esa-sceva/satcom-chunk-collection huggingface dataset:
# PIMA: Parameter-Shared Intelligent Media Analytics Framework for Low Resource Languages
## 3 Materials and Methods  
This section describes in detail both the data and the proposed framework. Specifically, we provide a detailed view of the data collection and annotation process, along with the detailed characteristics of the datasets created as a result of the process and their intended use and an in-depth overview of our proposed framework for the multi-task, multi-class classification of sentiments and emotions and the binary classification of irony and hate speech in text.  
Low resource languages (LRLs), by definition, are languages that lack the required resources to successfully tackle any NLP task. Greek is a LRL, given the scarcely available resources, both in terms of datasets to tackle tasks and the tools to assist in the creation of intelligent systems. Importantly, to successfully capture both target specific characteristics as well as period specific characteristics, we require both unlabeled domain-specific data and labeled target specific data to facilitate both an unsupervised and a supervised learning phase, respectively. The unsupervised phase is used to align a BERT-based language model (domain adaption), while the supervised phase is used to train our proposed framework's architectures on all downstream tasks. Notably, our data are collected from a variety of sources, making them more diverse than benchmark corpora even of high resource languages. Specifically, our collected data are divided into three source categories:  
* Internet. A collection of articles containing blog posts, news sites, and news aggregators.
* Social Media. A collection of posts from social media sites, namely Facebook, Twitter, and Instagram.
* Press. A collection of text clips from published newspapers, identical to the printed copy and newsletters.  
Both datasets consist of texts obtained through keyword-based searches on web domains related to each category. The unlabeled texts were utilized for the LM alignment, while the labeled texts were utilized for the classification tasks. Furthermore, the collected texts were filtered to obtain texts published between 2018 and 2022, while for specific user mentions on social media, search terms and accounts that were tied to official and personal accounts of corporate brands were followed to capture the relevant data. A four year gap allows for a certain degree of diversity in terms of textual content and avoids large language shifts occurring within that time period.  
The framework, called PIMA (Parameter-shared Intelligent Media Analytics), consists of a parameter sharing module that is comprised of a transformer-based language model, a transformer-based encoder block, and the individual classification heads. For a more comprehensive understanding, more information regarding the attention mechanism and the BERT LM can be found in the original works where these architectures were first introduced [41; 42].
# The Impact of Skinsuit Zigzag Tape Turbulators on Speed Skating Performance
## 5 The Impact of the Zigzag Strips on Skating Performance in a Real Skating Environment
### Analysis of Historical World Record Data
#### 5.3.2 Results for 1500 m  
A more detailed analysis is possible when we look at the development of the 1500 m world record presented in Figure 12 with data from Reference [22]. The figure shows an average improvement of 0.196 s/year (R\({}^{2}\) = 0.937) in the period 1984-1996 prior to the introduction of the clap skate, a large jump in the years of the introduction of the clap skate and the zigzag strips and an average improvement of 0.437 s per year (R\({}^{2}\) = 0.974) in the following 10 years.  
Figure 11: Cumulative improvement of the 5000 m world record since 1972.  
Figure 12: Cumulative improvement in seconds of the 1500 m world record for men since 1976.  
To unravel the respective contributions of clap skate and zigzag strips, let us start with the March 1996 world record of the Japanese [PERSON] in Calgary, the last on conventional skates. In March 1998, two years later, also in Calgary, the world record was 4.18 s faster. Of the 4.18 s, 3.52 s was realized in approximately one year (starting with [PERSON] on 16 March 1997) and 2.64 s (Overland, November 1997) in the four months prior to [PERSON]'s Calgary world record with drag-reducing strips. After the introduction of the zigzag devices in the first race of the Nagano Olympic speed-skating races, the 5000 m, [PERSON] adopted the zigzag strips and used them in his world-record race on the 1500 m, in Nagano as well. The world record of [PERSON] (December 1997, Heerenveen) was the last skated with clap skates but without aerodynamic changes to the suit at a low-land track. His record was 1.73 s faster than [PERSON]'s, but without the bonus of skating on a high altitude rink such as Calgary. In this respect, the Calgary track record of Dutchman [PERSON] may be of value, since this was skated on November 28 1997. His time of 1:48.68 (1.93 s faster than [PERSON]) was not a world record, due to the unofficial status of his participation in the Canada-USA international speed-skating match. [PERSON] was the last to skate on the Olympic Oval, breaking the world's fastest time on the 1500 m with clap skate but without improved aerodynamics. Taking into account the average of 0.20 s per year reduction of the 1500 m times, which could be realized irrespective of significant technology influences, it seems that about 2.20 s of the resulting 3.78 s gain on [PERSON]'s 1500 m world-record time of 1996 may be attributed to improved performance due to the zigzag strips, which means an approximate 0.59 s gain per lap. Note that, due to the clap skate coming of age but presumably more propelled by research into further aerodynamic drag reduction, in the decade following 1998, race-time improvement per year more than doubled.
# CRC-Based Reliable WiFi Backscatter Communication for Supply Chain Management
* The current study proposes a CRC reverse-algorithm-based single-AP backscatter system with ambient WiFi signals called CRCScatter. The system uses a CRC re  
Figure 1: The structure of backscatter communication systems. verse decoder to solve the problem of decoding original excitation data from a backscatter packet. * The current research present simulation results to verify the effectiveness of CRCScatter and analyze the performance. The CRCScatter system achieves a decoding tag data bit error rate of \(10^{-2}\) at SNR = \(-7.5\) dB. * The simulation results verify that the CRC reverse algorithm is better than the brute-force search method in decoding efficiency and the average decoding time of CRCScatter is independent of the tag data length. An improved method for adding redundant bits to the tag data is proposed to improve the decoding accuracy in the presence of noise interference.
# Unsteady Aerodynamic Design of a Flapping Wing Combined with a Bionic Wavy Leading Edge
## 3 Design of Wavy Leading Edge Flapping Wing  
### Flow Control Mechanism of Wavy Leading Edge  
Figure 11 shows that the leading edge of the flippers of the humpback whale has special nodular structures. These wavy bulges can maintain lift at a high angle of attack and provide higher maneuverability during the predation process [11].  
Many scholars have studied and analyzed the flow control mechanism of wavy leading edge structure on the wing or other blades. The numerical results of [PERSON] et al. [15] show that the wavy leading edge changes the flow field, and the flow separation on the upper surface of the wing is suppressed at the wavy leading edge, which has the effect of delaying stall. [PERSON] et al. [18] found that the unsteady aerodynamic force of the airfoil at the periodic vortex shedding frequency is reduced by the wavy leading edge through the large eddy simulation method. In the study of hydrofoil, [PERSON] et al. [30] pointed out that the effect of wavy leading edge structure on the flow field is similar to the principle of vortex generator. By generating shedding vortex, the pressure difference between the upper and lower surfaces of the wing is increased to achieve the effect of increasing lift and reducing drag. The longitudinal vortex also causes the downwash velocity at the peak position of the leading edge of the wing, which changes the flow state of the fluid. Under the condition of low angle of attack, flow separation will also occur at the leading edge of the wavy shape, and the vortex structure presents the \"bi-periodic\" state [13; 31]. The bi-periodic state means that when the fluid flows through the wavy leading edge, a pair of backflows will be formed at the trough, as shown in Figure 12. Therefore, under the influence of unsteady effect and vortex generated by wavy leading edge, even if the  
Figure 10: Velocity vector diagram of 1% chordwise section at t/T = 0.25.  
flapping wing does not exceed the stall angle of attack, its flow field characteristics will change.
## 1 Introduction
This profile is called the dispersion map [11]. It has been reported that nonlinear impact in EDFA-based can be well suppressed through the dispersion map optimization [3]. Through previous studies, the authors also confirmed that the dispersion map optimization has significant effect on signal distortion compensation in SMF-based WDM systems [12; 13]. Furthermore, even in the system where the OPC is not located in the middle of the entire transmission line (i.e., non-midway OPC system), we have confirmed that the improved compensation for the entire WDM signal can be obtained by applying a properly designed dispersion map considering the WDM channel data-rate, modulation format, and OPC location [13]. In this study, in the SMF-based WDM system with midway-OPC, the distortion compensation effect of the WDM signal is numerically analyzed through the application of the new-conceptual dispersion map, which the authors know has not been tried before. Unlike previously proposed methods, the dispersion maps evaluated in this study have the non-uniform structure where the zero-crossing place of cumulative dispersion is not constant. More specifically, we aim to examine the effect of various dispersion maps designed so that the cumulative dispersion is zero-crossing only at the 2 nd, 4 th, 8 th, and 16 th fiber span in each half transmission link (i.e., transmission link before or after midway-OPC) consisting of 30 fiber spans, on the distortion compensation of WDM channels.
## 2 Materials and Methods  
### Materials  
CTAB (cetyltrimethylammonium bromide; MW 364.45 g/mol, CAS Number: 57-09-0) was purchased from Sigma-Aldrich (Sintra, Portugal). DDAB (dimethyldioctadecylammonium bromide; MW 630.95 g/mol; CAS Number: 3700-67-2) was obtained from Avanti Polar Lipids (Alabama, USA). Softisan(r)100 (S100) was a gift from Sasol Germany GmbH (Witten, Germany), Lipoid(r) S75, composed of 75% soybean phosphatidylcholine was acquired from Lipoid GmbH (Ludwigshafen, Germany), Luttrol(r)F68 or Poloxamer 188 (P188) was a gift from BASF (Ludwigshafen, Germany). Anhydrous glycerol was acquired from Acopharma (Barcelona, Spain). In all assays ultra-pure water was used and obtained from a MiliQ Plus system (Millipore, Germany).  
Other reagents and salts, not mentioned, were of high purity and were acquired from Sigma-Aldrich (Sintra, Portugal).
# Device-Free Localization and Identification Using Sub-GHz Passive Radio Mapping
## 1 Introduction
As previously mentioned, the approach that is often used is based on the unique gait of the individuals between which one wants to differentiate. However, the use of only RSS does not suffice as a signal feature for these types of systems. Instead, they all require CSI measurements. The WiDisc system proposed by [PERSON] et al. [18] is one of the very few examples of an RSS-only identification system. The authors attempted to differentiate between a child, a woman and a tall man using four IEEE 802.15.4 transceivers communicating on the 2.4 GHz band in a 4.04 m by 5.33 m by 2.70 m lab environment. They used a deterministic passive fingerprinting method and managed to correctly estimate the presence of the child, woman and tall man respectively 43 %, 71 % and 86 % of the time. While these results indicated the feasibility of differentiating between these three size-based categories, it was quite clear that the system required further development and this was stated by the authors as well. While the information provided by only using signal strengths is likely to be insufficient to match the capabilities of CSI-based systems, even a limited form of identification could still prove to be very beneficial and potentially enable interesting applications. An example would be a safety system which can detect the presence of children in industrial environments. Furthermore, the information provided by such a differentiation system would likely aid tracking approaches as well. The remainder of this paper is structured as follows. In Section 2, we describe our experimental setup in detail and discuss our approach in analyzing the results, both in regards to localization and identification. In Section 3, we perform our localization for different combinations of frequency bands, number of nodes, classification algorithms and individuals used in the construction of the fingerprint database. Section 4 details our identification approach. Finally, in Section 5 a conclusion is presented in addition to an overview of our plans regarding future research.
## 1 Introduction
Subsequently, the internal liquid supply method was also applied to ECMG. [PERSON] et al. [18] opened a single row of liquid spray holes in the side wall of an electroplated diamond abrasive tubular cathode tool with a cutting depth of 3 mm, and processed a boss structure on GH4169. [PERSON] et al. [19] opened 4 outlet holes in the side wall of an electroplated diamond abrasive tubular tool with a cutting depth of 10 mm. By using a numerical simulation of the flow field and an experimental validation by an Inconel 718 cutting test, they found that compared with the vertical arrangement, the spiral arrangement effectively improved the flatness of the side of the workpiece. When ECMG adopts the method of spraying liquid on the side wall of the tubular tool, it can directly perform the \"cut-in\" processing with a large cutting depth from the side wall of the workpiece. It has significant advantages and broad application prospects in the field of efficient manufacturing of the structural parts of difficult-to-machine materials. However, the current research on ECMG technology is mainly focused on the nickel-based superalloy Inconel 718/GH4169 [17; 18; 19; 20], and there are no reports on the electrochemical mill-grinding of titanium alloys. In addition, the cutting depths of the previous studies are all within 10 mm. If the method of increasing the number of liquid outlet holes is still used to obtain a larger cutting depth, the reduction in the geometric accuracy of the cathode tool is possible. It is particularly important that the previous research showed that the uneven flow field distribution in the processing gap of the porous liquid outlet tool causes obvious flow marks on the processed surface of the workpiece [21; 22], which adversely affects the precision. In view of the above problems, the present research proposed the design and development of a cathode tool suitable for ECMG with large cutting depth. A reasonable electrolyte outlet layout ensured the uniformity of the flow field in the machining gap; so as to obtain a better precision in the formation of the rough-machining surface and reduce the removal of the finishing and tool wear. For this purpose, through the numerical simulation of the flow field, a scheme optimization study was carried out. Subsequently, using a larger cutting depth with the designed cathode tool scheme, the rough and finish machining of Ti6 Al4V titanium alloy was performed and analyzed. In addition, the effects of different processing parameters on the surface quality of titanium alloys were studied by measuring the micro-morphology, roughness and elemental composition of the processed surface.
## 3 Application and Comparison of Various Classification Methods
### Bidirectional ELM  
In the case of the standard ELM, which has a fixed network architecture, the parameter affecting its performance is the number of hidden nodes. However, determining the optimal number of hidden  
\begin{table}
\begin{tabular}{l} \hline \hline
**Input:** A training set \(\{X,T\}=\{x_{i},\,t_{i}\}_{i=1}^{N}\) \\
**Output:** A trained ELM model \\
**(_Standard ELM phase_)** \\ _Let k = 0,_ Calculate the hidden layer output matrix \(H_{0}\) using initial training data \\ Estimate the initial output weight \(\beta_{0}\to P_{0}=(H_{0}^{T}H_{0})^{-1}\) \\
**(OS- ELM phase)** \\ - When the \((k+1)\)-th chunk of new data \(\{X_{k+1},\,T_{k+1}\}\) arrives, update the hidden layer output matrix as \(H_{k+1}=[H_{k}^{T},\,\,\Delta H_{k+1}^{T}]^{T}\) \\ _where \(\Delta H_{k+1}\) is the hidden layer output matrix corresponding to the newly arrived data_ \\ - Update the output weights as \(\beta_{k+1}=\beta_{k}+P_{k+1}H_{k+1}^{T}(T_{k+1}-H_{k+1}\beta_{k})\) \\ _where \(P_{k+1}=P_{k}-P_{k}\,H_{k+1}^{T}(l+H_{k+1}PH_{k+1}T)^{-1}H_{k+1}P_{k}\)_ \\ - Set \(k=k+1\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Pseudo code of OS-ELM [47].  
nodes depends on the sensitivity analysis based on a trial and error approach. To solve this problem, incremental ELM (I-ELM) was proposed by [PERSON] et al. [46]. The I-ELM is an improved version of the standard ELM obtained by adding hidden nodes one-by-one until the expected training accuracy is achieved.  
Although I-ELM has been used to determine the appropriate number of hidden nodes, the problem of computation time still remains because I-ELM calculates \(n\) output weights one by one when \(n\) hidden nodes are used. For these reasons, [PERSON] et al. [49] developed the bidirectional ELM (B-ELM), improving upon the standard ELM algorithm by finding an appropriate number of hidden nodes and enhancing the computing speed and accuracy. The basic concept of B-ELM is the optimization of two main parameters (\(a_{i}\), \(b_{i}\)) related to the hidden nodes. \(a_{i}\) is the weight vector connecting the input layer to the \(i\)th hidden node and \(b_{i}\) is the bias of the \(i\)th hidden node. The optimization of these two parameters results in the rapid decrease in residual error. The B-ELM is discussed in detail in the pseudo code given in Table 4.
## 5 Experimental Evaluation
### Performance Metrics
#### 5.2.2 Latency  
Latency, also known as the network delay in fetching content, is the time taken for a user request to be served. MAN to MAN latency is set to 20 ms to test the efficiency of the schemes in worse scenarios.  
\[Latency=\frac{Total\ Cache\ Miss\times 10}{Queue\ size\ of\ all\ users\ in\ time\ stream}\]
# Deep Learning and Big Data in Healthcare: A Double Review for Critical Beginners
## 5 Applications in Healthcare from Biomedical Information
### Electrical Biomedical Signals  
Modern biomedical instrumentation produces electrical signals which come from sensors placed on the body skin, and whose characteristics are determined by the sensors location. These signals are an invaluable data source to use in disease detection and diagnosis. DL is able to implement reliable applications by using physiological signals such as electromyogram (EMG), electroencephalogram (EEG), electrooculogram (EOG) and electrocardiogram (ECG). Architectures most used to process these physiological signals are RNN and one-dimensional CNN [22; 50].  
The EMG measures the electrical activity of skeletal muscles: muscle activation, force and muscle state. All these factors are overlapped in the EMG signal, so observing it directly makes it difficult to gain information about one particular issue. DL algorithms can help with this problem [50]. For example, see limb movement estimation in [137], neuroprosthesis control in [138], movement intention decoding in [139], hand movement classification in [140], gesture recognition in [141], robotics and guidance in [142], and speech recognition with gestures in [143].  
The EEG evaluates the electrical activity of the brain. Brain Computer Interface (BCI) is the main application of EEG where DL is applied [50]. The real-time nature of BCI signal makes human interpretation impossible, so that it requires automated decision-making [144]. Other DL applications refer to sleep state identification [145], epileptogenicity localization [146], decoding excited movements [147], and seizure detection [148].  
The EOG quantifies the corneo-retinal potential between the back and front of the human eye. The signal is generated through two electrodes placed above and below each eye, and is useful for ophthalmological diagnosis. However, noise and artifacts complicate the interpretation [50]. Some examples of works seek to overcome these limitations by using DL algorithms to detect driving fatigue [149] and drowsiness [150], and other ones to classify momentary mental workload [151] and sleep stage [152]. The application on the ECG signals is dealt with in the next section.
## 3 Interfacial Phenomena between Solid-State Electrolytes and Electrodes
### Buffer Layers
#### 3.2.2 Buffer Layers at Solid-State Electrolyte/Anode
A porous-dense bilayer of LLZO garnet solid electrolyte as a 3D ionic framework for Li metal anode was developed by Liu et al. [313] where the framework consists of one porous layer as a volume-stable host of Li metal with a large contact area and one dense buffer layer as a solid-state separator preventing short-circuits. In this work, the cell was found to completely suppress dendrite formation due to the LLZO buffer layer after 150 h of cycling. Lou et al. [314] modified the surface of the LLZO-Ta (Li\({}_{6.4}\)La\({}_{3}\)Zr\({}_{1.4}\)Ta\({}_{0.6}\)O\({}_{12}\)) solid electrolyte with an indium tin oxide (ITO) buffer layer. According to the authors, the lithiated ITO buffer layer ensures tight contact between the Li metal and LLZO-Ta which leads to a uniform local current distribution of the interface, preventing lithium dendrite formation. The experimental results revealed that the ITO buffer layer reduced the interfacial resistance of Li/ITO-LLZO-Ta from 1192 to 32 \(\Omega\) cm\({}^{2}\). The summarized interfacial resistance of the SSBs with buffer layers on anode/electrolyte are listed in Table 5.
# An Evaluation of the Security of Bare Machine Computing (BMC) Systems against Cybersecurity Attacks
## 3 Bare Machine Computing (BMC) Systems
### Properties of the BMC Paradigm
#### 3.5.3 BMC Limitations  
As described before, the bare machine computing paradigm has unique system guidelines and characteristics to reduce obsolescence and provide inherent security in computer and information systems. However, this approach has its own limitations, as listed below:  
1. It is not a general-purpose global system.
2. It requires physical security.
3. It needs all users to be authenticated and vetted.
4. It uses a domain-specific application approach (by dividing applications into domains).
5. Only users within a domain can communicate.
6. When domain-specific users change roles, their authentication privileges are revoked.
7. All nodes in the network must be bare to guarantee high security.
8. Uses the bare Internet, where all nodes are bare and physical security is assumed.