esa-sceva/satcom-chunk-collection huggingface dataset:
# An Outdoor Navigation System for Blind Pedestrians Using GPS and Tactile-Foot Feedback
## 1 Introduction
Furthermore, both are the icons of a blind pedestrian, which is useful for getting assistance from other pedestrians. Some limitations of the white cane involve a limited range of scanning (1-2 m) and no overhanging obstacle detection, while the constant care and high cost of guide dogs may not suit every blind pedestrian. Unfortunately, both the white cane and guide dog are only meant for obstacle detection and still need to be complemented with another device that addresses the orientation process [20]. Decades of research and a wide assortment of academic prototypes and commercial products have shown that any attempt to replace the primary aids in the obstacle detection task has failed. One should wonder if it would be more pertinent to design complementary systems to the primary aids rather than to keep trying to replace them. This paper introduces a novel outdoor navigation assistive system that is a complement to the primary aids by trusting them with the immediate environment sensing. Localization is conducted by GPS data provided by a smartphone, which are processed in the context of spatial databases for the computation of optimal routes of travel. Guidance is achieved by mechanotactile sensations that the system delivers to the foot to identify the navigational directions to follow. This device addressesthe four aforementioned major challenges of navigation assistive devices: (1) the obstacle detection process is conducted through the traditional and successful haptic feedback provided by the white cane or dog; (2) tactile feedback is used to prevent user distraction from the environment; (3) such tactile feedback is simple, fast to understand, and provides small amounts of meaningful information, which reduces learning and training times; and (4) the system is totally wearable. The rest of the paper is organized as follows: Section 2 reviews relevant related work on complete navigation assistive systems integrating GPS and audio and haptic feedback. Section 3 presents a technical overview of the proposed system, while Section 4 presents a set of experiments that demonstrate the effectiveness of the prototype and the initial feasibility of the approach. Finally, the Conclusion summarizes the main contributions and gives future work perspectives.
## 2 Research Methodology
### General System
#### 2.3.2 Edge Servers  
The edge servers are located at the edge of the network. The benefit of the edge server is being close to the end-users, reducing latency and improving performance. They are typically used to cache content and deliver it to users without having to fetch videos from  
Figure 1: Proposed system components.  
a more distant server. The configuration of edge servers can vary depending on the specific requirements for a particular application or service. The edge servers have been configured according to two mechanisms. In the first mechanism, a copy of the video is to be stored and each edge server is aware of the availability of the video content over the other servers by considering the synchronization mechanism. In the second mechanism, these edge servers will take the responsibility of replying to the client's request with the requested video content. These servers have also been configured to listen to the broadcast of FASP, File Catalyst protocol, and Signiant protocols from the original servers.
## 3 Wireless Body Area Network (WBAN)
### Blood pressure sensors  
Blood pressure sensors measure and monitor blood pressure levels by detecting the pressure exerted by blood flow in the arteries. Modern blood pressure sensors often employ an oscillometer, which measures the pressure changes caused by the pulsatile flow of blood. The sensor inflates the cuff to restrict blood flow temporarily and then gradually deflates it while monitoring the pressure changes. The sensor can determine systolic and diastolic blood pressure values based on these measurements [51].  
Various types of blood pressure sensors are available, including those designed for home use, clinical settings, and wearable devices. Some sensors may connect to smartphones or other devices for data storage and analysis. It is always a good idea to consult a healthcare professional for advice on selecting and using blood pressure sensors, as accurate measurements and proper technique are essential for monitoring and managing blood pressure effectively. Alternative methods use biological sensors such as ECG and PPG sensors to estimate blood pressure without a cuff [52].
# A Crypto-Steganography Approach for Hiding Ransomware within HEVC Streams in Android IoT Devices
###### Abstract  
Steganography is a vital security approach that hides any secret content within ordinary data, such as multimedia. This hiding aims to achieve the confidentiality of the IoT secret data; whether it is benign or malicious (e.g., ransomware) and for defensive or offensive purposes. This paper introduces a hybrid crypto-steganography approach for ransomware hiding within high-resolution video frames. This proposed approach is based on hybridizing an AES (advanced encryption standard) algorithm and LSB (least significant bit) steganography process. Initially, AES encrypts the secret Android ransomware data, and then LSB embeds it based on random selection criteria for the cover video pixels. This research examined broad objective and subjective quality assessment metrics to evaluate the performance of the proposed hybrid approach. We used different sizes of ransomware samples and different resolutions of HEVC (high-efficiency video coding) frames to conduct simulation experiments and comparison studies. The assessment results prove the superior efficiency of the introduced hybrid crypto-steganography approach compared to other existing steganography approaches in terms of (a) achieving the integrity of the secret ransomware data, (b) ensuring higher imperceptibility of stego video frames, (3) introducing a multi-level security approach using the AES encryption in addition to the LSB steganography, (4) performing randomness embedding based on RPS (random pixel selection) for concealing secret ransomware bits, (5) succeeding in fully extracting the ransomware data at the receiver side, (6) obtaining strong subjective and objective qualities for all tested evaluation metrics, (7) embedding different sizes of secret data at the same time within the video frame, and finally (8) passing the security scanning tests of 70 antivirus engines without detecting the existence of the embedded ransomware.  
Keywords:ransomware hiding; multimedia steganography; encryption; embedding; IoT; HEVC; AES; LSB; quality assessment; multi-level security; antivirus; confidentiality and integrity +
Footnote †: journal: _Sensors_
# Nonlinear Analysis and Closed-Form Solution for Overhead Line Magnetic Energy Harvester Behavior
## 4 The Basic Assumptions and the Equivalent Circuit  
As simple as the OLMEH's power processing circuit in Figure 1 may look, the nonlinear properties of the magnetic core and the rectifiers make an exact analysis prohibitive. Therefore, the following simplifying assumptions were adopted:  
1. Since clamping the OLMEH on the line does not change the line current, and since the output power drawn by the OLMEH is negligible in comparison to the power carried by the high voltage transmission line, the OLMEH can be considered as fed by a sinusoidal current source.
2. The hysteresis phenomenon is neglected and the nonlinearity of the core is modeled by the Froelich Equations (1) and (2).
3. A simplified cantilever model is adopted to represent the OLMEH magnetic circuit with a nonlinear magnetizing inductance, \(\mathrm{L_{m}}\), placed on the secondary winding, whereas the leakage inductance and the winding resistance are considered negligible.
4. Also, ideal rectifiers with no voltage drop and no reverse recovery are assumed.  
Figure 3: PSIM—generated comparison plot of the simulated BH curve vs. the Froelich approximation (1) (a); MATHCAD—generated Froelich Equation (1) vs. \(atan(\)*\()\) approximation, vs. the piecewise-linear approximation of the BH curve (b).  
The assumptions above lead to the OLMEH model illustrated in Figure 4a. The model was simulated in PSIM v 9.1. The key simulated waveforms shown in Figure 5 reveal the intricate details of OLMEH operation.
## 3 Quality Control of Silicon Carbide Printed Part Formation
### The Impact and Control of Key Printing Parameters on Green Part Formation Quality
#### 3.1.1 Nozzle-Clogging Issues
This indicates that, under jetting pressure, high viscous dissipation prevents droplet ejection and significantly increases the likelihood of nozzle clogging. Conversely, when Z > 10, insufficient viscous forces result in continuous jetting phenomena, leading to satellite droplet formation behind the primary droplet, which may cause nozzle clogging or reduced resolution on the powder bed surface. Consequently, binders are considered unsuitable for printing when the Z parameter falls within either of these two ranges.
# Smart Infrastructure and Additive Manufacturing: Synergies, Advantages, and Limitations
## 2 3D Printing in Smart Infrastructure: An Overview
### Examples of 3D-Printed Infrastructure Components
The 3D Print Canal House project in Amsterdam, a collaborative effort between architects, engineers, and 3D printing experts, explored the potential of 3D printing in architecture and urban design [72]. The project involved the creation of a large-scale canal house and various urban furniture elements, such as benches and planners. By utilizing 3D printing, the project was able to produce highly sophisticated, customized designs that were both functional and visually appealing. One of the key innovations of the project was the use of the Kamermaker, a large-scale, mobile 3D printer capable of fabricating architectural components in situ. This approach reduced transportation costs and emissions while demonstrating the potential for decentralized, on-demand manufacturing for urban infrastructure. Similarly, the Bluecycle project in Piraeus, Greece, exemplifies the use of 3D printing to create sustainable urban furniture from recycled raw materials such as abandoned fishing nets [73]. By transforming waste into durable public furniture, Bluecycle contributes to both environmental sustainability and urban beautification, reinforcing the potential for 3D printing to support circular economy in urban development. These examples illustrate the diverse applications of 3D printing in infrastructure, highlighting its capacity to aid construction practices by enabling complex designs, reducing raw material waste, and accelerating project timelines.
###### Abstract  
The aim of this study is to determine what loads are likely to be applied to the head in the event of a horse falling onto it and to determine by how much a typical equestrian helmet reduces these loads. An instrumented headform was designed and built to measure applied dynamic loads from a falling horse. Two differently weighted equine cadavers were then dropped repeatedly from a height of 1 m (theoretical impact velocity of 4.43 m/s) onto both the un-helmeted and helmeted instrumented headforms to collect primary force-time history data. The highest mean peak loads applied to the headform by the lighter horse were measured at the bony sacral impact location (\(15.57\leavevmode\
obreak\ \mathrm{kN}\pm 1.11\leavevmode\
obreak\ \mathrm{SD}\)). The lowest mean peak loads were measured at the relatively fleshier right hind quarter (\(7.91\leavevmode\
obreak\ \mathrm{kN}\pm 1.84\leavevmode\
obreak\ \mathrm{SD}\)). For the heavier horse, highest mean peak loads applied to the headform were measured at the same bony sacral impact location (\(16.02\leavevmode\
obreak\ \mathrm{kN}\pm 0.83\leavevmode\
obreak\ \mathrm{SD}\)), whilst lowest mean peak loads were measured at the more compliant left hind quarter (\(10.47\leavevmode\
obreak\ \mathrm{kN}\pm 1.08\leavevmode\
obreak\ \mathrm{SD}\)). When compared with the un-helmeted mean values, a reduction of \(29.7\%\) was recorded for the sacral impact location and a reduction of \(43.3\%\) for the lumbosacral junction location for helmeted tests. Notably, all measured loads were within or exceeded the range of published data for the fracture of the adult lateral skull bone. Current helmet certification tests are not biofidelic and inadequately represent the loading conditions of real-world \"lateral crush\" accidents sustained in equestrian sports. This work presents the first ever evidence basis upon which any future changes to a certification standards test method might be established, thereby ensuring that such a test would be both useful, biofidelic, and could ensure the desired safety outcome.  
skull fracture; dynamic crush; lateral crush; roll over; head protection
# Numerical Study of Mixed Convection and Heat Transfer in Arc-Shaped Cavity with Inner Heat Sources
## 3 Results and Discussion
### Heat Transfer
\(T_{m}\) changes slightly in the range of Re from 6.15 \(\times\) 10\({}^{6}\) to 1.14 \(\times\) 10\({}^{7}\). When Re ranges from 1.14 \(\times\) 10\({}^{7}\) to 1.18 \(\times\) 10\({}^{7}\), the mean temperature rises sharply, corresponding to Figure 6g. \(T_{m}\) continues to decrease as Re increases, \(T_{m}\)\(\sim\) -6.4 \(\times\) 10\({}^{-5}\)Re. In conclusion, the high-temperature region between the two heat sources has a significant heat removal effect in the range of Re from 6.15 \(\times\) 10\({}^{6}\) to 1.14 \(\times\) 10\({}^{7}\). Figure 10 shows the change curve of effective heat coefficient \(m\) with Re. When Re is less than 6.14 \(\times\) 10\({}^{6}\) (the flow is turbulent), the effective heat coefficient increases linearly with Re, \(m\)-0.039\(\rm{Re}\). In the range of Re from 6.15 \(\times\) 10\({}^{6}\) to 1.14 \(\times\) 10\({}^{7}\), the effective heat  
Figure 8: The change of the averaged Nu on the heat source wall with Re. Figure 9: The average temperature in the middle region of the two heat sources varies with Re. coefficient increases slowly. As Re increases from 1.14 \(\times\) 10\({}^{7}\) to 1.18 \(\times\) 10\({}^{7}\), \(m\) rises sharply. When Re exceeds 1.18 \(\times\) 10\({}^{7}\), \(m\) shows a slow rising state. When Re is greater than 1.39 \(\times\) 10\({}^{7}\), that is, when the flow enters the quasi-steady stage, \(m\) has a power function development with the increase in Re, \(m\)-2.45 Re\({}^{0.23}\). Figure 10 also shows that the heat removal capacity of the curved cavity structure generally increases with the increase in Re. Especially in the range of 1.14 \(\times\) 10\({}^{7}\) to 1.18 \(\times\) 10\({}^{7}\), the heat removal capacity presents a steep rise. In actual application, wind speed can be properly controlled to adjust Re to achieve the maximum benefit of waste heat removal.
# Biosynthesis of Edible Terpenoids: Hosts and Applications
## 3 Application of Terpenoid Microbial Cell Factories in the Food Industry
### Acting as Food Fortifiers and Dietary Supplements
#### 3.3.2 Steviol Glycos  
The increasing prevalence of diabetes and its harm to health promote people to pay more and more attention to low-sugar diets. The use of low-calorie sweeteners instead of sugar in the daily diet is becoming popular and important. In this scene, steviol glycosides (SGs), which are GRAS, have received widespread attention [122]. They are not only used as sweeteners but also act as nutritional enhancers in the diet of diabetic patients due to their anti-diabetic properties. SGs are a type of glycoside derivative of tetracycline triterpenoids with various sweetness and taste. In _Stevia rebuudiana_, more than 20 types of SGs are glycosylated by only four glycosyltransferases using steviol as a backbone skeleton [97]. In order to meet the demands for low-sugar and low-calorie diets, scientists are dedicated to producing special steviol glycosides via de novo synthesis or whole-cell catalysis using microbial chassis.  
Due to the complex glycosyltransferase pathway and numerous by-products, attention has been focused on exploring targeted modification of glycosyltransferases [98]. They adopted a strategy of combinatorial modular operation to assemble the stevioside de novo synthetic pathway into _S. cerevisiae_. In the precursor GGPP supply module, they overexpressed the key enzyme tHMG1 and downregulated ERG9 shunt pathways. In the steviol synthesis pathway, they used steviol as an indicator and fusion-expressed the class I diterpene synthase _At_KS and the class II diterpene synthase _Sr_CPS. In the transglycoside pathway, they combined directed evolution and fusion expression of two glycosyltransferases to synthesize stevioside. By further enhancing the supply of UDP-glucose, the final engineered strain produced stevioside at a titer of 1149 mg/L [97]. Rebaudioside M (Reb M) provides more sweet taste than stevioside and is free of bitterness. However, the concentration is significantly lower (0.4-0.5%) than stevioside (22-62%) in _Stevia rebaudiana_[122]. [PERSON] et al. constructed a whole-cell catalytic pathway for producing Reb M from stevioside. They identified an efficient glycosyltransferase, UGT91D2, and co-expressed it with UG76G1 to convert stevioside to Reb M via Red E. In order to inhibit the hydrolysis of stevioside and strengthen the supply of sugar donor UDP-glucose, they knocked out endogenous glycoside hydrolase SCW2 and overexpressed UGP1. After introducing SIR2 to prolong the growth cycle, they obtained a titer of 12.5 g/L Reb M by using 10.0 g/L stevioside as a substrate.
## 6 Discussion and Future Considerations
### Flight Control  
Estimation of the UAV traveling distance to accomplish a task [109] is an important aspect of measuring the efficiency of the UAV's trajectory, which impacts energy consumption; however, this has not been considered in existing works in the context of AoI minimization. Similarly, there is a need to improve existing algorithms for efficient autonomous flight control for different environmental conditions and accomplishing different missions. This makes learning-based methods for UAV control popular. They can learn from real-world experience to provide adaptive control. For instance, deep learning allows UAVs to effectively learn a pattern from navigation [109].
# Software-Defined Small Cell-Linked Vehicular Networks: Architecture and Evaluation
## 2 Related Works
### Small Cells-Linked RSU Paradigm for V2X Services  
Road side units (RSUs) are infrastructure communication nodes with vehicular networks. This implies that the vehicle must have access to road infrastructures via RSUs via V2I [20]. Furthermore, RSUs use wide area networks to forward received messages to ITS application servers. The number of RSUs deployed and their coverage has a large impact on vehicle communication. However, RSUs are unquestionably expensive to install and maintain; thus, there is a trade-off between full connectivity via RSUs and the deployment cost. To cover the increased cost of RSU deployment, road operators (ROs) can also use small cell architecture owned by mobile network operators (MNOs) to best fit the network densification or dedicated coverage that the control traffic management services hope to deploy. This may also be an economic consideration. For multi-operator coverage within a building, virtualized RSU and open radio access network (RAN) architecture will work best, enabling the flexibility of more capacity for ROs. In this situation, ROs are almost certainly expected to deploy and manage RSUs in the public sector [21]. Following that, the ROs can enter into commercial agreements with MNOs, who will undoubtedly deploy RSUs and run V2X services provided by ITS authorities [21]. Therefore, MNOs should make use of the existing 5G small cells infrastructure to support V2X applications among ultra-reliable low latency communication services, then motivate the efficient deployment of V2X services. Having a radio platform that can adapt and scale to support new V2X services is critical for ROs.
# Fusion of Telecommunications and IT Services Boosted by Application Programming Interfaces
## 1 Introduction  
The landscape of fixed and wireless telecommunications has changed extremely quickly over the past three decades. Communication Service Providers (CSPs) continuously face challenges when operating various hardware (HW) and software (SW) from different equipment manufacturers in their multi-functional and multi-layered networks. On the one hand, the introduction of innovative technologies and new services has transformed legacy systems into a more and more sophisticated network architecture. As an example, and without completeness, an evolving network scenario is shown in Figure 1. The network contains fixed and mobile subscriber access technologies and different core network types. Such a CSP network environment can simultaneously serve consumer, industrial, and enterprise subscribers requiring various wired and wireless services. In several countries, including Hungary, third-generation (3G) mobile sunset projects have already started to switch off 3G NodeBs (NBs) completely. Similarly, the Plain Old Telephone Service (POTS) fixed lines of legacy Public Switched Telephone Networks (PSTNs) are in practice being continuously replaced by mobile or fixed VoIP (Voice over IP) solutions. The complex meshed network of Figure 1 can be divided into three main parts: subscriber access; cell sites, controller nodes, and backhauling; and, finally, the core network (horizontal scale). The various subscriber access methods are fixed, nomadic, or mobile (vertical scale in Figure 1). Since the appearance of smart devices and with the growing demand for the IoT (Internet of Things) and machine-to-machine communications (M2M), subscriptions are growing enormously [1, 2]. Subscribers are not any longer only human users using the network for simple telephone voice calls. Industry, transportation, modern agriculture, education, medicine, robotics, etc. all require data connections [3, 4, 5, 6]. The User Equipment (UE, either fixed or mobile) at the end of the data links can be sensors, machines, metering devices, cameras, vehicles, robots, or any other remote-controlled equipment. A massiverollout of 5G (fifth-generation mobile systems, also called New Radio, NR) systems is already ongoing in several countries to serve these new demands. In Figure 1, 5G core and NR are marked in light blue, and phase-out technologies are marked in gray. On the other hand, deployments of new technologies and services always provide the inherent possibility of optimizing, modernizing, or merging network layers towards a converged or 'flattened' architecture. The convergence and simplification possibilities arise at different layers: at the equipment level (either HW or SW) and at the Network Element (NE) and network levels. Finally, as shown in this paper, convergence has started even at the services level. Several important trends have paved the way for service convergence in the past years.
## 3 Algorithm Validation
### Analysis of Results  
#### 3.2.1 High-Dimensional Unimodal Test Function  
The table shows the results of the 30 solutions for the high-dimensional, single-peak functions (F1-F3). For the single-peak test function, the IESSA algorithm obtains the optimal values of the test functions F1-F3 after zero iterations with a convergence accuracy and standard deviation of 0, which is significantly better than the SSA, GWO, PSO, and CSSOA algorithms. This fully demonstrates that IESSA can obtain more stable and accurate results when solving high-dimensional, single-peak functions. The convergence curve of the single-peak test function is also shown in the figure, and IESSA can quickly arrive at the optimal solution. The IESSA algorithm performs better when dealing with single-peaked test functions.