esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**W/B**} & \multirow{2}{*}{**T** (\({}^{\circ}\)C)} & \multicolumn{6}{c}{**\#days =**} \\ \cline{3-8}  & & **3** & **7** & **28** & **56** & **90** & **120** \\ \hline \multirow{8}{*}{0.4} & \multirow{2}{*}{25} & 34.5, 34.5, 35.1 & 40.3, 40.5, 40.7 & 51.6, 51.5, 51.7 & 60.4, 60.5, 60 & 62.8, 62.8, 63.4 & 64.7, 64.9, 65.1 \\ \cline{2-8}  & & 0.35 & 0.20 & 0.10 & 0.26 & 0.35 & 0.20 \\ \cline{2-8}  & \multirow{2}{*}{50} & 36.7, 36.6, 37.1 & 46.7, 46.6, 47.1 & 55.2, 55.6, 55.1 & 63.7, 63.7, 64.3 & 66, 65.9, 66.7 & 69.3, 69, 68.7 \\ \cline{2-8}  & & 0.26 & 0.26 & 0.26 & 0.35 & 0.44 & 0.30 \\ \cline{2-8}  & \multirow{2}{*}{75} & 38.4, 38.2, 38 & 49.1, 49.3, 49.5 & 56.1, 55.6, 56.3 & 64.5, 64.6, 64.7 & 67.2, 67.7, 67.9 & 69.6, 69.4, 69.8 \\ \cline{2-8}  & & 0.20 & 0.20 & 0.36 & 0.10 & 0.36 & 0.20 \\ \hline \multirow{8}{*}{0.5} & \multirow{2}{*}{25} & 32.4, 32.3, 32.5 & 38.4, 38.8, 38.6 & 41.6, 41.8, 41.1 & 49, 49.4, 49.5 & 57.5, 57.4, 56.7 & 63.9, 63.6, 64.2 \\ \cline{2-8}  & & 0.10 & 0.20 & 0.36 & 0.26 & 0.44 & 0.30 \\ \cline{2-8}  & \multirow{2}{*}{50} & 32.8, 32.4, 32.6 & 42.3, 42.1, 41.9 & 48, 48, 47.7 & 59.8, 59.9, 59.7 & 63.6, 64, 64.4 & 66.8, 66.9, 67 \\ \cline{2-8}  & & 0.20 & 0.20 & 0.17 & 0.10 & 0.40 & 0.10 \\ \cline{2-8}  & \multirow{2}{*}{75} & 33.7, 33.8, 34.2 & 43.8, 43.9, 43.7 & 50, 49.7, 49.7 & 58.8, 58.9, 59 & 65.3, 65.6, 65.6 & 68.5, 68.7, 68.3 \\ \cline{2-8}  & & 0.26 & 0.10 & 0.17 & 0.10 & 0.17 & 0.20 \\ \hline \multirow{8}{*}{0.6} & \multirow{2}{*}{25} & 26.5, 26.5, 25.9 & 28.3, 28.2, 27.8 & 37.7, 37.9, 38.4 & 44.3, 44.5, 44.1 & 48.3, 48.2, 48.4 & 50.1, 50.4, 50.4 \\ \cline{2-8}  & & 0.35 & 0.26 & 0.36 & 0.20 & 0.10 & 0.17 \\ \cline{2-8}  & \multirow{2}{*}{50} & 26.9, 26.8, 27 & 32.4, 33.4, 32.9 & 41.5, 41.2, 41.2 & 52.6, 52.6, 52.3 & 58.9, 58.7, 58.5 & 59.7, 59.4, 60 \\ \cline{2-8}  & & 0.10 & 0.50 & 0.17 & 0.17 & 0.20 & 0.30 \\ \cline{2-8}  & \multirow{2}{*}{75} & 28.8, 29, 28.9 & 34.1, 33.5, 34.4 & 43.2, 43, 43.1 & 54.4, 54.2, 54.4 & 61, 60.9, 60.5 & 62.5, 62.6, 62.4 \\ \cline{2-8}  & & 0.10 & 0.46 & 0.10 & 0.20 & 0.26 & 0.10 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Raw data and standard deviation of compressive strength with 10% BJPA substitution (unit: MPa).
## 5 Attacks and Countermeasures
### MANET Countermeasures  
In order to increase robustness and reliability of MANET routing algorithms, several countermeasures were proposed in the recent years. We present selected countermeasures for the MANET attacks introduced previously.
# A Survey of OCR in Arabic Language: Applications, Techniques, and Challenges
## 3 OCR Process
### Preprocessing
#### 3.1.4 Keystone Correction  
Keystone correction is used to correct slanted images. OCR algorithms work best when the text in the image is aligned with the x-axis. However, the text may be slanted due to how the original document was scanned or photographed. Keystone correction involves applying mathematical transformations to the image to correct for the slant of the text, which can be done using various algorithms, such as Hough transform or RANSAC. Distortion is aligned at the top/bottom using vertical keystone correction and left/right of the image with horizontal keystone correction. After capturing the image, there will be many technical challenges with the image that make it difficult to read the text. The morphological process and Bezier curve method resolve these challenges [64].
## 4 Discussion
These results reaffirm the suggestion made by [PERSON] et al. (2019) [19] that \"any changes in running velocity will not impact the resulting CoD angle calculation\", as long as the action does not last less than the time window marked by the sample rate frequency (100 Hz = 10 ms). In this way, and contrary to what happened with GPS technology [36; 37; 38], the precision of inertial sensors when recognizing the angulation of a CoD does not decrease as speed increases. The data recorded by the three IMMUs reflect a similar behavior of the algorithm when applied to different devices of the same brand. A robust binding attaching all the devices during the test [39], as well as correct calibration of the inertial sensors prior to the test, could influence the results. These findings do not agree with those found by [PERSON], 2014) [40], where by using Global Positioning Systems (GPS) technology, a high variability among devices when recording high-intensity accelerations and decelerations (>4 m/s\({}^{2}\)) during the same movement was found. In this way, inertial sensors together with specific filtering algorithms could be a useful alternative for the analysis of movements in sports. This work is not exempt from limitations that must be taken into account when interpreting the results. In relation to the sample size, although only five participants were used, the main objective of this study was based on the comparison between the inertial sensor data and a high-speed video criterion; therefore, the number of repetitions performed is of the most importance. It would be essential to advance the understanding of the algorithm by analyzing precision instead of a standardized test in a real sports task. In this way, it would be interesting to assess the method in a real-game context, where its natural elements make the player's movement faster and more unpredictable. In addition, the fact that the study obtained its results from a standardized test means that the data should be used with caution when extrapolating them to real activities, such as training or competition matches.
# Hybrid Precoding Design for Wireless Fading Channels
## 5 Conclusions  
This paper proposes a hybrid technique that simultaneously applies a linear orthogonal MMSE precoding scheme and a non-linear orthogonal SLP scheme to control the SER performance and computational complexity of the entire system. If the SLP technique is applied to all users, the computational complexity increases too much, and if linear precoding is applied to all users, the SER performance deteriorates. Therefore, to solve this problem, we proposed a hybrid precoding technique that divides users into two groups and applies linear OMMSE precoding to users in group 1 and the non-linear OSLP technique to users in group 2. Because the SER performance deteriorates significantly when the signals of users applying different types of precoding interfere with each other, the precoding matrix and vector are designed to prevent interference between the two groups by utilizing the channel information for the two groups. Through computer simulation, it was confirmed that the SER performance of the proposed method is superior to that of the linear MMSE precoding method, and the computational complexity performance of the proposed method is superior to that of the SLP-2 method. Additionally, the proposed technique suggests that the SER performance and computational complexity performance can be appropriately controlled by adjusting the number of users belonging to group 1.  
This paper assumed a perfect channel estimation scenario, hence presuming the absence of channel estimation errors. Research on designing precoding methods considering partial information about the channel or the presence of channel estimation errors could be a significant area of study. However, due to the scope limitations of this paper, such considerations are planned for future work.  
This work was supported by a research grant from Kongju National University in 2022.  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.
## 3 Results and Discussion
### Agricultural Waste Generated in the Post-Harvest Facilities of the NEA: The Status Quo.
Moreover, it was observed that the decomposition of agricultural waste, such as coffee  
Figure 2: (**a**) Farmers in a cocoa and coffee plantation in the Ecuadorian Amazon; (**b**) an operator of one center during the process of threshing dry coffee fruits; (**c**) coffee husks that were separated during the threshing process; (**d**) one of the studied centers used a concrete hopper to store their coffee husks; (**e**) the coffee husks from one of the studied centers were dumped directly into a nearby Creek. husks, attracts mosquitoes. Mosquitoes are disease vectors that can threaten the people who live near these processing centers [42]. The drying of red coffee fruits and cocoa beans is one of the main activities at these processing centers. During times of less rain, this is done by spreading them on drying yards or in greenhouse dryers, with the process being driven by solar energy and natural convection. Each of these four centers also has a fixed-bed mechanical dryer with forced convection and thermal energy input from the combustion of diesel, liquefied petroleum gas (LPG), or wood (Figure 3). According to the staff, these mechanical dryers are used on rainy days because the cloud cover and the high humidity, typical of the NEA, hinder the drying process in solar dryers. Delayed drying can lead to the formation of mold, which reduces the quality and market price of these products. According to workers of these centers, the use of logs or coffee husks as fuel to produce thermal energy for the mechanical dryers results in a significant amount of smoke, and the temperature inside the drying room is less than optimal. They point out that the drying temperatures can vary between 30 \({}^{\circ}\)C and 50 \({}^{\circ}\)C, depending on the initial moisture of the material and the stage of drying. Combustion of agricultural waste, such as coffee husks, with no pretreatment, such as drying or particle size homogenization (pelletization), releases harmful compounds, including dioxins, furans, and carbon monoxide [43], which are often associated with improper or incomplete combustion. The combustion of untreated coffee husks has also been linked to the buildup of slag on the combustion grate, corrosion, and fouling of the heat exchange devices [44]. Thus, these cooperatives prefer to use diesel and LPG, which they have access to under subsidized prices thanks to authorization from the Hydrocarbon Regulation and Control Agency (ARCH, Agencia de Regulacion y Control Hidrocarburifero) up to a limit of 1000 gallons per month (4546 L). Despite the subsidy, the presidents of these cooperatives stated that the fuel costs of mechanical dryers are too high.
# Reference Broadcast-Based Secure Time Synchronization for Industrial Wireless Sensor Networks
## 3 System Models and Problem Analysis
### Attack Model  
Unattended operation and wireless communication make IWSNs vulnerable to various attacks, e.g., replay attacks, delay attacks, dos attacks, modifying and dropping timestamps, masquerade attacks, message manipulation attacks, etc. Referring to the definition in [15; 16], the message manipulation attacker can pretend to be a safe node and broadcast unregulated incorrect time information, including repeatedly broadcasting the same timestamp, increasing transmission delay, and injecting error time. A masquerade attacker, also known as a Sybil attacker, illegitimately pretends to be another node and disrupts the time synchronization process. Hence, security attacks on time synchronization can be simply divided into message manipulation attacks and Sybil attacks.  
Figure 1: Schematic illustration of a layered IWSN. Node 0 is the reference node.  
Currently, there are various studies on the defense of message manipulation attacks. Although threshold detection is an effective security mechanism, it performs poorly under Sybil attacks. Accordingly, in this paper, we mainly focus on the Sybil attacks. For example, a Sybil attacker \(A\) can send out a disguised clock reading, i.e.,  
\[\tau_{A}^{i}(t)=\alpha_{A}t+\beta_{A}+\omega_{A}(t), \tag{3}\]  
where \(\omega_{A}(t)\) denotes the attack power and \(i\) is the disguised node identity (or suspicious node).  
It should be noted that IWSNs usually adopt medium access control or a digital signature to verify the message. Local nodes cannot arbitrarily modify the received message from other nodes [16]. This is an important assumption for our next design of the RSTS protocol.
## 4 Materials and Methods
### Data and Methodology
#### 4.2.5 Albedo Data  
Albedo is a measure of a surface's ability to reflect sunlight. Light-coloured surfaces (high albedo) return a notable amount of the sun's energy back into the atmosphere. Dim surfaces (low albedo) absorb large amounts of the sun's light. Surface albedo is a way to measure how much short-wave irradiance is reflected away from the Earth's surface. The albedo data used in the study were sourced from EUMETSAT's Satellite Application Facility on Climate Monitoring (CMSAF) [95] as pentads. The desert has a high albedo, but because of its relatively dry and cloud-free atmosphere, its hot surface emits a lot of infrared radiation into space.
###### Abstract  
The negative influence of water pollution by heavy metals ions on human health represents a serious ecological problem which requires effective methods in the search for its solution. The creation of eco-friendly biodegradable polymer materials capable of performing the sorption of the water media of heavy metals followed by decomposition into harmless substances after the end of their service life presents an actual task. To this aim, binary compositions synthesized from natural raw polyesters polylactide (PLA) and poly(3-hydroxybutyrate) (PHB) with polysaccharide chitosan, corresponding to these requirements, were obtained in the liquid phase. The polyesters have mechanical characteristics close to the characteristics of synthetic polymers, while the chitosan containing the amino groups is capable of performing the sorption of heavy metals. The use of compositions on their base allows one to create the new inexpensive biodegradable sorbents stable in aqueous media as well as apply them as packing materials. The sorption capacity of PLA-chitosan and PHB-chitosan compositions in relation to iron ions from aqueous solutions was explored by a method of X-ray fluorescence analysis and it was established that the sorption of Fe\({}^{3+}\) ions by PHB-chitosan composition is more than twice as high as that by the PLA-chitosan composition (2.30 and 0.66 wt. %, correspondingly, after sorption from 0.008 mol/L FeCl\({}_{3}\) solution during 24 h). A comparative study of thermophysical parameters and the degree of crystallinity of PLA and PHB, as well as in their initial compositions and compositions, containing sorbed iron ions, was carried out by DSC method. The DSC analysis of the PLA-chitosan and PHB-chitosan compositions, containing sorbed iron ions, showed a slight decrease in the values of Tg, T\({}_{\rm{cc}}\), and T\({}_{\rm{m}}\) as well as an increase in the enthalpy of cold crystallization and a reduction in the degree of crystallinity of these polyesters. At the same time, an increasing of the thermal stability of polyester compositions in the presence of iron ions was established. The influence of UV irradiation on the structure of PLA and PHB for 2, 5, 24, and 144 h was analyzed by FTIR spectroscopy and significant changes in the spectrum were observed. Based on the analysis of the IR spectra of PHB and PLA, it was concluded that, under the action of UV radiation, the destruction of ester bonds takes place, which is expressed in the appearance of intense bands characterizing the formation of new structural units, resulting in the decrease in the molecular weight of polyesters.  
polylactide; poly(3-hydroxybutyrate); chitosan; composite films; sorption of iron ions; thermal transitions; UV radiation +
Footnote †: journal: Applied Sciences
## 6 Discussion
### Discussion of Long-Term DTLB Development  
Several authors have described changes in vegetation composition and structure, changes in soil moisture, peat accumulation, permafrost aggradation and development of ponded low-centered polygons in DTLBs [10, 12, 19, 29, 32]. The results from our remote sensing study of DTLBs on the northern Seward Peninsula agree with the general findings from the previous studies on DTLBs on the Arctic Coastal Plain of Alaska [12, 19, 29, 32, 36]. There is a post-drainage pattern of vegetation succession and change in surface soil properties as DTLBs age. However, our observation is not consistent with the classical concept of a \"thaw lake cycle\" that assumes that a thermokarst lake goes through a complete cycle from lake to drained basin and back to a lake in a specific time period [8, 34]. For the northern Seward Peninsula, there is no absolute frequency for a thermokarst lake cycle [10]. In addition to time since drainage, other factors determine the successional stage of a basin and formation of a new lake, including climate variability, basin topography, hydrologic framework, geomorphology and history of lake and basin evolution. A recent study on thermokarst lake dynamics in the northern Seward Peninsula that used multi-temporal satellite and aerial images from 1950 to 2007 demonstrated that small new lakes may reform just decades after drainage of large shallow thermokarst lakes, while remnant lakes from partially drained lake basins often start expanding into neighboring DTLBs or uplands due to shore thermal erosion [27]. The study found that the increase in lake numbers between 1950 and 2007 can be attributed to the partial drainage of larger thermokarst lakes and the formation of multiple smaller remnant ponds and lakes. In our study, the appearance of ponding in some radiocarbon-dated basins and the absence of distinct signs of new lake formation in others suggest that the formation of a new lake in an old drained basin is closely tied to the amount of ice content, local topography, hydrological regime, the rate of vegetation succession and polygonal development [12].  
There is a complex relationship between vegetation, topography, hydrology, geomorphic and climatic variables that determines the rate of lake expansion, lake drainage [62, 63], as well as permafrost aggradation following lake drainage [33]. This consequently affects the thermokarst lake cycle frequency. [PERSON] and [PERSON] [21] proposed a new conceptual model for the evolution of thermokarst lakes and DTLBs, taking into account the influence of basin topography, soil stratigraphy and ground ice dynamics for the development of the thermokarst lake cycle. However, this model for the North Slope of Alaska does not reflect the strong lateral dynamics we observe on the Seward Peninsula with multiple, mostly partially overlapping lake and basin generations. Future research should be directed towards improving knowledge on factors influencing lake drainage and post-drainage successional patterns of DTLBs and how they interact.
# Stochastic Extensions of the Elo Rating System
## 2 Preliminaries
### The Elo Rating System  
Elo's rating system assumes that in a game between two players \(A\) and \(B\), the result can be expressed by giving points \(p_{A},p_{B}\in[0,1]\) to \(A\) and \(B\), respectively, so that \(p_{B}+p_{A}=1\). The simplest case is a game with two results, in which \(p_{A}\) is one if \(A\) wins and zero if \(B\) wins, but in chess, a draw is represented by \(p_{A}=p_{B}=\frac{1}{2}\), since in traditional chess tournaments, the player with the higher number of wins plus half the number of draws wins. Then, if \(A\) and \(B\) have Elo ratings \(r_{A}\) and \(r_{B}\), respectively, the updated ratings after the game are given by  
\[r_{A}^{\prime}:=r_{A}+K(p_{A}-\mathbb{E}[p_{A}|r_{A},r_{B}])\qquad\text{ and}\qquad r_{B}^{\prime}:=r_{B}+K(p_{B}-\mathbb{E}[p_{B}|r_{B},r_{A}]) \tag{1}\]  
where \(\mathbb{E}[p_{A}|r_{A},r_{B}]\) is the expected score of player \(A\) in a game against \(B\), given by  
\[\mathbb{E}[p_{A}|r_{A},r_{B}]=F_{X}(r_{A}-r_{B}) \tag{2}\]  
Here, \(K\) is a positive constant, and \(F_{X}\) is the distribution function of some random variable \(X\) with mean zero, as depicted in Figure 1. The distribution function of \(X\) must also be symmetrical around zero so that \(\mathbb{E}[p_{A}|r_{A},r_{B}]+\mathbb{E}[p_{B}|r_{A},r_{B}]=1\). \(X\) was originally a normal variable, but it was later changed to follow a logistic distribution in the FIDE's ratings. This has been argued to produce better predictions [1] (Chapter 8.41), and it also leads to an explicit and more meaningful expression for \(\mathbb{E}[p_{A}]\). In fact, sometimes, the update rule is given simply as  
\[r_{A}^{\prime}:=r_{A}+K\bigg{(}p_{A}-\frac{1}{1+\exp(c(r_{A}-r_{B}))}\bigg{)} =r_{A}+K\bigg{(}p_{A}-\frac{a^{r_{B}}}{a^{r_{B}}+a^{r_{A}}}\bigg{)} \tag{3}\]  
for some \(c=\log(a)\in\mathbb{R}^{+}\).  
It is also possible to update the ratings with the results of a set of matches (for instance the results of a tournament). Given a sample \(M=\{m_{k}=(a_{k},b_{k},p_{k}^{a},p_{k}^{b})\}\) of matches with \(n\) intervening players \(i=1,\ldots,n\), where the \(k\)th match is between players \(a_{k}\) and \(b_{k}\) and ends with scores \(p_{k}^{a}\) for \(a_{k}\) and \(p_{k}^{b}=1-p_{k}^{a}\) for \(b_{k}\), and given initial ratings \(R:=(r_{1},r_{2},\ldots,r_{n})\), we similarly compute:  
\[r_{i}^{\prime}:=r_{i}+K\cdot\sum_{k|a_{k}=i}\left(p_{k}^{a}-\mathbb{E}[p_{k}^{ a}|R]\right)+K\cdot\sum_{k|b_{k}=i}\left(p_{k}^{b}-\mathbb{E}[p_{k}^{b}|R]\right) \tag{4}\]  
Obviously, if a player outperforms their expected score, their rating increases, and otherwise it decreases, but the total sum of ratings does not change, as we will see later. However, before discussing the update rule, we need to review the model where the expected score originally comes from, which we refer to as the static Elo model.
## QoS-Aware Error Recovery in Wireless Body Sensor Networks Using Adaptive Network Coding  
**[PERSON] 1,*, [PERSON] 2, [PERSON] 2 and [PERSON] 3**  
1 School of Computer Science and Statistics, Trinity College, Dublin 2, Ireland  
2 Faculty of Computing, Universiti Teknologi Malaysia, Skudai, 81310 Johor Bahru, Malaysia;  
E-Mails: [EMAIL_ADDRESS] (S.S.J.); [EMAIL_ADDRESS] (Y.C.)  
3 Faculty of Bioscience and Biomedical Engineering, Universiti Teknologi Malaysia, Skudai,  
81310 Johor Bahru, Malaysia; E-Mail: [EMAIL_ADDRESS]  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS];  
Tel.: +353-894003955.  
Academic Editor: [PERSON]  
_Received: 12 July 2014 / Accepted: 3 December 2014 / Published: 29 December 2014_  
**Abstract:** Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.  
keywords: wireless body sensor networks; QoS; network coding; adaptability; reliability; energy efficiency