esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Evaluation of the Machine Learning Models
Moving on to scenario 2, the highest and lowest RMSE values were observed with XGB at 5.19 and XGB-SVR at 3.28, respectively. In scenario 3, higher RMSE values were evident compared to other scenarios, with the highest values under RF and RF-XGB-SVR at 19.55 and 19.24, respectively, and the lowest RMSE value under RF at 17.5. For scenario 4, the highest and lowest RMSE values were found with XGB at 4.44 and SVR at 3.37, respectively. Finally, in scenario 5, the highest and lowest RMSE values were registered with XGB at 5.01 and XGB-SVR at 3.99, respectively (Figure 11).
# Energy Efficient Management of Pipelines in Buildings Using Linear Wireless Sensor Networks
## 3 Proposed Solution  
In recent years, researchers have used evolutionary approaches such as Genetic Algorithm and Ant Colony Optimization (ACO) [27] for solving the deployment problem in LWSNs. In [27], the authors claimed that evolutionary algorithms can solve the node deployment problem in LWSNs effectively and efficiently. Recently, a new evolutionary approach namely Lion Optimization Algorithm [28] has been proposed which has been proven better than the other existing techniques and has been used in several areas. The Ant Colony Optimization is more suitable for a single straight pipeline because the ants move in a straight-line one behind the other in one direction only. However, the problem considered in the paper includes multiple pipelines, and the data is to be sent to the Base Station  
Figure 2: Multiple straight pipelines.  
(BS) from multiple directions by the sensor nodes as shown in Figure 2. The group hunters such as lions attack the prey from multiple directions, and the Lion Optimization Algorithm tries to use this characteristic of lions to find the optimal solution of the problem being considered. This motivated us to use Lion Optimization Algorithm (LOA) for optimal node placement and Base Station (BS) in LWSN including multiple pipelines. To the best of our knowledge, LOA has not been used by any other researchers for this purpose.
## 3 Analysis of High Ground Temperature Monitoring Results  
### Project Overview  
A deep buried hydraulic tunnel in Xinjiang was selected as the studied object. It has a total length of 18 km and a general elevation of 3200-5000 m. The joint development is complex, mainly consisting of three groups of joints, namely J\({}_{1}\):71\({}^{\circ}\)NW \(\angle\) 89\({}^{\circ}\), J\({}_{2}\):55\({}^{\circ}\)NW \(\angle\) 42\({}^{\circ}\), and J\({}_{3}\):64\({}^{\circ}\)NW \(\angle\) 68\({}^{\circ}\). The joint surfaces are mostly straight without fillers and penetrate the tunnel. During the branch tunnel construction of this project, a high-temperature tunnel section with a total length of about 4111 m was found, with the pile number ranging from 2 + 688 m to 6 + 799 m. This section is located in the upstream and downstream sections of the 2\(\#\), 3\(\#\), and 4\(\#\) construction branch tunnels. During the excavation process, the highest temperature inside the tunnel reached around 80 \({}^{\circ}\)C. The high-temperature zone with the pile number ranging from 3 + 500 m to 5 + 500 m between the 2\(\#\) and 3\(\#\) branch tunnels was selected for analysis in this study. The profile of the tunnel section is shown in Figure 4.
# 4D-Flow MRI Characterization of Pulmonary Flow in Repaired Tetralogy of Fallot
## 2 Materials and Methods
### 4D-Flow Data Analysis  
All analyses were conducted by a single investigator using a prototype 4D-flow module within cvi42 version 5.11.5. The workflow for the plane and volume analysis included: (1) Pre-processing corrections included, when it was needed, eddy currents, velocity aliasing, and static tissue, Figure 2A; (2) To segment the entire volume of the pulmonary artery (PA), the phase-contrast angiogram (PC-MRA) was divided into sub-volumes including the main pulmonary artery (MPA), the right PA (RPA), and the left PA (LPA) for hemodynamic assessment; and (3) Six planes were placed along the PA at the  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Bandwidth** & **Repetition Time** & **Echo Time (ms)** & **Spatial Resolution (mm3)** & **Phases** &
\begin{tabular}{c} **Temporal** \\ **Resolution (ms)** \\ \end{tabular} \\ \hline
455–495 & 4.53–5.07 & 2.01–2.35 & 2.0–3.6 \(\times\) 2.0–3.0 \(\times\) 2.5–3.5 & 30 & 25–35 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Acquisition parameters for 4D flow.  
Figure 1: Pulmonary artery diameter measurement. Middle panel shows the contrast-enhanced magnetic resonance angiogram (CE-MRA) used to calculate the pulmonary artery (PA) diameter. For finding the appropriate mild PA location, multi-planar reconstruction (MPR) allowed us to freely navigate the volume, as it showed in the blue, green, and orange planes. An MPR maximum intensity projection was used for the green plane to accurately project the PA volume. Red arrows show samples of diameter measurements.  
following positions: pre-pulmonic, pulmonic valve, mid-pulmonary, pre-bifurcation, and 1 cm into both the left and right bifurcations, see Figure 2B. The following hemodynamic parameters were calculated at each plane position: total volume, peak velocity, regurgitant fraction, PD using pre-pulmonic plane as reference, WSS, and EL. Volume samples for WSS, PD, and EL are presented in Figure 2C-E.  
Then, VFA was performed by placing the inflow plane at the tricuspid valve and pulmonic valve. The flow area was manually traced on each valve plane at each phase of the cardiac cycle. The isovolumetric relaxation phase (right heart valves closed) at the end systole was used to release particles, characterizing the flow distribution. Four flow components of the right ventricle (RV) were obtained: direct flow (flow enters and exits from the RV), retained inflow (flow remaining in the RV), delayed ejection (part of the existing RV flow exiting the RV during ejection), and residual volume (flow entering the RV but retained for more than one cycle), see Figure 2F.
## 2 The Proposed Approach
### Demonstration of Hypothesis Rationality  
In this paper, it is assumed that the return of WEEE reverse logistics sites conforms to the second-order randomness, and the demonstration is given as follows.  
(1) From the perspective of the research object: the Kriging method traditionally studies the storage capacity of ore in different mines in a certain area, and different mines are represented by geographical coordinates. The research object of this paper is the WEEE return amount of different recycling sites in a certain area, and each recycling site is also represented by geographical coordinates. Both studies are aimed at the spatial relationship between variables with a correlation under different geographical coordinates in a certain area, and the situation is similar.  
(2) From the perspective of randomness: traditionally, the Kriging method predicts the ore quantity of unknown mines by the ore quantity of several known mines, and the ore quantity of each mine is uncertain and random. In this paper, the Kriging method is used to predict the WEEE return amounts of the unknown recycling site based on the return amounts of several known sites. The return amount of each site is also uncertain and random.  
(3) From the perspective of the constant overall mean value: due to the formation of geological structure, the total amount of ore storage in a certain area is determined, and the overall mean value is unchanged. Nevertheless, the distribution of ore storage amounts among different mines are different. For WEEE recycling, as long as the environmental protection related laws, regulations, policies and the environmental awareness of the residents remain stable in a certain area, the overall return amount of WEEE will not change much. Meanwhile, the return amounts of different recycling sites will be distributed randomly and differently, which is the same as the ore storage distribution.  
(4) From the perspective of the covariance analysis: whether it is in case of ore volume prediction or WEEE return prediction, the covariance of ore storage/return amount of any two mines/recycling sites is only dependent on the distance between these two mines/recycling sites. The farther the distance is, the weaker the correlation will be, and vice versa. From this perspective, the properties of covariance in these two cases are similar.  
The results of category demonstration are shown by Table 1.  
Therefore, compared with the traditional ore storage, the WEEE return in this paper conforms to the second-order randomness hypothesis of Kriging method.
## 2 Jamming Attack Models
### Jamming Attack Models from Academia
#### 2.2.2 Models of [PERSON] _et al._[11]  
The S-MAC protocol has these time segments: synchronization, listening, control, data, and sleep. [PERSON] _et al._[11] have suggested four types of energy-efficient jammers for attacking a network following the S-MAC protocol:  
* _Periodic Listening Interval Jammer_ attacks when the nodes are in listening period and sleeps at all other times.
* _Periodic Control Interval Jammer_ attacks when the nodes are in the control period and sleeps during rest of the time.  
* _Periodic Data Packet Jammer_ listens to the channel during the control interval and attacks the data segment.
* _Periodic Cluster Jammer_ is meant for attacking networks following encrypted packets. It uses k-means clustering algorithm to separate clusters of the network and statistical estimations to determine the timing of the data segment, and then attacks the same accordingly.
## 5 Conclusions  
The Paper reported on a data coding technique for high data rate low power optical wireless biotelemetry using sub-nanosecond pulsed laser as data transmitter and small sensitive area photodiode as data receiver. The implementation of this approach, based on an optical pulsed UWB synchronised-COK modulation, through FPGA board and prototype PCB with discrete off-the-shelf components allowed us to achieve a 128 Mbps data rate, a BER less than \(10^{-9}\) and a power efficiency of 35.9 \(\mathrm{J}\)/bit. These values have been obtained by inserting a diffuser between the transmitter and the receiver to emulate skin/tissue barrier. The achieved results demonstrate that the proposed approach enables, for example, the transmission of an 800-channel neural recording interface sampled at 16 kHz with 10-bit resolution for high performances (i.e., high data rate and good power efficiency) optical wireless implantable biotelemetry. The overall architecture that implements the developed technique has been designed to be integrated on-chip in a compact Si footprint lower than 1 mm\({}^{2}\) with about 180 transistors. In this regard, a suitable design of the complete circuitry in a proper standard technology (e.g., Bi-CMOS) and the use of fast pulsed lasers and high-speed photodiodes, will allow us to achieve high performances wireless optical links with data rates up to few Gbps. Finally, the presented optical pulsed coding technique can be also applied to bidirectional transcutaneous biomedical platforms for very high data rate and ultra low power optical wireless biotelemetry that would integrate a transmitter-receiver in the implantable unit and the corresponding receiver-transmitter in the external unit.  
The Authors contributed equally to this work. In particular: [PERSON] developed the new technique, implemented the analogue circuitry and performed experimental measurements. He contributed to writing and editing the manuscript. He coordinated the manuscript elaboration. [PERSON] optimised the use of the optoelectronic/photonic components, implemented the experimental set-up and analysed the data. He contributed to writing and editing the manuscript. [PERSON] developed, simulated and implemented the digital architectures on FPGA. He contributed to writing and editing the manuscript. [PERSON] developed the digital architectures and analysed the data. He contributed to writing and editing the manuscript. [PERSON] simulated and implemented the digital architectures on FPGA and performed tests and experimental measurements. He contributed to writing and editing the manuscript. [PERSON] supplied the overall system specifications and constrains, contributed in theoretical discussions and analysed the data. He contributed to writing and editing the manuscript.  
The authors declare no conflict of interest.
## 4 Results and Discussion
Therefore, the increase in temperature leads to a decrease in the NOx conversion efficiency, but the overall remains in a high conversion efficiency range (above 95%). \[4 NH_{3}+5O_{2}\to 4 NO+6H_{2}O \tag{15}\]  
On the other hand, the SCR inlet temperature is the main factor affecting the NOx conversion efficiency at low engine exhaust flow rates. The increase in exhaust temperature increases the chemical reaction rate inside the SCR. Therefore, at low exhaust flow rates, the NOx conversion efficiency shows a rapid increase with increasing temperature. When the exhaust flow rate is higher, the effect of SCR inlet temperature on NOx conversion efficiency becomes smaller and smaller with the increase of exhaust flow rate, but the increase of exhaust flow rate makes NH\({}_{3}\) slip more likely to occur, so the overall NH\({}_{3}\) slip shows a rising trend. Finally, the NH\({}_{3}\) slip always stays below 10 ppm throughout the SCR operating interval, as shown in Figure 5f. The optimized urea injection amount was written into the ECU, and the diesel engine was tested for the WHTC cycle. The cumulative NOx emissions are shown in Table 10. After optimization, the NOx accumulation of World Harmonized Transient Cycle (WHTC) is 1.62 g, and the test results show that the optimized urea injection rate can effectively reduce the NOx accumulation of the WHTC cycle, and the reduction is about 7.5%.
# Value Creation with Digital Twins: Application-Oriented Conceptual Framework and Case Study
## 5 Use Case: Shiptec
### From Data to Value  
This section describes how the data is used to create value with the DT seen in Figure 14. The ship's onboard systems already structured the product-related data received by the DT. Weather data added from external systems are an example of context data, and data from the internal CRM system are an example of customer data. The data from the three data sources arrive at the DT of Shiptec in various formats. For instance, engine data is structured and can be analyzed and interpreted either by the DT or by human users. The DT uses rule-based algorithms for power consumption optimization. Other services, such as error localization, require additional interpretation by human users using dashboarding tools. In this case, the DT of the ship analyzes data from the operation of the ship in combination with data from internal systems and can thus detect anomalies. However, interpretation by a Shiptec employee is required to locate the error further before taking action. The main interface between human users and the DT is the dashboard, where users can demand services or where services are proactively offered to them by the DT.  
Figure 13: Data flow at Shiptec.  
In addition, some services, such as schedule optimization for the ship operators, are provided by the ship's owner, in this case, SVG. Based on these services, the DT provides value propositions on three levels: availability, performance, and quality. The availability of the ship is increased by better adherence to schedules through optimization of ship deployment and fewer unforeseen breakdowns and service operations. Regarding performance, improved energy and fuel efficiency results in a smaller environmental footprint and cost savings. With the help of the intelligent HVAC system, Shiptecs DT optimizes air conditioning to increase passenger comfort and customer satisfaction regarding quality. Concerning smartness maturity, Shiptec covers two of the three in the application-oriented DTF distinguished levels: control and optimization. Currently, the focus is on controlling crucial functions and processes. However, some of the systems are already self-optimizing. For example, the propulsion system self-optimizes the energy and fuel consumption of the ship. The potential further development of the smartness of the DT and the additional services enabled by it are discussed in Section 6.1.
## 4 Harmonic Estimation Scheme  
The distorted signal can be considered as the sum of fundamental response and harmonic component. Each harmonic has its own amplitude and phase, and a frequency that is integral multiple of the fundamental response. Therefore, the sinusoidal acceleration response of the shaking table at time \(t\) can be expressed by  
\[a(t)=\sum_{n=1}^{N}A_{n}\sin(n\omega t+\phi_{n}) \tag{5}\]  
where \(N\) represents the order of the harmonic; \(\omega\) is the fundamental frequency; \(A_{n}\) and \(\phi_{n}\) are the amplitude and phase of \(n\)th harmonic, respectively.  
The discrete time version of Equation (5) can be represented as  
\[a(k)=\sum_{n=1}^{N}A_{n}\sin(n\omega k+\phi_{n}) \tag{6}\]  
Figure 4: Flow chart of the simulated annealing algorithm.  
For estimating amplitude and phase, Equation (6) can be rewritten as  
\[a(k)=\sum_{n=1}^{N}\left(A_{n}\cos\phi_{n}\sin n\omega k+A_{n}\sin\phi_{n}\cos n \omega k\right) \tag{7}\]  
Define \(x_{n1}=A_{n}\cos\phi_{n}\), \(x_{n2}=A_{n}\sin\phi_{n}\). Then, Equation (7) can be written as  
\[a(k)=\sum_{n=1}^{N}\left(x_{n1}\sin n\omega k+x_{n2}\cos n\omega k\right) \tag{8}\]  
Sinusoidal signal in parametric form becomes  
\[a(k)=\mathbf{h}(k)\mathbf{x}(k) \tag{9}\]  
where \(\mathbf{h}(k)=\left[\sin\omega k,\,\cos\omega k,\,\sin 2\omega k,\,\cos 2 \omega k,\,\cdots,\sin N\omega k,\,\cos N\omega k\right]^{\mathrm{T}}\) is the input vector and \(\mathbf{x}(k)=\left[x_{11},\,\,x_{12},\,x_{21},\,x_{22},\,\cdots\,\,x_{N1},\, \,x_{N2}\right]^{\mathrm{T}}\) is the weight vector.  
The estimation model for the algorithm is  
\[\hat{a}(k)=\mathbf{h}(k)\hat{\mathbf{x}}(k) \tag{10}\]  
where \(\hat{\mathbf{x}}(k)\) is the estimation weight vector.  
The estimate value \(\hat{\mathbf{x}}(k)\) for the requested parameters \(\hat{\mathbf{x}}(k)\) can be obtained by minimizing the objective function  
\[f(\mathbf{x})=\sum_{n=1}^{N}\left[e(k)\right]^{2}=\sum_{n=1}^{N}\left[a(k)- \hat{a}(k)\right]^{2} \tag{11}\]  
The harmonic estimation scheme based on simulated annealing algorithm can be illustrated with Figure 5. The sinusoidal acceleration response is used as desired signal, and the reference harmonic generates the input vector. The error between the actual value and the estimated value is optimized using simulated annealing algorithm. The problem is formulated as an optimization problem, where the goal is to minimize the objective function. After updating the weight vector, the amplitude and phase of the fundamental and \(n\)th harmonic are derived as follows  
\[\left\{\begin{array}{l}A_{n}=\sqrt{x_{n1}^{2}+x_{n2}^{2}}\\ \phi_{n}=\tan(x_{n2}/x_{n1})\end{array}\right. \tag{12}\]  
Figure 5: Block diagram of the harmonic estimation scheme.  
Moreover, fundamental as well as each harmonic can be directly extracted from the final updated weights  
\[\hat{a}_{n}(k)=x_{n1}\sin n\omega k+x_{n2}\cos n\omega k \tag{13}\]
# L-rCBF: Learning-Based Key-Value Data Structure for Dynamic Data Processing
## 2 Related Work
### Network Applications Using Bloom Filter Variants  
BF variants have been used in various network applications, such as IP address lookup, NDN, packet classification, and distributed systems, because BF structures can filter and search for specific information and the structures are space-efficient. Depending on the purpose of each application, appropriate BF variants can be utilized. For IP address lookup, an efficient prefix-matching algorithm is required to identify the longest prefix. Because a BF can filter out unnecessary accesses, parallel BF and BF-chaining methods were proposed for longest prefix matching [2; 3].  
In NDN, efficient name lookup algorithms are required in forwarding information base (FIB) and pending interest table (PIT). For FIB lookup, because name-based longest prefix matching should be performed for URL data, an index data structure was proposed with a hash table and a CBF to balance the load [4]. For PIT lookup, an efficient exact-matching algorithm is required, and frequent update operations (i.e., insertions and deletions) are performed. Hence, BF-based PIT architectures were proposed using the FBF and rCBF [5].  
Packet classification is a technique to categorize network traffic using multiple header fields to implement quality of service. In software defined networking (SDN), because more fields are used for packet classification, the flow table with all the information is stored in an external memory. Packet classification algorithms using BF variants, such as a standard BF, cuckoo BF, and LBF, were proposed to reduce the number of accesses to the external memory [7; 8].  
In distributed systems, two tasks exist: reconciliation to obtain the union of the sets of two hosts and data deduplication to eliminate duplicate data between two hosts [9; 10; 15]. In the tasks, the set difference between two hosts should be efficiently computed, and communication complexity should be minimized. Because of space and access efficiencies, BF structures (i.e., a standard BF and an invertible BF) were used for the tasks [9; 11].
###### Abstract  
Impaired motor control and musculotendon tightness in the lower extremities are characteristic features of patients with diplegic cerebral palsy (CP). Tendon release surgery (TRS) helps improve joint and leg stiffness, but the effects of TRS on inter-limb coordination in terms of the total leg stiffness, and the bilateral symmetry in leg stiffness during gait, remain unknown. Ten children with spastic diplegic CP scheduled for TRS and ten healthy controls participated in this study. The inter-limb sharing of total leg stiffness during double-limb support phase and bilateral leg stiffness symmetry during stance phase of gait were calculated using the kinematic and ground reaction force data measured by a motion analysis system. Before TRS, the patients with diplegic CP walked with a decreased share of total leg stiffness during weight-acceptance (\(p<0.05\)) and with increased bilateral leg stiffness asymmetry during single-limb support and weight-transfer during gait (\(p<0.05\)) when compared to healthy controls. After TRS, the bilateral leg stiffness asymmetry was significantly reduced in the CP group, especially in the terminal stance phase, with inter-limb sharing of total leg stiffness becoming similar to that in controls (\(p>0.05\)). The surgery seemed to improve the lower limb control and increased the bilateral limb symmetry during gait.  
cervical palsy (CP); gait analysis; leg stiffness; inter-limb sharing; symmetry +
Footnote †: journal: Applied Sciences
## 2 Data and Methods
### Methods
#### 2.2.4 Model Performance Assessment  
The performance of TL-LUEn, TL-LUE, and MOD17 was assessed using root mean square error (RMSE) and determination coefficient (R\({}^{2}\)). The paired \(t\) test was then conducted to evaluate the significance regarding the differences in R\({}^{2}\), RMSE between TL-LUEn and TL-LUE, TL-LUEn and MOD17, and TL-LUE and MOD17 when all vegetation types lumped together at three temporal scales for model evaluation, respectively [13].