esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Implementation and User Scenario
### Technical Validation and Experimental Results
#### 5.4.2 User Feedback Collection  
To strengthen the subjectivity and personalization of the UX model, we adopt a dual-feedback strategy that combines both direct (e.g., surveys and user ratings) and indirect feedback derived from user interaction patterns and behavioral data. This ensures comprehensive coverage of both perceived and behavioral aspects of the user experience.  
* **Direct Feedback via Surveys:** A structured survey is designed to capture users' subjective evaluations across key interface dimensions, including ease of navigation, visual appeal, responsiveness, content relevance, and overall satisfaction. Each dimension is rated using a 5-point Likert scale ranging from \"Strongly Disagree\" to \"Strongly Agree\". These surveys are contextually triggered, typically following the completion of key actions, such as purchase and product comparison. The responses are stored in a feedback matrix \(R_{u,i}\), where \(u\) represents the user and \(i\) represents the corresponding UX dimension.
* **Indirect Feedback via Interaction Logs:** Behavioral signals such as time spent on the UI, click-through rates, drop-off points, scroll depth, and hesitation metrics are captured anonymously through embedded tracking scripts. These signals are then associated with specific UX dimensions using heuristic mapping rules. For instance, prolonged hesitation during the checkout process may be interpreted as reduced ease of navigation.  
All feedback was collected automatically during simulation runs using Python scripts. Each user session was logged in detail, including state transitions, user actions, and system-driven UI adaptations. These logs are stored in a structured format using _pandas_ DataFrames, enabling structured analysis and comparative evaluation between static and dynamically adapted UI models.
## 3 Method
### Building the Surface at Icosphere Nodes  
As mentioned in Section 3.3, we cut the object by concentric spheres. Let us consider an SDF function \(f^{(i)}(\theta,\varphi)\)--the shortest distance from the point \((\theta,\varphi)\) of the \(i\)-th sphere to the surface \(S\). Function \(f^{(i)}(\theta,\varphi)\) is continuous by parameters \(\theta\) and \(\varphi\), as well as by the radius of the sphere and the vector \(\left(\theta,\varphi,f^{(i)}(\theta,\varphi)\right)\), which is defined in the spherical coordinate system. If the value of \(f^{(i)}(\theta,\varphi)<0\), the corresponding vector of length \(\left|f^{(i)}(\theta,\varphi)\right|\) is directed opposite vector \((\theta,\varphi,1)\).  
At each sphere, a grid of points, \(\left(\theta_{j},\varphi_{j}\right)\), \(j=1,\ldots,k\), is defined. We use an icosphere [51] set of points out of 10,242 vertices after five subdivisions. This icosphere has a dense and rather uniformly distributed set of vertices. Using values \(f^{(i)}\left(\theta_{j},\varphi_{j}\right)\), we compute (3) the spherical harmonic coefficients \(f^{(i)}_{lm}\); then, we partially reconstruct function \(\widetilde{f}^{(i)}\left(\theta_{j},\varphi_{j}\right)\) on the unit sphere at the icosphere grid \(\left(\theta_{j},\varphi_{j}\right)\) for degrees \(l=0,\ldots,10\) using (1).  
As was mentioned in steps P8-P11, on the unit sphere, we add functions \(\widetilde{f}^{(i)}\left(\theta_{j},\varphi_{j}\right)\) over the entire set of concentric spheres, see Formula (2), and connect the points \(\left(\theta_{j},\varphi_{j},\widetilde{f}\left(\theta_{j},\varphi_{j}\right)\right)\) to make a surface \(C\) with the adjacency matrix for the icosphere. We find this surface's extrema and saddle points and build the convex hull using the points found. The number of vertices in the convex hull built on these points is usually much smaller than the number of points in the original surface \(C\). These vertices are ordered in sequence \(F\) by the length of the radius vector. We obtain a similar sequence \(G\) for function \(g\).  
Let us form the sequence \(\widetilde{F}\) of lengths of vectors corresponding to the vertices of the convex hull \(F\). The global maxima of \(\widetilde{F}\) will have the same values as the global maxima for \(\widetilde{f}\left(\theta_{j},\varphi_{j}\right)\) and will be reached at the same icosphere grid nodes. The values corresponding to the global maxima will be concentrated in the right tail of the distribution \(S_{n}\). The number of extrema on a convex hull cannot be more than the number of extrema for the original surface \(S_{n}\) on which it is built.  
If objects \(O_{1}\) and \(O_{2}\) are similar, then to match them, we can only use the top extrema from \(F\) and \(G\) and later check the quality of the mapping.  
The process described here will be referred to as extrema amplification hereafter.
## 3 Results and Discussion
### Antioxidant Activities of Yogurt Samples
#### 3.1.2 Total Phenol Content of Yogurt Samples during Storage
1-Butanol-3-methyl-acetate ester was detected in all of the probiotic and symbiotic yogurt samples of this study up to four weeks of storage, but butanoic acid-3-methyl butyl ester was detected only up to the second week, while octanoic acid ethyl ester was only found in S4-Syn1.5 and S5-Syn2 having higher concentrations of inulin. Ester volatile compounds are generally produced at low concentrations in dairy products when lactose is fermented with lactic acid bacteria (LAB) [57]. Aldehydes are considered important aroma compounds contributing to the volatile profile of fermented dairy products with lactic acid bacteria [58]. The only aldehyde (3-hydroxy butanal) found was in probiotic yogurt (S2-P = 0.63 \(\pm\) 0.11 mg/100 g) and symbiotic yogurt (S3-Syn1 = 13.95 \(\pm\) 3.31 mg/100 g) samples of this study up to one week of storage. The formation of more volatile compounds in the symbiotic yogurt samples enriched its flavor, compared with the plain and probiotic yeast yogurts that contained fewer volatile compounds. [PERSON] et al. (2017) [PERSON] et al. (2017) also showed that the aroma profile of yogurt made with pure culture was different from those made with the addition of probiotics alone or with a combination of prebiotics.
# Transportation and Reserve of Emergency Medical Supplies during Public Health Events
## 7 Countermeasures and Suggestions
### Countermeasures and Suggestions Based on the Transportation and Reserve Model  
The effective transportation and storage of emergency medical materials is the most important means of solving public health issues. When public health emergencies occur, the demand for emergency medical materials will increase directly. According to the transportation and storage model designed in this document, relevant countermeasures and suggestions are presented:* To predict public health issues at the beginning and grasp the golden time before public health issues broke out, we should focus on strengthening the transportation capacity of emergency medical materials in areas where public health issues occurred, strengthening the manpower and material resources in areas where public health issues occurred in advance, and predict the demand for transportation in advance;
* The emergency medical material transport and reserve network can be established in advance [53], the processing speed of the emergency medical materials transport and reserve can be strengthened, and the public health emergency management center can be established. The urgency of demand for each city demand point can be calculated in advance, the emergency medical material storage center can be set according to the urgency of demand and through prediction and calculation, and the site selection of the emergency medical material storage center can be carried out in advance. When a large-scale public health event occurs, the transportation and storage of emergency medical material can be carried out for the first time, and the emergency medical material storage center should be established in advance for areas with weak transportation capacity and strict transportation conditions, to reduce the injury and transportation cost caused by public health issues;
* It is necessary to adopt a more scientific mode of transport and storage. After completing the construction of the emergency medical materials storage center, the latest unmanned aerial vehicle technology can be used for transportation tasks in areas with high transportation cost and strict transportation conditions. Compared to vehicles, unmanned aerial vehicles have lower cost and more flexible transportation modes and also reduce the spread of public health incidents and virus infection of emergency medical materials caused by floating personnel.
## 3 Data and Methodology
### Time-Series Analysis
Therefore, we can establish a system of equations:  
\[\delta\Phi_{\text{k}}(\text{x, y})=\varphi(\text{t}_{\text{B}},\,\text{x, y})-\varphi(\text{t}_{\text{A}},\,\text{x, y})\ \approx\ \frac{4\pi}{\lambda}[\text{d}(\text{t}_{\text{B}},\,\text{x, y})-\text{d}(\text{t}_{\text{A}},\,\text{x, y})] \tag{2}\]3  
On the basis of linear models, atmospheric phase and nonlinear deformation phase can be separated by appropriate filtering of residual phase in space and time. The main process of SBAS-InSAR method can be summarized as shown in \[\delta\Phi_{\text{k}}(\text{x, y})=\varphi(\text{t}_{\text{B}},\,\text{x, y})-\varphi(\text{t}_{\text{A}},\,\text{x, y})\ \approx\ \frac{4\pi}{\lambda}[\text{d}(\text{t}_{\text{B}},\,\text{x, y})-\text{d}(\text{t}_{\text{A}},\,\text{x, y})] \tag{2}\]4  
Therefore, in this study, SBAS is used to generate 82 differential interference pairs by setting a spatial baseline of 200 m and time baseline thresholds of 14 d and 35 d. Then, the singular value decomposition (SVD) is used to calculate the linear displacement velocity and elevation error, and the interference of atmosphere and noise phase is removed in the residual phase; thus, the deformation velocity and time series of coherent target points are obtained. In order to reduce errors and obtain more accurate deformation results, the interference threshold set in this study is 0.3, which reduces the error of phase unwrapping. The data set used in this study comes from the European Space Agency (ESA). The Sentinel-1 data set from 16 January 2019 to 14 August 2020 is used for SBAS time series analysis. The polarization mode is VV polarization, and the band is C-band. A total of 24 descent orbit data are selected, and in order to improve the orbit accuracy of Sentinel-1 images, the orbit error is corrected using POD Precise Orbit Ephemerides data. In addition, the SETM data with a resolution of 30 m released by NASA are used as external DEM data to remove the terrain phase of the interferogram. The interference combination of the selected Sentinel-1 dataset is shown in \[\delta\Phi_{\text{k}}(\text{x, y})=\varphi(\text{t}_{\text{B}},\,\text{x, y})-\varphi(\text{t}_{\text{A}},\,\text{x, y})\ \approx\ \frac{4\pi}{\lambda}[\text{d}(\text{t}_{\text{B}},\,\text{x, y})-\text{d}(\text{t}_{\text{A}},\,\text{x, y})] \tag{2}\]5  
\[\delta\Phi_{\text{k}}(\text{x, y})=\varphi(\text{t}_{\text{B}},\,\text{x, y})-\varphi(\text{t}_{\text{A}},\,\text{x, y})\ \approx\ \frac{4\pi}{\lambda}[\text{d}(\text{t}_{\text{B}},\,\text{x, y})-\text{d}(\text{t}_{\text{A}},\,\text{x, y})] \tag{2}\]6 The SBAS-InSAR processing flow chart. \[\delta\Phi_{\text{k}}(\text{x, y})=\varphi(\text{t}_{\text{B}},\,\text{x, y})-\varphi(\text{t}_{\text{A}},\,\text{x, y})\ \approx\ \frac{4\pi}{\lambda}[\text{d}(\text{t}_{\text{B}},\,\text{x, y})-\text{d}(\text{t}_{\text{A}},\,\text{x, y})] \tag{2}\]7 Temporal and spatial baselines of Sentinel-1 orbit reduction data.
# Compact and Accurate Scene Text Detector
## 4 Experiment
### Dataset  
We use three datasets: ICDAR2013 dataset [28], ICDAR2015 dataset [29], and ICDAR2017 MLT [30]. The ICDAR2013 dataset consists of 229 images and 223 images for training and testing, respectively. It is annotated at the word level, and different images have different resolutions. Each word is represented by a rectangular box, so every word has the same horizontal orientation. The ICDAR2015 dataset consists of 1000 images and 500 images for training and testing, respectively. It is annotated at the word level, and the images are of the same resolution (e.g., 1280 \(\times\) 720). To incorporate arbitrary-oriented text, each word is represented by a quadrilateral box. The ICDAR2017 MLT consists of 7200 images, 1800 images, and 9000 images for training, validation, and testing, respectively. It is annotated at the word level, and different images have different resolutions. Similar to the ICDAT2015 dataset, a bounding box is represented by a quadrilateral box. ICDAR2017 is consist of nine languages, whereas the ICDAR2013 and ICDAR2015 have only English words.  
As the images of the three datasets have different resolutions, we make each dataset have a consistent image size. There are mainly two types of image resizing techniques: short-side based and long-side based resizing. For our model, we take the long-side based resizing. After resizing, the ICDAR2013, ICDAR2015, and ICDAR2017 datasets have 512, 1280, and 2400 long-side images, respectively. For each dataset, our model is trained using the training instances and is evaluated using the testing instances.  
We prepared the ground truth as described in [12]. As shown in Figure 5, given a word box, the ground truth is generated by shrinking the word box to a compact area of the word. The resolution of the ground truth becomes four times smaller than the resolution of the input images. Each ground truth consists of an RBOX geometry and a score map. As depicted in (b) of Figure 5, the RBOX geometry consists of a rotation angle as well as distances from a given pixel to the four edges. The score map is a scalar value that represents whether the given pixel belongs to a word box or not, as shown in (a) of Figure 5.
## 2 Background and Related Work
### Related Work
The AMSTAR 2 tool outputs a rating of the overall confidence in the review results that indicates the methodological quality of the analyzed systematic review and can be one of the following: high, moderate, low, and critically low. High means that the systematic review yields either zero or one non-critical weakness. [PERSON] et al. [15] relied on the STRICTA (The STandards for Reporting Interventions in Controlled Trials of Acupuncture) reporting guidelines to assess the quality of the reporting in systematic reviews focusing on acupuncture interventions. In theirwork, [PERSON] et al. [15] focused on sixteen STRICTA checklist subitems and used them to assess twenty-eight acupuncture trials for chronic obstructive pulmonary disease (COPD). They concluded that, only four of the sixteen investigated STRICTA checklist subitems were appropriately reported in more than 70% of the trials. They also concluded that seven of the sixteen investigated STRICTA checklist subitems were correctly reported in less than 30% of the trials. They stated that the main limitation in their work was that it used STRICTA as a rating scale. Using reporting guidelines as tools to assess the quality of reporting is usually discouraged because reporting guidelines do not give guidance on how to judge/rate each of their checklist items and on when to consider each of these items as fully reported [5; 15]. [PERSON] et al. [5] conducted a study to evaluate the completeness of reporting in the animal health literature. They analyzed 91 systematic reviews to retrieve information on whether the reviews had reported each individual PRISMA item. Their analysis focused on three review types: systematic reviews only, systematic reviews with meta-analyses, and meta-analyses only. They leveraged the retrieved information to compute, for each review type, the percentages (proportion) of reviews for which information to address each PRISMA item was reported. These percentages allow them to conclude that the adherence to the recommended PRISMA reporting items is suboptimal and varies from an item to another. Notably, [PERSON] et al. [5] performed the information retrieval step before the release of the PRISMA 2020 statement and may have missed some information related to the revised items of the PRISMA 2020 checklist.
# A Tale of Many Networks: Splitting and Merging of Chord-like Overlays in Partitioned Networks
## 6 Conclusions  
In this paper, we address the issue of peer-to-peer overlays in the presence of dynamic Internet partitioning on national scale. We show that Chord [2], as well as previously proposed merging algorithms for ring-based overlays such as Chord-Zip [6] and the Ring-Unification Algorithm [7], are incapable of reliably merging several Chord overlays under the considered scenarios. While Chord-Zip already fails to merge more than two overlays in parallel and in reasonable time, the Ring-Unification Algorithm has its problems in merging overlays after heavy network partitioning events.  
We present in this paper a novel merging algorithm for ring-based peer-to-peer overlays, named the Ring Reunion Algorithm. The Ring Reunion Algorithm has been evaluated using either a public list of 160 randomly selected online contacts, which is used to select potential nodes for a merging attempt, or using a passive list which comprises previously seen nodes that left the overlay unexpectedly. Using a local ring size estimation in combination with a parameter \(\alpha\) allows us to define for each node a probability to initiate a merging approach. Each overlay construct initiates on average \(\alpha\) merging attempts within a specific time interval, independent of the number of nodes in the overlay construct. We present a simple and a parallelized merging protocol within the Ring Reunion Algorithm. While the simple approach reliably merges multiple Chord rings, the parallelized version systematically initiates further merging attempts at strategic positions in the overlay and accelerates the merging. Evaluation shows that the Ring Reunion Algorithm reliably merges two to five Chord rings in parallel, conducts subsequent mergers quickly, even in complex cases, and leads to a fully correct topology. We identify within the paper ideal values for the fanout parameter and the merge count parameter \(\alpha\) for the overlay constructs. The Ring Reunion Algorithm allows ring-based overlays to split and to merge quickly, cost efficiently, and--most of all--reliably. Using ring-based overlays with our merging approach allows us to create data-management applications which can survive network splits on global scale, but also in mobile peer-to-peer networks, and continue their operation once network connection is reestablished.  
Conceptualization, T.A. and K.G.; methodology, T.A. and K.G.; software, T.A. and K.G.; validation, T.A. and K.G.; formal analysis, T.A. and K.G.; investigation, T.A. and K.G.; resources, T.A. and K.G.; data curation, T.A. and K.G.; writing--original draft preparation, T.A.; writing--review and editing, K.G.; visualization, T.A.; supervision, K.G.; project administration, K.G.; funding acquisition, K.G. All authors have read and agreed to the published version of the manuscript.  
This research was partially funded by the Arab German Young Academy of Sciences and Humanities (AGYA).  
The authors declare no conflicts of interest.
## 4 Use Cases for Multimedia Analysis in Archiving Community Memories
### Detecting Media about Individuals, Organisations and Places
#### 4.4.3 Recognising Places  
Finally, place detection is an emerging research area. Given an image that has no location information, as long as the depicted location is visually unique, then it may be resolved by matching against a large corpus of geo-located images [37,48]. If metadata is available, it can be used together with visual information to improve the location estimation.  
As part of our participation in the MediaEval 2013 placing task [49], we developed an algorithm that estimates a continuous probability density function (pdf) over the surface of the Earth from a number of features extracted from the query image and, if available, its metadata [48,50]. From the pdf, we find the modes of the distribution and choose the position of the most likely mode as the estimated location. The key ideas of this approach are illustrated in Figure 6.  
Experiments with the dataset of 8.6 million Flickr photos from the MediaEval placing task indicate that we are able to achieve state-of-the-art performance with our model and predict the location of almost 25% of the images to within 1 km of there true location. If we exploit additional information about the  
Figure 6: Our approach to the geographical location of images. (**a**) A number of features are extracted from the content and metadata of a query image; each feature provides a set of latitude-longitude points associated with that feature (learned from the geotagged training images); (**b**) the location of predominant mode of the density distribution of all the features is determined using the standard mean-shift algorithm; this gives an estimate of the location, as well as the probability of it being correct (based on the likelihood of the mode).  
users taking the photos (by utilising their Flickr profiles and other photos that they have taken that have know locations), this rises to over 45%. It should be noted that it is predominantly the meta-information that is at work here; the best runs using only visual information at MediaEval achieved about 2.5% accuracy within 1 km of the true location. The reason for this is related to the fact that the majority of images on Flickr do not actually display any visibly recognisable places.
## 2 Related Work
### Basic Principles of Cryptography
#### 2.2.2 Cryptographic Namespaces  
Cryptographic namespaces take a different approach for key distribution. Instead of requiring a PKI, the public key is incorporated into the address of an end node. The Host Identity Protocol [9], for example, hashes the public key to a 128 bit value and uses this address as the identifier in a locator/identifier-split architecture. Other approaches like Accountable Internet Protocol [10] and Cryptographically Generated Addresses [11] incorporate a hash of the public key into an IPv6 address. In that way, a peer is able to instantly verify that the end node it is communicating with is in possession of the corresponding private key. There is no need to query a third party for the public key, hence no requirement for an additional trusted entity within the network.  
At a first glance, the cryptographic namespace seems to be a very promising idea, however, it has some major downsides. First of all, it adds inflexibility to key and address management. Whenever one of the items has to change (e.g., extended key length required), the other item has to change as well. Another problem is the missing link between the public key and a legal person. The cryptographic namespace only ensures that the end node with a certain address is also holding the valid private key for it. In practice, however, it is seldom relevant which end node we are talking to. For example, we want to talk to a specific person or our bank and not to a specific box of hardware down in a cellar. Another crucial point is the lack of key revocation. In case a private key gets lost or disclosed, the end node needs to generate a new \(\langle public\ key,private\ key,address\rangle\)-triple. Peers of that end node, however, might not immediately be aware of the address change and an attacker is able to use the old address combined with the private key to spoof his identity. Finally, in case the address space is quite full, it is easy for an attacker to generate a random key-address-triple which is already in use by another end node. In that way, an attacker is able to hide his identity.