esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
[27] suggested that the simulation capability of the SWAT model is slightly better than that of the HSPF model. Recently, the SWAT model has been linked with the EFDC model to simulate the upstream inflow and water quality in lakes or reservoirs [28; 29], and [29] pointed out that the SWAT-EFDC linkage model could be a useful tool for simulating water quality management scenarios and for applying the best management practices (BMPs) on a watershed scale. Therefore, this study evaluates the water quality improvement scenarios by linking the SWAT and EFDC models to consider the agricultural system and nonpoint source pollution of the upper watershed. The measures to resolve the water quality issues of estuarine reservoirs are mainly divided into watershed measures to reduce the external pollution load flowing into estuarine reservoirs and estuarine reservoir measures to reduce the internal occurrence load. There are two options for water quality management of watersheds: point source and nonpoint source pollution. A representative measure of point source pollution management is the quality management of discharged water from public sewage treatment works (PSTWs) for downstream reservoirs [30]. In the case of nonpoint source pollution related to estuaries or estuarine reservoirs, studies have mainly considered BMPs [31; 32; 33] and artificial wetlands [34; 35] to reduce the inflow of nonpoint source pollution from the upper watersheds. Water quality management measures within estuarine reservoirs include internal development, lake water management, seawater circulation, and dredging within estuarine reservoirs. Thus, this study simulates the measures for water quality improvement and assesses the results after considering low-quality soil improvement (internal factor) and inflow of the PSTW effluent (external factor). A list of acronyms and abbreviations used throughout this article in given Table 1.  
Ganwol Reservoir, the study area, suffers from point source water pollution from PSTWs located at the end of the upper watershed and nonpoint source pollution from the surrounding agricultural land. In addition, because the upstream and downstream of the estuarine reservoir are separated by levees, which have three small waterways, it is necessary to examine whether improving the water quality upstream can be spread throughout the reservoir. It is difficult to provide a simple interpretation of the effects resulting from water quality improvement techniques for estuarine reservoirs with sophisticated geographical features. Therefore, this study aims to analyze the annual average water quality concentrations and T-P reduction efficiency, and assess the water quality management of estuarine reservoirs using the SWAT-EFDC linkage model.
# Sensitivity Estimation for Differentially Private Query Processing
## 4 Sensitivity Estimation for Join Queries
### Sketch-Based Sensitivity Estimation  
Sketches are useful data stream summaries that are widely used for frequency estimation, heavy hitter finding, and join size estimation. In this section, we propose a sensitivity estimation method based on AGMS sketch.
# Energy Performance Forecasting of Residential Buildings Using Fuzzy Approaches
## 1 Introduction
Other studies used additional ML approaches, i.e., neural networks, support vector machines, evolutionary computation, etc., to deal with the same problem and working with the same data set [19; 20; 21]. The first goal of this paper, is to compare the performance of fuzzy approaches (FIR and ANFIS) with respect to 13 predictive modelling methodologies, from the prediction capability point of view. The study of the performance of fuzzy approaches is a novelty in respect of heating and cooling load prediction from building design characteristics, since none of the previous studies have worked with this kind of system. The second goal of this research is to study the feature selection capability of the FIR methodology to determine the relevance of each of the variables involved in the study from the prediction point of view. The reduced set of features selected by FIR are used as inputs to ANFIS models, showing that the level of prediction accuracy is not reduced but the computational time is decreased substantially. This is the first time that FIR is proposed as a feature selection pre-process for other modelling methodologies, as for example ANFIS. The structure of the paper is organized as follows: Section 2 introduces the FIR and ANFIS methodologies. In Section 3, FIR and ANFIS models are identified with the goal of energy performance forecasting of residential buildings. Section 4 presents a discussion of the results obtained by the fuzzy approaches and the FIR feature selection process, and performs an analysis of its usefulness. In Section 5, the main conclusions are offered.
## 5 Discussion
### Limitations and Future Directions  
The following research limitations need further investigation to achieve coordinated human-environment management of HF and EQ in China's lake-ring urban agglomerations. First, the representativeness of the indicator system can be further improved. Currently, the quantification of HF and EQ mainly relies on remote sensing indicators and land use data. In the future, incorporating multi-source data could improve the perception depth of the human-environment system. Second, the dual-dimensional HF-EQ classification framework effectively captures the spatiotemporal interactions of the human-environment system. Future research could further explore functional extensions supported by multi-source data to enhance the practical value of zoning results. Third, as this study focuses on China's lake-ring urban agglomerations, the findings' adaptability to other geomorphic units remains unverified. Future research could apply this management framework to different regions to test its generalizability. Meanwhile, efforts should focus on integrating research findings into territorial spatial planning practices and developing mechanisms to implement zoning results in land use control.
# Analysis of Internal Gas Leaks in an MCFC System Package for an LNG-Fueled Ship
## 1 Introduction
However, there have been no reports of a safety study on the application of the MCFC system to a ship that comprehensively evaluates a computational fluid dynamics (CFD) analysis while considering intentional leakage simulation in the marine environment. Analysis of intentional leakage can indicate the design guidelines for a safe system and thus prevent potential damage. Hence, to design highly efficient and stable MCFC green ships, we analyzed the characteristics (flows and distribution) of gas, heat, and pressure for the FC systems, e.g., stack, pipes, heat exchangers (HEXs) and balance-of-plant (BOP), by using the simulation tools referred to in the open literature. In particular, zones of localized high gas concentration, temperature, and pressure are identified, and design parameters needed to build safe MCFC ships, such as the location of the alarm unit with the gas leak detector and the capacity of exhaust fans, are recommended to prevent damage to system components from high heat and pressure. This study is expected to significantly contribute to the increased practical use of MCFCs in merchant marine applications. Figure 1 is a schematic diagram of a fuel-cell system (BOP and stack) as an auxiliary power unit that can produce 300 kW of electricity by using the boil-off gas (BOG) of the LNG carrier. The BOG (as the fuel) generated from the LNG tank is fed to the pre-converter and anode side, and air (oxidant) is supplied from the cathode side to produce 300 kW of electricity through chemical and electrochemical reactions in the stack. The reactions are as follows:  
\[\mathrm{Anode}:\mathrm{H_{2}}+\mathrm{CO_{3}^{2-}}\leftrightarrow\mathrm{H_{2 }O}+\mathrm{CO_{2}}+2\mathrm{e^{-}} \tag{1}\]  
\[\mathrm{CO}+\mathrm{CO_{3}^{2-}}\leftrightarrow 2\mathrm{CO_{2}}+2\mathrm{e^{-}} \tag{2}\]  
\[\mathrm{CH_{4}}+\mathrm{H  
In this study, the characteristics of flow inside the 300-kW fuel-cell system was analyzed using CFD. To prevent gas leaks from inside the BOP, it is very important to identify the status of internal air flow and to find an appropriate location for installing the equipment for gas detection.
# A Visual Analytics Framework for Inter-Hospital Transfer Network of Stroke Patients
## 3 Analysis of Data and User Task
### User Task Analysis
#### 3.4.4 Analysis of Interprovincial Transfers (T4)  
The medical researchers have attempted to analyze patient transfer patterns at the provincial level. Since the large catchment areas align with provincial areas in the Republic of Korea, investigating interprovincial patient transfers could indirectly examine whether the catchment area was well established. For example, it is commonly known that some regions in the Republic of Korea are highly dependent on specific hospitals. There were even cases where patients transferred to such hospitals from other provinces. The collaborating researchers wanted to confirm such known patterns with our framework and find other notable patterns from patient transfer data.
## 1 Introduction
### Main Contributions of the Study  
This study presents a comprehensive review and synthesis of state-of-the-art security paradigms for the IoE. The main contributions are as follows:  
1. _Layered Classification of IoE Security and Privacy Risks_: Security threats across all IoE architecture layers have been systematically classified, providing a holistic understanding of vulnerabilities and facilitating the development of targeted countermeasures.
2. _Comparative Analysis of Key Security Paradigms_: Blockchain, Edge AI, and Quantum-Resilient Cryptography have been comparatively analyzed, with their strengths, weaknesses, and application scenarios identified, and IoE-specific threats mapped to the most suitable defense mechanisms.
3. _Evaluation of Privacy-Preserving AI and Post-Quantum Solutions_: Privacy-preserving AI techniques such as Federated Learning, Differential Privacy, and Secure Multi-Party Computation, along with post-quantum cryptographic methods, have been analyzed, and their practical applicability in IoE environments has been assessed.
4. _Proposed Integrated and Hybrid Security Architecture for IoE_: An integrated layered security architecture combining Blockchain, AI, and Quantum-Resilient Technologies has been proposed, enhancing authentication, data integrity, and threat mitigation. Its functional components and workflows have been described with attention to both theoretical and practical deployment aspects.  
5. _Identification of Future Research Directions and Remaining Literature Gaps_: Current limitations and literature gaps have been identified, and clear priorities have been outlined for advancing hybrid, scalable, and quantum-resilient IoE security solutions.
## 3 Resource Allocation Considering NS and D2D
### System Model and Problem Formulation
\[s(t)=\{NPR_{i},csi_{j}\}.\quad\forall i\in F,\quad\forall j\in Z. \tag{14}\]  
Action: The action is given by the bandwidth \(w\) allocation to each slice \(i\) and by the power allocation using Equation (13) through the \(\lambda\) value, which is discretized in two decimal places \(\in\) (0.01, 1). The bandwidth is discretized in slots and can take discrete values in the range of 1 to 2000 slots for a bandwidth total of 10 MHz in a time of 1 s.  
\[a(t)=\{w_{i},\lambda\}.\quad\forall i\in F. \tag{15}\]  
Reward: We propose that the reward function \(r(s(t),a(t))\) be given by the weighted sum from the Shannon channel capacity (\(C\)), by the package delivery rate (\(PDR\)) satisfaction index to each slice and by the power allocated to UEs (\(p_{j}\)). The \(PDR\) is obtained by dividing the number of packets transmitted (\(NPT\)) by the total number of packets received (\(NPR\)). The reward penalty occurs if the chosen action does not meet the SLA requirements or exceeds the BS's total available resources, as follows:  
\[r(s(t),a(t))=\left\{ \begin{array}{l}0,\text{if the action chosen is undesirable}\\ \sum_{i=1}^{F}(\alpha\times C_{i})+\beta\times(PDR_{i}-\sum_{j=1}^{Z}p_{j}), \end{array} \right. \tag{16}\]  
where \(\alpha\) and \(\beta\) are constants used to add weight to values and maintain them with the same number of digits. The SLAs impose stringent requirements on the PDR [1]. Generally, RL agents learn with the main objective of maximizing the reward function. In this work, the main objective is to reduce the least amount of signal transmission power possible; the reward function is negative in the equation, thus minimizing its value. Figure 2: Power allocation using the water-filling algorithm.
# Alkali-Activated Mortars Modified by Epoxy-Carbon Fiber Composites Wastes
## 1 Introduction  
Epoxy resins reinforced by carbon fibers have outstanding mechanical properties and, because of their low density, high values of specific strength and modulus. As a result, they are applied in many sectors, such as the automotive, aeronautical, and nautical industries. Moreover, their demand is forecast to grow in the future [1, 2]. A large quantity of scraps is generated during production and, at present, these scraps are discarded. The recovery of bare fibers is either energy consuming (pyrolysis of the matrix) [3, 4] or involves the dissolution of the epoxy matrix through complex chemical reactions [5, 6]. The direct reuse of the scraps has been proposed for other types of composites, such as in the formulation of alkali-activated mortars (AAMs). These promising materials [7, 8] are used as binders as an alternative to traditional Portland cement, which has a significant carbon dioxide footprint [9]. Although characterized by a lower environmental impact, AAMs suffer from a number of drawbacks, such as extreme brittleness and low dimensional stability. The most frequently used solution to these problems is the addition of fibers. Polypropylene fibers [10], in addition to steel [11] or basalt [12] fibers, are commonly used for this task. The possible reuse of composite scraps [13] to obtain a similar improvement could provide a large environmental benefit. In this research, the effect of untreated scraps of different length on the properties of mortars formulated with metakaolin or fly ashes activated by alkaline solutions was investigated. The added amount of waste (about 4.6 vol% of the mortars) was derived from previous studies [13], which proved how this amount provided the best conditions to obtain good mechanical properties in similar materials. Moreover, amild chemical pre-treatment of the scraps was performed to investigate a possible means to improve the fibers-matrix interactions. In this case, the aim of the chemical treatment was not to dissolve the epoxy resin surrounding the fibers, but only to modify the outer surface of the epoxy layer.
## 2 Analysis of the Designing for Fairway Width
### Traffic Separation Scheme  
In order to cope with a series of major maritime accidents in Northern Europe in the 1960s, the West German, French, and British Navigation Society launched a study on how to separate ports in the Dover Strait, followed by studies on other seas with a statistically increased risk of collisions. In 1968, the number of participating bodies increased significantly after 41 ports were recommended by the International Maritime Organization (IMO) and two ports were decided by the IMO in 1973 to reduce marine accidents. In addition, Article 10 of the International Maritime Collision Prevention Regulations of 1972 describes the behavior of ships navigating within or near the customs separation method adopted by the IMO [19].  
It is stated that the IMO fairway separation method should take into account the fairway density, passage method, and available vessel traffic area when setting the fairway width, but the design width of the traffic separation scheme is not taken into account.  
As a result of a case study targeting the Strait of Dover, it was found that the number of marine accidents decreased by 23% compared to the previous level when the Traffic Separation Scheme was implemented [25]. In addition, it was determined that the number of collision accidents in Tokyo Bay, Japan, decreased by 18% after the implementation of the Traffic Separation Scheme [19; 26]. In addition, in studies focusing on the estimated effect of the introduction of the Traffic Separation Scheme, it was found that the number of collision accidents was reduced by about 24% in most cases [19]. Additionally, [PERSON] et al. (2003) calculated the effect of installing a traffic separator using a maritime traffic flow simulation for a round-trip waterway without a center line mark. As a result, it was determined that the psychological burden of ship operators was reduced by about 32% when the TSS was installed [27].  
Table 3 shows the customs clearance zones in Korea. The Traffic Separation Scheme (TSS) established in Korea can be divided into schemes established in approach waterways near ports and schemes established in coastal waters. The TSS for coastal waters can be further divided into natural forms with an island in the middle of the TSS and artificial forms with separate sections.  
\begin{table}
\begin{tabular}{c c} \hline
**Type** & **Width Range** \\ \hline One-way & 0.5–1.0 L* \\ Two-way & 1.0–2.0 L \\ \hline \end{tabular}  
* L: Length of Target Vessel.  
\end{table}
Table 2: Channel width according to the Korea design standard.
## 4 Design of the DRFTM  
The DRFTM trust model comprises three primary components: (1) trust evidence acquisition, (2) trust evaluation based on random forests, and (3) dynamic trust update based on deep reinforcement learning. The system architecture of the model is depicted in Figure 3. Trust evidence acquisition involves collecting relevant information from various nodes and sources. Random forests are utilized for node trust level evaluation, while deep reinforcement learning is employed for the dynamic update of node trust values to adapt to node mobility and network fluctuations. This comprehensive model contributes to enhancing network security and reliability, ensuring efficient trust management among nodes.  
Figure 2: Attack model: (**a**) DDoS attack; (**b**) selective forwarding attack; (**c**) data pollution attack.
## 4 Control Strategy and Configuration Optimization
### Control Strategy  
The state variable and control variable of the control strategy for the optimal fuel economy and the optimal dynamic performance are shown in Table 3.  
The cost function of the optimal fuel economy control strategy \(J_{fuel}\) is shown in Equation (15).  
\[J_{fuel}=\sum\limits_{k=0}^{N-1}(fuel_{k}+\beta\cdot\Delta Mode_{k}+\gamma \cdot|SOC_{0}-SOC_{k}|) \tag{15}\]  
where \(fuel_{k}\) is the fuel consumption at step \(k\); \(SOC_{k}\) is the SOC at step \(k\); \(\beta\), \(\gamma\) are the weight factors of the mode penalty function and the SOC penalty function, respectively. The cost function \(J_{fuel}\) consists of fuel consumption, mode penalty function, and SOC penalty function; the latter two penalty functions are set to avoid frequent mode switching and maintain the balance of initial and terminal SOC, respectively.  
In this paper, 0-120 km/h acceleration time is selected as the evaluation index of dynamic performance [30]. In the acceleration process, it is assumed that SOC is sufficient and battery power always meets the power requirements of the MG. The acceleration time \(J_{acc}\) as the cost function of the optimal dynamic performance control strategy is shown in Equation (16).  
\[\left\{\begin{array}{l}J_{acc}=\sum\limits_{k=1}^{120}\frac{\Delta v}{a_{k}} +\beta\cdot\Delta Mode_{k}\\ a_{k}=\frac{\mathrm{d}v}{\mathrm{d}t}=\frac{F_{\mathrm{k,max}}-(mgf_{t}\cos a +\frac{1}{2\mathrm{t}\mathrm{t}\mathrm{S}}C_{D}Av^{2}+mg\sin a)}{\partial m} \end{array}\right. \tag{16}\]  
where \(\Delta v\) is the speed sample selected as 1 km/h; \(\mathrm{a_{k}}\) is the acceleration at speed step k; \(\mathrm{F_{k,max}}\) is the maximum driving force at speed step k.
## 3 Results
### Prebreakdown Streamers
#### 3.2.1 Shape  
The propagation process of positive streamers can be divided into two stages in view of the shape development characteristics. In the initial stage, as shown in Figure 5, the streamers in pure oil and nanofluids behave similarly, exhibiting dense bush-like structures with slow velocities. While in the propagation stage, remarkable differences in the streamer shape are emerged in Fe\({}_{3}\)O\({}_{4}\) and TiO\({}_{2}\) nanofluids. In pure oil, certain filaments develop into main channels with a rapidly increased length accompanied by other filaments fading away. But in the case of Fe\({}_{3}\)O\({}_{4}\) and TiO\({}_{2}\) nanofluids, the main channels become much thicker with more lateral branches than that in pure oil during the whole propagation process, resulting in a much denser structure. In addition, the streamer propagation length is much shorter in Fe\({}_{3}\)O\({}_{4}\) and TiO\({}_{2}\) nanofluids, which is of notable importance due to its relationship with electric breakdown event. Whereas in the Al\({}_{2}\)O\({}_{3}\) nanofluid, streamers have no obvious change with a tree-like shape similar to that in pure oil.  
Figure 4: Positive breakdown strengths of pure oil and nanofluids.
## 3 Analytical Model Calculation and Validation
### Validation of Calculation Results
#### 3.3.1 Electromagnetic Forces Validation
The levitation forces acting on the PM all showed a tendency to increase first and then decrease with the increase in speed for different conductive plate materials, and the maximum levitation force that can be reached by various conductive plate materials is the same, while the corresponding speed when reaching the maximum levitation force is different for different materials. The smaller the material's conductivity is, the higher the corresponding speed at the peak of the levitation force is. In the same way, the drag forces increase first and then decrease with the increase in speed, and the maximum drag force for each conductive plate material is the same. However, for the same material, the corresponding speeds are different when the levitation force and drag force reach the maximum value. For example, when the conductive plate is an aluminum plate, the levitation force reaches the maximum value at \(v_{\rm x}=23\) m/s, while the drag force reaches the maximum value at \(v_{\rm x}=17\) m/s. Figure 11: Relative errors of electromagnetic forces between the analytical and FEA methods. (**a**) Relative error of levitation force; (**b**) Relative error of drag force; (**c**) Relative error of lateral force. Figure 12: Variations in the lift-to-drag ratio and lift-to-weight ratio.