esa-sceva/satcom-chunk-collection huggingface dataset:
# Privacy-Preserving E-Voting System Supporting Score Voting Using Blockchain
## 5 The Proposed Voting Scheme
### Setup Phase  
The \(\mathcal{EA}\) produces the list of candidates and eligible votes as well as the system parameters. Each voter \(\mathcal{V}_{i}\) produces his/her private/public key pair \(x_{i},y_{i}=g^{x_{i}}\) for \(i\in[n_{v}]\) during the **Register** algorithm. The \(\mathcal{EA}\) randomly selects a value \(\mathcal{S}\) and divides it into \(n\) values and secretly sends each eligible voter, \(v_{i}\), \(\mathcal{S}_{v_{i}}\). Then, the \(\mathcal{EA}\) selects an elliptic curve group \((G,g)\), where \(g\) is the generator of the elliptic curve group \(G\) of prime order \(q\), and \(\mathbb{Z}_{q}\) is the integer set \(\{0,1,\cdots,q-1\}\) and \(\mathbb{Z}^{*}{}_{q}=\{1,\cdots,q_{1}\}\). The \(\mathcal{EA}\) also selects a value \(p\) that represents the sum of the evaluation scores given to each candidate on the ballot; thus the \(\mathcal{EA}\) is also defining a set \(\phi\) where \(\phi=[0,1,2,\cdots,P]\). The public parameters \(PP\) are hence \((G,g,\mathcal{P})\). Finally, the election authority needs to initialize the ZKSM as follows.  
1. [noitemsep,topsep=0 pt]
2. Defines a set \(\phi\) of \(k\) scores where \(\phi=\{p_{1},\cdots,p_{k}\}\);
3. Picks a random number \(x\in_{R}\mathbb{Z}_{p}\) and computes a corresponding public \(y\in g^{x}\), where \(g\) is the generator of the order \(-q\) subgroup of \(\mathbb{Z}_{p}\);
4. Computes for every element \(i\in\phi\) the corresponding signature using \(g\) and \(x\): where, \(\mathcal{A}_{i}=g^{\frac{1}{(x+i)}}\);
5. Publishes a new smart-contract with the \(\phi\).  
Finally, the \(\mathcal{EA}\) also publishes a list of candidates \((\mathcal{C}_{1},\cdots,\mathcal{C}_{[n_{c}]})\) and list of eligible voters \((\mathcal{V}_{1},\cdots,\mathcal{V}_{[n_{v}]})\) to the Blockchain.  
Each voter \(\mathcal{V}_{i}\) randomly selects their private key \(x_{i}\in\mathbb{Z}^{*}{}_{q}\) and computes their public key \(y_{i}=g^{x_{i}}\), with \(i\in[n_{v}]\). Subsequently, \(\mathcal{V}_{i}\) generates a non-interactive zero-knowledge proof to show that they properly computed their keys: \(ZKPoK_{1}\{(x_{i}):y_{i}=g^{x_{i}}\}\). The prover \((\mathcal{V}_{i})\) knows the secret key \(x\) and public key \(y=g^{x}\), but needs to prove that they know \(x\). The prover selects another random \(w_{i}\in_{R}\mathbb{Z}_{q}\) and calculates \(a_{i}=g^{x_{i}}\). Using the Fiat-Shamir heuristic, a challenge \(c\) is issued via a secure cryptographic hash function so that \(c_{i}=H(g,y_{i},a_{i})=H(g,g^{x_{i}},g^{y_{i}})\). The user then computes \(r_{i}=w_{i}-x_{i}c_{i}\) and sends the proof to the Blockchain. If \(a_{i}\) can be verified to be equal to \(g^{x_{i}}y_{i}c_{i}^{x_{i}}\), then the proof is accepted. In addition to their decryption keys, each voter also needs a \(n_{c}\) keys \((x_{i,1},x_{i,2},\cdots,x_{i,n_{c}})\). Each voter \(\mathcal{V}_{i}\) submits the corresponding public keys \((y_{i,1},y_{i,2},\cdots,y_{i,n_{c}})=(g^{x_{i,1}},g^{x_{i}},\cdots,g^{x_{i}})\) and a corresponding ZKP \(\pi_{i,j}\) for each key.
## 16 Novel Beam Scan Method of Fabry-Perot Cavity (FPC) Antennas  
In this paper [15], a Fabry-Perot cavity (FPC) antenna using a new beam scanning method is proposed. The authors design a tapered partially reflective surface (PRS) as a superstrate to obtain high gain characteristics with a reduced sidelobe level (SLL). Moreover, a phase-controllable artificial magnetic conductor (AMC) ground plane with a broad reflection phase and high reflection is proposed to obtain various beam scanning directions. The FPC antenna can accurately scan the main beam in target directions with high gain. The authors also demonstrate the feasibility of electrical beam-scanning antennas by employing active RF systems on the AMC cells.  
Design of a Polarization-Selective EM Transparent Mesh-Type E-Shaped Antenna for Shared-Aperture Radar Applications  
In this paper [16], the authors propose a polarization-selective electromagnetic (EM) transparent E-shaped antenna. The proposed antenna has nine X-band antennas and one S-band antenna, where the simple E-shaped patch is applied for the antenna elements. The mesh structure is applied to reduce performance degradation for S-band antennas and to enhance EM transparency. To verify the performance of the proposed antenna, the antenna unit-cell is fabricated, and the radiation patterns are measured. The results demonstrate that the proposed E-shaped antenna is appropriate for shared-aperture radar applications.
# Three-Dimensional Imaging of Metallic Grain by Stacking the Microscopic Images
###### Abstract  
Three-dimensional observation of metal grains (MG) has a wide potential application serving the interdisciplinary community. It can be used for industrial applications and basic research to overcome the limitations of non-destructive testing methods, such as ultrasonic testing, magnetic particle testing, and eddy current testing. This study proposes a method and its implementation algorithm to observe (MG) metal grains in three dimensions in a general laboratory environment equipped with a polishing machine and a metal microscope. An image was taken by a metal microscope while polishing the mounted object to be measured. Then, the metal grains (MGs) were reconstructed into three dimensions through local positioning, binarization, boundary extraction, (MG) selection, and stacking. The goal is to reconstruct the 3D MG in a virtual form that reflects the real shape of the MG. The usefulness of the proposed method was verified using the carbon steel (SA106) specimen.  
3D imaging of metal grains; non-destructive testing methods; stacking images; SA106 carbon steel +
Footnote †: journal: Applied Sciences
# A Robust Scheduling Framework for Re-Manufacturing Activities of Turbine Blades
###### Abstract  
Refurbished products are gaining importance in many industrial sectors, specifically high-value products whose residual value is relevant and guarantee the economic viability of the re-manufacturing at an industrial level, e.g., turbine blades for power generation. In this paper, we address the robust scheduling scheme of re-manufacturing activities for turbine blades. Parts entering the process may have very different wear states or presence of defects. Thus, the repair process is affected by a significant degree of uncertainty. The paper investigates the uncertainties and discusses how they affect the scheduling performance of the re-manufacturing system. We then present a robust scheduling framework for the re-manufacturing scheduling strategies, policies, and methods. This framework is based on a wide variety of experimental and practical approaches in the re-manufacturing scheduling area, which will be a guideline for the planning and scheduling of re-manufacturing activities of turbine blades. A case study approach was adopted to examine how re-manufacturers design their scheduling strategies.  
turbine blades; re-manufacturing; uncertainty; robust scheduling +
Footnote †: journal: Applied sciences  
To hedge against unexpected events in the manufacturing system, predictive and reactive approaches can take advantage of advanced sensor technologies providing monitoring capability and artificial intelligence supporting analyses and decisions [5]. Taking advantage of the described scenario, smart management approaches for re-manufacturing systems are required to support management, planning and scheduling, within the circular economy paradigm [2].  
Grounding on this perspective, this paper focuses on scheduling approaches for re-manufacturing activities, able to cope with uncertainty affecting both processing times and steps. The aim is to devise a robust schedule to mitigate the impact of these uncertain events. The industrial application addressed is gas turbine blade, an extremely complex and high-value product.  
The paper is organized as follows: Section 2 reviews relevant literature; Section 3 describes the addressed re-manufacturing environment entails the characteristics and operating environment of turbine blades, re-manufacturing process and associated uncertainties; Section 4 presents the proposed robust scheduling framework, while a case study is reported in Section 5. Finally, Section 6 provides final considerations and conclusions.
## 4 Study Case
### GSMS Data Collection Phase
#### 4.1.1 Definition of the Research Questions Phase  
The definition of the GSMS research questions phase is the initial research question or questions. In GSMS, it is recommended that the research question is generic, using the paradigm proposed by [PERSON], 'What do we have here?' It also affects the outcome, 'Review Scope', on the topic under study. Therefore, it drives the data analysis phase, as illustrated in Figure 2 label P1, with its corresponding outcome Review Scope (Figure 2 O1). P1 corresponds to the definition of the research question phase and provides as an outcome the Review Scope within GSMS.  
In this research, it is interesting to know which areas of software development are suitable for studying with GT and which are not. The goal is to locate the application domain of GT in the area of software development. The aim is to establish relationships between different types of GT and various fields of software development, as well as different types of article distributions, such as annual mapping, types of GT, and areas of software development.  
Additionally, it is desired to know if GT is appropriately applied within software development and among its various activities. Due to qualitative data analysis in general and GT being relatively new in software development, its application and correct use in the area are essential.  
Finally, it is interesting to determine if GT is useful or not for software engineers and to see its practical utility in the industry. Given the importance of software engineering and its applicability in the industry, it is essential to locate the usefulness of GT.  
Figure 2: Data collection in the GSMS process as an activity diagram.  
The previous paragraphs determined the three research questions of this paper, which are:  
**RQ1: In what context is GT appropriate in the field of software development?**  
**RQ2: Is GT applied correctly in the process and tasks of software development?**  
**RQ3: Is GT useful for software engineers in the industry?**
## 2 Materials and Methods
### Theory
#### 2.1.3 Double Transmit Sequence  
In order to mitigate the effect of sidelobe motion in the precompounded LRIs, a repeated transmit sequence is proposed (Figure 1b). By repeating the transmit angle each time, motion can be analyzed  
Figure 2: The coherent compounding approach generates high-resolution images (HRIs)by summing together low-resolution images (LRIs) formed at different steering angles. If we look at each LRI individually, we can see that the point spread function (PSF) rotates about the center as the steering angle changes. If we use the LRIs to produce Doppler estimates, the sidelobe rotation could be misinterpreted as tissue motion by the lag-one autocorrelation algorithm. Images are rendered at a 60-dB scale and are normalized to their corresponding maxima.  
between frames with the same PSF at a shorter time interval than would be possible with a traditional linearly incrementing transmit sequence. Such an approach opens up the design space to new Doppler estimation approaches (Sections 2.1.6 and 2.1.7).  
One consequence of this design decision is that it doubles the length of the transmit sequence such that \(N_{T}=2N_{\phi}\) instead of \(N_{\phi}\) as before. This means that if we choose to compound the sequence to generate HRIs for review, the HRI frame rate will be half that of the linear transmit sequence. However, given that the maximum velocity range is increased by a factor of \(N_{\phi}\) as described in Sections 2.1.6 and 2.1.7, and that typically one averages over multiple HRI frames anyway, one can argue that the decision is justifiable. That being said, the efficacy of such an approach should be evaluated by the end user to determine if tradeoff is acceptable.
###### Abstract  
At present, the preparation cost of biodiesel is still higher than that of diesel. Thus, directly using vegetable oil before transesterification can greatly reduce the cost. This study investigated the application characteristics of the direct use of crude palm oil (CPO) in a common rail direct injection (CRDI) diesel engine. In this study, the combustion characteristics, engine performance, and emission characteristics of the CRDI diesel engine operated with CPO (neat diesel fuel), CPO10 (10% CPO blended with 90% diesel fuel by volume), CPO30 (30% CPO blended with 70% diesel fuel by volume), and CPO50 (50% CPO blended with 50% diesel fuel by volume) at three idling speeds (750 rpm, 1500 rpm, and 2250 rpm) were evaluated. The results obtained from the experiment elucidate that combustion starts earlier by increasing the idling speed. The addition of CPO to diesel fuel resulted in a decrease in the peak in-cylinder pressure at all idle speeds and a decrease in the maximum heat release rate (HRRmax) at 750 and 1500 rpm, but an increase in HRRmax at 2250 rpm. On the other hand, increasing idle speed is beneficial for reducing carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx), but it increases smoke emissions. In addition, adding 10% and 30% CPO to diesel fuel can reduce both HC, NOx, and smoke emissions simultaneously.  
c 2022 12 6294 10.3390/app1236294
## 6 Simulation Results  
The PV output profile used for the scheduling is the hourly average of the actual PV output shown in Figure 7a. Similarly, the load demand profile is shown in Figure 7b, and it is assumed that Nodes 1-10 have residential loads, while Nodes 11-15 are designated as an office area in Figure 2. For the sake of simplicity, the forecasting error of PV output and load demands is ignored in this research. The discussion in this section is divided into two parts: the guaranteed power quality of the grid and reliable profit of the customers (incentive DR participants), respectively. For all of the simulations, the optimal schedule was determined by solving the MINLP problem optimization by PSO algorithm, whilst the conventional scheduling and proposed dual scheduling methods were evaluated based on distribution power losses and convergence performance.
## 3 Synthetic Measurement Enhanced Parameter Error Correction  
### Framework for Parameter FDI Correction  
The parameter FDI correction framework is illustrated in Figure 2. Input data consists of historical measurements of the system for the past days, recorded measurements from meters, parameters data and system topology such as connectivity status. The Machine Learning (ML) model process measurements from past days to predict measurements of the current day. The resultant weights attained from ML model are considered in stage--I WLS state estimation, which generates SM. Meanwhile, gross error analysis is performed in stage--II WLS state estimation. In this stage, FDI detection and identification is taken place [18; 19]. Upon detecting and identifying parameter attacks in the network, a parameter FDI correction model is solved. Once parameter correction performed, system model is updated.  
The process of creating SM is referred to as stage--I WLS in Figure 2. In this stage, existing measurements (bus power injection, power flow and voltage measurements) are weighted based on weights derived from ML models described in Section 2.2. Upon WLS SE convergence, power flow estimates in lines with no real-life measurement recorded are to be used as SM. The idea here is to increase, artificially, local measurement redundancy, with linear independent information, providing thus the necessary condition for the development of an overdetermined database of network parameters FDI cyber attack correction model. Hence, for every line section, there will be power flow measurement  
Figure 2: Framework for parameter FDI correction.  
reading from both ends of the lines. These SM in addition to existing scan of measurements are processed in the FDI correction model, described in Section 3.2.
# A Survey on Satellite Communication System Security
## 2 Existing Surveys and Motivation
### Contributions  
The contributions of this survey are below.  
* We provide a comprehensive understanding of SCSs, including the background and attack and defense mechanisms based on intuitive criteria (i.e., confidentiality, integrity, and availability).
* From our understanding, we are the first to provide the non-technical aspects of space security, such as countries' security policies and the physical ASAT landscape.
* We present future research directions, including potential security issues arising from future SCSs, such as full quantum networks.
## 3 Results
### Exhaust Emissions from Diesel Engine
#### 3.4.3 Nitrogen Oxides (NOx) Emissions  
Figure 5 shows the NOx emissions (in ppm) recorded at different engine loads for the D/EHN/SO (Figure 5a) and D/EHN/CO (Figure 5b) triple blends. As expected, NOx emissions increase with higher power demands, which can be attributed to the rise in cylinder temperature and pressure, promoting NOx formation, as supported by previous studies [48]. Furthermore, NOx emissions increase as the biofuel concentration in the blend rises, with all biofuel blends producing higher NOx emissions than pure fossil diesel, regardless of the specific vegetable oil used.  
The observed increase in NOx emissions from the triple blends, compared to fossil diesel, is relatively modest. The highest NOx emissions were recorded for the B100 SO and B100 CO double blends, which are pure biodiesel blends without any fossil diesel content. Specifically, castor oil blends showed up to a 30% rise in NOx emissions, while sunflower oil blends exhibited values closer to those of fossil diesel. This trend aligns with previous findings for EHN-enhanced fuels, such as lemon peel oil, where improvements in other performance metrics were accompanied by elevated NOx levels [44]. The presence of nitrogen in 2-ethylhexyl nitrate (EHN) likely contributes to this increase, as it forms nitrogen oxides during combustion [44]. The nitrogen present in 2-ethylhexyl nitrate (EHN) likely contributes to this rise, as it forms nitrogen oxides during combustion [49].  
However, sunflower oil blends demonstrated lower NOx emissions compared to castor oil blends. This difference could be attributed to the lower cetane number of sunflower oil, which delays combustion and reduces peak temperatures, thereby mitigating NOx formation. Although elevated NOx emissions are a known drawback of using EHN,  
Figure 5: Nitrogen oxides (NOx) emissions (ppm) generated at various engine load levels (0 to 5 kW) for (**a**) D/EHN/SO and (**b**) D/EHN/CO triple blends.  
this trade-off must be considered alongside the significant reductions in soot and CO emissions demonstrated by these blends. To address the challenges posed by increased NOx emissions, future research should focus on mitigation strategies. These may include the incorporation of NOx-reducing additives or the optimization of blend ratios, and exploring formulations that balance NOx emissions with reductions in CO and soot could provide a more comprehensive and sustainable solution.
# Design of Adits for People Passing Spacing in High Altitude Highway Tunnels in Cold Regions
## 2 Materials and Methods
### Design of Adits for People Passing Spacing
#### 3.3.2 Required Safe Egress Time  
Adequate adits for people passing that allows for the secure passage of individuals must be established to facilitate the safe evacuation of all personnel in a hazardous range. The maximum safe egress distance should be determined as the distance that personnel can evacuate within the required safe egress time (RSET). The RSET is  
\[REST=T_{d}+T_{pre}+T_{t} \tag{5}\]  
where: \(T_{d}\) is the alarm time; \(T_{pre}\) is the pre-moving time for personnel evacuation; \(T_{t}\) is the time for personnel evacuation.  
The smoke detectors used in the project can detect a fire over 100 kW. The fire alarm duration, as determined by the preset fire detectors in this research, is calculated based on the \(t^{2}\) fire model. Equation (5) is used to calculate the time:  
\[Q_{f}=\alpha t^{2} \tag{6}\]  
where: \(t\) is the time of the fire occurrence; \(Q_{f}\) is HRR, which is set as 100 kW in the calculation of the alarm time; \(\alpha\) is the fire growth coefficient, which is set as 0.187 kW/s\({}^{2}\) in this study.  
Therefore, the alarm time of the fire detectors can be calculated as follow:  
\[T_{d}=sqrt\left(Q_{f}/\alpha\right)=sqrt(100/0.187)\approx 23.1\;\mathrm{s} \tag{7}\]  
The pre-action time is the time interval between the receipt of the fire alarm and the initiation of evacuation measures, which is significant in fire emergencies. The pre-action time primarily mainly depends on building types and characteristics associated with occupant safety. Previous studies [45; 49; 50; 51] show that the pre-moving time for personnel evacuation varies from 30 s to 210 s. The pre-action time was chosen as 60 s in this study.  
Figure 9 shows the RSET in tunnels at different altitudes with different spacing of adults for personal evacuation in a traffic jam situation based on the simulation results of Pathfinder models. It should be noted that when there are disabled people in the fire scenario, their evacuation needs to be specially designed. Therefore, this case is not considered in the article.  
The RSET at an altitude of 0 m is the same as the RSET at an altitude of 1 km. As the figure shows, the difference in RSET at different altitudes is small when the spacing of adults for personnel evacuation is small. However, when the pacing of adults for personnel evacuation comes to 150 m, the difference in the RSET between a high-altitude tunnel and a low-altitude tunnel becomes obvious. For example, the difference in the RSET between a tunnel at an altitude of 5 km and a tunnel at an altitude of 1 km is 167% greater when the spacing is 250 m compared to when it is 50 m.