esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Material and Methods
### Simulation Methodology  
The present investigation is a thermodynamic study performed in steady-state conditions. A thermodynamic model based on the equations of Section 2.2 has been written in a program in the Engineering Equation Solver (EES) [20]. The steady-state analysis enables the investigation of the system to be conducted without studying the long-term storage of the unit, while the thermal losses of the system are neglected. This aspect will be examined in future work about this system. Table 1 shows the two main scenarios of the system operation that are examined, namely the trigeneration in summer and the cogeneration in winter.  
The simulation details, including all the simulation data, are presented in Table 2. Specifically, the selected efficiency values, the selected temperature levels and a range of other simulation parameters are included in this table. During simulations, different parameters are investigated in order to present the unit's performance for various operating cases. In particular, the system is examined for different values of the high-temperature level (\(T_{heat,h}\)) which is a crucial design parameter, as well as for different ambient temperatures. It is worth noting that for ambient temperature levels lower than 20 \({}^{\circ}\)C, it is assumed to have a cogeneration system, while for temperature levels above 20 \({}^{\circ}\)C the trigeneration operation is selected. This is a simple and practical technique in order to separate the two examined scenarios. Moreover, different values of the loads (\(Q_{cool}\), \(Q_{heat,m}\) and \(Q_{heat,h}\)) are examined. In the last step of this investigation, the operating margins of the unit are defined in order to map the possible operating conditions. Practically, the ambient heat input is a critical parameter that can be used to counterbalance and cover the needed loads.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Parameters**} & \multicolumn{2}{c}{**Scenarios**} \\  & **Trigeneration** & **Cogeneration** \\ \hline \(Q_{cool}\) (kW) & 100 & 0 \\ \(Q_{heat,m}\) (kW) & 100 & 150 \\ \(Q_{heat,h}\) (kW) & 100 & 150 \\ \(T_{am}\) (\({}^{\circ}\)C) & 25 & 10 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Main parameters of the two scenarios in the thermodynamic simulation.
## 3 Survey Goals, Methodology, and Population  
The survey has been carried out using a qualitative questionnaire with multiple-choice questions and a Likert Scale, ranging from 1 to 6, with 1 corresponding to \"not important\" and 6 corresponding to \"very important\". To encourage a definite choice by respondents and reduce answers' uncertainty, the authors decided to have no neutral or mid-point on scale ([PERSON] et al., 2014). Organizations were firstly contacted by phone and then invited via email to complete the attached questionnaire. This survey aims to analyze the attitude of Italian EMAS organization towards the scheme, more specifically:  
* The motivations that push organization to register;
* The main difficulties encountered from an economic and technical viewpoint;
* The results obtained in terms of environmental, economic, and financial performances.  
In order to obtain generally significant results, useful to deeply understand organizations' perception of EMAS, the target population of the survey consisted of all the Italian registered organizations at the date. The organizations registered according to EMAS when the questionnaire was submitted (2012-2013) were 962. Respondents were 562, corresponding to 58.42% of the total. The result allows affirming that the sample size is representative of the given population. Using the table for sample size calculation proposed by [PERSON] and [PERSON] (1970) and assuming a standard error equal to 0.05 for a population between 900 and 1000 elements the required sample is between 260 and 280 elements. Thus, it can be assumed that a sample of 562 organizations is well representative of the population ([PERSON] et al., 2014).
# A Reliable Scheme for Synchronizing Multimedia Data Streams under Multicasting Environment
## 5 Implementation Setup and Results Discussion  
We used an RTP/RTCP library owned by Ericsson Research Corporate Unit, Lulea, Sweden and enhanced it as per our research requirements. This library was developed using Visual Studio 6.0 and protocol stack was developed using C but it has a C++ interface as well. It also includes an open source POSIX threading library to provide support for multithreading.  
Figure 10: RTCP-APP: Application-defined RTCP packet, to carry feedback from the receiver to sender.  
Figure 9: RTCP-APP: Application-defined RTCP packet, to carry Playout time from the sender.  
Following parameters have been set in our implementation. We tested our protocol in a real scenario over Ericson Research Wide Area Network (WAN). We modified RTP-based mbone tools for video and audio stream respectively. Both the audio and video streams were kept separated in the source application. The parameters of the setup are shown in Table 2.  
We have tested our algorithm by defining four different scenarios:  
Scenario 1: Same playout time for all receivers.  
Scenario 2: One-way delay calculated at the sender.  
Scenario 3: Sender view of idle time under normal circumstances.  
Scenario 4: Fluctuation in delay offset and idle time.
# Personalized Privacy Protection Based on Space Grid in Mobile Crowdsensing
## 2 Related Work  
### Differential Privacy  
A differential attack occurs when the attacker leverages existing knowledge to compare it with the query information, attempting to deduce the most probable guess. For instance, if a school releases the results of a course with 100 students, revealing that only six students failed, an attacker possessing the score information of 99 students can attempt to guess whether the remaining student passed or failed. Differential privacy protection technology introduces noise to the original data to ensure a similar data distribution. Consequently, when an attacker adds or removes data, the disparity in data distribution becomes indistinguishable, preventing the identification of specific users within the published data. The basic concepts and definitions of differential privacy are as follows:  
(\(\epsilon\)-differential privacy) In the algorithm, a series of queries \(Q\) are performed on any two adjacent datasets \(D\) and \(D^{{}^{\prime}}\), and \(P_{Q}\) is the probability of the set of all possible outputs of \(Q\). \(S_{Q}\) is any subset of \(P_{Q}\). If the algorithm satisfies:  
\[P[Q(D)\in S_{Q}]\leq\epsilon^{\epsilon}\cdot P[Q(D^{{}^{\prime}})\in S_{Q}] \tag{1}\]  
then this algorithm satisfies \(\epsilon\)-differential privacy, where datasets \(D\) and \(D^{{}^{\prime}}\) are adjacent datasets. That is, even if any tuple is changed, the probability difference of the output results is very small. The attacker cannot guess the dataset and can play a role in protecting user data [30].  
(Global sensitivity) When conducting a series of random queries \(Q\) on any two adjacent datasets \(D\) and \(D^{{}^{\prime}}\), the global sensitivity of the query function is the maximum Manhattan distance of the output. The global sensitivity can obtain the variation range of a query function on a pair of adjacent datasets. And the formula is as follows:  
\[QS_{q(D)}=\max_{D,D^{{}^{\prime}}}\
orm{Q(D)-Q(D^{\prime})}_{1} \tag{2}\]  
(Local sensitivity) When conducting a series of random queries \(Q\) on any two adjacent datasets \(D\) and \(D^{{}^{\prime}}\), the formula of local sensitivity is as follows:  
\[LS_{q(D)}=\max_{D^{{}^{\prime}}}\
orm{Q(D)-Q(D^{\prime})}_{1} \tag{3}\]The local sensitivity is determined via the query function and the distribution of the query dataset, whereas the global sensitivity is solely related to the query function and is independent of the query dataset. Utilizing local sensitivity poses a certain risk of data leakage. Therefore, in the algorithm proposed in this paper, we will adopt global sensitivity. As mentioned earlier, differential privacy can be achieved by introducing noise to the query results, yet excessive noise can impede data availability. Since sensitivity signifies a change in query results due to the deleting of any record in the dataset, it is commonly employed as a parameter to measure the amount of noise in differential privacy.
## 3 Our Approach
### Algorithm
```
1:the different strategies \(\sigma_{1},...,\sigma_{m}\)
2:partition of outcome spaces \(R\leftarrow\bigsqcup_{i}\{\Omega_{i}\}\)
3:CASE SGIM-TL: transfer dataset \(D_{3}=\{(\omega_{i},\omega_{j}),\omega_{r}\}\)
4:CASE SGIM-TL: episodic memory Memo \(\leftarrow\{(\omega_{i},\omega_{j}),\omega_{r}\}\)
5:loop
6:\(\omega_{g},\sigma\leftarrow\) Select Goal Outcome and Strategy(\(R\))
7:if\(\sigma=\) Autonomous action space exploration strategy then
8:\(Memo\leftarrow\) Goal-Directed Action Optimization(\(\omega_{g}\))
9:elseif\(\sigma=\) Autonomous procedural space exploration strategy then
10:\(Memo\leftarrow\) Goal-Directed Procedure Optimization(\(\omega_{g}\))
11:elseif\(\sigma=\) Mimicry of action teacher \(i\) strategy then
12:\((\pi_{d},\omega_{d})\leftarrow\) ask and observe demonstrated action to teacher \(i\)
13:\(Memo\leftarrow\) Mimic Action(\(\pi_{d}\))
14:elseif\(\sigma=\) Mimicry of procedural teacher \(i\) strategy then
15:\(((\omega_{di},\omega_{dj}),\omega_{d})\leftarrow\) ask and observe demonstrated procedure to teacher \(i\)
16:\(Memo\leftarrow\) Mimic Procedure(\((\omega_{di},\omega_{dj})\))
17:endif
18: Update \(M\) with collected data Memo
19:\(R\leftarrow\) Update Outcome and Strategy Interest Mapping(\(R\),Memo,\(\omega_{g}\))
20:endloop
```  
**Algorithm 1** SGIM-PB and its SGIM-TL variant  
At each episode, the robot and the environment are reset to their initial states. The learner uses the chosen strategy to build an action (based or not on a procedure), decomposed into action primitives which are then executed sequentially without getting back to its initial position. Whole actions are recorded, along with their outcomes. Each step (after each action primitive execution) of the sequence of action primitives execution is also recorded in Memo.
# A Sensor for Characterisation of Liquid Materials with High Permittivity and High Dielectric Loss
## 6 Conclusions  
A multi-element split-ring resonator has been designed, fabricated and verified using diluted ethanol samples for the dielectric measurement of liquids. This method used three circular ring resonators to enhance the local field so that more field interaction with samples can take place. A low-loss fused quartz was used to hold liquid so that high-loss liquid only occupies 36% volume, which enables the measurement of high-loss samples. By combining these two measures, it was demonstrated that water and diluted samples can be measured with an accuracy of 2.8%. In addition, an analytical function has been developed, facilitating the direct recovery of permittivity from measured \(S_{21}\). This method is also useful for the measurement of biological and corrosion samples. Further development may include systematic study on influential factors on sensitivity, and the development of sensors for the measurement of samples covering a wider range of loss and dielectric constants.  
Conceptualization, X.L. and X.S.; methodology, C.W.; validation, S.Y.; investigation, Z.H.; data curation, C.W.; writing--original draft preparation, C.W.; writing--review and editing, X.L. and X.S.; visualization, C.W.; software, X.Y.; funding acquisition, X.L., X.Y. and Z.H. All authors have read and agreed to the published version of the manuscript.  
This work is funded in part by the University Synergy Innovation Program of Anhui Province, GXT-2021-027, the National Natural Science Foundation of China under the contract number of 61871003 and the open project of the state key laboratory of complex electromagnetic environment effects on electronics and information system under grant number CEMEE202Z0201B. The work of [PERSON] was supported by the National Measurement System Programme of the UK government's Department for Business, Energy & Industrial Strategy (BEIS).  
Not applicable.  
The authors declare no conflict of interest.
# Using Satellite-Derived Vegetation Products to Evaluate LDAS-Monde over the Euro-Mediterranean Area
## 3 Results  
The impact of the joint assimilation of the SSM and LAI satellite products was evaluated. First, the assimilation performance was assessed by comparing the model open-loop and analysis simulations with the assimilated products (in order to demonstrate that the assimilation systemsperform well). In a second step, the consistency between the LDAS analysis and independent vegetation satellite products (evapotranspiration, GPP and fluorescence) was evaluated.
# Advances in Three Dimensional Bioprinting for Wound Healing: A Comprehensive Review
## 4 3D Bioprinting Techniques
### Extrusion-Based Bioprinting
#### 4.3.2 Fused Deposition Modeling (FDM)  
FDM is one of the more rapid production methods first introduced to the literature in 1980 by [PERSON] [189]. FDM is a printing method based on the deposition of various polymers in filament or powder form layer by layer from the printhead to the device by melting them with heat (Figure 2F). During printing, the position of the printhead is monitored by the device program. The designed printing shape is deposited in the XY plane. After the layer is printed, it completes the layer-by-layer process by moving the specified distance along the z-axis to print the upper layer. This process is repeated until the design is printed [190; 191].  
Among the advantages of FDM technology, it allows the possibility of multiple extrusions using various polymers [192; 193]. This process uses nozzles containing different thermoplastic materials, controls them via the system, and decouples them sequentially, and a complete model is obtained by combining various characteristics. This bio-printing system does not contain solvents, so it does not need organic solvents that can often damage cells in other systems. However, the number of usable thermoplastic materials is disadvantageously limited [194; 130].  
Recently, researchers have developed novel bioinks suitable for FDM printing, while simultaneously contributing to biomedical engineering. For example, a research group demonstrated that grafting a polyvinylpyrrolidone (PVP) hydrogel on the surface of poly-lactic acid (PLA) flat discs and 3D-printed scaffolds increases hydrophilicity. In this study, PVPs of two molecular masses were used in separate variations: 10 kDa and 360 kDa. The mean mass of printed scaffolds was 330.8 mg \(\pm\) 22.3 mg. The SEM photography of scaffolds revealed a hexagon-shaped pore with 560-590 \(\upmu\)m sides. The printed hydrogels were placed on wells containing mouse fibroblast cells with DMEM and incubated for 24 h. Cell viability analysis using mouse fibroblasts revealed that grafted scaffolds except the 360 kDa variant could retain viability above 70%, in compliance with ISO10993 [195]. This study proves that PVP grafting is suitable for more complex, porous 3D prints, albeit polymers with high molecular weight may generate cytotoxicity [196]. In another study, wound dressings consisting of CH-pectin (PEC) hydrogels were prepared for the delivery of lidocaine hydrochloride (LDC), using an extrusion-based 3D printer. LDC loaded hydrogels showed swelling rates and water contents of 2265% and 96%, correspondingly, whereas the hydrogel-only group displayed a swelling rate of 2832% and water content of 97%. In vitro drug assays revealed a fast, but controlled, LDC release over 5 h in all variations. The printed hydrogels had bioadhesion strength values of 86.5-126.9 g, like the commercially available wound dressings. Overall, the study confirmed that 3D-printed CH-PEC hydrogels can be used in fabricating wound dressings [165].
# Underwater Image Super-Resolution via Dual-aware Integrated Network
## 4 Experiments
### Model Analysis  
Analysis of varying numbers of DAEMs. To explore the influence of model depth on reconstruction accuracy, we set the number of DAEMs to \(D=10\), \(12\), and \(14\). From Table 4, it can be seen that there is no significant improvement in the reconstruction results as depth increases. This is because the deeper the depth of the network, the more prone network weights are to deactivation, which makes it difficult to improve performance. Considering the size of the network and restoration accuracy, we opted for \(D=12\) as the number of DAEMs.  
Analysis of edge detection. To further investigate different methods for preserving edge features in the restored images, we employed the Canny algorithm [64] to illustrate the benefits of our proposed method. As depicted in Figures 5 and 6, our DAIN exhibits more prominent edge detection features compared to the majority of methods. These outcomes demonstrate the efficiency of our DAIN in extracting feature information and aiding in the recovery of additional texture details, resulting in visually pleasing effects.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Numbers** & **FLOPs (G)** & **PSNR (dB)** & **SSIM** & **UIQM** \\ \hline
10 & 18.53 & 29.83 & 0.8177 & 2.7585 \\
12 & 21.79 & **29.86** & **0.8196** & 2.7724 \\
14 & 25.04 & 29.81 & 0.8177 & **2.7803** \\ \hline \hline \end{tabular}
\end{table}
Table 4: Effect of the number of DAEMs on the USR-248 dataset at a scale factor of \(\times 4\).  
Figure 4: Visual comparisons between our DAIN and popular methods were conducted utilizing the EUVP dataset. Left to right: the original HR image, LR image, UGAN, UGAN-P, Funie-GAN, Funie-GAN-UP, Deep-SESR, and the proposed DAIN.
# Two-Dimensional Permutation Vectors' (PV) Code for Optical Code Division Multiple Access Systems
## 4 2-Dimensional PV System Description
### Design of 2D-PV Receiver Part  
The receiver structure for a conventional 2D W-T OCDMA system is shown in Figure 5. The fiber output data is demultiplexed and sent to a 2D PV decoder circuit, which consists of low-pass Bessel  
Figure 4: Transmitter structure for 2D W-T PV optical code division multiple access system.  
filters and inverse time delay circuitry. Direct detection with a single-photo diode detector or balance detection technique can be employed for signal detection with a certain threshold level set to achieve the desired output. Finally, at the receiver, both input and output data are compared by BER test set and, therefore, BER analysis is carried out by BER test set. A Spectrum analyzer and optical time domain analyzer (OTDA) are used to analyze the changes in signal power and to measure spectrum of various signals with time at different points of the system.
# Random PWM Technique Based Two-State Markov Chain for Permanent Magnet Synchronous Motor Control
## 5 Conclusions  
This paper presents a control method for permanent magnet synchronous motors based on two-state Markov chain random spread spectrum. This method incorporates the concept of the Markov chain and establishes a two-state Markov chain model applicable to RPWM. It significantly optimizes the random number generation results, thereby effectively reducing the amplitude of high-frequency harmonics and enhancing the suppression effect of EMI. At the same time, the immune algorithm is used to optimize two important spread spectrum parameters, namely the transition probability and random gain, further enhancing the suppression ability of the proposed method for EMI. Moreover, this method does not require modifying the system hardware, changing the regulator parameters, or affecting the performance of the vector control system and has excellent universality. In addition, the content of this paper is based on the PWM-powered permanent magnet synchronous motor control system, which provides a theoretical and experimental basis for the subsequent research on system efficiency, torque fluctuation, vibration noise suppression, and so on.  
Conceptualization, Z.W. and X.L.; methodology, X.J. and G.Z.; software, X.L.; validation, G.Z.; formal analysis, X.L.; investigation, Z.W.; resources, X.J.; data curation, Z.L.; writing--original draft preparation, Z.W. and X.L.; writing--review and editing, Z.W. and X.L.; visualization, X.L.; supervision, X.J.; project administration, Z.L.; funding acquisition, Z.L. and Z.W. All authors have read and agreed to the published version of the manuscript.  
Figure 14: EMI suppression effect of the proposed method at different speeds and modulation indices.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Modulation Strategy** & **10 kHz** & **20 kHz** \\ \hline Conventional SVPWM & \(-8.04\) & \(-14.73\) \\ Conventional RPWM & \(-15.62\) & \(-23.90\) \\ Markov-RPWM & \(-16.10\) & \(-25.63\) \\ Proposed methodology & \(-17.89\) & \(-26.49\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Amplitude of the power spectral density near the main frequency under different modulation strategies when \(M\) is 1.0. (Unit: dB/Hz).  
**Funding:** This research was funded by Zhejiang Provincial Natural Science Foundation of China, grant number LD24E070001.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding authors.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
## 4 Experiments
### Experimental Results and Analysis
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{5}{c}{**Noise Level**} \\ \cline{2-7}  & \(\sigma\) = **10** & \(\sigma\) = **20** & \(\sigma\) = **30** & \(\sigma\) = **40** & \(\sigma\) = **50** & \(\sigma\) = **60** \\ \hline BM3D & 32.49 & 28.51 & 26.51 & 25.13 & 24.20 & 23.57 \\ FFDNet & 32.88 & 29.12 & 27.14 & 25.85 & 24.91 & 24.18 \\ NCSR & 32.61 & 28.59 & 26.56 & 25.13 & 24.21 & 21.66 \\ DrCNN & 33.07 & 29.19 & 27.14 & 25.80 & 24.87 & 24.06 \\ WNNM & 32.83 & 28.88 & 26.84 & 25.53 & 24.58 & 23.85 \\ RED-Net & 32.49 & 28.62 & 26.27 & 24.55 & 23.26 & 22.19 \\ TWSC & 32.67 & 28.78 & 26.76 & 25.43 & 24.47 & 23.71 \\ CsNet & 32.91 & 29.01 & 26.76 & 25.18 & 23.83 & 21.89 \\ DIP & 30.73 & 25.77 & 25.14 & 24.12 & 23.07 & 22.15 \\ Proposed & **33.63** & **30.62** & **28.30** & **26.78** & **25.58** & **24.69** \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Average PSNR results of different methods on 10 images in Flickr1024 with various noise levels.