esa-sceva/satcom-chunk-collection huggingface dataset:
# Perceived Usefulness of a Mandatory Information System
## 5 System Design and Development  
The \"Slot\" information system was developed to manage educational activities within an Israeli governmental organization. The system's architecture follows a modular design to ensure scalability and flexibility. Below are the key components and their functionalities:  
* User Interface (UI): The UI was designed using responsive web design principles to ensure accessibility across various devices. It provides intuitive navigation and user-friendly interactions.
* Backend Infrastructure: The backend was developed using a robust framework (e.g., Django) to handle data processing efficiently. It integrates with a relational database management system (RDBMS) to ensure data integrity and support complex queries.
* Security Measures: Given the sensitivity of the data, the system incorporates advanced security protocols, including encryption, multi-factor authentication, and regular security audits.
* Development Process: The development followed an agile methodology, allowing iterative improvements and continuous feedback integration from stakeholders. Regular sprint reviews and testing phases were conducted to ensure the system met user requirements and performed optimally.
* Technical Specifications: The system is hosted on cloud infrastructure to leverage scalability and reliability. It utilizes RESTful APIs for seamless integration with other organizational systems.
* Rationale for Design Choices: The modular architecture was chosen to facilitate future enhancements and maintenance. The use of an agile methodology ensured that the system remained aligned with the dynamic needs of the organization.  
By incorporating these details, the aim is to provide a clear understanding of the system's design and development process, thereby addressing the reviewer's concerns about the reliability of the research.
## 3 Results and Discussion
### Factors Influencing the Tool Wear
#### 3.2.2 Influence of Drilling Parameters on the Tool Wear  
Figure 9 is the VB value at different drilling parameters. When the feed rate was the same, the higher the cutting speed, the longer the machining distance of the cutting edge in unit time, and the more severe the tool wear, as seen in Figure 9a. At the cutting speed of 85 m/min, machining about 100 holes was the dividing point of the severe wear stage, and the VB of the drill bit rose rapidly.  
When the cutting speed was the same, the higher the feed rate, the greater the material removal rate of every cutting edge, and the more severe the tool wear, as shown in Figure 9b. When 200 holes were drilled, VB was 243 m at the low feed rate of 30 mm/min; at the high feed rate of 70 mm/min, VB reached 337 m. When the feed rate was higher than 70 mm/min, the drill bit needed to be sharpened or changed to ensure the machining quality and the stability of the drilling system.  
Therefore, the feed rate, cutting speed and the number of holes were the main factors influencing the tool wear and should be considered as the input data of the prediction model.  
Figure 9: VB at different drilling parameters: (**a**) different cutting speeds; (**b**) different feed rates.
# Lunar Calendar Usage to Improve Forecasting Accuracy Rainfall via Machine Learning Methods
## 4 Conclusions  
The lunar calendar model demonstrated higher accuracy in its prediction, exhibiting smaller errors (MAPE and MBE (mean bias error) values), whereas the Gregorian calendar model had somewhat larger errors and tended to underestimate the values. The MAPE trend for the four methods and two calendars increases with forecast length, with lunar calendar-based forecasting generally yielding a lower MAPE than the Gregorian calendar. For the BiLSTM method, the MAPE at a forecast length of 12 months is similar for both calendars. However, at forecast lengths of 16 and 18 months, lunar calendar forecasts tend to show a larger MAPE compared to the Gregorian calendar. This study compares MAPE for forecasting using the lunar and Gregorian calendars across various forecast lengths, with the smallest MAPE observed at a forecast length of 4 months and the largest at 24 months. For the Gregorian calendar, the smallest MAPE occurs at forecast lengths of 3 and 6 months, while the largest is at 24 months. Figure 5 illustrates the MAPE of different methods: GRU, 2-stacked GRU, BiGRU, and 2-stacked BiGRU. The lunar calendar approach consistently shows a smaller MAPE than the Gregorian calendar for forecast lengths of 3, 4, and 6 months, while the BiGRU and 2-Stacked BiGRU methods produce similar MAPE values at the 12-month forecasts. The comparison of MAPE between the two calendars across the four GRU methods reveals that the smallest MAPE (15%) occurs at a forecast length of 4 months, with the largest MAPE (35%) at 24 months. For the Gregorian calendar, the smallest MAPE is observed at forecast lengths of 3 and 6 months, while the largest MAPE is at 24 months. Consequently, the analysis based on the lunar calendar tends to be more accurate, as the longer time-series data it provides offers more detailed insights. Therefore, the lunar calendar may lead to better analysis results compared to the Gregorian calendar. Model performance: Stacked models, such as stacked LSTM and stacked BiLSTM, generally outperform their non-stacked counterparts. Additionally, bidirectional models like BiLSTM and BiGRU frequently outperform conventional LSTM and GRU models. The Gregorian calendar data tend to show greater prediction errors than the lunar calendar, likely due to differences in time patterns or data properties. Although all models exhibit significant prediction errors, the variations among them help identify the most suitable models for this type of data. For these predictions, stacked LSTM and stacked BiLSTM models are likely to yield the best results.  
Not applicable.  
The data presented in this study are available upon request from the corresponding author. The authors would like to acknowledge to Universitas Padjadjaran for funding this research. The authors declare no conflicts of interest.
## 1 _Article_
###### Abstract  
Interactions between internal tides and mesoscale eddies are an important topic. However, examining modulations of internal tides inside a mesoscale eddy based on observations is difficult due to limited observation duration and inaccurate positioning within the eddy. In order to overcome these two practical limitations, we use the active navigation capability of underwater gliders to conduct measurements inside the targeted eddy and utilize the wavelet approach to investigate modulations of internal tides with diurnal and semidiurnal periods inside the eddy. Based on the wavelet's frequency-time locality, we construct scale-specific networks via wavelet coherence (WC) from multivariate timeseries with a small sample size. The modulation of internal tides is then examined in terms of temporal evolutionary characteristics of the WC network's topological structure. Our findings are as follows: (1) the studied eddy is vertically separated into two layers, the upper (<400 m) and lower (>400 m) layers, indicating that the eddy is surface intensified; (2) the eddy is also horizontally divided into two domains, the inner and outer centers, where the modulation of internal tides seems to actively occur in the inner center; and (3) diurnal internal tides are more strongly modulated compared to semidiurnal ones, indicating the influence of spatial scales on the strength of interactions between internal tides and eddies.  
internal tides; mesoscale eddies; underwater glider; wavelet coherence; complex network theory 2024 14 1001 1
# Advanced Scheme to Generate MHz, Fully Coherent FEL Pulses at nm Wavelength
## 3 Resonator Considerations
### Reflectivity Adjustment  
The most direct way to control the net gain is to adjust the resonator reflectivity. In this case, initially the reflectivity (\(R_{build-up}\)) is as high as possible to enable a fast build-up of the power and then, when the desired peak power level is reached, the reflectivity has to drop to the value \(R_{equil}\), which ensures equilibrium between losses and power gain. The reflectivity applied during the build-up process, \(R_{build-up}\), is determined by the maximum total reflectivity allowed by the mirrors, and the maximum change in reflectivity that can be supported by a filter within the time separation of two consecutive bunches. The larger the difference in reflectivity \(\Delta R=R_{build-up}-R_{equil}\) is, the higher the net gain and the faster the steady-state regime will start, as shown in Figure 7a. For the present setup of resonator and beam parameters shown in at Table 1, the reflectivity at equilibrium is \(R_{equil}=10.6\%\)  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Electron Beam Parameters** & \\ \hline Energy & 1350 MeV \\ Energy spread & 120 keV \\ Peak current & 1 kA (flat-top) \\ Pulse duration & 300 fs \\ Normalized Emittance & 1 mm \(\cdot\) mrad \\ \hline \hline \end{tabular}
\end{table}
Table 1: Electron beam parameters used in simulations.  
including the losses in the monochromator. With \(R_{build-up}=14\%\), 46 passes are required in the build-up regime in order to reach a relative energy modulation of \(A=7\), while a reflectivity of \(R_{build-up}=12\%\) requires 99 passes. It is also possible to apply the reflectivity change in steps if a fast change is not possible. For instance, for the reflectivity change required as shown in Figure 7b, it is possible to apply the \(\Delta R=3.4\%\) (from \(R_{build-up}=14\%\) to \(R_{equil}=10.6\%\)) in steps of \(\Delta R=0.34\%\) in 10 passes. In the case of a burst-mode of operation, the number of steps must be reasonably small compared to the number of bunches at the steady-state. In the case of a continuous wave operation, these steps can be as small as required by the hardware limitations.  
In practice, the reflectivity change can be implemented by adding a filter in the return path of the radiation field. A total reflectivity change of several percent is currently not possible to be applied within 1 us, but would be possible in several steps during a transition time. For this reason, this method would be an option in CW machines, as it is currently unlikely to function in burst-mode in view of time constraints.
## 2 User Scenario  
The following user scenario is an example of how centimeter-level positioning, combined with smartphone multimedia and networking capabilities can be used to effectively deliver a variety of Location Based Services. In a history museum, there is a notice at the entrance that says the museum is equipped with a smartphone virtual tour/navigation infrastructure. There is a QR code under the message. The user scans the QR code that installs the required app. The system then enhances the user experience in the following ways:  
1. The user notices a small 12 th century vase and decides to learn more about it. S/he points the phone at the vase to initiate directional querying. The vase is located high up on a shelf in a row among other vases. Thanks to high accuracy positioning combined with accelerometer (tilt) and digital compass (azimuth) readings, the system is able to identify the correct vase. The smartphone displays a page with a brief description of the exhibit followed by links to relevant text, audio, video, and other interactive material. The user looks at images of the excavation site and even watches a video of the exhibit being excavated, taking advantage of the powerful multimedia capabilities of their own smartphone.
2. The user notices a painting they have seen before. S/he does directional querying and finds out it is by [PERSON], an impressionist. The user decides to read more about impressionism and accesses a Wikipedia page through a 3G connection on their mobile phone. S/he decides that they want to see more impressionist paintings and requests the museum app to guide him. The system generates the most efficient route to cover all the relevant paintings starting from the user's current location. Thanks to high accuracy positioning, the system is able to map on the display the location of the next painting, making navigation more comfortable and avoiding confusion[PERSON] Some notable impressionists are not represented in this museum, however the user is able to see their works through high-resolution digital versions of their paintings displayed on their smartphone[PERSON]
3. The user feels the need to find a bathroom. S/he presses the corresponding button in the mobile museum app. The system finds the closest bathroom and guides them there by displaying a map, current location, route, and directions.
4. The user realizes that they need assistance from museum staff. S/he presses the corresponding button and is informed to stay put and that they will be assisted shortly. The system locates the nearest staff member, who also has a smartphone with a staff version of the app, and gets quickly directed to the location of the user in need.  
Altogether, the new museum experience combines immersion with the tangibility of a traditional museum visit, plus the flexibility, richness, and comprehensiveness of online surfing. While other features of the system can make the visit more comfortable and safe.
## 5 Experimental Result  
This section first describes the experimental setup used to test the LSNN implementation presented in the previous sections. Then, it reports the results of the design trade-off characterisation for the proposed eLSNN. In particular:  
* Section 5.1 describes the hardware-in-the-loop system we implemented to profile the runtime and energy performance of the SHM application.
* In Section 5.2, we study the accuracy of the trained eLSNNs (current-driven and event-driven). We evaluated the MCC on the test dataset for the first order hyper-parameters, which impact the energy and computational efficiency of the eLSNN implementation. The first-order hyper-parameters are the input number (\(I\)) and inference ticks (\(t\_inf\)) of the networks.
* In Section 5.3, we study the impact of the eLSNN performance (\(\#execution\) cycles) considering the most accurate networks for each eLSNN version (current-driven and event-driven). We also considered different combinations of the first-order parameters as a function of the activity factors of the eLSNNs (number of non-zero elements (spikes), both in the input (\(x\)) and hidden/recurrent layer \(z\)).
* In Section 5.4, we perform a complete characterisation of the SHM sensing node firmware for a network implementation having median activity-factors. This corresponds to a typical behaviour of the sensor node for a real SHM application in terms of execution time and energy-consumption.
## 1 Introduction  
DoS (Denial of Service) attacks diminish a particular system's network bandwidth and computational resources by overloading it with malicious traffic, blocking it from providing normal services to authorized users. A DoS attack is a cyber-attack in which an attacker attempts to make systems and servers inaccessible, preventing consumers from accessing servers and resources. DDoS (Distributed Denial of Service) [1] takes things a step further on a wider scale. Distributed Denial of Service (DDoS) attacks are DoS attacks that are executed in a distributed way to increase the resource usage for one or more targets [2].  
As seen in Figure 1, DDoS attacks size control of the majority number of compromised systems, known as a botnet, and execute coordinated attacks on the target machine. DDoS attacks are developing and increasing in magnitude, frequency, and complexity in tandem with the introduction and growth of innovative Web-based technologies. Companies confront possible network risks that might have serious consequences for their activities, such as outages, data theft, or even blackmail threats from cybercriminals [3].  
Measures for DDoS mitigation should have been performed in the case of DDoS attacks, as described in [4]. Before any mitigation strategies can be used, DDoS strikes must first be detected. DDoS attacks were initially detected by traffic engineers using criteria they had written. This strategy appears to have fallen behind the changing and developing pattern of DDoS attacks. Academics and industry are studying the prospect of implementing machine learning/deep learning (ML/DL) for DDoS attack detection as ML/DL unlocks its potentiality in several domains. In identifying risks, conventional manual approaches have limited performance and a high latency. Attacks can be caught faster rapidly and effectively using machine learning techniques like Naive bayes Bayesian, K-nearest neighbors, and support vector machine [5]. In machine learning, features for classification should always be chosen by humans or by feature selection algorithms. Selection of features, on the other hand, is an essential element of DL. Deep learning methods like CNN and recurrent neural networks use a succession of nonlinear processing elements to learn several levels of data interpretation from a large number of labeled data. As a result, DL can be a useful technique for DDoS attack detection [2]. DDoS detection using machine learning and deep learning has been shown to be successful. Section 2 will look at some prominent cases of ML/DL use for DDoS attack detection. We use the Bi-Directional Long Short-Term Memory (BI-LSTM) after considering various possibilities.
## 2 Materials and Methods  
### Study Population  
The present multi-center retrospective case series study was performed at three different private clinics (Table 1), in compliance with the principles of the Declaration of Helsinki on medical protocol and ethics. Twelve patients who met the inclusion criteria were selected for the study. Healthy patients requiring single or double tooth extraction with the vestibular bone intact or with a fenestration were chosen, for a total of fourteen sites.  
The inclusion criteria were as follows:  
* Age \(>\)18 years old;
* General good health (ASA I-II);
* Adequate oral hygiene (full mouth plaque score \(\leq\)20%, full mouth bleeding score \(\leq\)20%);
* Presence of one or more hopeless teeth requiring extraction.
* The exclusion criteria were as follows:
* Pregnancy or lactation;  
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Center/Case** & **Sex/Age** & \begin{tabular}{c} **Tooth** \\ **Number** \\ \end{tabular} & \begin{tabular}{c} **Ridge Thickness** \\ **before (mm)** \\ \end{tabular} & \begin{tabular}{c} **Ridge Thickness** \\ **after (mm)** \\ \end{tabular} & \
\begin{tabular}{c} **Follow-up** \\ **Time** \\ \end{tabular} &
\begin{tabular}{c} **Difference** \\ **Loading** \\ \end{tabular} \\ \hline C1 case 1 & Female/31 & 21 & 10.00 & 11.00 & 6 months & 1.00 & yes \\ \hline C1 case 2 & Male/63 & 45 & 8.00 & 8.50 & 12 months & 0.50 & no \\ \hline C2 case 3 & Female/50 & 15 & 9.00 & 9.50 & 6 months & 0.50 & yes \\ \hline C2 case 4 & Female/50 & 14 & 9.40 & 9.50 & 6 months & 0.10 & yes \\ \hline C2 case 5 & Female/71 & 21 & 7.50 & 8.00 & 6 months & 0.50 & yes \\ \hline C2 case 6 & Female/63 & 23 & 6.40 & 6.80 & 6 months & 0.40 & yes \\ \hline C2 case 7 & Female/63 & 24 & 5.60 & 5.90 & 6 months & 0.30 & no \\ \hline C2 case 8 & Male/68 & 42 & 6.40 & 6.90 & 6 months & 0.50 & yes \\ \hline C3 case 9 & Male/62 & 21 & 7.18 & 7.20 & 8 months & 0.02 & yes \\ \hline C3 case 10 & Male/58 & 17 & 10.52 & 11.69 & 5 months & 1.17 & yes \\ \hline C1 case 11 & Male/68 & 24 & 10.10 & 10.70 & 6 months & 0.60 & yes \\ \hline C3 case 12 & Female/46 & 11 & 7.81 & 8.43 & 7 months & 0.62 & yes \\ \hline C2 case 13 & Male/77 & 24 & 12.00 & 12.70 & 6 months & 0.70 & yes \\ \hline C1 case 14 & Male/74 & 13 & 7.9 & 8.1 & 4 months & 0.20 & no \\ \hline \hline \end{tabular}
\end{table}
Table 1: C1: [PERSON]; C2: [PERSON]; C3: [PERSON].  
* Untreated periodontitis;
* Osteometabolic disease;
* Intravenous bisphosphonate therapy;
* History of chemotherapy or radiation therapy in the neck-head area;
* Heavy smoking (>15 cigarettes per day);
* Absence of buccal bone plate.  
The selected population was as follows:
* Age 31-77 years old;
* 7 men and 5 women.  
Written informed consent was provided by all patients for both the clinical procedure and participation in this study. Preoperative CBCT was performed. Patients were administered antibiotic prophylaxis starting the day before extraction with amoxicillin and clavulanic acid at 2 g per day for 6 days.
## 3 Results and Discussions
### Typical Samples of the Raw Data Collected During the Measurement Campaign
#### 3.2.1 Evaluated Measured Path Loss (MPL)
It indicates an increase with the increase in the Tx-Rx distance, which is consistent with the inverse square law, although a smooth exponential rise was not observed. The pattern depicts the influence of elevation and perhaps some other terrestrial features causing signal enhancements and degradation contrary to the theoretical expectations. In addition, it can be observed that there was no significant difference in their values from the DTBS up to 3 km. However, a significant difference was observed at distances between 3 and 10 km from the base station, with the wet season recording higher values. The need for DTBS operators and regulators to compensate for losses during wet season months in tropical environments is recommended.