esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
A novel optical signature and authentication cryptosystem is proposed by applying triangular association encryption algorithm (TAEA) and 3D Arnold transform in Gyrator domains. Firstly, a triangular association encryption algorithm (TAEA) is designed, which makes it possible to turn the diffusion of pixel values within bands into the diffusion within and between bands. Besides, the image signature function is considered and utilized in the proposed cryptosystem. Without the image signature, the original image cannot be restored even if all of the keys are obtained. Moreover, the image integrity authentication function is provided to prevent pixel values from being tampered with. Through the numerical simulation of various types of attacks, the effectiveness and capability of the proposed hyperspectral data signature and authentication cryptosystem is verified.  
optical hyperspectral image cryptosystem; 3D Arnold; image signature; image integrity authentication; gyrator; TAEA
# Path Planning of Underground Robots via Improved A* and Dynamic Window Approach
## 2 Improved A* Algorithm
### Anti-Diagonal Collision  
When the robot moves diagonally, it will directly cross the corner of the obstacle, which violates the safety requirements of the actual movement of the robot, which may lead to collision accidents. In order to solve this problem, the concept of the intersection point is introduced. The intersection point specifically refers to the key points that the robot must pass through when crossing the grid during oblique diagonal motion, as shown in Figure 5. The arrow points to an intersection.  
In the execution of the path search algorithm, when facing the diagonal connection between the current node and the next node, the following steps need to be performed to determine whether the diagonal obstacle exists.  
First, check the diagonal grid unit in another direction adjacent to the intersection. If either of the two grid units has an obstacle, it is determined that there is a diagonal obstacle.  
If it is confirmed that there are diagonal obstacles, the current node should be removed from the Open List and added to the Closed List. Skip the node to avoid the path crossing the diagonal obstacle. If it is confirmed that there is no diagonal obstacle, the path search process is continued, the current node is obtained, and the forward or reverse search is performed according to the algorithm logic.  
Taking Figure 5 as an example, if the blue node tries to move diagonally to the red node, the diagonal grid unit in the other direction adjacent to the intersection should be checked. If an obstacle is detected in the grid unit on the right side of the blue node, it is determined that the orange path is impassable and the path needs to be replanned. On the contrary, if the blue node moves to the light blue node, the inspection results show that the diagonal grid units in the other direction adjacent to the intersection have no obstacles, then the purple path can be determined as a passable path.  
Through the above process, the path search algorithm can effectively judge the existence of diagonal obstacles when diagonally moving, and adjust the search strategy accordingly to ensure that the generated path does not cross obstacles and is a feasible path.
# A Multi-Stage Method for Logo Detection in Scanned Official Documents Based on Image Processing
## 4 Experiments and Results
### Error Analysis  
In order to quantify the classification matches and errors, we computed a weighted value for the _precision_, the number of true logotype images retrieved divided by the total number of images retrieved, and the _recall_, which is the number of true logotype images retrieved divided by the total number of true logotypes in the set. Finally, we obtained with both parameters the _F-measure_, which is a combined measure of the precision and recall:  
\[\text{F-measure}=\frac{2*precision*recall}{precision+recall} \tag{5}\]  
The weight value that we used is the number of instances of each class. The results are summarized in Table 1. We compared our precision and recall values against eight methods from the literature [9; 19; 20; 23; 24; 25; 27]. The selection of [19] was due to its high precision, but this method is conceived for logo recognition more than logo detection. They used a gallery of logos for matching, which is not the case of our method, but it this shows that this approach, with the density-based clustering process, is more accurate than the methods of [9; 23; 24; 25]. Therefore, a fair comparison cannot be made because this method uses a different number of documents for testing.  
As we can observe in Table 1, in this study, we also compared the precision of our approach with different state-of-the-art methods for logo detection on the Tobacco-800 database [9; 23; 27], where the improvement of our novel method is evident. We selected [24; 25] because they are also based on the feature rectangles technique and are two of the most prominent results available in logotype detection. We observed an increment of a 3.5% in precision and 5.3% in recall with respect to those methods that we have compared to. That means that our method is able to retrieve more logotypes from the set of documents, also with a slight decrease in the number of false positives.  
Figure 9: C4.5 decision tree for the classification of unknown logotype instances.
###### Abstract
(2023) presented a streamlined modeling approach using EPANET, focusing on minimizing the computational load while maintaining accuracy, but the method's adaptability to complex networks has not been thoroughly explored [17]. [PERSON] et al. (2022) applied WaterCAD in extended period simulation (EPS), evaluating the performance of the existing network under varying demand and operational scenarios [18]. Finally, [PERSON] and [PERSON] (2012) and [PERSON] et al. (2015) contributed by analyzing pipe material technologies and proposing quasi-optimal design methods, respectively, highlighting the balance between cost efficiency and hydraulic performance [19; 20]. Data adequacy is one of the most important factors for the successful establishment and application of a WDS model [21; 22; 23]. Digitization plays a critical role in hydraulic modeling, enabling high-resolution representation of WDS for enhanced operational analysis, system optimization, and predictive maintenance [24]. The integration of GIS tools, CAD-based design, and real-time telemetry allows municipalities to overcome data gaps, ensuring more accurate infrastructure mapping and long-term planning [25; 26]. Among the available tools, WaterGEMS stands out due to its advanced interoperability, geospatial modeling, and optimization capabilities [27]. Unlike standalone simulation engines, WaterGEMS integrates seamlessly with GIS platforms (ArcGIS), CAD-based designs (AutoCAD), and SCADA telemetry systems, enabling real-time hydraulic assessment and predictive maintenance strategies [28; 29]. While the studies span modeling, detection, design, and materials, a gap remains in integrating these aspects into unified, adaptive decision-support frameworks applicable to real-world, data-limited urban systems. The novelty of this study is that it presents a methodological framework for the optimal digitization, modeling and simulation of a water supply network under data scarcity, through the conjunctive use of a series of software, while it can be continuously updated by the user and corrected where necessary. The study develops and calibrates a hydraulic model for Farsala's water distribution network, integrating AutoCAD, ArcGIS, and WaterGEMS to ensure accuracy. It digitizes the network, incorporates SCADA telemetry and field measurements, and performs EPS to assess system performance. Unlike traditional models, this study effectively integrates incomplete datasets to develop a reliable simulation. A key contribution is the scenario-based analysis framework, enabling decision-makers to test leakage reduction, pump optimization, and emergency planning. The study also automates demand allocation to improve efficiency with minimal monitoring infrastructure. Beyond simulation, it serves as a decision-support tool for urban water management, offering a scalable and adaptable approach for municipalities facing aging infrastructure and limited data availability.
## 3 Methods
### Feeding Outcomes  
We correlated the BDS with feeding outcomes. The feeding outcome study group consisted of term infants with CHD who had neonatal brain MRI with brain dysplasia score between 2003-2015, enrolled both prospectively for research MRI and retrospectively after clinical MRI, at CHLA and CHP. Participants with major gastrointestinal anomaliesor surgeries, a diagnosis of CHARGE syndrome, death within the first 30 days of life, or death prior to initiation of feeds were excluded from the feeding analysis. For the feeding study, we evaluated 177 term infants with CHD who had MRI that were used to calculate BDS as described above. Of those, 32 were excluded, including 14 with major gastrointestinal anomalies or surgeries, 1 with a brain anomaly, 6 with CHARGE syndrome, and 11 that died in the first 30 days or prior to initiation of feeds. Therefore, the feeding analysis group consisted of 145 subjects, of which 81 were from CHLA and 64 from CHP. The inpatient medical records were assessed for the following feeding-related variables: presence of dysphagia, aspiration, gastroesophageal reflux, gastrointestinal dysmotility, intestinal malrotation, vocal cord paralysis, use of enteral tube feeding (including nasogastric, nasojejunal, or surgically placed gastric or jejun tubes), lack of oral feeding prior to neonatal hospital discharge, and length of neonatal hospitalization.
# Recent Advances in Non-Traditional Elastic Wave Manipulation by Macroscopic Artificial Structures
## 2 Elastic Metamaterials
### Elastic Gradient-Index Lens Using Phononic Crystals
The relationship between \(r\) and \(n\) in this lens is written as  
\[rn^{4}+2n+1=0. \tag{3}\]  
Note that the extended version for an arbitrary rotating lens called generalized Eaton lens has theoretically been introduced [80], and experimentally been conducted [81] in the acoustic regime by exploiting the index profile described as  
\[n(r,\phi)=\left(\frac{2R}{r}-1\right)^{\phi/(\pi+\phi)}, \tag{4}\]  
for \(r<R\). \(\phi\) is the arbitrary desired refraction angle. The focusing of elastic waves in plates can be used in to harvest energy by collecting the energy of elastic waves. Numerical and experimental studies demonstrated that GRIN PCs that use blind holes and are coupled with piezoelectric transduction can improve the harvesting of elastic waves [82]. This concept was extended [83] to create a GRIN lens with continuously-varying index profile by gradually altering the rigidity properties to focus and harvest flexural waves. The GRIN lens coupled to piezoelectric harvesters can efficiently focus and harvest waves at the designed fixed focal points and work well in a broad frequency range (Figure 4a,b). The focal harvester was better than the baseline harvester (Figure 4c). One Luneburg lens enables precise focusing of an omnidirectional plane wave (Figure 4d,e); the harvested power output by a Luneburg lens was more than 10 times higher than by the baseline harvester (Figure 4f) [84].
## 2 TDLAS-WMS Detection Theory  
### Absorption Line of C\({}_{2}\)H\({}_{2}\)  
The transition between the ro-vibrational energy levels of a molecule need to absorb the energy of the infrared region, and it will form an infrared spectrum [18]. From the point of view of quantum mechanics, the transition between molecular energy levels satisfies the quantization conditions. Since the energy of the ro-vibrational level is discontinuous, when a level transition occurs, a specific molecule will only absorb a specific wavelength infrared light, which ensures the selectivity of the infrared absorption spectrum gas detection technique. The absorption peak of the C\({}_{2}\)H\({}_{2}\) molecule in the mid-infrared band is evidently stronger than in the near-infrared band [19]. However, the process of the near-infrared laser is mature, widely used, and relatively inexpensive. In the actual detection process, the optical path coupling of the mid-infrared laser is more difficult. Therefore, this study selects the characteristic absorption line at the near-infrared band of the C\({}_{2}\)H\({}_{2}\) molecule to detect its concentration.  
The absorption spectrum of the C\({}_{2}\)H\({}_{2}\) molecule in the range of 1520.05 to 1520.15 nm is shown in Figure 1, according to the high-resolution transmission molecular absorption database 2016 (HITRAN 2016). Evidently, the line intensity of the C\({}_{2}\)H\({}_{2}\) molecule is the largest near 1520 nm at 10\({}^{-20}\). The line intensity of common gas molecules, such as CO\({}_{2}\), H\({}_{2}\)O, and CH\({}_{4}\), is less than 10\({}^{-23}\) at 1520 nm, which is far less than that of the C\({}_{2}\)H\({}_{2}\) molecule. The interference generated can be ignored in the actual detection. Therefore, these disturbances can be ignored in the actual detection. The absorption line at 1520 nm of the C\({}_{2}\)H\({}_{2}\) molecule is used comprehensively. The line intensity is set to \(1.340\times 10^{-20}\) to obtain accurate detection results and avoid interference of other gas molecules as much as possible, considering these factors.
# Performance Tradeoff Analysis of Hybrid Signaling SWIPT Systems with Nonlinear Power Amplifiers
## 1 Introduction
Although there exists a wealth of conventional studies that investigate nonlinear transmit PA in communication systems, the signaling schemes in these studies are restricted to pure information signals. In the HSS-SWIPT system considered in this paper, the transmitted signal is a mixture of a high-power energy signal and low-power information signal. Nonlinear amplification will result in spectrum spreading of the in  
Figure 2: Illustration of SWIPT systems with identical and hybrid signaling schemes. formation signal. Furthermore, the two signals will produce intermodulation distortion, which will further degrade the information signal quality. On one hand, for high-power energy signals, we prefer the PA to work in the nonlinear region to improve the energy conversion efficiency; on the other hand, for low-power information signals, nonlinear distortions of the signal should be avoided as far as possible [48; 49]. As a result, achieving high efficiency of energy conversion and low distortion of the information signal become conflicting objectives. As nonlinear PA is practically unavoidable, it is of great importance to investigate the tradeoff between energy transfer and information transmission in a hybrid signaling SWIPT [50]. This paper is among the first efforts to analyze the performance of hybrid signaling SWIPT systems with nonlinear PA. Because nonlinear PA is a transmitter-side phenomenon, we restrict our study to performance metrics at the transmitter side. In other words, receiver-side particularities such as modulation and circuit designs are deliberately made irrelevant and neglected. This helps us to decouple the problem and obtain deeper insights. More specifically, we use the transmitter-side signal-to-noise-and-distortion ratio (SNDR) [51; 52] to measure the efficiency of information transmission, and the transmitter PA efficiency to measure the efficiency of energy transfer. This paper makes the following contributions: first, the SNDR metrics are redefined for the SWIPT system with hybrid signaling, which consists of a high-power energy signal and a small-power information signal; second, the SNDR and the PA efficiency are analytically evaluated for SWIPT systems with nonlinear PAs; finally, using the input back-off (IBO) as the intermediate parameter, we quantify the tradeoff between the SNDR and the PA efficiency. The remainder of this paper is organized as follows. Section 2 introduces the system model and presents definitions of the performance metrics. Theoretical evaluations of PA energy conversion efficiency and information signal SNDR are presented in Sections 3 and 4, respectively. Section 5 analyzes the tradeoff relationship between PA efficiency and SNDR in hybrid signaling SWIPT systems. Finally, conclusions are drawn in Section 6.
# Thangka Image--Text Matching Based on Adaptive Pooling Layer and Improved Transformer
## 2 Thangka Image-Text Matching Model
### Improved Transformer Encoding Module
#### 2.3.2 Improved Masked Attention Mechanism  
In the original Transformer model, the self-attention mechanism calculates the attention weights equally for all elements within the input vectors. While this method effectively captures the relationships between input vectors, it can lose the structural information present in input vectors with specific structures. However, in this paper, the established multi-granularity feature vectors for images and texts heavily rely on the structural information between entities. Therefore, the self-attention mechanism is improved in this paper by introducing a masking matrix M to the bidirectional residual Transformer network, aiming to preserve the structural information between entities. The modified structure is illustrated in Figure 4.  
The masking matrix is used to attenuate the influence of global semantic information on the structural information between entities in the multimodal feature vectors. This ensures the integrity of the structural information between entities. The masking matrix M is a diagonal matrix with dimensions \(|\mathbf{X}|\times|\mathbf{X}|\), where the default values of the matrix elements are set to 1. However, to treat the attention between image region nodes and global sentence nodes as unrelated, the elements of the masking matrix M are set to \(-\infty\). This reduces the attention between global sentence nodes and image region nodes, thereby preserving the structural information between entities. Similarly, to treat the attention between text region nodes and global image nodes as unrelated, the elements of the masking matrix M are also set to \(-\infty\). This reduces the attention between text region  
Figure 4: Masking attention mechanism.  
nodes and global image nodes, ensuring the integrity of the structural information between entities. The improved calculation process is shown in Equation (7):  
\[atten(Q,K,V,M)=softmax\bigg{(}M\frac{Q^{T}K}{\sqrt{dk}}\bigg{)}V \tag{7}\]  
Here, \(Q\), \(K\), and \(V\) are parameter matrices from the original attention calculation function, and M acts as the attention influence factor, implementing the masking for the attention in the two mentioned scenarios and reducing the influence of unrelated nodes on the final result.  
With the improved Transformer, a sequence containing structural features between entities can be obtained, as shown in Equation (8):  
\[Z=\left[x_{u}^{I},X_{u}^{I},x_{v}^{T},X_{v}^{T}\right] \tag{8}\]  
Here, \(x_{u}^{I}\) represents the local feature representation of the image, \(X_{u}^{I}\) represents the global feature representation of the image, \(x_{v}^{T}\) represents the local feature representation of the text, and \(x_{v}^{T}\) represents the global feature representation of the text.
## 2 System Model and Problem Formulation
### System Model
#### 2.1.2 Users Model  
In the model, we assume that the number of MUs, denoted as \(U(t)\), which requests interested contents from BS, follows the Poisson process with parameter \(\lambda\)[25; 26]. Thus, it yields:  
\[P(U(t)=k)=\frac{(\lambda t)^{k}}{k!}e^{-\lambda t} \tag{5}\]
## 5 Conclusions  
The ATR-FTIR method with chemometric evaluation was successfully applied as an objective method for the qualitative discrimination of essential oils from different plant species. ATR-FTIR spectra obtained from the essential oils were used as spectral fingerprints, and PCA was applied to characteristic key spectral bands that can be used as marker bands to discriminate different plant botanical families. It was demonstrated that essential oils could be grouped based on their purity and taxonomy (botanical family) using ATR-FTIR spectra with PCA and cluster analysis.  
ATR-FTIR spectroscopy offers a green, direct and cost-effective alternative analytical method for the quality control of essential oils. Vibrational spectroscopy combined with chemometric algorithms also provides an efficient and non-destructive chemotaxonomic classification of medicinal and aromatic essential oils. Furthermore, PCA analysis of IR spectra identifies characteristic key bands of the specific essential oil that allows for the discrimination of different essential oil profiles of individual oil plants among the same species (chemotypes).  
Conceptualization, S.A.-K.; Methodology, S.A.-K.; Investigation, S.A.-K., V.G. and D.W.M.; Resources, T.M.L.; Writing--Original Draft Preparation, S.A.-K.; Writing--Review and Editing. P.R., V.G. and D.W.M.; Visualization, D.W.M.; Project Administration, T.M.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors would like to acknowledge and thank FLAVEX(r) Naturextrakte GmbH for supplying many of the essential oils used in this work. This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.  
The authors declare no conflict of interest.  
Figure 5: Hierarchical cluster analysis (HCA) of ATR-FTIR essential oil spectra.
# An Entity Relation Extraction Method Based on Dynamic Context and Multi-Feature Fusion
## 4 Experiments  
### Dataset and Evaluation  
For the proposed method in this work, it is described with lots of detail, which needs to be proved the effectiveness on relation extraction tasks. Thus, this paper utilizes the CoNLL04 dataset and the ADE dataset for training and evaluation process. Furthermore, the two datasets contain plenty of entities composed of English words and entity-relation-entity tuple, which are widely adopted by models focusing on English entity relation extraction tasks.  
In this paper, a series of experiments are carried out on English sentences from the CoNLL04 dataset and the ADE dataset to evaluate the significant superiority and performance of the proposed method compared with the existing results. The detail of dataset is shown in Table 1 below:  
The CoNLL04 dataset contains texts with named entities and relations extracted from news articles, which has been applied for the research of entity relation extraction in recent years. It includes four entity classes, such as Location, Organization, People and Other, and five relation types, such as Work-For, Kill, Organization-Based-In, Live-In and Located-In.  
The ADE dataset comes from some medical reports describing adverse drug reactions, including a single relation type Adverse-Effect and the two entity types Adverse-Effect and Drug.  
There are some evaluation indicators for experiments such as precision, recall and F1-scores. To compare our method with other researches, this paper adopts the micro-average F1-scores as evaluation metric in the following experiments. The computing method of F1-scores is shown:  
\[pre=\frac{TP}{TP+FP}, \tag{18}\]  
\[rec=\frac{TP}{TP+FN}, \tag{19}\]  
\[\text{F1}=\frac{2\times pre\times rec}{pre+rec}. \tag{20}\]