esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion  
### Anticipated Advantages for Practical Applications  
This proof-of-concept study investigated an innovative delivery method of enzymes for biocmentation via EICP. The method was applied to a fine-grained soil. For this type of soil, MICP can be a challenge due to the pore throat size compared to bacteria size, and for this reason, EICP was suggested instead. Notably, EICP could also use ex situ produced enzyme by the action of bacteria. However, the main challenge of using free enzymes is the cost of the purified enzyme [67] and its stability in high temperatures and extreme pH conditions [68, 69]. The study was conducted to address the stability of the enzyme during EICP treatment using a cheap and easy-to-control protocol. The results were encouraging, as the hybrid carrier enabled the enzyme to maintain 94% of its activity over the study period. This is very promising, as the desired advantage of the proposed delivery method is precisely the long-term stability of the synthesized nanoflowers [25, 40, 70]. The long-term stability of synthesized nanoflowers can be further investigated at bench scale and field conditions in future research. Such studies can then be used for educated estimates of the cost of the technique in an industrial scale environment, and its overall sustainability in comparison with other soil stabilization methods currently used.  
Another advantage is the possibility of recovering and reusing the nanoflower. Reuse and recovery contribute to the sustainability of materials used and the circular economy [71, 72]. Therefore, practical ways of recovering the nanoflowers in situ merit further investigation. Moreover, researchers can explore the cost comparison between the suggested and traditional EICP/MICP treatment methods for field applications after establishing ways of nanoflower recovery. As mentioned in the Introduction, for the planned future research by the authors, the recovery of the carriers through an electrokinetic setup will be considered.  
Due to their versatility and other advantages discussed in the Introduction, nanoflowers have been used in various biomedical and environmental science applications such as to capture and store or convert and utilize CO\({}_{2}\), to diagnose disease biomarkers, biosensors, catalysts, and the therapeutic process along with wastewater remediation and gas sensing [22]. The results from our study proved the hybrid carriers for biocmentation for the first time. They indicated that they could play a significant role in enhancing the stability and efficiency of enzymes used for biocmentation. The proposed methodology in this study could be thus used for a number of civil and environmental engineering applications of biocmentation, such as manufacturing biobricks, enhancing the stability of earthworks and foundation soils, preventing erosion, suppressing dust contamination, or encapsulating and stabilizing pollutants in the soil. Finally, the synthesis of hybrid carriers for other enzymes such as urease [73] or asparaginease [74], which can promote biocmentation, could be investigated in future studies.
## 2 Related Works
Moreover, we assumed transmitting raw sensor data, which would require a severe data rate to clarify whether the conventional and the millimeter-wave communications can support it or not. The second is about clarifying the relation between the safety and performance of wireless communication. In [13], transmitting raw LiDAR sensor data and sharing processed data between vehicles and a mobile edge computing unit were realized by LTE-V2X. Although the authors concluded that there were no negative influences on the automated driving, the driving scenario did not include oncoming vehicles, so that a discussion about safe automated driving was not enough. We also worked with clarifying the relation as follows. In [14], the minimum data rate to overtake was derived, and cooperative perception using millimeter-wave V2V communications contributed to improving safe overtaking. However, the recognition method did not consider the density of lasers from a LiDAR sensor, so that a vehicle would recognize an object even if many lasers were emitted on a very small area of the object. In [15], the minimum data rate required for safe overtaking was derived. However, safe overtaking was discussed only for comfortable braking. In [16], a proof-of-concept of cooperative perception using millimeter-wave communications was performed. It was shown that millimeter-wave communications have the ability of sharing raw sensor data. Although a real-time LiDAR sensor sharing and visualizing blind spots were shown, safety was not analyzed. In this paper, we adopted edge points as feature points, and the recognition process considered the density of feature points on the visible area. Namely, in order to recognize an object, feature points had to be obtained on the whole area. We also considered the more realistic vehicle movement of overtaking.
# New and Efficient Algorithms for Producing Frequent Itemsets with the Map-Reduce Framework
## 4 Incremental Frequent Itemset Mining with Map-Reduce
### Experimental Evaluation  
#### 4.3.1 Data  
The first tested dataset is synthetically generated T20I10D100000K (will be referenced as T20) [37]. It contains almost 100,000,000 (D100000K) transactions of an average length of 20 (T20), and an average length of maximal potential itemset of 10 (I10). It is 13.7 GB in size. The second dataset is \"WebDocs\" [35; 36] (similar to Section 3.3.1).  
The datasets were each cut into two equal halves. The first half of each dataset was used as the baseline of 100% size (\(\mathcal{D}\)). The other part was used to generate the different \(\Delta\). For example, WebDocs was cut to a file size of 740 MB. Its delta of 5% was cut from the part that was left out, and its size was then 37 MB. The running time of the incremental algorithms on the 5% delta was compared to the full process of the 777 MB file (merged the 740 MB base file and the 5% delta of 37 MB as a single file for the test). Similarly, the T20 baseline of 100% has a size of 6.7 GB with 10% increments of 700 MB. We used different _minSup_ values for each dataset. For T20, we tested _minSup_ 0.1% and 0.2%. WebDocs was tested with 15%, 20%, 25%, 30% (although we show graphs only of 15% and 20%).
# Network Diffusion Algorithms and Simulators in IoT and Space IoT: A Systematic Review
## 4 Analysis
### Analysis of Research Question 3 and 5: Network Diffusion Algorithms and Performance Evaluation
#### 4.2.3 Cascading Models  
Cascading models, like the Independent Cascade (IC) model, describe the spread of information in a step-by-step process where activated nodes attempt to influence their neighbors. This method is particularly relevant to IoT networks that require hierarchical or multi-hop communication between devices.  
Strengths:  
* Detailed Propagation: The IC model captures the sequential nature of diffusion and can track the influence of individual nodes, like routers or gateways.  
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Category** & **Abbreviation** & **Full Name** & **Category** & **Abbreviation** & **Full Name** \\ \hline Dyn & & Not Applicable & Cat & EM & Epidemic Model \\ \hline Lay & SL & Single-Layer & Cat & TM & Threshold Model \\ \hline Lay & ML & Multi-Layer & Cat & Oth & Other \\ \hline Lay & Both & Both Single- and Multi-Layer & Cat & Many & Multiple Categories \\ \hline Lay & & Not Applicable & & & \\ \hline L & L & Loopy & & & \\ \hline Dir & Dir & Directed & & & \\ \hline Dir & Undir & Undirected & & & \\ \hline Dir & Both & Both Directed and Undirected & & & \\ \hline \hline \end{tabular}
\end{table}
Table 9: Abbreviation mapping table (part 2).  
Real-world Applicability: These models can represent the critical role of certain devices, such as smart hubs or gateways, that control the spread of data in IoT systems. Weaknesses:
* Computational Complexity: In large IoT configurations, the IC model becomes computationally intensive, particularly as the network scales.
* Fixed Activation Probability: The assumption of a constant activation probability can oversimplify dynamic IoT networks, where conditions vary in real time. Performance Metrics:
* Network Load: Cascading models tend to generate moderate traffic by selectively activating nodes, which helps reduce network load.
* Reachability: Cascading models often cover less ground compared to epidemic models but can efficiently propagate data in smaller IoT systems.  
Example: The IC model has been successfully applied in data diffusion studies where central nodes (e.g., routers) play a critical role. However, the fixed activation probabilities limit its performance in dynamic IoT environments.
## 7 Conclusions  
In this study, the dispersion curves of multi-mode Rayleigh surface wave were extracted from an ambient background noise signal, and through the dispersion curves the shear velocity structure of karst in the Wuhan area was inverted. The conclusions are as follows:1. Adding higher-mode dispersion information can improve the inversion fitting effect of the low-frequency band of the fundamental dispersion curve, and the joint inversion of the fundamental and higher-mode of the measured data improves the ability to identify the fine structure of the strata.
2. The shear wave velocity structure profile obtained from the inversion of background noise data in the limestone area of Wuhan depicts the range of the karst low-speed area, and the abnormal positions are in good agreement with the borehole data.
3. The thickness of the Quaternary overburden calculated by the frequency-Bessel algorithm is more accurate, and the undulation of the bottom interface of the Quaternary is closer to the real weathering state of the stratum.  
To sum up, the frequency-Bessel transform method provides a new idea and method for accurately detecting overburden thickness and karst in near-surface engineering, and we can try to utilize this method extensively whether in surface wave research or in solving practical geological problems.  
Conceptualization, S.C. and F.C.; methodology, S.C.; software, S.C.; validation, D.L.; formal analysis, S.C.; investigation, D.L.; resources, S.C.; data curation, S.C. and J.X.; writing--original draft preparation, S.C.; writing--review and editing, F.C.; visualization, S.C.; supervision, D.L.; project administration, S.C.; funding acquisition, D.L. and J.X. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Hubei Key Laboratory Foundation from the Hubei Key Laboratory of Paleontology and Geological Environment Evolution, Wuhan Center of China Geological Survey, grant number PEL202212; the National Key Research and Development Program of China, grant number 2020 YFC1512401; and the China Geological Survey Project, grant numbers DD20221729 and DD20221734.  
Not applicable.  
We greatly appreciate the comments and suggestions from two anonymous reviewers that significantly improved the quality of the manuscript. We are grateful to [PERSON] for sharing the synthetic data used in the synthetic analysis and [PERSON] for the discussion about the effect of extracting multi-mode dispersion from field data. We also thank [PERSON] for his help in drawing the geological map of Wuhan.  
The authors declare no conflict of interest.
# Time-Sensitive Networking Mechanism Aided by Multilevel Cyclic Queues in LEO Satellite Networks
## 1 Introduction
At the same time, delay-urgency priorities are precisely forwarded according to the delay-urgency level of the service. The delay-urgency status of the queues changes periodically, ensuring that time-sensitive traffic of different levels is provided with differentiated forwarding services. The results show that the proposed mechanism could improve the service capability and reduce packet loss. The main contributions of this paper are as follows:  
* An LEO satellite network management architecture for time-sensitive service is proposed, and a software-defined network-based (SDN-based) management mechanism is provided. * A time-sensitive networking technique aided by multilevel cyclic queues (TSN-MCQ) is studied. The traffic scheduling process of TSN-MCQ is investigated for LEO satellite networks. * We built a testbed for a 64-satellite constellation performing packet-level simulations by OMNET++. The result analysis for the proposed and existing TSN techniques is presented for comparison, which validated that the proposed algorithm could reduce the packet loss and time-out ratio. This paper is organized as follows. The related work is shown in Section 2. We introduce the LEO network architecture and management mechanism in Section 3. The TSN-MCQ mechanism is proposed in Section 4. Sections 5 and 6 present the evaluation results and conclusions, respectively.
## 4 Modeling and Implementing the Three-Level Framework of Heuristics and Simulation
### The Definition of Object-Oriented and Timed Predicate/Transition Net  
**Definition 5**.: _A Timed Pr/Tr net (TPr/Tr net) is defined as 8-tuple._  
\[\text{TPr/Tr net}=\left(P\text{,}T\text{,}A\text{,}\Sigma\text{,}L\text{,}L \text{,}L\text{,}M\text{,}F\text{,}F\right)\]  
_where_  
\begin{tabular}{l l} \(p\) & a set of predicates. \(P=P_{time}\cup P_{nontime}\), \(P_{i}\in P_{time}\) or \(\text{P}_{nontime}\). \(P_{time}\cap P_{nontime}=\varnothing\), \(P_{time}\) is the set of \\  & timed predicates while \(P_{nontime}\) is the set of predicates with zero time \\ \(T\) & a set of transitions (with logical formulas) \\ \(A\) & a set of arcs \\ \(\Sigma\) & a structure \(\Sigma\) consisting of some sort of individual tokens together with some operations (\(OP_{j}\)) and \\  & relations (\(R_{k}\)), i.e., \(\Sigma=(T_{1}\text{,}\ldots\text{,}T_{i}\text{;}\ OP_{1}\text{,}\ldots\text{,} OP_{j}\text{;}R_{1}\text{,}\ldots\text{,}R_{k})\) \\ \(L\) & a labeling of all arcs with a formal sum of a attributes of the token's variables (attributes), including \\  & zero-attributes that indicate a no-argument token \\ \(LF\) & a set of inscriptions on some transitions being logical formulas built from the operations and \\  & relations of the structure \(\Sigma\); Variables occurring free in a formula have to occur at an adjacent arc \\ \(M\) & a marking \(M\) of the predicates of \(P\) with formal sums of n-topples of individual tokens. \\  & firing rule of each element of \(T\) representing a class of possible changes of markings. Such a change, \\  & also called transition firing, consists of removing tokens from a subset of predicates and adding \\ \(F\) & them to other subsets of predicates according to the expressions labeling the arcs. A transition is \\  & enabled whenever a set of tokens associated with that transition are satisfied. \\ \(f\) & \(f(P_{i})\to T_{i}\); is a function mapping \(P_{i}\) to a handling time \(T_{i}\); \\  & \(T_{i}\) equals 0 _if_\(P_{i}\in P_{nontime}\); \(T_{i}\) is equal to or greater than 0 if \(P_{i}\in P_{time}\). \\ \end{tabular}  
**Definition 6**.: _An Object-Oriented Timed Pr/Tr net (OOTPr/Tr net) is defined as a 2-tuple:_  
\[\text{OOTPr}\text{/Tr net}=\left(O\text{,}R\right)\]  
_where_  
\(O\)_: is a set of finite subnet objects._  
\(R\)_: is a set of communication relations between_ \(O_{i}\)_._  
**Definition 7**.: _A subnet object is a TPr/Tr net with its structure defined in Definition 6._  
\[O_{i}=\left(P,T,A,\Sigma,L,F,f,M\right)\]Instead of focusing on what rules are to be executed, an Object-Oriented model pays more attention to the structure, sub-models, and the communications between subnets. In an OOTPr/Tr net, subnets establish communications through predicates. If \(P_{i}\cap P_{j}\
eq\varnothing\) (where \(P_{i}\in O_{i}\) and \(P_{j}\in O_{j}\)) then the two subnet objects \(O_{i}\) and \(O_{j}\) have communication. Formed by subnet objects, an OOTPr/Tr is more readable and maintainable than a traditional TPr/Tr net.
# Designing and Implementing Weather Generators as Web Services
## 2 Addressing Bottlenecks of Legacy Weather Generators for Service
### Addressing Issue on Standardization of Climatological Data and Weather Realization  
Many organizations have been working on monitoring and recording weather conditions and then providing those data on the Internet. For the convenience of users, some organizations operate climate data portals while serving data from other organizations. Each data source provides data in their own formats with different protocols. Weather realizations, which are generated from weather generators are in WTD or WTDE format. This growing number of data formats and protocols causes a problem for data exchange and application development. To enable information interoperability from observed and generated data by models, open standard web API can play an important role.  
Here, we worked on observed climate and model generated synthetic weather data. To ensure effective and interoperable access to data and services, outputs should be standardized.  
International Benchmark Sites Network for Agrotechnology Transfer (IBSNAT) project [17] developed ICASA standards. ICASA defined standard data formats for documenting experiments and modeling crop growth and development [16]. The ICASA standards are implemented in plain text in a hierarchical arrangement with major separations among descriptions of management practices or treatments, environmental conditions (soil and weather data), and measurements of crop responses. The goal of the ICASA standards is to provide a reliable and flexible structure for documenting experiment, detailed information is required on weather, soil, crop cultivars, weeds, diseases, pests, and crop management, along with measurements of crop growth and of dynamic soil characteristic.  
WTD file is one of ICASA standards, but it is not well-known in other application fields. Moreover, in WTD file, UOM is not shown which can lead to errors in the final result from using mismatched UOM. UOMs of these climate variables, known internally that UOM of SRAD, must be MJ per m\({}^{2}\)-day. UOM of TMAX and TMIN is degree Celsius and UOM of RAIN must be mm per day. These rules are not known in application fields except agriculture.  
Figure 3: Example of WTH, WTD and WTDE daily weather file, DATE format is YYYYDOY, (DOY is Day of year), SRAD = Solar exposure in MJ/m\({}^{2}\)-day, TMAX, TMIN are maximum and minimum temperature in Celsius, and RAIN is precipitation in mm.
## 4 PSI-CA Protocol Constructed Based on DH Key Exchange Mechanism
### Protocol Process
#### 4.1.2 Cardinality Calculation Stage  
1. **Receiver Decryption and Computation**: The receiver uses the inverse of \(\beta\) to decrypt \((H(y_{j})^{\beta})^{\alpha}\) to retrieve \(H(y_{j})^{\alpha}\). By comparing \(H(x_{i})^{\alpha}\) with \(H(y_{j})^{\alpha}\), the receiver can calculate the cardinality of the intersection between the two sets.  
Figure 1: PSI-CA protocol constructed based on DH key-exchange mechanism.
# DRL-Based Dynamic Destroy Approaches for Agile-Satellite Mission Planning
## 4 Experimental Simulation  
### Simulation Scenarios  
We obtained the original AEOS mission targets dataset from [35]. As shown in Table 2, the targets were generated over two geographical regions: Area and World. Area targets are defined by the area corresponding to \(3^{\circ}\)N-\(53^{\circ}\)N and \(74^{\circ}\)E-\(133^{\circ}\)E, and the World targets are located randomly in a region of \(65^{\circ}\)S-\(65^{\circ}\)N and \(180^{\circ}\)W-\(180^{\circ}\)E. Regarding the observed target data, there is currently no reliable publicly available real dataset. It is worth noting that the majority of the literature also uses simulated generated targets, often employing random generation. Maintaining generality, we have aligned the simulation scenarios with theirs [18; 19; 30; 31].  
The existing 1000 original point targets (Area: 400, World: 600) were sampled multiple times and divided into different scenarios of various sizes. A total of 50 to 200 Area tasks and 100 to 400 World tasks were sampled to simulate practical users' requests. We sampled randomly to generate 20 training scenarios and 10 test scenarios for each instance size.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Scenario** & **Region** & **Num of Points** & **Instance Sizes** & **Training Scenarios** & **Test Scenarios** \\ \hline Area & \(3^{\circ}\)N–\(53^{\circ}\)N, \(74^{\circ}\)E–\(133^{\circ}\)E & 400 & \(50,100,150,200\) & 20 & 10 \\ World & \(65^{\circ}\)S–\(65^{\circ}\)N, \(180^{\circ}\)W–\(180^{\circ}\)E & 600 & \(100,200,300,400\) & 20 & 10 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Simulation scenarios.
## 6 Conclusions  
As the need for high-speed internet increases substantially, the 5G system should have the ability to meet these requirements and provide aid for multi-fold improvement in channel capacity and network connectivity. This paper explains a comprehensive survey that carried on the basics of challenges involved in previous wireless networks, evolution, and implementation of 5G wireless network that has been described in terms of enhanced data, channel capacity, and spectral efficiency.  
To deliver ultra-fast data speed, SE improvement is vital in 5G networks that can be improved through D2D communications, mMIMO, by enhancing modulation order, and acquiring new effective transmission waveforms. To encounter substantial traffic growth, 5G wireless systems are expected to achieve higher channel capacity by utilizing mm-wave band, dense small cell deployment, beamforming and mMIMO technology. The critical review illustrates mMIMO technology is the solution to not only the increase in SE but also a motivation in relation to accomplishing higher orders of area throughput in 5G and B5G. However, it faces various critical challenges which need to be solved prior to the implementation of the next-generation wireless networks. Although the mMIMO is investigated as truly a key player amongst others due to its various features, still there are various secondary key emerging technologies such as FD, mmWave, UDense Net, and beamforming, their challenges and features with the focus on the enhancement of data rate, channel capacity, and SE. Moreover, this paper inspires researchers for the enhanced outcome of various problems, trends research gaps, and future directions in 5G and B5G networks.  
**Author Contributions:** Formal analysis, U.M.; Investigation, O.A.K.; Project administration, T.M.; Writing--original draft, A.S.; Writing--review and editing, K.B.K. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Data Availability Statement:** Data analyzed in this article was a re-analysis of existing data, which is openly available at locations cited in the reference section.  
**Acknowledgments:** The author is very grateful to all the co-authors for their contribution and support to this manuscript. The author would also like to thank the anonymous reviewers for their insightful suggestions that will help us to improve the quality of this paper. The author would like to grattite special thanks to [PERSON], [PERSON] and Engr. [PERSON] for their help during write-up.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# L-Band Erbium-Doped Fiber Optimization and Transmission Investigation +
## 1 Introduction
Furthermore, when applied in a few-mode transmission system, the L-band FM-EDFA supports each mode channel for 9.95 Gbps, NRZ signal transmission over the wavelength range of 1570 nm to 1610 nm, and has a bit error rate (BER) of below \(1\times 10^{-5}\). The rest of the paper is organized as follows: In Section 2, the fiber structure is optimized by the particle swarm optimization algorithm (PSO), and the gain characteristics are verified with experiments; in Section 3, the L-band FM-EDFA is applied in a transmission system to investigate the performance; in Section 4, we finally conclude this paper. The part regarding gain performance verification was published in a conference [17], while the remaining portions have been newly incorporated.