esa-sceva/satcom-chunk-collection huggingface dataset:
# Benefits and Impact of Joint Metric of AOA/RSS/TOF on Indoor Localization Error
## 1 Introduction  
Indoor localization has gained considerable attention over the past decade due to the significant development of ubiquitous Location-Based Services (LBSs). The popular Global Positioning System (GPS) [1] has been recognized as a success for outdoor localization under the Line-Of-Sight (LOS) propagation property, whereas extending the GPS to the indoor environment with the None-Line-Of-Sight (NLOS) propagation property faces a serious challenge due to the irregular signal fading and multi-path interference. An alternative approach to address this challenge is the site survey-based location fingerprinting approach, which is based on the construction of a database of location fingerprints collected at Reference Points (RPs). In this case, the target locations are estimated by mapping the newly-collected Received Signal Strengths (RSSs) against the pre-constructed database of location fingerprints [2; 3; 4; 5]. However, the existence of the multi-path effect, wall sheltering and channel interference still results in the significant temporal and spatial variation of RSSs and consequently leads to the increase of localization error [6].  
The emerging techniques in the Fifth Generation (5G) communication system enable us to measure the Angle-Of-Arrive (AOA), RSS and Time-Of-Flight (TOF) with various types of mobile devices [7]. Then, the indoor localization by using the Joint Metric of AOA/RSS/TOF (JMART) will be preferred compared to the conventional metric by using the AOA, RSS or TOF solely [8; 9; 10; 11], which is more vulnerable to the environmental changes.  
The motivation of this paper is to investigate the benefits and impact of the JMART on the indoor localization error. In concrete terms, we use the Fisher Information Matrix (FIM) [12; 13; 14] to measurethe information of the JMART and then rely on the Cramer-Rao Lower Bound (CRLB) [15] to solve the corresponding unbiased localization problem [16].  
The rest of this paper is structured as follows. We survey some related work in Section 2. In Section 3, we derive the error bound by selecting the conventional AOA, RSS or TOF solely as the metric, as well as investigate the impact of the metrics of RSS/AOA, RSS/TOF and AOA/TOF on indoor localization error, which helps to derive the error bound by the JMART. The extensive simulations are provided in Section 4 to verify the benefits of the JMART. Finally, we conclude the paper and give the future directions in Section 5.
# Online Intrusion Scenario Discovery and Prediction Based on Hierarchical Temporal Memory (HTM)
## 1 Introduction
[14] proposed a method to predict medical streams in real-time; the paper employs two machine learning algorithms: HTM (Hierarchical Temporal Memory) and LSTM (Long Short-Term Memory) to model the same medical data stream, and the experimental results show that the HTM algorithm is more effective than the LSTM algorithm in three aspects: no training process, no domain knowledge, and the ability to adapt to variations in the data. [PERSON] et al. [15] proposed a framework to detect the anomaly in the stream of air traffic data broadcasted between a flight and the air traffic control center. The HTM is used to encode the data and learns the patterns from the sequential data for the anomaly prediction, and then conducts the deviation analysis to identify the attack based on the former predictions. [PERSON] et al. [16] proposed a distributed vehicle network anomaly detection framework with the abilities of continuous online learning and exception scoring. The framework can learn the network data sequence and detect the abnormal states of the vehicle networks. [PERSON] et al. [17] proposed a framework to categorize documents using the SP (Spatial Pooling) algorithm of the HTM theory, and LSI (Latent Semantic Indexing) technology is used for extracting the top features from the input and converting them into binary format. The assessment shows that the HTM model is accurate compared to the conventional technologies used in text classification. [PERSON] et al. [18] have proposed a gait pattern recognition approach using the extended HTM algorithm. In the paper, the authors decomposed the gait image into sequences of movements of each body parts, and learns the features through three levels of neurons. A Markov chain is used to discover the feature groups in which the mutual transition probabilities are above the threshold, then the HTM algorithm, which is extended with a dynamic programming algorithm, is used to infer the complex sequences. The HTM algorithm proves the effectiveness of visual problems. The main contributions of this paper are: (1) to introduce a series of data preprocessing methods to refine the streaming data; (2) the HTM algorithm is introduced to enhance the ability of online learning; and (3) an auxiliary method is proposed to improve the accuracy of intrusion scenario discovery.
# Adaptive Relay Selection Scheme by Using Compound Channel
## 4 The Proposed Scheme  
The proposed scheme uses a new algorithm to improve the performance of a single link. This new algorithm consists of two selection stages. In the first selection stage, the candidates for relay selection are determined according to the outage. After the determination of candidates, best relays and antennas are selected in the second stage. The following subsections explain the selection of the two stages. Figure 2 shows the flow chart of the proposed scheme.
# Pipe Spatter Detection and Grinding Robot
## 5 Robotic System Verification
### Verification of Spatter Detection in Real Pipes  
Pipes produced at the actual production site were supplied and tested. Figure 12 shows the manufactured SGR prototype, where for user workability the status of the front and grinding operations mounted on the robot could be checked through the teaching pendant. The operator did not manually remove spatters from the pipe, and the test was conducted on a pipe with a lot of spatters inside it. Figure 13 shows one of the provided pipes with a 15 cm diameter. The following equipment was used in the test: a power supply for the robot and for general work, a manipulator that could remotely control and monitor the robot, and a prototype of the proposed spatter detection and grinding robot that was designed and manufactured.  
Figure 11: Tuning of the speed control PID gain.  
Figure 12: SGR prototype.  
As shown in Figure 14, the robot was inserted into the actual pipe, driving at a speed of 0.3 m/min, and the input image was analyzed in real time. A graphical user interface was designed so that the operator could intuitively check the location and information of the spatters identified using the proposed detection algorithm.  
Table 5 summarizes the image processing test results obtained for four pipes with 15 cm diameters with spatters, including the locations of the spatters in the pipe. The recalls and errors were computed based on the actual distance output, according to the actual image processing result. The total recall was 87.5%, and the error ranged from 0.1 to 10 cm. The main sources of error were confirmed to be mathematical rounding and the conversion from pixels to actual distance.  
Figure 14: Real-time spatter detection inside a test pipe.  
Figure 13: Pipe spatter detection test.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Test** & **Sputters (cm)** & **Detected Spatters (cm)** & **Recall/Error (cm)** \\ \hline \multirow{3}{*}{Pipe 1} & spatter 1: 20.2 & spatter 1: 20.1 & \multirow{3}{*}{\(1/0.1\)–\(10\)} \\  & spatter 2: 150.1 & spatter 2: 160.1 & \\ \cline{1-1}  & spatter 3: 217.7 & spatter 3: 220 & \\ \hline \multirow{3}{*}{Pipe 2} & spatter 1: 52.7 & spatter 1: failed & \multirow{3}{*}{\(0.5/\)about 3} \\  & spatter 2: 552.1 & spatter 2: 555 & \\ \hline \hline \end{tabular}
\end{table}
Table 5: Image processing test results.
## 3 Linearized System
### No-Slip Boundary Conditions  
Introducing the no-slip lower boundary makes a major structural change to the physics of the problem. It is well known that there are three fluid dynamical dissipative mechanisms that lead to the  
Figure 1: Growth rate \(-Im\{c\}\) vs. wavenumber \(k\) for \(M=12.1\), \(\mathrm{Pr}=10\), \(G=100\), \(K=0.00001\). The plot clearly illustrates an exponential growth of a long wave packet, subtended by \(k=0\) and \(k_{cutoff}\).  
attenuation of surface waves. _Bottom friction_ is the dominant mechanism wherever the layer depth is substantially less than the wavelength, so that the wave induces large horizontal motions near the bottom (see [12], Figure 55 for an illustration of this point).  
Deep fluid waves, however, do not induce movement near the bottom, and thus no frictional dissipation. _Internal dissipation_ by viscous stresses acting throughout the wave cause attentuation.  
_Surface dissipation_ is associated with departures of the surface from its equilibrium value, described, for example, by [PERSON] (1968) in the case of doping of the surface with a monolayer of surfactant leading to an elastic dissipative mechanism.  
In addition to these mechanisms, the configuration under study has internal dissipation from the thermal conduction and possible surface dissipation from the Marangoni effect, which can play the role of a Lucassen-like tangential surface stress.  
[PERSON] [12] estimated the proportional energy loss per period, due solely to the bottom friction, as  
\[\left[\frac{2\pi}{d}\sqrt{\frac{v}{2\Omega}}\right]\left\{\frac{2 kd}{sinh(2 kd )}\right\}, \tag{29}\]  
where \(\Omega=c/k\) is the wave frequency. The square bracket factor is the ratio of the thickness of the bottom viscous boundary layer induced by the wave to the depth. The curly bracket factor corrects for finite wavenumber--it is unity for infinitely long waves and zero for infinitely short ripples.  
A complementary analysis for internal dissipation leads to the opposite preferences. Infinitely long waves are unaffected by internal dissipation; infinitely short waves are massively damped by internal dissipation. No doubt that consideration of internal dissipation effects only influenced the search by [8] for long wave excitation of surface solitary waves.  
A priori, this estimate would suggest that excitation of solitary disturbances cannot occur for either long waves or short waves due to the dominance of the attenuation by bottom friction and internal dissipative mechanisms, respectively. Candidate wavenumbers for solitary wave excitation should be intermediate wavenumbers where the Marangoni effect induces sufficient disturbance energy to overcome internal dissipation and bottom friction.  
To investigate this hypothesis, the modal structure of the no-slip problem should be clarified. The principal reason is that the major branches can be described with analytic approximations, leading to better understanding of the structure, and highlighting changes that are possible at intermediate wavenumbers.
## 3 Experimental Setup  
The setup shown in Figure 1 was realized under laboratory conditions. Figure 2 illustrates the experimental setup; it is rotated by 90\({}^{\circ}\) in comparison to the scheme.  
The use of a laser with beam-shaping optics has some advantages in comparison to traditional flash lamps or halogen lamps. It enables spatially homogeneous heating with a well-defined pulse shape without afterglow or intensity variations during the pulse. Figure 3 demonstrates the spatial alignment of the sample and heated area. The technical parameters of the laser system are:  
* Output power at the fiber: 540 W;
* Wavelength: 935-940 nm (depending on output power);
* Pulse length: 10 ms to infinity;
* Beam width after optics: 130 \(\times\) 130 mm\({}^{2}\) square at 60 cm distance;
* Irradiance measured at this distance: 3.0 \(\pm\) 0.1 W/cm\({}^{2}\).  
Figure 1: Schematic of the technical implementation of the photothermal method. The red arrow indicates the optical axis of the infrared camera; the diagram with the blue curve represents the measured surface temperature transient.  
Figure 2: Experimental setup under lab conditions. The orange dotted lines indicate the beam shape of the laser optics on the left side; the infrared camera is located behind. With the related optical axis, the inspected object can be seen on the right margin, where the orange rectangle indicates the heated region (13 \(\times\) 13 cm\({}^{2}\) area) of the object.  
The technical specifications of the used infrared camera, an Image IR 8300 with a 25 mm objective, are:  
* Cooled InSb detector array with 640 \(\times\) 512 pixels;
* Frame rate: 300 Hz full frame;
* Sensitivity range: 2.5-5.7 \(\upmu\)m;
* NETD: \(>\)25 mK;
* Integration time (10-100 \({}^{\circ}\)C): 0.5 ms.  
The settings for the experiments were:
* Heating pulse length: 0.5 s;
* Observation period: 1-2 min variable;
* Frame rate: 40 Hz;
* Distance between camera and sample surface: 61 cm;
* Resulting spatial resolution: 5 pixels/mm.  
The measurements of the hemispherical reflectivity at 940 nm were conducted in a separate experiment with a Perkin-Elmer Lambda 1050s spectrometer on different parts of the inspected specimen to cover the different additives, as well as the cement matrix present on the surface. One measurement covered a circular area with a 2.5 cm diameter. More details can be found in [17].
# Mobile AR: User Evaluation in a Cultural Heritage Context
## 2 Methods
### Prototype Development
#### 2.1.1 AR (Augmented Reality) Tracking Techniques  
Depending on the context where the AR system will be used and on the people who will use it, the tracking technique should be selected accordingly. The literature presents techniques such as the mobile localization techniques proposed by [PERSON] et al. ([19]): (1) sensor-based localization; (2) marker-based localization; (3) visual simultaneous localization and mapping (visual SLAM); and (4) model-based localization. Another classification was presented in 2015: (1) magnetic tracking; (2) vision based tracking; (3) inertial tracking; (4) GPS tracking; and (5) hybrid tracking [20]. More recently, considering the state of the art of near-eye display and tracking technologies for virtual and augmented reality, the authors classified tracking technologies as: (1) mechanical (e.g., physical linkage as the first HMD for AR invented by [PERSON] in 1968); (2) electromagnetic (e.g., magnetic sensing); (3) inertial (e.g., accelerometers and MEMs); (4) acoustic (e.g., ultrasonic); (5) optical (e.g., computer vision); and (6) hybrid (combination of technologies) [21].  
For the current study, which evaluated an AR application to be used at an archaeological site, some prototypes exploring a vision based tracking were tested. To do so, 2D images and 3D models were tested to be used as marks or \"targets\", as referred by [PERSON]. A first prototype was developed by scanning real rocks, in order to use them as markers to trigger and track the user while experiencing AR. Figure 1 presents two of the rocks used for this prototype.  
The tests made with this approach revealed great sensitivity to any changes in lighting, especially, when objects were facing the sun, which resealed to be a critical remark for the object recognition outdoors [17].  
Thus, 2D images were tested for the following prototypes. Two types of images were examined: computerized images and captured images (from real world). Two examples may be observed in Figure 2.  
Figure 1: Two rocks, with approximately 20 cm wide, used to created a point cloud to generate the two models used for testing registration and tracking based on 3D models.  
Figure 2: Two images tested to be used as marks: (**a**) a captured image; and (**b**) a computerized image.  
According to a previous study, the computerized images provided more stable results regarding to steadiness and to positioning accuracy [18].
# Cascaded Nanorod Arrays for Ultrabroadband, Omnidirectional and Polarization-Insensitive Absorption
## 5 Conclusions  
An ultrabroadband, omnidirectional, and polarization-insensitive absorber based on CNAs is numerically demonstrated, which consists of the top Ti nanorods and the bottom Ti/SiO\({}_{2}\) multilayer nanorods separated by a SiO\({}_{2}\) buffer layer. The physical mechanism for ultrabroadband absorption of the proposed absorber results from the synergistic effect of the LSP and PRC modes, which is completely different from those HMM-based absorbers associated with the slow-light mode. The CNA-based absorber requires only several film stacks, and an average absorptivity of 98.2% with RAB = 149.8% can be achieved in the 0.38-2.65 \(\upmu\)m wavelength range. According to the impedance theory, the impedance of the structure matches well with the impedance of the free space from the visible to the near-infrared spectral range. It is remarkable that the absorption performance of the CNA-based absorber is robust to the variations of the structural parameters such as thickness and diameter of the top Ti nanorods, thickness and refractive index of the buffer layer, diameter and number of the Ti/SiO\({}_{2}\) stacks, period, and the metal/dielectric materials. In addition, the CNA-based absorber exhibits omnidirectional independence for both TM and TE polarizations in the range of 0-60\({}^{\circ}\). This design strategy and architecture may provide an alternative scheme towards ultrabroadband absorption and might find applications in photoelectric detection, optical imaging, and photovoltaic solar energy conversion.  
In this work, [PERSON] and [PERSON] conceived the idea, simulated the design, optimized the structural parameters, and drafted the manuscript; [PERSON] and [PERSON] discussed the idea and checked the data; [PERSON] and [PERSON] checked the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research work was supported by the National Natural Science Foundation of China (Grant No. 61975153), and Fundamental Research Funds for the Central Universities (Grant No. JUSRP21935).  
The authors declare no conflict of interest.  
Figure 9: Absorption of the CNA-based metasurface as a function of the incidence angle for (**a**) TM and (**b**) TE modes. Other parameters are the same as those in Figure 2b.
# Determination of Benefits of the Application of CMMS Database Improvement Proposals
## 4 Benefits of These Proposals  
The first step in improving the entire CMMS system is a detailed review of the database and the data it contains using the Evaluation Methodology for Ship PMS (Figure 2).  
This will uncover all the data needed for the improvement effort. This requires expertise, i.e., a good knowledge of the computer programs used and a good knowledge of seamanship, more specifically, marine engineering.  
Figure 2: CMMS database evaluation process.  
The evaluation methodology for a ship's PMS [30] should be applied during the development of the CMMS database and during the use of the system to avoid deficiencies of the database and to allow proper use with all its benefits. They are relatively easy to calculate using the basic equation:  
\[B=\frac{Nsd}{Nq\times Nv} \tag{1}\]  
where:  
\(Nsd\)--The number of discovered deficiencies;  
\(Nq\)--Total number of questions;  
\(Nv\)--The number of analyzed vessels.  
The application of the methodology will result in the following:  
* There will be 4% fewer databases with missing equipment, which will increase maintenance reliability and reduce corrective maintenance;
* There will be 7% fewer databases with missing work orders, which will increase maintenance reliability and decrease corrective maintenance actions;
* There will be 13% fewer databases of missing spare parts, which will increase inventory accuracy, resulting in financial savings and increased vessel safety;
* More than 60% of the databases will have improved data and fewer discrepancies, giving the crew better insight into the system;
* Overall costs will be significantly reduced as fewer repairs will need to be made and/or fewer emergency spare parts will need to be ordered.  
In order to calculate the benefit of the second part of the research (missing books problem), it is necessary to determine how many books are still missing when the database is created. According to two database factories (companies that specialize in creating databases), this number varies. It depends on whether the ship is new or used, whether the data is in electronic or paper form, and where the ship was built, etc.  
By studying all available databases according to [33] and calculating the number of these cases compared to the number of ship equipment, the estimated benefit of this part of the research will be the potential improvement of 4% of the databases (4% of the equipment will have a maintenance plan that will allow better maintenance of these systems).  
The given value was calculated for newbuildings (all analyzed ships were taken as newbuildings), and the value of solving the problem of missing books for second hand ships remains open as a task for future analysis.
# A Wideband Termination Based on Laser-Scribed Lossy Microstrip Line Structures
## 1 Introduction
Such a device can be employed for applications where cheap wideband planar terminations are needed. This study also illustrates the merits of the LDW method, which contained limited steps and non-toxic materials. This may promote fast, flexible, and low-cost prototyping or modification of the existing microwave circuits on demand.
# Spectral Data-Driven Prediction of Soil Properties Using LSTM-CNN-Attention Model
## 3 Results
### Impact of Spectrum Preprocessing on Model Performance  
To assess the effect of removing the 400-499.5 nm spectral band during preprocessing, a comparative experiment was conducted using four models: LSTM-CNN-Attention, CNN, PLSR, and RF. The results, presented in Table 4, indicate that removing this spectral range consistently improved prediction performance across all evaluated soil properties. For instance, the R\({}^{2}\) of the LSTM-CNN-Attention model for OC increased from 0.930 to 0.949, accompanied by a reduction in RMSE from 19.592 to 16.687. Similar performance enhancements were observed for N, CaCO\({}_{3}\), and pH predictions. These findings suggest that excluding the 400-499.5 nm band reduces noise and artifacts in the data, thereby improving the models' generalization capabilities and predictive accuracy.  
Figure 8: KDE plots of PCA-transformed spectral data for the total dataset, training set, and test set: (**a**) PC1 and (**b**) PC2.  
Figure 7: KDE plots of soil properties for the total dataset, training set, and test set: (**a**) OC, (**b**) N, (**c**) CaCO\({}_{3}\), and (**d**) pH(H\({}_{2}\)O).