esa-sceva/satcom-chunk-collection huggingface dataset:
# Research on Vehicle Re-Identification Algorithm Based on Fusion Attention Method
## 3 Experiments and Discussion
### Experimental Results and Analysis
#### 3.4.1 Experimental Results and Analysis of VeRi-776 Dataset
Vehicle data matching analysis is as follows: 7 vehicle samples are randomly selected from VeRi-776, queried, and then sorted by similarity. The results are shown in Figure 10. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **mAP** & **Rank-1** & **Rank-5** \\ \hline LOMO [25] & 9.7\% & 23.8\% & 39.1\% \\ GoogLeNet [26] & 17.8\% & 52.1\% & 66.7\% \\ FACT+Plate+STR [6] & 27.8\% & 61.4\% & 78.8\% \\ Siamese+Path [19] & 58.3\% & 83.5\% & 90.0\% \\ NuFACT [27] & 53.4\% & 81.5\% & 91.4\% \\ SDC [28] & 53.5\% & 83.5\% & 92.6\% \\ OIFE [21] & 48.0\% & 65.9\% & 87.7\% \\ VAMI [9] & 50.1\% & 77.0\% & 90.8\% \\ RAM [20] & 61.5\% & 88.6\% & 94.0\% \\ AAVER [22] & 61.2\% & 89.0\% & 94.7\% \\ VANet [23] & 66.3\% & 89.8\% & 95.9\% \\ PAMTRI [7] & 71.9\% & 92.8\% & 97.8\% \\ PRN [24] & 74.3\% & 94.3\% & **98.9\%** \\ StRDAN [29] & 76.1\% & 94.7\% & 98.3\% \\ \hline Our(SDLAU) & **78.3\%** & **96.3\%** & **98.5\%** \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Experimental comparison results of VeRi-776 dataset. Figure 9: Vehicle feature visualization by different methods. The matching results of the vehicles on the VeRi-776 dataset can be observed in the figure. The first image represents the vehicle's image to be queried, and the rest of the images are retrieved from the gallery and sorted by similarity score. Correct matches are marked with a green border. The first image in each original image is the query result, and the remaining 10 images are the top 10 retrieval results. It can be seen from the figure that the model proposed in this paper has a better recognition accuracy of the similarity between vehicle classes, the model can better pay attention to the local details of the vehicle and can accurately identify the vehicle image when it is occluded. The error rate is also relatively low.
## 4 Results and Discussions
### Effect of the Plastic Deformation on the Oblique Impact  
The following figures show the deformed shape of various geometries after the oblique impact. In the case of the cylindrical shape, as soon as the projectile strikes, the pressure caused by the collision is concentrated at the end of the cylinder. The direction of the cavity pressure is normal to the bottom surface. Because of the pressure concentration at the bottom surface of the cylinder, the cylindrical projectile shows very large plastic deformation with compressive deformation as shown in Figure 15a.  
For the blunt geometry, there was an asymmetric distribution of the cavity pressure because of the free surface effect, and the bending deformation of the projectile occurred. The maximum equivalent plastic strain was 0.557. The maximum plastic deformation occurred at the center of the projectile. Small pressure was applied to the projectile near the ground the projectile. However, on the opposite side, the depth of the target was considered as infinite, and full pressure was applied. Accordingly, the trajectory of the projectile shows '\(J\)' curve. As the bending deformation increases, the projectile further moves horizontally. As bending deformation increases, the path of the projectile's movement follows the direction of the bending deformation. Accordingly, as shown in Figure 14, the final coordinate of the projectile in the horizontal direction greatly increased.  
The projectile with a truncated geometry has a surface perpendicular to the moving direction. At that surface, the maximum plastic deformation occurred. The equivalent plastic strain was 0.295. Also, due to the asymmetric cavity pressure distribution, the bending deformation occurred. The deformed shape and final position of the projectile are shown in Figure 15c. Figure 15d presents the deformed shape and final position of the projectile having an ogive nose. The maximum plastic strain was 0.095, the smallest among four geometries. The bending deformation was very small, and thus, the penetration depth showed the largest value.  
Figure 15: Deformation of the projectile after the oblique penetration; (**a**) Cylinder, (**b**) Blunt, (**c**) Truncated, and (**d**) CRH = 3.  
From the aforementioned results, the projectile geometry for improved penetration characteristics was studied. When the projectile has a surface perpendicular to the moving direction, the reaction forces from the impact are concentrated on that surface. Consequently, the deformation of the projectile occurred. The loss of the energy changed from kinetic energy to penetration energy. Under the normal impact and the oblique impact, the projectile having an ogive geometry shows the best penetration characteristics. As the CRH value increases, the penetration depth was also increased. Particularly for the oblique impact, as the CRH value increases, the bending deformation of the projectile decreases, thereby greatly increasing the penetration depth of the projectile.
# Efficient Implementation of PRESENT and GIFT on Quantum Computers
## 3 Proposed Method
### Quantum Circuit for GIFT Block Cipher
#### 3.2.5 Keyschedule of GIFT Block Cipher  
In GIFT, the state of the key is updated after the round key is used, which is shown in Equation (9). The Keyschedule of PRESENT block cipher uses Sbox and round \(i\), while the GIFT only changes the bit positions of key \(K\). It can be done using only Swap gates, and using the method of relabeling qubits does not require quantum resources.
# Handover Management for D2D Communication in 5G Networks
## 3 System Model and Problem Formulation
### Problem Formulation
There are in total \(\left(n\right)^{2d}\) possibleconfigurations. We can examine the feasibility of configurations one by one and count the number of D2D pairs having both parties connected to the same eNB. The complexity of such an approach is \(O(n^{d})\). Since the order of the complexity is exponential, the optimization problem cannot be solved solely by a primal entity in a practical system due to its complexity. Even more challenging is the mobile and dynamic nature of the system as in operation. Therefore, we propose a novel D2D handover mechanism for every pair of D2D users to choose their potential handover target eNB. The proposed approach, with complexity \(O\left(d\cdot n\right)\), aims to reduce unnecessary handover and let both parties of a D2D pair connect to the same eNB.
# Remote Sensing for Irrigation of Horticultural Crops
## 4 Approaches to Precision Irrigation
### Remote Sensing and Soil  
Soil moisture measurements are critical components for climate studies, hydrology, weather predictions, analysis of flooded areas or the recharge of aquifers. Real time analysis of the soil water content is crucial for optimizing water management of agricultural fields.  
[PERSON] et al. [206] presented an overview of soil-moisture retrieval methods using different remote sensing data (active or passive). They reported the advantages and limitations of each method, and the evaluation of the most robust methods for retrieving soil-moisture information from bare and vegetated soils. The best results come from a combination of active and passive sensing methods. A backscatter empirical model (active method) gave a 95-97% correlation between the estimated and the field soil measurements. The \"neural networks method\" (passive method) gave a 100% correlation between the estimated and field soil measurements.  
[PERSON] et al. [62] reported the adoption of GNSS reflectometry (GNSS-R) based on a low-cost device and an airborne solution. For irrigation purposes, the GNSS-R system was useful for soil moisture monitoring. Classical probes were not considered representative of the field-soil moisture since they return punctual measurements. The authors considered the soil moisture monitored on a large scale to be appropriate, even at the expense of temporal and/or spatial resolution. Even satellite measurements were not sufficient to monitor diurnal variations.  
[PERSON] et al. [207] provided a review of the calibration, validation and assessment of Soil Moisture Active Passive (SMAP) instruments. The project conducted two activities aimed at enhancing the products' resolution: (i) the Backus Gilbert interpolation and de-convolution techniques based on the oversampling characteristics of the SMAP radiometer; (ii) the disaggregation of the SMAP radiometer data using the Sentinel-1 C-band synthetic aperture radar data to obtain a resolution from 1 km to 3 km.  
[PERSON] et al. [208] studied microwave remote sensing of soil moisture content. The system was founded on the different dielectric properties of water with respect to dry soil. The Soil Water Index (SWI) was combined with the METOP ASCAT and ENVISAT ASAR GM to obtain one layer with high resolution (1 km). The authors reported another way of assessing soil moisture, the Soil EnergyBALance (SEBAI). All of these models were applied on a local scale to produce the actual ET linked to soil water. The authors indicated that the most broadly used methods were the SEBAL, the Two-Source Energy Balance (TSEB) modeling approach, and the Surface Energy Balance System (SEBS).  
[PERSON] et al. (2016) performed a full-season experiment in a greenhouse with several objectives. Since CWSI (values between 0.6 and 1.0) was negatively correlated to soil moisture, the index may be considered _\"as an alternate irrigation scheduling method to quantify spatial soil moisture\"_.  
Other information is reported in the previous Sections 3.2.1 and 3.2.4.
## 3 Data Collection  
There are various methods used to detect roughness at the surface of the steel strip. [PERSON] et al. [19] have used a profilometer, which measures a surface's profile, and [PERSON] et al. [20] have used Hommel Tester T1000 wave to measure the surface roughness of the stainless steel strip. In this study, the roughness was measured with Focal-Spec's MicroProfiler MP9000 device [21] at an integrated rolling, annealing, and pickling line (RAP) in Outkumpu Stainless Oy, Tornio, Finland during 2016, with an accurate optical no-contact surface roughness measurement method based on LCI technology, which enables the laboratory-accurate on-line measurement of surface roughness during the production process. The surface roughness was defined as the arithmetic mean of the profile (Ra value). The collected data consist of 206 steel strips and 128 process variables, including 78 variables from hot rolling process and 50 variables from the RAP line. The small size of the data set narrowed down the number of suitable machine learning methods.
# Navigational Risk Assessment in Offshore Wind Farms Using Spatial Ship Domain Models
## 3 Results
### The Numeric Factors of \(R_{\text{ND}}\) and \(R_{\text{NH}}\) Estimated for Three Ship Types  
The analysis of navigational risk factors R\({}_{\text{ND}}\) for maintaining the required depth reserve was conducted using the ship domain depth (SD\({}_{\text{D}}\)) and navigational risk definitions (Formulas (1) and (20)). The study considered three ship types, assessing their navigational safety in relation to underwater obstacles in a sea area with limited depth, such as an offshore wind farm (OWF) (Figure 3). According to the data from Table A2 (Appendix C), the sea depths (36.5 m \(\leq\) h \(\leq\) 54.5 m) are sufficient for safe navigation for all three ships (VLCC, fishing boat, \(Z\)-Tug) as long as the sea depth (h) exceeds the domain depth (SD\({}_{\text{D}}\)). However, a corridor with a minimum sea depth of 14.5 m is non-navigable for the VLCC but safe for the smaller fishing boat and \(Z\)-Tug. In territorial waters with a minimum depth of 7.0 m, only the \(Z\)-Tug can navigate safely.  
Figure 3: The wind turbine generator parameters with air clearance under the rotor F = 22 m to 26 m.  
Regarding above-water obstacles, while the OWF area currently lacks any, future construction may introduce risks from wind turbine rotors for service vessels operating nearby. To ensure safe navigation under these rotors, which have a clearance from 22 m to 27 m, vessels must satisfy the condition SD\({}_{\text{H}}\) < Ho (rotor clearance). Based on the analysis in Table 11 (Appendix C), only the Z-Tug can safely operate under these conditions, as its domain height ensures clearance from the wind turbine rotors.
# INSPIRE-SAT 7, a Second CubeSat to Measure the Earth's Energy Budget and to Probe the Ionosphere
## 2 Scientific Objectives of the INSPIRE-SAT 7 Mission
### Ionosphere
It is necessary to understand the spatial and temporal evolution of the plasma and to investigate all scales of wave activity ranging from planetary waves and tides down to small-scale traveling ionospheric disturbances generated at the ground. Currently, most of the information about the ionosphere behavior comes from ground-based ionospheric sounders [6; 7], and indirectly from Geostationary Operational Environmental Satellites (GOES) but also from Swarm [8], FormoSat-3/COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate), e-TOP/CASSIOPE (Enhanced Polar Outflow Probe) [9], the Norwegian NorSat-1 [10]. With the exception of certain sounders able to operate with oblique incidence [11], these devices give information only on the local vertical. The INSPIRE-SAT 7 mission proposes an innovative approach based on one ground-based HF transmitter and one HF receiver onboard a CubeSat. The analysis of the HF signal received after passing through the ionosphere will provide information of the propagation medium along the portion of the CubeSat trajectory visible from the ground transmitter, i.e., approximately a 1000 km arc. As part of the INSPIRE-SAT 7 mission, we will test a new technology to perform ionospheric measurements and new concepts to analyze our data like map reconstruction technics.
## 3 Recent Developments and Progress
### Environmental Remote Sensing by GNSS-R
#### 3.5.2 Typhoon Monitoring  
Both wind direction and wind speed are key factors affecting the ocean. The scatterometer functions by emitting electromagnetic wave signals towards the ocean surface and subsequently receiving the reflected signals. This process is critical for retrieving essential data regarding wind speed and direction, which in turn facilitates the detection, estimation, and prediction of typhoons. The effective monitoring of these intense weather systems is heavily reliant on accurately locating the center of a typhoon and predicting its path. These two elements are fundamentally intertwined with the overall quality of forecasts concerning associated thunderstorms and the strong winds that they generate. GNSS-R possesses distinct advantages that make it a valuable tool in atmospheric observation. Notably, it is characterized by both low cost and low power consumption, making it an efficient choice for widespread deployment. When integrated with micro-satellites to create a constellation, GNSS-R can achieve a high spatial and temporal resolution across the globe. This capability enables comprehensive monitoring of weather phenomena. Furthermore, operating within the L-band frequency, GNSS-R is less susceptible to interference from precipitation, rendering it particularly effective for the observation of typhoons. This feature enhances its reliability and accuracy in this context, making it an important asset for meteorological studies.  
[PERSON] [53] created geophysical model functions (GMFs) by utilizing measurement data from CYGNSS, which serves to correlate the observations captured by the CYGNSS GNSS receivers with ocean surface wind speeds. These GMFs are constructed from observational data that closely align with independent assessments of the wind speed at a height of 10 m above the ocean surface. [PERSON] et al. [54] presented a technique for identifying cyclones and estimating their positions utilizing the full delay-Doppler map (FDDM), within which notable changes in asymmetry occur within the cyclone-affected area. Furthermore, by establishing two key features, slope and extremum difference, a detection device for tropical cyclones was introduced. Both the outcomes of simulations and the data from Cyclone GNSS (CYGNSS) demonstrated effective detection capabilities for tropical cyclones monitoring (Figure 13). This research acts as a foundational reference for the leveraging of space-borne GNSS-R technology to directly detect tropical cyclones and to gather real-time data on high wind speeds.
## 4 Performance of Waste-Plastic-Modified Bitumen Binder and Mixture
### Characteristics of Plastic-Modified Bituminous Mixtures
#### 4.2.1 Mechanical and Durability Performance
Moisture conditioning led to performance declines of up to 17% in rutting resistance and 9% in modulus across all modified mixtures, underscoring the significance of appropriate mix design for durability. Table 4 provides a comparative review of experimental research assessing the mechanical and durability performance of asphalt mixes modified with different types of plastics, doses, and blending methods. \begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**References** & **Plastic Type** & **Dosage** & **Incorporation Method** & **Performance Outcomes** & **Notable Insights** \\ \hline
[50] & PET (chemically recycled) & 1–3\% by wt. of binder & Wet method (aminolysis) & \(\uparrow\) Rutting and moisture resistance; \(\downarrow\) low-temp cracking; optimal dynamic creep at 1\% & Dosage–performance trade-off; ANOVA confirmed significance \\ \hline
[51] & LDPE/LLDPE & 0.25–1.0\% by wt. of aggregate & Dry method & \(\uparrow\) Rutting resistance, CTIndex (LLDPE); \(\uparrow\) moisture resistance (LDPE) & LLDPE showed better crack tolerance; LDPE showed better moisture resistant \\ \hline
[52,53] & PET fibres & Not specified (18 mm fibres) & Dry method (fibre reinforcement) & \(\uparrow\) Cracking resistance and toughness in SCB tests & More effective at low loading rates and cold climates \\ \hline
[55] & LLDPE & 0.5\% by wt. of aggregate (dry); 1.0\% by wt. of binder ( ) & Both dry and wet methods & Wet: comparable to SBS; dry: \(\downarrow\) CTIndex, \(\uparrow\) stiffness & Wet method showed more balanced overall performance; dry method leads to brittleness \\ \hline
[56] & LDPE/HDPE & Unspecified; flakes/powder & Modified dry method (Plastic Aid) & \(\uparrow\) Compactability, \(\downarrow\) rut depth, \(\uparrow\) crack resistance (flakes) & Powder less effective than flakes \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Plastic-modified asphalt mixture performance.
# Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A Survey
## 3 Games Theory for WSNs Security
### Security in WSNs: Requirements  
WSNs have emerged in the recent years because of their features and the applications that they can be used in. Due to these substantial reasons some requirements should be maintained for WSNs security as follows [76; 77]:  
* **Confidentiality:** A transmitted data to a specific sensor node must not be understood by any other node in WSNs.
* **Integrity:** The transmitted and received data must not be maliciously altered by the participant sensor nodes in WSNs.
* **Authentication:** A sensor node uses the data authentication to verify that the received data is actually sent by the claimed sender in WSNs.
* **Authorization:** The authorization is used to guarantee that the authorized sensor nodes are only able to perform certain operations in WSNs.
* **Availability:** The WSN services must be available whenever the WSN users need them.
* **Freshness:** The data produced by the WSN sensor nodes must be neoteric.
* **Forward and backward secrecy:** Forward secrecy is used to prevent a sensor node that has left a WSN from reading any future data. Backward secrecy means preventing a new comer to a WSN from reading any previous data.
Sensors_**2009**, 9, 4728-4750; doi:10.3390/s90604728  
_Sensors_  
**ISSN 1424-8220**  
www.mdpi.com/journal/sensors  
_Review_  
**A Review of Wireless Sensor Technologies and Applications in Agriculture and Food Industry: State of the Art and Current Trends**  
**[PERSON] 1,*, [PERSON] 1, [PERSON] 1 and [PERSON] 2**  
Footnote 1: [[http://www.sdss.org/sdss/sdss/sdss/sdss/sdss/sdss/](http://www.sdss.org/sdss/sdss/sdss/sdss/sdss/sdss/)]([http://www.sdss.org/sdss/sdss/sdss/sdss/sdss/sdss/](http://www.sdss.org/sdss/sdss/sdss/sdss/sdss/sdss/))  
ownership, the engineering of increasingly smaller sensing devices and the achievements in radio frequency technology and digital circuits.  
WST refers to Wireless Sensor Networks (WSN) and radio frequency identification (RFID) based sensor devices. WSN is one of the most significant technologies in the 21 st century. RFID was developed for identification purposes, but growing interest in the many other possible applications has led to the development of a new range of wireless sensor devices based on RFID. The main difference between a WSN and a RFID system is that RFID devices have no cooperative capabilities, while WSN allow different network topologies and multihop communication.  
These technologies have been attracting many research efforts during the past few years, driven by the increasing maturity and adoption of standards, such as Bluetooth [1] and ZigBee [2] for WSN, and various ISO (International Organization for Standards) standards for RFID (ISO 15693, ISO/IEC 18000, ISO 11784, etc.) [3-9]. Currently, they are very promising in several fields such as environmental monitoring, irrigation, livestock, greenhouse, cold chain control or traceability. The systems are usually composed of a few sinks and large quantity of small sensors nodes. Normally, these sensor nodes consist of three components: sensing, processing and communicating [10]. Each wireless sensor node communicates with a gateway unit which can communicate with other computers via other networks, such as a Local Area Networks (LAN), Wireless Local Area Networks (WLAN) [11,12], Internet [13], Controller Area Network (CAN) [14] or Wireless Wide Area Network (WWAN) using standard protocols like GSM (Global System for Mobile communication) [15-17] or GPRS (General Packet Radio Service) [18,19].  
In this paper, we review the standards and the numerous applications that utilize WST in agriculture and food industry and to classify them in appropriate categories. The analysis of their characteristics and contributions could be useful for perceiving new applications or relevant research opportunities.