esa-sceva/satcom-chunk-collection huggingface dataset:
# Complex Human-Object Interactions Analyzer Using a DCNN and SVM Hybrid Approach
## 3 Proposed System
### Temporal Segmentation  
We performed temporal segmentation over the input data to obtain groups of data representing human motion and object interaction patterns for each activity. This process groups the nearest frames into one segment, allowing extraction of changes in both spatial and temporal dimensions. Temporal segmentation is important because poor temporal segmentation often results in poor results for interaction recognition. For example, if the time duration threshold used in temporal segmentation is too short, features will not be well represented, and if the threshold is too long, distinguishing features within a set of interactions will be difficult to obtain. Here, we use a time duration threshold (a temporal sliding window size) of 15 frames over the input data with a frame rate of 15 fps. Therefore, each segment provides a good representation of changing interaction patterns within 1 second. The input data are uniformly segmented using a fixed temporal sliding window size of \(W.\) For action data with a total number of frames \(N\) which cannot be divided by 15, we replicate the first frame into \(R\) times that can be calculated using Equation (1).  
\[R=15-(N\bmod 15) \tag{1}\]  
where mod refers to the modulus operation for finding the total number of remaining frames \(R\) in order to perform uniform segmentation. Figure 3 shows an example of temporal segmentation over the skeletal movement data of the right shoulder, right elbow, and right hand while \"taking action using the right hand\".
# Development of a System for Cyclic Shear Tests on Full-Scale Walls
## 1 Introduction
#### Shear Test Types of Setup and Their Characteristics

Table 1: Experimental setup types used in cyclic shear tests. As seen from Table 1, most experimental setups adopt the model with rotation restriction at the top and bottom, resulting in the double-bending condition. This configuration is interesting to understand the shear effects in situations with similar boundary conditions, such as multi-story buildings where structural masonry panels act confined between two slabs and under high compression, which reduces rotations. However, a limitation of this type of experimental setup is that the restriction to rotation at the top of the panel also prevents torsion, especially in panels with an asymmetric cross-section. In this way, the understanding of the integrated effect of combined torsion and shear may be impaired. For situations involving low-height buildings (or for the upper floors of taller buildings), the vertical confinement effect of the panels tends to be significantly smaller. This is due to factors such as reduced panel compression, thin slabs, the eventual absence of a covering slab on the last floor, etc., which facilitate rotations at the top of the panels. In these cases, in addition to the bending effect becoming preponderant, the torsion effects can also be significant, especially in the case of panels with asymmetric cross-sections. The SHS-Multirisk house model fits into this last category as it has only one floor; ideally, it does not have a covering slab, and the masonry panels up to 1 m wide and about 2.20 m high act close to the behavior of cantilever columns. In this way, we sought to develop a system without rotation restrictions at the top, which is believed to better reflect the real operational conditions of the house's panels under seismic loads. Thus, the tests reflect the shear behavior combined with bending and torsion (albeit partial) from applying the load on the axis that passes through the cross-section geometric center at the top of the wall.
The loading and offloading of oil and other liquids mostly adopts the top loading method, while the loading and offloading of liquefied natural gas mostly adopts the bottom loading method. The two loading and offloading methods of top loading and bottom loading exhibit significant differences in terms of automation control, interface form, sealing requirements, etc. [1]. This paper forms part of a project that aims to transform the automatic docking and unmanned operation of the loading and offloading arms of liquefied natural gas tank trucks. The main component of liquefied natural gas (LNG) is methane [2], which is recognized as the cleanest fossil fuel on earth. LNG is in a gaseous state at atmospheric temperature and pressure. Many vaporized volatiles are generated when using top loading [3]. Therefore, bottom loading is mainly used for the loading and unloading of low-temperature LNG and small crane tubes are often used for the loading and offloading of LNG in trucks. The typical connection between the offloading arm and the tanker when loading and offloading LNG is shown in Figure 2. The flange port for the docking of the loading and offloading arm is set at the bottom of the LNG tank, and the diameter of the outer diameter of the flange is 165 mm. There are rotary joints on the small crane tube. For docking, the small crane tube is dragged to make the rotary joint rotate left and right and up and down. The flange on the vertical pipe is connected to the flange on the tank trucks and then locked on with bolts. This project studied the possibility of the automatic docking of the loading and offloading arm to replace the manual docking operation. The spatial position of the flange port of the tank truck is obtained by the method of visual image recognition. The integrated data processing program was used to calculate the normal vector and the circle center of the flange port. Then, the spatial position data of the flange port of the vehicle are transmitted to the automatic docking system of the loading and offloading arm, and the loading and offloading arm was driven by the actuator to realize automatic docking. Figure 1: Tank car top loading. Figure 2: Tank car bottom loading.
# Investigations into Picture Defogging Techniques Based on Dark Channel Prior and Retinex Theory
## 4 Experimental Outcomes and Discussion
### Subjective Evaluation  
With an emphasis on image contrast, feature preservation, and color fidelity, Figure 6 shows the outcomes of defogging for non-sky images from multiple datasets: Img2 and Img6, Img8 (NH-HAZE), and Img10 (RESIDE). The original hazy images exhibit monochromatic tones, low contrast, and fog-obscured details.  
The MSR enhancement technique improves contrast but retains noticeable haze, failing to enhance overall visibility. For non-sky images, the conventional dark channel prior (DCP) algorithm boosts contrast and recovers significant features without major color distortion, though mild halo artifacts persist at depth discontinuities. [PERSON] et al.'s technique restores natural colors effectively but lacks flexibility in complex scenes, as evidenced by obscured low-contrast details. [PERSON] et al.'s method achieves satisfactory contrast but introduces localized color variations (bluish tint on roads in Img8). Grid_Net robustly removes haze, but it overly smoothens the texture, and the defogged images show relatively severe color distortion (such as the colors of houses in Img2 and trees in Img5).  
In contrast, our proposed algorithm achieves an optimal balance between the following: contrast enhancement (vivid foreground vegetation in Img5); detail recovery (preserved road structures in Img8); and color integrity (natural tones without halos in Img9). This consistency across self-collected and public datasets (NH-HAZE and RESIDE) demonstrates strong adaptability to diverse haze distributions.  
Using several defogging techniques, Figure 7 shows the defogging outcomes for sky-containing images from multiple sources: self-collected data (Img1, Img3, Img4, Img5); the NH-HAZE benchmark (Img7); and the RESIDE dataset (Img9).  
Figure 6: Comparison of defogging results for each algorithm without sky region.  
The conventional dark channel prior produces significant sky region artifacts, including color distortion (cyan cast in Img4 and Img9 sky) and halo effects (Img5 tree boundaries). [PERSON]'s weighted L1-norm approach effectively removes haze but introduces color shifts (yellowish buildings in Img3) and inconsistent saturation (darkened skies in Img9). [PERSON]'s method causes over-saturation (mountain in Img3) and amplifies halo artifacts (Img5 tree edges). Grid_Net demonstrates competitive performance on synthetic haze (Img9) but exhibits limitations in real-world conditions: patchy sky restoration in Img1 and texture loss in dense haze (Img4 foreground).  
Our proposed method overcomes these limitations by achieving the following: 1. Eliminating color distortion through depth-guided transmission correction (neutral skies in Img5/Img9). 2. Suppressing halo artifacts via mean dark channel compensation (clean horizon in Img4 and Img5). 3. Preserving structural details in diverse haze densities. This consistent performance across self-collected and public benchmarks validates our approach's robustness for sky-containing hazy images.
# A New Collector Device for the Immediate Use of Particulate Autogenous Bone Grafts
## 4 Discussion  
Bone grafts in maxillofacial surgery are used to correct or replace the quality or quantity of bone. Bone defects can be the result of either congenital and developmental malformations, tumour surgery, trauma, or infection. There are also many other indications for bone grafting in functional and aesthetic surgery [25; 26; 27; 28; 29; 30; 31]. When it comes to the biological properties of bone substitutes for bone transplants, fresh autogenous bone remains the gold standard of all available graft materials. This is the main feature of the innovative BKS device, which is used as a bone graft collector for transplantation, to use fresh autogenous bone in a simplified and controlled manner, according to the surgeon's planning and needs. It can be used directly as a local bone filler or to activate scaffolds to support bone formation within the scaffold [27; 28; 29; 30; 31; 32; 33; 34].  
Some techniques use aspirators to collect bone particles during drilling. Despite these bone dust aspiration techniques and the preoperative use of chlorhexidine mouthwash, bacterial contamination of aspirated bone collected with these bone collector models is to be expected. In addition to the physiological bacteria of the oral flora, microorganisms commonly associated with implant failure may be found. Rinsing the bone collector with 200 mL of 0.1% chlorhexidine solution significantly reduces microbial contamination, but its effect on bone vitality is unknown [22]. The limited evidence available on the use of bone collectors suggests that the resulting graft material is less than ideal. Until other methods of avoiding bacterial contamination or other device designs are developed, clinicians should be cautious in the use of bone collectors [23; 28; 29; 32; 33; 34; 35].  
Figure 3: Accurately measuring the total volume of the BKS, indicating in yellow the amount of bone it will remove and harvest.  
The use of mineral bone graft materials such as hydroxyapatite is routine in bone implant surgery, with satisfactory clinical results; however, these results are still inferior to those obtained with autogenous grafts. Although this experiment was carried out on synthetic bone, the concept will be applied in vivo in future studies wherein the bone harvested is autogenous, thereby increasing the chances of success of the bone graft [1; 2; 3; 4; 5; 6; 7; 8; 9].  
In this paper, an experimental study on a synthetic human mandible using the new biomechanical device BKS [16; 17; 18; 19; 20] was presented; the device removed bone from the mandible like a rotary instrument and immediately, without direct manipulation of the bone graft, removed it from the BKS internal volume and used it to fill the bone-deficient region or scaffold with autogenous bone [32; 33; 34; 35]. With this technique, there is less manipulation of the bone graft, and the particulate bone is stabilized according to the surgeon's plan. The results described here will be compared with in vivo experiments in ongoing studies.
# A Completion Method for Missing Concrete Dam Deformation Monitoring Data Pieces
###### Abstract  
A concrete dam is an important water-retaining hydraulic structure that stops or restricts the flow of water or underground streams. It can be regarded as a constantly changing complex system. The deformation of a concrete dam can reflect its operation behaviors most directly among all the effect quantities. However, due to the change of the external environment, the failure of monitoring instruments, and the existence of human errors, the obtained deformation monitoring data usually miss pieces, and sometimes the missing pieces are so critical that the remaining data fail to fully reflect the actual deformation patterns. In this paper, the composition, characteristics, and contamination of the concrete dam deformation monitoring information are analyzed. From the single-value missing data completion method based on the nonlocal average method, a multi-value missing data completion method using BP (back propagation) mapping of spatial adjacent points is proposed to improve the accuracy of analysis and pattern prediction of concrete dam deformation behaviors. A case study is performed to validate the proposed method.  
hydraulic structure engineering; concrete dam; deformation monitoring information; missing data completion; behavior pattern prediction 2021  
114633390/app11010463
# MBMQA: A Multicriteria-Aware Routing Approach for the IoT 5G Network Based on D2D Communication
## 4 Simulation Results and Discussions
### Packet Delivery Ratio Comparison  
It can be seen from Figure 6 that the MBMQA scheme ensures a high packet delivery ratio (PDR) value over both MP-OLSRv2 and MEQSA-OLSRv2 schemes. This is due to the fact that MBMQA takes advantage of the MARS metric to select devices with a lower energy drain rate and an adequate amount of remaining energy level. Consequently, a reduced amount of retransmission is required to transfer packets from the source to the destination and avoid selecting low-resource devices. In addition, packet delivery is closely related to packets dropped by either low energy level nodes or packets dropped due to the full queue of nodes participating in multiple forwarding of packets. Therefore, the proposed scheme is shown to provide optimum results in delivering packets to the destination, since a limited number of packets dropped. Moreover, as the speed of devices increases, maintaining connections with neighboring nodes becomes difficult, while that is the next hop for data forwarding. Furthermore, in order to forward packets to the next hop, the device needs to select another candidate for the successful transmission of the packet while fulfilling the requirements of the MARS metric. Based on the results obtained, the MBMQA scheme delivered approximately 30% more packets than MP-OLSRv2 and approximately 15% to 20% more than MEQSA-OLSRv2.
###### Abstract  
The interaction between rainfall erosivity parameters and splash erosion is crucial for describing the soil erosion process; however, it is rarely investigated under natural rainfall conditions. In this study, we conducted splash erosion experiments under natural rainfall on three sites in Central Europe. The main goal was to obtain the relationship between splash erosion of the bare soil in seeded condition and commonly used rainfall erosivity parameters (kinetic energy, intensity, and rainfall erosivity (\(EI_{30}\))). All sites were equipped with a rain gauge and an optical laser dishormeter where the splash erosion was measured, with modified Morgan splash cups. In order to investigate which parameter best describes the splash erosion process for all sites, a regression analysis was performed. In total, 80 splash erosion events were evaluated. Splash erosion can be described as a linear function of total kinetic energy and a non-linear function of \(EI_{30}\). However, the use of the total kinetic energy led to underestimation of the splash erosion rates for highly intensive rainfalls. Therefore, better results were obtained when using average rainfall intensity as the splash erosion predictor or the kinetic energy divided by the rainfall duration. Minor differences between the replicates during splash erosion measurements indicate that the modified Morgan splash cup provides a good tool for soil erosion assessment.  
splash erosion; splash cup; kinetic energy; rainfall intensity; rainfall erosivity 2020
## 7 Process Optimization Through CFD Simulations
### Reduction of Energy Consumption and Improvement of Product Quality  
In modern food manufacturing, the concurrent pursuit of energy efficiency and superior product quality is paramount, with CFD serving as a pivotal technology to achieve these objectives. CFD provides profound insights into thermal distribution, flow dynamics, and physical interactions within processing systems, enabling optimization of equipment and conditions to minimize energy consumption while enhancing product attributes such as texture, moisture, and nutritional value [157]. Energy-intensive operations like drying, extrusion, and mixing particularly benefit from CFD, which helps identify thermal inefficiencies, redesign pathways to reduce energy loss, and optimize process parameters. For instance, in spray drying, CFD minimizes wall deposition and recirculation, while in extrusion, it helps configure screws and dies for minimal torque and thermal input. Beyond energy savings, CFD significantly contributes to product quality by modeling moisture profiles for uniform dehydration, ensuring adequate thermal processing without nutrient loss, and analyzing shear fields and RTD to design desired textures. It also aids in preserving color, flavor, and functional compounds by preventing localized overheating. Critically, CFD facilitates multi-objective optimization, allowing engineers to balance energy use and product quality through surrogate modeling techniques and integration with real-time control systems. Industrial case studies, such as CFD-based redesign of spray dryers for infant formula or optimization of pasteurization tunnels, have consistently demonstrated significant energy reductions (10-30%) alongside measurable improvements in product consistency. Future advancements will likely involve the integration of CFD with real-time sensor data, AI-driven predictive control, and digital twin platforms, alongside the incorporation of environmental metrics, to foster more sustainable food production [157].
# Double-Consensus Based Distributed Optimal Energy Management for Multiple Energy Hubs
## 4 Application Examples
### Plug and Play Capability  
This case study focuses on testing the plug and play performance of the proposed algorithm. The initial conditions are the same as those in case study 1. At \(t_{1}\) (\(k\) = 1000), hub3 is removed from the test system and the variables related to them are set to zero. As a result of this change, the original balance is broken, and the electricity and heat mismatches go to a non-zero state, as seen in Figure 6a,b.  
Figure 5: Time-varying demand: (**a**) the electricity mismatch; (**b**) the heat mismatch; (**c**) the electricity multiplier; (**d**) the heat multiplier; (**e**) electricity input; (**f**) gas input.  
By continually running the proposed DDC algorithm, it can be observed from Figure 6c-f that the remaining energy hubs have to increase their electricity and gas inputs to generate more electricity and heat to further compensate for the amount of electricity and heat previously generated by hub3; the corresponding electricity and heat Lagrangian multipliers increase, as well, to meet this change. After about 300 iterations, i.e., at \(k=1300\), the electricity and heat mismatches converge to zero again; meanwhile, the electricity and heat Lagrangian multipliers, as well as the electricity and heat inputs, converge to their corresponding optimal values. As a result, the new supply-demand balance can be satisfied after removing hub3. Then, at \(t_{2}\) (\(k=2000\)), hub3 is plugged back into the system again. Of course, hub3 gradually increases its electricity and heat generation, while the others decrease their generations to accommodate for hub3. After about 300 iterations, i.e., at \(k=2300\), it can be seen from Figure 5a-f that the algorithm converges to the new optimal solution in response to the new topological change. Additionally, the final convergence values for all variables are the same as those prior to disconnection. Therefore, the results clearly show that our proposed algorithm can provide good plug and play capability.
# Dynamic Mixed Reality Assembly Guidance Using Optical Recognition Methods
## 2 State of the Art
### Objectives of the Work  
Over recent years, MR technology has made significant strides, both as regards equipment and software platforms, as also demonstrated by recent research presented above. Results of the analyzed works indicate MR as a promising technology for operator assistance and training in manufacturing. Nevertheless, standardized methods to develop MR for industrial applications have not yet been widely employed.  
On the basis of the previous considerations, the aim of this work is to contribute to filling this gap by designing and developing a MR application based on commercial equipment and open-source optical recognition methods to assist the training of assembly operators. The proposed solution aims at guiding the operator through visual graphic animations, audio instructions and over imposed UI panels and at validating the correct execution of manual assembly tasks involving component selection and placement, with eventual correction steps.
## 3 Fabrication and Measurement  
To prove the properties of the proposed wide-beam antenna, a prototypical antenna was fabricated using the printed-circuit-board (PCB) process, and measured in the microwave anechoic chamber, as shown in Figure 7. The top and bottom view of the fabricated wide-beam antenna are presented in Figure 7a,b, respectively, and Figure 7c shows the measurement scene. In this section, we present the measured reflection coefficient in Figure 8. It can be observed that the \(\ket{S_{11}}\) \(\ket{}\) were less than \(-10\) dB in the whole frequency band. Additionally, we also display the measured gain results in different cut-planes at the central frequency and compare them with the simulated ones. Considering that Section 2 has given the simulated gain results, where phi was chosen from \(0^{\circ}\) to \(180^{\circ}\) at an interval of \(15^{\circ}\), the HPBW amplifications in different cut-planes were relatively consistent. Therefore, the gain consequences only in the phi = \(0^{\circ}\), \(45^{\circ}\), \(90^{\circ}\), and \(135^{\circ}\) cut-planes are demonstrated here, as shown in Figure 9. It can be seen that the measured and simulated results had a general consistency, with slight deviations caused by the dielectric loss and fabrication tolerances. Taking the phi = \(0^{\circ}\) cut-plane results as an example, the measured HPBW was about \(69^{\circ}\), covering a range from \(-32^{\circ}\) to \(37^{\circ}\), with a peak gain of \(6.1\) dBi. Meanwhile, the simulated HPBW in this cut-plane was approximately \(78^{\circ}\), overriding a scale from \(-38^{\circ}\) to \(40^{\circ}\), with a peak gain of \(6.7\) dBi. The difference between the measured and simulated HPBW was about \(9^{\circ}\). On the whole, the measured results are in good agreement with the simulated results.