esa-sceva/satcom-chunk-collection huggingface dataset:
# Artificial Intelligence vs. Human: Decoding Text Authenticity with Transformers
## 2 Background  
The rapid advancement of AI technologies has significantly enhanced the capabilities of text generation models, blurring the distinction between human and machine-generatedcontent. This evolution marks a shift from traditional machine learning techniques to more sophisticated models that excel in handling complex language tasks.  
In the past, text processing and classification tasks relied on various machine learning techniques such as Convolutional Neural Networks (CNNs) [19], Long Short-Term Memory (LSTM) networks [20], and hybrid models like CNN-LSTM [21; 22; 23; 24]. While these models, along with Support Vector Machines (SVMs) [25] and Decision Trees (DTs) [26], provided notable performance improvements, they often struggled with capturing intricate contextual relationships and generating coherent text.  
However, recent years have seen a transformative shift with the advent of transformer-based models in Natural Language Processing (NLP). Models like BERT [10], RoBERTa [27], and DistilBERT [28] have set new benchmarks across various NLP tasks, including Machine Translation (MT) [13; 29], Question Answering (QA) [30; 31], Text Summarization (TS) [32; 33], and Text Classification (TC) [34; 35]. These advancements have significantly improved the ability to discern between human-written and machine-generated text [36; 37].  
Transformers excel in capturing complex contextual relationships and generating coherent text, surpassing the capabilities of traditional models like CNNs and Bi-LSTMs [38]. This capability is particularly crucial for detecting AI-generated content, where subtle differences between human and machine-generated text pose significant challenges.  
Recent studies highlight the effectiveness of transformer models in text detection tasks, highlighting their superiority over traditional methods by leveraging their deep understanding and representation of intricate language patterns [39]. Moreover, fine-tuned transformer models have demonstrated substantial improvements in detection accuracy compared to earlier machine learning techniques [40].  
In the subsequent sections, we provide a detailed description of the methods and materials used in our study, including the specific transformer models employed and their application in detecting AI-generated text.
# One-Layer vs. Two-Layer SOM in the Context of Outlier Identification: A Simulation Study
###### Abstract  
In this work, we applied a stochastic simulation methodology to quantify the power of the detection of unifying mixture components of a stochastic model, when applying a reduced-dimension clustering technique such as Self-Organizing Maps (SOMs). The essential feature of SOMs, besides dimensional reduction into a discrete map, is the conservation of topology. In SOMs, two forms of learning are applied: competitive, by sequential allocation of sample observations to a winning node in the map, and cooperative, by the update of the weights of the winning node and its neighbors. By means of cooperative learning, the conservation of topology from the original data space to the reduced (typically 2D) map is achieved. Here, we compared the performance of one- and two-layer SOMs in the outlier representation task. The same stratified sampling was applied for both the one-layer and two-layer SOMs; although, stratification would only be relevant for the two-layer setting--to estimate the outlying mixture component detection power. Two distance measures between points in the map were defined to quantify the conservation of topology. The results of the experiment showed that the two-layer setting was more efficient in outlier detection while maintaining the basic properties of the SOM, which included adequately representing distances from the outlier component to the remaining ones.  
Keywords:self-organizing map; neural networks; robustness; nonlinear projections; dimensionality reduction; deep semisupervised learning +
Footnote †: journal: Applied Sciences
## 1 Introduction
However, most of the research on high-pressure grouting technology focuses on the displacement of soil around the pile after grouting, the influence on rock mass before and after grouting, and the practical application of high-pressure grouting technology, with limited case studies focusing on the deformation characteristics and influencing factors of circular diaphragm wall deep excavations with high-pressure jet grouting pile reinforcement in waterfront and confined water-rich zones [36; 37; 38; 39]. In particular, the stability calculation methods for foundation pits provided in existing standards ignore the significant contribution of foundation reinforcement in foundation pits with high-pressure jet grouting pile reinforcement, resulting in relatively conservative calculation results. In order to make the stability calculation results of foundation pits more in line with the actual situation, this study considers the impact of foundation reinforcement on the stability of the foundation pit bottom based on the standard calculation methods. This study is based on the south anchorage foundation pit project of the Zhangjinggao Yangtze River Bridge north channel bridge. Through continuous field monitoring of the circular diaphragm wall's deep lateral displacements, vertical displacements at the wall top, and earth pressures during excavation, the dynamic evolution of key parameters during construction is thoroughly analyzed. Numerical simulations of the foundation pit's failure mechanisms pre- and post-reinforcement are conducted to systematically investigate: (1) the spatiotemporal evolution of deformations in the circular diaphragm wall during staged excavation; (2) the failure mechanisms of base heave and hydraulic-uplift under pit bottom reinforcement; (3) the influence of high-pressure jet grouting pile reinforcement zones on stability calculations. Based on these findings, improved stability verification methods for anti-heave and anti-hydraulic-uplift are proposed, overcoming the limitations of traditional pressure equilibrium and bearing capacity methods in this project. The results provide theoretical and practical references for similar engineering applications.
# The Gyrotrons as Promising Radiation Sources for THz Sensing and Imaging
## 2 Advantages of the Gyrotrons as Powerful Radiation Sources for Sensing and Imaging
### Advanced Spectroscopic Techniques
#### 3.1.3 X-ray Detected Magnetic Resonance (XDMR) Spectroscopy  
The XDMR spectroscopy is a new and unique element- and edge-selective technique [75] which allows to resolve and study the precession dynamics of spin and local orbital magnetization components. In this Pump&Probe technique (see Figure 6), the X-ray magnetic circular dichroism (XMCD) is used to probe the resonant precession of the magnetization produced by the irradiation with a strong microwave pump wave applied perpendicularly to the static magnetic field. The utilization of gyrotrons as powerful pump sources allows to extend this technique to the sub-THz frequency range and, respectively, to stronger magnetic fields. The first proof-of-principle feasibility study on the  
Figure 5: Experimental setup for the measurement of the hyperfine splitting of positronium (Ps-HFS).  
sub-THz XDMR spectroscopy has been conducted at the European Synchrotron Radiation Facility using a refurbished version of the gyrotron FU II which was operated at 76 and 138 GHz (fundamental resonances of the TE011 and TE021 modes, respectively). It is anticipated that this promising spectroscopic technique can be used for investigation of various electro-optical and magneto-electric effects, including the dynamics of Van Vleck orbital paramagnetism, as well as for studies on both optical and acoustic modes in ferrimagnetic and antiferromagnetic systems [76].
## 2 Results and Discussion  
### Physicochemical Index  
In order to monitor the effect of the freeze concentration process on the juice composition, the physicochemical indices of the fresh juice from the grape berries, the concentrated juice after freezing, and the mixed juice to be fermented, as well as the removed portion were determined (Table 1). The sugar contents were significantly increased in the concentrated juice and the mixture. The mixed juice reached a final sugar content of 255.71 g/L, possessing a potential alcohol content of 14% approximately. In the removed portion, a low content of sugar was detected, because the practical operation could not obtain absolute pure ice [10; 16]. Total acid and pH were not significantly changed after the treatment, which was consistent with Belen [17]. Volatile acid was detected in a very low level in these samples, especially in the removed portion.  
After fermentation, the wine with the freeze concentration treatment basically had similar physicochemical properties to the control within an acceptable range [18]. It demonstrated that the freeze concentration technique did not change the basic properties of the Cabernet Sauvignon wine-making process significantly (Table 2).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Physicochemical Index** & **Fresh** & **Concentrated** & **Mixed** & **Removed** \\ \hline Sugar (g/L) & 228.23 \(\pm\) 2.96 c & 462.70 \(\pm\) 9.21 a & 255.71 \(\pm\) 6.51 b & 62.95 \(\pm\) 5.43 d \\ Total acid (g/L) & 5.44 \(\pm\) 0.01 b & 6.31 \(\pm\) 0.22 a & 5.44 \(\pm\) 0.05 b & 5.15 \(\pm\) 0.17 b \\ Volatile acid (g/L) & 0.08 \(\pm\) 0.01 c & 0.14 \(\pm\) \(\circ\)0.01 a & 0.10 \(\pm\) \(\circ\)0.01 b & / \\ pH & 3.78 \(\pm\) 0.02 a b & 3.74 \(\pm\) 0.01 b & 3.78 \(\pm\) 0.03 a b & 3.81 \(\pm\) 0.01 a \\ \hline \hline \end{tabular} Data are mean \(\pm\) standard deviation of duplicate tests. Different letters in the same category indicate significant differences at \(p\leq\) 0.05.  
\end{table}
Table 1: Physicochemical properties of juices before and after freeze concentration treatment.  
The alcohol content was increased by approximately 1 vol % (\(p\leq 0.05\)) in treated wine because of the concentration technology. The content of glycerol in the treated wine was also significantly higher than control; this may be related to the yeast metabolism. Under hyperosmotic conditions, yeasts have to produce osmoprotectant to protect themselves; while glycerol is a good osmoprotectant synthesized as a by-product of alcoholic fermentation [19]. Freeze concentration causes a hyperosmotic stress for yeasts because of the higher sugar content, so yeasts generate more glycerol during fermentation, and thus a higher content of glycerol was produced in the treated wine.
# AHC: Advanced Network-Hiding Access Control Framework
## 5 Experiments and Analysis
### Compatibility  
Compared to the SPA protocol, one of the important goals of the AHAC framework is to achieve good compatibility. In terms of encryption algorithms, AHAC adopts the Noise Protocol framework and is compatible with both international cryptographic algorithms (RSA, SHA256, AES, etc.) and Chinese cryptographic algorithms (SM2, SM3, SM4, etc.). The encryption time for data will vary depending on the length of the data packet header. In terms of hardware and software systems, AHAC is compatible with major domestic and international CPU hardware and operating system software, including Kunpeng, x86, Loongson, Shenwei, and others. In terms of standards, AHAC complies with the relevant specifications of the \"U.S. Department of Defense Zero Trust Reference Architecture\" and the Chinese standard \"Information Security Technology--Zero Trust Reference Architecture\" and is compatible with them.
# Collaborative Indoor Positioning by Localization Comparison at an Encounter Position
## 3 Proposed Method
### Encounter Communication Using Bluetooth Low Energy (BLE)  
Indoor localization using Bluetooth Low Energy (BLE) is an essential technology that is used in various indoor applications, such as emergency management [32], occupancy tracking [33], smart grids [34], and smart energy management [35] in buildings. In this paper, BLE is used to detect the user's encounters and exchange the user's localization performance, resulting in a realization of a collaborative localization.  
A novel method of encounter communication is devised for two users using BLE. There are two modes in BLE: broadcasting and connection. Generally, the broadcast mode is used for encounter communication. However, we experimentally confirmed that the relationship between the RSSI and distance is more stable in the connection mode. Hence, the connection mode is used to realize encounter communication. In connection mode, the device has two roles: central and peripheral. The central mode scans packets and initiates a connection. The peripheral mode sends request packets and follows the central to exchange data. Communication is established only between the central and peripheral modes. In addition, devices cannot communicate with other devices if they have the same role. Therefore, we develop an application that operates both central and peripheral modes. The application chooses a suitable role dynamically. The flow of the proposed encounter communication is shown in Figure 3. The application has a unique number for each device. Here, the device operates the central mode at the beginning of the communication if it has a larger number than the other. Thus, communication can be prevented from being unstable due to the establishment of multiple communications between devices.  
An encounter is detected using the relationship between the RSSI and distance. Figure 4 shows an example of a relationship measured in the connection mode. A Google Pixel 4a was used. Specifically, we detect an encounter when an average of three consecutive RSSI values are larger than a threshold. The threshold is set to \(-58\) (dBm) in this study. For example, the encounter interval is from one to four meters in Figure 4. Communication is not established for 10 s after the previous communication to prevent multiple communications with the same collaborator immediately after the data exchange. In other words, the communication will not be re-connected for 10 s. Thus, an encounter will not be detected if the two devices re-encounter right after they first meet. Multiple and immediate re-encounters are not assumed in this work.
## 4 Numerical Experiments
### Dataset
#### 4.1.2 Experiment Data  
For the size measurement experiments, we collected 33 pieces of clothing from the five clothing types, as described in Table 1. Regarding the clothing, there were varieties of designs, colors, and shapes, and they were all used clothes. Our team manually measured each garment size independently three times and recorded the minimum, maximum, and median values to validate the experimental results. To collect the data, we laid out each piece of clothing on the floor and collected a set of data (consisting of an image, depth map, and point cloud) with a single capture using iPad Pro (A2228, Apple Inc., assembled in China) device. In this manner, the process carried out 10 independent captures for each garment by collecting and replacing. With every capture, the position and shape of the clothes slightly changed. We also collected data in the same way in two experimental conditions with different backgrounds. As a result, we constructed a total of 660 sets of data (330 sets per experiment) with two different background settings.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Clothing** & & & & \multicolumn{3}{c}{**Dataset ***} \\ \cline{3-6}
**Type** & **Size** & **Design** & **Pieces** & & **Experiment. 1 *** & **Experiment. 2 ** \\ \hline \multirow{3}{*}{Short sleeve} & Total length & V neckline & \multirow{3}{*}{10} & \multirow{3}{*}{100} & \multirow{3}{*}{100} & \multirow{3}{*}{100} \\  & Chest width & Printed & & & \\ \cline{1-1} \cline{5-6} sleeve & Waist width & 3/4 sleeve & & & \\ \cline{1-1} \cline{5-6} top & Cuff opening & etc. & & & \\ \hline \multirow{3}{*}{Long sleeve} & Total length & Printed & & & \\ \cline{1-1} \cline{5-6}  & Chest width & Sweatshirt & & & \\ \cline{1-1} \cline{5-6} Long & Waist width & Plain white & & & \\ \cline{1-1} \cline{5-6} sleeve & Cuff opening & Banded & & & \\ \cline{1-1} \cline{5-6} top & Sleeve length & Stripped & & & \\ \cline{1-1} \cline{5-6}  & Collar width & etc. & & & \\ \hline \multirow{3}{*}{Shorts} & Waist width & Bending & & & \\ \cline{1-1} \cline{5-6}  & Outseam & Floral & 7 & 70 & 70 \\ \cline{1-1} \cline{5-6}  & Leg opening & etc. & & & \\ \hline \multirow{3}{*}{Trousers} & Waist width & Jeans & & & \\ \cline{1-1} \cline{5-6}  & Outseam & Chinos & & & \\ \cline{1-1} \cline{5-6}  & Leg opening & Ripped & & & \\ \cline{1-1} \cline{5-6}  & Front rise & etc. & & & \\ \hline \multirow{3}{*}{Skirts} & Waist length & Pleated & \multirow{3}{*}{6} & \multirow{3}{*}{60} & \multirow{3}{*}{60} \\  & Total length & etc. & & & \\ \hline \multirow{3}{*}{Total} & \multirow{3}{*}{19} & \multirow{3}{*}{33} & \multirow{3}{*}{660} & \multirow{3}{*}{60} \\  & & & & & \\ \cline{1-1} \cline{5-6}  & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Description of garments in the dataset. For the experiments, we gathered 33 different designs of clothes from five clothing types. The dataset consists of 10 independent sets * (: image, depth map, and point cloud) for each garment. As shown in Figures 2 and 3, experiments 1 and 2 ** were conducted on a white background plate and a floor without a background plate, respectively.
# A New Method for Calculating Prediction Parameters of Surface Deformation in the Mining Area
## 3 Methodology
### Analysis of Influencing Factors of PIM in Huainan Mining Area
#### 3.2.4 Propagation Angle of Extraction  
The propagation angle of extraction is an important parameter in the prediction model of the probability integration method, and its size is affected by the dip angle of the coal seam, which determines the degree to which the surface mobile basin deviates from the goaf. According to collected data, the regression formula between \(\theta_{0}\) and \(\alpha\) could be expressed as Equation (4) through regression analysis in Figure 6:  
\[\theta_{0}=-0.5927\alpha+90.566 \tag{4}\]  
The goodness of fit \(R^{2}\) =0.8533. The fitting results show that the propagation angle of extraction decreases with the increase in dip angle.
# Impact of Intracavity Power Variations toward Ultrashort Pulse Generation
## 1 Introduction
In this technique, by dipping the cleaved fiber into the material-based solution while injecting laser light, the material is attracted to the fiber core. The thickness of the material on the fiber core can be controlled by adjusting its deposition time and the intensity of laser light [30]. Last but not least, the simplest method of depositing graphene is found by the breakthrough discovery of peeling off graphite layer-by-layer using Scotch tape [32; 33]. This discovery is also known as mechanical exfoliation which can be applied directly in fabricating graphene-based SA using fiber ferrules [34]. The fabricated multi-layered graphene SA produced about 3.2 ps pulse duration based on the estimation of the transform-limited soliton theorem. Besides graphene, this technique has been utilized for other materials; black phosphorus [35; 36], platinum diselenide [37], rhenium disulfide [38], molybdenum disulfide [39], and graphene/indium selenide [40]. Mechanical exfoliation can also be adopted with mirror-based SA that has been incorporated in fiber laser setups that cover 2.8 \(\upmu\)m (graphene [41] and indium selenide [42]) and 3.5 \(\upmu\)m (black phosphorus [43] and single-walled CNTs [44]). Our group has also successfully developed multi-layered graphene SA on fiber ferrule using this technique [45; 46]. Previous works focused on the ultrashort pulse generation in a single- [45] and a dual-wavelength laser system [46]. In this work, we demonstrate the performance of soliton mode-locking generated from graphene nanoplatelet (GNP) as the SA by changing intracavity losses. The GNP in bulk form is transferred to a fiber ferrule, and then it is mechanically exfoliated. The fabricated GNP-SA is tested in a ring cavity erbium-doped fiber laser (EDFL) with a variation in output coupling ratios from 10% to 50%. The feedback reflectivity determines the population inversion level of the active gain medium. As a result, optical amplification in the gain medium becomes dynamic, which dictates the ultrashort pulse performance.
# An Innovative Internal Calibration Strategy and Implementation for LT-1 Bistatic Spaceborne SAR
## 3 Calibration Equipment
### Internal Calibrator  
Internal calibration involves using built-in radar equipment to add calibration signals to the radar data stream, characterizing the SAR performance. The internal calibrator's transfer function should not distort the signal, allowing extraction of the range reference function from calibration data. Moreover, it must not affect the main signal channel when inactive.  
The design features of the internal calibrator are as follows: A combined design approach of delay calibration and non-delay calibration is adopted, and the loops of full array transmitting/receiving calibration and single T/R transmitting/receiving calibration can only use delay calibration methods. The BiSAR phase calibration primarily uses non-delay methods. Moreover, unlike monostatic SAR calibration, synchronization link calibration functionality is added. Furthermore, switch modules in the internal calibrator adopts cold backup design, while the interface with the APAA employs a cross-backup approach. Moreover, a coupler has been added to connect the synchronization calibration signal to the internal calibrator. A block diagram of the internal calibrator is shown in Figure 3, and a physical photo is shown in Figure 4.  
As shown in Figure 5, the information flow design of six calibration loops is presented, including chirp receiving calibration loops, chirp reference calibration loop, chirp transmitting calibration loops, synchronization transmitting calibration loop, synchronization receiving calibration loop, and chirp transmitting and receiving calibration loop.  
The calibration signal formation unit of the internal calibrator is mainly composed of microwave switches, amplifiers, delays, and compensation amplifiers, and other components, which accomplish the gating and corresponding level conversion of different calibration loops. In the delay path, RF signals undergo electro-optical and optical-electrical conversion and transmission through several kilometers of optical fibers, resulting in significant loss. Therefore, multi-stage amplifiers must be employed to amplify the delayed signal to meet the level requirements. However, the use of multi-stage amplifiers leads to significant changes in the insertion loss with temperature variations. Consequently, a corresponding temperature compensation circuit must be added to ensure the stability of the optical delay loop within the entire temperature range. The block diagram of the control circuit for the optical delay path is shown in Figure 6. The peripheral control circuits include circuits that provide bias current for the optical transmitting module, circuits that provide  
Figure 5: _Cont_.