esa-sceva/satcom-chunk-collection huggingface dataset:
# A Multi-Gateway Behaviour Study for Traffic-Oriented LoRaWAN Deployment
## 4 Simulations and Results Analysis
### Studied Scenarios
#### 4.2.2 Effect of the Number of Gateways  
Figure 6 shows the obtained results for 10 and 100 bytes of payload length while varying the gateway number with a frequency of 1 packet/min and with unconfirmed traffic. We can see from Figure 5(a),b that, as expected, the more gateways we used, the higher the A-PDR that was achieved. In addition, we can see that the A-PDR decreased as the number of EDs increased, mainly in the case of 100 bytes. From Figure 5(c),d, we can see clearly that when the number of gateways increased, the number of packets sent also increased, regardless of the payload length. Such behaviour can be explained by the fact that using more gateways will make the ED use a low \(SF\) value (e.g., \(SF7\)), which allows them to send more packets, as we can see in Tables 4 and 5. Finally, Figure 5(e),f show that by increasing the number of gateways, the LPI indicator decreased considerably compared to the case of using one or two gateways. In addition, using a high payload length led to a low LPI compared to using a low payload length. As previously stated, such behaviour can be explained by the fact that with more gateways, the ED uses a low \(SF\) value (e.g., \(SF7\)), which leads it to send packets with low airtime. So, gateways will have a low probability of facing interferences and thus lose packets.  
Figure 7 shows the results obtained for a payload of 100 bytes while varying the gateway number with a different frequency of sending packets and unconfirmed traffic. Typically, with one packet every 3, 5, 7, and 9 min, the behaviour was still the same, as we can see in Figure 6(a)-d. These figures confirm that increasing the number of gateways leads to a higher number of packets sent.  
Figure 6: _Cont._
# Deep Learning-Based Automatic Safety Helmet Detection System for Construction Safety
## 2 Materials and Methods
Among all the architectures, YOLOv5x gives the best precision and YOLOv5s has the fastest speed. Similarly, [PERSON] et al. [31] and [PERSON] et al. [32] also used YOLO-based architecture for safety helmet detection. [PERSON] et al. [31] used YOLOv3 architecture to detect safety helmets for the unbalanced dataset. They have improved the accuracy of YOLOv3 by using the Gaussian blurring method to deal with the associated data imbalance problems. [PERSON] et al. [20] proposed a single shot-based CNN model to automatically detect hard hats and identify the corresponding color. They used SSD [33] to detect safety helmets and achieved a mAP of 83.89%. Similarly, [PERSON] et al. [18] and [PERSON] et al. [34] used SSD for helmet detection. [PERSON] et al. [18] proposed a deep learning-based method for real-time detection of safety helmets. An SSD-MobileNet algorithm was used in this study and presented good precision and recall. However, the model was not performing well for smaller images and complex backgrounds, resulting in very low mAP. [PERSON] et al. [35] used bounding-box regression and transfer learning to detect safety helmets. They have used DenseNet-based strategies to improve the efficiency of the model and achieved an excellent accuracy of 94.47%. One of the major limitations of their work is the use of a face detection-based approach, as the model fails when the worker is not facing the camera, which is very common on construction sites. This literature review shows that many studies have been conducted on safety helmet detection on construction sites based on sensor, machine learning, and deep learning techniques. Most of them fail in detecting safety helmets in complex scenarios, such as sites with multiple workers. Furthermore, helmet detection in low-light conditions and with small object sizes needs significant improvements for real-time systems deployment. Therefore, this study addresses both scenarios and proposes a deep learning (YOLO algorithm)-based automated helmet detection system to ensure the safety of construction workers. Furthermore, the performance of the proposed method was also compared with the existing helmet detection methods using other YOLO variants (YOLOv3, YOLOv4).
## 4 Analysis of Numerical Calculation Results  
### Acceleration Response  
To investigate the seismic response of the double-layer pipe jacking structure under different ground motion intensities, the acceleration time history curves of the bottom of the upper and lower pipe jacking tunnels under the action of El Centro waves with three different peak accelerations are shown in Figure 7. It can be seen that:  
1. With the increase of the input peak acceleration from 0.1 g to 0.4 g, the ratio of the acceleration response peaks at the bottom of the upper and lower pipes is 1.31, 1.28 and 1.12, respectively. That is, the greater the peak acceleration, the smaller the acceleration amplification coefficient.
2. With the increase of the seismic motion, the peak accelerations at the bottom of the upper and lower pipes are increased and the peak acceleration of the upper pipe is greater than that of the lower pipe. This is related to the fact that the upper pipe is located in the soil and the lower pipe is semi-embedded in the rock layer. Therefore, due to the amplification effect of the soil layer and the embedment constraint of the underlying rock, it is more likely to cause serious damage to the pipe jacking structure in the soil-rock composite stratum.  
Figure 6: Comparison of bending moment diagram between numerical simulation results and shaking table test results: (**a**) Shaking table test; (**b**) Finite element model.
# UPC: An Open Word-Sense Annotated Parallel Corpora for Machine Translation Study
## 5 Technical Validation
### Experimental Results  
Table 12 demonstrates the results of the Korean-English and Korean-Vietnamese MT systems in terms of BLEU and TER scores. The results present that the WSD process significantly improves the quality of all MT systems, and NMT systems also give better results than SMT systems in all parallel corpora. This further demonstrates that the Korean-English and Korean-Vietnamese language pairs are consistent with the popular language pairs (i.e., Arabic, Chinese, English, French, German, Japanese, Russian, and Spanish) where NMT was stated superior to SMT [47; 48; 49].  
Figure 8: A part of the Korean-Vietnamese parallel corpus. (**a**) The parallel corpus in its initial form. (**b**) The parallel corpus in the word-sense annotated form.  
In the Korean-English parallel corpus, the Korean-to-English MT system showed great performance; it improved the translation quality of the SMT and NMT systems by 5.68 and 6.17 BLEU points, respectively. The improvement of these MT systems was similar when evaluated by the TER scores. Besides, in Korean-Vietnamese parallel corpus, the Korean-to-Vietnamese NMT system with WSD showed impressive results by 3.29 BLEU points and 5.72 TER points of improvement. In addition, the disproportionate improvement of translation quality in different translation directions, because we applied the word-sense annotation for the Korean side only. Hence, in the Korean-to-English and Korean-to-Vietnamese translation direction, the improvement is more powerful than the reverse direction.  
Besides, in the Korean language, the boundaries between words are unclear; a word usually consists of the root of the word and one or more accompanying components, depending on the grammar. In addition, rare words generate plenty of out-of-vocabulary (OOV) words, and this is the challenge of MT [50]. The morphology analysis that was included in UTagger created clear word boundaries and reduced the OOV words. Therefore, applying WSD to the corpora improved the performance of the MT systems. In addition, the results of the MT systems using our parallel corpora also showed relatively good performances, even higher than some of the commercial parallel corpora [51; 52].  
Furthermore, UTagger disambiguated the senses of ambiguous words and labeled them with the appropriate sense codes. Therefore, the annotated sense codes helped the MT systems to generate more proper word alignments and select the appropriate translation candidates. Both the morphology analysis and word-sense annotation that were included in UTagger significantly improved the quality of the SMT and NMT systems.
# Mechanical Properties of Disconnectable Coupling Joints for Steel Bracing under Eccentric Load
## 5 Flexural Performance under Eccentric Load
### Parameters Analysis on Flexural Performance
#### 5.2.4 Influence of Steel Wedge Height  
The moment-rotation curves of different steel wedge heights are given in Figure 22a. The flexural performance of DC joints gradually decreases with steel wedge height. Figure 22b shows the relation curves of steel wedge height on initial rotational stiffness and moment resistance. Steel wedge height is inversely correlated with the initial rotational stiffness and moment resistance, and the correlation gradually weakens. When the steel wedge height increases from 50 mm to 100 mm, the initial rotational stiffness and moment resistance decrease by 10.1 MN\(\cdot\)m\(\cdot\)rad\({}^{-1}\) and 22 kN\(\cdot\)m, respectively. When the height increases from 200 mm to 250 mm, the initial rotational stiffness and moment resistance decrease 5.3 MN\(\cdot\)m\(\cdot\)rad\({}^{-1}\) and 8 kN\(\cdot\)m, respectively. The decrease rates of initial rotational stiffness  
Figure 20: Impact of the steel wedge length on flexural performance.  
are 14.5%, 13.3%, 9.3% and 3%, respectively, and those of moment resistance are 7.4%, 5.0%, 4.1% and 3.2%, respectively.
# Phonocardiography Signals Compression with Deep Convolutional Autoencoder for Telecare Applications
## 4 Experiments
### Results
#### 4.2.2 Compression Ratio Evaluation  
It has been shown that higher values of CR result in larger values of PRD. Given that PRD's desired values are less than 5%, we would like to evaluate the attainable best CR in this Section.  
During the training phase, the batch size is chosen as 60, and the number of the epoch is set to 400. We fix the length of the segment of 6000, and the total number of segments is about \(7.2\times 10^{3}\). The dataset was randomly split into approximately 80% for training, 10% for validation, and 10% for testing. Meanwhile, we use the conventional Adam optimizer, as we have described in Section 4.2.1. The evaluation results are shown in Table 4. Although the PRD corresponding to CR = 36 is less than the target PRD (5%), if we further considered the fixed-point computation issue, the resulting PRD may not meet the target PRD. Thus, we choose the value of CR as 32 in the rest of this paper.  
Figure 4: _Cont._  
Figure 3: Time domain traces for various time durations: (**a**) 1 s, (**b**) 1.5 s, (**c**) 3 s, and (**d**) 4 s. The corresponding lengths of segment are (**a**) 2000, (**b**) 3000, (**c**) 6000, and (**d**) 8000 samples.
## 5 Result and Discussion
### Performance Analysis Based on K-Fold  
Figure 5 showcases the results of the BCHO-TCN LightGBM model for predicting out-of-stock occurrences. Figure 5a shows that the accuracy increases with each epoch value, with percentages of 83.35%, 88.01%, 90.26%, 92.51%, and 94.81% for epochs of 100, 200, 300, 400, and 500, respectively, using a 10-fold method. Likewise, Figure 5b displays the outcomes of the BCHO-TCN Light GBM model for NPV with a k-fold of 10, with values of 93.34%, 93.48%, 93.49%, 94.76%, and 95.60%. The results shown in Figure 5c for the epoch values of 100, 200, 300, 400, and 500 are 91.29%, 91.76%, 92.86%, 93.63%, and 96.28% for PDV at a k-fold of 10. Similarly, Figure 5d illustrates the findings of the BCHO-TCN LightGBM model in terms of threat score with a k-fold of 10, with values of 88.25%, 93.93%, 94.14%, 94.34%, and 95.86%.
# Wind Pressure Coefficient on a Multi-Storey Building with External Shading Louvers
## 3 CFD Simulation
### Reference Case
#### 3.1.3 Computational Domain and Grid Resolution  
The computational domain around the studied building is demonstrated in Figure 6. Two standards were used to define the scales of the computational domain [46; 47], and the blockage ratio is below 3%. The minimum heights of the near-wall grids on the ground, building walls and shading louvers were 0.0003 m (0.0006\(h_{0}\)). Note that the near-wall grids are just the wall-adjacent grids closed to the solids, rather than all grids between two adjacent louvers. In near-wall boundary layers on these surfaces, enhanced wall treatment is applied for \(y+<5\) and \(y+\approx 1\)[51]. Figure 7 shows the grid resolution in computational domain and around the cubic building. Compared with published research of a building with louvered windows [12], we had much higher grid density along louver length but lower grid density along louver width, because in our pre-simulation, it was found that in the study of wind pressure coefficient, the deviations were mainly caused by the grid density along louver length, rather than that along louver width. Based on the grid resolution, a coarser mesh and a finer mesh were created to ensure grid accuracy. The Grid Convergence Index (GCI) [52; 53] was calculated to show the deviation between different mesh sizes. For the reference case, GCI of normalized velocity and wind pressure coefficient are 0.37% and 1.8%, which are small enough to ensure grid accuracy, as recommended by [PERSON] and [PERSON] [54].  
Figure 6: Dimensions of the computational domain for CFD simulation.
## 1 Introduction
In this respect, it is important to consider the atmospheric conditions and the number of satellites connected simultaneously during the measurement, as they could affect the accuracy of the signal reception [17]. The evolution of this tracking technology has allowed for the inclusion of other measurement tools within these devices, such as gyroscopes and accelerometers that allow the analysis of acceleration and deceleration variables, jumps, turns, impacts (bumps or falls while standing), or changes of direction. This information provides a comprehensive analysis of the external load of athletes through the interaction of all variables, obtaining parameters such as player load or total body load that have been validated in previous studies [17; 31]. The monitoring of athletes during training helps us know to what degree the training sessions replicate the physical and physiological demands of the players during competition [17; 32]. However, on some occasions, the specific regulations of the sporting modality prevent the use of the GPS system in official competition, so this information can only be obtained in non-official competitions [17]. The use of this technology in beach handball for monitoring physical demands during competition is limited. Previous studies only analyzed the distance travelled and the analysis of the internal load of the player using heart rate monitoring devices [8; 9]. These studies show total distances of 1118.2 \(\pm\) 221.8 m and maximum speeds of 18.5 km\(\cdot\)h\({}^{-1}\) during competition in elite players, with moderate-high intensity movements. On the other hand, [PERSON] and [PERSON] [9] revealed significant differences depending on the playing position in the physical demands required during the competition. However, the players kept the same playing position during the 10 min of the set in this study. The research did not analyze official competitions, so there is a lack of information on the physical demands of beach handball players during competition. Therefore, the objective of this study is to analyze the physical demands of beach handball during competition by applying GPS technology in elite female players. The results of this study will help to orientate the training objectives to the physical demands of the competition with the aim of optimizing the performance of the players.
# A Tiered Control Plane Model for Service Function Chaining Isolation
## 8 Future Work  
For future work, we will proceed by testing the capabilities of the architecture. We have selected three areas of focus in order to make a full-scale verification of the architecture: the BGP control plane, the encryption services and the KMS key distribution protocol.  
A tiered control plane with BGP can potentially raise the BGP convergence time, but since the BGP processes for Tiers 2 and 3 run in parallel, it is not known if the additional layer of SFC will significantly decrease the computational power on the control plane. In addition, it is not known how a full mesh of Transport Links will scale when the number of SFC routes and the number of interconnected NFV providers increase. Answering these questions will require a more extended test-case based validation of the proposed solutions, which is among our immediate plans.  
Furthermore, the architecture suggests using VNFs on the data plane to enable encryption services. To reduce computational consumption, it is possible to run one shared encryption application instead of multiple encryption VNF applications such as flow-based IPsec. To enable flow-based IPsec to work, the IPsec application must be capable of encrypting an IP packet without stripping or encrypting the SFC header. On the contrary, this SFC header introduces additional overhead that should be compared with the overhead of multiple encryption applications versus one application.  
Another aspect on which we intend to focus for our future work relates to the KMS server, which is suggested to be implemented as an extended version of the KINK protocol. The KINK protocol is limited to only support IKEv1 and has limited support of future encryption algorithms. It is suggested to investigate protocol alternatives for key exchange between two random endpoints (VNFs) with a trusted third party KMS server.
###### Abstract  
This paper presents a multi-user Visible Light Communication (VLC)-based Internet of Things (IoT) system using multi band-Carrierless Amplitude and Phase (m-CAP) modulation for IoT applications. The proposed system uses a digital m-CAP modulator embedded in a ceiling LED light fixture and analog receivers, aiming at low-cost, low-power, and small-sized IoT devices. The performance was evaluated in terms of the filtering stage design and the usage of guard bands. Different pairs of emitter and receiver filters were considered. While Bessel and Butterworth analog filters were tested in the analog receiver, the digital m-CAP modulator pulse shaping filter considered raised cosine filters, as well as digital matched filters for the analog Bessel and Butterworth filters. Regarding the guard bands, two approaches were considered: either by using the raised cosine roll-off factor (bandwidth compression) or by suppressing the even bands. The Bit Error Rate (BER) performance was obtained by simulation. The usage of the Bessel filter in the receiver, along with a digital matched filter, proved to be the best solution, achieving a BER lower than \(10^{-3}\) for an Eb/No of 6 dB, using a third-order filter. Furthermore, guard bands should be used in order to mitigate inter-band interference in order to have improved performance when multiple users intend to simultaneously communicate.  
visible light communications; Internet of Things; m-CAP modulation +
Footnote †: journal: Physics Letters  
1
## 4 Significance of Ray Tracing Approach  
As described above, ray tracing is a very useful approach which was previously used in field-strength simulation and transmission loss model that possess complex environment. It can be directly used for integration by using standard numerical integrators like the Runge-Kutta method. To develop the model for sound propagation in shallow water combination of the X-ray model and fourth-order Runge Kutta integration method can be used for ray tracing to full-field modeling of interactions with seabed [21]. A RAYSON model named as Ray in French is RAY and sound is SON is used for underwater communication of time-varying channels which is modeled with the integration of static parameters and variable parameters [22]. For the ray tracing of the ocean environment with irregular bottoms implementation, [PERSON]'s equations are used called versatile three-dimensional \"Hamiltonian acoustic ray-tracing program for ocean\" (HARPO) [23]. Another approach in which the domain of the problem is divided into different subdomains. And each subdomain is fitted by the sound speed in a simple form whose analytic solution is possible [24]. One of the earliest forms of Gaussian beam propagation in the sonar community Porter with BELLHOP is introduced by [PERSON] and [PERSON]. The Gaussian curve is sometimes calling a bell-shaped curve. So, BELLHOP is a hopping bell-shaped curve through the field. In this process, initial bandwidth and curvature are given to the Gaussian beam at the source point, which can expand and contract after going away from the source point [25; 26]. Another model called \"Comprehensive Acoustic Simulation System/Gaussian Ray Bundle\" (CASS/GRAB) related to ray tracing is used by the Gaussian ray bundle instead of Gaussian beams [27; 28], it has many applications such as Sonar Simulations in Applied Physics Laboratories of Washington Modular Ocean Data Assimilation System [29; 30].
# Reliability of NAND Flash Memories: Planar Cells and Emerging Issues in 3D Devices
## 3 NAND Flash Memory Reliability
### Interface State Recovery  
In analogy with oxide defects, interface states are created during P/E cycles and recover in-between. Besides their effect on the endurance figure of NAND devices, discussed in Section 3.1, they also influence the \(V_{T}\) shift after cycling. In fact, it has been proposed that interface state recovery represents the major source of \(V_{T}\) instability in 90 nm NAND Flash [63; 209; 248]. Interface state annealing manifests itself via a reduction of the activation energy, down from the 1.1 eV associated to detrapping to about 0.7 eV [230; 231] or even 0.15 eV [249], and are also characterized by a non-uniform distribution over the cell area, usually peaked at the STI edges [74; 250]. However, it has been suggested that their effect is dominant for high values of the read current only [230; 231], while playing a minor role with respect to charge detrapping as the read current is reduced.
# Design and Performance Analysis of Navigation Signal Based on OFDM
## 5 Performance Evaluation of OFDM Navigation Signals  
In the previous sections, we introduced the time domain model of the signal and analyzed the characteristics of the OFDM navigation signal, comprehensively analyzed the spectrum usage of different navigation signals, and qualitatively analyzed the tracking accuracy, code loop false lock probability, anti-jamming, etc. In this section, we quantita  
Figure 9: Comparison between the navigation signal and traditional signal. (**a**) ACF; (**b**) PSD.  
tively analyze the reception performance of the OFDM navigation signals and prove the superiority of OFDM navigation signals.