esa-sceva/satcom-chunk-collection huggingface dataset:
# Wireless Channel Models for Over-the-Sea Communication: A Comparative Study
## 1 Introduction
Our study can help researchers and engineers select an appropriate channel model based on their application. The main contributions of the paper are as follows:  
* Theoretical key concepts needed to understand channel models for over-the-sea radio wave propagation are briefly discussed. * Channel models are examined in relation to their operational principles and key features. * Channel models are classified based on their propagation type and the mobility of their transceiver platform. * Channel models are compared with each other in terms of major characteristics, pros, and cons. * The possibility of unique and novel applications and some possible future improvements of the channel models are addressed. * Key challenging issues for modeling a wireless channel for over-the-sea communication and the research directions to design a new channel model are discussed. The rest of the paper is organized as follows. In the following section (Section 2), key concepts related to wireless channel modeling for over-the-sea communication are discussed. In Section 3, existing channel models are classified. In Section 4, existing channel models are reviewed by functional principle, basic operation, and distinctive characteristics. In Section 5, the qualitative comparison of channel models is summarized and discussed. In Section 6, the possibility of unique and novel applications of the channel models is discussed and some possible future improvements of the channel models are presented. In Section 7, we discuss important challenging issues for modeling a wireless channel for over-the-sea communication and the research directions that can be helpful for researchers if they intend to design a new channel model. Finally, the paper is concluded in Section 8.
## 4 Experimental Evaluation  
In this example, we tested the proposed MILP and S-GAIPSO algorithm. All experiments were performed on a personal computer using Intel(R) Core (TM) i7-8565U CPU @1.99 GHz and 8.00 GB RAM. We used a CPLEX solver based on MATLAB to call the YAMLIP toolkit and MATLAB R2016a to implement the S-GAIPSO algorithm, which are compared and discussed in terms of the solution gap and computational power with various sizes of randomly generated problems; a1 and a2 are set to 10 and 100, respectively. The following cases were simulated and tested based on real large-scale community distribution. In this case, Figure 5 is a planning map of a community, with two service stations where robots can charge and load goods. A set of randomly generated data is used to represent the service information of customer, including the X/Y coordinates, time window, and service time. The position of the customer is represented by the two-dimensional coordinates of each point, and the distribution path between the two tasks is represented by calculating the Euclidean distance of the two points. Each customer has a serviceable time window, and the robot needs to complete the delivery for it during this time period. The speed of robot is 1.0-1.5 m/s under light load conditions. Some new small robots such as ABB, KUKA, FANUC, etc. can basically reach 5-6 m/s. We take the robot's speed as 4 m/s. During the transportation process, the robot does not consider the problem of congestion. It is only related to its load weight and drives at a constant speed between the two tasks. In delivery services, an effective delivery schedule achieved by minimizing the total travel distance is very important. In addition, our study considered the time window of customer service, that is, to provide service to each customer in the earliest and latest time period.
## 2 Background and Related Work
### VANET Applications and Classifications  
VANET primarily aims to provide both safety and non-safety assistance through various applications which can be classified into two main groups: message and file delivery, and internet connectivity. Safety applications are prioritized in VANETs. However, transmission collisions can occur when multiple safety messages need to be sent simultaneously. Localization techniques can be beneficial for certain VANET applications, but accurately determining the physical location of nodes can be challenging. GPS receivers with a Geographic Information System (GIS) are commonly used for mapping location, but their accuracy (up to 20-30 m) is limited. This makes it difficult for them to work indoors or in urban environments where higher reliability and accuracy are important.  
For safety-critical applications, combining GPS information with other localization techniques such as cellular localization, and image/video localization, may be necessary for enhanced accuracy and security. While VANET applications can function without localization, incorporating localization can improve the system performance when the vehicle's position is known (Table 2).  
VANETs use short-range networks for vehicle communication, allowing drivers to exchange messages with neighboring drivers [16; 17]. This includes exchanging information about road safety, traffic conditions, and even parking spaces. [PERSON] et al. [18] investigated the costs of searching for parking spaces and also closely investigated two cars on the move searching for a parking spot [19].
# Video Streaming Adaptive QoS Routing with Resource Reservation (VQoSRR) Model for SDN Networks
## 2 Related Work
However, it does not involve a mechanism to reserve the required resources [3]. It also imposes an overhead because it gathers traffic status information actively. On the other hand, using resource reservation alone provides a mechanism for reserving network resources. Although, it does not provide a method for determining which network path has sufficient resources for the requested QoS [3]. In addition, most studies focused on enhancing network performance without considering video streaming thresholds to ensure QoS/QoE requirements are maintained. Moreover, there have been multiple mechanisms in the traditional Internet for providing QoS in intra-domain and inter-domain networks, such as integrated services (IntServ) [25], differentiated services (DiffServ) [26], and multiprotocol label switching MPLS [27]. Nevertheless, they have restricted deployment due to the absence of global network views inherited from existing best effort networks. In addition, these techniques cannot adapt to changing conditions on the network topology. Furthermore, the lack of centralized and automated network configurations could cause significant administrative overhead in large networks, leading to network failures and difficulty applying policy enforcement. In our approach, instead, video flows are dynamically placed on QoS guaranteed routes that meet multiple individual QoE metrics, while reducing the overhead of obtaining network status by pre-computing alternative paths. Additionally, we reserve resources for network flows according to their importance to avoid degradation of video stream quality, especially during high network loads. A comparison of the proposed approach and other SDN QoS architectures is shown in Table 1.
## 4 Conclusions  
The AD method is a simple, rapid film deposition method at room temperature, in which ZnO films could be formed by direct bombardment of accelerated ZnO powder onto the FTO substrates. In this study, the effect of deposition cycles on the thickness and optical properties of the AZ films was first investigated. Next, the DSSCs' PCE using the AZ films were evaluated. The PCE increased from 0.73% to 1.78% with an increased deposition cycle from one (AZ-I) to two (AZ-II) cycles. However, the PCE % decreased to 0.19% when the AZ-III film (three cycles) was used due to the formation of loose particle agglomerates on the surface and a reduced thickness of aerosol-deposited ZnO film. The result indicated that abrasion of deposited ZnO thin film occurred with subsequent deposition cycles. The AZ-III contained crystal defects as indicated by the small \(\mathrm{I_{UV}}/\mathrm{I_{Vis}}\) ratio (0.53) in the RTPL analysis. The findings from this study could be beneficial for further development of scalable DSSCs using the AD method with low environmental impact (without high temperature annealing) and film deposition on substrates with low melting points.  
Conceptualization, M.Z.T. and W.K.T.; methodology, M.Z.T. and W.K.T.; formal analysis, M.Z.T. and S.-Y.P.; investigation, M.Z.T.; resources, W.K.T., G.K. and H.M.; writing--original draft preparation, M.Z.T.; writing--review and editing, W.K.T., H.M., G.K., A.M. and S.-Y.P.; supervision, S.-Y.P. and A.M.; funding acquisition, S.-Y.P., W.K.T. and H.M. All authors have read and agreed to the published version of the manuscript.  
This research was funded by AUN/SEED-Net grant number 304.PBAHAN.6050390/J135 and The Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number 18H05452, 22H01790 and 22K04737.  
Not applicable.  
The data presented in this study are available upon request.  
The authors want to express appreciation for the financial support from AUN/SEED-Net (Grant number: 304.PBAHAN.6050390/J135) and The JSPS KAKENHI Grant Number 18H05452, 22H01790 and 22K04737. [PERSON] of the Toyohashi University of Technology is acknowledged for the photoluminescence measurements.  
The authors declare no conflict of interest.
# FPGA-Based Pulse Compressor for Ultra Low Latency Visible Light Communications
## 2 Pulse Compression Basics
### Distance Gain in VLC through Pulse Compression  
The SNR gain that the chirp modulation produces can be exploited to extend the communication distance or the data rate in VLC. In this work we focus in particular on the distance gain. In this paragraph, a simple model on the relation between the maximum communication distance and chirp length is obtained.  
The amplitude of the radiated light is expected to decay proportionally to the square of the distance R between the LED and the receiver [25]; on the other hand, the same amplitude increases with the radix of the chirp duration \(T\) and bandwidth \(B\) (see above). Thus, for a receiver with a given input noise and sensitivity, the distance and chirp duration are approximatively related through:  
\[K=\frac{\sqrt{BT}}{R^{2}} \tag{3}\]  
where \(K\) is a constant that depends on several factors like the receiver sensitivity, the LED power, the optical gain of the link, the Bit-Error-Rate (BER), etc. For example, increasing N-fold the chirp duration and leaving all of the other parameters unaltered produces:  
\[K=\frac{\sqrt{BT}}{R_{1}^{2}}=\frac{\sqrt{BNT}}{R_{2}^{2}} \tag{4}\]  
where \(R_{1}\) and \(R_{2}\) are the communication distances achieved with chirps of length \(T\) and \(NT\), respectively. From (4) we finally have:  
\[R_{2}=\sqrt[4]{N}\cdot R_{1} \tag{5}\]
## 4 Results  
### Preprocessing Results  
As shown in Figure 13, the degree of change because of CLAHE was measured by analyzing and measuring the pixels of the bead, which represent the background part and welding defect part. In the raw image, the pixel value of the bead, the background part, was 80, whereas the pixel value of the defect part was 75, showing a difference of 5. In the CLAHE-applied image, the pixel value of the bead was 125, whereas the pixel value of the defect part was 98, showing a difference of 27. Table 2 shows the results of the raw image before applying CLAHE and the image after applying CLAHE by improving the entire defect data. Object detection in computer vision is mainly performed using pattern recognition. The recall becomes low unless the difference between the object and the background part is above a certain level [26]. Therefore, the defects in the data were divided into three levels, and the objects were classified based on the difference in pixels between the object and the background part. Level 1 is a difference of 30 pixels or more between the bead and defect, Level 2 is a difference of 15-30, and Level 3 is a difference of 0-15. The higher the level, the
# The Effects of Augmented Reality Interaction Techniques on Egocentric Distance Estimation Accuracy
## 3 Results
### Accuracy of Estimation  
As shown in Figure 4, the mean accuracy of the indirect cursor technique was higher (mean = 0.95, SD = 0.01) than the mean accuracy of the direct cursor technique (mean = 0.90, SD = 0.01) at all tested egocentric distances and IDs. The ANOVA exposed significant differences in accuracy between the two techniques (F [1; 13] = 12.26, \(p\) < 0.05). We found a significant main effect of egocentric distance (F [1.340, 17.419] = 6.719, \(p\) < 0.05) on accuracy. [PERSON] post-hoc test revealed that participants significantly performed more accurate judgment when the targets were 150 cm (\(p\) < 0.05) than when they were 120 cm and 90 cm from the participant. We found a two-way interaction between technique and egocentric distance (F [2; 26] = 8.759, \(p\) < 0.05) on accuracy. The post-hoc test showed that participants using direct pointing were significantly (\(p\) < 0.05) more precise when the targets were displayed at a distance of 150 cm than when they were displayed at the other distances. For the indirect cursor technique, we found no significant difference of distance on accuracy. In the direct pointing technique, the overall egocentric distance estimations were 96.797 cm (SD = 2.569 cm), 127.492 cm (SD = 2.151 cm), and 156.867 cm (SD = 1.543 cm) at distances of 90 cm, 120 cm, and 150 cm from the participant, respectively. These results showed that the overall egocentric distances were overestimated. Similarly, in the indirect cursor technique, the corresponding overall estimations were 86.015 cm (SD = 1.169 cm), 115.612 cm (SD = 1.295 cm), and 143.281 cm (SD = 1.794 cm) at 90 cm, 120 cm, and 150 cm, respectively. Unlike those with the direct pointing technique, the overall egocentric distances were underestimated.  
The effect of ID on egocentric distance estimation accuracy was also examined. The results showed that the main effect of ID on the accuracy of distance judgement was significant (F [1.35, 17.58] = 8.24, \(p\) < 0.05). The highest mean accuracy was 0.934 (SD = 0.007) at a low level of ID, followed by 0.927 (SD = 0.008) at a medium level of ID, and then 0.919 (SD = 0.009) at a high level of ID. However, the interaction between ID and interaction technique was not significant (F [1.35, 17.49] = 2.94, \(p\) > 0.05).
# Voxel-Based Digital Twin Framework for Earthwork Construction
## 3 Methodology
### Proposed Digital Twin Architecture
#### 3.2.5 Monitoring and Analysis Module  
The monitoring and analysis module uses the as-planned and as-built voxels to support the real-time tracking of progress. It enables monitoring the productivity of earthwork construction at the voxel level. The key characteristic of this module is that it not only tracks volumetric information but also material information. Additionally, it continuously provides earthwork quality information using a visualization model of the deviation between as-planned and as-built voxels. This module plays a significant role in facilitating project managers to make decisions based on data-driven analysis, ensuring that the project is completed according to the planned objectives.  
These five connected modules are linked together to form a robust and intelligent digital twin tailored for earthwork construction. Integrating voxel-based modeling, game-engine-supported model-equipment simulation, semantic data modeling, and real-time sensing data forms an advanced platform for earthwork construction visualization, simulation, and monitoring.
## 3 Results
### Synthesis and Characterization of the Complexes
Parallel-mode electron paramagnetic resonance (EPR) spectroscopy (microwave field B\({}_{1}\) is parallel to the static field B\({}_{0}\)) enables the detection of EPR transitions in non-Kramer spin systems (with integer electron spins), often unobservable using conventional perpendicular-mode EPR (B\({}_{1}\perp\) B\({}_{0}\)) [37]. Mn\({}^{3+}\) has an integer electron spin, \(S\) = 2, and has been shown in frozen solutions to develop a characteristic six-line pattern in parallel-mode EPR [38]. Figure 2 collects the parallel-mode EPR spectra measured for four complexes studied in the present work. For complexes **1** and **3**, the six-line EPR pattern is centered at \(g_{eff}\) = 8.08 and split by a hyperfine coupling \(A_{\parallel}\) = 42-43 G due to a \({}^{55}\)Mn nuclear spin (\(I\) = 5/2). For compounds **5** and **6**, the EPR spectra are distinctly different, with the six-line pattern centered at \(g_{eff}\) = 8.16 and split by \(A_{\parallel}\) = 49 G. The larger \(g_{eff}\) in **5** and **6** indicates a stronger ZFS rhombicity (a larger orthorhombic distortion in the ligand field symmetry) in these complexes [39]. The larger \(A_{\parallel}\) may be attributed to a decreased covalency of the chelating N\({}_{2}\)O\({}_{2}\) atoms because of a wider bite-angle (longer Mn-O and Mn-N distances) in **5** and **6** as compared to **1** and **3**[39]. Cyclic voltammetry indicates that the electrochemical behavior of the complexes, with both reduction and oxidation waves, can be defined as quasi-reversible. The low E\({}_{1/2}\) values in the range \(-\)54 to \(-\)196 mV are in accordance with the electron-donor character for the selected substituents (methoxy or ethoxy) on the phenolato rings. The redox waves, corresponding to the Mn\({}^{\text{III}}\)/Mn\({}^{\text{II}}\) redox couple of the complexes, exhibit peak to peak separation in the range 80 to 140 mV, which varies with the scan rate, showing a more reversible character at slower scan rates. Table 3 collects the E\({}_{\text{ox}}\)(Mn\({}^{\text{II}}\)\(\rightarrow\) Mn\({}^{\text{III}}\)) and E\({}_{\text{red}}\)(Mn\({}^{\text{III}}\)\(\rightarrow\) Mn\({}^{\text{II}}\)) potentials for the complexes. The cyclic voltammogram for **3** is illustrated in Figure 3.  
Figure 1: Example of paramagnetic \({}^{1}\)H nuclear magnetic resonance (NMR) spectrum, in this case corresponding to **6**. Figure 2: Parallel-mode electron paramagnetic resonance (EPR) spectra of **1, 3, 5** and **6** in frozen Toluene: dimethylformamide: EtOH (2:1:drop) solutions. EPR conditions: microwave frequency, 9.37 GHz; temperature, 6 K; microwave power, 2 mW.
## 3 Cyber-Physical Risk Assessment Approach
### Types of Physical Impact  
Physical impacts caused by disruption of a critical infrastructure are hard to quantify due to their inherent unmeasurable nature (e.g., social impact) and to different terminologies, in terms of risk, used by critical infrastructure stakeholders [32]. The problem is amplified when security issues of data breach and their impacts are considered, which are mainly based on economic losses [66,67]. However, a disruption of an IoT enabled transportation infrastructure due to vulnerability exploitation, will result in identical types of physical impacts as for a critical transportation infrastructure due to natural hazards or man-made attacks. Therefore, the following types of physical impact are considered: _User safety_, _Economic losses_, _Social and political impact_ as suggested by risk assessment policies within EU member states [32], individual national risk guidelines [68] and physical impacts from previous cyber events (e.g., casualties, economic losses) [11,12]. _User safety_ describes the number of casualties. Assessors should consider the occupancy capacity of their transportation infrastructure during the cyber-physical attack scenario. _Economic losses_ (monetary loss) describe the economic losses. Assessors should consider direct and indirect losses coming from the construction and repair/replacement costs of IoT application, disruption of primary services for hours or days, and due to business disruption. _Social and political impact_ describes the number of people affected by the cyber-physical attack, due to violation of public security, sense of fear and outrage within people, unstable environment etc. The assessment of physical impact (\(\text{X}_{\text{Pl}}\)) should be accomplished based on the sets of criteria established by stakeholders [68]. For the purposes of this approach, Table 3 presents the criteria, according to which physical impacts can be assessed following the suggestions of Canadian risk guidelines applicable for Critical Infrastructure Protection and Emergency Preparedness [69].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Level/Score (\(\text{X}_{\text{Pl}}\))** & **User Safety** & **Economic Losses** & **Social and Political Impact** \\ \hline
**Very Low/** &
\begin{tabular}{c} **Slight** \\ **injuries** \\ \end{tabular} & No losses & No impact \\ \hline
**Low/** & \begin{tabular}{c} Less than 100 \\ people \\ \end{tabular} & \
\begin{tabular}{c} Under \$10 million, \\ Closure for hours \\ \end{tabular} &
\begin{tabular}{c} Public perceives low \\ impact \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 3: Types of physical impacts (adapted to this study from [69]).  
The criteria, according to which physical impacts can be assessed, as shown in Table 3, can be modified according to the guidelines of individual national risk guidelines, as adapted in this study following the suggestions of Canadian risk guidelines applicable for Critical Infrastructure Protection and Emergency Preparedness [69].
## 3 Results and Discussion
Because the three reactions have their maximum cross sections at different proton energies, the produced isotopes will have maximum concentrations at different depths in the target material and thus have different mean distances to diffuse before reaching the surface. Therefore \({}^{124}\)I, which in \({}^{\mathrm{nat}}\)Te has a maximum cross section at \(>\)14 MeV, will be produced very close to the surface of the target and diffuse out the fastest, compared to \({}^{130}\)I which has its maximum cross section at a much lower energy and thus deeper in the target. This demonstrates the importance of optimizing the distillation parameters individually for each isotope of iodine one wishes to produce. Assuming that distillation parameters for all iodine isotopes are identical is an easy mistake to make when optimizing with natural tellurium, but one set of distillation parameters is not representative for all isotopes and assuming so, can have a pronounced effect on the distillation yield. There is debate about the chemical form of the distilled iodine. Ionic forms must be expected to be less volatile and therefore less consistent with the facile distillation of the iodine which is observed. Molecular iodine seems improbable due to the stoichiometry of the infinitesimal amount of iodine produced. If iodine atoms should encounter by diffusion inside the target material, to unite and form molecular iodine before distilling out, the distillation process would be expected to be very slow, which it is not. If interhalogens were the distilled form, formation of these would furthermore be complicated by gradual exhaustion of halogens such as chlorine and bromine in the target material. A 1 GBq production of \({}^{124}\)I corresponds to approximately 1 nmol of atomic iodine. With targets being used up to 50 times, it seems unlikely that the required amount of halogens should be present in the target matrix. Also due to the volatile character of interhalogens the trapping at room temperature should be hampered; we had an ascarite trap installed and saw no radioactive release during the distillation. Finally there is the possibility that iodine distils as free radicals. I\({}_{2}\) dissociation into free radicals is 18% at 460 \({}^{\circ}\)C [14], indicating that this is a fairly stable species at high temperatures. This  
Figure 7: Using SRIM software by [PERSON], the cross sections were converted from being a function of energy to being a function of depth in the target material, with a starting energy of 14.8 MeV. The cross sections have been summed and normalized to facilitate comparison of depths. would require no rate limiting formation of chemical species, and should distil easily. As these are the characteristics that we observe, we believe that it is free radicals distilling from the targets.