esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experiments  
### Datasets  
Experiments were conducted on two public datasets: HDFS [5], a distributed system log; and BGL [19], a supercomputer log.  
The HDFS log dataset is based on map-reduce jobs from running Hadoop with more than 200 AmazonEC2 nodes. It has 11,175,629 items of log information, including time (year, month, day, hour, minute, and second), source IP address, and data size. The block_id can be divided into 575,061 operation sequences, with 2.9% of them marked as exceptions by Hadoop domain-related experts.  
BGL was formed by the BlueGene/L supercomputer system at Lawrence Livermore National Laboratory (LLNL) [18]. Its 4,747,963 log messages include 348,460 logs regarded as anomalous. Unlike HDFS, BGL logs do not capture the block_id generated by each log event. Consequently, we must split the log messages into log sequences with sliding windows. Once there is an error log in a log sequence, it is deemed an exception.  
Log Anomaly Characteristics  
As computer systems continue to increase in complexity and size, complex log data and various types of anomalies become more common. A large-scale system will inevitably encounter failures that lead to changes in log patterns. Anomalies in log data sets refer to events that do not conform to the normal behavior pattern recorded over a certain period of time, which may be due to software errors, hardware failures, malicious attacks, or other reasons. The anomaly types of log data include log sequence anomalies, log event anomalies, and component value anomalies, as shown in Figure 8. A log sequence anomaly mainly refers to an obvious deviation or inconsistency between the sequence of log occurrences and the usual sequence. Abnormal log events mainly refer to content in the log that is inconsistent with normal situations, such as the appearance of unknown IP addresses or software version information. Component value anomalies mainly refer to component value information generated by logs that does not match normal situations, which may be caused by illegal acquisition of permissions or malicious attacks.  
If log anomalies in a system are not identified in a timely manner, they may lead to potential security risks and threats to the system, which can result in data breaches, system attacks, or malware infections.
## 3 Overall Design of the Communication Channel Reconstruction
### Synchronization  
To guarantee the correct action of differential protection, the current data has to be taken at the same time, and time difference between the protection relaying may lead to differential current and thus malfunctioning. In the suggested technique, Global Position System (GPS) is used for time synchronization. The two relay devices start to record the current signal after they receive pulse per second (PPS) signals and the current signals are sampled by the control of the corrected clock of crystal oscillators. In addition, the digital relays have the ability to modify the content of running data packets and each data packet storing sampled values has a corresponding timestamp in the synchronization field. The two relays on both sides continually check the synchronization field of the data packet and align the current values for differential elements.
## 3 Study of the Communication System
### Noise Resistance  
Both Matlab simulation and FPGA prototype testing results for the FM-ACSK digital chaotic communication system are shown in Figure 14. In the case of simulation, the BER curve pattern is smoother and shows slightly better noise resistance (for approximately 1 dB SNR) than BER curve obtained from the FPGA prototype tests. The fact that the prototype showed less noise resistance than the mathematical model is fully within expectations, as it is a more complex design, which also includes analog part. The irregular pattern observed in the FPGA BER curve is challenging to explain and requires further study. As the irregularities have repeating pattern, it is possible that they are related to the noise value distribution on fixed-point data bus taking one less or one more data bit and being constrained by the absolute limits of the data bus. It is an effect that is barely noticeable with large number of errors per test (several thousands) and more noticeable when there are few bit errors per test (hundreds). At the very least, it can be definitively stated that this irregularity is not due to limited statistics in the BER calculations. In the mathematical model simulations performed in Matlab Simulink, only 2000 data bits were used for most BER points, and 20,000 data bits for the four lowest BER points. In contrast, during the FPGA prototype tests, where performance speed is significantly higher, most BER points were calculated using approximately 1,563,000 transmitted data bits, with the number increasing to 473 billion data bits per point for higher SNR values and some BER points that initially raised concerns regarding accuracy. Further investigation might reveal these irregularities in Simulink model tests as well, if more dense SNR values with many more data bits per test to be taken.  
The first turning point of the FPGA prototype's BER curve from the FPGA prototype testing results (see Figure 14), at approximately 1.3 dB SNR, is most likely related to the FM demodulation threshold, where noise impact on the instantaneous phase is too strong for even partial recovery of information to be possible. With higher SNR values, the BER curve of the prototype mostly follows a trend where it drops with an increasing rate from more than 2 dB per decade to less than 1 dB per decade at highest SNR values. The data obtained allow us to predict the noise performance of the developed communication system.  
Figure 14: BER at different signal-to-noise power ratios for AWGN channel obtained from Matlab simulation and FPGA prototype tests of the FM-ACSK digital chaotic communication system.
## 2 Simulation Model
### Fluid Properties  
The model is set up to simulate a flow mixture made by a combination of oxygen, nitrogen, carbon dioxide, and water vapor. For each regeneration phase, the mass concentration \(w_{j}\) of each \(j^{th}\) chemical element is given as reported in Table 1. The mixture specific heat at constant pressure \(cp_{f}\), is calculated as a weighted sum of the specific heats, as in Equation 17. The specific heat of each \(j^{th}\) element is calculated using a 4\({}^{\text{th}}\) degree polynomial function with two temperature ranges. The mixtures are considered ideal gases, i.e., the specific gas constant of the mixtures \(R_{f}\) is a function of the chemical mass fraction and the molar mass \(MM_{j}\), as in Equation (18). The fluids density \(\rho_{f}\) can then be obtained using the equation of state for an ideal gas, as in Equation (19).  
The fluid specific heat at constant volume \(cv_{f}\) can be evaluated using the Mayer relation, as in Equation (20).  
\[cp_{f}\Big{(}T_{f}\Big{)}=\sum w_{j}\;cp_{j}\Big{(}T_{f}\Big{)}\quad\left[ \frac{\text{J}}{\text{kg}\cdot\text{K}}\right] \tag{19}\]  
\[R_{f}=8.314*\sum w_{j}/MM_{j}\quad\left[\frac{\text{J}}{\text{kg}\cdot\text{K }}\right] \tag{20}\]  
\[\rho_{f}\Big{(}T_{f}\Big{)}=p_{tot}/R_{f}T_{f}\quad\left[\text{kg}/\text{m}^{3}\right] \tag{21}\]  
\[cv_{f}\Big{(}T_{f}\Big{)}=cp_{f}\Big{(}T_{f}\Big{)}-R_{f}\quad\left[\frac{ \text{J}}{\text{kg}\cdot\text{K}}\right] \tag{22}\]  
The thermal properties of the solid domain, i.e., the refractories, are kept constant with temperature and along the regenerator height. It is assumed there exists a thermal conduction coefficient \(k_{s}\) equal to 5 W/m\({}^{2}\cdot\)K, a specific heat \(cv_{s}\) equal to 1200 J/kg\(\cdot\)K, and a density of 3500 kg/m\({}^{3}\).
# A Fuzzy-Logic-Based Load Balancing Scheme for a Satellite-Terrestrial Integrated Network
## 2 Materials and Methods
### The Fuzzy Evaluation Metric
The output fuzzy evaluation metric \(f\) is calculated by  
\[f=\frac{\sum w_{l}u_{l}}{\sum w_{l}}=\frac{\sum x_{i}y_{j}z_{k}u_{l}}{\sum x_{i} y_{j}z_{k}}, \tag{7}\]  
where \(l=(i-1)QR+(j-1)R+k\), \(i\in[1,P],j\in[1,Q],k\in[1,R]\). \(w_{l}\) is the weight of the \(l\)th rule calculated by the product method. In order to train the ANFN, multiple groups of user trajectories; SNR; relative speeds and data rate requirements at each time and location; and the average required bandwidth for a period of time, were generated via simulation. The ANFN was trained with these simulation data. The smaller the value is, the greater the impact is.
# Designed Circularly Polarized Two-Port Microstrip MIMO Antenna for WLAN Applications
## 2 Theory and Design
### MIMO-CP Antenna Design  
Figure 2 shows the proposed MIMO-CP antenna designed structure. Two single antennas were used to design the MIMO-CP antenna for WLAN applications. The two-corner, square-cut, square-shaped patch antenna is printed on the top side of the thick FR4 substrate. The FR4 substrate was not grounded and the air gap, ha, was inserted between the ground plane and the substrate. The height of the FR4 substrate (thickness = 1.6 mm, relative permittivity = 4.3 and tangent loss = 0.025). The length and width of the proposed MIMO antenna were \(22.5\times 50\) mm. The antenna was excited with a \(50\,\Omega\) coaxial cable, whose inner and outer parts were connected with the ground and patch. The edge-to-edge distance between the two MIMO antennas was \(0.227\lambda_{0}\). The CST microwave studio was used to simulate the antenna. The following sections present the design steps.  
Figure 1: (**a**) Single antenna geometry. (**b**) Simulated S11. (**c**) AR and Gain.  
Figure 2 gives the front and back views of a MIMO antenna. The geometry of the substrate was rectangular with a side length and width of \((L\times W)\). The gap between the ground and the patches was tuned to achieve the required impedance bandwidth and was kept at \(ha=3.5\,\mathrm{mm}\). The radiating elements consisted of two square patches in which a square-cut at the corner was used for CP. The length and width of the square-cut were \((ls\times ls)\). For the best MIMO antenna results, the edge-to-edge distance between the two patches was kept at \(d=12.2\,\mathrm{mm}\). The suggested antenna was designed with less return loss, high isolation (low mutual coupling), AR, and enough antenna gain, within the desired bandwidth impedance bandwidth. Various parameters of the MIMO antenna are shown in Table 1.
# Dynamic Matching of Reconstruction and Anti-Aliasing Filters in Adaptive Active Noise Control
###### Abstract  
Constrained by the computing power, adaptive active noise control systems often have a low sampling rate. Therefore, reconstruction filters and anti-aliasing filters with fixed parameters are generally adopted to eliminate the mirror noise and aliasing noise, respectively; however, they may boost the group delay of the system. A dynamic matching method based on dual sampling rates is proposed to dynamically adjust the parameters of the reconstruction and anti-aliasing filters, according to the characteristics of the primary sound source, for a compromise between high-frequency noise and group delay. In digital high-sampling-rate regions, data that include high-frequency information are analyzed regularly, following which the parameters of the reconstruction filters and those of the anti-aliasing filters are dynamically matched. In digital low-sampling-rate regions, the estimation of the secondary path transfer function is updated. The results of laboratory experiments show that the proposed method not only can suppress the mirror and aliasing noise for primary sound sources with different spectra, but can also effectively reduce the group delay and improve the noise reduction performance of a system.  
active noise control; anti-aliasing filter; multi-rate system; reconstruction filter +
Footnote †: journal:
# Transparent Redirections in Content Delivery Networks
## 2 State of the Art
### TCP Session Handoff  
To be able to perform a TCP session handoff to redirect an existing TCP session from the request router to a surrogate server, we must be able to predict what initial sequence number the surrogate server will choose during the TCP 3-way handshake phase, which is impossible without modifications to the TCP/IP stack on the surrogates. Another approach which was mentioned earlier is the TCP_REPAIR flag, which requires modifications on the endpoints, thus disallows the usage of commercial closed source solutions. To mimic the request router after a handoff, the IP addresses and the port numbers are re-written over the network. To keep the TCP session alive, such modifications must be applied to the sequence and acknowledgement numbers in the TCP header too. This approach could be achieved by creating a network element which can modify these values in the TCP segment. TCP session handoff requires further support from the network which could be possible thanks to the versatile possibilities of SDN (Software Defined Networking). Transparent redirection in CDN done by handing off the TCP sessions from a point of view of the visibility increases the security too, as it hides the topology behind a single IP address and does not exploit the addresses of surrogate servers to the public network.
## 5 Potential of the Data and First Results
### Profiles
#### 5.2.2 Evolution of Temperature Profile  
The evolution of the thermal structure of the ABL during the night from 26 to 27 February is shown in Figure 10. The observations were taken by the small multicopter UAV Bebop2 Met in a distance of roughly 20 m from the meteorological mast installed on the sea ice (Figure 1), and cover the time period from 17:38 UTC to 01:26 UTC (mean time of the ascent profiles). All profiles indicated a sharp, surface-based inversion reaching up to about 50 m. Above this level, the vertical temperature gradient decreased and eventually approached an isothermal gradient. The temperature above 150 m remained at roughly \(-9\,\mathrm{\SIUnitSymbolCelsius}\) to \(-8\,\mathrm{\SIUnitSymbolCelsius}\) for the entire 8 h period, with weak signs of warm air advection between 18:42 UTC and 19:50 UTC. The lowermost 50 m or so were, however, subject to rapid cooling, with temperatures at the surface decreasing from \(-14\,\mathrm{\SIUnitSymbolCelsius}\) to \(-22\,\mathrm{\SIUnitSymbolCelsius}\) after 23:04 UTC. During this event, the vertical temperature difference in the lowermost 20 m increased from values of around 2 \(\,\mathrm{\SIUnitSymbolCelsius}\) to 6 \(\,\mathrm{\SIUnitSymbolCelsius}\), causing a very strong static stability and inhibiting almost any vertical movement (see Section 5.3). The same behavior was also detected in the time series of profiles from the AMOR system which was operated roughly at the same time period (not shown here).  
Figure 10: Evolution of the temperature profile during the night of 26 to 27 February, observed by the Bebop2 Met UAV during ascent. The times in the legend refer to the mean times of each individual profile.
# Learning-Based Colorization of Grayscale Aerial Images Using Random Forest Regression
## 3 Results and Discussion
### Implementation and Performance
In the case of PSNR, the proposed method (Max: 35.0906, Min: 29.6542, Average (Avg): 32.8773) significantly outperforms those of [PERSON] et al. [1] (Max: 27.1564, Min: 23.5535, Avg: 25.9514), [PERSON] et al. [14] (Max: 29.1172, Min: 26.2594, Avg: 27.5596), [PERSON] et al. [15] (Max: 30.6962, Min: 27.1006, Avg: 29.3068), [PERSON] et al. [21] (Max: 32.6280, Min: 28.0476, Avg: 30.6694), and [PERSON] et al. [22] (Max: 31.5879, Min: 24.2211, Avg: 29.6766). The performance difference from the state-of-the-art methods ranges from 2.4626 to 7.9342 for the maximum PSNR, 1.6066-6.1007 for the minimum PSNR, and 2.1779-6.9259 for the average PSNR, which indicates high performance for all results, regardless of site. That is, it is possible to colorize images stably regardless of the object included in the image or the complexity of the included structure. Figure 8:0 Enlargement of site 4: our method retrieves color values well in this region, compared with other methods. The NCD of the proposed method (Max: 0.0707, Min: 0.1244, Avg: 0.0941) also show better performance than do [PERSON] et al. [1] (Max: 0.1408, Min: 0.2304, Avg: 0.1819), [PERSON] et al. [14] (Max: 0.1270, Min: 0.1722, Avg: 0.1561), [PERSON] et al. [15] (Max: 0.0963, Min: 0.1679, Avg: 0.1362), [PERSON] et al. [21] (Max: 0.0858, Min: 0.1422, Avg: 0.1148), and [PERSON] et al. [22] (Max: 0.1042, Min: 0.1801, Avg: 0.1231), in which the range of the improved performance difference is 0.0151-0.0701 for the maximum NCD, 0.0178-0.1244 for the minimum NCD, and 0.0207-0.0878 in the average NCD. This means that the degradation in color quality is lowest when performing colorization through the proposed method. In other words, both visual and quantitative evaluations confirm the superiority of the method proposed herein.
# Automatic Initialization Methods for Photonic Components on a Silicon-Based Optical Switch
## 5 Overall Performances of the IRIS Device
The figures reported in Figure 8 relate to the shortest optical path on chip (the input local port and the output line port were the closest to each other). Clearly, the performances were worsened when the pathway on chip was longer. The reason was because the optical signal had to propagate along longer pieces of waveguide and go through many more crossings. This, in turn, led to higher losses. By comparing the transmission spectra of the shortest and the longest optical path on the IRIS chip (Figure 9a), we realized an increase of 7.6 dB in the losses for the same wavelength channel. In fact, insertion losses rose up to \(31.4\pm 0.2\) dB, in the red curve. However, we could assign most of the loss increase to the presence of 48 additional crossings along the longest path (not to the propagation losses within the waveguides). This was consistent with the preliminary characterization of the IRIS building blocks, where we measured about 0.16 dB optical losses per single crossing [11]. Still in Figure 9a, we can see some side peaks rising form the noise plateau (especially in the black curve). This was due to some MRRs along the optical path which happened to be partially aligned, although all of the switching nodes should have been in the off-state by design, when not biased. This was because of inaccuracies introduced during the fabrication process. We could easily solve this issue by misaligning all of the switching nodes of the IRIS matrix in a preliminary step, before putting the device into operation. Of course this task could be addressed by exploiting the same optimization method discussed in the previous section. In fact, we could simply turn the search into a minimization problem, by looking at lowering the optical signal in the through port of the switching nodes. An example of such an operation is shown in Figure 9b, where a better channel isolation was retrieved after the misalignment of all the switching node but the one in the on-state (red curve). Figure 8: **(left)** Schematics of the light-paths on-chip when all 12 channels were added to a line port. **(right)** Channel-output spectra when the optical signal was injected from one local port and collected out-of-chip through an external detector. Each colored curve refers to a separate measurement, where only one wavelength channel at a time is added to the line port. Further measurements demonstrated that similar optimization performances could be achieved in all the other 11 wavelength channels. Clearly, this affected the energy budget needed to switch one wavelength channel, as more electrical power was used to keep the other switching nodes misaligned (about 20 mW per node).
## 5 Conclusions  
This study simulated various urban scenes using the DART model to investigate the impact of the urban geometry and background reflectance on the NDVI, and it also explored how to select a suitable FVC estimation method using the NDVI to estimate the urban vegetation component abundance when using space-borne multi-spectral data. Some insightful findings are the following:  
1. When building wall and roof materials are heterogeneous, the effects of material differences on the NDVI are essentially negligible if there is minimal or no shadow components within the mixed urban pixels in space-borne satellite images. Conversely, when shadow components are present, the effects are non-negligible (Section 3.2).
2. The NDVI of an urban mixed pixel is determined by a combination of the pixel's internal shadow components, which increase the NDVI, and the proportion of building area, which decreases the NDVI (Section 4). To enhance the accuracy of NDVI-based FVC algorithms, the ideal NDVI exclusively reflects the vegetation component and is not affected by buildings. When the H/W increases, the NDVI will be underestimated because of the reduced NIR reflectance caused by multiple scattering and reabsorption (Section 3.1), which will affect the accuracy of NDVI-based FVC algorithms.
3. Introducing the SVF to correct the NDVI has proven an effective means of estimating the urban FVC (Section 3.4). Further improvements in the FVC estimation accuracy may be achieved by combining this approach with the characteristics of the study area and the FVC algorithm selection recommendations (Section 3.3).  
Conceptualization, J.Y., Y.X. and H.C.H.; methodology, J.Y.; software, W.X.; validation, W.X.; investigation, W.X.; data curation, W.X. and L.F.; writing--original draft preparation, W.X., L.F. and J.Y.; writing--review and editing, J.Y., Y.X., H.C.H., M.M., R.L. and M.S.W.; visualization, W.X.; supervision, J.Y. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Grants by the National Natural Science Foundation of China (42271345, 42071394) and National College Students Innovation and Entrepreneurship Training Program (S202411078029, 202311078005). [PERSON] is thankful for the support from the MOST High Level Foreign Expert program (Grant No. G20202055010L) and the Chinese Academy of Sciences President's International Fellowship Initiative (Grant No. 2020 VTA0001). [PERSON]. [PERSON] thanks the funding support from the General Research Fund (Grant No. 15603920 and 15609421), and the Collaborative Research Fund (Grant No. C5062-21 GF) from the Research Grants Council, Hong Kong, China.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.
# Evolution of Access Network Sharing and Its Role in 5G Networks
## 3 Sharing of Optical Access Networks
### Logical Security
The OLT uses the Request_Registrator PLOAM message to progress the authentication of the ONT and the exchange of encryption keys. While attacks to the availability of the optical access system might at best be inconvenient, they are less insidious than attacks to integrity and confidentiality. The effect of unavailability are known immediately and can be fixed in real time. It can take months or years for attacks to integrity and confidentiality to come to light, with consequences snowballing significantly over time.