esa-sceva/satcom-chunk-collection huggingface dataset:
# Low-Power Wake-Up Receivers for Resilient Cellular Internet of Things
## 6 State-of-the-Art NB-IoT WUR
### WUR RF Front End  
Figure 16 shows the block diagram of the WUR. The WUR is designed to efficiently receive and process the NWUS as specified in Rel. 15 of the 3 GPP standard. The receiver front end utilizes a low-noise transconductance amplifier (LNTA)-first low-IF architecture. A low IF is preferred over direct conversion to reduce the center frequency offset (CFO) effects as well as flicker noise on subcarriers near DC. An oscillator, a fractional-N phase-locked loop (PLL), and a 25% duty-cycle generator are implemented to generate the local oscillator (LO) signal. For each of the I/Q paths, the WUR RF front-end consists of an active mixer, a complex filter, a bandpass filter (BPF), a programmable-gain amplifier (PGA), and a successive-approximation analog-to-digital converter (SAR ADC), The RF front end operates in the RF frequency range of 750-960 MHz and converts the signal to a low IF of 360 kHz.  
Figure 14: Architecture of a passive mixer-first ULP receiver.  
Figure 15: Architecture of an LNA-first ULP receiver.  
An optimized LNTA is followed by active mixers to down-convert and generate quadrature IF signals. Second-order complex poly-phase filters provide bandpass filtering and reject the image frequency. A frequency synthesizer consisting of a fine-step fractional-N PLL and low-power LC-VCO allows for tuning over a wide range of input frequencies. The phase noise of the LC-VCO can be relaxed to save power thanks to the lower SNR requirement of the correlation-based NWUS. The 8-bit SAR ADCs operate at 1.4 MS/s for an oversample rate of \(\sim\)4x. This allows an increase of \(\sim\)6 dB of SNDR (\(\sim\)1 ENOB) to the ADC output.
# Lightweight Design and Evaluation of Square Reflector
## 2 Square Reflector Lightweight Design
### Mirror Thickness Design  
The size of the mirror includes the mirror size and thickness. This paper studies a square reflector whose size is 500 mm \(\times\) 500 mm, and the diameter of the circumscribed circle is calculated to be 707 mm.  
At present, for square reflectors, there is no general empirical formula to determine the thickness of the mirror. According to [PERSON]'s study regarding the relationship between diameter-to-thickness ratio dr (D/t) and self-weight deformation, an empirical formula can be given for initial calculation [11; 12; 13]. The formula is as follows:  
\[\delta=\frac{3 gga^{4}}{16 El^{2}}=\frac{3 gg(\
icefrac{{D}}{{t}})^{2}D^{2}}{256E} \tag{1}\]  
In the formula, \(\delta\) is the maximum self-weight deformation, \(\rho\) is the material density, \(g\) is the acceleration of gravity, \(a\) is the radius of the disc, \(a=D/2\), and \(E\) is the modulus of elasticity; \(t\) is the thickness of the disc, and \(D\) is the diameter of the disc. Substituting the circumcircle diameter \(\Phi\)707 mm into the Formula (1), the thickness of the square reflector is calculated to be 78 mm, and this result can be used as an initial reference value.
# Augmented Reality: A Systematic Review of Its Benefits and Challenges in E-learning Contexts
## Augmented Reality  
### Definition and Taxonomy  
Ref. [10] defined AR as a technology that overlays virtual objects (augmented constituents) onto the real world. The Oxford Dictionary defines this as a technology that superimposes a computer-produced portrayal on a user's outlook of the real world and, therefore, shows a composite perspective. In their handbook of AR, [11] hypothesize that AR is a real-time direct or indirect outlook on a real-world physical environment, which is improved (augmented) by adding virtual computer-generated information to it. This definition is congruent with that of [PERSON], [PERSON], and [PERSON] [12], who view AR as a concept used for computer-generated 3D environments, which allow the user to cross the threshold and interact with synthetic environments. In other words, the individual using the computer is able to \"immerse\" him/herself to varying degrees into the computer's synthetic virtual world that may be either a simulation of some form of reality or a simulation of a complex phenomenon.  
According to [13], AR can be viewed as a computerized extension of people's reality in a system that is characterized by three key features: combined reality and virtuality, interactive in real time, and presented in 3D. As noted by [11], AR is within the context of reality and virtuality, which [PERSON] and [PERSON] described as a continuum spanning real and virtual environments. In this context, AR and augmented virtuality (AV) arise, where AR represents the real world and AV represents the virtual world. For this reason, [14] consider AR to be a concept in technology rather than a certain form of technology. Similarly, [6] posited that AR should not be limited to any particular type of technology but viewed as a broad concept that can be conceptualized beyond technology. Thus, AR should play a supplementary role in any setting rather than replace reality in such settings. For instance, in academic settings, virtual objects can be incorporated into the real world, and AR implementation could exploit the affordances of that real world by offering supplementary and contextual information that enhances (augments) students' experiences of reality [15].
## 6 Related Work
### Routing in Mobile Sensor Networks  
There are many works related to data harvesting in MSN, however, mostly focused on delay or fault-tolerant MSN (e.g., [14; 15]).  
Pervasive information gathering in Mobile Sensor Networks is studied in [14]. This human oriented data collection is analyzed when flooding and optimized flooding is used. Then, new method based on two components, namely the probability of message delivery and queue management, is proposed. Data is forwarded to the neighbor only when the neighbor has higher probability of delivery. Queuemanagement algorithm evaluates whether to drop or transmit the message based on the fault tolerance. Another interesting solution for dynamic networks with mobile sensor nodes is epidemic routing [9]. Message delivery is ensured by random pair-wise exchange of messages among mobile sensor nodes. There are three main goals for epidemic routing, such as maximizing packet delivery, minimizing message latency and also minimizing total resources consumed in message delivery. Semi-epidemic approach is explored in [16], where the probability of replication is proportional to the time of the last encounters and their frequency. Each sensor node maintains delivery predictability vector, which indicates likelihood to meet other sensors. Data collection is based on the message forwarding from the lower predictability sensor nodes to the higher predictability sensors.  
Another group of communication protocols for wireless sensor networks is based on widely studied area of wireless _ad-hoc_ networks. Robustness of the routing when nodes have mobility is one of the key goals of Mobile _Ad-Hoc_ Network (MANET) protocols. However, limited energy, low computation capability and memory makes direct use of such protocols difficult, sometimes prohibitive. In the recent years, several MANET protocols have been simplified and adapted to sensor networks to be more suitable for energy constraint nodes with low computational capability (e.g., [7; 17; 18]). _Ad-Hoc_ On Demand Vector (AODV) [19] routing protocol was adapted to sensor node's capabilities in [7] as AODVjr. The authors show that AODVjr can reach almost the same performance as the original AODV while having much less complexity. In [18], the authors proposed Not-So-Tiny AODV (NST-AODV) protocol, which provides support for mesh sensor networks. The drawback is that it requires large memory storage.
###### Abstract
[44] tested the use of FTIR spectrometry in conjunction with multiple linear regression (MLR), PCR and PLS regression. The MLR calibration model proved to be the best in the spectral range 650-4000 cm\({}^{-1}\), which made it possible to predict the viscosity with a relative standard deviation (RSD) of 3.2% from the spectra. [PERSON] et al. [45] discussed the development of the FTIR-PLS model for fast and accurate simultaneous determination of lubricant parameters for gas engines and turbines: density, viscosity and pour point. These wavenumber regions were identified as suitable spectral regions: 4000-3097 cm\({}^{-1}\), 1864-1552 cm\({}^{-1}\), 1320-665 cm\({}^{-1}\). The excluded spectral regions did not contain any spectral data or were ranges showing absorbance higher than 1.5 a.u. According to the authors, the spectral region and the number of principal components (PCs) are the main criteria for the construction of a good calibration model. FTIR spectrometry in conjunction with PLS (iPLS) has also been used to quantify the penetration of contaminants (petrol, ethylene glycol and water) into lubricating oils [46] and to examine the adulteration of high-quality motor oils with used or lower quality oils [47]. A large number of chemometric methods have been used to classify motor oil according to the origin of the base oil (synthetic, polysynthetic and mineral oil) and according to the relationship between oil viscosity and winter temperatures (SAE 0W, 5W, 10W, 15W) and high summer temperatures (SAE 20, 30, 40, 50) [48]. The summer viscosity number is determined by the kinematic viscosity at 100 \({}^{\circ}\)C, i.e., approximately the operating temperature of the motor oil. The aim of this paper is to present the methodology of design and validation of FTIR model in conjunction with PLS and PCR regression for rapid determination of one of the most important parameters of motor oils-kinematic viscosity at 100 \({}^{\circ}\)C (\(\text{KV}_{100}\)\({}^{\circ}\)C). The proposed methodology for determining the viscosity of motor oils from the Infrared (IR) spectrum in conjunction with powerful mathematical and statistical software is an alternative to the standardized method for determining the kinematic viscosity at 100 \({}^{\circ}\)C with an Ubbelohde capillary viscometer. The methodology is designed to determine \(\text{KV}_{100}\)\({}^{\circ}\)C of motor oils of the grade SAE 15W-40, which are the best-selling motor oils in most of Europe and, due to the weather conditions in this geographical area, are sufficient for most users of turbo-diesels.
# An Energy Efficient Sink Location Service for Continuous Objects in Wireless Sensor Networks
## 5 Conclusions  
In this paper, we propose a novel continuous object tracking scheme, Origin-based Continuous Object Tracking (OCOT), which provides energy-efficient sink mobility support in wireless sensor network. OCOT integrates location updates from a mobile sink using regional locality of sources detecting a continuous object. Also, OCOT exploits distributed data report to avoid the hot-spot problem. Additionally, the reactive and static clustering in OCOT increases the efficiency of location update and data report. Simulation result proves that OCOT is greatly efficient in terms of the total energy consumption and distributional energy consumption. Especially, OCOT reduces at least 49% of energy compared to the existing scheme during 100 s of continuous object tracking process. Under the same simulation setting, in addition, the over 7.25% and 1.25% of sensors consumed over 25% of the energy budget in the existing schemes and OCOT respectively, which suggests that the enhanced network lifetime of OCOT.  
Conceptualization, S.-H.K.; Investigation, S.K.; Methodology, H.C.; Writing--original draft, C.K.; Writing--review & editing, S.O. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2020R1C1C1010692).  
The authors declare no conflict of interest.  
Figure 18: Distribution of energy consumption in TTDD (**left**), LBDD (**center**), OCOT (right).
## 3 Results and Analysis
### Analysis of OVA in Kouniss from Different Regions  
Different regions of koumiss have unique flavors, mainly determined by the types, amounts, and corresponding thresholds of volatile flavor substances they contain. Studies have shown that the contribution of a single aroma component to the overall aroma of koumiss depends on its concentration and odor threshold [37]. Although the above analysis provides a quantitative characterization of the flavor substances in koumiss, it is only by understanding the threshold of each substance that the key flavor substances can be directly linked to their contribution to the overall aroma of koumiss. The OAV can be used to evaluate the composite contribution of flavor substances to food. Compounds with an OAV \(\geq\)1 are generally considered to be aroma-contributing components in koumiss, while substances with an OAV \(\geq\)10 are important aroma-contributing components [38]. The results (shown in Table 3) indicate that 20 volatile flavor substances can be used to calculate OAV, and their OAV values are all greater than 1. Among them, the OAV values of caprylic acid ethyl ester, caprylic acid, 9-decenyl acetate, decanoic acid ethyl ester, decanoic acid, isoamyl alcohol, phenethyl alcohol, and hexanoic acid ethyl ester in koumiss from different regions are all higher than 10, indicating that these volatile substances may be key flavor components in koumiss.  
The results are shown in Table 3. The YL region stands out from other regions regarding its OVA values, with notable components including ethyl decanoate, ethyl octanoate, and ethyl 9-decenoate. In particular, ethyl decanoate and ethyl octanoate in the YL region have OVA values more than seven times higher than those in the ALT region and are therefore the most important characteristic aromas of the YL region. Ethyl decanoate and ethyl octanoate impart fruity and creamy aromas and have OVA values exceeding 100 in all regions of koumiss and have repeatedly been confirmed as key aroma components in koumiss from different regions of China [41]. The OVA value of phenethyl alcohol in the ALTe region is significantly higher than in other areas, making it one of the main aroma components that affect koumiss in this region. It is worth noting that previous studies on koumiss in other regions did not find phenethyl alcohol as a leading aroma sample, making it a unique flavor in the traditional fermented koumiss of the Kazakh ethnic group in Xinjiang. Both octanoic acid and decanoic acid, as sour aromas with OVA values greater than 10, contribute positively to the koumiss flavor and the dairy aroma of koumiss, providing a unique and distinctive taste.
# Research on Location Selection Model of 5G Micro Base Station Based on Smart Street Lighting System
## 4 Location Selection Model of 5G Micro Base Station
### Location Selection Model Construction
#### 4.2.3 Objective Function
Then all the particles were divided into elite individuals (top 50%) and ordinary individuals (bottom 50%), with each individual representing a particle. The new generation of populations was all generated by elite individuals, half of which was generated by elite individuals through the speed \(v_{\text{id}}\) and position update of the particle swarm algorithm. The new individuals generated are regarded as enhanced elites. The other half are enhanced elites as parent nodes, through selection, crossover, and mutation operations are generated. The specific generation method is as follows:  
Figure 3: Schematic Diagram of Partition Mode. * Selection: randomly select four individuals from the enhanced elite for fitness value comparison, and the top two with the highest fitness value are selected as the parent nodes;
* Crossover: preset crossover probability \(P_{c}\), randomly select a crossover point among all binary bits and generate two new individuals by single-point crossover. Before each crossover, a random number \(P_{j}\) is generated in [0, 1]. If \(P_{j}<P_{j}\), then perform the crossover operation;
* Mutation: preset mutation probability \(P_{m}\), randomly select a mutation bit, generate a new individual utilizing basic bit mutation and a random number \(P_{\text{b}}\) in [0, 1] before each mutation, and perform mutation operation if \(P_{\text{b}}<P_{\text{m}}\);
* The overall process of location selection is shown in Algorithm 1. ```
Input: Map information, the coverage radius \(r\), and coverage requirement \(\gamma\). Output: The optimal number \(N\) and location \(L\) corresponding to the global extreme value. Start: Step1: Partition processing; Step2: Calculate the constraints on the number of base stations; Step3: Initialize population position and velocity \(v_{\text{id}}\); Step4: Iterative optimization:  Calculate the fitness of each particle through objective function \(F^{\prime}\);  Update individual extremum and global extremum;  Screening for elite individuals;  Generate a new generation:  Update particle flight speed \(v_{\text{id}}\) through update formula \(s(v_{\text{id}})\);  Selection, crossover, mutation;  Determine whether the conditions are met. ```  
**Algorithm 1** The location selection model algorithm (Overall location selection process).
## 2 Related Work
In this paper, computation offloading and resource allocation in an integrated space-air-marine network composed of multiple UAVs equipped with edge servers, an LEO satellite, and heterogeneous maritime IoT devices are investigated. A cloud-edge-device collaborative MEC system supporting partial task offloading under joint latency and energy consumption constraints is first modeled, with the joint association control, power allocation, task partitioning, and resource distribution is formulated as a non-convex mixed-integer optimization problem. To efficiently solve this problem in a dynamic, partially observable environment, it is reformulated as a POMDP and a multi-agent deep deterministic policy gradient (MADDPG)-based algorithm is developed that leverages centralized training with decentralized execution, enabling each agent to learn continuous control policies for offloading decisions and resource allocation. The main contributions of this paper are as follow:  
1. A hierarchical cloud-edge-device collaborative MEC system is established, which integrates LEO satellites, UAVs and maritime IoT devices, then a joint optimization problem for task offloading and resource allocation is formulated under latency and energy constraints based on the system model. 2. The optimization problem is reformulated as a partially observable Markov decision process (POMDP) and a multi-agent reinforcement learning framework based on the MADDPG is presented, which enables decentralized agents to perform collaborative offloading decisions through centralized training, effectively handling the non-station dynamics of space-air-marine networks. 3. Extensive numerical simulations are carried out to validate the effectiveness of the proposed MADDPG-based offloading and allocation scheme. The results demonstrate that the algorithm consistently outperforms baseline strategies in terms of the energy-delay tradeoff, convergence rate and overall system efficiency. The reminder of this paper is structured as follows. The details of the system model and problem formulation are introduced in Section 3. In Section 4, the proposed MADDPG-based algorithm for computation offloading and resource allocation in the integrated space-air-marine network is presented in detail. The performance of the proposed algorithm will be evaluated through simulation experiments and compared with baseline methods in Section 5. Finally, this paper is concluded in Section 6.
## 2 Study Area and Data
### Data
#### 2.2.2 Climate Variables
\begin{table}
\begin{tabular}{l c c} \hline \hline
**GCM Model** & **Spatial Resolution** & **Research Institute and Country** \\ \hline ACCESS-CM2 & 0.25\({}^{\circ}\)\(\times\) 0.25\({}^{\circ}\) & Commonwealth Scientific and Industrial Research Organization (CSIRO) and the Bureau of Meteorology (BoM), Australia \\ CanESM5 & 0.25\({}^{\circ}\)\(\times\) 0.25\({}^{\circ}\) & Canadian Centre for Climate Modelling and Analysis (CCCma), Canada \\ CNRM-CM6-1 & 0.25\({}^{\circ}\)\(\times\) 0.25\({}^{\circ}\) & Centre National de Recherches Meteorologiques (CNRM), France \\ MIROC6 & 0.25\({}^{\circ}\)\(\times\) 0.25\({}^{\circ}\) & Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Japan \\ BCC-CSM2-MR & 0.25\({}^{\circ}\)\(\times\) 0.25\({}^{\circ}\) & Beijing Climate Center, China Meteorological Administration, Beijing, China \\ MPI-ESM1-2-LR & 0.25\({}^{\circ}\)\(\times\) 0.25\({}^{\circ}\) & Max Planck Institute for Meteorology (MPI-M), Germany \\ UKESM1-0-LL & 0.25\({}^{\circ}\)\(\times\) 0.25\({}^{\circ}\) & A collaborative effort between the Met Office Hadley Centre and the Natural Environment Research Council (NERC), United Kingdom \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Brief introduction to the employed GCMs from NEX-GDDP-CMIP6.
###### Abstract  
This paper presents experimental investigations into the effects of ultrafine blast furnace slag on microstructure improvements against chloride penetration in saturated and unsaturated cementitious systems exposed to cyclic drying-wetting conditions. The hydration kinetics of ultrafine slag powders and pore solution chemistry in slag-blended cementitious systems at different ages, together with the main hydration products and pore structure characteristics, were determined. The chloride profiles accounting for different slag contents and drying-wetting cycles were measured. The results reveal that the reactivity of ultrafine slag can be well described with Avrami's equation. The dilution effect of the slag predominated the pore solution chemistry, and the pH value decreased with a higher inclusion of slag. An optimal inclusion of 65% slag by mass of the binder corresponding to the finest pore structure and highest hydrolatic content was found, which provides a reasonable basis for the slow chloride diffusion and high chloride binding. Under drying-wetting exposure, the specimen with a lower saturation exhibited a higher chloride transport caused by capillary absorption in the skin layer. The chloride transport tended to be diffusion controlled after sufficient drying-wetting cycles.  
ultra-fline blast furnace slag; pore solution chemistry; microstructure; chloride transport; drying-wetting; unsaturated +
Footnote †: journal: Applied Physics Letters