esa-sceva/satcom-chunk-collection huggingface dataset:
# An Embedded Sensor Node Microcontroller with Crypto-Processors
## 2 Hardware Accelerated Crypto-Algorithms
### Public Key Cryptography  
Public-key algorithms are often seen as inappropriate for implemention on wireless sensor nodes. This is mainly driven by the large code size and expensive computation requirements of these implementations. Standard public-key schemes such as the Diffie-Hellman key agreement protocol [39] or the Rivest, Shamir und Adleman (RSA) signature algorithms [40] require a large number of multiplications to perform a single cryptographic operation. The elliptic curve cryptography (ECC) as an advanced replacement of RSA offers smaller keys and faster computation. Furthermore, it promises savings in data bandwidth, memory utilization and energy consumption. The performance superiority of ECC over RSA when implemented on an 8-bit ATmega128L processor is presented in [41]. The authors of [42] have shown that a challenge-response authentication based on ECC-160 uses only \(1/12\) of the energy of its RSA-1024 counterpart.  
Although the software implementation of public key cryptography on small scale sensor devices is proved to be possible, the introduced power overhead is still too high. A promising solution to make asymmetric cryptography suitable for small scale platforms is the usage of hardware accelerators. It can improve efficiency and performance of crypto operations in order of magnitudes on those nodes. A hardware platform containing an additional off-the-shelf coprocessor from ATMEL is presented in [43]. The coprocessor is used to improve RSA computation. A VHDL implementation of the [PERSON]'s scheme and the NtruEncrypt algorithm is presented in [44] and a design of ECC-163 coprocessor is presented in [25]. A comparison between the ECC software solution on a TI MSP430 microcontroller and an FPGA implementation is given in [27]. It shows that the power consumption can be improved three orders of magnitudes when ECC is implemented on an FPGA.
## 4 Results and Analysis
### Gts-Allocated Nodes  
Fog nodes, after receiving several GTS requests during CAP of a session, scrutinize the nodes that are allowed to send their data in their allocated GTS during that session. The proposed \(TMPAD\) assists fog computing nodes in scrutinizing nodes by applying the 0/1 knapsack algorithm on TOPSIS values. However, FCFS assigns GTSs to nodes by applying a first come first serve algorithm, SJF allocates GTSs to those nodes first which have initiated the least number of time slot requests, and in IJF, the nodes with the highest slot requests will be allocated GTSs first. The results are compared for varying numbers of nodes, varying channel bandwidth, and varying transmission power of the GTS-requesting nodes and are shown in Figures 8, 9 and 10, respectively.  
Results shown in Figure 8 verify that the \(TMPAD\) entertains more GTS-requesting nodes in a session as compared to the other three algorithms. When the number of GTS-requesting nodes is 50, then \(TMPAD\) scrutinizes 32 legitimate nodes to transmit their data as compared to 20 legitimate nodes in other algorithms within the same time slot capacity in a session, because \(TMPAD\) scrutinizes the nodes with higher trust values. However, the other three algorithms do not differentiate between legitimate and malicious nodes. With the increase in the number of GTS-requesting nodes, more legitimate nodes are entertained in \(TMPAD\) as it allocates GTSs to nodes efficiently to transmit more data. However, the other standards have the same number of GTS-requesting nodes because they have already fulfilled all of the available GTSs in the session.  
Results in Figures 9 and 10 verify that \(TMPAD\) allocates the same number of available GTSs to more GTS-requesting nodes as compared to the other three algorithms for varying channel bandwidth and varying transmission power of the nodes. Results in Figure 9 show that the proposed \(TMPAD\) entertains more legitimate nodes in allocating GTSs as compared to all three standards. The increase in channel bandwidth allows nodes to send fewer GTSs for the same amount of data. This results in allowing more GTS-requesting nodes to assign their requested GTSs in a communication session. However, for all varying channel bandwidths, \(TMPAD\) allocates time slots to more GTS-requesting nodes as compared to the other three standards. The same trend follows for varying transmission power of nodes, as shown in Figure 10. It is evident from the results that the \(TMPAD\) assigns the same number of GTSs to more GTS-requesting nodes for all different transmission power levels.  
Figure 7: Data transmitted by legitimate nodes in session for varying transmission power.  
The increase in power allows more data transmission capacity within a time slot, which allows nodes to transmit the same amount of data in fewer time slots, resulting in more GTS-requesting nodes to be assigned the same number of GTSs within a current session.  
Figure 8: Number of GTS-allocating nodes for varying number of GTS-requesting nodes.  
Figure 9: Number of GTS-allocating nodes for varying channel bandwidth of GTS-requesting nodes.
# Efficient Secure Routing Mechanisms for the Low-Powered IoT Network: A Literature Review
## 1 Introduction
These attacks are further categorized into physical layer-based, network layer-based, software-based, and data-based attacks. Inaddition, the security processes associated with Industry 4.0 are addressed. The suggested research performed a comparative analysis with current work based on various criteria, indicating that the proposed work covers several factors, whereas existing work discusses fewer. Based on the preceding explanation, the proposed work focuses on four questions and targets them as follows:  
1. What are the applications utilized in IoT-LPN? 2. What are the existing protocols in IoT-LPN and their strengths and limitations? 3. What are the security objectives of WSN-IoT? 4. What are the security issues and challenges in WSN-IoT? Figure 3 depicts the research collection mechanism, including identifying the data, title screening, exclusion criteria, and finally, the included papers. The rest of the paper can be described as follows. Section 2 briefly discusses IoT in Industry 4.0. Similarly, Section 3 is related to IoT-LPN architecture and its applications. Section 4 is about security issues and challenges in WSN-IoT. Section 5 covers the categories of network attacks in WSN-IoT layers. Section 6 is related to the WSN-IoT security mechanism in Industry 4.0. Subsequently, the existing literature is discussed in Section 7. Similarly, a comparative analysis of the proposed work with the current work is discussed in Section 8, and finally, the conclusion and findings are described in Section 9.
## 3 Algorithms for Managing Complex Traffic Scenarios and Violations
### Detection and Prediction Methods
#### 3.2.4 Machine Learning for Object Classification and Movement Prediction  
Convolutional neural networks (CNNs) remain the backbone of many object classification systems in autonomous driving. ResNet and its variants, such as ResNeXt introduced by [PERSON] et al. [70], have demonstrated exceptional performance in classifying a wide range of objects relevant to driving scenarios.
Appl. Sci._**2015**, \(5\), 1942-1954; doi:10.3390/app5041942  
_applied sciences_  
**ISSN 2076-3417**  
www.mdpi.com/journal/applsci  
_Article_  
**A Novel Piezoelectric Energy Harvester Using the Macro Fiber Composite Cantilever with a Bicylinder in Water [PERSON] 1, [PERSON] 1, [PERSON] 1, [PERSON] 2 and [PERSON] 1,*  
1 School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China; E-Mails: [EMAIL_ADDRESS] (R.S.); [EMAIL_ADDRESS] (X.S.); [EMAIL_ADDRESS] (F.L.)  
2 College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China; E-Mail: 1990 [EMAIL_ADDRESS]  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +86-451-8641-7891; Fax: +86-451-8641-6119.  
Academic Editor: [PERSON]  
_Received: 27 October 2015 / Accepted: 11 December 2015 / Published: 17 December 2015_  
**Abstract:** A novel piezoelectric energy harvester equipped with two piezoelectric beams and two cylinders was proposed in this work. The energy harvester can convert the kinetic energy of water into electrical energy by means of vortex-induced vibration (VIV) and wake-induced vibration (WIV). The effects of load resistance, water velocity and cylinder diameter on the performance of the harvester were investigated. It was found that the vibration of the upstream cylinder was VIV which enhanced the energy harvesting capacity of the upstream piezoelectric beam. As for the downstream cylinder, both VIV and the WIV could be obtained. The VIV was found with small \(L/D\), e.g., 2.125, 2.28, 2.5, and 2.8. Additionally, the WIV was stimulated with the increase of \(L/D\) (such as 3.25, 4, and 5.5). Due to the WIV, the downstream beam presented better performance in energy harvesting with the increase of water velocity. Furthermore, it revealed that more electrical energy could be obtained by appropriately matching the resistance and the diameter of the cylinder. With optimal resistance (170 k\(\Omega\)) and diameter of the cylinder (30 mm), the maximum output power of 21.86 uW (sum of both piezoelectric beams) was obtained at a water velocity of 0.31 m/s.  
**Keywords:** vortex-induced vibration; wake-induced vibration; energy harvesting; piezoelectric beam; cylinder
# Migrating from Developing Asynchronous Multi-Threading Programs to Reactive Programs in Java
## 6 Implementation Details
### Handling System Errors
```
@CircuitBreaker( name=\"followedIdsCircuitBreaker\", fallbackMethod=\"getUserFeedWithCachedFollowed\" ) publicFlux<TweetDto>getUserFeed(UUIDuserId){ returninteractionClient.getFollowerIds(userId).collectList().flatMapMany( tweetRepository::findByUserIdInOrderByCreatedAtDesc ).flatMap(this::enrichTweetDto); } publicFlux<TweetDto>getUserFeedWithCachedFollowed( UUIDuserId, Throwable t ) { Stringkey=FOLLOWED_CACHE+\"::\"+userId; returnredisTemplate.opsForValue().get(key).map(v->{ try{ returnobjectMapper.readValue( v,newTypeReference+List<UUID>>>(){ } ); } catch(JsonProcessingExceptione){ thrownewRuntimeException(e); } }).flatMapMany(Flux::fromIterable).collectList().flatMapMany( tweetRepository::findByUserIdInOrderByCreatedAtDesc ).flatMap(this::enrichTweetDto); }
```  
**Listing 1** Example of using Circuit Breaker in reactive applications. In the code above, the _getFollowerIdsFromCache_ method will be called automatically if a high number of errors are detected in the communication with the interaction microservice. Specifically, the circuit breaker is configured to open when more than 50% of requests fail within a rolling window of 100 calls. Once appropriate functionality is restored and the service can accept requests again, the traffic will be completely re-routed back through the default method.
## 5 Results and Discussion  
This section includes the results of the simulations carried out in some study cases, aiming at the assessment of OWiNoC link performance in terms of SNR and BEP. The outcomes of the corresponding link-level RT simulations are discussed, highlighting some general trends and constraints for the feasibility of wireless networks-on-chip at optical frequency.
## 6 Simulation Verification
### Verification of the Inertial Response and Primary Frequency Regulation  
Figure 8 presents simulation results of inertial response and primary frequency regulation when the grid frequency fluctuates, where the grid-side filter inductor, L\({}_{t}\), is 0.038 mH, the short-circuit ratio is 2.5, i.e., the line inductor, L\({}_{\text{line}}\), is 0.304 mH and the line resistor, R\({}_{\text{line}}\), is 0.045 \(\Omega\). In Figure 8, when the grid frequency rises from 1.00 p.u. to 1.01 p.u. at 40 s, the DC-link voltage, u\({}_{\text{dc}}\), follows the real-time fluctuation of the grid frequency and increases to 1.01 p.u. The MSC reduces the output power and then recovers. At the same time, the wind turbine speed rises and then recovers, realizing the inertial response function. The ESC absorbs power, realizing the primary frequency regulation function. When the grid frequency decreases from 1.00 p.u to 0.99 p.u. at 60 s, the DC-link voltage, u\({}_{\text{dc}}\), follows the real-time fluctuation of the grid frequency and decreases to 0.99 p.u. The MSC increases the output power and then recovers. At the same time, the wind turbine speed decreases and then recovers, realizing the inertial response function. The ESC releases power to realize the primary frequency regulation function.  
It can be seen from Figure 8 that under the proposed VS control strategy, the DC-link voltage of the GSC can sense the fluctuation of the grid frequency in real time. In addition, according to the dynamics of the DC-link voltage, the PMSG-based wind turbine with the auxiliary energy storage battery can realize the function of inertial response and primary frequency regulation at the same time, where the inertial response function is realized relying on the inertia of the wind wheel, and the primary frequency regulation function is realized through the ESC.
## 2 Materials and Methods
### Representing SIF Retrieval Methods
Indirect methods aim to utilize baseline knowledge of the quantitative relationship between the radiances of specific spectral bands in the absence of SIF (typically a proportion) to infer the presence of an additive signal of SIF in collected observations (see Appendix A.1 for the quantitative approach). When applied to Fraunhofer lines specifically, this approach is called Fraunhofer line discrimination (FLD), but the principle is the same when considering oxygen bands. The baseline knowledge of proportional depth can be established by utilizing a reference target that is known not to contain SIF, captured as part of an acquisition (an in-scene target), or a non-SIF-containing reference target that comes from a different acquisition or a simulation (an out-of-scene target). By utilizing proportional relationships between band radiances, rather than relying on absolute radiance, indirect methods can circumvent the need to estimate, or otherwise account for, any influence that would scale the bands in question uniformly, such as atmospheric absorption, or target reflectivity. However, since indirect retrievals rely on pairs or groups of bands at different spectral locations, there can be some secondary reactions in the uncertainty in SIF retrievals when influences act non-uniformly on the targeted spectral bands. These principals are demonstrated in Figure 3. Indirect SIF retrieval methods presented in this study are based on pairs of bands for oxygen and solar absorption features, with each pair having an established proportional relationship between a lower-radiance \"valley\" band, and a higher radiance \"peak\" band. The processes of selecting the bands and quantifying the expected proportional radiance is detailed in Section 2.3.1.
## Problem Description and Contribution
### Paper Contribution  
In this paper, a novel ADRC is constructed by connecting a second LESO in parallel with an original LESO (the inner LESO) to construct a nested LESO. The advantage of this configuration is that the second LESO estimates and eliminates the remaining generalized disturbance that eluded from the inner LESO due to bandwidth limitations. Its excellent performance becomes very evident when considered in terms of measurement noise. The proposed observer with nested structure differs from the state observer with a cascade structure, where the latter is just a state observer and used in special applications with delayed measurements such as the presence of an arbitrarily long delay in the output [22] or for position and attitude estimation of Unmanned Air Vehicles (UAVs) [23]. It should be emphasized that our main contribution is proposing a new structure to build a modified linear extended state observer by nesting two LESOs, sharing the same output rather than modifying the internal structure of the LESO. To the best of the authors' knowledge, using double LESOs within the same ADRC structure, with applications in highly uncertain nonlinear systems, has not previously appeared in the literature.
###### Abstract
However, this technique can be associated with high cost which limits the use of this system [16; 19]. This study takes the Porong Estuary, Indonesia, as a case study. Porong Estuary provided a unique setting as this area is characterised by a rapidly prograding delta and concomitant mangrove expansion [21; 22; 23]. It is because of the mud volcanic eruption in 2006 and subsequent mudflow diversion known as LUSI (acronym of lumpur (mud) and sidoarjo (the regency name)) [23]. Several studies have been conducted to investigate the effects of LUSI's high sediment load on the Porong River, the Porong Estuary, and surrounding coastal waters [21; 24; 25] and the development of mangrove on the created wetland in general [26; 27; 28]. However, none of them explored the mangrove dynamics and investigated the structural characterisation of the mangroves in the rapidly prograding delta. This study aims to analyse mangrove dynamics on a rapidly prograding delta by a novel integration of UAV SfM Photogrammetry and multiple sources of satellite imagery in cloud computing Google Earth Engine (GEE). The first objective of this study is to retrieve mangrove biophysical properties (height and individual location of trees) employing the off-the-shelf UAV SfM photogrammetry, in combination with ground-truthing based on field data. The second objective is to generate a three-monthly classification of mangrove areas using Landsat 7, Landsat 8, Sentinel 1, and Sentinel 2 in GEE. These mangrove extent maps represent the dry season and wet season, where two maps were created during each of these seasons every three months. The third objective is to estimate the mangrove age and age-height relationship based on the combination of UAV and GEE analysis.
# Analysis of 5G and LTE Signals for Opportunistic Navigation and Time Holdover
## 2 Materials and Methods
### Tracked Signals  
STARE operates on the primary and secondary synchronization signals (PSS and SSS, respectively) embedded in LTE and 5G signals. These synchronization signals are broadcast by towers as a fundamental part of the signal structure and can be used without any form of authentication or subscription, thus making them particularly suitable for SoP purposes. The signals are, for the most part, known a priori, and they significantly help in the detection of available towers, as well as in initial signal acquisition. The fact that we operated in a fully non-authenticated state also implied that any operator- or situation-specific effects (such as the number of connected devices, current network utilization, operator specific settings, type and quantity of data traffic, quality of service settings, etc.) had no impact on the measurements.  
The only factor the authors believed to have a potential effect on the measurements were the base station power saving measures. Since the base stations cannot suspend the transmission of PSS and SSS without becoming invisible to the user equipment (UE), they generally do not do so outside of specific situations, as discussed in Section 4.1.  
All cellular transmissions in Norway work in frequency division duplex (FDD) mode, and--while the bandwidth of signals varies--the PSS and SSS features are, in all cases, constrained to a subset of the central 63 (LTE [15]) or 240 (5G [16]) orthogonal frequency division multiplexing (OFDM) subcarriers.
## 2 Bulk Crystal Characteristics
### Crystal Growth  
ScBO\({}_{3}\) crystals are usually grown utilizing the Czochralski method due to the congruent characteristics of this crystal [37]. However, difficulties, such as the intense volatilization of B\({}_{2}\)O\({}_{3}\), not only lead to segregation of the composition, but also give rise to instability in growth, which greatly affects the optical quality of the crystals [37]. Here, a 10.0 at.% Yb\({}^{3+}\)-doped ScBO\({}_{3}\) single crystal with a 20-mm-diameter was successfully grown using an argon atmosphere in an iridium crucible. The starting materials, Yb\({}_{2}\)O\({}_{3}\), Sc\({}_{2}\)O\({}_{3}\), and H\({}_{3}\)BO\({}_{3}\), were weighed according to the chemical formula Yb\({}_{0.1}\)Sc\({}_{0.9}\)BO\({}_{3}\). Generally, an additional 3 wt% H\({}_{3}\)BO\({}_{3}\) was put in the raw ingredients during the batching process, which was used to compensate for B\({}_{2}\)O\({}_{3}\) volatilization during crystal growth and polycrystalline material preparation. The equation for the chemical reaction is as follows:  
\[0.1\text{Yb}_{2}\text{O}_{3}+0.9\text{Sc}_{2}\text{O}_{3}+2\text{H}_{3}\text{ BO}_{3}\to 2\text{Yb}_{0.1}\text{Sc}_{0.9}\text{BO}_{3}+3\text{H}_{2}\text{O} \tag{1}\]  
A mullite brick with an appropriate thickness was used in the furnace to create a large temperature gradient to avoid constitutional supercooling and reduce volatilization. First, the seed was a platinum wire to obtain polycrystal with plenty of cracks, as shown in Figure 2a. To diminish the cracking, the seed was cut from the bulk polycrystal along _c_-axis. Meanwhile, a micro-convex solid-liquid interface was achieved by optimizing the temperature field and rotation speed, thereby balancing the natural convection and forced convection during the growth process. Although some subsidiary white matter took shape owing to the volatilization, the samples for laser experiments (as presented in the inset of Figure 2b) could be extracted from this optical-quality crystal (Figure 2b). Polycrystalline material was used as the standard to measure and calculate the density of elemental Yb\({}^{3+}\) in this crystal. The effective distribution coefficient of Yb\({}^{3+}\) was ascertained as 0.95.
## 5 Feasibility Study
### LTC System for Large Enterprises  
The proposed LTC system depends on an embedded Linux platform to provide VoIP functionalities along with LTC capabilities. Based on the performance evaluation carried out in Section 5.2, this meets home and small business requirements. However, this setup would not be suitable for large enterprises. As a result, for LTC deployment in large enterprises, the PoT gateway can be added as an integral part of the existing UC solution to enrich it with LTC capabilities. Otherwise, a powerful computing platform (servers, workstations, etc.) can be utilized rather than embedded Linux platforms. Figure 14 contrasts the LTC implementation for small offices and large enterprises.  
Figure 12: Relation between the number of active channels and the operating system load average (transcoding).  
Figure 13: Relation between the number of active channels and the CPU utilization (transcoding).
## 3 Results and Discussion  
The proposed antennas were designed in CST Studio Suite V2021 and fabricated by using a PCB milling machine. Figure 10 shows the fabricated two-element MIMO antenna. The measurements were conducted using the MS2028C VNA and radiation pattern measurement setup at Yasar University's Antenna and Microwave Laboratory.