esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Results and Discussion
### GC-MS Volatile Compounds Analysis  
The SPME-GC-MS analysis in the current study aimed to identify the relationships between the volatiles at relative concentrations. The compound identification was performed using a commercial MS database (NIST 2011 Mass Spectral Library). A Linear Retention Index (LRI) was calculated for each detected component. For the calculation of the LRI indices, a mixture of n-alkanes (C7-C40) was used as a reference series. The quantification was obtained directly from the total number of ions in the chromatogram (Total Ion Chromatogram, TIC), and it was expressed as a relative percentage. A total number of 49 volatile compounds were identified in the bee pollen samples. The list of volatile compounds, along with the retention time (RT), relative concentration (R%), and LRI, are displayed in Table 4.  
The identified compounds cover different classes of organic structures, including terpen (as thymol or eucalypt), linear alcohols (as octanol or 1-hexanol), aldehydes (as nonanal or decanal), ketones (as jasmone), hydrocarbons (as nonadecane or hexadecane), esters (as ethyl decanoate or ethyl nonanoate), and fatty acids (as decanoic acid). Esters were detected in all the samples with different R%: BP1 contained less than 20%, whereas the ester composition of BP7 was more than 80%. Terpenes were only identified in the BP4, BP5, and BP6 samples. Yet, only the latter sample comprised compounds that did not belong to the abovementioned classes, at a level of more than 25%. _Castanea_ sp., BP7, was composed of almost 69% nonanals, and a significant %R profile of alcohols; this could be associated with the nectar that the bees used to form the bee pollen pellets, or even the honeybee itself. BP1 was the only sample that presented fatty acids among all the pollen samples. Similar to our results, [PERSON] et al. [35], [PERSON] et al. [36], and [PERSON] et al. [37] reported that hexanal, heptanal, 6-methyl-5-hepten-2-one, and nonanal compounds were frequently detected at higher concentrations in bee pollen samples from countries such as Lithuania, Poland, Spain, Latvia, and China. Most of the studies investigating the volatile composition of bee pollen have been conducted without referring to the botanical origin of the pollen, and therefore, they lack the ability to associate specific volatile compounds with their plant origin. Therefore, after identifying the botanical origins and volatile organic compounds of our monofloral bee pollen samples, we discuss whether there is a potential relationship between pollen type and compounds.
## 3 Results and Analysis
### Disc Cutter Breakage Analysis
#### 3.2.3 Cutting Edge Breakage Width  
The all-round observation of the cutting edge of the disc cutter revealed that the overall broken parts were randomly distributed, with the majority of micro-chipping. With the increase in the cutting length, the number of chippings also increased, and the cutting edge breakage width was increasing. By taking the morphological images of the same area at the cutting edge breakage after different cutting lengths, the changes in the cutting edge breakage in this area during the whole wear experiment were obtained. Figures 19-21 show the breakage morphologies of the disc cutter at the same cutting position under different cutting lengths and the cutting edge breakage width variation curves, respectively. From Figures 19-21, it can be seen that when the cutting length was 23.25 m, the cutting edge positions 1 and 2 were both chipped and broken, and the degree of chipping in position 2 was somewhat greater. At this time, when the disc cutter under the action of ultrasonic vibration failed to form an effective cut on the honeycomb core, with only continuously intermittent contact and longitudinal friction, it made the breakage width and breakage length of the cutting edge became larger. Examples include the change in breakage width from position 1 (b) to (e) and the change in breakage length indicated by the yellow arrow, as well as the change in breakage width from position 2 (b) to (d). When the cutting length increased from 69.75 m to 93.00 m, the breakage depth also increased; i.e., the breakage depth increased to a certain value; a larger degree of breakage occurred; and the position failed to make contact with the honeycomb core during cutting, or the degree of friction was small, making the breakage width change slowly. At this time, the disc cutter was in the normal wear stage, as shown in position 1 (d) to (e) and position 2 (d) to (e).  
Figure 19: Breakage morphologies of disc cutter at the same cutting position 1 under different cutting lengths. (**a**) 0 m; (**b**) 23.25 m; (**c**) 46.50 m; (**d**) 69.75 m; (**e**) 93.00 m.  
Figure 18: SEM observation of continuous chipping and cracks (cutting length is 93.00 m).
## 3 Proposed Method  
The SecPri-BGMPOP approach is suggested and can offer a solution that involves several different steps in order to handle the numerous problems relating to security and protecting privacy. The Boost Graph Convolutional Network Clustering (BGCNC) algorithm, which reduces computational complexity in terms of time and memory measurements, is first applied to the input dataset to begin the clustering process. Figure 3 shows the architecture of the data security and privacy model. The way Boost Graph convolutional network clustering operates is as follows: the BGCNC training algorithm is fast and memory-efficient. It samples a block of nodes linked to a dense subnetwork at each phase and restricts the neighbourhood search towards this substring. The dense subgraph is identified via a graph-clustering algorithm. Memory and computational efficiency are greatly increased by using this straightforward yet efficient technique. An encryption method based on Magnify Pinpointing prevents identity leaks even if an adversary or attacker decodes the key or encrypted material by creating a safe key utilising a portion of the identification bit string. Based on the Hybrid Fragment Horde Bland Lobo Optimisation framework, an enhanced meta-heuristic algorithmic framework, an optimum key was obtained. Our suggested SecPri-BGMPOP is intended to offer a better security method for cloud-based big data in healthcare.
# New Light on Phtyoremediation: The Use of Luminescent Solar Concentrators
###### Abstract  
The latest developments in photovoltaic studies focus on the best use of the solar spectrum through Luminescent Solar Concentrators (LSC). Due to their structural characteristics, LSC panels allow considerable energy savings. This significant saving can also be of great interest in the remediation of contaminated sites, which nowadays requires green interventions characterized by high environmental sustainability. This study reported the evaluation of LSC panels in phytoremediation feasibility tests. Three plant species were used at a microcosm scale on soil contaminated by arsenic and lead. The experiments were conducted by comparing plants grown under LSC panels doped with Lumogen Red F305 (BASF) with plants grown under polycarbonate panels used for greenhouse construction. The results showed a higher production of biomass by the plants grown under the LSC panels. The uptake of the two contaminants by plants was the same in both the growing conditions, thus resulting in an increased total accumulation (defined as metal concentration times produced biomass) in plants grown under LSC panels, indicating an overall higher phytoextraction efficiency. This seems to confirm the potential that LSCs have to be building-integrated on greenhouse roofs, canopies, and shelters to produce electricity while increasing plants productivity, thus reducing environmental pollution, and increasing sustainability.  
soil remediation; soil contamination; greenhouse; phytoextraction; mobilizing agents; photosynthetic efficiency; photovoltaics; luminescent dyes; energy savings; sustainability +
Footnote †: journal: Applied Sciences
## 3 Measurement Results and Discussion
### Mode Control in Frequency Domain Spectrometer  
One of the important issues to record qualitative spectra, is the precise alignment of the spectroscopic or imaging systems. To illustrate suitability of Ti-mB for such aims, we have performed  
Figure 3: Scheme of polarisation orientation and THz beam profiles obtained using electronic multiplier chain source operating in a continuous wave (CW) mode at different frequencies: 0.6 THz, 0.3 THz and 0.15 THz. Reference measurements using pyroelectric detector (**a**); results using microbolometer when the dipole antenna is in parallel to the electric field of the incident light (**b**); results using microbolometer when the dipole antenna is perpendicular to the electric field of the incident light (**c**). White lines indicate intensity cross sections along the relevant axes.  
a special study using optical mixer-based frequency domain spectrometer. The THz FDS is operating within the frequency range 0.1-2 THz and it delivers radiation of circular polarization of about 1 \(\upmu\)W power at 0.2 THz. Therefore, no exceptional attention was attributed to the polarization-related features; however, we restricted ourselves to subTHz range, close to the designed antennas resonances. The mode profile was disturbed intentionally to reveal abilities of the device in recording spatial mode structure. The mode profile was not corrected intentionally. A linear array of the bolometers coupled with antennas exhibiting resonances around 0.2 THz and 0.4 THz was investigated. The results of the measurements are presented in Figure 4. As it is seen, spatial mode profiles are clearly resolved, in particular, at 0.2 THz (panel (a)), where delivered power is close to the maximal value.  
Moreover, the frequency selected exactly falls into relatively broad antenna resonance. The spatial profile presented at 0.4 THz (Figure 4b) is less expressed. It was intentionally done aiming to highlight the convenience and universal operation of the device by detuning the emission frequency to the red side of the spectrum of the antenna resonance as can be evident from panel (c). Despite this fact, the spatial profile can still be precisely controlled although the power absorbed by the microbolometer is significantly reduced. This advantage can further be exploited in determining and monitoring spectral properties of frequency domain spectrometer. It can be illuminated, for instance, via determination of full-width half-maximum (FWHM) dependency on the wavelength of the emission. The results are depicted in Figure 4d. As one can see, the FWHM increases with the wavelength, and the dependence can be approximated by a linear law represented by a dark yellow line (Figure 4d). Thus, Ti-mB microbolometers and their linear array (Figure 4e) can manifest themselves as powerful instruments in fine alignment and control in spectrometers employing weak power CW THz sources.
# EmbeddedPigDet--Fast and Accurate Pig Detection for Embedded Board Implementations
## 4 Experimental Results
### Comparison of Detection Performance
Across the platforms, furthermore, the proposed method on a Nano could provide better per-cost integrated performance than that of a PC by a factor of 2.4. TinyYOLOv2 could also provide slightly better per-cost integrated performance on a Nano than on a PC, whereas YOLOv2 could provide better per-cost integrated performance on a PC than on a Nano. That is, the lighter the method, the higher the per-cost integrated performance. Even with low-cost embedded boards, the accuracy of the proposed method was not degraded and thus the proposed method can be a practical solution for large-scale pig farms. In fact, this analysis of cost effectiveness is closely related with the \"on-device\" AI issue (i.e., processing deep networks directly on embedded devices instead of cloud server platforms) [51; 52; 53; 54; 55]. For continuous monitoring of individual pigs with a cloud server, we should transmit the video stream of each pig room into the cloud server. However, the cost of a transmitter is not lower than the cost of a Nano board. Once we transmit the video stream, then we should consider the additional cost to detect individual pigs on the cloud server. As shown in Table 7, the higher the platform cost, the lower the per-cost integrated performance with the proposed method. This situation is very similar to _automated driving_ and thus the on-device AI community is developing light-weight versions of deep \begin{table}
\begin{tabular}{l c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{2}{c}{**Per-Cost Integrated Performance**} \\ \cline{2-3}  & \multicolumn{2}{c}{**(AP \(\times\) fps\(+\)cost) \(\uparrow\)**} \\ \cline{2-3}  & **PC** & **Nano** \\  & **(\$2000)** & **(\$100)** \\ \hline YOLOv2 [75] & 8.47 & 3.84 \\ \hline TinyYOLOv2 [75] & 11.94 & 12.39 \\ \hline
**EmbeddedPigDet**pipe (v2)** & **13.79** & **33.57** \\ (Ours) & **13.79** & (\(\times\)2.4 than PC) \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Comparison of per-cost integrated performance on PC and Nano board platforms. networks for low-cost embedded boards. To the best of our knowledge, the main idea of this study (i.e., applying _filter clustering_ to \(3\times 3\) convolutional layers in order to obtain a light-weight version of deep learning-based object detector, then applying _image preprocessing_ for generating a three-channel composite image in order to improve its accuracy) was not reported by the on-device AI community. We believe the proposed idea can be one of the possible solutions for developing light-weight versions of deep networks for low-cost embedded boards. Furthermore, the proposed method can monitor individual pigs in a pig room with $200 total cost (including a RealSense camera and a Nano board). Since any owner of a large-scale farm does not want to pay a large monitoring cost, the proposed method can be one of the possible \"practical\" solutions for developing deep learning-based smart farm applications.
# Hybrid Data Hiding Based on AMBTC Using Enhanced Hamming Code
## 3 The Proposed Scheme
### Extraction Procedure  
The procedure for extracting the hidden secret bits is shown in Figure 5. The process is explained in detail according to the following procedure.  
**Input:**: Stego AMBTC compressed codes _trios_, matrix \(H=\begin{bmatrix}0&0&0&1&1&1&1\\ 0&1&1&0&0&1&1\\ 1&0&1&0&1&0&1\end{bmatrix}\), and threshold \(T\).
**Output:**: Secret data \(M=(m_{1},m_{2},\ldots,m_{n})\).
**Step 1:**: Read one block of \(trio(a,b,BM)\) from a set of _trios_ as a defined order, where the \(trio\) consists of two quantization levels and one bitmap.
**Step 2:**: The quantization levels are \(a=(a_{8}a_{7}\ldots a_{1})\) and \(b=(b_{8}b_{7}\ldots b_{1})\), where \(a_{8}\) is the MSB of \(a\) and \(a_{1}\) is the LSB of \(a\). Similarly, \(b_{8}\) is the MSB of \(b\) and \(b_{1}\) is the LSB of \(b\). The rearranged seven bit codeword is \(y=(a_{4}a_{3}a_{1}a_{1}||b_{3}b_{2}b_{1})\) by Equation (8).
**Step 3:**: Obtain the syndrome \(S=y\cdot H^{T}\). Then, assign \(S\) to \(m_{i}^{i+2}\), and add three to \(i\).
**Step 4:**: If \(|a-b|\leq T\), it is a smooth block \(trio\). In this case, this means that the hidden bits were embedded in the BM in the form of pixels. Therefore, by assigning the pixels of the BM to \(m\) in order, all the values concealed in the BM can be obtained. That is, \(m_{i}^{i+15}=BM_{1}^{16}\) and \(i=i+15\). If \(|a-b|>T\) and \(|a-b|\geq 8\), one bit is hidden in the \(trio\) by using the order of two quantization levels. If the order of two quantization levels is \(trio(b,a,BM)\), this means that \(m_{i}^{i}=1\), otherwise \(m_{i}^{i}=0\).
**Step 5:**: Repeat Steps \(1\sim 4\) until all the _trios_ are completely processed, and the extracted bit sequence constitutes the secret data \(m\).
## 2 Materials and Methods  
The initial structure from which this analysis begins is presented in Figure 1, and it is the result of some studies previously published by the authors in [7]. The antenna is constructed on an FR4 epoxy substrate with the relative permittivity of 4.4 and a thickness of 1.51 mm. On one side of the dielectric, there are the 5 directors, while on the other side, there is the reflector. The distance between the feeding dipole and the first director is 5.5 mm, while between the directors, the distance is maintained constant at 3.5 mm. The antenna was constructed with the LPKF ProtoMat S103 Plotter (Figure 2) by importing the geometry designed in the ANSYS High Frequency Software Simulator (HFSS) module to the dedicated design software for the plotter, LPKF Circuit Pro.  
After the construction of the structure on the FR4 epoxy substrate, the S parameters were measured with the help of the nanoVNA SAA-2N, and the experimental stand is presented in Figure 3. The parameters can be obtained on the display of the VNA and also using the dedicated software NanoVNA Saver v0.5.3.  
In Figure 4, the S parameters obtained after numerically modeling the antenna in Ansys HFSS and the same S parameters measured with the help of the nanoVNA SAA-2N are presented and as expected, they are in accordance. The bandwidth calculated for this structure after considering S11 values obtained through numerical modeling is 15.98%, while that from the measurements is 13.73%.  
In Figure 5, the gain of the antenna is presented, and the maximum value obtained from the numerical modeling of this structure is 3.6917. The antenna is linearly polarized.  
Beginning from this point, the antenna must be improved from the gain and bandwidth point of view; thus, a number of variations were considered. For a better understanding of this process, a diagram is presented in Figure 6.  
It must be stated that the process of reaching an optimum takes a few steps, each step representing a variation of a parameter to reach larger bandwidth and higher gain. Once an optimum structure was reached from this point of view, another parameter is varied. At any time, the better structure is kept as an etalon for the future results and compared to the previous results.  
Once an optimum is reached, the authors tried increasing its gain a little bit more while keeping the bandwidth as close as possible to the maximum bandwidth obtained for the optimized structure.  
Figure 1: The dimensions of the initial antenna structure: (**a**) modeled with HFSS; (**b**) constructed on an FR4 epoxy dielectric.  
Figure 3: Experimental stand for the measurements of the S parameters with nanoVNA SAA-2N.  
Figure 2: The PCB production line LPFK.  
Figure 4: S\(11\) values obtained for the initial structure: (**a**) measured; (**b**) obtained through numerical analysis.  
Figure 5: Gain of the initial structure.  
Figure 6: Diagram of the optimization process for the planar Yagi Uda antenna analyzed.
# Sustainability in Bio-Based Edible Films, Coatings, and Packaging for Small Fruits
## 5 Edible Film and Coating Functionalities Important for the Small Fruit Industry
### Pitfalls of the Bioactives Present in Edible Films and Coatings  
Even though edible coatings and films present enormous advantages, there are still some limitations or disadvantages. Indeed, the interaction of encapsulated compounds with the capsule or the food that they are \"protecting\" must be carefully characterized to limit alteration caused by the mode of action of bioactive compounds [2] or to reduce changes in color or sensory characteristics of coated products [206]. The effect on sensory characteristics has to be carefully monitored. Indeed, different studies show that edible coating can positively or negatively affect the sensory traits of coated products. Storage conditions (like temperature or humidity) that allow the expected activity of edible films and their encapsulated material must be detailed [207]. As referred to before, the encapsulated bioactive compounds must be GRAS to avoid cytotoxic effects, toxicological reasons, or allergenicity, and, in addition, nanoparticles, due to their small size, can enter human tissues and damage them. Hence, the size and quantity of nanoparticles are key when added to edible packaging [125]. The use of antimicrobial coatings must also address the issue of microbial resistance, aiming at the use of compounds or extracts that do not cause such a phenomenon. In contrast, the release speed of encapsulated compounds must be correlated with the growth rate of microorganisms. Otherwise, and if the release rate of an antimicrobial agent is faster than the growth of the organisms, the bioactive agent will be depleted before the storage period. The packaging system will lose its activity, resulting in the development of microorganisms, and, on the other hand, when the release rate is too slow, the organisms may grow before the antimicrobial agent is released. Edible films and coatings are biodegradable and environmentally friendly packaging, and the bioactive compounds to be added to those coatings must follow the same rationale. Using the more economical and green methodologies, possible extraction procedures will focus on two major concerns: the costs of extracting some bioactive and using toxic solvents. Finally, regulations exist for edible coatings, their ingredients and additives, dosages, and concentrations.
# Land-Cover Classification Using Deep Learning with High-Resolution Remote-Sensing Imagery
## 2 Proposed Methodology
### DenseNet121 Model  
A deep learning architecture called DenseNet121 [32] was revealed in 2017 for use in computer vision and image categorization applications. It is distinguished by its deep connectivity, in which every layer has a direct connection to every layer that comes before it and after it, encouraging feature reuse and gradient flow across the network. It employs bottleneck and transition layers to regulate the number of parameters and geographical dimensions to manage model complexity. This architecture, shown in Figure 5, has gained popularity in the computer vision field due to its efficiency and leading-edge performance, which address important issues with deep neural networks and produce amazing results in image classification applications.
# Secure K-Means Clustering Scheme for Confidential Data Based on Paillier Cryptosystem
## 7 Security Analysis
### Security Against Semi-Honest Computation Service Provider (CSP)  
Now, we prove security against a semi-honest CSP.  
**Theorem 2**.: _Let CSP be a PPT adversary corrupting the computation service provider. Then, there exists a simulator \(\mathcal{S}_{\text{CSP}}\) such that_  
\[\text{REAL}_{\Pi_{\text{KMeans}},\text{CSP}}(x)\approx_{c}\text{IDEAL}_{ \mathcal{F}_{\text{KMeans}},\mathcal{S}_{\text{CSP}}}(x,\mathsf{L}_{\text{CSP }})\]  
Proof.: The simulator \(\mathcal{S}_{\text{CSP}}\) proceeds as follows:1. Generate simulated ciphertexts for all values involved in distance comparisons, cluster assignments, and aggregations using fresh encryptions of random or zero values.
2. Simulate the communication flow and message patterns as per protocol specification, revealing only the number of clusters \(K\), dimension \(d\), and iteration count \(T\) as per L\({}_{\text{CSP}}\).
3. Since the CSP does not receive any plaintext input, and all messages are encrypted or masked using semantically secure schemes, the view is indistinguishable from that in the real world.  
Hence, \(\mathcal{S}_{\text{CSP}}\) produces a simulated execution that is computationally indistinguishable from the real one.  
From the above proofs, we conclude that the proposed protocol securely realizes \(\mathcal{F}_{\text{KMeans}}\) in the presence of a semi-honest adversary corrupting either CS or CSP, under the standard assumption of semantic security of the underlying encryption schemes.