esa-sceva/satcom-chunk-collection huggingface dataset:
# Anchor-Based Method for Inter-Domain Mobility Management in Software-Defined Networking
## 5 Performance Evaluation
### Performance Criteria  
#### 5.1.1 Data Transfer Delay  
Data transfer delay is a key criterion in evaluating the performance of a routing algorithm, especially in networks where latency is critical (e.g., real-time networks). The transfer delay is calculated between the correspondent node (CN) and the mobile node (MN). In RI-SDN, the best path is the one with the smallest combined metric of the number of domains, bandwidth, and delay. Moreover, the RI-SDN method takes into account the delays on each link and the service requirement, whereas in [19], the focus is on a metric that considers the number of domains, bandwidth, and flow operations.  
According to the RI-SDN method, the data transfer delay is given by the formula:  
\[T_{k}=\frac{L}{B_{k}}+\sum_{e\in E_{k}}^{N_{k}}T_{e} \tag{10}\]  
* \(L\): Packet size to be transferred;
* \(B_{k}\): Minimum bandwidth on the route \(r_{k}\);
* \(N_{h}\): The number of hops between the correspondent node (CN) and the mobile node (MN);
* \(T_{c}\): The delay on link \(e\).
# Towards Automatic License Plate Detection
## 3 Proposed Method
### The License Plate Localization Module (LPLM)  
The processed image that contains the spotted vehicle (\(X\)), which is obtained in line (20) of Algorithm 1, is fed to the LPLM. The LPLM after processing the vehicle detected image locates the position of license plate(s) within the detected vehicle region. The proposed LPLM module has three major interconnected steps, which are (**a**) RGB to HSV domain transformation, (**b**) Morphological operations application, and (**c**) Dimensions analysis. Below, we briefly define these modules.
## Materials and Methods  
### Description of the Study Area  
The climate types in China vary from tropical to cold temperate with latitude and from humid to dry with longitude (Figure 1). Many vegetation types of the world can be found in China due to diverse climates bringing about high biodiversity [40]. Vegetation types are spatially dominated by the local climate characteristics [41]. The grassland ecosystems are mainly distributed in the arid and semiarid regions of Northwestern China due to relatively scarce precipitation, whereas deciduous forest and evergreen forest are mainly planted in the cold northern and warm southern regions of China, respectively. Generally, dense vegetation types cover the areas with ample precipitation and heat resources [42; 43]. Thus, the species composition and vegetation distribution are especially sensitive to global climate change. In this study, a total of eight climatic zones across China were divided, including (I) cold temperate humid region, (II) midtemperate humid region, (III) midtemperate semiarid region, (VI) warm temperate arid region, (V) warm temperate subhumid region, (VI) plateau zone, (VII) subtropical humid region, and (VIII) tropical humid region [44]. These climate zones can represent the main climate characteristics in China, and the remotely-derived GPP products of terrestrial ecosystems were evaluated over these contrasting climate regions. The details about three GPP datasets including MODIS, BESS and VPM are listed in Table 1.  
Figure 1: Climate zones and vegetation types in China. The base map is derived from moderate resolution imaging spectroradiometer (MODIS) product MCD12Q1 C5.5 (500 m spatial resolution) based on the University of Maryland (UMD) global vegetation classification scheme in 2010. (I) Cold temperate humid region, (II) midtemperate humid region, (III) midtemperate semiarid region, (IV) warm temperate arid region, (V) warm temperate subhumid region, (VI) plateau zone, (VII) subtropical humid region, and (VIII) tropical humid region.
## 2 Methods
### Indicators to Evaluate Node Importance
#### 2.3.2 Destination and Source Node Count  
The destination node count (DNC) is defined as the number of nodes that can be reached from a given node, reflecting the node's influence as a source. A higher DNC indicates that the failure of this node could lead to the failure of a greater number of other nodes, thereby suggesting higher importance.  
The source node count (SNC) is defined as the number of nodes that can reach the given node, reflecting the influence of other nodes on it. A higher SNC indicates that more nodes can reach this node, thereby suggesting higher importance.  
The expressions for the DNC and SNC are as follows:  
\[DNC_{i}^{(m)}=\sum_{j\in V^{(m)}}RM_{ij}^{(m)}, \tag{10}\]  
\[SNC_{i}^{(m)}=\sum_{j\in V^{(m)}}RM_{ji}^{(m)}, \tag{11}\]where  
* \(V_{i}^{(m)}\), \(V_{j}^{(m)}\): Represent nodes within \(V^{(m)}\);
* \(V^{(m)}\): Denotes the finite, non-empty set of nodes constituting the \(RSCN^{(m)}\);
* \(RM_{ij}^{(m)}\): The structural matrix of the \(RSCN^{(m)}\).
# A Review of Foot-Terrain Interaction Mechanics for Heavy-Duty Legged Robots
## 2 Supporting Feet of Heavy-Duty Legged Robots
### Supporting Foot Configurations of Heavy-Duty Legged Robots
#### 2.1.1 Feet with Passive Adaptive Joints
The 3D model of the robot MBBOT is shown in Figure 9a. The prototype of the robot MBBOT is shown in Figure 9b. Researchers from Shanghai Jiao Tong University have designed a disaster relief hexapod robot, HexbotIV [42; 43; 44]. The overall dimension of the robot is about 1.10 m \(\times\) 0.72 m \(\times\) 1.00 m. The robot has a total mass of 268 kg and can provide a load of 50 kg. In addition, to reduce the impact of the robot during movement, semi-cylindrical rubber cushions are installed at the end of the feet. The prototype of HexbotIV is shown in Figure 10a. The three-dimensional drawing of the parallel mechanism leg with an erect posture is shown in Figure 10b. Figure 8: Big Dog robot: (**a**) main components of robot [1]; (**b**) foot. Figure 9: MBBOT robot: (**a**) 3D model [40]; (**b**) robot prototype [41]. LS3 is tailored for the Marine Corps to handle cargo, as shown in Figure 11a. It can bear a payload of approximately 182 kg, carry enough fuel to sustain for 24 h, and cover approximately 32.2 km. Its feet are semi-cylindrical [45]. The SCalf-I robot, SCalf-II robot, and SCalf-III robot developed by the research team of Shandong University are all quadruped hydraulic heavy-duty robots, as shown in Figure 11b-d, respectively. The payload-total mass ratio can reach 0.5. The feet are designed as semi-cylindrical shapes [46; 47; 48]. Compared with cylindrical feet, the semi-cylindrical feet of heavy-duty legged robots can effectively reduce the mass of the robot. However, the contact surface area between the semi-cylindrical feet and the terrain is relatively small for the cylindrical feet. Then, the stability of the heavy-duty legged robots is slightly worse than that of the cylindrical feet.
## 1 Introduction
Despite the many advantages provided by this technique, a wider diffusion of HSI is hampered by the high amount of data that can be collected in very short times: it is thus necessary a to utilize robust and reliable statistical approaches to manage the data [23; 24]. The proposed strategy, based on the combined use of HSI and chemometric techniques, can represent a valid and efficient innovative analytical approach that can support the currently adopted techniques for asbestos recognition [25; 26]. The techniques currently adopted to detect asbestos require the physical collection and preparation of samples and usually allow punctual measurements and/or small areas mapping. HSI, on the contrary, does not require any sample preparation, thus allowing the acquisition of large quantities of samples in shorter time. The aim of this work was to apply HSI technique for detection and classification of ACM, embedded in a real C&DW. The spectral range utilized to reach these goals is the Short-Wave InfraRed (SWIR: from 1000 to 2500 nm), the same utilized for the analysis carried out by remote sensing [27; 28]. ACM acquired images were processed using chemometric techniques, in order to operate an automatic classification and in particular to separate samples with spectral fingerprint similar to ACM (i.e., uncontaminated mortars from asbestos mortars). More in detail, the chosen acquisition set-up allows the rapid acquisition of a large quantity of samples at a resolution of about 150 \(\upmu\)m. Asbestos fibers are smaller than the chosen pixel resolution, but the spectral signature of the pure matrix is different from the spectral signature of the matrix containing asbestos fibers. Starting from the collected spectra it was thus possible to create a classification model able to recognize, inside a C&DW flow stream, the presence of uncontaminated (i.e., absence of asbestos fibers in the matrix) and contaminated samples (i.e., presence of asbestos fibers in the matrix). Multivariate approach, HIS based, was largely adopted in many research fields [29; 30; 31; 32] to manage the huge amount of data and to utilize the information to identify, to characterize and to sort ACM. The aim of the chemometric approach was to obtain a data dimensionality reduction for a better data spectral evaluation and to develop classification algorithm for an efficient handling of multiple classes when hyperspectral imaging [33; 34; 35; 36; 37; 38; 39; 40; 41] sorting strategies have to be set up. Furthermore, the proposed approach also represents a step forward with respect to safety, being applied with a minor exposure risk for workers.
## Data and Methods
### Definitions and Calculations of the Climate Indices  
In scientific literature, climate extremes are based on the use of so-called \"extreme indices\", which can either be based on the probability of occurrence of given quantities or on threshold exceedances [6]. As a result, there are a variety of definitions for climate extremes [14; 48]. The ETCCDI has developed and recommended 27 core climate indices [12], which have been widely used [2; 4; 48; 22; 49] and adopted by the Fifth Assessment Report of Intergovernmental Panel on Climate Change [1]. Seven monthly indices of the recommended 27 climate indices were excluded, and one additional index of hot days (SU35) was included. Hence, a total of 21 indices (Table 2) were therefore calculated with the RClimDex software package [50; 51] in the R-project 3.3.2 (Free Software Foundation: Boston, MA, USA), which can automatically check the quality of original daily data.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Data** & **Temporal** & **Temporal** & **Spatial** & **Spatial** & **Source** \\  & **Coverage** & **Resolution** & **Coverage** & **Resolution** & **Coverage** \\ \hline TX/TN/Ta & 1961–2015 & Daily & Whole China & 52 sites & CMA \\ p & 1961–2015 & Daily & Whole China & 52 sites & CMA \\ MEI/PDO/AMO & 1961–2015 & Monthly & - & - & NOAA \\ LAI & 1982–2015 & 8 days/hall month & Globe & 8 km & GLOBMAP \\ NDVI & 1982–2015 & 15 days & Globe & 1/12\({}^{\circ}\) & GIMMS \\ GPP & 1982–2015 & Monthly & Whole China & 0.1\({}^{\circ}\) & [PERSON] et al. [35] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Summary of the data used in this study.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**ID** & **Inclators** & **Definitions** & **Units** \\ \hline FD0 & Frost days & Annual count when TN \(<\) 0 \({}^{\circ}\)C & Days \\ \hline SU25 & Summer days & Annual count when TX \(>\) 25 \({}^{\circ}\)C & Days \\ \hline SU35 & Hot days & Annual count when TX \(>\) 35 \({}^{\circ}\)C & Days \\ \hline ID0 & Ice days & Annual count when TX \(<\) 0 \({}^{\circ}\)C & Days \\ \hline TR20 & Tropical nights & Annual count when TN \(>\) 20 \({}^{\circ}\)C & Days \\ \hline \multirow{2}{*}{GSL} & \multirow{2}{*}{Growing season length} & Annual count between first span of at least 6 days with a daily \\  & & mean temperature \(\text{TG}>\) 5 \({}^{\circ}\)C and first span after 1 July of 6 days \\ \cline{1-1}  & & with a TG \(<\) 5 \({}^{\circ}\)C \\ \hline \hline \end{tabular}
\end{table}
Table 2: The definitions of the 21 climate indices used in this study.
# Influence of the Road Model on the Optimal Maneuver of a Racing Motorcycle
## 3 Three-Dimensional Free-Trajectory Quasi-Steady-State MLTS
### Vehicle Model and Related Vehicle Performance Constraint
Road camber \(\phi\) affects the maximum lateral acceleration by shifting the envelope of the g-g diagram along the abscissa axis. Road pitch \(\mu\) affects the allowable longitudinal acceleration by shifting the g-g diagram along the ordinate axis. The term \(\hat{\omega}_{y}\) represents variations in normal road curvature (which may be associated with driving through a valley bottom or over the crest of a hill) and scales the envelope of the graph. \begin{table}
\begin{tabular}{c c c} \hline
**Symbol** & **Description** & **Value** \\ \hline g & Standard gravity & 9.81 m/s\({}^{2}\) \\ \(m\) & Total mass (vehicle + rider) & 255 kg \\ \(w\) & Wheelbase & 1.40 m \\ \(b\) & Longitudinal position of CoG & 0.69 m \\ \(h\) & Height of CoG & 0.66 m \\ \(h_{p}\) & Height of CoP & 0.66 m \\ \(f_{w}\) & Rolling resistance coefficient & 0.02 \\ \(\mathcal{C}_{d}A\) & Drag area coefficient & 0.28 m\({}^{2}\) \\ \(\rho_{a}\) & Air density & 1.20 kg/m\({}^{3}\) \\ \(\mu_{x}\) & Longitudinal friction coefficient & 1.18 \\ \(\mu_{y}\) & Lateral friction coefficient & 1.13 \\ \(i_{p}\) & Primary transmission ratio & 2.07 \\ \(i_{g2}\) & Second gear ratio & 2.00 \\ \(i_{g3}\) & Third gear ratio & 1.67 \\ \(i_{g4}\) & Fourth gear ratio & 1.44 \\ \(i_{g5}\) & Fifth gear ratio & 1.29 \\ \(i_{g6}\) & Sixth gear ratio & 1.15 \\ \(i_{s}\) & Secondary transmission ratio & 2.88 \\ \(r_{t}\) & Tire rolling radius & 0.330 m \\ \hline \end{tabular}
\end{table} 
Table 1: Supersport motorcycle parameters. The g-g-g diagrams generated for different vehicle speeds \(V\) and \(\widetilde{\text{g}}\) can be represented using hypersurfaces shown in Figure 4b. The parameters \(\widetilde{\rho}\) and \(\widetilde{\widetilde{\alpha}}\), called the adherence radius and its orientation, respectively, are related to the description of the g-g diagram envelope in polar coordinates and are given by  
\[\widetilde{\rho}=\sqrt{\left(\frac{\widetilde{a}_{x}}{\text{g}}\right)^{2}+ \left(\frac{\widetilde{a}_{y}}{\text{g}}\right)^{2}}, \tag{32}\]  
\[\widetilde{\alpha}=\text{arctan2}\left(\widetilde{a}_{y},\widetilde{a}_{x} \right). \tag{33}\]  
The vehicle's performance in the OCP is limited using the following relationship:  
\[\widetilde{\rho}\leq\widetilde{\rho}_{max}\left(\widetilde{\alpha},V, \widetilde{\text{g}}\right), \tag{34}\]  
where \(\widetilde{\rho}_{max}\) represents boundary of the g-g-g diagram. Figure 4: Vehicle performance envelope: (**a**) exemplary g-g diagram of motorcycle at selected speed \(V\) modified by road camber \(\phi\), road inclination \(\mu\) and road normal curvature variations represented by the term \(\hat{\omega}_{y}V\); (**b**) hypersurfaces of the adhesion radius generated for various values of apparent gravity \(\widetilde{\text{g}}\). A more detailed description of the construction of g-g diagrams and related hypersurfaces can be found in the examples of [20; 22; 40].
# Modifications of Wound Dressings with Bioactive Agents to Achieve Improved Pro-Healing Properties
## 3 Pro-Healing Wound Dressings
### The Effect of Natural Compounds on Skin Regeneration
#### 3.1.2 Essential-Oil-Loaded Biomaterials
[69] modified biomaterial with EOs from palmarosa grasses and hinoki cypresses. Membranes containing palmarosa oil revealed better antimicrobial activity against _S. aureus_ and _C. albicans_ compared to phytoncide oil. It was also confirmed that the biomaterial's aqueous stability was enhanced by the heat treatment method. To provide better antibacterial activity, [PERSON] et al. [70] used different EOs (clove oil, tea tree oil, and oregano oil) in the production of potential wound dressings. It was revealed that pore generation and mass immiscibility were significantly affected by increasing oil concentrations. Among all tested natural compounds, the strongest inhibition of bacterial growth (_E.coli_ and _S. aureus_) was obtained with clove-oil-loaded biomaterial. The use of EO-derived compounds for the production of biomaterials mainly contributed to the increase of their antimicrobial activity and wound regeneration speed. Side effects and limitations related to the addition of EOs to the biomaterial were basically associated with a reduction in physicochemical and mechanical properties, decreasing mechanical strength, swelling degree, water vapor transmission rate, and material wettability [67, 68, 69, 70, 71, 72, 73]. Nevertheless, the rationality of using plant compounds is strictly dependent on the type of wound and treatment strategy, where giving preference to chosen properties requires some consideration. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Type of** **Biomaterial** & **Composition of the** **Biomaterial** & **Experimental Model** & **Biological Properties** **and Advantages** & **Limitations** & **Ref.** \\ \hline Nanofiber & \begin{tabular}{c} _Cymbrogon martini_ \\ essential oil, \\ _Chumacervais glusus_ \\ essential oil, PVA_ \\ \end{tabular} & Not provided & \begin{tabular}{c} Enhanced antimicrobial activity \\ _(S. aureus, C. albicans)_ and \\ aqueous stability \\ \end{tabular} & Not provided & [69] \\ \hline Hydrogel & \
\begin{tabular}{c} Clove essential oil, tea \\ tree essential oil, oregano \\ essential oil, PVA, starch \\ \end{tabular} & Not provided &
\begin{tabular}{c} Enhanced antibacterial activity \\ _(E.coli, S. aureus)_ \\ \end{tabular} & Decreased & [70] \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._
# Energy Harvesting for TDS-OFDM in NOMA-Based Underwater Communication Systems
## 1 Introduction
The performance of the proposed TDS-OFDM-NOMA scheme is evaluated in terms of average system throughput, bit error rate analysis, and energy harvesting improvement based on the SWIPT. The system performance is conducted over a statistical UWA channel. The rest of this paper is organized as follows. In Section 2, we overview the basics of the TDS-OFDM system model. The proposed TDS-OFDM-NOMA scheme is modeled in Section 3. The proposed energy harvesting scheme of the proposed TDS-OFDM-NOMA is addressed in Section 4. Section 5 discusses the detailed TDS-OFDM-NOMA receiver proposed for decoding information. Experimental results are presented in Section 6, and the paper's conclusions are summarized in Section 7.
## 4 Overview of the Proposed Error Recovery Mechanism
### Marinkovic and [PERSON]'s Mechanism  
In [PERSON]'s NC-based error recovery mechanism, body sensors send their packets to the relay nodes, and the relay nodes XOR the received packets, then transmit them to the destination (PS). The network is designed in such way that each body sensor sends its data through two relay nodes and every relay node collects the data from six sensors (for the considered scenario). Sensor allocations are shown in Figure 3. The idea behind this approach is that every relay node sends two uncoded packets, and four packets coded using the XoR operation instead of sending six uncoded packets, as shown in Figure 4. With this approach, redundancies are available in the received packet, as seen (Figure 5) in the received matrix at the destination. The \(N\times N\) received matrix in Figure 5 shows the available redundancy for every packet received from sensors, where \(P_{m}\) represents the data packet from the sensor node \(S_{m}\), \(m=1,2,...,12\) and cell \(P_{m\times m}\) is the uncoded and \(P_{m\times n}\) the encoded packet, where \(n=1,2,...,12\). These redundancies ultimately help this approach to recover packets in the case of high PLR and improves the reliability. For instance (as shown in Figure 5), if packet \(P_{1}\) is lost, still, it can be recovered, as the destination might have received one or two encoded packets (\(P_{12}\oplus P_{1}\) and \(P_{1}\oplus P_{2}\)), which contain \(P_{1}\).  
Figure 4: The packet coding schema used in Marinkovic and Popovici’s (MP’s) mechanism.  
Figure 5: Received matrix at the destination.
# A Review of SATis5: Perspectives on Commercial and Defense 5G SATCOM Integration
## 6 Outlook Perspectives on SATis5 for Commercial and Defense Applications  
In general, satellite enterprise perspectives can be classified into three categories, namely, commercial SATCOM (also known as COMSATCOM) enterprise, civilian SATCOM enterprise, and defense SATCOM (also known as MILSATCOM) enterprise. The COMSATCOM and civilian SATCOM enterprises have similar SATCOM requirements and associated characteristics in terms of acquisition, deployment, maintenance, operations, and satellite network management. Thus, perspectives on the commercial SATis5 architectures are expected to be the same as civilian architectures. COMSATCOM SATis5 architectures can be extended to civilian architectures. On the other hand, the defense SATCOM enterprise is quite different as compared to COMSATCOM and civilian SATCOM enterprises. Presently, the US defense acquisition process has been revised to adapt to the latest commercial technologies to combat dynamic threats from adversaries. This section provides outlooks on perspectives for potential SATis5 architectures with emphasis on commercial and defense applications.  
The survey results described in Section 4 have provided a perspective on a potential SATis5 architecture for civilian and commercial applications. Section 6.1 below captures this outlook perspective that is agnostic of 5G access and use cases. Likewise, the survey results presented in Section 5 have provided a perspective on potential SATis5 architecture for defense applications. Section 6.2 captures this outlook perspective.
## 3 Results and Discussion
### Optimizing Synthesis Conditions
#### 3.1.3 Effect of Initiator Concentration  
Figure 5 shows the influence of the mass fraction of the initiator ammonium persulfate (mass ratio of ammonium persulfate to the DMDAAC monomer) on the intrinsic viscosity of the hybrid flocculant. As illustrated in Figure 5, the quantity of initiator exerted a significant influence on the intrinsic viscosity of the hybrid flocculant. With an increase in the initiator dosage, there was an initial rise in intrinsic viscosity followed by a gradual decrease. This phenomenon could be attributed to the initiation of monomer polymerization by the initiator. Upon reaching a certain threshold of concentration, an excess of free radicals may lead to an elevated risk of termination reactions between these free radicals, ultimately resulting in a reduction of intrinsic viscosity. This pattern closely resembles the typical behavior observed in free-radical polymerization processes. When the amount of  
Figure 4: The influence of DMDAAC on intrinsic viscosity.  
Figure 3: FTIR spectra of modified products when mass ratios of KH570 and polyhydroxy aluminum were 3/100 (**a**), 5/100 (**b**), 7/100 (**c**), 9/100 (**d**).  
ammonium persulfate was 0.7% of the mass of dimethyl diallyl ammonium chloride, the intrinsic viscosity of the product reached the maximum, 719.59 mL/g.