esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
This study includes the use of a multi-spindle drill head to perform a multi-hole simultaneous drilling process to increase productivity and save time. To assess the quality of holes, uncoated carbide and (TiN and TiCN) coated drills were used. It was concluded that low thrust force, low surface roughness and small burrs were observed with the use of the uncoated drills during multi-spindle drilling of Al2024, while the TiN-coated drill gave the highest thrust force and poor hole quality. However, at a high spindle speed, the TiCN performed better than the uncoated drills because of its high hardness value and low coefficient of friction. Therefore, the performance of the TiCN coating tool was good at high spindle speeds and feed rates since it provides similar or less thrust force and better surface finish than the other tools. This means combining TiCN coating with poly drilling can give both better hole quality and also reduce drilling time. Regarding the drilling parameters, the thrust force was highly influenced by the feed, while the effect of spindle speed on thrust force was insignificant. The surface roughness was affected more by the spindle speed than the feed. However, most of the burrs were observed at a high feed as compared to the increase in spindle speed. Furthermore, more burrs were observed at the holes' exits. In addition, an ANN model, which can be part of a portfolio for the manufacturing engineering work on the drilling of Al2024, was developed for the prediction of surface roughness when using the multi-hole simultaneous drilling process. The ANN model is reliable for the prediction of surface roughness with the values of RMSE, MAPD and R\({}^{2}\) of 0.127, 4.69 and 0.95 for the training dataset, and 0.204, 8.12, and 0.88 for the testing dataset, which showed the satisfactory performance of the developed model. This work can be further extended to examine the deviation of the hole from the nominal size and circularity error in the multi-spindle drilling process.  
Conceptualization, M.T.-R. and M.A.; methodology, K.G.; software, M.N.A.R. validation, M.A., M.T.-R, K.G. and M.N.A.R.; investigation, M.A.; writing--original draft preparation, M.A.; writing--review and editing, M.T.-R, K.G., A.V. and M.N.A.R.; supervision, M.T.-R., K.G. and A.V. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors would like to thank the technical staff, especially [PERSON] for his help and support in experiments at the Manufacturing Engineering Lab, School of Engineering, Edith Cowan University, Australia. The first author would also like to thank Edith Cowan University for the awarded (ECU-HDR) higher degree research scholarship.  
The authors declare no conflict of interest.  
Figure 11: Sensitivity analysis.
# Multi-View Visual Relationship Detection with Estimated Depth Map
## 4 Experimental Procedure
### Visual Relationship Detection
#### 4.1.3 Recall Performance Evaluation and Comparison
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & \multicolumn{1}{c}{**Pre. Det. (\(R_{50\&100}\))**} & \multicolumn{2}{c}{**Phr. Det. (\(R_{50\&100}\))**} & \multicolumn{2}{c}{**Rel. Det. (\(R_{50\&100}\))**} \\ \cline{2-7}  & **Unseen** & **All** & **Unseen** & **All** & **Unseen** & **All** \\ \hline VRD-Full [1] & 12.3 & 47.9 & 5.1/5.7 & 16.2/17.0 & 4.8/5.4 & 13.9/14.7 \\ VTransE [2] & - & 44.8 & 2.7/3.5 & 19.4/22.4 & 1.7/2.1 & 14.1/15.2 \\ Weakly [4] & 19.8 & 49.7 & 6.8/7.4 & 16.1/17.7 & 6.2/6.8 & 14.5/15.8 \\ PPR-FCN [5] & - & 47.4 & - & 19.6/23.2 & - & 14.4/15.7 \\ IEKLD:S [3] & 17.0 & - & 10.4/10.9 & - & 8.9/9.1 & - \\ IEKLD:T [3] & 8.8 & - & 6.5/6.7 & - & 6.1/6.4 & - \\ IEKLD:S+T [3] & - & 55.2 & - & 23.1/24.0 & - & 19.2/21.3 \\ DVSRL [6] & - & - & 9.2/10.3 & 21.4/22.6 & 7.9/8.5 & 18.2/20.8 \\ Robust [34] & 17.3 & 52.3 & 5.8/7.1 & 17.4/19.1 & 5.3/6.5 & 15.2/16.8 \\ Zoom-Net [35] & - & 50.7 & - & 24.8/28.1 & - & 18.9/21.4 \\ CAI+SCA-M [35] & - & 56.0 & - & 25.2/28.9 & - & 19.5/22.4 \\ MR-NET [36] & - & 61.2 & - & - & - & 16.7/17.6 \\ RelDN [37] & - & - & - & 31.3/36.4 & - & 25.3/28.6 \\ MF-URLN [38] & 26.9 & 58.2 & 5.9/7.9 & 31.5/36.1 & 4.3/5.5 & 23.9/26.8 \\ MF-URLN-IM [38] & 27.2 & - & 6.2/9.2 & - & 4.5/6.4 & - \\ \hline RDBN [7] & 22.5 & 50.1 & 7.4/8.2 & 16.1/17.8 & 6.8/7.3 & 14.4/15.8 \\ RDBN (\(10<|\Delta\text{Depth}|<30\)) [7] & 21.6 & 52.3 & 9.8/11.2 & 17.8/19.6 & 9.5/10.3 & 15.9/17.3 \\ RDBN (\(|\Delta\text{Depth}|>100\)) [7] & 42.6 & 55.2 & 11.5/11.5 & 19.6/20.6 & 6.6/6.6 & 14.1/15.0 \\ \hline
**Multi-view[Img]** & 22.7 & 50.2 & 7.4/8.2 & 16.1/17.9 & 6.8/7.3 & 14.4/15.9 \\
**Multi-view[Img]**(\(10<|\Delta\text{Depth}|<30\)) & 21.3 & 52.0 & 9.5/10.3 & 17.6/19.4 & 9.2/9.8 & 15.8/17.2 \\
**Multi-view[Img]**(\(|\Delta\text{Depth}|>100\)) & **44.3** & **55.8** & **11.5/11.5** & **19.6/20.9** & **6.6/6.6** & **14.1/15.3** \\ \hline
**Multi-view[Reg]** & 22.9 & 50.3 & 7.0/7.9 & 16.1/17.8 & 6.4/7.0 & 14.4/15.8 \\
**Multi-view[Reg]**(\(10<|\Delta\text{Depth}|<30\)) & **22.4** & 52.2 & 9.5/10.6 & 17.8/19.5 & 9.2/10.1 & 15.8/17.2 \\
**Multi-view[Reg]**(\(|\Delta\text{Depth}|>100\)) & 42.6 & 55.5 & **11.5/11.5** & 19.6/20.6 & **6.6/6.6** & **14.1/15.3** \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Recall performance comparison (%) with existing strong VRD baselines on VRD dataset [1]. Multi-view[Img] and Multi-view[Reg] represent multi-view VRD framework with ImageNetNorm and RegionNorm normalization strategy, respectively. The “Unseen” column shows zero-shot learning performance and the “All” column shows performance in normal dataset condition. “-” denotes the result is unavailable. The best performances in the specific depth condition are highlighted in boldface. Note that in existing methods, only the multi-view framework and RDBN [7] can evaluate the performance in specific depth ranges.
# Augmented Reality and the Digital Twin: State-of-the-Art and Perspectives for Cybersecurity
## 5 Conclusions  
In this work, existing knowledge on the combined application of Augmented Reality and Digital Twins is systematized. We analyze academic literature to understand why, where, how, and with what technologies this combination is realized. We are able to identify the possibility of improving monitoring, education, and analysis as the major reason why AR is applied with DT. Several application areas already implement respective approaches, and the leading area is the manufacturing sector, followed by education, as well as others, such as the energy sector. The existing approaches are mostly built on proprietary architectures but can be generalized using a layered architecture, including a physical layer, the DT, an application layer, and AR. To realize individual use cases, currently, the majority of existing applications build on the Microsoft HoloLens.  
The systematized knowledge and the findings drawn from the existing work enlightens a path to how AR, together with DT, can also play a significant role in cybersecurity, especially in the context of CPS. Therefore, we discuss several main benefits which can be realized with AR-powered DTs. The combined approach enables real situational awareness, including the actual physical situation, and allows respective insights derived from DT data and simulations to be analyzed together with the physical assets. These aspects significantly improve the integration of human domain knowledge into any security measure. In a final step, we discuss a general, conceptual architecture of how AR and DT can be integrated with existing security mechanisms.  
When used (for security), harnessing AR for DTs will only be beneficial when sufficiently secured. Otherwise, an attacker will find an easy target that provides especially relevant knowledge of a real-world system, violating confidentiality and potentially turning into an existential threat for the company. Additionally, research in improving cybersecurity with a combination of AR and DT is in its infancy. There is little to no existing conceptual or empirical work on the topic. Nevertheless, we show that following down this road can result in significant progress for cybersecurity.  
Conceptualization, F.B. and M.D.; Data curation, T.P. and F.B.; Investigation: F.B., M.D. and T.P.; Methodology, F.B. and T.P.; Writing--original draft, T.P., F.B. and M.D.; Writing--review & editing, F.B., M.D., T.P. and G.P.; Supervision: G.P. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.  
The following technical abbreviations are used in this manuscript:  
\begin{tabular}{l l} AR & Augmented Reality \\ CPS & Cyber Physical System \\ CVE & Common Vulnerabilities Enumeration \\ DT & Digital Twin \\ IDS & Intrusion Detection System \\ IoT & Internet of Things \\ \end{tabular}
## 5 III-V-on-Silicon Devices for Optical Sensing Applications  
While PICs are mainly targeting optical communication applications, the use of the integration platform is currently also being considered for optical sensing applications. Most efforts so far have been focused on bio-sensors, using chemically functionalized integrated optical resonators as the transducer for the binding of bio-molecules to the silicon surface. Large arrays of chemically functionalized resonators can this way be integrated on a low-cost, disposable chip. In this application, the selectivity of the sensor is completely determined by the functionalization chemistry. Therefore, it is interesting to study whether other integrated sensor systems could be realized on the silicon photonic platform, and  
Figure 19: (**a**) Bias dependent normalized transmission of each channel. (**b–f**) Optical eye diagrams at 20 Gbps for each channel. Reproduced from [56].  
Figure 18: (**a**) Schematic diagram of the chip layout. (**b**) top-view of the III-V on silicon EAMs. Reproduced from [56].  
could get their selectivity not from chemical functionalization, but rather from the specific absorption spectrum that each molecule possesses. This absorption spectrum serves as a fingerprint for the molecule and allows for the analysis of the composition of a liquid, gas or solid sample. Opposite to small gas molecules, which have very sharp absorption lines, the absorption spectrum of many molecules of interest in the context of bio-applications show rather broad absorption spectra. This makes the use of integrated laser sources less suitable for this purpose. Rather, there is a need for broadband light sources and integrated spectrometers integrated on a single chip. Depending on the molecules of interest, the operational wavelength range of the spectroscopic sensor will also be different. In this section, we will elaborate on our work towards the integration of broadband optical sources on a silicon PIC, as well as the realization of integrated spectrometers. For the broadband sources, we will focus on the 1.2 um to 2 um wavelength range, while for the integrated spectrometers operation up to 3.8 um wavelength will be described.
# Analysis of New Orthogonal Transforms for Digital Watermarking
## 4 Experimental Results
### Transforms Selected for the Experiments  
The following transforms and their parameters were selected for watermark embedding:  
1. Full non-exponential matrix (NONEXP): \(n=3,\quad a_{1}=1,\quad a_{2}=2,\quad a_{3}=3\)
2. Sparse non-exponential matrix (NONEXP_SPARSE): \(n=3,\quad m=2,\quad a_{1}=1,\quad a_{2}=2,\quad a_{3}=3\)
3. Full non-exponential matrix with arbitrary \(\beta\) parameter (NONEXP_BETA): \(n=3,\quad a_{1}=1,\quad a_{2}=2,\quad a_{3}=3,\quad\beta=1.5\)
4. Full exponential matrix (EXP): \(n=3,\quad a=1\)
5. Sparse exponential matrix (EXP_SPARSE): \(n=3,\quad m=2,\quad a=1\)
# Recent Progress on Irradiation-Induced Defect Engineering of Two-Dimensional 2H-MoS2 Few Layers
## 2 Charged Particle Irradiation
### Proton Irradiation
Figure 14c shows PL spectra of suspending MoS\({}_{2}\) mono-layers after proton irradiation with a fluence of \(6\times 10^{14}\) particles/cm\({}^{2}\) with and without annealing, compared with those taken before the irradiation. The intensity of the direct band-gap emission of suspending mono-layers decreased two-fold after the irradiation due to the irradiation-induced defects. The defects caused non-radiative recombination and shortened the lifetime of the photo-excited carriers. On the contrary, the intensity of the direct band-gap emission at 1.85 eV increased after the irradiation for the substrate-supported regions, as shown in Figure 14d. After being annealed at 300 \({}^{\circ}\)C for 1 h in argon, the defect-induced sideband peak disappeared in the bi-layers and mono-layers, and the direct band emission reverted to its original pre-irradiated intensity for both kinds of MoS\({}_{2}\) layers.
# Manipulating Stress Responses during Spaceflight Training with Virtual Stressors
## 4 Materials and Methods
### Dependent Variables
#### 4.4.1 Heart Rate and Heart Rate Variability  
Heart rate increases with higher physiological stress response. Heart rate data were collected via electrocardiogram (ECG, modified CSS5 lead configuration). The ECG was sampled at 2048 Hz using Biopac MP150 hardware and recorded using AcqKnowledge software (Version 3.8.2, Biopac Systems Inc.). Heart Rate is influenced by both sympathetic and parasympathetic branches of the autonomic nervous system [46]. Activity in these branches is indicative of the body's state of excitation vs. relaxation (vagal response).  
Time domain analysis of the ECG was performed to quantify changes in Heart Rate Variability (HRV). The vagal response, which is indicative of relaxation, was assessed with two HRV metrics relating to the amount of variance in the inter-beat-interval through the root-mean-square difference of successive normal R-wave intervals (RMSSD) and the proportion of the number of pairs of successive normal R-waves that differ by more than 50 ms (pNN50). Increased pNN50 and RMSSD indicated a more relaxed state and greater ability to cope with increased stress. More specifically, both RMSSD and pNN50 represent vagal control within the time domain and are correlated to high frequency power [46]. The HRV time domain for each participant were calculated in 30-s intervals over the duration of each session.
## 2 Communication System Model and Theory
### Polar Data Decoding  
Before performing polar decoding, we first generate the local signal \(y=e^{j2\pi f_{\mathrm{c}in}t}\), followed by down-conversion and despreading. According to the preceding discussion, the despreading gain can be expressed as \(\delta=<c_{i,b_{i}}(t-\tau_{i}(t)-iT_{s}),c_{j}(t)>\), and thus, the polar decoding result for the \(i\)-th symbol can be represented by the following formula:  
\[I_{i}=a_{i}[0]\delta e^{i\phi_{i}(t)}+\mu \tag{19}\]  
\(\phi_{i}(t)\) represents the carrier phase shift for the \(i\)-th symbol, \(\mu\) denotes the noise after despreading. Taking the conjugate of the above expression and then obtaining the absolute value of the real part yields  
\[I_{i}^{*}=|a_{i}[0]|\delta e^{-i\phi_{i}(t)}+\mu \tag{20}\]When \(\mu\) is much smaller than \(\delta\), the carrier phase jump \(\phi_{i}(t)\) is eliminated by conjugate multiplication.  
\[l_{i}l_{i}^{*}\approx a_{i}[0]|a_{i}[0]|\delta^{2} \tag{21}\]  
The polarity \(a_{i}(0)\) of the \(i\)-th symbol is determined by the sign of the output result.
## 3 Mathematical Background
### Polynomial Ideals and Algebraic Sets  
Consider the finite field of \(q\) elements \(\mathbb{F}_{q}\) and the ring of polynomials in \(n\) variables over \(\mathbb{F}_{q}\), denoted \(R=\mathbb{F}_{q}[X_{1},\ldots,X_{n}]\). A subset \(I\subset R\) is an _ideal_ if For every \(f,g\in I,f+g\in I\);  
For every \(f\in I\), \(h\in R\) the product \(hf\in I\).  
Then, considering a finite set of polynomials \(F=\{f_{1},\ldots,f_{m}\}\subset R\), we can define the _ideal generated by \(F\)_ as follows  
\[(F)=\{h_{1}f_{1}+\ldots+h_{m}f_{m}|h_{i}\in R,i=1,\ldots,m\}.\]  
A common root for the polynomials \(f_{i}\) for \(i=1,\ldots,m\) is also a root for any \(f\in(F)\). The _zero-set_ for the ideal \(I\), denoted \(V_{I}\), consists of all the points \((x_{1},\ldots,x_{n})\in\mathbb{F}_{q}^{n}\) such that \(f(x_{1},\ldots,x_{n})=0\) for every \(f\in I\). By considering an algebraic extension of the base field \(\mathbb{F}_{q}\), the zero-set is known as the _algebraic set_ of \(I\).  
We can now formalize \(\mathcal{MQ}\) as a decision problem. Additionally, we state the related search problem.  
**Decision problem.**  
**Instance:** An ideal \(I\subset\mathbb{F}_{q}[X_{1},\ldots,X_{n}]\).  
**Solution:**\(\left\{\begin{array}{ll}1&\text{If }V_{I}\
eq\emptyset;\\ 0&\text{Otherwise.}\end{array}\right.\)  
**Search problem**  
**Instance:** An ideal \(I\subset\mathbb{F}_{q}[X_{1},\ldots,X_{n}]\).  
**Solution:** Either a proof that \(V_{I}=\emptyset\) or a point \(x\in\mathbb{F}_{q}^{n}\) such that \(x\in V_{I}\).  
A solution to the search problem provides a solution to the decision problem immediately. If we are able to find a solution for the polynomial system \(f_{1}=\ldots=f_{m}=0\) we conclude that \(V_{I}\
eq\emptyset\). This means that solving the search problem is at least as difficult as solving the decision problem, which is known to be NP-complete.  
As mentioned before, any solution for a set of polynomials is also a solution for the ideal generated by that set. Most of the system solvers work based on this fact, by finding a set of \"representatives\" with better properties, making the resolution task easier. Finding these representatives has been already explored by [PERSON], who proposed the construction of the so-called Groebner bases. We can mention improved versions of the Buchberger algorithm, such as F4 and F5. They have been successful in attacking cryptographic schemes, such as the HFE and the Matsumoto-Imai [26], and some variations of UOV [27]. Despite these efforts, the complexity of these algorithms, even in average instances of \(\mathcal{MQ}\), is fully exponential [28].
## 8 Conclusions
###### Nomenclature  
**Acronyms**  
CAPEX CAPital EXpenditure  
CNG Compressed Natural Gas  
FFSO Floating Production Storage and Offloading  
LNG Liquefied Natural Gas  
NG Natural Gas  
OPEX Operating EXpenditure  
**Symbols**  
\(A\) flow area [m\({}^{2}\)]  
\(C_{I}\) C\({}_{g}\)/C\({}_{v}\) [-]  
\(C_{d}\) outflow coefficient [-]  
\(C_{g}\) gas flow sizing coefficient [lb/h/(psia \(\cdot\) lb/ft\({}^{3}\))\({}^{0.5}\)]  
\(C_{p}\) constant pressure specific heat [J/kg/K]  
\(C_{p}\) fluid flow sizing coefficient [lb/h/(psia \(\cdot\) lb/ft\({}^{3}\))\({}^{0.5}\)]  
\(D\) diameter [m]  
h enthalpy [J/kg]  
k specific heat ratio [-]  
\(L\) length [m]  
\(m\) mass [kg]  
\(m\) mass flow rate [kg/s]  
n polytropic exponent [-]  
\(p\) pressure [Pa]  
\(p\) power [W]  
Q heat [J]  
R gas constant [J/kg/K]  
S surface [m\({}^{2}\)]  
T temperature [K]  
u internal energy [J/kg]  
v velocity [m/s]  
Z compressibility factor [-]  
\(\alpha\) convective heat exchange coefficient [W/m\({}^{2}\)/K]  
\(\beta\) compression ratio [-]  
\(\varrho\) density [kg/m\({}^{3}\)]  
\(\eta\) efficiency [-]  
\(\lambda\) Darcy friction factor [-]  
**Subscripts**  
_O1_  
stagnation condition at compressor inlet  
_amb_
## 3 FRBs in the Era of SKAO/ngVLA  
The radio astronomy landscape will be further transformed in the coming years. On the one hand, new, more advanced radio telescopes--the Square Kilometre Array (SKA) [37], the next-generation Very Large Array (ngVLA) [38], the Deep Synoptic Array (DSA-2000) [39], and the Canadian Hydrogen Observations and Radio-transient Detector (CHORD) [40]--will bring about an exponential increase in the data volume that will need to be processed in order to detect and localise FRBs. Compounding this challenge, on the other hand, is the recent realisation that the parameter space populated by FRBs may be larger than what we have been searching so-far. Some of the existing FRB detection algorithms may not be able to keep up with such high data rates of multiple TBs per second over large ranges of search parameters. In this section we first describe the opportunities for searching outside the existing box and next look at newer, faster, and more efficient algorithms. We note that some of these algorithms have already been tested on a conceptual level and may be deployed on these next-generation telescopes, as their FRB search software stack is not yet set in stone. Here, we look a number of possible alternatives for future FRB searches with next-generation facilities. We note that this by no means is an exhaustive list and describe the ones that we find the most promising.
# Sink-Type-Dependent Data-Gathering Frameworks in Wireless Sensor Networks: A Comparative Study
## 2 Data-Gathering Frameworks Depending on Sink Types
### Protocol Selection Criteria for Qualitative Comparison  
This study examines three categories of WSN data-gathering techniques. First, total ten data-collection protocols are chosen for a qualitative comparison. As mentioned earlier, the protocols are chosen based on the sink types (i.e., static, ground mobile, and aerial mobile sinks). The protocols discussed in the static sink-based data-gathering section are chosen based on popularity and citations in the literature. To choose the ground and aerial mobile sink-based data-gathering techniques, we focus on journal articles. The mobility pattern of the ground mobile sink heavily depends on the terrain type. While choosing the protocols for ground mobile sinks and aerial mobile sinks, we also take the mobility pattern. Besides the aforementioned criteria, we also focus on maximizing the difference of the protocols for each section in terms of configuration and working principle.