esa-sceva/satcom-chunk-collection huggingface dataset:
# Towards a Cyber-Physical Range for the Integrated Navigation System (INS) System (INS)
## 3 The Composition of the INS  
Flag state requirements, class requirements, features of manufacturer products, and owner decisions directly affect the equipment in the INS. Given that the IMO identifies minimum international requirements for member states, the IMO rules and regulations constitute a baseline for this study. The stakeholders must meet the minimum IMO requirements, but they are allowed to enhance their own requirements. Therefore, defining basic criteria was required to determine the list of INS components. Even so, defining a generic equipment list comprising the INS is difficult, since several variables, such as the vessel's gross tonnage, the vessel's type, the navigation zone, the ship construction date, the assigned navigational tasks of the INS directly affect equipment fittings onboard ships. Accordingly, these parameters were also ignored in this study.  
Consequently, the INS component list was determined according to the documents mentioned in Section 2.1. Then, these components were investigated in terms of sub-components, services, data, interfaces, communication protocols, connections, and dependencies, using relevant IMO, ITU, International Organization for Standardization (ISO), and IEC standards and documents. A visual representation of the composition of the INS is depicted in Figure 1.
## 4 Conclusions  
* Summary of findings: Pure anatase, mixed anatase-rutile, or pure rutile-containing Cu-TiO\({}_{2}\) coatings were successfully obtained by varying the substrate bias during the one-step direct current magnetron sputtering of the mosaic Ti-Cu target metal in a pure O\({}_{2}\) atmosphere. During the deposition, the energy differences between the bombarding positive ions and the depositing atoms play a more significant role in the formation of film phase composition than the thermal mobility of the depositing atoms on the surface. The higher bias leads to thinner coatings with smaller grains, more lattice microstrain, and more defects, which together result in larger water contact angles and hardness values. The samples biased at \(-75\) V had the best coating-substrate adhesion strength, whereas the specimen biased at \(-50\) V showed superior corrosion resistance. The \(-25\) V biased sample with the highest copper content (2.62 wt.%) provided excellent antibacterial activity against both _E. coli_ and _S. aureus_ stains while that obtained at \(-50\) V indicated excellent bactericidal effects only against the Gram-positive germ. These one-step-fabricated Cu-containing TiO\({}_{2}\) coatings are appealing because they may achieve multifunctionality by changing the target composition and substrate biasing.
* Limitations: Even with these improvements, several drawbacks were found. The primary limitation is the possible mechanical or electrochemical instability of the coatings in a physiological medium during long-term exposure in the body. Additionally, the long-term antibacterial properties and biocompatibility of the coated implants have to undergo extensive in vitro and in vivo testing.
* Future work: By increasing the copper content in the target, the antibacterial performance of both \(-50\) V and \(-75\) V biased samples can be adjusted. Future research should explore the in vitro integration of the coatings with optimized process production parameters by assessing the molecular biomarkers that can further demonstrate their biomedical benefits.  
Conceptualization, M.P.N.; methodology, M.P.N. and M.D.A.; software, M.P.N. and S.Y.; validation, M.P.N., S.Y. and M.D.A.; formal analysis, Y.H.; investigation, M.P.N., S.Y., Y.H. and M.D.A.; resources, M.P.N. and M.D.A.; data curation, M.P.N.; writing--original draft preparation, M.P.N.; writing--review and editing, M.P.N., M.D.A. and S.Y.; visualization, M.P.N.; supervision, M.D.A.; project administration, M.P.N.; funding acquisition, M.P.N. All authors have read and agreed to the published version of the manuscript.  
This study was financed by the European Union-Next Generation EU, through the National Recovery and Resilience Plan of the Republic of Bulgaria, project BG-RRP-2.013-0001-C01.  
Not applicable.  
The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.
# Monitoring Acute Heart Failure Patients Using Internet-of-Things-Based Smart Monitoring System
## 4 Materials and Methods
### Rnn  
When we are talking about sequential neural networks, the Recurrent Neural Network (RNN) is the best choice [12]. During processing, the input sequence of one neuron is fed to other neurons in the same weighted sequence of words in a sentence. RNN sequences are designed in a manner that generates the sequence and predicts the next word coming in the loop.  
Convolutional Neural Network  
CNN is an effective neural network model that can learn complex relations among different data attributes. A CNN is a deep learning model that can analyze the input image, rank various features and objects within the image, and distinguish between them. CNN is made of a hidden layer, node layer, input, and output layer. To obtain better results, this study uses a customized CNN architecture, as shown in Figure 3.  
The proposed 8-layer architecture includes 2 dense layers, 2 max-pooling layers, and 2 convolution layers. For classification purposes in the medical field, CNN performance is the best and most accurate. In the CNN model, the Sigmoid is used as the error function and it is a backpropagation algorithm. CNN has been used for the classification of multiple diseases i.e., brain tumors, lung disease, and cardiac disease. Nowadays, it is extensively used in the medical field and deals with large amounts of data. The pooling layer in CNN can be maximum and average pooling, maximum pooling is mostly used for sharp feature extraction, while the average is used for flat feature extraction.
## 2 Volunteered Geographic Information
### Comparison of Recent VGI Projects  
In this section, we compare six different VGI projects that collect geodata in a collaborative way (Table 1). The comparison focuses on platforms that are providing more advanced geographical information, such as real-world features, in comparison to other VGI portals that solely share geolocated tweets or images. Furthermore, the comparison does not include other widely used LBS platforms, such as Google Maps, Telenav or Apple Maps, due to their limited VGI functionality.  
The oldest VGI project in our comparison is the aforementioned OSM project. A similar project, Wikimapia [39], was founded in 2006 and is not related to Wikipedia in any way. The four other projects listed in Table 1 (Map Maker [40], Here Map Creator [41], Map Share [42] and Waze [43]) were established several years after OSM claimed more popularity and are partially owned by well-known proprietary geodata providers. In the past, these platforms had a limited functionality that only allowedvolunteers to report an error in the map data in the form of a note (e.g., Map Share). Nowadays, registered members can create or make corrections to existing street data on almost all of the aforementioned commercial platforms. The data license and the availability of the collected information is a major difference between the compared VGI projects. In contrast to the aforementioned proprietary data providers, the OSM dataset is available under the Open Data Commons Open Database License (ODbL) [44], which allows users to copy, distribute, transmit and adapt the data, as long as OSM and its contributors are credited. More importantly, if the user alters or builds upon the OSM dataset, the results can be distributed under the same license. The collected data of the OSM and Wikimapia projects can be downloaded through a designated application programming interface (API) or as a complete database dump file.  
Although the Waze project claims to have the largest contributor base, we will discuss, at a later point, that a large number of registered members does not always imply better data quantity or quality.
# Real-Time 3D Reconstruction Pipeline for Room-Scale, Immersive, Medical Teleconsultation
## 4 Dual Contouring for Voxelized Point Clouds  
### Extension for Diagonal Connections  
Dual contouring is an isosurface extraction method for signed distance fields. In the work of [PERSON] et al. [17], the signed-distance samples and gradients are located at the corners of each cell. Therefore, a dual quad face is generated for each sign-changing cell edge with four incident cells. From the perspective of the sign-changing cell, each dual edge connection is formed across the 6-point neighborhood. The dual vertex is already present in the cell with voxelized point clouds, but it is not guaranteed that all occupied cells will neighbor across a shared edge (Figure 4a). Thus, the neighborhood must be extended to include all sets of four neighboring occupied cells, which share a common corner, i.e., the 26-point neighborhood of a 3D grid (Figure 4b).  
Figure 4: Neighborhood Sizes. Comparison of the neighborhood sizes and its consequences for 3D surface mesh reconstruction. The blue board is not aligned with the axes of the world coordinate system, causing a lot of diagonal connections to be missed in (**a**) that we consider with our method in (**b**).  
Figure 5: Mesh Texturing. Comparison between per-face and per-pixel selection of the optimal RGB-D camera. Per-face selection is inferior due to the simplified mesh topology.  
To accommodate the larger neighborhood that must be checked for point clouds, we extend the recursive procedures of [PERSON] et al. [17], named cellProc, faceProc, and edgeProc, with two new procedures, which we also name after the shared primal element, diagonalEdgeProc and cornerProc.  
For cellProc, up to 12 subprocedures of diagonalEdgeProc (Figure 6a) and 32 permutations of cornerProc (Figure 7) are added to original 8 cellProc, 12 faceProc, and 6 edgeProc subprocedures. In faceProc, 8 subprocedures of diagonalEdgeProc (Figure 6b) and all 32 combinations of cornerProc (Figure 8a) are added, since they additionally cross through both nodes. For edgeProc, 14 possible cornerProc combinations that involve all input nodes are added to the 2 faceProc subprocedures. If 1 of the 4 nodes in cornerProc is not a leaf, a single recursive case is generated (Figure 8c).  
Our diagonalEdgeProc procedure contains at least both involved nodes marked in green (Figure 6) and the 2 additional nodes neighboring this cell edge, if available because only 14 of 32 cornerProc cases are handled in edgeProc. The remaining 18 are handled here since some do not require 4 parent nodes like in Figure 8b. This representation will cause duplicate recursive calls to cornerProc if all 4 nodes in a primal edge are present, which can be solved by not calling the recursions on one of the two directions of diagonalEdgeProc. We chose this encoding for consistency with the original recursion [17]. More optimal encodings without duplicate cases may exist; e.g., if edgeProc is modified to have optional nodes, it accommodates all cases of diagonalEdgeProc.
# A Systematic Review of the Role of BIM in Building Sustainability Assessment Methods
## 4 Results
### BIM Application in SBTool  
The application of BIM in SBTool is still in an initial stage, with the proposal of conceptual approaches. The only identified study regarding SBTool and BIM dates from 2019 and has identified a BIM-based framework to assess the SBToolPT-H--Portuguese method--to assess the sustainability of residential buildings [5]. This study proposed the creation of an Autodesk Revit API, which can directly and/or indirectly support the evaluation of 24 out of the 25 sustainability criteria. Autodesk Revit was identified as the most useful BIM software in the SBToolPT-H case. It has the capability to support the assessment of more than a dozen criteria. This is due to the criteria characteristics, which are mainly quantitative data from the building model. Authors have also identified several common software that can be used to assess the remaining criteria, such as Autodesk Green Building Studio (GBS, developed by Autodesk, Inc, San Rafael, USA), Google Maps or Microsoft Excel [5].  
A practical application of the proposed framework was already preformed for 17 criteria on the categories of Land Use and Biodiversity (5 out of 5), Energy Efficiency (2 out of 2), Materials and Waste Management (5 out of 5) and Occupant's Health and Comfort (5 out of 5). From all, 12 of these criteria were assessed by creating shared parameters and using the schedule function of Autodesk Revit (and Microsoft Excel as an interface). The two criteria from the Energy Efficiency category (and one from the Occupant's Health and Comfort category) were assessed by exporting a 3D-model for Cypetherm REH (Cype Ingenieros, Alicante, Spain) and GBS, to perform the energy analysis. The two remaining criteria from the Occupant's Health and Comfort category were evaluated by exporting the Autodesk Revit model to Cypetherm EPlus and Cypesound RRAE (both from Cype Ingenieros, Alicante, Spain). Currently, seven criteria are still requiring practical validation, namely on the water efficiency category (2), accessibility category (2), lifecycle environmental impact (1) and the economic dimension (2). With a BIM-based API, authors aim at optimising and automating the assessment procedure of SBToolPT-H and support designers during the project phase. This study was published in the _Automation in Construction_ journal.
## 4 Discussion  
The model presented in this research can help to locate tall buildings. The method presented in this research is a combination of the two methods of planning and visual analysis. In the planning section, the criteria and sub-criteria are considered to determine the appropriate areas for the erection of tall buildings. Visual analysis is done in three dimensions based on fuzzy visibility; the positive and negative effects of tall buildings on the city are identified and help to decide on the appropriate location of the tall buildings. This model can be used for every desirable region and it suggests proper spots for all of them, provided there is localization of criteria.  
In most previous researches, the influential factors in locating tall buildings have been mentioned [32; 33], but the prioritization and weighting of these criteria have not been studied in detail. In this study, according to the results, land price, urban texture, population density, and traffic sub-criteria are at the highest level, and surface and groundwater sub-criteria are at the lowest level in locating tall buildings by prioritization. Other criteria like buffer, slope, per capita service, traffic nodes, fault, compatibility, and parcels are also placed among the list.  
Lack of access to accurate 3D images and maps of the city was one of the main limitations of this research. Although we tried to develop a comprehensive model, further studies can examine designing adjacent sidewalks criteria, facades and their details, a building's 3D model, parametric design according to the background characteristics, etc. The effects of vegetation have not been applied in the fuzzy visibility analysis in this research. By minimizing the study area, this factor can be included.  
Another thing to consider is the amount of visibility from inside of the yard. The visual analysis could accommodate different factors such as increasing legibility, making memories, and preparing maps to protect visually valuable axes.
## 2 Statistical Model
### Complex Watson Distribution  
Divide the acoustic space into \(K\) spatial regions and assume that the source, either the target speaker or the interference, is coming from one potential spatial region, TSL is then to infer the region that has the highest target presence probability. To describe the unit-length directional statistics, the complex Watson distribution is introduced. The probability density function is:  
\[\mathcal{W}(\mathbf{z};\mathbf{a},\eta)=\frac{(M-1)!}{2\pi^{M}\mathcal{K}(1,M,\eta)}\exp^{(\eta|\mathbf{a}^{H}\mathbf{z}|^{2})} \tag{4}\]  
where \(\mathcal{K}(\cdot)\) is the confluent hypergeometric function of the first kind, \(\mathbf{a}\) is a spatial centroid satisfying \(||\mathbf{a}||_{2}=1\), and \(\eta\) is a real-valued concentration parameter that governs the smoothness of the distribution [29]. Higher concentration values result in a peaky kernel, meaning that more weight is put on observations that are close to the centroid, while lower values of \(\eta\) lead to smoother score functions, however sacrificing resolution. This distribution features some good properties. Its value is properly normalized, and it naturally accounts for spatial aliasing, because the distance score \(|\mathbf{a}^{H}\mathbf{z}|^{2}\), which is equivalent to the normalized response of a beamformer, does not change if individual components of \(\mathbf{z}\) are multiplied with \(e^{l2\pi}\). The observation vector is then modeled by a mixture of [PERSON] distributions as:  
\[p(\mathbf{z}(t,f))=\sum_{k=0}^{K}\alpha_{k}(t)\mathcal{W}(\mathbf{z}(t,f); \mathbf{a}_{k}(f),\eta_{k}(f)) \tag{5}\]where the mixture weight \(\alpha_{k}(t)\) is the spatial presence probability in the \(k\)-th region at time \(t\) and satisfies \(\sum_{k=0}^{K}\alpha_{k}(t)=1\). Note that we additionally use \(k=0\) to model the background noise, which has an even probability of coming from all directions.  
For each candidate region, \(\mathbf{a}_{k}\) and \(\eta_{k}\) can be determined through Maximum Likelihood (ML) estimation given training data collected in advance [30]. They are stored as spatial dictionaries for the training environment and applied in further localization tests. In the localization phase, the mixture weights \(\alpha_{k}(t)\) are estimated by the maximization of \(\prod_{l=1}^{T}\prod_{f=1}^{F}p(\mathbf{z}(t,f))\), and the maximum peak in the weights would coincide with the target source.
# Anomaly Detection for Service-Oriented Business Processes Using Conformance Analysis
## 4 Data Preparation
### Checkpoints during Process Execution  
This section presents the steps to create checkpoints in the executing instances. Several techniques can be used to divide the complete trace of the process into several segments. The technique used by [PERSON] et al. in [PERSON] et al. (2018) used the percentage of the time spent from the starting date and time \((S_{d}t)\) of the process until target date and time \((E_{d}t)\), where \((E_{d}t)\) is an initial target for the process to be completed, as defined at the start of the process. Another technique is to create checkpoints based on the fixed duration checkpoints for the executing process instance. However, both of these techniques do not consider the domain knowledge of businesses. Process owners should be able to identify certain points in the process execution at which the identification of possible anomalies may be beneficial.  
In this work, a hybrid approach to checkpoint creation is used. Time-based thresholds are used as suggested in [PERSON] et al. (2018), and domain knowledge of business users provides major steps in the process of marking the time-based checkpoints. For experiments, two sub-logs are created from the event log of CDP as illustrated in Figure 5: one sub-log with only successful cases and the other with unsuccessful (failed) cases. Subsequently, each of these individual event logs is split into several segments contains the events that occurred during the identified period. The end-state of each case in the considered event log is labelled as either _successful_ or _failed_.  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Category** & **Number of Instances** \\ \hline Product-A customers & 2737 \\ \hline Product-B customers & 232 \\ \hline Product-C customers & 2 \\ \hline Product-D customers & 68 \\ \hline Product-E customers & 10 \\ \hline Product-F customers & 19 \\ \hline Product-G customers & 1036 \\ \hline Undetermined customers & 51 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Categories of customers in the diagnostic process dataset.  
Figure 4: Duration of cases in collected dataset from CDP. Screenshot of data explorer in ProM 6.10.
# Review of Photodetectors for Space Lidars
## 3 Space Lidar Detectors from Short-Wave to Mid-Wave Infrared
### Use of HgCdTe APD Arrays in Airborne and Future Spaceborne Lidars  
HgCdTe APD arrays were first used in an airborne continuous wave (CW) IPDA lidar for carbon dioxide (CO\({}_{2}\)) measurements at 1.57 \(\upmu\)m laser wavelength in 2013 [64]. The device was an 8 \(\times\) 8 pixel array from Leonardo DRS. The outputs from individual pixels were connected in parallel and then to a low-noise preamplifier outside the Dewar. Although the overall receiver noise was high due to the large stray capacitance, the HgCdTe APD array was instrumental in the successful demonstration of CO\({}_{2}\) measurement at 1.57 \(\upmu\)m from an airborne platform.  
The 4 \(\times\) 4 pixel HgCdTe APD arrays were successfully used in the airborne pulsed CO\({}_{2}\) IPDA lidar at 1.57 \(\upmu\)m laser wavelengths in 2014, 2016, and 2017 [65], and an airborne methane (CH\({}_{4}\)) IPDA lidar at 1.65 \(\upmu\)m laser wavelengths in 2017 [66]. The APD arrays were housed in closed-cycle cryo-coolers and cooled to 80 K. These detectors greatly improved the receiver performance compared to those with the near-infrared PMTs used earlier. The receiver linear dynamic range spanned four orders of magnitude, which was sufficient to measure aerosol backscatter and much stronger ground returns at a fixed APD gain and TIA gain setting. A similar detector system has been used for an airborne IPDA CO\({}_{2}\) lidar at 2.05 \(\upmu\)m laser wavelength and showed a major improvement in the receiver performance over the InGaAs APDs [67].  
The 4 \(\times\) 4 pixel HgCdTe APD arrays have also been used for prototype planetary science lidars. One such detector system was used in the development of a multifunction climate lidar for Mars to measure wind and atmospheric backscatter profiles from orbit [68]. A 4 \(\times\) 4 pixel IDCA is being used in the Spectroscopic Infra-Red Reflectance Lidar (SpIRRL) to measure water ice on the Moon in the 3 \(\upmu\)m water band. A 2 \(\times\) 8 pixel LMPC IDCA has been used in a prototype lidar instrument for small airless bodies such as asteroids and comet cores [69].