esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Simulation of IoT Networks
### Requirements  
From the various works on the subject presented in Section 2, the most prevailing requirements for a simulator of the IoT have been gathered. Additionally, some requirements have arisen from the involvement of the Chair Design of Cyber-physical Systems with the VICINITY project. Those requirements are examined in the following:  
* The possibility to simulate thousands of interconnected devices [8]: Depending on the scenario, it can be necessary to simulate thousands of entities that partake in the IoT. While for example in the simulation of a smart home, there are only a relatively small few devices that need to be simulated, during the simulation of a new area wide service, the number of simulated entities has to rise rather quickly, to provide useful data.
* The ability to run in (almost) real-time for proactive approaches: While high detailed simulation runs can provide insight into the fine-grained processes within the interplay of different devices and technologies, with the sheer size of Internet of Things scenarios in the context of a smart city, these simulation runs tend to be too slow in order to enable proactive approaches. The framework under development should provide some techniques to enable these approaches.
* Hardware in the loop capabilities: To analyze the behavior of prototypes, it would be most beneficial if the developed simulation framework would provide hardware in the loop simulation capabilities or provide the interfaces to enable simple integration of already existing approaches.
* Fig scalability of scenarios: Somehow connected to the first two requirements is the high scalability of scenarios. The simulation framework's real-time capabilities should not be lost, when thousands of entities that communicate with each other need to be simulated on a large scale.
* The possibility to employ parallel and distributed simulations: Based on the observations in [10], the developed framework should provide either out of the box parallel and distributed capabilities, or at least be built in a way that facilitates later adaption of these principles to further support the aforementioned requirements.  
* Fast model development for fast employment in use cases: To be employed in the VICINITY project, the developed framework should offer possibilities that support rapid model development and possibly even the use of functional mock-up interfaces.
* The possibility to unify multiple heterogeneous technologies on all levels of IoT: The simulator should support modeling the prevalent technologies of the respective domain and enable the interplay between them.
* The possibility to integrate further domain specific simulators into the framework: This last requirement pretty much speaks for itself. If during the deployment of the developed simulation framework the necessity of integrating further domain specific simulators arises, it should be doable with little effort.
# Comparative Analysis of Audio Features for Unsupervised Speaker Change Detection
## 4 Experiments
### Experimental Setup  
To conduct a fair and comparable experiments, we define the following points: (i) choose 16 kHz as the main sample rate of audios; (ii) set parameter of hop length to 512 and n_fft set to 2048 for extracting the audio feature from raw signals. Each meeting was segmented to short 1s audio, before extracting the features.  
Since the true labels of speaker change points are given as timestamps on the raw audio signal, such as beginning time, we match this beginning times for obtain the labels for each segment. The test set was used solely for final evaluation, guaranteeing that the chosen thresholds are fair, as they are not influenced by direct tuning on the test data. Validation set was used for threshold optimization for KL divergence with GMM. For simplicity, in the experiments, we refer to the method of KL-divergence with GMM as KL-GMM. BIC-GMM models are simplified to BIC.
## 4 Experiment and Analysis
### Simulation Environment
Nevertheless, its advantage lies in resource consumption, as it operates with lightweight execution. For the second phase, in E2E IIoT networks, the primary processes on SDN/NFV MANO are addressed in the simulation using the configured testbed with TOSCA language [46; 47]. The descriptors are programmable, following the outputs of the MLSTM module. In this stage, the final orchestration between the MLSTM-CP outputs and controllers takes the form of the proposed MLSTM-CEFL. The parameter setup is detailed in Table 3, and the system is executed across three consecutive congestion states for 250 s, including non-congestion, normal congestion, and heavy congestion scenarios. Traffic generation occurs for each congestion state evaluation. For each state transition from non-congestion to heavy congestion, queueing algorithms within each path's gateway buffer are observed. Fair-queueing-based pacing is employed in this study. To evaluate the proposed policy, metrics assessing the overall control QoS performance are analyzed by conducting simulations comparing the proposed MLSTM-CEFL with other baseline policies. In the final phase, after orchestrating the proposed MLSTM-CEFL, EFL communications are executed for the development of the final learning model using TensorFlow \begin{table}
\begin{tabular}{c c} \hline \hline
**Purpose/Platform** & **Specification** \\ \hline Hosting infrastructure & Intel(R) Xeon(R) Silver 4280 CPU @ 2.10 GHz, 128 GB, NVIDIA Quadro RTX 4000 GPU \\ \hline DL platform & Python (TensorFlow and Keras) \\ \hline FL platform & TensorFlow Federated (MNIST dataset) \\ \hline Number of models & 3 (CLSTM-CFL, MLSTM-CCFL, and MLSTM-CEFL) \\ \hline Input shape & (Number of time steps, number of features) \\ \hline Dropout rate & 0.2 \\ \hline Recurrent dropout rate & 0.1 \\ \hline Batch sizes & 512 \\ \hline Dense units & 4 times of MLSTM units \\ \hline MLSTM units & 128 \\ \hline Number of epochs (training, testing) & (1000, 125) \\ \hline Optimizer & Adam \\ \hline Loss & Mean Squared Error \\ \hline Activation function & Sigmoid and Tanh \\ \hline Learning rate & 0.001 \\ \hline Validation split & 0.2 \\ \hline Simulation times for capturing QoS & 250 s (Fair-queueing-based pacing) \\ \hline SDN/NFV-UE, control, and interfaces & Mininet+MiniNFV, RESTful API \\ \hline Number of participants, edge aggregator, & (500, 5, 1) \\ and server & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Primary parameter configuration for our experiment setup. Federated with data contributions from the MNIST handwritten digits dataset. The adapted configuration of the EFL framework is rooted in the differentiation of drop ratios from the second phase, aimed at constraining the count of participants and model updates during specific congestion state intervals. The performance evaluation of this phase refers to accuracy and loss for comparative analysis.
# Perspectives in Liquid-Crystal-Aided Nanotechnology and Nanoscience
## 2 Modification of Physical Properties of LC Materials by Nanodopants
reported a 30-50% reduction of the threshold voltage and switching time in partially reduced graphene oxide (PRGO)-doped nematic LCs and a 20-25% increment of the spontaneous polarization in PRGO-doped ferroelectric LCs [228]. [PERSON] et al. found that the dielectric anisotropy of nematic LC (6 CB) would be increased with an increasing concentration of GO [115]. In a very recent investigation, [PERSON] et al. systematically investigated the physical properties of nematic LC (5 CB) dispersed with GO at a wide concentration range from 0.05 to 0.3 wt %. They observed a decrease in the threshold  
Figure 6: (**a**) Transmission voltage function of the sample device with single-walled carbon nanotube doping. (**b**) Relative permittivities (transverse (\(\varepsilon_{\perp}\)’) and longitudinal (\(\varepsilon_{\parallel}\)’) components) with temperature for pure and dispersed samples. Reproduced with permission from [215]. Copyright (2018) ELSEVIER. voltage in electro-optic and dielectric spectroscopy measurements. This was attributed to the disrupted homogeneous alignment induced by the strong \(\pi\)-\(\pi\) stacking effect between the graphene oxide and the LC molecules' benzene rings. In addition, they presented the dependence of the first-order phase transition temperature, elastic constants, dielectric permittivity and switching duration on the GO doping concentration [229]. Additionally, except for fullerenes, CNTs and GOs, modified physical properties of LC hosts can also arise from other carbon nanoparticles including carbon dots [230], detonation nanodiamonds [231] and graphene quantum dots [232]. A small number of added nanomaterials in LCs can produce composite materials with modified physical properties and improved electro-optical performance--for example, a shorter response time, a higher birefringence, a lower threshold voltage, a larger dielectric anisotropy, better contrast, enhanced nonlinear-optical properties, etc., which has great potential for the design of next-generation LC equipment including LC displays, tunable LC lasers and filters, electro-optical switchers and shutters, nonlinear-optical valves for photonic information processing systems, telecommunication and many other aspects of modern technology. At present, though, experimental results are still inconclusive, lacking reproducibility. Thus, further research is needed in the near future, both experimental as well as theoretical, to identify the main underlying aspects that lead to the modification of liquid-crystal-based composite materials' properties, as well as the causes for the range of behaviours observed. Developing a good understanding of the latter will clear the way for an optimized development of novel materials for improved future technologies.
## 4 Evaluation and Results
### Results
#### 4.2.3 QoE  
A resource block is a scarce resource and the basic data unit in LTE and 5G cellular networks. In Orthogonal Frequency Division Multiple Access (OFDMA), an eNB sends the data to a User Equipment (UE) encapsulated within multiple frames. An LTE frame is composed of various symbols or RBs. The number of RBs within a frame depends on the Channel Quality Indicator (CQI) and the Modulation and Coding Scheme (MCS) of the UE. The better the CQI/MCS, the lower the number of RBs that are required to transmit a block of data increasing the network efficiency at the access layer. If the CQI of an UE is bad, the eNB needs to assign a higher number of RBs to the UE to maintain a favorable QoE for the users. The usage of RBs and the achieved QoE are highly dependable on each other. Therefore, during our simulations, we conducted extensive experiments to specifically calculate the number of RBs assigned to a user while maintaining the optimum QoE. Figure 5 shows that, when the unicast mode is used, the collective QoE is 0.597143. On the other hand, QoE increases to a perfect 1 when the multicast transmission is exploited. These numbers show that the collective QoE of the users can be increased in the VNF based multicast mode.  
Figure 4: Bandwidth consumption at backhaul link unicast vs. multicast.  
Figure 3: Data fetched from CDN.
## 4 Conclusions  
Compared to the longitudinal EO CEP shifter, the major advantages of the new configuration described here are the possibility to work without induced group delay and the lower static electric field needed for a given CEP shift. In addition, the system can also be used to control a group delay without shifting the CEP (PGD generator). The combination of two such systems should allow us to control separately the CEP and the group delay at a very high speed. The induced GDD can be estimated from table 1 and can be neglected, provided that the condition, \(\Delta\phi^{(2)}\leq r_{p}^{2}\) / 10, is verified. This shows that corrections can be made, even on very short pulses, the most important point being the ability of the system to correct the CEP at a very high speed, which can very probably be extended to the 100 kHz range.  
The EO phase shifter cannot be used to stabilize the CEP of the optical pulse train outside the mode-locked (ML) oscillator (see Appendix V). This new set-up should be well suited to stabilizing the CEP of the amplified pulses of a chirped pulse amplification (CPA) laser system seeded by a CEP  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline  & \multicolumn{2}{c}{**EO CEP Shifter**} & \multicolumn{2}{c}{**Dazzler**} & \multicolumn{2}{c}{**Grating compressor**} & \multicolumn{2}{c}{**Glass wedges**} & \multicolumn{2}{c}{**4f + LCD**} & \multicolumn{2}{c}{**Lens + rotating grating**} \\ \cline{2-7}  & **Longitudinal** & **Prism pair** & \multicolumn{2}{c}{_Double pass_} & & & \\  & **single pass** & **double pass** & & & & & \\ \hline \(\Delta\tau_{g}\) (fs) & –5.78 & 0 & 0 & 7.9 & 43.7 & 0 & 0 \\ \(\Delta\Phi^{(2)}\) (fs\({}^{2}\)) & -2 & 2.6 & 0 & 1.7 & 1 & 0 & 0 \\ \(E\) (kV/cm) & 2.86 & –0.43 & - & - & - & - & - \\
**Displacement** & - & - & - & 0.54 & - & - & - \\
**(\(\mu\)m)** & & & & & & & \\
**Bandwidth** & MHz & MHz & \(<\)30 kHz & \(\sim\)10–100 Hz & \(\sim\)1–10 Hz & \(\sim\)10–100 Hz & \(\sim\)1 kHz \\ \hline \end{tabular}
\end{table}
Table 1: Comparison between different CEP shifters.  
stabilized mode locked oscillator (slow feedback loop), as was demonstrated in the case of the longitudinal EO shifter [19].  
The authors strongly believe that this type of system could be of interest for different applications, like coherent control, polarization shaping, stabilization of interferometric systems, coherent combination of fiber amplifiers and frequency synthesizers.  
This work was done within the framework of the IMPULSE laboratory, which is a joint R & D laboratory associating CEA Saclay and Amplitude Technologies.
## 4 Discussion
### Activities
#### 4.1.9 Antioxidant Activity  
An extensive body of literature discusses the topic of antioxidant activity of plants belonging to the Apiaceae and Rosaceae families. Responsible for these properties are compounds such as flavonoids (**1-13**), anthocyanins (**14-15**), and other polyphenols [178].  
[PERSON] and co-workers [63] reported that active compounds obtained from _Coriandrum sativum_ seeds (Aplaceae) show significant antioxidant activity tested by DPPH method, namely the following: coriander oil IC\({}_{50}\): 67.2 \(\pm\) 18.2 \(\upmu\)g/mL; linalool (**29**) IC\({}_{50}\): 94.0 \(\pm\) 17.1 \(\upmu\)g/mL; fennel oil IC\({}_{50}\): 83.6 \(\pm\) 17.1 \(\upmu\)g/mL; and anethole (**30**) IC\({}_{50}\): 111.1 \(\pm\) 13.5 \(\upmu\)g/mL. What is more, [PERSON] et al. [72] established that _Daucus carota_ possesses antioxidant activity in vivo (male Wistar rats). The researchers examined the effects of a 3-week supplementation of rat diets with carrot (15% dry matter) on antioxidant status. The consumption of carrots improved antioxidant status significantly. It led to a notable decrease in urinary excretion of thiobarbituric acid reactive substances (TBARS), reduced TBARS levels in the heart, increased plasma levels of vitamin E, and showed a tendency to enhance the ferric reducing ability of plasma (FRAP) compared to the control group. The carrot-enriched diet provided carotenoid antioxidants: 5.1 mg \(\upbeta\)-carotene, 1.6 mg \(\upalpha\)-carotene, and 0.25 mg lutein per 100 g of diet. Methanol extract obtained from _Petroselinum crispum_ seeds revealed antioxidant activity in vivo (male albino rats) in a study conducted by [PERSON] and co-workers [80]. The authors investigated the antioxidant and hypolipidemic effects of supplementing the diet of hypercholesterolmale rats with a 20 % (\(w/w\)) extract of parsley seeds for 8 weeks, potentially providing hepatocardioprotection.  
_Crataegus oxvacantha_ fruits (ethanol extract, 0.5 mL/100 g orally for 30 days) showed antioxidant ability through increasing activities of antioxidant enzymes in vivo (male albino Wistar) [103]. _Fragaria ananassa_ fruits demonstrate antioxidant activity via reducing the MDA level in vivo (randomized, double-blind, placebo-controlled trial on diabetic patients treated with the plant or placebo) [137].  
Nevertheless, the antioxidant effect of plants from the Rosaceae and Apiaceae families is a very extensive topic and definitely requires a separate publication.
# Anomaly Detection in Microservice-Based Systems
## 2 Data and Materials
### Installation and Setup  
Figure 1 illustrates the general design used to create the dataset.  
The dataset used for this study was built from the open-source benchmark of a microservices system, Sock-shop [4]. The installation was performed on two VMs. Each VM has 7 CPUs, a 300 Gigabyte (GB) disk, and 14 GB memory. The Sock-shop system is a microservices-structured application that is the user-facing part of an online store that sells socks. It is a polyglot system, characteristic of microservices systems, using technologies, for example, Spring Boot ([[https://spring.io/](https://spring.io/)]([https://spring.io/](https://spring.io/))(accessed on 1 May 2023)), Golang ([[https://go.dev/doc/](https://go.dev/doc/)]([https://go.dev/doc/](https://go.dev/doc/))(accessed on 1 May 2023)), and Node.js ([[https://nodejs.org/](https://nodejs.org/)]([https://nodejs.org/](https://nodejs.org/))(accessed on 1 May 2023)), and is packaged in Docker containers. It comprises seven services: Frontend, Order, Cart, Payment, User, Catalogue, and Shipping. All services communicate using REST over HTTP. Besides REST, the Sock-shop system also includes a queue for asynchronous communication in the Shipping service.  
The system was deployed in a Kubernetes ([[https://kubernetes.io/](https://kubernetes.io/)]([https://kubernetes.io/](https://kubernetes.io/))(accessed on 1 May 2023)) environment. Kubernetes is an open-source system that helps automate, scale, and manage containerized applications, such as Sock-shop. In the case of this study, a Kubernetes cluster was set up with two servers, the two available VMs, described above.  
Observability in microservices-based systems is understanding and diagnosing system behavior and performance by collecting, analyzing, and visualizing relevant system data. It typically involves monitoring the interactions between different services, the system infrastructure, and user behavior to extract valuable information for any issues that may arise [51]. In the case of this study, technologies were used for this purpose, in this case, Grafana and Prometheus, which collect metric data regarding the behaviors of the different services.
## 5 Experimental Verification
### Comparasion Results with the Published Literatures  
Table 2 shows the comparison results between the proposed method and the traditional ways studied in [13; 14; 15; 16; 17; 18]. Since the power transfer and data transfer functions of the proposed method are decoupled, the SNR is very high, so as the data transfer rate can reach 560 kbps. It should be noted that a 25 W prototype was set up for demonstration. This method could be used in high power systems due to its high SNR characteristics. Moreover, the data transfer method is especially suitable to monitor the load status in WPT applications such as biomedical implants and robot charging.
# A Hybrid Bio-Optical Transformation for Satellite Bathymetry Modeling Using Sentinel-2 Imagery
## 3 Results
### Satellite Derived Bathymetry (SDB) Results
The HBT model calculated bathymetry down to 30 m, by exhibiting a better correlation degree (R\({}^{2}\) = 0.96) and smaller error (RMSE = 2.0 m) compared to the model developed by [PERSON] et al. (2003) (R\({}^{2}\) = 0.903, RMSE = 5.4 m) (Figure 10). The ratio transform presents a correlation only down to 20 m, whereas in deeper waters it deviates considerably from the chart measurements (RMSE > 7 m). Figure 10: Bathymetric model evaluation of HBT model (left) and the model of [PERSON] et al. (right). Figure 9: Final bathymetric model (right) and the relevant nautical chart (left).
# Experimentation Environments for Data Center Routing Protocols: A Comprehensive Review
## 3 Experimentation Environments
### Traffic Analysis Tools  
Traffic analyzers (also known as packet sniffers) are specific software tools that intercept and log network traffic traversing a network link using packet capturing. The captured packets can then be analyzed by decoding their raw data and visualized via displaying various fields to interpret the content, using, for example, the Wireshark [54] graphical tool or the well-known command-line packet analyzer Tcpdump [55]. On their default behavior, these tools use the pcap library to capture traffic from the first available network interface and display a summary line on the standard output for each received packet.  
Wireshark functionalities are also available in a command-line tool called _TShark_[56]. As well as Wireshark, _TShark_ is a network protocol analyzer. It allows for capturing packet data from a live network or read packets from a previously saved capture file. _TShark_ works very similar to Tcpdump, being the main difference in the variety of options supported on its default behavior. One of the most notable advantages of _TShark_ over Tcpdump is the possibility of using Wireshark dissectors for live filtering. The dissection of a packet is composed of as many dissectors as protocols involved, e.g., an HTTP packet captured in a classical residential network may involve one dissector per layer: Ethernet, IP, TCP, and HTTP. Each dissector decodes its part of the protocol and then hands off decoding to subsequent dissectors for an encapsulated protocol. Every dissection starts with the Frame dissector, which dissects the details of the capture file itself (e.g., timestamps). After that, the process goes on like the HTTP packet dissection example.  
Dissectors can either be built-in into Wireshark or written as a self-registering plugin (a shared library or DLL). This functionality is key for the customization of the packet dissections, allowing, for example, the incorporation of dissectors for protocols under development. Moreover, _Tshark_ and all its functionalities can be used with Python through a wrapper called Pyshark [57].  
A comprehensive guide on practical usage of Wireshark and Tcpdump, including a discussion of traffic formats and other tools, can be found in [58; 59].