esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
### Motivation  
Many factors have motivated us to perform this study. Major factors are discussed below:  
1. Researchers want to study the effects of UML modeling on different software development phases, particularly on the maintenance phase. As many empirical studies in Software Engineering are done on open source projects, the automated extraction and analysis of large sets of project data become possible. For researching the effects of UML modeling in open source projects, we need a way to automatically determine the type of UML use in a project [15].
2. Nowadays, there are many UML CASE tools, which give many features like creating and modifying UML models, exporting models into XMI files, export models into images and automatically generating the user code backbone. UML CASE tools typically can work with different file types for storing UML models. Unfortunately, these file types cannot be exchanged with another one. Until now, CASE tools do not support extracting UML models from images. Thus, there is a need to automatically extract UML Class models from images without redrawing the model using a CASE tool [7].
3. As discussed above, it is not easy to learn UML, and because of that, creating a repository of different diagrams of UML will help novice developers to learn from the experience of expert developers who created UML diagrams that were used to develop good quality software and kept in the repository. Many different kinds of UML images on the web make the possibility to retrieve their modeling information for reuse purposes exciting.
4. Different UML diagrams need to be analyzed because of several reasons. Identifying syntactic inconsistencies is one of the reasons. To analyze the supposed class diagrams, it would be required to automatically classify class diagrams from the repository of different UML diagrams.
## 2 System Model and Channel Description
### Maritime Wireless Channels  
Compared with terrestrial communications, marine communications possess a distinctive and prominent characteristic, namely sparsity, which is crucial to determining the performance and operational modalities of marine communication systems. This sparsity is primarily manifested in two significant aspects: one is sparse scattering, and the other is sparse user distribution [31]. Since there are few obstacles over the sea, the scattering of electromagnetic waves is sparse. Consequently, line-of-sight (LoS) paths prevail in most maritime communication links. From this perspective, the Rayleigh fading model, which is commonly adopted in terrestrial communications with rich scattering, is not suitable for marine communications. The inadequacy of Rayleigh fading stems from its assumption of omnidirectional scattering, which contradicts the sparse scattering nature of maritime environments. In contrast, the Rician model's explicit incorporation of a dominant LoS component aligns with empirical observations of over-sea propagation, where non-line-of-sight (NLoS) paths are typically limited to sea surface bounce and sporadic atmospheric refraction.  
As stated in [9], the Rician fading model, consisting of LoS and NLoS components, is capable of predicting the propagation behavior of electromagnetic waves over the sea. The channel coefficient \(h\) under Rician fading can be modeled as  
\[h=\sqrt{\frac{\mathcal{K}}{\mathcal{K}+1}}+\sqrt{\frac{1}{\mathcal{K}+1}}h_{s}, \tag{3}\]  
where \(\mathcal{K}\) is known as Rician factor. It quantifies the relative strength of LoS versus NLoS components [32]. A high \(\mathcal{K}\) value indicates that the LoS component dominates, suggesting a relatively clear and less obstructed path for the electromagnetic waves, while a low \(\mathcal{K}\) value implies a more complicated environment with significant contributions from the NLoS component due to multiple reflections and scatterings. Here, \(h_{s}\) is modeled as a complex Gaussian random variable with zero mean and unit variance. Notably, when \(\mathcal{K}=0\), Rician fading is equivalent to Rayleigh fading. In [10], a log-normal distribution with mean \(\mu_{\mathcal{K}}\) and variance \(\sigma_{\mathcal{K}}^{2}\) is proposed to characterize the Rician factor \(\mathcal{K}\) at sea. This means that the signal attenuation at sea exhibits exponential scaling in dB-domain measurements. The \(\mathcal{K}\) satisfies the equation  
\[\widetilde{\mathcal{K}}=10\cdot\log_{10}\mathcal{K}\sim\mathcal{N}(\mu_{ \mathcal{K}},\sigma_{\mathcal{K}}^{2}). \tag{4}\]  
The log-normal distribution of \(\mathcal{K}\) reflects the composite effects of maritime channel variations, including sea surface roughness, atmospheric ducting, and evaporation layer effects. Throughout this manuscript, we use \(\mu_{K,j}\) and \(\sigma_{K,j}\) to denote the mean and the standard deviation of Rician factor characterizing the channel between source node \(N_{i}\) and relay node \(N_{R}\), respectively, \(i\in\{1,2\}\).
# Secure and Efficient Deduplication for Cloud Storage with Dynamic Ownership Management
## 1 Introduction
### Contributions  
In this paper, we propose a secure and efficient deduplication protocol for cloud storage. Our proposed protocol offers the following advantages:  
* **Efficient alleviation of client's computational costs.** Our study focuses on scenarios where clients upload data directly to cloud storage services, necessitating the encryption of data for secure storage. Our proposed deduplication protocol is based on the secure data sharing in cloud (SeDaSC) protocol [5], which aims to enhance the computational efficiency for clients utilizing cloud services. Similar to the SeDaSC protocol, ours also integrates a third party called a cryptographic server (CS). The CS encrypts data and the CS executes the data deduplication process. And, our proposed protocol demonstrates efficiency in terms of client-side computational cost compared to existing server-side deduplication protocols.
* **Strong assurance of data privacy.** In the SeDaSC protocol [5], as clients transmit plaintext to the CS, there is a requirement for trust in the CS, leading to potential privacy infringements. Our protocol prevents the exposure of data to the CS by having clients blind encrypt the data before transmitting them to the CS. The CS then performs CE on the blind encrypted data, enabling deduplication on the encrypted data in cloud storage. Essentially, our protocol ensures privacy for both the CS and cloud storage.
* **Reduced third-party dependency.** Given that the CS in the SeDaSC protocol has access to data in plaintext, the security of the protocol relies heavily on placing strong trust in the CS. To reduce dependency on the CS, [PERSON] et al. proposed a method where the client employs convergent encryption even when a CS is in place [7]. However, this approach negates the advantage of the CS in reducing the client's computational overhead. In our protocol, the CS still performs convergent encryption, but the client has the capability to reduce its level of trust in the CS by providing data that are blindly encrypted.
* **Secure data management in cases of dynamic ownership changes.** Existing deduplication protocols using a CS [5; 7] do not specifically consider changes in ownership of data (stored in cloud storage) that may occur due to clients modifying or deleting data. Ref. [5] states that, upon revocation of ownership, clients cannot access the data stored in cloud storage. However, the method mentioned assumes that, without proper authentication of being the rightful owner, the client cannot decrypt the data as they possess only encryption key fragments. Hence, the mentioned process differs in dynamically managing ownership to acquire security elements. Clients' ownership changes are common scenarios in cloud services and data deduplication. Our protocol allows for secure deduplication even in situations where ownership changes occur frequently. By providing dynamic ownership updates, our protocol enhances security, ensuring both forward and backward secrecy.
## 1 Introduction
### Analyses Based Only on Modelling of Heat Transfer Through Window
[21] investigated the impact of different types of windows on energy consumption and CO\({}_{2}\) emission reduction in two locations: Merida and Yucatan (Mexico). Calculations of heat transfer in transient states through multi-glazed windows were performed based on a numerical model using the control volume method. It took into account heat conduction, free convection and radiation. The results of multivariate numerical simulations showed that the use of triple-glazed windows instead of single-glazed windows reduced heat losses under the design conditions by over 56% and 31% during the coldest and warmest day, respectively. The reduction in energy consumption and CO\({}_{2}\) emissions for this type of window installed in the north facade was 32.8%; in the south facade it was 29.2%, in the east facade 31.3%, while in the west facade the result was the smallest and amounted to 29%. [PERSON] et al. [22] investigated the value of the heat transfer coefficient of double-glazed windows placed in a roof. The calculations were performed using computational fluid dynamics algorithms in the Ansys/Fluent software environment. The numerical model was prepared for double-, triple-, and quadruple-pane window configurations. The results of the computer simulations indicated that the highest thermal resistance was obtained with an air gap width of 9 mm, regardless of the number of panes. The lowest heat transfer coefficient (U-value = 0.77 W/m\({}^{2}\)-K) was achieved in the case of a four-glazed window with a low-emission filter. Moreover, such a high thermal resistance increased the thermal comfort in the room, because the temperature of the inner surface of the glass was close to the internal air temperature. A very similar analysis to that described in article [22] was also performed by [PERSON] and [PERSON] [23]. The difference was that the windows were positioned vertically, and argon was additionally taken into account as a gas filling the space between the panes. The results of comprehensive numerical simulations performed in Ansys/Fluent software indicated that the optimal gap width was 12 mm regardless of the glazing unit. In addition, the four-glazed window filled with argon and covered with low-emission materials achieved a very low heat transfer coefficient of 0.4 W/m\({}^{2}\)-K. This study presented a correlation enabling the calculation of the U-value of a window depending on the number of panes,the emissivity of the coatings covering the panes, the width of the space between the panes and the type of gas filling this space. [PERSON] et al. [24] developed a comprehensive literature review that included a discussion of glazing system technologies and an assessment of opportunities to reduce energy consumption under various climatic conditions. Inter-pane fillings with gases, liquids, phase-change materials (PCMs) and aerogels were discussed in detail. The article was written in order to select the appropriate glazing system and the possible further direction of development of this type of technology.
## 3 Results and Discussions
### Workability of Mortar Incorporating Fibers  
The investigation into the impact of fiber length (five different lengths) and volume percentage (0.3%, 0.5%, and 1%) on the performance of CM revealed intriguing insights. Mortar formulations, designated as MC (without fibers), MWFT4, MWFT8, MWFT10, MWFT20, and MWFT-WO (made with WFT fibers obtained using 4 mm, 8 mm, 10 mm, and 20 mm sieves and without sieve, respectively), as well as MWFR4, MWFR8, MWFR10, MWFR20, and MWFR-WO (containing WFR fibers obtained using 4 mm, 8 mm, 10 mm, and 20 mm sieves and without sieve, respectively), were subjected to thorough analysis.  
The findings of the flow table for mortar, including fiber proportions of 0.3%, 0.5%, and 1% by volume, are presented in Figures 10-12, respectively.  
Previous studies [28; 29; 34; 35] have already revealed a decrease in the workability of mortar with fiber inclusion. The workability is affected by the length, surface morphology, and surface area of fibers [36]. Our study confirms and supports this observed trend. The results indicate that the length of the fibers has a minimal impact on the workability of mortar; however, the proportion of fibers has a more significant effect. When the volume of fibers is constant, it implies that the mass also remains constant. This correlation can account for the minimal impact of fiber length on the workability of the mortar. However, a marginal decrease in workability was noted when the length of fibers increased. A rise in percentage results in a drop in workability, and the addition of 1% of fibers demonstrates the lowest level of workability. When comparing WFT (polyethylene) and WFR (polypropylene), the inclusion of WFR fibers results in a greater decrease in workability compared to WFT fibers. The increased water absorption coefficient of WFR fibers may be the reason for this relatively higher decrease in workability.  
Figure 10: Workability of mortar, measured using a flow table for each size (the proportion for each fiber length included is 0.3% by volume).  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Sieve Size**} & \multicolumn{2}{c}{**Electricity Consumption (kWh)**} & \multicolumn{2}{c}{**Time Required (Minutes)**} & \multicolumn{2}{c}{**Average Length (mm)**} \\ \cline{2-7}  & **WFT** & **WFR** & **WFT** & **WFR** & **WFT** & **WFR** \\ \hline
4 mm & 1.24 & 1.21 & 25.85 & 23.58 & 3.67 & 3.81 \\ \hline
8 mm & 1.07 & 0.98 & 22.48 & 19.45 & 8.67 & 7.22 \\ \hline
10 mm & 0.91 & 0.62 & 19.20 & 15.42 & 9.81 & 10.44 \\ \hline
20 mm & 0.74 & 0.44 & 15.87 & 13.73 & 15.81 & 14.
# Area of Operation Planning for Free-Floating Car Sharing Systems
## 3 Case Study for Vienna
### Mobility Demand Forecast
#### 3.2.3 Comparison of Data Sets  
We analyzed different properties of the data sets and identified trip durations as the most important one for comparing them, as these can be used directly as the trips' revenues within our optimization algorithm due to ELOOP's duration-based pricing model [15].  
Both the ELOOP and the OEU data set exhibit a wide variety of mobility behaviors that are typical for urban areas. Most trips take up to one hour, including a large number of regularly recurring trips for, e.g., commuting and shopping purposes. In contrast, longer trips, which gradually decrease in frequency as their duration increases, often represent those trips that do not recur on a regular daily or weekly schedule. Figures 2-4 show the absolute frequency of trips of different durations (up to three hours) for the three data sets.  
While the ELOOP data set contains more trips under 10 min than the OEU data set, the latter contains more trips with durations between 35 and 60 min due to the inclusion of public transport trips that could be replaced by comparatively shorter car sharing trips. Conversely, the taxi data set contains notably fewer trips of longer duration, most likely since taxi trips are more expensive and thus, mostly considered only for shorter trips. Like the ELOOP data set, both the OEU and taxi data set skew heavily towards shorter trips with 95 percent of their trips taking at most three or one hours, respectively.  
Although the ELOOP data set does contain a few exceptionally long trips with a duration of multiple weeks, over 95 percent of all ELOOP trips have a duration that is smaller than four hours. Trips of such long durations (spanning multiple days) are not present in the OEU and taxi data sets (on which our computational results are based). However, the absence of such extreme outliers is unlikely to significantly affect the design of the optimal area of operation.  
Figure 3: Duration histogram of the OEU data set.  
Figure 2: Duration histogram of the ELOOP data set.
## 3 Phase Change Materials
### Classification of PCMs
#### 3.1.3 Eutectic Mixtures  
The eutectic accrues from the mixture of two or more compounds of organic, inorganic, or both PCMs. In this way, an immeasurable number of eutectic mixtures can be fabricated. This gives the opportunity to produce a material with the desiring thermal properties, such as phase change temperature and latent heat. So, the most important advantage of eutectic mixtures is the ability of producing a material with the suitable phase change temperature for an application. The organic eutectic mixtures show some extra advantages in comparison with inorganic or inorganic/organic mixtures. These are the long-term stability, high phase change enthalpy, and facility of impregnating into porous support material due to their high chemical compatibility and surface tension. The main disadvantage is their high cost [14; 18]. Thermal properties of some hydrated salts and eutectic mixtures are presented in Table 4.  
\begin{table}
\begin{tabular}{l l l} \hline \hline  & **Advantages** & **Disadvantages** \\ \hline  & \multicolumn{2}{l}{Wide phase change temperature range.} \\  & \multicolumn{2}{l}{Thermally stable—no degradation.} \\  & \multicolumn{2}{l}{Chemically inert.} \\  & \multicolumn{2}{l}{Noncorrosive.} \\  & \multicolumn{2}{l}{Congruent melting process—no phase} \\  & \multicolumn{2}{l}{segregation.} \\ Organic & \multicolumn{2}{l}{High latent heat.} \\  & \multicolumn{2}{l}{Low thermal conductivity.} \\  & \multicolumn{2}{l}{Good nucleation properties.} \\  & \multicolumn{2}{l}{Low liquid phase sub-cooling capability.} \\  & \multicolumn{2}{l}{Minimal volume variation.} \\  & \multicolumn{2}{l}{Compatible with most of the construction} \\  & \multicolumn{2}{l}{materials.} \\  & \multicolumn{2}{l}{Recyclable.} \\  & \multicolumn{2}{l}{Low cost.} \\ \hline  & \multicolumn{2}{l}{Incongruent melting—phase} \\  & \multicolumn{2}{l}{High thermal conductivity.} \\  & \multicolumn{2}{l}{Poor nucleating.} \\  & \multicolumn{2}{l}{High energy efficiency (high enthalpy).} \\  & \multicolumn{2}{l}{Low volume change during phase} \\  & \multicolumn{2}{l}{transition.} \\  & \multicolumn{2}{l}{Non-flammable.} \\  & \multicolumn{2}{l}{Limited compatibility with} \\  & \multicolumn{2}{l}{construction materials.} \\  & \multicolumn{2}{l}{Higher cost.} \\ \hline \hline \end{tabular}
\end{table}
Table 3: Advantages and disadvantages of organic and inorganic phase change materials (PCMs).
## 3 Application Verification of Typical Karst Curtain Grouting Project
### Hydrogeological Conditions of Working Area  
#### 3.2.1 Law of Karst Development in Working Area  
According to the geological data of the field geological survey, the strata exposed by the surface and boreholes in the construction area are the Quaternary and the Shang-Lun formation in the Lower Devonian. The aquifer of the Shang-Lun formation in the Lower Devonian is the direct water-filled aquifer in the Da-Ling section of Panlong lead-zinc mine, which is the curtain protection area of the anti-seepage curtain project. The maximum depth level of strata exposure is \(-152.4\) m. According to the statistical results of karst revealed by drilling (Figure 4), the karst encountered by boreholes accounts for 87.09% of the total karst above the elevation of \(-80\) m, so this segment is a strong karst segment. In the elevation of \(-80\) to \(-120\) m, the karst encountered by boreholes accounts for 9.68% of the total karst, so this segment is a middle karst segment. Below the elevation of \(-120\) m, the karst encountered by boreholes accounts for 3.23% of the total karst, so this segment is a weak karst segment. From the vertical development law of karst revealed by boreholes, it can be seen that there are differences and inhomogeneity in the development of karst, and the degree of karst decreases with the increase of the depth of strata, which is consistent with the research conclusions of many scholars [13; 30; 31; 32].
# Statistical Model for Mobile User Positioning Based on Social Information
## 4 Model Assessment
### Results
These subfigures also point out that, as expected, high population density scenarios (Figures 5(a), 6(a) and 7(a)) embrace a greater number of connections than areas relatively depopulated, thus the use of population density to weigh the more probable areas is justified. More specifically, Figure 5(a),b shows the spatial distribution of the users applying the traditional E-CID method in both density cases. These subfigures evidence that the method equally distributes all the connections in the area covered by the serving ring, independently of the topology of the field or the high (Figure 5(a)) or low (Figure 5(b)) population density. The only variability is observed in Figure 5(a), where the greater number of connections and overlapped rings of TA show some irregularities in ring areas. Similarly, Figure 6(a),b presents the results obtained in the same areas with the context model (i.e., adding indoor context to the E-CID method). This positioning methodology takes advantage of the indoor context to segregate connections between buildings and open space. Although this behavior can be observed in areas with peaks of connections of both subfigures, this is more evident in Figure 6(a), where the amount of connections allowed to observe this effect, being able to clearly differentiate between connections on streets and inside buildings. Finally, Figure 7(a),b illustrates the results of the Social model, where the E-CID method is improved with both indoor context and social networks spatial information. With the inclusion of the social information, the context model is greatly improved in high populated areas (Figure 7(a)), enabling to obtain a much higher resolution in the location process. On the contrary, areas relatively depopulated (Figure 7(b)) are much less improved by the social information, performing similarly to the context model (Figure 6(b)).
## 2 Materials and Methods
### Characterization  
The crystalline compositions of PCS were identified by XRD (MAX-RB RU-200B) (Rigaku, Tokyo, Japan) at the scanning speed of 8\({}^{\circ}\) min\({}^{-1}\) and scanning range from 10\({}^{\circ}\) to 80\({}^{\circ}\)[17]. The scanning electron microscopy (SEM) images were obtained through SEM (Quanta FEG 450, FEI) analyzer (FEI, Hillsboro, OR, USA), together with Genesis EDS for compositional analysis. Chemical valence states of PCS were investigated by X-ray photoelectron spectroscopy (XPS), which was performed on a Thermo Fisher ESCALAB 250 Xi instrument (Thermo Fisher Scientific, Waltham, MA, USA) with an monochromatic Al K Alpha (1486.68 eV) X-ray source. The apparent morphology of CS, PCS and PCM were observed by digital camera. The specific surface area was measured from N\({}_{2}\) adsorption isotherms by Brunauer-Emmett-Teller surface area measurement (BET, ASAP 2020M, Atlanta, GA, USA). The pore size distribution, available pore volume and total porosity of CS and PCS were determined by Mercury intrusion porosimetry (Pore Master 60, Quantachrome, Boynton Beach, FL, USA). The working pressure was 3.45 kPa-413 MPa, allowing mercury intrusion in pores with diameters 1 nm-350 \(\upmu\)m.