esa-sceva/satcom-chunk-collection huggingface dataset:
# Surface Morphology of Three-Dimensionally Printed Replicas of Upper Dental Arches
## 3 Results
### SLA Clinical Application--Case Report  
A 13-year-old boy with severe ID and motor delay, autism, growth delay, a high, narrow palate, widely spaced teeth, and vestibular eruption of the upper canines was referred from his dentist to the orthodontic department of the clinic (Figure 4a). This patient suffers from a rare disease--Kabuki syndrome--which is caused by a mutation in the KMT2D gene and is inherited in an autosomal dominant manner. Due to very complicated cooperation of the patient and a need for specialized orthodontic treatment of vestibular eruption of the maxillary canines, we used intraoral scanning and 3D printing to provide the patient with an appliance. Based on the treatment plan (Figure 4b), a fixed orthodontic appliance was applied in the upper jaw (Figure 4c). After 1 year of therapy, the treatment was successfully finished. The boy was not able to accept a conventional impression so an intraoral scan was prepared (Figure 4d). The digital file for the upper jaw was first converted into the STA file format (STL). The SLA 3D printer prepared a model from liquid polymer--dental SG resin (autoclavable, Class 1 biocompatible resin)--from a special resin tank during a light-based process (Figure 4e) in which the layers are polymerized by a laser beam (blue 405 nm laser). The sensor was then exposed to the laser light continuously for 5 s, and data points were recorded every 0.3 s. The laser was headed and regulated using two galvanometers. The height of one layer was 50 \(\upmu\)m. The SLA model was completed with an orthodontic splint (Figure 4f). An orthopantomogram and photo (Figure 4g,h) were used to check the results of successful multidisciplinary therapy.  
Figure 4: Orthodontic treatment based on intraoral scan and 3D print. (**a**) Boy with Kabuki syndrome—high, narrow palate, widely spaced teeth and vestibular eruption of the upper canines—before orthodontic therapy; (**b**) treatment plan; (**c**) intraoral scan of fixed orthodontic appliance in upper jaw; (**d**) intraoral 3D image of successfully finished treatment after 1 year of therapy; (**e**) intraoral scan converted into the stereolithography file format (STL) and 3D print SLA model from liquid polymer—dental SG resin; (**f**) model completed with orthodontic splint; (**g,h**) orthopantomogram and 2D photo after successful multidisciplinary therapy.
## 1 Introduction
In order to distinguish it from event-triggered, this sort of feedback is called pull-based event-triggered. The critical advantage of the pull-based strategy is to avoid continuous transmission requests. It is worth noting that there are still challenges remains in the investigated problem, such as how to design the pull-based event-triggered condition to determine the pulling instants, and can the circle formation problem of MASs over such interactive topology be solvable under the designed control law and event-triggered condition.The main contributions of this paper are listed as follows: firstly, combined with a pull-based event-triggered scheme, an alternative algorithm is designed to solve the circle formation problem for MASs with directed topology, where each agent obtains the state information of its neighbors and the weight function does not need a priori knowledge of any other parameters. Secondly, under the scenarios of discontinuous communication, a model-based self-triggered strategy is proposed based on the pull-based methods to reduce the number of control actions and communication without a significant performance reduction. At last, the existence of such a bound is a stronger result than just prove the absence of [PERSON] behavior. The remainder of this paper is organized as below. In Section 2, preliminary definitions, and the problem formulation are presented. A distributed pull-based event-triggered principle for MASs with directed topologies is designed in Section 3. Section 4 extend the pull-based event trigger method to the scenario of discontinuous communication to form a self-trigger circle formation control scheme. Simulation results are given in Section 5 before we conclude in Section 6.
## 3 Algorithm Design and Analysis
### TCP-SCTP Switch Process  
The third part compared the performance indicators of SCTP and TCP in the process of data transmission. Although SCTP had a higher throughput than TCP, TCP was superior to SCTP in terms of stability. Meanwhile, TCP was faster than SCTP connection during connection establishment. We proposed the TCP-SCTP algorithm, which alternated TCP and SCTP protocols in data transmission. The TCP-SCTP method judged performance of the protocol undergoing data transmission and decided whether to switch to another protocol for data transmission. The TCP-SCTP switch process could switch the current protocol to another protocol. The following is a detailed analysis and process design of TCP-SCTP switch process.
# Real-Time Localization of Epileptogenic Foci EEG Signals: An FPGA-Based Implementation
###### Abstract  
The epileptogenic focus is a brain area that may be surgically removed to control of epileptic seizures. Locating it is an essential and crucial step prior to the surgical treatment. However, given the difficulty of determining the localization of this brain region responsible of the initial seizure discharge, many works have proposed machine learning methods for the automatic classification of focal and non-focal electroencephalographic (EEG) signals. These works use automatic classification as an analysis tool for helping neurosurgeons to identify focal areas off-line, out of surgery, during the processing of the huge amount of information collected during several days of patient monitoring. In turn, this paper proposes an automatic classification procedure capable of assisting neurosurgeons online, during the resective epilepsy surgery, to refine the localization of the epileptogenic area to be resected, if they have doubts. This goal requires a real-time implementation with as low a computational cost as possible. For that reason, this work proposes both a feature set and a classifier model that minimizes the computational load while preserving the classification accuracy at 95.5%, a level similar to previous works. In addition, the classification procedure has been implemented on a FPGA device to determine its resource needs and throughput. Thus, it can be concluded that such a device can embed the whole classification process, from accepting raw signals to the delivery of the classification results in a cost-effective Xilinx Spartan-6 FPGA device. This real-time implementation begins providing results after a 5 s latency, and later, can deliver floating-point classification results at 3.5 Hz rate, using overlapped time-windows.  
electroencephalogram; epileptic EEG signal classification; epilepsy; epileptogenic focus; real-time implementation; FPGA 2020 10 827 10.3390/app10030827
## 2 Classification Algorithms Theory
### K-Nearest-Neighbors
In addition, it is very useful when dealing with not linearly separable data and/or when there is no model that fits it well enough. Moreover, it is accurate for simple regression and classification tasks, so usually, it does not need to be compared with better-supervised learning models when dealing with this kind of problem. Figure 2: Classification based on different values of \(K\). However, this algorithm also has some drawbacks, such as its accuracy depending on the data quality and being sensitive to irrelevant features. Furthermore, if there is a large quantity of data, the prediction time can be slower, turning it into a computationally expensive algorithm in some cases. As a summary of the behavior of the KNN algorithm, we provide the pseudo-code shown in Algorithm 1, which is an interpretation of the algorithm developed by [PERSON], [PERSON], and [PERSON] [32; 33]. ```
Input:\(x,l,s\) // \(x\) : training data; \(l\) : label; \(s\) : sample to classify for\(i\) to training data size do:  Compute the distance \(d(x_{i},s)\) endfor  Select the desired number \(k\) of nearest neighbors  Sort the distances by increasing order  Count the number of occurrences of each label among the top \(k\) neighbors Output: Assign to \(s\) the most frequent label \(l\)
```  
**Algorithm 1** KNN Pseudo-code
# A Review on Standardizing Electric Vehicles Community Charging Service Operator Infrastructure
## 6 Open Issues and Research Challenges/ Future Challenges and Research Opportunities
### Power Supply Quality  
_What is the challenge?_  
Power supply quality is one of the critical aspects that need to be considered while ensuring the charging safety of the EV. Different measures are responsible for the poor power supply quality, i.e., high voltage load, harmonic fluctuations in voltage, current, etc., causing EV charging distortion. So, the power supply needs to be improved to improve EV charging efficiency.  
_Possible solution: Battery management system_  
A battery management system is a plausible solution to monitor parameters such as high voltage load, harmonics fluctuation, current, etc., which affect the quality of power supply to the EVs. Monitoring is required to maintain the battery voltage and current level to ensure controlled EV charging.
# Analysis of Key Issues on GNSS-R Soil Moisture Retrieval Based on Different Antenna Patterns
###### Abstract  
GNSS-R (Global Navigation Satellite System-Reflectometry) has been demonstrated to be a new and powerful tool to sense soil moisture in recent years. Multi-antenna pattern and single-antenna pattern have been proposed regarding how to receive and process reflected signals. Great efforts have been made concerning ground-based and air-borne observations. Meanwhile, a number of satellite-based missions have also been implemented. For the in-depth study of soil moisture remote sensing by the technique of GNSS-R, regardless of the extraction methods of the reflected signals or the types of the observation platform, three key issues have to be determined: The specular reflection point, the spatial resolution and the detection depth in the soil. However, in current literatures, there are no comprehensive explanations of the above three key issues. This paper conducts theoretical analysis and formula derivation, aiming to systematically and quantitatively determine the extent of soil moisture being detected in three dimensions from the above-mentioned aspects. To further explain how the three factors behave in the specific application, the results of two application scenarios are shown: (1) a ground-based GPS measurement in Marshall, Colorado, US from the Plate Boundary Observatory, corresponding to single-antenna pattern. The relative location of the specular reflection points, the average area of the First Fresnel Ellipse Clusters and the sensing depth of the time-series soil moisture are analyzed, and (2) an aviation experiment conducted in Zhengzhou to retrieve soil moisture content, corresponding to the multi-antenna pattern. The spatial distribution of soil moisture estimation with a certain resolution based on the flight tracks and the relevant sensing depth are manifested. For remote sensing using GNSS reflected signals, BeiDou is different from GPS mainly in the carrier frequency. Therefore, the results of this study can provide references for China's future development of the BeiDou-R technique.  
GNSS-R; antenna pattern; soil moisture; spatial resolution; detection depth +
Footnote †: journal: Sensors  
_Article_
# SDMw: Secure Dynamic Middleware for Defeating Port and OS Scanning
## 5 SDMw: The Secure Dynamic Middleware Architecture
### The SDMw Architecture
#### 5.1.1 The Unified Header Generation Algorithm (UHGA)  
We consider several popular OSs like Windows, Linux, Solaris, etc. As a first step, we adopt a unified algorithm to determine the TCP/IP parameters (including IP-ID, TCP-Initial Sequence Number (TCP-ISN), timestamp, the choice of a congestion control algorithm, window size, etc.) that are typical to the OS we considered. Let every host in the network use the same unified algorithm transparently. For an attacker, every host (including legacy hardware devices like printers, fax etc.) appears to run the same OS, (either known OS, in case we adapt known OS fingerprint parameters; or unknown OS if we design our own algorithm to decide on the TCP/IP parameters).
# A Disruption Tolerant Distributed Routing Algorithm in LEO Satellite Networks
## 1 Introduction
Before the link status of the entire network is fully synchronized, routing loops are easily formed between satellite nodes due to the lack of reliable backup paths. At the same time, the cost of broadcasting link failure information in the entire network is relatively large, and the synchronization time is long, which causes a large amount of data loss. In response to the above problems, we designed an LEO satellite network disruption tolerant distributed routing algorithm (DTDR) based on partial link status information. This algorithm can not only provide instant alternative backup paths for space segment routing but also balance the load around the failed link, while the routing cost is limited. Since the research in this paper focuses on the routing scheme for link failure, no clear strategy is given for global or local load balancing. It was mentioned above the current solution for realizing the load balance of the space segment network, this algorithm can better combine the above three types of solutions to form a complete space segment routing system.
## 2 Materials and Methods
### Instrumentation Used  
Both the transmitter and receiver of the laboratory model of the OFDM data transmission system use laptop computers with the Matlab environment for digital signal generation and analysis. Laptop computers communicate with underwater HTL-10 telephones from Sorel Sp. z o o. The HTL-10 was developed in 2006 for the needs of the Polish Navy as a device to perform underwater communication with the parameters specified in the STANAG 1074 standardisation agreement. It is a compact device enclosed in a cassette with a height of 150 mm, a width of 380 mm, and a depth of 330 mm. It performs the generation of the communication signal, and an analysis of the received signals, with the use of digital signal processors by Texas Instruments: a 16-bit TMS320 VC5416 fixed-point processor, and a TMS320C6713B (DSP) 32-bit floating-point processor. It contains multichannel analogue-to-digital converters with a 16-bit resolution and a maximum sampling frequency of 250 kHz. The source of the sampling frequency is an AD9834 direct digital synthesis circuit from Analog Devices. The underwater telephone works with a NI-USB6363 external recording and generating device from National Instruments. The HTL-10 devices pass the analog signal to a hydroacoustic transducer and receive the signal from a receiving transducer. Both the transmitting and receiving transducers are omnidirectional transducers with a resonant frequency of 34 kHz. The decay of their Transmitting Voltage Response (TVR) is equal to 3 dB in \(\pm\)5 kHz range from 34 kHz [9].
## 3 Meshing and Computational Method Validation
### Meshing  
The single-channel spatial discrete mesh of the axial flow compressor is generated based on CFX/TurboGrid [18], a hexahedral structured mesh generator specially designed for rotating machinery. In this paper, sub-area meshing was used, with an O4H-type mesh topology for the interior of the channel, an H-type mesh topology for the inlet and outlet, and an O-type mesh topology for the blades. The leaf top gap adopted butterfly mesh topology, the inner layer was an H-type mesh structure, and the outer layer surrounded the O-mesh. The number of single-channel mesh nodes was 741,244, and the number of meshes was 706,419. The mesh schematic is shown in Figure 6.  
To appraise the influence of the number of meshes on the numerical calculation results, eight sets of meshes with different numbers of nodes, 380,000, 470,000, 580,000, 740,000, 1,030,000, 1,360,000, 1,660,000, and 2,110,000, were obtained by adjusting the mesh sizes of the surface area of the blades and the top clearance of the blades, respectively. Considering that this paper focused on the near-stall condition of axial-flow compressors, different outlet back pressures (0.102 MPa, 0.108 MPa, 0.114 MPa, 0.120 MPa, and 0.125 MPa) were considered to ensure the accuracy of mesh irrelevance, and the total pressure ratio was used as a parameter to assess the impact of mesh density on performance. Figure 7 shows the mesh around the blade for different numbers of nodes at 0.120 MPa.  
As shown in Figure 8, under varying outlet back pressure conditions, when the mesh node count reached 740,000, the maximum deviation in total pressure ratio compared to other mesh quantities was 0.5%. Therefore, to balance computational efficiency and accuracy, this study ultimately selected a mesh node count of 740,000.
# Seismic Behaviour of CFST Space Intersecting Nodes in an Oblique Mesh
## 8 Theoretical Bearing Capacity of OMSIN
The results calculated using Formula (10) are based on monotonic axial compression loads, and so, they have significant discreteness compared to the ultimate bearing capacity of finite element axial compression. Therefore, multi-parameter optimization was performed on it. By using SPSS.27 data analysis software and the ultimate bearing capacity and yield load data in Table 3, the formula was fitted and corrected as follows:  
\[N_{u}^{\Theta}=N_{\text{u}}[k_{1}\sin\beta+k_{2}\cos\alpha+k_{3}K+k_{4}U+k_{5} S+k_{6}F+\omega] \tag{16}\]  
where \(\beta\) is the space oblique angle; \(\alpha\) is the plane oblique angle; \(O\) is the symmetry coefficient; and \(S\) is the steel content (%); \(K\) is the out-of-plane constraint (kN/mm); \(F\) is the compressive strength of concrete (MPa); \(k_{\text{i}}\) (i = 1, 2,... 7) is the undetermined coefficient; \(\omega\) is a constant term; The undetermined coefficients are shown in Equations (17)-(22):  
When calculating the ultimate bearing capacity:  
\[k_{1}=-1.90156;\,k_{2}=0.30973;\,k_{3}=0.14871 \tag{17}\]  
\[k_{4}=6.4378\times 10^{-4};\,k_{5}=0.93488;\,k_{6}=-4.08\times 10^{-3} \tag{18}\]  
\[\omega=0.86973 \tag{19}\]  
When calculating the theoretical yield force:  
\[k_{1}=-0.96552;\,k_{2}=0.38402;\,k_{3}=0.08769 \tag{20}\]  
\[k_{4}=5.23\times 10^{-4};\,k_{5}=0.0509;\,k_{6}=-3.52\times 10^{-3} \tag{21}\]  
\[\omega=0.7978 \tag{22}\]  
Comparing the theoretical calculation values with the ultimate bearing capacity and yield load of the finite element model, as shown in Figure 19. The mean ratio of the two was 0.999 and 1.0323, respectively, and the error was within 20%. Obviously, the two had good consistency and could be used to estimate the node's yield load and ultimate load. Figure 18: Schematic diagram for selecting the cross-section of 1/4 intersecting nodes.
# Recent Advances in Artificial Intelligence-Assisted Ultrasound Scanning
## 1 Introduction
### Current Challenges of Ultrasound Imaging  
Portable ultrasound has the potential to become the new stethoscope. The ultrasound imaging modality stands out for its safety, portability, non-invasiveness, and relatively low cost, which support its use in many different clinical scenarios. In fact, ultrasound imaging has become an important diagnostic tool for an increasing number and range of clinical conditions, enabling a greater variety of treatment options. This situation has led to the design of multiple complex diagnostic procedures and the atomization of their medical use.  
However, there are several challenges currently associated with ultrasound imaging:  
* Operator dependency. As US imaging depends on the ability of the operator to position the transducer and interpret the images correctly, it can be difficult to obtain consistent and reliable results from different operators, requiring long and specialized training.
* Subjectivity in image interpretation. The interpretation of the US images is quite subjective. Unlike other imaging modalities, which produce objective, quantitative data, the interpretation of US images depends heavily on the experience and skills of the person performing the scan. This can lead to variability in the accuracy and reliability of the images, particularly when they are used for diagnostic purposes.
* Limited penetration depth, which limits its use for imaging deep structures in the body, and an inability to penetrate certain tissues or structures, such as bone and air-filled cavities.
* Limited quality of US images. Ultrasound images are typically less detailed than those produced by other modalities. This can make it difficult to accurately diagnose certain conditions, particularly when the structures being imaged are small or located deep within the body.  
While advances in technology are helping to address some of these challenges, they still remain an important consideration in the use of ultrasound imaging.
## 4 Application Design and Implementation
### System Architecture  
In Figure 6, a general illustration of the X-NETAD mobile application is shown. Traffic updates are transferred from the AS to the PUs via the cellular network. Content can also be exchanged directly between PUs and SUs when they are within the communication range of one another. In this work, we focus primarily on the system design with respect to content diffusion between nodes in the _ad hoc_ domain.  
The architectural differences between the two distinct types of nodes are restricted to the ability of PUs to connect to a cellular network, in order to communicate with the AS. For this reason, a PU's architecture exhibits a Cellular Manager block--drawn with a dotted line, to remark on its presence only at PUs--that is in charge of the communications taking place with the AS (see Section 4.2.1.) using the cellular interface. The Wireless Manager block, on the other hand, is present at any node, because it drives the IEEE 802.11 interface and is fundamental in the dissemination process taking place in the _ad hoc_ domain. The X-NETAD Dissemination Manager is the key component of the whole system, due to the fact that it is in charge of the logical system management. If a new update is received from the AS, its content is stored locally, split in smaller chunks and the dissemination process is started. Upon the reception of an X-NETAD message on the IEEE 802.11 interface, the Dissemination Manager performs all the actions required to handle the message (see Section 4.2.2.). For example, when the system receives a _DATA_ message, the Dissemination Manager checks if the received  
Figure 5: Temporal diagram of a generic X-NETAD message flow.  
chunk is missing, updates (if required) its local bit-vector and, with the help of the IF and the GPS blocks, decides if the message has to be re-broadcast.  
When a new traffic update is available, regardless of whether it was retrieved from the cellular or the IEEE 802.11 interface, it is presented to the user through the User Interface (UI) application. If the update contains an audio message, then this message is played, and the additional content is presented according to the user's preferences.