-Precipitation Method  
Very recently, [PERSON] and coworkers developed a general ambient aqueous method for large-scale production of different nanostructured metal chalcogenides (y via a reduction-precipitation process without using any surfactants [70]. In a typical experiment (Figure 6a), NaBH\({}_{4}\) was used to reduce Se powder in an aqueous solution. Copper precursor in distilled water was then added into the reaction mixture to yield black precipitates due to the poor solubility of copper selenide. The whole synthesis process took only one hour with high yield over 90%. Figure 6b-e presents the TEM images of different metal chalcogenide nanostructures prepared by this method. Most metal chalcogenides exhibit spherical morphology with a narrow size distribution of 10-20 nm. The possibility of such uniformed nanosized particles without addition of surfactants is due to the extremely low solubility of the nanoparticles, which gives rise to homogeneous precipitation from the aqueous solution. The thermoelectric properties of these nanoparticles were investigated after sintering into pellets using the spark plasma sintering technique. Pronounced enhancement in the ZT value was observed with some metal chalcogenide nanostructures (ZT\({}_{\text{max}}\) = 0.38 at 300 \({}^{\circ}\)C for SnSe; ZT\({}_{\text{max}}\) = 0.27 at 230 \({}^{\circ}\)C for Bi\({}_{2}\)Se\({}_{3}\)) due to the effectively reduced thermal conductivity. [PERSON] and coworkers also reported a wet coprecipitation method for large-scale synthesis of Cu\({}_{2}\)Se nanoparticles, which exhibited an outstanding ZT value (up to 1.35 at 850 K) after hot press sintering [71]. [PERSON] et al. developed a similar eco-friendly reduction-precipitation approach to prepare SnSe nanoparticles in a short reaction time of 10 min [78].  
Figure 5: (**a**) Schematic illustration of the formation mechanism of the Bi\({}_{2}\)Te\({}_{3}\) nanowires via a template-assisted solution-phase process. (**b,c**) Transmission electron microscopy (TEM) images of ultrathin Bi\({}_{2}\)Te\({}_{3}\) nanowires prepared by the process. The inset in (**c**) is the high-resolution TEM image for the prepared Bi\({}_{2}\)Te\({}_{3}\) nanowires. (**d**) ZT value of the Bi\({}_{2}\)Te\({}_{3}\) nanowire bulk pellet at different temperatures. Readapted with permission from The Royal Society of Chemistry [68] and American Chemical Society [69]. PVP: polyvinylpyrrolidone.
## 8 Discussion  
This review is centered on the papers published in the Web of Science that are related to \"mobility\" and \"multi-modal\" in recent years. To systematically review and categorize existing works related to multi-modal mobility, the keywords \"mobility\" and \"multi-modal\" were used in the initial search. The results showed that the number of published papers grew from 34 (during the years 2006 to 2015) to 185 (during the years 2016 to 2024). The exponential growth in the number of published papers related to \"mobility\" and \"multi-modal\" over the years shows that many emerging research directions have attracted the attention of related research communities. The results of the initial search were analyzed using VOSviewer to identify terms or keywords for refining the search. We classified papers into five categories by combining different terms or keywords to perform the refined search. The first category of works was obtained by searching with string AB = (\"MaaS\" AND \"multi-modal\") and the second category was obtained by searching with string AB = (\"sustainable\" AND \"mobility\" AND \"multi-modal\") or string AB = (\"sustainability\" AND \"mobility\" AND \"multi-modal\"). The third category of works was obtained by searching with string AB = (\"shared mobility\" AND \"multi-modal\") or string AB = (\"ridesharing\" AND \"multi-modal\"). The fourth category of works was obtained by searching with strings AB = (\"bike\" AND \"transport\" AND \"multi-modal\"), AB = (\"micromobility\" AND \"multi-modal\") and AB = (\"scooter\" AND \"transport\" AND \"multi-modal\"). The fifth category of works was obtained by searching with the query strings AB = (\"MaaS\" AND \"integration\") and AB = (\"MaaS\" AND \"pricing\"). Content analysis was performed after the refined search. If a paper was not appropriate for a category, it would be reassigned to another category that is more relevant. This review was based on the five categories obtained. The number of papers is 17 in Category 1, 19 in Category 2, 10 in Category 3, 11 in Category 4, and 21 in Category 5. Category 5 ranks highest and Category 2 ranks second highest in terms of the numbers of papers.  
In the remainder of this section, we will first analyze research topics and issues identified in this review and then discuss opportunities and challenges for future research.
# A Performance Analysis of VANETs Propagation Models and Routing Protocols
## 3 Proposed Work
### Propagation Models  
The propagation models are essential for determining channel characteristics vital in V2V and V2I communication. The propagation factors affect the signal strength travelling from source to destination in a wireless medium, including path loss and signal fading. For the analysis, this work considers four models: FRIS (FS) path loss, Two-Ray Ground (TR), Log-Distance path loss (LD), and Nakagami (NK) fading models [40; 41; 42]. The pictorial representation of FRIS and Two-Ray Ground propagation model is shown in Figure 3a and Figure 3b respectively.