esa-sceva/satcom-chunk-collection huggingface dataset:
# On-Orbit Experimental Result of a Non-Deployable 430-MHz-Band Antenna Using a 1U CubeSat Structure
## 1 Introduction
On the other hand, its performance is not as good as deployable antennas due to its small size. It barely satisfies the link budget. To have a larger antenna area without deploying, one generally needs to allocate a part of the satellite surface to the antenna, which consumes a precious surface for power generation. In the past, most 1U CubeSat developers chose the performance, i.e., the antenna gain, over the reliability. According to the Nanosatellite and CubeSat Database complied by [PERSON] [9], there are 166 of 1U CubeSats that uses 430-MHz as the primary downlink frequency if we count the satellites launched up to November 2021. In the database, we can also see a photograph of each CubeSat. Judging from the photographs, we see only nine CubeSats and three projects use non-deployable antennas including BIRDS-1 [7], BIRDS-4 [10], and ITF-2 [8]. In this paper, a non-deployable antenna for the 430-MHz band using a different method from patch antennas is proposed. This uses the aluminum frame of a CubeSat as an antenna. This antenna does not require the deployable structure or occupy an external panel. This antenna was adopted as a sub-mission of the BIRDS-4 project [10] and was launched on three 1U CubeSats. This paper describes the results of the ground tests conducted before launching the satellites and the on-orbit demonstration conducted after launch. The purpose of the present paper is to propose a novel non-deployable UHF antenna for 1U CubeSats and show the on-orbit results. The novelty is to use a part of the structure as an antenna that is specified by the CubeSat standard. We target 1U or 1.5U CubeSats where the resource such as volume or surface area available to the antenna is very scarce. The proposed antenna is reliable due to its nature of non-deployable antenna and consumesthe least resources in terms of volume and area. The paper is made of eight parts. The second part introduces a Loop Hentenna and the third part introduces the BIRDS-4 project. The fourth part introduces the HNT mission of BIRDS-4. The fifth part describes ground testing. The sixth part describes on-orbit demonstration. The seventh part presents analysis of the on-orbit results. The final part includes the conclusion and details of future plans.
# Compliance of Distribution System Reactive Flows with Transmission System Requirements
## 4 Conclusions  
This paper addresses the problem of compliance of distribution systems with transmission system requirements with regards to keeping reactive power flows within limits. This objective is achieved by exploiting DER reactive power support capabilities. Compared to relevant literature, the main contribution of this work lies in the implementation of complex requirements, as the ones imposed by the Finish TSO, Fingrid. Previous approaches of the same problem have proposed a controller that in real-time reacts to the conditions on the HV/MV connection points. This paper proposes an optimisation method that considers a detailed grid model and can act predictively to the upcoming network conditions. The method relies on a quadratic program that can be efficiently solved by commercial solvers and is easily formulated into a MPC equivalent.  
Results show that the proposed method achieves DN compliance with TSO limits on reactive power exchange. Compared to the benchmark case, the proposed method achieves 100% compliance to the distribution system's reactive power import/export limits imposed by TSO requirements, compared to only 42% compliance by the benchmark QV droop method. Moreover, the proposed method utilises 60% less reactive power support from DERs. Finally, the execution time of each instance of the method is under a second, rendering it perfectly satisfactory for the requirements of the problem.  
Conceptualization, K.S., P.P. and N.H.; methodology, P.P. and N.H.; software, P.P.; validation, P.P. and N.H.; formal analysis, P.P.; investigation, P.P., N.H. and K.S.; resources, K.S. and P.P.; data curation, K.S. and P.P.; writing--original draft preparation, P.P.; writing--review and editing, P.P.; K.S., C.Z., N.H., K.K. and H.L.; visualization, P.P., N.H. and C.Z.; supervision, N.H.; project administration, N.H.; funding acquisition, K.S., K.K. and H.L. All authors have read and agreed to the published version of the manuscript.  
Part of this work was carried out in the SolarX research project with financial support provided by Business Finland, 2019-2021 (grant No. 6844/31/2018).  
The authors declare no conflict of interest.
## 3 Technology
### Current Research Challenges
#### 3.7.1 Detector Active Area  
As explained in Section 2, the collection area is a crucial parameter and the major limitation of TG SPADs applied to DO. Indeed, having a Lambertian distribution, the light exiting from diffusive media cannot be efficiently focused onto detectors featuring small active areas. The possibility to collect light with a detector featuring, e.g., a 1 cm\({}^{2}\) area would increase the signal level with respect to commercial TG detectors embedding a 100 \(\upmu\)m active area device by about five orders of magnitude (four due to the increased area and one due to the possibility to avoid optical fibers, exploiting the full numerical aperture of the detector) [61]. With respect to more advanced solutions like the compact probe embedding a 200 \(\upmu\)m diameter TG SPAD [61], used in direct contact with the tissue under investigation, it could be still possible to gain a remarkable factor of 3000 in the signal level, making a clear difference with respect to performance of state of the art devices. This increase will result in the possibility of computing the contrast produced by a localized perturbation at much later times along the recorded DTOF thanks to the increased collection of late photons, thus enhancing the depth sensitivity. To this purpose, SiPMs have been recently introduced in TD-DO [103; 104; 105; 106] giving rise to a new generation of devices [100; 107; 106]. SiPMs are large-area microelectronics single-photon detectors based on multiple SPADs, each one with an integrated quenching resistor, with a common output signal. These devices feature an active area comparable to that of PMTs or of hybrid PMTs, but being just silicon dice (i.e., microelectronic integrated circuits), they are compact, cheap and rugged, allowing their use in contact with the tissue as well as the fabrication of innovative tomographic systems. However, traditional SiPMs detectors cannot be time-gated due to the presence of the quenching resistor preventing the application of a fast voltage transition to each SPAD of the SiPM. The design of a TG large-area detector is therefore an open challenge. Furthermore, as a good SiPM detector can easily have a dark count rate of 50-100 thousand counts per second (cps) per square millimeter, a 1 cm\({}^{2}\) detector could easily feature 10 Mcps, posing serious problems like the need to work beyond the single-photon statistics with high-throughput systems [108; 109].
# Stereo Digital Image Correlation in MATLAB
## 2 Framework Theory
### Calibration
#### 2.2.1 Pinhole Camera Model  
The projection matrix \(\mathbf{Q}_{j}\), consisting of intrinsic (\(\mathbf{K}_{j}\)) and extrinsic (\(\mathbf{V}_{j}\)) parameter matrices, relates a coordinate in the world CS, \(\hat{\mathbf{x}}_{w}=\left[\begin{array}{cc}\hat{x}_{w}&\hat{y}_{w}&\hat{z}_{w}&1 \end{array}\right]^{T}\), to a coordinate in the ideal sensor CS, \(\hat{\mathbf{x}}_{s_{j}}=\left[\begin{array}{cc}\hat{x}_{s_{j}}&\hat{y}_{s_{j}}&1 \end{array}\right]^{T}\), as  
\[\alpha_{j}\hat{\mathbf{x}}_{s_{j}}=\mathbf{Q}_{j}\hat{\mathbf{x}}_{w}=\mathbf{K}_{j}\mathbf{V}_{j} \hat{\mathbf{x}}_{w}=\left[\begin{array}{ccc}\xi_{x_{j}}&c_{s_{j}}&c_{x_{j}}\\ 0&\xi_{y_{j}}&c_{y_{j}}\\ 0&0&1\end{array}\right]\left[\begin{array}{ccc}R_{1}^{11}&R_{1}^{12}&R_{1}^{ 13}&T_{j}^{1}\\ \begin{array}{ccc}R_{1}^{21}&R_{1}^{22}&R_{1}^{23}&T_{j}^{2}\\ R_{j}^{31}&R_{j}^{32}&R_{j}^{33}&T_{j}^{3}\end{array}\end{array}\right]\hat{ \mathbf{x}}_{w}. \tag{1}\]  
Here \(\alpha_{j}\) is the arbitrary scaling variable of the homogenous coordinates. First, the rotation matrix, \(\mathbf{R}_{j}\), and translation vector, \(\mathbf{T}_{j}\), transform \(\hat{\mathbf{x}}_{w}\) to the camera CS. Thereafter this 3D coordinate is projected to the ideal sensor CS using \(\mathbf{K}_{j}\) which performs four operations: (i) projects the 3D coordinate to a 2D coordinate on the plane of the CCD; (ii) scales the coordinate from metric units to units of pixels using ratios \(\xi_{x_{j}}\) and \(\xi_{y_{j}}\) in the x- and y-directions respectively; (iii) applies a translation, \(c_{x_{j}}\) and \(c_{y_{j}}\) in the x- and y-directions respectively, placing the origin of the ideal sensor CS at the top left of the image; and (iv) converts from the orthogonal camera CS to a skew ideal sensor CS using \(c_{s_{j}}\). In this work \(c_{s_{j}}=0\) since an orthogonal ideal sensor CS is assumed.  
\(\mathbf{K}_{j}\) is only dependent on the camera system and does not change if the camera position changes. In contrast, \(\mathbf{V}_{j}\) depends on the relative position and orientation between the camera and the world CS.
# Hierarchical Classification of Botnet Using Lightweight CNN
## 3 Materials and Method
### Dataset  
The Bot-IoT dataset, as discussed in [19] serves as a valuable resource for researchers and practitioners involved in network security within the Internet of Things (IoT) domain. The dataset, introduced by the authors, is designed to address the growing need for realistic and representative datasets that can aid in the analysis of botnets operating within IoT networks.  
The paper emphasizes the importance of understanding and countering security threats posed by botnets in the dynamic landscape of IoT. The dataset is crafted to capture various aspects of IoT device behavior, network traffic, and communication patterns, encompassing both normal and malicious activities. It facilitates the development, testing, and evaluation of detection and prevention mechanisms specifically tailored to IoT-based botnets. Researchers can leverage the Bot-IoT dataset to conduct experiments, validate algorithms, and advance the field of IoT security. The ultimate goal is to enhance the capabilities of network forensic analytics, providing insights and solutions to combat the evolving challenges associated with botnets in the IoT ecosystem. The dataset's significance lies in its contribution to creating a more secure IoT environment through the development and refinement of cutting-edge security measures [19].  
The dataset consists of 72 million records and encompasses 42 features, rendering it notably extensive with a substantial size of 17.87 GB. The dataset contains a hierarchical structure as depicted in Figure 1. The dataset exhibits imbalance, evident in the significant variation among the instance counts for each class, as illustrated in Figures 2 and 3. Due to the extensive size of the dataset, making it impractical to train the proposed method, we addressed this challenge by undersampling classes with more than one million instances.  
normalized using a standard scaler. The dataset is divided into training, validation, and testing sets using random selection, with a split ratio of 80%, 10%, and 10%, respectively.
## 1 Introduction
After exposure to temperatures of 150 \({}^{\circ}\)C, 200 \({}^{\circ}\)C and 250 \({}^{\circ}\)C, using heating and cooling rates of 1 \({}^{\circ}\)C/min, and 10 h of exposure for each temperature, gas permeability and porosity tests revealed microstructural changes in the mortar, namely microcracks due to the thermal expansion of the aggregates, an increase in the number of voids due to the loss of water and increased permeability for exposure temperatures above 150 \({}^{\circ}\)C.  
As mentioned, for some industrial applications or in the case of accidents (e.g., fire or blast explosion), mortars may be exposed to elevated temperatures. The influence of such exposure on the physical and mechanical properties of conventional cement-based mortars is reasonably well understood. Despite the actual concern about the behavior of lightweight mortars when exposed to elevated temperatures [33; 34; 35], the information about the influence of such exposure on the performance of thermal mortars is very scarce. In order to bridge the research gap mentioned above, the present study aims at understanding the influence of exposure to elevated temperature on the residual physical and mechanical properties of cement-based thermal mortars made of expanded clay, granular expanded cork and silica aerogel lightweight insulating aggregates. In this paper different formulations of mortars were produced, then exposed to various elevated temperatures and finally subjected to a set of tests, with the following main objectives:  
* To evaluate the influence of exposure to elevated temperatures on cement-based mortars with the incorporation of insulating aggregates (expanded clay, granular expanded cork, silica aerogel) and admixtures (air entrainer agent and rheological agent);
* To study the influence of exposure to elevated temperatures in the different mortars produced, namely on the following physical and mechanical properties: bulk density; ultrasonic pulse velocity; dynamic elasticity modulus; dynamic shear modulus and Poisson coefficient; compressive strength and thermal conductivity;
* To compare the behavior of the different mortars and understand the effects of exposure to elevated temperature on their performance and on the correlations between the most affected properties.
## 5 Proposed Models
### Architecture Overview
#### 5.3.4 Data Fusion and Multi-Task Regression Stage  
Figure 3 showcases the MSCR model, comprising six components: INT, daily INT, weekly INT, Milano Today, Social Pulse, and external weather data. While data fusion effectively enhances the deep learning model's performance, it introduces challenges regarding the fusion methodology and timing.  
To address these challenges, we adopt a **parametric matrix-based fusion** strategy. This strategy entails the integration of a learnable weight fusion layer following the LSTM modules, allowing the model to determine the data fusion method autonomously. The fusion equation is delineated as follows:  
\[y=W_{1}\circ F_{\text{C}}+W_{2}\circ F_{D}+W_{3}\circ F_{W}+W_{4}\circ F_{M}+W_ {5}\circ F_{S}+W_{6}\circ F_{E} \tag{9}\]  
where \(\circ\) denotes the Hadamard product, \(W_{1}\) through \(W_{6}\) represent the learnable weights, and \(F_{\text{C}}\) through \(F_{E}\) symbolize the outputs of each LSTM module. This fusion technique proficiently amalgamates features from varied data sources.  
For fusion timing, we employ late fusion, which combines features extracted from different networks using distinct learnable weights after the CNN and LSTM modules. This typically results in superior performance compared to early fusion methods.  
The multi-task regression layer's structure mirrors that of our previous work [13], comprising two stages: feature extraction and multi-task regression. The lower stage conducts feature extraction, conveying values to the multi-task regression layer. Inputs \(X_{1},X_{2},\ldots,X_{n}\) undergo several layers of nonlinear feature transformations via diverse deep learning architectures.  
The upper stage consists of flattened and regression layers, producing outputs for multiple tasks, denoted as \(Y_{1},Y_{2},\ldots,Y_{n}\). Multi-task learning (MTL) enhances predictions by joint training on related tasks and sharing parameters across different tasks, facilitating more efficient learning [14; 46]. This study aims to predict maximum, average, and minimum INT values within an hour, offering insights into the best, worst, and average network conditions at the forecasted time \(t\) and aiding SON management.
## 4 Modulation Techniques for Underwater VLC
### Orthogonal Frequency Division Multiplexing (OFDM)  
OFDM is a widely used modulation technique in UVLC systems for its capabilities of achieving high spectral efficiency while offering robust resistance to multipath propagation and interference. In OFDM, the data stream is split into multiple parallel subcarriers that are orthogonal to each other. This division allows for better utilization of the available bandwidth and minimizes interference between subcarriers, making it an ideal choice for UVLC systems operating in challenging underwater environments where multipath interference, caused by the reflection and scattering of light, is common [37; 38].  
One of the most crucial advantages of OFDM in UVLC is its potential to mitigate the effect caused by multipath propagation, which could be severe in an underwater communication environment by various reflections from the bottom or even other floating objects. The use of multiple orthogonal subcarriers will minimize ISI with this approach and enable higher data rates even in a distorted environment. This makes OFDM superior for use as opposed to any other single-carrier modulation technique due to the unfriendly underwater channels changing with currents of water, depth, and even optical noise constantly, as recorded in [39; 40].  
Very recently, various articles have been conducted by including some Spatial Division Transmission techniques to leverage OFDM further in the improved performance of a UVLC system. Including Subcarrier Division Duplex (SDD) and Space Division Multiplexing (SDM), among other techniques, greatly enhances bandwidth utilization for the system and reduces disturbances from underwater turbulence. These are spatial diversity techniques that make use of multiple paths to enhance reliability and capacity, thus allowing efficient transmission over longer distances or in difficult underwater conditions. A combination of OFDM with SDT techniques increases the overall data rate of the system while maintaining low BER [41].  
A state-of-the-art implementation of an OFDM-based UVLC system combined with spatial division techniques realizes up to a 560 Mbps data rate coupled with robust BER performance even in the presence of underwater turbulence. This will not only maximize the spectral efficiency of the communication system by incorporating SDT but also provide more resilience against channel impairments, which makes it suitable for high-speed underwater communication applications such as communication with AUVs or real-time underwater monitoring systems [46]. Some works have been carried out on adaptive OFDM schemes to adapt the number of subcarriers and modulation schemes according to real-time channel conditions, further enhancing the adaptiveness of the system to time-varying underwater environments for optimal performance [45].
###### Abstract  
New positioning solutions are a key factor in the pursuit of autonomous driving. Global Navigation Satellite System (GNSS) is the most common method; however, traditional systems may have high position errors due to the signal's path between the satellite and the receiver's antenna. In this work, we present a GNSS adaptive antenna with beamforming capabilities that can apply spatial filtering to mitigate interferences and improve satellite connectivity, reducing the positioning error. The array, developed with off-the-shelf GNSS antennas, was used to demonstrate the improvement of the gain comparatively to the traditional GNSS antenna, while maintaining circular polarization in all directions. A digital beamforming solution was employed with the software-defined platform based on a Xilinx ZCU216. The full system performance was tested in an anechoic chamber, where good results were obtained in both single- and multibeam scenarios, with great agreement between the simulated and measured data. The results presented in this paper validate the proposed Field-Programmable Gate Array (FPGA)-based antenna array and beamforming development platform, paving the way for the seamless and rapid design and testing of numerous antenna array geometries with up to 16 channels and beamforming algorithms, including adaptive ones. This powerful and versatile tool will accelerate research on the performance improvement of GNSS reception.  
GNSS; FPGA; digital beamforming; antenna array Article
# Performance of Solar Control Films on Building Glazing: A Literature Review
## 3 Solar Control Films
### Impact of Solar Control Films on the Main Thermal and Solar Optical Properties of Clear Glass
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**Glazing Solution** & \(\tau_{e}\) & \(\tau_{V}\) & \(\rho_{V,e}\) & \(\rho_{V,i}\) & \(\epsilon_{e}\) & \(\epsilon_{i}\) & \(g\) & **U-Value** \\  & **[-]** & **[-]** & **[-]** & **[-]** & **[-]** & **[-]** & **[-]** & **[-]** & **[W/m\({}^{2}\cdot\)K]** \\ \hline Clear single-glazing (6 mm) & 0.82 & 0.89 & 0.08 & 0.08 & 0.84 & 0.84 & 0.85 & 5.81 \\ Clear double-glazing (6 + 16 + 6 mm) & 0.68 & 0.80 & 0.15 & 0.15 & 0.84 & 0.84 & 0.75 & 2.69 \\ \hline \end{tabular}
\end{table} 
Table 1: Main solar optical and thermal properties of the glazing solutions (clear single and double-glazing) representative of common building glazing: solar transmittance, \(\tau_{e}\); visible light transmittance, \(\tau_{V}\); visible exterior reflectance, \(\rho_{V,e}\); visible interior reflectance, \(\rho_{V,i}\); external emissivity, \(\epsilon_{e}\); internal emissivity, \(\epsilon_{i}\); solar factor, \(g\); and thermal transmittance coefficient, U-value [W/m\({}^{2}\cdot\)K]. Figure 6: Ranges of values of the main thermal and solar optical properties of clear single glazing with and without different types of SCFs applied to the internal (**a**) and external (**b**) glass surfaces. thermal transmittance coefficient (lowest U of 1.83 W/(m\({}^{2}\cdot\)K), equivalent to a reduction of 32%), as previously obtained with single glazing. Figure 7b shows the ranges of the main thermal and solar optical property values of clear double glazing with and without different types of SCFs applied to the external glass surface. The changes obtained in the presence of SCFs are similar, but of less magnitude, than those obtained with single-glazing. The ranges of values presented in Figures 6 and 7 are relevant to better understanding the impact of the different types of SCFs on each clear single and double-glazing property. Selecting the type of SCFs to install in a specific glazing system depends on the solar control purpose (to increase or reduce specific glazing properties) and on the installation position (internal or external). Reflective and dual reflective SCFs should be installed in glazing systems to increase their solar and visible transmittance and, consequently, reduce solar heat gains and potential glare. Neutral, spectrally selective and ceramic films are advised to maintain the neutral appearance of the glazing (lower impact on increasing the reflectance of the glass substrate). Low emissivity films should be installed in cases where the main aim is to drastically reduce the emissivity and U-value of the glazing. The impact of SCFs on the main properties of clear glazing is more noteworthy in the case of the single-glazing substrate.