esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
This paper has introduced an algorithm that can efficiently compare how accurately a patient wearing an exoskeleton-type device performs a set of reference postures during rehabilitation training.  
When the slice count method was applied, the accuracy did not differ significantly from the optimal value. However, application of the slice count method greatly enhanced the execution speed. Additionally, with the proposed TSPDA algorithm, the analysis target is not limited to the walking posture in posture analyses; the algorithm can universally accommodate various input postures using a full-body motion capture device.  
Mobility solutions for people with physical disabilities continue to advance with new developments in robot technology, and high-performance assistance algorithms are needed to optimize patient rehabilitation and safety. The proposed TSPDA can be used to evaluate the training scale in the rehabilitation process necessary for the social advancement of paraplegic patients who cannot move their lower extremities. Given the broad scope of full-body motion tracking and the price declines in sensor components, we expect more availability and more demand for these devices as existing barriers are overcome. The TSPDA presented in this paper is expected to benefit society.  
The TSPDA directly compares the raw data of motion capture equipment, thereby solving the problems associated with the limited postural analyses of the studies cited in Section 2; the TSPDA quickly and accurately defines data-rich areas using the real-time measures described in Section 4. TSPDA accuracy is assured by the fact that the initial settings can be modified. It is possible to obtain the desired results (via adjustment) even if the calculations are inaccurate.  
Conceptualization, H.-W.L., K.-O.L. and Y.-J.C.; Formal analysis, H.-W.L., K.-O.L., S.-Y.K. and Y.-Y.P.; Investigation, H.-W.L., K.-O.L., S.-Y.K. and Y.-Y.P.; Project administration, H.-W.L.; Resources, Y.-J.C.; Software, H.-W.L.; Supervision, K.-O.L., Y.-J.C. and Y.-Y.P.; Validation, H.-W.L., K.-O.L. and Y.-Y.P.; Writing--Original draft, H.-W.L.; Writing--Review and editing, H.-W.L., K.-O.L. and Y.-Y.P. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Sun Moon University Research Grant of 2021.  
**Institutional Review Board Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
Figure 10: Execution time of the TSPDA by Slice Count.
## 4 Conclusions
\begin{table}
\begin{tabular}{c c c c} \hline
**CE-Technique** & **Food Matrix** & **Sensitivity** & **Ref.** \\ \hline \multicolumn{4}{c}{**Tetracyclines**} \\ \hline CZE-ECL & fish & LOD: 1.8 ng/mL & [60] \\ \hline FASI-CZE-UV & water & LOQ: 23–59 ug/L & [61] \\ \hline SPE-LVSS-PS-CS-CEE-UV & milk & LOD: 18.60–23.83 (ug/L) & [62] \\ \hline MSPD-CZE-UV & milk & LOD: 0.0745–0.0808 (ug/mL) & [65] \\ \hline SPE-LVSS-PS-CS-CEE-UV & water & LOQ: 67–167 (ng/L) & [63] \\ \hline LVSS-CZE-UV & water & LOD: 8.1–14.5 (ug/L) & [64] \\ \hline CZE-AD & water & LOD: 0.33–0.67 (uM) & [66] \\ \hline SPE- CZE-UV & honey & LOD: 23.9–49.3 (ug/kg) & [67] \\ \hline \multicolumn{4}{c}{**Solitonamides**} \\ \hline SPE-CEC-MS & meat & LOD: 0.01–0.14 (ug/L) & [71] \\ microchip-CE-LIF & milk, meat & LOQ: 0.6–7.7 (ug/L) & [72] \\ SPE-CZE-ECL & milk, meat & LOD: 0.62–3.14 (ug/mL) & [73] \\ CZE-UV and CZE-MS & meat, water & LOD: 0.33–180 (ug/L) & [68] \\ CITP-CZE-UV & beverages, water & LOD: 2.29 (ng/mL) & [69] \\ \hline \multicolumn{4}{c}{**Aminoglycosoides**} \\ \hline MISPE-FASS-CZE-MS/MS & honey & LOQ: 1.4–94.8 (ug/kg) & [75] \\ \hline microchip-CE-CCD & standard solutions & LODs: 0.89–3.1 (ug/mL) & [77] \\ \hline \multicolumn{4}{c}{**Macrolides**} \\ \hline FASS-MEKC-UV & milk & LOD: 0.002–0.004 (mg/kg) & [83] \\ \hline R-USAEME-CZE-DAD & chicken fat & LOQ: 22.1–47.0 (ug/kg) & [84] \\ \hline \multicolumn{4}{c}{**\(\beta\)-lactam antibiotics (penicillins)**} \\ \hline PPT/CZE-UV & milk & LOQ: 0.04–1.7 (ug/mL) & [89] \\ \hline ASEI-CEC-MS & milk & LOD: 0.05–0.2 (ug/L) & [90] \\ \hline \multicolumn{4}{c}{**\(\beta\)-lactam antibiotics (cephalosporins)**} \\ \hline CZE-UV & complex matrices & LOQ: 4.33–8.00 (ug/mL) & [88] \\ \hline \multicolumn{4}{c}{**Estrogens**} \\ \hline SPE-p-CEC-AD & bovine milk, diary products & LOD: 2–50 (ng/mL) & [98] \\ DLIME-MEKC-ESI-MS/MS & bovine and goat milk, & LOD: 1–61 (ug/L) & [32] \\  & diary products & & \\ DLIME-MEKC-UV & water & LOD: 0.3–0.6 (ug/L) & [33] \\ \hline \multicolumn{4}{c}{**NSAIDs**} \\ \hline DLIME-FASS-CZE-UV & bovine milk, dairy products & LOQ: 10–43.7 (ug/kg) & [99] \\ SPME-CZE-UV & water & LOQ: 2.91–3.86 (ug/L) & [102] \\ \hline \multicolumn{4}{c}{**\(\beta\)-agonists**} \\ \hline SPE-NACE-MS & meat & LOD: 0.3 (ppb) & [103] \\ CSEI-sweep-MEKC-UV & meat & LOD: 3–5 (ng/g) & [104] \\ FASI-sweep-MEKC-UV & commercial animal feeds & LOD: 5–20 (ng/mL) & [105] \\ FESI-CE-C\({}^{4}\)D & pig feed & LOD: 0.02 (mg/L) & [106] \\ \hline \end{tabular}
\end{table} 
Table 1: _Cont._
# A Novel Method for 3D Lung Tumor Reconstruction Using Generative Models
## 3 The Proposed Model
### The 3D Reconstruction Method  
As Figure 1 shows, segmenting tumors results in \(N\) series of 2D slices. These slices undergo feature extraction using the VGG-16 network. The feature vectors from VGG-16 simplify the data by reducing their dimensionality, making them suitable for sequential analysis by the LSTM. This method enables the LSTM to effectively analyze the sequence of slices, which is crucial for accurate 3D tumor reconstruction while avoiding issues like overfitting and the high computational demands associated with processing large image dimensions directly. The outputs from VGG-16 feed into the LSTM, whose results are then employed by a GAN framework for further processing. The GAN framework is designed to create 3D images from the sequences of 2D slices. In this setup, the GAN discriminator differentiates between the images generated by its generator and real images.
# Cosine-Based Embedding for Completing Lightweight Schematic Knowledge in DL-Lite\({}_{core}\)+
## 3 Preliminary
### Schematic Knowledge Embedding for DL-Lite\({}_{core}\)  
**Definition 2** (Schematic Knowledge Embedding).: _Given a set of axioms \(\mathcal{T}=\{(C_{i},r,C_{j})\}\), where \(C_{i},C_{j}\) are two concepts and \(r\) is a relation of them. Its embedding model is a function \(f(C_{i},r,C_{j})\rightarrow\mathbb{R}\) that can encode all the concepts and relations in \(\mathcal{T}\) into the semantic space, in which the logical property of each relation \(r\) can be preserved w.r.t. the asserted axioms \(\{(C_{i},r,C_{j})\}\) and inferred ones at the numerical level._  
According to Definition 2, we formulate its properties for preserving the transitivity and symmetry of relations \(subclassOf\) and \(disjointWith\) in axioms during this process.  
**Definition 3** (Schematic Knowledge Embedding for DL-Lite\({}_{core}\)).: _Given a TBox \(\mathcal{T}=\{(C_{i},r,C_{j})\}\) expressed in DL-Lite\({}_{core}\), its embedding model denoted by \(f(C_{i},r,C_{j})\) should satisfy the following properties to preserve the transitivity of subclass\(Of\) and symmetry of disjointWith:_  
1. _If_ \(r=subclassOf\) _and_ \((C_{1},r,C_{2})\)_,_ \((C_{2},r,C_{3})\) _are two axioms asserted in_ \(\mathcal{T}\)_, then_ \(f(C_{1},r,C_{3})\)__\(\approx f(C_{1},r,C_{2})\approx f(C_{2},r,C_{3})\)_._
2. _If_ \(r=disjointWith\) _and_ \((C_{1},r,C_{2})\) _is an axiom asserted in_ \(\mathcal{T}\)_, then_ \(f(C_{1},r,C_{2})\approx f(C_{2},r,C_{1})\)_._  
Notice that the properties in Definition 3 are preconditions for the model of lightweight schematic knowledge embedding. The object function still needs to be competent for the task of completing lightweight schematic knowledge in DL-Lite\({}_{core}\). Our proposed model is subsequently designed to achieve these goals.
# A Method of Barkhausen Noise Feature Extraction Based on an Adaptive Threshold
## 4 Conclusions  
In this paper, appropriate thresholds are selected adaptively by standard deviation criterion and 'overlap' with a genetic algorithm for MBN features. The criteria for selecting the optimal threshold is when 'overlap' is 0 and the sum of standard deviation is the lowest.  
1. The results obtained have proven that adaptive threshold features can effectively distinguish between different stress conditions. Adaptive pulse count has good stability and repeatability.
2. Compared with a single threshold, different thresholds are selected for tensile stress and compressive stress respectively, the obtained features have better linearity and stability.
3. By comparing different modeling methods including MLR and MLP, the results show that adding the adaptive pulse count feature to stress prediction model will result in a lower RMSE and can improve the accuracy of stress prediction.
4. The new method proposed in the paper can be used for other feature extraction situations where thresholds need be selected. For an incremental permeability (IP) signal, curve width at the certain percentage of \(\upmu\)MAX can be selected optimally [3]. For multi-frequency eddy current testing, the appropriate excitation frequency also can be chosen optimally.  
Writing: C.H.; Formal Analysis: C.H.; Software: C.H.; Validation: C.H.; Visualization: C.H.; Funding acquisition: [PERSON] and P.W.; Project administration: [PERSON] and P.W.; Data curation: P.W.; Supervision: W.L. All authors were involved in experimental investigations.  
This work was supported in part by Aviation science funds under Grant 2015 ZF52067, in part by Special scientific instrument development of Ministry of science and technology of China under Grant 2016 YFF0103702, in part by National Natural Science Foundation of China under Grant 61527803, in part by National key research and development program of Ministry of science and technology of China under Grant 2016 YFB1100205, in part by National quality foundation key research and development plan of common research and application under Grant 2017 YFF0209700, and in part by Graduate innovation center fund NUAA under Grant KFJJ20180317.  
The authors declare no conflict of interest.
## 3 Methodology of the Resampling Strategy and Variable Circular Correlation Time
### Coarse Acquisition with Variable Circular Correlation Time
Denote the corresponding carrier frequency and code phase as \(\hat{f}_{dc}\) and \(\hat{\theta}_{d}\), respectively. In this paper, acquisition threshold is defined as the ratio of the highest and second highest correlation values in the search space of carrier frequency and code phase. The second highest peak is found out in the neighborhood range of the highest one. The left neighborhood range is obtained as \([0,\ \hat{\theta}_{d}]\cap[\theta_{l2},\ \theta_{l1}]\) and the right is \([\theta_{r1},\ \theta_{r2}]\cap[\hat{\theta}_{d},\ L_{r}]\). \[\left\{ \begin{array}{c}\theta_{l1}=\hat{\theta}_{d}-\Delta_{\theta}\\ \theta_{l2}=\hat{\theta}_{d}-L_{x}+\Delta_{\theta}\\ \theta_{r1}=\hat{\theta}_{d}+\Delta_{\theta}\\ \theta_{r2}=\hat{\theta}_{d}+L_{x}-\Delta_{\theta}\end{array} \right. \tag{22}\]  
where \(\Delta_{\theta}\) is the one-chip-period range, excluded from the neighborhood range, for it is too close to the highest peak to find out the useful second peak. If the correlation ratio is bigger than the acquisition threshold, it is confirmed that the corresponding satellite is visible and the signal of frequency \(\hat{f}_{dc}\) and code phase \(\hat{\theta}_{d}\) is acquired successfully. Note that the frequency spectrum of \(C_{r}(p)\) is asymmetrical, such that the former half part occupies most of signal power. Thus, we just use the former to compute circular correlation results. This reduces FFT samples by half, so as to decrease computation of signal acquisition. Additionally, \(L_{x}\) is highly related to the amount of FFT samples for signal acquisition. Equation (19) provides a good indication to reduce computation and time cost of signal acquisition by decreasing the sampling frequency \(f_{s}\) and circular correlation time \(P_{x}\). That is exactly realized by the proposed resampling strategy and variable circular correlation time.
## 6 Conclusions  
The purpose of this study is to compare methods for measuring the depth of an object using a single camera image for application in locating real-world objects through digital twin models of underground utility tunnels. Therefore, the DenseDepth transfer learning method and the coordinate system conversion method through floor plane projection were selected and compared. The coordinate system conversion method was found to be more suitable. This study is meaningful as a study that applied and tested depth-estimation technology that can utilize CCTV, a single camera installed in the underground utility tunnel, to link objects in the real world to digital twin models. Further additional follow-up studies, such as the application of the coordinate system conversion method to actual underground utility tunnels and reviews of other methodologies, are required.  
Conceptualization, S.P. and I.H.; methodology, C.H. and I.H.; investigation, J.L., S.P., and C.H.; data curation, S.P.; writing--original draft preparation, S.P.; writing--review and editing, S.P.; All authors have read and agreed to the published version of the manuscript.  
This research was supported by an Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT, MOIS, MOLIT, MOTIE) (No. 2020-0-00061, Development of integrated platform technology for fire and disaster management in underground utility tunnel based on digital twin).  
Not applicable.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Distance from** & **Point** & \multicolumn{3}{c}{**Real World Coordinates**} & \multicolumn{3}{c}{**Floor Projection Intersection**} & \multicolumn{1}{c}{**Error (cm)**} \\ \cline{2-7}
**Camera** & & **X** & **Y** & **Z** & **X** & **Y** & **Z** & \\ \hline
5 m 60 cm & 1 & 0 & 0 & 0 & 23 & \(-\)14 & 0 & 27 \\  & 2 & 560 & 0 & 0 & 555 & 25 & 0 & 25 \\  & 3 & 1120 & 0 & 0 & 1108 & \(-\)20 & 0 & 23 \\
21 m 40 cm & 4 & 0 & 2140 & 0 & \(-\)12 & 2167 & 0 & 30 \\  & 5 & 560 & 2140 & 0 & 545 & 2223 & 0 & 84 \\  & 6 & 1120 & 2140 & 0 & 1107 & 2029 & 0 & 112 \\
42 m 80 cm & 7 & 0 & 4280 & 0 & \(-\)22 & 4341 & 0 & 65 \\  & 8 & 560 & 4280 & 0 & 528 & 4711 & 0 & 432 \\  & 9 & 1120 & 4280 & 0 & 1111 & 4130 & 0 & 150 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Floor projection intersection errors.  
Data Availability Statement: The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
# Operationalizing Dyadic Urban Traffic Interaction Studies: From Theory to Practice
## 2 Background
### Related Frameworks on Experiment Design  
While there are other papers addressing design of studies on traffic interaction (e.g., [50; 51; 52]), they have a tendency to focus on particular road users or certain measurements, leaving a gap when it comes to a holistic methodological approach in the design of controlled studies for traffic interactions. For instance, [PERSON] et al. [52] present in their framework only a set of guidelines for analysis of road user behavior data, particularly focusing on non-driving related task. Similarly, [PERSON] et al. [50] focuses on analysis of data from semi-controlled experiments from driver perspective. [PERSON] et al. [51] present a methodology for conducting usability study with focus on situations involving automated vehicles and pedestrians or bicyclists. These works are limited to usability and lack a holistic approach to critical decisions and trade-offs that experimenters need to make. The systematic review by [PERSON] et al. [11] provides a comprehensive taxonomy of challenging scenarios involving automated vehicles (AVs) and vulnerable road users (VRUs), with a strong emphasis on identifying critical interaction points that AVs must navigate to ensure safety and effectiveness. Though this work offers a valuable foundation for understanding the scope and diversity of traffic interactions, its focus is largely theoretical, with limited consideration of the practical challenges involved in translating these scenarios into experimental settings. To address this gap, we contribute with a methodological framework that explicitly addresses the operationalization of traffic interaction studies, providing a structured approach to selecting, designing, and running scenarios under real-world constraints. We emphasize the logistics of running factorial experiments, including scenario selection criteria, decision-making processes, and strategies to mitigate participant burden.
# Novel Bionic Design Method for Skeleton Structures Based on Load Path Analysis
## 1 Introduction
In addition, the combination of topology optimization and porous structure of biological micro-structure makes the manufacturing process of these hollow structures very poor. It is difficult to manufacture directly by traditional mechanical processing, which restricts the engineering application of bionic design. The development of AM promotes the manufacturability of this kind of difficult-to-process structures to a certain extent [23; 24]. However, due to its long processing time, high material cost and process defects, the performance of parts is lower than that of traditional manufacturing technology, which leads to some difficulties in engineering application. Therefore, in the process of bionic design, if we can fully consider the manufacturing process and make the model adopt the traditional manufacturing method as far as possible, it will greatly improve the engineering application. Based on the above background, it is known that new bionic design methods are needed to improve the efficiency and effectiveness of bionic design, especially for complex structures such as vehicle components. The difficulties in selecting bionic prototypes for the whole structure could be avoid if the main load-transferred skeleton is extracted as the bionic main-branch and the bionic prototype is then selected for each sub-branch based on the specific load-transferred features. In this way, the efficiency of bionic design would be significantly improved. In this study, a novel bionic design method based on load path analysis is proposed by the bio-inspired design idea of main-branch and sub-branch to address the above-mentioned problems for the skeleton structures. The sections are organized as follows: the bionic design method is elaborated on in detail in Section 2. Taking the control arm of automobile suspension system as an example, the bionic design is carried out in Section 3. Section 4 verifies the effectiveness of bionic design followed by the conclusion in Section 5.
# Automatic 2D Floorplan CAD Generation from 3D Point Clouds
###### Abstract  
In the architecture, engineering, and construction (AEC) industry, creating an indoor model of existing buildings has been a challenging task since the introduction of building information modeling (BIM). Because the process of BIM is primarily manual and implies a high possibility of error, the automated creation of indoor models remains an ongoing research. In this paper, we propose a fully automated method to generate 2D floorplan computer-aided designs (CADs) from 3D point clouds. The proposed method consists of two main parts. The first is to detect planes in buildings, such as walls, floors, and ceilings, from unstructured 3D point clouds and to classify them based on the Manhattan-World (MW) assumption. The second is to generate 3D BIM in the industry foundation classes (IFC) format and a 2D floorplan CAD using the proposed line-detection algorithm. We experimented the proposed method on 3D point cloud data from a university building, residential houses, and apartments and evaluated the geometric quality of a wall reconstruction. We also offer the source code for the proposed method on GitHub.  
building information modeling (BIM); 3D reconstruction; 2D floorplan CAD; 3D point clouds +
Footnote †: journal: Applied Sciences
# On the Detection and Removal of Oxides from Laser-Treated Surfaces
## 3 Results
### Oxide Removal
At the same time, it increases with decreasing velocity. For the lowest frequency (6 MHz), oxide removal is the most effective, while the other two parameters do not have any pronounced effect. Even the least intense treatment (24 MHz, 480 m/s, 1 pass) resulted in noticeable oxide reduction. Such treatment also has an effect on the surface morphology, as shown in Figure 3. A comparison of Figure 3a (as-textured surface) and Figure 3b (treated with gentle ablation at the most intense setting) reveals that the major geometrical features of the texture are preserved, while only the micromorphology is affected. Specifically, the microroughness on the texture ridges is partially smoothed. In this figure, only the most diverse examples are shown, while for the other parameter combination, intermediate effects were observed. The heat accumulation temperatures measured during gentle pulsed laser ablation are shown in Table 6. Although intuitively the heat accumulation should increase with increasing pulse repetition frequency, as mentioned, e.g., in [37], in this case, the observed temperatures decreased with increasing frequency. This was due to the decrease in pulse energy with the increase in frequency while maintaining the same pulse overlap. When analyzing the correlation of oxide content with the heat accumulation temperature (Figure 5), an interesting result is seen. At temperatures higher than \(\sim\)370 \({}^{\circ}\)C, the oxide is removed completely, and at low temperatures, the removal is only partial and the oxide values are scattered. The ablation is performed in a short time (hundreds of picoseconds to units of nanoseconds) after the femtosecond laser pulses, and the measured temperature is the heat accumulation in hundreds of nanoseconds. But nonetheless, the process seems to be governed by thermal effects, as was observed for similar processes (cleaning, polishing) conducted through the laser ablation of an AM1 superalloy [38], where changes in the process were observed in a similar temperature range, from 325 to 405 \({}^{\circ}\)C, for the calculated heat accumulation. In this case, an increase in the repetition frequency also led to a decrease in the heat accumulation temperature. The scatter of the oxygen values on the left side of Figure 5 (high frequency, 24 MHz) is due to the different numbers of passes. When repeating the laser process, the oxides on the surface are partially removed in each pass, but the heat accumulation should stay the same. The measured difference in heat accumulation could be due to change in emissivity caused by the removal of oxides. This does not happen for lower frequencies, where the oxides are already removed in the first pass.