esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion

Table 3: Paris law parameters, \(C\) and \(m\) determined from _da/dN_ vs. \(\Delta\)K curves (mm/cycle; MPa m\({}^{1/2}\)). Figure 9: \(R\) effect on _da/dN_-\(\Delta\)K curves for specimens: (**a**) \(B=4\) mm, MP; (**b**) \(B=8\) mm, \(MP\); (**c**) \(B=4\) mm, SP; and (**d**) \(B=8\) mm, \(SP\). constant amplitude loading tests. Figure 10a-d shows the collected results from the tests performed in specimens with 8 mm thick. The typical transient behavior after overloads is not detected in all blocks because of the reduced transient zone and the crack measuring method. The analysis of the figure shows that for MP specimens the fatigue crack growth rate reduction reaches the maximum value for \(N_{int}\) = 7500 cycles, while for the SP specimens the crack growth rate continues to decrease, although slightly, when \(N_{int}\) increases from 7500 to 15,000 cycles. For MP specimens, fatigue crack growth decreases more for 7500 cycles because induced plasticity of crack closure retardation is more critical (Figure 10d). This behavior cannot be confirmed when crack closure is not measured. For the SP specimens with \(R\) = 0, the behavior is similar. This effect is more noticeable for \(N_{int}\) = 7500 cycles then for 15,000 cycles. To understand better the fatigue mechanisms processes, fracture surfaces of the samples were observed in a Philips XL30 scanning electron microscope. Figure 11 shows two exemplary photos with different magnification of the crack propagated region in Paris' law regime, representative of various observations done during the study. Both images in Figure 11 show that fatigue crack propagation occurs mainly by striation. Figure 10: Block overload effect on _da/dN_-\(\Delta K\) curves for 8 mm thick specimens: (**a**) \(R\) = 0.05, MP; (**b**) \(R\) = 0.05, SP; (**c**) \(R\) = 0.4, MP; and (**d**) \(R\) = 0.4, SP.
###### Abstract  
The inter-satellite link is an important technology to improve the accuracy of clock offset measurement and prediction for BeiDou Navigation Satellite System (BDS). At present, BDS measures clock offsets of invisible satellite mainly through the \"one-hop\" reduction mode based on the satellite-ground clock offset of the node visible satellite and the inter-satellite clock offset between the two satellites. However, there exists a systematic deviation caused by the node satellite reduction, and there is still a large room for improvement in clock offset measurement and prediction. Therefore, this paper firstly proposes a method of whole-network adjustment for clock offset based on the satellite-ground and inter-satellite two-way data. The least square method is used to realize the whole-network adjustment of clock offset based on the observations of two sources, and to obtain optimal estimates of different clock offset reduction. Secondly, the evaluation method combining internal and external symbols are proposed by the fitting residual, prediction error and clock offset closure error. Finally, experimental verification is completed based on BDS measured data. In comparison with the \"one-hop\" reduction method, the fitting residual and prediction error of the whole-network adjustment method reduces about 45.06% and 52.15%, respectively. In addition, inter-satellite station closure error and three-satellite closure error are reduced from 0.69 ns and 0.23 ns to about 0 ns. It can be seen that the accuracy of BDS time synchronization is significantly improved.  
D 2022145073[[https://doi.org/10.3390/rs14205073](https://doi.org/10.3390/rs14205073)]([https://doi.org/10.3390/rs14205073](https://doi.org/10.3390/rs14205073))  
1
# Electricity Losses in Focus: Detection and Reduction Strategies--State of the Art
## 2 Primary Classifications of Electrical Energy Losses
### Technical Energy Losses
#### 2.1.1 Heat Losses Through Resistance  
\[\Delta P_{1}=I^{2}\times R, \tag{4}\]  
where,  
* I--current through the cable (A).
* R--cable resistance (\(\Omega\)).
# MT-CMVAD: A Multi-Modal Transformer Framework for Cross-Modal Video Anomaly Detection
## 3 Supposed Method
### Overview of Method
#### 3.1.1 Hierarchical Feature Extraction  
The vision-centric feature extraction module processes raw RGB frames using a Vision Transformer (ViT) [27] backbone. Each video frame is divided into non-overlapping 16 \(\times\) 16 patches, which then undergo linear projection and spatiotemporal positional encoding, where learnable embeddings simultaneously capture spatial layout and temporal sequence information. A sliding window mechanism with stride-controlled temporal convolution aligns features across consecutive frames, generating synchronized feature sequences that preserve both local details and global temporal dependencies.
# Optimization of a Truss Structure Used to Design of the Manipulator Arm from a Set of Components
## 6 Conclusions  
This paper presents the component optimization approach for a truss structure with a verification example and the manipulator arm application.  
The optimization process is based on components and the use of penalty functions. This framework is applied to a truss structure and additional sorting conditions for the components proposed. GA was used to minimize the objective function. The optimization procedure was created in Python language, and the structure was analyzed by FEM in commercial software. The proposed procedure was tested on the truss structure, and the results were compared with several results available in the literature. Based on this, it can be said that the obtained results are comparable with the reference results.  
The proposed procedure was applied to the arm of the manipulator, which includes two flanges and optimizes the truss structure. The practical application includes, in addition to the optimization of the truss structure, other steps:  
* Components design;
* Component vector selection;
* Creation of the component model based on a truss structure;
* Component inspection using buckling analysis;
* Solution of the component model;
* The design of the verification model topology optimization with the SIMP method.  
The method is applicable to the design of the manipulator arm, and the results are comparable to the arm designed by topology optimization. In addition, the presented framework allows simple modifications of the component, where different types of elements, materials, material models, etc., can be used. The modification of the optimization algorithm for beam-type elements would probably better suit the type of components applied. Welds for joining parts also seem to be very interesting. Another goal could be designing a component system for a selected set of arms of different dimensions. This step will include designing the truss topology and minimizing the number of components for the task set. This will be the subject of further work.  
Conceptualization, J.R. and V.M.; methodology, J.R. and M.F.; software, J.R.; methods, J.R., A.S. and Z.B.; manipulators and application selection, Z.B.; selection of a construction kit, J.R. and V.M.; topology optimization, Z.P.; FEM analysis, J.R.; component optimizations, J.R.; writing--original draft preparation, J.R., D.L.; writing--review, J.R., A.S., Z.B., M.F., Z.P. and V.M. All authors have read and agreed to the published version of the manuscript.  
This article has been conducted with the support of the project Research Centre of Advanced Mechatronic Systems, reg. no. CZ.02.1.01/0.0/0.0/16_019/0000867, in the frame of the Operational Program Research, Development and Education.  
Not applicable.  
On behalf of all the authors, the corresponding author states that there is no conflict of interest.  
The following abbreviations are used in this manuscript:  
MDTI Multidisciplinary Digital Publishing Institute  
DOAJ Directory of open access journals  
FEM Finite Element Method  
GA Genetic Algorithm
## 3 Simulations
### Periodic Impulsive Interference  
Periodic impulsive noise is also common in acoustic signals [20], to test the tracking and robust performance of DMPFxNLMS in this environment, several simulations are conducted. The 300 Hz sinusoidal wave is added periodically to represent the periodic impulsive noise. The interferences of 300 Hz noise are amplified as 15 dB and 5 dB compared with the reference signal in Figure 4a. The comparisons of ANR performance for the mentioned algorithms are shown in Figure 7a,b.  
In Figure 7a, the PFxNLMS(Opt) diverged at about 50,000 iterations. The FxlogLMS maintains the steady state all the times, but it had bad ANR performance. The FxRMC had the best initial tracking, but its fluctuation became bigger when the impulsive occurred. In fact, the FxRMC had nearly perfect tracking due to the RLS core. But the bigger fluctuation was also led by its perfect tracking. When burst noise occurred, the weight vectors of FxRMC were changing fast. But the impulsive interferences often disappeared quickly, the weight vector needed to be changed again. It changed too fast such that the FxRMC had bigger fluctuations in Figure 7a. However, under the same conditions, the DMPFxNLMS had a good initial tracking rate and remained stable when exposed to periodic burst signals.  
As shown in Figure 7b, the periodic impulsive interference was smaller than that in Figure 7a, although the mentioned methods had different tracking rates and ANR performance when interference happens, they all kept steady.  
In Sections 3.1 and 3.2, the simulation results show that the PFxNLMS(Opt) with a certain \(\rho\) cannot fit different SaS environment. The FxlogLMS had a bad ANR performance. As for the FxRMC, it really had a superior tracking performance due to it's RLS core, but it cannot fit strong impulsive noise environment. Compared with these mentioned methods, the DMPFxNLMS had comprehensive using. To get further details of robust performance of DMPFxNLMS, the robustness analysis is discussed deeply in the next section.
## 3 Materials and Methods
### Separation of Normal and Anomalous Observations  
The criterion for distinguishing between normal and anomalous situations was determined through a detailed analysis of dashboard metrics and discussions with INFN-CNAF system technicians. A consistent anomaly pattern was identified: during system crashes or malfunctions, the \"TPC pull success/error\" metric exhibited a clear interruption in data reception. This interruption, as illustrated in Figure 4, was visually evident as a gap in the metric's graphical representation.  
Figure 3: The HTTP request rate section in the INFN-CNAF dashboard. Each plot of a particular color represents the HTTP request rate related to the specific host indicated in the “Name” column.  
Figure 2: The load average section in the INFN-CNAF dashboard. Each plot of a particular color represents the load average values related to the specific host indicated in the “Name” column.  
This gap does not reflect the absence of TPC pull requests but rather a disruption in monitoring processes that prevent the system from recording data. Such disruptions indicate a specific system malfunction, which is the sole anomaly addressed in this article. The absence of values in this metric often coincides with gaps in other dashboard metrics, further confirming system inactivity during these periods.  
The anomalous behavior identified by the \"TPC pull success/error\" metric is corroborated by other metrics in the dashboard, reinforcing its reliability as an indicator of this particular type of system malfunction. This metric was used to delineate periods of normal activity from those characterized by disruptions, focusing exclusively on this specific anomaly.  
Our study centers on accurately predicting this anomaly by analyzing the sequence of indicators collected in the temporal window preceding its occurrence.
Remote Sens._**2013**, \(5\), 808-809; doi:10.3390/rs5020808  
_remote sensing_  
**ISSN 2072-4292**  
www.mdpi.com/journal/remotesensing  
_New Book Received_  
_GPS/GNSS Antennas._ **By [PERSON], [PERSON], [PERSON] and [PERSON], Artech House, 2012; 420 Pages.**  
**Price \(\boldsymbol{\xi}\)109.00, ISBN 978-1-59693-150-3**  
**[PERSON]**  
MDPI AG, Kandererstrasse 25, CH-4057 Basel, Switzerland; E-Mail: [EMAIL_ADDRESS]  
_Received: 1 February 2013 / Accepted: 1 February 2013 / Published: 5 February 2013_  
The following paragraphs are reproduced from the website of the publisher [1].  
This practical resource provides a current and comprehensive treatment of GPS/GNSS antennas, taking into account modernized systems and new and developing applications. The book presents a number of key applications, describing corresponding receiver architectures and antenna details. You find important discussions on antenna characteristics, including theory of operation, gain, bandwidth, polarization, phase center, mutual coupling effects, and integration with active components.  
Moreover, you get expert guidance on the design of adaptive arrays and signal processing techniques used to mitigate interference such as jamming. Addressing critical GNSS antenna high precision requirements, this in-depth book explains the relationships between antenna gain, satellite visibility, geometric dilution of precision, and the carrier-to-noise density ratio. The book delineates requirements for both dual-band and tri-band antennas.  
You get detailed coverage of a wide range of antenna designs, including microstrip patch, quadrafilar helix, axial mode helix, spiral, inverted L, and planar inverted F antennas. Moreover, you find a discussion on new magnetic \"metamaterial\" substrates and other dielectric substrate materials. Further, this comprehensive book presents designs for very compact GNSS antennas for personal handheld devices and automobiles.  
**Table of Contents**  
Preface  
Chapter 1. Introduction to GNSS Antenna Performance Parameters  
Chapter 2. FRPAs and High-Gain Directional Antennas* [3] Multiband, Handset, and Active GNSS Antennas
* [4] Adaptive GPS Antennas
* [5] Ground Plane, Aircraft Fuselage, and Other Platform Effects on GPS Antennas
* [6] Measurement of the Characteristics of GNSS Antennas
* [7] Antennas and Site Considerations for Precise Applications
* [8] About the Authors
* [9] Index
* [10] _Editor's Note_: The brief summary and the contents of the books are reported as provided by the author or the publishers. Authors and publishers are encouraged to send review copies of their recent books of potential interest to readers of _Remote Sensing_ to the Publisher (Dr. [PERSON], Multidisciplinary Digital Publishing Institute (MDPI), Kandererstrasse 25, CH-4057 Basel, Switzerland. Tel.: +41-61-683-77-34; Fax: +41-61-302-89-18, E-Mail: [EMAIL_ADDRESS]). Some books will be offered to the scholarly community for the purpose of preparing full-length reviews.
## 4 Proposed Algorithm
### Genetic Algorithm  
To reduce the computation time, the proposed GA performs the visibility test before the mutation, crossover, and selection loops. The entire genetic algorithm procedure can be described as follows:  
1. An initial population of N chromosomes is generated by a random algorithm [9] based on the camera placement information, including positions, types, and poses in the visibility matrix.
2. For each chromosome of the population, the total cost and coverage level are calculated. The coverage level is calculated as the number of covered grid points of the surveillance target divided by the total number of grid points of the surveillance target.
3. A population group that satisfies the minimum level of coverage is selected for reproduction by using the tournament selection method.
4. From the population selected in step 3, a new population of the next generation is generated by using crossover and mutation operations.
5. 2, 3, and 4 are repeated until the stopping criterion is satisfied.
# Regeneration Performance of Activated Carbon for Desulfurization
###### Abstract  
This study explored the regenerated performance of activated carbon (AC) as SO\({}_{2}\) adsorbent. The optimal conditions of SO\({}_{2}\) removal were determined by experiment, and then the adsorption efficiency of AC was studied by a method of thermal regeneration. The characteristics of regenerated AC were analyzed by Brunauer-Emmett-Teller (BET) and Scanning Electron Microscopy (SEM) methods. The test results showed that the most suitable adsorption conditions were using 4 g of activated carbon, 1.65 L/min gas flue rate, and 5% O\({}_{2}\). During the ten regenerations, the desulfurization efficiency and sulfur capacity of AC still maintained a high level. The characterization results showed that the increase of material surface area and pore volume were 101 m\({}^{2}\) g\({}^{-1}\), and 0.13 cm\({}^{3}\) g\({}^{-1}\), respectively, after the cycles.  
Keywords:activated carbons; desulfurization; regeneration +
Footnote †: journal: Applied sciences
## 3 Numerical Analysis Model of the NCS
### Material Parameters
#### 3.3.2 Steel  
The liner of the NCS is made of P265 GH-grade steels (manufacturer, city, and country), and a bi-linear model is employed to characterize its stress-strain behavior, as depicted in Figure 6. To accurately describe the mechanical behavior of the corroded liner, it is necessary to establish the corresponding stress-strain relationships. In this paper, the stress-strain relationship for the corroded liner is modeled by discounting the mechanical parameters of the uncorroded liner. Utilizing the outcomes of uniaxial tensile tests conducted on corroded liners, the mechanical parameters for liners under various degrees of corrosion can be determined through the following equations:  
\[\begin{cases}E_{\text{s,c}}=\left(1-0.04\eta\right)\,E_{\text{s}}\\ f_{\text{s,c}}=\left(1-0.46\eta\right)\,f_{\text{s}}\,\,\,\,\,\,\,\left(0\,\leq \eta\leq 50\%\right)\\ f_{\text{u,c}}=\left(1-0.37\eta\right)\,f_{\text{u}}\end{cases} \tag{5}\]  
where \(E_{\text{s}}\), \(f_{\text{s}}\), and \(f_{\text{u}}\) represent the elastic modulus, yield strength, and ultimate strength of the uncorroded liner, respectively; \(E_{\text{s,c}}\), \(f_{\text{s,c}}\), and \(f_{\text{u,c}}\) represent the corresponding parameters under corrosion conditions, respectively. \(\eta\) represents the corrosion degree, which is defined in this paper as the reduction rate of the average cross-sectional area of the corroded liner.  
In addition, the reinforcement employed in the NCS consists of HRB400 and HRB335-grade steel, while the 1770-grade strand is utilized for the prestressed tendons. In the analytical model, an ideal elasto-plastic model is used to characterize the stress-strain behavior of both the reinforcement and prestressed tendons, as it can greatly enhance the efficiency of the calculations.
## 4 Discussion
### Comparison of FSOF and QPAML  
By introducing perturbations into the metabolic model and propagating them, we were able to take advantage of the flux variation profiles observed by [PERSON] et al. (2010) [30], extending the ability of FSOF from only predicting reactions for activation to also predicting candidate reactions to be silenced or attenuated.  
By comparing the reactions predicted by both models to be activated, FSOF selects as candidates the reactions that contribute to the production of a metabolite under specific growth conditions; however, QPAML first considers which is the optimal pathway to produce a metabolite without the limitations of the culture medium. This allowed our algorithm to correctly classify 26 reactions of the 27 that have experimental evidence, while FSOF identified only 20 of these reactions (See Figure 3). QPAML also uses the FSOF approach to identify which reactions can be overexpressed. However, it integrates information from multiple perturbations to identify which reactions are more robust in producing a metabolite when there are limitations in the culture medium.  
By introducing enzymatic perturbations, emergent properties of the metabolic network arose; FSOF classifies reactions by whether they favor, affect, or have no effect on producing a metabolite. We found that among the reactions that affect the production of a metabolite, there is a large group of reactions whose fluxes are positively correlated with biomass production but are not affected by changes in the production of a metabolite, so they are not good candidates to be modified.  
Finally, introducing perturbations allowed us to identify candidate reactions to be silenced, such as the reaction catalyzed by the enzyme tryptophanase. Using only FSOF, this reaction does not present flux. It is considered a reaction that does not affect the production of tryptophan. However, using FSOF in the context of QPAML, _tnaA_ presents an inverse relationship with tryptophan and classifies it correctly as a candidate to be silenced.  
To a difference of FSOF, QPAML is a classification model that can integrate other types of information to be trained, for example, it uses the essentiality of reactions to distinguish between reactions that are candidates to be silenced or attenuated.
# Imperceptible-Visible Watermarking to Information Security Tasks in Color Imaging
## 4 Experimental Results
### Suitability for Any Class of Images  
Similar to the most recent and sophisticated reported algorithms [24], the proposed algorithm can use any class of images to embed any binary watermarks, mainly QR codes. As mentioned above, to evaluate the performance of the proposed algorithm, the binary watermark patterns FI, QR, and UNAM are used.  
Although not all images of the UCID dataset ensure the largest homogeneous region to embed the mentioned watermark patterns, the proposed algorithm is able to obtain a low visual quality degradation and high imperceptibility; e.g., Table 4 shows three images that ensure the largest homogeneous region with the minimum required variance and three that do not ensure it, and its corresponding exhibited watermark pattern. Additionally, its performance evaluation in terms of quality degradation, imperceptibility, and robustness is shown, wherein both kinds of images offer a good quantitative and visual performance in non-attacked images.