esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Literature Review
### Wakeup Schedule  
This study considered a time-slotted WSN in which each node is energy-constrained. Neighbor discovery among nodes allows two nodes with independent duty cycles and no prior synchronization information to discover each other periodically when the nodes are within their radio range. A rendezvous allows nodes to deliver messages to previously discovered neighbors with predictable latencies. Nodes follow a neighbor discovery wakeup schedule that defines the time pattern required to wake up or sleep, so that nodes in the network can discover their respective neighbors in an energy-efficient manner. Neighboring nodes share common neighbors by using many techniques [13,14]. If nodes broadcast their two-hop neighbor tables in active slots, a node can indirectly discover its new neighbors through a direct rendezvous with assistance from the already discovered neighbor. Figure 1a shows the example of rendezvous maintenance. Node S can contact node B via neighbor node A.  
Node S can rendezvous indirectly with another node B by directly rendezvousing with an intermediate node A. In other words, nodes A and B have already been rendezvoused. This is achieved by node A, which passes the neighbor table of node B to node S. In addition, based on the state-of-the-art discovery protocol DISCO [9], two nodes, A and B, start counting the passage of these periods, which are divided into fixed-width reference periods and consecutive periods labeled with consecutive integers. Figure 1b shows the neighbor discovery and rendezvous maintenance among nodes S, A, and B. Figure 2 shows three nodes S, A, and B. According to the DISCO protocol, node S directly rendezvouses with its already discovered neighbors A and B in global time slots 4 and 8. In addition, node S can continue to indirectly discover the neighbor in global time slots 0, 1, 4, and 8. Before time slot 9, node S lacks the opportunity to connect directly with node B. However, in global time 0, nodes S and A can rendezvous their neighbor table. Node A's table containing the neighbors of S propagates to B. Therefore, even if node S cannot directly rendezvous with node B before global time 9, node S can rendezvous with B by using a transiting relationship that is the rendezvous between nodes A and B and between S and A in global time 3 and 5, respectively. These transiting relationships, which are denoted by red arrow lines in Figure 2, indicate  
Figure 1: (**a**) Example of rendezvous maintenance; (**b**) example of neighbor discovery and rendezvous maintenance.  
the indirect connection for the resource saving reasons. Considering neighbor discovery and rendezvous maintenance in our system design, it is possible to eliminate the need for fully meshed pairwise discovery and rendezvous.
## 3 Application and Comparison of Various Classification Methods  
The proposed novel detection model is a tool for the effective detection of cyber-attacks on WDSs. To develop detection approaches, this study applied a set of well-known and commonly used machine learning approaches. The applied cyber-attacks scenarios are expected to lead to anomalous hydraulic results in various WDSs components (e.g., the nodal pressure, tank level, and pipe flow), and to a corresponding significant system error. Therefore, each machine learning approach was trained using historical SCADA data representing normal operating conditions. Then, these approaches were simulated with new SCADA data, and the reconstruction error produced at each time step was monitored. The monitoring data of the WDSs is classified as under attack if the average reconstruction error across all system variables is larger than a user-defined threshold (this study used 0.95 [30]) and is classified as safe otherwise. The prediction performance of each algorithm is evaluated using the performance indices that have various characteristics and the most suitable algorithm for the detection model was identified by comparing the performances of the top four standard algorithms (i.e., KNN algorithm, SVM, ANNs, and ELM). Then, the classification results of the model using improved versions of the best algorithm were compared and analyzed in detail.
# Correct Pronunciation Detection of the Arabic Alphabet Using Deep Learning
## 4 Results and Discussion
### Arabic Alphabet Classification
#### 4.3.1 Without Data Augmentation  
In this section, we are going to discuss the DCNN, AlexNet, and BLSTM network trained over the dataset without data augmentation in detail.  
DCNN: The DCNN without data augmentation has an accuracy of 65.89%. The alphabet 'jeem','saud', and 'wao' have 100% accuracy, whereas 10 alphabets have accuracy above 70% and the other 10 alphabets have accuracy above 50% and the remaining alphabet have very low accuracy rate. The alphabet'sa' is confused with 'hha','saud', 'fa', and 'ya', due to which these samples are misclassified.  
Pre-trained AlexNet: The AlexNet network performed better than DCNN without data augmentation. The alphabet such as 'alif', 'jeem', 'dal', 'za','seen','sheem', 'duad', 'zua', 'aain', 'laam','meem', 'noon', 'wao', 'ya', and 'hamzah' have 100% accuracy. The 4 alphabets have accuracy above 80%, and the alphabet 'hha', 'tua', and 'ha' have accuracy less than 40%. The network is confusing 5 samples of 'ha' with'sa' because the network is unable to classify these alphabets due to few data elements.  
BLSTM: By using the BLSTM network, we have achieved an accuracy of 53.18% which is comparatively less than the other networks (DCNN and AlexNet). 'Alif' has 100% accuracy whereas only 2 alphabets have 80% accuracy and the other 10 alphabets have an accuracy between 70% and 60%. The remaining alphabet, i.e.,'sa' and 'fa', have the lowest accuracy of 16.7% because the network is confusing'sa' with 'fa', 'ta', and 'ha'. The network is also confusing 'fa' with'sa', 'za', and 'ha'.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{**Models**} & \multicolumn{2}{c}{**Without Data Augmentation**} & \multicolumn{2}{c}{**With Data Augmentation**} \\ \cline{2-7}  & **Random Split** & **Hold-Out** & **5-Fold CV** & **Random Split** & **Hold-Out** & **5-Fold CV** \\ \hline DCNN & 65.89\% & 64.56\% & 64.03\% & 95.95\% & 93.32\% & 93.46\% \\ Alex Net(TL) & 78.03\% & 78.73\% & 79.15\% & 98.41\% & 96.72\% & 96.36\% \\ BLSTM & 53.18\% & 52.62\% & 53.17\% & 87.90\% & 88.38\% & 87.95\% \\ \hline \hline \end{tabular}
\end{table}
Table 4: Alphabet classification with and without data augmentation.  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Models** & **Mean** & **SD** & **Margin of Error** \\ \hline DCNN & 94.63\% & \(\pm\)1.17 & \(\pm\)0.41 \\ Alex Net(TL) & 96.03\% & \(\pm\)1.599 & \(\pm\)0.57 \\ BLSTM & 87.025\% & \(\pm\)1.95 & \(\pm\)0.69 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Alphabet classification values of mean, standard deviation, and error.
# Secure PD-NOMA with Multi-User Cooperation and User Clustering in Both Uplink and Downlink PD-NOMA
## 2 System Model for Multi-User Downlink and Uplink PD-NOMA  
In this section, we explain the basic ideas behind downlink and uplink NOMA for multiple users in a cluster with different channel gains. Multiple signals are superposed using the different power levels at the transmitter, and the superposed signals are decoded using an SIC mechanism at the receivers.
###### Abstract  
This paper introduces the structure of a \(Q\)-ary pulse position modulation (PPM) signal and presents a noncoherent suboptimal receiver and a noncoherent optimal receiver. Aiming at addressing the lack of an accurate theoretical formula of the bit error rate (BER) of a \(Q\)-ary PPM receiver in the additive white Gaussian noise (AWGN) channel in the existing literature, the theoretical formulas of the BER of a noncoherent suboptimal receiver and noncoherent optimal receiver are derived, respectively. The simulation results verify the correctness of the theoretical formulas. The theoretical formulas can be applied to a \(Q\)-ary PPM system including binary PPM. In addition, the analysis shows that the larger the \(Q\), the better the error performance of the receiver and that the error performance of the optimal receiver is about 2 dB better than that of the suboptimal receiver. The relationship between the threshold coefficient of the suboptimal receiver and the error performance is also given.  
Q-ary; pulse position modulation; AWGN channel; non-coherent; bit error rate +
Footnote †: journal: Sensors
## 4 Results and Discussions
### Spatial and Temporal Changes in Water Conservation Function at Different Spatial Scales
#### 4.2.1 Average Water Conservation Depth of Different Cities and States  
From 2000 to 2018, seven cities and prefectures demonstrated an average water conservation depth exceeding the regional average, as depicted in Figure 3a. The ranking from highest to lowest water conservation depth is as follows: Xishuangbanna (115.50 mm) > Dehong (103.32 mm) > Wenshan (90.95 mm) > Pu'er (89.69 mm) > Lincang (78.48 mm) > Baoshan (79.45 mm) > Nujiang (73.09 mm). Conversely, the remaining nine cities and prefectures exhibited water conservation depth below the regional average, with Honghe (63.71 mm) > Yuxi (56.66 mm) > Zhaotong (52.32 mm) > Kunming (48.79 mm) > Qujing (48.16 mm) > Dali (45.37 mm) > Diqing (43.53 mm) > Lijiang (41.02 mm) > Chuxiong (35.65 mm). As shown in Figure 3b, the water conservation services in all cities and prefectures exhibited a similar trend in response to precipitation and actual evapotranspiration, reflecting the characteristics of a monsoon climate with concurrent rainy and warm seasons in the region. Regional statistics did not reveal a conspicuous change trend in low-value areas and population density. However, high-value areas and population density displayed an opposite change pattern. Concerning inter-annual variations, Xishuangbanna, Yuxi, Chuxiong, Wenshan, Kunming, Qujing, Honghe, Pu'er, Zhaotong, and Lincang consistently followed the regional change trend.  
Figure 2: Spatial change in water conservation function in Yunnan Province from 2000 to 2018.  
otranspiration, as illustrated in Figure 4b. Conversely, at altitudes ranging from 1500 m to 2000 m and 2000 m to 2500 m, a substantial decline in water conservation depth was observed, indicating a contrary pattern to population density., This suggests that human activities at these elevations had a notable impact on water conservation, whereas the influence of population density at other altitudes was less pronounced.  
In terms of interannual fluctuations, the analysis revealed the following trends: at elevations of 3000 m to 3500 m, 3500 m to 4000 m, 4000 m to 4500 m, and above 4500 m, the water conservation depth was higher in 2000 than in 2010 and 2018. In the altitude range of 2500 m to 3000 m, the water conservation depth was greater in 2000 than in 2018 and 2010.  
Figure 4: Water conservation function and its influencing factors at different elevations in Yunnan Province. (**a**) The relationship between altitude and water conservation capacity. (**b**) The relationship between altitude and precipitation, actual evapotranspiration, and population density.  
For all other elevations, the water conservation depth in 2018 exceeded that of 2000 and 2010, mirroring the ranking seen in the change in regional average conservation depth.
# Analysis of Small-Loop Electromagnetic Signals to Detect Subsurface Anomaly Zones
## 2 Background of Electromagnetic Exploration  
### Principles of the Frequency Domain Electromagnetic Method  
In this study, a CMD Mini Explorer, which is a piece of small-loop EM exploration equipment that uses the frequency domain electromagnetic (FDEM) method for frequencies below 30 kHz, was used to survey the ground conditions within a depth of 1.5 m [11]. The FDEM exploration method has a higher resolution than other exploration methods in cases where the target objects have large electrical conductivity (EC). In addition, the FDEM exploration method does not require a grounding transmitting and receiving system [12].  
The basic principles of the FDEM exploration method are shown in Figure 1. The primary EM field develops around the transmission coils in accordance with [PERSON]'s law in the event that an alternating current with a range of frequency is transmitted to the coils. Then, a new current is induced in accordance with [PERSON]'s law when the primary EM field passes through an anomaly zone in the ground [13]. The new current induced in the anomaly zone forms a secondary EM field, which includes an in-phase component with the same phase as the primary EM field and a quadrature component with a 90\({}^{\circ}\) different phase from the primary EM field at the same time. The in-phase and quadrature components of the secondary EM field are divided by the primary EM field to obtain the transmittance of the EM field and, consequently, calculate the EC. The EC can be easily converted to ER because they have a reciprocal relationship.
## 3 Related Studies
A total of 36 sets with a different number of requirements in various SRS domains were gathered from various sources. DARA examines the number of detected sentences, number of resolved sentences, and time spent for each SRS that undergoes ambiguity detection in addition to calculating the percentages for each ambiguity found as indicators. The results of utilizing DARA on these 36 case studies reveal that potential ambiguities occur frequently, accounting for almost 60% of the total number of requirements sentences (lexical ambiguity 37%, referential ambiguity 9%,coordination ambiguity 13%, scope ambiguity 25%, and vague 16%). DARA resolves 67% of ambiguity in the total number of required sentences. However, the performance of the proposed approach was not evaluated. [PERSON] and [PERSON] [10] proposed an automated approach, Ambi-Detect, for detecting ambiguities in Malay SRS documents, which consist of 180 manually labeled requirements, and used supervised machine learning methods, such as Random Forest, to classify the ambiguous and unambiguous software requirements. The classification result achieved an accuracy score of 89.67%, precision score of 0.90, recall score of 0.88, and F-Measure of 0.89, which is reasonably acceptable and may improve the productivity of formulating SRS. The proposed automated approach is a valuable tool for improving the quality of SRS documents and reducing the potential for misunderstandings and errors in Malay SRS. Nevertheless, this study uses a small dataset that affects the accuracy of the performance, thus making the classification arguable. Hence, the researchers have not stated which classification of ambiguity is covered in the research. However, further research is needed to evaluate the approach on a larger dataset.
## 5 Research Trends in Ge Photodetectors
### Remaining Technical Issues and Future Research Trends  
#### 5.5.1 Pursuit of Higher Bandwidth  
Nowadays, the reported Ge photodetectors' bandwidths are approaching 50 GHz, ready for near-future 40 Gb/s applications. On the other hand, in correspondence with III-V photodetectors, it can be seen that there is still much room for enhancement. For bandwidths beyond 100 GHz, much thinner Ge intrinsic layers should be used. As in the high frequency region, undesirable parasitic effect such as contact resistance, stray capacitance and inductance may become the main limiting factors in bandwidth performance. Given the fact that reducing the intrinsic region's thickness for smaller carrier transition time at the same time leads to increase of device capacitance, the mushroom-mesa structure [43] (Figure 9) may be of help for further bandwidth evolution, since it is capable of reducing the Rs and capacitance simultaneously.  
Figure 9: Schematic view of III-V photodetector based on mushroom structure. From [43].
# My Smartphone tattles: Considering Popularity of Messages in Opportunistic Data Dissemination
## 8 Performance Evaluations  
In this section, we explore in detail the performance of Keetchi against Epidemic. As discussed in Section 3, Epidemic is considered the best performing data forwarding algorithm for destination-less applications. Although we have described previously two other destination-less protocols (RRS and Spray and Wait), our evaluations here excluded them due to the reasons explained in Section 3.  
In these evaluations, we explored the performance of both protocols (Keetchi and Epidemic) for different numbers of nodes and different cache sizes (see Table 2).
## 6 A Physical Experiment Case Study
It can be assumed that if the leakage was not stopped during the experiment and the leakage was kept to a steady state, the estimated leakage rate of EKF would maintain a relatively stable state after rising to the highest point, which is similar to the result in Figure 7.4 In the experiment, the maximum value of the leakage rate read by the rotor flowmeter at the leakage point 1 was about 6.8 kg/h, and the highest point of the estimated curve of leakage rate was about 6.2 kg/h. The absolute error was 0.6 kg/h and the relative error was 8.8%. Experimental results and simulation results show that the method based on EKF is feasible to detect the leakage of a natural gas pipeline and estimate the leakage rate. The red line in Figure 10 represents the actual leakage location, and the blue line represents the estimated curve of the leakage location. It is not difficult to explain why the estimated curve of the leakage position rises and then falls, according to the change of the estimated value of leakage  
Figure 7.5 Estimated leak position using experimental data. Figure 7.6 Estimated leakage rate using experimental data. rate and Equation (13). The actual pipeline leakage point 1 is 3.9 m away from the pipeline starting point pressure sensor P1, while the peak of the estimated leakage position curve is about 3.3 m. The absolute error is 0.6 m. As the distance between pressure sensor P1 and P2 is 9 m, the relative error is 6.7%. It is conjectured that if the leakage was not stopped, the positioning accuracy would be further improved. The result of the experiment shows that the proposed method based on EKF is feasible to locate leakages in natural gas pipelines.
## 1 Introduction
### Conventional Corrosion Assessment Codes  
Various corrosion assessment methods have been developed to assess the integrity of a pipeline under various conditions to ensure safe operations. Failure pressure predictions based on conventional corrosion assessment codes, such as ASME B31G, Modified B31G, SHELL 92, RSTRENG, PCORRC, and DNV-RP-F101, are conservative, resulting in premature pipeline repairs and replacements [13]. Of all the codes that are being used in the industry for failure pressure prediction of corroded pipes subjected to combined loading, the DNV-RP-F101 code (DNV) is the most comprehensive [2; 6; 14; 15; 16; 17].  
Over the years, various studies have been carried out to develop accurate interaction rules based on corrosion defect categories such as longitudinal interacting defects, circumferential interacting defects, or single defects. The interaction rule applied for circumferentially aligned interacting defects in commonly used corrosion assessment codes in the industry are presented in Table 2.  
However, since the validation of the DNV approach was based on burst tests carried out on pipes of grades API 5L X45 to API 5L X65, it was designed primarily to examine the integrity of medium toughness pipelines. When applied to high toughness pipelines, it results in inaccurate and overly conservative predictions [4; 6]. In addition, this method is only applicable for interacting defects subjected to internal pressure only.
# Internet of Nano-Things, Things and Everything: Future Growth Trends
## 6 Challenges and Impediments to IoT
### Standardization  
Foremost in addressing the latest requirements for the pervasive implementation of IoT in terms of meeting stringent privacy and security requirements and at the same time adopting an elastic network architecture [69], is the work of the IEEE standardization organization--especially in regard to adoption of IPv6 packet routing through increasingly heterogeneous networks [5].  
Because of heterogeneity in networks as well as devices, interoperability is a fundamental need for the functioning of the Internet. This is more obvious for the IoT ecosystem since billions of devices are connected to the Internet as well as to each other. Each IoT device should converse in the same language (protocol) so that other devices can understand and thus standardization is paramount. The so called \"walled gardens\", providing a closed platform or ecosystem, which only allows communications limited among the devices belonging to the same vendor, restricts the advantages of having Internet access. Because IoE comprises multi-vendor devices, IoT systems need to go through intense and rigorous interoperability and compatibility tests before they are formally launched. This, however, does add to extra complexity and cost.  
While standardization is still in progress, constraints such as cost, time to market and technological limitations faced by IoT device manufacturers also adversely result in poor interoperability, lack of conformation to standards and often a compromised design. Technical and technological constraints include having to deal with limited memory and lower processing power as well as power consumptions having to be satisfied by limited non-renewable power supplies. Moreover, industrialists are under the compulsion to minimize the unit cost and thus the overall product costs to maximize profits. It has become a norm to use cost-benefit analysis, which may indicate it to be economically attractive to trade-off interoperability and performance (with their additional costs) against short-term goals of producing cheap IoT devices (potentially non-secure), even sometimes leading to proprietary products. However, approaches should be implemented to compel manufacturers to actively consider international policies such as adopting interoperability and conformance to international standards that yield long-term benefits, including product life-cycle gains.
# Mobility Management of Unmanned Aerial Vehicles in Ultra-Dense Heterogeneous Networks
## 6 Proposed Solutions
### Delay-Tolerant Networking (DTN) Algorithm  
A novel concept known as the DTN method (also known as Weighted Flight Path Planning (WFPP)) was proposed to maximize packet steering in UAV communication. The weight of packets is determined by their requirements, the time they must survive, and the amount of electricity they may consume. If the UAV's maximum length is less than the maximum length it can fly, the method generates an unused path that can be used. The path is obliterated if this is not the case [83].