esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
With the rapid development of object detection, its application has penetrated various fields of our daily lives. The primary purpose of object detection is to distinguish the categories of objects and locate their positions. Pedestrian and vehicle detection is an essential branch of object detection. In real life, pedestrians and vehicles introduce problems such as severe occlusion, large-scale variation, and multiple poses. These problems lead to poor performances by detectors.  
In recent years, object detection algorithms based on deep learning have achieved high accuracy using classic datasets such as MS COCO [1] and Pascal VOC [2]. However, in these two datasets, the resolution of pictures is 640 px, and each picture contains only a few objects, which affects the real-world application of target detection. Although there are some high-resolution remote-sensing image datasets, such as VisDrone [3] and UAVDT [4], the resolution of pictures in these datasets is about 2000 px, which does not match real-world scenarios. Recently, the gigapixel dataset PANDA [5] (25,000 \(\times\) 14,000 pixels) proposed by Tsing University has gradually become the key to studying real-world object detection. Thanks to the development of array camera technology, PANDA contains gigapixel-level images, and the field of vision covers a reasonably wide range. Gigapixel-level surveillance videos recently became necessary materials to analyze group behavior in public space [6].  
In recent years, object detection has gradually changed from relying on manual feature extraction methods to deep learning networks. Whether using the traditional datasets MSCOCO and Pascal VOC or the remote-sensing datasets VisDrone and UAVDT, the performance of object detectors is improving daily. However, gigapixel-level object detection still needs further research. The following sub-sections discuss the existing algorithms for traditional and gigapixel-level object detection.
## 5 Conclusions  
Since the discovery of MSHs in plants, many researchers have studied the effects of exogenous MSHs on plant development and growth. In the present study, for the first time, we investigated the effects of four different MSHs at four different concentrations on the genetic and epigenetic stability of wheat plants at the seedling growth stage using CRED-iPBS and iPBS analyses. The study identified MSH-induced retrotranson polymorphisms, as well as methylation changes. The current results showed that MSH treatments altered the stability of the genomic template of wheat plants and affected the cytosine methylation status of wheat plants at the seedling growth stage. In the context of progesterone therapy,an inverse relationship was found between the concentration of progesterone and the levels of GTS, indicating a reduction in GTS as the concentration of progesterone increased. On the basis of the mean proportion of polymorphisms detected in _Hpall_ and _Mspl_ digestion, it may be deduced that elevated amounts of MSHs (17-\(\beta\)-estradiol, progesterone, and estrogen) would provide a safeguarding impact against hypermethylation. Nevertheless, further studies are recommended to better understand the function that MSHs play in the molecular mechanisms affecting wheat plant growth. In conclusion, our work shows that MSHs induce genetic and epigenetic changes and play an active role in maintaining genomic stability.  
Conceptualization, K.H., A.T. and F.D.; methodology, K.H., A.T. and F.D.; software, A.T. and A.P.-A.; validation, K.H., P.U., A.L.-B. and J.B.; formal analysis, K.H., A.T. and G.O.; investigation, K.H., A.T., A.P.-A., A.L.-B. and J.B.; resources, K.H. and A.T.; data curation, K.H., A.T., P.U., B.J. and B.E.; writing--original draft preparation, A.T.; writing--review and editing, J.B., A.L.-B., B.E. and A.P.-A.; visualization, K.H., A.T. and J.B.; supervision, K.H. and A.T.; project administration, A.T., K.H. and J.B. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
All data supporting the conclusions of this article are included in this article.  
The authors thank the anonymous reviewers and editors for their constructive comments on this manuscript.  
The authors declare no conflict of interest.
## 4 Solution to the Problem of OFN/vOFNs with Non-Convex Shapes
### Summary  
The analysis of all 256 possible OFN shapes revealed that approximately 12.7% of cases required normalization. Proper shapes and singletons remained unaffected.  
Normalization first involves determining the number's current order according to Definition 19, followed by applying the normalization rule in Definition 20. After normalization, only proper numbers with \(\text{core}(A)\leq\text{supp}(A)\) are obtained, ensuring full interpretability. Importantly, the original order of each number is preserved after normalization, carrying valuable trend information.
# Estimation of Resonance Frequency for Systems with Contact Using Linear Dynamics Methods
## 5 Experimental Verification  
### Tests on Cantilever Beam  
To perform experimental verification of the formula, a test stand was designed and manufactured. The test bench for the vibration examination was designed as a rail and a guide car, with an attached sample holder. The sample was mounted vertically to eliminate the influence of gravity and avoid the need to mount the rail vertically. The vibrations were forced by the inductor attached with the base to the frame shared with the rail; the vibrating head was connected with the carriage by a rod.  
The MTS Systems Corporation shaker model 2100E11 was used as mechanical excitation. The imposing signal was an audio file sent to the QSC RMX2450 be amplifier, which was directly connected to the shaker.  
Vibration measurement was performed with laser vibrometer Polytec PSV-400 connected to the Polytec OFV-5000 controller. Additionally, the Siemens LMS system with PCB 356A16 was used for signal calibration and additional measurements in the sample holder. The complete test bench is shown in Figure 6.  
Figure 5: Error visualization of non-linear dynamics resonance frequencies and estimated with the presented formula.  
For imposing signal generation, the Python script was written, which can create a wave file with sinusoidal signal with variable frequency and amplitude. The script allows one to impose the sine sweep test of constant acceleration, which was used to find resonance frequency of the system.  
The experiment was planned with the following assumptions:  
* A total of three flat specimens made out of CFRP composite, with the same dimensions as described for nonlinear dynamics simulation, to investigate manufacturing deviations;
* Five different grips to support specimens with four different lengths of contact (20 mm, 40 mm, 60 mm, 80 mm) and without contact (one side simple fixation);
* Two additional masses that were attached to the free end of each sample to verify the system with different natural frequencies (case without attached mass and two cases with different masses).  
Each of the probes was repeated three times to compensate for variation on mounting the specimen on the test bench. The cumulative number of probes performed was:  
\[n_{prob}=3\times 3\times 5\times 3=135 \tag{3}\]  
The measured dimensions of the prepared specimens are presented in Table 2.
## 4 Effects of the Parameters of Oceanic Turbulence and Mathieu-Gaussian Beam  
To explore the influence of beam structure parameters and oceanic turbulence parameters on the transmission of vortex modes, in this section, we numerically study the transmitting probability of signal vortex modes for a MG beam propagating in an anisotropic oceanic turbulence. In the following analysis, we set the calculation parameters as: \(q=0.2\), \(2l_{0}=2\), \(l=2\), \(w_{0}=0.05\) m, \(D=0.1\) m, \(\beta=0.0001\), \(z=150\) m, \(\lambda=561\) nm, \(\chi_{t}=10^{-8}\) K\({}^{2}/\)s, \(\varepsilon=10^{-5}\) m\({}^{2}/\)s\({}^{3}\), \(\eta=1\) mm, \(\varpi=-4.5\), and \(\zeta=2\), unless other variable parameters are specified in calculation. In this section, we first analyze the influence of system parameters on the transmission of signal vortex modes, and then analyze the influence of oceanic turbulence on them.
## 1 Introduction  
Many decision problems related to transportation involve optimizing two or even multiple objectives simultaneously to better simulate the real-world scenarios [1, 2, 3]. For instance, a logistics company aims to maximize customer satisfaction with its delivery services while minimizing logistics costs [4]. Bi-objective optimization is a specialized type of multi-objective optimization, aiming to identify solutions that satisfy two trade-off objective functions to the maximum extent within a feasible set of decision variables. Compared with the optimization problems with a single objective, the bi-objective optimization problems are more challenging [5].  
Generally, in bi-objective optimization problems, it may be difficult for a solution to achieve high performance in both objective dimensions. Thus, bi-objective optimization seeks to balance two conflicting objectives as much as possible while meeting all constraints [6, 7]. As a result, the optimal solutions for bi-objective optimization problems are typically a set of compromise solutions, that is, Pareto optimal solutions, also referred to as efficient solutions, nondominated solutions, or noninferior solutions [8,9].  
In the context of bi-objective optimization, this study investigates whether finding the full set of Pareto optimal solutions is an excessive requirement and how to identify an appropriate subset of Pareto optimal solutions. The main contributions of this study address the two questions. First, this study demonstrates that it is not necessary to find the full set of Pareto optimal solutions for practical purposes; instead, the focus should be on finding a subset of Pareto optimal solutions whose resulting set of nondominated objective vectors is the same as, or at least a good approximation of, the full set of nondominated objective vectors for the problem. As a result, the workload of solving bi-objective problems is significantly reduced. Second, we provide a detailed and rigorous justification of the methods for generating a near-optimal subset of Pareto optimal solutions, including the revised \(\epsilon\)-constraint method, the improved revised \(\epsilon\)-constraint method, and the augmented \(\epsilon\)-constraint method. We also present strict mathematical proofs for the proposed lemmas, propositions, and corollaries.  
The remainder of this study is organized as follows. In Section 3, we introduce some basic concepts of bi-objective optimization and propose the idea of adopting a subset of Pareto optimal solutions to solve bi-objective optimization problems. In Section 4, we analyze the near-optimality of the Pareto optimal solution subset and provide rigorous mathematical proofs. In Section 5, computational results are carried out based on a real-world bi-objective optimization problem to validate the effectiveness and efficiency of our methods. Section 6 summarizes the main findings of this study and discusses potential directions for future studies.
## 9 Challenges  
### Security  
Securing the vehicle from external attacks so that vehicle is not hijacked remotely is a very real threat and will be the most important challenge to address. This will be especially challenging in autonomous or driver-less vehicles, as by design the vehicle is required to navigate on its own by controlling the steering and control system of the vehicle. The brains of the vehicle or the OBU will control the movement of the vehicle and the OBU will be connected to the internet and the vehicular cloud. Therefore, securing the control systems of the vehicle will be the first thing that has to be done and is only possible with very strong security systems in place to secure the vehicles from a cyber attack.
# Unifying Aspects of Generalized Calculus
## Appendix C Proof of Lemma 2  
\(g(p_{1})+\cdots+g(p_{n})=1\) must hold for any choice of probabilities. Setting \(p_{1}=p\), \(p_{2}=1-p\), we find  
\[g(p)+g(1-p)+(n-2)g(0)=1, \tag{108}\]  
If \(g(0)=0\) then, by Lemma 1, \(g(p)=1/2+h(p-1/2)\), with antisymmetric \(h\). Returning to arbitrary \(p_{k}\), we get  
\[1=\frac{n}{2}+\sum_{k=1}^{n-1}h\left(p_{k}-\frac{1}{2}\right)+h\left(1-\sum_{ k=1}^{n-1}p_{k}-\frac{1}{2}\right). \tag{109}\]  
By antisymmetry of \(h\),  
\[1-\frac{n}{2}-\sum_{k=2}^{n-1}h\left(p_{k}-\frac{1}{2}\right)=h\left(p_{1}- \frac{1}{2}\right)-h\left(p_{1}-\frac{1}{2}+\sum_{k=2}^{n-1}p_{k}\right), \tag{110}\]which implies that the right-hand side of (A12) is independent of \(p_{1}\) for any choice of \(p_{2},\ldots,p_{n-1}\). In other words, the difference \(h(x)-h(x+p)\) is independent of \(x\) for any \(0\leq p\leq 1/2-x\), so \(h(x)=ax\). \(g(0)=0\) implies \(h(1/2)=1/2\), \(a=1\), and \(g(p)=p\) for any \(p\).  
Now let \(g(0)>0\). Normalization  
\[g(1)+(n-1)g(0)=1\] (A13)  
combined with (A10), imply  
\[g(p)+g(1-p)=g(0)+g(1)>0.\] (A14)  
Accordingly, \(G(p)=g(p)/(g(0)+g(1))\) satisfies \(G(p)+G(1-p)=1\), so that  
\[G(p)=\frac{1}{2}+H\left(p-\frac{1}{2}\right),\] (A15)  
where \(H(-x)=-H(x)\). Returning to  
\[g(p)=\left(g(0)+g(1)\right)\left[\frac{1}{2}+H\left(p-\frac{1}{2}\right) \right],\] (A16)  
we find  
\[\frac{1}{g(0)+g(1)} = \frac{n}{2}+\sum_{k=1}^{n-1}H\left(p_{k}-\frac{1}{2}\right)+H \left(1-\sum_{k=1}^{n-1}p_{k}-\frac{1}{2}\right).\] (A17)  
and \(H(x)=ax\) by the same argument as before. Now,  
\[g(p)=\left(g(0)+g(1)\right)\frac{1-a+2 ap}{2}\] (A18)  
Summing over all the probabilities,  
\[1=\sum_{k=1}^{n}g(p_{k})=\left(g(0)+g(1)\right)\frac{n-an+2a}{2},\] (A19)  
we get  
\[g(p) = \frac{1-a+2 ap}{n+(2-n)a},\] (A20) \[g(0) = \frac{1-a}{n+(2-n)a},\] (A21) \[g(1) = \frac{1+a}{n+(2-n)a}.\] (A22)  
For \(a=1\) we reconstruct the case \(g(0)=0\), \(g(p)=p\). \(g(0)>0\) and \(g(1)\geq 0\) imply either  
\[1-a>0,\quad 1+a\geq 0,\quad n+(2-n)a>0,\] (A23)  
or  
\[1-a<0,\quad 1+a\leq 0,\quad n+(2-n)a<0,\] (A24)  
but (A24) is inconsistent. The first two inequalities of (A23) imply \(-1\leq a<1\), but then \(n+(2-n)a>0\) is fulfilled automatically for \(n\geq 3\). Non-negativity of \(g(p)\) requires \(0\leq 1-a+2 ap\) for all \(0\leq p\leq 1\). For positive \(a\) the affine function \(p\mapsto 1-a+2 ap\) is minimal at \(p=0\)implying \(0<a\leq 1\). For negative \(a\) the map \(p\mapsto 1-a+2 ap\) is minimal at \(p=1\), so \(-1\leq a<0\). Finally, \(-1\leq a\leq 1\) covers all the cases. The case \(a=0\) implies \(g(p_{k})=1/n\), which is possible, but uninteresting for non-Newtonian applications as such a \(g\) is not one-to-one.
# An Improved Aeromagnetic Compensation Method Robust to Geomagnetic Gradient
## 4 Field Experiments and Data Analysis
### Data Evaluation Methods  
The key data evaluation methods are the standard deviations of compensated and uncompensated signals and the improvement ratio (IR) derived from them. The IR can be expressed as follows [32]:  
\[IR=\frac{\sigma_{u}}{\sigma_{c}}, \tag{18}\]  
where \(\sigma_{u}\) and \(\sigma_{c}\) are, respectively, the standard deviation of the uncompensated and compensated signals. The larger the IR, the better the compensation result.
## 2 Materials and Methods  
### Photoelectrochemical System  
The photoelectrochemical system consisted of a batch-type reactor, where homogeneous photocatalysis in the advanced oxidation process (AOP) was applied for dye degradation. To assemble it, a 500 mL glass beaker was used, its exterior coated with aluminum foil to enhance ultraviolet light absorption. Within the beaker, a 250 mL glass Erlenmeyer flask housed three generic UV LED bulbs with a total power of 9 W, providing a UV light intensity of 810 \(\mu\)W \(\times\) cm\({}^{-2}\) and a maximum peak wavelength of 365 nm. Two titanium (Ti) electrodes, in sheet form with a geometric area of 48 cm\({}^{2}\) and an electroactive area of 28.6 cm\({}^{2}\), served as the anode and cathode. These electrodes were electrically polarized using a galvanostatic technique with a BK Precision model 1670A (BK, Mandeville, LA, USA) power source. Subsequent experiments involved UV light exposure, activating the photocatalytic reaction and leading to the in situ production of titanium dioxide (TiO\({}_{2}\)). Control experiments without UV light exposure were conducted to assess the photocatalyst's effects in the absence of photoactivation. Rigorous safety measures were adhered to, and comprehensive data, including UV light intensity, current density, and reaction kinetics, were collected to evaluate the system's efficiency in dye degradation. The design showcased the system's potential as an environmentally friendly and cost-effective solution for treating wastewater with dye contaminants.
# Failure Mechanism and Structural Analysis of Chain Slings with Non-Standard Connections
## 3 Failure Cause Analysis
### Dimensional Measurement and Analysis of Chain Slings  
Table 1 and Figure 6 present the specifications and dimensional data of the chain used in the incident. The chain corresponds to the standard specified in KS B 6243 [32], with a nominal diameter of 7.1 mm. In addition, Table 2 and Figure 7 summarize the actual measurement results of the two failed chains. For each chain, the diameter (d), pitch (p), inner width (a), and outer width (b) were measured three times. The diameter (d) was measured at the interlocking section between adjacent links, and the three most degraded (i.e., most worn or deformed) locations were selected and recorded.  
Figure 4: Indentation around the fracture surface.  
Figure 5: Deformation and damage of the chain.  
of the failed chains analyzed in this study, it is presumed that prolonged use resulted in continuous friction at the interlocking sections of the chain links, leading to a decrease in diameter due to wear and an increase in pitch. This pattern of deformation corresponds to a typical failure mode in which the chain elongates under repeated tensile loading while the diameter progressively decreases.  
According to the Occupational Safety and Health Act and the KS B 2818 standard [33; 34], chains must be discarded if the diameter (d) is reduced by more than 10% from the nominal value, or if the pitch (p) increases by more than 5%. Therefore, it is essential to thoroughly inspect the condition of the chain prior to use. Any chain exhibiting signs of deformation or damage must be immediately removed from service. Such preventive measures are critical for avoiding serious accidents caused by sudden chain failure.
## 2 Principle and Design Analysis of Novel SSPP and SIW with Wide Passband Characteristics
### The Hybrid Siw-SSPP  
With the slot structure fixed and the period set to 2.88 mm, the cutoff frequency of the SSPP is 29.5 GHz. Under these conditions, the combination of SIW and SSPP structures enables convenient implementation of a bandpass filter. The SSPP integrates with the SIW to obtain a wide bandpass structure. Figure 3 demonstrates the hybrid SIW-SSPP unit's structure and dispersion properties. Figure 3a shows the schematic unit structure of SIW-SSPP units. Figure 3b shows the dispersion properties of SIW-SSPP units under the optimal geometric conditions, where \(W_{sisn}=4.5\) mm, \(a_{1}=0.5\) mm, \(b_{1}=1\) mm, and \(g_{1}=0.1\) mm, obtained from the SIW-SSPP dispersion calculation results given in Figures 1 and 2; thus, this structure exhibits both an upper cutoff frequency and a lower cutoff frequency, forming a bandpass response ranging from 24.25 GHz to 29.5 GHz, which complies with the requirements of n257, n258, and n261.  
Figure 3: Structural and dispersion characteristics of the SIW-SSPP unit cell: **(a)** schematic of the unit structure; **(b)** dispersion diagram.
## 4 Case Study and Results Discussion
### Analysis 1: Covariate Weight Sensitivity Analysis
#### 4.2.1 Reliability Metrics
It suggested that all transformers should be replaced at around the 5000 h mark, resulting in a very aggressive policy. Similar outcomes were observed in case M5, where the policy suggested replacing all equipment after just 2000 h of use. Case M3 performed the worst, recommending immediate replacement as soon as the equipment was put into operation. While most configurations failed to generate satisfactory policies, case M4 produced a feasible policy, proposing equipment intervention at the 22,000 h mark, which suggested that transformer 13 was nearing the point of needing intervention. Although case M4 did not perfectly match the reference case, it demonstrated that the IPOPT, NS, and IPCRidge configuration yielded the closest results. This showed the framework's capability to produce feasible policies when the correct optimization parameters were applied. Figure 5: RUL results for each case.
## 3 Research Methodology
### Evaluation and Validation  
Multi-Class Confusion Matrix  
The confusion matrix allows the visualization of the performance of an algorithm. The evaluation of this model presents two variants: quantitative and qualitative. The first is estimated by calculating the precision of the frequency at which a document is correctly categorized. Three data classes were considered in this study: positive, negative, and neutral. The accuracy is represented by the number of correctly classified data instances divided by the total number of instances. This metric is not very reliable when there is a high skew in the classes; therefore, we also strengthened it with precision, recall, and F--measure [87]. Precision is the percentage of documents correctly classified and recall represents the percentage of papers categorized by the classifier. By contrast, the F-measure harmonically balances both precision and recall [88]:  
\[\text{Accuracy}=\frac{\text{TP}+\text{TN}}{\text{TP}+\text{FP}+\text{FN}+ \text{TN}} \tag{1}\]  
\[\text{Precision}=\frac{\text{TP}}{\text{TP}+\text{FP}} \tag{2}\]\[\text{Recall}=\frac{\text{TP}}{\text{TP}+\text{FN}} \tag{3}\] \[\text{F}-\text{measure}=\frac{2*\text{Precision}*\text{Recall}}{ \text{Precision}+\text{Recall}} \tag{4}\]  
where true positives (TP) are correctly classified, true negatives (TN) refer to the number of instances where the classifier accurately predicts the negative class as unfavorable, false positives (FP) are the number of predictions where the classifier incorrectly predicts the negative class as positive, and false negatives (FN) are the number of instances where the classifier incorrectly predicts the positive type as negative.  
Finally, during the qualitative stage of the research, a group of experts manually labeled the comments to validate the polarity. This strategy allowed for the incorporation of valuable knowledge from experts, capitalizing on more robust and reliable work.