esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Ischemic Heart Disease
### LIE in Acute MI versus Chronic MI  
In cases of acute MI, in which membrane disruption leads to extracellular volume expansion and a subsequent increase in the distribution of iodinated contrast medium in a way similar to gadolinium, LIE-CT has demonstrated its efficacy in assessing the infarct size and myocardial viability, as evidenced by various studies [17]. In individuals who received a primary percutaneous coronary intervention for ST segment elevation acute MI, [PERSON] et al. found an association between the LIE-CT, thrombolysis in MI, the myocardial perfusion grade following stent placement, and the electrocardiogram ST segment resolution [21]. In another study conducted by [PERSON] et al., 92 patients with acute MI underwent CCT immediately after a percutaneous coronary intervention. In this cohort, the heterogeneous enhancement detected by CCT after the percutaneous coronary intervention showed promise in predicting microvascular obstruction and left ventricular remodeling [22]. Furthermore, LIE-CT may decrease from the acute to chronic phases of MI due to the reduction in the surrounding edema [23]. Despite the initially promising results in the acute setting, among the major limitations, most clinical LIE-CT studies have used small sample sizes.  
In case of chronic MI, the literature results are discordant. In the study conducted by [PERSON] et al. using LGE-CMR as the reference standard, LIE-CT identified only 9 out of 17 ischemic scars, demonstrating high specificity (98%) but poor sensitivity (53%) among chronic MI patients [24]. This weakness in LIE-CT's performance in chronic MI cases may be attributed to various factors, including the relatively poor contrast resolution compared to LGE-CMR and the involvement of different physio-pathological mechanisms in the extracellular expansion of acute and chronic MI. On the other hand, in a study conducted by [PERSON] et al., the effectiveness of dual-energy LIE-CT, selective myocardial iodine mapping, and 3-tesla CMR in detecting chronic MI was compared. Dual-energy LIE-CT showed high sensitivity, specificity, and accuracy in identifying chronic MI, with the best image quality score and infarct size correlation found at certain settings. However, theiodine distribution maps were less accurate, with sensitivity of 52%, specificity of 88%, and accuracy of 81%, overestimating transmural scars [25].
# Rotor Fault Diagnosis Method Based on VMD Symmetrical Polar Image and Fuzzy Neural Network
## 1 Introduction
The signal feature information is extracted by VMD symmetrical polar image, and fault recognition is achieved using fuzzy neural network. The major contributions of this paper compared to the existing approaches are that:  
1. Combining the advantages of the VMD method in non-stationary signal processing with the effectiveness of symmetric polar image in feature information representation, it provides a new idea for introducing image processing technology into the field of rotating machinery fault diagnosis. 2. Aiming at the problem of selecting key parameters in the VMD decomposition process, a parameter selection method based on the maximum central frequency criterion and the minimum multi-scale fuzzy entropy criterion is proposed. The proposed method is simple, efficient and accurate, which can effectively improve the decomposition accuracy of the VMD method. 3. In order to solve the problem that false IMF components affect the accuracy of signal feature extraction, a comprehensive evaluation factor method is proposed. This method fully considers the characteristics of each IMF component in the time domain and frequency domain and the degree of correlation with the original signal, which \begin{table}
\begin{tabular}{c c} \hline \hline
**Method** & **Shortcomings** \\ \hline \multirow{3}{*}{WT} & 1  & Non-adaptive; \\  & 2  & Lack of selection criteria for wavelet basis functions; \\  & 3  & Different wavelet basis analysis results are different. \\ \hline \multirow{3}{*}{EMD} & 1  & End effect; 2  & Mode mixing; 3  & Envelopes fitting; \\  & 3  & Illusive mode component; 3  & Poor anti-noise performance. \\ \hline \multirow{3}{*}{LMD} & 1  & End effect; 2  & Mode mixing; 3  & Envelopes fitting; \\  & 3  & Illusive mode component; 3  & Poor anti-noise performance. \\ \hline \multirow{3}{*}{EMD} & 1  & End effect; 2  & Mode mixing; 3  & Envelopes fitting; \\  & 3  & Illusive mode component; 3  & Poor anti-noise performance. \\ \hline \multirow{3}{*}{VMD} & 1  & Lack of criteria for the selection of key parameters; \\  & 2  & Illusive mode component. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The characteristics of common signal decomposition methods. can effectively filter out noise and other interference components, and select IMF components sensitive to signal feature information. 4. In view of the fact that the fault diagnosis is a usually small sample, the fuzzy neural network is used to identify the rotor fault features obtained from the VMD symmetrical polar image. Compared with BP neural network, SVM and Random Forest, this method has higher average recognition accuracy of 98.4%, which provides a solution to the fault diagnosis problem in the case of a small sample.
# Method of Feature Reduction in Short Text Classification Based on Feature Clustering
## 3 The Proposed Approach
### Construct the Feature Word Bags  
The experimental corpus of this paper is the Fudan Chinese text classification dataset and the China Mobile SMS dataset. The steps of text preprocessing are as follows:  
* Collection of an internet dictionary. Social network texts are more informal and colloquial than formal texts. They contain many new internet buzzwords, such as \"laotie\" and \"lanshouxianggu\". The internet dictionary is a user-defined dictionary. It includes internet terms that contribute to the precision of word segmentation.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Symbol** & **Definition** \\ \hline \(C_{i}\) & Initial feature cluster \\ \(C_{s}\) & Similar feature cluster \\ \(W_{r}\) & Feature words in similar feature clusters \\ \(T\) & Word bags \\ \(D\) & An unclassified document set consisting of text documents \\ V(w) & The vector representation of the feature word w \\ \hline \hline \end{tabular}
\end{table}
Table 1: Symbols and their definitions.  
Figure 1: The framework of the two-stage feature clustering (TSFC) approach.  
* Stopword removal. Stopwords are words that contain no concrete meanings (e.g., prepositions, pronouns, and conjunctions). Therefore, stopwords need to be removed from each document, so as to avert a negative impact on the method. A Chinese stopword list with 2929 entries is applied here.
* Word segmentation. Chinese word segmentation refers to the cutting of a Chinese character sequence into individual words. Word segmentation is the process of regrouping consecutive word sequences into compound word sequences. The NLTK (Natural Language Toolkit) [35] segmentation kit is used in this method.
* Construct feature word bags. In all corpuses, after word segmentation, feature words whose word frequency is higher than the set threshold and that are without repetition are selected to construct the feature word bags.
# An Improved PIN Diode Model Design for a Tunable Frequency Selective Absorber
## 5 Conclusions  
This study presents a novel active frequency selective surface (AFSS) that utilizes improved PIN diodes to achieve tunable and switchable functionality within the X-band. The design was comprehensively analyzed using an HFSS and validated through an equivalent circuit model. A prototype was fabricated and tested in a microwave anechoic chamber, with experimental results closely matching the simulations. The AFSS demonstrates dual-mode operation, seamlessly switching between reflection and absorption states. In the \"off\" state, the device functions as a reflector, achieving a reflection coefficient greater than \(-3\) dB across the entire X-band. In the \"on\" state, it transitions to an absorption mode, enabling continuous frequency tuning of a 1 GHz-wide absorption band, with absorption rates exceeding 97%. This exceptional tunability and dual-mode capability highlight the  
Figure 12: Measured results for several typical bias voltage values.  
AFSS's significant potential in applications such as stealth technology, adaptive radomes, and dynamic electromagnetic control systems.  
To further enhance the device's performance, several improvements are recommended. First, the design could be optimized to achieve dual-polarization capability, allowing the AFSS to maintain high performance under different polarization directions, which would increase its versatility in complex electromagnetic environments. Second, improving angular stability by refining the structure would ensure consistent absorption performance over a wider range of incidence angles, making it more suitable for dynamic scenarios. Additionally, extending the absorption bandwidth to cover a broader frequency range would make the device applicable to a wider variety of use cases. Lastly, optimizing the bias network could reduce electromagnetic interference and improve switching speed. These enhancements would further strengthen the AFSS's robustness and adaptability, solidifying its value for advanced electromagnetic applications.  
Conceptualization, X.F.; methodology, X.F.; software, H.L.; validation, H.L.; formal analysis, H.L.; investigation, H.L.; resources, X.F.; data curation, H.L.; writing--original draft preparation, H.L.; writing--review and editing, H.L.; visualization, X.F.; supervision, X.F.; project administration, X.F.; funding acquisition, X.F. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China under Grant 62201269 and by the Postgraduate Research and Practice in Part by Interdisciplinary Innovation Program of Jiangsu Province, NO. KYCX23_0382.  
Not applicable.  
Data Availability Statement: Data are contained within the article.  
The authors declare no conflicts of interest.
# Fatigue Assessment of Explosive Bolts Considering Vibration of Fixtures
## 1 Introduction  
Explosive bolts are typical pyrotechnic release devices used for diverse applications, including launcher operation, rocket sled release, etc. [1; 2; 3; 4]. Compared with normal bolts, an explosive bolt usually has a cavity filled with a removable cartridge or an explosive charge. By detonating the explosives, a shock wave is generated and the explosive bolt is broken so as to realize multistage separation between interfaces. Hence, the separation reliability is of great significance for release devices.  
The reliability, efficiency, and design of explosive bolts has been studied [1; 4; 5; 6]. [PERSON] et al. [1; 4] established separation behavior analysis environments for ridge-cut explosive bolts and verified the numerical analysis method, including appropriate failure criteria. Their works focused on the separation mechanism and design parameters of explosive bolts. [PERSON] et al. [5] proposed a non-contact, multipoint, and remote pyroshock measurement system to measure the pyroshock waves generated, which is very important to understand the characteristics of pyroshock on the host structure. [PERSON] et al. [6; 7] proposed dynamic reliability models based on equivalent strengthdegradation paths and discussed the dynamic reliability analysis of explosive bolts in the launch process of satellites. Most of the literature has focused on the reliability of the structures in the exploding procedure and static strength design problems.  
Yet, for missile devices, this reliability issue should cover the procedure of long-distance carrying on vehicles. In this procedure, missile vehicles experience alternating road surfaces. In addition to the vehicle parts, the missile and its connecting explosive bolts also undergo vibrations, which may cause fatigue damage and result in the failure of the release device. This connecting reliability is affected by the pretension force, structural geometry, failure probability of materials, and so on. Thus, it needs a comprehensive safety analysis. So far, no literature outlines how to design and prevent fatigue failure or how to perform fatigue assessments for explosive bolts.  
Thus, in this article we state the process to evaluate the fatigue of explosive bolts on missiles during carrying on roads of Class A, C, and E. First, road roughness curves are generated via the displacement power spectral density (PSD) function according to ISO standard. Dynamics analyses are then performed by code ADAMS to obtain acceleration responses of different points on the vehicle, and the corresponding stress distribution of explosive bolts are calculated with FEM code ABAQUS. Finally, the fatigue life of the explosive bolt is evaluated by the stress-life method.
# A DRL-Based Satellite Service Allocation Method in LEO Satellite Networks
## 4 Proposed Method  
### DRL-Based Method  
The SSA problem is established in the context of the ISTN, where the number of satellites in the network tends to be relatively fixed, but the fluctuation in user numbers occurs on a smaller time scale. An effective solution should be capable of providing allocation schemes for varying user counts. In addressing this issue, we experimented with various traditional methods in this work, but their efficiency was relatively low. Therefore, considering the dynamic nature of user numbers, we explored the application of reinforcement learning to tackle this problem. For the MDP process constructed earlier, we devised a reinforcement learning approach based on small-sample training. This method can  
We optimize L by gradient descent using the double DQN algorithm:  
\[L=r+\gamma Q_{\omega^{-}}\bigg{(}s^{\prime},arg\ \max_{a^{\prime}}Q_{\omega} \big{(}s^{\prime},a^{\prime}\big{)}\bigg{)}. \tag{33}\]  
The procedural flowchart of the methodology we employed is illustrated in Figure 5.
## 4 SHINE Additional Building Blocks
### RMAP Modules  
Remote Memory Access Protocol (RMAP) [14] is the most common protocol used directly on top of SpaceWire. It allows accessing a remote memory region on the target device in several operation modes. The RMAP standard specifies two types of device: i) the Initiator, which is responsible for issuing the requests and ii) the Target, which must react to the requests and, if necessary, send a reply back to the Initiator. SHINe fully implements the RMAP standard specifications, for both the Initiator and the Target. They are implemented as application modules for the SpaceFibre and SpaceWire Endpoints, actually creating an additional layer between the final application of the user and the network infrastructure (see Figure 6).  
The top-level user application, in order to be connected with the RMAP modules, must extend the C++ abstract classes _AppRMAPTarget_ or _AppRMAPInitiator_, depending on the case. Extending these interfaces allows the underlying RMAP layer to call callback functions of the user application, for example when a new complete RMAP Request is received. Among the other features, the SHINe RMAP implementation supports:  
* All the three RMAP commands: Write, Read and Read-Modify-Write;
* Both Acknowledged and non-Acknowledged commands. In the first case, an Ack is automatically sent back by the RMAP Target to the Initiator with the status of the transaction (containing an error code in case something went wrong). In the second case, the Initiator is not notified about the result of the transaction;
* Both Verified and non-Verified commands. The data field of Verified commands is covered by a Cyclic redundancy Check (CRC) code, which is checked before executing the Read or Write request;
* Multiple ongoing requests support for the RMAP Initiator. The Initiator can send multiple requests before receiving the associated replies. The pending requests are identified, associating a Transaction Identifier ID to them;  
Hence, SHINe provides easy to use RMAP blocks with complete functionalities that can be used to simulate any kind of RMAP transaction for both SpaceFibre and SpaceWire.  
Figure 5: SpaceFibre and SpaceWire Test Applications.
## 3 Research Methodology
### Weight of Parameters
#### 3.1.2 Eigenvalue Approach  
The matrix of Eigenvector had formed to evaluate the corresponding weights of the chosen parameters. These matrices have developed through an application of the pairwise comparison amid essential requirements or alternatives. After that, the selected parameters are ranked according to the Saaty linear scale. The Saaty linear scale is set between 9 and 1/9 and each digit describes the damage level [43]. The scale can be represented as if the number from a pairwise comparison matrix is \(a_{ij}=3\), \(a_{ji}=1/3\), so the Saaty scale is \(a_{ij}=1/a_{ji}\). If the created matrix is perfectly consistent as in Equation (1), then the principle right Eigenvector of pairwise comparison matrix will be the weights of the parameter (Equation (2)).  
\[a_{ij}=a_{ik}\times a_{kj}, \tag{1}\]  
\[AW=NW, \tag{2}\]  
where \(N\) is right Eigenvalue of \(A\) with \(W\) as corresponding principle right Eigenvector and the values in the matrix \(A\) are \(a\) with \(i\), \(j\) and \(k\) as \(1,2,3,\ldots,n\) and \(n\) as number of parameters or alternatives. If the matrix is inconsistent, then the Eigenvector corresponding to the maximum right Eigenvalue \(\lambda_{max}\), where:  
\[AW=\lambda_{max}W,\lambda_{max}\geq n. \tag{3}\]  
Right Eigenvector can be found by multiplying the values in each row of pairwise comparison matrix together and taking the \(n\)th root. Where \(n\) is the number of elements in a row. Later the column matrix obtained will be normalized either by dividing each entity with sum of all values in Eigenvector or by the maximum value [41; 45].
## 3 Information-Centric Networking
### Named Data Networking: Basics
#### 3.2.2 Forwarding Fabric  
When an Interest packet arrives at an NDN node \(N\), the forwarding process begins by checking the CS. If the requested Data are found in the CS, \(N\) immediately responds with the cached data, without forwarding the Interest further. Otherwise, \(N\) accesses the PIT to determine whether the same Interest has already been forwarded. If a match exists, \(N\) aggregates the request by appending the incoming interface to the PIT entry and discards the Interest, thus avoiding duplicate forwarding. If the PIT check fails, \(N\) looks for a matching in the FIB and forwards the Interest to one or more next hops, based on the established forwarding policy.  
Once the requested Data packet returns to \(N\), it checks the PIT for a matching entry, forwards the Data to all interfaces listed in that entry, and then removes it.  
If the Data are not returned within a predefined lifetime, the \(N\) can try alternative paths or send back a negative ack (NACK) to the previous node. The latter can decide to retry the request via a different interface listed in the FIB, or propagate the NACK downstream to inform the previous nodes in the Interest path about the failure. In addition to the Interest expiration, NACKs can also identify other errors [56], including (i) no data, when the requested Data are not available at the upstream node; (ii) congestion, when the upstream path is experiencing congestion or packet loss; (iii) no route, when there is no available forwarding route to reach the producer of the requested Data.  
This mechanism ensures that the forwarding strategy in NDN can dynamically adapt to network conditions, such as link failures or congestion, without requiring global routing table updates [57].  
Figure 2: NDN node architecture.
# A Low-Profile Ferrite Dipole VHF Antenna for Integrated Mast Applications
## 4 Conclusions  
An extremely low-profile and lightweight ferrite dipole VHF antenna with a five-loop feed structure was proposed for application to an integrated mast. Ferrite with high permeability was used as the magnetic radiator to ensure low-profile. To consider a proper size and weight of the antenna, the radiator was implemented with only 44 plate-type ferrite cells with an overall weight of 1.45 kg. A multiple-loop feed structure was applied to realize a quasi-uniform magnetic field distribution which enhanced the gain of the antenna over the operating frequency band. Within the VHF band, the measured realized gains of the proposed antenna were from \(-31.48\) to \(-2.44\) dBi. Measured radiation patterns in the low and high frequency bands were omnidirectional and directional, respectively. The performance of the proposed antenna mounted on an OPV was also analyzed. The proposed antenna with overall dimensions of \(0.0636\times 0.0112\times 0.0008\lambda_{L}^{3}\) at the lowest operating frequency shows an extremely low-profile, making it feasible for use as a receiving antenna for integrated mast applications.  
Writing, W.B.P.; Antenna design and simulation, W.B.P. and S.T.-V.; Laboratory tests, W.B.P.; Methodology, Y.Y., K.-Y.L., B.Y., J.P., H.Y. and K.C.H.; Writing Review and Editing, W.B.P., S.T.-V. and K.C.H.; Conceptualization, W.B.P., S.T.-V., Y.Y., K.-Y.L., B.Y., J.P., H.Y. and K.C.H. All authors have read and agreed to the published version of the manuscript.  
This work was supported by a grant-in-aid of HANWHA SYSTEMS.  
The authors declare no conflicts of interest.
## 2 Related Work
The implicit erasing guidance used avoids the excessive erasure of the original background, thereby improving the overall quality of the final erased image. MTRNet++ [12], building upon MTRNet, adopts a similar coarseness-to-fineness strategy as EraseNet, with the network divided into coarse erasing, mask optimization, and fine erasing branches. MTRNet++ refines the mask from the candidate box level to the stroke level using the mask optimization branch and then sends the coarse erased image and optimized mask to the fine erasing branch to obtain the final erased image. [PERSON] et al. [13] proposed a weak supervision method that pre-trains text detection and background repair networks using text detection datasets and texture repair datasets. They utilize limited marked data for model fine-tuning. [PERSON] et al. [14] have introduced a novel model that facilitates stroke-level recognition by leveraging text masks. The process involves the deployment of a mask prediction module, which employs bounding boxes to delineate the textual regions within images. Subsequently, this module utilizes a U-Net architecture to predict the respective text masks. Simultaneously, a background completion module conducts partial convolutions, aligning with the ongoing enhancement of the mask. [PERSON] et al. [15] integrated a text mask generator into the text detection network to generate pixel-level binary segmentation masks. In the background repair network, they combined loss functions to create more realistic images and concatenated the two networks during inference. Beyond enhancing the logo text erasure effect, the security of AI models in practical applications, particularly the issue of adversarial examples, is another pressing and important subject that needs to be addressed. Despite the significant advancements that deep neural networks have made in fields such as image recognition and text recognition, their potential security risks should not be overlooked. Research indicates [16] that, by adding specific triggers to input samples, backdoor samples can be generated to mislead the model into making erroneous predictions. In the task of logo text erasure, the model requires the precise removal of text and the recovery of the background, and its ability to defend against malicious inputs is equally crucial. Therefore, future research should focus on strengthening the model's resistance to adversarial attacks in order to ensure its safety and reliability in real-world applications.