esa-sceva/satcom-chunk-collection huggingface dataset:
# A Quantum-Resistant FHE Framework for Privacy-Preserving Image Processing in the Cloud
## 4 Experimental Evaluation
### Security Analysis
#### 4.7.2 Security of the Homomorphic Computation  
Computational privacy against the honest-but-curious server (\(\mathcal{A}_{cloud}\)) is provided by the FHE scheme.  
IND-CPA Security  
The CKKS scheme is IND-CPA secure, assuming the hardness of the Ring Learning with Errors (R-LWE) problem, which is also widely believed to be post-quantum secure [5]. The client-centric key model ensures that the server never possesses the secret key required to break this security.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Framework** & **Quantum Safe** & **Comp. Private** & **Setup (ms)** & **Per Image (ms)** & **Key Limitation** \\ \hline Plaintext Baseline & No & No & – & \(0.12\pm 0.01\) & No privacy protection \\ TLS 1.3 + Server & No & No & \(4.2\pm 0.8\) & \(0.51\pm 0.05\) & Server sees plaintext \\ PQC-TLS + Server **\({}^{**}\)** & Yes & No & \(8.9\pm 1.2\) & \(0.78\pm 0.08\) & Server sees plaintext \\ SEAL (Pixel-wise) \(\ddagger\) & Yes \$ & Yes & \(45\pm 5\) & \(2847\pm 215\) & No SIMD batching \\ Approximate FHE \(\ddagger\) & Yes \$ & Yes & \(52\pm 6\) & \(156\pm 18\) & Limited to approximations \\ Our Framework & Yes & Yes & \(285\pm 22\) & \(18.6\pm 2.1\) & Higher setup cost \\ \hline \hline \end{tabular}  
* Using Kyber-512 for the post-quantum key exchange. \(\ddagger\) Implemented in Microsoft SEAL 3.6 with per-pixel encryption. \$ Transport layer may use post-quantum cryptography, but FHE operations assume classical security. \(\ddagger\) Estimated from CKKS SIMD operations in SEAL with reduced precision.  
\end{table}
Table 4: Performance comparison of privacy-preserving image processing frameworks for brightness adjustment on 64 x 64 grayscale images.  
Preservation of Indistinguishability  
A key requirement for IND-CPA security is that the encryption scheme must be probabilistic. The CKKS encryption process meets this requirement by incorporating a small, freshly sampled error term into every new ciphertext. This ensures that, even if the same image vector were encrypted multiple times, the resulting ciphertexts would be different and computationally indistinguishable. Homomorphic operations themselves are deterministic functions (e.g., adding two ciphertexts always produces the same resultant ciphertext), but since they operate on inputs that are already indistinguishable, the final encrypted result does not leak information about the specific underlying plaintexts. This property is fundamental to how FHE provides computational privacy.  
Practical Considerations  
A practical threats like side-channel attacks must be considered. Our framework mitigates this risk by relying on high-level libraries like TenSEAL, which benefit from constant-time implementation practices in their underlying backends [22]. This, combined with high-security parameters to make decryption failures negligible, provides a robust defense in practice.
# A Statistical Approach for Modeling Individual Vertical Walking Forces
## 5 Simulation of Human-Induced Vibrations
### Footbridge Parameters  
The footbridge is modeled as a simply-supported beam 50 m long and 3 m wide with a linear dynamic behavior. Only the contribution of the fundamental mode, namely the first bending mode with a half-sine mode shape, is taken into account. The damping ratio \(\xi_{1}\) and the modal mass \(M_{1}\) are, respectively, 0.04% and \(25\times 10^{3}\) kg, while the natural frequency \(f_{1}\) is assumed to vary from 0.1 Hz to 8.0 Hz with step 0.01 Hz. Since the case study is a one-dimensional problem, the pedestrian is assumed to walk on the footbridge centerline. Hence, in this case, the step direction \(\theta\) is equal to zero, and the step length \(l\) represents the distance between two successive heel-strikes projected on the footbridge centerline. Note that this assumption would not be appropriate if a torsional mode contributed to the structural response.
# A Direction-Sensitive Microwave Sensor for Metal Crack Detection
## 1 Introduction
The achieved depth and width sensitivity are 57.5 MHz/mm and 77.5 MHz/mm, respectively. In [20], the article presents a methodology for SHM using a passive microwave sensor, which uses the signal phase shift to realize crack detection. The microstrip sensors listed above have different performances in crack detection, but all those sensors are also not sensitive to crack direction. Therefore, to solve this problem, the direction detection of metal crack will be studied and realized in this paper. In addition, for the conventional microstrip patch sensor, there is a deficiency that the metal cracks need to be placed in the center region of a patch, because of the nonuniform current distribution. In [21], a metal crack sensor based on a highly conductive flexible graphene film is proposed. The sensor is designed based on conformal microstrip antenna composed of a flexible graphene film radiation patch and a flexible dielectric substrate. This sensor exhibited a detection sensitivity of 36.82 MHz/mm demonstrated by both experimental and simulation results. Additionally, the direction information can be reflected by the change in resonant frequency of sensor, but cannot be quantified. Due to nonuniform current distribution, the crack sensor must be arranged at the center region of the sensor patch. To summarize, presently there are few state-of-the-art works on the crack direction detection for microwave sensors. Additionally, it is significant to improve the current distribution of microstrip patch sensor for crack detection in practical application. Aiming at these problems, a direction-sensitive microwave sensor for metal crack detection is proposed in this paper. The presented sensor employs the dual-port coupled feeding to improve the current distribution and excite vertical and horizontal polarization current, respectively. The mutually perpendicular currents mean that the proposed sensor has direction sensibility for crack detection on the metal surface. The presented sensor can avoid the disadvantage of blind region for detection, compared with single-port crack detection sensor, which is able to improve the sensibility for detecting crack direction. In this paper, various nondestructive detection methods are described and compared at first. Then, the equivalent circuit model is established to analyze the working principles of the proposed sensor, and electromagnetic simulation experiments are conducted to analyze the influence of crack's dimensions. Lastly, the proposed sensor is fabricated, and experimentsare carried out to verify the simulation results. The structure of the paper is arranged as follows. The sensor design is described detailly in Section 2. Simulation studies are discussed in Section 3. Section 4 shows the experimental results of the proposed sensor. Finally, the conclusion is presented in Section 5.
## 2 Structure and Methods  
Figure 1 illustrates a schematic view of the proposed surface-enhanced infrared sensor employing angle-tunable narrowband absorber, where a patterned dielectric grating strips array is resting on a thick metal (aluminum) film. The material of the dielectric grating can be CaF\({}_{2}\), which has no substrate phonon effect in the considered infrared regime, and the material of the substrate is Si. Here, aluminum is used because the small absorption coefficient that leads to a narrower absorption as compared to gold and silver [32]. As a transverse magnetic (TM) polarized light irradiates upon the metasurface with an angle of \(\theta\) (\(0^{\circ}\leq\theta<90^{\circ}\)), dielectric guide mode resonance can be excited at the resonant wavelength, and the energy stored in the excited guided-mode resonance is efficiently absorbed by the metal layer, yielding a peak in the absorption spectra. Such a resonant peak is sensitive to the refractive index change around the dielectric grating. The refractive index change of surrounding analytes would induce a wavelength shift (\(\Delta\lambda\)) in the absorption spectrum, which enables us to detect the refractive index of the surrounding analytes, as shown in the schematic diagram in Figure 1. Moreover, this resonant peak also can be tuned (from \(\lambda_{1}\) to\(\lambda_{3}\)) to overlap with the molecular vibrational mode by adjusting the incidence angle (from \(\theta_{1}\) to \(\theta_{3}\)), so as to selectively identify the vibrational mode of analyte. The combination of these features exhibits great potential application of our device for the infrared refractive index sensing and surface-enhanced infrared absorption spectroscopy in a single substrate.  
Simulations are performed employing finite element software COMSOL Multiphysics to investigate the absorption properties of the dielectric-metal metasurface narrowband absorber and its application in RI sensing and SEIRAS. The periodic boundary condition is used in the x-direction, while the perfectly matched layers and scattering boundary conditions are applied in the z direction at two ends of computational space. The Figure S1 shows the cross-section view of the absorber in COMSOL. A TM polarized light with an electric field intensity of 1V/m vertically irradiates upon the structure. In the simulations, the dielectric grating strip array has a period of P, width of W, height of H, and refractive index of \(\rm n_{g}\). The refractive index of aluminum comes from Ref [33].
## 3 Perception of the User in the Environment: Methodologies and Technologies for Localization
### Technologies for Localization  
Some technologies providing localization services are already consolidated on the market, such as WiFi, Bluetooth, ZigBee, and UltraWide Band (UWB); in addition, emerging technologies, like SigFox, LoRa, IEEE 802.11 ah and Weightless, are gaining interest. The IEEE 802.11 standard, known also as WiFi, was conceived for providing network capabilities and Internet connection to different devices. The initial reception range was about 100 m increased to about 1 km by the IEEE 802.11 ah. The aforementioned RSS, CSI, ToF and AoA techniques (alone or in combined form) allow WiFi-based localization systems [22; 23; 24]. The latest version of Bluetooth (Bluetooth Low Energy--BLE), can be used with RSSI, AoA, and ToF for localization. Two BLE based protocols have been proposed for proximity-based services--iBeacons proposed by Apple and Eddystone proposed by Google. IBeacons transmit signals (beacon) at periodic intervals, by RSSI the proximity is classified into immediate (<1 m) near (1-3 m), far (>3 m) and unknown. Zigbee is based on IEEE 802.15.4 standard, it defines the higher levels of the protocol stack, and it is exploited in wireless sensor networks (WSN). Although it is favorable for localization of sensors in WSN, it is not readily available on the majority of the user devices, as a consequence, it would be preferable for users to use a personal device such as a smartphone both for pandemic and for cheapness, it is considered not suitable for indoor localization [25]. The Ultra Wide Band (UWB) technology is based on ultra short-pulses with a time period lower than 1 ns. It is attractive for indoor localization since it is relatively immune to interferences due to other signals and exhibit a low power consumption; despite this, it has limited use in consumer products and portable user devices [26; 27]. The Visible Light Communication (VLC) uses light sensors by LEDs behaving like iBeacons; on the other hand, a sight line is necessary between LED and sensors [28; 29]. The acoustic signal technique shows a potential advantage since it can exploit the smartphones sensors to receive signals by sources and can use the ToF technique. However, the low emission level to be respected to avoid sound pollution and the energy consumption limit the use. The problem of sound pollution is solved by ultrasound-based localization but limitations due to the degradation of the signal with humidity and temperature (contrarily to RF) remain [30].
# Resource Management in Cloud Radio Access Network: Conventional and New Approaches
## 4 Challenges and Open Research Issues
### User Mobility  
User mobility has a remarkable impact on resource management in C-RANs. Understanding user mobility is highly important for resource optimization and algorithm evaluation in mobile network planning and handover mechanisms [64]. The virtualized BBUs in a C-RAN require resources based on the mobility of the users in the network. Therefore, the disregard of user mobility in the problem while managing resources may result in an inefficient solution. A few mobility-aware resource management mechanisms have been proposed for C-RANs. In [49], a location and mobility-aware clustering and packing algorithm were designed for virtual BBU clustering and placement, to minimize resource consumption.  
In the future, researchers can design a user mobility-aware clustering algorithm for BBU or RRH clustering in a C-RAN from a load balancing perspective. Moreover, machine learning techniques can be applied for user mobility prediction such that resource allocation can be performed according to the prediction.
# Hybrid FSK-FDM Scheme for Data Rate Enhancement in Dual-Function Radar and Communication
###### Abstract  
In this paper, we present a hybrid frequency shift keying and frequency division multiplexing (i.e., FSK-FDM) approach for information embedding in dual-function radar and communication (DFRC) design to achieve an improved communication data rate. Since most of the existing works focus on merely two-bit transmission in each pulse repetition interval (PRI) using different amplitude modulation (AM)- and phased modulation (PM)-based techniques, this paper proposes a new technique that doubles the data rate by using a hybrid FSK-FDM technique. Note that the AM-based techniques are used when the communication receiver resides in the side lobe region of the radar. In contrast, the PM-based techniques perform better if the communication receiver is in the main lobe region. However, the proposed design facilitates the delivery of information bits to the communication receivers with an improved bit rate (BR) and bit error rate (BER) regardless of their locations in the radar's main lobe or side lobe regions. That is, the proposed scheme enables information encoding according to the transmitted waveforms and frequencies using FSK modulation. Next, the modulated symbols are added together to achieve a double data rate using the FDM technique. Finally, each transmitted composite symbol contains multiple FSK-modulated symbols, resulting in an increased data rate for the communication receiver. Numerous simulation results are presented to validate the effectiveness of the proposed technique.  
spectrum sharing DFRC; FSK-FDM DFRC; DFRC information embedding; DFRC waveform design; waveform diversity; frequency diversity; joint waveform and frequency; frequency division multiplexing 202323540. [[https://doi.org/10.3390/s23125440](https://doi.org/10.3390/s23125440)]([https://doi.org/10.3390/s23125440](https://doi.org/10.3390/s23125440))
# ChatGPT as a Virtual Dietitian: Exploring Its Potential as a Tool for Improving Nutrition Knowledge
## 3 ChatGPT as a Nutrition Tool
### What Are the Features of Nutrition Applications That ChatGPT Can or Cannot Emulate?
#### 3.1.6 Assessment Tools and Calculators  
Assessment tools and calculators are also essential features of nutrition applications because they provide users with personalized insights, guidance, and a quantifiable understanding of their dietary habits. These tools can evaluate nutrient intake, identify deficiencies or excesses, and suggest appropriate adjustments. Additionally, they assist users in determining their daily calorie requirements, macronutrient distribution, and body mass index. ChatGPT possesses the capability to emulate these functions by replicating the underlying algorithms and formulas used in assessment tools and calculators. For example, ChatGPT can calculate the Total Daily Energy Expenditure by considering parameters such as height, weight, age, gender, and activity level, as shown in the given prompt:  
**Sample prompt**: \"I am interested in knowing the number of calories I burn in a day. Here are my details: I am 31 years old, male, with a height of 177 cm and a weight of 92 kg. Additionally, I would describe my activity level as very active. While you are at it, how much food should I eat in day to safely lose weight?\"
# Random Access for Underwater Acoustic Cellular Systems
## 3 RAP Design
### Proposed RAP
#### 3.2.2 Proposed RAP 2
The upper bound value and maximum magnitude are symmetric about the origin because they both depend only on the parameters (\(\Delta\beta\), \(\tau\)). On the positive side of \(\Delta\beta\), \(\beta_{c}\) is set to \(\beta_{0}\) and \(\beta_{d}\) is a variable selected from the set \(\mathbb{S}_{P}\), whereas \(\beta_{c}=-\beta_{0}\) and \(\beta_{d}\in\mathbb{S}_{N}\) on the negative side of \(\Delta\beta\). Figure 11: Upper bound and maximum value of CAF of RAP 2. Figure 12 shows the number of possible RAPs in RAP 2, obtained using (20), when the value of \(\Delta\beta\) varies for three different values of \(\beta_{0}\). As shown in this figure, the number of possible RAPs decreases with the increase of \(\Delta\beta\). For example, the number of possible RAPs is approximately 16 when \(\Delta\beta\) is 0.5 kHz. In this case (\(\Delta\beta\) = 0.5 kHz), the maximum value of CAF can be obtained from Figure 9 as 16%, 11%, and 7.5% for symbol durations of 125, 25 and 50 ms, respectively. Notably, the number of possible RAPs in (20) or Figure 10 corresponds to the case where only \(\Delta\beta\) is considered. The number of RAPs increases when the frequency shift parameter is also considered. If we re-calculate the number of RAPs by considering \(\Delta f=\beta_{c}\leq B/3\) in (21) with the same value of \(\beta_{0}\) (0.5 kHz), we can obtain eight additional RAPs. The first six RAPs are generated with \(\beta_{c}\) = 0.5 kHz and \(|f_{c}|\in\{0.5,\,1,\,1.5\}\) kHz, and the remaining two RAPs are generated with \(\beta_{c}\) = 1 kHz and \(|f_{c}|=1\) kHz. In total, we can obtain 24 different RAPs when \(\Delta\beta\) = 0.5 kHz. The number of RAPs that can be generated from an LFM waveform is given by:  
\[\kappa(\Delta\beta)=2\bigg{(}\frac{B-\beta_{0}}{\Delta\beta}+1\bigg{)} \tag{20}\]  
where \(\Delta\beta\) can be determined from either Figure 9 or the upper bound in (19) as follows:  
\[\Delta\beta=4\frac{a_{C}^{2}+a_{S}^{2}}{\tau\tau\Gamma^{2}(\tau,\Delta\beta)}, \Gamma^{2}(\tau,\Delta\beta)>0 \tag{21}\]  
In summary, the cross-correlation level in the CAF of RAP 2 varies depending on the selection of \(\Delta\beta\) and \(\tau\). By increasing the values of \(\Delta\beta\) and \(\tau\), we can reduce the cross-correlation level between the RAPs. However, the number of possible RAPs decreases with the increase of \(\Delta\beta\). Therefore, when RAP 2 is designed, there is a trade-off between the cross-correlation level and number of RAPs in selecting the value of \(\Delta\beta\).
# Improved ADRC-Based Autonomous Vehicle Path-Tracking Control Study Considering Lateral Stability
## 5 Results and Discussion
### Validation of Controller Effectiveness without Disturbance  
#### 5.1.1 IADRC Controller Validation  
Figures 7 and 8 show the path-tracking result and heading-angle-tracking result; it can be seen that the vehicle controlled by all three controllers are able to follow the desired path precisely. Figures 9 and 10 show the lateral deviation and heading error of the vehicle; we can see that the lateral deviation and heading error of the vehicle are controlled within a smaller range. Moreover, from Table 2, it can be seen that the maximum (absolute value,  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Symbol** & **Parameters** & **Value and Units** \\ \hline \(m\) & Vehicle total mass & 1610 kg \\ \(l_{z}\) & Moment of inertia & 2410 kg\(\cdot\)m\({}^{2}\) \\ \(C_{f}\) & Cornering stiffness of front wheel & 66,900 N/rad \\ \(C_{r}\) & Cornering stiffness of rear wheel & 62,700 N/rad \\ \(h_{cg}\) & Height of the vehicle center of mass & 0.65 m \\ \(l_{f}\) & Front wheel base & 1.05 m \\ \(l_{r}\) & Rear wheel base & 1.51 m \\ \(t_{w1}\) & Track width of the front wheels & 1.565 m \\ \(t_{w2}\) & Track width of the rear wheels & 1.565 m \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of the autonomous vehicle.  
Figure 5: CarSim/Simulink cosimulation structure diagram.  
Figure 6: Desired responses of double-lane change maneuver.  
same below) and root mean square (RMS) values of lateral deviation and heading error of these three controllers are not very different, among which, the value of IADRC lateral deviation is the smallest with a maximum value of 0.1840 and an RMS value of 0.0593.  
Figure 8: Heading-angle tracking result.  
Figure 10: Heading error.  
Figure 7: Path-tracking result.  
Figure 9: Lateral deviation.  
Figure 11 shows the front-wheel steering angle. It can be seen that the wheel steering angle decided by the LQR controller is small; the front-wheel steering angle decided by the ADRC controller has the phenomenon of jittering from about the fourth to the fifth second--the wheel steering angle input is not smooth; while for the IADRC controller proposed in Section 3, because it uses a nonlinear function with continuity, as shown in Equation (14), the wheel steering angle is smooth and the control input jittering phenomenon is solved.  
Therefore, according to these simulation results, it can be concluded that the IADRC controller proposed in this paper has higher control performance; the IESO proposed in this paper is able to solve the jittering problem of the control input, and the nonlinear function proposed in this paper is valid.
## 4 End-to-End SNR Correlation Analysis
However, for Nakagami-\(m\) fading channels, \(\eta_{k,l_{k}}\) is affected by \(\rho_{k,n}\)'s as well as \(m_{k,n}\)'s, as seen in Equations (6) and (12).