esa-sceva/satcom-chunk-collection huggingface dataset:
# A Cross-Level Iterative Subtraction Network for Camouflaged Object Detection
## 4 Experiments
### Ablation Studies
#### 4.5.1 Effectiveness of Cross-Level Integration Mechanism and Strip Convolutions in MSCSub  
On the one hand, we utilize features from adjacent levels as inputs to validate the effectiveness of our cross-level integration mechanism. On the other hand, we evaluate the effectiveness of strip convolutions in MSCSub by either removing all strip convolutions or replacing them with ordinary convolutions using kernel sizes of \(3\times 3\) and \(5\times 5\). The experimental results, as shown in Table 2 (#1-#5 and #OUR), indicate that our method achieves the best performance compared to the other experimental setups. We also conduct the visualization of feature maps generated by employing different convolution methods and integration strategies in MSCSub to demonstrate the superiority of our method more intuitively. In Figure 6, (a) shows the visualization of using convolution with \(3\times 3\) and \(5\times 5\) in MSCSub and feeding the adjacent level features as input, (b) shows the visualization of using convolution with \(1\times 3\), \(3\times 1\), \(1\times 5\), and \(5\times 1\) in MSCSub and feeding the adjacent level features as input, (c) shows the visualization of using convolution with \(3\times 3\) and \(5\times 5\) in MSCSub and feeding the highest-level features with their relevant lower-level features as input, respectively, and (d) shows the visualization of using convolution with \(1\times 3\), \(3\times 1\), \(1\times 5\), and \(5\times 1\) in MSCSub and feeding the highest-level features with their relevant lower-level features as input, respectively. As the results illustrate in Figure 6, in (a), the first feature map contains rich texture information but exhibits more background noise and the location of objects in the third feature map is a little thin. Similarly, (b) has issues similar to (a), but the edge texture information in the first feature map is more obvious than that in (a), and there is less background noise. This indicates that our strip convolutions can effectively capture richer local context information while reducing noise interference. However, we cannot see distinct texture information in the first feature map in (c). However, in the first feature map in (d), we can observe abundant edge texture information and less influence of background noise, and the third feature map has more plump object localization. Comparing (b) and (d), our cross-level integration mechanism focuses more on edge details, possesses stronger background noise suppression capabilities, and achieves more precise object localization. Based on the above, the cross-level integrative mechanism and multi-scale strip convolution subtraction effectively compensate for the differences in cross-level features and enrich the semantic context and edge details required for COD performance. This allows us to exploit the multi-scale characteristics of different features better.
## 3 Research Methodology and Components  
Figure 2 illustrates the research methodology followed in this paper. The main aim of this research is to investigate the impact of applying SDLC processes on the performance of IDS in WSN. Therefore, this research started by investigating current energy efficient IDSs in WSNs. As LEACH is one of the famous and heavily used energy-efficient protocols [15; 16; 17; 18; 21; 22; 23; 24; 27; 28; 29; 30; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44] to serve the routing and communication services in WSN, consequently, IDSs built over LEACH were investigated. One of the current LEACH-based IDS (SCH-IDS) has been chosen by this study to be deeply analyzed from SE perspectives. This analysis resulted in addressing the shortcomings of the chosen SCH-IDS in regard to missing requirements and inefficient design, development, and testing processes.  
Figure 2: Research methodology and components.  
In order to show the value of applying proper SDLC to the development of IDS in the field of WSN, a study was conducted to find the best SE process model to be integrated with the development of IDSs. Spiral model was applied including its phases: Determine objectives and constraint, identify risks and evaluate alternatives, develop and verify the system, and plan the next phase.  
To examine the influence of applying SE processes, this research focused on the design and development phases. The authors of SCH-IDS did not detail the design used to build their IDS. Therefore, three different designs were proposed to provide the defined services of the SCH-IDS. These designs were called: Scheduling, Broadcasting, and Watchdog.  
After that, these designs were evaluated analytically and then implemented using a network simulator. The evaluation metrics used were the energy consumption and the network life time. The consumed energy was measured in joules, whereas the network lifetime was measured using: number of alive nodes, number of rounds, and the time of the first/last node to die (in seconds).  
The results of the evaluations were analyzed and then summarized. These results showed how integrating SE and IDS processes could improve the performances of IDSs, which in turn will enhance the security of the applications and systems running over different types of WSNs.
# Extended L-Band InAs/InP Quantum-Dash Laser in Millimeter-Wave Applications
## 2 Experimental Setup  
This section discusses two experimental setups; the first was employed for the optical generation of an MMW signal, while the second was used for the transmission of the MMW signal via various channels.
## 3 Bibliometric Analysis: Findings and Research Insights
### Bibliometric Overview of Green Shipping Corridors  
3.1.1. Dataset Main Information  
This bibliometric dataset spans the period from 2002 to 2025, covering 238 documents derived from 93 sources (journals, books, and other outlets). The annual growth rate of these publications stands at 12.16%, reflecting a steady increase in scholarly output over time. In terms of temporal characteristics, the documents' average age is 4.09 years. Each document garners a mean of 23.08 citations, with the entire dataset collectively citing 11,357 references.  
3.1.2. Document Contents  
The dataset contains 565 Keywords Plus (ID) and 866 distinct Author's Keywords (DE). These sets of keywords offer insight into the major thematic areas and conceptual approaches within the field of green shipping corridors.  
3.1.3. Authors and Author Collaboration  
A total of 654 authors contributed to this body of work, with 24 authors producing single-authored documents. Across the dataset, 27 documents are single-authored, contrasting with multi-authored papers, which have an average of 3.68 co-authors per document. International collaboration is notably high, accounting for 38.24% of all co-authorships, underscoring significant global engagement and cross-border research efforts within green shipping corridor studies.  
3.1.4. Document Types  
Among the collected publications, 230 are categorized as journal articles. Additionally, there is a small array of hybrid designations, including (1) one item listed as both an article and book chapter; (2) three as an article and early access; and (3) four as an article and proceedings paper. This distribution underscores the varied channels of scholarly communication within the field.  
3.2. Annual Scholarly Output  
The annual publication counts provide insights into the evolution of research on green shipping corridors. The annual publication counts are depicted in Figure 2.  
Figure 2 reveals that the earliest recorded scholarly contribution to green shipping corridors appeared in 2002, represented by a single publication. Over the following decade from 2003 to 2012, the output remained minimal or nonexistent, featuring only sporadic entries (particularly in 2010 and 2011). Beginning in 2013, however, the domain underwent a discernible increase, rising from three articles in 2013 to four in 2014. A marked surge followed in 2015, with 10 publications, suggesting growing academic engagement.  
Despite a slight decline to 5 publications in 2016, the broader trend remained upward, as the number of publications more than doubled by 2018 (reaching 14) and subsequently climbed to 20 in 2019 and 29 by 2021. The highest output recorded in the dataset was observed in 2024, with 42 publications. By 2025, the count stands at 14 publications.  
However, this figure may reflect partial reporting due to ongoing studies or pending publications. Overall, these findings underscore a robust and accelerating trajectory of scholarly attention toward green shipping corridors, particularly since the mid-2010s.
# An Overview of Terahertz Imaging with Resonant Tunneling Diodes
## 4 Compact RTD THz Imaging and Other NDT Systems
With further improvements of the system, such as a high power RTD source, varactor diode integrated RTD VCO, high responsivity and low NEP detector, and better signal and data processing algorithm, the RTD THz radar technique can rapidly evolve to the next level to realize long-distance high precision THz radar with compact size and low power consumption. Since RTDs have narrow linewidths, an RTD voltage-control oscillator (VCO) array has been proposed to cover frequencies from 420 GHz to 970 GHz [69]. This was used in absorbance measurements with the setup as shown in Figure 8, where RTD VCOs is composed of seven individual RTD oscillators covering different frequency bands. The THz wave radiated from RTD VCO is collimated by an off-axis parabolic mirror and transmitted through a specimen, which is an allopurniol pellet; i.e., a medicine used to lower levels of uric acid in blood. The detector utilized is a liquid-He-cooled Si composite bolometer. The system successfully demonstrated the detection of allopurniol with absorption peak at around 700 GHz. The achieved results show agreement with TDS measurements. The system setup could be more compact and even simpler if the bolometer was replaced by another type of non-cryogenic detector, e.g., an RTD detector.
# Effective Blind Frequency Offset Estimation Scheme for BST-OFDM Based HDTV Broadcast Systems
## 2 System Model
The TMCC signal, which is inserted in the same format independent of segment types, includes system control information like the segment type and transmission parameters that the receiver has to decode first. Since the TMCC is information-bearing, the frequency estimation  
schemes that rely on the explicit pilots such as CP and SP are thus not adequate in this case of using TMCC signals as pilot symbols.
# Rank and Wormhole Attack Detection Model for RPL-Based Internet of Things Using Machine Learning
## 3 Methodology
### Network Model Setup, Simulation, and Network Scenarios for Data Collection
#### 3.2.1 Benign Network Model Simulation  
The benign network model is simulated for benchmarking purposes, and two scenarios are considered for data collection. In the first scenario, the number of nodes is increased from twenty to fifty, while in the second scenario, the state of the node is considered, which is either static or mobile. The data were collected from two use cases of each scenario and used as a baseline dataset against attack datasets. The simulations were implemented in random and grid positionings backed by the methods used by researchers in the existing relevant literature which can be referred to in [13; 27; 28; 29]. The raw data were collected as PCAP (packet capture) files and exported as a CSV file using Wireshark. Next, the two attack models are discussed in the respective sub-sections.
## 3 Results
### Accuracy of Neural Network  
To test the accuracy of the neural network, 34 faults were simulated at different fault locations and classified by the neural network. The result of the network was then compared to the fault location, and an accuracy rate was calculated to determine the viability of the system, see details in Table 2.  
From Table 2 it may be observed that the network was able to correctly classify all the faults in locations F1, F2, and F3. However, at location F4, the network was unable to correctly classify the location. Each fault condition at location F4 was classified as a main line fault, which corresponds to a fault at location F2 or F3. This resulted in an overall success rate of 70.59%. Since the requirement of the network was to correctly classify faults in the different boundaries of a multiline transmission network, it can be regarded as partly successful. The network was able to correctly classify both back line and main line faults. However, it was unable to correctly classify forward line faults and continuously classified forward line faults as main line faults.
# Cellular Entry, Cytotoxicityicity, and Antifungal Activity of Newly Synthesized Dendrimers
## 2 Materials and Methods
### Cell Cytotoxicityicity  
#### 2.5.1 MTT-Test  
MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolzolium bromide) analysis was utilized to assess metabolic activity as an indicator of cell viability, proliferation, and cytotoxicity [26]. Dendrimer dispersions at concentrations of 3 \(\upmu\)g/mL, 7.5 \(\upmu\)g/mL, 15 \(\upmu\)g/mL, 30 \(\upmu\)g/mL, 45 \(\upmu\)g/mL, 60 \(\upmu\)g/mL, and 120 \(\upmu\)g/mL were added to a 96-well plate, containing HFF-1 cells. The plate was then incubated in a CO\({}_{2}\) incubator at 37 \({}^{\circ}\)C for 2, 24, and 48 h. Following the incubation periods, the medium containing the dendrimers was removed, and the MTT reagent was added to each well. The plate was further incubated in darkness at 37 \({}^{\circ}\)C for 4 h. Subsequently, the formazan was dissolved, and the optical density was measured at 570 nm using a spectrofluorometer (Epoch Microplate Reader Bio BioTek/USA, Shoreline, WA, USA). The experimental setup was performed in three repetitions.
## 4 Building Damage Prediction Based on the Calculated Ground Motions
### Method of Damage Prediction  
The damage prediction method for realistic damage prediction should reflect both the difference of the input motion characteristics and the difference in the seismic capacity of the target category of buildings. Empirical methods represented by the conventional vulnerability function use a strength index for the former and the building types for the latter based on the statistical properties of the observed damage during the past devastating earthquakes [34; 35]. The former, such as PGA or PGV, is a crude index to represent the real damaging demand of the input. The latter, such as wooden houses or reinforced concrete (RC) buildings, is also a crude category to differentiate their seismic capacity. The method proposed by [PERSON] and [PERSON] [2; 3; 4], hereafter referred to as the Nagato-Kawase model, uses multiple structural models in their nonlinear response analyses with the input acceleration waveforms calculated at a target site. By comparing the observed damage ratios from the 1995 Hyogo-ken Nanbu earthquake and the results of the earthquake response analyses from the reproduced strong ground motions in Kobe by [PERSON] and [PERSON] [5], [PERSON] and [PERSON] [2; 3; 4] successfully constructed a total of 15 nonlinear response models for different structural categories and construction ages, namely, for a two-storied wooden house without age differences, three-, six-, nine-, and twelve-storied RC buildings, as well as three-, four-, and five-storied steel buildings with the construction age considered (before 1981 large code modification and after 1981). The criterion for a wooden house is considered to suffer heavy damage or collapse when the maximum inter-story deformation angle exceeds 1/10 rad, whereas those for RC and steel structures are defined as the maximum inter-story deformation angle being more than 1/30 rad. In the actual calculation of the damage ratio from a single waveform at a site, we utilized 12 sub-models for each category to represent the statistical variation of the building capacities in Japan, without which we cannot reproduce statistical properties of the observed damage distribution. Figure 12 shows an example of the log-normal distribution for RC buildings. Figure 13 shows an example of the comparison of the reproduced andobserved damage ratio distributions for wooden houses in the Higashinada Ward during the 1995 Hyogo-ken Nanbu earthquake, calculated by [PERSON] and [PERSON] [4].
## 5 Conclusions  
We report the pressure broadening coefficients of the NO R(11.5) \(\Omega\)3/2 and \(\Omega\)1/2 lines in the 1\(\leftarrow\)0 bands at 1915.77 cm\({}^{-1}\) and 1914.98 cm\({}^{-1}\) caused by N\({}_{2}\), CO\({}_{2}\), Ar, H\({}_{2}\), O\({}_{2}\), He and Air, measured using a Mid-IR ICL-based TDLAS spectrometer. The NO-CO\({}_{2}\), NO-N\({}_{2}\), NO-Ar, NO-O\({}_{2}\), NO-H\({}_{2}\) and NO-He pressure broadening coefficients were measured for the pressure range of 100-970 mbar at 294 K using high-quality gases. The measured NO-N\({}_{2}\) and NO-O\({}_{2}\) data were used to compute the NO-Air broadening coefficients. Using the MID-IR TDLAS spectrometer, including both hardware and software, as well as the calibrated pressure and temperature sensors (SI traceable), the experimental findings provide accurate and repeatable results utilizing the same equipment and evaluation procedure. We analyzed the newly measured results to existing data from the literature and addressed the discrepancy. When compared to published data, the relative precision of the measured pressure broadening coefficients show significant improvement. For the first time, the newly measured NO-CO\({}_{2}\) and NO-H\({}_{2}\) broadening coefficients were reported. The obtained broadening coefficients in this work have been used for quantifying the NO amount fraction in a recent publication of a gas-phase study of ammonia in a shock tube reactor which employed a fixed wavelength TDLAS spectrometer. The broadening coefficients can also be used in all industrial and energy gas applications, especially for monitoring the combustion process as well as the NO emission quantification.  
Conceptualization, S.A. and Z.Q.; methodology, S.A. and Z.Q.; formal analysis, S.A. and Z.Q.; writing--original draft preparation, S.A. and D.Z.; writing--review and editing, all authors. All authors have read and agreed to the published version of the manuscript.  
We ([PERSON] and [PERSON]) would like to acknowledge the Alexander von Humboldt (AvH) Foundation for financial support. The State of Lower Saxony/Germany's funding within the H2-WaVe project Grant number ZN3772 is gratefully acknowledged.  
Not applicable.  
The authors declare no conflict of interest.
## 5 Experiment Results
### Navigation Results in Tunnel  
In order to further analyze the effectiveness and navigation accuracy of the MIMU/ODO/MC algorithm inside the tunnel, a section of open area data was selected, and the smoothed result of the GNSS/MIMU integrated navigation was used as reference. GNSS data was disconnected for 100 s to simulate the GNSS signal outage in a tunnel. The differences between the results of the four algorithms and the reference were defined as corresponding errors. The train traveled 9515 m during the GNSS outage, as shown in Figure 10.  
The position errors of the four algorithms are presented in Figure 11. The velocity errors of the four algorithms are presented in Figure 12.The attitude angle errors of the four algorithms are presented in Figure 13. The 100 s error and root mean square error (RMSE) of the navigation results of the four algorithms are shown in Table 3.  
As shown in Figure 11 and Table 3, the position error of MIMU/ODO/MC was significantly less than those of P-INS, TMC-INS, and CIAMC-INS. Both CIAMC-INS and TMC-INS were able to suppress the position errors of P-INS, but the effect on the upwards position error was better. This is related to the higher accuracy of pitch installation angle estimation. Due to the lack of constraints on the forward speed of the vehicle body, the position errors associated with the CIAMC-INS and TMC-INS algorithms still accumulated significantly. By adding the forward speed of the train body measured by the odometer as an observation, the MIMU/ODO/MC integrated navigation was able to obtain meter-level positioning accuracy and realize seamless positioning inside  
Figure 11: Position error curves of four algorithms without GNSS signal. (**a**) East position error curves; (**b**) north position error curves; (**c**) height position error curves. Figure 10: Test trajectory with disconnected GNSS signal. and outside the tunnel. The position error percentages of the four algorithms were 3.25%, 0.87%, 0.43%, and 0.05%. As shown in Figure 12 and Table 3, the velocity error of MIMU/ODO/MC was significantly less than those of P-INS, TMC-INS, and CIAMC-INS  
TMC-INS, CIAMC-INS, and MIMU/ODO/MC all suppressed the velocity errors of P-INS. However, MIMU/ODO/MC had the lowest 100 s velocity errors and RMSE. Compared with TMC-INS and CIAMC-INS, MIMU/ODO/MC was able tosuppressthe velocity errors of P-INS more effectively. Figure 12: Velocity error curves of four algorithms without GNSS signal. (**a**) East velocity error curves; (**b**) north velocity error curves; (**c**) upwards velocity error curves. Figure 13: Attitude error curves of four algorithms without GNSS signal. (**a**) Pitch angle error curves; (**b**) roll angle error curves; (**c**) heading angle error curves.
## 6 Conclusions and Future Work  
In this paper, the QoSensing of the wireless sensor network is improved by enhancing the coverage in the network. This is executed by proposing the MiA-CODER mechanism. Initially, the energy consumption of each node is minimized by performing the unequal Sierpinski cluster-tree topology (USCT) in which the network area is divided into unequal triangles in such a way that the triangle nearer to the base station will be larger, thereby consuming less energy in order to eliminate the hotspot problem. From each cluster, the most efficient node based on energy distance and capacity is selected as the CH by implementing multi-objective black widow optimization (MoBWo). Further, the energy consumption in the network is minimized by performing dynamic sleep scheduling by implementing Tsallis entropy enabled Bayesian probability (TE2 BP) in which the probability of the node to be in either sleep mode or active mode is computed based on the entropy value for significant parameters. Due to the minimization of energy consumption in the network, the possibility of the occurrence of hole coverage is less; however, in the case of the network facing a coverage hole problem, the coverage holes are detected by performing the virtual sector-based hole detection (ViSHD) protocol in which the virtual sectors are constructed and the hole detection is carried out by the CH both within the cell and among the cells. Once the hole is detected accurately, the BS executes the multi-agent SARSA algorithm in which the hole repair process is carried out by optimally selecting a mobile node to cover the hole which is completed based on distance, lifetime and coverage level. This enhances the coverage, thereby improving QoSensing in the network. The proposed MiA-CODER approach is experimented with in the network simulator NS 3.26 tool and the efficiency of this approach is proven by comparing it with several existing approaches in terms of coverage rate, number of dead nodes, average energy consumption and throughput. In the future, the proposed coverage hole detection and repair mechanism is to be improved in security aspects and evaluated in a real-time IoT environment.  
Conceptualization and methodology, L.O.P. and L.M. Software, validation and formal analysis, E.E. and L.O.P. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.