esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Related Research Analysis  
The most current TE applications are intended for software-defined networking [3; 7; 8; 9; 16; 18; 21; 23; 26; 27; 28]. While a significant number of solutions found their field of use in wireless networks [4; 6; 19; 20; 23], Internet of Things technology [18; 24; 28], smart cities [8; 18; 23], edge, and fog computing [8; 19; 28]. Particularly noteworthy are the developments of complex (joint) solutions for TE-based load balancing problems and ensuring network fault tolerance [8; 17; 21; 22]. The following overview was performed based on analyzing existing TE solutions research results in promising telecommunication networks (Table 1). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Ref. ** & **Contribution** & **Underlying Approach** & **Field of Application** \\ \hline \multirow{4}{*}{[10]} & Legacy networking devices’ gradual deployment to SDN switches, using traffic engineering measures such as minimizing the highest link utilization.
# No-Wait Job Shop Scheduling Using a Population-Based Iterated Greedy Algorithm
## 2 No-Wait Job Shop Scheduling Problem (NWJSP) with Makespan Minimization  
### Problem Statement  
The NWJSP involves a set of machines and a set of jobs which have to be processed on the machines. Each job has its own processing route, namely its own sequence of operations. Each operation is associated with a processing time and a processing machine. The no-wait constraint holds for each job, which means no waiting time is allowed between two consecutive operations of the same job. Besides, we have the following assumptions: (1) all the jobs and machines are available at time zero; (2) at any time, a machine can process at most one job, and a job can be processed on at most one machine; (3) preemption is not allowed; (4) the set-up, release, and transfer time is incorporated in the processing time; (5) no job is allowed to reenter previous machines.  
The objective is to find a feasible schedule that minimizes the maximum completion time of all jobs, namely the makespan.
# Nucleotides as Bacterial Second Messengers
## 2 The c-di-GMP Nucleotide
### Exopolysaccharide as a Target of c-di-GMP  
The polysaccharide intercellular adhesin (PIA), also known as the poly-\(\beta\)(1-6)-N-acetylglucosamine (PNAG) component of the biofilm matrix, is produced by a wide variety of Gram-negative and Gram-positive. In _E. coli_, _Yersinia pestis_, and _Pectinobacterium atrosetitum_, c-di-GMP activates the PNAG biosynthesis [31].  
In _E. coli_ K-12, two DGCs, DoSc (YddV) and YdeH, are involved in PNAG-dependent biofilm formation, as DoSc affects the transcription of the pgaABCD operon and YdeH stabilizes the transmembrane protein glycosyltransferase PgaD. The mechanism of PNAG synthesis is by binding of c-di-GMP to PgaC and PgaD proteins (both transmembrane glycostransferases) leading to their interaction and stimulation of glycosyltransferase activity [32].  
Interestingly, PNAG is also produced in _Staphylococcus epidermidis_ and _Staphylococcus aureus_. However, the mechanism of PNAG biosynthesis is independent of c-di-GMP. In fact, in staphylococci there is no c-di-GMP signaling, since only proteins with functional GGDEF domains (GdpS) are present [33].
## 3 Distance Vector-Hop (DV-Hop) and Differential Evolution (DE) Algorithms
### Differential Evolution Algorithm
#### 3.2.1 Initialization  
DE uses \(NP\) D-dimensional real-valued parameter vectors as the population of each generation, and the \(t-th\) generation is denoted as \(x_{i}^{t}=\left[x_{i,1}^{t},x_{i,2}^{t},\cdots,x_{i,D}^{t}\right]\). Let the boundary of the parameter variable be \(x_{j}^{(L)}<x_{j}<x_{j}^{(U)}\), the initial value of the \(i-th\) individual is generated by Equation (9).  
\[x_{i,j}^{0}=x_{j}^{(L)}+\left(x_{j}^{(U)}-x_{j}^{(L)}\right)*rand[0,1] \tag{9}\]  
where \(rand[0,1]\) represents a uniform random number generated between \([0,1]\), \(i=1,2,\cdots,NP\), \(j=1,2,\cdots,D\).
# Study of Mixed-Mode Cracking of Dovetail Root of an Aero-Engine Blade Like Structure
## 2 Problem Description  
The aim of this work is to study the effect on crack propagation of two important design variables of the geometry of the dovetail root in a compressor blade-like structure like the one shown in Figure 1.  
The design variables are shown in Figure 2, on a cross section sketch of the 3D root. They are:  
* The length of the contact flank (Figure 2).
* The flank angle \(\vartheta\) (Figure 2).  
Three flank design angles were investigated: 30\({}^{\circ}\), 45\({}^{\circ}\), and 60\({}^{\circ}\). For each of these flank angles, two flank lengths were investigated. The short flank was 6.5 mm whilst the long flank was 13 mm. For only one specific case (each analysis takes around 1 week to run on a 12 processors PC), the 45\({}^{\circ}\) model with a short flank, the effect of two different friction coefficients (0.1 and 0.7) was studied in order to understand the difference between a perfect frictionless contact and the contact between two worn surfaces.  
For the same geometry, two different crack propagation criteria were investigated: A crack driven by an opening mode K\({}_{\text{I}}\) and a crack driven by mixed-mode represented by K\({}_{\text{eq}}\)[14]. All the crack propagation analyses were performed under LCF, with a ratio of R = 0. It is important to remark that in the aero-engine industry, LCF is intended as the cyclic application of the major load (centrifugal force and aerodynamic pressure in the case of a blade) and its release. The R-ratio is 0. In other words, in LCF, no vibration is taken into account. Linear elastic fracture mechanics can still be applied as the  
Figure 1: A dovetail joint between the compressor-blade-like structure and the disc representative geometry.  
Figure 2: The flank length and flank angle, the design variables in this study.  
material is far from yielding, with the only exception of a small region close to the crack tip. Given that R = 0, the notation \"K\" or \"\(\Delta\)K\" is therefore used equivalently in this paper.  
The initial flaw was assumed as a corner crack. This option was given by [PERSON] and [PERSON] in [PERSON] et al. [1]. The other option to be used, as discussed in [1], would be a semi-elliptic side crack. In reference [1], experimental evidence of these options was also provided.  
In this paper, the authors chose the corner crack as the stress field calculated with a finite element model which gave its peak towards the edge of the contact. A crack is more likely to start there.
# Gaussian Mixture Reduction for Time-Constrained Approximate Inference in Hybrid Bayesian Networks +
## 6 Conclusions  
We have developed an extended message passing algorithm for CG hybrid Bayesian networks to overcome the exponential growth in components of the Gaussian mixture model. Our experiments demonstrated scalability, accuracy and optimal settings for the complex hybrid BNs. In our experiments, both the original hybrid message passing inference and the hybrid junction tree inference showed exponential growth in execution time. The Gaussian mixture reduction method presented in this paper addressed this problem. Another issue we should address was to define ways to choose the optimal settings to achieve desired accuracy and execution time. For this, we presented a pre-processing algorithm to optimize the maximum allowable number of components and the optimal maximum iteration.  
The algorithm enables HMP-GMR to provide better accuracy within a predefined time. For the four CLG BNs we investigated, we observed that the accuracy from using a single Gaussian component was nearly as good as the setting found by our optimization method and the difference in accuracy was not statistically significant. Note that other networks with complex topologies, very unlikely evidence configurations and/or deterministic or near-deterministic relationships might be different. We observed that the accuracy results for a loopy CG BN were less than for a poly CG BN. To address this, we can use a clustering inference (e.g., Hybrid-JT) with Gaussian mixture reduction. These issues will be addressed in future work.  
Conceptualization, C.Y.P. and S.M.; methodology, C.Y.P.; software, C.Y.P.; validation, C.Y.P. and K.B.L.; formal analysis, C.Y.P.; investigation, K.B.L.; writing-original draft preparation, C.Y.P.; writing-review and editing, K.B.L.; supervision, K.B.L. and P.C.G.C.; project administration, P.C.G.C.; funding acquisition, P.C.G.C.  
The research was partially supported by the Office of Naval Research (ONR), under Contract#: N00173-09-C-4008.  
**Acknowledgments:** We appreciate [PERSON] and [PERSON] for the initial research regarding HMP-GMR.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 4 Results
### Validation
In addition to the comparison with WW3 data, the InIRA SWH values were statistically compared with collocated traditional altimeter data, as illustrated in Figure 8. The figure shows that the statistical RMSEs with JASON2, JASON3, SARAL, and HY2A are 0.46, 0.55, 0.40, and 0.49 m, respectively. All BIASs are within 0.2 m. To obtain unified statistics, we simply averaged the RMSEs and BIASs of the data from the four types of traditional altimeters. The average RMSE and BIAS are 0.48 m and 0.02 m, respectively. The comparisons indicate that the retrieved InIRA SWHs also have consistency with the traditional altimeter data. Figure 6: SWH comparison between InIRA retrievals and collocated WW3 data. Figure 7: SWH accuracy trends in terms of **(a)** BIAS with incidence angle; **(b)** RMSE with incidence angle; **(c)** BIAS with relative wave direction; and **(d)** RMSE with relative wave direction.
# Multidimensional Study on Users' Evaluation of the KRAKEN Personal Data Sharing Platform
## 1 Introduction
This paper presents a multidimensional evaluation of a blockchain-based platform developed in the H2020 project KRAKEN (BroKeRage and MArKet platform for pErsoNal data, grant agreement No 871473) to enable personal data sharing in the health and education domains [16]. KRAKEN is devoted to developing a trusted and secure personal data platform using cutting-edge privacy preserving analytics technologies. Metadata and query privacy are also guaranteed, allowing data providers to control their personal and sensitive data, facilitating and encouraging citizens to share data [17]. The main pillars of the KRAKEN solution are the Self-Sovereign Identity (SSI) paradigm that provides a decentralized user-centric approach for access control to data, where the data provider controls their data and their later use under explicit user consent; the provision of different analytic techniques based on advanced crypto tools to enable privacy-preserving data analysis, by ensuring end-to-end secure data sharing, using tools such as SMPC (Secure Multi-Party Computation), FE (Functional Encryption), PRE (Proxy Re-Encryption), or ZKP (Zero Knowldege Proof); and, finally, a data marketplace that brings both pillars together on an open and decentralized exchange system leveraging blockchain and smart contracts, following GDPR (General Data Protection Regulation), allowing privacy preserving sharing of personal data in the health and education pilot domains, and developing fair-trading protocols and incentive models to be applied on the data space domain [18]. Results from group interviews with initial testers of the KRAKEN prototype helped us to better understand users' expectations, preferences, and possible concerns in adopting such a system for personal data sharing in the two piloting domains.
# A Peak Absorption Filtering Method for Radiated EMI from a High-Speed PWM Fan
## 2 Circuits Structure and Radiated EMI Measurement  
### Drive Circuit Structure and Speed Control Strategy  
The axial flow fan is driven by a PWM permanent magnet brushless DC motor. The drive circuit mainly consists of a control chip, a MOSFET drive circuit, an inverter circuit, a protection circuit, and a winding coil, as shown in Figure 3.  
The inverter circuit adopts a three-phase half-bridge inverter topology consisting of six power MOSFETs. The control chip outputs a gate drive signal by recognizing the duty cycle of the modulated square wave to control the switching of the MOSFETs, thus changing the winding terminal voltage to adjust the motor speed. In this paper, the fan adopted the HPWM-LON modulation mode, i.e., the power MOSFETs in the upper bridge arm were controlled by the PWM signal, while the MOSFETs in the lower bridge arm were continuously conducting within one cycle of phase alternation. The modulation frequency was 15.5 kHz. Figure 4 shows the waveforms of each bridge arm drive signal in the time domain during the modulation process. Q1, Q2, and Q3 are the drive signals for MOSFET in the upper bridge arm, and Q4, Q5, and Q6 are the drive signals for the ones in the lower bridge arm.  
Figure 3: Schematic diagram of the fan drive system.
# An Untraceable Data Sharing Scheme in Wireless Sensor Networks
## 5 Secure Data Sharing between the Source Node and Sink Node
### Data Delivery from the Source Node to the Sink Node  
At the border of the cloud, the fake source nodes send the shares to the sink node independently. To hinder the adversary locating the cloud easily, we integrate the All-direction Random Routing algorithm (ARR) [21] into our scheme. In the ARR scheme, the relay node is defined as the nearest node to the virtual location that is randomly selected by the source node. To balance the security and energy-efficiency of our scheme, the fake source node employs only one relay node and the possible area of the virtual location is presented in Figure 6. Initially, the real source node randomly selects a parameter \(R\) for message \(X\) and adds the parameter to all the shares of \(X\). Then, the fake source node selects the virtual location based on parameter \(R\). Specifically, the virtual location can be any point on the half circle with the source node as the center and \(R\) as the radius.  
In theory, the adversary needs to first find the relay node, the fake source node and, finally, the real source node. As shown in Figure 6, the shares of message \(X\) are transmitted to the sink node from different directions. Therefore, it is almost impossible for the local adversary to locate the relay nodes, let alone the fake source node and the real source node. For different real source nodes and messages, the fake source nodes, relay nodes are totally different. The adversary cannot receive continuous package flows and hence the adversary can hardly trace back to the cloud. However, the adversary  
Figure 5: An example of cloud with two real shares.  
Figure 6: The possible area of the relay nodes.  
may occasionally locate the cloud sometime and, in this case, he still cannot find the real source node, because all the nodes in the cloud are indistinguishable.  
Both simulation and theoretical analysis show that our network has a similar performance with typical WSNs in terms of energy consumption about the surrounding nodes of the sink node. Specifically, the nodes near to the sink node in both our network and a typical network have a similar life time. This can be explained by the fact that though more packets are delivered to the sink node, they are much shorter in length compared with the original messages. Overall, the total transmission amount of data that is received by the sink node is similar and considering that the locations of the targets are uniformly randomly generated in the network, the nodes around the sink node have a similar workload with that in typical networks.
# Mining Hidden and Fragmented API Usages in Android Applications
## 2 Related Work
### Existing API Usage Mining Tools  
Mining API usages from Open-source repositories (MAPO) [4; 8] is a tool proposed for providing frequent API usages for a given API query. To search the common usages, the API sequences are clustered based on three similarities computed from the method names, API members, and subsequences in each cluster.  
Usage Pattern Miner (UP-Miner) [9] was proposed to improve the quality of API usages by removing the redundant ones among them. This goal was achieved by mining frequent closed sequences based on SeqSim, which is an \(n\)-gram based similarity metric. For example, given the API sequences \(a\), \(b\), and \(ab\), UP-Miner attempts to select the longest sequences \(ab\). Despite the improvement, the metric could not reflect the similarity between the usages in which the same library APIs involved through class inheritance.  
[PERSON] et al. [10] proposed a graph representation of the API usages involving multiple objects. Based on the graph representation, common API usages could be found by finding the frequent induced subgraphs. It was demonstrated that this approach was effective in detecting anomalies that could cause the defects in a program.  
Method USage Examples (MUSE) [11] provided example codes extracted from the source code with the clone detection technique. The clone detection technique was used to provide one representative usage among the clones.  
Probabilistic API Miner (PAM) [5] aims to overcome the limitation that the frequency-based mining approach tends to include uninteresting usages. The basic idea is to include only the API sequence that improves the overall probability of the API model.  
API FunctiOn Calls and USage patterns (FOCUS) [12] is a state-of-the-art recommendation system based on the collaborative filtering. The basic idea is that the valuable API usages in a target program can be collected from the similar program. The experimental results demonstrated that FOCUS outperformed PAM.  
LibraryGuru [13] focused on the API usages found in event-based frameworks such as Android. This tool recommends the most suitable callback methods for a given API query.  
All the aforementioned tools focused on mining frequent API usages while reducing redundant usages. Although these tools contribute to improving the collected dataset, several API usages could be either fragmented or hidden because of the APIs used by inheriting library classes.
## 1 Introduction
It uses a hexagonal patch with an offset feed to realize a transmitarray unit cell design and a transition waveguide. Full-wave simulations have been carried out in the ANSYS HFSS and CST microwave studio to analyze and observe the behavior of the transmitarray unit cell. A reconfigurable transmitarray with 20 \(\times\) 20 antenna elements has been realized. A full-wave simulation of 400 elements has been performed to observe the E- and H-plane scanning capability of the transmitarray, along with the directivity, gain, side-lobe level (SLL), and aperture efficiency. This paper is organized as follows: The design and optimization of the transmitarray unit cell and the operating principle of the unit cell are described in Section 2. The numerical scattering parameters of the proposed unit cell and the effects of the bias circuit are demonstrated in Section 3. The measured results of the unit cell in the waveguide environment are described in Section 4. The design and full-wave simulations of the 20 \(\times\) 20 transmitarray are illustrated in Section 5. Finally, this paper is concluded in Section 6.
## 3 Infinite Array Performance  
The total size of the antenna is about 0.53\(\lambda_{0}\)\(\times\) 0.53\(\lambda_{0}\), which enables the PAA to provide a wide-angle scan from \(-\)45\({}^{\circ}\) to 45\({}^{\circ}\) without grating lobes theoretically. Figure 4 shows the simulated active VSWRs under broadside and scanned status in E-, H-, and D-planes (diagonal plane) in an infinite array environment. Under the criterion of active VSWR \(\leq\) 3, it can be seen that the Ant-1 array can scan up to \(\pm\)45\({}^{\circ}\) at broadside with a 15.7% bandwidth, and it was approximately 7.6% with a two-dimensional scanning range of \(\pm\)45\({}^{\circ}\). Due to the feeding asymmetry, the array exhibits a blind spot. With the help of the modified SIW, scan blindness has been shifted from 1.06\(f_{0}\) in Ant-1 to 1.09\(f_{0}\) in Ant-2, far away from the operating band. The bandwidth of Ant-2 array is approximately 7.5% with VSWR \(\leq\) 2.6 when the pattern steers up to \(\pm\)45\({}^{\circ}\) in all planes. The SIW cavity led to a good wide-scanning performance because it can act as a wide-angle impedance matching layer [25; 26].
# Modelica-Based Energy Management of PEMFC Hybrid Power System of Vehicle
## 3 Energy Management Strategy and Power Distribution Method
### Sm-Mpc-Ems
#### 3.3.2 Framework of SM-MPC-EMS  
This section proposes an energy management method that combines SM and MPC, as shown in Figure 5. Firstly, the power demand stage of the vehicle--whether it is in the high-demand stage or the low-demand stage--is determined based on the required power and the initial SOC state of the lithium-ion battery. Then, we determine the response conditions based on the electricity demand. The SM method is used when the power gradient changes significantly, while the MPC method is used when the power change is slower. For times with high power demand, use the SM1 method; otherwise, use the SM2 method.  
Figure 4: Power load curve for the fuel cell vehicle in this study, **(a)** NEDC, and **(b)** HWFET.  
Figure 5: The flowchart of the SM-MPC-based EMS.
## 1 Introduction
highlighting the satisfactory bond performance between the UHPC and conventional concrete substrate [18]. The second material chosen for this repair was a fiber reinforced, self-consolidating concrete (FRSCC) also developed at the University of Oklahoma [19]. FRSCC incorporates both shrinkage compensating cement and polypropylene fibers to improve post-crack performance, reduce the potential for cracking caused by shrinkage, and improve the material performance when used as a repair material [20]. [PERSON] also noted that the presences of fibers in addition to an expansive agent improved flexural strength and flexural toughness [21]. This material was successfully used to repair a damaged, full scale AASHTO Type II girder and restored 83% of the original capacity of the girder. The FRSCC was able to flow around congested reinforcement without creating any major voids [22]. The third and final material chosen for this repair was a magnesium-aluminum-liquid-phosphate (MALP) concrete. This material was originally developed for repairs of industrial floors exposed to spills of high-temperature materials [23]. The material has been shown to rapidly gain compressive strength, have high bond strength, and have excellent durability performance [24, 25]. MALP concrete can potentially halt the progression of steel reinforcement corrosion by converting the iron oxide to a metal phosphate [26]. This material has been successfully used to repair expansion joint headers and as a patching material on bridge decks in several states [23, 27, 28]. While the mentioned materials have been successfully used as repair materials in a number of applications, the above referenced repair methods have not been attempted on continuity joints connecting individual prestressed, precast concrete girders. The encapsulation repair method was evaluated by testing specimens consisting of two approximately half scale AASHTO girders connected by a continuity joint. The joint was artificially damaged through positive bending until the specimens mimicked damage observed on in-service bridges. After being damaged, the continuity joints of the specimens were repaired with the three chosen repair materials. The repaired girders were then tested and compared to control, undamaged connected girder specimens to assess the ability of the repair to re-establish continuity and design strength of the system. The validation of this repair method provides an alternative to bridge owners to removing and replacing in-kind materials and protects the damaged areas from additional deterioration by using high performance materials in a new application. This method allows for repair of bridges without closure of the bridge and interruption to traffic. In addition, it would provide a cost-effective interim solution to the reduction of performance of aging infrastructure, effectively extending service life until replacement is possible.