esa-sceva/satcom-chunk-collection huggingface dataset:
# High-Speed GaN-Based Superluminescent Diode for 4.57 Gbps Visible Light Communication
## 4 Discussion  
Table 1 summarizes the device performance of recently reported GaN-based SLDs for high-speed modulation applications. The emission wavelength, spectral FWHM, modulation bandwidth, achieved data rate and modulation scheme are compared. In 2016, a group of researchers from KAUST utilized a 405 nm SLD as a transmitter to transmit data at 1.3 Gbps using an OOK modulation scheme [12]. In 2018, the same group reported a blue SLD-based VLC link that enabled a data rate of 1.45 Gbps using an NRZ-OOK modulation scheme [5]. In 2019, KAUST and Fudan University utilized a 443 nm c-GaN SLD with a bit-loading DMT modulation scheme, and reached a data rate of 3.4 Gbps [8]. In 2020, a 443 nm SLD on a c-GaN substrate was demonstrated with a 750 MHz modulation bandwidth. A data rate of 3.8 Gbps was reported [13]. The University of New Mexico successfully fabricated an m-GaN SLD and reached a modulation bandwidth of 2.5 GHz [14]. A c-GaN SLD-based VLC system with an MAPNN-CAP modulation scheme was reported in 2020, which contained neural network applications [15]. In this work, we reported a high-speed VLC system with a data  
Figure 6: Average QAM order versus DC bias current and signal VPP. SE represents the spectrum efficiency.  
Figure 7: (**a**) Transmission data rate and BER versus modulation bandwidth; (**b**) subcarrier SNR and bit allocation. Insets: constellation diagrams of 64 QAM, 32 QAM, 16 QAM, 8 QAM, 4 QAM and 2 QAM (BPSK).  
rate of 4.57 Gbps, utilizing a 442 nm SLD as a transmitter, partially attributed to the optimized design and fabrication of the SLD device, and the high spectral efficiency of the bit-loading modulation scheme. The record data transmission rate achieved may be attributed to the high-performance blue SLD and the optimized adaptive DMT modulation scheme used for higher spectral efficiency, which approaches the Shannon limit. Compared with other SLDs, the demonstrated SLD shows a large modulation bandwidth, as well as a good frequency response in the range of 0-1.35 GHz. The narrow (\(\sim\)2 \(\upmu\)m) ridge waveguide structure might be one of the main factors enabling high-frequency performance in the compact SLD emitter. A device with a small form factor enjoys a reduced RC time constant, making it promising for high-speed operations.
## 4 Experimental Results and Discussion
### Comparisons with Best Known Results
In Table 3, the average number of vehicle as well as the average traveled distance, of both the best-published (BP) solutions and the solutions produced by the MOLNS algorithm, are presented for each case. In addition, the percentage deviation between the solutions was calculated for each objective (deviation in the NV and deviation in the TD). More specifically, the mean deviation for all cases concerning the number of vehicles is 6.63%, and 10.60% for the traveled distance. On the contrary, the corresponding percentage in the TD in [PERSON]'s instances is 2.85%, indicating that the quality of results is affected to a small extent when the number of customers increases. However, the mean computational time needed (Time column) for each case to be solved remains reasonable and low, given the volume of customers.
# Multi-Dimensional Sparse-Coded Ambient Backscatter Communication for Massive IoT Networks
## 2 System Model
### Channel Model
The frequency-domain representation of the channels can be obtained by  
\[\hat{\mathbf{f}}_{n,u}=\mathbf{\Omega}^{-1}[\mathbf{f}_{n,u}^{T}\ \mathbf{O}_{L-L_{\mathbf{f}_{n,u}}}^{T}]^{T}\in\mathbb{C}^{L\times 1}. \tag{9}\]  
Likewise, the time-domain representation is given by  
\[\mathbf{F}_{n,u}^{+}=\sum_{l^{\prime}=1}^{L_{\mathbf{f}_{n,u}}}f_{n,u}(l^{ \prime})\left(\mathbf{J}_{L}^{+}\right)^{l^{\prime}-1}\in\mathbb{C}^{L\times L },\quad\mathbf{F}_{n,u}^{-}=\sum_{l^{\prime}=1}^{L_{\mathbf{f}_{n,u}}}f_{n,u }(l^{\prime})\left(\mathbf{J}_{L}^{-}\right)^{L-l^{\prime}+1}\in\where \(d_{T_{n},R}\) denotes the distance from the tag \(n\) to the reader. The channels in frequency domain are represented by  
\[\hat{\mathbf{g}}_{n}=\mathbf{\Omega}^{-1}[\mathbf{g}_{n}^{T}\mathbf{ O}_{L-L_{\mathbf{g}_{n}}}^{T}]^{T}\in\mathbb{C}^{L\times 1}. \tag{12}\]  
In the similar way, the time-domain representation is given by  
\[\mathbf{G}_{n}^{+}=\sum_{l^{\prime}=1}^{L_{\mathbf{g}_{n}}}g_{n}(l^{\prime}) \left(\mathbf{J}_{L}^{+}\right)^{l^{\prime}-1}\in\mathbb{C}^{L\times L},\quad \mathbf{G}_{n}^{-}=\sum_{l^{\prime}=1}^{L_{\mathbf{g}_{n}}}g_{n}(l^{\prime}) \left(\mathbf{J}_{L}^{-}\right)^{L-l^{\prime}+1}\in\mathbb{C}^{L\times L}. \tag{13}\]  
When the time-domain ambient signals \(\mathbf{s}_{u,k}\), \(u=1,\cdots,U\), \(k=1,\cdots,K\) are emitted from the sources, these signals can be received by \(N\) multiple tags after faded by the forward channels \(\mathbf{f}_{n,u}\). Hence, the incident signal at the tag's antenna can be expressed by [25]  
\[\mathbf{y}_{k,n}=\sum_{u=1}^{U}\left(\mathbf{F}_{n,u}^{+}\mathbf{s}_{u,k}+ \mathbf{F}_{n,u}^{-}\mathbf{s}_{u,k-1}\right)\in\mathbb{C}^{L\times 1}. \tag{14}\]  
It is noteworthy that there are \(U\) OFDM carriers interfering with each other as well as intersymbol interference (ISI) \(\mathbf{s}_{u,k-1}\) from the previous \((k-1)\)-th time slot rather than a single carrier from frequency-flat fading channel. Then, these carriers \(\mathbf{y}_{k,n}\) are utilized for both the ambient energy harvesting and data modulation at the tags. In the following section, we discuss a design criteria of the proposed sparse codes toward these goals.
# Research on the Principle of a New Flexible Screw Conveyor and Its Power Consumption
## 2 Analysis of the Mechanical Properties of a Single Flexible Blade
### The Structural Parameters Analysis of the Flexible Blade  
The material of the flexible blade is wear-resistant fiber. The flexible screw diameter is slightly longer than the spiral pipe's diameter. According to the principle of material mechanics [6; 7; 8], the flexible blade is bent and contacts the inner wall of the tube. With the fibers rotation, there is no material-gathering phenomenon occurring. The structural parameters of the flexible blade are shown in Figure 3.  
Based on Formula (1):  
\[l=\frac{\pi{d_{\text{s}}}^{2}}{4}\sqrt{\frac{E\pi}{dN_{1}}} \tag{4}\]  
\(d_{\text{s}}\) is from 0.5 mm to 2.5 mm. \(E\) is 3.2 \(\times\) 10\({}^{9}\) N/m\({}^{2}\). \(dN_{1}\) = 100 N, 1.5625 mm \(\leq l\leq\) 39 mm, Stress must satisfy the condition that, less than the allowable stress [\(\sigma\)], the material or institutions allowable stress is the national standard.  
\[\sigma_{\text{max}}\leq[\sigma] \tag{5}\]  
Figure 3: Flexible blade characteristics.  
Based on Formula (2), \(l\) is:  
\[l\leq\frac{0.2{d_{\mathrm{s}}}^{3}[\sigma]}{\mu_{1}\mathrm{d}N_{1}}\]  
[\(\sigma\)] of nylon 66 is 12 MPa, \(dN_{1}\) = 100 N, the friction factor between plastic and plastic \(\mu_{k}\) is 0.4, the calculation is  
\[1.5\;\mathrm{mm}\leq l\leq 187.5\;\mathrm{mm}\]  
The design should meet the stiffness conditions as follow:  
\[\omega_{\mathrm{max}}=\frac{64f_{3}l^{3}}{3\pi{E{d_{\mathrm{s}}}^{4}}}\leq[ \omega] \tag{6}\]  
The formula is:  
\[l\leq\frac{1}{8}\sqrt[3]{\frac{3\pi{E{d_{\mathrm{s}}}^{4}}[\omega]}{f_{3}}} \tag{7}\]  
With \(d_{\mathrm{s}}\) from 0.5 mm to 2.5 mm, and \(f_{3}\) = 30 N, the calculation is:  
\[6.5\;\mathrm{mm}\leq l\leq 38.75\;\mathrm{mm}\]
## 3 Background in Feature Models and Validation Mechanisms
As aforementioned, the analysis of a product line enables inferring certain information, whether a feature model or a certain configuration (c) is valid or not. Figure 1.5  
Figure 1.6  
For instance, given a configuration \(c=\{PS2\to true,A\to,A1\to true,B\to false,...\}\) is a valid configuration whether \(c\) belongs to the set of valid assignments of the formalised feature model, \(FMF\)  
Figure 1.7 List of configurations. Figure 1.8 An example of code to check signatures. In this case, the configuration is valid as previously indicated hence it belongs to the set of valid assignments. In the Table 1, relevant characteristics of the example of Figure 1 are shown, and the results of applying two operations: (1) to verify whether the model is valid (symbol ) and (2) to obtain the number of all possible configurations. When a configuration \(c\) is not valid, there are some failures (no correct assignment to features) in that configuration. The minimal diagnosis represents the explanation which makes the configuration invalid changing the value of minimal features. For simplification reasons, also a configuration could be represented as a set of only features that have value true in the assignment. In the previous example, the tuple \(c\) could be represented as the set \(C=\{PS2,A,A1\}\). **Definition 5**: _Diagnosis of Configurations. Let \(\triangle\) be the minimal diagnosis of an invalid configuration \(C\) with regard to \(FMF\) is the minimal subset of features of \(C\) that must be modified their values such that the resultant configuration \(C^{\prime}\) is a valid configuration._  
Figure 1.9  
Invalid configurations could have different \(\Delta\) which satisfies the previous assert. For instance, the configuration \(C=\{PS2,A\}\) is invalid according to the Figure 1:0 The problem is that the features \(A1\) or \(A2\) must be selected but they were not. Therefore, the minimal diagnosis could be \(\triangle_{1}=\{A1\}\) or \(\triangle_{2}=\{A2\}\). In the first minimal diagnosis, \(C^{\prime}\) is \(\{PS2,A,A1\}\) and in the second minimal diagnosis, is \(\{PS2,A,A2\}\).
###### Abstract  
This paper investigates how to optimally orient the photovoltaic solar trackers of an axis parallel to the terrain, applying the sky model of Hay-Davies. This problem has been widely studied. However, the number of studies that consider the orientation (inclination and azimuth of the terrain) is very limited. This paper provides an examination of incident solar irradiance that can be extended to terrain with variable orientation and in consideration of different azimuths of the axis of rotation. Furthermore, a case study of the south of Spain is provided, considering different inclination and orientation terrain values. The results obtained in this study indicate, as a novelty, that for lands that are not south facing, the rotation axis azimuth of solar trackers should be different from zero and adjusted to the same direction as the land azimuth in order to maximize energy production. Annual energy production is sensitive to changes in the rotation axis azimuths of solar trackers (an influence of around 3% of annual energy production).  
solar energy; single-axis solar tracker; backtracking; optimisation Article
## 4 Experiments and Results
### Robustness Analysis
#### 4.3.6 Robustness against Geometry-Property Separation  
In practice, BIM data are often parsed and converted into various formats to facilitate their use on different technical platforms. In BIM, the practice of storing geometric models  
Figure 11: Results of changes in level of detail.  
\begin{table}
\begin{tabular}{c c c} \hline
**BIM Data** & **Level of Detail** & **NC Value** \\ \hline \multirow{3}{*}{Office building} & Detailed & 1.00 \\  & Medium & 1.00 \\  & Rough & 1.00 \\ \hline \multirow{3}{*}{Gymnasium} & Detailed & 1.00 \\  & Medium & 1.00 \\  & Rough & 1.00 \\ \hline \multirow{3}{*}{Structural model} & Detailed & 1.00 \\  & Medium & 1.00 \\  & Rough & 1.00 \\ \hline \end{tabular}
\end{table}
Table 8: Results of changes in the level of detail.  
and attributes separately is referred to as geometry-property separation. This process typically involves geometry-property separation, where geometric and attribute information is classified and managed in different formats. However, this separation can potentially affect the watermark information carried by the data. To evaluate the robustness of our watermarking algorithm against geometry-property separation attacks, we conducted experiments in which BIM data in RVT format were converted into FBX geometry format and JSON text format, and watermark extraction was performed on the two data formats separately. The experimental results are presented in Table 9.  
As shown in Table 9, the watermark extraction of the office building model was not affected by the number-mode separation, and the watermark extraction of the gymnasium and structure models showed only slight effects. Nonetheless, both the watermark NC values were higher than 0.98, which significantly exceeds the threshold value of 0.75, indicating that the watermark information was essentially complete. Therefore, our algorithm exhibited superior robustness against geometry-property separation attacks on BIM data and could ensure the integrity of the watermark information. Furthermore, the experimental results illustrate that the proposed algorithm is not only resistant to such attacks, but also applicable to data with only geometric information or only attribute information, such as building management models.
## 4 Evaluation and Results
\begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Questions** & **Mean** & **s.d.** & **Min** & **Max** \\ \hline
1. I liked very much playing with the video games & 2.75 & 1.16 & 1 & 4 \\
2. I find the video games appropriated for my age & 2.63 & 1.19 & 1 & 4 \\
3. I liked very much the concept of playing with the elements of the park inside HybridPLAY & 2.88 & 1.36 & 1 & 4 \\
4. I find it very easy to collaborate with other people in HybridPLAY & 3.13 & 0.83 & 2 & 4 \\
5. I would like to play more with HybridPLAY & 2.50 & 1.20 & 1 & 4 \\
6. I would like to recommend others to play with HybridPLAY & 2.75 & 1.04 & 1 & 4 \\
7. I think that I would go more frequently to the park if I had a HybridPLAY device & 2.50 & 1.31 & 1 & 4 \\
8. I think that the use of HybridPLAY can foster me to do more exercise & 2.25 & 1.28 & 0 & 4 \\
9. I think that HybridPLAY is interesting to do exercise with my partner or colleagues & 2.75 & 1.49 & 0 & 4 \\
10. I think that HybridPLAY can help me to be more in touch with the new technologies & 2.88 & 1.13 & 1 & 4 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results of the individuals’ satisfaction questionnaires (mean, standard deviation, minimum and maximum). particularly remarkable that question 4, which deals with the collaboration capabilities of HybridPLAY, gets very high results with a minimum value of 2 and a mean value of 3.13, highlighting the potential of this system in this area. Additionally, we asked users to give us further feedback on the tool. Most of them highlighted that it was a very interesting idea. Some of them acknowledged that it may help them exercise and socialize, fostering their desire for performing outdoor activities. Regarding to the complexity of the mini-games, they found all of them easy to follow, although some users had a few problems with the right/left indications, either when giving instructions (the person holding the mobile phone) or while doing the exercise (the person interacting with the OFE). Overall, we had the feeling that they really enjoyed the experience.
## 3 Dynamic Response Topology Optimization with Condensed Localized Mortar Method
### Optimization Formulation with Condensed Localized Mortar Method
The sensitivity of the objective function is calculated by using the adjoint method, as follows:  
\[\frac{\partial J_{d}}{\partial\eta_{e}}=\frac{\partial J_{d}}{\partial\eta_{e }}+\int\limits_{0}^{t_{f}}\mathbf{\lambda}^{T}\frac{\partial}{\partial\eta_{e }}(\hat{\mathbf{M}}\ddot{\hat{\mathbf{u}}}+\hat{\mathbf{K}}\hat{\mathbf{u}}- \hat{\mathbf{F}})\text{dt}=\int\limits_{0}^{t_{f}}\left[\left\{\frac{\partial c }{\partial\eta_{e}}+\frac{\partial\hat{\mathbf{u}}}{\partial\eta_{e}}^{T} \frac{\partial c}{\partial\hat{\mathbf{u}}}\right\}+\left\{\mathbf{\lambda}^{T} \frac{\partial}{\partial\eta_{e}}(\hat{\mathbf{M}}\ddot{\hat{\mathbf{u}}}+ \hat{\mathbf{K}}\hat{\mathbf{u}})\right\}\right]\text{dt} \tag{19}\]  
Subsequently, by integrating-by-parts and re-organizing, Equation (19) yields:  
\[\frac{\partial J_{d}}{\partial\eta_{e}}=\int\limits_{0}^{t_{f}}\left[\mathbf{ \lambda}^{T}\frac{\partial\hat{\mathbf{M}}}{\partial\eta_{e}}\ddot{\hat{ \mathbf{u}}}+\mathbf{\lambda}^{T}\frac{\partial\hat{\mathbf{K}}}{\partial\eta_ {e}}\dot{\hat{\mathbf{u}}}+\frac{\partial c}{\partial\eta_{e}}\right]\text{dt}+ \int\limits_{0}^{t_{f}}\left[\frac{\partial\hat{\mathbf{u}}}{\partial\eta_{e}}^{T }\left(\frac{\partial c}{\partial\hat{\mathbf{u}}}+\hat{\mathbf{M}}\ddot{ \hat{\mathbf{\lambda}}}+\hat{\mathbf{K}}\hat{\mathbf{\lambda}}\right)\right] \text{dt}+\left.\left[\frac{\partial\hat{\mathbf{u}}}{\partial\eta_{e}}^{T} \hat{\mathbf{M}}\dot{\mathbf{\lambda}}-\frac{\partial\hat{\mathbf{u}}}{\partial \eta_{e}}^{T}\hat{\mathbf{M}}\dot{\hat{\mathbf{\lambda}}}\right]\right|_{t=t_ {f}} \tag{20}\]In Equation (20), to obtain the adjoint variable \(\uplambda_{\text{adj}}\) that is arbitrarily inserted to simplify the sensitivity process, the following differential equation must be solved:  
\[\hat{\mathbf{M}}\tilde{\mathbf{\Lambda}}+\hat{\mathbf{K}}\mathbf{\Lambda}=- \frac{\partial c}{\partial\tilde{\mathbf{u}}},\;\mathbf{t}\in\left[0,t_{f} \right]\;\text{where}\;\uplambda_{t_{f}}=0,\dot{\uplambda}_{t_{f}}=0 \tag{21}\]  
where Equation (21) is a similar form of the equation of motion (11), which is widely known. Therefore, the adjoint variable is transformed by \(\Lambda(s)=\uplambda_{\text{adj}}(t_{f}-s)\) in order to make an equivalent form, and Equation (21) is re-written as:  
\[\hat{\mathbf{M}}\tilde{\Lambda}(s)+\hat{\mathbf{K}}\Lambda(s)=-\left.\frac{ \partial c}{\partial\tilde{\mathbf{u}}}\right|_{t_{f}-s},\;\mathbf{s}\in\left[ 0,t_{f}\right]\;\text{where}\;\Lambda(0)=0,\dot{\Lambda}(0)=0 \tag{22}\]  
Since the form of Equation (22) is exactly identical to that of Equation (11), the transformed adjoint variable \(\Lambda(s)\) can be easily calculated, along with the adjoint variable \(\uplambda_{\text{adj}}\) through an inverse transformation.
# Monitoring a Pre-Normative Multi-Family Housing Case-Study in a Mediterranean Climate
## 4 Results
### Outdoor Temperature  
In order to analyze the evolution of the monitored outdoor temperature, weather data from the Spanish Weather for Energy Calculations (SWEC) database [33] are used. Values from a variety of environmental parameters have been gathered on an hourly basis for the past 20 years in the weather station of San Pablo airport, in Seville. The graph shows that average monthly outdoor temperature values recorded in situ are superior to the values from the database in the spring and summer seasons, while these values from the monitoring campaign decrease in autumn, to eventually increase in winter to a higher temperature trend than that of the database values (Figure 8).
## 2 Background and Literature Review
### Methods for Dynamic Malware Analysis  
In order to perform a forensic dynamic malware analysis, it is of the utmost importance to first create a secure environment in which the malware can be safely executed. One of the fundamental aspects of this process is the creation of an isolated environment. This is because the analysis of malware requires the complete disabling of antivirus software, along with the termination of any other security settings present on the client system. It is also imperative to prevent the machine from accessing the World Wide Web, as this enables the downloading of more unpredictable code and the transmission of information to a command and control (C2) server. The majority of malware developers incorporate a kill switch into their code, which deletes the malware from the disk in the event of a failed web request. In this regard, INetSim is a particularly useful tool. This tool is part of the popular REMnux distribution [20]. By setting this toolkit up as a virtual machine, it is possible to configure the machine's IP as the primary DNS server of the victim's machine, thereby enabling the malware to receive successful web responses and believe it has web access. Should the malware then attempt to download another payload, INetSim effectively simulates a download, making it even more challenging for the malware to discern that it is being examined.  
In order to further reverse-engineer the malware, it is useful to employ the network analysis tool WireShark in order to gain insight into the network activities. In a recent publication, the online magazine Medium presented an informative article [21] on the subject of dynamic analysis with the network analyser WireShark. In essence, WireSharkenables the capture of network traffic in real time, thereby facilitating the extraction of potential signatures and the identification of a C2 server.  
Real-time endpoint protection software, including Microsoft Defender and Bitdefender, as well as other endpoint detection and response (EDR) software, also perform dynamic analysis. They analyse each process running on a client in real-time, assessing its potentially suspicious behaviour. Further information on EDR can be found in an article by Trellix [22].  
Combining static and dynamic malware analysis provides the fundamental tools for detecting malicious software as it attempts to enter a network, as well as for identifying previously installed malware and its potential actions. Furthermore, both static and dynamic analysis are crucial for reverse engineering software to understand its purpose and to assess its potential harmfulness.  
However, it is evident from empirical evidence that malware still manages to evade detection, leading to significant issues for the affected victims. The subsequent section investigates the limitations of these static techniques.