esa-sceva/satcom-chunk-collection huggingface dataset:
# Suitability of Graph Database Technology for the Analysis of Spatio-Temporal Data
## 7 Conclusions and Future Work
### Migration and Product Maturity  
Graph database technology is currently under rapid development, with each vendor having their own API and query language. Each graph query language is designed to express graph traversals in a more graph-oriented approach. The learning curve when migrating from SQL may pose an issue, but languages such as Cypher or GSQL make this minimal by applying concepts from SQL in the graph context.  
Security and reliability used to be an issue when considering migrating to graph database technology, but both of the products we considered can be configured to use encrypted communication and can be robust to failures. For example, TigerGraph's Rest++ API can be encrypted, integrated with Single Sign-On, and require authorization with LDAP authentication. It is important to note that PostgreSQL can create function-linked, encrypted HTTP endpoints, similar to TigerGraph's Rest++,by combining PostgreREST and PL/pgSQL functions. JanusGraph transactions can be configured to be ACID-compliant when using BerkeleyDB, but this is not generally the case with Cassandra or HBase. TigerGraph and Neo4j are already ACID-compliant, so it is in competition with relational databases with regards to reliable transactions. The implication of this is that graph database technology can provide the same level of robustness and security as relational database technology can, so one should not have to sacrifice on either of these when migrating.
# Low-Complexity Multi-Size Circular-Shift Network for 5G New Radio LDPC Decoders
## 3 Proposed Low-Complexity Multi-Size Circular-Shift Network for 5G New Radio LDPC Decoder  
### Modified Lifting Size Table for 5G New Radio LDPC Codes  
LDPC codes for the 5G NR wireless communication standard are defined for 51 different lifting sizes \(Z\) as shown in Figure 4a. The set of lifting sizes \(Z\) supported for the base graph are all values of the form \(Z=a\times 2^{j}\) for \(a=2,3,5,7,9,11,13,15\) where \(0\leq j\leq 7\) and includes all such \(Z\) distributed over the range from 2 to 384. The lifting sizes \(Z\) can be organized into eight sets, one for each value of \(a\). To make it more convenient for our proposed MSCS network structure, the lifting size table is efficiently modified as shown in Figure 4b. Precisely, the two rows for \(j=6\) and 7 are removed from the modified table. Instead, three new columns for \(a=8\), 10, and 12 are created in the table. Accordingly, the value of lifting sizes \(Z=128\), 192, 256, 320, and 384 are sufficiently reallocated into new positions in the modified table.
# The Impact of Distributed Energy Storage on Distribution and Transmission Networks' Power Quality
## 4 Results
### Comparing the Variants' Power Quality Performance Results with Expectations  
4.3.1 Significance of ESS Integration within an Interconnected Transmission and Distribution Network  
The data analysis presented in paragraph 3, and Table 3 shows that integrating ESS into the benchmark network improved the voltage magnitude and voltage angle deviation performance parameters of power quality. The range of performance for improvement in average voltage magnitude ranged between 0.13% (for TN-C_WST and TN-C_EST variants) and 4.57% (for DN-D_All variant). While the improvement in voltage angle also at the same variants ranged between 0.04\({}^{\circ}\) and 2.07\({}^{\circ}\).
# A Simplified Matrix Formulation for Sensitivity Analysis of Hidden Markov Models
## 4 Sensitivity Analysis of Smoothing Probability
### Initial Parameter Variation
#### 4.2.1 Algorithm Implementation  
As discussed above, the sensitivity function for the backward probability \(p(\mathbf{y}_{\mathbf{e}}^{t+1:T}|x_{v}^{t})(\theta_{\gamma})\) with \(\theta_{\gamma}=\gamma_{t}\) is a polynomial of degree zero. The contents of the backward matrices \(B^{k}\) are filled as follows. \(B^{T}\) is initialized as a vector of ones for \(n\) hidden states.  
\[B^{T}=ones(n,1)\]  
The remaining matrices \(B^{k}\) of size \(n\times k,k=T-1\leq k\leq t\), are computed by filling them as follows. Once the observation matrix \(O^{k+1}\) is represented as a diagonal matrix, \(B^{k}\) is set as the matrix multiplication of \(A\), \(O^{k+1}\) and \(B^{k+1}\). \(B^{k+1}\) represents the recursion in the backward probability.
## 2 Materials and Methods
### N-Way Wilkinson Power Dividers Based on Slow-Wave Structures
#### 2.2.2 WPDs with Meandered Transmission Lines  
The meandered line model taken into consideration in this paper is shown in Figure 9. According to the even or odd number of meandered sections, the equivalent circuit model is depicted in Table 1[29].  
Figure 8: (a) Four-way WPD loading with narrow slits. (b) Eight-way WPD loading with narrow slits.  
Figure 7: (a) Effects of narrow slits on the frequency response. (b) Effects of locations of the isolation resistor on the frequency response.  
Figure 9: Meandered line model.  
In a similar manner to the slit-loaded transmission lines, meandered sections can also be used for size reduction. Figure 10a illustrates a 2-way cascaded WPD constructed by meandered transmission lines. An RT/Duroid substrate with a relative dielectric constant of 10.2 and a thickness of 1.27 mm was used in all design processes. Effects of the number of meandered sections on the frequency response are depicted in Figure 10b. Here, the number of meandered sections is changed, starting from the middle of the transmission line. Depending on the proposed approach, a size reduction of 20.14% can be achieved.  
In addition to 2-way WPDs, more than 2 power-dividing operations can be necessary for the antenna arrays to be used in multi-way systems. For this purpose, the designed 2-way WPDs can be enhanced to 4-and 8-way circuits by means of meandered transmission lines, as shown in Figure 11a,b. As can be seen from Figure 11a, two two-way WPDs were connected in cascade for the four-way design. In this case, two reflection zeros can be observed since there are two identical transmission lines. In the eight-way WPDs, three reflection zeros appear due to the three cascaded transmission lines shown in Figure 11b. Here, the dimensions of the transmission lines, the isolation resistor and the resistor position are same as the 2-way WPDs. Accordingly, it is possible to achieve power-dividing operations in wider frequency bands by using more cascaded sections. The size reductions for the proposed 4- and 8-way power dividers are 16.62% and 9.99%, respectively. Electrical lengths of the proposed 2-, 4-, and 8-way WPDs are 0.20 \(\lambda_{\text{g}}\)\(\times\) 0.078 \(\lambda_{\text{g}}\), 0.56 \(\lambda_{\text{g}}\)\(\times\) 0.25 \(\lambda_{\text{g}}\), and 0.63 \(\lambda_{\text{g}}\)\(\times\) 0.57 \(\lambda_{\text{g}}\), respectively, where \(\lambda_{\text{g}}\) is the guided wavelength at the center frequency. Frequency responses of the designed circuits are given with the experimental studies in the following section.  
\begin{table}
\begin{tabular}{c c} \hline Odd line & \(\bullet\bullet\bullet\bullet\) \\ Even line & \(\bullet\bullet\bullet\bullet\) \\ \hline \end{tabular}
\end{table}
Table 1: Meandered line models and their equivalent circuits.  
Figure 10: (**a**) Conventional 2-way WPD having meandered transmission lines. (**b**) Effects of WPD meandering on the frequency response.
# Traditional Bangladeshi Sports Video Classification Using Deep Learning Method
## 4 Experiments
### Dataset Description
#### 4.1.1 TBSV Dataset  
As mentioned earlier, a few attempts can be found to classify traditional Bangladesh sports videos. However, unfortunately, there is no standard dataset for this task. Therefore, one of the vital contributions of this work is to develop the novel TBSV dataset. This dataset  
Figure 2: The architecture of the scratch model.  
consists of 500 traditional Bangladeshi sports videos belonging to five classes: Kabaddi, Boli Khela, Kho Kho, Lathi Khela, and Nouka Baich, collected from Youtube. The details of this dataset are illustrated in Table 1. Examples of sequential frames of five classes are portrayed in Figure 3.
## 5 Discussion  
To this point, we have assumed that the distance between entity centers is always at least 2 (i.e., entities never properly intersect), and that the encroachment threshold is exactly 2 (i.e., we are only concerned with avoiding entity contact). However, without changing the units of distance and time, we can model a collection of unit-radius entities, any pair of which possibly intersect but whose centers always maintain distance at least some positive constant \(\rho_{0}<2\), by simply scaling the constant \(c_{d,x}\) by \(\rho_{0}/2\). Similarly (and simultaneously), we can model a collection of unit-radius entities with encroachment threshold \(\Xi>2\) by(i) changing the _basic uncertainty radius_ (the radius of the uncertainty region of an entity immediately after it has been queried) to \(\Xi/2\) thereby ensuring that entities with disjoint uncertainty regions do not encroach on one another, and (ii) changing \(X_{d}\) to be the largest \(x\) such that \(c_{d,x}\geq\Xi-2\) since for \(x\) exceeding this changed \(X_{d}\) there can be at most \(x-1\) entities that are within the encroachment threshold of any fixed entity.  
This relaxation of our basic assumptions makes it possible to additionally relax our assumption that location queries are answered exactly since potential errors in the response to location queries can be modeled by an increase in the basic uncertainty radius. Furthermore, it increases significantly the scope of applications of our results.  
For example, recall the problem concerning collision avoidance mentioned in the introduction. Here, it would be useful to consider encroachment occurring well before contact (inviting the use of an encroachment threshold \(\Xi>2\)). It follows from our results that, by achieving an uncertainty degree at most \(x\) at time \(\tau\), we obtain for each entity \(e_{i}\) a certificate identifying the, at most \(x-1\), other entities that could potentially encroach (in this more general sense) upon \(e_{i}\) at that time (those warranting more careful local monitoring).  
An additional application, considered in [2], concerns entities that are mobile transmission sources with associated broadcast ranges that one would expect might sometimes properly intersect, where the goal is to minimize the number of broadcast channels at time \(\tau\) so as to eliminate potential transmission interference. In this case, achieving uncertainty thickness at most \(x\) using minimum query frequency serves to obtain a fixed bound on the number of broadcast channels required at time \(\tau\), an objective that seems to be at least as well-motivated as optimizing the number of channels for a fixed query frequency (the objective in [2]).  
Both authors contributed to the investigation and writing of the presented research. All authors have read and agreed to the published version of the manuscript.  
This work was funded in part by Discovery Grants from the Natural Sciences and Engineering Research Council of Canada.  
Data Availability Statement: Data sharing is not applicable.  
The authors declare no conflicts of interest.
## 3 Proposed Method
### Integrity Checking Using a Watermark-Based Method for JPEG Privacy and Security  
A watermark-based integrity-checking approach based on JPEG Privacy and Security is shown in Figure 10, allowing for the verification of modifications in an image stream and/or a selected part of the metadata without the involvement of an authorized agency. The procedure involves the selection of a specific portion of the metadata using the index obtained from the XML content-type JUMBF box.  
Figure 8: Proposed watermark embedding scheme.  
Figure 10: Example of an integrity-checking procedure using a watermark-based method without an authorized agency.  
Figure 9: Proposed watermark detection scheme.  
In this procedure, the input consists of the watermarked image streams, the selected metadata, and the owner's key, which are fed into the watermark generation process. The resulting watermark (RBS) is then compared to the extracted watermark from the watermarked image stream. If the integrity check fails, information regarding the modified regions is provided. This procedure checks if an image stream and/or a selected part of the metadata are modified or not. If even minor changes in image streams and/or metadata occur, the generated watermark is different from the inserted watermark and does not prove its integrity. The owner's key is used for this encapsulating procedure as well. If this owner's key is mismatched when the integrity is checked, the result of the check is always that the checked image is the modified one. The procedure serves as a means of verifying the copyright holder. Integrity can only be demonstrated if the user has set an owner's key.
## 5 Experimental Results
### Case 2: Sudden Load Change  
Introducing a load disturbance, in Area 1, at 3 s, there is a sudden loss of 40 MW in the active power load. The frequency, DC link active power, generator output, and voltage in Area 1 continue to be monitored. The simulation results are compared between no additional frequency control and those using AFC and AGC coordinated auxiliary frequency control strategy, as shown in Figures 10-13.  
Figure 8: Comparison of DC link active power variations.  
Figure 7: Comparison of system frequency variations.  
Figure 9: Comparison of G1 and G2 output variations.  
Figure 11: Comparison of changes in generator output.  
Figure 12: Variation of DC voltage with different control strategies.  
Figure 10: Comparison of system frequency variations.  
According to the system frequency variation illustrated in Figure 10, following the abrupt reduction in load in Area 1, the surplus active power prompts an increase in the system frequency. In the absence of auxiliary frequency control, the frequency continues to rise, reaching a maximum deviation of up to 0.40 Hz, and then it slowly returns to a value close to the steady state around 38 s. In contrast, using the coordinated control strategy of AFC and AGC, the frequency peaks at approximately 50.3 Hz and, within about 5 s, swiftly reverts to the nominal value. Overall, the system frequency maintains a relatively stable condition. As shown in Figure 11, generators G1 and G2 jointly address the active power disturbance, with their output changes mirroring each other, with both manifesting sustained oscillations after the disturbance. When implementing the coordinated control strategy, the AGC unit in G1 assumes the primary responsibility for the load disturbance, resulting in smoother changes in generator output. Due to the response of the AFC controller, the DC link engages in short-term adjustments, facilitating the system's rapid return to steady-state operation within 10 s.  
As illustrated in Figures 12 and 13, it can be seen that the disturbance causes a change in DC voltage. The VSC2 station and VSC3 station, using the traditional control strategy, respond quickly, but the fixed droop coefficient fails to fulfill the adjustment demands, resulting in DC voltage oscillations. However, upon implementing the coordinated control strategy that includes adaptive DC voltage droop control and auxiliary frequency control, VSC2 and VSC3 stations effectively respond to DC voltage changes. They adaptively adjust the droop coefficient in real-time based on their own adjustment capacity and voltage fluctuations, thereby adjusting the active power of the converter station. The VSC2 station achieves the steady-state range following a brief adjustment period of approximately 1.6 s, thereafter requiring only minimal fine-tuning. The VSC3 station persistently responds to voltage fluctuations, continuously adjusting its power, and attains the steady-state range within approximately 8 s. This approach fully capitalizes on the VSC-MTDC's capabilities for rapid and controllable active power adjustments, thereby enhancing the system's frequency stability.
## 1 Introduction
The first approach can be tuning the production by altering physiological conditions, the use of elicitors/chemicals, and modulating the regulatory system in the native host. The second approach can be production in the rationally engineered heterologous host [18]. However, the heterologous expression suffers from various disadvantages, such as the limited efficiencies in the cloning of large BGCs; unavailability of a suitable expression platform; and incompatibility of the biosynthetic elements, such as biosynthetic precursors, regulations, and cofactors. These constraints provide strong support for the quest for mining NPs from native producers, including genetic and chemical induction-based approaches [18; 24]. Moreover, it is evident that a single potent _Streptomyces_ encodes more than 20-30 BGCs for diverse bioactive compounds among them most of them are cryptic, but it is not feasible to transfer all BGCs to heterologous host in the single setting. The holistic transfer of individual gene clusters in the single heterologous host or each gene cluster in separate heterologous hosts along with optimization of production parameters for target molecules is next to impossible effort. Therefore, the tuning or activation of the cryptic BGCs by the chemical modulation or the genetic intersection in the native host provides a tremendous opportunity for obtaining targeted, as well as untargeted NPs. Thus, this approach in most cases uncovers the unprecedented discovery of novel chemical structures with efficient biological activities [18]. In addition, the engineering/modulation steps may be less rigorous than the optimizations required in heterologous expressions, which requires rigorous steps of host selection and cloning, and in most cases, engineering of the producer host, optimizing the media components, and even the perturbation of regulation systems [24]. This review summarizes recent advancements in strategies for activation and discovery cryptic BGCs in _Streptomyces_, thus utilizing it as the most efficient native host for the production of promising bioactive molecules.
# Post-Processing for Shadow Detection in Drone-Acquired Images Using U-NET
## 2 Related Studies
### Shadow Detection Methods in Drone Images  
There has been a lot of research using various techniques to detect shadows as the importance of shadow detection in drone images has become more significant. Based on various research studies [9; 10; 11], shadow detection methods in drone images can be divided into three categories, which are property-based methods, model-based methods, and machine learning methods.
## 4 Mycobacteria Ecological Niches
### Plants  
NTM are frequently isolated from plants. _M. terramassiliense_, _M. rhizamassiliense_, and _M. numidiamassiliense_ were first described in tomato plant roots [210] and _M. sarraceniue_ and _M. helvum_ were first isolated in the pitcher plant in Minnesota sphagnnum peat bogs [211]. _M. avium_ was detected in the stems and leaves of different plant species after internalization into plant tissue through intact, as well as damaged, root systems, which can imply the role of plants in the spread and transmission of mycobacteria to other organisms in the environment [212]. Moreover, several plant-based foods have been investigated and found to be contaminated with NTM, namely those that are close to, or beneath, the soil surface [213]. NTM can still be present in contaminated food after washing. Additionally, a previous study reported the same genotypes of _M. avium_ in both infected patients and ingested contaminated food items [214]. [PERSON] et al. (2008) studied the lactic bacterial communities present in the phyllosphere of lettuce leaves and detected several _Mycobacterium_ spp. sequences, mostly _M. alvei_, in both leaves and soil [215]. _M. scrofulacecum_ is a frequent contaminant in the culture of plant tissue cell lines [216]. Furthermore, _M. ulcerans_ have been reported to grow and form biofilms associated with aquatic plants, implicating these plants as reservoirs of _M. ulcerans_ and establishing potential new links in the transmission chains involving humans [217]. Nevertheless, no clear proof of a real association (e.g., symbiotic, pathogenic, or mutualistic relation) between mycobacteria and plants has been demonstrated, with only co-isolation being confirmed.
# LightSeg: Local Spatial Perception Convolution for Real-Time Semantic Segmentation
## 2 Related Works  
### Semantic Segmentation  
Semantic segmentation has been a focus of research in computer vision, and several models have contributed significantly to this field.  
The fully convolutional network (FCN) [13] was a pioneering network that extended end-to-end convolutional networks to semantic segmentation tasks. It introduced a deconvolutional layer for upsampling, enabling the network to recover spatial information lost during downsampling. Another influential model, U-Net [14], built upon the FCN architecture by incorporating skip connections to combine high-level semantic information with coarse and fine surface details. While FCN adds corresponding pixel values, U-Net performs concatenation on its channels.  
The Deeplab series, including Deeplab [15], DeeplabV2 [16], and DeeplabV3 [17], have made significant contributions to semantic segmentation. These models introduced hole convolution, which increases the field of view without sacrificing spatial resolution. Deeplab models also incorporate Atrous spatial pyramid pooling (ASPP) [16] to extract multi-scale features using multiple dilation rates. Additionally, they leverage fully connected conditional random fields [15] (CRFs) to refine segmentation results and improve boundary smoothness.  
However, recent advancements in semantic segmentation have explored limitations inherent in CNN methods, which primarily rely on local information processing. To overcome these limitations, researchers have started to incorporate Transformer schemes such as VIT [18], SETR [19], TransUNET [20], and SegFormer [21]. These models tokenize the input image, enabling the exploitation of global information for better semantic segmentation performance.
# Intelligent Edge-Cloud Framework for Water Quality Monitoring in Water Distribution System
## 5 Results and Discussion
### Numerical Results
#### 5.3.2 Results of Scenario 2  
In this scenario, the MLP model trains and develops in the cloud and then needs to be sent back down to the edge, and we expect the latency to be higher than the latency of the previous scenario. Figure 22 depicts the total average latency that passed through three hops: sensor-edge, edge-cloud, cloud-edge (end-to-end) for the three areas. The result shows a high value at Area-3 and a low value at Area-1. The throughput used to send all data and models, and the PDR are presented in Figures 23 and 24, respectively. Power consumption of the edge servers seems to be reduced compared to the previous scenario because the model's training has been moved to the cloud, and the edge servers are used only for detection; see Figure 25 for the total average of power consumption for edge servers.