esa-sceva/satcom-chunk-collection huggingface dataset:
# Firmware Updates over the Air via LoRa: Unicast and Broadcast Combination for Boosting Update Speed
## 3 Proposed Update Methods  
A firmware update is a critical procedure which must be performed carefully. For that reason, after sending the binary file, a checksum must also be sent. Only if the checksum is correct will the new firmware be flashed. Three different methods are defined, which only differ in the firmware exchange stage.  
The _only unicast_ method is the most straightforward one: it always sends unicast frames, which need an ACK. It employs a \"stop and wait\" policy, so it only moves to the next chunk when the gateway is sure that the previous one has been received, and it only moves to the next node when the gateway is sure that all the chunks have been correctly received by the previous one. It simplifies the control and the processing burden of the node, with the counterpart of bad scalability: the update time will grow linearly with the number of nodes.  
The _broadcast + unicast_ method just adds an initial broadcast round (or a number of them) and then runs the _only unicast_ method, but only with the missing chunks. It is expected to provide a significant scalability improvement, especially in scenarios with a low frame loss probability. However, if the loss probability is high, the initial broadcast round(s) may not be as effective and the update times will be similar to those of the _only unicast_ method. As a counterpart, more intricate control will be necessary: as there are no ACKs in broadcast transmissions, the node will have to transmit to the gateway the frames it is missing. As we will see, a bitmap will be employed for that aim.  
Finally, the _only broadcast_ method is a variation of the previous one, with the objective of increasing the scalability even more: by sending the missing chunks in broadcast frames, it can be expected that other nodes will also benefit from these transmissions to store some of the pending chunks.  
In the next subsections, each method will be explained in detail.
## 2 Methodology
### Application of Optimization Procedures  
In order to apply the optimization procedures, it was first necessary to retrieve the data through a selection and extraction process. This selection and extraction process was implemented and tested for the data of both case studies. This step allows the user (statistician) to understand the available data series, their origins, and field observation contexts, such as precipitation classes and other types of observations which may also explain outliers (Figure 7).
# Numerical Voids Detection in Bonded Metal/Composite Assemblies Using Acousto-Ultrasonic Method
## 2 Materials and Experimental Setup
### Samples  
The investigated geometry, which consisted of a steel substrate and a composite plate bonded together by an epoxy adhesive layer, is shown in Figure 1. The composite (T800 S carbon fibers and epoxy matrix) and adhesive layer dimensions were 300 mm \(\times\) 50 mm with thicknesses of 1.4 mm and 1 mm, respectively. The steel substrate (dimensions 320 mm \(\times\) 100 mm) was 5 mm thick. A two-component cold-curing epoxy resin (Sikadur 30) was employed as the adhesive. The properties of the materials are summarized in Table 1. Figure 1 also indicates the location of the voids. The reference sample, with no voids in the adhesive layer, was denoted the \(\alpha\)-type sample. For the \(\beta\) samples, a void was present in the middle of the adhesive bond line. The void defects had two different sizes. A \(\beta\)1-type defect was simulated with a lack of adhesive on a central area of dimensions 50 \(\times\) 25 mm\({}^{2}\), and a \(\beta\)2-type defect corresponded to a lack of adhesive on 1/3 of the bonded surface at the center of the joint (100 \(\times\) 50 mm\({}^{2}\)). The assemblies were instrumented with 3 sensors located on the composite plate.
## 3 Results of the Field Experiment
### Static Behavior
Additionally, the theoretical pinhole sag (\(\text{Sag}=dn^{2}/8\)) of 28.48 mm for self-weight, where \(d\) was 3.56 (constant), and \(n\) number of bays. From the experimental results, the maximum deflection obtained was 14.42 mm from the transducer's influence line that is below the prescribed limit. Figure 8 illustrates the load-strain and stress-strain relationship. Bailey Bridges experience significant stress at mid-span than end-shear during loading [14]. This aspect is of great importance in designing truss structures ensuring reinforcement of the critical elements at mid-span that are fully stressed. The strains were established during loading cases 1-3. Figure 8a,b indicates the effects of strain with loading. The strains increased with the loading with no anomaly to indicate underlying local issues such as fatigue. The strains had similar characteristics apart from differences due to the strain gauge placement distances, which were not precisely co-linear (Us1 & Ds1) and alternate (Us2 & Ds2). However, a symmetric relationship varies from the center, as shown in Figure 8a,b. The situation is critical for fixed-panel bridges indicating that the end posts/shears are not fully utilized. Consequently, reinforcing the center bays ensures uniform distribution of stresses. The panel stress was calculated using averaged values of Us1 and Ds1 with a modulus of elasticity of 2.0 \(\times\) 10\({}^{5}\) MPa for a steel superstructure with a concrete deck to establish the linearity. Figure 8c shows the stress-strain relationship. It was clear that the bridge operated within the linear elastic range. Moreover, the stresses experienced in Loading case 3 correspond to a similar study on the same bridge [29].
# Line Clipping in 3D: Overview, Techniques and Algorithms
## 3 Line-Clipping Algorithms in Three-Dimensions
### Three-Dimensional Liang-Barsky Line Clipping  
The Liang-Barsky algorithm is a line-clipping algorithm and is considered more efficient than Cohen-Sutherland [5]. It is considered to be a fast parametric line-clipping algorithm and can be applied to two dimensions as well as to three dimensions. The following concepts are used when three-dimensional clipping is applied:  
1. The parametric equation of the line.  
2. The inequalities describing each side (boundaries) of the clipping region, which are used to determine the intersections between the line and each side.  
The parametric equation of a line can be given by the following equations:  
\[x =x_{0}+(x_{1}-x_{0})\cdot t\] \[y =y_{0}+(y_{1}-y_{0})\cdot t\]  
Figure 11: Three-dimensional six-bit region codes.  
Figure 10: Cohen–Sutherland 3D six-bit representation.  
\[z=z_{0}+(z_{1}-z_{0})\cdot t\]  
where \(t\) is between 0 and 1. The point-clipping conditions in the parametric form are then written as  
\[x_{min}\leq x_{0}+(x_{1}-x_{0})\cdot t\leq x_{max}\] \[y_{min}\leq y=y_{0}+(y_{1}-y_{0})\cdot t\leq y_{max}\] \[z_{min}\leq z=z_{0}+(z_{1}-z_{0})\cdot t\leq z_{max}\]  
and the above six inequalities can be expressed as  
\[p_{k}\cdot\ t\leq q_{k},\]  
where \(k=1,2,3,4,5,6\) correspond to the left (\(x_{min}\)), right (\(x_{max}\)), bottom (\(y_{min}\)), top (\(y_{max}\)), far (\(z_{min}\)), and near (\(z_{max}\)) boundaries, respectively. The \(p\) and \(q\) are defined as follows:  
\[p_{1} =-(x_{1}-x_{0}), q_{1} =(x_{0}-x_{min}) \text{(left boundary)};\] \[p_{2} =(x_{1}-x_{0}), q_{2} =(x_{max}-x_{0}) \text{(right boundary)};\] \[p_{3} =-(y_{1}-y_{0}), q_{3} =(y_{0}-y_{min}) \text{(bottom boundary)};\] \[p_{4} =(y_{1}-y_{0}), q_{4} =(y_{max}-y_{0}) \text{(top boundary)};\] \[p_{5} =-(z_{1}-z_{0}), q_{5} =(z_{0}-z_{min}) \text{(far boundary)};\] \[p_{6} =(z_{1}-z_{0}), q_{6} =(z_{max}-z_{0}) \text{(near boundary)}.\]  
Using the following conditions, the position of the line can be determined as follows.  
* When the line is parallel to a clipping boundary, the \(p\) value for that boundary is zero.
* When \(p_{k}<0\), as \(t\) increases the line goes from the outside to the inside (entering).
* When \(p_{k}>0\), the line goes from the inside to the outside (exiting).
* When \(p_{k}=0\) and \(q_{k}<0\), the line is trivially invisible because it is outside the clipping region.
* When \(p_{k}=0\) and \(q_{k}>0\), the line is inside the corresponding clipping region.  
Parameters \(t_{1}\) and \(t_{2}\) can be calculated to define the part of the line that lies within the clipping region. The following points hold:  
* When \(p_{k}<0\), \(maximum(0,q_{k}/p_{k})\) is taken.
* When \(p_{k}>0\), \(minimum(1,q_{k}/p_{k})\) is taken.  
If \(t_{1}>t_{2}\), the line is completely outside the clipping region and it can be rejected. Otherwise, the endpoints of the clipped line are calculated from the two values of parameter \(t\).
## 3 Materials and Methods  
### Gpm Imerg  
The GPM-CO was launched on 14 February 2014 by the United States National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA). The mission was anticipated to succeed and improve the TRMM, which had ended its 17 years of service on 8 April 2015. The GPM-CO covers a wider region (68\({}^{\circ}\)N-68\({}^{\circ}\)S) compared to the TRMM (37\({}^{\circ}\)N-37\({}^{\circ}\)S) [4]. In addition, the sensors of GPM (DPR and GMI) are superior to TRMM. For example, the GMI has 13 channels of frequency ranges, while the TRMM Microwave Imager was only equipped with 9 channels.  
The physical retrieval of precipitation rates is made by the DPR data, then a complete suite of algorithms provides other products with increased coverage by using GMI and other microwave radiometers on board other constellation satellites. IMERG also makes use of Infrared (IR) data, and rain gauges. There are three main GPM SPPs: (1) IMERG Early Run (IMERG_E)--near real-time with latency of 6 h; (2) IMERG Late Run (IMERG_L)--reprocessed near real-time with latency of 18 h; and (3) IMERG Final Run (IMERG_F)--gauged-adjusted with latency of four months. The temporal scales of these products are divided into 30 min, daily, and monthly. According to [PERSON] et al. [17], the IMERG_F is more accurate compared to other IMERG products as it is bias corrected using the Global Precipitation Climatology Centre (GPCC) precipitation gauges. In this study, the IMERG_E, IMERG_L and IMERG_F daily version 5 products that are available from 12 March 2014 were evaluated. These products are freely available on the Precipitation Measurement Missions website [18].  
Figure 1: Maps of (**a**) Peninsula Malaysia and (**b**) Kelantan River Basin.  
We only considered daily precipitation assessments due to a lack of 30 min observed precipitation and streamflow data.
## 2 Related Work
### Multipath Routing  
Multipath routing uses multiple paths to transmit data, which can achieve both load balancing and fault tolerance. There are two different multipath routings between the source node and the sink node. One is disjoint multipath routing [14], where the alternative paths do not intersect with each other. The other is braided multipath routing, where there are typically no completely disjoint paths [15-16].  
In [14], [PERSON] _et al._ presented a disjoint multipath routing based on local information, which is a distributed algorithm and can achieve load balancing. This algorithm uses a primary route to transmit data. Only when the primary route fails, the alternative route can be used. However, this algorithm is not attractive for the network lifetime.  
In [15], a meshed multipath routing with efficient strategy has been described. Such an algorithm can achieve a better throughput than the traditional multipath algorithms. However, this approach requires nodes to be equipped with GPS (Global Positioning System), which increases the cost of the node.  
In [16], [PERSON] _et al._ introduced a multipath routing algorithm based on Ant Colony Optimization (ACO), which uses a class of agent-like ants to develop multiple reliable routes between the source and sink. It is very effective in dealing with the failure of links and searching for the routes. Due to thelarge number of nodes, the number of ants is quite large so that it may lead to much higher traffic in the network than other algorithms.
## 3 Results and Discussion
### Flexural Toughness  
Figure 7 shows the flexural toughness of 28-day old base concrete with hybrid fibers. When the fiber content was 0.54%, the increase in the volume proportion of polyolefin fiber clearly decreased the flexural toughness of the base concrete. With 0% polyolefin fiber, the flexural toughness was 99.16 kN\(\cdot\)mm, and decreased to 85.34 kN\(\cdot\)mm, 78.49 kN\(\cdot\)mm, 80.05 kN\(\cdot\)mm, 70.58 kN\(\cdot\)mm, as the volume proportion of polyolefin fiber increased to 25%, 50%, 75%, and 100%, respectively. This means that, as in the case of flexural strength at a fiber content of 0.54 vol%, the amount of steel fiber has a more significant influence on the flexural behavior of the base concrete.  
As fiber content increased from 0.54% to 1.08%, the flexural toughness of the base concrete increased. Similar to the case of flexural strength, a synergetic effect was observed by hybridization of the steel and polyolefin fibers. The synergetic effect seems to be associated with the increase in the amount of polyolefin fiber because the flexural toughness of the base concrete with 100% polyolefin fiber (137.94 kN\(\cdot\)mm) was higher than that with 100% steel fiber (123.53 kN\(\cdot\)mm). Due to the higher contribution of polyolefin fiber to flexural toughness, the flexural toughness of the concrete increased to 123.53 kN\(\cdot\)mm, 170.18 kN\(\cdot\)mm, and 179.11 kN\(\cdot\)mm, as the volume proportion of polyolefin fiber increased from 0%, 25%, to 50%, respectively. At 75% and 100% with polyolefin fiber, flexural toughness was reduced to 138.15 kN\(\cdot\)mm and 137.94 kN\(\cdot\)mm, but these values were still higher than that with 100% steel fiber.  
Considering these findings, the synergetic effect starts to occur after the necessary amount of fiber is incorporated into the base concrete. The synergetic effect was maximized at 50% steel fiber and 50% polyolefin fiber hybridization. It should be noted that the aspect ratio of the fiber is a very important factor, so that the fiber content and hybrid proportion where the synergetic effect occurs may change as fibers with different aspect ratios are used.
# Automatic Text Summarization for Hindi Using Real Coded Genetic Algorithm
## 4 Experimental Setup
### Results and Discussion
#### 4.3.2 Summary of Compression Rates
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Feature Set** & **Features** & **Precision** & **Recall** & **F-Measure** \\ \hline Set1 & \(F_{sp}\) & 0.54 & 0.51 & 0.52 \\ Set2 & \(F_{sp}\), \(F_{nd}\) & 0.64 & 0.53 & 0.58 \\ Set3 & \(F_{sp}\), \(F_{nd}\), \(F_{ls}\) & 0.57 & 0.54 & 0.55 \\ Set4 & \(F_{sp}\), \(F_{hd}\), \(F_{hw}\) & 0.62 & 0.59 & 0.60 \\ Set5 & \(F_{sp}\), \(F_{h2w}\), \(F_{ss}\) & 0.66 & 0.63 & 0.64 \\ Set6 & \(F_{sp}\), \(F_{hid}\), \(F_{ls}\), \(F_{hw}\) & 0.63 & 0.66 & 0.64 \\ Set7 & \(F_{ss}\), \(F_{ne}\) & 0.71 & 0.65 & 0.68 \\ Set8 & \(F_{nd}\), \(F_{lb}\), \(F_{ks}\), \(F_{ne}\) & 0.72 & 0.73 & 0.72 \\ Set9 & \(F_{sp}\), \(F_{ls}\), \(F_{kup}\)Observation of Tables 7-9, with an F-measure around 0.8, suggests that some elements are missing to better explain the pattern. These values match or exceed other published work for Hindi, detailed in Table 1, but nevertheless suggest that there is room for improvement. Although the present study compiles the most commonly used features in ATS, other features, which are not usually considered, could improve the quality of the summaries, such as semantic relations between terms, polysemy, coherence between sentences, or readability of the resulting summary. In the case of Hindi, most of the studies do not provide information on the relative importance of each of the features. It is interesting to note that the least influential variable in the models is sentence length. This factor is highly correlated with readability, but has little impact on the accuracy of the summary [72]. Some works have suggested that the readability has a greater impact on the accuracy of the summaries [73]. The presence of numerical values, which the readability guidelines suggest replacing with textual quantifiers (e.g., greater than, similar, etc. ), is also related to the readability recommendations. On the other hand, features that are traditionally more related to information retrieval because of their discriminatory value in relation to other documents have a higher weight, such as named entities, the presence of keywords, the frequency of terms, or the inverse frequency in the sentence. The number of English words in Hindi texts also has a clear discriminatory value, as the use of a foreign term is often due to the absence of the term or its synonyms in Hindi. As can be seen in Tables 7-9, the higher the compression ratio, the lower the F-measure. Another observation that seems obvious but needs clarification is that the more features the better the F-measure, even though there are sets, such as 7 that use only two features. This corroborates that even in elements that seem to be of lesser importance, such as sentence length, they also explain a part of the model not covered by other variables.
# Geometrical Calibration of a 2.5D Periapical Radiography System
## 1 Introduction
Therefore, such previous methods [18; 19; 20; 21; 22; 23] are unsuitable for the geometric calibration of the proposed system. This study proposes an approach for the geometrical calibration of hardware component positioning that is suitable for digital tomosynthesis using small-area sensors with an extremely short distance between the sensor and object. The calibration approach involves using a two-steel-ball phantom with precise known sizes and placing the phantom in front of the sensor. The two steps of the calibration process are conducted separately to calculate the error values of the X-ray tube at the x, y, and z axes. The linking lines of the X-ray tube and rotation axis can intersect orthogonally at the center of the sensor.
# A Novel Traffic Analysis Zone Division Methodology Based on Individual Travel Data
## 3 Traffic Subdivision Methods
### Preliminary Screening Conditions of Polymerization Unit  
In order to ensure that the shape of the formed traffic zone remains regular, that the travel in the traffic zone is similar, and that the computational performance of the aggregation model is improved, the grid is preliminarily screened. The screening conditions are as follows:  
(1) Distance constraint: The distance between the cell centroid found using the above aggregation rules and the local highest-peak cell centroid cannot exceed 1000 m, which ensures the regularity of the traffic zone and avoids the formation of a concave or narrow traffic zone. It is convenient to simplify the centroid position of the traffic zone in specific practical projects.  
(2) Time distribution similarity constraint: Based on the time distribution similarity coefficient between adjacent grids, the similarity coefficient between the grid found using the aggregation rule and the aggregated adjacent grid cannot be less than 0.4, which ensures the similarity of travel within the same traffic community.
# Distributed Extended Kalman Filtering Based Techniques for 3-D UAV Jamming Localization
## 1 Introduction
In [23], the adaptive RSSI filtering technique is employed to improve the measured RSSI signal degraded due to multipath effects with the aim to enhance the localization accuracy and to reduce the computational complexity of the tracking system. The RSSI based approaches that Kalman filtering to estimate the target position are presented in [24; 25]. They considered that, during jamming attacks, both the Signal to Noise Ratio (SNR) and PDR decrease as the amount of noise increases. Therefore, any node that has a lower PDR than expected is considered as a near jammer node and the gradient descent technique is employed in order to track the jamming source [22]. Wide-band jammer localization method introduced in [26], where a combination of Difference of Arrivals (DOA), Time Difference of Arrivals (TDOA), and EKF used. More explicitly, the DOA was utilized in order to provide the EKF with an accurate initial position, while the TDOA helped the EKF for fast converge. The efficiency of this method depends on the number nodes used for localization and tracking processes [26]. In summary, the aforementioned existing solutions have one of several drawbacks, such as (i) higher computationally complex due to heavy computational requirements for DOA/TDOA estimation [26], (ii) sensitive to node locations and the number of nodes deployed [18; 19], (iii) require a large computations for centralized processing and dependency on large number of boundary nodes [20], and (iv) highly sensitive to noise power (or SNR) [22]. Against these techniques, we proposed two novels distributed Extended Kalman Filter (EKF) based schemes:  
* Distributed EKF (DEKF) scheme while using information of the received power from the jammer at a single boundary node only. Distance Ratio aided Distributed EKF (DEKF-DR) based scheme utilizing an edge node in addition to a single boundary node. In general, these two methods require less computation due to distributed processing. Among these methods, DEKF-DR is the most promising, as it only uses a single node and its one neighbor to estimate received powers while offering the best accuracy when compared to the DEKF and the EKF-Centr (which is also modified for the 3-D scenario) techniques. The paper is organized, as follows: following the introduction, the system model is presented in Section 2. Section 3 introduces the concept of Distance Ratio. In Section 4, an overview of the standard Extended Kalman Filter is provided and the proposed distributed Extended Kalman Filter for 3-D Jammer's Localization are developed. Section 5 provides extension of the existing centralized EKF-aided jammers Localization scheme to 3-D scenario. The results and discussion are provided in Section 6. Finally, concluding remarks are given in Section 7.