esa-sceva/satcom-chunk-collection huggingface dataset:
# Distributed Ledger Technologies and Their Applications: A Review
## 2 Distributed Ledger Technology
### Tangle
#### 2.2.2. Advantage of Tangle  
The Tangle network has higher scalability than traditional Blockchains since all users validate transactions to request a transaction, and as the network grows the number of validators also increases. The other advantage of IOTA Tangle is that there is no fee for any transaction, and the nature of IoT devices requires a high number of micro transactions that would cost too much on a Blockchain network, but not on IOTA [87]. Moreover, IoTA is built for devices with low computing power capability since the consensus algorithm is much lighter than the ones that use PoW in Blockchain.
# Recognition and Location Algorithm for Pallets in Warehouses Using RGB-D Sensor
## 5 Discussion  
### Comparative Performance Analysis  
The template matching method provided by OpenCV 3.0 has a strict requirement that the template must be similar to the target in the image; pallet images change with angle changes. In addition, those matching methods are designed for gray or color images, not a label matrix. This method shows worse performance when the pallet angle is larger than \(\pm 15^{\circ}\). Occasionally, the matching result is easily affected by environmental interference.  
In contrast, the proposed algorithm compresses the category matrix and template to reduce the environment effect, and the matching method is a probability calculation that is more suitable for a label matrix. Consequently, the proposed algorithm was shown to perform better in the face of pallet and environmental changes.  
Moreover, the grid compression matching algorithm has many advantages. For instance, the label pallet template has more rich information--including spatial relationships among goods, the ground, pallet feet, and pallet holes--than that of an individual pallet. Meanwhile, it is easy to create a template other than a gray or color template because the labeled template is unchanged under different illumination conditions and only has four labels. The labeled template algorithm, with its strong robustness and implementation, could be applied to many object recognition problems.
# Controllable Image Captioning with Feature Refinement and Multilayer Fusion
## 4 Experiments
### Comparative Experiment  
Table 3 shows the performance comparison between the current state-of-the-art controllable and uncontrollable models with the proposed method. In this comparison, we use  
\begin{table}
\begin{tabular}{l l l l l l l l l l l l l l l l} \hline \hline
**Dataset** & **\#** & **SCA** & **GSA** & **Gupta** & **FCD** & **B64** & **M** & **R** & **C** & **S** & **NW** & **D-1** & **D-2** & **s-C** \\ \hline  & 1 & ✓ & & & & & 24.17 & 25.27 & 51.39 & 215.69 & 43.77 & 71.07 & 48.10 & 74.24 & 70.44 \\ MSCOCO & 2 & ✓ & & & & ✓ & 24.35 & 25.45 & 51.52 & 217.79 & 44.08 & 71.16 & 48.38 & 74.53 & 70.55 \\ Entities & 3 & ✓ & & & ✓ & ✓ & **24.81** & 25.61 & **51.80** & 22.32 & 44.14 & 71.48 & 48.43 & 74.55 & 68.03 \\  & 4 & ✓ & ✓ & ✓ & ✓ & 24.67 & **25.71** & 57.35 & **22.23** & **44.41** & **71.51** & **48.95** & **75.06** & **70.57** \\ \hline  & 5 & ✓ & & & & & 14.11 & 18.29 & 39.70 & 110.15 & 29.72 & 61.90 & 41.64 & 68.33 & 86.12 \\ Flickr30k & 6 & ✓ & & & & & 14.10 & 18.43 & 39.73 & 112.72 & 29.76 & 62.36 & 43.40 & 70.39 & 87.25 \\ Entities & 7 & ✓ & & & ✓ & 13.98 & 18.59 & 39.70 & 114.50 & 29.99 & 62.31 & 43.47 & 70.59 & 87.10 \\  & 8 & ✓ & ✓ & ✓ & ✓ & **14.48** & **18.63** & **40.12** & **17.28** & **30.69** & **62.93** & **44.02** & **71.22** & **87.21** \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of variants for proposed modules in decoder on MSCOCO Entities. (✓) indicates “used” (SCA:semantic content attention; GSA:graph structure attention; gupda:graph updating; FCD: Fusion Constraint Decode). Bold for the best.  
Figure 3: Examples of captions generated by various ablation models. GT represents one of the corresponding ground truth sentences. SCA denotes the model has MR-WGCN, MA, and RD modules, but the decoder only has semantic content attention (SCA). SCA+FCD, SCA+FCD+gupda, and SCA+FCD+gupda+GSA is to add FCD, gupda, GSA modules into SCA step by step.  
the same MSCOCO Entities dataset set as Refs. [11; 16; 35]. Compared with other controllable image caption models, IANR was higher than SOAT in METEOR, CIDEr, and SPICE by 0.64, 50.58, and 4.91. All these enhancements show that IANR can significantly improve the ability to describe objects and relationships.
## 2 Materials and Methods
### Data Processing  
It is necessary to conduct the study using images at regular intervals starting from the forest fire date; however, multispectral images could not be acquired at precise intervals  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Satellite** & **Sensor Type** & **Acquisition Date** & **Resolution** & **Properties** \\ \hline Sentinel-2A & Multispectral & Pre-event & 26 March 2019 & \\  & Post-event & 8 August 2019 & 10, 20 m & B2, B4, B8, B12 \\ Sentinel-2B & Multispectral & Post-event & 20 April 2019 & \\ \hline \end{tabular}
\end{table}
Table 1: Satellite details.  
Figure 1: Study area (37.59215114967223, 129.0474188183951).  
because they are affected by weather conditions, such as clouds. The analysis should be conducted through continuous image acquisition to extract vegetation regeneration areas, but no image has been acquired since September due to reclamation of the forest fire-hit areas in the Republic of Korea.  
Images of the forests were compared to determine the degree of vegetation regeneration after the forest fire. The vegetation index NDVI was used for the comparison, but there is a lower accuracy limit when the forest is thick due to distortion, such as scattering by light. Therefore, the EVI and SAVI indices were further extracted to identify the final vegetative regeneration site to ensure more accurate reproduction. Figure 2 presents a flowchart of the study design. In the study flowchart, difference images refer to calculating the difference between two images.
# Towards a Near-Real-Time Protocol Tunneling Detector Based on Machine Learning Techniques +
## 3 Background
### Support Vector Machines  
The original formulation of support vector machines [31] (SVMs) is related to the resolution of supervised tasks with the objective of finding a maximum margin hyperplane that separates two or more classes of observations. In the last years, one-class SVMs have also been shown to represent a suitable choice in the context of anomaly and outlier detection [32]. It is defined as a boundary-based anomaly detection method, which modifies the original SVM approach by extending it in order to deal with unlabeled data. Like traditional SVMs, one-class SVMs can also benefit from the so called kernel trick when extended to non-linearly transformed spaces, by defining an appropriate scalar product in the feature space.
# Numerical Analysis of a Spiral Tube Damping Busbar to Suppress VFTO in 1000 kV GIS
###### Abstract  
Gas insulated substations (GISs) are broadly used for transmission and distribution in electric power networks. Very fast transient overvoltage (VFTO) caused by SF\({}_{6}\) discharge during switching operations in a GIS may threaten the insulation of electrical equipment. In this paper, a novel VFTO suppression method with great prospects in engineering, called the spiral tube damping busbar, is proposed. The suppressing mechanism of the new method is analyzed. The structure and the design characteristics of the damping busbar are introduced as well. Moreover, a calculation method for the self-inductance of the damping busbar at high frequency is presented. According to the structural characteristics of the damping busbar, the inductance effect on suppressing VFTO is analyzed. A further improvement in damping VFTO is investigated by designing a spiral litz coil connected in series with the busbar, which increases the damping effect. The simulation results show that the improved damping busbar has a significant suppressing effect on the amplitude and the frequency of VFTO.  
VFTO suppression; GIS; high-frequency inductance calculation; damping busbar Article
## 2 Simulation of Plasma Sheath Fluid Model
### Fluid Dynamics Model  
We carry out a numerical simulation with the basic RAM-C II model in this research to investigate the interaction of EM waves with the hypersonic vehicle under HPM irradiation. In 1960, the National Aeronautics and Space Administration (NASA) embarked on a research effort to investigate the subject of communication blackout, and the RAM-C II was the vehicle. The RAM-C II model's construction is shown in Figure 1a. The head of the RAM-C II model is a nose cap with a radius of R = 0.15 m, a half-angle of \(\alpha\) = 9 deg, a cone length of L = 1.275 m, and a tail width of W = 0.67 m.  
The flight status of the vehicle in this paper is a flight test at 71 km altitude [30], the speed of the vehicle is 7650 m/s, the surrounding area temperature is 216 K, the pressure is 4.764 Pa, and the air density is \(7.68\times 10^{-5}\) kg/m\({}^{3}\). The wall temperature of the vehicle is 1500 K, and it is considered to be a non-catalytic wall. In addition, the free flow air is composed of 79% N\({}_{2}\) and 21% O\({}_{2}\). To solve the N-S equations, the finite volume method (FVM) is utilized [21; 31], which is based on the fundamental condition of physical quantity conservation and creates the discrete equation by discretizing the finite sub-region in fluid motion with integral discretization.  
This paper adopts the chemical kinetic model of the 7-component (O\({}_{2}\), N\({}_{2}\), O, N, NO, NO\({}^{+}\), and e\({}^{-}\)), 7-reaction model proposed by [PERSON] [26]. In 1990, [PERSON] proposed an 11-component, 20-reaction model for chemical reactions in air. Among them, at lower Mach numbers (Ma < 9), less ionization occurs in the air, and the ion content is negligible when only a 5-component (O\({}_{2}\), N\({}_{2}\), O, N, NO) model needs to be considered. When in a hypersonic non-equilibrium flow, the high-temperature environment around the vehicle causes the air molecules internal energy excitation and ionization reaction. At this time, the chemical reaction model of the 7-component or 11-component model (O\({}_{2}\), N\({}_{2}\), O, N, NO, O\({}_{2}^{+}\), N\({}_{2}^{+}\), O\({}^{+}\), N\({}^{+}\), NO\({}^{+}\), e\({}^{-}\)) should be selected.  
According to the actual simulation results and the calculation results in refs. [18; 32], the results of the electron density calculated by using the chemical model with the 7-component model are in good agreement with the NASA experimental data. Therefore, the 7-component chemical model is used to simulate the fluid of the plasma sheath with the RAM-C II model in this paper. Since the flight environment simulated is a thermodynamic and chemical non-equilibrium state, in the thermodynamic non-equilibrium state, the dual temperature model is used. The non-equilibrium states of molecular advection, rotation, and vibration are included in the dual-temperature model, so this article will not consider them separately.
# Flavour Generation during Lactic Acid Fermentation of Brassica Vegetables--Literature Review
## 6 Changes in Flavour during the Fermentation of _Brassica_ Vegetables
### Lipid Metabolism  
Although Brassica vegetables are not a rich source of lipids (except the oil crops such as rapeseed and amelina), the products of their degradation during fermentation contribute to the aroma of fermented vegetables. Free fatty acids are precursors of esters, methyl ketones, aldehydes, secondary alcohols and lactones. The majority of LAB contain intracellular esterases [68], and thus they cannot hydrolyse lipids until they are released from the lysed cell. Esterases also have the ability to directly synthesize esters from glycerides and alcohols in alcoholysis occurring in an aqueous medium [25; 50]. For instance, spontaneously fermented sauerkraut contains a higher content of ethyl octanoate, an ester derived from acrylic acid (C8:0), compared to the commercial product [54; 69]. The authors explained that the formation of fatty acid-derived esters is highly dependent on the LAB used for fermentation. Many esters found in fermented Brassica vegetables possess pleasant fruity notes [70]. The compounds responsible for the green (some of them cabbage) aroma, such as 1-penten-3-ol, (Z)-3-hexenol, hexanol, and 1-octen-3-ol, can be formed during enzymatic oxidation of linoleic and linolenic acids and are commonly detected in fruits and vegetables, which were crushed or cut [71].
## 3 Results
### Estimation of Battery's End-of-life  
The SOC estimation for the collection scenario was the first step in estimating the change in the SOH with the number of charge/discharge cycles. The value of the DOD reached by the battery pack, at each cycle, is linked to the ageing of the KiBaM parameters and, therefore, to the deterioration of the performance of the battery pack as the number of cycles increases.  
Figure 18: The battery pack SOC trend during a collection scenario.  
The rate of deterioration of the battery pack performance was evaluated by the KiBaM, proposed in literature [42] for a comparable DOD at each cycle. The changes in both k and c parameters are responsible for the ageing of the battery pack. Equations (2) and (3) were run for 3000 cycles, while both the values of parameters k and c were decreased with the number of cycles. Simulation software, such as Polysun, provides tables with values of k and c for lithium battery cells [43]; furthermore, the values of the KiBaM compatible with lithium cells can be widely found in the literature [30; 42; 44; 45]. Figure 19 shows the SOH estimate obtained by the simulation.  
Figure 19 shows that 80% of the SOH is reached after about 1500 cycles. This result is in accordance with that reported in [33] for the same DOD of the battery pack, for each discharge cycle.
## 4 Experiments and Results  
### Filtered Audio and Features  
Acoustic features extracted from raw data at intervals of 15 min during the entire cycle showed a considerable deviation among the samples of the same day, and some of these samples are very noisy due to the farmer management routine practices and the noise of the machinery previously studied in [35]. Two filters are applied to the data for noise reduction.  
An automatic filter based in a threshold of the parameter Zero Crossing Rate (ZCR) has been implemented to discriminate audio samples containing machinery sounds. Figure 3a shows the spectrum, ZCR and temporal waveform of an audio file with external noise where it is clear identified the machinery spectrum pattern, with energy in almost all frequencies and a ZCR superior to 0.10. Figure 3b shows post-filtering audio data.  
Acoustical features obtained from each filtered audio file are still too noisy to observe tendencies. Some filters selected from the Python Library [44] were tested to find the one that could reduce wrong values of features produced by management practices noise in order to obtain more invariant descriptors of bird's vocalisations between each day and each cycle.  
The optimal feature filter considered for this study is the one that achieves the minimum Euclidean pitch distance [45] with respect to the same moment of two cycles of the same farm. Having three cycles, the distance is calculated as the sum of distances, as described in the formula (1). According to the Table 1, the minimum distance is obtained by applying the exponential filter that smoothes time series data using the exponential window function.  
\[Distance=\sqrt{\sum_{i=1}^{N}(P_{AAi}-P_{ABi})^{2}}+\sqrt{\sum_{i=1}^{N}(P_{ ABi}-P_{ACi})^{2}}+\sqrt{\sum_{i=1}^{N}(P_{AAi}-P_{ACi})^{2}} \tag{1}\]  
Formula (1) calculates the sum of euclidean distance between three cycles of farm \(A\) where \(P\) is the filtered pitch value of the corresponding instance \(i\) of cycle \(AA\), \(AB\) or \(AC\) indicated as a sub index, and \(N\) is the length of P vector.
## 4 Measurements Validation
### Measured Broadside Radiation Pattern  
To obtain the broadside radiation pattern, the individual patch antenna elements (A\({}_{1}\), A\({}_{2}\), A\({}_{3}\) and A\({}_{4}\) in Figure 13c) in the \(1\times 4\) phased array must be excited with the same phases. Therefore, the four patches in Figure 13 are equally excited with the unit cell P-CRLH phase shifters in Figure 13b. This will then result in the constructive addition of individual antenna patterns making an overall array pattern with a higher main lobe toward the broadside as shown in the measured results of Figure 15. The measured broadside gain is 10.1 dB and the measured first sidelobe level is 9.1 dB.
## 4 UWB Indoor Positioning System  
### Architecture of UWB-Based IPS  
Figure 5 depicts a typical UWB-based indoor localization system consisting of two types of nodes- anchors with known positions and tags with unknown positions. The system also includes a location server for sensor processing data and an interface device for viewing the positioning results. The localization process involves setting one of the anchors as the reference point and using the time-of-flight (ToF) technique to estimate the distance between each anchor and tag. Trilateration or multi-angulation techniques are then used to determine the coordinates of the tag in a 2D or 3D environment, depending on the number of anchors available. To improve accuracy in complex indoor environments, additional units, such as navigation frameworks, network gateways, user interfaces, multi-sensor technologies, and NLoS mitigation methods, are required. An NLoS detection algorithm is used to detect the presence of NLoS signals in the measurement data, and the model obtained from this algorithm is then used to refine the positioning algorithm. The choice of the NLoS detection algorithm and the positioning algorithm depends on the specific application requirements and the properties of the environment to achieve accurate positioning using the UWB IPS.
# A Survey of Deep Learning for Data Caching in Edge Network
## 5 Research Challenges and Future Directions
### Caching as a Virtual Network Function Chain  
The concept of Network Function Virtualization (NFV) has been firstly discussed and proposed within the realms of the European Telecommunication Standardization Institute (ETSI) (Network Functions Virtualization, An Introduction, Benefits, Enablers, Challenges, and Call for Action, ETSI, 2012 [[https://portal.etsi.org/NFV/NFV_White_Paper.pdf](https://portal.etsi.org/NFV/NFV_White_Paper.pdf)]([https://portal.etsi.org/NFV/NFV_White_Paper.pdf](https://portal.etsi.org/NFV/NFV_White_Paper.pdf))). The rationale is to facilitate the dynamic provisioning of network services through virtualization technologies to decouple the service creation process form the underlying hardware. The framework allows network services to be implemented by specific chaining and ordering of a set of functions which can be implemented either on a more traditional dedicated hardware, which, in this case, are called Physical Network Functions (PNFs), alternatively, as Virtual Network Functions (VNFs), which is a software running on top of virtualized general-purpose hardware. The decoupling between the hardware and the software is one of the important considerations the other--equally important--is that a virtualized service lend itself naturally to a dynamic programmable service creation where VNF resources can be deployed as required. Hence, edge cloud and network resource usage can be adapted to the instantaneous user demand whilst avoiding more static over-provisioned configurations.  
Within that framework, the incoming network service requests include the specification of the service function chain that need to be created in the form of an ordered sequence of VNFs. For example, different types of VNFs, such as a firewall or a NAT mechanism, need to be visited in a specific order. In such a constructed service chain, each independent VNF requires specific underlying resources in terms for example of CPU cycles and/or memory.  
Under this framework, caching of popular content can be considered as a specialized VNF chain function since inevitably delivery of the cached popular content to users will require a set of other functions to be supported related to security, optimization of the content etc. However, the issue of data caching and VNF chaining have evolved rather independently in the literature and the issue on how to optimize data caching when seeing it as part of VNF chain is still an interesting open ended issue. In this case, the aforementioned DL architectures can be applied to this augmented problem where in addition to caching, the associated VNF issues need to be taken into account, such as VNF chaining, routing, and hosting.
# A Survey of Secure Time Synchronization
## 3 Current Time Synchronization Methods
### Comparable Analysis of the Different Time Synchronization Protocols
At a 1 MHz hardware clock, on the well-known MICAz wireless sensor network node platform, PISync achieves the best synchronization accuracy with the slowest increasing rate concerning hop distance, for example, 2 us at the single hop and around 7 us at the 9 th hop [12], which is better than the long-standing FTSP. However, at a 50 MHz FPGA hardware clock [13], the performance of PISync degrades to 3 us at the single hop and to 17 us at the 9 th hop, and the results of DCBTS in [13] are slightly better than those of PISync, although the clock granularity has increased. A similar performance is observed in a simulation at a 32.768 MHz clock. This may be due to the better configuration of a 1 MHz clock (e.g., a very stable clock with tiny skews) used in [12], but the real clock and realistically simulated clock have worse skews than that used in [12]. For a fair comparison, more factors associated with the platform and clock should be considered. At a software-simulated 32.768 MHz clock with realistic skews, the recently proposed D-PKCOs [15] protocol outperformed PISync and the long-existing TPSN, mainly due to the feedback control mechanism used to simultaneously correct both clock offset and skew using the proposed dynamic controller of D-PKCOs, while PISync adjusted the clock offset by only using an adaptive PI controller. Since the 32.768 kHz real-time clock (RTC) is widely used in most existing industrial systems as a standard source of the clock, we also simulated the performance of a 32.768 kHz clock synchronized using PKCO, which is a better protocol at a higher granularity 32.768 MHz clock. Although PkCO has around 2 us error at the single hop and only 11 us at the 9 th hop at the 32.768 MHz clock, the same PkCO synchronization protocol degrades to 40 us and 175 us at the single hop and the 9 th hop, respectively, at the 32.768 kHz clock. The above observations are only some of many examples in the literature that show the complexity of a performance comparison of different synchronization protocols. In particular, cross-platform performance comparisons sometimes do not agree with each other. It is recommended that the comparison results are more reliable and useful when the same types of clocks and platforms are compared. Figure 12: Performance comparison of time synchronization precision of different protocols in a multi-hop sensor network. Different clock configurations are used for a comprehensive comparison, covering both hardware test results and simulation results.