esa-sceva/satcom-chunk-collection huggingface dataset:
# Research on Microhole Processing Technology Based on the Femtosecond-Laser Spiral Trepanning Method
## 1 Introduction
Therefore, in this study, femtosecond-laser spiral trepanning was used to process microholes. By varying the path of spiral scanning and laser power, microhole with different tapers can be realized. Meanwhile, the roundness, accuracy, and taper of microholes can be controlled. To achieve a larger taper, the defocusing amount was investigated. The experimental results showed that the method is viable. Compared with the previously reported method [11; 12; 13; 14; 15; 16; 17; 21; 22; 23], the femtosecond-laser spiral trepanning method is very simple and highly efficient for processing different taper microholes. Besides, the formation mechanism of different microholes is also explained in this paper.
# Towards Feasible Capsule Network for Vision Tasks
## 1 Introduction
However, this limited depth with only two-to-three capsule layers inherently restricts the expressivity and potential of CapsNets. In prior studies, it has been observed that incorporating dense connections [34] and residual blocks [35; 36] can be beneficial for CapsNets. However, these studies have not fully extrapolated the idea due to a lack of comprehensive comparisons with the original models. Additionally, some researchers have attempted to stack capsule layers by simplifying the routing mechanisms [16; 24; 37; 38; 39; 40], but this approach often results in a non-faithful implementation of CapsNets. Building upon these insights, our study aims to bridge these gaps by thoroughly investigating the deeper backbone within the context of CapsNets. Furthermore, we strive to provide a faithful and comprehensive evaluation by conducting thorough comparisons with the original models. Our contributions are as follows:  
* We explore deeper architectures to unlock the capabilities of CapsNets;
* By leveraging the strengths of various backbone models, we propose a capsule head wrapping (CapsHead) approach and carefully experiment with modifications to the capsule head and routing mechanism;
* We aim to enhance the expressivity and performance of CapsHead in tasks such as classification, medical image segmentation, and semantic segmentation. This paper follows a structured organization: Section 2 presents the methodology, then Section 3 reviews related works, Section 4 showcases experimental results, and Section 5 concludes the study.
## 5 Discussion and Conclusions  
A modified DLO procedure for steel parts without bolts and steel connections with a single bolt was presented. The modified approach includes slip line and yield zone mechanisms acting together. Furthermore, a compression-only contact was included too. A modification factor for single bolts has been worked out to ensure the correct bearing behaviour. For all considered cases, a comparison between the ultimate loads from DLO, literature, and Eurocode EN 1993-1-8 were made. The following conclusions can be drawn:  
First, specimens without bolts were investigated. It was shown that slip line and yield zone mechanisms must both be included, otherwise mechanisms with higher loads were obtained in some cases. In doing so, the DLO procedure shows in all cases a correct behaviour. The LP-algorithm was able to find in all considered cases the minimum load, which corresponds to the _lower bound_ solution, and therefore, equals the correct ultimate load, independent of the failure criterion used.  
For bolted specimens, the simple case of a connection with a single bolt was considered. It was found that a second ring of discontinuities close to the bolt hole is necessary to obtain convergent solutions, represented by the modification factor \(\mathbf{k}_{\text{d0}}\). Compared to the bearing resistances from codes, the DLO delivers conservative loads in many cases. Therefore, the modification factor \(\mathbf{k}_{\text{fy},\text{c}}\) was recalculated from the Eurocode and literature, and verified by a parameter study. Depending on the edge distances, the DLO results still in conservative resistances for most of the cases.  
A first study to the application of the DLO procedure to steel parts and steel connections has been presented in this paper. In general, the behaviour and the obtained loads are in a good agreement with the analytical solutions and the results from the FEA. Therefore, future work will be done in this field of research, which will focus on more sophisticated connections with bolt groups and further components (as stated in Table 1). Compared to standards, the DLO can also be used to analyze \"automatic\" arbitrary geometries (such as the FEM). Compared to the FEM, the DLO approach is much simpler for calculating the limit load. Maybe one day, the DLO could also become a standard tool in designing steel constructions and connections as the FEM already is.  
The open access fee was funded by the publication fund of the University of Innsbruck.  
The author would like to thank the University of Innsbruck, for giving me the opportunity to carry out this research and for providing the open access funding.  
The author declares that there is no conflict of interest. The funder had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript or in the decision to publish the results.
# HyperIO: A Hypervisor-Based Framework for Secure IO
## 2 Background
### Tpm  
The trusted platform module (TPM) provides secure, tamper-resistant storage and cryptographic functions that can operate on this storage. In addition to key storage functionality, symmetric and asymmetric cryptography, and hashing, TPM can seal a key to its internal state. Later the key can be fetched only when the TPM is in this exact state. The state of the TPM is defined by its platform configuration registers (PCRs). The PCRs can be read but not directly written. Instead, PCRs are extended by hashing their current value with some new value: \(\mathrm{PCR}_{n}=\mathrm{hash}(\mathrm{PCR}_{n},\mathrm{Value})\).  
Each time an EFI application [15] is loaded, the EFI firmware extends the PCRs with the hash value of the application's image. When an EFI application seals a key, it guarantees that only the current and previously loaded applications can retrieve the key in the future. VirtSecIO, embedded in an EFI application, uses the TPM to store cryptographic keys that cannot be accessed by the operating system.
## 2 Related Work
### Approaches Based on Emerging Technologies  
The authors of [30] proposed a deep learning-based solution to detect cybersecurity threats. The authors proved the effectiveness of their approach using experimental analysis. The proposed solution achieved promising results. However, similar approaches must be tested in real environments to prove their effectiveness.  
The BLOCKchain-Based Platform for Healthcare Information Exchange (BlocHIE) was introduced in [31]. The security requirements (privacy and authentication in particular) were evaluated by analyzing healthcare data extracted from different sources. Based on the evaluation, the authors implemented a pair of loosely coupled blockchains to process heterogeneous healthcare data. The privacy and authentication requirements were further fulfilled by integrating on-chain verification and off-chain storage. To enhance the system fairness among users and the throughput, the authors also proposed two packing algorithms. This platform is a useful solution because it can provide both privacy and authenticity. However, the system throughput and fairness might decrease the effectiveness of the platform.  
The fairness-based transaction packing algorithm was introduced in [32]. Based on theoretical analysis, the authors deduced that fairness is somehow associated with the sum of waiting times of chosen transactions. Thus, a mini-heap-based optimal algorithm was presented, and the time complexity of this algorithm was analyzed to prove its effectiveness. The proposed algorithm achieved superior results compared to existing solutions in terms of both transaction response time and fairness.  
[PERSON] et al. [33] proposed a protocol utilizing a bloom filter and a multi-keyword search. The proposed solution is efficient and enhances privacy preservation. To carry out a multi-keyword search process, the bloom filter is used to choose a low-frequency keyword in order to be utilized to filter the database. This procedure would decrease the computational complexity because the algorithm chooses a low-frequency keyword, meaning most of the data will be excluded. Moreover, the authors proposed a technique known as pseudorandom tags to perform each search process in a single round
# 5G-Based Smart Healthcare and Mobile Network Security: Combating Fake Base Stations
## 2 Background
### Security Concerns of Smart Healthcare  
The cyber security of smart healthcare networks stands as a pivotal aspect in ensuring the safe and seamless deployment of critical healthcare services. Protecting sensitive data and personal smart healthcare devices is imperative to safeguard the privacy of patients and medical personnel. Given the mission-critical nature of smart healthcare services, which directly influence human well-being, maintaining high availability and reliability is paramount. Any security breach or service interruption could have life-or-death implications for patients.  
[PERSON] et al.'s research [7] presents an all-encompassing review of 5G-based smart healthcare network security. Their study delves into the technological features and services linked to 5G smart healthcare security, covering aspects such as authentication, confidentiality, availability, nonrepudiation, and integrity. Furthermore, the paper examines various  
Figure 1: An example of a 5G-based smart healthcare network.  
security threats inherent in 5G smart healthcare connectivity along with the available solutions. It also identifies several research issues and outlines potential future research directions for 5G-based smart healthcare security.  
[PERSON]'s research [8] contributes a novel classification scheme for smart healthcare systems and offers insights into the existing literature concerning smart healthcare systems. The study also explores crucial security issues and the countermeasures proposed in the current literature. Lastly, it identifies open research challenges and outlines directions for future research in the domain of smart healthcare systems.
# A Lightweight Crop Pest Detection Method Based on Convolutional Neural Networks
###### Abstract  
Existing object detection methods with many parameters and computations are not suitable for deployment on devices with poor performance in agricultural environments. Therefore, this study proposes a lightweight crop pest detection method based on convolutional neural networks, named YOLOLite-CSG. The basic architecture of the method is derived from a simplified version of YOLOv3, namely YOLOLite, and k-means++ is utilized to improve the generation process of the prior boxes. In addition, a lightweight sandglass block and coordinate attention are used to optimize the structure of residual blocks. The method was evaluated on the CP15 crop pest dataset. Its detection precision exceeds that of YOLOv3, at 82.9%, while the number of parameters is 5 million, only 8.1% of the number used by YOLOv3, and the number of computations is 9.8 GFLOPs, only 15% of that used by YOLOv3. Furthermore, the detection precision of the method is superior to all other commonly used object detection methods evaluated in this study, with a maximum improvement of 10.6%, and it still has a significant edge in the number of parameters and computation required. The method has excellent pest detection precision with extremely few parameters and computations. It is well-suited to be deployed on equipment for detecting crop pests in agricultural environments.  
crop pest detection; parameter; computation; k-means++; lightweight sandglass block; coordinate attention +
Footnote †: journal: Applied Sciences  
Article  
A Lightweight Crop Pest Detection Method Based on Convolutional Neural Networks
# High-Harmonic and Terahertz Spectroscopy (HATS): Methods and Applications
## 3 HATS for Molecules
### The Alignment Dependent Electron Dynamics for HHG with THz Phase Reference
If the driving laser is polarized perpendicular to the molecular axis, the dipole for the HOMO will be weakened, whereas the HOMO-1 induced dipole will be strengthened [73]. For harmonics at the cut off region, the HOMO-1 contribution may  
Figure 9: The normalized THz yields as functions of the dual-color relative phase for xenon (blue), carbon dioxide (red), nitrogen (orange) and argon (green) under the same experimental conditions (laser intensity of the \(\omega\) and 2\(\omega\) is about 1.8 \(\times\) 10\({}^{14}\) W/cm\({}^{2}\) and 1.8 \(\times\) 10\({}^{13}\) W/cm\({}^{2}\), respectively). The optimal phases for THz outputs are highlighted by the black dashed lines. Vertical shifts are applied on the baselines of different gas types to offer a more clear version. be strong especially when the N\({}_{2}\) molecule is aligned perpendicular to the generation laser pulses. This may be the reason for the alignment dependent optimal phases for the 32 nd harmonic. Meanwhile, the optimal phases of THz yield can be determined as 0.8\(\pi\) due to the previous experiments on argon and nitrogen [17; 82]. With the help of this THz phase reference, the optimal phases for different harmonics could be compared to the theoretical results directly. Nitrogen is not the only molecule for multi-orbital effect and another case could be found on carbon dioxide by applying the HATS method [95; 96], which also exhibits the participation of the lower-lying molecular orbitals within the harmonic emission process [72]. In brief, the combined measurement of HATS from aligned nitrogen reveals the absolute optimal phases with the help of the THz reference, which would be hardly accessible with HHG or THz spectroscopy alone. It may be sufficient to detect the harmonics' relative phases by applying the ex situ measurements. However, the absolute phase of high harmonics matters for compression of attosecond pulse (train) [97], for which the in situ HATS approach could provide valuable information.
## 4 Inorganic Fertilizers  
The need for inorganic fertilizers arises in order to supplement the soil nutrients needed for crop production. The soil could be deficient in some nutrients because, e.g. constant use of the soil, which negates recycling; post-harvest practices, which may take away the nutrients with the harvested crops; etc. However, for sustainability and excellent crop production, there is need for plant supplements, which could be in form of organic manure or inorganic fertilizers. Inorganic fertilizers are synthetic fertilizers made from petroleum, the formulation of which could either be single nutrients or combination of different nutrients. In the case of different nutrients, they are referred to as multi-nutrient fertilizers and they contain majorly nitrogen, phosphorus and potassium among other nutrients and can be complete or balanced. They are balanced when they are of the same ratio and complete when they are needed in a particular formula. The soil supplies most of the nutrients needed for plant growth, but sometimes the nutrients are depleted during harvest and need to be replaced using fertilizers.  
Fertilizers help plants to grow and absorb the appropriate nutrients required in crops. Most conventional fertilizers contain the macronutrients, namely nitrogen, phosphorus and potassium, with little calcium, sulfur and magnesium. Other micronutrients such as zinc, iron, copper and manganese become lacking, making the crops deficient. A typical fertilizer with all nutrients should have the following: N (2-4%), P (0.3-1%), K (1.5-5%), S (0.15-0.8%), Ca (0.2-1.5%), Mg (0.15-1%), Zn (10-100 ppm), Fe (20-500 ppm), Mn (15-250 ppm), Cl (4-50 ppm), Co (2.5-50 ppm), Cu (5-75 ppm), and Mo (0.03-10 ppm) [52]. The confronting issues are: How much of the nutrients are absorbed by the plants? Are they in a manner that could be absorbable? Do the crops get the complete nutrients that fulfils the human requirement when consumed?  
There is no doubt that inorganic fertilizers are made having full knowledge of the necessary ingredients needed by the plants. With this complete formula of ingredients, when applied to the soil, they are dispersed by water molecules and the nutrients are broken down into various forms that are needed by the plants. There are various soil reactions and mechanisms that determine the quantity absorbed by the plants.  
Soil test is a preliminary operation that must be done before application of fertilizers. If the soil is acidic, using urea fertilizer, for example, the NH\({}_{3}\) released from the reaction of the urea fertilizers with sufficient water molecules is absorbed in the form of ammonium ions and, when they are basic, there is no change. In neutral or near neutral pH (7-8), the ammonia may escape into the environment, causing pollution such as greenhouse gases. These are the challenges that need to be addressed.
# A New Defect Diagnosis Method for Wire Rope Based on CNN-Transformer and Transfer Learning
## 3 Methodology
### Image Establishment  
#### 3.2.1 Defect Location  
For the establishment of normal and defect feature images, defect location is necessary and crucial to further model training outcomes. According to the characteristics of the LMA signals, the defect samples are small when compared with the normal components, and their fluctuations and changes are obvious. Therefore, an excellent anomaly detection algorithm, isolation forest (iForest), was used in this study to complete defect pre-locations from the numerous normal data. The detail of iForest can be observed in reference [32]. The detection results are different as the hyper-parameters change. According to the professional's prior knowledge, the number of iterations, isolation trees, and sub-sample heights were set as 10, 100, and 256, respectively. Meantime, the detection threshold was 99.5%, that is, 0.05% of abnormal components could be detected. Although the defect signals indicated by the red spot can be clearly located, as shown in Figure 4, multipledata for each defect location still exist, which need to be processed further to meet the requirements of data extension and image processing.  
Although the iForest method can effectively detect the defect signals, an additional processing step is required to obtain the single maxima and minima values for each defect sample. Local extremum is a common and simple algorithm used in signal processing methods, which can be used as a filter for data optimization. The window size of the local extremum filter is an important parameter and it must be adjusted according to real  
Figure 3: Comparison between original loss of metallic cross-sectional area signals following preprocessing step. (**a**) original LMA signals; (**b**) refined signals following the EMD method.  
Figure 2: Decomposition results for wire rope loss of metallic cross-sectional area signal based on empirical mode decomposition method. (**a**) original signal; (**b**) IMF1; (**c**) IMF2; (**d**) IMF3; (**e**) IMF4; (**f**) IMF5; (**g**) IMF6; (**h**) IMF7; (**i**) IMF8; (**j**) IMF9; (**k**) IMF10; (**l**) residual signal IMF11; IMF denotes intrinsic mode function.  
applications. In this study, the window size was 100 and the final output results were acceptable. As shown in Figure 5, every result (red dot) can clearly locate each defect sample, which provides a foundation for feature image establishment.
# Micro-Focusing of Broadband High-Order Harmonic Radiation by a Double Toroidal Mirror
## 4 Conclusions  
We have presented a micro-focusing setup for a broadband harmonic beam based on two toroidal mirrors in a Wolter configuration. The setup is capable of focusing the beam to a spot size of 3.6 \(\times\) 4.0 \(\upmu\)m\({}^{2}\), which was optimized and characterized using an XUV wavefront sensor. The focus dimensions agree well with the expected value according to the ray-tracing simulations. The wavefront sensor was found to be an excellent tool to optimize the focusing optics alignment, providing quick and precise feedback. Pre-existing aberrations of the XUV beam could also be corrected. The non-invasive property of wavefront measurements makes it possible to control the focusing quality and thus guarantees the highest intensity on target during experiments.  
Figure 6: Focal spot (**a**) calculated from wavefront measurement by back-propagation; and (**b**) calculated from ray-tracing simulations.  
**Acknowledgments:** The research was supported by the Swedish Research Council, the Swedish Foundation for Strategic Research, the European Research Council (grant 339253 PALP), LASERLAB-EUROPE (proposal LLC002276), and the European COST Actions MP1203 and CM1204. This project received funding from the European Union's Horizon 2020 research and innovation program under Marie Sklodowska-Curie Grant Agreement No. 641789 MEDEA and the FET-open grant No. 665207 VOXEL. The authors would like to thank [PERSON] and [PERSON] for lending high-sensitivity cameras. The ELI-ALAPS project (GINOP-23.6-15-2015-0001) is supported by the European Union and co-financed by the European Regional Development Fund.  
[PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] conceived and designed the experiments; [PERSON], [PERSON], [PERSON], and [PERSON] performed the spot characterization by the scintillator microscope; [PERSON]. designed the scintillator microscope; [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON]. performed the wavefront optimization experiments; [PERSON] and H.C.-A. performed the ray-tracing simulations; [PERSON] performed the back-propagation of the wavefronts and intensity recorded by the wavefront sensor; [PERSON] contributed to the analysis tools. All authors participated in writing the manuscript.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Research on Safety Prediction of Sector Traffic Operation Based on a Long Short Term Memory Model
## 2 Air Traffic Parameters in Sectors  
### Definition of Traffic Parameters  
(1) Volume: the number of aircraft operating in this sector during statistical period. We calculate this parameter using Equation (1), where \(l\) represents the number of segments in current sector, \(T\) represents observation time, and \(n_{i}\) represents the number of aircrafts in each segment:  
\[volume=\sum\limits_{i=1}^{l}\frac{n_{i}}{T} \tag{1}\]  
(2) Density: the number of aircraft per unit length of each segment in sector during statistical period. We calculate this parameter using Equation (2), where \(l\) represents the number of flight segments in the sector, \(q_{i}\) represents the number of aircraft in each segment during observation period, and \(length_{i}\) represents the length of each flight segment (unit: km):  
\[density=\sum\limits_{i=1}^{l}\frac{q_{i}}{length_{i}} \tag{2}\]  
(3) Velocity: the average velocity of aircrafts which are in operation during statistical period. We calculate this parameter using Equation (3), where \(m\) represents the number of filtered data, \(q_{i}^{*}\) represents number of aircrafts in sector, and \(v_{m}\) represents each aircraft speed which recorded in related data:  
\[velocity=\frac{1}{q_{i}^{*}}\sum\limits_{i=1}^{q_{i}^{*}}\frac{\sum\limits_{i= 1}^{m}v_{m}}{m} \tag{3}\]  
Figure 1: Research framework.