esa-sceva/satcom-chunk-collection huggingface dataset:
# Object-Oriented Remote Sensing Image Change Detection Based on Color Co-Occurrence Matrix
## 3 Experimental Results and Discussion  
### Study Area and Experimental Data  
Shenzhen is located in the southern part of Guangdong Province, between 113\({}^{\circ}\)43\({}^{\prime}\) to 114\({}^{\circ}\)38\({}^{\prime}\) east longitude and 22\({}^{\circ}\)24\({}^{\prime}\) to 22\({}^{\circ}\)52\({}^{\prime}\) north latitude, adjacent to Hong Kong, as shown in Figure 4a. It belongs to the subtropical monsoon climate, and the annual rainfall is 1933.3 mm. Shenzhen is the national economic center, scientific and technological innovation center, regional financial center, and trade and logistics center. Dapeng is located in the southeast of Shenzhen, and it is an important node in the Guangdong Hong Kong Macao Greater Bay Area (GBA). In the past 40 years of urbanization, Shenzhen has made remarkable achievements in economic and social aspects. The urbanization rate of Shenzhen has reached 100%; the land possesses high spatial heterogeneity and changes frequently. At the same time, the relevant departments attach great importance to the ecological environment construction in Shenzhen. The forest protection and bareland management have gradually developed into the center of urban supervision. In view of this, we take Shenzhen and Dapeng as the research areas and the forest-bareland change as an example to verify the effectiveness of the proposed algorithm. The locations of the research areas are shown in Figure 4.  
Figure 3: Flow chart of CBSS.  
Considering that Shenzhen is often cloudy and rainy and the land is fragmented, the Sentinel-2 images of Shenzhen with 10 m resolution in January of winter 2020 and 2021 are selected as the Experimental Data 1. In order to ensure the full coverage of the image, the target image is synthesized by finding the useful image set under a three-month time window centered on January, with a cloud content less than 5%, as shown in Figure 5a1,b1. In order to ensure the consistency of spatial resolution of the data, the R, G, B, and NIR bands are selected in this experiment. In addition, to verify the effectiveness of the proposed method on other datasets of different resolutions, the Skysat images of Dapeng with 1 m resolution and R, G, and B bands during October 2021 and May 2022 are purchased as the Experimental Data 2, as shown in Figure 5a2,b2.
## 6 Key Issues and Challenges
### Energy Efficiency  
The solar PV monitoring system consists of multiple nodes of transmitters. The energy efficiency issues are related to the lifetime of the node battery [138]. Any failure of the node battery results in the low life of the network, thus disturbing real-time communication. This hampers the extraction of data from different nodes which could affect the performance of the whole system. Hence, it is essential to develop an energy-efficient communication protocol [139]. Moreover, the utilization of multiple paths allows better energy efficiency for real-time communication in the monitoring system.
## 3 Experiments  
To obtain the initial data, an experimental site was constructed, consisting of ten CFA piles with defects, which corresponded to types of defects such as soil inclusions and washout of the concrete mixture in the pile body [55].  
The piles were constructed using CFA (continuous flight auger) technology, namely by rotation of a 450 mm diameter hollow auger to a depth of 3 m. After this, the concrete mixture was pumped into and filled the drilled borehole. The defects were made of polystyrene with the following dimensions: (1) \(\mathcal{O}\)250 mm, 100 mm thick; (2) \(100\times 150\times 300\) mm; (3) \(100\times 150\times 150\) mm. Such defect sizes were chosen to test the resolution of the low strain integrity testing and its ability to localize and recognize small defects. Defects in expanded polystyrene correspond to such defects as soil inclusions and washing out of concrete from the pile shaft. Taking into account the production experience with piles, such defects are the most common in weak and water-saturated soils. The defects were fixed in the middle of the reinforcement cage with a tying wire and lowered in a borehole filled with concrete mixture. Three piles were constructed for each type of defect, including one flawless pile (Figure 1).  
The test was performed 7 days after casting. The pile tops were cleaned and smoothly grinded. The test was carried out with the Interpribor Spectr-4 equipment set, which includes a tablet computer, a special hammer, and an accelerometer sensor. At least five impacts were applied to each pile top at several locations, with a rubber hammer weighing approximately 0.5 kg. The accelerometer was attached to the top of the pile with a special putty for better acoustic contact. A low strain integrity testing diagram is shown in Figure 2.  
This paper is the first in the search for an algorithm for the automatic interpretation of pile integrity test results obtained by low strain integrity testing. Therefore, experiments were carried out to test the validity of the proposed hypothesis. Only the shape and position of the artificially created pile defect was a variable parameter. The length, diameter, and casting method of the pile were constant. It is exactly these experimental conditions that the authors believe will answer the following question: can an ANN classifier be used to recognize defects and develop an initial methodology for applying the classifier when interpreting the results?
# Matching Quality Detection System of Synchronizer Ring and Cone
## 4 Detection System of Matching Quality between Synchronizer ring and Cone
### Detection Result and Qualification Criteria  
A workpiece is chosen as the example for the experiments, but the detection process for other models is the same. One-hundred sets of the synchronizer ring and cone matching components of the workpiece are selected to be detected, of which 80 sets are qualified and 20 sets are unqualified. This type of synchronizer cone is shown in Figure 12. They are mounted on the detection platform one by one. A fixed force of 120 N is applied, and the synchronous ring and the synchronizer cone are kept at a relative rotational speed of 20 r/min, at which time their friction torque and backup gap were measured.  
The measured average torque and backup gap of the 100 sets of workpieces are shown in (a) and (b) in Figure 13, respectively. In the figure, the first 80 sets are qualified, and the last 20 sets are unqualified.  
On the basis of a large amount of samples, the RSS variance analysis method of interval estimation is used to determine the qualified range of the main index, average torque, which is 7.50-13.00 N\(\cdot\)m,  
Figure 11: Partial operation results of the system program.  
Figure 10: Synchronizer detection host.  
and the optimum value is about 10.00 N-m. The qualified range of the backup gap is the specified 1.50-1.75 mm. A distribution map of sample points can be obtained by taking two indicators, as the coordinate axes show in Figure 14.  
Figure 14: Distribution map of sample points.  
Figure 12: The workpiece of synchronizer cone.  
Figure 13: Measured results of the 100 sets of workpieces. (**a**) average torque; (**b**) backup gap.  
Low friction torque indicates poor matching quality, and a low backup gap indicates a high degree of wear. It can be seen from the figure that a workpiece will be judged to be qualified only when both two indicators are within the range of values. The method proposed in this paper has an accurate detection effect.  
Next, for comparison, a synchronizer ring and cone matching component of the same type are detected using the traditional color lead powder detection method, with an average torque of 9.792192 and backup gap of 1.576577. The color lead powder detection method can be divided into two steps: Smearing color lead powder and rotating and matching, as shown in Figure 15. Then, by manual observation, the workpiece is determined as a qualified piece. However, this method can only provide qualitative results and is not that accurate.
## 3 Results
### Test of MLA Trained with Each Range of \(f^{\prime}_{c,meas}\) (Case-3)  
Because it is speculated that a wide range of \(f^{\prime}_{c,meas}\) databases affected the MLA, the MLA case for each \(f^{\prime}_{c,meas}\) range was generated (total of six subcases), and the operation and verification were conducted independently for each case (Case-3). Table 4 presents the evaluation indices obtained using the evaluation method proposed in Section 3.1, and Figure 6 presents the relationship between \(\gamma\) and \(f^{\prime}_{c,meas}\) in each subcase. The \(m\) of all the ranges was 0.99-1.04, and the \(\sigma\) appeared to be 0.08-0.14. The average values of CV, RMSE, MAE, and MAPE of subcases were found to be 0.11, 4.56 MPa, 3.73 MPa, and 8.42%, respectively, which were superior to those for Case-1. The maximum range of \(\gamma\) values included in the 90% confidence interval was 0.76-1.24 in Case-3-2 (20-30 MPa), and the minimum range was 0.87-1.13 in Case-3-6 (80-100 MPa). This suggests that if the MLA is learned after using a training dataset divided by strength ranges, the predicted values with a maximum error rate of 24% and a minimum error rate of 13% will be included in >90% of all the result values. Therefore, if the MLA is trained using a training dataset with specific \(f^{\prime}_{c,meas}\) ranges related to the desired result, the prediction accuracy and reliability can be enhanced.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Subcases According to Range of \(f^{\prime}_{c,meas}\)**} \\ \hline  & **Case-3-1** & **Case-3-2** & **Case-3-3** & **Case-3-4** & **Case-3-5** & **Case-3-6** & **Average** \\ \hline  & **7-20 MPa** & **20–30 MPa** & **30–40 MPa** & **40–60 MPa** & **60–80 MPa** & **80–100 MPa** & \\ \hline Training & \multirow{2}{*}{\(189\)} & \multirow{2}{*}{\(675\)} & \multirow{2}{*}{\(680\)} & \multirow{2}{*}{\(842\)} & \multirow{2}{*}{\(420\)} & \multirow{2}{*}{\(185\)} \\ dataset & & & & & & & \\ \hline Testing & \multirow{2}{*}{\(86\)} & \multirow{2}{*}{\(297\)} & \multirow{2}{*}{\(282\)} & \multirow{2}{*}{\(348\)} & \multirow{2}{*}{\(183\)} & \multirow{2}{*}{\(92\)} \\ dataset & & & & & & & \\ \hline Mean (\(m\)) & 1.04 & 1.03 & 1.01 & 0.99 & 1.01 & 1.01 & 1.02 \\ \hline \(\sigma\) & 0.12 & 0.14 & 0.11 & 0.11 & 0.09 & 0.08 & 0.11 \\ \hline CV & 0.11 & 0.14 & 0.11 & 0.11 & 0.086 & 0.080 & 0.11 \\ \hline RMSE (MPa) & 2.00 & 3.36 & 3.39 & 5.41 & 5.96 & 7.24 & 4.56 \\ \hline MAE (MPa) & 1.49 & 2.78 & 2.56 & 4.55 & 5.01 & 5.99 & 3.73 \\ \hline MAPE (\%) & 9.03 & 10.96 & 7.28 & 9.42 & 7.21 & 6.63 & 8.42 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Analysis accuracy of ML trained with data in each range.  
Figure 5: Relationship between \(\gamma\) obtained from Case-2 and \(f^{\prime}_{c,meas}\).
# Progress in the Development of Electrodeposited Catalysts for Direct Liquid Fuel Cell Applications
## 7 Conclusions  
The present review summarised the developments in the electrodeposition of Pt and Pd-based catalysts on carbon supports, non-carbon supports with conventional supporting electrolytes, ILs, and DESs as the potential supporting electrolytes. Electrodeposited Pt and Pd-based catalysts supported on various supports have shown to be very effective atimproving the performance of electrochemical reactions in DLFCs, with Pt-based (Pt-Ru for methanol; Pt-Sn for ethanol) being predominant for direct alcohol-based fuel cells and Pd-based for direct formic acid fuel cells. Remarkable progress has been observed in producing shape-controlled Pt, Pd-based catalysts via template free approach including programmed electrodeposition approach, utilizing IL and DES as the potential supporting electrolyte. While IL serves multiple functions in the electroreduction system, its ionic interactions and contributions to electrolyte stability require further investigation. The works cited demonstrate the scientific community's substantial efforts to develop efficient Pt and Pd-based electrodeposits on Ti, anodized Ti/TNTs, Ti meshes, stainless steel mesh, gold plated steel mesh, and perform real-time evaluations utilizing different liquid fuels.  
With a better understanding of the advancements in the electrochemical deposition of Pt and Pd-based catalysts, electrodepositing metal catalysts with different shapes, structures on metal support could be a potential way forward for their commercialization. Substantial improvements in the durability of MEAs integrated with electrodes comprised of electrodeposited catalysts are desired to achieve the long-term strategic goals of US DOE targets. While significant progress has been made in understanding the features of Pt and Pd-based electrodepositions in various aqueous media, investigations involving DES as the electrolyte deserve detailed research. This review has outlined the major challenges to focus on at this point, which is intended to potentially benefit the research community working in this field and aid in the scale-up and rapid industrialization of electrodeposited catalysts for fuel cell applications.  
Conceptualization, All; methodology, K.K.M. and R.T.; resources, R.C. and K.K.M.; writing--K.K.M. and R.T.; writing--review and editing, R.C., S.P. and K.K.M.; supervision, R.C. and S.P. All authors have read and agreed to the published version of the manuscript.  
This research has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 885793. A full fee waiver APC was granted for this article to be published in _Applied Sciences_.  
Not applicable.  
The data presented in this study are available upon request from the corresponding author.  
The authors declare no conflict of interest.
## 3 Development and Results
### Interface  
The interface that was created to implement the detection system is shown in Figure 10. The surveillance video is on the right side of the interface. When the system makes a detection, it locates the segment of the image where the firearm was detected, showing this segment on the left side of the interface in addition to an alert message that a firearm has been potentially detected.
# Microbially Induced Desaturation and Carbonate Precipitation through Denitrification: A Review
## 3 Advantages of Denitrification Metabolism in MICP  
Denitrification has been proposed as a promising alternative metabolic pathway for biomineralization applications in subsurface environments because it possesses several advantages over other microbial metabolisms when MICP process is considered [8]. Denitrifying bacteria are widespread in subterranean environments, and as such, MICP through denitrification can be achieved using the indigenous populations of denitrifying bacteria in the relevant application area [29]. Different from the oxygen dependent microbial metabolisms such as ureolysis and aerobic respiration, denitrification occurs in the presence of nitrate in oxygen-deficient subsurface environments. When specific strains are used, denitrification can even occur in the absence of micronutrients. [PERSON] et al. [30] revealed that significant CaCO3 can be precipitated in minimal nutrient conditions (only in the presence of macronutrients) by either _Diaphroobacter nitroreducens_ or _Pseudomonas aeruginosa_ culture. Moreover, compared to other microbial metabolic activities (except aerobic respiration), denitrification has a negative change in Gibbs free energy (\(-785\) kJ/mol acetate) under standard conditions and in fact it surpasses the free energy of ureolysis (\(-27\) kJ/mol acetate) and the other anaerobic metabolic pathways [6; 8]. Therefore, denitrification is thermodynamically more suitable than all the other metabolic pathways except aerobic respiration, and thus, in various MICP applications, it can be expected to dominate at greater depths where presence of oxygen is unlikely.  
Unlike aerobic respiration, MICP through denitrification does not rely on external alkalinity, as the process itself generates enough alkalinity to raise the pH to levels favoring calcium carbonate precipitation [24]. Furthermore, when complete nitrate reduction (denitrification) occurs, the side products of denitrification (i.e., N2 gas and possibly small amounts of unprecipitated CO2) are non-toxic and chemically inert, whereas the gases produced in other metabolic pathways such as, ammonia (from ureolysis), and hydrogen sulfide (from sulfate reduction), may pose risks for environment, structures and human health [11; 24]. In addition, denitrification yields a larger calcium carbonate precipitation per mole of electron donor (i.e., acetate) than other MICP pathways (Table 1). This greater production of carbonate promotes more precipitation of CaCO3 per mole of external substance. Overall, MICP through denitrification appears to be more sustainable for applications in situ.
# A New Bit Repair Fast Reroute Mechanism for Smart Sensors IoT Network Infrastructure
## 1 Introduction
The network topology shown in Figure 1 will be used for further explanation. The router that is detecting a link or neighboring router failure with the further activation of the FRR repair mechanism is defined as the source router (S). Consequently, router S becoming an active element of the FRR repair process (see Figure 1) referred to as the point of local repair (PLR). Router D denotes the destination router under discussion. Finally, the next-hop routers are specified by the routers N1, N2, N3, and others, which will compose the alternative path for FRR. The router not actively involved in the FRR repair process is designated the R router (here R1). The paper presents a new bit repair (B-REP) FRR mechanism (hereinafter B-REP). The B-REP FRR mechanism is a type of proactive FRR mechanism. Unlike other FRR solutions, B-REP uses a standardized BIER header-based solution to circumvent failures. Mainly we focused on the ability to efficiently mark the entire alternative precalculated backup path thanks to its bit-string field. In addition, compared to other existing solutions (such as LFA or R-LFA), the B-REP mechanism can provide full repair coverage and repair all possible network failures within the topology. The B-REP can be deployed in an IP network that uses a link-state protocol, such as for example OSPF or intermediate system to intermediate system (IS-IS). The B-REP is applicable to any network that operates the IP protocol stack and works with a link-state routing protocol. However, the deployment of the B-REP mechanism is more suitable for networks that are less dynamic, than usual WSN networks. B-REP works well for networks with static network nodes (some IoT deployments), or those networks behind the WSN BS towards the access/transport/ISP networks. In this environment, the B-REP mechanism provides the protection of important data flows generated from IoT/WSN devices-sensors and other devices. Our B-REP solution addresses the negative impacts of network failures and provides the solution that for the period of convergence guarantees correct packet delivery. The remainder of this paper is structured as follows: Section 2 contains a summary of the latest knowledge in the FRR field and provides an analysis of existing solutions and their problem areas are discussed. Section 3 proposes the new B-REP FRR mechanism. Section 4 focuses on the evaluation of the B-REP mechanism and compares its features with other FRR solutions. Section 5 presents the conclusions of our work and plans for future research.
# A Dyna-Q-Based Solution for UAV Networks Against Smart Jamming Attacks
## 2 Related Work
### SDN-Based UAV Network Control  
SDN architecture is essential to enhance the controllability of networks against attackers, since it can calculate an optimal forwarding path according to the approximately real-time network status. This architecture has had many successful applications in ground networks, and therefore many researchers have attempted to replicate this success in the UAV networks. [PERSON] et al. [1] designed a SDN-based network framework for UAV backbone networks. In this framework, an SDN controller is deployed in the ground control station. They showed that the deployment of an SDN can extend the UAV's battery life due to a load balance algorithm integrated in the SDN controller. [PERSON] et al. [2] proposed a SDN/NFV (Network Function Virtualization)-based lightweight modular network architecture which meets the high mobility requirement of a UAV swarm. Their main contribution is realizing the highly robust migration of many network services related to UAV networks, such as network monitoring, intrusion detection, and smooth migration of UAVs among different clusters, etc. [PERSON] et al. [3] developed a SDN architecture-based UAV networks with a single centralized SDN controller to solve the problem about how to replan the location of the relay UAVs, thus improving the QoS (Quality of Service) of a real-time video monitoring service. [PERSON] et al. [4] implemented SDN-based UAV-aided VANETs and investigated how to realize efficient data processing by offloading of computing tasksand sharing of state information. They modeled the tradeoff between computational delay and energy expenditure as a two-person sequential game problem. [PERSON] et al. [5] introduced a network framework called a temporospatial software-defined Network (TS-SDN), which can be applied in UAV networks. [PERSON] et al. [6] proposed a software-defined flight ubiquitous sensor network (FUSN) and a set of message interaction rules between a UAV and ground control station. They suggested that sensor modules and routing control modules should be deployed in different UAVs. [PERSON] et al. [7] conducted a study on how to adjust the location of SDN controller to reduce the communication overhead of the control messages. [PERSON] et al. [8] claimed that they exploited a SDN-based scheme to control routing. The goal of their work was to maximize throughput, balance traffic, and reduce network delay. [PERSON] et al. [9] defined a topology-discovering service for SDN-based hybrid VANETs. Their method fully considered flow load balancing of an SDN controller and calculation resources needed. [PERSON] et al. [10] studied the deployment of an SDN controller. They claimed that SDN controllers should be deployed in the central area of UAV networks to reduce hopping counts of control packets and reduce network delay.