esa-sceva/satcom-chunk-collection huggingface dataset:
# Analyzing Port State Control Data to Explore Future Improvements to GMDSS Training
###### Abstract  
This article uses data generated by Port State Control (PSC) inspections of ships in national ports (Paris MoU) to assess their compliance with radio-communications safety regulations. By mainly applying binary logistic regression methods, the aim is to examine and understand the relationship between the severity of deficiencies in maritime communications and some characteristics of inspected ships. The raw data from the PSC detention database from 2005 to 2022 undergoes post-processing before being analyzed to explore patterns and coincidences with the rest of the potential risk areas. To do so, 23,725 PSC inspections were used. Several classification criteria have been proposed that can better gauge the risk related to distress communications at sea from the dataset. The results connect the probability of detention with the ship age at the inspection date, the flag of the registry, the type of ship, and the location of the port within the countries adhering to the Paris MoU. Another achievement is that the number of PSC inspections of maritime communications in a given period is a better indicator of the risk to safety than the total number of deficiencies detected in these inspections during the same period. This study also explores inspection deficiencies related to competency gaps identified in the Global Maritime Distress Safety System (GMDSS) operators, and precisely using the number of PSC inspections as a criterion of risk for safety is consistent with the recommendations of the Maritime Safety Committee Circular (2006), MSC.1/Circ.1208. Another finding from the time series is that a greater rate of decrease is identified for GMDSS equipment-related deficiencies compared to GMDSS training-related deficiencies. This alone poses a review of the refreshing courses and methods to maintain the General Operator Certificate (GOC) qualification to operate maritime radio communications facilities belonging to the (current and future) GMDSS.  
GMDSS; PSC inspections; maritime communication safety; General Operators Certificate 100, 2023, 11, 2379.
## 4 Results
### Experiment with Data-1
In contrast, deep learning-based methods, such as DnCNN, achieved some improvement in PSNR, but their performance in SSIM, ENL, and CNR was not satisfactory, which may imply that while noise was removed, the details and contrast of the image were lost to a certain extent. SDSR-OCT also performed well in PSNR and SSIM, but its ENL values were abnormally high, which may imply an oversmoothing effect during image edge processing, resulting in a loss of edge detail. Figure 7: The OCT retinal image from Data-1 that was processed by different denoising methods: (**a**) noisy image, (**b**) ground-truth image, (**c**) NLM, (**d**) BM3D, (**e**) DnCNN, (**f**) SDSR-OCT, (**g**) DudeNet, (**h**) MDGAN, (**i**) MDRGAN, (**j**) DCANet, (**k**) DRANet, and (**l**) MFFA-GAN. The blue square represents the background area, and the red square represents the signal area. It can be seen that the deep learning models, such as DudeNet, MDGAN, MDRGAN, DCANet, and DRANet had good performance in terms of PSNR and SSIM, which indicates that they had an advantage in reducing the difference between the reconstructed image and the original image and preserving the structural information of the image. However, the performance of these models varied widely in terms of ENL and CNR, reflecting their different abilities in dealing with image edge details. In contrast, MFFA-GAN achieved excellent performance in all key performance metrics, especially with high values in PSNR and CNR, which fully verifies its ability to retain image details and contrast well while effectively removing noise. In addition, the moderate ENL values also indicate that our model can maintain good detail retention ability when processing image edges and can solve the problem of blurring structural information due to excessive smoothing. In summary, the performance metrics of the above results prove the effectiveness of our model in denoising. In order to further enhance the interpretability of the model, we made a visual pixel error map for Data-1, where the absolute error is visually presented by color coding. Red represents the negative error between the denoised image and the real image, blue represents the positive error between the denoised image and the real image, and white represents the absence of error. The darker the color, the larger the error. As shown in Figure 8, compared with the error maps of other methods, the MFFA-GAN error map only shows a tiny blue color at the edges, with lower pixel error, and it retained the brightness and structure of the retinal layers more completely. It further shows that the image quality after MFFA-GAN noise reduction was higher and the absolute error was smaller.
# Enhancing Indoor Localization with Room-to-Room Transition Time: A Multi-Dataset Study
## 3 Material and Method
### Online (Learning-and-Test) Phase
#### 3.2.3 Efficient Logistic Regression  
Efficient Logistic Regression [49] operates faster and more scalably compared to traditional Logistic Regression methods, even on larger-scale datasets. Efficient Logistic Regression utilizes the fitclinear function for binary-class data and the fitececoc function for multi-class data [50]. These functions enable the model to train on datasets with a large number of observations by significantly reducing training computation time compared to traditional Logistic Regression models. Specifically, it employs various optimization techniques to shorten training times for large datasets.
# Study on Seismic Performance of a Mold Transformer through Shaking Table Tests
## 3 Test Results and Discussion
### Damage Observation  
Figure 11 presents the typical damage of test specimen observed during a series of shaking table tests. Overall, three weak points are shown, as evident in Figure 11a: The failure of the spacers, the slippage of coils, and the loosening of linked bolts between the bottom beam and bed beam. The first damage was observed after AC156_50 (Test no. 5), with respect to the PGA of 0.15, 0.14, and 0.16\(\times\)\(g\) in the X, Y, and Z-directions, respectively. The local damage could be observed in the spacers located on the right and left coils of the transformer in terms of vertical and horizontal crack, as shown in Figure 11b.  
Figure 11c-f demonstrate the damage of the test specimen observed after AC156_75, AC156_125, AC156_250, and AC156_300, respectively. To be more specific, after AC156_75 (Test no. 6), with respect to the PGA of 0.21, 0.17, and 0.18\(\times\)\(g\) in the X, Y and Z-directions, respectively, the horizontal crack continues to develop in the spacers located on the left coil at the bottom of the transformer (Figure 11c). Simultaneously, the bolts connecting the bottom beam and bed beam partially loosen. After AC156_125 (Test no. 11), with respect to the PGA of 0.33, 0.31, and 0.27\(\times\)\(g\) in the X, Y and Z-directions, respectively, the HV and LV coils have slipped away from the original positions (Figure 11d). This is due to the fact that the inertia force caused by the high acceleration level exceeds the friction force between the spaces and bottom beams, leading to the slippage of the HV and LV coils. The slippage of the HV and LV coils continued to grow during test AC156_250 and caused bond loss between the upper part and lower part of the spacers (Figure 11e). After the final test (AC156_300), with respect to the PGA of  
Figure 11: Damage observation after different shaking table tests: (**a**) Weak points of test specimen; (**b**) After AC156_50; (**c**) After AC156_75; (**d**) After AC156_125; (**e**) After AC156_250; (**f**) After AC156_300.  
0.90, 0.79, and 0.66\(\times\)\(g\) in the X, Y, and Z-directions, respectively, the bond between the upper part and lower part of the spacers located at the bottom of the transformer was completely lost, leading to the failure of the spacers. Simultaneously, the bolts connecting the bottom beam and bed beam became completely loose, as shown in Figure 11f.  
In general, at the final test, the specimen neither overturned nor collapsed; however, the spacers showed severe slippage, which to avoid magnetic stress and dangerous geometrical dissymmetry, should keep constant distances between the core and the coils, and between the HV coils and LV coils [23]. Such failure of the spacers was mainly concentrated at the bottom region of the test specimen, along with the loosening of the linked bolts between the bottom beam and bed beam.
# Threat Analysis and Risk Assessment (TARA) Analysis of an Autonomous Emergency Braking (AEB) System
## 6 Risk Analysis
### Critical-Risk-Level Threats and Mitigation Strategies
#### 6.1.3 Tampering with WSS-to_ESC_CAN  
**Security Risks**. The manipulation of WSS- and ESC-CAN communication threatens security by tampering with critical vehicle sensors used by safety systems. In general, an attacker physically accesses the vehicle through the OBD connector and can manipulate sensor data, thereby giving wrong information to the ESC system. The AEB system operates in an incorrect manner due to interference and causes accidents or driving in unsafe conditions. The operational impact is severe; vehicle safety is directly compromised, while the privacy concerns are minimal. Due to the potential consequences and medium feasibility of such an attack, the overall risk is classified as high. Ensuring the integrity of WSS and ESC communications is vital for maintaining vehicle safety. **Security Measures**. Tampering with WSS- and ESC-CAN communication must be minimized through robust security measures regarding the integrity and authenticity of data. The implementation of cryptographic message integrity protection, such as HMAC, ensures that data are not altered without authorization. The strict physical security, for example, of the OBD connector reduces the possibility of unauthorized access, while the auditing of the system and its constant monitoring enable the early detection of tampering. The threat vectors keep evolving with WSS and ESC software updated for the latest threats; quarterly risk reviews should be performed. Software integrity and strict access controls allow only authorized changes to be introduced to these systems.
## 7 Conclusions  
In this paper, we proposed a secure architecture for M2M layer communications. A security mechanism is suggested for mutual authentication between base stations and end devices once registered. A blockchain technology is used to provide security for M2M communications while improving the identity management and facilitating traceability, integrity and availability of data transactions.  
The proposal is based on lightweight procedures involving limited overhead storage and a limited number of exchanged messages for identity management. Moreover, the security analysis of our proposal confirms that our proposal resists different attacks. As future work, we project to extend the proposed scheme in order to support mobility of devices and heterogeneity of networks. Moreover, we plan to evaluate through simulations the performance of the extended blockchain-based scheme, in which devices need to access the authentication service across high levels of the M2M architecture, and implement a new adapted PBFT lightweight consensus.  
Writing--original draft, K.E.B. and P.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**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.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Protocol** & **Proposed** & **[8]** & **[15]** & **[16]** & **[17]** & **[18]** & **[24]** \\ \hline Centralized & No & Yes & Yes & Yes & Yes & Yes & No \\ \hline Trust Level & High & Low & Low & Medium & Low & High \\ \hline Single point failure & No & Yes & Yes & Yes & Yes & Yes & No \\ \hline Mutual Authentication & Yes & Yes & Yes & Yes & Yes & Yes & Yes \\ \hline Key Agreement & Yes & Yes & Yes & Yes & Yes & Yes & Yes \\ \hline Resist Man in the middle & Yes & No & Yes & Yes & Yes & No & Yes \\ \hline Transaction History & Yes & No & No & Yes & No & No & Yes \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparison with other schemes.
# Combined Optical Fiber Transmission System Based on QNSC and BER-LM
###### Abstract  
A quantum noise stream cipher (QNSC) is a physical layer encryption technology based on quantum noise. Bit error rate loopback measurement (BER-LM) is a method to measure the BER of a loopback channel and extract channel characteristics. Then, channel characteristics can be extracted, and consensus keys can be obtained through negotiation. In previous studies, encryption and key distribution were implemented in independent channels. In this paper, we propose a scheme that combines these two technologies in a single fiber channel to achieve encrypted transmission and key distribution. We verified a 20 Gbps QPSK coherent optical transmission system with a PSK/QNSC scheme. The results show that by reasonably setting the negotiation bit position, the consensus key could be obtained through negotiation, and the requirements of transmission performance could be met. When the negotiation bit position was set to seven, the Q-factor of the system was nine, which met the error-free condition of the 7% forward error correction (FEC) limit.  
physical layer; key distribution; quantum noise stream cipher; optical fiber communication 2023
# Analytical Model for Enhancing the Adoptability of Continuous Descent Approach at Airports
## 3 CDA Adoptability and Aircraft Descent Times
### Factors Impacting CDA Adoptability and Aircraft Descent Times
Often, such constraints are contingent on the original airspace design, which gradually became less efficient due to increasing demand and fluctuating traffic patterns, or airspace redesign, which necessitates consideration of nearby restricted airspace. On the other hand, a restricted airspace, which is an area of airspace typically used by military operations, could be close to an airport and would impose a specific airspace design that affects the pattern of the arriving aircraft. Other airspace constraints include the topographical nature and terrain (e.g., an airport close to a mountainous terrain). Airspace constraints, collectively as a single factor, are beyond the scope of this work. While estimating the effect of this factor is beyond the scope of this work, our model's behavior reflects its ability to capture such effect. Growth in air traffic at airports within close geographical proximity likely will create congestion, especially if these airports are in a large, busy metropolitan area. The impact of air traffic at neighboring airports comes from systems of airports commonly referred to as _metroplexes_. Operationally, air traffic that flows into and out of airports within a metroplexes airport system needs to be coordinated between airports in such systems to maintain efficient air traffic and individual airports' throughput, while contributing little (if any) impact to the AAR of an airport over another in such a system [38; 39] and, therefore, limiting or even preventing the use of our model. The FAA is having ongoing efforts to accommodate CDAs within metroplexes, with plans to deploy during a later phase of NextGen.
# Control of _Francisella tulareis_ Virulence at Gene Level: Network of Transcription Factors
## 5 Regulators Necessary for Regulation of Iron and Metabolism  
### Ferric Uptake Regulator, Fur  
The ferric uptake regulator (Fur) crystal structure was described, and the ability of Fur to bind to promoter sequences containing a Fur box was demonstrated [52]. Fur is a tetrameric protein that is able to bind specific DNA sequences by its splitting into two dimers [52].  
Fur is an important component involved in the regulation of iron concentration and contributes to metal homeostasis in the bacterial cell. The concentration of iron is limiting for optimal growth and physiological balance of bacteria, but higher concentrations could be fatal, therefore, it is highly regulated. The activity of Fur and the intracellular concentration of iron affect many key components critical for the virulence of pathogenic bacteria [115; 116]. Fur works mainly as a Fe\({}^{2+}\)-dependent transcriptional repressor, but some genes require Fur for their expression [117]. It is necessary for the regulation of several genes involved in the tricarboxylic acid cycle (_ftdABD_, _aspA_, _sucCD_, _funmAB_) [118] and superoxide dismutase (SodB) as well [119]. Regulation of iron homeostasis and the functioning of metallo-regulating proteins are crucial for the Francisella physiology [54; 55]. The level of host cell iron influences _F. tulareis_ subsp. _holarctica_ LVS intracellular replication and virulence [120]. On the other hand, if grown under iron-restricted conditions, _F. tulareis_ subsp. _holarctica_ LVS and _F. tulareis_ subsp. _tularensis_ Schu S4 were found to produce their own siderophores [53], FslA, which is similar to the polycarboxylate siderophore rhizoferrin [53]. Later, it was found that FslE is also required during iron starvation and could act as a membrane receptor for FslA [121]. The encoding genes belong to _fslABCDEF_ operon (also called _fig_ operon), which is under Fur control [52] and upregulated during iron starvation [52; 53]. Fur is required for full virulence of _F. tulareis_ subsp. _holarctica_ in both macrophage-like cells and mice [52].
## 3 Results and Discussion
### Regeneration and Reusability Study  
The reusability of any adsorbent is a key factor determining its sustainability, effectiveness, and applicability for real samples treatment. The reusability of Fe\({}_{3}\)O\({}_{4}\)/CS/PEI nanocomposite for the uptake of As(III) and As(V) ions was studied up to five sequential cycles as shown in Figure 8. Each cycle included the adsorption of polluted ions followed by desorption of adsorbed ions using alkaline solution (0.1 M of NaOH) as eluent. Herein, the magnetic separation was used to collect the adsorbent to be washed and dried for the next cycle.  
According to Figure 8, the removal efficiency of As(III) and As(V) ions using Fe\({}_{3}\)O\({}_{4}\)/CS/PEI nanocomposite was dropped from 99.5% to 92.0% and from 99.7% to 94.0%, respectively, after the 5 th cycle. The literature reported the use of Fe\({}_{3}\)O\({}_{4}\)/CS for the uptake of As(III) and As(V) ions from water with the retention of only 76.0% and 88.0% of the initial efficiency after the 5 th cycle [59]. The small drop of the removal efficiencies of As(III) and As(V) ions over Fe\({}_{3}\)O\({}_{4}\)/CS/PEI nanocomposite was attributed to the damaged adsorption sites after each cycle. However, the removal efficiencies for the uptake of both ions over Fe\({}_{3}\)O\({}_{4}\)/CS/PEI nanocomposite remain over 90.0% after the 5 th cycle indicating the ability to reuse this synthesized adsorbent to remove arsenic ions for several times. As a result,  
Figure 8: The reusability of Fe\({}_{3}\)O\({}_{4}\)/CS/PEI magnetic nanomaterials for the removal of As(V) and As(III) ions up to five successive cycles.  
the Fe\({}_{3}\)O\({}_{4}\)/CS/PEI nanocomposite can be used for real water treatment with a low cost of processing due to the excellent results of reusability.
## 2 Existing Leak Detection and Localization Methods
### Methods Based on Model Estimation
#### 2.2.3 Kalman Filter [26]  
This method first sets up discrete state space models of pressure and flow. Pressure and flow at the head and end of the pipeline are used as inputs. The whole pipeline is divided into several sections and three sorts of states (pressure, flow and leak amount) are set at each section point. Then an appropriate discriminate criterion is adopted for leak point detection and localization. However, this method has to acquire mean value and variance of process noise in advance and the degrees of accuracy of detection and localization are related to the number of sections.
# Calculation Method of Earth Pressure Considering Wall Displacement and Axial Stress Variations
## 2 Theoretical Analysis
### Discussion on the Existence of Inflection Point  
As mentioned above, the condition for the existence of the minor principal stress second inflection point is \(\sigma_{xp}\geq\sigma_{x3r}\). For cohesionless soil, the equation derived on the basis of this condition is given by Equation (23).  
\[\sigma_{xp}-\sigma_{x3r}=(K_{p}-\frac{1}{K_{0}})\sigma_{z}\geq 0 \tag{23}\]  
After simplification, the following formula can be obtained.  
\[\tan^{2}(45^{\circ}+\frac{\varphi}{2})\geq\frac{1-\mu}{\mu} \tag{24}\]  
\[\varphi\geq\frac{360}{\pi}\text{arctan}\sqrt{\frac{1-\mu}{\mu}}-90 \tag{25}\]  
From Figure 5 it can be concluded that for cohesionless soils, the existence of the inflection point can be determined by the location of the point with a given Poisson's  
Figure 4: Earth pressure zoning by soil stress magnitude (\(\varepsilon_{x3r}\) does not exist).  
Figure 3: Earth pressure zoning by soil stress magnitude (\(\varepsilon_{x3r}\) exists).  
ratio \(\mu\) and friction angle \(\varphi\) relative to the \(\varphi\)-\(\mu\) curve. If the point is above the curve, the inflection point exists. If the point is exactly on the curve, the inflection point also exists, and \(\sigma_{x3r}=\sigma_{xp}\). If the point is below the curve, the inflection point does not exist.  
For cohesive soils, the situation is somewhat more complex. The conditions for the existence of the minor principal stress second inflection point are given in Equation (26).  
\[\sigma_{xp}-\sigma_{x3r}=\left[\tan^{2}(45^{\circ}+\frac{\varphi}{2})-\frac{1 -\mu}{\mu}\right]\sigma_{z}+2c\tan(45^{\circ}+\frac{\varphi}{2})\geq 0 \tag{26}\]  
Based on Equation (26), the condition to be satisfied by the self-weight stress \(\sigma_{z}\) is expressed in Equation (27).  
\[\sigma_{z}\leq\frac{2\mu c\tan(45^{\circ}+\frac{\varphi}{2})}{1-\mu\sec^{2}(45 ^{\circ}+\frac{\varphi}{2})} \tag{27}\]  
Alternatively, the depth \(z_{x3r}\) of the soil behind the wall should satisfy the following condition.  
\[z_{x3r}\leq\frac{2\mu c\tan(45^{\circ}+\frac{\varphi}{2})}{\gamma-\mu\gamma \sec^{2}(45^{\circ}+\frac{\varphi}{2})} \tag{28}\]  
This indicates that even if the \(\varphi\) and \(\mu\) distribution of the clay is below the \(\varphi-\mu\) curve, an inflection point still exists if the self-weight stress \(\sigma_{z}\) or depth \(z_{x3r}\) of the soil satisfies the aforementioned conditions.