esa-sceva/satcom-chunk-collection huggingface dataset:
# A Synergistic Elixir-EDA-MQTT Framework for Advanced Smart Transportation Systems
## 6 Evaluation
### Constrained Network Conditions Testing  
In real-world edge network environments, a variety of factors can contribute to unstable network conditions. Examples in edge networks include varying signal strengths due to geographical locations, network congestion caused by high user density, and intermittent connectivity issues in remote areas. Testing system performance under such unstable network conditions is crucial for improving our framework in edge computing scenarios.  
We set three groups of contained network conditions and evaluated them as shown in Figure 10.  
* Constrained_1: This scenario involved a network condition with a fixed delay of 100 ms and a packet loss rate of 1%. Under these conditions, the system managed to handle 8184 requests without any failures, maintaining an average RPS of 28.0. The mean latency was recorded at 114.19 ms, with the 90 th percentile latency reaching 119.0 ms.
* Constrained_2: This scenario set a base latency of 100 ms with a random fluctuation of up to \(\pm\)20 ms. The system processed 4575 requests and exhibited an average RPS of 20.7. The mean latency increased slightly to 121.32 ms, and the 90 th percentile latency rose to 165.0 ms, reflecting the impact of variable delay conditions.
* Constrained_3: This scenario tested the system's response to a higher packet loss rate of 5%. Despite this challenge, the system processed 6358 requests and achieved an average RPS of 22.6. Without extra latency added in this test, the mean latency in this scenario was significantly lower, at 29.92 ms, and the 90 th percentile latency was 20.0 ms.  
For comparison, under normal conditions without any imposed network constraints, the average latency of the system was around 8 ms. The observed latency showed an accordingly additional increase over the standard measurements, demonstrating a linear response to the network delay introduced.
# Data Extraction Method for Industrial Data Matrix Codes Based on Local Adjacent Modules Structure
###### Abstract  
A 2D barcode is a reliable way to provide lifetime traceability of parts that are exposed to harsh environments. However, there are considerable challenges in adopting mobile cameras to read symbols directly marked on metal surfaces. Images captured by mobile cameras are usually of low quality with poor contrast due to the reflective surface of 2D barcode symbols. To deal with this problem, a novel laser-marked Data Matrix symbols reading method based on deep learning is proposed for mobile phone captured images. Utilizing the barcode module features, we train different convolutional neural network (CNN) models to learn the colors of two adjacent modules of a Data Matrix symbol. Depending on whether the colors of the two adjacent modules are the same or not, an edge image is transformed from a square grid, which is the same size as the barcode. A correction method based on the KM algorithm is used to get a corrected edge image, which helps to reconstruct the final barcode image. Experiments are carried out on our database, and the results show that the proposed algorithm outperforms in high accuracy of barcode recognition.  
metal surface; barcode; data matrix; data extraction; deep learning Article
## 3 Results
### Functional Effect of SNPs Identified with MR in the Analysis with MDD and Insomnia  
The forest plots in which we compared the MR estimates using different MR methods against single SNP tests are shown in Figures 4 and 5. Ten and eight SNPs showed a significant effect when evaluating the effect of MDD on insomnia (Figure 4) or the effect of insomnia on MDD (Figure 5), respectively. These SNPs were further investigated to obtain information on their potential functional effect.  
RegulomeDB scores for the ten SNPs driving the effect of MDD on insomnia ranged from 0.03 to 0.92 (Table 4). Six SNPs were found to act as eQTLs for a total of 20 genes in different brain regions (Table 4). We found that proteins encoded by these genes show more interactions among themselves compared to what would be expected for a random set of proteins of the same size and degree distribution drawn from the genome (PPI enrichment value = 0.001, Figure 6).  
RegulomeDB scores for the eight SNPs driving the effect of insomnia on MDD ranged from 0.18 to 0.99 (Table 5). Four SNPs were found to act as eQTLs for a total of 5 genes in different brain regions (Table 5). Proteins encoded by these genes did not show a significant enrichment as regards to their interactions (PPI enrichment = 1).  
Figure 5: Forest plot of SNP specific estimates of the MR analysis with insomnia as the exposure and MDD as the outcome. For each SNP selected as an IV (n = 12), the upper part of the figure shows results of MR analyses conducted using the single SNP test implemented in the TwoSampleMR package, while the lower part of the figure shows results for analyses including all SNPs selected as IVs (these results are reported in red). Single SNP tests showed a significant causal effect of insomnia on MDD for 8 of the 12 IVs.
# Towards Incidence Management in 5G Based on Situal Awareness
## 5 Analysis and Decision-Making
### Analysis
#### 5.1.2 Risk Assessment  
Risk assessment combines some of the most widely spread strategies approved by the research community for Information Security Risk Assessment (ISRA), among them the guidelines ISO/IEC 27000 [7], NIST-SP 800 [8], CVSS-SIG-First [9] or MAGERIT [10]. The approach to identify risk factors assumes the basis on ISO/IEC 2700 series and NIST-SP800. However, since these are mainly aimed at general purpose risk assessment, they lack specificity; in particular, they do not take into account the 5G design principles, infrastructure or requirements. Because of this, they must be adapted to the 5G mobile networks circumstances. Another obstacle is that they are based on metrics that are too simple. In order to improve the ability to understand the impact and facilitate decision-making, as well as consider a more current model, a group of advanced measures similar to those proposed in CVSS-SIG-First should be adapted. Thereby, a larger amount of characteristics on the potential vulnerabilities should be studied, thus assuming the union of three metric sets that contain intrinsic (base), temporal and specific (environmental) features. On the other hand, approaches like MAGERIT provide alternative ways to calculate risks, which may be particularly useful in certain use cases. In general terms, the risk assessment component may be integrated as part of the detection module or could be deployed completely independently. Bearing in mind the taxonomy of ISRA approaches [20], it is recommended that its development considers qualitative assessment criteria, service-based perspectives, vertical valuation and propagated measurement.
# Multi-Mode Lithium-Ion Battery Balancing Circuit Based on Forward Converter with Resonant Reset
## 7 Conclusions  
A symmetrical lithium-ion battery active balancing circuit based on a forward converter with resonant reset is proposed in this paper, and an \"adaptive selection mode based on the state of high energy battery\" balancing strategy is proposed. As a result of this balancing method, the lithium-ion batteries have greater balancing power and faster balancing speed during balancing. The following conclusions can be drawn:  
* The proposed balancing circuit utilizes a forward converter to achieve high-power balancing.
* A switching matrix consisting of an SPST relay realizes the MC2 MC (Multi-Cell-to-Multi-Cell)) balancing method, simplifies the structure of the balancing circuit, makes the circuit easier to drive and control, and reduces the cost of the balancing circuit.
* The proposed balancing strategy allows the balancing circuit to have both n-cell-to-n-cell and n-cell-to-(n-1)-cell balancing modes and provides a flexible transmission path for energy.
* An experiment with an eight-cell lithium-ion battery pack was performed. The experiment result at 1260 s shows that the proposed method has a fast balancing speed, and the comparison with [31] shows that the balancing time in the proposed method is reduced by about 82.5%. Moreover, the maximum balancing efficiency of the proposed method is about 83.31%. Consequently, the proposed method has a good balancing performance.  
In the proposed method, the switching matrix consisting of the SPST relay is easy to drive and control; however, this results in the balancing circuit having a large size. Thisis the most significant limitation of the proposed method. In the future, a key work of the MC2 MC balancing circuit will be to study the switching matrix having a simple drive method and smaller size.  
Conceptualization, Y.Z. and K.L.; Methodology, Y.Z. and K.L.; Software, Y.Z.; Validation, K.L.; Formal analysis, Y.Z. and K.L.; Data curation, Y.Z. and Q.W.; Writing--original draft, Y.Z.; Writing--review & editing, K.L.; Visualization, Y.Z., Q.W. and J.M.; Supervision, K.L.; Project administration, K.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The research data in this paper are presented in the manuscript in the form of graphs or tables, which can be viewed in the manuscript.  
The authors declare no conflict of interest.
## 3 Summary of the Considered Mobility Models and Routing Protocols
### The Routing Protocols
#### 3.2.5 Flooding  
Flooding indicates that no routing protocol is used. The source node simply broadcasts the data packet to all of its neighbors. Each neighbor receiving the data packet also blindly broadcasts it to its neighbors. This simple receive-and-broadcast mechanism continues until the destination is reached. Obviously, this method is expected to add a high traffic load to the network, and that traffic load can be viewed as overhead. The advantage of this method is that it guarantees the delivery of any data packet unless the network is partitioned and the destination completely unreachable. Therefore, the packet delivery ratio obtained by this method can be viewed as the upper bound for any routing protocol in the given network.
## 3 Experimental Results and Analysis
### Strain Rate Effects on Characteristic Stresses
Notably, the rate of increase in \(\sigma_{\rm ci}\) relative to the logarithm of strain rate is lower than that observed for \(\sigma_{\rm cd}\) and \(\sigma_{\rm p}\). This pattern is consistent with previously reported strain rate dependency characteristics of \(\sigma_{\rm ci}\) under uniaxial loading conditions [19], suggesting that the strain rate exerts minimal influence on \(\sigma_{\rm ci}\) across the quasi-static strain rate regime. Figure 5: The different deformation stages in granite specimen stress–strain curve (\(\sigma_{\rm cc}\)—compaction limit; \(\sigma_{\rm ci}\)—crack initiation stress; \(\sigma_{\rm cd}\)—crack damage stress; \(\sigma_{\rm p}\)—peak stress; \(\sigma_{\rm i}\)—failure stress). \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Scheme 1. ** & \begin{tabular}{c} **Strain** \\ **Rate (s-1)** \\ \end{tabular}  & **CP (MPa)** & \(\sigma_{\text{cl}}\) **(MPa)** & \(\sigma_{\text{cd}}\) **(MPa)** & \(\sigma_{\text{p}}\) **(MPa)** & \(\sigma_{\text{cl}}\)**(\(\sigma_{\text{cl}}\)/\(\sigma_  
Table 3 provides the linear regression equations between characteristic stresses and the logarithm of the strain rate, while Figure 8 illustrates the relationship between linear correlation coefficients and the confining pressure. The results reveal three key patterns: (1) the linear correlation coefficients for \(\sigma_{\text{ci}}\), \(\sigma_{\text{cd}}\), and \(\sigma_{\text{p}}\) progressively increase with elevated confining pressure; (2) under identical confining pressure conditions, \(\sigma_{\text{ci}}\) exhibits significantly lower correlation coefficients compared to \(\sigma_{\text{cd}}\) and \(\sigma_{\text{p}}\); (3) the correlation coefficients of \(\sigma_{\text{cd}}\) and \(\sigma_{\text{p}}\) demonstrate consistent variation trends with confining pressure and maintain comparable magnitudes across the experimental pressure range. Figure 8: The relationship between linear correlation coefficient (characteristic stresses and the logarithm of strain rate) and confining pressure. Figure 7: The relationship between characteristic stresses and the logarithm of strain rate under triaxial loading ((**a**) \(\sigma_{\text{ci}}\); (**b**) \(\sigma_{\text{cd}}\); (**c**) \(\sigma_{\text{p}}\)). The related investigations have demonstrated that under triaxial quasi-static loading conditions, the strain rate sensitivity of \(\sigma_{\rm p}\) exhibits a decreasing trend with increasing confining pressure, a phenomenon commonly observed in brittle rocks such as granite and sandstone [13; 21]. However, the underlying mechanisms governing this confining pressure-induced suppression of rate-dependent strength remain inadequately understood. Furthermore, the potential existence of similar confining pressure dependencies in strain rate effects on characteristic damage thresholds--specifically \(\sigma_{\rm cl}\) and \(\sigma_{\rm cd}\)--requires experimental verification. To address these problems, this study proposes dynamic strength
## 3 Development of a Two-Dimensional Finite Element Model of a Unit Load Segment
### FEA Material and Section Assignments  
The pallet analog, or board, was modeled as a two-dimensional object with dimensions of 1016 mm along the length and a thickness of 19 mm, made out of Poly-methyl methacrylate (PMMA). Boxes were also 2D objects with dimensions 338 mm \(\times\) 318 mm. A homogeneous solid section thickness of 254 mm was used for all instances as the material depth along the \(Z\)-axis. The materials utilized for the pallet analog and boxes were defined as homogeneous, isotropic, and linear elastic, specified by the Young's modulus and Poisson's ratio. A stiffness value high enough as to be effectively considered rigid (600 GPa) was used for the boxes or packages to simulate non-deformable objects under the loading events presented but maintaining the additional material properties of linear elastic objects. Additionally, the mass densities of the board and boxes were required, since loading was applied through gravitational acceleration. A summary of the model's material properties is presented in Table 1. The aluminum rack beams of a warehouse rack were modeled as 2D discrete rigid objects measuring 50.8 mm \(\times\) 50.8 mm with their corners rounded to a 5 mm radius in order to replicate the same contact properties experienced by the board, representing the pallet analogue, and the beams in the racking condition simulated.  
\begin{table}
\begin{tabular}{c c c c} \hline
## 2 Materials and Methods
### Timber Image Acquisition and Crack Severity Classification  
We prepared 32 square cedar timbers with a 3000 mm length, as shown in Figure 4a, and then carried out high-temperature drying. Orange block pieces were cut out, and 32 blocks were obtained for the upper and root sides. As shown in Figure 4b, we scanned the images of the cross-sections surrounded by the green dashed lines using a scanner. Hence, 32 pictures for the upper side blocks and 32 pictures for the root side blocks were obtained, i.e., a total of 64 pictures.  
A crosscut saw (KM-3C; Kobayashi Kikai Kogyo Co., Ltd.; Mishima-City, Shizuoka, Japan) was used to cut square timbers, as shown in Figure 5a. A belt sander (HUS-3: Hasegawa Wood Tech Co., Ltd.; Fuchu-City, Hiroshima, Japan) was used to flatten the cross-section. A scanner (Canon CanoScan LiDe 700F) was used to photograph the cross-section, as shown in Figure 5b. The scanning resolution was 200 dpi.  
Figure 4: Timber details and scanning method for cross-sectional images. (**a**) Size of 32 square cedar timbers. Orange block pieces were cut out; (**b**) We scanned the images of the cross-sections surrounded by the green dashed lines.  
Figure 5: Scenes for timber processing and image acquisition. (**a**) Cutting scene of square timber; (**b**) Image of the cross-section is scanned using a scanner.  
We classified the obtained 64 images depending on the cracking severity into classes A (Good), B (Neutral), and C (Bad), expressing the timber condition. Examples of these images are shown in Figure 6. Figure 6a shows the images categorized as class A (Good) with almost no cracks. Figure 6b shows class B (Neutral) with minor cracking. Figure 6c, which is labeled as class C (Bad), shows a lot of noticeable cracking with risk to strength. Among all 64 images, 20 images were in class A (Good), 20 in class B (Neutral), and 24 in class C (Bad).
## 3 Proposed Methodology
### Receiver Structure  
A receiver with channel estimation and MIMO detection is proposed using LS-DFT with overlapping pilots. Without sacrificing generality, each subcarrier in each frame-block is assumed to have a pilot, i.e., NF = NT = 1, yielding N(T.S.) = N.N.T., and pilot existence of multiple or redundancy N.R. = N (T.S.)/N.G. The phase difference of the received signal causes multipath fading. This is because the signal strength moves over varying distances and paths. Use a Rayleigh distribution to reach the receiver via multiple paths. For fast-fading situations, the Rayleigh distribution is most commonly used. The pilots are assigned by reusing the pilot sequence from the multiple request pilot requests themselves. The multi-objective optimization algorithm can easily optimize the time-varying channel metric. The proposed pilot allocation method has the potential to provide a powerful method for counting the sends with a request to users within their cells. The fitness function (F.F.) is a crucial component of evolutionary algorithms. The pilot pattern of multiple pilot requests is reused in this document for the pilot assignment. The optimization algorithm can optimize the channel measure that changes over time.  
The proposed pilot allocation method has the potential to provide a powerful method for counting the requesting users in their cells. The fitness function (F.F.) is critical to the receiver-side optimization concept.  
In order to develop a solution for parallel search optimization and the continuous process, the DFT-LS-WIENER technique is proposed. Because control parameters are included, the suggested DFT-LS-WIENER offers improved convergence benefits. With efficient continuous variable handling and integer variable optimization, the suggested DFT-LS-WIENER is provided in canonical form.
## 2 Datasets and Preprocess
### MODIS Land Surface Phenology Product  
The MODIS land surface phenology (LSP) product (MCD12Q2, V061) provided by NASA is an annual dataset with a spatial resolution of 500 m that estimates phenological parameters via spline fit based on the 2-band enhanced vegetation index calculated from MODIS nadir BRDF adjusted surface reflectances (NBAR-EVI2). Previous comparisons and validations have shown that MCD12Q2 exhibits high accuracy and good generalizability [48; 49; 50; 51] and has been applied in many studies worldwide. In this study, the \"greenup\" and \"dormancy\" bands of MCD12Q2 were used to represent the SOS and EOS, respectively.
## 3 Experimental Investigation
### Evaluation of the Initial Numerical Model
#### 4.1.1 Evaluation of the Vertical Compression Stress  
In the numerical model of the structure, the vertical compressive stress caused by self-weight was validated at the measurement points where the compressive stress determination test was carried out (Table 5).  
In the numerical model, the concentration of tensile or compressive stress occurs in the corners and at the joints of finite elements of different directions. The numerically obtained vertical stress level at the ground floor corresponds approximately to the experimental results, but the stress level on the 1 st floor is slightly differ from the experimental result. The difference in results in both cases can be justified by the floor plan position of the load-bearing walls. The wall of the FJ-GR-1 measurement point is an internal load-bearing wall and, as such, transmits the load of the slab on both sides, while the wall of the FJ-GR-2 measurement point can be considered as an external load-bearing wall and, therefore, transfers the load of the slab from one side only.  
Figure 9: Initial numerical model of the case study: (**a**) mass of the staircase and (**b**) representation of the mass of partition walls in the numerical model.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Floor, m**} & **Measurement** & \(\sigma_{0}^{exp}\) & \(\sigma_{0}^{num}\) & \(\Delta\sigma_{0}^{exp,num}\) \\  & **Point** & **[MPa]** & **[MPa]** & **[MPa]** \\ \hline GR & FJ-GR-1 & 0.54 & 0.55 & 0.01 \\ GR & FJ-GR-2 & 0.43 & 0.35 & 0.08 \\
1F & FJ-1F-1 & 0.59 & 0.38 & 0.21 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Comparison of the vertical compressive stress numerically obtained \(\left(\sigma_{0}^{num}\right)\) with the experimentally obtained \(\left(\sigma_{0}^{exp}\right)\) in form of their differences \(\left(\Delta\sigma_{0}^{exp,num}\right)\).
# Virtual Fire Evacuation Drills through a Web-Based Serious Game
## 3 Technical Methods
### System Design  
The web-based serious game includes three main functions: registration/login, evacuation drill, and result feedback. Firstly, trainees need to register or log into the game, from where their basic information (e.g., usernames and IDs) can be collected. Secondly, trainees can perform the virtual evacuation drill using the game. In this process, the game records the drill data of the trainees, such as the evacuation path, evacuation time, and smoke hazards. Lastly, the game calculates the safety scores of evacuations and shows them to the trainees after the training.  
To implement the above functions, the system of the web-based serious game is composed of a front end, back end, and database, as shown in Figure 2. The front end is designed as the interface of the above three functions, whereas the back end is used for the operation of these functions. Additionally, the database is used to store and manage the data of this system.  
A widely used database, MySQL [41], was selected as the database for this system. The database includes two main groups of data. One is the user information, and the other is the drill data (e.g., evacuation path, evacuation time, and smoke hazard value). In the front end, the functions of registration/login and result feedback are easily implemented using JavaScript [42], and the evacuation drill function can be developed by WebGL [43]. However, efficiently visiting the database from the front end is a primary issue for the above functions. In this study, the widely used Socket protocol was employed to directly access the MySQL database from the front end.  
As mentioned before, the front end was developed using JavaScript. To match the front end, the Spring MVC [44], a Java framework, was used to build the back-end web applications. Note that the key algorithms of the back end for the result evaluation will be elaborated in the chapters of drill evaluation.