esa-sceva/satcom-chunk-collection huggingface dataset:
# Performance Evaluation of GFDM Channel Estimation Using DFT for Tactile Internet Application
## 2 GFDM Systems and Channel Model
\begin{array}{rcl}\overrightarrow{z}&=&\mathbf{A}^{-1}(\overrightarrow{x} \mathbf{H}+\overrightarrow{w})\\ &=&\mathbf{A}^{-1}(\mathbf{A}\overset{\rightarrow}{d}\mathbf{H}+ \overrightarrow{w})\\ &=&\overset{\rightarrow}{d}\mathbf{H}+\mathbf{A}^{-1}\overset{\rightarrow}{w} \end{array}  \tag{8}\]  
It is important to equalize the channel in order to rectify the transmitted data. However, the first thing needs to be done before equalizing the channel is to estimate the channel. The pilot symbol is an aid to help the receiver in recovering data.
## 2 Materials and Methods
### Geophysical Investigations  
The geophysical studies for habitat mapping in the northern Romanian marine unit, corresponding to ROSCI0066, were carried out with the help of a multibeam echosounder (MBES) and a sidescan sonar (SS). During 2019-2020, 3 cruises were carried out (MN-198, MN-227, MN-229, respectively) with the R/V \"Mare Nigrum\" for data acquisition in shallow waters between 20 and 40 m water depth (Supplementary Material Table S1). Geophysical data coupled with ground truth sediment and biological samples are widely used for habitat classification [42] and allowed us to characterize a large area in a short time.  
Two types of MBES were used to record bathymetric and backscatter data: Norbit iWBMSh, with a frequency range of 200-700 KHz, used both for bathymetry and backscatter data, and Elac 1050D MBES, with 50 KHz transducers, for bathymetry only. In addition, a Klein L3900 sidescan sonar, with 455 KHz transducers, was used for the backscatter data. Both MBES systems have transducers mounted on the vessel's keel. Calibration for roll, heave, pitch, roll and a GPS latency test were performed prior to beginning the geophysical investigations. Two real-time corrections were made to the MBES recordings. Corrections from a Motion Reference Unit (MRU) that determines the motion of the vessel/transducers (heave, roll, pitch, and yaw) are critical for the measurements' precision [43]. These were carried out by either an integrated MRU in the head of the MBES system for Norbit MBES or with an iXBlue Octans III MRU for the Elac system. The second set of corrections are for the speed of sound in the water column and were measured using a Valeport MiniSVP probe. Positioning was executed using a differential Global Navigation Satellite System receiver or a Global Navigation Satellite System receiver with Real Time Kinematic correction.  
While bathymetry was used to create a high-precision digital elevation model (DEM) of the seafloor, backscatter data along with sediment/biological samples were used to characterize physical/biological habitats. Multibeam data were processed onboard using the Hypack suite: MBMAX64 for bathymetry processing and Geocoder for backscatter data. Sidescan data were processed with Sidescan Targeting and Mosaicking in the Hypack suite. The sampling points design was established following the bathymetric and the backscatter mosaic maps and was analyzed onboard by an interdisciplinary team of researchers.
## 5 Case Study from Practical Business
From the results, it can be clearly concluded that that the proposed VRPSDP-TW-LO model may improve the efficiency of the service operations and reduce the total cost by considering the left-over  
Figure 5: The comparison of a case study of time penalty and left-over tray. Figure 6: Difference of performance between VRPSDP-TW-LO and VRPSDP-TW. cost, which was not included in previous research. For the example of a distribution service supporting convenience stores used in this case study, it is possible to secure a significant benefit for daily operations by reducing the cost from left-over trays, improving the service for stores. The proposed model can be applied not only to a distribution service for supporting convenience stores, but also to other services using unit containers, such as grocery stores, pharmacies, and marine container shipping businesses.
# Efficient Regression Testing of Software Product Lines by Reducing Redundant Test Executions
## 2 Background
### Software Product Lines  
**Definition 1**: **(product family)** _A product family is a set of products that have a significant amount of commonality._  
**Definition 2**: **(platform artifact)** _A platform artifact of a product family is an artifact (e.g., source code, test cases, etc.) that consists of the common parts of the product family and the abstractions of their variable parts._Definition 3: (product line) A product line is a product family that has a set of platform artifacts for its planned products.  
A product line with many features can potentially produce a huge number of products. However, in practice, only a subset of those products is actually planned for production as a product family. So, our method focuses on testing of the products planned as a product family because retesting all the (planned and unplanned) products whenever a change is made would be costly and unnecessary. When unplanned products are added as planned products to a product family, our method to be developed in this paper still can handle such a case by just obtaining information of source code and test cases for the added products.  
Definition 4: (product line code base) Product line code base is the entire set of code fragments that is used to produce products of a product line.  
A product line has its code base partitioned into fragments and certain combinations (or integrations) of them constitute products [3]. Given a product line code base \(CB=\{\text{cf}_{1},\text{cf}_{2},\ldots,\text{cf}_{n}\}\) where \(\text{cf}_{1},\text{cf}_{2},\ldots,\text{cf}_{n}\) are code fragments, each product of a product family is produced by combining a subset of \(CB\).  
Figure 1 presents an SPL project: (a) product line code base, (b) a product family that has three products, P\({}_{1}\), P\({}_{2}\) and P\({}_{3}\) and (c) test cases, t1, t2,... tn. t1 and t2 are common to all the products and t3 is common to P\({}_{2}\) and P\({}_{3}\). The products of the family are produced by copying code fragments for each product from the product line code base. For example, P\({}_{1}\) is produced by copying the code fragments of @Feature 1 and @Feature 2 and, P\({}_{2}\) and P\({}_{3}\) are produced by copying the code fragments of @Feature 1 and @Feature 3. These products have common code fragments between them. P\({}_{1}\), P\({}_{2}\) and P\({}_{3}\) share the code fragments of @Feature 1, and P\({}_{2}\) and P\({}_{3}\) share the code fragments of @Feature 3. The code fragments of @Feature 2 are unique to P1. In practice, this approach has been used by some major companies that adopted product line development [14; 15] and also by well-known existing SPL development tools such as FeatureIDE [16], Pure::variants [17] and CIDE [18].  
Figure 1: Examples of product line code base, product line test cases and product family.
# Innovative Vaporization of Wood Panel Waste into Activated Biochar for Efficient Phenol Adsorption
## 2 Materials and Methods  
### Preparation of Biochar and Activated Biochar  
Wood panel waste (WPW) was sourced from sawmills in the Abitbi-Temiscamingue region, QC, Canada. According to the manufacturer and the literature [33], the WPW contained approximately 88-90% wood particles, 10-12% urea-formaldehyde(UF) resin, and less than 0.5% melamine-formaldehyde(MF) resin by dry weight. The collected residues were ground and milled to <1 mm particle size to ensure homogeneity. Further details on these processes are available in previous studies [34].  
Biochar samples were prepared using CarbonFX fast pyrolysis (Airex Energy Inc., Becancour, QC, Canada) at up to 250 kg/h process capacity. First, the biomass moisture content in the WPW particles was reduced to below 40%. They were then subjected to pyrolysis at 450 \({}^{\circ}\)C for 2 s in a cyclonic fluidized bed reactor under a low-oxygen atmosphere. The resulting biochar was then transferred to a custom-designed furnace for physical activation at temperatures of 750, 850, and 950 \({}^{\circ}\)C under continuous CO\({}_{2}\) and N\({}_{2}\) flow at a rate of 3 L/min. The biochar and its activated forms were labeled as BWP, BWP750, BWP850, and BWP950, respectively.
## 3 Results  
### Trueness and Pricison  
To evaluate the distortion of the quadrant scan images of the experimental model, the trueness and precision of the four experimental groups were compared. The trueness shows  
Figure 3: Measuring the linear distance of the interarch marker using the surface matching software.  
different deviation according to dedentulous conditions. In Trios, significant difference was founded by pairwise comparison in following groups: FPS vs. PPS, FPS vs. SSDEB, PPS vs. LSDEB, SSDEB vs. LSDEB. In case of CS 3600, there was no significant difference among the dedentulous conditions. In 1500, there was significant difference between PPS and SSDEB.  
The result of trueness was different according to the scanner utilized. Trios had the best trueness, followed by CS 3600 and i500. In the FPS group, Trios (median 43.4 \(\upmu\)m) and CS 3600 (median 45.4 \(\upmu\)m) were statistically truer than i500 (median 65.0 \(\upmu\)m) (Figure 4). In the PPS group, Trios was statistically (median 24.6 \(\upmu\)m) truer than i500 (median 85.5 \(\upmu\)m). In the SSDEB and LSDEB groups, Trios (median 24.3 and 41.7 \(\upmu\)m) was statistically truer than CS3600 (median 38.4 and 45.8 \(\upmu\)m) and i500 (median 47.5 and 65.4 \(\upmu\)m).  
In case of the precision, a similar result was observed according to dedentulous conditions. In T500, FPS showed a significant difference in comparison with PPS and SSDEB. In case of Trios, there was a significant difference in the following groups: FPS vs. PPS, FPS vs. LSDEB, PPS vs. SSDEB, SSDEB vs. LSDEB. In CS3600, a significant difference was shown in PPS vs. SSDEB and PPS vs. LSDEB. No significant difference was shown in i500.  
Depending on the scanner utilized, T500 had the best precision, followed by Trios, CS3600, and i500. In the FPS group, T500 (median 18.6 \(\upmu\)m) and Trios (median 17.4 \(\upmu\)m) were statistically more precise than CS3600 (median 42.4 \(\upmu\)m) and i500 (median 50.1 \(\upmu\)m). In the PPS group, T500 (median 9.2 \(\upmu\)m) was statistically more precise than Trios (median 23.5 \(\upmu\)m), CS3600 (median 49.2 \(\upmu\)m), and i500 (median 55.3 \(\upmu\)m) (Figure 5). Trios was statistically more precise than CS3600, i500. In the SSDEB group, T500 (median 9.8 \(\upmu\)m) was the most precise, followed by Trios (median 18.9 \(\upmu\)m), CS3600 (median 35.6 \(\upmu\)m), and i500 (median 73.9 \(\upmu\)m). In the LSDEB group, T500 (median 1.7 \(\upmu\)m) was statistically more precise than Trios (median 23.4 \(\upmu\)m), CS3600 (median 34.6 \(\upmu\)m), and i500 (median 61.1 \(\upmu\)m). Trios, CS3600, was statistically more precise than i500. The trueness and precision results are summarized in Figure 6.  
Figure 4: Representative images of a color map for assessing the trueness of the IOS. (**A**) Trios 3, (**B**) CS3600, (**C**) i500. Trios shows a slight deviation on the occlusal surface. In CS3600, the minus deviation is observed in the central groove area. In i500, the minus deviation is mainly located on the inclined plane of the cusp. In color map analysis, maximum range was 1.0 mm, minimum range was 1.0 mm and tolerance level was \(\pm\)0.05 mm.
# Seismic Response Effect on Base-Isolated Rigid Structures by Mass Eccentricity in Nuclear Plants
## 6 Conclusions  
In this study, an investigation was carried out to assess the effects of seismic responses when mass eccentricity occurs in the base-isolated concentrated mass structure within a nuclear power plant. Sensitivity analysis, simulation analysis, and vibration table tests were employed for this purpose. Generally, when mass eccentricity occurs in the base-isolated upper structure, the dynamic characteristics are influenced by torsional or rocking behavior. The summarized findings are as follows:  
1. In case of horizontally mass-eccentric base-isolated structures, torsional modes can become dominant modes, and, as eccentricity increases, the contribution of torsional response increases.
2. For base-isolated upper structures, the influence of eccentric mass on the seismic response may not be significant compared with non-base-isolated structures. However, seismic response can increase or decrease by more than 40% depending on the location in the structure, so caution is required during design.
3. Actual tests using a 3D shaking table showed similar trends to sensitivity analysis and simulation results for horizontal motion.
4. The seismic response of secondary structures installed in base-isolated upper structures is relatively less affected by the mass eccentricity of the upper structure; however, it can reach around a 30-40% increase in the frequency range above 10 Hz.  
These findings provide valuable insights into the seismic response of base-isolated structures with irregular mass distribution and emphasize the importance of considering horizontal and vertical mass eccentricity effects during design and analysis.  
Conceptualization, T.-M.S.; methodology, T.-M.S. and B.-C.L.; validation, T.-M.S.; formal analysis, T.-M.S.; investigation, T.-M.S. and B.-C.L.; writing--original draft preparation, T.-M.S.; writing--review and editing, T.-M.S. and B.-C.L.; funding acquisition, T.-M.S. All authors have read and agreed to the published version of the manuscript.  
This study was funded by the Ministry of Trade, Industry, and Energy through KETEP. (Korea Institute of Energy Technology Evaluation Planning) (No. 20224B10200080).  
The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to preventing misuse for unwanted purpose by third party.  
This paper was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) under Grant No. 20224B10200080.
# Food System Digitalization as a Means to Promote Food and Nutrition Security in the Barents Region
## 4 Transforming the Food System through Digitalization to Promote Food and Nutrition Security
An essential feature of the knowledge base, which determines the requirements of the technologies for its implementation, is the high dynamism of its content. In our modern world, new products, ingredients, trademarks, supply chains appear and disappear very quickly over time. In such conditions it is extremely difficult to create and maintain the relevance of the knowledge base directly, relying only on the knowledge of experts. This increases the demand for intelligent information systems with feedback that implement the principle of \"user as an expert\" [70]. Another opportunity for digitalization in transforming the food system is that widely available e-communications will provide a basis for peer-to-peer networking within food systems that will include customer-to-customer, business-to-business, and business-to-customer (C2C, B2B, and B2C, networking respectively). One modern example of such a P2P network that partly cover the Barents region is the REKO system, which implements a new model of a sustainable marketing channel based on SNS interactions. The system unites small food producers (farmers) and consumers and \"offer consumers a way of ordering products directly from the producer, without the need for middlemen\" [71]. In addition, the system provides the production of food products in volumes and in assortment, taking into account the actual needs of consumers. Such a model of food producing and marketing makes the food system more diversified and resistant to disruptions from individual components including transportation. The example of REKO demonstrates the potential of digital modern ICT in the creation of sustainable distributed food systems for providing the population of the Barents region with quality nutritious food. Technically, there are no obstacles in using such technologies to create similar cross-border networks, including for larger businesses. However, this potential is not used due to organizational and political problems, such as sanction restrictions and differences within food systems regulations in different countries.
# Design and Performance Research of a Wearable Airbag for the Human Body
## 7 Conclusions  
In this paper, a wearable airbag system for pedestrians in a vehicle-pedestrian accident is proposed. Based on the verified gas inflator model, the finite element models of the wearable airbag systems and vehicle-pedestrian collision are established. The collision simulation is carried out, and the protection performance of the designed wearable airbag is evaluated. The main conclusions are summarized as follows:  
1. An integrated wearable airbag, which combines an inflation helmet and jacket is proposed to protect the safety of pedestrians during a vehicle-pedestrian collision. The gas mass of the inflator and the length of the pulling straps are the design parameters to improve the protection effectiveness.
2. The finite element model of the airbag inflator is first verified via an inflator pressure-tight vessel test. Then, the finite element model of vehicle-pedestrian collision is constructed to evaluate the protection performance of the newly proposed wearable airbag. The proposed wearable airbag shows an effective protection towards the HBM's head and chest. In particular, the protection effectiveness of the head is examined via HIC\({}_{15}\), 3 ms resultant acceleration, and the intracranial pressure.
3. The parametric study of the gas mass and the pulling straps length shows that 26 g gas and 20 mm pulling straps length provide the best protection for the HBM's head. If the gas mass is below 20 g, the head will smash through the airbag and hit directly on the vehicle hood. If the gas mass is too big, the airbag pressure will rigidize the airbag and weaken the protection effectiveness of the airbag.  
Conceptualization, W.T.; Methodology, X.Z.; Software, Z.X.; Validation, Z.X.; Formal analysis, X.Z. and Z.X.; Investigation, W.T.; Data curation, X.Z. and Z.X.; Writing--original draft, X.Z.; Writing--review & editing, W.T.; Supervision, W.T. All authors have read and agreed to the published version of the manuscript.  
[PERSON] acknowledges the support of Goodbaby International Holdings Limited for test data. [PERSON] also acknowledges funding support of 2021 Jiangsu High-value Patent Cultivation Program (upgrade category) (8411123002) and Goodbaby International (8421123004). [PERSON] acknowledges the support of Jiangsu University Faculty Startup Fund (5501120014) and Jiangsu Shuangchuang Doctor Program (171120022).  
The data used to support the findings of this research are included within the article.  
The authors declare no conflict of interest.
# People Detection Using Artificial Intelligence with Panchromatic Satellite Images
## 5 Conclusions  
The detection of people from satellite images remains a challenge. Faster R-CNN, YOLOv3, SSD, and RetinaNet in ArcGIS Pro implementation were tested for people detection. A validation method based on the calculation of distances between point-based locations of people (ground truth data) and gravity centers of polygons for predicted people was employed. Variants with buffers, masks, and data augmentation were analyzed. The most promising results were obtained with Faster R-CNN using a 15 cm buffer, no mask, the application of data augmentation, and a 60 cm validation distance, resulting in an F1 score of almost 55%. In the future, results may be improved with the implementation of selected textural features and other CNN models, using image super-resolution methods such as fast Fourier convolutions [41], or using deblurring techniques to increase image quality [42].  
Software, P.G.; Resources, L.O. and P.P.; Writing--original draft, P.G.; Writing --review & editing, P.K.; Supervision, J.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by grant SP2024/076 from VSB--Technical University of Ostrava.  
Not applicable.  
The datasets presented in this article are not readily available because data has to be purchased from WorldView3. Requests to access the datasets should be directed to the corresponding author.  
The authors declare no conflict of interest.
## 5 Conclusions  
In this study, four new sets of sensitive spectral indices were identified: NDSI (R\({}_{520}\), R\({}_{528}\)), RSI (R\({}_{748}\), R\({}_{561}\)), DSI (R\({}_{758}\), R\({}_{602}\)) and SASI (R\({}_{753}\), R\({}_{624}\)); these generated corresponding regression models (y = \(-\)78.33x + 17.6, y = \(-\)17.29x + 69.8, y = \(-\)160.5x + 57.1, y = \(-\)132.6x + 56.5). Some research results show that the non-destructive estimation of leaf chlorophyll content in the green and red-edge spectral range is optimal [32; 33], which is consistent with the results of our study. At the same time, the model established in our study is simple and practical and can be used to estimate the chlorophyll content of the peanut leaves. However, it is worth noting that since our study was only carried out in one ecological region, further experimental verification using plant species in different geographical and climatic regions and under different measurement conditions is necessary if these spectral indices are to be developed as a universal tool for vegetation remote sensing [34]. This will increase their value in the non-destructive monitoring and accurate diagnosis of crop chlorophyll content during peanut growth.  
Conceptualization, H.Q. and L.Z.; Data curation, B.Z., L.K., W.Y. and J.Z.; Formal analysis, B.Z.; Funding acquisition, Y.L.; Investigation, H.Q., B.Z., W.Y., L.K., J.Z. and L.Z.; Project administration, Y.L.; Resources, Y.L., L.Z.; Writing--original draft, B.Z.; Writing--review and editing, H.Q. and L.Z. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Key R&D Program of China (2018 YFD1000906), Key Science and Technology Planning Project of Guangdong Province (2019B020214003) and Guangdong Technical System of Peanut and Soybean Industry (2019 KJ136-05), Characteristic innovation projects of Guangdong Provincial Department of education in 2019: Study on variable spray system of plant protection UAV Based on small grid prescription map (2019 Ktscx015).  
The authors declare that there are no conflict of interest in the reported research.
# Industrial Image Anomaly Detection via Self-Supervised Learning with Feature Enhancement Assistance
## 3 Materials and Methods
### Datasets  
In order to validate the effectiveness and generalization of the algorithm proposed in this paper, we evaluate the proposed anomaly detection algorithm on two challenging publicly available unsupervised anomaly detection datasets--the MVTec [3] and the BTAD dataset [46].  
MVTec AD is an industrial anomaly detection dataset specifically proposed for unsupervised anomaly detection, which contains 15 subsets totaling 5354 high-resolution images across 10 target categories and 5 texture categories. The training set includes 3629 normal images, while the test set includes 1725 images of both normal and abnormal instances. Anomalies in the dataset include scratches, dents, missing defects, amounting to a total of 73 different defect categories to simulate real-world industrial anomaly detection scenarios. It is noteworthy that MVTec provides precise pixel-level annotations for each anomaly image in the test set, representing the anomalous areas. The BeanTech Anomaly Detection Dataset (BTAD) is a real-world industrial image dataset consisting of normal and defective products, with a total of 2542 images across three types of industrial products. Similar to MVTec, the training set comprises only normal images, whereas the test set contains both normal and abnormal images.