esa-sceva/satcom-chunk-collection huggingface dataset:
# Moisture Sorption Behavior of Deproteinized Sunflower Meal and Patterned Food Extrudate
## 1 Introduction  
The increase in demand for food due to the rise of the world population has led to the production of substantial numbers of by-products [1]. The incomplete use and accumulation of these by-products have a negative economic, environmental, and social impact [2]. Byproducts of food processing are rich in protein, fibers, and bioactive compounds such as phenolic substances, minerals, antioxidants, and vitamins [3; 4; 5; 6].  
Sunflower meal is a by-product from oil production with higher nutritional value compared to other by-products such as cottonseed, rapeseed, and soybean meals [7]. It is rich in proteins, essential amino acids, minerals, fibers, and polyphenols such as chlorogenic acid [8]. Numerous studies exist for the production of protein isolates from meals [9]. For example, the authors in Ref. [10] used an alkaline extraction of sunflower meal and estimated that the deproteinized sunflower meal residue was rich in dietary fibers.  
Extrusion is one of the potential processes used for the utilization of oilseed by-products like defatted flaxseed meal [11], cottonseed meal [12], canola meal [13], and sesame protein concentrate [14]. High-temperature-high-pressure treatment is also usedto utilize the sunflower meal after mixing with starch-based grits [15; 16]. According to Ref. [17], the extruded snacks produced with food by-products have positive economic sustainability and an environmental impact. The authors in Ref. [13] established that extrusion leads to a decrease in the antinutritional polyphenols of cold-press oilseed cakes, including chlorogenic acid in sunflower cakes.  
The quality, stability, and physico-chemical properties of sunflower meal and its deproteinized derivatives such as DSM and extrudates are related to their moisture content and depend on the conditions of storage (temperature and relative humidity of the air) [18; 19; 20; 21]. The equilibrium moisture content (EMC) of each product depends in a different way on the temperature and humidity conditions [22]. The net isosteric heat of sorption indicates the bond energy between water molecules and the adsorbent surface. There is a lack of experiments on the sorption behavior of DSM and the effect of extrusion on the sorption capacity of the extruded product. There are insufficient data for net isosteric heat of sorption of extruded products.  
This research was carried out to evaluate the equilibrium moisture sorption behavior of DSM and a PFE at several temperatures and air equilibrium relative humidity (\(Rh\)), as well as the suitable conditions for long-term storage of both products.
# Low-Cost Solution for Kinematic Mapping Using Spherical Camera and GNSS
###### Abstract
However, to use this method, it is necessary to have many overlapping images that contain clearly identifiable points, and it is important that the images are taken close to each other. As the name suggests, the carrier must be in motion when collecting image data, and the images taken must capture the object of interest from different positions [22; 23; 24; 25]. Many projects also deal with mapping and visualizing interior spaces using panoramic cameras in virtual museum projects [26; 27; 28]. When measuring outdoors, it is useful to equip the low-cost camera with a GNSS. As with professional mapping devices, georeferenced imagery will provide easier photo alignment, and fewer ground control points will be needed in the field. The resulting cloud accuracy depends on the type of method used. When data are collected using static photos and GNSS RTK measurements, a final point cloud accuracy of around 3 cm can be achieved. The problem comes with the kinematic method: data collection is achieved through video recording, where even in a relatively suitable environment for GNSS measurements, 2D clouds reach an accuracy of 17-20 cm. This problem is most likely due to the asynchronization of camera time and GNSS time [29]. This article focuses on mapping using the low-cost Insta360 X3 camera in conjunction with low-cost GNSS equipment [30]. For this work, software and methodologies were developed that enable georeferencing of the taken spherical images with GNSS RTK or GNSS PPK coordinates. Special attention is given to testing a novel method of image georeferencing based on a visual timestamp synchronization of the spherical camera. Furthermore, the study investigates the potential of artificial intelligence tools to improve the quality of mapping outputs, particularly in point cloud generation and orthophoto production. The article also includes tests of this method against GNSS RTK ground points and mobile scanning with the Faro Orbis device using the SLAM method.
# A MSA-YOLO Obstacle Detection Algorithm for Rail Transit in Foggy Weather
## 2 Related Work  
### Feature-Based Obstacle Detection  
Using feature extraction to identify obstacles is a traditional technical approach that demands relatively low computational power from hardware. This method involves ana lyzing specific attributes of the image, such as edges, textures, and shapes, to distinguish obstacles from the background. Due to its efficiency, feature extraction has been widely adopted in various real-time applications where computational resources are limited. [PERSON] discussed an autonomous train driving system using artificial vision algorithms to detect obstacles on railway tracks [15]. By employing the Hough transform, the system identifies rails and areas of interest and conducts real-time video analysis to detect potential obstacles, improving safety and performance. [PERSON] introduced a new method based on the Hough Transform for fast detection of lines and circles in images [16]. [PERSON] presented an image processing-based obstacle detection system using laser measurement for railway safety [17]. [PERSON] presented a method for obstacle detection on railway tracks using a moving camera with background subtraction. By comparing input and reference camera images, the method effectively detects various obstacles [18]. [PERSON] introduced an image-based obstacle detection system for automatic train supervision. It improved grayscale and binarization algorithms and used Canny edge detection with detection windows to filter out irrelevant information [19]. [PERSON] proposed a robust rail track extraction method using inverse projective mapping and the Hough transform [20]. In some straightforward scenarios, feature-based obstacle detection methods can perform effectively. These methods leverage predefined image features, allowing for reliable detection when environmental conditions are relatively simple and controlled. However, traditional feature extraction techniques may struggle with complex or dynamic environments where the appearance of obstacles can vary significantly. Thus, while effective in certain scenarios, these methods may require augmentation with more advanced techniques to ensure robust performance in diverse conditions.
# Telecommunication Technologies for Smart Grid Projects with Focus on Smart Metering Applications
## 4 Smart Metering Applications--Smart Grid Projects
### Remarks--Trends on the Smart Grid Research Field
In detail, one of these projects focuses on how the consumers could adjust their electrical device utilization according to generated energy from RES. Two of these 10 projects aim at achieving positive energy neighborhoods with an efficient integration of RES and one of them specifically refers to energy management in public areas, like ports and airports. In addition, four of these 20 projects address issues regarding the real-time LV and MV network monitoring, while another one is related only on MV network monitoring. It should be noted that in our work, the projects analysed that deal with MV smart grid issues are only the ones that combine such activities with smart metering applications. In general, the MV network is an important part of the smart grid and there have been several projects with relevant research work. According to the smart grid projects list, as it is presented in [6], there are over 30 projects, where it is explicitly stated in the projects' description that MV aspects are examined. Such aspects would be: balancing the power in the system, while the integration of RES increases; remote control and MV system automation; network management; regulating bi-directional energy flow; installation of intelligent components; dealing with faults in the network; communicationsissues; substation control; automation, control and measuring equipment; voltage regulation issues. Analysing the projects that focus on the MV smart grid is out of the scope of this paper.
# Industrial IoT Monitoring: Technologies and Architecture Proposal
## 2 Technologies for Industrial IoT
### Management Protocols
Distinct from NETCONF, which uses SSH and TCP, RESTCONF allows the communication between server and client using HTTP operations. Using HTTP at the application layer enables clients to receive notifications without maintaining a permanent connection with the server, as it is the case of NETCONF (one of its major drawbacks). The syntax used in RESTCONF is YANG, the same syntax used in NETCONF. Also using an ROA-based architecture but with a different application protocol, the CoAP Management Interface [47] (COMI) is an internet draft that intends to provide access to resources specified in YANG or SMIv2, using CoAP. The draft defines, as in the cases of NETCONF and RESTCONF, a separation between operational and configuration data store, the use of DTLS, and a conversion of YANG string identifiers to numeric identifiers that contributes to reducing the payload size. Last but not least, LwM2M [39] is also a protocol designed for resource-constrained devices. This protocol provides device management and application management, an aspect that differs from the previously mentioned network management protocols. As COMI, LwM2M also supports the use of CoAP at the application layer. Being a REST-based protocol, LwM2M uses GET/PUT/POST operations to perform read/write/execute operations over the managed objects resources. In this protocol, the definition of managed objects is done using XML. An extensive list of managed objects is available in OMA [48]. In addition to these, OMA allows the creation of specific objects by individuals, organizations, and companies. Summing up, in this sub-section, a set of network management protocols were presented (see Table 3). By analysing the protocols presented here, we identified protocols suitable to managing traditional networks (switches, routers, computers), and protocols designed for networks of resource-constrained devices (e.g., sensor nodes). An important trend is that new protocols like LwM2M use general-purpose languages to describe the managed objects (e.g., XML), instead of YANGand SMIv2. All of these management protocols can be incorporated into the different gateways identified in the industrial standards presented before (i.e., ZigBee coordinator, WirelessHART network manager, ISA100.11a system manager, and WIA-PA network gateway) because these roles are performed by unconstrained devices. Finally, protocols like SNMP, NETCONF, RESTCONF, COMI and LwM2M cannot be directly used in sensor nodes because current standard industrial technologies do not allow running application protocols other than their own. Thus, the management of these kinds of networks can only be done in a standardized way at gateway level. Only new standards like 6 tisch [49] support the management of sensor node devices using COMI or LwM2M because 6 tisch uses the CoAP protocol at the application level. Nevertheless, due to the fact that no 6 tisch-based products are available and, consequently, it is not yet used in industrial settings, 6 tisch will not be addressed in this paper.
# Transmissive Polarizer Metasurfaces: From Microwave to Optical Regimes
## 6 Review of Recent Progress of MSs Based Polarization Conversion
### Single Band Transmissive MS-Based Converters
It can be seen that the unit cell in Figure 5b can be seen as that in Figure 5c once the diagonal strips are removed. Incident wave 'E' can be divided into two orthogonal components as E1 and E2, as shown in Figure 5b,c. The equivalent circuit theory can be applied by superposition, using diagonal strips removed and with diagonal strips. The structure in Figure 5c is symmetric in both planes. With the diagonal strips along E2, equivalent inductances will appear and will produce a phase difference between two orthogonal components. The length and width of the strip can be optimized to achieve a 90\({}^{\circ}\) phase difference between the two orthogonal transmitted waves, resulting in transmitted circular polarized waves. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Ref** & **Operating Frequency** & **Operating Bandwidth** & **No. of Metallic Layers** & **Angular Stability** \\ \hline [67] & 2.45 GHz & 9\% & 1 & 10 \\ \hline [68] & 31 & 34\% & 4 & 25 \\ \hline [69] & 14.05 & 60\% & 2 & - \\ \hline [70] & 9 & 70\% (numerical), 40\% (experimental) & 2 & 25 \\ \hline [79] & 3 & 5\% & 1 & - \\ \hline [73] & 15.3 & 40\% & 3 & - \\ \hline [74] & 9.38 & 37.3\% & 2 & 75\({}^{\circ}\) \\ \hline [80] & 8.9 & 11\% & 2 & \(\pm\)30\({}^{\circ}\) \\ \hline [75] & 29.5 & 7.4\% & 3 & - \\ \hline [76] & 1205 & 43.9\% & 2 & - \\ \hline [71] & 870 & - & 2 & - \\ \hline [72] & \(\lambda=4.55\)\(\upmu\)m & - & 2 & - \\ \hline \hline \end{tabular}
\end{table} 
Table 1: State-of-the-art single-band MS-T-based LP-to-CP converters. Figure 5: Equivalent circuit approach for polarization conversion operation (**a**)array for MS-based LP-to-CP conversion [81], (**b**) new unit cell [81] and (**c**) new unit cell with diagonal strips removed [81].
## 4 Results and Discussion  
### Concentration Profile  
To examine the behavior of multiple particles in a two-dimensional parallel-plate flow, we evaluated the particle density distribution (PDD) [25]. PDD refers to the distribution of particle concentration, defined as the total area occupied by particles in the flow path relative to the total area of the flow path, which is divided into 20 sections along the width.  
The normalized change in PDD over time for a power-law index \(n=1.0\)--where the solvent portion of the suspension behaves as a Newtonian fluid--is shown in Figure 6 at intervals of \(T^{*}=10\). Here, \(T^{*}=D/U\) represents non-dimensional time. The solid line in the figure represents a homogeneous dispersion state at 0.5. Additionally, Figure 6 shows that at \(T^{*}=0\), the PDD is nearly flat, indicating that the particles are evenly distributed across the width of the channel.  
Figure 7 shows a color map of the normalized PDD for various power-law indices. In this map, green represents homogeneous particle dispersion, blue indicates solvent layers, and red signifies areas of particle accumulation. The observed trends are consistent across all power-law indices. Over time, particles migrate toward the channel center, accumulating at two points symmetrical to the center and disappearing near the walls. Moreover, as the power-law index increases, the accumulation shifts closer to the channel center, whereas, with a smaller power-law index, the accumulation occurs nearer to the walls.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \(n\) & 0.6 & 0.8 & 1.0 & 1.2 & 1.4 \\ Error [\%] & 0.60 & 0.66 & 0.79 & 0.99 & 1.22 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Mean squared error compared to theoretical values of non-Newtonian fluids for different power-law indices.  
Figure 5: Velocity profile of particle-free flow in two-dimensional channel for different power-law indices.  
Figure 6: Normalized PDD change over time for \(n=1.0\), \(Re=256\) and \(\phi=0.79\). Data are represented as mean \(\pm\) standard deviation.
## 1 Introduction
It can separate and identify individual VOCs  
Figure 1: Previously identified biotransformation reactions of geraniol [5; 6; 20; 21; 22]. measure a wide range of VOC concentrations, from low parts-per-billion (ppb) to high parts-per-million (ppm) levels [23]. However, drawbacks of GC/MS include the long time required for a single analysis due to its labour-intensive sample preparation and quantitative analysis requiring reference standards [24]. In contrast, PTR-ToF-MS suits rapid quantitative analysis of VOCs in complex mixtures. It is an ultra-high sensitive technique that allows for the online analysis of VOCs based on their mass-to-charge ratio and can detect trace gases at ultra-low concentration levels (low ppt). A limitation of PTR-ToF-MS is that isomers are not distinguishable. Therefore, identification should be complemented by another analytical technique, such as GC/MS [25; 26; 27] or by implementing additional tools, such as fast-GC [28]. These two techniques have been previously used to measure VOCs in cheese, potatoes, infant formula, blueberries, milk, olive oil and truffles [29; 30; 31; 26] and can support the identification of spectrometric peaks used for rapid monitoring over time [26; 32]. The rapid PTR-MS-based methods also allow for the measurement of a larger number of replicates, making results statistically more robust. Therefore, two separate analyses were carried out at the same time in this study: one using SPME-GC/MS of a few select time points to identify the VOCs present, and the other using PTR-ToF-MS at more time points to monitor the generation of the VOC overtime more accurately. The overall aim of the current study was to monitor the dynamic changes of geraniol during beer fermentation to understand and quantify in real time the point at which differences between _S. cerevisiae_ and _S. pastorianus_ yeast occurred and to provide new information on the biotransformation of geraniol during beer production.
# Detection of Personality Traits Using Handwriting and Deep Learning
## 4 Proposed Architecture
### Level 1--Image Preprocessing
#### 4.1.1 Noise Removal  
Noise removal from scanned images is an essential process in digital image processing, used to improve visual quality and facilitate further analysis. Image noise can be caused by factors such as poor lighting conditions, low-quality camera sensors, or image compression. To remove the noise, we used a Gaussian filter, weighing the neighboring pixels according to their distance from the central pixel.
## 3 Numerical Examples
### Numerical Example--Maximum Displacement Mechanism Design
This means not only that overly high values are obtained for the output displacements, but also that at the same time the actual stress level is underestimated. Looking at topology in Table 3b this important impact of nonlinear effects on the results becomes evident. Here, for linear theory, the stress constraint could successfully limit the stresses, but taking nonlinear effects into account stress levels still exceed by far the prescribed limit of \(\sigma_{\text{allow}}\). In contrast, topologies in Table 3c,d were found considering the nonlinearities during optimization and therefore lead to a better mechanism performance. As prior to manufacturing, the results are commonly smoothed, e.g., in order to eliminate jagged edges from the mechanisms, slight changes in the stress field and objective function values will be the consequence. The effect of smoothing the results obtained here is investigated in Figure 4, where the stress field of the smoothed topology for the nonlinear stress constrained solution in Figure 3d is shown. A Laplacian filter was used to generate the smoothed result, which then was remeshed resulting in a nonregular FE mesh. It can be seen that no significant changes in the stress field occur. In Table 3, the maximum stress field is found to be \(\sigma_{\text{allow}}=0.01\). The results obtained here are shown in Figure 4. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Symbol** & **Value** & **Units** \\ \hline Minimum Young’s modulus & \(E_{\text{min}}\) & 4.232 \(\times 10^{-6}\) & MPa \\ Input force & \(P_{\text{in}}\) & 50 & N \\ Length & \(\ell\) & 200 & mm \\ Height & \(h\) & 80 & mm \\ Thickness & \(t\) & 5 & mm \\ Input stiffness & \(k_{\text{in}}\) & 1.5 & N/mm \\ Output stiffness & \(k_{\text{out}}\) & 4 & N/mm \\ Filter radius & \(r_{\text{min}}\) & 4.7 & mm \\ Volume fraction & \(\varphi_{\text{allow}}\) & 0.3 & – \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameters specific for maximum displacement example. Figure 2: Example definition scheme for maximum output displacement gripper (gray: design space, black: non-design space of solid material, white: non-design space of voids). stress and the objective function value for the smoothed solution are shown. Due to slight geometrical changes and the lack of low stiffness void elements the objective function was improved by 5%, meanwhile the maximum stress increased by 4%. It can be stated that as long as geometrical changes due to smoothing of the results topologies are marginal, sufficiently accurate values are obtained by the introduced method. Figure 4: Stress field for gripper result based on Figure 3(d) with smoothed boundary (12,451 solid elements and 0 void elements). Figure 3: Comparison of topology optimization results for the maximum output displacement gripper example (400 \(\times\) 80 elements).
# A Review of Multifunctional Antenna Designs for Internet of Things
## 2 Materials and Methods
### Smart Cities  
Smart cities harness technology and data to significantly improve the quality of life for their citizens by enhancing efficiency, promoting sustainability, and encouraging economic growth [93]. By integrating a network of interconnected technologies, these cities enable real-time data collection and analysis, which, in turn, allows for informed decision making and optimal resource utilization. Through the incorporation of sensors, IoT devices, artificial intelligence (AI), and machine learning, smart cities can efficiently manage and improve various urban services, such as transportation, energy usage, waste management, and public safety. The transition to smart cities requires significant investments in infrastructure and innovation, but the benefits are manifold. For residents, it means living in environments that are safer, more convenient, and more responsive to their needs. For businesses, it opens up new opportunities for growth and innovation. In terms of the environment, smart cities promise reduced pollution and more sustainable living practices. Ultimately, the goal of smart cities is to create more resilient and adaptable urban spaces that can rise to the challenges of the 21 st century. By minimizing the environmental impact of urban living and fostering economic development, smart cities aim to redefine what it means to live in urban areas, making them better places for future generations.  
In this context, the demand for highly directive antennas becomes evident, driven by the unique challenges and opportunities presented by urban environments. Unlike the more confined spaces of homes, where omnidirectional antennas might suffice, smart cities require a more strategic approach to signal transmission due to their large scale and the longer distances between sensors and base stations. Directive antennas, especially those with electronically controllable beamforming capabilities, emerge as optimal solutions in this setting. Beamforming allows for focused signal coverage, directing power efficiently towards intended targets or users rather than dispersing it indiscriminately. This targeted approach not only conserves energy but also enhances the quality of communication, leveraging the urban landscape's potential for line-of-sight (LoS) connections. These LoS pathways between sensors or between sensors and base stations minimize latency and ensure high-quality signal transmission, which is crucial for the stable operation of smart city infrastructure.