esa-sceva/satcom-chunk-collection huggingface dataset:
# Analytical Model for the Duty Cycle in Solar-Based EH-WSN for Environmental Monitoring
## 6 Solar Energy Harvesting Model  
Another fundamental component in the analysis of an energy-harvesting system is the energy production model. Thus, for a solar-based EH-WSN, the energy that can be harvested by a solar module embedded into a sensor node needs to be characterized. Specifically, we use the energy production model proposed and validated in [58], which takes into account the relevant parameters of the solar cell, namely efficiency and surface, as well as the solar irradiance or solar intensity, defined as the amount of solar power incident per unit of surface. For the solar irradiance, the model proposed in [58] is based on data obtained from the RetScreen NASA program [59], which consists of two parameter sets for any given location in terms of its longitude and latitude coordinates: \(STDHOURS_{month}\), the standard number of hours of solar light in a month, and \(D_{month}\), the standard value of maximum irradiance in a month. Note that \(t_{surtise}=h-\frac{STDHOURS}{2}\) and \(t_{sunset}=h+\frac{STDHOURS}{2}\) are the time instants corresponding, respectively, to the sunrise and sunset. Based on these parameters, the proposed model for the irradiance at a given time, \(D(t)\), obeys a quadratic trend:  
\[D(t)=\begin{cases}-\frac{(t-h)^{2}}{p}+D_{month}&\text{if }t_{surtise}\leq t \leq t_{sunset}\\ 0&\text{otherwise}\end{cases} \tag{34}\]  
Figure 14: Avrora vs. energy model comparison for the 20-nodes network with \(DC=3\%\) (**left**) and \(DC=10\%\) (**right**).  
Figure 13: Energy consumption after the simulation of the 20-node topology, with \(DC=3\%\) (**left**) and \(DC=10\%\) (**right**), for 2, 3, 4, 10, 20 and 30 rounds.  
In this expression, \(p=\frac{STDHOURS^{2}}{4D_{month}}\), \(t\) is any hour between 0:00 and 24:00 and \(h\) denotes the hour of maximum solar light (12:00). Though this model was further refined in [60], it predicts very accurately the solar irradiance that can be expected at given spatio-temporal coordinates. For illustration, Figure 15 shows the hourly irradiance curves for the cities of Madrid and Hamburg during the months of January and July. These curves have been obtained by using the data shown in Table 5 (extracted from the RetScreen database).  
Then, the power output delivered by a solar cell of efficiency \(\eta\) and surface \(S\) can be expressed in the following way:  
\[P_{out}(t)=D(t)\eta S \tag{35}\]  
Unfortunately, the efficiency of solar cells is still rather small. For instance, the efficiency of the widely used solar module KL-SUN3W is \(\eta=12.8\%\) under standard conditions, which means that only 12.8% of the solar power absorbed is converted into electrical power.
# Dynamic Modeling of McKibben Muscle Using Empirical Model and Particle Swarm Optimization Method
## 3 Hysteresis Phenomena  
The research on hysteresis phenomenon has been recorded for decades. Early study on this phenomenon is first observed in 1881 by [PERSON] within the field of ferromagnetism [36]. It is historic dependence, where it can be considered as a system that has memory function. The effects produce from the input to the system are reflected with a certain delay in time. According to research conducted by [PERSON] and [PERSON] in 2005, hysteresis is a quasi-static phenomenon in which a sequence of periodic inputs produces a nontrivial input-output loop as the period of input increases without bound [37]. This phenomenon arises in diverse fields ranging from physics to biology, from material science to mechanics, and from electronics to economics [38; 39]. The focus in this paper is on the inherent hysteresis phenomena in McKibben muscle. The hysteresis phenomena in McKibben muscle have more asymmetry and can be difficult to model when compared to other fields such as smart actuators, material, ferromagnetism, etc. This is especially at low and high input pressure region where the contraction length behavior is highly nonlinear.
# Investigation of Salt and Water Diffusion During Dry Salting, Wet Curing, and Ultrasonic Wet Curing
###### Abstract  
In the meat industry, significant time is required for curing, which is determined by the rate of salt and water migration within the meat. The aim of our research was to determine the diffusion rate of salt and water during different curing processes by measuring salt and water content at different times. The diffusion coefficients were determined in three curing processes: dry salting (traditional process), wet curing (industry standard process), and wet curing combined with active ultrasound (innovative process). Three theoretical models were examined to describe the diffusion in meat. The salt diffusion coefficient of a cylindrical loin meat sample (80 mm \(\times\) 015 mm) treated with dry salting was found to be 4.22 \(\times\) 10\({}^{-10}\) m\({}^{2}\)/s, which increased by one-third when wet curing was applied and doubled when active ultrasound with an intensity of 14.1474 W/cm\({}^{2}\) and a frequency of 19 kHz was added. The water diffusion coefficient was found to be 2.42 \(\times\) 10\({}^{-9}\) m\({}^{2}\)/s in the case of dry salting, which decreased by 75-80% when wet curing was applied. In wet curing supplemented with ultrasound, water diffusion decreases less than in traditional wet curing. Our research has confirmed that active ultrasound can be used as a part of a combined treatment to accelerate curing.  
salt diffusion in meat; diffusion model for meat; curing with active ultrasound; meat curing; dry salting; wet curing 2025
## 2 Materials and Methods
### Pretreatment  
Rectangular electrical pulses were used in the pretreatment process using PEF. A voltage of 40 kV amplitude was applied to the electrodes. Based on the preliminary studies, the process parameters were selected [23; 24; 25]. The generated electrical pulses were characterised by a width of 50 us and a frequency of 5 kHz. Considering the chamber's coaxial characteristics, the generated electric field intensity was non-uniform. The highest electric field intensity was at the inner electrode surface (38.66 kV/cm), and the lowest was at the outer electrode surface (11.66 kV/cm). Previously crushed and hydrated samples with a volume of 0.5 L were introduced into the disintegration chamber using a hopper. In the filled chamber, the substrate was sandwiched between two electrodes to which high-voltage electrical pulses were applied. As a result, during processing, the substrate was in the zone of interaction of a high-intensity electric field. The UP process was carried out in a beehive disintegrator with a HIUS probe with 400 W power, 24 kHz frequency, and 10 mm probe diameter. According to the manufacturer's equipment specifications, the acoustic power density for the electrode tip is 300 W/cm\({}^{2}\). Samples with a volume of 0.25 L were placed in a flat-bottomed beaker, and then a titanium probe with a diameter of 10 mm was immersed to a depth of 4 cm in the liquid sample and subjected to ultrasound. Ultrasonic radiation was produced directly from the probe's tip in continuous mode. Using a rotary controller, the mode was set for continuous acoustic irradiation without pulse interruption. The amplitude of the oscillations was adjusted, and the ultrasound output power was set at 100% of the nominal power. This study was divided into nine series. The criterion for the division was based on the energy consumed for the disintegration process: UP0, PEF0--0 Wh/ kg TS--control sample; UP1, PEF1--0.05 Wh/g TS; UP2, PEF2--0.1 Wh/g  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Hydration [\%] & 71.1 \(\pm\) 1.09 \\ Dry weight [\%] & 28.91 \(\pm\) 1.09 \\ Dry organic weight [\% TS] & 73.03 \(\pm\) 1.04 \\ Total carbon (TC) [mg C/g TS] & 380.75 \(\pm\) 11.22 \\ Total organic carbon (TOC) [mg C/g TS] & 326.9 \(\pm\) 18.78 \\ Total nitrogen (TN) [mg N/g TS] & 44.28 \(\pm\) 4.56 \\ C/N & 8.60 \\ Cellulose & 23.68 \(\pm\) 2.23 \\ Hemicellulose & 17.81 \(\pm\) 1.55 \\ Lignin & 4.27 \(\pm\) 0.42 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of chicken manure.  
Figure 1: PEF disintegration installation: (1) substrate chopper; (2) substrate container with a stirrer; (3) peristalic pump for substrate; (4) charging hopper; (5) disintegration chamber cabinet.  
TS; UP3, PEF3--0.15 Wh/g TS; UP4, PEF4--0.2 Wh/g TS; UP5, PEF5--0.26 Wh/g TS; UP6, PEF6--0.3 Wh/g TS; UP7, PEF7--0.36 Wh/g TS; UP8, PEF8--0.41 Wh/g TS.
# Nucleobase-Containing Polymers: Structure, Synthesis, and Applications
## 4 Applications of Nucleobase-Containing Polymers in Materials Science
### DNA Delivery  
DNA delivery, especially non-viral DNA delivery, is a powerful and popular tool for gene silencing in various diseases [104; 105; 106; 107]. However, there are still challenges to building an efficient delivery system. In most cases, cationic polymers have been widely studied and investigated for DNA delivery, but they usually encounter some difficulties such as low DNA uptake, slow DNA release, and lack of nuclear targeting [108; 109]. To expand the materials toolbox for DNA delivery, [PERSON] et al. utilized synthetic DNA analogs (CNAs) and synthesized triblock copolymer (PEG-CNA-PLGA) for sequester high loading of DNA [90]. These synthetic triblock copolymers were translated into polymer nanoparticles through an emulsion technique. In addition, these CNA-containing particles exhibited high encapsulation of complementary DNA sequences through specific nucleobase recognition interactions, which demonstrated the potential application of these CNA-containing particles as DNA carriers for specific gene silencing (Figure 10).  
Figure 10: DNA loading measurement of triblock PEG-CNA-PLGA nanoparticles [90]. Reproduced with permission. Copyright John Wiley and Sons, 2017.
# Study on EEMD-Based KICA and Its Application in Fault-Feature Extraction of Rotating Machinery
## 4 Application and Validation
### Experimental Analysis of Faulty Gear
#### 4.1.6 Results and Discussions  
Compared with the methods of wavelets and EMD, the proposed method has a significantly better performance for the feature extraction of a single-channel vibration signal of faulty gear. Although VMD and EEMD can extract fault features, the noise energy is still very high. Compared with the method of EEMD, the noise energy has been reduced in the proposed method, which is efficient for fault-feature extraction.
## 3 Attacks on AES
### Attacking AES
#### 3.3.1 Attack on AES-128  
We assume that the attacker shares the cache with the victim, which means he can monitor accesses to the cache with line granularity. We also assume that the attacker has access to the ciphertext. The attacker needs to recover information from each of the four T-tables. To do so, he can monitor one line of one table, one line of each T-table or even try to monitor the 16 lines of each of the four tables at the same time (64 lines). The number of samples required to retrieve all the bits of the key will vary in each case as will the effect of the attack observed by the victim [18]. The more lines monitored at a time, the more noticeable the attack will be. While a slight increase in the encryption time can be assumed to have been caused by other programs or virtual machines running on the same CPU, a higher increase in the encryption time would be quite suspicious.  
For each of the evaluated techniques, i.e., _Prime+Probe_, _Prime+Abort_, _Flush+Reload_ and _Flush+Flush_, we use a similar process to retrieve the desired information. The process followed during the attack involves three steps and is the same in all cases:  
* **Setup:** Prior to the attack, the attacker has to retrieve the necessary information about where the T-tables are located in memory; that is, their virtual addresses or the cache set in which they are going to be loaded. This way he ensures that the cache is in a known state, ready to perform the attack.
2. **Measurement collection:** In this step, the attacker monitors the desired tables, applying each technique between the requested encryptions and stores the gathered information together with the ciphertext. As explained in Section 2.2, this step can be subdivided into three stages: initialization, waiting and recovering.
3. **Information processing:** Finally, the attacker uses the information recovered in the previous steps and the information about the T-tables (the contents of the monitored line) to retrieve the secret key.  
These main steps are equivalent to previous proposals [36; 44]. Other proposals are also applicable to our non-access attack, such as the one suggested by [PERSON] et al. [47], which aims to detect the bounds of the encryptions instead of triggering them. However, this approach also depends on the accuracy of the detection, which introduces a new variable to be considered when comparing the effectiveness of the attack approaches. In contrast, the aforementioned setup can be generalized for all the considered techniques, allowing a fair comparison.  
In the following, we describe each of the steps for each of the considered algorithms and their particularities in our experimental setup. We consider two scenarios. In the first one, the attack is performed from a spy process running in the same OS as the victim. In the second one, the attacker runs in a VM and the victim runs in a different VM and they are both allocated in the same host. Table 1 includes the details of the machine in which the experiments are performed. The steps are equal in the two considered scenarios.
## 1 Introduction
The instrumental noise and transfer function of a double-flexure two-axis tilt sensor with a tilt readout based on an optical walk-off sensor were investigated theoretically and experimentally [11]. The VIGRO GW group used a rotational accelerometer with a sensitivity of 2-3 nrad\(/\sqrt{\mathrm{Hz}}\) for frequencies below 2 Hz to measure the seismic ground tilt spectrum [12]. Recently, a new rotational vibration isolator with an extremely low resonant frequency of \(0.055\pm 0.002\) Hz, consisting of two concentric spheres separated by a layer of water and joined by very soft silicone springs, was reported to reduce rotational vibration noise at all frequencies above its resonance [13]. This paper reports a tilt active vibration isolator using a vertical pendulum (VP) tiltmeter, with a flat elastic spring suspension and PZTs, as a detector of tilt vibration and a servo-controlled actuator, respectively. To extend the dynamic range, the actuator needs to produce a much larger displacement, and therefore the significant dynamic hysteresis caused by the driving process has to be considered carefully. A high-performance piezoelectric servo-controlled actuator is developed through a parallel controller using an inverse-model actuator and a proportional-integral-differential (PID) digital adjuster.
# A Method for the Rapid Propagation of Emergency Event Notifications in a Long Vehicle Convoy
###### Abstract  
Convoys composed of autonomous vehicles could improve the transportation and freight industries in several ways. One of the avenues of improvement is in fuel efficiency, where the vehicles maintain a close following distance to each other in order to reduce air resistance by way of the draft effect. While close following distances improve fuel efficiency, they also reduce both the margin of safety and the system's tolerance to disturbances in relative position. The system's tolerance to disturbances is known as string stability, where the error magnitude either grows or decays as it propagates rearward through the convoy. One of the major factors in a system's string stability is its delay in sending state updates to other vehicles, the most pertinent being a hard braking maneuver. Both external sensors and vehicle-to-vehicle communication standards have relatively long delays between peer vehicle state changes and the information being actionable by the ego vehicle. The system presented here, called the Convoy Vehicular Ad Hoc Network (Convoy VANET), was designed to reliably propagate emergency event messages with low delay while maintaining reasonable channel efficiency. It accomplishes this using a combination of several techniques, notably relative position-based retransmission delays. Our results using Network Simulator 3 (ns3) show the system propagating messages down a 20-vehicle convoy in less than 100 ms even with more than a 35% message loss between vehicles that are not immediately adjacent. These simulation results show the potential for this kind of system in situations where emergency information must be disseminated quickly in low-reliability wireless environments.
# Strength Correlation and Prediction of Engineered Cementitious Composites with Microwave Properties
###### Abstract  
This paper presents the results of microwave and mechanical measurements of engineered cementitious composites (ECCs) using a nondestructive microwave near-field detecting technique. The objective of this research is to investigate the correlations between effective conductance and compressive strength of ECCs at various curing ages under the influence of different initial water contents. Parallel measurements and regression analysis on compressive strength and microwave conductance were undertaken. It is shown that the strength evolution of ECCs can be accurately modeled and predicted by using microwave conductance at the early ages using bi-exponential functions. Compressive strength grows as a function of decreasing effective conductance, whereas the regression coefficients of the correlation models have a linear variation with water-to-binder ratios. These findings have highlighted the effectiveness of the microwave technique in detecting the variation of liquid phase morphology and pore structure.  
engheered cementitious composite; strength prediction; microwave technique; electrical conductance; structural health monitoring; water-to-binder ratio Article
# Passive RFID-Based Inventory of Traffic Signs on Roads and Urban Environments
###### Abstract  
This paper presents a system with location functionalities for the inventory of traffic signs based on passive RFID technology. The proposed system simplifies the current video-based techniques, whose requirements regarding visibility are difficult to meet in some scenarios, such as dense urban areas. In addition, the system can be easily extended to consider any other street facilities, such as dumpsters or traffic lights. Furthermore, the system can perform the inventory process at night and at a vehicle's usual speed, thus avoiding interfering with the normal traffic flow of the road. Moreover, the proposed system exploits the benefits of the passive RFID technologies over active RFID, which are typically employed on inventory and vehicular routing applications. Since the performance of passive RFID is not obvious for the required distance ranges on these in-motion scenarios, this paper, as its main contribution, addresses the problem in two different ways, on the one hand theoretically, presenting a radio wave propagation model at theoretical and simulation level for these scenarios; and on the other hand experimentally, comparing passive and active RFID alternatives regarding costs, power consumption, distance ranges, collision problems, and ease of reconfiguration. Finally, the performance of the proposed on-board system is experimentally validated, testing its capabilities for inventory purposes.  
inventory; infrastructure-to-vehicle; location systems; radio propagation; RFID; traffic signs; urban environment +
Footnote †: journal: Sensors
# Reliability Analysis of Multi-Process Machining Based on Information Entropy
## 1 Introduction
When using the weighted network to analyze the transmission of machining error, the weight is directly related to the accuracy of analysis results, so the method of determining the weight is very critical. In view of the limitations of the above methods, this paper introduces information entropy and mutual information [20] into the analysis of machining process reliability. It establishes a reliability analysis model of the machining process based on information entropy. The proposed model can quantitatively analyze the inherent machining error of each process and the error transmission and combine the two for comprehensive consideration. The model proposed in this paper is not specifically designed for a certain machining process, but rather for analyzing data generated from various machining processes within actual process flow. In actual production, the collected machining quality data can be input into the model to evaluate the weak links with large fluctuations in processing quality and the processes that have a greater impact on the machining quality of mechanical parts. Using the model to evaluate the same machining process, the accuracy of the evaluation results depends on the completeness of the machining quality data used (including the inherent error data of equipment and the machining quality inspection data of processes). The more complete the machining quality data, the more accurate the evaluation result will be. Therefore, certain labor and time costs are required to obtain relevant machining quality data. The reliability analysis model of the machining process based on information entropy has strong adaptability to scenarios, which provides a new idea for research on the reliability of the machining process.
## 4 Proposed CLCQ Protocol
### Overview of CLCQ  
The process of the CLCQ protocol is shown in Algorithm 1. The main steps of the CLCQ algorithm are outlined below:  
Figure 7: Packet structure.  
1. Initialize the network: Set parameters such as node coordinates, Q-values, V-values, communication range, maximum buffer length, and initial energy.
2. Broadcast beacon: Obtain the status information of neighbor nodes, such as the residual energy, current buffer state, and locations.
3. Send RTS: Broadcast RTS packet with a test data segment. After receiving the RTS packet, the neighbor node uses the test data segment to calculate the BER and writes the result to the CTS packet.
4. Receive CTS packets from neighbor nodes.
5. Determine the forwarding candidate set: Select based on node depth, remaining energy, and buffer state.
6. Calculate the Q-values of all nodes in the forwarding candidate set.
7. Select the node with the highest Q-value as the next hop, update the V-value, and then proceed with the data packet transmission.
8. Determine if the sink node has received the data packet: If the sink node has received the data packet, the process ends; if not, repeat steps (3) to (7) until the sink node receives it.  
```
1: Initialize network;
2: Broadcast beacon;
3: Get\(E_{\text{res}}\), \(Buff_{nour}\), \(Buff_{max}\), and the location of neighbors;
4: Begin
5: If (node \(n_{i}!=\text{sink node}\)) then
6: Send RTS;
7: Receive CTS;
8: Select forwarding candidate set;
9: While the next hop is not found do
10: For\(n_{j}\in\text{candidateSet}\)do
11: Calculate the reward function \(R_{ij}\);
12: Calculate the action-utility function \(Q^{*}(s_{i},a_{i})\);
13: End for
14: Select \(n_{j}\) with the max \(Q^{*}(s_{i},a_{i})\) as the next hop;
15: Update the \(V(s_{i})\) of \(n_{i}\) with max \(Q^{*}(s_{i},a_{i})\);
16: End while
17: Packet transmission;
18: Receive ACK;
19: End if
20: End
```  
**Algorithm 1** CLCQ Algorithm