esa-sceva/satcom-chunk-collection huggingface dataset:
# Safety Risk Assessment in Urban Public Space Using Structural Equation Modelling
## 6 Conclusions  
### Benefits  
As the symbol of human civilization and the carrier of economic and social development, cities are the gathering centres of population, economic and social development. Previously, there were more than 2000 cities in the Northern Hemisphere alone, and nearly 50% of the world's population lived in cities [3]. Therefore, no matter in terms of quantity, scale, or role in social development, cities are in a stage of rapid development. To improve the population carrying capacity and economic efficiency of the city, developers and the government are vigorously building urban public spaces such as rail transit and commercial streets. However, urban public space is a complex giant system. It is not only complex in structure and densely covered with buildings but also relatively closed and highly mobile, which will inevitably lead to fire, stampedes and other safety accidents. How to optimize urban public space management and avoid risks on the basis of existing conditions has become the mainstream in the academic field of urban safety.  
This study uses literature analysis, a questionnaire survey, and SEM to build an index system of urban public space safety-influencing factors, and finally determines the key factors and proposes efficient risk management measures. We believe that this study can serve as an academic supplement to the academic field of urban safety. It can also provide feasible ideas for the government to formulate an urban public space safety management scheme. First of all, we use literature as a reference, a questionnaire survey as a data source, and SEM to build an initial model. Then, CFA is used to finally determine an index system consisting of three levels and 17 indexes. Finally, the standardized path coefficient is used to calculate the weight proportion of these 17 indexes in the whole system and rank them according to the weight. From the criterion layer, the factors that affect the safety of urban public space are construction equipment, road traffic, social governance, urban environment and urban behavior. Regarding the comprehensive standard layer, index layer and urban status quo, we should pay attention to fire awareness and epidemic prevention awareness.
# Depth-Oriented Gray Image for Unseen Pig Detection in Real Time
## 4 Experiment Results
Grayscale images demonstrated that detection results can be negatively affected when the brightness of objects and backgrounds is similar. While HSV-Saturation images effectively represented achromatic pigs with pixel values close to zero in various environments, they suffer from the drawback of losing texture information. The depth of the background played a crucial role in generating DOG images. Although generating depth images for every frame using Depth Anything was not feasible for real-time processing,  
Figure 7: Object detection results with different test image types. combining grayscale images and depth background images with equal weighting created an image similar to a depth image through simple image processing on a CPU. The Otsu algorithm was also applied to the generated depth background image to define the RoI region. Figure 8: Results of each step of the proposed method with different unseen environments. The RoI remained unchanged after initialization in the pigsty environment, where a fixed camera was used. This initial setup helped the object detection model identify the areas to detect, improving detection accuracy. The DOG images created from the above components generalized the foreground (pigs) across various environments while reducing the brightness values of the background. The images enabled a clear distinction between the foreground and background, and the DOG images enabled clearer object boundaries, with the green boxes representing the detected objects, resulting in more robust and precise detection even in challenging unseen environments. The DOG images not only addressed varying lighting conditions effectively but also enhanced object boundaries, resulting in robust and precise detection performance. For example, in the first column, the gray image shows a heat lamp positioned in the upper left corner near the feeding trough, where the brightness of objects decreases as they move further away from the lamp. Despite this variation in lighting conditions within a single image, the DOG image effectively distinguishes the boundaries between the white flooring and objects while maintaining similar brightness levels among the objects. The second column depicts an environment with natural light, where pigs near the light source appear brighter, and those farther away exhibit darker brightness levels. Similarly to the first column, the DOG image equalized the brightness levels among the objects, even under varying lighting conditions within the same image. In the third column, the gray image presents a scenario where the brightness of the pigs and the floor are similar, making differentiation challenging. However, the DOG image clearly separates the objects from the background, demonstrating its effectiveness. Lastly, in the fourth column, the black pig image highlights pigs darker than the floor. The DOG image adjusted the brightness of the black pigs to a level comparable to the white pigs in other DOG images, further enhancing the distinction between objects and improving overall clarity.
# Removal of Chromium from Synthetic Wastewater Using Modified Maghemite Nanoparticles
## 1 Introduction
NPs have been used in various fields, such as in cleaning applications, lubrication, stabilization of emulsions, preparation of nano- and microparticles, and even as model systems for biological membranes in protein research [21; 22]. SDS molecules contain a 12-carbon saturated alkyl chain bound to a negatively charged sulfonate head (-OSO3-), and therefore are structurally comparable to many bio-surfactants [23]. This makes them suitable for adsorption over the maghemite surface. To the best of our knowledge, NPs modified with SDS have not been used so far to study Cr+6 removal from wastewater. The main objectives of this study were to investigate the adsorption efficiency of modified maghemite nanoparticles (MNPs) for chromium removal and to determine their viability as an alternative for chromium removal from wastewater. The specific objectives of the present work are: (i) to synthesize MNPs using SDS and characterize them using XRD and FTIR; (ii) to determine the optimal process conditions for enhanced chromium removal; and (iii) to study the effects of pH, adsorbent dosage, and initial concentration on chromium removal using MNPs.
## 4 Discussion
### Uncertainty Analysis  
Assessing the uncertainty of a dataset is essential to understanding its reliability and limitations, as well as aiding other researchers in comprehension and validation. Previous analyses have shown fairly significant seasonal characteristics in the distribution of XCO2 data and its errors. Therefore, in this section, we independently analyze the uncertainty of the CNN-STK XCO2 dataset for different seasons using both the CAMS XCO2 dataset and the open-source 1\({}^{\circ}\) Mapping-XCO2 product. Furthermore, the RF feature importance algorithm will be used to explore the key impact factors on XCO2 data.  
Figure 8: The accuracies of XCO2 in different seasons and different clustering regions.
# When Intelligent Transportation Systems Sensing Meets Edge Computing: Vision and Challenges
## 4 Edge Computing: Opportunities in ITS Sensing Challenges
### Challenges in ITS Sensing
#### 4.3.1 Challenge 1: Heterogeneity
[238] developed an onboard edge computing system based on Nvidia Jetson TX2 for near-crash detection based on video streams. The system leveraged edge computing for real-time video analytics and communicated with another LiDAR-based system onboard; while the sensor sets and data generated from the two onboard systems were very different, the designed edge data fusion framework was able to address the data heterogeneity of the two groups neatly through a CAN-based triggering mechanism. In future ITS, data heterogeneity problems are expected to be more complex, involving not only data from different sensors on the same entity but also data with completely different characteristics and generation processes. Edge computing will make it one step closer to an ideal solution by formatting the data immediately after they are produced.
# Enhancing Ability Estimation with Time-Sensitive IRT Models in Computerized Adaptive Testing
## 6 Discussion
To clarify the experimental structure, it is important to note that the TestYourself platform utilized a standard 1 PL-IRT (Rasch) model for item selection during test administration,employing the Fisher Information Criterion to identify the most informative items based on current ability estimates. The six time-sensitive models introduced in this study (e.g., DTA-IRT, ART-IRT) were applied exclusively in the post-hoc analysis phase after the response accuracy and timing data were collected. This separation was intentional, ensuring that the live test administration remained stable and interpretable while allowing for a controlled evaluation of each model's ability estimation capabilities. Although response-time-informed models were not used in the real-time item selection process, their offline evaluation provided valuable insights into their performance without introducing bias during data collection. Future iterations of TestYourself may incorporate these models in real time to achieve a fully integrated adaptive testing system. In particular, we recommend extending this work by designing CAT systems that integrate expected response time into the item selection algorithm itself. Such a unified, real-time framework could enhance both fairness and measurement precision, especially for examinees across a wide range of ability levels. Importantly, the causal interpretation of our results is grounded in a controlled modeling framework. Since all response accuracy and timing data were collected under the same conditions using the standard 1 PL-IRT model, and item selection was held constant across all examinees, any observed improvements in AIC, BIC, or AUC across models can be directly attributed to the integration of response time during post-hoc ability estimation. The variation in results between subtractive and multiplicative time-aware models reflects differences in how response time is mathematically incorporated rather than experimental variability, thus establishing a clear cause-effect link between the modeling approach and estimation performance. However, we acknowledge that our current investigation is limited to post-hoc scoring, and the adaptive item selection process itself did not incorporate response time. Therefore, our findings, while theoretically supportive of time-aware item selection, do not provide empirical validation for its effects on real-time test efficiency or learning outcomes. Future research should simulate or implement real-time CAT algorithms that integrate response time into both selection and scoring procedures to empirically assess their impact on fairness and performance estimation.
## 4 Conclusions  
The results obtained have allowed us to verify our working hypothesis that the incorporation of \({}^{238}\)U and \({}^{226}\)Ra in a climate similar to a semi-arid one is related to that of stable elements. The study area was characterized by the high presence of radionuclides from uranium and actinium series, along with Cu and Fe values well above the global values for soils. Despite the complexity of this type of soil and the similarity of the climate in the study area to a semi-arid climate, no different TFs were obtained compared to those of areas with different climates, such as tropical ones. The range of transfer factors for \({}^{238}\)U varied between 1.5\(\cdot\)10\({}^{-4}\) kg\({}^{-1}\) kg\({}^{-1}\) and 7.8\(\cdot\)10\({}^{-3}\) kg\({}^{-1}\) kg\({}^{-1}\), while for \({}^{226}\)Ra, the range was between 1.8\(\cdot\)10\({}^{-4}\) kg\({}^{-1}\) kg\({}^{-1}\) and 4.0\(\cdot\)10\({}^{-2}\) kg\({}^{-1}\) kg\({}^{-1}\). Likewise, in addition to the values obtained for the TFs, the behavior of the natural radionuclides in relation to the stable elements, mainly K, Mg, Ca, Fe, and Ti, is similar to those observed in the literature. The results showed how K and Mg lead to the reduced incorporation of \({}^{238}\)U and \({}^{226}\)Ra due to the possible presence of mycorrhizal fungi, resulting from the greater incorporation of K and also competition between Mg and the remaining alkaline earth metals (Ra, Ca, and Sr). The presence of arbuscular mycorrhizal fungi has not been verified, and this conclusion is based on the results of previous studies; however, a count of arbuscular mycorrhizal fungi vesicles is necessary to ensure this conclusion. Furthermore, the mobility of \({}^{226}\)Ra is related to the presence of Ti, an aspect observed by the \({}^{226}\)Ra/Ti correlation in the biplot graph representing the TFs. Finally, the incorporation of U showed the expected behavior and correlated with the presence of Fe and Al typical of granitic soils like that of the study area. The correlations found were consistent with the parameters with the most weight in the absorption models of \({}^{238}\)U and \({}^{226}\)Ra. The interaction between Al and \({}^{238}\)U and \({}^{226}\)Ra was similar to that observed in clays, showing a positive relationship between them. On the other hand, Ti facilitates the movement of \({}^{226}\)Ra, which matched the positive relationship in the model. Finally, Fe retains Ra by forming a complex with Fe\({}_{2}\)O\({}_{3}\) when there is a high concentration of Fe, an aspect that is consistent with the levels found in the study area. Our results indicate that both _Scolymus hispanicus_ L. and _Erryingum campestre_ L. could be utilized in the phytoremediation of soils contaminated by natural radionuclides in semi-arid climates. Therefore, our results have confirmed that there is a significant relationship between the incorporation of stable and radioactive elements, which helps in understanding the absorption mechanisms of plants under conditions similar to a semi-arid climate.
# Two-Stage Metaheuristic Algorithms for Order-Batching and Routing Problems
## 1 Introduction  
Achieving high efficiency in order batching and picking operations has become highly crucial. To achieve low-cost and large-quantity throughput with fast delivery, batching and picking operations are the most effective picking activities. Picking time constitutes approximately 30-40% of the total working hours, and labor cost constitutes 15-20% of the total cost; moreover, traveling and picking time form 60% and 20%, respectively, of the total picking time [1]. Consequently, effectively reducing operating costs necessitates focusing on enhancing the efficiency of traveling and picking procedures.  
Warehouse management involves several categories, including storage planning, order batching, order picking, warehouse layout design, and storage policies [2]. The major challenge in warehouse management is the planning required to reduce the time, cost, and distance in picking operations. Regarding batching and picking problems, the major objective of this study is to effectively obtain an optimal solution within a limited time frame. We adopted the model of batching and picking problems proposed by [PERSON] et al. [3] as the study background and proposed five batch ordering strategies with two-stage simulated annealing (SA) and variable neighborhood search (VNS) algorithms to improve the solution. Finally, the results were compared with the same questions to determine which batch ordering strategy can quickly and effectively obtain solutions.  
The rest of this paper is organized as follows. Section 2 describes related work, and Section 3 introduces the integrated order-batching and routing problem, and presents the formulation of a mixed-integer optimization model. The two-stage SA and VNS algorithms proposed for deriving near-optimal solutions are presented in Section 4. Section 5 presents the performance evaluation of the proposed algorithms, conducted through computational analysis. The final section provides the conclusion and potential applications of the proposed algorithms.
## 3 Results  
### Diurnal and Seasonal Courses of GPP, PRI, and SIF  
The different cultivars planted each year produced variable leaf area indices (LAI) and maximum mid-season GPP, having been influenced by planting date and environmental conditions (Table 1). Daily GPP derived from tower-based eddy covariance measurements in the cornfield over four growing seasons is shown in Figure 1a. The grey dashed lines indicate the days when field campaigns were conducted. Corresponding daily precipitation, daily PAR, and daily average and high temperature observations are reported in Figure 1b-d, respectively. Clear seasonal dynamics were observed for GPP, which increased during the green-up vegetative stage, reached the highest productivity during mid-season, and steadily declined after that (Figure 1a). Within this general seasonal trend, an increase in GPP was usually observed after a noticeable precipitation event (Figure 1a,b). The highest mid-season GPP value (~75 g CO\({}_{2}\)/m\({}^{2}\)/d) was observed in early August of 2008 and in mid-July of 2010 (Figure 1a; Table 1), and comparable GPP values and seasonal patterns were observed in those two years. Lower maximum mid-season GPP values were observed in 2011 and 2012, mostly due to unfavorable environmental conditions, such as unseasonably high temperature and/or lower precipitation (Figure 1b,d).  
Our dataset consists of a total of 30 days of carbon fluxes and spectral observations. The diurnal patterns of GPP, LUE, SIF (red), and PRI are shown in Figure 2a-d, respectively, for a sample dataset of eight days. In general, all four variables showed different maximum (or minimum) values and clearly expressed diurnal dynamics (Figure 2). Lower GPP values occurred in early morning and late afternoon, and higher values occurred around mid-day, in concert with illumination and air temperature changes (Figure 2a). In contrast, LUE exhibited higher values in early morning and late afternoon, with lower values during mid-day, indicating lower efficiency due to mid-day thermal or moisture stress (Figure 2b). SIF (red) and GPP exhibited similar diurnal courses (Figure 2c). Diurnal patterns of (**a**) GPP, (**b**) LUE, (**c**) SIF (red), and (**d**) PRI for selected field days in four growing season.  
Figure 2: Diurnal patterns of (**a**) GPP, (**b**) LUE, (**c**) SIF (red), and (**d**) PRI for selected field days in four growing season.  
changes of PRI and LUE showed similar patterns, with higher values in early morning and the late afternoon, but lower values during mid-day (Figure 2d).  
The seasonal changes of NDVI, PRI and SIF are shown as daily average values, along with daily GPP values, in Figure 3. NDVI expressed little seasonal change during the 2008 field season but had more variation in the other years. However, the PRI and SIF values exhibited pronounced variations in magnitude and seasonal dynamics across the four growing seasons. Towards the end of the growing season in 2008, 2011, 2012, the PRI values declined rapidly to notably lower values during the senescent stage (Figure 3). In general, the PRI and all of the SIF variables had seasonal trends similar to GPP.
## 5 Analysis of Numerical-Simulation Results  
The spherical particles and ellipsoidal particles were utilized to construct a three-dimensional filter-layer soil column model with a height of 20 cm and a diameter of 10 cm in PFC. Tailings-sand particles of varying sizes were then added above the soil column for a muddy-water-seepage simulation test. The particle size of the filter layer was 2-5 mm, with spherical and ellipsoidal particle shapes, respectively, used for modeling. The ratio of the long axis to the short axis of the ellipsoidal particles, \(\lambda\), was 1.9. The tailings-sand muddy-water particles were assumed to be uniformly spherical, with particle sizes of 0.5-1 mm, 0.25-0.5 mm, and 0.075-0.25 mm. The walls were designated as impermeable. The model contained a total of 5 \(\times\) 5 \(\times\) 10 fluid units, with each fluid unit measuring 2 cm \(\times\) 2 cm \(\times\) 5 cm. The initial porosity of the model was set at 0.4, with a water pressure of 20 kPa applied at the top. The seepage direction was from top to bottom. A layer of filter with a pore size of 1.25 mm was placed at the bottom of the model.
## 4 Comparison of Attacks According to Affected Parameters
### Data Threats and Response Options  
As a result of global networking, which promotes data outsourcing and open access, data leakage has become a major risk in the context of big data, targeting databases and threatening privacy. Furthermore, data integrity, availability, and confidentiality are major concerns in large-scale collaborations, involving big data that frequently change [68; 69]. Computer attacks usually violate three major parameters denoted by CIA plus control [58]. As defined in Section 6, the components of CIA are the usual targets of attackers. As for attacks on control, a control violation occurs when an (unauthorized) attacker is granted privilege to violate the access control policy of a system [70].  
All the above incidents, as explained in Section 3, affect the integrity, confidentiality, and availability of a computer system and network resources [61]. Specifically, in DDoS and DoS attacks an attacker slows down a computer system by sending a huge number of queries to a network and trying to make resources unavailable to authorized users. For such attacks, a response that increases performance (or service availability) is necessary. In spoof attacks, internal attacks, distributed attacks, and password-based attacks, a computer system is under the control of attackers who can play with personal credentials. In this case an efficient response is needed for improving data integrity and confidentiality. In probing, phishing, and eavesdropping attacks, cyber-attackers attempt to collect private data and possible vulnerabilities from worldwide networks. In such cases, the response mechanism should improve service availability and data confidentiality.
## 4 Experiment and Analysis
### Experiment Result
#### 4.3.2 The Result of the Second Experiment
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Motion** & **Algorithm** & **AE** & **RMSE** & **ME** & **CEP of 75\%** & **CEP of 95\%** \\ \hline \multirow{3}{*}{Calling mode} & PDR & 7.98 & 9.24 & 14.28 & 11.23 & 13.48 \\  & PF & 1.01 & 1.26 & 3.30 & 1.51 & 2.27 \\  & APF & 1.84 & 2.39 & 6.39 & 2.76 & 4.27 \\  & AO-PSO-PF & 0.93 & 1.18 & 3.03 & 1.43 & 2.27 \\ \hline \multirow{3}{*}{Dangling mode} & PDR & 22.67 & 26.48 & 55.95 & 32.13 & 42.67 \\  & PF & 2.57 & 3.32 & 8.74 & 3.93 & 6.17 \\  & APF & 2.49 & 3.14 & 8.02 & 3.43 & 5.97 \\  & AO-PSO-PF & 1.95 & 2.58 & 6.28 & 2.73 & 4.87 \\ \hline \multirow{3}{*}{Handheld mode} & PDR & 42.37 & 50.01 & 107.89 & 57.53 & 88.67 \\  & PF & 1.80 & 2.35 & 6.50 & 2.83 & 4.47 \\  & APF & 6.97 & 10.12 & 29.60 & 9.93 & 26.57 \\  & AO-PSO-PF & 1.57 & 2.01 & 6.10 & 1.97 & 3.87 \\ \hline \multirow{3}{*}{Pocketed mode} & PDR & 2.94 & 3.56 & 8.69 & 3.83 & 6.97 \\  & PF & 1.37 & 1.95 & 4.97 & 2.33 & 4.27 \\  & APF & 1.70 & 1.89 & 3.40 & 2.03 & 3.37 \\  & AO-PSO-PF & 1.21 & 1.66 & 4.70 & 1.93 & 3.47 \\ \hline \multirow{3}{*}{General} & PDR & 18.99 & 22.32 & 46.20 & 26.28 & 37.45 \\  & PF & 1.69 & 2.22 & 5.88 & 2.65 & 4.29 \\ \cline{1-1}  & APF & 3.06 & 4.03 & 11.85 & 3.89 & 7.85 \\ \cline{1-1}  & AO-PSO-PF & 1.42 & 1.86 & 5.03 & 2.02 & 3.62 \\ \hline \end{tabular}
\end{table} 
Table 4: The detailed data for the PDR, PF, APF, and AO-PSO-PF with four postures. Figure 23: CDF errors for PDR, PF, APF, and AO-PSO-PF under different smartphone usage gestures in the 2 nd experiment: (**a**) CDF errors in the calling gesture; (**b**) CDF errors in the dangling gesture; (**c**) CDF errors in the handheld gesture; (**d**) CDF errors in the pocketed gesture.