esa-sceva/satcom-chunk-collection huggingface dataset:
# Secure Automatic Identification System (SecAIS): Proof-of-Concept Implementation
## 4 Proof-of-Concept Implementation
### The SecAIS-App  
The SecAIS-App is the application that enhances conventional AIS devices with SecAIS capabilities. For the purposes of this paper, the code implementing the SecAIS-App supports only the Authenticated-SecAIS (mode 2) and the SK-IBE-SecAIS (mode 4). It is written in Java and it permits the integration of arbitrary open-source code and cryptographic libraries. We use the open-source Java cryptographic libraries provided by the \"Legion of the Bouncey Castle\" ([[https://www.bounceycastle.org/java.html](https://www.bounceycastle.org/java.html)]([https://www.bounceycastle.org/java.html](https://www.bounceycastle.org/java.html)), accessed on 6 June 2022), which provides robust and well-preserved Java cryptographic libraries with an MIT-type license. Some parts of the SecAIS-App implementation are copied from or are based on the jim-b/ ECCSI-SAKKE project on GitHub ([[https://github.com/jim-b/ECCSI-SAKKE](https://github.com/jim-b/ECCSI-SAKKE)]([https://github.com/jim-b/ECCSI-SAKKE](https://github.com/jim-b/ECCSI-SAKKE)), accessed on 6 June 2022), which is part of an open-source implementation of ECCSI-SAKKE (RFC6507-RFC608), MIKEY-SAKKE, and the MIKEY-SAKKE key management server (KMS) (RFC6509). In a SecAIS production environment, each AIS device will be equipped with a SecAIS-App that will act as both a SecAIS transmitter and receiver.
## 5 Security Analysis
### Heuristic Analysis
#### 5.2.3 User Anonymity  
In our development of the 2 FAKA-C/S protocol, we employ a novel strategy to bolster user anonymity. By allocating a pseudo-identity \(PID_{i}\) to each user and updating it periodically, the proposed protocol significantly enhances both anonymity and untraceability. This pseudo-identity is derived from the user's actual identity \(PID_{i}^{network}=H(PID_{i}\parallel x)\). This approach effectively obstructs efforts to deduce the user's identity from interaction data. Moreover, we ensure that neither the smart card nor any transmitted data reveal any details that could disclose the user's real or pseudo-identity. Consequently, even if an adversary manages to extract the smart card's parameters \(\{a_{i},A_{i},B_{i},P,n_{0}\}\) or intercept communication data \(\{M_{2},K_{1},K_{2},t_{u}\}\), \(\{K_{3},M_{3}\}\), they will be unable to ascertain the user's true or pseudo-identity. Our design not only precludes the direct exposure of user identities but also protects against the tracing of identities and behaviors in the face of persistent communication threats.
# Tamed Warping Network for High-Resolution Semantic Video Segmentation
## 5 Experiments
### Ablation Study
#### 5.2.4 Category-Level Improvement  
The IoU improvements for different categories are shown in Table 4. The IoUs of **non-rigid objects** (human, object, and vehicle) are improved greatly. The moving of non-rigid objects are hard to predict and thus warping is prone to fail. With our correction, wrong predictions significantly decrease.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Warping Layer** & **FT** & **CFR** & **RGA** & **mIoU \(\uparrow\)** & **FPS \(\uparrow\)** & **GFLOPs \(\downarrow\)** \\ \hline \hline \multirow{4}{*}{Layer 1.} & \(\checkmark\) & & & 67.3 & 65.5 & 113.28 \\  & \(\checkmark\) & & & 69.6 & **65.5** & +0 \\  & \(\checkmark\) & \(\checkmark\) & & 70.6 & 63.1 & +2.42 \\  & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & **71.6** & 61.8 & +0.0012 \\ \hline \multirow{4}{*}{Layer 2.} & \(\checkmark\) & & & 65.4 & 89.8 & 73.00 \\  & \(\checkmark\) & & & 67.8 & **89.8** & +0 \\ \cline{1-1}  & \(\checkmark\) & \(\checkmark\) & & 68.6 & 86.3 & +2.42 \\ \cline{1-1}  & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & **69.5** & 84.9 & +0.0029 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Effect of each module of TWNet. FT: the fine-tuning of the non-key CNN (the second training step); CFR: context feature rectification; and RGA: residual-guided attention. \"\(\checkmark\)\" means the model utilizes the corresponding module. We also show the extra cost of adding our modules. \(\uparrow\): higher is better; \(\downarrow\): lower is better. The best results are shown in bold.  
Figure 6: Qualitative results on Cityscapes. GT: ground truth; warping: normal warping; NKFC: the non-key-frame CNN; CFR: context feature rectification; and RGA: residual-guided attention.
## 3 Results and Discussion
### Recyclability of the Catalysts with Both Substrates and **MRImd@PMo11 VO40**  
Recyclability experiments were realized with **MRImd@PMo11 VO40**, the catalyst displaying the best conversion/yield under the optimized tested conditions (5 h with TBHPaq as oxidant). After the first catalytic experiment, the reaction mixture was filtered and the resulting solid was washed with ethyl acetate, then dried to be reused. By applying the same condition reactions, no decrease in the yields and conversions of both evaluated substrates were observed after three cycles (Figure 7).  
**Imd@PMo11 VO40** maintained the same performance in three consecutive runs with the same \(\beta\)-myrrene conversion (75%) and with 25% \(\beta\)-myrrene oxide formation.  
Promising results were also obtained with **MRImd@PMo11 VO40** for \(\beta\)-caryophyllene oxidation, with constant conversion (92%) and oxide yields (60%) after each of the three runs, and thus without any leaching being obtained, as described in the leaching experiment.  
This highlights the stability of the grafted catalyst and its stability under oxidative condition reactions. Also, as confirmed by the leaching test previously described, the absence of catalyst leaching supported its stability. These results highlight the strong durability and reusability of the catalyst, making it a valuable tool for terpene oxidation.  
The stability of the catalyst was also evaluated by solid-state NMR by conducting \({}^{31}\)P and \({}^{13}\)C MAS NMR experiments on the catalysts before and after catalysis. Only minor structural modifications upon reuse were observed (Figure 8), indicating the good stability of the catalyst. Notably, the \({}^{31}\)P MAS NMR spectra (a and c) displayed a sharp peak at \(-4.29\) ppm, which remained unchanged after three catalytic cycles (\(-4.28\) ppm). This is also confirmed in the \({}^{13}\)C MAS NMR spectra (b and d), with the main peak at around 128.7 ppm still present. Some minor changes may be observed, perhaps due to the adsorption of organic species, which may contribute to minor structural modifications. Thus, the spectra suggested that the overall structure of the catalyst remained preserved. However, while the catalyst retained its main structural features, some surface modifications or partial deactivations may occur upon reuse.  
Figure 7: Recyclability tests using **MRImd@PMo11 VO40** as catalyst for (a) \(\beta\)-myrrene oxidation and (b) \(\beta\)-caryophyllene oxidation. Green bars: conversion (%) and blue line: oxide yield (%).
# Floral Scent Evaluation of Three Cut Flowers Through Sensorial and Gas Chromatography Analysis
## 2 Materials and Methods
### Sensory Analysis of Floral Scent  
For the sensorial analysis, 80 individuals, including males and females with no restriction on age, were part of a 'non-trained' panel that performed the sensorial analysis carried out at the Laboratory  
Figure 1: Flowers of oriental lily (_Lilium_ spp. cv. ‘Sweetness’), freesia (_Freesia_ x hybrid cv. ‘Oberon’), and chrysanthemum (_Chrysanthemum_ spp. cv. ‘Marble’) (from left to right) used for the sensorial analysis (**A**) and GC-MS analysis (**B**).  
of Sensorial Analysis, Faculty of Agricultural Sciences, University of Chile. They were recruited via email and using advertising posters, and their participation was absolutely voluntary.  
The floral scent from fresh cut flowers of three species (oriental lily, freesia, and chrysanthemum) was evaluated. Each sample was identified by a three-digit numerical code and presented to the evaluators as previously described (Figure 1A).  
Individuals were firstly asked to complete a survey regarding general information about themselves (i.e., age, sex, income, flower purchasing frequency, and consumption habits) and about what they appreciate more when buying or looking at flowers. Five characters were presented (flower color and size, floral scent, stem length, and vase life) and the assessment was performed using the following Likert scale: 'Strongly agree', 'agree', 'neutral', 'disagree', and'strongly disagree'.  
After the first survey, individuals were asked to evaluate floral scent liking and intensity by randomly approaching each flower and sniffing at an approximate distance of 10 cm. They were asked to wait about 1 min in between the evaluation of each sample. Assessment of floral scent liking was performed using a survey with the following hedonic scale: 'Like extremely'; 'like very much'; 'like moderately'; 'like slightly'; 'neither like nor dislike'; 'dislike slightly'; 'dislike moderately'; 'dislike very much', and 'dislike extremely'. Floral scent intensity was also assessed with the following scale: 'Extremely high';'very high';'moderately high';'slightly high'; 'neither high nor low';'slightly low';'moderately low';'very low'; and 'extremely low'.
## 5 Simulations and Results Analysis

Table 3: Simulation Parameters. It can be seen from Figure 6 that PRR does not perform well in our simulations because of the poor communication conditions. PRR drops with time under each protocol. AODV shows the best performance at the beginning of emergency communication (0-150 s) on PRR, which is because  
Figure 4: Nodes left with more than 10% energy over time. Figure 5: Nodes left with more than 10% energy over time. nodes can find destinations easily by multicasting their requests with AODV protocol. After 150 s, MCDM-ECP gains the highest PRR due to the multi-criteria method, while AODV performs the worst, since too much energy is consumed on multicasting requests. LEACH performs slightly worse than MCDM-ECP after 150 s, as the energy load is evenly distributed among the nodes in the network. In emergency communications, rescue and post-disaster recovery for long periods are needed; thus, the performance over the long term is more important than in the short term. Our proposed MCDM-ECP algorithm performs better regarding energy consumption as well as in PRR than the other two protocols we discussed.
## Materials and Methods
### Discriminant Analysis Algorithms  
#### 2.5.1 K-Nearest Neighbor (KNN)  
The KNN Classifier is a simple but widely used method for classification purposes. It determines the category of the unknown sample according to the categories of its K nearest samples in the training set. In this study, Euclidean distance was used as a measure of the distance, and the unknown sample was assigned to a category that got more votes from the K nearest samples by means of a vote. The different number of neighbors K were tested from 3 to 19, with a step of 2 during the cross-validation process, and the number that resulted in the highest accuracy was selected as the optimal K value for discriminating samples in the testing set.
## 3 Materials and Methods  
The analysis was conducted in the 1 st phase development of the Sihwa Industrial District, a National Industrial Complex located in Ansan-si, Gyeonggi-do, South Korea. The area is covered with multi types of building such as industrial buildings, detached and semi-detached buildings. The Korean National Geographic Information Service supplied the researchers with a collection of orthophotos taken by drones in 2016. These photos were 0.25 m resolution and utilized a coordinate system based on the GSR80 geodetic reference system. Orthophotos were used for this study because these images suitable for area computing. In contrast to an uncorrected aerial image, an orthophoto may be used to accurately measure distances since it is an exact portrayal of the earth's surface that has been corrected for topographic relief, lens distortion, and camera tilt [36]. In other words,  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Study** & **Objectives** & **Method** & **Remarks** & **Data** & **Scale** \\ \hline \multirow{8}{*}{**[PERSON] et al., 2016**[30] & Proposed an automated method for computing BCR and FAR & Modified Mean Shift Algorithm & Extracts buildings as homogeneous objects rather than MSH & \multirow{8}{*}{**USM**} & \multirow{8}{*}{**BS**} \\  & & & & & \\ \hline \multirow{8}{*}{**[PERSON] et al., 2018**[12] & Examine the extent to which implementation of BCR influences land-use changes & Field Survey, Quantitative & Time-consuming, intensive & Observation Data & \multirow{8}{*}{**BS**, **PS**} \\  & Develop a model for estimating building coverage & Statistics & Required various types of input data and complexity & & \\ \hline \hline \end{tabular} Note: RC: Regional-scale; DS: District-scale; BS: Block-scale; PS: Parcel-scale. SI: Satellite imagery, SAR: Synthetic Aperture Radar image, DSM: Digital model surface, OSM: Open Street map, UAV: Unmanned aerial vehicle (Drone).  
\end{table}
Table 1: _Cont._orthophotos have been geometrically rectified to have a consistent scale, which is crucial for achieving an accurate building area calculation.  
The dataset includes images taken of two Zones, A and B (Figure 1), which were used to export image chips to form the training dataset. Due to a lack of available data for training deep learning models, images taken in Zone B were divided into two parts; one part was used to combine with that of Zone A to form the training dataset. This makes sure that the training data set is large enough and includes various building types for effective model training. The remaining part of Zone B was used to test model performance, extract the building footprints, and perform the BCR calculations.
## 4 Experiments and Results
### Results of Image Quality Enhancement
#### 4.2.3 Experiment and Evaluation of the Model Performance Optimized by Member
As the optimized detection model for each member was constructed through learning, precise detection was possible, and the accuracy performance demonstrably improved by 11.31% (Blendmask), and 8.893% (Mask-RCNN). In experimental model for each member, the overall performance of the Blendmask (mAP 92.87) is better than that of the mask-RCNN (mAP 90.374). In the case of rail and road pavement models, the mask-RCNN performance is higher, so mask-RCNN can be used as the optimal model for this member. In conclusion, the optimal model for each member could be verified through experiments. The experimental results confirmed that the proposed model exhibited better overall performance in detecting various types of damages. As, in some cases, the occurrence of the type of damage differs with the bridge member, constructing an optimized model for each member could serve as an approach for improving the model performance for the automatic detection of different types of damage.
# RAMC: A Rotation Adaptive Tracker with Motion Constraint for Satellite Video Single-Object Tracking
###### Abstract
Moreover, compared to the rotating bounding box, it cannot express accurate semantic information, such as the real size and orientation of the object, as shown in Figure 2. To address the object rotation and tracking drift issues of SOT in SVs, we proposed a rotation adaptive tracker with motion constraint (RAMC) consisting of a rotation and a translation branch in this paper. We performed quantitative and qualitative experiments on the space-born SV datasets. The experimental results demonstrate that the RAMC tracker  
Figure 1: Visualization of object rotation and tracking drift in SVs. The symbol # represents the prefix of the frame number. The current frame is shown in the upper-left corner of each image. The yellow arrow indicates the orientation of the object. (**a**) and (**e**) show the original frames, and the selected objects are enlarged. (**b–d**) show the object rotation. (**f–h**) show the tracking drift due to the complex background and low contrast of the ship and wake. outperforms state-of-the-art algorithms and runs at over 40 FPS. The major contributions are summarized as follows:  
1. We analyze the relationship between the intuitive rotation and the potential translation. And the rotation and translation motion patterns are decoupled by decomposing the rotation phenomenon into a translation solution. It could achieve adaptive rotation estimation when applied to SOT in SVs. 2. The appearance and motion information, contained in adjacent frames, are then synergized into the framework. It constructs the motion constraint term on the appearance model to prevent tracking drift and guarantee precise localization. 3. An internal shrinkage strategy is proposed to narrow the gap between the rotating and axis-aligned bounding boxes in the evaluation benchmark. It models axis-aligned rectangles with ellipse-like distributions to optimize the evaluation process.
# Review of Photodetectors for Space Lidars
###### Abstract  
Photodetectors play a critical role in space lidars designed for scientific investigations from orbit around planetary bodies. The detectors must be highly sensitive due to the long range of measurements and tight constraints on the size, weight, and power of the instrument. The detectors must also be space radiation tolerant over multi-year mission lifetimes with no significant performance degradation. Early space lidars used diode-pumped Nd:YAG lasers with a single beam for range and atmospheric backscattering measurements at 1064 nm or its frequency harmonics. The photodetectors used were single-element photomultiplier tubes and infrared performance-enhanced silicon avalanche photodiodes. Space lidars have advanced to multiple beams for surface topographic mapping and active infrared spectroscopic measurements of atmospheric species and surface composition, which demand increased performance and new capabilities for lidar detectors. Higher sensitivity detectors are required so that multi-beam and multi-wavelength measurements can be performed without increasing the laser and instrument power. Pixelated photodetectors are needed so that a single detector assembly can be used for simultaneous multi-channel measurements. Photon-counting photodetectors are needed for active spectroscopy measurements from short-wave infrared to mid-wave infrared. HgCdTe avalanche photodiode arrays have emerged recently as a promising technology to fill these needs. This paper gives a review of the photodetectors used in past and present lidars and the development and outlook of HgCdTe APD arrays for future space lidars.  
a 2024 24 6620 10.3390/s24206620
# Endophytic Colonization of Pepper (_Capsicum annum_) Controls Aphids (_Myzus persicae_ Sulzer)
## 1 Introduction  
Endophytes are microorganisms that spend at least part of their lives living non-parasistically within plants [1]. There is accumulated evidence that many entomopathogenic fungi are symbiotic with several plant species while others are species-specific. Usually, this endophytic relationship reinforces plants with insecticidal or insect repellent traits, a characteristic that could be exploited for designing environmentally friendly applications for insect control in agriculture [1, 2]. Fungal entomopathogens such as _Beauveria bassiana_ Balsamo ([PERSON]) (Hypocreales: Cordycipitaceae), _Metarhizium anisopliae_ ([PERSON]) [PERSON] (Hypocreales: Clavicipitaceae) and _Isaria fumosorosa_ ([PERSON] & [PERSON] (Hypocreales: Clavicipitaceae), are important participants in the regulation of pest populations.  
There is a plethora of recent studies on the insecticidal and insect-repellent attributes of endophytic entomopathogenic fungi [1, 3, 4, 5, 6, 7]. In fact, as well as being potentially beneficial to plant growth [3], they are also capable of increasing rates of infection and mortality among feeding insects, compared to other biological agents. Noteworthy is also the fact that their symbiosis with the host plant is usually asymptomatic while it triggers the plant to adjust its response to abiotic changes [8, 9, 10, 11]. Endophytic entomopathogenic fungi are thus considered as a promising alternative for chemical insecticides and transgenic plants [12]. Aphids are important plant pests, causing considerable direct or indirect losses to several crop species [13].  
The green peach aphid _Myzus persicae_ Sulzer (Homoptera: Aphididae) is a cosmopolitan aphid species responsible for serious economic losses. It is polyphagous, feeding on more than 50 plant families, damaging agricultural, industrial and horticultural crops, as well as stone fruits. In Greece, _M. persicae_ is an important pest in pepper crops [14], and aphid control is predominantly achieved with chemical insecticides. However, this practice has caused environmental and resistance problems [14]. Consequently, there is an increasing interest in the use of endophytic entomopathogenic fungi in biological plant protection. In this context, we documented the effects of the endophytic _B. bassiana_, _M. anisopliae_ and _I. fumosorsea_, in the sweet pepper _Capsicum annum_, on the development of the green peach aphid _Myzus persicae_. To this end, we sprayed the pepper plant with \(10^{8}\) conidia/mL of each fungus. Aphid mortality, aphid population and plant growth parameters were monitored and recorded for three months.
## 4 Hardware Design of Dual-Phase Sensitive Lock-in Amplifier Circuits
### Phase Sensitive Detector Module  
A phase-sensitive detector is the central component of a phase-locked amplification circuit. It multiplies the reference signal and the filtered target detection signal. Analog Devices Inc (ADI) offers the AD835, a four-quadrant analog multiplier chip with excellent multiplication gain bandwidth that fully meets the design requirements. Figure 7 shows the internal structure and pinout of this chip. In this design, pins X2 (7) and Y2 (2) are grounded. Pin Y1 (1) is connected to the output of the target signal channel, while pin X1 (6) is connected to the output of the reference signal channel. Pin W (5) is connected to the input of the low-pass filtering module, and pins VP (6) and VB (3) are connected to the positive and negative 5 V DC power supplies, respectively. Based on Equation (7), the signal passing through the phase-sensitive detector comprises a DC component and an alternating current (AC) component, with the effective signal located in the DC component. To retain the valid signal, a low-pass filter is used to remove the DC component after a multiplication operation.  
Figure 6: Structure diagram of phase shifter.