esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Establishment of the Seasonally Frozen Ground-Pipeline System Model
### Basic Assumptions and Fundamental Governing Equations of the Physical Fields  
#### 2.2.1 Basic Assumptions  
In conjunction with engineering requirements, the following assumptions are made for the mathematical model of the frost heave and thaw settlement in pipe-soil systems:  
1. The soil is assumed to be an isotropic continuous medium. While natural soils may exhibit anisotropy due to layering or particle orientation, the isotropic assumption simplifies the multiphysics coupling by reducing computational complexity. This approach is widely adopted in frozen soil mechanics studies and aligns with the focus on macroscopic thermal-hydraulic-mechanical interactions rather than microscale heterogeneity.
2. The soil is assumed to undergo small deformations, with strains within the linear elastic range. The assumption of small strains (linear elasticity) is valid for frost heave and thaw settlement in seasonally frozen regions, where cumulative displacements are typically within millimeter-to-centimeter scales. Large plastic deformations or soil failure were not observed in field measurements, supporting this simplification.
3. Soil particles and ice are assumed to be incompressible. Volume changes in frozen soil primarily arise from ice-water phase transitions and moisture migration, not particle compressibility. This simplification avoids unnecessary complexity in stress-strain calculations while preserving the dominant deformation mechanisms.
4. The influence of moisture evaporation is not considered in the processes of water-ice phase change and moisture migration. Evaporation effects are minimal in frozen soil due to low temperatures and suppressed vapor diffusion. The study focuses on phase change-driven moisture migration, which dominates frost heave and thaw settlement.  
Building upon these foundational assumptions, we now derive the governing equations for the thermal, hydrological, and mechanical fields to fully characterize the pipe-frozen soil interaction system.
## 4 Applications  
Two simple theoretical examples are proposed in this Section, to illustrate some applications of the methodology presented. The first is focused on the hazard mitigation effects provided by an existing protection system installed at the source area; the second deals with hazard mitigation in presence of a structural measure in the propagation zone. For what concerns the assessment of rock fall hazards, with and without account for the protection measures, both examples will be presented with the help of the intensity-frequency matrix diagram in the Swiss Codes, which is already introduced (Figure 2).  
Figure 2: Requalification of hazard zones and corresponding representation in hazard zoning maps, with reference to the rock fall intensity–frequency diagram used in the Swiss Codes.  
As an appropriate calibration of the penalty coefficients is currently under development, it is worth pointing out here that the objective of these applications, in line with the scope of the paper, is mostly to help present a detailed and informative view on how to perform the evaluations featured in the procedure, rather than underlining the quality of the results. Data and information about the protections, the penalty coefficients established for the factors included in the examples and the values for the parameters determining the rock fall hazards are therefore based on assumptions, serving the purpose of clarity in illustrating the principles of the computations and the interpretation of the results obtained.
## 2 Materials and Methods
### Synthesis of Native MSN, MSN-PLH and MSN-PLH-TAM  
The synthesis of three MSN-based systems; namely native MSNs, MSN-PLH and MSN-PLH-TAM directly followed our recently published study [16]. Native MSNs were synthesized via the Stober method, using CTAB as the templating structure and TEOS as the silica precursor. The surface (OH-) moieties of MSNs were converted to thiols using MPTES and conjugated to Mal-PLH-NH\({}_{2}\) molecules via Michael addition at pH 5, to give MSN-PLH. Resulting MSN-PLH nanostructure was then reacted with mesylated TAM-TEG building blocks prepared in-house (in which TEG- Tetraethylene glycol was used as an organic linker) to give the requisite MSN-PLH-TAM nanomaterial.
###### Abstract  
The development of intrusion detection systems (IDS) that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines spectral clustering (SC) and deep neural network (DNN) algorithms. First, the dataset is divided into \(k\) subsets based on sample similarity using cluster centres, as in SC. Next, the distance between data points in a testing set and the training set is measured based on similarity features and is fed into the deep neural network algorithm for intrusion detection. Six KDD-Cup99 and NSL-KDD datasets and a sensor network dataset were employed to test the performance of the model. These experimental results indicate that the SCDNN classifier not only performs better than backpropagation neural network (BPNN), support vector machine (SVM), random forest (RF) and Bayes tree models in detection accuracy and the types of abnormal attacks found. It also provides an effective tool of study and analysis of intrusion detection in large networks.  
intrusion detection system; deep neural network; ensemble model; wireless sensor network; spectral clustering +
Footnote †: journal: Sensors
## 3 Results
### Evaluation Metrics  
This paper utilizes several metrics to assess the effectiveness of segmentation, including _Accuracy_, _Precision_, _Recall_, and _IoU_. A confusion matrix is employed initially to highlight the probability of misclassification among different categories. In the context of path extraction, paths are designated as positive and the background as negative. The evaluation begins by calculating the four basic indicators for binary classification tasks based on actual and model-predicted categories: True Positive (_TP_), True Negative (_TN_), False Positive (_FP_), and False Negative (_FN_). Below are the formulas used to compute these metrics:  
\[Accuracy=\frac{TP+TN}{TP+TN+FP+FN} \tag{3}\]  
\[Precision=\frac{TP}{TP+FP} \tag{4}\]  
\[Recall=\frac{TP}{TP+FN} \tag{5}\]  
\[IoU=\frac{TP}{TP+FP+FN} \tag{6}\]
# Digital Content Management Using Non-Fungible Tokens and the Interplanetary File System
## 4 Digital Content Management (DCM) System  
IPFS is a new protocol that addresses the limitations of the existing hypertext transfer protocol (HTTP). Figure 4 shows the processing of an IPFS-based DC call. The processing sequence after the content address is addressed as follows: DHT/routing->BITTORRENT/File exchange->DAG/merkledag->SFS/naming->application. Herein, IPFS is invoked through the content hash instead of the traditional method of addressing the domain name.  
NFT-based DCMs employ the tamper-proof characteristic of IPFS files to the DC procedure on the blockchain and check for changes in the DC metadata, as shown in Algorithm 2. If we explain the procedure in Algorithm 2, the digital content (DC) is comprised of blocks (b), each having three components, such as b1, b2, b3. Utilizing these three elements (b1, b2, b3), a hash function (H) is employed to generate a single value, represented as p[p1, p2, p3]. The 'generate' function maps the digital contents to each block, where, for instance, p1 is mapped to b1 and p2 is mapped to b2. The interplanetary file system (IPFS) is responsible for storing digital content and includes users (u) and servers, such as S1, S2, S3, Sn. Each server (S1, S2, S3, Sn) currently holds subsets of digital content, and lastly, S4 does not hold any content.  
```
DC: Digital Contents  b: block = {b1, b2, b3}  p[p1, p2, p3] = H(b1, b2, b3)  generate = {p1,b1}(p2,b2)(p3,b2)  IPFS = {u, S1, S2, S3, Sn}DC  S1 = {p1, P2, P3}  S2 = {p1, P2, P3}  S3 = {p1, P2, P3}  S4 = {}
```  
**Algorithm 2**_IfProcedure of DCM_  
First, IPFS allows node u to request a DC sent via a smart contract using the systems connected to the IPFS. If the system sends a DC that is not stored at u, the node constructs the complete DC by assembling the partially received pieces of information. The DC, which comprises multiple blocks, is processed block-by-block using a hash and then assigned a unique name. After storing the names of all files in a database, duplicate files are eliminated, and the version information of each file is tracked. Subsequently, each node (u, S1, S2, S3, S4) stores only the required files, and the indexing information is used to determine the file stored at each node. To find a file on the network, the file name is first searched; thereafter, the node that has the file stored is contacted.
# Mdpi
## 2 System Model
### Additive Noise Model  
For indoor BB-PLC systems, asynchronous IN is the dominant source of noise [26]. In this paper, we consider two additive noise sources: background noise and asynchronous IN. We assume that background noise \(w[n]\) is additive white Gaussian noise (AWGN) with zero mean and variance of \(\sigma_{w}^{2}\). The asynchronous IN \(i[n]\) is modeled as Bernoulli-Gaussian (BG) IN [27] with zero mean and variance \(\sigma_{i}^{2}\) and can be described as follows:  
\[i[n]=b[n]\cdot g[n], \tag{3}\]  
where \(b[n]\) denotes the Bernoulli process with a probability of success \(p\) and \(g[n]\) is the white Gaussian process with zero mean and variance \(\sigma_{g}^{2}\). Note that we use the occurrence probability of IN \(p\) and the Gaussian-to-impulsive-noise ratio (GINR) \(\Gamma:=\sigma_{w}^{2}/\sigma_{l}^{2}\) to characterize the intensity of the IN. A higher value for \(p\) and smaller value for \(\Gamma\) indicate a situation with a stronger noise within a channel. The  
Figure 2: Details in an inverse IDWT block with \(M\) subchannels.  
probability density function (PDF) of the aggregated noise \(\eta[n]=w[n]+i[n]\) seen by the receiver is given as follows:  
\[P_{\eta}(\eta)=(1-p)G(\eta,0,\sigma_{w}^{2})+pG\left(\eta,0,(1+\Gamma)\sigma_{I}^ {2}\right), \tag{4}\]  
where \(G\left(\cdot\right)\) denotes the Gaussian PDF, which is defined by:  
\[G(\eta,\mu,\sigma^{2})=\frac{1}{\sqrt{2\pi}\sigma}\exp\left(\frac{-(\eta-\mu) ^{2}}{2\sigma^{2}}\right), \tag{5}\]  
where \(\mu\) and \(\sigma^{2}\), respectively, denote the associated mean and variance. Thus, the received signal can be expressed as follows:  
\[r[n]=s[n]\otimes h[n]+w[n]+i[n], \tag{6}\]  
where \(s[n]\) is the channel input signal; \(h[n]\) denotes the channel impulse response (CIR) of the powerline; and \(\otimes\) represents the convolution operation.
## 5 Proposed User Authentication System  
Under the threat model described in Section 4, we showed that the existing certificate-based authentication system could be vulnerable to _offline_ password guessing attacks. This is because the stored key data are encrypted only with the user's password in such systems.  
We suggest a new method to protect the user's sign key, \(sk_{u}\), from offline guessing attacks. The encryption key can only be generated with the assistance of a secondary device. To develop a fully working system, we considered two types of secondary devices: (1) an Internet server and (2) another user device that is nearby via a short-range network channel (e.g., Bluetooth or ZigBee).  
We assume that the user device \(d\) is connected to the Internet in most cases through Wi-Fi or the mobile device's LTE/4G connection. In some situations, however, \(d\) cannot be connected directly to the Internet. First, even though LTE/4G connection can cover most places in which controllers are located, the cost of LTE/4G data service plans is not widely in favor of end users; hence, they may resist using the LTE/4G service. Second, many client devices such as laptops do not directly support LTE/4G radios and hence rely on Bluetooth or Wi-Fi to send/receive data. Third, the service coverage is not guaranteed in certain areas (e.g., rural or underground buildings). Therefore, we considered a secondary device equipped with short-range communication as a backup plan in case an Internet server is unreachable from device \(d\), for example, while it is being restored.  
The proposed user authentication system consists of five components: user \(u\), device \(d\), controller \(c\), salt server \(s\), and mobile phone \(m\). Device \(d\) could be a mobile phone or laptop of user \(u\) and refers to a separate device from \(m\). Salt server \(s\) and mobile phone \(m\) in the proposed system provide two complementary options to obtain the additional parameters, i.e., \(salt^{1}\) and \(salt^{2}\), which are required to generate the encryption keys, i.e., \(k^{1}\) and \(k^{2}\), respectively. The only difference between \(s\) and \(m\) is that \(s\) is connected with \(d\) via the Internet and \(m\) is connected with \(d\) via short-range communication. It is assumed that \(d\) has secure network sessions with \(s\) and \(m\) via, for example, SSL/TLS and Bluetooth protocols. The proposed system also has two phases: (1) encryption key generation and (2) user authentication. We present the detailed procedure of each phase in the following sections.
Comparison of Physical Activity Training Using Augmented Reality and Conventional Therapy on Physical Performance following a Total Knee Replacement: A Randomized Controlled Trial  
[PERSON]  
Department of Physical Therapy, Summoon University, Asan 31460, Republic of Korea  
[PERSON]  
Correspondence: [EMAIL_ADDRESS]  
[PERSON]  
Department of Physical Therapy, Summoon University, Asan 31460, Republic of Korea  
[PERSON]  
Department of Physical Therapy, Summoon University, Asan 31460, Republic of Korea
factors [10; 12], may impact early functional recovery. For instance, [PERSON], et al. [9] found that gender affected muscle and physical function during the first month after TKR. Their study showed that women had a smaller decrease in quadric strength but had a higher decline in physical function compared to men after physiotherapy sessions. Regarding self-motivation, it is important to introduce exercises that may constantly draw one's attention.  
In order to increase motivation, many health professionals have recently implemented augmented reality (AR) technology in training sessions [13]. Hence, as the demand and interest for AR technology in rehabilitation have grown, the number of studies on AR has suddenly increased in the last ten years [14]. AR is a technology that combines digital information with information from physical environments and allows users to interact simultaneously with virtual objects in real time using enhanced 3D effects [15].  
According to a previous systematic review, there are many studies that evaluated the effectiveness of virtual technology using telerehabilitation systems, but only a few studies used AR [16]. Previous studies using AR have focused heavily on its efficacy in surgery methods [17; 18] or on the physical performance of older adults [19]. In other words, there is a need for evidence regarding the effectiveness of AR-based training on the physical performance of patients after orthopedic surgeries. A previous pilot study on healthy adults showed the potential effectiveness of physical exercise using AR on balance and ROM [20]. However, it remains unclear whether physical exercise using AR in patients post-TKA would be effective to reduce pain and improve functional ability (ROM, balance, muscle strength). Moreover, there is less evidence on whether physical exercise using AR would be more effective than conventional physical therapy.  
Therefore, the purpose of this study was to investigate the effectiveness of physical exercise using AR on pain, ROM, muscle strength, and balance during the early stage of rehabilitation in patients post-TKR and compare it to conventional physical therapy. Our hypothesis is that training with AR would rapidly decrease pain through the sensation of distraction (cognitive distraction) and improve functional ability and its effects would be superior to conventional physical therapy in patients after TKR.
# Advancing Crop Yield Predictions: AQUACROP Model Application in Poland's JECAM Fields
## 2 Materials and Methods
### Data Processing Methodology  
This section provides details regarding the methodology (Figure 2) used for acquiring predictive data based on the AquaCrop model and input data obtained from various sources.
## 6 Conclusions  
In this research, the monitoring system was improved, the results of the microseismic events were analyzed, and the data were processed. The following three conclusions were obtained from the data from the real-time monitoring using the cumulative apparent volume and energy index algorithms.  
1. On the basis of the original monitoring system, a monitoring system suitable for the bottom stability of the first mining section of the Pulang copper mine was established, and the design of the bottom structural stability monitoring scheme and system construction were completed on the premise of ensuring the accuracy and reliability of monitoring data and reducing the maintenance of the system, which met the testing requirements after the error and sensitivity calibration and debugging.
2. Using the cumulative apparent volume and energy indices to visualize the propensity for rockbursts, the rise in the cumulative apparent volume leads to an increase in the number of rock ruptures, while the rise in energy index indicates a continuous accumulation of energy density with a tendency to rockburst; the timeliness of both makes the cumulative apparent volume predictive of rock rupture and rockburst occurrence.
3. The test results are timely and standardized compared with conventional monitoring and physical simulation. In addition, the test results guide the prediction of rockburst propensity, the analysis of fault activation mechanisms, and the safety of over-fault coal mine operations.  
Conceptualization, Z.C. and C.Z.; data curation, D.Z., P.W. and Q.L.; formal analysis, F.S.; project administration, D.Z.; resources, Z.C., D.Z. and P.W.; visualization, Z.C., Q.L. and F.S.; writing--original draft, Z.C. and C.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Youth Science and Technology Innovation Fund, BGRIMM Technology Group (Grant No. 04-2228), and the National Key Research and Development Program of China (Grant No. 2017 YFC0602904).  
Not applicable.  
The data used to support the findings of this study are available from the corresponding author upon request.  
We thank [PERSON], [PERSON], and [PERSON] for improving the manuscript.  
The authors declare no conflict of interest.
## 3 Problem Analysis
### The Test Procedure  
A new test procedure was designed to correctly identify the influence of the system architecture on the accuracy of cylinder movements. As the tests indirectly involved the phenomenon of mutual interactions between the control elements and the hydraulic cylinder, an assumption was made that the experiment results will be subjected to a comparative analysis with the use of statistical tools. This approach resulted from the fact that the accuracy of the hydraulic cylinder movements is affected by a number of factors, such as the temperature, and thus also the viscosity of the liquid, the design and dynamic characteristics of the valves, momentary value of mechanical and hydraulic energy in the system, the influence of the pressure load on the dynamic response of the valves, etc. Not all of such relationships are currently known and described, as for example is the effect of possible temporary opening of the valves due to the variable pressure load and not to the control signal. Moreover, some parameters, such as the liquid temperature, are variable in time and change during the tests. Therefore, in order to ensure possibly constant test conditions, the proposed test procedure involved a limited number of repetitions, which still allowed the comparative analysis with the use of statistical tools.  
The control system sent the signal to close the valve at the moment when the cylinder reached its preset extended position. During the tests, the cylinder started its movement from the completely retracted position. In the next step, hydraulic power was supplied to the piston chamber and simultaneously the piston rod chamber was connected to the reservoir. After the cylinder reached the maximum extension speed of 75 mm/s and the preset extension of 95 mm, the control system disconnected the power supply to the coil (first and third solution) or to the coils (second solution). Five test cycles were performed for five different loads of the boom system (Figure 4). Each of the cycles served to measure the responses of the system in all three control system architectures. Each measurement was performed three times. The measured signals were recorded at a frequency of 500 Hz.  
Figure 4: Test stand with visible loading masses.  
The pressure relief valves were set to 20 MPa. During the tests, the hydraulic oil temperatures remained within a range from 45 to 55 \({}^{\circ}\)C. The oil was heated in a circuit which allowed for the flow through the valves and the cylinder.
# Privacy-Preserving Solution for European Union Digital Vaccine Certificates
## 6 Security Analysis
: Since the modifications of the Show-Verify protocol do not affect the credential generation, the proof follows directly from the anonymity of the KVAC protocol [21]. We recall the definition of key-parameter consistency:  
**Definition 4**. : _A keyed-verification credential system is key-parameter consistent if for any PPT adversary, the probability that \(\mathcal{A}\) given \(params_{I}\) can produce \((params_{I},sk_{I_{1}},sk_{I_{2}})\) with \(sk_{I_{1}}\
eq sk_{I_{2}}\) such that \((params_{I},sk_{I_{1}})\) and \((params_{I},sk_{I_{2}})\) are both in the range of \(\texttt{Setup}(1^{x})\) is negligible in \(\kappa\) (where the probability is taken over the choice of \(params_{I}\) and the random coins of \(\mathcal{A}\))._  
**Theorem 5** (Key-parameter consistency). : _Our scheme is key-parameter consistent as defined in Definition 4._  
Proof. : Following the KVAC protocol proof [21], Setup outputs \(sk=(x_{0},\ldots,x_{n})\in\mathbb{Z}_{q}^{*}\) and \(params_{I}=(x_{0},\ldots,x_{n})\), where \(x_{i}=g_{2}^{x_{i}}\). Since \(\mathbb{Z}_{q}^{*}\) is a prime order group, all of its elements have a unique discrete logarithm, and therefore, there is a unique \(sk\) corresponding to every \(params_{I}\). **7. Implementation Details**  
In this section, we present our proof of concept implementation of privacy-preserving digital vaccine certifications. The implementation serves primarily to evaluate performance tests and verify the functionality of the proposed solution. On one side, we have a smartphone application that is used by users to download and store their own digital vaccine certificates. If users need to prove themselves with the certificates, the application has the functionality to check the attributes required by the verifier (i.e., the service provider). These attributes are then displayed to the users, and their action is required (i.e., their approval or rejection). The user application is developed for the Android platform. We use the Kotlin programming language and the Android Studio development environment for its implementation. The application implements all algorithms presented in Section 5.2 and uses BLE communication to send the digital certificates from the user to the verifier. On the second side, we have a verifier's terminal application which is also implemented in Kotlin and partially shares the program code with a user's smartphone application. The source codes of our applications are publicly available on the online GitLab repository here: [[https://gitlab.com/brno-axe/mvcr-adiposio](https://gitlab.com/brno-axe/mvcr-adiposio)]([https://gitlab.com/brno-axe/mvcr-adiposio](https://gitlab.com/brno-axe/mvcr-adiposio)), accessed on 1 September 2023.