esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Notations  
For accuracy of description, by 'unavailability interval' we denote the time interval in which the machine is not available for processing any job, whereas the time interval between two consecutive unavailability intervals is called the 'availability interval' of the machine.  
In this paper, we consider \(m\) uniform parallel machines that can process \(n\) jobs. Each job \(j\), \(j=1,\ldots,n\) is characterized by processing time \(p_{j}\) and completion time \(C_{j}\). We assumed that the jobs were ready at time \(0\) and could be processed once at any time, but could not be interrupted once started. Since we consider uniform parallel machines, each machine \(i\), \(i=1,\ldots,m\), can process at most one job at a time at speed \(s_{i}\). So, the processing time of any job \(j\) depends on the machine on which it is processed and is equal to \(p_{ji}=p_{j}/s_{i}\), \(i=1,\ldots,m\); \(j=1,\ldots,n\). Without loss of generality, we assumed that jobs were indexed in _LPT_ order, that is, \(p_{i1}\geq p_{i2}\geq\ldots\geq p_{in}\). We assumed that the machine could process the next job once the previous one was finished. Thus, no setup time was considered. Let \(s_{ik}\) and \(e_{ik}\) be the starting and ending time of the \(k^{th}\) unavailability period on machine \(i\), respectively. Without loss of generality, we assumed that all machines were available at the beginning of the planning horizon. By \(L_{ik}\), we denote the length of the \(k^{th}\) availability interval on machine \(i\).  
The problem was to find a job assignment on machines that minimizes the makespan. As stated earlier, the problem of scheduling jobs on uniform parallel machines subject to unavailability constraints has not been studied before. Therefore, a mathematical formulation of the problem can be of great interest. Thus, in Section 3.1, we detail a mathematical model to describe the problem under consideration.
## 3 Results and Discussion
### Economic Analysis  
As useful working hours of CSR depend upon the weather conditions, therefore the economic evaluation of the system was carried out on hourly basis. The capital cost of the system along with fabrication of Scheffler concentrator was 2308 USD and life span of CSR was assumed to be 10 years (\(\sim\)22,000 useful working hours). The economic analysis was performed in terms of fuel saving in comparison with other fossil-fuel based resources i.e., electricity, diesel, and gasoline. The total cost per hour of CSR including fixed and variable costs was calculated to be 0.237 USDh\({}^{-1}\). Based on the fuel and electricity prices in Pakistan, it was determined that a fuel costing 1.16, 0.83 and 0.58 USDh\({}^{-1}\) has been saved when gasoline, diesel, and electricity were used as primary source for equivalent roasting energy generation. The payback period (break-even point) of CSR was calculated by plotting the useful working hours against the expenses to calculate the break-even point for each case.  
Figure 11 shows the graphical representation of the break-even point analysis of CSR. The golden, green and red line cuts the blue line at 2450, 3450, and 5200 useful working hours respectively which are the payback periods when gasoline, diesel, and electricity were used for energy generation respectively.
## 4 Experimental Results  
### Curves of the A-Scan's Peak  
The A-scan technique is a common and widely-used method in pulsed eddy current testing, but it can't be used in ordinary eddy currents testing. The third specimen was used and detected with defect 3 in this experiment.  
In this experiment, the rectangular coil driven by the excitation pulse could induce a uniform eddy current in the material being tested. First, we obtained the A-scan response to the PEC, as shown in Figure 3. Then, the peak (the maximum value, shown as the peak point in Figure 3) could be extracted from the A-scan response to form the curves of the A-scan's peak, as seen in Figures 4 and 5. In future work, other features such as rising time and time to peak will be extracted.  
When the sensor was on the defect-free area of the specimen, the eddy currents were uniform and the curve of the A-scan's peak measured by the \(By\) pickup coil was inherent. We suppose that there  
Figure 3: A-scan response and its features.  
Figure 2: The planform of specimen 4 with irregular defect 4.  
was a rectangular defect on the exterior of the specimen. When the eddy current in the specimen was disturbed by the defect, which was larger than the resistance of the specimen, the eddy current flowed to the corner of the defect. Nevertheless, the flow directions of the eddy currents in the two opposite corners were contrary. Consequently, the magnetic force induced by the changed eddy currents in the two opposite corners was also opposite. The current in the _By_ pickup coil changed adversely when the sensor was on the opposite corner of the defect. In other words, as the probe scanned along one side (two corners) of the defect, a crest and a trough appeared in an orderly manner on the peak wave. In addition, as the probe scanned along the other side of the defect (two corners), a trough and a crest also appeared in an orderly manner on the peak wave. The maximum and minimum values of the curves on the A-scan's peak respectively corresponded to the instant of the sensor entering and leaving the corner of the defect. This analytical result may be useful for us in imagining the defect's shape and estimating the distance between the two corners of the defect (i.e., the length and width).  
Figure 4: Curves of the A-scan’s peak on the defect’s two sides in the direction of magnetic flux.  
Figure 5: Curves of the A-scan’s peak on the defect’s two sides in the direction of the current.  
The _By_ curves on the peak of the A-scan sensor scanning along the defect's two sides in both directions are shown in Figures 4 and 5. The horizontal axis represents scanning time, and the vertical axis represents amplitude. As can be seen from the graph, with the approaching of the defect, there were always peaks and troughs on the peak wave. On the other hand, the order of the peaks and troughs on the sensor scanning along both sides of the defect 1 was the opposite. This is in line with the analytical results in Section 3.1. The C-scan imaging technique we employed is explained next.
# AI-Enabled Interference Mitigation for Autonomous Aerial Vehicles in Urban 5G Networks +
###### Abstract  
Integrating autonomous unmanned aerial vehicles (UAVs) with fifth-generation (5G) networks presents a significant challenge due to network interference. UAVs' high altitude and propagation conditions increase vulnerability to interference from neighbouring 5G base stations (gNBs) in the downlink direction. This paper proposes a novel deep reinforcement learning algorithm, powered by AI, to address interference through power control. By formulating and solving a signal-to-interference-and-noise ratio (SINR) optimization problem using the deep Q-learning (DQL) algorithm, interference is effectively mitigated, and link performance is improved. Performance comparison with existing interference mitigation schemes, such as fixed power allocation (FPA), tabular Q-learning, particle swarm optimization, and game theory demonstrates the superiority of the DQL algorithm, where it outperforms the next best method by 41.66% and converges to an optimal solution faster. It is also observed that, at higher speeds, the UAV sees only a 10.52% decrease in performance, which means the algorithm is able to perform effectively at high speeds. The proposed solution effectively integrates UAVs with 5G networks, mitigates interference, and enhances link performance, offering a significant advancement in this field.  
autonomous vehicles; unmanned aerial vehicles (UAVs); fifth-generation (5G); interference mitigation; artificial intelligence; deep Q-learning Article AI-Enabled Interference Mitigation for Autonomous Aerial Vehicles in Urban 5G Networks +
Footnote †: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/)]([https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/))).
## 2 Islanding Detection Methods
### Passive Methods
#### 2.1.2 Rate of Change of Frequency Method (ROCOF)  
This method uses the variation in frequency (df/dt) that happens when the primary utility grid is disconnected with a specific power mismatch to detect islanding and trigger the inverter over a few cycles. A phase-locked loop (PLL) is used to measure the change in frequency df/dt over a brief amount of time so that it may be compared to the established threshold value, which states that the tripping time of frequency relays should not be more than 4-6 cycles [7; 8].  
This method is highly reliable and timely, especially when there is a significant power imbalance between the load and DG. However, this approach is extremely susceptible to variations in load, which is why it fails to differentiate whether the frequency change occurs due to islanding or load variations. Hence, it can be an appropriate method for loads with fewer fluctuations [8].
# Automating Visual Blockage Classification of Culverts with Deep Learning
## 2 Deep Learning Models
### DensNet121  
[PERSON] et al. [21] proposed densely connected convolutional networks called DenseNet by extending the concept of residual connections in the traditional networks. The authors proposed the idea of connecting each layer in the network to every other layer in the feedforward direction. This way, each layer will have the feature maps of all preceding layers at its input. In terms of the number of layer connections, a traditional network with \(L\) layers have \(L\) connections, while a densely connected convolutional network will have \(L(L+1)/2\) connections. Densely connected networks have advantages including better feature propagation, feature reuse, a significant reduction in the number of network parameters, and improving the vanishing-gradient problem. A key difference between residual networks and densely connected networks is that in a densely connected network, feature maps from preceding layers are combined by concatenation rather than summation before feeding it to the next layer.  
Mathematically, if a network consists of \(L\) number of layers each with a non-linear transformation through a composite function \(F_{l}\), the output \(x_{l}\) for the densely connected layer can be represented as in Equation (2).  
\[x_{l}=F_{l}([x_{0},x_{1},\dots,x_{l-1}]) \tag{2}\]  
where \([x_{0},x_{1},\dots,x_{l-1}]\) denotes the concatenation of the feature maps from the previous layers.
# Optical Injection Locking for Generation of Tunable Low-Noise Millimeter Wave and THz Signals
## 3 Materials and Methods--Experimental Setups and Employed Lasers
During the experiment, the slave lasers were placed on a thermal control stage with a constant temperature of 20 \({}^{\circ}\)C to avoid detuning due to temperature drifts. It is important to note that in this work, thermal tuning was the dominant mechanism of adjustment of the emitting wavelength, achieved through the change of the injected current with the thermal control stage as an effective heatsink and temperature reference plane. The light was injected into the chips with the help of lensed fibers. To simplify the analysis, the light was injected from the side of MIR [40], which is broadband compared with the DBR. This configuration ensures that all optical tones of the OFC can penetrate the cavity in a similar proportion without additional filtering. In the case of injection from the DBR side, the reflector suppresses all side tones outside of the transfer function of DBR, which makes estimation of the suppression ratio more complicated. Prior to injection, each slave laser was thermally tuned to match one of the comb lines. After injection, achieving of a stable locking state was monitored with the OSA and ESA, and fine adjustments were made by both thermal tuning and phase shifter bias tuning. Achieving a fully locked state was accompanied by a significant linewidth reduction of the beating tone, detected with the ESA as seen in Figure 4a, and as the canceling of all additional tones, observed from the point where the interaction of master seed and slave laser started and before the slave was fully locked. Another figure of merit if the laser was locked or not was frequency stability: frequency variation of the heterodyne beating of the two free-running lasers was in the range of hundreds of MHz, while after injection of the seed (and even before full locking) the frequency stabilized and followed the frequency of the RF source, which determined the spacing between tones of the optical comb. In terms of linewidth reduction, a great impact of locking is seen, allowing to reduce the linewidth below 100 kHz (Figure 4b).
## 3 Technical and Operational Challenges  
Technical architecture classification summary: From a technical architecture perspective, low-code platforms are mainly divided into three categories: model-driven, Form-Driven, and Hybrid-Driven. Model-driven platforms center on business models, defining relationships between data entities, processes, and interfaces through metadata modeling tools, and generating executable code via model parsing engines. They excel in complex data modeling, BPMN process orchestration, and dynamic interface rendering, suitable for building enterprise-level applications like ERP and CRM, with support for multi-terminal adaptation and deep business logic extension. Form-Driven platforms focus on form design, rapidly creating data entry interfaces through drag-and-drop tools and integrating simple workflow engines for process automation. They feature short development cycles and low learning curves, ideal for lightweight scenarios such as expense approval and data collection, though with limited flexibility in data modeling and support for complex logic. Hybrid-Driven platforms combine the strengths of both, adopting a hierarchical architecture where the core data and business logic are built via model-driven approaches at the bottom, while the front-end uses form/page designers for quick interface generation with custom code extensions. This \"dual-engine\" architecture meets both the need for fast process building and the deep customization requirements of medium-sized enterprises' complex businesses, emerging as a mainstream choice balancing efficiency and flexibility.  
While LCDPs offer significant advantages in accelerating digital transformation, their adoption in mission-critical industries such as aerospace, energy, and automotive faces persistent technical and operational hurdles [60; 61; 62]. This section synthesizes challengesidentified in academic research and industry practices, emphasizing the need for domain-specific adaptations and governance frameworks.
## 5 Discussion  
As shown in the results of this study, the shielding standard of a uniform 80 dB in the South Korean military requires only protection facilities with shielding rooms. However, for common protection facilities of the military, underground or semi-underground structures have been built to ensure initial survivability. Nevertheless, a fixed form of permanent EMP shielding facility is not suitable for division or brigade-level troops because they conduct military operations by frequently moving their stations. Furthermore, they are not required to have a strategic level of capability that does not allow malfunctions of their command-and-control equipment. As momentary failures or simple malfunctions can be repaired within an acceptable time, the differential EMP shielding standard can be applied. Considering the 20 dB of EMP resistance of military equipment and the 30 dB of attenuation of wet soil, new materials with 30 dB shielding efficiency can be used to meet the EMP protection level of 80 dB. For example, it is possible to construct a EMP protection facility using various materials that satisfy the minimum shielding effectiveness of 30 dB such as shielding paper, film, and fabrics. Therefore, we confirmed that EMP protection measures could be established to build mobile lightweight shelters. Moreover, lightweight structures using shielding fabrics will be more effective than the shielding rooms of heavyweight structures using steel plates for the brigade level or lower. If EMP protection facilities built in the future are replaced with lightweight protection facilities, then a large amount of concrete and steel will be saved. If lightweight shelters are constructed by applying the differential protection level scheme, they can be applied as more effective EMP protection measures. Furthermore, differential protection measures can be adopted as a sustainable defense facility policy approach, wherein lightweight protection facilities replace conventional heavyweight facilities.
# Investigation of the Influence of Splitter Blades on the Resonance Conditions of Impellers
## 4 Validation and Discussion
### Mistuned Results  
The mistuned harmonic response results are shown in Figure 9a. It can be seen that the engine orders of excitation corresponding to the largest three response amplitudes are \(n_{1}^{\prime}=15\), \(n_{2}^{\prime}=2\), and \(n_{3}^{\prime}=4\). This means the most harmful excitations are the excitations of \(n_{1}^{\prime}\), \(n_{2}^{\prime}\), and \(n_{3}^{\prime}\) respectively, which is in line with the evaluation results obtained based on the proposed resonance conditions in Section 3.3.2. Moreover, the maximum response amplitude of each excitation and the amplitude of each harmonic component are all normalized and compared in Figure 9b. It shows the variation trends are almost the same.  
Once again, it has been proved by the mistuned case that the resonance can be effectively identified by the proposed resonance conditions. More importantly, the results above indicate that when analyzing the harmonic content of a mistuned mode for impellers with splitter blades, the RMV should be extracted based on all blades rather than sectors. Analyzing in the conventional way may lead to the misjudgment of the harmfulness of the excitations.  
Figure 8: Amplitude–frequency response curves under EO1–EO17.
###### Abstract  
This study investigated the reliability and validity of linear sprint tests (LS) and curvilinear sprint tests (CS) using a GPS device (GPEXE It). Twenty-one (21) student athletes completed a 40 m LS as well as a left and right CS. Maximum sprint speed (MSS) and split times at short (0-10 m), intermediate (0-20 m), and long (0-30 m) distances were determined using the GPEXE It and single-beam timing gates (TG). Intrasession reliability and concurrent validity of GPEXE It were assessed. The GPEXE It consistently showed high reliability for MSS (ICC \(\geq\) 0.95; CV \(\leq\) 1.8%), despite underestimation compared to TG (bias = \(-\)2.57 to \(-\)0.95%; ICC \(\geq\) 0.87). Acceptable reliability was observed for CS and LS intermediate and long distance split times (ICC \(\geq\) 0.91; CV \(\leq\) 2.1%), with lower reliability for short distances (ICC \(\geq\) 0.70; CV \(\leq\) 3.6%). The GPEXE It split times for CS and LS showed good agreement with TG (ICC \(\geq\) 0.66), but were overestimated at long distances (5.5-9.7%) and short distances (11.1-14.6%). Although the MSS was found to be the most reliable and valid variable to assess LS and CS speed performance with GPEXE It, caution is needed due to limited validity.  
curvilinear sprint; GPS; reliability; validity; maximal sprinting speed; split times 20202146116. [[https://doi.org/10.3390/app141466116](https://doi.org/10.3390/app141466116)]([https://doi.org/10.3390/app141466116](https://doi.org/10.3390/app141466116))  
1 Faculty of Forest, Universidad Catolica de la Santisima Concepcion, Concepcion 2850, Chile 3  
Lotwig Boltzmann Institute for Rehabilitation Research, 1100 Vienna, Austria 11  
Football Association of Slovenia, 4000 Kranj, Slovenia; [EMAIL_ADDRESS] (Corresponded: [EMAIL_ADDRESS]; Tel.: +386-40-727-407  
###### Abstract  
This study investigated the reliability and validity of linear sprint tests (LS) and curvilinear sprint tests (CS) using a GPS device (GPEXE It). Twenty-one (21) student athletes completed a 40 m LS as well as a left and right CS. Maximum sprint speed (MSS) and split times at short (0-10 m), intermediate (0-20 m), and long (0-30 m) distances were determined using the GPEXE It and single-beam timing gates (TG). Intrasession reliability and concurrent validity of GPEXE It were assessed. The GPEXE It consistently showed high reliability for MSS (ICC \(\geq\) 0.95; CV \(\leq\) 1.8%), despite underestimation compared to TG (bias = \(-\)2.57 to \(-\)0.95%; ICC \(\geq\) 0.87). Acceptable reliability was observed for CS and LS intermediate and long distance split times (ICC \(\geq\) 0.91; CV \(\leq\) 2.1%), with lower reliability for short distances (ICC \(\geq\) 0.70; CV \(\leq\) 3.6%). The GPEXE It split times for CS and LS showed good agreement with TG (ICC \(\geq\) 0.66), but were overestimated at long distances (5.5-9.7%) and short distances (11.1-14.6%). Although the MSS was found to be the most reliable and valid variable to assess LS and CS speed performance with GPEXE It, caution is needed due to limited validity.