esa-sceva/satcom-chunk-collection huggingface dataset:
# A Comprehensive Failure Risk Assessment Method of
## 2 Comprehensive Risk Assessment of the Machining Center Component Based on Topological Analysis
### Calculation of Independent Failure Risk of Machining Center Component Based on ANP
#### 2.1.3 Failure Rate Function of Machining Center Component  
In this paper, the Johnson method is used to correct the failure time sequence of components [22]. The two-parameter Weibull distribution commonly used in engineering is used as the hypothetical distribution of failure data of machining center components [23]. The construction process of the failure rate function is detailed in the literature [24], and then the failure probability function can be obtained as:  
\[F(t)=1-\exp\left[-\left(\frac{t}{\theta}\right)^{\gamma}\right],\;t\geq 0. \tag{2}\]  
The failure rate function is:  
\[\lambda(t)=\frac{\gamma}{\theta\gamma}t^{\gamma-1},\;t\geq 0, \tag{3}\]  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Score** & **Representation** \\ \hline
1 & Have the same degree of influence \\
3 & One element is slightly more influential than another \\
5 & One element is significantly more influential than another \\
7 & One element has a stronger influence than another \\
9 & One element is extremely influential than another \\
2, 4, 6, 8 & Represents the median value of the above adjacent judgment \\ Reciprocal & The degree of influence of element \(i\) on element \(j\) and the degree of \\  & influence of element \(j\) on element \(i\) are the reciprocal of each other \\ \hline \hline \end{tabular}
\end{table}
Table 1: 1–9 scale scoring method.  
where \(t\) is a time variable, \(t\geq 0\). \(\theta\) stands for scale parameter, \(\theta>0\), \(\gamma\) stands for shape parameter, \(\gamma>0\). The shape parameter determines the shape of the failure rate function curve. When \(0<\gamma<1\), it indicates that the failure rate is a decreasing function of time, which is characterized as early failure. When \(\gamma\approx 1\), it indicates that the failure rate is constant. When \(\gamma>1\), it indicates that the failure rate function is an increasing function of time, which represents loss failure.
## 3 Proposed System
### Calibration Method  
In this study, we assumed that the knee joint angle and the stretch sensor values can be represented by a linear function, and we calibrated the estimated knee joint angles accordingly. This calibration process for the stretch sensor was designed to reduce fitting errors and individual differences in knee bending. The calibration values were calculated from the flexion data included in the estimation data and the flexion data at the start of system use.  
First, a linear approximation is created from the scatter plot of the stretch sensor values and knee joint angles in the flexion data used for estimation. This approximation can be expressed by Equation (1), where \(y_{1}\) is the knee joint angle, \(x\) is the stretch sensor value, \(a_{1}\) is the slope, and \(b_{1}\) is the intercept.  
\[y_{1}=a_{1}x+b_{1} \tag{1}\]  
Next, a linear approximation is created from the scatter plot of the stretch sensor values and knee joint angles in the flexion data at the start of system use. This approximation can be expressed by Equation (2), where \(y_{2}\) is the knee joint angle, \(x\) is the stretch sensor value, \(a_{2}\) is the slope, and \(b_{2}\) is the intercept.  
\[y_{2}=a_{2}x+b_{2} \tag{2}\]  
Expressing \(y_{2}\) in terms of \(y_{1}\) gives Equation (3).  
\[y_{2}=\frac{a_{2}}{a_{1}}(y_{1}-b_{1})+b_{2} \tag{3}\]  
Figure 3: Supporter-type device.  
Therefore, the knee joint angle \(z_{1}\) estimated by machine learning to \(z_{2}\) can be calibrated using Equation (4).  
\[z_{2}=\frac{a_{2}}{a_{1}}(z_{1}-b_{1})+b_{2} \tag{4}\]  
For calibration in the flexion direction, the stretch sensor attached to the patella side is used, and for calibration in the valgus direction, the stretch sensor attached to the inner side of the knee is used.
## 3 Conventional Offline Motion Preparation
### Relevant Preparation Algorithms
Figure 3: B-spline-based least square algorithm bsLSQ, using [24]. **bsITER**: in the second B-Spline approach evaluated, [21] is used in the core, Figure 4. [21] uses an iterative algorithm to approximate the numerical solution of the equation system. By extending the calculation of the first and last control points from [24], C\({}^{2}\)-continuity between end of the spline and its beginning can be guaranteed. The algorithm is similar to bsLSQ, only the calculation of the solution differs. bsITER is also evaluated for the two check modes \"maximum only\" (bsITERmax) and \"all\" (bsITERall). **msITER**: this approach represents a very simple implementation of an iterative algorithm, Figure 5. It searches step by step for the shortest spline segment that meets the requirements. As described above, the considered segment is halved if it does not meet the requirements. The segment boundaries are thereby always set to already given, optimized points. If a segment fulfilling the requirements is found, a further run with the remaining points is performed. It is expected that the algorithm will be more performant than B-spline approaches with a similar or smaller amount of data. Figure 4: B-spline-based iterative algorithm bsITER, using [21]. Figure 5: Monomial spline-based iterative algorithm msITER. **msRECUR**: the fourth approach examined is a recursive one, Figure 6. It checks for a given part of the motion if the spline segment is as accurate as required. For this purpose, the function _calculateSplineSeg()_ is initially called with the complete motion, Figure 6, below. The function checks whether a spline segment, which was calculated using the 0 th to 2 nd derivatives at the ends, meets the given requirements. If this check is successful, the monomial spline segment is returned as a result. Otherwise, the motion is split into two parts at 50%. Again, the segment boundaries are located at given points. Both sub-motions are passed to another instance of the function. It is expected that this algorithm will achieve a minimum calculation effort with higher data volumes than msITER. This algorithm is the only one suitable for multi-threaded implementation. However, it does not reduce the required effort, but leads to faster processing. This case is not considered here.
# A Software Defined Radio Evaluation Platform for WBAN Systems
## 2 Preliminary and Related Work
### Radio Frequency Characteristic of WBAN  
The IEEE 802.15.6 standard covers a series of operating frequency bands: 402 MHz-405 MHz, 420 MHz-450 MHz, 863 MHz-870 MHz, 902 MHz-928 MHz, 950 MHz-958 MHz, 2360 MHz-2400 MHz, and 2400 MHz-2483.5 MHz. Each frequency band includes several sub-channels, which are shown in Table 2, where \(g_{1}(n_{c})\) and \(g_{2}(n_{c})\) are mapping functions used in the 420 MHz-450 MHz and 863 MHz-870 MHz frequency bands, respectively.  
\[g_{1}(n_{c})=\begin{cases}n_{c},&0\leq n_{c}\leq 1;\\ n_{c}+6.875,&2\leq n_{c}\leq 1;\\ n_{c}+13.40,&n_{c}=5;\\ n_{c}+35.025,&6\leq n_{c}\leq 7;\\ n_{c}+40.925,&8\leq n_{c}\leq 9;\\ n_{c}+47.250,&10\leq n_{c}\leq 11;\\ \end{cases} \tag{2}\]  
\[g_{2}(n_{c})=\begin{cases}n_{c},&0\leq n_{c}\leq 7;\\ n_{c}+0.5,&n_{c}=8;\\ n_{c}+1,&9\leq n_{c}\leq 12;\\ n_{c}+1.5,&n_{c}=13;\\ \end{cases} \tag{3}\]  
Based on the different bandwidth of these frequency bands and using the corresponding baseband parameter configuration, the data transmission rate is shown in Table 3.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Frequency Band (MHz)** & **Relationship between \(f_{c}\) and \(n_{c}\)** & **Number of Channels** \\ \hline
402–405 & \(f_{c}=402.15+0.30\times n_{c}\) (MHz), \(n_{c}=0,\ldots,9\) & 10 \\
420–450 & \(f_{c}=420.30+0.50\times g_{1}(n_{c})\) (MHz), \(n_{c}=0,\ldots,11\) & 12 \\
863–870 & \(f_{c}=863.20+0.40\times g_{2}(n_{c})\) (MHz), \(n_{c}=0,\ldots,13\) & 14 \\
902–928 & \(f_{c}=903.20+0.40\times n_{c}\) (MHz), \(n_{c}=0,\ldots,59\) & 60 \\
950–958 & \(f_{c}=951.10+0.40\times n_{c}\) (MHz), \(n_{c}=0,\ldots,15\) & 16 \\
2360–2400 & \(f_{c}=2361.00+1.00\times n_{c}\) (MHz), \(n_{c}=0,\ldots,38\) & 39 \\
2400–2483.5 & \(f_{c}=2402.00+1.00\times n_{c}\) (MHz), \(n_{c}=0,\ldots,78\) & 79 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The central frequency and number of sub-channels in each frequency band.  
Figure 6: The block diagram of the baseband transmitter.
## 6 Conclusions and Future Work  
Two routing protocols: reliability-aware routing (RAR) and reliability-aware cooperative routing with adaptive amplification (RACAA) are proposed for underwater acoustic wireless sensor networks (UAWSNs). RAR considers routing paths towards water surface with available relay nodes. Among all the selected paths, the most reliable path is chosen for packets forwarding. A reliable path has connected sensor nodes towards water surface and the highest probability of successfully transferring the data packets to surface sink. RACAA adds cooperative routing to RAR with adaptive amplification in which a relay node can increase its transmit power to cope with the fluctuating channel effects on data. Simulation results exhibit that RAR has superior performance in packets delivery to sea surface with lower delay. Similarly, RACAA further improves the packets delivery as RAR considers a single link for data routing which may not be always reliable. Since connected paths to water surface are chosen, nodes close to water surface bear more data traffic. To address this issue, a specific time frame for data processing will be defined in future investigation. The sensors nodes will process data only when they are requested by other nodes or when they sense some attribute and generate data packets by themselves. Otherwise, the sensor nodes will remain in dormant mode to conserve energy.  
[PERSON] proposed and implemented the main idea. [PERSON], I.A. and A.U.R. responded to the comments of the reviewers and streamlined the presentation of the manuscript.  
This research work is supported in part by the University of Malaya under Postgraduate Research Grant (PG035-2016A).  
The authors declare no conflict of interest.
# Cellulose Nanofibers and Other Biopolymers for Biomedical Applications. A Review
## 4 Outline of Biomedical Applications
### Delivery of Bioactive Molecules
Tumour molecular targeting peptide-1 (TMTP-1) was delivered via DBPs and shown to successfully target metastatic prostate cancer cells which express TMTP-1 receptors on their surface and exhibited low toxicity based on cell recovery post-transfection [174]. Hemicellulose/chitosan films cross-linked with epichlorohydrin were shown to be biocompatible, non-toxic and could be loaded with up to 18% of a model drug (ciprofloxacin). This material shows promise in both wound healing and drug delivery applications [175]. Xylan-based temperature and pH sensitive hydrogels were prepared, which showed a drug encapsulation efficiency of up to 97.6% and cumulative release of acetylsalicylic acid of 90.12% and 26.35% in intestinal and gastric fluids, respectively. The hydrogels were shown to be biocompatible and could be promising candidates for drug carriers for intestinal targeted oral drug delivery [176]. pH-responsive prodrug nanoparticles based on xylan-curcurcumin conjugates were developed to enhance the therapeutic efficacy of curcumin in cancer therapy. The cytotoxic activity of the prodrug nanoparticles against human colon cancer cells (HT-29, HCT-15) showed a greater cytotoxic effect than curcumin alone. Therefore, these results reveal xylan-curcumin nanoparticles could be a promising candidate for improving the intracellular delivery of curcumin in cancer therapy [177]. Lignin-based hydrogels were prepared with lignin contents ranging from 24% to 40% and water uptake capabilities up to 500%. The hydrophobic nature of lignin facilitated loading of a model hydrophobic drug (curcumin). The hydrogels were capable of sustaining the delivery of this compound for up to four days, and the inclusion of lignin also provided the material with significant resistance to bacterial adherence when compared to similar hydrogels without lignin [156]. Lignin was combined with microcrystalline cellulose and investigated as an excipient in the production of directly compressed tablets containing tetracycline. The presence of lignin in the tablets significantly modified the release profile and the maximum amount of tetracycline released, and lignin provided antioxidant properties to the formulations. Accordingly, this showed the potential of lignin to be used as a pharmaceutical excipient [112].
## 4 Properties
### Surface Properties
#### 4.3.1 Contact Angle  
CA measurements represent one of the simplest methods to determine changes that take place in the very outer layer of materials. CA is the angle at which a liquid/vapor interface meets a solid surface. By analyzing water CA information on the surface hydrophilicity and hydrophobicity can be gained. CA is a function of the chemical and physical nature of the surface, which depend on the material itself, i.e., its chemical composition, the surface treatment (physical, chemical, and thermal), the surface \"history\", and the surface cleanliness.  
If the selected liquid is very strongly attracted to the sample surface the droplet will completely spread out on the surface, hence the measured contact angle will be very low, less than 10\({}^{\circ}\). Surface with water contact angle until 90\({}^{\circ}\) will be defined as hydrophilic, while surface will be defined hydrophobic, if the water contact angle is higher than 90\({}^{\circ}\), or more in the case of materials with high rough surface that show water CA greater than 150\({}^{\circ}\), called superhydrophobic surfaces. Furthermore by analyzing the CA of two liquids with completely different properties information on the surface energy can be gathered.  
Polymers display a typical water CA that could be modified by chemical and physical methods. Wettability is remarkably affected by the copolymer composition. For example, in the case of PBCE it has been observed a wettability increase with the increasing of BDG co-units content, that is the increment of ether-oxygen atoms along the PBCE backbone [38]. It ranged from 110\({}^{\circ}\) for PBCE, the more hydrophobic material, to 85\({}^{\circ}\) for P(BCE40 BDG60). As expected, hydrophilicity regularly increased with the enhancement of the BDG mol% [19; 39].  
The introduction of nanofillers could modify the surface properties of the materials, and further tune the CA. Usually, a hydrophilic surface could better interact with the cell environment. PBCE nanocomposites containing MWCNTs showed in all cases a decrease of the water contact angle with respect to the pristine polymers. These results may be ascribed to the different surface morphology of the samples under investigation, which is affected by the nanofiller introduction, in terms of content, shape, aspect ratio, and processing technology. Through this study it has been possible to demonstrate that the surface wettability is mainly affected by two factors, i.e., the chemical composition and the surface morphology [38].
# Design of CubeSat-Based Multi-Regional Positioning Navigation and Timing System in Low Earth Orbit
## 3 Results
### System Budgets
#### 3.6.4 \(\Delta\)V Budget  
Regarding the \(\Delta\)V budget, it consists of two sources of fuel consumption; the station-keeping of the S/C and the phasing maneuver required for the S/C to be equally spaced within each orbital plane. An STK analysis was performed in both cases.  
The primary causes of a satellite's loss of altitude are atmospheric drag and solar radiation pressure. Their combined vector was modeled in STK, and by analyzing its values over a year, the average deceleration exerted on the satellite can be determined. Therefore, the \(\Delta\)V required for 3 years of station-keeping can be calculated. In the STK simulation, a worst-case scenario was considered, where the S/C's cross-sectional area was assumed to be 2133 cm\({}^{2}\) (S/C's larger cross section). This resulted in 41.7 m/s or 62.6 m/s with a 50% margin needed for station-keeping.  
The mission requires ten S/Cs to be phased within a single orbital plane at an altitude of 550 km so that they are evenly spaced in it. To account for the worst-case scenario, the \(\Delta\)V required to phase a single satellite by 180 degrees is to be calculated.  
Additionally, it is assumed that after this maneuver is completed, N days or approximately N-15 orbital periods of the satellite at its original altitude of 550 km are going to pass before readjusting its orbit to the original one with a second burn.  
The philosophy behind these maneuvers is that by performing a burn to change the altitude of the satellite, its period is going to change by \(\Delta\)T. More specifically, by lowering the altitude of a satellite that has a period of T, it will change to T', and the periods will be related by the formula \(\mathrm{T^{\prime}=T-\Delta T}\). Over the course of N orbits, this difference in orbital period will accumulate into a 180-degree phase shift, equivalent to half of the original  
Figure 11: Battery SoC—day in the life simulation—nominal scenario for a single day (**a**) and for 5 days (**b**).  
orbital period, and then by performing a second burn in the opposite direction, the satellite shall return to its original orbit. This can be expressed mathematically as N\(\cdot\)\(\Delta\)T = T/2. By having knowledge of the S/C's initial state and its desired orbital period after the maneuver, it is possible to calculate the \(\Delta\)V required via STK. This is achieved using the Astrogator propagator by inserting a \"Target Sequence\" item with a \"maneuver\" nested within it. The results are shown in Table 8.  
Thus, the total \(\Delta\)V required for a 10-day phasing maneuver and station-keeping is 89.6 m/s. Using the Tsiolkovsky equation and having the assumptions that the S/C's mass is 11.3 kg, out of which 200 g is propellant and an Isp of 1500 s, the S/C's \(\Delta\)V capabilities are calculated to be >260 m/s. This results for a residual \(\Delta\)V for collision avoidance maneuvers and deorbiting of >170 m/s.
## 6 Key Findings
### Open Challenges and Future Work
#### 6.2.3 Revocation of Certificates  
Most of the analyzed state-of-the-art academic platforms include the possibility of invalidating previously issued certificates, something which is challenging due to the immutable nature of a blockchain. However, the platform proposed in this article makes this process seamless. This is because the revocation can be seen as another update in the state of an AR that it is aimed at correcting an error. Therefore, a specific department of the university would amend the error on the off-chain AR of the student.  
For instance, an example of use case can occur when the completion of a degree needs to be amended, which in the proposed platform would involve to set the corresponding boolean field to false. Such a change would be confirmed in the validation process by a specific commission of administrators. Once confirmed, the prior AR hash would be overwritten with the amended one. This means that if a third-party introduces the AR that specifies the completion of a degree marked as true, the platform would not find such AR hash in the smart contract, so it would mark it as invalid. This process would be enabled thanks to the enhancement proposed in Section 6.2.2, where student addresses would be linked to their AR hash.
## 2 Technologies Involved
### RESTful Web Services for Communicating with the Cloud  
Access to the services provided by the cloud has to be direct, open and interoperable, so the communication mechanisms used and the APIs provided should be easy to implement for each platform and development environment [15]. The principal mechanism for providing access to cloud platforms is Web Services. Using standard communication mechanisms based on HTTP, a Web Service can give certain functionality to other developers so that they can integrate it into their applications without knowing how it is implemented or the platform on which it is deployed. As advantages, we can mention the independence of both the language and the platform, and Web Services are based on the exchange of XML message standards. Moreover, most Web Services send HTTP messages, resulting in an advantage for the development of Internet-based applications.  
There are currently two options for the development of web services: the traditional approach based on the exchange of SOAP messages and other REST-based approaches [16; 17]. SOAP is a standard that describes the exchange of XML-based information with a specific format that describes the communication between clients and Web Service messages. REST is a software architectural style for distributed systems such as the Web. The exchange of messages and extendable standards and the use of a global addressing scheme have led to the success of the Web, making it scalable to the level of the Internet. REST motivation arises in the extension of these features. Its aim is to describe any interface that transmits specific data from a domain over HTTP without an additional layer, as SOAP does. It should be noted that REST is not a standard, just a style of architecture that is based on standards such as HTTP, URL, XML, etc. Accordingly, unlike SOAP, REST can access the contents of a service using HTTP GET or POST requests, remove it through HTTP DELETE requests, or update with HTTP UPDATE requests. A REST-based service includes four aspects: (i) the URI that represents and identifies the service; (ii) the types of service supported by the data (usually JSON, XML or CSV); (iii) the set of operations supported by service and accessible via HTTP; and (iv) the API requests to be specified in a hypertext language. REST's decoupled architecture and lighter weight communications between producer and consumer make REST a popular building style for cloud-based APIs
## 4 Results and Discussion  
### Testing Datasets  
Three datasets were selected for testing the methodology, which are characterized by different statistical and probabilistic characteristics:  
* A load profile extracted from a house located in the region of Ruse, Bulgaria, in the period 1-29 February 2024 (Figure 6a). It is characterized by power consumption varying in a wide range and significant peaks during the weekends. Residential load profiles are generally influenced by many factors, such as the type of day (weekday or weekend), hour of the day, meteorological conditions, people's lifestyle, holidays, etc.
* A load profile of a pig farm located in the region of Silistra, Bulgaria, in the period 1-31 August 2023 (Figure 6b). It is characterized by relatively similar daily variations, which can be explained by the agrotechnological requirements. Load profiles in livestock farming are influenced mostly by the schedule of the technological processes (lighting, feeding, ventilation, etc.) and the meteorological conditions.
* A load profile of a printing house, located in the region of Varna, Bulgaria, for the period 1-29 February 2024 (Figure 6c). It is characterized by significant electrical consumption during the working hours of the weekdays and almost zero consumption during the rest of the time. Industrial load profiles are greatly influenced by factors such as the type of day (weekday or weekend), hour of the day, daily schedule, holidays, and the meteorological conditions.  
\end{table}
Table 1: Sample training tab-delimited file containing a load profile.