esa-sceva/satcom-chunk-collection huggingface dataset:
# Hybrid Power System Design for Multifunctional Mini-Loader Vehicles
## 2 Materials and Methods
### Design of the Hybrid Power System  
The mild-hybrid power system is divided into two categories, the integrated starter generator (ISG) and the belt-starter generator (BSG) [20]. The ISG system has the advantages of having a fast reaction speed and a smooth motion; the disadvantage is high cost. The BSG system employs a parallel hybrid power technology that uses an EM to drive a serpentine belt to power the crankshaft of the ICE. The EM unit is installed in the position of a conventional vehicle alternator, as shown in Figure 1. This is a low-cost approach to achieving mild hybrid power functions such as the start and stop of vehicles, power assistance, and mild applications of regenerative braking. It has been valued and adopted by many car companies [21]. After evaluation, the BSG system was concluded to be more suitable for this study. In addition to the advantage of not requiring special modifications to the ICE structure, it also is of low cost. Hence, the vehicle power system is designed for conversion according to the requirements of operators, switching to the motor mode in narrow space operations to reduce the amount of exhaust in the area, accomplishing carbon reduction benefits and improving the performance of the vehicle. The system switches to the engine mode when the battery is low and uses the gearbox to output power, while the belt drives the generator to charge the battery. When a large torque output is required, the system is switched to the hybrid power mode; the torques of the ICE and the EM are combined simultaneously for high torque outputs.  
Because the state-of-art charging strategy can significantly prolong the cycle-life of Li-ion battery, Li-ion batteries were chosen as electric power source/storage [22; 23]. Thus, the hybrid power system of the vehicle is composed of a Li-ion battery, a hydraulic pump, a hydraulic valve, a motor/generator, a fuel engine, a transmission mechanism, and a motor controller. The Li-ion battery provides electricity to the motor and the hydraulic pump, and the hydraulic pump drives the hydraulic valve to actuate the hydraulic system. The motor provides power to start the fuel engine or to transfer power to the transmission mechanism through the belt to move the loader vehicle. When the fuel engine is actuated, the motor can also be converted to a generator to charge the Li-ion battery or to output power through the belt to the transmission mechanism to move the loader vehicle with hybrid power. The hybrid power system structure is shown in Figure 2.
# Numerical Simulation of KBKZ Integral Constitutive Equations in Hierarchical Grids
## 3 Numerical Method
### OpenFOAM System  
All numerical experiments carried out in the present work will be compared with the results obtained using the OpenFOAM solver for integral models implemented by [PERSON] et al. [26]. The meshes were adapted in order to have simulations with similar conditions (and as close as possible) to the HiGFlow meshes. For the simulation of the contraction problem, for instance, the mesh shown in Figure 3 was used, where five regions with different refinements in the \(x\) direction can be observed. Notice that the upstream and downstream regions of the contraction geometry have volumes with exactly the same dimensions used in the HiGFlow simulations. On the other hand, a regular mesh was used for the channel-flow case. It is worth noting that the simulations were performed using the PISO method and half of the computational domain, considering the flow symmetry and the lower computational cost.  
The coupling between stress and velocity was performed using the Improved Both Sides Diffusion (iBSD) [30] method, which adds a diffusive term on both sides of the momentum equation. For the solution of the linear systems resulting from the discretization of the velocity, the Bi-CGSTAB (BiConjugate Gradient Stabilized) method [31] was used with DILU (Simplified Diagonal-based Incomplete LU preconditioner) preconditioner, and, for the pressure, the conjugated preconditioned gradients (PCG) method was used with DIC (Simplified Diagonal-based Incomplete Cholesky) preconditioner.  
In OpenFOAM, it is possible to choose the methods of discretization for some terms of an equation--for instance, diffusive or convective terms. Regarding this work, the numerical schemes used are described in Table 1.  
Computation of the Finger Tensors  
In OpenFOAM implementation, the Finger tensors, \(\mathbf{B}(\mathbf{x},t,t-s)\), are labeled by the elapsed time, \(s\). The integration points, \(s_{k}\), are distributed in the interval \([t-s_{max},t]\), according to the following expression:  
\[s_{k}=t_{c}\times\frac{e^{jk}-1}{e^{jk}-1} \tag{15}\]  
where \(t_{c}=\min\{t,s_{max}\}\), \(N\) is the number of integration points and \(\xi\) is a parameter that depends on the value of \(s_{1}\) (for more details, see [26]). All the simulations were performed using \(s_{1}=\Delta t\) and \(N=51\).  
The Finger tensors \(\mathbf{B}(t_{n},t_{n}-s_{k})\) are convected according to Equation (14). We use a Euler explict scheme to obtain the fields \(\mathbf{B}(t_{n+1},t_{n}-s_{k})\). These fields are then interpolated, allowing us to calculate the fields \(\mathbf{B}(t_{n+1},t_{n+1}-s_{k})\).
## 3 Results
### UHFUS Examination  
On UHFUS, the average TT of exophytic lesions was 5.17 \(\pm\) 2.48 mm, while the TT of endophytic lesions was 2.40 \(\pm\) 1.40 mm. The mean DOI for exophytic lesions was 2.44 \(\pm\) 1.57 mm, while for endophytic lesions the value was 1.92 \(\pm\) 1.65 mm. TT and DOI assessments by means of UHFUS were found to correlate with histology (\(R\) = 0.9835, \(p\) < 0.05 for TT, \(R\) = 0.9631, \(p\) < 0.05 for DOI) (Figure 4). TT was slightly underestimated on UHFUS (mean difference 0.10 mm), while DOI was overestimated (mean difference 0.14 mm).  
Figure 4: Scatterplot showing the correlation between DOI (**A**) and TT (**B**) estimated by means of UHFUS and histology. The dots represent individual patients and their combination of UHFUS and histology values of DOI and TT.  
Figure 3: OSCC of the mouth floor in a 56-year-old female: (**A**) clinical aspects of the lesion; (**B**) B-mode UHFUS (ultra-high frequency ultrasound) examination, showing a lobulated exophytic lesion with characteristics of hypoechogenicity compared to the surrounding tissue; the lower margins appear blurred and the lesion seems partially extended to the underlying submuc; (**C**) color Doppler image, showing intense (score 3) intralesional and perilesional vascularization with diffused aliasing phenomena.
## 3 Results
### EMI-Based Monitoring
#### 3.2.3 Beam \"B200b-J\"  
Figure 16 illustrates the shear stress of the \"B200b-J\" in terms of mid-span deflection. Further, the crack width acquired by the crack meter transducers is also depicted in the same figure. As designed, the beam showed brittle shear failure, forming a feature critical diagonal crack on the right span. One crack meter transducer is affixed in the middle of the beam, monitoring the propagation of flexural cracking, while the other two are attached to monitor the widening rate of the right and left shear diagonal cracks. Figure 17 presents the crack meters' locations and the cracking pattern of \"B200b-J\" at each loading state. Figure 16 also illustrates, in a red circle, the values of shear stress and mid-span deflections, at the time of the experimental voltage measurements, acquired through the EMI-based method (damage states).  
Further, for \"B200b-J\", seven EMI measurements were acquired. The primary measurement was performed in the healthy state (pristine condition), while the six subsequent were conducted during the loading augmentation and cracking propagation. Figure 16 illustrates these states as \"Dam1-Dam6\", respectively.  
According to the presented cracking pattern, apparently, the beam failed in the right span. Hence, according to their positions, the PZTs with the highest involvement are SA3, SA4, J3, and J6. Figure 18 presents comparative typical voltage response curves in terms of the set frequency range for PZTs J1 and J3.  
From the observation of Figure 18, apparently, the PZT positioned on the failure side shows significant alterations in the voltage response curves with significant peak and curve shifting. Further, the curves' variations commence at early damage states (Dam1), which is an essential indicator of the method's effectiveness in detec  
Figure 16: Mechanical response for beam “B200b-J”, EMI measurements, and crack meters.  
interfacial surface, and thus potential slippage and structural degradation of the retrofitting scheme (PZT J3). Further, PZT J3 could not perform the measurement at loading state Dam6 due to malfunction, which occurred through the extensive cracking in its region. This case also confirms the process described in Section 2.4 regarding the functionality of the PZTs under the development of severe cracking propagation.  
As illustrated in Figure 16, the fatal shear right crack development starts at Dam2, while Dam3 starts the recording of the widening values. Up to the 4 th damage state, the crack width gradually increases (from 1 mm to 2 mm). Thereafter, up to the 5 th damage state, the width reached a 5 mm range, and between the 5 th and 6 th states, the crack width doubled, reaching approximately 14 mm.
# Fast Real-Time Data Process Analysis Based on NoSQL for IoT Pavement Quality Management Platform
## 2 Related Works
### NoSQL  
NoSQL (original meaning: non-SQL or non-relational) provides a mechanism for data storage and search using a less restrictive consistency model than that of the traditional relational database. The motives behind this approach include simplification of design, horizontal expandability, and detailed control [16]. NoSQL is a highly optimized key-value storage for simple search and additional tasks, and aims to achieve high performance gains in relation to latency and throughput. Thus, it is widely used in the commercial utilization of big data and real-time web applications. Furthermore, it can be used with an SQL-like query language, which can help make development more familiar; as such, it is also called \"Not only SQL\" to emphasize this feature [17].  
However, as shown in Figure 3, NoSQL is different from SQL, which maps information based on the relations between two-dimensional tables. There are many different types of NoSQL because they encompass \"not-relational\" (complementary set) databases. Representative examples include key-value, which uses an associative array; column-based, which stores data in columns instead of rows as in conventional databases; and document-oriented, which uses JavaScript Object Notation (JSON) or Extensible Markup Language (XML) as the data format. The major characteristics of NoSQL as a database are as follows [18]:* Suitable for semi-structured and unstructured data: NoSQL is useful for storing unstructured data. To express the hierarchical structure of the data, the database can be organized in a tree type or expressed as abstract graphs.
* Advantageous for storing large volumes of data: NoSQL can easily store large volumes of data because of its very nature, which is advantageous for distributed computing because only machines need to be added to the cluster.
* Excellent for solving problems for a specific domain: NoSQL stores data in data types of key values and graphs. As a result, it can achieve a high performance in a specific domain.
* Diversity of data-querying application programming interfaces (APIs): NoSQL can use various query languages by type and product. Also referred to as UnQL (unstructured query language), the query languages used with NoSQL are mostly lower than SQL, and thus complex queries can be difficult. When complex queries are required, the data structure may be massaged, multiple queries may be overlapped, or, in some cases, the ideas of SQL can be borrowed.  
NoSQL can search and store various types of information in the web environment but does not guarantee data integrity and accuracy. Furthermore, it does not use modification and deletion, which are replaced with input; does not require strong consistency; and is flexible for the addition and deletion of nodes and data distribution [20].
# Flexible Phased Antenna Arrays: A Review
## 2 Manufacturing Techniques
### Hybrid Rigid-Flexible Designs  
The combination of rigid components with flexible substrates offers a practical balance between structural stability and mechanical adaptability. This concept is known as rigid-flex antenna array (RFAA), which is a hybrid architecture. It employs rigid radiators fabricated on substrates like Rogers(r)RO4350, integrated with flexible polyimide circuitry. These designs facilitate rollable and deployable configurations, such as for small satellite (SmallSat) applications. Rigid areas provide mechanical support for antenna elements and soldered active components, while flexible circuits route RF signals. In some circumstances, capacitive feed mechanisms eliminate the need for conductive vias, simplifying assembly while maintaining performance during repeated mechanical deformation [53]. In a similar attempt, a combination of flexible DuPont Pyralux(r)AP PCBs (flexible substrate) and rigid Rogers Duroid(r)5880 PCBs was recently utilized in a novel checkerboard configuration. The flexible material and rigid one were arranged in an alternating pattern to enable flexibility in both the \(x\) and \(y\) axes without compromising overall mechanical integrity. Novel checkerboard design provided the system with the ability to conform to a cylindrical geometry with a radius of 50 mm, expanding the range of potential applications [54].  
Figure 3: Photograph of the FPA antenna (front and back view). The FPA is equiped with deformation correction and is able to transfer RF- direct current (DC) wireless power transfer of about 80 mW at 1 m away from the transmitter [50].  
Another work focusing on hybrid design for SATCOM demonstrated a deployable PA system where a 32-element Ka-band active PA was implemented on a flexible four-layer LCP substrate [55]. This trend of utilizing deployable PAs continued with more novelties, and in 2023, a heterosegmented LCP substrate was used combining six-layer and two-layer LCP substrates to achieve deployability and flexibility [56]. Other novel strategies have also been used to counter different challenges in FPAs. For example, to achieve a scalable production, a novel strategy of thermal drawing process was utilized for the design of a photonics based FPA for the first time. It integrated photonics and RF systems embedded in Polyetherimide (PEI) fiber carriers. This novel design achieved broadband matching and stable performance with flexibility across the ultra-high-frequency (UHF) band [57].  
The diverse range of manufacturing techniques for FPAs reflected the adaptability of these methods to a large variety of application requirements, but along with the manufacturing techniques, the choice of materials used in the design of FPAs is also critically important.
###### Abstract  
The most common method for inspection of insulators is to measure the change of electrical characteristics such as electric resistance and partial discharge. However, even if there is no physical damage, these values vary depending on the temperature, humidity, and chloride content of the atmosphere. In this respect, an alternative to such methods can be the impact response test, and a frequency response function (FRF) obtained from the test has been widely used as a tool for damage detection. In this study the FRF was applied to identify the cap damage of porcelain insulators. In addition, to solve the danger of high voltage and poor field accessibility near the insulator, a device with high field applicability was developed to measure FRF from a long distance using an auto impact hammer and Micro Electro Mechanical Systems (MEMS) technology. Even though the FRF is most suitable for inspection of porcelain insulators, dynamic characteristics such as natural frequencies may vary depending on manufacturing errors, installation conditions, etc., which may cause difficulties in damage identification. To overcome this limitation, the machine learning (ML) method was applied in this study to provide a diagnostic method that ensured consistent and accurate judgment. As a result of predicting the normal and the cap damage data using the support vector machine (SVM), bagging, k-nearest neighbor (kNN), and discriminant analysis (DA) methods, the overall F1 score was over 87% and the bagging method achieved the highest accuracy. In this study, the frequency range and dynamic characteristics that are sensitive to the physical damage of the insulator were derived and, based on this, the optimum ML methods with improved equipment could provide analysis with higher accuracy and consistency than general analysis using the FRF.  
Keywords:frequency response function; porcelain insulator; cap; auto impact hammer; MEMS; non-destructive method; damage detection; machine learning +
Footnote †: journal: Applied Sciences
# Development and Biomechanical Evaluation of a Back Exoskeleton to Support Lifting Tasks
## 4 Results
### EMG Data  
The mean EMG data of the m. erector spinae and m. semitendinosus muscles are depicted in Figures 8 and 9, respectively. As the motion capture and EMG systems were synchronized, the lifting cycle of the EMG data was equivalent to the percentage time of the kinematics data. Likewise, the blue curve corresponds to the baseline condition, and the red curve corresponds to the repetitions with the exoskeleton.  
Figure 8: (**a**) Mean activity of m. erector spinae during lifting task with (red) and without (blue) exoskeleton and (**b**) paired-samples \(t\)-test statistic SPM {t}; * critical t-value.  
Throughout the lifting task, two distinct peaks in the muscle activation of the m. erector spinae can be observed. The first peak, occurring at approximately 40% of the movement cycle, corresponds to the increased strain on the back muscles when lifting the weight from the ground. The second peak represents the subsequent muscle effort required when bending forward to place the weight on the platform.  
When comparing the conditions with and without the exoskeleton, higher muscle activation is visually noticeable without the exoskeleton between 18% and 85% of the movement cycle. The maximum reduction in muscle activation when using the exoskeleton occurs at 38% of the motion cycle, with a recorded decrease of 15.82 \(\pm\) 13.35%.  
The corresponding statistical test results are illustrated on the right side of Figure 8. A significant difference in muscle activation is evident between 25% and 80% of the movement cycle, except for a short, non-significant phase, around 40%. During this moment, the participant grasped the object and initiated the uplift motion.  
The EMG data of the m. semitendinosus are shown in Figure 9. A reduction in muscle activation can be observed during the load phase from 30 to 80% of the movement cycle. Due to the high variability in muscle activation, a statistically significant difference was observed only at approximately 40%, with a peak reduction of 19.89 \(\pm\) 20.84%. This section corresponds to the initial phase of lifting weights from the ground. This phase coincides with a gap in the significance test for the m. erector spinae, suggesting a temporary shift in support from the lower back muscles to the posterior thigh muscles during the task.
# Smart Meter Gateways: Options for a BSI-Compliant Integration of Energy Management Systems
## 2 Related Work
### Interoperable Implementations: FNN Requirements Specifications  
Regarding the practical implementation of SMGWs, the _Forum Grid Technology/Grid Operation_ (\"Forum Netztechnik/Netzbetrieb\", FNN) within the _German Association for Electrical, Electronic & Information Technologies_ (\"Verband der Elektrotechnik, Elektronik und Informationstechnik\", VDE) works on specifications to ensure the efficient and interoperable grid operation in the context of various stakeholders. Members of the FNN are from different sectors (including, e.g., grid operators, device manufacturers, installers, plant operators, or authorities) and want to align their interests and interfaces. Results of the FNN are published in the form of application rules (\"VDE-Anwendungsregeln\") or suggestions (\"FNN-Hinweis\"), neither of which, however, is legally binding. While the _BSI TR-03109_ defines the technical SMGW architecture on a conceptual level, the FNN specifies minimum requirements for the inter-operable and manufacturer-independent operation of _Smart Metering Systems_ on the implementation level [19]. This covers specifications for SMGW firmware processes [20], and other SMGW related processes such as the ordering and configuration of SMGWs with cryptographically signed keys [21], or the constructive hardware design. By implementing SMGWs on basis of the respective FNN specifications, manufacturers benefit from decisions that are aligned with a broad set of relevant stakeholders.
# A Data-Driven Deep Learning Framework for Prediction of Traffic Crashes at Road Intersections
## 3 Preliminaries
### Problem Formulation
For an intersection \(v_{i}\) in the time interval \(\Delta t\), the additional thematic information is defined as follows:  
\[\text{ATI}_{\text{v}_{i}}=\{T_{\text{v}_{i}}(\Delta t),W_{\text{v}_{i}}(\Delta t ),E_{\text{v}_{i}},C_{\text{v}_{i}}\} \tag{3}\]  
where \(T_{\text{v}_{i}}(\Delta t)\) and \(W_{\text{v}_{i}}(\Delta t)\) represent the traffic features and weather features, respectively, in time interval \(\Delta t\). \(E_{\text{v}_{i}}\) and \(C_{\text{v}_{i}}\) are the environmental and calendar features, respectively. In particular, we consider three types of traffic features \(T_{\text{v}_{i}}(\Delta t)\) at intersection \(v_{i}\) in time interval \(\Delta t\), including the average speed of vehicles \(Speed_{\text{v}_{i}}(\Delta t)\), estimated traffic flow \(Flow_{\text{v}_{i}}(\Delta t)\), the static speed limitation \(Lim_{\text{v}_{i}}\). The environmental feature \(E_{\text{v}_{i}}\) is a \(\mathcal{C}_{poi}\)-dimensional vector of POIs in the intersection \(v_{i}\), \(\mathcal{C}_{poi}\) is the total number of POI types, i.e., 13. For weather features, \(W_{\text{v}_{i}}(\Delta t)\) contains the meteorological information in the time interval \(\Delta t\), including weather conditions, temperature, dew point, humidity, pressure, wind speed, wind direction and visibility. The calendar features \(C_{\text{v}_{i}}\) include hours of the day, working days, weekends and holidays or not. Definition 6: Traffic Crash Prediction at Road Intersections (TCP@RI). In this paper, we formulate the task of TCP@RI as a classification problem. Let \(F_{i}\in\mathcal{G}\) denote the raw features of all the road networks for a time interval \(\Delta t\) (\(|\Delta t|\)=one hour), including topological-relational features and additional thematic information. Given all the historical observations of road networks \((F_{0},F_{1},\dots,F_{T})\), our goal is to learn a model to predict whether traffic crashes are going to happen or not at a specific intersection \(v_{i}\) in the next period. Note that the topological-relational features (_tr-features_) of road intersections in this paper are latent vectors that encode topological information of a road network by exploring geo-locality and intrinsic properties of intersections and moving behaviors of road users. We discuss how to extract the tr-features in Phase I of RoadInTCP in Section 4.