esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Conclusions  
In this paper, we propose a visual network that distinguishes small moving objects in dynamic, complex environments by utilizing the temporal feature differences in contrast between the target and background false positives. The visual neural network consists of two channels: one for motion information detection and another for extracting local contrast information. The network extracts target position information and motion trajectories through the motion information detection channel, and obtains the contrast information of motion features through the contrast information extraction channel. Subsequently, the network uses the target motion trajectory to determine the contrast trajectory and calculates the contrast variance. Finally, by utilizing the contrast feature fluctuations between the target and background false positives and applying a threshold, false positives are suppressed, enabling the detection of small target motion. To assess the effectiveness of our approach, we conducted a series of experiments on both synthetic and real-world datasets. The empirical results clearly indicate that our visual network significantly outperforms existing methods in terms of suppressing false alarms and improving detection accuracy. Contrast information proves highly effective in small target detection when there is a marked disparity between the target and the background. Nonetheless, the model's detection capabilities are significantly undermined when the target and background have similar brightness levels. Therefore, in the future, it may be worthwhile to consider integrating other visual information, such as entropy, to address the issue of difficulty in detecting small targets when their brightness aligns with that of the background.  
Methodology, J.L.; validation, J.L.; investigation, H.M.; data curation, J.L. and H.M.; writing--original draft preparation, J.L.; writing--review and editing, J.L., H.M. and D.G.; visualization, J.L.; supervision, H.M. and D.G.; project administration, H.M. and D.G. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
Author [PERSON] was employed by the company Mltor Numerical Control Technology Limited Company. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
# Internet of Things Applications as Energy Internet in Smart Grids and Smart Environments
## 3 IoT Applications in Smart Cities
[PERSON] and [PERSON] suggested a layer structure model for the smart city concept in [40], where this model is called a smart city infrastructure (SCI) and is established based on four major layers. The first layer defined is based on IoT to fulfill several processes, such as context management, computational procedures, and ICT infrastructures. The second layer includes a smart home system, which combines smart devices with user interfaces by means of a server. The third layer is characterized as the Cloud of Things (CoT), which integrates smart home and smart city services placed in the final layer of the SCI. The last layer comprises further service structures, resource management infrastructure, and integration with communication systems [40]. This system is described as the cyber-physical system (CPS) enabling IoT (IoT-CPS) in [41], in which authors have taken into account several application scenarios for air traffics, traffic control systems, and environmental monitoring and control systems. It is important to specify that a well-designed CPS system can remarkably improve both the energy efficiency and safety of the smart city concept and the comfort of smart homes. Energy-based smart city applications are considered in [42], which authors analyzed energy-related applications of smart cities depending on several parameters, such as energy generation, storage, infrastructure, facilities, and transport (mobility). An energy management and test system for analyzing novel control policies in the smart city concept is presented in [43], in which the combination case of heterogeneous data sources are also considered. The recommended middleware in this study ensures interoperability of heterogeneous systems containing building information models (BIMs), GISs, and system information models (SIMs). On the other hand, when practical applications of the smart city concept are analyzed, it is shown that various urban IoT applications are developed in several locations. A set of IoT applications related to lighting, mobility, and public applications are launched in Amsterdam, The Netherlands to enhance living and working quality. New concepts and innovations based on network-enabled LED lightning have been proposed by Philips and Cisco for smart city applications [44]. Another smart city application is the City 24/7 smart screen project, which is being developed in New York, USA to present an information platform. In this project, smart screens that can be connected over Wi-Fi systems are utilized to broadcast associating audio, voice, and touch screen technologies. In addition, another application of smart cities is realized in Nice, France. In this application, four major services are considered that are related to smart transportation, smart lighting, smart waste management, and smart environmental monitoring [44].
## 3 Experiments
### The Effect of Two-Stage KD  
A two-stage KD process is employed to further reduce the complexity of the network. An intermediate model with six layers of lightweight RIMformer blocks is trained first, which serves as a bridge between the large teacher model and the final student model. The assistant teacher model is then used to train a smaller, more efficient student model with two layers of lightweight RIMformer blocks. The effectiveness of two-stage KD is analyzed by comparing direct training, one-stage KD, and two-stage KD. In direct training, the student model is trained directly on the dataset. While in one-stage KD, the student model is trained using the teacher model, and the loss weight \(\alpha\) is set to 0.5 in the intermediate process of dynamic distillation.  
Figure 8 shows the results for the models with different training methods, including the PSINR and SINR. The performance of the model using one-stage KD is inferior to that of the directly trained model. This is because the significant differences between the teacher and student models hinder the effective transfer of knowledge from the former to the latter during the training phase. Two-stage distillation results in a smaller student model with an improvement in both the PSINR and SINR compared to direct training and one-stage KD.  
As depicted in Figure 9, all three models effectively reduce most of the interference. However, residual spurious peaks persist in the RD maps of both the directly trained model and the model trained using one-stage KD. The latter exhibits more pronounced noise. In contrast, the model trained with two-stage distillation reproduces the RD image of a signal without interference accurately. The two-stage KD significantly reduces the model size and inference time while maintaining a high SNR. In addition, the performances of the models trained by the three different ways are investigated at different SNRs, as shown in Figure 10. The model derived from two-stage distillation achieves better PSINR across various SNRs and demonstrates superior performance.  
Figure 8: Comparison of results from different training methods.
## 3 Results and Discussion
### Effect of Pin Fin  
3.4.1. Effect of Pin Fin Height  
6 kinds of pin fin heights including 0 mm, 3 mm, 6 mm, 12 mm, 18 mm and 24 mm are investigated in this part. The average Nusselt number of the lower surface under various pin fin heights at \(Re\) = 2 \(\times\) 10\({}^{3}\)-6 \(\times\) 10\({}^{4}\) is shown in Figure 14. Due to the limitation of impingement cavity thickness, the pin fin height only includes 0 mm\(\sim\)24 mm. The higher the pin fin height, the smaller the average Nusselt number of the lower surface generally. Among the five kinds of pin fin heights investigated, the impingement cooling effect of 3 mm is the best. Compared with the pin fin height of 24 mm, the average Nusselt number of the lower surface with that of 3 mm is increased by 11.2%.  
As the pin fin height increases, the air flow space decreases, and the probability of mutual collision and loss increases. Moreover, the increase in the pin fin height will cause the air flow to roll over and climb, which will reduce the cooling effect on the surfaces of the impingement cavity.  
Figure 14: Comparison of the average Nusselt number of the lower surface under various pin fin heights.  
Figure 13: Comparison of the frictional factor under various impingement hole numbers.  
Figure 15 is _Nu_ distribution of the lower surface at _Re_ = 2 \(\times\) 10\({}^{4}\) under different pin fin heights. It can be found that when the pin fin height is 3 mm, the area of high _Nu_ area is the largest, and the distribution is more uniform than that without pin fins. The pin fins can improve the heat transfer area where the _Nu_ is too small, which is beneficial to avoid ablation. At this time, the maximum _Nu_ on the lower surface reaches 62.74, which is greater than that of other pin fin heights.  
It is found that there is little difference between the average Nusselt number of the lower surface without pin fins and that with pin fin height of 3 mm by the above research. The pressure drop also needs to be considered when selecting the appropriate pin fin height.  
Figure 16 is a comparison of frictional resistance under various pin fin heights. The pin fin height gets lower, the flow resistance increases and the pressure drop increases. The pin fins can buffer the reduction in the velocity of impingement air flow, so the pressure drop for the impingement cavity with pin fins is smaller than that without pin fins.  
The flow resistance of the impingement cavity with the pin fin height of 3 mm is 40.1% higher than that with the pin fin height of 24 mm. That of 3 mm is 6.6% lower than that without pin fins. Considering the heat transfer and pressure drop, the pin fin height can be selected as 3 mm.  
Figure 16: Comparison of the frictional factor under various pin fin heights.  
Figure 15: _Nu_ distribution of the lower surface under different pin fin heights at _Re_ = 2 \(\times\) 10\({}^{4}\).
## 2 Materials and Methods
### Microemulsion Phase Behaviors  
The microemulsion phase behavior of SDHS was discussed thoroughly in our previous study [51]. In this part of the current work, we investigated the microemulsion formation of AAE(6 EO4 PO) and the SDHS-AAE(6 EO4 PO) mixed system. For AAE(6 EO4 PO), the concentration was fixed at 1% wt/v with various model oils (i.e., n-heptane, n-decane, and n-hexadecane) and temperatures (i.e., 25, 30, 35 and 40 \({}^{\circ}\)C). The 2.5-mL surfactant solutions were prepared by varying the salinity in flattened tubes with Teflon screw caps. After being well mixed, an equal volume of oil was added to each tube. The samples were shaken each day for the first three days and were kept in an oven to maintain the required temperatures. They were then left in order to reach equilibrium and observed for the Winsor Type by visual observation. For the mixed system, the total concentration of the surfactant was fixed at 2% wt/v because the preliminary data showed that this concentration of SDHS could first form the middle phase (Winsor Type III). The anionic-nonionic ratio was varied from the anionic side to achieve the following by weight ratios: 10:0, 9:1, 8:2, 7:3, 6:4, and 5:5. Additionally, the 2.5-mL samples were prepared with different salinities. After that, they were mixed with 2.5 mL of oil (i.e., n-pentane, n-heptane, n-octane, n-decane, and diesel oil). All the samples were shaken once a day for three days and left to achieve equilibrium in the same way as in the phase behavior study of AAE(6 EO4 PO). However, the mixed system was controlled at a temperature of 25 \(\pm\) 2 \({}^{\circ}\)C.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Surfactant Name** & **Formula** & **MW (g/mol)** & **L (Å)** & **CMC (\%wt/v)** & **HLB** \\ \hline Sodium dihexyl sulfosuccinate (SDHS) & C16\({}_{\text{H}}\)29 NaO\(\gamma\)S & 388 1 & 10 3 & 0.25 & - \\ \hline Alcohol, C16-18, 6-ethoxylated & & & & & \\
4-propylated Alkyl polyglycol ether (AAE(6 EO4 PO)) & C17\({}_{\text{H}}\)35(PO)4(EO)6 OH & 784 2 & 35.7 4 & 0.08 & 10 2 \\ \hline \hline \end{tabular}  
* obtained from Acosta and Bhakta, 2009 [42]. 2 obtained from Sasol Performance Chemicals, 2019 [54]. 3 obtained from [PERSON] et al., 2008 [41]. 4 calculated from L\({}_{\text{nonionic}}\) = 1.4 \(\times\) linear carbon tail \(\times\) 1.5 Å [55].  
\end{table}
Table 1: Properties of surfactants.
## 2 Current Technology
### Enabling Technologies and eHealth  
Thanks to advancements in cross-sectoral technology, remote prevention, diagnosis, therapy services [16], consultancy [17], follow-up services [18], remote monitoring, and rehabilitation connected to telemedicine have become more efficient since 1906 [15]. Additionally, the increasingly \"open\" network, while being controlled for data security, has made it possible to integrate patient-owned technologies with eHealth models used globally. This information can be found in telemedicine application trends such as \"mobile health\" or mHealth [19], which encompasses mobile devices, such as smartphones, ded  
Figure 1: Product–service system framework: processes and market/organizational strategies.  
Figure 2: User-centered design philosophy: strategic key points and related technologies.  
icated apps, and smart wearables in the healthcare model, or \"social health\" [20], which involves the use of tablets as a dispensing technology for \"serious games\" [21] intended for patients suffering from neurodegenerative diseases [22]. The new frontiers of advanced technological industry (i.e., Industry 5.0) offer numerous opportunities for improving telemedicine systems. Key enabling technologies [23], sets of tools/resources capable of communicating between systems and the network, are among the most important elements to consider while planning the future of telemedicine systems. These include edge computing [24], which involves data computation on local devices rather than on servers; artificial intelligence or AI, a series of algorithms with human-like capabilities, such as learning; cobots, collaborative robots that fall within the sphere of additive manufacturing; 6G, the sixth generation of mobile communication technologies; digital twins, a digital copy of a real \"asset\" that reports any changes, following the lifecycle of the original or vice versa; blockchain, a type of programming based on nodes that favors transparency and data security; the Internet of Everything (IoE), a natural evolution of the philosophy linked to the IoT, which aims to interconnect what is not yet digitizable or integrated today into a digital system; and big data analysis, which can analyze vast amounts of data in a short time [25].
## 3 Effect of Surface Chemistry on Sensitivity and Selectivity
In their study, different PAHs--2-hydroxy-1-naphthaldehyde (2H-1N), 9,10-phenanthraquinone (PQ), 9-anthracenecarboxaldehyde(9-AC) and quinolone (Q)--showed different quenching effects, and this has been attributed to the molecular structure or functional groups of the PAHs [66]. The interaction of the surface-modified QDs, PAHs and NACs is schematically illustrated in Schemes 1 and 2. Surface modification is also believed to improve the lifetime of a sensor. [PERSON] et al. (2016) explored the effect of lifetime on the sensing of organic pollutants such as bisphenol A, 1-naphth, phenol and picric acid (Figure 5) [67]. Apart from the functionalization and conjugation, reaction parameters were said to cause an effect on the sensing of the pollutants. [PERSON] et al. (2016) investigated the effect of pH in the reaction between AgInZnS and Cu ion [68]. Furthermore, the sensitivity of the sensors is also dependent on the types of functional groups of the sensors in addition to the functionalization approaches [69,70]. Different results on sensitivity of different sensors towards PAHs and NACs are shown in Table 1. Apart from surface functional groups, the sensitivity of fluorescent probes has been shown to be dependent on the type of synthetic method. Recently, [PERSON] et al. prepared GQDs using GO and citric acid via the \"top-down\" approach and \"bottom-up\" approach, respectively. The as-prepared materials successfully detected pyrene in an aqueous medium. The GQDs prepared via the \"bottom-up\" route gave a better limit of detection (LOD) as compared to the result obtained by the GQDs synthesized through the \"top-down\" route. Furthermore, the two types of GQDs exhibited different optical properties, and this can be observed from their emission spectra (Figure 5) [58]. QD-based sensors can also be modified through doping with a metal or non-metal. Surface doping with a metal has been reported to enhance the electrochemical properties of QD sensors; however, there have been few reports on the doping of fluorescent probes and electrochemical sensors [56; 58; 71; 72]. Figure 5: The effect of excitation wavelength on the emission spectra of (**A**) GO-GQDs and (**C**) CA-GQDs. (**B**,**D**) the effect of excitation wavelength on the maximum PL intensity (PLmax) in each case.
## 4 Conclusions  
This work constructed a new type of micro-impinging stream reactor (MISR), and explored the syntheses of NiS, Co\({}_{3}\)S\({}_{4}\), NiCo\({}_{2}\)S\({}_{4}\), and NiCo\({}_{2}\)S\({}_{4}\)/rGO composites by the co-precipitation process using this equipment and their applications in hybrid supercapacitor electrode materials. As compared to NiS and Co\({}_{3}\)S\({}_{4}\), the NiCo\({}_{2}\)S\({}_{4}\) composites were found to possess several advantages such as smaller particle size, more uniform mesoporous structure, larger specific surface area and, in turn, more superior electrochemical performance. In addition, NiCo\({}_{2}\)S\({}_{4}\) could be quickly anchored on the surface of rGO through MISR to enhance its performance. The NiCo\({}_{2}\)S\({}_{4}\)/rGO composites had the highest specific capacity  
Figure 11: (**a**) Leakage current and (**b**) self-discharge of supercapacitor device.  
Figure 10: (**a**) Scheme of the hybrid supercapacitor (NiCo\({}_{2}\)S\({}_{4}\)/rGO//activated carbon); (**b**) CV measurements of NiCo\({}_{2}\)S\({}_{4}\)/rGO and activated carbon electrodes at a scan rate of 5 mV s\({}^{-1}\) in a three-electrode system; (**c**) CV curves of NiCo\({}_{2}\)S\({}_{4}\)/rGO//activated carbon HSC device at different scan rates; (**d**) initial GCD curves of NiCo\({}_{2}\)S\({}_{4}\)/rGO//activated carbon HSC device at different current densities; (**e**) the cycle stability and coulombic efficiency of NiCo\({}_{2}\)S\({}_{4}\)/rGO//activated carbon HSC device at a current density of 1 A g\({}^{-1}\); (**f**) IR drop of HSC device under different current densities.  
of 198.0 F g\({}^{-1}\) and the capacity retention after 1000 electrochemical cycles was 83.6% under a current density of 1 A g\({}^{-1}\). Changing the current density to 20 A g\({}^{-1}\), the specific capacity of NiCo\({}_{2}\)S\({}_{4}\)/rGO could reach 161.1 mAh g\({}^{-1}\), and the retention rate was 81.4%, suggesting an outstanding rate capability. Furthermore, the NiCo\({}_{2}\)S\({}_{4}\)/rGO//AC asymmetric supercapacitor exhibited a fine cycling performance with 83.8% of the maximum capacitance retention after 1000 electrochemical cycles at a current density of 1 A g\({}^{-1}\). This work shows that the MISR method may have great prospects in preparing high-performance ultrafine composites.  
Conceptualization, J.Z. and L.W.; methodology, J.Z. and L.W.; investigation, J.Z., X.C. and C.L.; resources, L.W. and X.C.; data curation, J.Z.; writing--original draft preparation, J.Z. and X.C.; writing--review and editing, J.Z. and L.W.; supervision, L.W.; funding acquisition, L.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Major Project of National Science and Technology from China (No. 2018 ZX09721002-002), the National Key R&D Program of China (No. 2017 YFB0307202), and the National Natural Science Foundation of China (Nos. 21576012).  
Not applicable.  
The authors declare no conflict of interest.
# Game theory-based Routing for Wireless Sensor Networks: A Comparative Survey
## 2 Preliminaries
### Games in Routing for WMSNs
The goal is to use evolutionary game theory to increase the network lifetime through the interaction of the sensor nodes. A node which is CH will have to send data to the sink node, which is a costly operation in terms of energy expenditure. Conversely, nodes in the cluster which will not become CH will have to send data to the CH. This is an operation with a low cost in terms of energy. We assume that it is an inherent nature of the nodes to remain selfish and avoid becoming the CH, to save their energy for surviving in the network. If none of the nodes becomes the CH, the cluster will fall, and every single node will have to send data to the sink node in a single hop manner, which will deplete energy very fast. Under these circumstances, to survive in the network, all the nodes will have to choose their strategies to play their role as a CH or as a cluster member (CM) in such a way that both kinds can survive in the network longer, while interacting in the cluster. If the game is designed well, it will eventually lead to an evolutionarily stable strategy and the network lifetime will increase. Routing protocols based on the evolutionary game theory are elaborately discussed in Section 3. Further mathematical formulations can be observed in that section regarding evolutionary game theory. Reputation is one of the most practical tools for measuring the partners' quality and incentivizing the partners' behaviors [52]. To the best of our knowledge, only one routing protocol so far has used reputation-based games. In fact, the approach is cooperative but depends highly on the reputations of the nodes. This leads us to classify it as a separate type of game, applied for the design of routing protocols for WSNs. The above-mentioned four kinds of games used in various routing protocols for WSNs are comparatively summarized in Table 3.