esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 State-Of-Art
### Synthesizer Parameters Optimization  
In the past years, the automatic parameterization of synthesizers has been the subject of several studies [3, 4, 16]. All of these approaches share the objective to optimize the correspondence between the generated sound and a given target sound. In the approach proposed by [PERSON] et al. [2], audio descriptors such as the _Mel Frequency Cepstral Coefficients_ (MFCCs) are used to evaluate the perceptual similarity to the target sound. This similarity is then iteratively refined during the search phase by weighting the different descriptors based on relevance feedback provided by the user [2]. Although this approach allow for user interaction, it seems to be very inaccurate and slow. Severalapproaches were proposed based on genetic algorithms and Genetic Programming (GP) [17] in order to automatically construct modular synthesizer patches that approximate a given target sound. The heuristic is conditioned on a set of input control functions (target amplitude and frequency over time). The approach proved quite successful, managing to retrieve complicated frequency modulation sounds with high precision. Yet, the main limitation of this system is that it induce very high computation times, with as much as 10 to 200 h required to produce a single audio approximation. Hence, this renders the approach unusable in realistic studio or stage contexts. [PERSON] et al. [16] compared different optimization techniques, namely _genetic programming_, iterative _hill-climbing_, a single-layer artificial _neural network_ and a simple nearest neighbour algorithm performed on a grid sampling of the parameter space of the synthesizer. In this study, the genetic programming approach appears to provide the best results. Very recently, [PERSON] et al. [4] tackled the same problem by using more advanced recurrent neural networks (bidirectional LSTMs). However, the number of parameters and complexity of the sounds studied remains in a quite low setting.  
All of these approaches share the same flaws that they do not account for the non-linear relationships that exist between parameters and the corresponding synthesized audio, nor do they provide higher-level controls than the target-based parameters inference task. Here, we argue that it is mandatory to unveil the relationships between the _auditory_ and _parameters_ spaces of a synthesizer, and show that it provides multiple forms of high-level control.
## 4 Applications of AR and VR in Dentistry
### AR and VR in Paediatric Dentistry  
Pediatric dentistry is one of the most challenging specialties of dentistry as the commonest factor determining the treatment outcomes in such patients is their compliance. To improve patient cooperation and compliance, different tools have been used ranging from the armamentarium of the dentist, such as behavior modification, and pharmacological interventions. Pediatric patients who are visiting the dental practice often present with tremendous amounts of anxiety as most of the time it is their first interaction with dentists [30]. So, managing the anxieties and behavior of children is one of the crucial factors in patient management.  
To decrease the levels of anxiety and stress of such patients, virtual reality is one of the innovative tools that have been discussed in the literature, although to a limited extent. Different techniques to manage anxiety include in vivo exposure therapy (IVET) and virtual reality exposure therapy (VRET). IVET consists of the direct confrontation of patient's fear to reduce their anxiety levels and this method has been categorized as a gold standard method. VRET is a recent technique that consists of computer-generated images for patients where the simulation makes the patient experience their fears without facing them in reality, thereby helping them to reduce their anxiety [31]. In a study by [PERSON] et al. [9], the effect of virtual reality on the behavioral management of children was studied, where it was concluded that the average anxiety and behavioral scores of the patients with virtual reality was significantly reduced as compared to the control group. Since virtual reality makes use of interactive and creative audiovisual representations of information that is attractive to children, such a method of anxiety reduction can be beneficial.  
Another study by [PERSON] et al. [10] assessed the effect of virtual reality on the pain and anxiety of pediatric patients during infiltration anesthesia, where it was found that virtual reality was effective in reducing the anxiety and stress of these patients. Since the patients experience the entire scenario virtually before the actual procedure commences, this helps patients to understand the treatment and face their fears. So, one of the most important factors that determine the treatment outcomes in patients in this age group is the anxiety and stress associated with visiting the dental practice. Virtual reality can help to provide an artificial environment that is more relaxing for the patients, which can help them forget their fears.
# A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks
## 4 Heterogeneous WBAN Simulator  
The analysis of the selected algorithms' usefulness for the adaptive bitrate control requires the development of a reliable simulator of a heterogeneous WBAN for off-body communication. Reliable is understood as the most accurate representation of the real phenomena occurring in these types of networks, starting from the mean system loss, through distribution of fading, and ending with the distribution of RDMs values.  
In current research, the efficiency analysis of the adaptive bitrate algorithms is carried out using simulators that enable the determination of channel parameters, deployment of network nodes, or the implementation of communication protocols. These simulators, e.g., OMNeT++, NetworkSimulator, enable effective multidimensional analysis of sensor networks for the same propagation environments, without a time-consuming implementation of individual algorithms on the real devices. It allowsthe comparison of all methods under the same conditions, which gives a reliable assessment of their usefulness and efficiency.  
However, constantly evolving simulation software is mainly designed for standardized homogeneous sensor networks, e.g., ZigBee or Bluetooth. The implementation of a heterogeneous WBAN, which uses previously described methods of adaptive data streams allocation, would be very difficult. For this reason, the authors have taken the task of developing an original simulation tool. The results of the real measurements as the input parameters of the simulator were used. Thus, it enables a reliable reconstruction of the radio link specificity of a heterogeneous WBAN, including the radio channel parameters, variable user movement speed, corridor design, or simultaneous operation of the NB and UWB RIs.
## 1 Introduction
In the context of this work, we take an end-to-end look at the data management process, i.e., we deal with data acquisition, data refinement, data storage, and data provision. 3. We present a concept for a novel reliable information retrieval and delivery platform, called REFINERY Platform, which addresses the data administration challenges, we have identified. In this context,'reliable' refers to both the data producers--in those terms, it is ensured that sensitive data are handled in a trustworthy manner--and the data consumers--in those terms, it is ensured that data have the promised quality. The remainder of this paper is structured as follows: In Section 2, we elaborate on the characteristics of data that inherently distinguish them from tangible commodities and address specific and novel challenges that arise when handling such intangible assets. We provide an overview of the state of the art in modern data administration in Section 3 and discuss how it responds to these challenges. Based on these findings, we introduce our concept of the REFINERY Platform in Section 4. This holistic end-to-end concept not only takes into account the unique characteristics of data but also addresses the weaknesses of current approaches. We then assess our approach in Section 5. To this end, we present a security and privacy assessment, a feature discussion, a case study, and a performance evaluation. Finally, the lessons learned are summarized in Section 6.
## 3 Results
### Relationships between SIF and GPP and between NDVI and GPP  
Figure 4 shows the spatial distributions of the correlations between the SIF (NDVI) and the GPP obtained in different seasons. During the growing season, the PCC values (Figure 4a,e) mainly ranged from 0.80 to 1.00 (for SIF) and from 0.20 to 0.60 (for NDVI) in the SC. In the YGP, the PCC values ranged from 0.80 to 1.00 (for SIF) and from \(-0.50\) to 0.80 (for the NDVI). The SIF had a higher degree of consistency with the GPP than the NDVI during the growing season. During spring, negative PCC values were found in the western YGP and QTP regions (Figure 4b,f), indicating that the SIF had a higher degree of consistency with the GPP than the NDVI did in southwestern China. There was a large amount of BSV coverage in the northwestern part of China, and GPP data were missing in these areas [4; 28]. The missing data resulted in gaps in coverage for the northwestern part of China. The relations between the SIF (NDVI) and the GPP during the other two seasons were similar to those identified during the growing season.  
To further analyze the relationships between the SIF (NDVI) and the GPP, the correlations between the SIF (NDVI) and the GPP were calculated for different land-cover types, as shown in Figure 5. As shown in Figure 5a, during the growing season, the SIF and the GPP showed relatively strong correlations for most of the land-cover types except for the EBF and the BSV; the NDVI and GPP also showed high correlations for most of the land-cover types except for the ENF, EBF, and CS. However, the PCC values derived between the SIF and the GPP were essentially greater and less variable than those obtained between the NDVI and the GPP. During spring (Figure 5b), a significant correlation was found between the SIF and the GPP, while the correlation between the NDVI and the GPP was relatively small, and the fluctuation ranges of the PCC values were relatively large in the regions characterized by the ENF, EBF, DNF, and DBF land-cover types. During summer (Figure 5c), the PCC values obtained between the SIF (NDVI) and the GPP fluctuated widely. In particular, the correlations were all relatively small in regions characterized by forest vegetation types, and the fluctuation ranges were relatively large. During autumn (Figure 5d), the PCC values derived between the SIF and the GPP were large, while those  
Figure 4: Spatial distributions of the correlations between GPP and SIF (**(a)** growing season; **(b)** spring; **(c)** summer; and **(d)** autumn) and between GPP and NDVI (**(e)** growing season; **(f)** spring; **(g)** summer; and **(h)** autumn).  
obtained between the NDVI and the GPP were smaller, especially in the regions comprising ENF, EBF, and CS vegetation. Overall, the correlations between the SIF and the GPP were more significant than those between the NDVI and the GPP.
# Integrity Monitoring of PPP-RTK Positioning: Part II: LEO Augmentation
###### Abstract  
Low Earth orbit (LEO) satellites benefit future ground-based positioning with their high number, strong signal strength and high speed. The rapid geometry change with the LEO augmentation offers acceleration of the convergence of the precision point positioning (PPP) solution. This contribution discusses the influences of the LEO augmentation on the precise point positioning--real-time kinematic (PPP-RTK) positioning and its integrity monitoring. Using 1 Hz simulated data around Beijing for global positioning system (GPS)/Galileo/Beidou navigation satellite system (BDS)-3 and the tested LEO constellation with 150 satellites on L1/L5, it was found that the convergence of the formal horizontal precision can be significantly shortened in the ambiguity-float case, especially for the single-constellation scenarios with low precision of the interpolated ionospheric delays. The LEO augmentation also improves the efficiency of the user ambiguity resolution and the formal horizontal precision with the ambiguities fixed. Using the integrity monitoring (IM) procedure introduced in the first part of this series of papers, the ambiguity-float horizontal protection levels (HPLs) are sharply reduced in various tested scenarios, with an improvement of more than 60% from 5 to 30 min after the processing start. The ambiguity-fixed HPLs can generally be improved by 10% to 60% with the LEO augmentation, depending on the global navigation satellite system (GNSS) constellations used and the precision of the ionospheric interpolation.  
integrity monitoring; PPP-RTK; LEO; GNSS; L5
# Multi-Level Credit Assignment for Cooperative Multi-Agent Reinforcement Learning
## 2 Background  
### Dec-POMDPs Formulation  
Dec-POMDPs serve as a general framework for cooperative multi-agent tasks and we also adopt this formulation in the paper. Dec-POMDPs can defined as  
\(M=\langle S,A,P,R,O,n,\gamma,T\rangle:\)  
* \(S\) is a finite set of hidden states;
* \(A\) is a finite set of joint actions;
* \(P\) is the transition model and \(P(s_{t+1}|s_{t},a_{t})\) represents the probability of next state \(s_{t+1}\) when all agents select joint action \(a_{t}\in A\) at state \(s_{t}\);
* \(R\) is the reward function which returns one total credit for all agents when they choose \(a_{t}\in A\) at state \(s_{t}\), i.e \(R(s_{t},a_{t})\);
* \(O\) is the observation function where agent \(i\) obtains its own observation \(o_{i}\in O(s,i)\);
* \(n\) is the number of agents, \(\gamma\in[0,1]\) is the discount factor;
* \(\gamma\) is the discount factor;
* \(T\) is the decision-making timestep set.  
Following this setting, each agent receives its current observation \(s\), selects its action \(a\) based on \(s\) and executes. Then, the environment reacts to all agents' actions and returns the next observation \(s^{\prime}\) and a global reward for each agent according to the transition model and reward function \(R\). It is worth noticing that each agent can neither see the actual state of the world nor explicitly communicate with each other, which explains the difficulty of finding optimal policies for agents. Thus, each agent aims to learn unilaterally to cooperate with others and maximize the cumulative global reward, which can be defined as the total Q-value, i.e., \(Q_{tot}(s,a)=E[\sum_{t=0}^{T}\gamma^{t}R(s_{t},a_{t})|s_{0}=s,a_{0}=a]\).
## 6 Simulation Setup and Results
### Summary of Results and Main Findings
* There is only one drawback with using event-driven DSS techniques: although the downtime is very limited, short periods with high packet loss of a few seconds are possible. For this simulation study, conservative link statistics measurements were used for detecting interference events. Interference was only detected after packets have been lost. This could be mitigated by applying techniques for the prediction of interference events (e.g., more advanced SINR analytics for early detection of SINR degradation or pattern recognition of recurring interference events using artificial intelligence and machine learning techniques) and proactive resource reallocation before packet loss occurs.
# Planning-Level Optimisation of Headway Regularity
###### Abstract  
Headway variability has a negative impact on the public transport passengers' perception of service quality. However, most of the existing methods aimed at improving the headway regularity operate in real time and require precise vehicle location data, making it difficult to implement them in practice. On the other hand, planning-level methods can be used to increase the resilience of public passenger transport (PPT) to the accumulation of headway disturbances. As this is typically done from the operator's perspective, the passengers' perspective tends to be overlooked, motivating the current work. In this article, an optimisation procedure for evaluating the viability of diametrical line splitting in terms of passenger travel time and headway regularity is proposed. The aim is to increase the robustness/resistance of the PPT system to the propagation of headway disturbances without reducing the service quality. The developed optimisation procedure was validated by applying it to real data pertaining to an urban PPT line. The results show that there is a positive correlation between the transport demand and the effects of the optimisation procedure, whereby an increase in the primary headway disturbance increases the sensitivity of the optimisation procedure to the transport demand.  
public passenger transport; headway regularity; disturbance propagation; travel time
## 3 Models' Application  
### Input Selection  
We employed a hybrid approach for input selection. This technique was applied to six inputs for predicting the PPV values. The model was developed using the following parameters and settings: the tree growing algorithm was set to CHAID; the maximum tree depth was set as five; the minimum records in parent and child branches were assigned to two and one, respectively; the number of component models for boosting was selected as 10, and significance level for splitting and merging was set as 0.05. The accuracy of the CHAID and boosted CHAID models were 79.6% and 0.89%, which showed the superiority of the boosted model over the single tree model. According to the boosted-CHAID model results, four inputs, including distance (m), stemming (m), powder factor (kg/m\({}^{3}\)), and maximum charge per delay (kg), were the most important predictors/variables for the PPV forecast. Then, these critical inputs were used to apply the SVM models with diverse Kernels to predict the PPV caused by quarry blasting.
# Image Encryption Algorithms: A Survey of Design and Evaluation Metrics
###### Abstract  
Ensuring confidentiality and privacy is critical when it comes to sharing images over unsecured networks such as the internet. Since widely used and secure encryption methods, such as AES, Twofish, and RSA, are not suitable for real-time image encryption due to their slow encryption speeds and high computational requirements, researchers have proposed specialized algorithms for image encryption. This paper provides an introduction and overview of the image encryption algorithms and metrics used, aiming to evaluate them and help researchers and practitioners starting in this field obtain adequate information to understand the current state of image encryption algorithms. This paper classifies image encryption into seven different approaches based on the techniques used and analyzes the strengths and weaknesses of each approach. Furthermore, this paper provides a detailed review of a comprehensive set of security, quality, and efficiency evaluation metrics for image encryption algorithms, and provides upper and lower bounds for these evaluation metrics. Finally, this paper discusses the pros and cons of different image encryption approaches as well as the suitability of different image encryption approaches for different applications.  
image encryption; chaotic system; DNA encoding; compressive sensing substitution; permutation +
Footnote †: journal: Cybersecurity and Privacy  
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## 4 Soft-Collision M* (SC-M*)
### Soft-Collision Constraint on Common Resources
#### 4.1.2 Definition 2 (Collision Score)  
We use the resource experience results from Definition 1 to calculate the _collision scores_. This is defined from the view point of collision probability, that must be constrained under some threshold. Let  
* \(Col_{j}\) be the event that agent \(j\) announces a collision (i.e., when agent \(j\) calls for one of the resources, the allocated resource is less than satisfying);
* \(D^{j}=\{D_{1}^{j},\ldots,D_{L}^{j}\}\), where \(D_{k}^{j}=D\left(\pi^{j},A_{k}\right)\), be the set of dissatisfying experiences of agent \(j\) along path \(\pi^{j}\) on the resource \(A_{k}\); and
* \(f_{k}\in f=\{f_{1},\ldots,f_{L}\}\) be a customized cumulative distribution function (CDF) defined on \([0,+\infty)\), mapping the resource experience \(D\) to a probability of collision on the resource \(A_{k}\).  
The _collision score_ of the agent \(j\) is defined as the probability of how likely a collision occurs to the agent \(j\) on _at least_ one of the resources given its resource experience \(D^{j}\):  
\[P\left(Col_{j}\middle|D^{j}\right)=1-\prod_{k\in\{1,\ldots,L\}}\left(1-f_{k}(D_ {k}^{j})\right). \tag{8}\]  
Note that \(P\left(Col_{j}\middle|D^{j}\right)\) calculates the _complement_ of the success probability--the joint probability of being tolerable at all resources.  
Figure 2 shows two example designs of \(f\): \(f_{1}(D)=sigmoid(D-\delta)\), with a discontinuity point \(f_{1}(0)=0\), is a sigmoid-based CDF function, featuring a surge in the collision score (the derivative is bump-shaped) at the experience value around \(\delta\). This function is suitable to important resources that are sensitive to the agent; \(f_{2}(D)=min(1,D/(4\delta))\) is a linear CDF with a shallow slope (the derivative is flat). This function can apply to trivial resources that are not very sensitive to the agent but still accumulate to contribute to the collision score. We use the offset parameter \(\delta\) to adjust the _tolerance level_  
of the dissatisfying experience. With larger \(\delta\), the agent will tolerate a longer unpleasant experience before announcing a collision.  
Although the definition of the collision score can be customized according to different practices, the probabilistic definition of collision score introduced here is a general one: Different types of resources may have different value ranges, and Equation (8) standardizes the resource ranges, mapping them to a value within \([0,1]\) and enabling an efficient integration of different types of resources to the framework.
###### Abstract  
The undrained shear strength in cohesive soils can be evaluated based on measurements obtained from the standard dilatometer test (DMT) using single- and multi-factor empirical relationships. However, the empirical relationships presented in the literature may sometimes show relatively high values of the maximum relative error. The add-on seismic module to the seismic dilatometer test (SDMT) extends parameters measurable in a standard dilatometer test by the shear wave velocity \(V_{s}\) as an independent variable. Therefore, a method for evaluating the undrained shear strength in cohesive soils based on data obtained from the seismic dilatometer test is presented in this study. In the method proposed, the two-factor empirical relationship for evaluating the normalized undrained shear strength \(\tau_{\mu}\)/\(\sigma^{\prime}v\) is used based on independent variables: The normalized difference between the corrected second pressure reading and the corrected first pressure reading \((p_{1}-p_{o})\)/\(\sigma^{\prime}v\) and the normalized shear wave velocity \(V_{s}\)/100. The proposed two-factor empirical relationship provides a more reliable evaluation of the undrained shear strength in the tested Pleistocene and Pliocene clays in comparison to the empirical relationships presented in the literature, with a maximum relative error max \(RE\) at about \(\pm\)20% and the mean relative error \(RE\) at about 8%.  
Keywords:cohesive soils; undrained shear strength; seismic dilatometer test; statistical analysis +
Footnote †: journal: Applied