esa-sceva/satcom-chunk-collection huggingface dataset:
# Optimizing Perishable Product Supply Chain Network Using Hybrid Metaheuristic Algorithms
## 2 Problem Description  
Given the perishable nature of products and the importance of managing their logistics, it is crucial to design an appropriate SCN and focus on the flow of products within the network's nodes and arcs. Hence, supply chain managers need to consider both the overall cost of the system and the duration of product perishability. This study incorporates the perishable characteristics of the products into the model, known as LIRP, and proposes an integrated approach to minimize the total cost. Specifically, we investigate an SCN that comprises manufacturers, DCs, and retailers, considering multiple periods and multiple perishable products.  
In this study, the locations of the retailers and manufacturers are predetermined, while those of the DCs are determined by the model. In each period, DCs receive products from manufacturers and subsequently distribute them to retailers by optimized routing and a fleet of heterogeneous vehicles. Wastage may occur during both the inventory process and transportation process, encompassing transportation from manufacturers to DCs and from DCs to retailers. Products exhibit variations in terms of shelf life, thus requiring DCs to ensure that the products delivered to retailers are within their designated shelf life. To minimize product waste, DCs adopt a First-In-First-Out (FIFO) approach [29]. The proposed model aims to reduce the overall network cost by addressing the following key challenges: (1) determining the optimal quantity and locations of DCs, (2) allocating the retailers to the identified DCs for any given product and period, and (3) determining the most efficient vehicle routes from DCs to retailers for any given period.
## 1 Introduction
These methods also produce large data sets and require complex processing algorithms which also increase the power consumption of the sensor nodes. GPR based systems can be used to non-invasively (both to the pipe and surface) detect leaks in the pipes [17]. However performance and detection reliability of these systems is highly dependent on the soil type and condition and they are more suited to dry soils. Moreover, these systems are not suitable for continuous monitoring of large pipe networks (thousands of metres of pipes). Fibre optic technology can potentially solve the major problems with current pipeline monitoring systems. There are many research projects with different levels of success regarding the use of fibre optics in structural health monitoring [18, 19, 20, 21, 22]. Fibre optic cables can be deployed over long distances (few kilometres) to detect leaks or measure temperatures and strains in the pipes [11, 13]. This makes it a suitable technique for pipeline monitoring. Moreover, different types of measurements can be taken via embedded fibre optic sensors. A major fundamental disadvantage of these systems is the potential for redundancy, which currently makes them unsuitable for general adaptation in pipeline monitoring. If, for any reason, a section of the pipe is damaged or it is required to be replaced, the fibre optic system after that location could be potentially put out of service. Moreover, the fibre optic systems are difficult to install and are usually required to be installed while the pipe is being constructed. Furthermore retro fitting of these systems in the case of damage to the fibre can be difficult, uneconomic and potentially can cause blind spots in the system [21]. A multimodal Underground Wireless Sensor Network (UWSN) using low power sensors offers a good solution to the mentioned issues. Dense deployment allows these systems to have an acceptable level of redundancy within the system. Underground wireless sensor networks offer many advantages over the other methods, such as concealment, ease of deployment, retro fitting, reliability and coverage density [23]. Sensor nodes can be retro fitted to the existing pipes individually without the need for a continuous trench. Moreover, flexibility of deployment makes spot monitoring possible where pipe monitoring is only required for a limited section of the pipe. This paper reports on the design and development of a multimodal Underground Wireless Sensor Network (UWSN) for pipeline structural health monitoring. A non-invasive method (to the structure of the pipe) of pressure monitoring is designed and developed based on Force Sensitive Resistor (FSR) technology. This method is then tested and validated in laboratory and field trials. Moreover, power consumption requirements of a suitable UWSN are identified and based on these findings an ultra-low power wireless sensor node is designed and developed.
# Neural Network-Based Cost-Effective Estimation of Useful Variables to Improve Wind Turbine Control
## 3 Neural Network Based Estimators
### Existing Estimators
#### 3.1.2 Torque Estimation  
Typically, aerodynamic torque is estimated (rather than measured) using an estimator that uses generator torque measurements as follows:  
\[\hat{T}_{f}=NT_{g}+10\Omega\] \[\frac{d\Omega}{dt}+10\Omega=(I_{1}+N^{2}I_{2})\frac{dH}{dt}+( \gamma_{1}+N^{2}\gamma_{2})H, \tag{9}\]  
where \(\hat{T}_{f}\) denotes the aerodynamic torque estimate, \(N\) is the gearbox ratio, \(I_{1}\) is the rotor inertia, \(I_{2}\) is the generator inertia, \(\gamma_{1}\) is the low-speed shaft damping coefficient, \(\gamma_{2}\) is the high-speed shaft damping coefficient and \(H\) is the hub speed.  
This is a common aerodynamic torque estimator [7], and the estimation results of the proposed NN-based torque estimator (Section 3.2) are compared to those of this torque estimator (Equation (9)) in this section.
## 4 Results
### Constructs and Methodological Approaches
#### 4.3.4 Interaction Behavior, Drowsiness/Fatigue, and User Experience
\begin{table}
\begin{tabular}{l l} \hline \hline
**Collection Method for Interaction Behavior (n)** & **Parameter** & \(\text{n}_{\text{p}}\) \\ \hline \multirow{7}{*}{Observation (6)} & Walking Behavior & 2 \\ \cline{2-3}  & Automation Enabled/Disabled & 2 \\ \cline{2-3}  & Glancing Behavior & 1 \\ \cline{2-3}  & Pathways & 1 \\ \cline{2-3}  & Reaction Time & 1 \\ \cline{2-3}  & NDRT Engagement & 1 \\ \cline{2-3}  & N/D & 2 \\ \hline \multirow{7}{*}{Standardized Questionnaire (3)} & Brief Sensation Seeking Scale (BSS-8) & 1 \\ \cline{2-3}  & Pedestrian Behavior Questionnaire (PBQ) & 1 \\ \cline{2-3}  & Theory of Planned Behavior (TPB) & 1 \\ \hline Self-Defined Questionnaire (2) & N/D & 2 \\ \hline Eye Tracking/Gaze Behavior (1) & Gaze Percentages & 1 \\ \hline Interviews (1) & Semi-structured Interview & 1 \\ \hline Secondary Task Performance (1) & Single-choice Quiz & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Interaction Behavior collection methods and parameters. User Experience is mainly investigated by self-reported measurements \(\mathrm{n_{p}}\) = 16, \(\mathrm{n_{p}}\) = 5 collect behavioral data, only once psycho-physiological measures by capturing Heart Rate Variability is utilized. Various standardized questionnaires (n = 4) like AttrakDiff [113], UEQ [114], etc. are applied, or interviews (n = 4), and other qualitative methods like UX curve [112], think aloud, and sorting have been conducted. Behavioral data are collected by one paper regarding participants' driving performance, e.g., acceleration, braking, speed, and lane changes. See Table 11. In total, \(\mathrm{n_{p}}\) = 13 different parameters were collected across all papers investigating UX.
# Precision Farming in Hilly Areas: The Use of Network RTK in GNSS Technology
###### Abstract  
The number of GNSS satellites has greatly increased over the last few decades, which has led to increased interest in developing self-propelled vehicles. Even agricultural vehicles have a great potential for use of these systems. In fact, it is possible to improve the efficiency of machining in terms of their uniformity, reduction of fertilizers, pesticides, etc. with the aim of (i) reducing the timeframes of cultivation operations with significant economic benefits and, above all, (ii) decreasing environmental impact. These systems face some perplexity in hilly environments but, with specific devices, it is possible to overcome any signal deficiencies. In hilly areas then, the satellite-based system can also be used to safeguard operators' safety from the risk of rollover. This paper reports the results obtained from a rural development program (RDP) in the Lazio Region 2007/2013 (measure project 1.2.4) for the introduction and diffusion of GNSS satellites systems in hilly areas.  
p 10.3390/agriculture 2017/60; doi:10.3390/agriculture70/0060
# Ephemeral Node Identifiers for Enhanced Flow Privacy
## 1 Introduction
### Contributions  
This work demonstrates how to perturb use of IP addresses for attacks on identity privacy, without modifying any applications and maintaining the correct operation of existing transport protocols as well as normal network routing and forwarding functions. We show that IP's use of time-based 'Temporary Address' values [6] provides little protection against correlation attacks--only by constraining the _linkability_ of the address bytes to within _individual packet flows_ is it possible to prevent flow correlation attacks.  
Using the Identifier-Locator Network Protocol (ILNP) [7], an extension of IPv6 which specifies cleaner semantics and bindings for the bytes of an IPv6 address, we show privacy protection against address-based flow correlation attacks. This can be achieved without disrupting network operations by exploiting ILNP's separation of identity and location semantics in IPv6 addresses. Our solution can be deployed with updates to only the endpoints that require protection, and requires only standard IPv6 connectivity. We also discuss the additional security and privacy capabilities that are possible by building on this defence with ILNP.
## 5 Conclusions  
This study demonstrates that using sEMG sensors to clinically monitor upper extremity muscle activity during acute and subacute stroke recovery is feasible, and preliminary outcomes suggest that changes in muscle activity are observed that track quantitative and qualitative changes in function. Wireless sEMG sensors have the potential to significantly improve tracking and training activities in neurorehabilitation following stroke and may be able to aid in long-term prognostication or improve targeted interventions to promote functional outcomes. Surface EMG technology may also offer hope and motivation to stroke survivors during their early recovery, provided they have access to a simple, intuitive user interface as well as appropriate feedback and education on the signals measured and how they correlate to function. However, current limitations in technology, processing time and procedures, and the user interface must be addressed to provide more useful and valuable information to both clinicians and users. Future studies should examine qualitative and quantitative outcomes in greater numbers of participants with diverse post-stroke presentations, and the further trial of other types of wearable sEMG sensor technologies should be undertaken in healthcare and community settings. Further research should also consider which sEMG metrics most accurately reflect recovery.  
Conceptualization, H.A.F., C.P. and K.M.S.; methodology, H.A.F., C.P., K.M.P., C.J.C. and K.M.S.; project administration, K.M.P.; software, K.M.P. and C.P.; formal analysis, H.A.F. and C.P.; resources, C.J.C.; data curation, C.P.; writing--original draft preparation, H.A.F.; writing--review and editing, C.P., K.M.P., C.J.C. and K.M.S.; visualization, C.P.; supervision, K.M.S.; funding acquisition, K.M.S. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering #R01 EB021935. Additional funding for the first author's time was supported by the NIH National Center on Advancing Translational Science, KL2 TR002317.  
This study was conducted with institutional review board approval from the University of Washington (STUDY 47743).  
Informed Consent Statement: Informed written consent was obtained from the subject involved in the study.  
Data Availability Statement: Data from this study available upon request.  
The authors would like to thank \"[PERSON]\" and his family for their willingness to participate in this study and share their experiences of recovery. Additionally, the authors would like to thank the medical staff at the acute care and rehabilitation hospitals who allowed us to conduct this study in their facilities.  
The authors declare no conflict of interest. The study funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
## 4 Discussion
### Future Research  
Further work needs to be carried out to classify minerals in an attempt to negate or reduce false positives (such as FWP analysis, land, and mineral classification through machine learning). A four-way multivariate correlation test between all remote sensing instruments is a logical next step, including the use of quality indicators such as mean structural similarity index measure (MSSIM) to measure subtle variations between all four similar resampled images. The next step would be to extract more spectral profiles from the Halo handheld spectrometer and identity additional Fe secondary mineral endmembers beyond that of goethite. USGS MICA spectral end-member information could also be used within GEE API to study the nuances between multi and hyperspectral sensors. The FWP analysis would also benefit from incorporating a sub-pixel mapping (SPM) algorithm to improve river boundary delineation accuracies, with coarser imagery benefiting the most [66], and aid the spatial allocation of fractioned water pixels. Methods such as sub-pixel mapping and further detailed sub-pixel swapping techniques could also compliment the FWP analysis and conduct band ratio operations. To fully investigate sensor sensitivity to external factors, such as heavy rainfall events or changes in climatic conditions, the UAV Nano-Hyperspec would need to be used year-round, preferably with all instruments across a range of varying weather conditions.
## 3 Results  
Short-circuit effect verification includes the verification of dynamic effects and thermal effects. The peak current \(\rm i_{p}\) should be used for dynamic effect verification; thermal effect verification requires the calculation of the thermal effect with the Joule integral (\(\int\rm i^{2}dt\)) [32]. The IEC61660-1, 2 (1997) standards provide calculation methods for the short-circuit current and its thermal effect, which will be discussed in Section 4. The methods proposed in this research are introduced first.  
Figure 6: Waveforms of the short-circuit current \(\rm i_{s}\) and DC-bus voltage \(\rm V_{c}\). (**a**) The waveforms of \(\rm i_{s}\). (**b**) The waveforms of \(\rm V_{c}\).
## A Cluster-Based Architecture to Structure the Topology of Parallel Wireless Sensor Networks  
**[PERSON] *, [PERSON], [PERSON] and [PERSON]**  
Departamento de Comunicaciones, Universidad Polit e cnica de Valencia. Camino Vera s/n, 46022, Valencia, Spain; E-Mails: [EMAIL_ADDRESS] (M.G.); [EMAIL_ADDRESS] (D.B.); [EMAIL_ADDRESS] (J.R.D.)  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +34-609-549-043; Fax: +34-962-849-313.  
_Received: 23 November 2009; in revised form: 2 December 2009 / Accepted: 10 December 2009 / Published: 23 December 2009_  
**Abstract:** A wireless sensor network is a self-configuring network of mobile nodes connected by wireless links where the nodes have limited capacity and energy. In many cases, the application environment requires the design of an exclusive network topology for a particular case. Cluster-based network developments and proposals in existence have been designed to build a network for just one type of node, where all nodes can communicate with any other nodes in their coverage area. Let us suppose a set of clusters of sensor nodes where each cluster is formed by different types of nodes (e.g., they could be classified by the sensed parameter using different transmitting interfaces, by the node profile or by the type of device: laptops, PDAs, sensor _etc._) and exclusive networks, as virtual networks, are needed with the same type of sensed data, or the same type of devices, or even the same type of profiles. In this paper, we propose an algorithm that is able to structure the topology of different wireless sensor networks to coexist in the same environment. It allows control and management of the topology of each network. The architecture operation and the protocol messages will be described. Measurements from a real test-bench will show that the designed protocol has low bandwidth consumption and also demonstrates the viability and the scalability of the proposed architecture. Our cluster-based algorithm is compared with other algorithms reported in the literature in terms of architecture and protocol measurements.  
**Keywords:** sensor algorithms; sensor network; clusters architecture
## 5 Discussion
### Key Advantages  
The proposed system offers several advantages:  
* Cost-effectiveness: Ultrasound components are inexpensive compared to other localization technologies, making the system more affordable for large-scale deployments.
* Environmental robustness: The system performs well in various lighting conditions, unlike optical or laser-based methods.
* Differential measurement: By focusing on time differences rather than absolute times, this approach mitigates variations due to environmental factors.
* Scalability: The system can be easily expanded by adding more beacons, allowing for coverage of larger areas or improved accuracy.  
Figure 14: Localization error over time during circular motion. The graph shows how the error varies as the robot completes multiple revolutions.
# Edge-Computing Meshed Wireless Acoustic Sensor Network for Indoor Sound Monitoring
## 4 WASN Design
### Physical Topology  
To design the physical topology of the network (i.e., where the acoustic nodes will be located), it must be considered that in large spaces--more than 10 m\({}^{2}\) scenarios (e.g., room 1 in Figure 6)--several sensors are required, as different areas can generate diverse pressure levels. In this case, at least one sensor per activity area (where an activity area refers to a part of the room that usually produces a similar and meaningful type of sound,  
Figure 5: Conceptual integration of the hardware elements of the sensor. The 3D model of the Raspberry Pi has been retrieved from [41].  
such as a television or a piano) in the room is required for correctly mapping the sound in contrast of a small space (e.g., rooms 2 or 3 in Figure 6) where one microphone is enough to capture a representative value of the sound level of the room. Although the microphone pattern of the proposed sensor is omnidirectional, given that the node and microphone are mounted in the protection box, it is recommended to position the microphone in corners or walls targeting the sound activity zone.  
Despite having tested the prototype in a single location, the design of the Wireless Acoustic Sensor Network is invariant to the deployment characteristics. The only part that is dependent on the environment is the final location of nodes in the areas to be monitored. The design of the WASN consists of:  
* Nodes: \(N\) number of sensors identical to the ones described in Section 3.4, located in strategical places to sense the environment. In the proposed prototype, uninterruptedly, each node sends the acoustical level measured over a programmable period of time to the core of the network.
* Core: A single Raspberry Pi 4B per network that acts as a gateway. The purpose of this node is to receive data from all the synchronized nodes and upload them to the cloud, where a graphic representation of the acoustic map could be visualized. Centralizing the nodes allows fast remote management accessing through the core. It is important to place the core next to the router of the indoor space and do a wired connection to it to minimize connectivity problems. This node does not compute any measurement by itself, and it does not need any microphone.  
An optimized database for Internet of Things (IoT) is required to save all the nodes' data in each programmable period. A potential IoT platform could be Thingspeak, implemented and used in this project, which is an IoT analytics platform service that allows the user to aggregate, visualize and analyze live data streams in the cloud [42].
# Reduction of Pesticide Use in Fresh-Cut Salad Production through Artificial Intelligence
###### Abstract  
Incorrect pesticide use in plant protection often involve a risk to the health of operators and consumers and can have negative impacts on the environment and the crops. The application of artificial intelligence techniques can help the reduction of the volume sprayed, decreasing these impacts. In Italy, the production of ready-to-eat salad in greenhouses requires usually from 8 to 12 treatments per year. Moreover, inappropriate sprayers are frequently used, being originally designed for open-field operations. To solve this problem, a small vehicle suitable for moving over rough ground (named \"rover\"), was designed, able to carry out treatments based on a single row pass in the greenhouse, devoted to reduce significantly the sprayed product amount. To ascertain its potential, the prototype has been tested at two growth stages of some salad cultivars, adopting different nozzles and boom settings. Parameters such as boom height, nozzle spacing and inclination, pump pressure and rover traveling speed were studied. To assess the effectiveness of the spraying coverage, for each run several water-sensitive papers were placed throughout the vegetation. Compared to the commonly distributed mixture volume (1000 L/ha), the prototype is able to reduce up to 55% of product sprayed, but still assure an excellent crop coverage.  
greenhouse; precision spraying; rover; environment protection; operator's health; consumer's safety
## 1 Introduction
The main limitation is the low intensity of Raman scattering from gases. So far, the application of Raman spectroscopy for routine trace gas analysis has not found widespread use due to the inherent weakness of Raman transitions and it was mainly employed in condensed phases [28]. The above-mentioned limitation can be overcome by using intense excitation beams and high-pressure gas cavities. For the reliable \({}^{13}\)C/\({}^{12}\)C ratio measurements, it is critical to calibrate the instruments. The preparation of calibration gas mixtures requires the analysis of the parent gases, such as pure \({}^{12}\)CO\({}_{2}\) and \({}^{13}\)CO\({}_{2}\)[29]. In the present work, we report on the method of quantitative analysis of \({}^{12}\)CO\({}_{2}\), \({}^{13}\)CO\({}_{2}\), \({}^{12}\)CH\({}_{4}\) and \({}^{13}\)CH\({}_{4}\) greenhouse gases based on Raman laser gas spectroscopy.