esa-sceva/satcom-chunk-collection huggingface dataset:
These algorithms have allowed more accurate and detailed analysis of thermal data to be obtained, making it possible to identify even small thermal anomalies that might otherwise have gone unnoticed. Another area of research is the development of new hardware for 3D-IRT, including cameras and sensors that are capable of capturing high-resolution thermal data from a building's exterior [24]. This has led to a greater understanding of the thermal behaviour of buildings, allowing for more accurate predictions of energy performance. However, unlike RGB images, thermal images pose greater difficulties for correlation algorithms. Thermal images generally contain far fewer textural elements than conventional visible-band images; therefore, the tie point detection algorithms incorporated in SfM-MVS photogrammetry programs can fail with thermal images in complex 3D environments [25]. In fact, apart from the other analyses mentioned above, the main objective of this study is to present a simple but efficient thermal image pre-processing methodology which, to the authors' knowledge, has never been applied before. With it, and despite the adverse conditions during the collection of images, which will be shown later, three-dimensional thermal models will be obtained that will demonstrate the advantages already mentioned. One area where 3D-IRT has yet to be fully explored is in the application of this technology for understanding structures such as wine cellars. The unique thermal properties of these structures make them difficult to analyse using traditional methods, and a more detailed understanding of their thermal behaviour could lead to improved energy efficiency and better preservation of stored wines. The aim of this study is to demonstrate how, by combining different techniques and tools--aerial photographs taken by low-cost thermal cameras on board a UAS, close-up images from hand-held cameras installed on a simple lifting device, development of three-dimensional thermal image models using photogrammetry, and installation of passive IR sensors--it is possible to detect thermal anomalies in building envelopes. Digital image pre-processing is proposed and applied to improve the 3D-IRT accuracy. These procedures will be specifically applied to the wine cellar described in the following section. The results of the study will demonstrate that it is possible to detect issues that could compromise the wine aging process as well as taking the necessary corrective measures. A 3D-IRT of the exterior of a wine cellar could provide valuable information on the thermal performance of the structure, including the location and extent of thermal bridges, areas of air leakage, and the presence of moisture in the walls. This information could then be used to make targeted improvements to the thermal envelope, leading to significant energy savings and improved wine storage conditions. Additionally, 3D-IRT could be used to monitor the thermal performance of the cellar over time, allowing for early detection of any issues that may arise.
# Building Equi-Width Histograms on Homomorphically Encrypted Data
###### Abstract  
Histograms are widely used for summarizing data distributions, detecting anomalies, and improving machine learning models' accuracy. However, traditional histogram-based methods require access to raw data, raising privacy concerns, particularly in sensitive IoT applications. Encryption-based techniques offer potential solutions; however, they secure the data in transit or storage, requiring decryption during analysis, which exposes raw data to potential privacy risks. In this paper, we propose a method for constructing privacy-preserving histograms directly on homomorphically encrypted IoT data, leveraging the Fast Fully Homomorphic Encryption over the Torus (TFHE) scheme implemented in the Concrete framework. To overcome the challenges posed by homomorphic encryption, we redesign the traditional histogram construction algorithm, optimizing it for secure computation by addressing constraints related to nested loops and conditional statements. As an evaluation use case, we have considered an outlier detection mechanism based on histogram frequency counts, ensuring that all data and computations remain encrypted throughout the process. Our method achieves results consistent with plaintext-based outlier detection while maintaining reasonable computational overhead compared to those reported in the existing literature.  
Keywords:histogram computation; histogram-based outlier detection; homomorphic encryption; internet of things; privacy +
Footnote †: journal:
## 3 Network Model
### QKD Protocol, Model and Related Definitions
First, for data packets that only require traditional encryption methods or no encryption at all, they do not need to pass through the QKD layer and can be directly processed at the traditional data layer. Therefore, they can choose the shortest path. Second, data packets encrypted using quantum keys generated by the BB84 protocol can only pass through backbone nodes and trusted relay nodes that utilize the BB84 protocol. Finally, data packets encrypted using quantum keys generated by the MDI-QKD protocol can only pass through backbone nodes, pairs of trusted relays, and untrusted relays located between the pairs of trusted relays that utilize the MDI-QKD protocol. 6. Time Slot: In the field of communications, a time slot is a unit of time used for the allocation and management of resources in multiplexing techniques. Time slots divide time into non-overlapping intervals, with each time slot designated for the transmission of specific data or signals. One of the advantages of using time-division multiplexing is the efficient utilization of transmission resources and shared bandwidth. By allocating time slots appropriately, different users or channels can transmit data simultaneously over the same physical link, thereby improving transmission efficiency. In the CPSR-HQKDN scheme, time slots primarily serve the purpose of calculating the remaining quantity of keys and various key rates, among others, in preparation for addressing the routing issues of data packets. Key Update Rate: In QKD technology, the key update rate refers to the number of newly generated key bits successfully generated within a unit of time. In this scheme, the key update rate is calculated based on the total number of key bits successfully generated and the total time taken. * Packet Encryption Request: Within the SDN network framework, a packet encryption request refers to a series of subsequent packet encryption requests issued by an application to the controller through the northbound interface. It plays a crucial role in determining the security requirements of the packets. The request involves a significant volume of packets, indicating that allocating resources for the current network will pose greater challenges and requires the comprehensive consideration of the existing network resource status.
## 2 Materials and Methods
### Metabolites Analysis with GC-MS  
DI-SPME samples were analyzed using an Agilent 8890 gas chromatograph (GC) coupled with an Agilent 5977B mass spectrometry detector (MSD) system in splitless mode. The HP-5 MS capillary column (30 m \(\times\) 0.25 mm, 0.25 \(\upmu\)m; Agilent J&W Scientific, Santa Clara, CA, USA) was used for separation. Helium gas (\(>\)99.999%) was employed as the carrier gas at a constant flow rate of 1.0 mL/min. The GC-MS injection temperature was maintained at 270 \({}^{\circ}\)C. The initial temperature was set at 60 \({}^{\circ}\)C and held for 2 min, then ramped at 7 \({}^{\circ}\)C/min to 200 \({}^{\circ}\)C, 5 \({}^{\circ}\)C/min to 300 \({}^{\circ}\)C, and was finally increased to 320 \({}^{\circ}\)C at a rate of 50 \({}^{\circ}\)C/min, and held for 3 min. The ion source temperature was set at 230 \({}^{\circ}\)C, and the MSD transfer line temperature was set at 280 \({}^{\circ}\)C. Electron impact ionization (70 eV) was utilized in full-scan mode (\(m/z\) 30-550), with the default settings for the other parameters. The solvent delay time was set to 5 min, and the total run time was 50.4 min. Additionally, quality control samples were first analyzed during the experimental process to assess stability.
## 3 Variation in the Phytosterols Content of Oils from Unconventional Plant Sources
\begin{table}
\begin{tabular}{l c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Campesterol**} & \multicolumn{2}{c}{**Stignasterol**} & \multicolumn{2}{c}{**DS-Avenasterol**} & \multicolumn{2}{c}{**DS-Avenasterol**} & \multicolumn{2}{c}{**DT-Stignasterol**} & \multicolumn{2}{c}{**DT-Avenasterol**} & \multicolumn{2}{c}{**Others**} & \multicolumn{2}{c}{**Total**} & \multicolumn{1}{c}{**Reference**} \\ \hline \multicolumn{2}{c}{Fruits} & & & & & & & & & & \\ \hline \multirow{2}{*}{apple} & 8.0–60.0 & 1.0–7.0 & 73.0–532.0 & 1.0–22.0 & 1.0–22.0 & 1.0–23.0 & & 1.0–136.0 & 113.0–780.0 & [97] \\  & 22.0 & 1.3 & 262.9 & 34.8 & & 25.0 & 346.0 & [163] \\  & 17.7–49.2 & 1.6–4.0 & 166.5–585.5 & & & 13.2–154.7 & 219.2–822.4 & [58] \\ \multirow{2}{*}{apricot} & 9 & 15 & 155.5 & 2.0 & 1.4 & 5.8 & 17.62 & [107] \\  & 11.2–48.7 & & 184.6–821.5 & 9.5–31.4 & 2.1–7.4 & 0.8–13.9 & 9.2–44.0 & 215.7–973.6 & [171] \\  & 8.8–15.5 & 1.4–3.2 & 251.4–294.2 & 21.9–56.8 & 2.3–4.7 & & 1.7–48 & 300.6-376.1 & [193] \\ \multirow{2}{*}{blackberry} & 21.4 & 7.3 & 342.0 & & 5.2 & 27.8 & 403.7 & [197] \\  & 75.7–78.2 & 105.3–109.0 & 433.2–457.0 & & & 0.1–8.616.0-424.3 & [167] \\  & 49.7–8.0 & 70.1–119.1 & 1026.3–1383.2 & & & 171.1–27.7 & 1146.1–1582.6 & [199] \\ \multirow{2}{*}{blackcurrant} & 51.3 & 4.5 & 363.7 & 12.4 & 7.6 & 14.6 & 228.3 & 682.5 & [163] \\  & 93.7 & & 546.9 & 31.1 & 125.6 & 210.4 & 1023 & [141] \\  & 403.3–511.2 & 23.7–31.0 & 3984.3–5083.0 & 159.0–292.3 & 143.1–182.4 & 98.2–135.1 & 711.6–996.5 & 5787.8–6994.4 & [60] \\ \hline \multirow{2}{*}{blueberry} & 10.2 & 31 & 104.5 & & & 25.1 & 142.9 & [97] \\  & 6.3 & 1.3 & 72.5 & & & 21.6 & 101.7 & [99] \\  & 8.0 & & 138.0 & 3.0 & 5.0 & 42.0 & 196.0 & [61] \\ \multirow{2}{*}{cherry} & 12.0 & 0.4 & 324.4 & 8.2 & 9.5 & 1.5 & 11.0 & 385.0 & [55] \\  & 18.7 & 1.0 & 601.8 & 17.7 & 7.2 & 1.8 & 29.2 & 67.85 & [57] \\  & 0.0–8.7 & & 201.5–533.1 & 00–11.9 & 1.6–2.7 & & 17.8–55.1 & 233.6–419.4 & [93] \\ \multirow{2}{*}{chokeberry} & 43.0 & 12.6 & 446.5 & 50.7 & & 38.4 & 27.8 & 619.1 & [141] \\  & 6.6 & & 110.3 & & & 31.3 & 148.2 & [79] \\ \multirow{2}{*}{Japanese} & 524.05 & 341–408 & 6910.7–885 & 469–569 & 56–91 & & 46–57 & 8480.9–697.7 & [143] \\  & 45.0 & 18.0 & 631.0 & 53.0 & & 14.0 & 761.0 & [99] \\  & 71.1–85.0 & 19.4–23.2 & 1268.2–1490.9 & & & & 1358.7–1599.1 & [62] \\  & 481.0–733.0 & & 6016–11,162 & 373–1207 & 34-125 & 15–154 & & 7830.1–41.66 & [142] \\  & 554.6–684.5 & 295.9–456.6 & 6152.9–7356.9 & 418.9–525.5 & 95.1–110.9 & 82.4–1153 & 137.4-156.0 & 8017.5–9518.5 & [171] \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Phytosterols content of oils from unconventional plant sources (mg/100 g of oil).
# Determination of Arsenic Species Distribution
## 2 Study Object  
The Khovu-Aksy deposit of cobalt-nickel arsenide ores is located in the village of Khovu-Aksy of the Republic of Tyva (Russia) (Figure 1). The deposit had been developed by the Tuvakobalt plant since 1970 until it was mothballed in 1991 [36].  
Primary ore mineralization led to the formation of carbonate mineral veins that cut the Silurian skarns [37]. The principal ore minerals within the vein system correspond to two paragenetic stages: skutterudite-safflorite and skutterudite-niccolite-rammelsbergite. The minor ore minerals include galena, sphalerite, argentite, native silver, native arsenic, and native bismuth. Small quantities of tennantite, chalcopyrite, bornite, and pyrite are formed in a subsequent stage (the sulfide-tetrahedrite stage).  
One processing technology was developed by the Gipronickel Institute (St. Petersburg, Russia). Hydrometallurgical ore processing was carried out by autoclave ammonia-carbonate leaching without preliminary enrichment and subsequent purification of technological solutions from arsenic. After the ore was crushed and ground, autoclave leaching was carried out with a solution of carbonate and ammonium hydrate (100-110 g/L) with the introduction of 0.5 m\({}^{3}\) of air per 1 kg of ore and heating to 90 \({}^{\circ}\)C and a pressure of 14-15 atm. for 2-3 h.  
At the second stage, technological solutions were purified from soluble arsenic by precipitation of sparingly soluble compounds of arsenic oxyanions and magnesium/ammonium (Mg(NH\({}_{4}\))AsO\({}_{4}*\)H\({}_{2}\)O, Mg\({}_{3}\)(AsO\({}_{4}\))\({}_{2}*\)H\({}_{2}\)O) with the addition of caustic magnesite (MgO) or sorption of arsenic oxyanions on the surface of magnesite. After this procedure, according to the standards, the residual arsenic content in the solution should not exceed 0.5 g/L. Further, excess carbon dioxide was passed through the ammonia solution of Co, Ni, and Cu to precipitate them as carbonates. The resulting precipitate was separated from the solution and sent for further processing [35].  
screen made of polyethylene film laid on a sandy underlying layer. After the slurry arrived and the solids settled, the waste was dehydrated, and the water returned to the mill for further use. The residual water evaporated naturally. Temporary water bodies with snow and rain supplies also appeared on the surface of the ponds. The tailings in pond 1 were covered by a soil layer of 10-20 cm and initially were seeded with scattered perennial grasses. Currently, vegetation covers the surface of the former pond site and grows well. Pond 2 was reclaimed after pond 1, and vegetation only partially covers its surface. The exposed surfaces of the ponds were a source of soil pollution in the surrounding area used for grazing [35; 38].  
Previous studies demonstrated the transformation of waste over 20 years of waste storage, the data obtained indicate the occurrence of active processes of metal (Cu, Co, and Ni) precipitation and their transition to poorly soluble forms, whereas As remained in highly movable forms [39].
###### Abstract  
Security is considered a critical issue in the deployment of 5G networks because of the vulnerability of information that can be intercepted by eavesdroppers in wireless transmission environments. Thus, physical layer security has emerged as an alternative for the secure enabling of 5G technologies and for tackling this security issue. In this paper, we study the secrecy energy efficiency (SEE) in a downlink underlying cognitive radio (CR)--non-orthogonal multiple access (NOMA) system with a cooperative relay. The system has an energy-harvesting (EH) user and an eavesdropper, where the transmitter provides direct communication with a close secondary user and a distant secondary user via the relay. Our objective is to maximize the SEE of the CR-NOMA system under the constraints of a minimum information rate for the secondary users, a minimum amount of energy harvested by the EH user, and maximum power availability at the transmitter and the relay that still prevents them from causing unacceptable interference with the primary user. The proposed solution to maximize the SEE is based on the low-computational--complexity particle swarm optimization (PSO) algorithm. For validation purposes, we compare the optimization outcomes obtained by the PSO algorithm with the optimal exhaustive search method. Furthermore, we compare the performance of our proposed CR-NOMA scheme with the conventional orthogonal multiple access (OMA) scheme.  
secrecy energy efficiency; 5G networks; cognitive radio; non-orthogonal multiple access (NOMA); particle swarm optimization (PSO) Article
# A Novel Reliability Analysis Approach under Multiple Failure Modes Using an Adaptive MGRP Model
## 4 Case Studies
### A Numerical Parallel System Analysis
Compared with methods of MRGP + H and MRGP + EFF, the computational efficiency of the proposed method is doubled, and the reliability error is lower than that of MRGP + EFF. Although the MRGP + H method has the highest accuracy of reliability in a parallel system, the accuracy of reliability is low in a series system. Overall, numerical examples prove that the proposed method considers both accuracy and efficiency in dealing with the reliability problem under multiple failure modes and can complete the reliability analysis of complex structures efficiently and quickly.
## 1 Introduction
However, if MPTCP is utilized properly, it can enhance throughput, fairness, and robustness by introducing reliability and seamless fail-over as well as increased network capacity [13]. In our previous work [14], we propose a Dynamic Multi Path Finder (DMPF) algorithm that leverages the properties of multiple paths available in the network to transfer each client request SVC layers over different paths. Now we propose a DMPF scheduler to maximize QoE and network bandwidth of DASH streaming using SVC in an SDN environment. A SDN controller runs the DMPF Scheduler Application module to provide the basic QoE for the clients. The DMPF scheduler determines the optimal flow paths for customer requests through the use of a holistic network view provided by the SDN controller. In brief, we can describe the main contributions of the present study:  
* Describe SDN-based scheduler application for DASH using SVC
* Consider QoE metrics and bandwidth utilization in the process of designing the architecture of the proposed scheduler
* Propose a mathematical model which determines the optimal data paths for delivering the requested video files and the quality adaptation. * Implement the proposed architecture and evaluate its performance in real network topology. The rest of this paper is organized as follows--a brief overview of DASH and SVC is provided in Section 2. We present related work that explores the foundation for multimedia steaming based on SVC in an SDN environment using multiple connections, in Section 3. We introduce the Dynamic Multi Path Finder (DMPF) Module which contains DMPF Scheduler and its processing and forwarding modesin Section 4. To enhance QoE, we present a mathematical formulation of the problem in Section 5. Detailed analysis of the performance of the proposed algorithms in given in Section 6. We finally conclude in Section 7.
## 3 Proposed Hybrid Precoding-Companding Technique  
This research aims to propose a competitive PAPR reduction technique for low latency applications in 5G and B5G, such as autonomous driving and vehicle to vehicle communications. Techniques with minimal computational complexity are favorable for low latency applications. Considering the computational complexity, hybrid precoding-companding techniques are the first selection for PAPR reduction. Unfortunately, precoding-companding techniques degrade the BER performance and increase OBB-radiation in the presence of HPA and may worsen them than the case of no PAPR reduction technique is used. Literature review reveals that previous precoding-companding techniques are concerned in the PAPR reduction gain increase. Most of the previous works did not explain the rationale of selection among different precoding matrices and different companding transforms to be used in hybridization. In other words, they did not mention how and why they choose the precoding matrix or the companding transform used.  
We propose a precoding-companding technique to enhance the BER and reduce the OBB-radiation instead of increasing the PAPR reduction gain. The technique selects the best precoding and companding techniques from BER and OOB-radiation reduction points of view.  
The authors in [10; 11] showed that SRC precoding (Section 3.1) and Log companding (Section 3.2) are the best precoding and the best companding techniques from BER and OOB-radiation reduction points of view. Therefore, they are selected to be hybridized in the proposed technique, and their parameters are adjusted to increase the reduction of BER and OOB-radiation. Figure 2 shows the block diagram of the proposed model. The model considers HPA into account, Rayleigh and AWGN channels are simulated. In contrast, most of the previous works neglect HPA and simulate only the AWGN channel. However, OFDM was designed originally for Rayleigh channels, and PAPR reduction techniques are used to mitigate the nonlinear distortion of HPA.  
Although the proposed technique's goal is to decrease BER and OBB-radiation; this does not mean that Although the PAPR reduction gain of the proposed technique is limited. Although To highlight the proposed technique's PAPR reduction capability, the proposed technique is compared with PTS (The most powerful PAPR reduction technique that has excessive computational complexity) from PAPR reduction and computational complexity points of view. The computational complexity of the proposed technique is the summation of SRC precoding and Log companding. In (17) and (19), respectively, the computational complexity of both SRC precoding and Log companding is determined. They are not calculated in the previous works.
## 2 The Information Bottleneck Method and Coarsely Quantized Information Bottleneck Signal Processing
### An Example of Information Bottleneck Receiver Design with Iterative Detection and Decoding
#### 2.3.3 Information Bottleneck LDPC Decoder Design
To obtain extrinsic information on the codeword bit \(x\), the variable nodes process \(d_{\mathrm{v}}-1\) messages from the connected check nodes and a message \(y_{0}\) from the channel. In the considered data transmission scheme, the channel messages correspond to \(t_{k}\in\{0,1,\ldots,2^{\mathrm{\prime}\alpha}-1\}\) from the detection scheme described in Section 2.3.2. As a result, the design of the variable node operation with the information bottleneck method processes the joint probability distribution \(p(x,y_{0})\), which is equivalent to \(p(s_{k},t_{k})\) and \(p(x,t^{(i)}_{\mathrm{c}\to\mathrm{v}})\) from the design process of the check node operation. For the equations needed to obtain all involved joint probability distributions, the reader is asked to refer to [18; 61]. Most importantly, the information bottleneck algorithm applied to the variable node design delivers \(p(x,t^{(i)}_{\mathrm{v}\to\mathrm{c}})\). This distribution has to be processed to design the check node operation for the next decoder iteration \(i+1\), which will in turn deliver \(p(x,t^{(i+1)}_{\mathrm{c}\to\mathrm{v}})\) for the check nodes in the next decoding iteration. This naturally suggests an iterative algorithm to determine lookup tables used as node operations in an information bottleneck LDPC decoder. This algorithm is iterated for a desired number of \(i_{\mathrm{max}}\) iterations of the constructed LDPC decoder, and the lookup tables constructed for the variable and the check node operations in each iteration of the decoder are stored. Finally, an important note on the proposed receiver design shall be made. Obviously, the joint probability distributions that are processed for the decoder design and also for the channel estimation and detection scheme studied before depend on the channel conditions. As a result, the reader might expect that the lookup tables designed with the information bottleneck method need to be adjusted to the signal-to-noise ratio or, equivalently, to the current \(E_{b}/N_{0}\) on the channel. As the design process of the detection, channel estimation and especially the LDPC decoder is computationally quite complex and involves numerous information bottleneck algorithms, this would clearly question the practical use of the proposed receiver design. However, interestingly, the proposed receiver design provides excellent performance, even with information bottleneck lookup tables that are used being mismatched to the actual channel conditions. This allows conducting the entire receiver design process offline to store the resulting lookup tables and to use them in a receiver with coarse quantization and very simple operations only. We will analyze the performance of the resulting receiver and compare it to several reference receivers in the following to prove our statement on excellent performance.