esa-sceva/satcom-chunk-collection huggingface dataset:
# Utilizing Multi-Dimensional MmWave MIMO Channel Features for Location Verification
###### Abstract  
In this paper, we address the problem of authenticating transmitters in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication systems, and propose a location verification scheme based on multi-dimensional mmWave MIMO channel features. In particular, we first examine the mmWave MIMO channel features in terms of azimuth angle of arrival (AAoA), elevation angle of arrival (EAoA), and path gain, and then extract these fine-grained channel features through the maximum-likelihood (ML) estimation method. Based on the extracted feature parameters, authentication validation is cast in the framework of hypothesis testing theory. We also derive the analytical expressions for the typical false alarm and detection rates by using the likelihood ratio test and thus the statistical performance is analytically established. Finally, extensive numerical results are provided to demonstrate the performance of the proposed authentication scheme.  
location verification; physical layer authentication; millimeter-wave (mmWave) communications; multiple-input multiple-output (MIMO); channel features +
Footnote †: journal: _Sensors_  
1
Footnote 1: School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China 1  
22
Footnote 2: School of Computer Science, Xidian University, Xi’an 710071, China 2
# Evaluation of Pressure Effect on Accelerated Aging Tests of Polymer-Insulated Aircraft Wires
###### Abstract  
Most current international standards for qualifying polymer-insulated wires for aircraft applications rely on degradation tests conducted under standard pressure conditions. However, some wires are used in unpressurized areas and therefore need to withstand low-pressure conditions. In the technical literature, there is a shortage of data on this topic. This article focuses on accelerated wet arc tracking tests of insulated wires and evaluates three methods that assess the performance of surface discharges generated during degradation, based on the light emitted, under different pressure conditions in the range of 100 kPa-16 kPa. The experimental results presented in this paper show that the sensitivity of the proposed methods increases with atmospheric pressure, allowing a better quantification of the degradation effects at higher pressures. These results can also help to gain experience and understanding in how commercial optoelectronic sensors can be used to assess the insulation condition by analyzing the light generated by the surface discharges.  
optoelectronic sensors; arc tracking; insulated wires; electrical discharge; high voltage; aging tests; wet arc tracking; erosion; low pressure +
Footnote †: journal: Applied sciences
# A Hybrid Hidden Markov Model for Pipeline Leakage Detection
## 4 Conclusions  
In this paper, a DNN-HMM hybrid model was proposed to detect pipeline leakage location. DNN computes the emission probabilities for the HMM instead of Gaussian mixture model. This hybrid model showed the feasibility of converting leakage state posteriors to the emission probabilities by training a DNN which uses the damage indices as the training set. DNN is more efficient for modeling leakage features. The DNN is a pre-trained model built by stacking top-down RBM that computes the emission probabilities for the HMM. Two comparative tests based on different numbers of states using GMM-HMM and DNN-HMM were studied. The results demonstrate that the DNN-HMM can learn better models of data and achieve better performance compared to GMM-HMM. The micro \(F_{1}\) score approaches 0.94 for three states, and it approaches 0.96 for five states when the hybrid HMM was applied.  
In this paper, two damage indices, i.e., one time domain damage index and one frequency domain index, were used to extract features from the negative pressure waves collected by PZT transducers. In future work, other damage indices or even without using damage indices for pipeline leakage detection will be explored.  
Conceptualization, M.Z., X.C. and W.L.; software, M.Z.; validation, M.Z., X.C. and W.L.; writing--original draft preparation, M.Z.; writing--review and editing, X.C. and W.L.; visualization, M.Z.; project administration, X.C.; and funding acquisition, X.C. All authors have read and agreed to the published version of the manuscript.  
This material is based upon work supported by the National Science Foundation under Grants No. 1801811.  
Not applicable.  
Thanks to Smart Materials and Structures Laboratory at the University of Houston for providing the pipeline leakage experimental data.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### NO Formation in Pure Ammonia Combustion
#### 3.1.2 Effect of Ammonia Concentration on NO Production  
In this section, the ammonia concentration was doubled by doubling the NH\({}_{3}\) flow rate in the NH\({}_{3}\)/O\({}_{2}\)/Ar mixture and the O\({}_{2}\) flow rate corresponding to the excess air coefficient at the same time. The excess air coefficients were 0.9, 1.0, and 1.1, and the combustion temperature was 1500 \({}^{\circ}\)C. The experimental results are shown in Figure 3. Under several of the temperature conditions set in this experiment, NO production also increased when \(\alpha\) was not less than 1 and the ammonia concentration doubled, and the influence of concentration-doubling increased with the increase in excess air coefficient. When \(\alpha\) was less than 1, the NO production was always low. When \(\alpha\) was smaller, the competition between H + O\({}_{2}\) + M = HO\({}_{2}\) + M and H + O\({}_{2}\) = O + OH reactions was more intense, and the tendency to prevent the generation of O/H radicals increased, which inhibited the conversion of NH\({}_{3}\) to NH\({}_{2}\) and ultimately inhibit the reduction of NO [32]. Hence NO production was invariably low when \(\alpha\) is less than 1.
## 5 Conclusions  
In this paper, we present a multiple-connectivity operation in wireless networks operating in three bands (i.e., the sub-6 GHz band, mmWave band, sub-THz band) simultaneously. In addition, we propose a transmission point selection algorithm, which is suitable for both single connectivity and multi-connectivities. The proposed algorithm finds the allowed transmission point sequentially and adds it into a candidate set of selected transmission sets in the network without considering other users' situations, e.g., channel status, service time. To maintain the candidate set of selected transmission sets, we compare the TP with the minimum service rate to the temporally selected TP's service rate. Then, the TP with the lower service rate is eliminated from the candidate set until no more TPs are available to compare. We also derive the performance bounds and the approximation ratios of the proposed algorithm, which is a 2-approximation of optimal solution. Our simulation results show that selecting and serving multiple transmission points regardless of frequency band performs better than services through single-band single-connectivity operation. The study presented in this paper, and its further extension, taking into account multi-band multi-connectivity operation technology, can be employed extensively in several network environments such as multi-layer networks, IoT networks, AI-embedded networks, etc.  
Conceptualization, E.K.; methodology, E.K., D.K. and C.C.; software, E.K.; validation, E.K., D.K. and C.C.; formal analysis, E.K.; investigation, D.K. and C.C.; writing--original draft preparation, E.K.; writing--review and editing, E.K., D.K. and C.C. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Hanbat National University research fund in 2022.  
Not applicable.  
Data Availability Statement: Data is contained within the article.  
The authors declare no conflicts of interest.  
Figure 4: TP and/or serving beam change rate with different users (U = 1, 10,..., 100) in the case where (**a**) only one connection is allowed (C = 1), (**b**) two connections are allowed (C = 2), and (**c**) three connections are allowed (C = 3).
## 4 Simulation Results
### Results on the Benchmark Test-Suite
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Function**} & \multirow{2}{*}{**PopSize**} & \multirow{2}{*}{**Gens**} & \multicolumn{4}{c}{**Best-of-Run Fitness**} & \multicolumn{4}{c}{**FirstHitEvals**} \\ \cline{3-10}  & & & **Best** & **Mean** & **Std Dev** & **Success** & **Best** & **Mean** & **Std Dev** \\ \hline Ackley & 100 & 3000 & \(7.4347\times 10^{-10}\) & \(1.8900\times 10^{-9}\) & \(9.1920\times 10^{-10}\) & 30 & 209,499 & 217,209.4333 & 4885.3830 \\  & 150 & 5000 & \(1.0938\times 10^{-12}\) & \(2.7097\times 10^{-12}\) & \(7.9283\times 10^{-13}\) & 30 & 407,146 & 426,516.7667 & 7522.8400 \\ Rosenbrock & 100 & 3000 & 0.0015 & 25.4532 & 28.8764 & 0 & — & — \\  & 150 & 5000 & 0.0001 & 17.0565 & 26.9145 & 0 & — & — \\ Chu-Rey & 100 & 3000 & \(5.0261\times 10^{-37}\) & \(1.1798\times 10^{-35}\) & \(3.0313\times 10^{-35}\) & 30 & 77,035 & 84,420.6 & 3325.8495 \\  & 150 & 5000 & \(1.2691\times 10^{-48}\) & \(4.9288\times 10^{-47}\) & \(6.4529\times 10^{-47}\) & 30 & 153,594 & 162,497.0667 & 3651.8492 \\ Step & 100 & 3000 & 0.0 & 0.0667 & 0.2494 & 28 & 39004 & 43,895.0357 & 5319.6538 \\  & 150 & 5000 & 0.0 & 0.0 & 0.0 & 30 & 68,099 & 73,154.9333 & 3639.5311 \\ Alpine-1 & 100 & 3000 & 0.0247 & 6.8245 & 6.4345 & 0 & — & — \\  & 150 & 5000 & 0.0137 & 4.5976 & 5.7499 & 0 & — & — \\ SumSquares & 100 & 3000 & \(6.1724\times 10^{-18}\) & \(3.8440\times 10^{-17}\) & \(4.0234\times 10^{-17}\) & 30 & 138,646 & 144,029.4333 & 3771.9204 \\  & 150 & 5000 & \(1.3309\times 10^{-23}\) & \(7.2599\times 10^{-23}\) & \(5.5164\times 10^{-23}\) & 30 & 266,653 & 280,539.4333 & 6344.5950 \\ Sphere & 100 & 3000 & \(5.6661\times 10^{-17}\) & \(2.9297\times 10^{-16}\) & \(2.6115\times 10^{-16}\) & 30 & 152,133 & 157,149.2333 & 2954.1983 \\  & 150 & 5000 & \(1.3981\times 10^{-22}\) & \(6.1597\times 10^{-22}\) & \(4.1632\times 10^{-22}\) & 30 & 298,554 & 306,880.0667 & 4927.0814 \\ Boha-3 & 15 & 5000 & 0.0 & 0.0 & 0.0 & 30 & 882 & 1322.4667 & 308.4498 \\ Boha-2 & 20 & 5000 & 0.0 & 0.0 & 0.0 & 30 & 1182 & 1838.7 & 333.6645 \\  & 15 & 5000 & 0.0 & 0.0 & 0.0 & 30 & 718 & 1005.3333 & 268.2153 \\ Boha-2 & 20 & 5000 & 0.0 & 0.0 & 0.0 & 30 & 890 & 1443.3667 & 222.3957 \\ Bartels & 15 & 5000 & 1.0 & 1.0 & 0.0 & 30 & 893 & 1061.0 & 90.1706 \\  & 20 & 5000 & 1.0 & 1.0 & 0.0 & 30 & 1128 & 1523.4333 & 124.4451 \\ Gold-Pr & 15 & 5000 & 3.0000 & 3.0000 & \(1.0820\times 10^{-5}\) & 6 & 28,320 & 55,857.5 & 14,917.3860 \\  & 20 & 5000 & 3.0000 & 3.0000 & \(1.8986\times 10^{-5}\) & 5 & 58,442 & 82,977.0 & 14,243.2530 \\ Matyas & 15 & 5000 & 0.0 & \(3.0482\times 10^{-35}\) & \(1.6415\times 10^{-34}\) & 30 & 471 & 856.1 & 169.1497 \\  & 20 & 5000 & 0.0 & \(5.6005\times 10^{-123}\) & \(3.0160\times 10^{-122}\) & 30 & 692 & 1152.7333 & 264.9280 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Results of Słaya on the 12-function test-suite (each row corresponds to 30 independent runs). Most numbers are shown with rounding at the fourth place after the decimal.
###### Abstract  
The wastewater effluents from textile industries contain highly toxic metal complex dyes. For instance, azo dye has received significant attention owing to its toxicity and environmental stability. This study investigated the oxidation and coagulation processes to effectively remove azo dye from wastewater effluents. Potassium ferrite (K\({}_{2}\)FeO\({}_{4}\)) was selected as an oxidant because it has a high oxidation potential, is environmentally stable, and does not generate toxic byproducts. Moreover, it has a combination effect of coagulation and oxidation. Its performance was compared with a single oxidation process (using NaCl) and a single coagulation process (using FeCl\({}_{3}\)-6H\({}_{2}\)O). Based on the jar test experiment, the optimized pH was estimated to be 3 and the optimal dosage was 56.4 mg/L for K\({}_{2}\)FeO\({}_{4}\), and it removed nearly 100% of orange II azo dye (OD) and lissamine green B dye (LCB). However, its removal efficiency decreased when the pH increased to 12. In all processes, dye removal was completed in 5 min of the reaction. Overall, OD and LGB were effectively removed by K\({}_{2}\)FeO\({}_{4}\), compared to the NaCl and FeCl\({}_{3}\)-6H\({}_{2}\)O. This indicates that the combination of oxidation and coagulation of K\({}_{2}\)FeO\({}_{4}\) outperformed the single treatment process without toxic byproduct production.  
azo dye removal; potassium ferrite; coagulation; oxidation; textile wastewater
# Simplified Derivative-Based Carrierless PPM Using VCO and Monostable Multivibrator
## 6 Discussion and Analysis of Results
### Clarification of Signal Recovery Characteristics  
The experimental results demonstrate that all demodulation methods recover the derivative of the original message signal, representing the theoretically expected behavior of the proposed derivative-based PPM technique. This clarifies the conceptual framework and addresses signal recovery characteristics.  
The negative Pearson correlation coefficients in Table 2 (\(-\)0.8908 to \(-\)0.1505) mathematically confirm that recovered signals correlate with the differentiated input signal, validating successful derivative-based implementation. Visual evidence in Figures 15-18, 20, 22, and 24 shows consistent phase shifts characteristic of differentiation operations across all demodulation methods.  
This derivative recovery provides system flexibility rather than limitation. Applications requiring the original signal can incorporate integration stages for signal reconstruction, while others can directly utilize derivative information for differential processing applications. The consistency across all three demodulation techniques confirms this characteristic is fundamental to the modulation approach, validating the robustness of the derivative-based PPM concept.
## 4 Architecture of Real-Time AI Agents for Autonomous Ships
### Communication Interfaces and Data Exchange  
Reliable communication systems are essential for autonomous maritime operations, enabling AI agents to maintain situational awareness beyond onboard sensors and to ensure compliance with external instructions, regulations, and dynamic traffic information. These interfaces allow the autonomous vessel to function as part of a wider, interconnected maritime ecosystem.  
Autonomous ships typically integrate the following three main categories of communication technologies:  
1. Very High Frequency (VHF) radio provides short-range communication with nearby vessels and coastal stations. This is used for voice- and data-based exchanges, particularly in congested waters or near ports [73].
2. Automatic Identification Systems (AIS) broadcast and receive real-time navigational data, including vessel identity, position, course, and speed, thereby enhancing situational awareness and supporting cooperative maneuvering [74].
3. Satellite communication systems ensure long-range data exchange, especially in open ocean areas where terrestrial networks are unavailable. This includes receiving weather data, regulatory updates, and mission instructions [69].  
The AI agent uses these inputs to adjust its decision-making processes in real time. For instance, satellite-fed storm warnings can prompt proactive rerouting, while AIS data help avoid traffic conflicts. The seamless integration of external data enhances not only safety and efficiency but also compliance with dynamic maritime regulations [80; 81].  
Robust communication also plays a critical role in enabling human-AI collaboration. When operating in semi-autonomous or monitored modes, AI agents must transmit status updates, escalate anomalies, or accept override commands from remote operators.  
To ensure secure and trustworthy operations, these communication channels are fortified with encryption, authentication protocols, and intrusion detection mechanisms. Protecting the integrity of data exchanged between ship and shore is vital, particularly in safety-critical scenarios or during navigation near sensitive areas.  
In essence, the communication infrastructure acts as the AI agent's external sensory and regulatory interface, extending its perception, supporting collaboration, and anchoring its decisions in a broader maritime context.
## 4 Analysis of the Representations
### Comparison of Representations under Adversarial Attacks  
Canonical correlation analysis (CCA) is a method used to compare the representations of neural networks. Its objective is to identify linear combinations of two sets of random variables that maximise their correlation. CCA has been employed to compare activations from different layers of neural networks, for example, by [PERSON] et al. (2018) and [PERSON] et al. (2019). [PERSON] et al. (2019) proposed an extension of CCA, singular value canonical correlation analysis (SVCCA), for neural network analysis.  
We employed SVCCA to compare the representations of the original and corresponding adversarial images. For each experiment, we took a batch of 128 images, computed the related adversarial examples under some attack, calculated the SVCCA for the representations, and took the mean. In each experiment, we tested the same models as in the previous experiments: a regularly and two adversarially trained ResNet50-s. In this experiment, a high mean correlation coefficient indicated that the representations were similar to each other and that small perturbations did not impact the model.  
Figure 3: Distributions of samples for regularly trained ResNet50.  
Although attack norms were the primary variables in these experiments, we also tested two different attacks (FGSM and PGD) to eliminate the threat of validity. The means of SVCCA are presented in Table 7. The results of the same for the best and worst cases from Tables 1 and 2 in Table 10 can be found in Appendix B.  
The results in Tables 7 and 10 demonstrate that adversarial attacks with \(L_{\infty}\)-norm perturbation have the most significant impact on the representations. This effect is evident even in models that were trained specifically to handle \(L_{\infty}\)-norm attacks. These findings emphasise the importance of considering adversarial attack norms when evaluating model robustness because testing in the \(L_{2}\)-norm may provide a false sense of security.
## Materials
### Data used for Geoscience Laser Altimeter System (GLAS) Leaf Area Index (LAI) Inversion
#### 2.2.3 Shuttle Radar Topography Mission (SRTM) Data  
The version 4 Shuttle Radar Topography Mission (SRTM) digital elevation dataset was used to produce the slope maps of the study areas with a resolution of 90 m. \(5^{\circ}\times 5^{\circ}\) SRTM tiles in GeoTIFF format corresponding to our study areas were downloaded from [[http://srtm.csi.cgiar.org/srtmdata/](http://srtm.csi.cgiar.org/srtmdata/)]([http://srtm.csi.cgiar.org/srtmdata/](http://srtm.csi.cgiar.org/srtmdata/)) and the downloaded data have been processed to fill data voids.  
Figure 1: Land cover distribution and locations of Geoscience Laser Altimeter System (GLAS) footprints over study areas A and B. (**a**) A is Heilongjiang Province, China. We conducted province-level leaf area index (LAI) inversion in this study area. (**b**) B is Saihanba National Forest Park in Heibei Province, China, which is our ground investigation area.
## 6 Evaluation
### Evaluation Based on the Questionnaire Survey
#### 6.1.4 Evaluation Concerning the Usefulness of the Overall System  
Evaluation concerning utilization.  
Figure 12 shows the evaluation results of the utilization of the overall system. Regarding the comprehensibility of the interface, while 83% answered \"I think so\" or \"I somewhat think so\", 9% answered \"Neither\", and 8% answered \"I don't think so\" or \"I don't think so at all\". The reason for this low rating may be due to the overlapping of the pictograms or images displayed on the AR screens.  
Regarding the operability of the overall system, though 87% answered \"I think so\" or \"I somewhat think so\", 10% answered \"Neither\" and 3% answered \"I don't think so at all\". The reason for the low rating may be, as mentioned in Section 6.1.2, because the users were not familiar with applications using AR, thereby making it difficult for them to understand the operation method of the functions using AR. However, such an issue may be solved by having users use the system for a longer period.  
Regarding the operability during disasters, users were asked to answer the questionnaire survey by assuming Typhoon Hagibis of October 2019 was the disaster. Though 80% answered \"I think so\" or \"I somewhat think so\", 12% answered \"Neither\", and 8% answered \"I don't think so\". The reason for this low rating can be assumed to be that the users felt that there would be difficulty operating the system while evacuating outside during a typhoon.  
Evaluation concerning usefulness.  
Figure 13 shows the evaluation results of the usefulness of the overall system. Regarding usefulness while sightseeing, 93% answered \"I think so\" or \"I somewhat think so\". Therefore, it can be said that the present study was successful in developing a system that provided information concerning sightseeing spots and tourism-related facilities using AR and pictograms.  
Figure 11: Evaluation results of the originality of the system.  
Figure 12: Evaluation results concerning the utilization of the overall system.  
Regarding usefulness during disasters, the users were asked to answer by assuming Typhoon Hagibis of October 2019 for the disaster. Though 87% answered \"I think so\" or \"I somewhat think so\", 7% answered \"Neither\", and 6% answered \"I don't think so\". This indicates that the rating of the usefulness of the system during disasters was slightly lower than its usefulness when sightseeing. This may be due to users feeling anxious about whether the system would work well during disasters other than typhoons, as well as the fact that the users who were not affected by Typhoon Hagibis found it difficult to imagine the situation.  
Regarding the wish to continue using the system in the future, 82% answered \"I think so\" or \"I somewhat think so\", 8% answered \"Neither\", and 10% answered \"I don't think so\" or \"I don't think so at all\". The reason for this low rating was considered to be over 60% of the users lacking a sense of locality as they had not frequently visited Chofu City, as was introduced in Section 6.1.1.