esa-sceva/satcom-chunk-collection huggingface dataset:
# IPCB: Intelligent Pseudolite Constellation Based on High-Altitude Balloons
## 8 Conclusions  
IPCBs are a novel pseudolite application with many advantages and unique features. Compared with traditional ground-based pseudolites and other air-based pseudolites, IPCB uses high-altitude balloons to achieve higher altitudes and wider coverage. Compared with pseudolites based on powered platforms, IPCBs can save energy costs greatly by utilizing buoyancy and wind. When bringing advantages to applications, these features also bring great challenges to IPCB geometry configuration.  
This paper proposes an IPCB geometry configuration planning algorithm that considers the unique features of the IPCB and implements simulations to verify the effectiveness of the proposed algorithm. Furthermore, this paper implements simulations with some typical IPCB geometry configurations and compares their performances.  
Simulations show that, in the vertical direction, it can achieve better performance to deploy IPCBs at the altitude of the local quasi-zero wind layer; if the expected service duration is short, IPCBs can be deployed at higher altitudes, and if the expected service duration is long, IPCBs can be deployed at the altitude of local quasi-zero wind layer. In the horizontal direction, the direction of local wind should be treated as an important factor in designing the initial constellation geometry configuration. A quasi-zero wind layer is helpful in improving IPCB geometry performance.  
In the future, attention can be paid to approaches to enhance robust algorithms and enhance tolerance to different environment models. Improvements in algorithm performance are also desired to realize real-time control.  
Conceptualization, Y.Q.; methodology, Y.Q. and S.W.; software, Y.Q.; validation, T.P. and H.F.; writing--original draft preparation, Y.Q.; writing--review and editing, S.W. and T.P.; visualization, Y.Q. and T.P.; supervision, S.W. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Key Research and Development Program of China (Grant No. 2022 YFB3901805).  
Data Availability Statement: Data are contained within the article.  
The authors declare no conflicts of interest.
# Secure Cloud Infrastructure: A Survey on Issues, Current Solutions, and Open Challenges
## 4 Security Issues in Cloud Computing Infrastructure
### Data-Level Issues
#### 4.1.2 Data Loss or Leakage Issues  
Data are transferred from data centers to the client's systems and are transmitted from one execution mode to multiple execution mode, which may cause data loss or leakage. Even though data are stored away from the client system, there could be a possibility of data loss or leakage. As a result, data leakage is becoming a critical security issue among the various security issues in the cloud environment [34]. The loss and/or leakage of data may be carried out by internal threat actors such as disgruntled employees, contractors, and other partners. Likewise, external actors could gain access to the cloud infrastructure and disclose, delete, or lock the data they may locate. This could be done with the aid of a wide range of tools and tricks such as malware, identity theft, and password brute force. To protect data in the cloud environment from being leaked, two main types of countermeasures are employed, namely encryption and watermarking. However, encryption cannot protect data at rest if intruders manage to gain access into the cloud using valid credentials. As such, it is imperative to scrutinize cloud access requests and ensure that they come from legitimate users.
## 3 Results and Discussion
### Fiber Length  
Figure 4a shows that as the fiber length increased, the output power of the 3.5 \(\upmu\)m laser increased and then decreased, and the best length of fiber was strongly related to the power of \(P_{1976}\). Under the current pump power level, a fiber of 5-15 m long was proper for the core pumped scheme. However, for the DWCP situation in Figure 4b, a fiber of about 15 m long was good for different pump powers. This was caused by the different pump absorbed rates in different schemes. For the DWP scheme, \(P_{1976}\) was absorbed much faster than \(P_{976}\) when propagating in the fiber, as shown in Figure 4c. Thus, at the latter part of the fiber, a 1976 nm laser did not have enough power, making the gain of the 3.5 \(\upmu\)m laser smaller than the loss, and the output power decreased. For a different \(P_{1976}\) power, the pump absorbed rates were similar, so the higher the power of \(P_{1976}\) was, the longer the fiber needed to deplete the pump. However, for the DWCP scheme, the \(\alpha_{1976}\) was much lower than that in the core pumped situation. In this case \(P_{976}\) was absorbed to a lower level first and caused the gain of the 3.5 \(\upmu\)m laser to be smaller than the loss, as Figure 4d shows. The absorbed rate of \(P_{976}\) did not change significantly along the power of \(P_{976}\), therefore this 15-m-long fiber would be suitable for a wide range of pump configurations. It is worth noticing that in the DWCP scheme, there was a significant amount of residual \(P_{1976}\). Because most 1976 nm lasers are transmitted in fiber cladding, which means they do not interact with Er\({}^{3+}\) ions, it is necessary to have a higher power level of \(P_{1976}\) than that in the DWP scheme in order to maintain the gain of the fiber. In Figure 4c,d, 10 W of \(P_{976}\) was chosen to show the drain of \(P_{1976}\) while 5 W of \(P_{976}\) was still used in other parts of this paper for consistency.  
Figure 4: Output power of a 3.5 \(\upmu\)m laser as a function of fiber length at 5 W of \(P_{976}\) and different powers of \(P_{1976}\) under (**a**) the DWP scheme and (**b**) the DWCP scheme. Laser power distribution of \(P_{976}\), \(P_{1976}\), and the 3.5 \(\upmu\)m laser under conditions of \(P_{976}\) power 10 W, \(P_{1976}\) power 20 W, fiber length 15 m (**c**) DWP scheme, (**d**) DWCP scheme.
## 4 Results in Practical Cases
### Results by Simulation Practical Cases
#### 4.1.3 UpfC Tests by Frequency Deviations  
One of the relevant objectives of this work was the robust behavior of the control system under the contingency of frequency deviation. For the ANN training, the distorted waveform patterns included different fundamental frequency values. The UpfC control performance was tested in two different ways. In the first test, the performance of the compensation system was analyzed in a range of frequencies between 45 and 55 Hz, in terms of _ITHD_ and _PF_. In the second test, the dynamic response was evaluated in case of frequency changes during system operation.  
Figure 10: Dynamic response with UpfC control, applying at \(t\) = 0.1 s a load change: linear load addition. Up: one phase load current. Middle: source currents, with _ITHD_ = 2.2% after the change. Down: one phase source current and voltage, showing the PF compensation.  
With the same system parameters of Table 2, the measurements for different frequencies were established. In previous subsections, with a 50 Hz frequency, it has been reported that the load _ITHD_ was 43% and the _PF_ was 0.583. Now, it can be observed in Figure 12 the graphical results of _ITHD_ and _PF_ versus frequency. The load _ITHD_ is high for every frequency, but the source _ITHD_ remains under 5%, with values under 4% inside the important interval proposed by the IEC Standard [31], from 47 to 52 Hz. Regarding the _PF_ achieved, the values are very close to unity, over 0.997 in the whole frequency interval, and over 0.999 in the interval from 47 to 52 Hz.  
In the second test, step changes of 0.5 Hz were applied during system operation. In particular, Figure 13 shows the behavior for an increase from 50 to 50.5 Hz at \(t=0.09\) s, and a decrease from 50 to 49.5 Hz at \(t=0.09\) s. The source current reaches steady state after one cycle.  
In conclusion, the UpfC control performance is robust enough under frequency deviations. It achieves the required compensation inside a wide frequency range and can respond quickly to the frequency changes.
# Equipment Health Assessment: Time Series Analysis for Wind Turbine Performance
## 2 Data and Methods
### Model Settings  
#### 2.3.1 Hyperparameter Search  
To obtain robust power prediction results over all wind turbines, we have conducted an exhaustive hyperparameter search in a grid search manner to understand the performance of the model settings over the dataset with different feature selections. The experiments were conducted separately for two network types: LSTM and FNN. In the end, we have settled on a small set of selected features which are described in Table 1 for the two model types.  
For the hyperparameters, we have not only investigated different model sizes but also tested different activation functions (i.e., tanh, ReLU, LeakyReLU, ELU, Sigmoid), learning rates, and error criterions (i.e., MSE, MAE). In addition, wind turbine power output is generally limited to a maximum and minimum possible power output and our models were often over- or underpredicting these limits. Therefore, we have also experimented with different output cutoff methods such as tanh, sigmoid, and a hard cutoff at the minimum and maximum. For the experiments presented in this study, we set our hyperparameters as stated in Table 2.
## 2 Materials and Methods  
### Experiment  
This study recruited twenty healthy adults (17 males, 3 females; 23.3 \(\pm\) 2.0 years old, 173.0 \(\pm\) 6.7 cm, 74.5 \(\pm\) 13.0 kg) from Yonsei University. Individuals with musculoskeletal problems were excluded from the study. The experiment received approval from the Yonsei University Mirae Campus Institutional Review Board (IRB) (1041849-202109-BM-139-02), and all participants provided written informed consent. An IMU sensor (Xsens Dot, Movella Holdings Inc., Henderson, NV, USA) was attached to the T7 position of each subject. The three-axis acceleration and the three-axis angular velocity signals were measured at a sampling frequency of 60 Hz. The subjects were required to perform four types of normal driving (straight driving, speed-bump driving, counterclockwise (CCW) roundabout driving, and clockwise (CW) roundabout driving) and one type of fall on an e-scooter (Ninebot Segway ES2, Xiaomi Technology Co., Ltd., Beijing, China, Figure 1). They were instructed to drive at a speed of 15 km/h in the straight section and 12 km/h during the turns. The fall involved a fall maneuver, where the subjects were instructed to drive at a speed of 15 km/h and then perform a fall (Table 1). Participants performed normal driving for a duration of 30 s to 1 min during each trial, covering distances of approximately 20 to 50 m. Data collection started prior to the participants' start and continued until they came to a complete stop. Each normal driving session was recorded at least three times. To balance the dataset with non-fall data, falls were intentionally recorded at least 10 times. The fall was executed by having the front wheel of the scooter make the initial impact, followed by the participant experiencing a second impact with the ground.  
The real-road surfaces like asphalt are not as smooth and are expected to produce more noise in the sensors. Additional experiments in a more realistic environment were conducted on roads. Only normal driving data were collected, since performing fall maneuvers on roads posed too much danger. Figure 2 illustrates a map of the route for a 3 min trial conducted on general roads. Ten participants repeated the course five times, with each trial consisting of one full lap.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Code** & **Description** & **Speed (km/h)** \\ \hline \multirow{4}{*}{Normal driving} & D1 & Straight Driving & 15 \\  & D2 & Speed-Bump Driving & 15 \\  & D3 & Counterclockwise Roundabout Driving (CCW) & 12 \\  & D4 & Clockwise Roundabout Driving (CW) & 12 \\ \cline{1-1}  & F1 & Fall & 15 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Experimental movements.  
Figure 1: The e-scooter and an IMU sensor (position: T7).
# Time Domain NMR in Polymer Science: From the Laboratory to the Industry
## 4 Conclusions  
The review aimed to present an overview of the most recent results obtained with low-field NMR in time domain, for the characterization of polymeric materials. Special attention has been drawn to the possibilities that this technique offers both for research and for the industry. Validation of theoretical models and characterization of the properties of new materials, especially when there are not many other techniques able to do it, for example for nanostructures, are possible. The sensitivity over the chemistry and modification of polymeric items is enough to enable the technology transfer in industrial contexts for ordinary controls.  
The most common methods to acquire information about phase composition, molecular dynamics, proton density, domains sizes, local order, diffusivity have been explained, taking into account sequences that measure relaxivity, multiple-quantum coherences, spin diffusion, as well as new methods that promise to be faster in determining relaxation times, such as wave free precession, or improvement of analytical elaborations with more complex models to exploit parameters that can be obtained with faster sequences to draw out further information. This point should be specially underlined in view of industrial applications, where the rapidity for results is fundamental.  
Several examples have been presented in order to show that TD-NMR is a very promising analytical tool to check the impact of internal and external factors on the structure and properties of polymeric materials. The results of low-field NMR experiments correlate very well with results obtained with more traditional techniques, such as swelling or mechanical analysis, but with the advantage of not being destructive and that they require far less sample quantity, thus enabling the evaluation on traces or directly on final products with unusual geometries. This could allow the a priori rational design of polymers and development of transformation processes to meet the requested macroscopic properties, acting on the microscopic ones, which could be an important breakthrough for industrial-scale production.  
Despite the already great achievements of TD-NMR, further development of sequences and analytical procedures will be necessary to match the tool performances with the routinely use, even for non-experts in the technique.  
D.B. thanks Trelleborg Coated Systems Italy S.p.A for the PhD scholarship.  
The authors declare no conflict of interest.
# Bridging the Gap: Enhancing Maritime Vessel Cyber Resilience through Security Operation Centers
## 1 Introduction
### _Maritime Digitalization_  
At the heart of this digitalization wave is the Internet of Things (IoT) which is enabled by a proliferation of sensors resulting in complex digital systems onboard modern vessels and on shoreside port infrastructure. The same digitalization wave is also key to the recent advancements in autonomous vessel development. To ensure their safe operation, autonomous vessels will be ever more reliant on sensor technology for propulsion control,route planning, situational awareness, and collision avoidance [4; 5]. The large amount of data being generated by these sensors means that both vessel and port operators have the opportunity to optimize their operations. Some of the innovative applications of maritime big data include remote monitoring of vessels, demand forecasting, predictive maintenance, and digital twin development [6]. A case example is the Port of Hamburg which utilizes data from more than 300 sensors to assist with vessel and port vehicle monitoring. These have been shown to contribute to an overall reduction in idle units which results in lower carbon emissions and increased port operation efficiency [7].  
The ever-improving connectivity levels and increasing IoT adoption have led to concerns from both nation-states and infrastructure operators on the need for better cyber resilience of critical infrastructure within the maritime domain, particularly vessels. This is because the 'air-gapped by default' status of vessels, necessitated by previously limited bandwidth availability, meant that onboard systems were not designed with cyber security as a consideration. The increased threat-attack surface means that a successful attack could have dire consequences on public safety, economic stability, and environmental concerns [8].  
To further reinforce these concerns, in early 2023, the DNV asked 800 maritime professionals what impacts of cyber-attacks they expect to see in the next 1-2 years. A total of 80% of respondents believed that a closure of a major port or waterway, 68% believed a vessel would run aground, 60% believed there would be a collision, and 56% believed there would be a physical injury or loss of life [9; 10]. When it comes to autonomous vessels, cyber-attacks have been ranked as one of the top hazards that they face [5].  
From a cyber criminal's perspective, such a threat landscape presents an opportunity to inflict maximum damage with minimal effort. There have been documented cyber-attacks on critical infrastructure in other safety-critical domains, such as the 2010 Stuxnet attack on an Iranian nuclear facility, the 2015 Ukrainian power grid hack, and the recent colonial pipeline ransomware attack in 2021 [11; 12].
# HPT: A High Spatial Resolution Multispectral Sensor for Microsatellite Remote Sensing
## 5 Conclusions  
The HPT on the RISING-2 microsatellite was developed to demonstrate the efficacy of high resolution multispectral remote sensing nano/microsatellite platforms. LCTF technology was applied for the first time to realize a compact multispectral spaceborne sensor. The advantages offered by the LCTF technology are reductions in the size, weight, and power consumption of the sensor, the flexibility of the spectral bands and data volume, and compatibility with off-nadir pointing. The RGB color and NIR multispectral images were acquired successfully by the HPT and processed by image analysis methods. LCTF technology, as demonstrated by its application in the HPT on the RISING-2 microsatellite, can be considered an innovative tool suitable for future multi/hyperspectral remote sensing by nano/microsatellites.  
This research was supported by the microsatellite research and development program of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. This research was also supported by the Japan Society for the Promotion of Science (JSPS) Core-to-Core Program, B. Asia-Africa Science Platforms. The scale-invariant feature transform algorithm, available from the OpenCV library, was used for feature matching. Landsat images were downloaded from the United States Geological Survey website.  
[PERSON] and [PERSON] conceived and designed the experiments; [PERSON], T.K., and K.Y. performed the experiments and contributed materials; [PERSON] analyzed the data and wrote the paper.  
The authors declare no conflict of interest.
# Q-Pandora Unboxed: Characterizing Resilience of Quantum Error Correction Codes Under Biased Noise
## 6 Strategies for Optimal and Scalable Code Selection
### Resource Requirement for Fault Tolerance  
Our findings prompt pivotal questions: Is it always essential to operate surface codes at their maximum distance and rounds? Can we design adaptable surface codes with dynamic parameters for various noise types and models?  
In reality, the achievement of true fault tolerance involves maintaining a low, albeit non-zero, error rate. For a quantum computer dominated by specific types of errors or noise models, understanding the system's targeted logical error rate and noise characteristics allows us to optimize surface code parameters. This will reduce unnecessary qubit and gate overhead. Different quantum hardware may experience varying types of errors. Consequently, it is crucial to customize QECC parameters, i.e., the distance and number of qubits, to optimally benefit each unique system. Table 2 provides the minimum distance  
Figure 7: Logical error rate vs. number of rounds for rotated surface codes of (**a**) distances 3 and 5 under a physical noise level of \(10^{-4}\). (**b**) Distances 7, 9 and 11 under a physical noise level of \(10^{-3}\). Subfigures (**c–e**) show magnified views for distances 5, 9, and 11.  
and qubit requirements for achieving fault tolerance (logical error rate \(<10^{-9}\)) at a physical noise level of \(10^{-3}\) using rotated surface codes.  
As shown in Table 2, the resource demands for implementing surface codes differ based on the dominant error type in a quantum hardware system. Among the errors, reset and readout errors are the least resource-intensive, followed by depolarizing errors, and lastly, gate errors, which require the most resources. This ranking is consistent across various types of quantum codes, including repetition codes, unrotated surface codes, and rotated surface codes.  
Similar to the error types, when a specific noise model predominantly characterizes quantum hardware, there is a corresponding ranking in terms of resource requirements for surface code implementation. The phenomenological model requires the fewest resources, followed by the code-capacity model, and finally, the circuit-level model, which is the most resource demanding. This order is universal and applies to repetition, unrotated, and rotated surface codes alike.
###### Abstract  
The spatiotemporal change characteristics of Cultivated Land Productivity (CLP) are imperative for ensuring regional food security, especially given recent global warming, social development and population growth. Based on the hypothesis that the Gross Primary Productivity (GPP) is a proxy of land productivity, the Moderate Resolution Imaging Spectroradiometer (MODIS) data with 500-m spatial resolution and 8-day temporal resolution was employed by the Vegetation Photosynthesis Model (VPM) to calculate GPP in Jilin Province, China. We explored the level of CLP using the GPP mean from 2000 to 2018, and analyzed the changing trend and amplitude of CLP in the whole study period using both Theil-Sen median trend analysis and the Mann-Kendall (MK) test, and forecasted the sustainability of CLP with the Hurst exponent. The trend result and the Hurst exponent were integrated to acquire the future direction of change. The results revealed that: (1) The CLP level was generally high in the southeast and low in the northwest in cultivated land in Jilin, China. The area with the lowest productivity, located in the northwest of Jilin, accounted for 15.56%. (2) The majority (84.77%) of the area showed an increasing trend in 2000-2018, which was larger than the area that was decreasing, which accounted for 3.97%. (3) The overall change amplitude was dominated by a slightly increasing trend, which accounted for 51.48%. (4) The area with sustainability accounted for 33.45% and was mainly distributed in the northwest of Jilin. The area with anti-sustainability accounted for 26.78% and was mainly distributed in the northwest and central Jilin. (5) The Hurst exponent result showed that uncertain variation of CLP is likely to occur in the future over the entire region, and the central region is prone to display degeneration. Therefore, the results of this study indicated that quality improvement policy could be implemented for the middle-to-low yield fields in northwest Jilin, and dynamic monitoring and protection measures could be implemented for the areas with uncertain future changes and decreasing sustainability.  
sustainability; cultivated land productivity; GPP; time series analysis; Mann-Kendall; Hurst exponent; MODIS +
Footnote †: journal: Journal of Sustainable Energy