esa-sceva/satcom-chunk-collection huggingface dataset:
# Privacy-Preserving E-Voting System Supporting Score Voting Using Blockchain
###### Abstract
Despite the number of existing schemes that have been proposed, many still suffer from several shortcomings such as lack of fairness and high computational and communication overheads to preserve privacy. This paper introduces a protocol for an e-voting supporting score-voting system using blockchain technology. The paper addresses the challenge between the open nature of Blockchain and privacy. To preserve privacy, voters will send their votes encrypted to the Blockchain. However, a malicious voter may modify the score value for a specific candidate to manipulate the elections result in favor of a certain candidate. This is a serious problem, especially in the case of score voting compared to the regular yes/no voting approach, because in score voting a voter is allowed to assign a score from a defined range for each candidate. The proposed approach ensures the security against that malicious behavior by leveraging the zero knowledge set membership proof so that the voter shall prove first in a zero knowledge that the selected score lies in the predefined set without allowing the Blockchain and/or eavesdroppers to know the score value per candidate. In addition, the score value is masked to preserve privacy. Finally, to obtain the election results, all participants including the election authority can tally the election results in a decentralized manner. We also conduct an empirical evaluation of our protocol on the Ethereum Blockchain, and find that it is able to sustain workloads up to 10,000 transactions sent at a rate of 200 per second before the system begins to experience significant declines in performance metrics. Such results suggest that, if deployed on the Ethereum network, our scheme is ideal for small and mid-sized elections and other selection processes of under 10,000 participants. The remainder of this paper is organized as follows. In Section 2, we discuss the most recent related works. Section 3 outlines the preliminaries used in this research work. In Section 4, the system/threat models, as well as the components of the proposed scheme are presented. Section 5 lays out the detailed construction of the proposed scheme. Then, Section 6 discusses the experiments and results to evaluate the scalability and efficiency of the proposed scheme. Finally, Section 8 concludes the paper and the findings of this research.
# Efficient Data Delivery Scheme for Large-Scale Microservices in Distributed Cloud Environment
## 4 Simulation Scenarios and Results
### Assessment of Delays and Forwarding Traffic While Changing the Number of Topics  
In this simulation scenario, the number of topics that every pub/sub broker is responsible for was varied in order to observe the performance of the four schemes through the mentioned metrics where appropriate for processing/forwarding. A pool of 1000 event channels or topics was formed and 100 brokers were deployed, with random coordinates chosen from the pool of coordinates. Each broker dealt with 100, 150, and 200 topics for each simulation run period. These topics were chosen in a distribution that followed Zipf's law from a pool of 1000 topics.  
Figures 3 and 4 display the respective ADL and AFT values of the comparative pub/sub schemes with varying numbers of topics. The proposed scheme was the best in AFT, and better than PSCoreCloud and PubSubCoord-like in ADL. As expected, the PSCoreCloud scheme experienced the highest (worst) ADL in the experiment, approximately 75.09 ms, because of the long delay when messages were transferred from clients to cloud brokers and returned to the interested clients. The PubSubCoord-like approach experienced high delay as well, approximately 73.36 ms on average, because the edge brokers forwarded joint topic channel data to cloud brokers for the relaying service for other interested brokers. In contrast, the ADL of the proposed scheme increased slightly from 44.54 ms to 45.68 ms and to 49.49 ms, while the brokers' workload was increased from 100 to 150 and 200 topics, respectively. In addition, the AFT of the proposed scheme experienced only a small increment, from 6.26% to 6.67% of the average forwarding traffic among the pub/sub brokers, in the evaluation scenario. These performance metrics demonstrate that the suggested strategy can effectively handle data delivery while altering the workloads of the brokers. Note that the PSCoreCloud AFT results were excluded because all the relay brokers are positioned in the Core Cloud. Even if the AFT of this scheme is good, it does not preserve internetwork traffic significantly because of its inefficient relaying mechanism, as shown above. Thus, the PSCoreCloud approach was omitted from the following comparison scenarios.  
Figure 3: Effect of varying the number of topics on the average delay.
## 5 Conclusions
Future research directions recommend planning subsequent research phases to gather data from broader demographics, conducting longitudinal studies to track changes in user behavior over time, and expanding the study to include comparative analyses with other universities or urban areas. The limitations of the research mainly concern the fact that the poll was addressed only to members of two universities in Greece and Italy and not to the residents of the urban areas where they are located, and secondly, the fact that the structure of the questionnaire did not allow us to explore the underlying reasons behind participants' behavior and the reasons for their preferences. Moreover, the number of filled-out questionnaires for the Italian case study was lower than that required in order to achieve a confidence level of 95%. However, the Italian case study is considered supplementary to our approach, allowing us to compare the two living areas for future research. Future research will include a larger sample involving the residents of urban areas instead of only university students and staff, as well as a statistical analysis testing the effectiveness of PUPs through the selection of customer populations; sampling, formulating, and testing hypotheses with confidence intervals; and comparing the results across different groups. Conceptualization, E.B. and S.B. ; methodology, E.B., S.F. and A.R. ; validation, S.B. and T.C. ; formal analysis, S.F. and A.R. ; data curation, P.S. ; writing--original draft preparation, E.B., S.F. and A.R. ; writing--review and editing, E.B., S.B. and T.C. ; visualization, E.B. ; supervision, S.B. and T.C. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Ethics Committee of Aristotle University of Thessaloniki (protocol code 296317/2023; date of approval 15 November 2023). Concerning the University of Enna Kore in Italy, ethical review and approval were waived for this study due to it being a non-interventional study that did not involve biological human experiments or patient data. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. In addition, this study was completely voluntary and non-coercive, and responses remain anonymous. Every user interviewed has in fact agreed to the sentence \"I authorise the processing of my personal data pursuant to Legislative Decree 196 of 30 June 2003 and Article 13 GDPR\". The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author. The authors declare no conflicts of interest.
## 5 The Radiology Point of View  
As discussed above, there are many advantages of physician-performed ultrasound. Nevertheless, there are also compelling advantages for ultrasound scanning by highly trained sonographers under the supervision of radiologists and working within a radiology department.  
First, this approach enhances efficiency, flexibility, and coverage. A single radiologist can reasonably and accurately report over 100 ultrasound exams a day when the scanning is performed by a team of experienced sonographers. It would not be possible for a clinician to scan nearly as many patients. Additionally, since all sonographers on the team are skilled in performing a broad array of exams involving different organ systems, exams can be scheduled flexibly based on urgency and patient convenience; except for rare highly specialized exams requiring particular expertise, the type of exam is not relevant since a number of sonographers have the necessary technical ability. Moreover, since US is often a front-line modality, the frequency of normal exams is high. In the authors' experience, most US exams are negative or reveal only relatively simple abnormalities (e.g., renal cysts, gallstones, small fibroids, etc.); the benefits of a physician performing all exams, including those with routine findings, have not been proved. Rather than systematically scanning all patients, radiologists scan only those patients in which their direct involvement is necessitated by confusing findings, complex anatomy, or complicated history. Finally, by centralizing US scanning within a radiology department, it is possible to ensure that all US procedures are offered to patients consistently and throughout the year, without having to schedule around particular physicians' availability.  
Second, this approach enables standardization and rigorous quality assurance, since all exams are performed using standard institutional protocols and reviewed by radiologists, which provides a mechanism for feedback to the sonographers. Additionally, one of the more experienced sonographers can serve as personnel supervisor and, in this capacity, organize and lead regular quality improvement projects requiring the participation of all sonographers in the department. Finally, it should be emphasized that sonographers accrue extremely high levels of sonographic skill, experience, and expertise. By performing many hours of scanning every day for many years, they achieve a mastery of their art that would be hard to match by a busy physician that performs many complex tasks in addition to sonography.  
Third, this approach facilitates the purchase and maintenance of the highest quality, state-of-the-art scanners. Since departments often purchase multiple scanners, they can negotiate competitive prices from scanner manufacturers, which allows them to purchase top-end scanners at relatively low costs. Additionally, departments may have greater access to physics and technical support, either internally from their own personnel or externally from the manufacturers, which allows the scanners to be maintained at the highest performance levels.
# A Deep Learning Approach for Short-Term Electricity Demand Forecasting: Analysis of Thailand Data
## 6 Results and Analysis
### Parameters Tuning for Scenario 2  
The electricity demand for the year 2018 is forecasted, utilizing the refined parameters illustrated in Table 6 with a dataset size of 70,608 and a test size of 11,808. Compared to the other two RNN-LSTM and RNN models, the RNN-GRU model performed better. We achieved the lowest minimum loss of validation (MAE) of 179 MW compared to 189.87 MW and 195.11 MW using the RNN-GRU simulation setup.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameters** & **LSTM** & **GRU** & **RNN** \\ \hline Number of hidden layers & 1 & 1 & 3 \\ Number of nodes & 128 & 64 & 64 \\ Epochs & 36 & 42 & 38 \\ Batch size & 48 & 48 & 48 \\ Look back period & 8 days & 5 days & 8 days \\ Dropout & 0.15 & 0.15 & 0.15 \\ Time period & 48 & 48 & 48 \\ Validation loss (MAE) & 221.79 & 213.36 & 242.35 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Sets of parameters for lowest validation loss of Scenario 1.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Model** & **Nodes** & **Layers** & **Dropout** & **Lookback Period** & **Epochs** & **Test MAE** & **Test MAPE (\%)** \\ \hline LSTM & 128 & 1 & 0.15 & 8 days & 36 & 224.75 & 2.12 \\ GRU & 64 & 1 & 0.15 & 5 days & 42 & 214.79 & 2.08 \\ RNN & 64 & 3 & 0.15 & 8 days & 38 & 248.64 & 2.28 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Implementing the optimal parameter settings for day-ahead forecasting using the test dataset of Scenario 1.  
In Scenario 2, as stated in Table 6, we were able to attain the following outcomes:  
* The LSTM model with nodes = 128, layers = 1, dropout = 0.15, lookback period = 5 days, and epochs = 57 produced the minimal validation loss of 189.87 MW.
* The GRU model with nodes = 64, layers = 1, dropout = 0.15, lookback period = 8 days, and epochs = 61 obtained the minimal validation loss of 179 MW, which was the lowest loss across all three models.
* The RNN model with nodes = 64, layers = 2, dropout = 0.2, lookback period = 8 days, and epochs = 51 achieved the minimal validation loss of 195.11 MW. which was the highest loss across all three models. When optimized hyperparameters are used, Table 7 shows that the RNN-GRU model achieved its best performance in terms of both performance metrics (MAE and MAPE) with MAE = 181.63 MW and MAPE = 1.89%.
## 3 Results
### Phosphate Reduction Analysis
Similarly, on the second  
Figure 8: Bar plot of the average phosphate vs. the sampling period with a 24 h retention time. day of the sampling period, a phosphate concentration of 20.01 \(\pm\) 0.01 mg/L was recorded for the influent sample. However, the test plants were able to reduce the influent phosphate values from \(20.01\pm 0.01\) mg/L to 10.50 \(\pm\) 0.01 mg/L, 13.16 \(\pm\) 0.01 mg/L, and 6.53 \(\pm\) 0.15 mg/L for _P. striatiotes_, _S. molesta_, and _E. crassipes_, respectively. On the eighth day, the test plants lowered the influent phosphate concentration from 5.56 \(\pm\) 0.05 mg/L to 2.76 \(\pm\) 0.05 mg/L (_P. striatiotes_), 0.96 \(\pm\) 0.01 mg/L (_S. molesta_), and 2.83 \(\pm\) 0.05 mg/L (_E. crassipes_). The highest phosphate reduction efficiencies for the _P. striatiotes_ and _E. crassipes_ treatment systems were observed on the 10 th day, with values of 81.2% and 88.5%, respectively. The maximum percentage reduction efficiency for _S. molesta_ was found to be 82.7% on the eighth day of the sampling period. In this present work, a more advanced phosphate removal by _E. crassipes_ was recorded compared to the _P. striatiotes_ and _S. molesta_ plant treatment systems. The short roots of _P. striatiotes_ played a vital part in the uptake of phosphate from the treatment system. However, the ANOVA test demonstrated a significant difference (\(p<0.05\)) in the phosphate reduction values obtained between the influent and the effluent wastewater treatment systems, except for _S. molesta_, which was found to be not significant (\(p>0.05\)).
# An Image-Processing Method for Extracting Kinematic Characteristics of Droplets during Pulsed GMAW
###### Abstract  
Pulsed gas metal arc welding (GMAW) is widely applied in industrial manufacturing. The use of pulsed GMAW was found superior to the traditional direct-current (DC) welding method with respect to spatter, welding performance, and adaptability of all-position welding. These features are closely related to the special pulsed projected metal transfer process. In this paper, a monitoring system based on a high-speed camera and laser backlight is proposed. High-quality images with clear droplets and a translucent arc can be obtained at the same time. Furthermore, a novel image-processing algorithm is proposed in this paper, which was successfully applied to remove the interference of the arc. As a result, the edge and region of droplets were precisely extracted, which is not possible using only the threshold method. Based on the algorithm, centroid coordinates of undetached and detached droplets can be calculated, and more parameters of the kinematic characteristics of droplets can be derived, such as velocity, acceleration, external force, and momentum. The proposed monitoring system and image-processing algorithm give a simple and feasible way to investigate kinematic characteristics, which can provide a new method for possible applications in studying mathematic descriptions of droplet flight trajectory and developing a precise automatic welding system.  
high-speed camera; image processing; edge detection; pulsed GMAW; metal transfer; droplet +
Footnote †: journal: Applied Mechanics and Physics Letters
# Vehicular Alarm System Using mHealth Data and Lightweight Security Algorithms
## 4 mHealth Integrated Vehicular Alarm System
### Alarm Notification  
If an alarm notification is triggered, it can be sent to the relevant parties with multiple phases of communication. This is categorized into two phases including the warning phase and alarm phase.  
Warning phase--a warning notification is issued to alert the driver when distraction is detected. These could include movements such as checking a phone, deteriorating health conditions such as fatigue, and the cabin environment, e.g., faulty HVAC. The warnings can be raised by sound or visual cues e.g., playing a warning message from the mobile phone or vehicle or a flickering light.  
Alarm phase--an alarm notification is issued to the driver as well as the relevant parties such as company headquarters and health service providers when the health condition of the driver is not suitable for driving. For example, the heart rate may be out of the threshold limits and a heart attack is envisioned. A paramedic may be dispatched to the site in case of emergency even though the driver is not in a position of sending for help as per pre-scheduled processes of an emergency situation. To avoid faulty alarms, there may be a confirmation message to the driver's smartphone requesting a reply via voice prompts and voice recognition with a timeout period, which will trigger the alarm if the reply is not received within the pre-set timer value. When the driver is not available to reply on the phone even though the truck is in a stopped or parked condition, they may be able to reply by voice recognition.
# SNA: Sensitivity-Aware Neural Architecture Adaptation for Uniform Quantization
## 2 Related Work
### Mixed-Precision Quantization  
Conventional quantization approaches project full-precision weights and activations to fixed-point numbers, using the same bitwidth for all layers of a network [18]. However, mixed-precision quantization provides flexibility in selecting different precisions for different network layers [19; 20; 21]. Selecting mixed-precision for each layer can be seen as a searching problem, and many methods have been proposed to solve it [2; 3; 22; 23]. In particular, [PERSON] et al. [3] leveraged reinforcement learning (RL) to automatically determine the quantization policy and took the hardware accelerator as part of the RL agent feedback. [PERSON] et al. [24] converted the bitwidth search into a neural architecture search (NAS) problem and explored the search space using the differentiable NAS (DNAS) method [25]. Different from these exploration-based approaches, [PERSON] et al. [5; 26] introduced HAWQ, which measures the layer sensitivity based on the trace of the second-order operator, which is faster than exploration-based mixed-precision methods.
# An LSM-Tree Index for Spatial Data
## 4 ER-Tree Index
### ER-Tree Index Design  
The traditional R-tree index of spatial data on an LSM-tree uses the method of indexing multiple SSTables by a single file to reduce the number of index files, which simplifies the design, but reduces the data query efficiency and increases the index update overhead. In this paper, a single index file is used to maintain a single SSTable. Although many index files are added, the cost of index update can be reduced when the compaction operation occurs because only a few indexes on SSTable are updated. In terms of data querying, since the related records are available on the SSTable corresponding to the index, there is no need to perform dual index queries, which reduces the read amplification and improves the spatial data query performance.  
In the external storage of an LSM-tree, the storage structure is logically divided into several layers and each layer contains multiple SSTable files. To avoid scanning the SER-tree indexes on each SSTable, the indexes need to be organised according to the hierarchical idea of LSM-trees to improve the efficiency of the data query. Figure 6 shows the ER-tree index structure of the spatial data on the LSM-tree designed in this paper and the details of the build method are presented in Section 4.2. The SER-tree on the SSTable in each level of the external storage LSM-tree is organised into a linked list by connecting all the root nodes of the SER-tree at the level and then the headers of all the level lists are organised into a linked list. The formed double linked list organises all the SER-tree indexes on the SSTable together. The query can be filtered by the tMBR range of each node on the double linked list level by level and can filter some SER-tree indexes unrelated to the query scope to avoid scanning all indexes.
# A Survey on Underwater Acoustic Sensor Network Routing Protocols
## 3 The Knowledge of Underwater Acoustic Sensor Networks  
Since an underwater acoustic sensor network is used to collect data when events occur in the underwater environment, a reliable and effective route from source node to the destination node is necessary. Even though many routing protocols have been proposed for terrestrial wireless sensor networks, considering the differences between the underwater environment and the terrestrial environment, terrestrial routing protocols are different from UASN routing protocols. For better understanding the differences between underwater communication and terrestrial communication, and the difficulties in routing protocol design for underwater acoustic sensor networks, some investigation of the characteristics of underwater acoustic communication is necessary.