esa-sceva/satcom-chunk-collection huggingface dataset:
# Comparative Study of Energy Efficient Routing Techniques in Wireless Sensor Networks
## 3 The Proposed Taxonomy
### Network Architecture
#### 3.3.2 Position Centric (Geocentric)  
Location-aware use the location information accessed from the GPS signals or received radio signal strength as forwarding metrics during the forwarding of queries to that  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Protocol**} & \multicolumn{2}{c}{**Delivery Mode**} & \multicolumn{2}{c}{**RT-Type**} & \multicolumn{2}{c}{**Energy**} & \multirow{2}{*}{**Reliability**} \\ \cline{2-2} \cline{4-6}  & **RT Delivery** & **NRT Delivery** & & & **(Soft/Hard)** & \\ \hline
**PATH** & ✓ & & SRT & High & Medium \\ \hline
**CBRR** & ✓ & & SRT & Medium & High \\ \hline
**OMLRP** & ✓ & ✓ & SRT & Low & High \\ \hline \hline \end{tabular}
\end{table}
Table 3: Delivery mode-based routing protocols for WSNs.  
particular region and to relay data to the destination in order to reduce transmissions. This family of protocols includes:  
* **Minimum hop routing protocol (Min-Hop)** Min-Hop is designed as a location-based energy-aware routing protocol. It forwards packets with minimum energy consumption based on the two phases: initialization and routing phase. During the initialization phase, min-hop builds the routing tables to be able to construct the optimal path to the destination, which is the shortest path used in the routing phase to forward packets to the destination. Using the short path, this protocol enhances the energy consumption, but the nodes forming this path will be overused and quickly die, which creates various problems such as isolated areas [56].
* **Path Energy Weight (PEW)** PEW is designed as a location-based protocol. It uses a global view mechanism to globally map energy levels in the network [57]. The selection of forwarding routes in this protocol is made according to the energy distribution along paths, and the one with a balanced energy level will be promoted to avoid energy holes to improve the network lifespan.  
Table 4 establishes a comparison between network architecture-based protocols.
# Application of Plasma Technology in Bioscience and Biomedicine
## 3 Antimicrobial Applications  
The antimicrobial efficacy of cold plasmas and plasma-treated liquids is of interest in a variety of fields, ranging from the food industry [5] to the medical field [6; 7; 8; 9].  
For the decontamination of surfaces in the food production industry, plasma-treated water showed efficiency on _Pseudomonas fluorescens_ biofilms, related to a decrease of pH in the plasma-treated water as the basis for the chemically active components of plasma-treated water and its antimicrobial effects. The findings by [PERSON] et al. provide valuable insights into the mechanisms of inactivation of biofilms by plasma-generated compounds such as plasma-treated water [5].  
More focused on medical applications, [PERSON] and co-workers demonstrated the fungicidal effects of plasma-treated water and plasma-processed air on _Candida albicans_. The authors investigated the possible combination of plasma-treated water and plasma-processed air to obtain synergistic effects by combining the former for cleaning and the latter for drying. The authors propose these as an innovative alternative to the sanitization processes currently used in production plants [6]. Also, on the topic of fungicidal effects, in the work by [PERSON] et al. the effects of a plasma torch on the inactivation of model yeast (_Candida glabrata_) provided insights into the effects of the reactive species from the plasma gas phase [7].  
[PERSON] et al. investigated the biological activity of plasma-treated water on different biological targets, including both microbial and mammalian cells in vitro. Different trends were observed for cytotoxic activities and effects on enzyme function, which were translated through the selective generation of chemical species and indicate very distinct mechanisms of action which may be exploited when tailoring plasma treated liquids to various applications [8].  
Focusing on a specific dental application, the possible use of cold plasma jets on cariongenic films, [PERSON] et al. recorded reduction in viability both in single- and multi-species biofilms formed by _Streptococcus mutans_, _Streptococcus sanguinis_, and _Streptococcus gordonii_ formed on hydroxyapatite discs, simulating the natural biocearamic present in teeth. Single species biofilms were found to be more sensitive to the treatment, showing total elimination for certain strains, but low exposure times of plasma affected both single- and multi-species carigenic biofilms, which indicates that the treatment is a promising source for the development of new protocols for the control of dental caries [9].
# Sensor Network Environments: A Review of the Attacks and Trust Management Models for Securing Them
## 2 Previous Works  
There have been previous reviews carried out on the topic of trust management and modeling. A detailed comprehensive study of trust modeling is conducted in [4], where a detailed look into what trust actually is, not only from a digital perspective but also from a human social perspective, is conducted. Many attack types and mathematical trust calculation techniques are discussed, along with recommendations for what a trust model should provide in terms of security.  
In [5; 6], a brief overview of trust models in VANETs is provided. Both papers offer a perspective on the characteristics of VANETs and their unique security challenges, as well as the attack types they are facing and the models that have been used to attempt to mitigate these attacks.  
In [7], a specific look at fuzzy trust modeling techniques in cloud computing environments is offered, providing a detailed overview of the cloud infrastructure, along with trust models being used to secure this fast-growing technology.  
A discussion of the challenges of traditional security measures in [8] considers how trust is used as a method for overcoming these challenges. The use of trust models for providing authentication, access control, secure service provisioning and secure routing is also analyzed in this paper, along with the usual run-down of the attack types and robustness of trust models.  
The previous works all contain an analysis of the attack types and model types. This paper aims to provide an understanding of the attack and model types, but also aims to provide an understanding as to how trust models are generally structured and used. From reviewing previous works in the area, there appears to be a gap in the research regarding the actual parameters used to measure trust. This paper takes a much closer look at the specific parameters used to provide the data for trust calculations (Section 5). The parameters used in the measuring and calculation of trust can be just as, if not more, important to the model than the mathematical classification technique itself.
## 2 Evaluation Methods
### Extraction of Amplitude and Time Constant of RTN  
Two-level type RTN is characterized by only three parameters, which are the mean time to capture (\(<\)\(\tau_{\text{c}}\)\(>\)), mean time to emission (\(<\)\(\tau_{\text{c}}\)\(>\)), and amplitude (\(\Delta\)V\({}_{\text{gs}}\)). The time constants correspond to two physical states of a trap, that is, \(\tau_{\text{c}}\) and \(\tau_{\text{e}}\) represent spans in a low V\({}_{\text{gs}}\) level (carrier trapping state) and high V\({}_{\text{gs}}\) level (carrier emission state), respectively (Figure 4a). The RTN amplitude \(\Delta\)V\({}_{\text{gs}}\) is defined as the difference between two normal distributions in a voltage histogram (Figure 4b). We extract the time constants by fitting the distributions of \(\tau_{\text{c}}\) and \(\tau_{\text{e}}\) to the exponential distribution (Ae\({}^{-t/<\tau_{\text{c}}}\)) because the phenomenon is governed by the Poisson process. The time constants can be extracted with us accuracy using the specific MOSFET measurement mode.  
Figure 4: Definitions and extractions of two time constants (\(<\)\(\tau_{\text{c}}\)\(>\), \(<\)\(\tau_{\text{e}}\)\(>\)) and amplitude (\(\Delta\)V\({}_{\text{gs}}\)) from RTN (**a**)waveform data, (**b**)histogram of Vgs.  
Figure 3: (**a**) Schematic block diagram of a test pattern. (**b**) Unit cell.  
The time constant ratio <\(\tau_{\rm e}\)>/<\(\tau_{\rm c}\)> is also an important parameter in RTN because the energy level of a trap that causes RTN is related to the constant ratio as follows [12; 41; 42; 43].  
\[\frac{<\tau_{\rm c}>}{<\tau_{\rm e}>}=\rm{gexp}\bigg{(}\frac{E_{T}-E_{F}}{kT} \bigg{)} \tag{11}\]  
where \(E_{T}\) and \(E_{F}\) represent the energy of the trap and Fermi energy of the channel, respectively; k, T, and g represent Boltzmann constant, temperature, and degeneracy factor, respectively, where g is assumed to 1. Then, the energy of the trap level is indicated by (12).  
\[E_{T}-E_{F}=kT\rm{ln}\bigg{(}\frac{<\tau_{c}>}{<\tau_{\rm e}>}\bigg{)} \tag{12}\]  
We can use the frame measurement mode to extract the time constant ratio, and the 1.2 million MOSFETs can be measured 10,000 times in 7000 s (sampling period = 0.7 s). An average of the time constant ratio <\(\tau_{\rm e}\)>/<\(\tau_{\rm c}\)> is the same as Count-L/Count-H (shown in Figure 4b), where Count-L and count-H are the numbers of low and high states, respectively [41; 42; 43; 44]. When the time constant is greater than a sampling frequency of 0.7 s, the detected number of transition times is the same as the transition time of RTS characteristics. However, when the time constant is less than 0.7 s, the detected number of transition times is less than the real one; however, it is proportional to the real one because the absolute value of the time constant, which is less than the sampling frequency, cannot be extracted in this measurement. Then, the number of transition times is defined as the detected ones in the sampling frequency of 0.7 s.
# An Overview of Emerging Nuclear Sensor Technologies: Challenges, Advancements and Applications
## 3 Applications of Nuclear Sensors  
### Nuclear Power Plant Safety  
Nuclear sensors have a wide array of applications. In NPPs, nuclear sensors are invaluable for measuring the levels of radiation inside and outside the nuclear power plant. Without nuclear sensors, the safety of the workers and environment would be largely uncertain. Nuclear sensors can detect leaks in the reactor coolant system, measure the amount of radioactive material released into the environment, and monitor the levels of radiation of spent nuclear fuel in waste storage environments.
## 6 Conclusions
### Key Contributions and Achievements  
This study proposed a more efficient and precise 3D modeling technique by integrating vector-based 3D object generation, texture mapping, and optimized data processing techniques, surpassing traditional approaches in terms of speed, visual quality, and processing efficiency.  
The key contributions and achievements of this research are as follows:  
* Enhanced 3D Model Generation Speed and Visual Quality: the proposed method improves 3D object generation speed, enhances visual realism, and optimizes data processing performance, ensuring a more efficient and scalable modeling workflow.
* Optimized Data Processing Efficiency: by applying vector-based processing techniques, the method significantly reduces query time and minimizes memory consumption compared to traditional raster-based approaches, improving the efficiency of large-scale spatial data handling.
* Efficient 3D Object Generation with Reduced Computational Load: This study introduces an optimized triangulation and polygon simplification algorithm, effectively reducing computational overhead while maintaining geometric accuracy in 3D object creation. The method was validated in an OpenGL 2.21.0 environment, confirming its capability to generate optimized 3D terrain and urban models efficiently.
* Advanced Texture Mapping with WIT (Wise Interpolated Texture) Technique: This study applies the WIT technique to minimize discontinuities between interpolated textures and optimize high-resolution texture mapping based on orthoimages. This approach improves loading speed, reduces texture distortion through refined UV mapping alignment, and enhances visual fidelity in 3D representations. The experimental results demonstrate that the WIT-based texture mapping delivers smoother and more uniform visual outputs compared to commercial mapping services.
* Superior 3D Object Generation Performance: Performance evaluations indicate that the proposed method significantly outperforms existing approaches in processing speed, effectively handling vector data conversion, mesh generation, and DEM mapping with higher efficiency.
* CityGML 3.0 Compliance and Validation: by automating data transformation and validation processes for compliance with the CityGML 3.0 standard, this study improves the practicality of large-scale 3D urban modeling, ensuring seamless integration with standardized geospatial data frameworks.  
Through these technological advancements, this study contributes to the efficient processing of large-scale spatial data, optimized texture mapping, and standardized data transformation techniques. Based on these improvements, the proposed approach demonstrates applicability across various domains, including smart cities, disaster management, and urban planning, highlighting its potential for practical implementation in real-world geospatial applications.
# A Survey of Target Detection and Recognition Methods in Underwater Turbid Areas
## 5 Applications of Underwater Target Detection and Recognition Technology  
Underwater turbid area target detection and identification technologies are used in a wide range of applications, including the detection of underwater organisms and underwater equipment. The need for productivity and automation in the aquaculture industry has given rise to technologies for the detection of underwater organisms, including fishes and sea cucumbers and shrimps, crabs, and scallops. This technology's aim is to achieve automated identification of the species, numbers, health status, and behavior patterns of underwater organisms. The detection of coral reefs has also been extensively studied due to the need for ecological monitoring. In addition, some underwater environments require habitat mapping and mineral identification. The inspection of underwater equipment includes many aspects, such as cables, pipes, hull corrosion, cracks, and welds.
# Mobility-Multihoming Duality
## 5 Evaluation of Mobility Multihoming Duality
### Testbed Hardware, Network Topology, and Configuration
Figure 6: A scenario diagram describing host movement for the mobility–multihoming duality evaluation. There are four IPv6 networks, aa–dd, connected via the 4 routers, R1–R4, scenario. Network dd is used connect R1, R2, and R3 to R4, and it represents connectivity on over the Internet between MN and CN. The arrow labelled 1 is the first movement the MN carries out: moving from network aa on R1 to network cc on R3. The arrow labelled 2 shows the second set of movement, where the MN returns from network cc back to network aa.
## 2 Proposed SST Circuit, Specifications and Control Layout
### Ferrite Core High Frequency Transformer Design  
The importance of ferrite materials is worth mentioning in modern power and industrial electronics application. Design constraints of ferrite materials and losses incorporated in soft magnetic materials due to high switching frequency are already discussed in literature [38; 39]. More elaborate models that discuss the modeling and dependence of ferrite losses at high flux densities and high frequencies are also discussed in [40].  
The operation of ferrites at square waves with 50% duty cycle offer 0%-15% smaller losses as compared to sinusoidal signals of the same peak and frequency [41; 42; 43; 44]. These properties and performance make ferrite materials suitable for many switching applications where square wave switching is desired without using any auxiliary filter circuits.  
In this research work ferrite medium, operated at 50% duty cycle within DAB, is used not only to provide galvanic isolation but also to decrease voltage levels. The ANSYS/Maxwell platform is chosen to design the high frequency ferrite core transformer. The specified design parameters of the simulated Maxwell model, as shown in Figure 7, are tabulated in Table 4.  
Figure 7: High frequency ferrite core transformer. (**a**) Primary and secondary coil. (**b**) Complete transformer model placed within an air medium.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Quantiy** & **Specifications** \\ \hline DC-link & Input DC Voltage & 500 V \\ DC-capacitors & 2- DC capacitors in series & Each 250 V \& 20 mF \\ \(V_{out}\) & Output Voltage & Variable \\ \(F_{out}\) & Output Frequency & Variable \\ \hline \hline \end{tabular}
\end{table}
Table 3: Voltage source inverter (VSI) specifications for SST.  
The parameters of a high frequency transformer, simulated using ANSYS/Maxwell software, tabulated in Table 4, were used in MATLAB/Simulink to carry out the simulation of SST.
## 4 Sensitivity Analysis
### K Factor  
The k factors are fed into the PAV sizing tool calculation, in this case with the calculated weight and drag force as weighted parameters. Additionally, a k factor sensitivity analysis enables us to analyze how each k factor affects the design space. Accordingly, the k-factor sensitivity analysis can help decision makers during the PAV design process find the proper technologies that contain the best combinations of technologies. In this study, a k-factor sensitivity analysis was conducted with 19 factors that could have an impact on the optimized design results. The lower and upper bounds for the k factors were correspondingly defined with negative and positive 10% intervals. As a result, 12 factors were finally chosen after considering the sensitivity results. The selected factors are as follows: the combustion engine Specific Fuel Consumption (SFC), combustion engine weight, propulsion efficiency, structure weight, landing gear weight, car system weight, cabin weight, morphing mechanism weight, electronic weight, parachute weight, induced drag, and friction drag. Based on the observations from the k-factor sensitivity analysis, here are the findings. (i) As the \"combustion engine SFC\" factor increases, the MTOW/wing span/wing root chord value increases while the power-to-weight ratio/fuel efficiency decreases. (ii) As the \"combustion engine weight\" factor increases, the MTOW/wing span/wing root chord value increases while the power-to-weight ratio/fuel efficiency decreases. (iii) As the \"propulsion efficiency\" factor increases, the MTOW/wing span/wing root chord/power-to-weight ratio decreases while the fuel efficiency increases. (iv) As the \"structure weight\" factor increases, the MTOW/wing span/wing root chord value increases while the power-to-weight ratio/fuel efficiency decreases. As can be seen, the factors related to the weight (i.e., the \"combustion engine weight\" and the \"structure weight\") have identical tendencies as the k factors are varied. (v) As the \"induced drag\" and \"friction drag\" increase, the MTOW/wing span/wing root chord/power-to-weight ratio increases while the fuel efficiency decreases. All of these results are shown in Figures 14 and 15.  
Figure 13: Technology sensitivity analysis: deviation from optimal fuel efficiency target value.
## 2 Computational Framework
### Governing Equations and Solution Details
The rotating domain contained a cylinder-type boundary, and the central axis which was coincident with the rotational axis of the propeller. The height and radius of the rotational domain were determined based on the propeller diameter (\(\text{D}_{\text{ia}}\)), indicating 2.55\(\text{D}_{\text{ia}}\) and 7.6\(\text{D}_{\text{ia}}\), respectively. The stationary domain, on the other hand, was set as a cubic block with a distance being roughly about 12.75\(\text{D}_{\text{ia}}\), 20.5\(\text{D}_{\text{ia}}\), and 12.75\(\text{D}_{\text{ia}}\) for upstream, downstream, and height, respectively; see Figure 1e,f. Structured mesh for both rotational and statiional domain was generated, shown in Figure 1a,b. Mesh with high quality was considered and generated due to the importance of interpolation relationship between the interface surfaces, and a mapped mesh topology was proceeded between the interface boundaries. For the rotating domain, two O-topologies were created to cover the propeller and the center spinner segments. The O-grid included 10 cells normal to the propeller wall surface with a first cell distance of 2 \(\times\) 10\({}^{-5}\) m. There were 30 grid points in propeller radial direction and 56 grid points in the circumferential direction. A cylindrical wake block was used to ensure a good resolution of the blade wakes and the tip vortices, which have a significant influence on the MAV domain. For the outer domain, a similar mesh topology as we showed in the validation case section was used. The total size of the mesh was about \(8\times 10^{6}\) nodes. The standard characteristic boundary conditions were applied on the farfield boundaries. For the case of low Reynolds number flow, total pressure, incoming freestream velocity, freestream turbulent intensity (\(T_{i}\)), and the turbulence length scale were imposed  
Figure 1: Non-conformal mesh interface for propeller MAV geometry, (**a**) propeller-MAV configuration, (**b**) detailed structured mesh for propeller-MAV, (**c**) Mesh slice cut though domains, (**d**) propeller structured mesh, (**e**) computational domain in front view, and (**f**) computational domain in side view. at the inlet, whereas pressure was prescribed at the outlet boundary. Furthermore, at the solid wall, the non-slip boundary condition was applied. The turbulent kinetic energy was set to zero, and the pressure on the wall had zero normal gradients. High performance computing (HPC) with a parallel-processing implementation over 48 partitions and efficient message-passing interface between the partitions was adopted.
###### Abstract  
Low-power wide-area network (LPWAN) technologies play a pivotal role in IoT applications, owing to their capability to meet the key IoT requirements (e.g., long range, low cost, small data volumes, massive device number, and low energy consumption). Between all obtainable LPWAN technologies, long-range wide-area network (LoRaWAN) technology has attracted much interest from both industry and academia due to networking autonomous architecture and an open standard specification. This paper presents a comparative review of five selected driving LPWAN technologies, including NB-IoT, SigFox, Telensa, Ingenu (RPMA), and LoRa/LoRaWAN. The comparison shows that LoRa/LoRaWAN and SigFox surpass other technologies in terms of device lifetime, network capacity, adaptive data rate, and cost. In contrast, NB-IoT technology excels in latency and quality of service. Furthermore, we present a technical overview of LoRa/LoRaWAN technology by considering its main features, opportunities, and open issues. We also compare the most important simulation tools for investigating and analyzing LoRa/LoRaWAN network performance that has been developed recently. Then, we introduce a comparative evaluation of LoRa simulators to highlight their features. Furthermore, we classify the recent efforts to improve LoRa/LoRaWAN performance in terms of energy consumption, pure data extraction rate, network scalability, network coverage, quality of service, and security. Finally, although we focus more on LoRa/LoRaWAN issues and solutions, we introduce guidance and directions for future research on LPWAN technologies.  
IoT; LPWAN; LoRa; LoRaWAN; LoRa simulation tools +
Footnote †: journal: Electronics Letters  
_et al._