esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Signal Performance
### Pseudorange Code Bias and Signal Noise
The S/N performance is displayed in Figure 4. As shown in the figure, the S/N values of all signals are weak at low elevations, but the S/N can be improved as the elevation increases. Besides, the S/N values reach a maximum when the elevation is larger than 60 deg. Figure 3: The BD2 (**a**), BD3 MEO satellites (**b**) together with the Global Positioning System (GPS) (**c**) and Galileo satellites (**d**) multipath combination versus elevation and azimuth (units: meter). As shown in Figure 4, for BD3 signals, the S/N of B1C is about 3 dBHz weaker than that of the other three signals and its S/N is about 35-37 dBHz at low elevation (10 deg), and 52 dBHz at high elevation (90 deg), while the S/N values of the other three signals are about 40-42 dBHz at low elevation (10 deg) and 55 dBHz at high elevation (90 deg). This may be caused by the signal constitution of the BD3 satellites. The structure of the BIC signal consists of two components, namely, the data branch and pilot branch, which is similar to the GPS L1C and Galileo E1 OS. The navigation message was modulated on the data branch only, which can reduce the signal acquisition time and improve the accuracy of the weak signals [2]. The power distribution ratio of the data and the pilot branch is 1:3, which can improve the tracking threshold by 4.8 dB [23]. The designed minimum received power level on the ground is \(-\)159 dBW for B1C, which is 1.5 dB lower than that of the Galileo E1 OS and GPS L1C signals. These designs may be the reason for the weak S/N and a slightly noisier signal performance for B1C. Besides, compared with BD3 satellites, signal S/N values of Galileo E1 and GPS L1 are presented at the same level, but the B1I, B2a and B3I S/N values are obviously stronger than the Galileo and GPS S/N values. This may be related to the special configuration used by receivers, which may enhance the capability of the BDS signal tracking.
## 5 Experiment Analysis
### Non-Detectability Test  
As the basic property, concealment is a prerequisite for covert channels in practice. In the normal end hopping, the hopping pattern of end information keeps appearance irregularity (i.e., pseudo-randomness), resulting in bewildering attackers proactively. Hence, only when the CCES scheme equips approximate pseudo-randomness can it avoid arousing the adversary's attention and gain great non-detectability. So, we modulated the m-sequences with the original message to increase the non-detectability. In Section 4, we propose to measure the pseudo-randomness with entropy and test the non-detectability of the CCES scheme by comparing the entropy difference between the CCES scheme and normal end hopping.  
Firstly, we collected about 1,000,000 packets from the normal end hopping and divided them into 100 groups. Extracting the end information used in the CCES scheme separately, we obtained 100 combinations of SrcPort-DstIP-DstPort sequences. After calculating their entropy, the entropy ranges of _SrcPort_, _Dst1P_, and _DstPort_ are [0.15, 0.82], [0.40, 0.75], and [0.2, 0.8] separately.  
Then, we measured the corresponding entropy ranges of the CCES scheme. Since the end information entropy is greatly affected by the m-sequences and the end spreading degree in the CCES scheme, we conducted the measurement with different combinations of \(n\) and \(e\), where \(n\in\{7,9,14,16\}\) and \(e\in\{2,3,4,5,6,7,8,9,10\}\). For each \((n,e)\), we took the same step with the normal traffic to obtain the entropy range of _SrcPort_, _Dst1P_, and _DstPort_ separately. The final results are shown in Figure 6.  
We can observe from Figure 6 that different \((n,e)\) pairs present various entropy distributions. To develop the non-detectability of the CCES scheme, the \((n,e)\) pairs whose entropy ranges of _SrcPort_, _Dst1P_, and _DstPort_ all within the corresponding normal entropy range ought to be utilized to generate end spreading sequences. Obviously, our scheme provides various alternative \((n,e)\) pairs accorded with the above requirement, like \((7,e),e\in\{4,5,6,7,8,9,10\},(n,4),n\in\{7,9,14,16\}\), etc., which allows \(P_{s}\) to generate the appropriate end spreading sequences for covert communication.  
Without loss of generality, we select several typical \((n,e)\) pairs to perform the following tests, including \((14,e),e\in 4,5,6,7,8,9\), and the experimental process is also applicable to other pairs.
# A Full-Duplex LED-to-LED Visible Light Communication System
## 2 Positive Negative Junction  
A positive negative (PN) junction, a basic physical structure for a photodiode (PD) and a LED, is a combination of p-type and n-type semiconductors. LEDs are PN junction semiconductor devices that were originally designed to emit photons with energy smaller than or equal to the bandgap energy. In contrast, PDs are also PN junction semiconductor devices, which were originally made to generate electric currents by accepting photons with energy greater than or equal to the bandgap energy. In general, forward bias is applied to LEDs and reverse bias is applied to PDs according to their usage purposes. However, an LED can function as a photodetector when reverse bias is applied. The reason why LEDs can operate as optical emitters and optical receivers is because the physical structures of LEDs and PDs are the same. It was experimentally demonstrated that LEDs can be also utilized as optical receivers [15].
# A Frame-to-Frame Scan Matching Algorithm for 2D Lidar Based on Attention
###### Abstract
Additionally, the proposed method only uses the lidar data covered by the attention area, so it has very high computational efficiency. First, we selected a frame as a reference frame and chose an object as a landmark that was far enough away. The size of the landmark must be larger than the given threshold, and the landmark must provide enough information to obtain the relative pose; secondly, we chose the odometer to determine the initial pose of the selected frame and to determine the relative pose between the current frame and the landmark, extracting the corresponding data. Thirdly, the relative pose between the current frame and the reference frame was obtained based on the corresponding data. Finally, if the selected landmark reached the edge of the visual field of the current frame, then a new landmark was selected from the current frame as the reference landmark for the subsequent frame, and the current frame became the new reference frame. Landmark selection is part of the attention construction process, and once the attention has been constructed, the scan matching algorithm only considers the area covered by the attention and ignores other areas. As a result, the number of required calculations is greatly reduced. Since most current lidars have a measurement range of 20 m, the robot can move 20 m without accumulating errors using the ASM method in the ideal conditions. The main contributions of this work are as follows:  
1. This paper proposes the concept of an attention mechanism. Additionally, we introduce this mechanism into the frame-to-frame scan matching algorithm, significantly improving the accuracy and computational efficiency of the scan matching algorithm. 2. This paper proposes attention area selection, attention area update, and attention area scan matching methods that successfully integrate the attention mechanism into the scan matching algorithm. 3. The proposed attention-based scan matching algorithm is evaluated on multiple real-world datasets, and it outperforms the current state-of-the-art methods in terms of accuracy and efficiency.
## 3 Application of Integrated Transducer Arrays for Generation of Sound Waves  
In order to confirm the capability to apply the integrated transducer arrays for effective generation of sound waves, firstly, a numerical model has been elaborated, where the possibility to generate a directional wave is analyzed. These investigations were followed by the experimental investigations where, firstly, the manufacturing process of the active composite is described, followed by the characterization of the waves in the plate using a laser scanning vibrometer and the measurement of the resulting sound waves in the air using a microphone.
# A Study on the Design and Control of the Overhead Hoist Railway-Based Transportation System
## 2 General Concepts
### The Controller Design  
In order to simplify the electrical systems, the RDIF readers are employed as a slave unit to gather all signals from the RFID tags [13]. After that, the data will be transmitted to a PC to control the shuttles' operation. The RFID tag and encoder signal from the shuttles' motors are utilized to determine the relative position of the shuttles on each rail. The idea of using RFID devices was inspired by [14; 15]. The authors in [14] also stated that the radio frequency of 13.56 MHz is used in the access control and payment systems, as well as for identifying goods in warehouse systems and books in library systems. The RFID system is chosen to identify containers that are moving in the system based on previous ideas [16]. The 24 V battery is chosen as the main power source for the entire shuttle.  
Our goal which is shown in Figure 3, have all the shuttles carry out the required tasks and, at the same time, optimize travel distances. The route that the shuttles use for delivering can be considered a closed circle, and the shuttles can only move in two directions, which leads to the process of other shuttles being obstructed. It is therefore necessary to optimize the system in terms of time and energy.
## 1 Introduction
For fault diagnosis of wind turbine systems, [PERSON] and [PERSON] presented viable fault detection and isolation techniques which rely on fault estimation using data-driven methods and effective tools for managing partial knowledge of system dynamics, as well as noise and disturbance effects [18]. In contrast to previous publications, the observer designed in this study is not related to the object model, and the method is universal. With respect to fault reconstruction in the framework of FTC, an improved second-order SMO is designed to estimate the thruster fault effect. Considering the characteristics of the observer and the fact that weight of the forklift cargo changes with time, an adaptive sliding mode observer (ASMO) based on the forklift sensor fault model with output disturbance is proposed. It solves the problem that some fault reconstruction methods demand the upper bound value of the fault. According to the adaptive algorithm, adjustable gain parameters are adjusted adaptively without knowing the upper bound of the unknown fault, and the output disturbance can also be limited. The method is fairly robust and is more in accordance with the actual situation. The paper has the following structure: Section 2 presents the three-degree-of-freedom (3-DOF) forklift model and the sensor fault model; Section 3 proposes the ASMO; in Sections 4 and 5, sensor fault reconstruction and its improvement are presented; in Section 6, validation of the experiment is given; finally, the discussion and the conclusions are given.
## 3 Physical Layer in WMSN
\begin{table}
\begin{tabular}{|p{56.9 pt}|p{56.9 pt}|p{56.9 pt}|p{56.9 pt}|p{56.9 pt}|} \hline  & ZigBee & Bluetooth & **802.11** & **UWB** \\ \hline  & 250 Kbps & 1 Mbps (v1.2) 3 Mbps (v2.0) & 54 Mbps & 250 Mbps (up to now) \\ \hline  & 1 - 2 mW & 1 - 100 mW & 40 - 200 mW & 1 mW \\ \hline  & 10-100 meters & 1 - 100 meters & 30 - 100 meters & \textless{} 10 meters \\ \hline  & 2.4 GHz or 915 MHz or 868 MHz & 2.4 GHz & 2.4 GHz & 3.1 GHz - 10.6 GHz \\ \hline  & 76.52\% & 94.41\% & 97.18\% & 97.94\% \\ \hline  & \textless{} 65000 & 7 & 30 & - \\ \hline \end{tabular}
\end{table} 
Table 1: Specifications of the Physical Layer Standards in WMSNs. For the network layer, with the new characteristics of UWB such as low power transmission and low accurate ranging capabilities, the addressing and location-aware routing protocols can be optimized for better performance and they can get rid from the overhead caused by traditional flooding technique for routing and IPv6 scheme for addressing. Also UWB properties, especially the positioning capabilities, can be exploited to simplify the hardware used in location-aware routing instead of using of GPS enabled devices. It is pointed in [16] that UWB characteristics should be taken in account in the MAC layer for channel access, scheduling, and error control wherein the low duty cycle and low power transmission reduce the probability of collisions between pulses and interference. TH-IR-UWB system could be used, for example, for simultaneous transmissions based on the adoption of different time hopping code on each active link; and the rich resolvable multipath components of IR-UWB could be exploited, for example, at the receiver side for multipath diversity and channel estimation. It is worth to point out that, in order to further increase capacity and mitigate the impairment by fading and co-channel interference, multi-antenna systems such as antenna diversity, smart antenna, and MIMO systems, can be combined with UWB. Since UWB has almost impulse-like channel response, the combination with multiple antenna techniques such as MIMO systems may give the possibility of short-range networks with multi-gigabit rates. However, these physical-layer techniques have many challenging problems to be developed for WMSNs. Although UWB appears to be a promising alternative physical layer technology and it has many attractive features, it is still not very mature and there are many challenges and issues that need to be resolved and better understood.
## 5 Results and Iterative Feature Refinement
### Implementation of Feedback: Feature Refinement
#### 5.3.2 Acceptance and Commitment Therapy-Based Dialogue Reframing  
Experts expressed concern regarding the use of 'promise'-based dialogue, suggesting that it could evoke feelings of guilt or anxiety. Subsequently, the dialogue structure was revised to begin with the name of the child, establish attention, and incorporate empathy-led language grounded in ACT. This reframing process is illustrated in Table 3, which contrasts the original promise-based dialogue with the revised ACT-informed structure across three key components: Acceptance, Value Connection, and Committed Action.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**ACT Framework** & **Before Consultation** & **After Consultation** \\ \hline \multirow{6}{*}{Accept \& Acknowledge} & Dialogue: “[Child’s name], it’s time for me to go now. We made a promise, remember?” & Dialogue: “[Child’s name], I know it’s disappointing, but it’s time for me to rest. I’m sad about it, too.” \\  & Limitation: Focused on reminding the child of a rule, failing to acknowledge or accept their feelings. & Refinement: Implements ‘Acceptance’ by first verbalizing the child’s emotion, creating an empathetic foundation. \\ \hline \multirow{6}{*}{Connect to Value} & Dialogue: “If you don’t keep our promise, I might have less energy to play next time.” & Dialogue: “After I get some rest, I’ll have even more energy to play with you next time!” \\  & Limitation: Motivates through a negative consequence prospect, not a positive value. & Refinement: Links the present action to a more desirable future state, motivating the child with a positive goal. \\ \hline \multirow{6}{*}{Encourage Committed Action} & Dialogue: Binary success (“Thanks!”) or failure (Sad expression) responses. Limitation: Lacks supportive scaffolding for a child who is hesitating. & Dialogue: (On hesitation) “It looks like you’re not quite ready. That’s okay, I can wait a little longer.” (On success) “Thank you! I’m going to get such a good rest because of you. See you next time!” \\  & & Refinement: Adds a supportive path for hesitation and provides specific, positive reinforcement for the committed action. \\ \hline \hline \end{tabular}
\end{table}
Table 3: Dialogue reframed from ’promise’-based language to empathetic requests with attention-checking structure.  
Figure 4: Redesigned visual timer supporting persistent self-monitoring and intuitive colour transitions. (**a**) Idle and pause states before expert consultation; (**b**) corresponding states after expert consultation.
# A Comparison of the Effects of Binaural Beats of Audible and Inaudible Frequencies on Brainwaves
## 2 Materials and Methods
### EEG Analysis  
The EEG data were analyzed using MATLAB 2017 (MathWorks, Boston, MA, USA). Artifacts caused by eye blinking and movement were removed through visual inspection. Initially, the noise artifact due to eye blinking and motions was manually removed. Next, noise due to the power supply and electromagnetic noise was removed using a 0.5-50 Hz bandpass filter. The noise that may occur at the beginning and end of the experiment was reduced by capturing only the EEG signals from the rest (270 s) and stimulation (270 s) phases based on the trigger signal (Figure 1).  
A power spectral analysis was performed to observe the average alpha power of the rest and stimulation phases. Each phase was subjected to a fast Fourier transform and converted into power values based on its frequency. The relative power of the alpha band was calculated for each data point to reduce variability between subjects. Therefore, the alpha frequency range (8-13 Hz) was divided by the total frequency range (0.5-50 Hz) to calculate the ratio.  
The relative power values for each of the five brain regions (frontal, central, parietal, temporal, and occipital) were averaged, followed by a two-way analysis of variance (ANOVA), with the phase (phase: rest/stimulation) and audible state (state: audible/inaudible) as the independent variables. Additionally, an independent t-test was performed to compare the relative power values of the two types of baseline frequencies (audible and inaudible) for each brain region (SPSS, version 25, IBM, Armonk, NY, USA).
# A Collaborative UAV-WSN Network for Monitoring Large Areas
## 3 Results
### Method Validation on Real Test-Bed
This particular sensor node also illustrates the induced variability through vegetation effects in the wireless communication performance. To mitigate such situations a probabilistic approach can be implemented which establishes reliable bounds on the RSSI values and availability of the sensor nodes. Also, areas with reduced RSSI can be compensated by increasing the node coverage density e.g., increasing the number of nodes in a given area. Using the data available from the UAV's node logs we further analyze the RSSI evolutions illustrated in Figure 16. It can be seen how the RSSI's evolution changes depending on the position of the UAV.
# Automatic Scaffolding Workface Assessment for Activity Analysis through Machine Learning
## 3 Research Design
### Using a 2D Ordinary Video Camera for Data Collection  
Using an ordinary video camera for human motion capture has many advantages over the other data capture approaches mentioned above. Video surveillance employs ordinary video cameras and provides 2D videos to monitor and record activities and it has been broadly installed for management purposes in a large variety of industries. Compared to IMUs, an ordinary camera is non-intrusive: there is no requisite of devices attached to a worker's body; a depth sensor works properly under indoor conditions, but it is sensitive to the outdoor environment in that it produces numerous noises when it is exposed to outdoor radiation [47]. On the other hand, compared to depth sensors, an ordinary video camera is more cost-efficient and performs steadily on outdoor construction sites [47]. Furthermore, the video contains rich and intuitive information, which can not only be applied for monitoring, recording and safety management, but also can be broadly used for teaching purposes and accident analysis. To this end, the ordinary video camera was employed in this research as the human motion capture device for workforce assessment in construction [72].  
Looking deep into human action estimation from video frames captured by a 2D ordinary camera, scholars have explored several principle approaches such as appearance-based [73], trajectories-based [74], volume-based [75], and interest-point-based [76]. As human body joint points contain rich, meaningful information for action estimation, the approach based on the extraction of key joint points has been widely studied in the field of computer vision and has become the state-of-the-art method for human activity recognition. Hence, the extraction of human key joint points and body skeleton estimation are adopted in our research for workforce assessment in construction.  
This study proposes a vision-based method using 3D skeleton point estimation and supervised machine learning for workforce assessment from video sequences. For activity definition, we followed the guidelines for workforce assessments and divided the scaffolding operation into three categories: direct work, essential contributory work, and ineffective work. For model validation, we collected video data from actual scaffolding operations to train and test our model.
###### Abstract  
Copper-based alloys are widely known for their high thermal and electrical conductivity. Although the use of these alloys in powder-based additive manufacturing (AM) shows significant promise, applying this method in wire arc additive manufacturing (WAAM) processes poses various considerable challenges, including porosity, delamination, surface oxidation, etc. The limited research on WAAM of copper alloys, especially Cu1897, highlights the need for a more in-depth investigation. This study addresses the effects of process parameters in pulse cold metal transfer (CMT)-based WAAM of Cu1897, i.e., pulse correction (PC) and arc length correction (ALC), on bead penetration and porosity. The results showed that as PC was increased from \(-5\) to \(+5\), weld bead penetration increased from \(2.38\) mm to \(3.87\) mm. To further enhance penetration and reduce the porosity, the ALC was varied from \(+30\%\) to \(-30\%\) with a step size of \(15\%\). The results showed that weld bead penetration increased to \(4.47\) mm by altering the ALC from \(+30\%\) to \(-30\%\). Additionally, as the ALC varied within this range, porosity decreased significantly from \(3.98\%\) to \(0.28\%\). Overall, it is concluded that a lower value of ALC is recommended to improve bead penetration and reduce porosity in WAAM of Cu1897.  
Keywords:additive manufacturing (AM); arc length correction (ALC); porosity; pulse correction (PC); wire arc additive manufacturing (WAAM); weld bead penetration +
Footnote †: journal: Applied sciences