esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 HSP-QGA Algorithm Design  
### Algorithm Analysis  
The traditional genetic algorithm is based on [PERSON]'s theory of biological evolution. It is a mathematical optimization technology based on a biological model that enables the evolution of populations through reproduction, variation, competition, and selection. The operation flow is shown in Figure 3.  
In order to improve the efficiency of heterogeneous platforms, this paper designs the HSP-QGA with improvements to the genetic algorithm using qubits and quantum rotation gates, and scenario adaptation. The core framework consists mainly of two parts: the task preordering phase and the quantum genetic optimization stage, shown in Figure 4.  
In the task pre-ranking stage, the rank of tasks in the table scheduling algorithm is used to recursively calculate the priority value of each task in the heterogeneous system, shown in Formula (1). Then all tasks are sorted in descending order according to the rank  
Figure 4: Design framework of HSP-QGA.  
Figure 3: Diagram of classical genetic algorithm.  
value, and the scheduling strategy of the processor in the system is obtained by the table scheduling algorithm.  
\[\text{rank}(v_{i})\ =\ \overline{w_{i}}+\max_{v_{j}\in succ(v_{i})}(\overline{c_{ij}} +\text{rank}(v_{j})) \tag{1}\]  
where \(\overline{w_{i}}\) represents the average computational cost of task \(v_{i}\), \(succ(v_{i})\) represents the set of successor nodes (tasks) of \(v_{i}\), \(\overline{c_{ij}}\) represents the average communication cost between task \(v_{i}\) and \(v_{j}\). The calculation method is as follows (2).  
\[\overline{c_{ij}}\ =\ (\sum_{m\ =\ 1}^{n-1}\sum_{s\ =\ =\ +1}^{n}c_{i,j}/q_{k,f})/(p \times(p-1)/2) \tag{2}\]  
where \(q_{k,f}\) represents the number of communication paths between processors \(k\) and \(f\), and \(p\) represents the number of processors.  
For example, we can sort the tasks shown in Figure 2a to obtain the scheduling list shown in Table 1.  
In the quantum genetic optimization stage, based on the initial scheduling policy of the processor obtained in the task pre-ordering phase, the initial scheduling policy is encoded by using qubits to obtain the initial individuals and population. This avoids the unpredictability of randomly generated initial populations and reduces the search space for understanding. The results are kept from falling into a local optimum by a full-interference crossover. The quantum rotation gate is used to make the population evolve in the direction of greater fitness, while accelerating the convergence of the solution. Finally, an approximate optimal solution is obtained with the objective of minimizing the earliest completion time in the solution space provided by this algorithm.
# BSD-YOLOv8: Enhancing YOLOv8 for Book Signature Marks Detection
###### Abstract  
In the field of bookbinding, accurately and efficiently detecting signature sequences during the binding process is crucial for enhancing quality, improving production efficiency, and advancing industrial automation. Despite significant advancements in object detection technology, verifying the correctness of signature sequences remains challenging due to the small size, dense distribution, and abundance of low-quality signature marks. To tackle these challenges, we introduce the Book Signature Marks Detection (BSMD-YOLOv8) model, specifically designed for scenarios involving small, closely spaced objects such as signature marks. Our proposed backbone, the Lightweight Multiscale Residual Network (LMRNet), achieves a lightweight network while enhancing the accuracy of small object detection. To address the issue of insufficient fusion of local and global feature information in PANet, we design the Low-stage gather-and-distribute (Low-GD) module and the High-stage gather-and-distribute (High-GD) module to enhance the model's multi-scale feature fusion capabilities, thereby refining the integration of local and global features of signature marks. Furthermore, we introduce Wise-IoU (WIoU) as a replacement for CIoU, prioritizing anchor boxes with moderate quality and mitigating harmful gradients from low-quality examples. Experimental results demonstrate that, compared to YOLOv8n, BSMD-YOLOv8 reduces the number of parameters by 65%, increases the frame rate by 7 FPS, and enhances accuracy, recall, and mAP50 by 2.2%, 8.6%, and 3.9% respectively, achieving rapid and accurate detection of signature marks.  
small object detection; YOLOv8; book signature marks detection; WIoU
## 1 Introduction
Although these studies have shown the great potential of sensor networks for high-density air quality monitoring, their spatial resolution (city scale) was too large to examine intra-community scale variability and the target air pollutants were limited to a few primary gases or PM. Thus, more integrated air quality monitoring, including various gaseous and particulate pollutants with a sensor network on the intra-community scale, is still rare. In a previous study, the profiles of traffic-related pollutants were reconstructed at various distances from major roadways in different urban environments [21]. The results showed that the concentrations of traffic-related pollutants decreased sharply within 150-400 m of a road during the daytime [21]. Thus, the monitoring of various traffic-related air pollutants at a high spatial resolution is required, particularly in the urban center with its dense road network, large volumes of traffic, and complicated built environments. In this study, 30 sets of air quality sensor-nodes (for gaseous and particulate pollutants: CO, NO\({}_{2}\), O\({}_{3}\), and PM\({}_{2.5}\)) were deployed in an 800 \(\times\) 800 m monitoring domain in the center of Seoul, the largest megacity in Korea. The monitoring site consisted of four microenvironments with distinctly different traffic and built environments. This study aims to understand the heterogeneity of air pollutant distributions in space and time on the intra-community scale and to suggest the spatial resolution adequate for traffic-related air pollutants monitoring in urban areas.
# Spectral Envelope Transformation in Singing Voice for Advanced Pitch Shifting
## 7 Conclusions  
This paper presented a novel scheme to achieve more natural modifications of singing voice when applying a pitch shifting process. The system addresses the problem of timbre variation with the pitch  
Figure 14: Quality score. Distributions obtained with the survey for isolated notes and melodies. (**a**) Global results including all participants; (**b**) participants using headphones for the test; (**c**) participants with professional music studies or a professional music production background using headphones; (**d**) participants using headphones for the test with elementary music studies or an elementary music production background; (**e**) participants using speakers during the test.  
by modifying the spectral envelope, unlike most of the systems developed until now, which are based on the idea of formant preservation.  
To this end, a parametric model of the spectral envelope with four-pole resonators is employed to synthesize the vocal formants. With this model, a set of vowels sung at different notes has been analyzed in order to define a set of functions describing the variation of formants along pitch in singing voice. Then, a pitch shifting process for sung vowels has been defined by using a PSOLA algorithm with envelope processing according to the obtained functions. Special attention has also been paid to the estimation of the spectral envelope and the determination of pitch marks.  
The method devised was evaluated by using both objective and subjective measures. The objective results show more precise envelope adjustment when using our method than with the competitors, when comparing the spectra of the shifted notes against the target samples, especially in the most important features analyzed.  
The subjective evaluation of the system performance was carried out by means of an open survey, comparing the performance of our system with the Flex Pitch plugin of Logic Pro X and PSOLA. The results showed that our FDPS approach performed better than the two other schemes. Moreover, musically-trained participants doing the survey in good listening conditions rated our FDPS scheme higher.  
This work has been funded by the Ministerio de Economia y Competitividad of the Spanish Government under Project No. TIN2013-47276-C6-2-R. This work has been done at Universidad de Malaga, Campus de Excelencia Internacional (CEI) Andalucia TECH.  
[PERSON], [PERSON], [PERSON] and [PERSON] jointly conceived of and designed the envelope transformation model and the pitch shifting scheme; they also defined the evaluation methodology, analyzed the results obtained and wrote the manuscript.  
The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript; nor in the decision to publish the results.
## 3 Results and Discussion
### Operation Process  
Concerning the user experience in the operation process, we conducted a comparative evaluation across eight aspects, as can be seen from EQ13 to EQ20 in Table 2.  
As described in Figure 8, the results of the SPSS analysis indicate that all significance levels were \(p>0.05\), except for that of EQ19 (Operating Efficiency with the Next-step button), which exhibited a significance level of \(p<0.05\).  
Based on the results of EQ13-EQ14, the users' familiarity with tap and swipe operations remained unaffected by the MUI. Furthermore, the findings for EQ15, EQ16, and EQ17 suggest that the users could easily locate the \"Back\" button and \"Next-step\" button and effectively control the step flow in both the OUI and MUI. Concerning EQ18 and EQ20, the users' efficiency in utilizing navigation components such as the \"Back\" button and vertical swipe operation was not influenced by the MUI.  
However, it is worth noting that the significance value of Question 19 was below 0.05, indicating a significant difference in the use of the \"Next-step\" button. The worst experience on MUI shows that the design of commonly used basic elements, such as the \"Next-Step\" button, should be fixed in the interface and should not be displayed after both sides have completed tasks, and it is not recommended that buttons keep moving as the cooking step page is swiped.
# Secure Data Sharing in Federated Learning through Blockchain-Based Aggregation
### Contribution and Organization  
As privacy and integrity are two key challenges hindering the widespread adoption of FL, this paper is dedicated to investigating a rigorous solution to address these challenges. Referring to [11], FL can be categorized into two categories: cross-silo FL and cross-device FL. In this paper, we focus on the cross-silo setting, wherein model training occurs on siloed data belonging to several clients from different organizations. These clients can communicate with third-party servers in a synchronous manner.  
Our first contribution involves investigating the architecture and workflow of the EIFFeL framework along with analyzing its security guarantees. To this end, we identify specific areas where the EIFFeL framework exhibits potential risks, such as the compromise of the central server and/or the public bulletin board. We also highlight other efficiency concerns.  
Our second contribution involves adapting the EIFFeL framework to leverage the security guarantees of blockchain platforms. To this end, we adapt the operations in the EIFFeL framework so that the functions of both the central server and the public bulletin board can be replaced by a blockchain platform. To address the challenge posed by blockchain's limitation to only perform deterministic operations and the requirement that no direct communication among clients is necessary, we integrate the Burmester-Desmedt group key exchange protocol into our solution, to make sure that the clients can jointly compute the final parameter update without breaching its confidentiality.  
Our last contribution involves implementing our solution and shedding some light on the computational complexities. Note that the proposed solution is blockchain platform agnostic, so we omit the implementation details related to the blockchain part. This is earmarked for future work.  
It is worth noting that privacy protection for FL is a very challenging task. Even with secure aggregation, some privacy risks may still remain [11]. To address this, differential privacy, particularly local differential privacy, can be applied. Since such measures are used to secure aggregation and can be applied independently, we leave this out in this paper.  
The paper consists of the following sections: we present the background and motivation of FL and blockchain in Section 2. In Section 3, we review the design and analysis of the EIFFeL framework. Following this, an enhanced scheme is proposed; its security analysis, along with a demonstration of performance, is presented in Section 4. Finally, we summarize our work in Section 5.
# Energy-Efficient Region Shift Scheme to Support Mobile Sink Group in Wireless Sensor Networks
###### Abstract  
Mobile sink groups play crucial roles to perform their own missions in many wireless sensor network (WSN) applications. In order to support mobility of such sink groups, it is important to design a mechanism for effective discovery of the group in motion. However, earlier studies obtain group region information by periodic query. For that reason, the mechanism leads to significant signaling overhead due to frequent flooding for the query regardless of the group movement. Furthermore, the mechanism worsens the problem by the flooding in the whole expected area. To deal with this problem, we propose a novel mobile sink group support scheme with low communication cost, called Region-Shift-based Mobile Geocasting Protocol (RSMGP). In this study, we utilize the group mobility feature for which members of a group have joint motion patterns. Thus, we could trace group movement by shifting the region as much as partial members move out of the previous region. Furthermore, the region acquisition is only performed at the moment by just deviated members without collaboration of all members. Experimental results validate the improved signaling overhead of our study compared to the previous studies.  
mobile sink group; geocasting; mobility support; wireless sensor networks +
Footnote †: journal: Sensors
# Road to Efficiency: V2V Enabled Intelligent Transportation System
## 4 V2V Communication Architectures
### V2V-Based Cloud-Integrated Hub  
The Cloud-Integrated V2V Hub is a modern technology that merges cloud computing and vehicular communication. Each vehicle has communication modules, allowing real-time exchanges and transmitting essential data [52]. The hub uses cloud-based analytics to analyze patterns, predict traffic conditions, and derive insights for intelligent traffic management. This allows for global connectivity, enabling communication between vehicles regardless of their physical proximity [53]. The decentralized communication ensures low-latency interactions for safety-critical applications, while vehicles maintain peer-to-peer communication for instantaneous exchanges. End-to-end encryption safeguards sensitive information, preventing unauthorized access and tampering. Vehicles  
Figure 2: Decentralized Mesh Network for V2V Communication.  
authenticate to the hub, ensuring only authorized individuals contribute to and access V2V communication information. Edge computing, where nodes process time-sensitive data quickly, lowers latency for safety-critical applications and allows for predictive analytics from traffic management [54]. Cloud-integrated V2V Hub is a powerful, resourceful, and elegant technology that controls vehicle communications in a broad, organized ecosystem.  
Figure 3 illustrates a cloud-integrated V2V hub, a centralized component within a V2V communication architecture. It acts as a bridge between vehicles and cloud infrastructure, facilitating data exchange, processing, and coordination among linked vehicles. The V2V Hub receives data from individual vehicles, processes it, and transmits it to other vehicles within the network. It also allows for connectivity with external organizations such as roadside infrastructure or cloud servers. The V2V Hub's connection to the cloud infrastructure demonstrates the incorporation of cloud computing resources into the V2V communication architecture. By leveraging cloud services, the V2V Hub can offload computationally heavy operations, store and analyze massive volumes of data, and leverage additional processing capabilities that are not available locally. The bi-directional flow of data between vehicles and the V2V Hub and the cloud is illustrated by the bi-directional flow of sensor data, status updates, and safety-related information. The V2V Hub may also relay processed data to the cloud for further analysis or storage.
# Fatigue of Friction Stir Welded Aluminum Alloy Joints: A Review
## 2 Fatigue Failure Mechanism of FSW Weld
### Fractography  
Specimens for fatigue test are usually sectioned and loaded perpendicular to the joint centerline [21; 22; 23; 24; 25; 27; 28; 29; 30; 31]. [PERSON] [32] studied the fatigue fracture surface for a 6005 aluminum alloy FSW joint by Philips X130 SEM. The crack was found in the HAZ zone close to TMAZ. As shown in Figure 3, the fracture surface was divided into three regions. The crack initiation zone, which is located at the specimen surface, exhibited a relatively smooth microstructure. The crack propagation zone (Figure 3b) had prominent striation marks with a river-like appearance. The final failure zone of fatigue was the ultimate damage caused by void nucleation, coalescence, and crack growth, showing a rough and fine dimple structure [24; 27; 32]. [PERSON] et al. [PERSON] et al. [23] performed 22 tests in the very high cycle fatigue range, and found that only one specimen's crack initiation site was located in the NZ zone at the subsurface rather than the surface. The crack initiation originated from the inclusions inside the material and was accompanied by the annular fracture surface with a fisheye morphology, as shown in Figure 4 [23].  
Figure 4: Magnification of crack initiation position (**a**) The crack location with whole morphology; (**b**) detail of the crack initiation site [23].  
Figure 3: Fatigue fractography of 6005 aluminum alloys joint after stationary shoulder friction stir welding [32].  
Due to the high temperature and plastic deformation of the material, the fatigue crack initiation point was mainly located between the TMAZ region and the HAZ region. The crack initiation position was on the surface of the sample which was related to material flow, heat, and distribution of some intermetallic compounds [23; 25]. In the NZ region, the dynamic recrystallization process reduced the residual stress, and hence improved fatigue performance [7; 24; 33]. In addition, the crack initiation area was affected by defects such as porosity and inclusions. When there are defects, the crack starts from the defect position. The crack in some defects did not fully expand to the fracture, but the fatigue life of the material was greatly reduced.  
[PERSON] et al. [34] found a relationship between hardness and fracture location. The hardness distribution diagram showed a \"W\" shape. The hardness of the NZ region was the highest, and the lowest point was between HAZ and TMAZ. The area with low hardness value and high hardness gradient value was easy to become the fracture position of the joint. Since the crack initiation point of single-phase materials or materials without impurities mostly occurs on the surface, shot peening can effectively increase the fatigue crack initiation time, and even close some cracks. As the crack initiation process accounts for 90% of the total life, a higher surface quality will increase material fatigue life [25; 35].
## 2 Background
### Logging Interpretation
#### 2.1.2 Subjectivity of Manual Interpretation  
Due to VDL containing a large number of light and dark stripes, the shape of the strip and the degree of light and dark depend entirely on the subjective feelings of the evaluator. Therefore, the evaluation results are mixed with the subjectivity of the evaluator. Different experts can view the same image and draw different conclusions [13]. An observer will make different judgments when interpreting the same VDL many times.  
To reduce the subjectivity of manual interpretation, oil companies usually use multiple logging interpreters to work together to interpret and analyze the same logging results to obtain more accurate results, but this also further increases the time and consumes more manpower. Therefore, it is very difficult to evaluate the cementing quality accurately and efficiently. If a computer program is compiled to realize the interpretation and decision-making process of logging interpretation experts, the accuracy and efficiency of cementing quality identification will be greatly improved.
# An Efficient Opportunistic Routing Protocol with Low Latency for Farm Wireless Sensor Networks
## 2 Related Works
In addition, node capacity was also used as an indicator to evaluate the performance of candidate nodes. [PERSON] et al. designed a new hybrid fitness function based on parameters such as energy, trust, QoS, connectivity, distance, hop count, and network traffic, so as to select the best opportunistic routing [27]. In addition, some scholars took geographical location and distance as routing metrics and proposed a routing protocol based on geographic location strategy [28; 29; 30]. Considering node location, link quality, and node density, a greedy scheme was proposed by [PERSON] et al. [31]. The relay node selected the nearest neighbor to minimize the hops between the source node and the target node. A forwarding decision method was used to select the relay node according to the forwarding probability [32]. Based on the location information, depth information, and current residual energy, [PERSON] et al. weighted the normalized energy, transmission probability, and normalized distance to reduce the energy consumption and improve the network lifetime [33]. [PERSON] et al. proposed an energy-aware geographic routing algorithm, which can manage the residual energy and available energy [34]. In view of the highly dynamic network environment and link cost, [PERSON] et al. selected the neighbor closest to the target as the next forwarder according to the geographical location information of each node, regardless of the topology structure [35]. The above methods did not consider the interaction between links when constructing opportunistic routing. [PERSON] et al. proposed a least-cost opportunistic routing (LCOR) [36]. By calculating the end-to-end multipath weighted cost, the candidate set is constructed and the forwarding nodes are sorted. LCOR selects an excellent neighbor combination and uses the Bellman-Ford algorithm to obtain forwarding priority. However, in large-scale networks, the Bellman algorithm has a high computational cost. The OAPF algorithm calculated the weighted average of all possible paths from the source node to the sink based on the metric EAX [37]. [PERSON] studied the energy consumption model and made routing decisions based on the duty cycle to balance energy consumption and delay [38]. However, the protocol sums the probability of successful transmission as the probability that at least one node successfully forwards data, and its accuracy is limited. Compared with the above research, this paper focuses on the contribution of forwarding nodes to the whole network connectivity, aiming to reduce the forwarding times and energy consumption of important nodes to ensure network reliability.