esa-sceva/satcom-chunk-collection huggingface dataset:
## Memetic Algorithm-Based Multi-Objective Coverage Optimization for Wireless Sensor Networks  
**[PERSON] 1,2,3,*, [PERSON] 1 and [PERSON] 4**  
1 College of Computer, Nanjing University of Posts and Telecommunications, No.9, Wenyuan Road, Yadong new District, Nanjing 210023, China; E-Mail: [EMAIL_ADDRESS]  
2 Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, No.66, New Mofan Road, Gulou District, Nanjing 210003, China  
3 State Key Laboratory for Novel Software Technology, Nanjing University, No.163, Xianlin Road, Qixia District, Nanjing 210023, China  
4 Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, No.66, New Mofan Road, Gulou District, Nanjing 210003, China; E-Mail: [EMAIL_ADDRESS]  
*Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +86-25-8586-6422; Fax: +86-25-8586-6433.  
External Editor: [PERSON]  
_Received: 9 August 2014; in revised form: 8 October 2014 / Accepted: 18 October 2014 / Published: 30 October 2014_  
Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MOCADMA, which models the coverage control of WSNs as the multi-objective optimization problem. MOCADMA uses a memetic algorithm with a dynamic local search strategy to optimize the coverage of WSNs and achieve the objectives such as high network coverage, effective node utilization and more residual energy. In MOCADMA, the alternative solutions are represented as the chromosomes in matrix form, and the optimal solutions are selected through numerous iterations of the evolution process, including selection, crossover, mutation, local enhancement, and fitness evaluation. The experiment and evaluation results show MOCADMA can have good capabilities in maintaining the sensing coverage, achieve higher network coverage while improving the energy efficiency and effectively prolonging the network lifetime, and have a significant improvement over some existing algorithms.  
keywords: sensor networks; coverage algorithm; memetic algorithm; multi-objective optimization +
Footnote †: journal: Journal of Computational Physics
# Resource Management in Converged Optical and Millimeter Wave Radio Networks: A Review
## 4 Throughput Maximization and Resource Allocation Algorithms
### Selected Papers
Dual-connectivity with a macro cell and mmWave cells is also considered as an alternative architecture for fair scheduling in the presence of interference in [56] with approximation algorithms based on the fractional weighted vertex coloring of conflict graphs method are used for throughput optimization under mutual interference. Different stakeholders become involved in the decision-making framework of converged optical and radio mmWave networks, such as competing network operators in [42], network services with different QoS demands in [52], and users in [57]. The interactions among these stakeholders are defined by distributed cooperative and competitive models depending on their relation. Evolutionary game theory is used to model the interactions among the BSs and the PON for DBA in [42] and BSs change their strategies based on replicator dynamics. Three algorithms are developed in [52] to assign appropriate bandwidth to each service with priority based differentiation of the QoS demands of different services. A user and network sub-channel resource allocation problem is analyzed in a joint algorithm in [57] and the interactions are defined with an optimal algorithm based on Lagrange duality and a greedy algorithm based sub-optimal solution. Distributed resource allocation methods are used not only to define the interactions between the stakeholders as in [42], but also to enable information exchange at the network edge [43; 54]. In [54], a distributed control plane shifts control tasks to FiWi access nodes with interleaved polling with adaptive cycle time DBA scheme. The nodes are able to exchange control information, such as queue states and transmission needs with each other. In [43], a load balancing game and a bandwidth allocation game based on a bidding system are designed to overcome the problem of mapping the channels to ONUs in a PON for different traffic scenarios. Throughput maximization for eMBB is a two sided problem for mmWave radio and optical networks, as priority based QoS-aware solutions are discussed [52] to realize such services with QoS guarantees, whereas minimum throughput targets for other services are also considered by applying fair scheduling [56]. Among the existing works, centralized management decisions are mainly used to respond to the throughput maximization-resource allocation fairness trade-off. The optimization solution in [43] has a centralized regulator, as the optical line terminal (OLT) acts as the resource manager to keep optimal fairness values. Another centralized solution is provided in [58] for solving the UE-RRH and RRH-BBU uplink sum-rate optimization problem with a differential evolutionary algorithm. Apart from this general trade-off discussion, the problem of translating eMBB application specific requirements to mmWave radio and optical resource allocation is not discussed in detail in the existing works.
# Research Needs for Realization of Zero-Carbon Power Grids with Selected Case Studies
## 2 Critical Research Agenda
### Supply-and-Demand Balancing
#### 2.1.3 Algorithms and Tools  
The algorithms and technical tools of traditional power grids must be improved to ensure a stable balance between supply and demand in power grids with high portions of VRE. Power balancing then becomes more dynamic and uncertain, requiring a change from deterministic algorithms and tools to more probabilistic methods [27]. This aids grid operators to maximize the availability of existing flexible resources and hence minimize the reinforcement of operational flexibility. As we move toward 100% renewable electricity, emerging flexible resources, such as EVs and heating, ventilation, and air-conditioning (HVAC) units, enhance the flexibility of grid operations. To encourage customer engagement, the prices and incentives offered by the electricity, transportation, and heating/cooling sectors must be both transparent and practical, thus based on accurate assessments of the contributions of flexible resources. As such contributions have expanded on sector coupling, algorithms and tools that handle data acquisition, pre-processing, and visualization will become increasingly important and complex. It will become more difficult to remain fully aware of all grid operating states, and to maintain the supply-and-demand balance at all times. Moreover, the large increases in the numbers of flexible resources within distribution networks render it essential to develop interfacing algorithms and tools that estimate the availability, duration, and responsiveness of grid services for transmission networks [2,15]. This will facilitate coordination across remotely located regional grid operators at different voltage levels, fulfilling their new roles in system operations and interconnections.
## 3 Results and Discussion
### Textural Characterization (BET)  
To assess the texture of the heat-treated powders, N\({}_{2}\) adsorption-desorption isotherms were obtained and are displayed in Figure 12. The textural properties (BET surface area, total pore volume, and average pore size) are provided in Table 7.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Sample** & **Composition** & **Values (Mass \%)** & **Line** \\ \hline \multirow{3}{*}{LTA-Pt} & Ti & 26.46 & Ti-K\(\alpha\) \\  & La & 72.50 & La-L\(\alpha\) \\ \cline{1-1}  & Pt & 1.03 & Pt-L\(\alpha\) \\ \hline \hline \end{tabular}
\end{table}
Table 6: Elemental composition of the analyzed samples.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Sample**} & \multirow{2}{*}{**Crystalline**} & \multicolumn{2}{c}{**Lattice Parameters (Å)**} & \multirow{2}{*}{**Crystallite**} \\  & & **a** & **b** & **c** \\ \hline LTA & La\({}_{2}\)Ti\({}_{2}\)O\({}_{7}\) & 7.816 & 13.022 & 5.539 & 14 \\ LTA-Pt & La\({}_{2}\)Ti\({}_{2}\)O\({}_{7}\) & 7.829 & 13.034 & 5.553 & 15 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Phase identification, lattice parameters, and crystallite sizes of the thermally treated samples.  
Both samples exhibit type IV isotherms with H3 hysteresis loops, according to the IUPAC classification [71]. The small hysteresis loop area and its appearance at relatively high pressures (P/P\({}_{0}\) > 0.8) in all samples suggest the presence of relatively large, well-defined mesopores, with some contribution from macropores. This observation is further supported by the pore size distribution (PSD) graphs (shown as inserts in the figures) which confirm broad distributions spanning almost the entire mesopore range and extending into the macropore domain. As expected for materials of this type, the specific surface areas and total pore volumes are relatively low (see Table 7).
## 2 Materials and Methods  
### Isolation and Identification of a Suitable Urease Active Bacterium  
#### 2.1.1 Soil Sampling and Isolation of Ureolytic Bacteria  
The coastal hydrodynamics along the southern, south western, and western coastal belt of Sri Lanka are highly affected by the strong waves generated by the south western monsoon and are the most susceptible to erosion of sandy slopes. Therefore, the study area for the current study was demarcated from Tangalle in southern province to Uswetakeiyawa, Colombo, in western province. Beach sand samples, each approximately weighing 50 g, were randomly collected from 11 sampling locations (M1-M11) along the shoreline and soil samples from 2 inland localities (L1 and L2) into sterile tubes (see Supplementary Materials). All the samples were exported from Sri Lanka to Japan following the Japanese Minister Permission System and stored at 4 \({}^{\circ}\)C. Each soil sample of 5 g was then serially diluted (10\({}^{-1}\)-10\({}^{-6}\) times) under sterile conditions. 50 \(\mu\)L of beach sand and inland soil suspensions thus prepared were then plated on Zobell 2216E agar medium (5.0 g/L hipolypettone, 1.0 g/L yeast extract, 0.1 g/L FePO\({}_{4}\), 30.0 g/L agar in artificial seawater, pH 7.6-7.8) and NH\({}_{4}\)-YE agar medium (15.75 g/L tris buffer, 10.0 g/L (NH\({}_{4}\))\({}_{2}\)SO\({}_{4}\), 20.0 g/L yeast extract, 20.0 g/L agar in distilled water), respectively. After incubating at 30 \({}^{\circ}\)C for 2 days, colonies were identified from a plate with 30-200 colonies. Different types of colonies were visually identified and separately cultivated on the plates prepared in the same manner described above.  
A simple urease activity test was then conducted for qualitative assessment of urease producing bacteria. Each colony was mixed with 20 mL of cresol red solution containing urea (0.4 g/L cresol red and 25 g/L CO(NH\({}_{2}\))\({}_{2}\) in distilled water) and incubated at 45 \({}^{\circ}\)C for two hours. Colonies that changed the initial yellow color to pink (Cresol red changes from yellow to pink when pH changes to 7.2-8.8, which is accomplished during urea hydrolysis) were identified as urease active bacteria.
# The Current Development Status of Agricultural Machinery
## 5 Summary and Future Perspectives  
The advancement of agricultural mechanization in China's hilly and mountainous regions constitutes a critical foundation for achieving agricultural and rural modernization. In recent years, driven by national policy incentives and research initiatives, significant breakthroughs have been made in the development of intelligent agricultural machinery tailored for these challenging terrains. Currently, the technology underlying agricultural machinery chassis designed for hilly areas is transitioning from traditional mechanical drives to intelligent systems characterized by high adaptability. Core challenges include addressing coupling issues related to power, structure, and control within complex terrain environments.  
Figure 19: BP neural network PID control block diagram.  
Figure 18: Fuzzy PID control block diagram.  
Existing equipment and operational techniques remain largely experimental, indicating substantial opportunities for improvement in constructing reliable, comfortable, safe, and universally applicable chassis systems. To establish an intelligent chassis framework that can adapt to small plots, steep slopes (exceeding 25\({}^{\circ}\)), and obstacle-rich terrains while facilitating efficient low-carbon agricultural mechanization, future research should prioritize three key directions:  
1. Innovative Multi-Modal Mobility Mechanisms: Enhance adaptability to wet and cohesive soils through terrain-adaptive structural optimization coupled with soil-friendly mobility design.
2. Cooperative Control Algorithm Optimization: Improve power distribution efficiency by 15-20% through energy-driven approaches alongside energy efficiency optimization.
3. Integrated Intelligent Sensing Systems: Upgrade leveling systems utilizing dual-loop fuzzy PID controllers combined with sliding mode observer technologies to achieve high precision and adaptability; develop specialized MEMS tilt sensors along with multi-source fusion positioning modules specifically designed for hilly terrain; establish real-time mapping models of terrain-load-energy consumption aimed at mitigating chassis instability on slopes exceeding 25\({}^{\circ}\).  
By integrating structural optimization with cooperative control algorithms, an intelligent platform will be developed to create efficient, smart, and low-carbon chassis systems. This initiative aims to accelerate the modernization of agricultural machinery in hilly and mountainous regions. The detailed research framework is illustrated in Figure 20.
# An Optimization Route Selection Method of Urban Oversize Cargo Transportation
## 3 Materials and Methods
### Influence Factor Analysis
#### 3.1.5 Bridges  
Due to the intersection of roads and overpass bridges and pedestrian bridges in urban roads, the available headroom of the road changes. This research counts the number of overpass bridges and pedestrian bridges in each route and uses the 5 m clearance height usually required for oversize cargos as the demarcation point to count the number of flyovers with a clearance height of less than 5 m.  
Many intersections use overpass bridges to reduce the conflict of traffic flow lines. Due to the existence of overpass bridges, the usable road headroom changes. This paper counts the number of overpass bridges on each road and counts the number of bridges with a headroom less than 5 m. The number of bridges with a headroom less than 5 m is a cost attribute, denoted as BN, and the unit is quantity.  
Based on the road design drawings and on-site measurements, the data of four routes through Suzhou are selected as alternative route sections for urban oversize cargo transportation. The attribute values of the four routes are in Table 1:  
In all Tables of this paper:  
FC is the number of horizontal curves with a radius less than 20 m.  
TC is the number of switch-back curves.  
TM is the total mileage.  
LG is the road mileage with a longitudinal gradient greater than 5%.  
RW is the road mileage with a width greater than 25 m.  
RN is the road mileage with a width less than 15 m.  
BN is the number of bridges with headroom less than 5 m.
## 3 System Model and Problem Description  
The UAV-assisted MEC system model studied in this paper is shown in Figure 1. The system architecture \(U(u=1,2,\ldots,U)\) consists of a UAV equipped with high-performance edge servers and user devices distributed at different height levels, with \(K(k=1,2,\ldots,K)\) high-threat obstacles present in the scene. The UAV takes off from its initial position to perform communication service tasks. During the flight, it needs to dynamically avoid obstacles and provide stable communication service support for user devices. After completing the service period, the UAV returns to its initial position for energy supply. The user device adopts a partial offloading strategy, offloading some tasks to the UAV edge server for processing, while the remaining tasks are retained for local execution.
# Closed-Form Performance Analysis of the Inverse Power Lomax Fading Channel Model
## 3 IPL Fading Channel Model Application
### Amount of Fading  
The amount of fading is defined as the variance \(\mathbb{V}\mathrm{ar}\{\gamma\}\) of the instantaneous SNR \(\gamma\) normalized by its squared average value:  
\[\mathrm{AoF}=\frac{\mathbb{V}\mathrm{ar}\{\gamma\}}{\left(\mathbb{E}\{ \gamma\}\right)^{2}}=\frac{\mathbb{E}\{\gamma^{2}\}}{\left(\mathbb{E}\{\gamma \}\right)^{2}}-1, \tag{18}\]  
**Theorem 2**.: _The amount of fading (\(\mathrm{AoF}\)) for the IPL channel model is given by_  
\[\mathrm{AoF}=\Gamma(\alpha)\frac{\Gamma\left(1-\frac{2}{\beta}\right)\Gamma \left(\alpha+\frac{2}{\beta}\right)}{\left(\Gamma\left(1-\frac{1}{\beta} \right)\Gamma\left(\alpha+\frac{1}{\beta}\right)\right)^{2}}-1. \tag{19}\]  
**Proof of Theorem 2.** The proof of Theorem 2 is trivially obtained by combining the definition of the amount of fading (18) with the expression for the SNR \(r\)-th order moment (4c) obtained in Lemma 1. \(\qed\)  
Treating the AoF as a function of channel parameters (i.e., \(\mathrm{AoF}(\alpha,\beta)\)), one can see that  
\[\lim_{\alpha\to\infty}\mathrm{AoF}(\alpha,\beta) =\frac{\Gamma\Big{(}1-\frac{2}{\beta}\Big{)}}{\Gamma\Big{(}1- \frac{1}{\beta}\Big{)}^{2}}-1\gtrless 1, \tag{20a}\] \[\lim_{\beta\to\infty}\mathrm{AoF}(\alpha,\beta) =\lim_{\alpha,\beta\to\infty}\mathrm{AoF}(\alpha,\beta)=0, \tag{20b}\]  
which means that the IPL channel model can exhibit a hyper-Rayleigh regime (according to [54]) depending on the parameters.
## 3 Methodology
### Flash Flood Impact Data Collection
During the fieldwork, the data collection focused heavily on capturing photographic and video recordings of the study area, ensuring comprehensive visual documentation of the flood events and their impacts. After the fieldwork, the collected data were returned to the laboratory for further analysis. At this stage, the data underwent georeferencing, a critical step that involved aligning the visual information with spatial coordinates to enable precise mapping and analysis. The Flood Flow Impact Severity Scale (FFISS) was applied to assess the severity of the flood impacts. This step was supported by Geographic Information System GIS software (ArcMap 10.5), which allowed for the integration and processing of spatial data with a high degree of accuracy. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Type of Source** & & **Description of Data** \\ \hline Official damage records & \(\bullet\) & Catalogue of 759 distinct damages to properties, households, and businesses recorded on central government records. \\  & \(\bullet\) & Official records from local authorities regarding compensation for impacted properties \\  & \(\bullet\) & Official reports of local authorities with detailed descriptions of infrastructure damages that included information on address, type of damage, and costs. \\ \hline Emergency services & \begin{tabular}{c} Reports from the fire service regarding rescue operations, injuries, fatalities, and additional emergency interventions, such as providing aid to citizens and conducting property water removal. \\ \end{tabular} \\ \hline Media & Imagery (522 photos and 12 videos uploaded via various internet portals) captured during or immediately after the two floods, with known locations. \\ \hline Deliverables of applied scientific projects including & \
\begin{tabular}{c} 5 post-flood field surveys that produced a total of 1215 pictures (560 for the 2009 event and 890 for the 2020 event), 11 UAS videos of a total duration of 60 min, and detailed \\ results from post-event field surveys \\ \end{tabular} &
\begin{tabular}{c} 5 post-flood field surveys that produced a total of 1215 pictures (560 for the 2009 event and 890 for the 2020 event), 11 UAS videos of a total duration of 60 min, and detailed \\ field notes and geolocations on impacts of both events \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Different sources of data were collected and evaluated for applying the FFISS for the impacts of the 2009 and 2020 flood events on Evia Island. The final phase of the research focused on the production of detailed maps. These maps were designed to provide a visual representation of the maximum impact severity associated with each flood event. They addressed the specific categories of impacts individually, while also combining them to illustrate the cumulative effects of the flood events. The resulting maps served as a comprehensive tool for understanding the spatial distribution and severity of the flood impacts (Figure 7).
## 1 Introduction
### Related Work
#### 1.1.3 Privacy and Trustworthiness  
Nevertheless, challenges emerge in the crowdsourcing process concerning the _privacy_ of crowdworkers and the _trustworthiness_ of the information they provide to the crowdsourcers [22]. A novel crowdsourcing network architecture addressing location privacy concerns during task allocation is proposed in [23] by implementing a privacy-preserving, decentralized dispute arbitration protocol to handle payment disputes without revealing users' private information, showcasing resistance to forgery attacks and efficient performance. A game-theoretic model is introduced in [24] to analyze the dissemination of user personal information in online social networks, considering factors like intimacy and subject popularity [25]. The authors in [26] focused on user privacy and data trustworthiness and proposed game-theoretic solutions, specifically revisiting coalitional game formation and subgame perfect equilibrium-based concepts.
# Multi-Path Data Distribution Mechanism Based on RPL for Energy Consumption and Time Delay
## 4 Analysis of the Performance
### Evaluation Environment  
The experimental parameters are set as shown in Table 4.
# Evaluation of Resilient Modulus and Rutting for Warm Asphalt Mixtures: A Local Study in Iraq
## 1 Introduction
The findings indicate that the rutting potential of the asphalt mixtures is not increased by including these elements. Although utilizing WMA technology can greatly contribute to environmentally friendly building practices, Iraqi mixtures must be assessed using well-known WMA methods to produce the performance data required to construct asphalt concrete pavements with WMA. Most Iraqi roads are paved with HMA mixtures, and WMA mixtures are rarely used, so the purpose of this study is to evaluate a laboratory study's performance and suitability to determine whether zeolite may be used in conventional pavement and environmental conditions typically found in Iraq in comparison to the HMA using (0.3 and 0.5) percent of zeolite by total mix weight and using local Iraqi paving materials. The two mixtures, HMA and WMA, for the two percentages of zeolite will be assessed using the Marshall Stability, Marshall Flow, resilient modulus, and rutting tests.