esa-sceva/satcom-chunk-collection huggingface dataset:
# Rhythm-Based Attention Analysis: A Comprehensive Model for Music Hierarchy
## 2 Related Works
### Fractal Theory in Rhythm Analysis of Music  
Several related works have explored the fractal nature of music, particularly in the context of rhythm and structure, offering valuable insights that complement our proposed rhythm-based attention analysis. [PERSON] and [PERSON] (2000) explored the fractal dimension of music in the time domain using statistical methods, aiming to quantify and classify different music genres based on their fractal properties [32]. [PERSON] and [PERSON] (2007) investigated the fractal properties of music by converting musical note sequences into \"music walks\" and analyzing them using Hurst exponents and Fourier spectral analysis. Their findings indicated that music exhibits fractal characteristics akin to fractional Brownian motion (fBm) [33]. [PERSON], [PERSON], and [PERSON] (2012) demonstrated that musical rhythm adheres to a \(1/f\) power law distribution. They confirmed the universality of fractal structures in rhythm and revealed unique \(1/f\) rhythm spectra across composers, pointing to both conscious and unconscious manipulation of rhythmic predictability [34]. More recently, [PERSON] and [PERSON] (2023) introduced the concept of \"temporal scaling\", which examines the recurrence of melodic lines at various time scales and defines a corresponding fractal dimension, highlighting the multifaceted nature of fractal patterns in music [35].  
While these studies primarily focus on frequency and spectral analysis, they provide a critical foundation for understanding the complex fractal nature of music. Our paper's contribution lies in exploring the fractal structure of music through a novel approach that emphasizes rhythmic patterns and their hierarchical organization. By focusing on rhythm-based attention analysis, we aim to reveal new dimensions of musical complexity and structure, advancing the field towards more sophisticated and comprehensive analytical methodologies.
## 4 Non-Parametric Methods
### Genetic Algorithms  
Genetic algorithms (GA) are based on the principle of natural selection. Given a population of possible solutions, the GA uses a subset of them (referred to as parents) to create the \"next generation\" which will also be used to create their successors and so on. This evolutionary process continues until it produces an optimal solution. The different types of GA's differ in the way \"parents\" are selected and how the \"next generation\" is produced.  
A GA-based node attribute behaviour anomaly detection scheme was proposed by the authors in [53]. The scheme uses the fact that particular node attributes can be used determine whether or not a particular node is behaving \"normally\". These attributes can then be mapped into the feature set which is used by the GA to detect anomalies. The proposed scheme is capable of adapting to changes in system behaviour over time. The system was simulated in NS-2 and yielded a detection accuracy of 87.5% with a false positive rate of 12.5%. The authors however noted that these values can be significantly improved by using more behaviour indices.  
A GA based scheme that be used to improve reputation systems was developed by the authors in [54]. The scheme uses trust and reputation principles to identify misbehaving nodes and then isolate them from the network. The reputation of a node is determined by an unsupervised GA which monitors the network for suspicious behaviour. Nodes that are misbehaving will have their reputation scores sharply reduced until it is deemed to be untrustworthy. Should the misbehaving node start to behave \"normally\" its reputation score will gradually increase until it becomes trusted again. This possibility for redemption accounts for selective behaviour of nodes, which may not be the result of an attack. The proposed scheme had a high detection accuracy and low false positive rate when tested with known attacks.  
Besides GAs, there are other biologically inspired artificial intelligence algorithms that can be used in anomaly detection schemes. For instance, the use of the negative selection algorithm (NSA) of the artificial immune system (AIS) to detect anomalies was proposed by the authors in [55]. The AIS is modelled after the human immune system and is advantageous because it is inherently adaptive making it ideal for anomaly detection schemes. The proposed scheme uses a modified version of NSA (modelled after the natural system of the same name) that has an added injection feature step referred to as vaccination. This allows for an ad hoc update of the detector set without having to retrain the system. Experimental results show that the proposed scheme outperforms state of the art techniques
# Dynamic Induction Heating Temperature Field Analysis of Spiral Bevel Gears
###### Abstract
The results showed that the thickness of the workpiece affects heating rate, and the induction coil position affects heating uniformity. To investigate the induction heating of gears, [PERSON] et al. [12] studied the moving in-duction heating process of a wind turbine's inner gear ring and reduced the gear ring's temperature inhomogeneity by changing the heating's starting and stopping positions. [PERSON] et al. [13] analyzed the effect of the number of iterations of heating on temperature distribution uniformity during asynchronous dual-frequency induction heating of bevel gears. The results showed that temperature distribution uniformity in the bevel gear tooth width and tooth profile direction improved with an increase in the number of iterations. Induction heating has been discussed extensively in previous studies; however, induction heating of spiral bevel gears has rarely been discussed. Here, two structures of induction heating coils were designed for spiral bevel gear geometry and shot peening process requirements. A dynamic induction heating simulation analysis was performed with the spiral bevel gear rotating at a constant speed of 20 r/min. According to the characteristics of tooth surface area division, induction-heating experiments were conducted using longitudinal coils to validate the simulation model [14; 15; 16]. This study can be applied to the construction of heating devices in the shot peening of induction heating composite, which provides a reference for selecting the induction coil and a theoretical basis for dynamic induction heating, as well as a prerequisite for induction heating shot peening.
## 5 Research Gaps and Challenges and Future Direction  
During the past few years, many advances have been made using camera imaging-based methods and numerous studies have been published in this field. However, the existing studies have several limitations that need to be overcome in the future.  
* Most of the current studies focus on either motion artefacts or illumination variations. However, in real time scenarios both motion and illumination play an important role in degrading accuracy and usability. Only a few researchers have given solutions to both motion artefacts and illumination variations. Therefore, it can be a further topic of research for new researchers to develop a method which can deal with both motion and illumination artefacts.
* Researchers are still mainly interested in extracting HR and RR. Nevertheless, blood oxygen also plays an important role in assessing a human's health condition. Blood glucose [151; 152; 153] is another important vital sign which helps to identify and maintain the welfare of diabetes patients. Therefore, more research needs to be done to monitor blood oxygen saturation and blood glucose.
* All of the studies except [PERSON] et al. (3 subjects), [PERSON] et al. (2 subjects) and [PERSON] et al. (6 subjects), considered only a single subject at a time when monitoring vital signs. Detecting multiple persons simultaneously is a major issue in the current studies that need to be overcome in the future.
* The distance between the camera and a subject is another challenge for current researchers. All the studies except [PERSON] et al. (60 m) considered very small distances while monitoring vital signs.
* The number of ROI and selecting ROI are important issues to overcome as very few researchers have paid attention to these problems well enough for industrial or commercial use. Most of the studies have used manual processes while some have used automatic methods to select from a very limited number of ROI in limited scenarios. However, advanced techniques are required to automatically select multiple ROIs.
* Researchers mainly considered healthy young participants as their subjects to do the experiments and did not use patients, elderly people and premature babies. More research needs to be done considering different subjects such as premature babies and elderly people.
* Most of the existing works considered privately owned databases. Only a few used publicly available databases such as the MAHNOB-HCI (human computer interaction) or DEAP (Databasefor Emotion Analysis using Physiological Signals). Lack of publicly available datasets taken under a realistic situation is another challenge to deal with in the future.
* To validate proposed methods, researchers have mainly used a pulse oximeter as a ground truth. The ECG was used by very few researchers as a ground truth. There are indications that no commercial instrumentation is truly accurate and most are simply accepted as accurate [110].
* Future research could also include multi-camera fusion as well as new non-visible light sensors to tackle the visible light camera's shortcomings.
# Mueller Matrix Decomposition and Image for Non-Destructive Testing of UAVs Skin
## 4 Conclusions  
In this work, UMMMD is proposed for the NDT of UAVs skin. The method utilizes unitary matrix transformation to generate a depolarized space related to multiple scattering. In this way, the depolarizing Mueller matrix is decomposed into polarized and depolarized parts related to the reflection and the multiple scattering, respectively. The non-uniform depolarization effects can be calculated with the given depolarization matrix and entropy. The method provides more polarization information related to non-uniform scattering than some traditional methods.  
Moreover, UMMMD is used for the NDT of UAV skin. By using the method, the contrast of the polarization images has been greatly improved since the noises in the images are effectively suppressed. The Mueller matrix images of the UAV skin are consistent with the Mueller matrix decomposition results. Meanwhile, the provided method exhibits large dynamic ranges, and is sensitive to the non-uniform structure of the UAV skin. The key features of the NDT such as the deformation, shear angles, and density are successfully obtained.  
It has demonstrated that the method is feasible and flexible for the NDT of UAVs skin. The proposed method could be beneficial for the NDT of 3D composite materials, intelligent skin design and manufacture, and light-matter interactions of rough materials.  
Conceptualization, H.L.; data curation, C.G.; funding acquisition, Z.Z.; investigation, D.M.; methodology, H.L., L.L., X.Y. and Z.Z.; project administration, Z.L.; resources, D.M.; writing\(-\)original draft, H.L.; writing\(-\)review and editing, X.Y. All authors have read and agreed to the published version of the manuscript.  
The work is financially supported by the National Natural Science Foundation of China (NSFC) (61771240, 61475071), China Postdoctoral Science Foundation (2022M711620), Jiangsu Province Postgraduate Research Innovation Plan (KYZZ16\(\_\)0168), and China Fundamental Research Funds for the Central Universities (No. 30917014107).  
Not applicable.  
The authors declare no conflict of interest.
# Gamification and Immersive Experiences: A Gamified Approach for Promoting Active Aging
## 2 Background
### Active Aging and Addressing Ageism Through Digital Interventions
Gamified cognitive training programs have also demonstrated advantages in their adaptability, accessibility, and capacity to engage users over time. Platforms like BrainHQ and Lumosity provide structured cognitive exercises that adjust to a user's performance, promoting sustained engagement and incremental improvements [8]. However, [PERSON] et al. (2022) [9] noted that while these programs effectively target specific cognitive functions, the lack of far-transfer effects highlights the need for further exploration to achieve broader and longer-lasting impacts. Inconsistencies in study quality, such as variability in design, sample size, and the inclusion of control groups, limit the current literature on cognitive training for older adults. As [PERSON] and [PERSON] (2017) [13] observed, many studies rely on self-reported outcomes, which are susceptible to subjective bias and are often influenced by commercial funding, complicating the objective assessment of efficacy. Compared to existing platforms like CogniFit, BrainHQ, Lumosity, Elevate, or NeuroNation, the Twist platform incorporates novel elements that enhance appeal and effectiveness. While traditional platforms focus on gamified cognitive exercises, Twist integrates immersive 360-degree virtual experiences, allowing users to participate in virtual tours of real-world locations. This immersive component stimulates memory recall and spatial awareness and provides emotional engagement, aspects often overlooked by conventional platforms. Furthermore, unlike these platforms, which prioritize individualized cognitive training, Twist emphasizes social connectivity by including social forums, ranking systems, and community-based challenges. These elements foster interaction, reduce loneliness, and enhance emotional well-being, addressing the social isolation that other platforms tend to neglect. By combining gamification with immersive technologies and social connectivity, Twist represents an approach to active aging addressing the cognitive, social, and emotional needs of older adults within a single platform.
## 3 Valve Characteristics  
### Static Characteristics  
We measured the static characteristics of the developed valve. The camshaft was connected to the DC motor, and the angle of the camshaft was controlled using a microcomputer (Arduino). We measured the flow rates by changing the rotational angles of the cam. The supply and downstream pressures were set to 500 kPa and atmospheric-pressure values, respectively.  
The experimental results are shown in Figure 7. The hysteresis of the flow rate to the cam angle was small. Flow rate changed linearly with respect to the cam angle. The maximum flow rate was 27 L/min, which was almost the same as the designed value. We confirmed that the value could achieve an almost zero-lap condition. Air leakage was 0.1 L/min or less, and the ratio of air leakage to the maximum flow rate was 0.37%. These values were fairly low compared to those of a spool-type servo valve (FESTO MPYE-5-M5-010-B), which exhibited air leakage of 1.9 L/min and a ratio of approximately 3.5%.  
Then, we measured the flow characteristics of the valve using the experimental setup in accordance with the procedure recommended by ISO 6358. An experimental result with a cam angle of 40 deg is shown in Figure 8. As shown in the figure, the critical pressure ratio was 0.44 at a supply pressure of 500 kPa. The critical pressure ratios of commercially available valves are approximately 0.3 to 0.45 [17; 19]. The path is geometrically symmetrical because the flow path is between the orifice and the ball. Therefore, the developed valve has a wide choke range compared with conventional valves.  
Furthermore, we measured the pressure gain characteristics at zero flow. The pressure sensor was directly connected to the control port of the servo valve. The relation between the rotation angle of the cam and the pressure in the control port was measured. Figure 9 shows the results at a supply pressure of 500 kPa. We confirmed that the pressure gain was large because the valve leakage rate is small.  
Figure 8: Flow characteristics of developed valve.  
Figure 7: Static characteristics of developed valve.
# Advanced Control and Fault Detection Strategies for District Heating and Cooling Systems--A Review
## 2 State of the Art Control Strategies for District Heating (DH) and District Cooling (DC) Systems
### Basic Control Strategies in 4 GDH and 5 GDHC Systems
Remote smart metering is a mature technology, and it is an important aspect to improve the operation in both 4 GDH and 5 GDHC systems such as with the implementations of demand response (DR) strategies for peak shaving as presented in Section 2.5 as well as to detect faults in substations as described in Section 3.2. Nevertheless, there are still some barriers to overcome to achieve this as the lack of trust between the DHC operators and the users as well as additional services to provide by DHC companies such as substation maintenance [32].
## 3 Elasto-Plastic Constitutive Model
### Plastic Strain Analyses of UGM
#### 3.5.3 Vertical Plastic Strain and Loading Cycle  
In the typical three-layer pavement structure, the vertical stress on the top surface of UGM layer was 65 kPa using the three elastic-plastic model. Then at the centerline of the loading system, the average vertical plastic strain of UGM layer obtained by the three models as shown in Figure 8. When the Mohr-Coulomb and Druck-Prage models were adopted for UGM layer, the plastic strains increased rapidly in the initial loading cycles, which were up to 275 \(\mu\varepsilon\) and 90 \(\mu\varepsilon\), respectively. In the following loading cycles, the calculated plastic strain had a small growth, and it increased by 35 \(\mu\varepsilon\) and 12 \(\mu\varepsilon\), respectively. For the revised SMP model, the plastic strain was only 18 \(\mu\varepsilon\) at the first loading cycle. It had an obvious increase tendency during the following loading cycles, and the growth was up to 160 \(\mu\varepsilon\). Figure 8 suggested that the plastic strain would continuously increase after 100 loading cycles.  
Comparing the plastic strains, it showed that the plastic strains calculated by the Mohr-Coulomb model were significantly greater than those calculated by the revised SMP model. However, the plastic strain rate of Mohr-Coulomb was far smaller than that of the revised SMP model. The plastic strain of Mohr-Coulomb model mainly occurred during the first several loading cycles. With the increase of load cycles, the yield hardening stage was short and increment of the plastic strain was small. Using the revised SMP model, the loading cycle was introduced into the yield surface and hardening law which would change with the increased loading cycles. Therefore, the plastic strain presented an obviously increasing  
Figure 7: Vertical plastic strain of UGM layer using the three models.  
tendency. Before the first 30 th loading cycle, the plastic strain from the Druck-Prage model was greater than that from the revised SMP model. And it reversed after the loading cycle was above the 30 th loading cycle. Similar as the Mohr-Coulomb model, the plastic strain calculated by the Druck-Prage model changed little along with the loading cycle.  
When comparing with the experimental results of UGM in the literature [11; 26; 33], it showed that the plastic strain calculated by the revised SMP model can well describe the deformation properties of UGM. The Mohr-Coulomb and Druck-Prage models cannot characterize the process of long-term load performance.
## 4 Experimental Validation
### Case 2: Laboratory Bearing Dataset of Shenzhen Technology University (SZTU)  
#### 4.2.1 Experimental Apparatus  
In addition to the experimental verification on the above public dataset of PU, the laboratory motor fault diagnosis test rig is used to conduct experiments and collect relevant data. The test rig can provide fault data for motors and bearings and mainly consists of the following modules: motor, frequency transformer, rolling bearing, magnetic particle brake, and junction block. The specific details of the test rig are shown in Figure 10. By replacing the bearings of different fault categories, the corresponding two-phase current signal in the frequency transformer is extracted at a sampling frequency of 40.96 kHz. All the test bearings are of type UCPH206. There are five types of faulty bearings, excluding healthy bearings; their specific descriptions are shown in Table 7. The load torque of the magnetic particle brake can be adjusted between 0 and 50 N\(\cdot\)m according to the load braking current since the torque is linear with the current. According to rotational speed and different load sizes, a total of four groups of experiments are designed, which are shown in Table 8. To ensure sufficient sample points, each group is extracted for 12 s and repeated 20 times. Finally, the data are saved as a MATLAB file (such as FBM_1_C.mat).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **Class** & **Type** & **Accuracy** \\ \hline ViT & 5 & M & 51.8\% \\ ISCV-ResNet50 & 5 & M & 81.9\% \\
**ISCV-ViT** & **5** & **M** & **95.4\%** \\
[53] & 4 & M & 96.3\% \\
[54] & 3 & M & 97\% \\
[55] & 3 & M & 97.2\% \\
[56] & 5 & M\&E & 92.4\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparison between the proposed method and relevant works.  
Figure 10: The composition of the motor fault diagnosis test rig.
## 4 Proposed System  
Sensor networks are vulnerable to many types of security attack. A malicious node tries to create blocks that occur while messages are being transferred between sensor nodes in the network by, for instance, forwarding a message along another path, generating an inaccurate network route, and delaying the transfer of packets between nodes. With a limited radio communication range, wireless sensor nodes communicate with each other by a multi-hop path [16]. In a sensor network area, data are sent to the base station through routers. An attacker compromises the nodes by attacking the network resources. Selective forwarding attacks destroy the packets transmitted between the source and base station. For this purpose, a malicious node refuses to transfer the whole packet, attempting to drop considerable data and therefore, the whole packet is not transferred to the base station. Furthermore, physical attacks frequently occur in WSNs because they are easy for adversaries to execute. Selective forwarding attacks can seriously impact the data collection of WSNs and data will be lost with compromised sensor nodes [17]. Selective forwarding detection (SFD) discovers a secure route for data to be sent from one node to other  
Figure 1: Selective Forwarding Attacks-Redrawn [15].  
nodes. In this section of the paper, we introduce the assumptions and a multi-layer approach for detecting selective forwarding attacks.