esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 System Model  
A spatially Cartesian coordinate system for UWOC can be established as shown in the following Figure 1: point light source \(O\) is assumed to be located at the origin of the coordinates; the APD receiver moves on a quarter circle plane with radius \(r\) m (for simplicity of analysis, only quarter circle plane is considered and the quadrant where the receiver is located is set as the first one) in clear ocean water environment with related typical set of absorption and scattering coefficients of \((a,b)=(0.069,\ 0.08)\) m\({}^{-1}\)[3]; the horizontal distance between the light source and the circular surface is \(D\) m, and the coordinates of the light source and receiver are [0,0,0] and \([x_{0},y_{0},z_{0}]\) respectively; the field of view (FOV)of the receiver is 180\({}^{\circ}\), and \(d\) is the separation between the light source and the receiver. Please also note that, the distance parameters set in Figure 1 are determined by channel path simulations; one can find more details in Section 5. We additionally assume that the beam of the light source is always aimed at the receiver. For the receiver, the vector from the receiver to the light source \(O\) is \(\overset{\rightarrow}{V}_{or}\), \(\overset{\rightarrow}{V}_{n}\) is the unit normal vector perpendicular to the receiver plane, the angle between the tilted receiver plane and the horizontal X-Y circular surface is \(\theta\), and the angle between the normal vector \(\overset{\rightarrow}{V}_{n}\) and pointing vector \(\overset{\rightarrow}{V}_{or}\) is set to \(\beta\). To further simplify the analysis, we have set the Z axis, \(\overset{\rightarrow}{V}_{n}\) and \(\overset{\rightarrow}{V}_{or}\) coplanar. In this way, the relationship between them can be listed in the dashed box in the upper-right corner of Figure 1. In addition, we ignore the influence of the size of the receiver on \(\overset{\rightarrow}{V}_{or}\), that is, once the receiver's coordinate \([x_{0},y_{0},z_{0}]\) is fixed, the direction of \(\overset{\rightarrow}{V}_{or}\) will not change with the tilting of the receiver plane. However, the direction of \(\overset{\rightarrow}{V}_{n}\) will obviously change with the tilting of the receiver, that is, the pointing error angle \(\beta\) between \(\overset{\rightarrow}{V}_{n}\) and \(\overset{\rightarrow}{V}_{or}\) will change, which should be a function of parameter \(\theta\).
# Drilling Condition Identification Method for Imbalanced Datasets
## 3 Sliding-Window-Based SMOTE Oversampling Method
### SMOTE Oversampling  
SMOTE generates new samples based on the distribution of the minority-class samples by analyzing them, adding these synthetic samples to the original dataset to increase the number of minority-class samples, thus balancing the class distribution and improving the prediction performance of classification algorithms for the minority class [30]. The main steps of the SMOTE method are as follows:  
1. Neighboring sample set construction: For each minority-class sample, calculate the distance to other minority-class samples using methods like Euclidean distance or Manhattan distance. The \(k\) nearest minority-class samples are selected to form the sample's neighborhood set;
2. Random selection of neighboring samples: Based on the class imbalance level \(q\), randomly select \(q\) samples from the neighborhood set;
3. Generation of new samples: For each original minority-class sample, linear interpolation is performed with the randomly selected \(q\) neighboring samples to generate new minority-class samples. The formula for generating new samples is as follows: \[x_{new}=x+\alpha(x_{nn}-x)\] (7) where \(x_{new}\) is the newly generated synthetic sample, \(x\) is the original minority-class sample, \(x_{nn}\) is the selected neighboring sample, and \(\alpha\) is a random number within the range \([0,1]\) used to control the interpolation ratio. The principle of SMOTE data synthesis is illustrated in Figure 2.
## 3 Current Status of the Circuit Component in the MMW Regime
### Other MMW Control Circuits
#### Circulator and Isolator in Si-Based Technology  
Circulator, which is a three ports component, is usually utilized to provide simultaneously transmit and receive signals without diplexer filters or RF switches [179, 188, 190, 191, 192, 193, 194, 195, 196]. An active circulator has wider operation bandwidth, lower insertion loss and smaller area than a passive circulator. In an active circulator, isolation can be enhanced by couplers with the cost of its operation bandwidth [190]. By using common-drain or common source configurations, the operation bandwidth of the active circulator can be extended; however, it demonstrates a high insertion loss and NF [191]. Moreover, good port-to-port isolation can be achieved by phase compensating technique, which is proposed in [192] with complex matching network and large chip area. These can be solved by active balun and current combiner [193] with the cost of reduction in operation bandwidth. Two quasi-circulators exploiting CMOS technology are presented to demonstrate high port-to-port isolations, but the bandwidth of these quasi-circulators were narrow and consume considerable power [194, 195]. In addition, current-reuse technique can be applied to an active circulator to save dc power consumptions, nevertheless, the narrow band performances is inevitable [196]. In [189], a 90 nm CMOS 60 GHz quasi-circulator is implemented with distributed amplifiers. By taking advantages of distributed amplifier and Lange couplers, the quasi-circulator has god insertion gain, low NF as well as high isolation performances. As a result, it is suitable for MMW communication systems. In addition, a novel 24-GHz MMIC isolator is developed in TSMC 0.18-\(\upmu\)m CMOS. A new topology using the nonreciprocal common-source amplifier and the directional coupler is proposed to realize an isolator without ferrite. This isolator achieves 36-dB isolation with 1.8-dB insertion loss. The dc power consumption is only 3.6 mW. The performance of this isolator is comparable to those of the ferrite isolators except for the bandwidth [197].
## 2 Related Work
### Waufinding Focusing Indoor-Outdoor Navigation  
Complex working environments, such as organizations with large campuses and multiple buildings, require the integration of indoor and outdoor navigation [10; 11; 12]. Although several studies have been conducted on navigation and wayfinding, more research focusing on combined indoor-outdoor navigation is required to meet the needs of wayfinding in complex urban environments [29].  
Only recently, researchers have started to focus on combined indoor-outdoor navigation. For instance, [PERSON] et al. [9] reported on the development of a research plan for integrating outdoor and indoor spaces and discussed potential application domains and a variety of models (from formal models to functional models) related to the usability of indoor and indoor-outdoor information systems. [PERSON] et al. [27] presented a systematic mapping study focusing on software applications and devices intended to foster accessible wayfinding and navigation in outdoor and indoor environments [27]. [PERSON] et al. [30] proposed an integrated navigation method (using differential GNSS and Lidar SLAM) to meet the needs of indoor and outdoor navigation. Similarly, [PERSON] et al. [31] described an integrated navigation system to support seamless indoor-outdoor navigation based on Global Navigation Satellite Systems (GNSS), Inertial Navigation Systems (INS), and Terrestrial Ranging Techniques. The proposed system was evaluated by conducting an indoor-outdoor test, and results showed that it could provide reliable and continuous position and attitude solutions. Moreover, [PERSON] and [PERSON] [14] studied the impact of combining indoor and outdoor navigation on route planners by reviewing several case studies in multiple route planners. The study revealed different aspects and requirements, such as data constraints (preventing optimal use of navigation routes) and addressed matching methodologies (the exit influencing the exit choice of the building) for integration of indoor with outdoor connection in wayfinding. Furthermore, [PERSON] et al. [32] proposed an approach based on multi-level surface maps for navigation in combined outdoor and indoor environments. The approach does not rely on GPS information, and the presented technique allows the robot to actively explore the environment [32]. [PERSON] et al. [11] presented a prototype for an indoor and outdoor mobile navigation system using floor plans together with street maps for route finding and displaying a hybrid map for a university campus. The prototype is implemented on iPad, but the work is still under process; GPS is used for outdoor positioning, and QR codes are used for indoor positioning.
## 4 Imaging System Characterization and Performance
### Optical Resolution and Depth of Field
It is unclear if the inaccuracy at such small length scale comes from a fundamental resolution limit of the system, or because of the limited number of pixels to resolve such a small feature (an area equivalent to approximately 2 pixels). For drop or particle sizing applications, such as the current work, the response of an imaging system with respect to out-of-focus features is yet another important aspect. It is well known that image sharpness, in other terms the effective resolution, degrades when imaging objects away from the object plane. This aspect can be characterized by evaluating the MTF of the system at various depth around the object plane. To synthesize the information, Figure 9 plots the spatial frequency the system  
Figure 7: Modulation transfer function of the imaging system at the object plane with both the LED and VCSEL illumination systems. The results report the modulation transfer function (MTF) evaluated with both the knife-edge method and the USAF-1951 resolution chart. can resolve with a half intensity difference, or the spatial frequency at half modulation, as function of the distance on both sides of the object plane. Figure 9 confirms the marginal differences between LED and VCSEL-based illumination when it comes to resolution and depth of field. The subtle difference in peak spatial frequency at 50% modulation was already appreciated in Figure 7, whereas the slightly wider distribution of the VCSEL in Figure 9 can be explained by the increased distance to the microscope objective (due to chromatic focus shift). The results of Figure 9 show how quickly spatial resolution deteriorates as an imaged object is moved away from the plane of optimal focus. The spatial frequency at 50% modulation approaches half its peak value only about 0.3 mm away from the object plane. Even with such degradation in spatial resolution, the test results still indicate that the system should be able to resolve features on the order of 10 um over half a millimeter around the object plane.
## 2 Materials and Methods
### Three-Dimensional Posture Measurement  
To determine the three-dimensional pelvis contour, marker spheres (diameter 8 mm) were applied to anatomical landmarks on the shaved skin in the pelvic area [20] by means of double-sided adhesive pads (Figure 1). All palpations were performed by the same experienced examiner. The test persons were standing in habitual posture, arms crossed in front of the chest. Three-dimensional posture scans were performed dorsally and ventrally using the Rothballer 3D Scanner (Rothballer electronic systems, Weiden, Germany). This system generated a three-dimensional image of the pelvis in the shape of a mathematical point cloud. System reliability and validity for postural measurements have been confirmed by other studies (comparable inter-trial reliability to 3D motion analysis systems: intraclass correlation coefficient difference = 0.06 \(\pm\) 0.05, range 0.00\(-\)0.16; very good validity: [PERSON]'s r = 0.96 \(\pm\) 0.04; range 0.84\(-\)0.99 [21; 22]).  
For the evaluation, the position of the marker spheres was determined individually using the analysis software, and their spatial coordinates were extracted. The marker spheres on the trochanters were visible on both 3D images and served as reference points for the spatial coordinates of all points. Figure 2 shows the simplified geometries of both hemi-pelvises, calculated trigonometrically from the coordinates. The torsion of both triangles against each other was calculated as an angle using MATLAB (R230a, MathWorks Inc., Natick, MA, USA) and Microsoft Excel (Microsoft, Redmond, WA, USA); this angle was then used as the measured value for pelvic torsion. In addition, pelvic anteversion was calculated as the angle of the connection line between pubic symphysis and S1 and the horizontal.
## 5 LoW Mob Mobity Support Scheme
### New MN Joining the PAN  
Figure 2 shows a PAN with multiple SNs, a single GW/PAN coordinator and a MN which enters the PAN for the first time. When the BNs detect a movement, they switch from quasi-sleep state to active state. In active state, they frequently transmit beacons. The beacons contain the information about the SN's short address and PAN ID. Once the MN receives the beacon, it checks the PAN ID and determines whether it has moved to a new PAN or not. If the MN is in different PAN, it sends a _join request_ message to the SN from which it receives the beacon of highest signal strength. The _join request_ message indicates to the SN that the MN is new to the PAN and wants to associate with the PAN. The message contains information regarding MN's Home address and its EUI 64 bits address. The MN then sends _CN_address_ messages that contain the IPv6 addresses of the CN with which the MN usually communicates. The SN then forwards the messages to the GW.  
Figure 2: The MN as joining the PAN.  
When the _join_request_ message reaches the GW, it creates a binding entry for the MN and, assigns [PERSON] with a unique 16 bits ID. Also the GW maps the IPv6 address of its CNs to a unique 16 bits address. This is done in order to save the number of bits used in the IP addressing, which might waste useful energy and bandwidth of the SNs when routing the data and mobility-related packets of the MNs. Then the GW sends a _join_confirm_ message to the SN that forwards it to the [PERSON]. The _Join_confirm_ message contains [PERSON]'s ID and the short address of its CNs.  
If, in future, the [PERSON] wants to communicate with a CN for the first time then the MN will request the GW to provide a 16 bits address by sending CN's alias name. Thus the GW will run an Address Resolution Protocol (ARP) and provides a 16-bits address against the CN's IP address or its alias name. Similarly, when a packet for the MN can arrive from CN that is located outside the PAN, for which the GW does not have a pre-existing binding. In this case, the GW will first create a binding and sends this binding to the MN before sending the data packet.
# A Comprehensive Review of Indoor Localization Techniques and Applications in Various Sectors
## 3 Methodology and Application of Indoor Localization in Various Fields
### Indoor Localization Applications and Methodologies in Healthcare
#### 3.1.3 IoT-Based Healthcare Applications  
[PERSON] et al. [27] proposed an indoor positioning system, as illustrated in Figure 11, that focuses on providing accurate localization within IoT-based environments, addressing the challenges of real-time tracking and data integration. The system comprises two primary components: fixed reference nodes (RNs) and mobile nodes (MNs). The RNs serve as anchors with known coordinates, while the MNs are wearable devices or tags that need to be localized. The architecture employs various positioning techniques such as lateration, angulation, and fingerprinting to determine the MN's position based on signal measurements.  
First, the MN receives signals from multiple RNs, capturing data such as the RSSI and TOA. These measurements are then processed using machine learning algorithms, such as ANNs and deep neural networks (DNNs), to improve accuracy. Advanced filtering techniques, such as Kalman filters and particle filters, are used to minimize noise and refine the localization estimates. The data are then sent to a cloud or edge server for further processing and analysis, enabling real-time feedback and decision-making. The system also supports hybrid positioning approaches by integrating multiple technologies, such as BLE, Wi-Fi, UWB, and RFID, to enhance reliability and adaptability in dynamic environments. This multi-technology approach addresses challenges like signal attenuation, multipath interference, and NLOS conditions. For healthcare applications, the system can integrate with sensor networks (e.g., accelerometers and heart rate monitors) to provide health monitoring and fall detection capabilities [27].  
In addition to its positioning capabilities, the architecture enables data fusion from diverse IoT devices and incorporates artificial intelligence for behavior analysis and predictive maintenance. This is demonstrated in Figure 12, which illustrates the Positioning System Classification for IoT-Based Healthcare Applications. The flexibility of the system allows it to be deployed in diverse environments, such as hospitals, industrial facilities, and military operations, improving safety, efficiency, and resource management [27].  
Figure 11: IPS configuration with RNs and MNs using advanced localization technologies.
# Calculation Method of New Assembled Corrugated Steel Initial Support Structure of Highway Tunnel
## 5 Conclusions  
A series of full-scale tests and numerical simulations were conducted to investigate the mechanical mechanism of the assembled fast CSP initial support structure. Utilizing equivalent stiffness coefficients and a rotational stiffness model, a simplified calculation method was established. The primary conclusions drawn are as follows:  
1. Full-scale tests were performed to characterize the stiffness properties of the CSP plate's load-deformation curve in two stages: clearance elimination and elastic stages. The presence of initial gaps within the structure and loading system was found to initiate the clearance elimination stage. To refine the calculated CSP stiffness values, a general equivalent stiffness coefficient table for CSP plates was established, and its variation pattern was analyzed: the equivalent stiffness coefficient decreases with increasing relative displacement between plates (RDP). When the RDP exceeds 0.333, the equivalent stiffness coefficient positively correlates with thickness; otherwise, it exhibits a negative correlation.
2. The entire loading process of the CSFJ was generalized into a rotational stiffness model encompassing two stages: elastic and plastic. Both stages demonstrated linear behavior. Based on the rotational stiffness values from these stages, a plane strain-spring simplified model for the assembled corrugated steel initial support structure, accounting for joint conditions, was proposed.
3. Leveraging the Qipanshan Tunnel in Yunnan Province, a numerical model of the assembled corrugated steel initial support structure was established, incorporating structural contact relationships and constitutive models. A comparative analysis of calculation results and monitoring data was conducted to validate the accuracy and reliability of the calculation mentioned in the above method.  
**Author Contributions:** Methodology, C.Y.; Investigation, T.W.; Writing--original draft, X.H.; Writing--review & editing, Q.Z.; Supervision, W.D. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This study has been supported by research grants from the General Program of Gansu Provincial Department of Transport Science and Technology Project (2022-01) and by the National Natural Science Foundation of China (No. 52378405).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 3 Results and Discussion
### Modeling of Bentonite Evolution Experiment
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Mineral** & **S, m\({}^{2}\)/g** & \(\mathbf{k_{25}^{m}}\) & \(\mathbf{E_{a}^{m}}\) & \(\mathbf{k_{25}^{m}}\) & \(\mathbf{E_{a}^{H^{\star}}}\) & \(\mathbf{n_{H}}^{\star}\) & \(\mathbf{k_{25}^{OH^{-}}}\) & \(\mathbf{E_{a}^{OH^{-}}}\) & \(\mathbf{n_{OH^{-}}}\) \\ \hline Albite & 2 & \(5.1\times 10^{-20}\) & 57 & \(8.5\times 10^{-11}\) & 58 & 0.34 & \(1.4\times 10^{-10}\) & 56 & 0.32 \\ Chlorite & 1 & \(6.4\times 10^{-17}\) & 16 & \(8.2\times 10^{-9}\) & 17 & 0.28 & \(6.9\times 10^{-9}\) & 16 & 0.34 \\ Illite & 30 & \(3.3\times 10^{-17}\) & 35 & \(9.8\times 10^{-12}\) & 36 & 0.52 & \(3.1\times 10^{-12}\) & 48 & 0.38 \\ Kaolinite & 5 & \(1.1\times 10^{-14}\) & 38 & \(7.5\times 10^{-12}\) & 43 & 0.51 & \(2.5\times 10^{-11}\) & 46 & 0.58 \\ Microcline & 1 & \(1.0\times 10^{-14}\) & 31 & \(1.7\times 10^{-11}\) & 31 & 0.27 & \(1.4\times 10^{-10}\) & 31 & 0.35 \\ Quartz & 0.03 & \(6.4\times 10^{-14}\) & 77 & & & & 1.9 \(\times 10^{-10}\) & 80 & 0.34 \\ Smectite & 40 & \(9.3\times 10^{-15}\) & 63 & \(5.3\times 10^{-11}\) & 54 & 0.69 & \(2.9\times 10^{-12}\) & 61 & 0.34 \\  & & \(4.7\times 10^{-16}\ast\) & 2.7 \(\times 10^{-12}\ast\) & 2.7 \(\times 10^{-12}\ast\) & 36 & \(3.6\times 10^{-15}\ast\) & 61 & 0.34 \\ \hline \hline \end{tabular}  
* The kinetic constant and the activation energy according calibration  
\end{table} 
Table 8: Parameters for the dissolution rate model. The kinetic constant (\(k\)) is given in \(\mathrm{mol}\cdot\mathrm{m}^{-2}\,\mathrm{s}^{-1}\) and the activation energy (\(E_{a}\)) is given in \(\mathrm{kj}\cdot\mathrm{mol}^{-1}\) (according to [65] and calibration *) in Equation (2).
# A Network Analysis Approach to Detecting Social Issues with Web-Based Data
## 4 Illustrative Example: Diesel Exhaust Fluid Issue in South Korea  
This section illustrates the social issue detection process of the proposed approach using web-based data. Specifically, to illustrate whether a social issue that occurred in the past is appropriately detected from web-based data generated at that time, this study selected the diesel exhaust fluid (DEF) issue in South Korea as a case of a social issue.  
In late 2021, South Korea confronted an issue about shortage of DEF, which is an essential liquid used in modern diesel engines to reduce emissions of harmful nitrogen oxides. The issue was caused by several factors such as difficulties in importing DEF, a surge in demand due to stricter environmental regulations, supply chain disruptions caused by the COVID-19 pandemic, etc. According to the South Korean Ministry of Environment, there were approximately 9.8 million diesel vehicles registered in South Korea at the end of 2021. Among them, the vehicles requiring DEF were about 2.1 million, including passenger cars, cargo trucks, and public transportation buses [38]. Since vehicles that require DEF cannot operate without it, the DEF issue caused damages in various fields of society, such as trucks being unable to transport cargo and the commuting of workers being restricted. As a result, the DEF issue developed into the transport, logistics and public service crisis of South Korea. This section illustrates the process of detecting the DEF issue from web-based data generated at that time.