esa-sceva/satcom-chunk-collection huggingface dataset:
# Multi-Level Split Federated Learning for Large-Scale AIoT System Based on Smart Cities
## 4 Experiment
### Impact of Different Level Layer on the SFL Model Training  
Traditional split federated learning architecture, such as SFLV1 and SFLV2 [29], has only two levels: the server executing FedAvg and the clients with the master server. It has only one operation of model parameter aggregation, and when a client is corrupted, the FedAvg server will wait and freeze. Multi-level SFL performs model aggregation operations at multiple levels, and due to the MQTT protocol, nodes performing aggregation operations can communicate with clients by publishing topics, so there is no need to wait for broken nodes. Therefore, we set up two SFL scenarios: traditional SFL (SFLV1) and multi-level SFL, both of which have 20 clients for collaborative learning, and multi-level SFL with 4 edge nodes and 2 fog nodes to perform aggregation of global model weights. In addition, we make the dataset to which each client is assigned non-independent and identically distributed (non-IID). Moreover, the local dataset of the clients is divided according to the label distribution of the sample, which means the sample label distribution on each client is different.  
Figure 7 shows the relationship between epochs and model test accuracy by non-IID SFLV1 and multi-level SFL architectures under the MQTT communication protocol. After 50 epochs, multi-level SFL and SFLV1-trained LeNet models can achieve approximately 88% and 86% accuracy, respectively, under non-IID. As can be seen from the figure, in the non-IID scenario, multi-level SFL is superior to traditional SFL, with faster convergence and higher model accuracy. This indicates that non-IID has a negative effect on splitting federated learning, but multi-level SFL can improve this problem. In the federated learning part, compared with traditional split federation learning, multi-level split federation learning can aggregate more clients at the same time for model training, so the model convergence speed will be faster. In the split learning part, since the multi-level SFL performs aggregation operations at each layer, the multi-level SFL clients undergo more local model updates, which alleviates the non-IID problem.
# NN-Based 8 FSK Demodulator for the Covert Channel
## 5 Simulations Results
### Demodulation with Hard/Soft Viterbi Decoder  
As expected, the Viterbi decoder can improve BER performance, but the final results strongly depend on the demodulator.  
Figure 16 shows the performance of the correlator-based 8 FSK demodulator for hard and soft decoding (output a1 vs output a2, Figure 10). In his case, soft decoding has a negligible impact, in comparison to hard decoding. It is due to the fact that the metrics are calculated for unknown channel parameters.  
In the case of the NN demodulator (output b1 vs output b2, Figure 10), the channel coding significantly improves the performance of the system (Figure 17). It guarantees, in comparison to the system without a coder (Figure 15), the BER = 0 for \(e_{abs}\) = 0. Moreover, the soft decoding, in addition to NN, remarkably enhances detection. This results from the fact that the metrics calculated based on NN perform much better than those that are theoretically calculated.  
Figure 16: Hard and soft correlator-based FSK demodulator with Viterbi decoder. BER performance vs. \(e_{abs}\)[%].  
Figure 15: Hard-decision FSK correlator-based and NN-based demodulator. BER performance vs. \(e_{abs}\)[%].
## 2 Materials and Methods
### Culture of Bioprinted Constructs  
The printed constructs were treated with a cocktail of small molecules suspended in NPM containing 1% Penicillin-Streptomycin to promote differentiation of the bioprinted NPCs into MNs. Media changes were performed every third day by replacing 750 \(\upmu\)L with fresh media from day 1 to day 15. Table 1 shows the five different treatments analyzed with the combinations of small molecules added, each treatment is represented by a letter. Treatments consisted of: (i) Negative (N+); 2 \(\upmu\)M of SB, 2 \(\upmu\)M of LDN and 1 \(\upmu\)M of CHIR; (ii) uro positive (P+); 0.1 \(\upmu\)M of Puro, 2 \(\upmu\)M of SB, 2 \(\upmu\)M of LDN and 1 \(\upmu\)M of CHIR; (iii) RA positive (R+); 0.5 \(\upmu\)M of RA, 2 \(\upmu\)M of SB, 2 \(\upmu\)M of LDN and 1 \(\upmu\)M of CHIR; (iv) Puro and RA positive (PR+); 0.1 \(\upmu\)M of Puro, 0.5 \(\upmu\)M of RA, 2 \(\upmu\)M of SD, 2 \(\upmu\)M of LDN and 1 \(\upmu\)M of CHIR; (v) Puro and RA negative (PR\(-\)); 0.1 \(\upmu\)M of Puro and 0.5 \(\upmu\)M of RA. Starting on day 15, concentrations of puro and RA were 0.1 \(\upmu\)M and 0.5 \(\upmu\)M, respectively. By day 15, the media was gradually replaced as previously reported by BrainPhys Neuronal Medium (BP) (05790, Stemcell, Vancouver, CA) supplemented with growth factors; 10 ng/mL of GDNF 10 ng/m (450-10, Peprotech, Rocky Hill, NJ, USA), 10 ng/mL of IGF-1 (AF-100-11, Peprotech, Rocky Hill, NJ, USA), 1 \(\upmu\)M of C-AMP (A6885, Sigma, St. Louis, MO, USA), 1% of N2 (17502048 Thermo Fisher, Waltham, MA, USA), 1% of B27 (17504001, Thermo Fisher, Waltham, MA, USA), 200 ng/mL of Ascorbic Acid (Sigma, St. Louis, MO, USA), 10 ng/mL of BDNF (450-02, Peprotech, Rocky Hill, NJ, USA ), and 1% penstep [27]. The bioprinted constructs were maintained at 37 \({}^{\circ}\)C with 5% CO\({}_{2}\)  
\begin{table}
\begin{tabular}{c c c} \hline Name & Letter Code & Treatment \\ \hline Negative & N+ & CHIR, SB, LDN \\ Puro & P+ & Puro + CHIR, SB, LDN \\ RA & R+ & RA + CHIR, SB, LDN \\ Puro and RA & PR+ & Puro and RA + CHIR, SB, LDN \\ Puro and RA & PR\(-\) & Puro and RA \\ \hline \end{tabular}
\end{table}
Table 1: Name, letter code, and treatment for each group.  
Figure 1: (a) Schematic representation of LOPTM printhead and bioprinted cylindrical construct; (b) bioprinted cylindrical construct consisting of hiPSC-derived NPCs and our novel fibrin-based bioink. Scale bar represents 3000 \(\upmu\)m. hiPSC: human induced pluripotent stem cells; NPCs: neural progenitor cells.
## 3 Novel Design of a Cross Axis Wind Turbine (CAWT)
### Selection of Airfoil  
The choice of a suitable airfoil section can significantly improve both the peak performance and the starting characteristics of a wind turbine. Symmetrical NACA 0015 airfoil with a 15% thickness to chord ratio has been chosen for this study. It is an indisputable fact that a cambered airfoil is preferable for the VAWT, due to the curved nature of the airfoil as reported by [39; 40; 41]. However, VAWT researchers have used one of the original NACA four digit series airfoil sections, usually either a NACA 0012 or a NACA 0015 section. This is because their lift, drag, and pitching moment characteristics are presumably well documented thus making validation of theoretical predictions easier [19]. [PERSON] et al. [42] reported that a maximum \(C_{\text{p}}\) of 0.32 at TSR (\(\lambda\)) of 1.6 could be achieved with a symmetrical NACA 0015 airfoil. [PERSON] and [PERSON] [43] reported that the symmetrical airfoil is utilized for small scale VAWTs in order to have the same characteristics of lift and drag on the upper and lower surfaces. They asserted that the major advantage is that symmetrical airfoils provide lift from both sides of the airfoil and therefore it will provide lift during the complete 360\({}^{\circ}\) rotation of the turbine.  
Although cambered airfoils are usually used in wind turbines because of their high L/D ratio (compared to symmetrical airfoils) at positive incidence (relative wind approaching the concave side of the airfoil), however they perform poorly at negative incidence (relative wind approaching the convex side of the airfoil. Because the angle of attack (\(\alpha\)) on a VAWT blade reverses twice per revolution, it is impossible to avoid negative incidence. It has apparently been assumed by most researchers that any performance gain by a cambered airfoil when angle of attack (\(\alpha\)) is positive would be more than offset by the reduction in performance when the angle of attack (\(\alpha\)) reverses, and symmetrical airfoils have usually been used on VAWTs [19].
# Advanced Hybrid Beamforming Technique in MU-MIMO Systems
## 5 Simulation Results  
Simulation results compare the error performance and the average sum rate according to the SNR. Also, simulation results show the number of transmit antennas according to the SNR. As simulation parameters, the size of FFT is 128 and the modulation schemes are quadrature phase shift keying (QPSK) and 16 quadrature amplitude modulation (16-QAM). Also, \(N_{s}\), \(\mathbf{N}_{t}^{RF}\) and the number of users are 4.
###### Abstract  
Developing materials for efficient energy storage and effective electromagnetic interference (EMI) shielding is crucial in modern technology. This study explores the synthesis and characterization of carbonaceous shape-stabilized octadecane/MWCNT (multi-walled carbon nanotube) composites, utilizing activated carbon, expanded graphite or ceramic carbon foam, as shape stabilizers for phase change materials (PCMs) to enhance thermal energy storage and EMI shielding, for energy-efficient and advanced applications. The integration of octadecane, a phase change material (PCM) with carbonaceous stabilizers ensures the material's stability during phase transitions, while MWCNTs contribute to improved thermal storage properties and EMI shielding capabilities. The research aims to develop novel composites with dual functionality for thermal storage and EMI shielding, emphasizing the role of carbon matrices and their MWCNT composites. SEM and CT microtomography analyses reveal variations in MWCNT incorporation across the matrices, influenced by surface properties and porosity. Leaching tests, infrared spectroscopy (FT-IR) and differential scanning calorimetry (DSC) confirm the composite's stability and high latent heat storage. The presence of nanotubes enhances the thermal properties of octadecane and \(\Delta\)H values almost reached their theoretical values. EMI shielding effectiveness measurements indicate that the composites show improved electric properties in the presence of MWCNTs.  
activated carbon; carbon foam; expanded graphite; multi-walled carbon nanotubes (MWCNTs); phase change materials; octadecane; thermal storage; EMI shielding effectiveness Article
# Lightweight NFC Protocol for Privacy Protection in Mobile IoT
## 2 Relative Works
### The Requirements of Mobile IoT
#### 2.1.1 Security Requirements  
Compared to a traditional RFID reader in an authentication system, NFC-enable devices make the message reading much easier. However, such devices also bring some security problems. On the one hand, it can deal with the events in real-time and undertake the process faster and more efficiently. On the other hand, although short distance communication enhances the privacy property, the mobile IoT network still leads to many security challenges.  
In an unsafe authentication system, an attacker can interact with a tag to uncover its identifier and then deduce the nature of the product it is attached to. Weaker attacks can also compromise privacy [16]. Meanwhile, some typical attacks, such as DoS attack, replay attack, forgery attack, may exist in the system.  
In a secure authentication system, the following requirements are often considered [25]:  
* Tag Anonymity: A tag's identity should be protected during the transmission on the channel.
* Prevent Replay Attacks: Even if attackers can get legitimate messages sent from the tag to the reader, the data cannot be sent repeatedly to trick the authentication server.  
Prevent Denial of Service Attacks: Even if attackers send lots of authentication messages to analyze the system, the authentication system can still provide a service.  
* Mutual Authentication: Each party in the system is able to confirm that the other parties are legitimated.  
User privacy: Even if an attacker can get legitimate information sent from the tag to the reader, the tag's identity and other private information remain confidential.
* Prevent Man in the Middle Attack: Even if attackers can sniff the data transportation in the communication channel, they cannot get any useful information after analysis.
## 2 Classification of Localization Algorithms
### Evaluation Criteria  
In this paper, we analyze and summarize typical localization algorithms of each category. Furthermore, the localization algorithms are compared from following aspects:  
* Anchor type: Most localization algorithms of UWSNs use anchor nodes to localize unknown nodes. Unfortunately, GPS cannot work well in sub-sea environment. Thus, some researchers propose self-localization algorithms, e.g., the Node Discovery and Localization Protocol (NDLP) in [8,9].  
Figure 1: Localization Algorithms Classification in UWSNs.  
* Ranging method: In UWSNs, in order to take advantage of the slow propagation speed of sound under water, range-based schemes that use ToA (Time of Arrival) and TDoA (Time Difference of Arrival) are suggested for UWSNs [10].
* Message communication: There are two kinds of message communication: silent and active. \"Silent communication\" is that unknown nodes passively listen messages from neighbor nodes and do not transmit any packets, while \"active communication\" needs unknown nodes to participate in localization message exchange. Relatively speaking, silent communication is much more energy efficient than active communication.
* Time synchronization: Time synchronization is an important technology for UWSNs. Precise time synchronization is difficult to achieve in underwater environments. Therefore, in most localization algorithms, sensor nodes are assumed to be perfectly synchronized with each other.
* Localization coverage: Maximizing sensing coverage is a fundamental requirement for UWSNs. Many researchers have been focused on the coverage issue, e.g., [11], where the goal is to find a node placement strategy with 100% sensing coverage of a 3D space, while minimizing the number of nodes required for surveillance.
* Localization time: Localization time of any localization algorithm cannot be too long. If localization process needs long time, the calculated locations are different from the real ones, since sensor nodes may move to new places.
* Localization accuracy: Localization accuracy is the most important evaluation criterion. Although some coarse-grained localization algorithms have been proposed, most applications, e.g., target tracking, require high localization accuracy.
* Computational complexity: Due to limited energy resource, computation of localization algorithms should be as simple as possible.
* Energy consumption: Any localization algorithm cannot be feasible if energy consumption is too high.
## 2 Materials and Methods
### Measurement Technique and Equipment  
Kinematic data were captured by using the OptiTrack system (6 cameras, 120 Hz). To capture the position of the right and left upper limbs (hand, forearm, and arm), head, neck, and torso, the passive markers were used and set according to the OptiTrack protocol to identify described segments of the body.  
To collect EMG data, the Noraxon MyoTrace400 system (4 channels, 1000 Hz of sampling frequency) was used. This technique is well known and widely used in assessing muscle activity [29]. The reference electrode was attached to the medial clavicular head (RS in NC) or olecranon (RS in PMC, DMD in NC, and PMC). To collect data, the Noraxon dual EMG disposable electrodes were placed according to SENIAM recommendations [30] on the properly prepared skin above four muscle bellies: long head of biceps brachii (BB, EMG1), lateral head of triceps brachii (TB, EMG2), anterior deltoid (AD, EMG3), and upper trapezius (UT, EMG4). To reduce motion artefacts, all electrodes/cables were protected by using medical tape. The commercial MyoResearchXP software (Noraxon, Scottsdale, AZ, USA) and MATLAB R2020b (MathWorks, Natick, MA, USA) were used to collect raw data, record, and process these EMG data. The processing included filtering, rectification, and smoothing by using RootMeanSquare (RMS) algorithm with a 50 ms window (this algorithm was implemented in MyoResearchXP). Due to the fact that during one visit the chosen DMD patient was not able to perform maximum voluntary contraction (MVC) without fatigue, the processed EMG data were normalized with respect to the maximum value registered during the test (reference voluntary contraction). The activity of each examined muscle was assessed by applying our own codes written in MATLAB; the EMG threshold was equal to 0.005 and electromechanical delay was equal to 50 ms. The time scale was normalized to the motion timing and described as a percentage of motion.  
To perform testing under PMC, a passive manipulator composed of four serially linked segments (the first shoulder joint, the second shoulder joint, the third shoulder joint and elbow joint) was used. All segments were fixed by low-friction pin connections allowing performing rotations (Figure 2b,d). This manipulator was manufactured from the aluminum alloy thin-walled beam and its weight was 357 g with the following mass distribution between segments: 26:16:26:32. The first shoulder joint segment was fixed to the backrest of the DMD patient's wheelchair or back of the stool used to test the RS. The second point of the elbow segment (a collar) was fixed to the wrist joint of the tested subject by using medical tape and soft foam placed between the skin and the collar. The passive manipulator dimensions were designed to maintain the working space of the upper limb of each subject from the control group and DMD patient group.
# Towards Single 2D Image-Level Self-Supervision for 3D Human Pose and Shape Estimation
## 4 Experiments  
In this section, we explain the datasets and evaluation method and then analyze the obtained results in a qualitative and quantitative manner. We also provide ablation results by varying the parameters of our framework.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Methods** & **Dataset** & **MPJPE(\(\downarrow\))** & **PA-MPJPE(\(\downarrow\))** \\ \hline _Ours (self-sup)_–\(L_{\text{real}}\)–\(L_{\text{mask}}\) & Full & 96.8 & 62.1 \\ _Ours (self-sup)_–\(L_{\text{real}}\) & Full & 95.7 & 60.3 \\ \hline _Ours (self-sup)_ & H36M & 90.4 & 55.4 \\ _Ours (self-sup)_ & Full w/o Y & 86.5 & 54.9 \\ \hline _Ours (self-sup)_ & Full & **84.2** & **54.4** \\ \hline _Ours (weakly-sup)_ & Full & 80.7 & 52.7 \\ _Ours (semi-sup)_ & Full & **65.8** & **44.9** \\ \hline \hline \end{tabular}
\end{table}
Table 5: Ablation study on Human3.6M to analyze the effectiveness of the objective functions (first 2 rows) and results of weakly-supervised and semi-supervised approaches (last 2 rows). We also conducted an ablation study depending on the different training dataset compositions: “Full” denotes the full training dataset that we described in Section 4.1. Rows 3–4 show the ablation results using different training datasets, where “H36M” and “Full w/o Y” denote the Human3.6M dataset and full datasets without the collection of wild YouTube data, respectively. We use protocol-2 for “H36M”.
# Computer-Generated Holography Methods for Data Page Reconstruction Using Phase-Only Medium
## 4 Experiments on Reconstructing Binary Data Page Images  
The data page shown in Figure 1 with an added two-level pseudo-random phase mask was used as an object of study. This format can be considered an analog to a complex ternary modulation. A single element of the data page can provide the values \(-1\), 0 or +1 of the normalized complex amplitude of the light field. For simplicity, these data pages can be registered with a digital camera sensitive to the spatial intensity distribution. This method does not allow distinguishing elements with values \(-1\) and \(+1\). However, the amplitude modulus distribution (the square root of intensity) will allow the estimation of the complex amplitude noise.  
Figure 4 shows a scheme for reconstructing the data page images using Fourier CGH. A Cobolt Samba (200 mW, 532 nm) laser was used as a light source. The coherent beam was collimated using lenses L1 and L2 and aperture M. The Fourier CGH was displayed onto phase LCoS SLM HoloEye PLUTO-2 (1920 \(\times\) 1080 pixels; pixel size is 8 \(\times\) 8 \(\upmu\)m). Fourier CGH were calculated using bipolar intensity and double-phase coding methods. The modulation depth of the SLM was equal to 2\(\upmu\). The reconstructed data page was registered by Flare 48 M digital camera (7920 \(\times\) 6004 pixels; pixel size is 4.6 \(\times\) 4.6 \(\upmu\)m) in the Fourier plane. The beam splitter BS allows for directing both the collimated beam into the SLM plane and the reflected beam from the SLM to the digital camera plane. An L3 lens (40 mm focal length) coupled the registration plane and the SLM far diffraction zone. The registered images of the data page were digitally processed. Processing algorithms included linearization of a sinc-shaped envelope caused by the square shape of SLM pixels. The width of the main maximum of the sinc envelope was estimated as 2\(\lambda F/\Delta\) where \(\lambda\) is the wavelength, \(F\) is the focal length of the Fourier objective, and \(\Delta\) is pixel linear size. The informative area of the data page image was cropped, geometrically corrected, and spatially sampled. Examples of reconstructed light field intensity distributions registered in the experiments and data page enlarged images are shown in Figure 5. Both methods of Fourier CGH synthesis were used.  
Figure 4: The experimental scheme for reconstructing and registering binary data page images using phase Fourier CGH: laser, lenses L1, L2, and L3, beam splitter BS, spatial light modulator SLM, and digital camera.
# Research Status and Progress of All-Position Narrow-Gap GMAW for Pipelines
## 3 Methods to Improve Weld Bead Formation in Narrow-Gap GMAW
### Improvement of Weld Formation by Combined Laser and Arc Welding Methods
The interaction between the laser and the arc shows that the presence of the laser significantly enhances the degree of ionization of the arc plasma, reduces the resistance of the arc channel, and increases the density of free electrons and charged particles. These effects, in turn, promotes the stability and conductivity of the arc plasma. However, full-position welding still faces many challenges, especially in the overhead welding position where the effect of gravity is significant. Composite heat sources can reduce the volume of the molten pool, effectively minimizing the impact of gravity and thus inhibiting the formation of concavities on the backside and hump defects on the front side of overhead welding joints. [PERSON] et al. [70] used a laser-MAG composite heat source to study the overhead welding position of 5 mm thick E36 high-strength steel. The results showed that this composite heat source could significantly improve the stability of the molten pool, ultimately achieving a well-formed overhead butt welding joint. [PERSON] et al. [71] conducted a study on the force analysis of the molten pool in all-position welding of 16 mm-thick X65 and 20 mm-thick X80 pipeline steels using low-energy laser-arc hybrid welding technology. The study found that heat input is the primary factor influencing the formation of internal concavity defects in root-pass welding. Research indicates that an increase in heat input leads to an enlargement of the molten pool volume, thereby increasing the gravitational force on the molten pool and enhancing its fluidity, which exacerbates the internal concavity defects in root pass welding. These findings highlight the importance of controlling heat input to manage the stability and quality of the molten pool in all-position welding processes.
## 4 Results and Validation
### Quality Assessment and Discussion
Further investigations also showed that there are no clear dependencies between surface area, respectively final correlation coefficients \(R^{2}\) with other parameters such as lake shore, climate zone, annual cloud coverage, or annual rainfall. Finally, one can conclude that this new approach can be used for nearly all lakes and reservoirs as they are large enough to be observed successfully by Landsat or Sentinel-2.