esa-sceva/satcom-chunk-collection huggingface dataset:
# SSKM_DP: Differential Privacy Data Publishing Method via SFLA-Kohonen Network
## 2 Related Works
[18]proposed an enhanced t-closeness algorithm for multiple sensitive attributes. The algorithm applies the t-closeness [19] on the MSB k-anonymous clustering attribute layer (MSB-kaca) algorithm and uses the EMD method to avoid the probabilistic reasoning attack caused by bucking. [PERSON] et al. [20] proposed a new method of differential privacy protection based on neural networks, which combine differential privacy and neural networks to generate high-dimensional data satisfying differential privacy. The DP-OPTIC-BASED differential privacy protection method to balance the privacy protection capability and data utility to improve the availability of data was proposed [21]. However, this method is only applicable to numerical data. Therefore, using the idea of the machine learning model for reference, this paper proposes a differential privacy data publishing method (SSKM_DP) based on the SFLA-Kohonen network, which meets the requirements of differential privacy protection and improves the availability of published data compared to the algorithm in Table 1. SSKM_DP no longer uses the traditional clustering method to cluster data, but it introduces the clustering method of the Kohonen neural network, which avoids the defect of the traditional method requiring the artificial specified number of clustering, and makes the clustering more reasonable. Aiming at the problem of selecting the initial weight of the Kohonen network, the single-population frog leaping algorithm was introduced to optimize the initial connection weight of the Kohonen network to obtain the best initial weight. Considering that there is a complex correlation between insensitive attributes and sensitive attributes of data, the largest information coefficient is introduced as a measure of the correlation intensity. For non-sensitive attributes with relevance, noise is added to further protect sensitive information from disclosure so that the released data can meet the requirements of privacy protection and improve data utility to a large extent.
## 3 Results and Discussion
### Training of the FTSW Prediction Model
\begin{table}
\begin{tabular}{l l l l l l l} \hline \hline \multirow{3}{*}{**Input Variables**} & \multirow{3}{*}{**Look-Back**} & \multirow{3}{*}{**Output**} & \multicolumn{3}{c}{**Colinas do Douro**} \\ \cline{3-7}  & & & \multicolumn{1}{l}{**Validation Set**} & \multicolumn{1}{l}{**Test Set**} \\ \cline{3-7}  & & & \multicolumn{1}{l}{**\(R^{2}\)-Score**} & \multicolumn{1}{l}{**RMSE**} & \multicolumn{1}{l}{\(R^{2}\)**-Score**} & \multicolumn{1}{l}{**RMSE**} \\ \hline \multirow{3}{*}{Month, ETo, RH (avg), rainfall, irr} & 3 & 3 & 0.61 & 0.60 & 0.58 & 21.37 \\ \cline{2-7}  & 5 & 5 & 0.80 & 0.46 & 0.74 & 16.77 \\ \cline{2-7}  & 7 & 7 & 0.32 & 0.89 & 0.90 & 10.35 \\ \hline \multirow{3}{*}{Month, ETo, RH (avg), rainfall, irr} & 3 & 3 & 0.69 & 0.57 & 0.64 & 19.68 \\ \cline{2-7}  & 5 & 5 & 0.44 & 0.80 & 0.81 & 14.54 \\ \cline{1-1} \cline{2-7}  & 7 & 7 & 0.31 & 0.88 & 0.92 & 9.19 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: The performance of the BiLSTM-trained model to predict the FTSW with different look-backs and lengths of the output. Figure 9: Comparison between the observed and predicted values of the FTSW. The results of the model with the Vapor Pressure Deficit (VPD) as the input are shown in (**a**,**c**), while the results of the model without this variable as the input are shown in (**b**,**d**). A perfect fit is represented as a yellow line.
## 4 Results
### Denoising Results for Real Data
#### 4.2.2 Denoising Results for In Vivo Human Cardiac DTI
We also find that only LPCA, BM3D, and Node2 Node can generate small residual values in the DW images, but the FA values derived from BM3D are little higher, and the TA maps obtained using LPCA and BM3D are worse than those of our method (a little noisy.) Figure 6: Denoised results for in vivo human cardiac DTI acquired at end systole phase with different methods. The 2 nd and 7 th rows demonstrate the zoomed-in red rectangle regions for DW images and fiber orientations, respectively. DIP and P2S achieve the worst performance.
# Intelligent Evaluation of Chinese Hard-Pen Calligraphy Using a Siamese Transformer Network
## 2 Proposed Dataset  
Currently, deep learning-based network models rely primarily on data-driven approaches. Existing publicly available Chinese character datasets are mainly used for offline or online handwritten Chinese character recognition tasks. The HCL2000 dataset [27], an offline, handwritten simplified Chinese character dataset, encompasses 3755 frequently used primary-level characters. It contains handwriting samples contributed by 1000 participants from various age groups, genders, educational backgrounds, and occupations. Another dataset, HCD [28], is also an offline primary-level Chinese character dataset. It is categorized into ten subsets based on the quality of handwriting and contains samples written by 1999 participants, doubling the size of HCL2000 dataset. The CASIA-HWD dataset [29] includes samples of handwritten Chinese characters and texts, comprising 7185 Chinese characters and 171 English letters, digits, and symbols, gathered from 1020 individuals. This dataset is applicable for both offline and online handwritten Chinese character recognition tasks. However, there is currently a lack of publicly available datasets specifically designed for evaluating hard-pen writing, necessitating the creation of such a dataset. To facilitate network training and enhance model accuracy, annotation of the dataset is essential. Moreover, to improve the generalization capability of detection and recognition models, data augmentation is required.
# Noise Reduction in CWRU Data Using DAE and Classification with ViT
## 3 Application Example
### Classification Result Analysis
#### 3.4.1 Comparison with Machine Learning-Based Classification Techniques  
[PERSON] classified the CWRU data set using several machine learning techniques. RF, XGBoost, Gradient Boost, AdaBoost, Extra Tree, and Majority Voting techniques were used for classification, and the classification performance was evaluated using various performance evaluation techniques such as Accuracy, Recall, and Precision [36]. When compared with Accuracy, which is the same criterion as this study, the Majority Voting technique was the highest at 97.91%, and the XGBoost technique was 90.62%. For other techniques, the accuracy was measured at 91 to 94%.
## 2 Materials and Methods
### Characterizations  
FTIR spectroscopy was executed by an FTIR-4100 (JASCO, Tokyo, Japan) spectrometer to investigate the structural features of SOMs. An FT-NMR spectrophotometer (JEOL, Tokyo, Japan) was applied for the proton/C\({}^{13}\) nuclear magnetic resonance (\({}^{1}\)HNMR (500 MHz) and \({}^{13}\)CNMR (125 MHz)) spectra and measured the chemical shift (\(\delta\)) in ppm, using tetramethylsilane (TMS) as an internal standard in the reference solvents of CDCl\({}_{3}\) and (CD\({}_{3}\))\({}_{2}\)SO. A XEVO TQ-S spectrophotometer was used to determine the mass spectra (MS) of synthesized SOMs. The UV-Vis (V-670 (JASCO, Tokyo, Japan)) and photoluminescence (PL, FP-6500 fluorometer, excitation wavelength: 480 nm) spectroscopies were utilized for investigating the optical behavior of SOMs. Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) were measured by a TA instrument (DSC-2910, Q-50) at the fixed scan rate of 10 \({}^{\circ}\)C/min under N\({}_{2}\) gas. The electrochemical cyclic voltammogram (CV) was evaluated by a WPG 100 Potentiostat/Galvanostat (WonaTech) with three electrode electrochemical systems, including a working SOM-coated glassy carbon electrode, saturated calomel reference electrode (SCE) and a counter electrode composed of platinum wire, using 0.1 M TBAPF\({}_{6}\) in acetonitrile as the supporting electrolyte at a scan rate of 150 mV/s. The surface morphologies of the blended thin films were analyzed by AFM in tapping and 3D mode, using an AFM Nanoscope instrument. To extract the photovoltaic parameters, the current density-voltage (J-V) characteristics of the solar cells were tested under 1 sun (AM 1.5 G, 100 mW/cm\({}^{2}\)) using the light source of a metal halide lamp (Phillips, 1000 W, Newyork City, NY, USA). The radiation power of the light was fixed by using a Si photodiode as a reference, calibrated at NREL (Golden, CO, USA).
## 6 Key Findings
### Open Challenges and Future Work
#### 6.2.5 Additional Improvements  
After carrying out the previously described work, other potential enhancements have been identified that could significantly increase the value of the proposed verification platform:  
* Users appreciated the implemented functionality for its straightforward operation. Section 4.3 provided insightful areas of improvement to the current state of the front-end. A future version of the platform should be aligned not only with standardized UX practices, but also with the aim of making DLTs as transparent as possible for non-experienced and non-technical users, which is crucial for future adoption and potential use.
* Section 2.5 analyzed the standardization efforts for digital identity and credential management. It was demonstrated that DIDs and VCs standards could be easilyadded to the platform to standardize the current operation. Additionally, a future version of the platform could aim for cross-border interoperability by being deployed in initiatives such as the EBSI, as the grade of trust in DLT-based applications is directly proportional to the number of stakeholders that take part of the network.
* A comprehensive smart contract audit extending beyond the formal assessment of the proposed system should be performed. For instance, Section 2.6 analyzed the regulatory compliance of the platform, which can be fully achieved with ZKPs. The integration of such technique within the platform was demonstrated.
* A thorough design should be carried out to explore the latest architecture proposals of the literature that aim for sustainability, performance and other scalability mechanisms in order to make the system robust for real scenarios.
* A thorough access control with standardized libraries should be added to strengthen the security of the platform.
* The database activity could be secured by the use of an oracle [123]. Such an oracle could be connected to the smart contract, so every interaction to the database would be registered on the decentralized ledger. Hence, this would provide an increased security to centralized databases, allowing for a progressive decentralization of current centralized systems.
## 2 ISP and Performance Indicators  
A typical ISP has two basic axis systems, the azimuth axis and the elevation axis; the pointing device is installed inside the elevation axis, and the elevation axis is located in the azimuth frame. A schematic diagram of the ISP is shown in Figure 1. The two-axis gyro is mounted inside the elevation frame, which is used to measure the angular velocity of the elevation and azimuth axes in the inertial space, and to realize the stabilization control of the ISP. The servo device is the basic drive transmission component to realize high-precision pointing control, which is mainly composed of key components such as the driver controller, motor, reducer, and encoder.  
This paper takes the elevation axis of the ISP as the research background, and the servo device of the ISP as the research object, to study the change law of the servo performance under the complex operating conditions of external and internal disturbances. The main indicators of the ISP are stabilization accuracy, minimum pointing speed, and maximum speed. The maximum speed is determined by the rated speed of the motor and the reduction ratio of the reducer, which has been considered in the design stage of the ISP and is not discussed in this paper. The minimum pointing speed essentially describes the degree of stability of the system speed, and this paper evaluates the output speed of the servo device in terms of speed stability. Stabilization accuracy is used to evaluate the stabilization performance of the pointing device under disturbance, and this paper proposes the concept of equivalent stabilization accuracy, which requires inputting the disturbance into the servo system in the form of command, and equating the stabilization accuracy of the system with the command-following error. The specific definitions are as follows.  
Figure 1: A schematic diagram of the ISP.
## 4 Application of NDT in Identification of Local Damage
### Field Testing and Geological Inversion  
Based on the calibration results obtained by laboratory testing, the GPR was applied for field investigation. The typical geophysical inversion results in grouting holes were obtained, as shown in Figure 9. Subsequently, the infrared camera was adopted to further detect the status of grouting holes filled with water and grout. The infrared detection results included two classes, as expressed  
Figure 8: The different patterns of grouting holes obtained from GPR detection results: (**a**) empty; (**b**) filled with water; (**c**) filled with grout.  
Figure 7: Laboratory Experiment: (**a**) the experiment model and detection equipment; (**b**) the procedure for detecting the conditions in holes.  
in Figure 10a,b. The characteristics of temperature distribution were uniform in the former case, thus indicating the current state of the structure is safe. However, the temperature distribution expressed an obvious low temperature boundary in the latter case, due to the influence of leakage water. In order to verify the reasonability of the derived method, manual testing in the field was carried out to check the actual status of leakage in the grouting holes. For example, the actual condition of a damaged position was checked, as shown in Figure 10c, which expressed great agreement with the detected results, shown in Figure 10b.
## 5 Results and Discussion
### RQ1: What Cyber-Attacks in the MSCN Have Been Reported in the Academic Literature?
#### 5.1.3 Taxonomy
In addition to comparing our taxonomy with alternative classification systems, it is important to link it with established cybersecurity guidelines, such as those presented in Table 1. As detailed in Section 2.2, the NIST cybersecurity framework outlines five core functions (identify, protect, detect, respond, and recover), which serve as the foundation for mitigating cybersecurity risks. Our taxonomy directly supports these functions by offering a detailed method for identifying and classifying the specific risks associated with cyber-attacks in the maritime sector. For example, the categorization of hacker groups and attack types in our taxonomy aligns with the identify function of NIST, helping stakeholders understand who might be targeting their systems and what methods they might use. Similarly, the focus on systems and technologies affected and the AIC triad helps maritime agents develop targeted protect and detect strategies. The inclusion of geopolitical impact and potential consequences provides insights into how maritime stakeholders should respond and recover from cyber-attacks, especially when dealing with nation-state actors or attacks that have broader geopolitical ramifications. The IMO guidelines, particularly IMO Resolution MSC.428(98), also emphasize the importance of cyber risk management within the safety management systems of maritime organizations. The five functional elements of the IMO's cyber risk management strategy (identify, protect, detect, respond, and recover) are aligned with the NIST framework and further supported by our taxonomy, which breaks down the risk landscape into specific, actionable categories. By mapping cyber risks across factors such as compromised systems, maritime agents impacted, and global consequences, our taxonomy provides a detailed tool for applying the IMO's guidelines in real-world maritime cybersecurity scenarios. RQ2: What Preventive and Mitigating Practices for Cyber-Attacks in the MSCN Are Reported in the Literature? The impact of cyber-attacks on MSCN agents has led to several studies identifying effective prevention and mitigation practices. This literature review identifies 18 practices, which are classified into three sections according to the framework developed by ref. [95]: managing information security, informing security policy, and raising cybersecurity awareness and training. Mitigation practices aim to decrease the likelihood of cyber risks before incidents occur, whereas contingency practices focus on minimizing the repercussions after an event has taken place [96].
## 3 Results and Discussion
### Material Removal Rate  
Material removal rates for all of the drilled holes are shown in Figure 7. The process becomes significantly faster with the increase in pulse length: the drilling is over six times faster with the longest pulse length compared to the shortest. The increase is fairly linear. Similar results have been published by [PERSON], who investigated the effect of pulse duration on drilling depth in the microsecond range, and [PERSON] et al., who investigated the same in the nanosecond range [34; 35]. No significant difference can be noticed between the cold-rolled sheets and the PBF sheets. Generally, the MRR is about 0-10% higher when PBF sheets were drilled, except in the 200 ns case, when the cold-rolled sheet was drilled 4% faster.  
Similar to the results in hole diameters, the significant increase in material removal rate following an increase in pulse length can be attributed to a longer interaction time between the laser pulse and the base material. As the laser pulse heats up and eventually melts a portion of the base material, the resulting melt pool will be ejected from the bottom of the drilled hole by vapor pressure. The longer the interaction time, the more material will be melted, and thus ejected. It is surprising how significant this effect is, given that the same average laser power was used for both 200 ns and 8 ns processing.  
Figure 6: Measured entry and exit hole diameters for the laser drilled holes.  
Compared with drilling with 200 ns pulses, six times more energy had to be used when drilling with 8 ns pulses. The excess energy likely heated up the base material, provided the beam was not reflected. However, compared with longer pulses, the melt ejection phenomenon could not last as long, since the pulses were much shorter. Instead, the majority of the pulse energy likely went into heating up the base material instead of material removal. As the pulse length was increased, a higher portion of the pulse energy was expended in actual material removal once the material was molten. This problem seems to exist only in the range of tens of nanoseconds to hundreds of picoseconds, because at ultrashort pulse regime (picosecond to femtosecond), the power density is so high that the material is directly vaporized.
## 4 Experimental Results and Performance Analysis
### Smart Collaborative Positioning: Selection of the Best RS
To properly analyze the impact of using the best satellites or the best RS in the CD algorithm, compare the following four functions and evaluate the performance in terms of sensitivity and complexity:  
* CD in function of best satellites and best RS \"CD/Best_Sat/Best_RS\",
* CD in function of best satellites and all RS \"CD/Best_Sat/All_RS\",
* CD in function of all visible satellites and best RS \"CD/All_Sat/Best_RS\", and
* CD in function of all visible satellites and all RS \"CD/All_Sat/All_RS\". For the CD process using the best RS and/or the best satellites, the algorithm described in Section 3.2 is used. In cases where all RS are used, the CD algorithm described in Equation (23) is used, in which the measurements of RS1 and RS2 are combined in the CD algorithm. The best RS is RS1, the best satellites are: SV 1, SV 6, SV 11, SV 17, SV 22, SV 28; and all satellites are: SV 1, SV 3, SV 6, SV 11, SV 17, SV 19, SV 22, SV 28, SV 30.
## 1 Introduction  
Frequent exposure to various digital devices, such as smartphones and computers, may cause humans to experience digital eye strain (including blurred vision and eye fatigue), which is commonly linked to eye-related diseases [1]. In addition to the use of digital devices, aging [2] is recognized to be a primary factor increasing the risks to eye health. While age-related macular degeneration is a leading cause of blindness in the population over 65 years of age, the number of macular degeneration patients is steadily increasing every year [3]. Therefore, the global market of vision care is dramatically on the rise, and it is expected to reach approximately US $74 billion by 2024 [4].  
Health-conscious consumers have recently shifted the focus of the food industry to functional foods with beneficial health effects, since the bioactive compounds in foods are recognized to be very effective in reducing the risk of disease incidence and preventing illness [5]; the foods for eye health and eyesight are no exceptions. As a type of carotenoid, lutein is a major pigment in the macular region of the retina [6]. In addition, since lutein has an antioxidant effect that removes free radicals, it is recognized to prevent damage to the retinal cells [7]. [PERSON], et al. [8] reported that lutein played a significant role in promoting the health of the eyes, reducing the risk of age-related macular degeneration. It was also reported that lutein had great abilities to block blue light and to positively affect immune responses and inflammation [9]. However, since lutein cannot be synthesized by the body, it must be obtained from the diet [10]. It is known that lutein is available naturally in fruits,cereals, and vegetables [11]. Marigold (_Tagetes erecta_ L.) is also recognized to be a rich source of lutein. Thus, marigold powder has been commercially used as a nutritional supplement in capsules and tablets [12]. However, the applications of marigold powder to food products are very limited. [PERSON] et al. [13] incorporated marigold powder (0.40-0.55%) to milk-based beverages whose physicochemical and sensory properties were characterized. The rheological changes of wheat flour by marigold powder were also reported [14]. However, there are no systematic studies about the processing performance of marigold powder high in lutein in a food system, which is typically subjected to a variety of processing conditions such as heat treatments and mixing with other ingredients. Consequently, the food industry may be discouraged to develop a variety of food products to maintain good eyesight and eye health.  
In this study, marigold powder was incorporated as a source of lutein into the formulation of fresh noodles for lutein fortification, and its functionalities were investigated in terms of thermo-rheological, structural, and antioxidant properties.