esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Performance Evaluation  
### Simulation Environment  
For performance evaluation, we use MATLAB software which is similar to C language where the code is executed line by line. As is shown in Table 4, there are 300 sensor nodes randomly deployed in a 300 \(\times\) 300 m\({}^{2}\) area WSN with BS placed in the middle of the area. The maximal transmission radius is 150 meters. Each node takes turn to transmit a 2,000 bits message to BS using either direct transmission or multi-hop transmission based on different routing algorithms. We compare our DEAR algorithm with the following three popular routing algorithms which are direct transmission, greedy and maximal residual energy (MRE) algorithms.
# A Novel Feature Selection Based on VMD and Information Gain for Pipe Blockages
## 2 Materials and Methods
### Sound Pressure Level Conversion  
The conversion of sound pressure level amplifies the content of acoustic signals and enhances the distinction among various severities of blockages, thus that the characteristic information about different pipe conditions is more easily extractable in the subsequent decomposition [34]. The computational formula for the sound pressure level is as follows:  
\[L_{p}=20\lg\frac{p_{e}}{p_{0}} \tag{4}\]  
where \(p_{e}\) denotes the effective sound pressure value of the original acoustic signal and \(p_{0}\) denotes the effective value of reference sound pressure, whose value is assigned as \(2\times 10^{-5}\) Pa herein.
## 2 Background and Related Technologies
### Ng-IoT  
Narrowband Internet of Things (NB-IoT) is a core component of LPWAN technologies, effectively leveraging existing cellular network infrastructure to provide low power consumption, long-range communication, and massive device connectivity, significantly contributing to the expansion of the IoT ecosystem. Standardized in 3 GPP Release 13, NB-IoT supports both extended transmission ranges and power efficiency, enabling reliable and efficient communication for large-scale IoT deployments. Large-scale field trials have demonstrated an average energy consumption of 0.25 mJ bit\({}^{-1}\), support for up to 50,000 devices per cell, and a mean latency of 1.5-10 s [16].  
NB-IoT employs sub-carriers to support both single-tone and multi-tone transmissions. Single-tone transmission utilizes a single sub-carrier to maximize power efficiency, making it suitable for low-rate data transfer and periodic sensing applications. In contrast, multi-tone transmission leverages multiple sub-carriers simultaneously, increasing data rates and making it ideal for applications requiring higher throughput.  
For uplink (UL) transmissions, multi-tone transmission uses QPSK modulation, while single-tone transmission employs either \(\pi\)/2-BPSK or \(\pi\)/4-QPSK modulation. On the downlink (DL), QPSK modulation is predominantly used to ensure signal robustness. These modulation techniques provide both energy efficiency and signal stability, ensuring reliable communication, even in interference-prone environments.  
Notably, NB-IoT offers the highest data transmission rates among LPWAN technologies, excluding LTE-M, making it suitable for IoT applications with higher data-rate demands.
## 2 Concrete Additives  
Admixtures are added to concrete to provide the desired properties in fresh and hardened concrete. Indeed, the utilization of additives in concrete mix design can help to enhance the concrete properties, such as compressive strength and durability, due to the reduction of water to cement ratio. Chemical admixtures such as superplasticizers (SPs) are the major additives added to the concrete mixture at around 2-3% of cement weight, whereas mineral admixtures are the powders that are added to concrete at 10-20% of cement weight or even more to ameliorate durability, strength, and workability in concrete.  
An acidic alkaline activator solution consists of an alkaline solution such as sodium hydroxide (NaOH) alone, or with a two combinative solution, including an alkaline hydroxide along with a silicate solution such as sodium silicate (Na\({}_{2}\)SiO\({}_{3}\)) or potassium silicate (K\({}_{2}\)SiO\({}_{3}\)) with specific mole and weight ratios. Studies indicate that the alkaline hydroxide type of MOH (where M is alkaline cation), and its concentration (molarity), as well as the ratios of two combinative solutions including weight ratio of M\({}_{2}\)SiO\({}_{3}\)/MOH or mole ratio of SiO\({}_{2}\)/M\({}_{2}\)O, have notable effects on chemical and mechanical properties and the durability of geo-polymer concrete [9; 10]. The changes in the properties of GPC are not only attributed to the activator solution, but to the reactive amounts of Si and Al in the powder along with the number of water molecules and total mole ratios, such as H\({}_{2}\)O/M\({}_{2}\)O, M\({}_{2}\)O/SiO\({}_{2}\), and SiO\({}_{2}\)/Al\({}_{2}\)O\({}_{3}\). These ratios have a conclusive effect on the formation of M-A-S-H polymer gel, where A is aluminum oxide, S is silica oxide and H is H\({}_{2}\)O. As a result, a geopolymeric combination can be expressed with the formula (nM\({}_{2}\)O.Al\({}_{2}\)O\({}_{3}\).xSiO\({}_{2}\).yH\({}_{2}\)O) [11; 12; 13].  
As discussed briefly, in modern concrete technology a wide variety of mineral and chemical admixtures and chemical activators can be used extensively in the production of concrete, especially GPC concrete. The most significant goals in this regard are:* Optimal economic use of this type of concrete in the construction industry
* Preserving the environment
* Workability improvement in fresh concrete
* Increasing compressive strength and durability of hardened concrete
* Reducing hydration temperature in concrete
## 2 Materials and Methods
### Coverage Path Planning
#### 2.3.1 Coding  
Using the genetic algorithm to solve the problem, the possible solutions to the problem need to be encoded first. Traditional optimization problems mostly use binary coding, but the chromosomes in a point planning problem are composed of subregions of interest (sampling points), so coding based on the sampling point number is sufficient and more in line with the reality of the problem. For example, a detection task has a total of seven sampling points, which can be represented by the sampling point set \(P=\{p_{i}|i=1,2,\cdots\}\), then a possible solution (chromosome) of the waypoint planning problem is \(p_{2}-p_{4}-p_{1}-p_{6}-p_{7}-p_{3}-p_{5}\), where each code (gene) represents a sampling point.
# Mobile Autonomous Sensing Unit (MASU): A Framework That Supports Distributed Pervasive Data Sensing
## 5 MASU Empirical Evaluation
### Role Selection and Activation Methods  
The implementation of the Role Selection and Activation processes was done according to the following procedure:  
* The Manager is fixed for the duration of the collaborative sensing activity and it is responsible of selecting and activating roles in the Sensing Tier (i.e., Consumer, Producer and Storage), sending messages to other units accordingly.
* When a new node accesses the network, it announces its state, capabilities and the sensing services that can provide. As a result, the Manager knows which sensors are available in the network and therefore which units are suitable candidates to play Producer roles.
* In case that various units meet the requirements to play a particular Producer role, the Manager takes the decision considering the quality of the sensor and the battery level of the device. Thus, the units that have sensors with the highest quality and the highest battery level, will be selected as Producers.
* After a specific Producer role is selected and activated, the Manager automatically activates Consumers of the information sensed by that Producer in all the units connected to the network.
* Consumers can receive information from Producers (i) periodically or (ii) only when the information changes, receiving a notification as well as the new data when it is available.  
Figure 13: Average number of messages for different network infrastructures.  
* Every time a new node joins the network, the Manager starts the Role Selection and Activation process in the Sensing Tier, activating a Consumer role in the new node.
* The Manager selects and activates a unit to act as Storage of the data collected by a specific Producer. This unit stores all the information sent by such a Producer in a SQLite database.
* Consumers receive data from the Storage periodically, according to the data rate specified by the Consumers in the data request.
## 4 Fuzzy Fatigue Reliability Assessment of Welded A-Type Frame
### Assessment of Fuzzy Fatigue Reliability  
Before the estimation of fuzzy fatigue reliability of welded A-type frame started, randomness of Young Modulus \(E\), thickness of roof plate \(t_{2}\), and vertical force at front traction joint \(F_{1}\) are shown in Figure 19 by one million times sampling. The random sampling results showed that they all appeared with normal distribution. Finally, according to Equations (10)-(14), the fuzzy fatigue reliability of welded A-type frame under conditions of downhill and turning braking with full load was acquired by programming in MATLAB software. Afterwards, it was found that the fuzzy fatigue reliability was only 69.47% under this severe case, which was far less than the engineering requirement. Therefore, the optimal design for improving the fuzzy fatigue reliability was needed.  
Figure 19: Distribution of the variables: (**a**) elastic Young modulus; (**b**) thickness of roof plate; and, (**c**) vertical force at front traction joint.
# Sparse Low-Rank Based Signal Analysis Method for Bearing Fault Feature Extraction
###### Abstract
In addition, to further facilitate the sparsity of the solution, non-convex penalty functions (NPFs) are introduced into the sparse model [28; 31; 32]. The above analysis shows that a sparse-assisted algorithm is successfully applied in bearing structural damage detection. However, the sparse model-based algorithm needs to be further studied in processing signals with complex components and weak fault features. The sparse low-rank model-based method has made remarkable achievements in many fields, such as graph denoising [33], subspace clustering [34], image classification [35] and so on. In addition, the sparse low-rank model-based algorithm can extract fault features more effectively since it can take into account the low rank characteristic and sparsity of the bearing fault features simultaneously [36]. Therefore, the sparse low-rank model-based signal processing method has shown great potential for the fault detection of REBs. However, so far the research on applying the sparse low-rank model to bearing defect detection is in the preliminary stage. It is found that the extraction of fault features via directly applying the traditional sparse low-rank model without considering the characteristics of bearing vibration signal is susceptible to interference from harmonic components (HCs). In this work, to effectively extract the periodical fault transients even when HCs present in the noisy signal, a fault information-based sparse low-rank algorithm (FISLRA) is proposed. Concretely, a sparse and low-rank model is formulated in the time-frequency domain. Then, a fast converging algorithm is derived based on the alternating direction method of multipliers (ADMM) to solve the formulated model. Moreover, to further highlight the periodical transients, the correlated kurtosis-based thresholding (CKT) scheme proposed in this paper is also incorporated to solve the proposed low-rank spare model, and a parameter selection scheme is presented in detail. The performance of FISLRA is validated by simulated and real vibration signals while being compared with other state-of-the-art methods. The results indicate that FISLRA can accurately extract the fault transients from noisy signals and achieve better performance than other comparison methods. The main contributions of the paper are described as follows:  
1. A fault information-based sparse low-rank algorithm (FISLRA) is proposed and applied for fault feature extraction of rolling bearing. 2. A correlated kurtosis-based thresholding (CKT) scheme is proposed and it is incorporated to solve the proposed low-rank spare model. The remaining parts of this paper are organized as follows: Section 2 introduces the prior knowledge of sparsity and low-rank characteristic. Section 3 introduces the proposed FISLRA. In Section 4, the simulation analysis is implemented for the verification of the proposed FISLRA. In Section 5, experimental analysis is performed. The conclusion is summarized in Section 6.
## 5 Field Application and Monitoring Analysis  
The SRGB support structure belongs to a new type of technology and new process. In order to further clarify the adaptability and feasibility of this support structure in the subway tunnels in bustling urban areas, and to grasp the supporting working status, the field application test of the spatial reticulated grid was carried out. It highlights the performance advantages of the spatial reticulated grid, and provides a safety guarantee for the mechanized and rapid construction of urban underground space engineering.
## 1 Introduction
However, despite their ability to achieve high voltage gain ratios, these converters exhibit drawbacks that affect their performance and limit their usefulness, including the need for high duty ratios, increased losses, reduced efficiency at high voltage gain, and a negative impact on component durability [32]. This paper introduces a high-efficiency DC-DC converter utilizing the MHSLCS interleaved with an MSC and MHSLCP. The primary goal of this design is to validate exceptionally high voltage gain in photovoltaic applications. To achieve this objective, the proposed converter incorporates an MHSLCS with an MSC interleaved with the main switch, effectively doubling the voltage transfer gain. Additionally, the MHSLCP, serving as interleaved components, is integrated in parallel into the converter design with an auxiliary switch. This design not only optimizes voltage transfer gain but also ensures low voltage stress across the auxiliary switch by combining the main switch and auxiliary switch with the MSC. Furthermore, each pair of inductors is connected in series, with both having the same voltage and current, aiming to reduce the number of passive elements and enhance the overall performance of the proposed converter. In addition, the series-parallel inductors have very low voltage across them when the converter supplies 500 V output voltage. In addition, the inductors of the MHSLCP operate in DCM, which leads to significant stress reduction in power diodes and switches at high output voltage. In addition, the proposed converter operates at high efficiency when the inductors of the MHSLCP operate in DCM. This means that the voltage stress across power switches and diodes is significantly reduced when the proposed converter operates at high power applications. In addition, the inclusion of only one input capacitor serves to eliminate pulsations in input current at both low and high duty ratios. Additionally, a dual PI controller is designed as the control strategy for the proposed converter. This controller is designed to validate constant output voltage while accommodating variable input voltage, contributing to the robust performance of the system.
# Applicability Evaluation of Soil Algae Pipe Assay in Silver Nanoparticle-Contaminated Soils
## 1 Introduction  
To evaluate the impact of pollutants in the soil environment, it is important to recognize the significance of an integrated approach with real bioavailability via bioassay, as well as measured pollutants via chemical analysis [1]. Under international standard test guidelines for soil ecotoxicity assessments, limited soil toxicity test species were recommended, namely, plants, earthworms, and springtails [2]. For the better probabilistic ecological risk assessments based on species sensitivity distributions, the development of test species in a new taxonomic group is required, and algae could be a potential candidate for soil tests. Soil algae, spread on and beneath the soil, are primary microflora and a valuable food source for mesofauna and microfauna [3, 4]. Currently, various test methods in soil ecotoxicity have been developed using algae via whole soil [5, 6, 7, 3] or soil with intermediate carriers [8, 9, 10, 11]. Using these methods, the evaluation, growth, photosynthesis, morphology, or physiology of green algae (e.g., _Chlamydomonas_, _Chlorella_, _Chlorococcus_, _Klebsormidium_, and _Prasiola_) have been quantified. In particular, [PERSON] et al. [7] and [PERSON] et al. [11] developed an algae-soaked disc seeding assay as an indirect bioindicator and a soil algae pipe assay as a direct bioindicator under a non-sterile open system (field and greenhouse experiments, respectively). In a previous study [11], we presented a decrease in in vivo chlorophyll \(a\) fluorescence for green alga _Chlamydomonas reinhardtii_ after exposure to heavy metal-contaminated soils by a soil algae pipe assay. The results of that study identified that a soil algae pipe assay was effective for direct soil quality assessments in a pot test. However, [PERSON] et al. [11] only assessed the chlorophyll content of _C. reinhardtii_ in homogenous soils collected from the field after 7 days. In this study, we extended our experimentto evaluate its applicability in the following two cases: (1) when applied to an extended exposure duration under the open system; (2) when applied to a heterogeneously contaminated soil, along with the examination of cell granularity, cell size, and lipid contents using flow cytometry after a soil algae pipe assay. Silver nanoparticles (AgNPs) were studied as the test chemical due to their extensive use in practical life [12; 13] and their adverse effects on plants [14; 15; 16], arthropods [17; 18], oligochaete earthworms [19], soil algae [20], and exoenzymes [21]. _C. reinhardtii_ is widely dispersed in freshwater and soil and has been used as a soil test species in previous studies [7; 11; 22]. To the best of our knowledge, this is the first study that evaluates the applicability of a soil algae pipe assay considering long-term exposure duration and heterogeneously contaminated soil under open system, as part of an efficient soil algae pipe assay.
## 2 Experimental Setup  
Figure 1a shows an experimental setup for multiwavelength digital holography with an exemplary gear tooth. However, the algorithm introduced in this paper is not limited to this setup, but is applicable to holographic setups in general. A detailed description of our optical setup has been introduced by the authors of [38].  
Figure 1: Experimental setup for temporal phase-shifting multiwavelength digital holography: (**a**) sensor internals including laser system (1); lens (2); polarizing beam splitter cubes (3)/(7); piezo (4); camera (8); gear test object (5); and imaging lens (6). The interferometric optical path includes reference and object beams, which are superimposed on the imaging device. Lenses (2) and (6) ensure maximal light yield; (**b**) data acquisition time series using three lasers and three piezo steps for temporal phase shifting. In total, nine camera images are acquired.  
Three separate grating-stabilized diode lasers (632.9443 nm, 636.2661 nm, and 635.8239 nm) are used. The typical linewidth of the individual laser is specified to be between 0.5 and 1 MHz. With two wavelengths, \(\lambda_{j}\) and \(\lambda_{k}\), the artificial wavelengths \(\lambda_{a}\), as follows,  
\[\lambda_{a}\ =\ \frac{\lambda_{j}\cdot\lambda_{k}}{\left|\lambda_{j}-\lambda_{k} \right|}\ =\ \frac{\lambda_{j}\cdot\lambda_{k}}{\left|\Delta\lambda\right|} \tag{1}\]  
can be calculated to 915 um, 140 um, and 121 um. The different lasers are connected through a fiber switch to the interferometer. Only one wavelength is present in the sensor at a time. To ensure a common source point, single-mode fibers are used to connect the lasers (1) to the sensor. The beam is split into reference and object beam by a polarizing beam splitter cube (3). By rotating the angle of the polarizing-maintaining fiber, the ratio between the beams can be adjusted. Later, the orthogonally polarized beams are combined without losses by the second polarizing beam splitter cube. For the reference beam path, an achromatic lens (2) converts the beam to a convergent beam with an interim focus on the piezo (4). Having passed a polarizing beam splitter cube (7), the beam is deflected onto the camera (8). For temporal phase shifting, the piezo introduces a minimum of three phase steps \(n\) by an angle of approximately \(2\pi/n\), respectively. The piezo runs in an open-loop mode and the exact phase-steps are calculated subsequently (Section 3) [1; 39]. Passing a polarizing beam splitter cube (3), the object beam is reflected by the sample (5), and focused onto the camera by an imaging lens (6) as an interference pattern.  
Figure 1b shows the measurement data acquisition time series for our three laser setup at three phase steps \(n\). With this configuration, the data acquisition for one measurement takes 60 ms and includes nine raw images.
## 5 Conclusions  
In this study, we established a procedure for fatigue damage evaluation by considering the springing response of a large container ship based on a widely used linear statistical analysis method using 1D beam and 3D global models. The purpose of our study was to apply the established procedure to a real ship to perform fatigue strength evaluation and to analyze the fatigue damage calculated from the rigid and flexible body theories. Based on the study results described so far, the following conclusions are derived.  
* The fatigue damage of the upper deck hatch corner where the internal and external loads do not act can be estimated using only the hull girder loads (VBM, HBM, TM) calculated from the 1D beam model.
* In particular, the location of the hot spot where the fatigue damage is the greatest in a very large container ship has almost the same stress transfer function calculated from the 1D beam and the 3D global model.
* When estimating the fatigue damage by considering the linear springing component, the fatigue damage is increased by 30-100% compared to the rigid body response-based value used in the design stage, and these are caused by the response increase at low frequencies due to waves, as well as by high-frequency responses, such as the springing response.
* In the case of calculating only hull girder loads based on the hydroelastic model at the actual design stage, the fatigue damage at hot spot locations can be estimated using the proposed method.  
The fatigue damage results calculated from each application method were analyzed, and their applicability and efficiency were examined at the design stage of the actual ship. Finally, because of the nature of container ships with large nonlinearities, we believe that a study considering the nonlinear components as mentioned in the Introduction is necessary.  
Figure 16: Fatigue damage at weak points.  
**Author Contributions:** S.-I.L. conceptualized and supervised; S.-H.B. analyzed and validated; B.-I.K. wrote the manuscript and analyzed. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was a part of the project titled, \"Development of safety standards for hydrogen fueled ships bunkering and loading/unloading of Hydrogen Carriers (Project NO. 20200478).\" funded by the Ministry of Oceans and Fisheries, Korea.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.