esa-sceva/satcom-chunk-collection huggingface dataset:
# Narrowband Internet of Things (NB-IoT):
## 5 Open Research Questions and Discussion
### Backward Compatibility and Interoperability  
A ten-year telecommunication generation is characterized by different changes in releases and updates. In order to reach their lifespan as compared to what the standards stipulate, NB-IoT devices should operate for around ten years with a single battery charge. Whenever new releases or updates are introduced, backward compatibility and interoperability should be possible. Apparently, the device complexity is set as low as possible; will these simple devices (hardware) support hard and robust algorithms that will be implemented by over-the-air upgrades/updates to satisfy the demands of future NB-IoT use cases?  
**Summary:** This section has presented the open research questions regarding battery life, radio resource allocation, cell search, and initial acquisition procedures, mobility management, latency, random access, etc., as summarized in Table 4, in order to motivate future research directions. The next section concludes the paper.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Physical Layer** & **MAC Layer** & **Standard** \\ \hline Radio resource management & Timing advance adjustment & Support for small cell \\ \hline Frequency and time & Dynamic scheduling and & TDD support \\ synchronization & semi-persistent scheduling & \\ \hline Random access & Latency & Antenna diversity \\ \hline Channel estimation & Power management & Mobility and handover support \\ \hline Error correction & Network throughput & More efficient group messages \\ \hline Link adaptation & Control packet overhead & Multicarrier operation \\ \hline Interference mitigation & Control plane small data & Network management tool for UE \\  & transmission & differentiation \\ \hline \hline \end{tabular}
\end{table}
Table 4: Open Research Questions related to the physical layer, MAC layer, and standard.
# Few-Shot Image Classification via Mutual Distillation
## 4 Experiments
### Ablation Study
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multirow{2}{*}{**Backbone**} & \multicolumn{4}{c}{**5-Way Accuracy (\%)**} \\ \cline{3-6}  & & **MinilImageNet** & & **CUB** \\ \hline \multicolumn{6}{c}{**1-Shot**} \\ \hline RN & ResNet12 & 54.68 \(\pm\) 0.29 & 71.61 \(\pm\) 0.24 & 72.69 \(\pm\) 0.49 & 86.98 \(\pm\) 0.28 \\ \hline PN & ResNet12 & 55.39 \(\pm\) 0.29 & 75.27 \(\pm\) 0.2 & 76.41 \(\pm\) 0.49 & 89.40 \(\pm\) 0.24 \\ \hline MDMM-RN & ResNet12 & 54.93 \(\pm\) 0.30 & 73.58 \(\pm\) 0.23 & 74.19 \(\pm\) 0.50 & 91.03 \(\pm\) 0.22 \\ \hline MDMM-PN & ResNet12 & 57.73 \(\pm\) 0.30 & 75.32 \(\pm\) 0.22 & 75.36 \(\pm\) 0.50 & 89.00 \(\pm\) 0.27 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The results of mutual distillation among individual networks using various similarity metrics are presented, reporting mean accuracies along with 95% confidence intervals for the MiniImageNet and CUB datasets in the context of both 5-way, 1-shot and 5-shot tasks. The second column provides information on the backbone used for the embedding function.
# Mapping a Guided Image Filter on the HARP Reconfigurable Architecture Using OpenCL
## 6 Experimental Results  
### Design Space Exploration  
Optimizing the OpenCL program for best performance is done in two phases. In the first phase the code and data structures are optimized for parallel and pipelined execution, as is shown in Section 5.2. In the second phase, pragmas are inserted to guide the synthesis for best performance. The goal is to achieve an initiation interval of one for each loop and avoid dependencies which enlarge the critical path. This is done by inserting #pragma unroll in a typical kernel layout shown in Listing 6. The results are shown in Table 3. The first run through the compiler with no pragmas reveals that all loops are executed serially except the last one which is enrolled completely as an automatic optimization by the compiler. The report indicates that there is a memory dependency in the shift register loop at line 6 due to a read and write at the same memory location, and a data dependency in Step 12 due to a summation calculation, creating loops with respectively II = 6 and II = 48. Unrolling the inner kernel loop is not beneficial due to data dependencies in the outer loop. Therefore, both kernel loops in lines 9 and 11 are fully unrolled to create deep pipelines. Now, the kernel loops are in-lined and the shift register loops have II = 1, but the report states that the shift register loops cannot be pipelined due to memory dependencies. After enrolling all shift register loops we obtain an initiation interval II = 1 for the whole shift operation and a drastic reduction of memory use from 94% to 41%. Furthermore, all loops are fused into one while loop (line 3) with an initiation interval of one. The resource usage of the different unroll optimizations with radius \(r=3\) are shown in Table 3. Now it is time to generate the bitstream and profile the resulting design.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Resource** & **No Pragmas** & **Inner Loops** & **Both Loops** & **Shift Registers** \\ \hline Logic & 61\% & 65\% & 93\% & 90\% \\ LUT & 27\% & 29\% & 40\% & 39\% \\ RAM & 46\% & 49\% & 94\% & 41\% \\ DSP & 20\% & 28\% & 87\% & 87\% \\ II & 48 & 48 & 1 & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Resource usage and maximum initiation interval (II) for various loop unroll pragmas in the code.  
```
1__kernelguided_filter(structimage*I,structguide*G){
2 count=0;
3 while(count++<image_width=image_height){
4<#pragmaunroll>
5 forsallshift_registers
6 reg[i]=reg[i-1];
7
8<#pragmaunroll>
9 fors(inti=0;i<2*RADIUS+1;i++){
10<#pragmaunroll>
11 for(intj=0;j<2*RADIUS+1;j++){
12 Steps1-3/Steps4-5
13}
14}
15}
```  
Listing 6: Places for pragmas in the kernel code.
# Detection of Transmission State of Multiple Wireless Sources: A Statistical Mechanics Approach
## 1 Introduction
By using well-known algorithms, such as the forward-backward algorithm, they can estimate the most likely sequence of hidden states, even when some observations are missing or incomplete. Drawbacks Compared to the Belief Propagation Algorithm  
Strong assumptions, since they assume that the system being modeled follows a Markov process with discrete states and that observations are conditionally independent given the hidden states. These assumptions may limit their applicability in scenarios where the underlying system does not conform to these assumptions. * Lack of scalability, since the computational complexity of HMMs increases exponentially with the number of hidden states and observations. This can make training and inference computationally intensive, particularly for large-scale problems with a large number of states or observations. * Lack of flexibility and generalization, since they are limited to specific assumptions about the system or the data. * Lack of distributed computations, since HMMs are typically formulated as centralized models, where the inference and learning processes are performed on a single machine or system. Variations and extensions of HMMs have been proposed to enable distributed computations in certain scenarios, but they raise the overall complexity of the detection process. The remainder of this paper is organized as follows. The system model is presented in Section 2, whereas Section 4 describes the connection to the statistical mechanics framework. Section 3 introduces the basic tools used in this paper, namely the belief propagation algorithm, which is then applied to detect the operational state of multiple primary sources. Section 5 introduces the replica symmetric solution for the particular model. In Section 6, the results obtained from numerical simulations are discussed. In Section 7, we introduce the idea of single-source detection through a myopic secondary user. We conclude this paper in Section 8 with a summary and plans for future work.
## 1 Introduction
Advanced characterization techniques, such as X-ray fluorescence (XRF), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and energy dispersive X-ray spectroscopy (EDS), were employed alongside adsorption isotherm studies to understand the mechanisms involved in this process. The results of this research will contribute to the development of more sustainable water treatment technologies, expanding the potential applications of bentonite in the remediation of pharmaceutical pollutants and reducing the ecological risks posed by contaminants like tetracycline and other pharmaceutical residues.
## 2 System Model
### Frequency-Selective Channel  
After pre-equalization, the signal passes the frequency-selective Rayleigh fading channel. Hereby, we assume the channel is constant during the symbol period, thus a block fading channel. The channel between the source node and the user's antenna is denoted as \(\mathbf{h}=[h_{1};\;h_{2};\ldots;h_{N_{t}}]\), where \(h_{n}\sim\mathcal{CN}\left(0,1\right)\)[25] and the channel white Gaussian noise is denoted as \(\mathbf{n}=[n_{1};\;n_{2};\ldots;h_{N_{t}}]\), where \(n_{n}\sim\mathcal{CN}\left(0,\sigma^{2}\right)\), \(\sigma^{2}\) is the noise power of \(n\)-th bin.
# Modeling Movement Stability of Machine-Tractor Units Based on Modular Type Tractor
## 4 Results and Discussion
In this case, an appropriate analysis is required using the mathematical model (1). In principle, the mathematical model (1) allows one to estimate the MTU movement stability based on only one energy module (i.e., without TM). To do this, in the system of Equation (1), it is necessary to remove (that is, equate to zero) all those forces, moments, and design parameters associated with the presence of a technological module. It should be noted that the traction capabilities of the KIY-14102 tractor, when ballasted with a weight of 500 kg, allow it to be independently aggregated with three cultivators of the KRN-4.2 type. But calculations show that, in this case, there may be a problem with such unit movement stability. This is especially problematic at low oscillation frequencies of the disturbing torque. As the analysis of the obtained AFC (Figure 9) shows, already at \(\omega\) = 1.5 s\({}^{-1}\), the amplification coefficient of the external disturbance by the unit based on KIY-14102 (without TM) is 3.0 \(\times\) 10\({}^{-5}\) rad/N-m. With the above-mentioned value of the turning moment \(\Delta P_{t}\) = 4200 N-m, this will cause such a unit to turn at an angle of 0.126 rad or 7.2\({}^{\circ}\). This means a complete loss of the unit's movement controllability in the horizontal plane. Figure 8: Difference in response delays of a dynamic system to disturbing influence. Figure 9: Frequency response of processing the disturbing influence of the unit without TM (—) and with it (- - -) when its vertical hinge is locked. At the same time, when the same disturbing influence is processed at the same frequency (1.5 s\({}^{-1}\)) by a unit based on a modular tractor (KIY-14102 + TM), the deviation of the unit heading angle will be only 1.1\({}^{\circ}\). The tractor driver can quickly correct such deviation of the MTU from the course. Moreover, there is no deterioration in the quality of the technological process.
## 1 Introduction
attempted to synthesize Bi\({}_{2}\)Te\({}_{3}\) by MW-assisted polyol method [24], where they obtained Bi\({}_{3}\)Te\({}_{4}\) instead of Bi\({}_{2}\)Te\({}_{3}\). The synthesis of Bi\({}_{2}\)Te\({}_{3}\) nanorods and nanoflakes in ethylene glycol by MW heating method has been reported [25] where the reaction duration ranged from 0.5 h to 6 h. [PERSON] et al. [14] synthesized hollow Bi\({}_{2}\)Te\({}_{3}\) nanospheres at 150 \({}^{\circ}\)C through the MW-assisted heating method. They also reported on hollow spheres, nanosaws, and sheets [26]. [PERSON] et al. presented a MW-assisted heating route for Bi\({}_{2}\)Te\({}_{3}\) nanosheets and nanotubes using ethylene glycol as the solvent with a synthesis duration from 0.5 to 1 h. They demonstrated that the morphology of the resultant structure was strongly dependent on the reaction conditions, forming only nanosheets at low temperature (180 \({}^{\circ}\)C), transforming to nanotubes at high temperature (195 \({}^{\circ}\)C) [26]. [PERSON] et al. reported on the MW-assisted synthesis of spherical Bi\({}_{2}\)Te\({}_{3}\) nanoparticles from a homogeneous solution of tartarate complex of Bi\({}^{3+}\) and Te\({}^{4+}\) in a reaction time of 10 min [27]. Despite the recent developments in the synthesis of thermoelectric Bi\({}_{2}\)Te\({}_{3}\) nanostructures using the MW-assisted heating, only one of the above listed works reported on transport properties of the fabricated materials [27], leaving a gap from the synthesis to application. This could be mainly due to the quantity of material synthesized per batch being rather limited, as can be assessed from the experimental details (concentrations and volumes of the precursors used; see Table S1 for overview of the literature on MW-assisted synthesis of Bi\({}_{2}\)Te\({}_{3}\)). It is also well-known that consolidation process, and the resultant microstructure, is critical for the final performance of the thermoelectric materials. Here, we present on the MW-assisted synthesis of Bi\({}_{2-x}\)Sb\({}_{x}\)Te\({}_{3}\) nanoparticles from a homogeneous solution of ethylene glycol and chloride salts of Bi and Sb, while Te is complexed with TOP/TBP, producing high purity thermoelectric nanopowders in a matter of minutes due to very effective volume heating. Besides yielding large quantity (>8 g) of the investigated materials per batch, the processing of these materials towards compacts is described, resulting in high ZT values of 1.04 for Bi\({}_{2}\)Te\({}_{3}\) and 1.37 for Sb\({}_{2}\)Te\({}_{3}\) as n- and p-type materials, respectively.
# 10 Gb/s Bidirectional Transmission with an Optimized SOA and a SOA-EAM Based ONU
## 4 Conclusions  
In this paper, we investigated an effective optimization of an SOA and an SOA-EAM in an NGPON2- ONU and analyzed their impacts on the system. The main characteristics of the SOA, namely the gain and NF, were obtained from the relationship between the bias current and the input power. The proper conditions of the SOA for phase and amplitude modulation were a bias current of 200 mA with an input power of \(-25\) dBm and \(-5\) dBm, respectively. We set up and analyzed the 10 Gb/s single-ONU and the multi-ONU bidirectional DWDM-PON based on an SOA-EAM. The results show that the sensitivities in 20 km US and DS transmissions reach \(-28.9\) dBm and \(-33.1\) dBm for the single-ONU and reach \(-28.2\) dBm and \(-32.6\) dBm for the multi-ONU at the BER of \(2.4\times 10^{-4}\) with V\({}_{\rm PP}\) = 2 V (Pi = \(-10\) dBm, I\({}_{\rm bias}\) = 80 mA), respectively. As evidenced by their measured performance, such integration devices as SOAs and SOA-EAMs have the potential for low-cost use in metro-area network applications of NGPON2s.  
Figure 4: The BER against the received power in 10 Gb/s bidirectional transmission: (**a**) single\(-\)ONU bidirectional transmission; (**b**) multi\(-\)ONU bidirectional transmission.  
**Author Contributions:** [PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments; [PERSON] supervised the project. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by [the Natural Science Foundation of Jiangsu Province] grant number [BK20170199, BK20180598], [the Fundamental Research Funds for the Central Universities] grant number [JUSRP11835], [Postgraduate Research & Practice Innovation Program of Jiangsu Province] grant number [SJC20_0762] And The APC was funded by [the Natural Science Foundation of Jiangsu Province] grant number [BK20170199].  
**Acknowledgments:** This work was supported in part by the Jiangsu Provincial Research Center of Light Industrial Optoelectronic Engineering and Technology.  
**Conflicts of Interest:** The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
## 2 Background to GPP, SPP and PPI Approaches
The importance of guidelines, toolkits and documents in promoting GPP and SPP practices has been highlighted by several studies [5; 30] and also applies to PPI. Furthermore, this can be especially important for small public authorities [5]. The lack of guidelines was tackled, at the EU level, by the Buying Green Handbook, published by the European Commission in several languages [31] and by the EU training toolkit on GPP [32]. The European Secretariat of ICLEI (Local Governments for Sustainability) has also published the Procura+ Manual [33; 34], which is a reference for procurers. The European Commission has launchedvery recently the \"eafip\" toolkit to provide support to policy makers in designing PPI strategies and to procurers and their legal departments in implementing such procurements [35]. A large variety of tools and guides is available in grey literature, namely through the Procurement Forum platform [36], which developed a compilation of existing tools and guides. A thorough analysis of such compilation provides an idea of the type of available tools. First, in what regards to format, the tools/guides provide the information in descriptive documents, not allowing to be filled, in an interactive mode (e.g., the Buying Green Handbook). Second, concerning the content, we have identified tools/guides which are very general, applying to all sectors and discussing a wide range of issues (e.g., the Buying Green Handbook, Buying for a better world UNEP); tools that address just one approach to public procurement--GPP and/or SPP, social procurement (e.g., BuyGreen and make a difference, +Sustainable City Council, Buy Fair); tools addressing specific territories, at national, region or local level; tools that are sector-specific, addressing, for instance, the purchase of vehicles, energy, timber, catering (e.g., Clean fleets guide, Guide of purchasing electric and hybrid vehicles); and, tools addressing specific technical issues--life-cycle costs (LCC), functional specifications (e.g., Climate information for green procurers, Functional specifications guide). Even though there is such a diversity of tools and guides, there is evidence of a considerable gap for tools focusing on: (a) the integration of GPP, SPP and PPI together, as part of an organizational evolution towards more complex forms of procurement; (b) the framework to address the different levels of GPP, SPP and PPI and their role in the socio-technical transitions.
## 4 Different Types of Publisher-Advertiser Contract in Digital Advertising
### Programmatic Media Buying
#### 4.2.1 Real-Time Bidding (RTB)  
In the RTB system, buying and selling the ad space occurs via an auction within the time-interval that it takes for a web page to load, which can be only a few milliseconds. All advertisers interested in the auctioned ad space will bid for an impression in an automated manner, and eventually, the highest paying bidder will win the auction and display their ad on the given web page. RTB is the most prevalent ad placement method in online digital advertising.  
In the RTB ecosystem, when bidding on an impression for a particular user, advertisers base their decisions/actions on the information about that user's previous browsing behavior. This requires as much information as possible to be gathered about that particular user through various mechanisms such as user tracking and cookie synchronizing. Figure 3 gives an example of how RTB works in combination with behavioral targeting. A user ([PERSON]) visits a website (CNN here), which provides an opportunity for the publisher (CNN) to send an ad offer/auction to the ad exchange (DoubleClick) via its SSP (OpenX). (Note here, the SSP sends the ad request to an ad exchange, not an ad network). Consequently, the ad exchange (DoubleClick) queries multiple DSPs for advertisers' bids. A DSP (in this case, StackAdapt) may contact a data exchange (Oracle BlueKai) for the third-party user data, which will help the DSP's customer/advertiser decide whether to participate in the auction or not. If the advertiser (in this case, Netflix) decides to bid, the bid is generated and submitted. The winning advertiser is first selected by the ad exchange, then the SSP, if the SSP sends the bid request through multiple ad exchanges and receives multiple bid offers. In Figure 3, we assumed Netflix was the highest bidder, so its ad finally got to be displayed to [PERSON] through CNN's website [14]. It is worth stressing that the key benefits of RTB include:  
1. RTB has a flexible per-impression buying process which allows brands to bid on single impressions and in real-time, as opposed to the in-advance buying of publishers' inventory and for a predetermined fixed price as is the case in the manual media buying.
2. Advertisers and publishers use a single consolidated dashboard on their DSP or SSP platforms to deal with multiple partners, which results in much more straightforward and easier-to-manage campaigns and facilitates a more effective gathering of impression-level data/statistics.
3. Effective gathering of impression-level data/statistics can generally lead to a more adaptable, and ultimately a more profitable, advertising strategy.
4. RTB gives publishers the ability to sell ad space that was previously unwanted or unsold by making the pricing of this space flexible (i.e., self-adjusting) [13].
# The Value of Simple Heuristics for Virtualized Network Function Placement
## 3 Placement Heuristics  
As discussed in the previous section, the main focus of the models proposed for embedding VNFs into a physical network is on designing a heuristic that can achieve near-optimal results. However, the main reason for avoiding optimization models is their complexity and high execution time. Here we aim at exploring how much complexity is required and what benefit we can achieve with simple heuristics, studying a sequence of four, increasingly complex, heuristics. Each heuristic is designed to show the effect of the added parameter on the number of accepted requests, the average cost of the resources consumed by a SG, and the execution time of the algorithm. We start from the simplest heuristic and in each heuristic consider an additional parameter in the NFs' placement.  
In all heuristics, it is assumed that requests arrive one at a time and are placed separately. Each request has a duration, once an accepted request expires, it will be removed from the network and the associated used resources will be released. Each SG request has a specific source and destination, nodal resource demand for each NF, and a BW demand for all virtual links. The physical network consists of nodes with a given amount of nodal resource and links with a specific available BW. We only consider a single nodal resource and its consumption. The nodal resource could represent memory, storage, or CPU resources of a physical node. The model is designed for a wireless multi-hop network and considers the effect of interference in BW consumption. To include the effect of interference in the BW consumption we use an interference model widely used in the literature called the protocol model [14].  
The protocol interference model defines an interference set for each link in the physical network. The interference set for each link consists of all the links \(E_{u,v}\) that are connected to the nodes in the transmission range \(R\) of the sender or receiver. \(d_{u^{\prime}u}\) represents the distance between node \(u\) and \(u^{\prime}\). \(intset_{E_{uu}}\) captures that transmission on the link between node \(u\) and \(v\) will reduce the available BW of all the links whose transmitter is within the transmission range of the sender \(u\) or the receiver \(v\).  
\[\forall E_{uv}\in L_{p}:intset_{E_{uv}}=\{E_{u^{\prime}v^{\prime}}d_{u^{\prime }u}\lor d_{v^{\prime}v}\lor d_{v^{\prime}u}\lor d_{u^{\prime}v}\leq R\} \tag{1}\]