esa-sceva/satcom-chunk-collection huggingface dataset:
# DAG Hierarchical Schedulability Analysis for Avionics Hypervisor in Multicore Processors
## 4 Schedulability Analysis
### Analysis of Response Time
#### 4.2.2 Bounding \(\alpha_{i}\) and \(\beta_{i}\)  
For \(v_{j}\), it can subject to interference (\(I_{j}\)) from the concurrent joints upon arrival. Until constraint \(h(v_{j})\), first distinguish two particular senses in which the interference of a joint \(v_{j}\) is 0 in Theorem 4, \(C(v_{j})\) provides \(v_{j}\)'s concurrent joints, \(\wedge V\) is paths in a given joint set \(V\) and \(|\cdot|\) returns the size of a given set.  
**Theorem 4**.: _According to a schedule with CPPE, joint \(v_{j}\) does not lead to any interference from its concurrent joints \(C(v_{j})\), if \(v_{j}\in\delta^{*}\vee\left|\Lambda_{C(v_{j})/\delta^{*}}\right|<m-1\)._  
Proof.: First, the interference of \(v_{j}\) is zero if \(v_{j}\in\delta^{*}\). This is enforced by CPFE, where a critical node always starts immediately after all nodes in \(predecessor(v_{j})\) have finished their executions.  
Second, a node \(v_{j}\in V^{\
eg}\) does not incur any interference if \(\left|\Lambda_{C(v_{j})\setminus\delta^{*}}\right|<m-1\). The concurrent nodes that can interfere \(v_{j}\) on \((m-1)\) cores are \(C(v_{j})\setminus\delta^{*}\). Given that the number of paths in \(C(v_{j})\setminus\delta^{*}\) is less than \(m-1\), at least one core is idle when \(v_{j}\) is ready so that it can start directly with no interference.  
**Theorem 5**.: _With respect to the end joint \(v_{e}\) in the longest path of \(H(\phi_{i}^{*})\), \(h(v_{e})=h(H(\phi_{i}^{*}))\)._  
Proof.: Given two paths \(\delta_{a}\) and \(\delta_{b}\) with length \(L_{a}>L_{b}\) and a total workload of \(C\), it follows that \(h(\delta_{a})=L_{a}+\left(C-L_{a}\right)/m\geq h(\delta_{b})=L_{b}+\left(C-L_{ b}\right)/m\), as \(h(\delta_{a})-h(\delta_{b})=L_{a}-L_{b}+\left(L_{b}-L_{a}\right)/m\geq 0\). Therefore, node \(v_{e}\) with \(h(v_{e})=h(H(\phi_{i}^{*}))\) gives the end node of the longest path in the interfering workload.  
**Theorem 6**.: _The leading joint of the end joint \(v_{e}\) in the longest path of \(H(\phi_{i}^{*})\) is given by \(\operatorname*{argmax}_{v_{j}}\{h(v_{j})\left|\forall v_{j}\in predecessor(v_{e}) \cap H(\phi_{i}^{*})\right\}.\)_Proof.: Given \(v_{a},v_{b}\in predecessor(v_{c})\) with \(h(v_{a})\geq h(v_{b})\), we have \(length(\delta_{v_{a}}\cup v_{c})>length(\delta_{v_{b}}\cup v_{c})\). Therefore, the predecessor node of \(v_{\ell}\) with the latest finish is in the longest path ending with \(v_{e}\) in \(H(\phi_{i}^{*})\).
# A CNN-RNN Combined Structure for Real-World Violence Detection in Surveillance Cameras
## 4 Experimental Results
### Dataset  
In this paper, we implement the proposed model on the UCF-Crime dataset [27] including lots of abnormal, illegal and violent behaviour captured by surveillance cameras in public places like schools, stores, and streets. The reason for selecting this dataset is that this dataset is extracted from actual everyday events that can happen every day and everywhere. Moreover, these kinds of abnormal behaviours can lead to severe problems for individuals and society. Several papers use some handcrafted dataset or a particular dataset with the same background and environment (i.e., hockey fight dataset and movie dataset), which is rarely found in our daily routine. This dataset includes long untrimmed surveillance camera feeds in 13 categories of anomalous events (i.e., Abuse, Arrest, Arson, Assault, Road Accident, Burglary, Explosion, Fighting, Robbery, Shooting, Stealing, Shoplifting, and Vandalism) as well as Normal events category. Figure 4 indicates part of the UCF-Crime dataset. To have a fair comparison with other works in this field, we used 75% of data for training and 25% for testing in our experiments.  
Figure 4: Examples of UCF-Crime dataset.  
We used four variants of the UCF-Crime dataset: Ucfcrimes, Binary, 4 MajorCat, and NREF. The Ucfcrimes is our original dataset in which we have 14 classes. While in the Binary, we consider all 13 abnormal events as one class of anomalous. In the 4 MajorCat, we categorized the abnormal events into three big groups versus one normal group. Therefore, the three groups named Theft (i.e., Burglary, Robbery, Stealing, Shoplifting), Vandalism (i.e., Arson, Road Accident, Explosion, Vandalism), and Violence behaviours (i.e., Abuse, Arrest, Assault, Fighting, Shooting). The NREF is another manipulated data that focuses only on three anomalies (Road Accident, Explosion, and Fighting). In this dataset, instead of using predefined abnormal and normal videos, in each abnormal video, the segments include anomalies considered abnormal. In contrast, the rest of the video file is labeled as normal. Besides, we trimmed all videos in NREF into 10 seconds videos to have more related frames from each file. The number of videos for each category for Ucfcrimes and Binary datasets are shown in Table 1. Furthermore, Table 2 indicates the number of videos for 4 MajCat and NREF datasets.
## 2 Numerical Simulation
### Governing Equations  
When numerically approaching phenomena that cause large deformations, such as explosions, it is important to address contact and element distortion problems. These element distortions can lead to analysis errors, and one effective way to solve this problem is to use the Coupled Eulerian Lagrangian (CEL) modeling technique. The CEL modeling technique was first proposed by [PERSON] [24], who demonstrated that issues related to element distortion and the flow of Lagrangian materials can be alleviated when describing the motion of microvolume elements over time by combining the advantages of Lagrangian and Eulerian techniques [25]. In the calculation of the CEL modeling method, the Euler  
Figure 1: The main distribution pattern of global underground salt cavern gas storage (image from Ref. [22], data from Ref. [23]).  
Figure 2: Conceptual design of underground hydrogen storage facility in Korea.  
and Lagrange meshes can be set simultaneously, depending on the specific problem, and a penalty function combination is applied at the interface. The governing equations consist of the continuity, momentum, and energy conservation equations [26; 27]:  
\[\frac{D\rho}{Dt}+\rho\
abla\cdot v=\frac{\partial\rho}{\partial t}+v\cdot\
abla \rho+\rho\
abla\cdot v=0 \tag{1}\]  
\[\rho\frac{Dv}{Dt}=\
abla\cdot\sigma+\rho\cdot b \tag{2}\]  
\[\rho\frac{DE}{Dt}=\sigma\cdot\dot{\epsilon}+\rho\dot{Q} \tag{3}\]  
where \(D\rho/Dt\) and \(\partial\rho/\partial t\) are the material and spatial time derivatives of \(\rho\), respectively, \(\rho\) is the density of air (kg/m\({}^{3}\)), \(\
abla\) is a vector differential operator, \(v\) is the airflow vector, \(\sigma\) is the Cauchy stress tensor (Pa), \(b\) is the unit resultant force tensor, \(E\) is energy (J), \(\dot{\epsilon}\) is train rate, and \(\dot{Q}\) is heat conductivity (W/(m\(\cdot\)K)).
# Life Cycle Assessment of Mortars Produced Partially Replacing Cement by Treated Mining Residues
###### Abstract  
The use of secondary mining resources to replace conventional constituents in mortars production has proved the effectiveness to preserve the quality of mechanical, physical, and chemical properties. However, minimal research has been performed to quantify the environmental impacts of mortars with mining residues. In the present work, a life cycle assessment of 10 mortars was carried out. A reference mortar (100% of cement binder) and mortars with cement substitutions in 10%, 25%, and 50% by raw, electrodialytic treated, and electrodialytic plus thermal treated mining residues were analysed. The impacts were studied in six environmental categories: (1) abiotic depletion; (2) global warming; (3) ozone depletion; (4) photochemical ozone creation; (5) acidification; and (6) eutrophication potentials. The results demonstrated that mortars formulated with raw mining residues may decrease the environmental impacts, namely in global warming potential (55.1 kg CO\({}_{2}\) eq./t modified mortar). Considering the treatments applied to mining residues, the major mitigations were reported in photochemical ozone creation (\(-99\%\)), ozone depletion (\(-76\) to \(-98\%\)), and acidification potential (\(-90\) to \(-94\%\)), mainly due to the disposal impacts avoided in comparison to the reference mortar. Analysing all mortars' constituents and their management options, products with electrodialytic treated mining residues showed higher influence in ozone depletion (18 to 52%). Coupling a thermal procedure, mining residues contributed for 99% of the abiotic depletion potential of mortars.  
life cycle assessment; environmental impact; mortar; secondary mining resources; electrodialytic technology; thermal treatment +
Footnote †: journal: Applied Sciences  
0
Footnote 0: Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.**
# The Efficiency of Binaural Beats on Anxiety and Depression--A Systematic Review
## 3 Results
### Gait Assessment in Neurologic Pathology  
Among the studies eligible for this review, one investigated the use of binaural beats as a therapeutic intervention for individuals diagnosed with Parkinson's disease. [PERSON] et al. [30], in addition to assessing anxiety levels, explored the potential impact of binaural beats on the gait patterns of patients. Upon conducting their assessments, they did not observe any significant association between binaural beats and gait, except for an increase in patients' cadence when exposed to music tuned at 120 beats per minute (bpm).
# An Efficient Multi-Lane SpaceFibre Core for Spacecraft Data-Handling Networks
## 4 FPGA Implementation and Analysis
### Performance Analysis  
The previous analysis shows that the E-ML-SpFi core saves more resources compared with other designs, and this conclusion is also confirmed in terms of recovery time. We utilize recovery time to quantify the performance of multi-lane SpaceFibre cores. The recovery time after a lane failure consists of two contributions: the Multi-Lane layer recovery (MLRec) time and the Data-Link layer recovery (DLRec) time [23]. The MLRec time begins with the moment when the Lane layer starts to send IDLEs. The MLRec time ends when the last multi-lane control word is sent and the alignment FSM moves to the Both-End Ready state. The beginning of DLRec time is a RETRY control word transmitted by the near end, and the ending is an EDF control word sent by the same end.  
Because the total recovery time of cases with two VCs appears to be higher than that of the cases featuring one VC [23], Table 2 provides the overall recovery time of cases with two VCs. There are two test cases in Table 2. One case has only one data-sending lane at the beginning, and the second lane is then reactivated (this process can be denoted as Case 1.) Another case starts with two data-sending lanes, and one of the lanes is then disconnected (using Case 2 to represent this process.) In Table 2, Each case is repeated 100 times and the results are averaged. The average DLRec time in Case 1 of both designs is approximately equal. In Case 1, the E-ML-SpFi core has the similar average MLRec time as the design in [23]. In Case 2, the average MLRec time of the E-ML-SpFi core is reduced by 21.6% compared with the design in [23]. The average DLRec time in Case 2 of the E-ML-SpFi core is decreased by 33.2%. Benefiting from the architecture of hierarchical error recovery and fast alignment, the E-ML-SpFi core can save an average 11.8% and 30.8% of total recovery  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline
\begin{tabular}{c} 8115 \\ (1.99\%) \\ \end{tabular} & 613 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Evaluation of hardware utilization.  
time in the two cases, respectively. The retry process can be completely restored in the 4.36 us to 4.56 us range with the system frequency of 62.5 MHz. As a result, the E-ML-SpFi core can achieve an improvement in recovery time.
###### Abstract  
This paper describes the vibration characteristics of a dual-bimorph piezoelectric pumping element under fluid-structure coupling. Unlike the single bimorph used in most previous studies, the proposed device comprises two piezoelectric bimorphs within an acrylic housing. Amplitude-fluctuation electronic speckle pattern interferometry (AF-ESPI) was used to examine the visible displacement fringes in order to elucidate the anti-phase as well as in-phase motions associated with vibration. Analysis was also conducted using impedance analysis and laser Doppler vibrometer (LDV) based on the measurement of point-wise displacement. The experimental results of resonant frequencies and the corresponding mode shapes are in good agreement with those obtained using finite element analysis. The gain of flow rate obtained by the anti-phase motion of the dual-bimorph pumping element is larger than both those obtained by in-phase motion and the single bimorph pumping element. This work greatly enhances our understanding of the vibration characteristics of piezoelectric pumping elements with two bimorphs, and provides a valuable reference for the further development of bionic pump designs.  
Keywords: piezoceramic pump; piezoelectric bimorph; solid-liquid coupled vibration; amplitude-fluctuation electronic speckle pattern interferometry (AF-ESPI); laser Doppler vibrometer (LDV); impedance analysis +
Footnote †: journal: Applied Physics Letters
# Using Full Pose Measurement for Serial Robot Calibration
## 3 Determination of Link Twist  
To ensure that forward kinematics correctly predict the tool pose in the robot coordinate frame, the DH parameters must be determined first during the robot calibration process. Once calibrated, they remain fixed during robot on-line operations. Calibration may be performed by installing a spherically-mounted retro-reflector (SMR) at the robot's TCP, and tracking it with a laser tracker. From four vectors of DH parameters \((\mathbf{\alpha},\mathbf{\epsilon},\mathbf{r},\mathbf{d})\), the twist angles \(\mathbf{\alpha}\) can be determined independently of other DH parameters by using 3D data acquired for CPA procedure. The twist angle \(\alpha_{n}\) is defined as the angle between two consecutive joint axes of rotation, \(\mathbf{u}_{n}\) and \(\mathbf{u}_{n+1}\) (the last twist \(\alpha_{N}\) is, by definition, set to zero). If \(\mathbf{C}_{n,K}\) denotes a set of \(K\) 3D points \(\mathbf{t}_{k}\) calculated in (8) and acquired for \(n\)-th joint in CPA procedure, then these points are distributed along an arch (section of a circle) on a plane in 3D space. Thus, for each joint \(n=1,...,N\), a unit vector \(\mathbf{c}_{n}\) normal to the fitted plane can be calculated. While the exact locations of \(\mathbf{C}_{n,K}\) points depend on all DH parameters \((\mathbf{\epsilon},\mathbf{\alpha},\mathbf{r},\mathbf{d})\), vector \(\mathbf{c}_{n}\) is parallel to the axis of rotation \(\mathbf{u}_{n}\) and, therefore, \(\alpha_{n}\) can be determined from the scalar product of two consecutive axes, \(\alpha_{n}=\arccos\left(\mathbf{c}_{n}\cdot\mathbf{c}_{n+1}\right)\). If \(\mathbf{B}_{n,K}\) is the set of 3D points measured by laser tracker which correspond to \(\mathbf{C}_{n,K}\), then a unit vector \(\mathbf{b}_{n}\) normal to the plane fitted to \(\mathbf{B}_{n,K}\) can be calculated and the angle between two consecutive \(\mathbf{b}_{n}\) and \(\mathbf{b}_{n+1}\) is used as the estimate of \(\alpha_{n}\).  
To get correctly estimated twist angles \(\alpha_{n}\), two important steps must be followed. First, since \(\arccos\left(\right)\) is an even function, a sign of estimated angle must be equal to the sign of the default (i.e., theoretical) twist angle, \(sign(\alpha_{0,n})\). Second, plane fitting procedure provides only a normal to the plane, its particular direction (up or down) depends on a bounding box containing the points. To remove this ambiguity, fitted normal \(\tilde{\mathbf{b}}_{n}\) must obey the right hand rule together with acquired 3D points \(\mathbf{B}_{n,K}\), which are located on a section of a circle. Thus, the estimated corrected twist angle \(\tilde{\alpha}_{n}\) is determined as  
\[\tilde{\alpha}_{n}=sign(\alpha_{0,n})\arccos\left(\tilde{\mathbf{b}}_{n}\cdot \tilde{\mathbf{b}}_{n+1}\right). \tag{9}\]
## 2 Main Results
### UAV Yaw-Channel Model  
In UAV helicopters, which are distinct from other types of robots because of their small-scale structure, the torque associated with the yaw control channel is provided with high sensitivity. To enhance the performance of helicopter yaw control, we consider a more precise model to characterize the yaw channel. In this paper, the model is adopted from [39], the framework of a rigid body UAV helicopter.  
Based on [10], the yaw channel dynamic equation is described as  
\[\left\{\begin{aligned} \dot{\varphi}&=r\\ I_{zz}\dot{r}&=-Q_{mr}+T_{tr}l_{tr}+b_{1}r+b_{2}\varphi \end{aligned}\right. \tag{1}\]  
where \(\varphi\) and \(r\) are the helicopter's yaw angle and angular rate and \(I_{zz}\) is the inertia around the z-axis. The z-axis is perpendicular to the design axis of the helicopter and points at the nose and below the fuselage in the helicopter's symmetrical plane. \(Q_{mr}\) is the torque of main rotor, \(T_{tr}\) is the thrust of tail rotor, \(l_{tr}\) is the distance between the tail rotor and z-axis, and \(b_{1}\) and \(b_{2}\) are damping constants.  
By using the blade element method [39], the torque \(Q_{mr}\) can be formulated as  
\[Q_{mr}=\int_{R_{0}}^{R}\left(\frac{\rho\Omega^{2}r^{2}C_{l}c\phi}{2}+\frac{ \rho\Omega^{2}r^{2}C_{d}c}{2}\right)rdr \tag{2}\]  
therein, \(\phi=v_{1}/(\Omega r)\), \(C_{l}=a\alpha\), \(C_{d}\approx C_{d0}+C_{d1}\alpha+C_{d2}\alpha^{2}\), where \(\rho,a,r,a,c,v_{1},\phi\) and \(\Omega\) are the density of air, slope of the lift curve, speed radial distance, angle of attack of the blade element, chord of the blade, induced speed, inflow angle, and rotor speed of the main rotor, respectively.  
The non-affine nonlinear yaw-channel model is rewritten as  
\[\left\{\begin{aligned} \dot{\varphi}&=r\\ I_{zz}\dot{r}&=b_{1}r+b_{2}\varphi-(k_{Q_{2}}\theta_{mr }^{2}+k_{Q_{1}}\theta_{mr}+k_{Q_{0}})+(k_{T_{2}}\theta_{tr}^{2}+k_{T_{1}} \theta_{tr}+k_{T_{2}})l_{tr}\end{aligned}\right. \tag{3}\]where \(k_{Q_{2}},k_{Q_{1}}\) and \(k_{Q_{0}}\) are decided by the shape of the blades and the speed of the main rotor, \(\theta_{mr}\) is pitch angle of main rotor, \(k_{T_{2}},k_{T_{1}}\) and \(k_{T_{0}}\) depend on the shape of the blades and the speed of the tail rotor, \(\theta_{tr}\) is pitch angle. According to Equation (3), the yaw dynamics of a UAV helicopter can be represented by a second-order time-varying non-affine system with input nonlinearity. The input nonlinearity is mainly caused by the main rotor collective, the speed of main rotor, and the speed of tail rotor.  
The deduction process of non-affine nonlinear helicopter yaw-channel model is given in the Appendix A.
## 3 Theoretical Background
### Baseline Models  
In order to benchmark the results of the DL methods that we propose, we select two methods to compare with, namely, the Stacked Single-Target (SST) method and a modified Ensemble of Regression Chains (ERC), both of them being state-of-the-art methods in multi-output regression [23; 24]. It is important to note that these two methods build an independent regression model for each time step in the output curve \(y\).
## 3 Case Study  
In this study, the performance of our moving window decision-making algorithm was compared with the previous method using a fixed time horizon. Figure 2 shows the 10-unit HEN system chosen for this purpose, which was adopted from the work of [PERSON] and [PERSON] [15]. This HEN system uses 6 different heat sources and some heat exchanger units share the same heat source interconnectedly. While the crude oil passes through a series of heat exchangers, its temperature increases up to the crude inlet temperature, CIT. The effect of fouling in the heat exchangers results in the decrease of CIT, which requires extra energy consumption in the furnace after all.  
The model parameter values of each heat exchanger used in the simulation studies are summarized in Table 1. Other common parameters are: \(U_{c}=88.1\) BTU/ft\({}^{2}\) h \({}^{\circ}\)F, \(\Delta t^{CL}=0.2\) month, \(\Delta t^{OP}=0.8\) month, \(\eta_{f}=0.75\), \(C_{E}=2.93\)\(\pounds/\)MM BTU, and \(C_{C}=4000\)\(\pounds/\) cleaning action, which was also adopted from the work of [PERSON] et al. [18]. In our study the  
Figure 1: Scheme of HEN cleaning schedule decision-making algorithm using the moving window method.  
Figure 2: Schematic diagram of 10-unit HEN system; solid lines, cold (crude) streams; dashed lines, hot streams; CIT, crude inlet temperature to furnace; the temperature given in each stream represents the value at initial cleaned condition; adopted from [15].  
target temperature entering the furnace was 420 \({}^{\circ}\)F. The following operational constraints were also considered during the simulation studies: only one unit of exchangers 1-4 can be cleaned in each period; only one unit of exchangers 5-7 can be cleaned in each period; there is a temperature drop (18 \({}^{\circ}\)F) across desalter.  
All simulation studies were conducted using the MATLAB software (MATLAB(r) R2016b) together with Optimization Toolbox(tm) and Parallel Computing Toolbox(tm) (The MathWorks Inc., Natick, MA, USA, 2016). We used the 'ode15s' for the solver of DAEs and the 'fmincon' for the optimizer with the option of Sequential Quadratic Programming (SQP) algorithm. To compare the computational time for optimization, all simulations were conducted on a single desktop PC of which spec is rather outdated (3 GHz Intel Core i5, 8 GB RAM).
# An Emergency Message Routing Protocol for Improved Congestion Management in Hybrid RF/VLC VANETs
## 1 Introduction
### Paper Outline and Contributions
The remainder of the paper is organized as follows. In Section 2, some related work in the areas of emergency message routing in VANETs, interference avoidance techniques, and congestion detection algorithms, are discussed. In Section 3, the considered system model is described, including the network architecture, channel characterization, and propagation models. In Section 4, our proposed algorithm is described, outlining the zone partitioning and RSU assignment approach, the methodology, the emergency message broadcasting protocol, and the congestion prediction and mitigation scheme. In Section 5, our proposed protocol is evaluated by simulations and compared against the predefined benchmark schemes in terms of packet delivery ratio and transmission delay. Finally, Section 6 concludes the paper.