esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
The search algorithm can be used to scan the prefabricated dispersion range to estimate the dispersion, but this kind of method has the problems of high complexity and slow convergence speed [14; 21]. Therefore, a fast and effective CD estimation method must be proposed to compensate the accumulated CD in the digital coherent receiver with less power consumption. In this paper, we propose a fast and blind method to estimate CD with a lower computation complexity, with the fractional Fourier transform (FrFT) theory. The energy concentration characteristic of the chirped signal is used, and the optimal transform order is obtained according to the peak point. According to the similarity between the chirped signal and CD, the relationship between the estimated dispersion value and the transform order is obtained from the point of view of the fractional domain by taking advantage of the unique advantages of the time-frequency domain joint analysis. Moreover, the estimation accuracy can be improved by increasing the number of samples. On this basis, we propose a stepwise optimal order search method. For this method, the search process is divided into two parts, including a coarse search and a fine search for multi-step adjustment, which greatly reduces the computational complexity. The rest of this paper is structured as follows. Section 2 introduces the basic principle of FrFT and how to compare the energy concentration characteristics of the chirped signal to CD estimation. Section 3 describes the structure of the CD monitoring experimental configuration of PM-QPSK and PM-16 QAM signals. Some simulation results and the discussion are presented in Section 4. Finally, Section 5 sums up the conclusions.
# Tracking and Registration Technology Based on Panoramic Cameras
## 3 Method
### Panoramic Depth Estimation Sub-Network
The feature map produced by the first large-kernel convolution (C8) undergoes a second upsampling via transposed convolution (T2) and is again concatenated with the corresponding shallow features from the encoder. The resulting features are further processed using another large-kernel convolution (C10), while the coarse depth map is simultaneously upsampled using nearest-neighbor interpolation. These two sources of feature information are fused to enhance the quality of the final fine-grained depth prediction. Specifically, two small-kernel convolutional layers (C11 and C12) are employed to fuse the concatenated features and produce a high-resolution depth map with the same resolution as the input image. In addition, except for the convolutional layers used for depth prediction (C9 and C12), all other convolutional operations in the decoder are followed by the ELU activation function to enhance the non-linear representational capacity and stability of the network. Since the depth values estimated by the depth estimation sub-network are relative and the depth range in panoramic images is typically wide, the estimated depth values are normalized to a reasonable range to facilitate more effective utilization of the depth information. The estimated depth values are normalized as follows (Equation (1)):  
\[D_{s}=\frac{1}{\alpha\cdot\sigma(f_{s})+\beta} \tag{1}\]  
where \(f_{s}\) denotes the output of the sub-network predicting depth, \(\sigma(\cdot)\) is the Sigmoid activation function, \(\alpha\) and \(\beta\) are hyperparameters. \(D_{s}\) is the normalized depth map, and \(s\in\{1,2\}\) represents different resolutions, where s = 1 indicates half-resolution, and s = 2 indicates full-resolution. In the experiment, \(\alpha=10\) and \(\beta=0.1\) are used to normalize the depth values within a range of 10 m.
## 3 Methods  
The research content can be divided into three parts: data acquisition and processing, spatiotemporal evolution analysis, and driving factor analysis (Figure 2). All data processing for this study, including tasks such as stitching, clipping, resampling, and downloading, was performed on the Google Earth Engine (GEE) platform. Due to the varying resolutions of the data, a 500 m WUE dataset was used for the spatiotemporal evolution analysis, and for the driving factor analysis, the WUE resolution was resampled to match the resolution of the driving data, which is 4 km. The Theil-Sen slope estimator and Mann-Kendall significance analysis were then used to explore the temporal trends and spatial significance of WUE in the study area. Finally, XGBoost was employed to establish the relationship between the driving factors, and the SHAP model was used to interpret the importance of these driving factors and their specific relationship with WUE.
# UAV Detection and Tracking in Urban Environments Using Passive Sensors: A Survey
## 3 UAV Localization and Tracking  
UAV localization and tracking play a crucial role in anti-UAV research. This section provides a review of UAV localization and UAV tracking methods. UAV localization research primarily concentrates on utilizing RF and acoustic-based methods. These methods are preferred due to their ability to accurately determine the location of UAVs. Regarding UAV tracking, we categorize the studies into filter-based approaches and deep Siamese networks approaches. Filter-based methods utilize various filters for tracking UAVs, while deep Siamese networks approaches leverage deep learning techniques for tracking. The advancements made in these research areas are thoroughly discussed, highlighting the progress and innovations achieved in UAV tracking.
# On the Utilization of Reversible Colour Transforms for Lossless 2-D Data Compression
## 2 Burrows-Wheeler Compression Algorithm (BWCA)
Once RLE has been done, the output is encoded by an entropy coder such as Huffman or arithmetic encoder. An entropy coder compresses data by assigning fewer bits to frequently occurring symbols. This way symbols with elevated occurrence are decreased effectively. Both Huffman and arithmetic encoder models considers the probability of each data symbol or pixel. Huffman encoders provide better speed while arithmetic coders provide better compression. This research work has employed the arithmetic coder. Details of the arithmetic encoder are given in the Appendix A. The BWCA is not complex in logic and offers high compression due to its main component, the Burrows-Wheeler Transform (BWT) which increases the redundancy of the data, in turn leading to higher compression. To further enhance the compression ability of the scheme, various modifications to the BWCA have been made including the works of [PERSON] et al. in in [24], [PERSON] et al. in [23], [PERSON] in [17; 18; 22], [PERSON] in [25], [PERSON] and [PERSON] in [26], [PERSON] et al. in [27] and [PERSON] et al. in [28] to name a few. This research work augments the compression performance of the Bi-level Burrows-Wheeler Compression Algorithm (BBWCA) devised by [PERSON] et al. in [14]. The scheme offers higher image compression as compared to other benchmarks schemes by transforming the colour intensity levels over the dimensional space using a Reversible Colour Transform (RCT). The RCT increases the inter-pixel redundancy aiding in the compressibility of the data at the later stages of the algorithm. Figure 3 shows an overview of the BBWCA. Prior to the input to RCT, true colour image data is DC shifted resulting in a grey-level range from \(-128\) to \(+127\). In comparison to the original image, the resulting image becomes more skewed aiding in much better compression during the later stages. Once the data is DC shifted; converted to YUV colour space from RGB, it is further processed during the BWT stage. To achieve better compression results [PERSON] et al. in [14] employed the JPEG 2000 RCT [29]. In contrast to the conventional BWCA approach, BBWCA transfigures the image through row-wise and column-wise application of BWT over image data resulting in a highly correlated 2-D image. Redundancy among the pixels is enhanced by the utilization of the KMTF transform [28; 30], in conjunction with RLE-0 and arithmetic encoding. By utilizing the RCT, BBWCA is able to achieve higher inter-pixel redundancy and in turn higher compression. There exist various RCTs, time and frequency based, which can be employed and explored for higher compression. The main aim of this research work is to investigate these RCTs and demonstrate their effect on the compression performance offered by the BBWCA. The following section presents a brief history and various types of RCTs designed and devised by the research community in the field of image processing.
## 2 State-of-Art Review
### General Parameters Affecting the Performance of RFA in Concrete
#### 2.1.3 Quality of the Source Material  
[PERSON] [66] analysed the influence incorporation of different types and levels of fine RA on concrete's modulus of elasticity and workability of the resulting RAC. As seen in Figure 3, among 9 different types of CDW, it was concluded that using 80% old concrete +20% old bricks as RFA yields the least drop in workability and in elastic modulus with the higher incorporation rates. The reason could also be related to optimizing the water absorption potential.  
Figure 3: Effect of replacing different incorporation ratios and types of fine RA content on (**a**) workability and (**b**) relative modulus of elasticity of concrete [66].  
Figure 2: Influence of minimum fine recycled fine aggregates (RFA) particles size on 28 days strength of concrete [67].
###### Abstract
A number of early review articles showed lower survival rates for short implants than those for standard length implants [11; 12]. [PERSON] et al. (2005) concluded that implant length correlates significantly with implant success rates [13]. However, with the technological improvements in implant designs, surface treatments, and surgical techniques, recent studies have demonstrated that implant length did not appear to influence significantly the survival rate [14; 15]. Short implants appeared to be the preferable method for augmented posterior regions to longer implants in several studies [16; 17]. Despite positive results of short implants studies, some clinicians still have doubts about them, because of smaller bone-to-implant contact area and unfavorable crown-to-implant ratio. With an emerging demand for reduced implant treatment time and advances in implant surface, immediate and early loading protocols have gained predictability among the recent studies as well as clinicians [18; 19]. As for single implants, recent systematic reviews show immediately loaded single implants to be in greater risk of failure than full arch restorations, because occlusal forces may impact directly on the implant without cross arch stabilization [20]. However, some authors have reported immediately and conventionally loaded single-implant crowns to exhibit equal implant survival and marginal bone loss when implants are inserted with a torque \(\geq\) 20 to 45 Ncm or an implant stability quotient (ISQ) \(\geq\) 60-65 [21]. The purpose of this randomized clinical trial is to evaluate immediately loaded single implants with varying lengths in the posterior mandible using a fully digital, model-free prosthetic-driven implant planning pathway, and to compare clinical and radiological outcomes of short and long implants during 48 weeks of observation period.
## 3 Results and Discussion  
### The Changes of Exhaust Gas Temperature and Pressure Drop  
Different engine loads correspond to different sailing conditions of the ship, whether the diesel engine is used as a main engine or a generator. When it is used as the main engine, the engine load is generally below 35% (6 kW or less) under maneuvering sailing, around 45% (6-9 kW) under low-speed sailing, around 75% (about 12 kW) under normal sailing, and 100% (15 kW) under maximum speed sailing. Large-scale ocean-going vessels generally have three or four diesel engine generators. When a diesel engine is used to drive a generator, the typical load is 80% to 90% (about 12 kW), regardless of whether the ship is anchored or sailing. Different exhaust temperatures correspond to different engine loads. Therefore, whether as a main engine or as a power generation diesel engine, the engine load and exhaust gas temperature can correspond to different ship working conditions to a certain extent. The diesel engine used in this paper is a small one and is generally used as a power generation diesel engine for ships. The engine load is commonly about 12 kW.  
Figure 3 shows the pressure drop of the AC reactor and exhaust temperature changes at different engine powers. It can be seen from Figure 3 that as the power increased, the exhaust temperature continuously rose. As part of the heat is lost to the environment, the exhaust temperature after passing through the reactor was slightly lower. Moreover, when the power was 6 kW, the exhaust temperature was about 200 \({}^{\circ}\)C, and when the power was 15 kW, the diesel engine reached full load, and the exhaust temperature reached 358 \({}^{\circ}\)C at the highest. The pressure drop of the reactor was maintained at about 210 Pa in the range of 0-9 kW. When the power further increased, the pressure drop increased significantly, eventually reaching 260 Pa. A possible reason for the pressure increase is that the PM adsorbed on the surface of the activated carbon gradually increased with time, thus causing a certain extent of blockage of the exhaust gas passage, thereby causing an increase in the pressure drop. In practical applications, the activated carbon in the front section of the reactor may be replaced in time according to the exhaust back pressure recommended by the diesel engine manufacturer, or an exhaust fan may be installed after the AC reactor.
## 5 Medical Imaging-Based Kinematics
### Ultrasound Technology (US)
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Technology** & **Technique** & **Principle** & **Resolution** & **Applications** \\ \hline \multirow{3}{*}{US} & Echo and Vector Doppler & Measurement of frequency shift of the reflected acoustic wave. & Spatial resolution \(<\)1 mm/pixel & Identification of: septal defects, CHD, valve structure. Assessment of cardiac and arterial function. \\ \cline{3-5}  & 2D PC & Applied magnetic field gradients produce a phase shift on proton spins proportional to its relative velocity. & Pixel size \(\sim\)1.5 mm 30 images per cardiac cycle & Assessment of cardiac, arterial, and venous flow, cardiac output, regurgitan flow, pulse wave velocity. \\ \cline{3-5}  & 4D flow & spins proportional to its relative velocity. & \multirow{2}{*}{Pixel size \(\sim\)2.5 mm 25 images per cardiac cycle} & Same as 2D PC plus measurements of wall shear stress, vorticity and pressure drop. \\ \cline{3-5}  & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Image-based technique for assessment of blood flow. Figure 7: Resolution comparison of left ventricular myocardium at diastole and systole with clinical grade (**a**) MRI, (**b**) CT (Reprinted/adapted with permission from Ref. [158], 2019, Korean Society of Echocardiography, open access), and (**c**) 2D ultrasound.
###### Abstract  
This study selected the most common illnesses in children and older adults and aimed to provide a customized degree of daily risk for each illness based on patient data for specific regions and illnesses. Sample medical data of one million people provided by the National Health Insurance Corporation and information regarding the meteorological environment and atmosphere from the Korea Meteorological Administration and a public data portal using application programing interface were collected. Learning and predictions were carried out with machine learning. Models with high R\({}^{2}\) were selected and tuned to determine the optimal hyperparameter for predicting the degree of daily risk of an illness. Illness with an R\({}^{2}\) value greater than 0.65 were considered significant. For children, these consisted of acute bronchitis, the common cold, rhinitis and tonsillitis, and middle ear inflammation. For older adults, they consisted of high blood pressure and heart disease, the common cold, esophageal inflammation and gastritis, acute bronchitis, eczema and dermatitis, and chronic bronchitis. This study provides the degree of daily risk for the most common illnesses in each age group. Furthermore, the results of this study are expected to raise awareness of illnesses that occur in certain climates and to help prevent them.  
daily illness risk; medical information; meteorological data; prediction Article
## 2 Design Methodology for Integrated Signal
### OFDM Chirp Signal
\begin{array}{rl}Y_{l}[k]&=\sum\limits_{n=0}^{N-1}y_{l}[n]e^{-j2\pi ktn/N}\\ \\ &=\sum\limits_{n=0}^{N-1}\biggl{\{}\sum\limits_{m=0}^{\infty}h_{l}[m]x_{l}[n- m]+z_{l}[m]\biggr{\}}e^{-j2\pi ktn/N}\\ \\ &=\sum\limits_{n=0}^{N-1}\biggl{\{}\sum\limits_{m=0}^{\infty}h_{l}[m]\biggl{\{} \sum\limits_{N=0}^{N-1}X_{l}[i]e^{-j2\pi i(n-m)/N}\biggr{\}}\biggr{\}}e^{-j2 \pi ktn/N}+Z_{l}[k]\\ \\ &=\sum\limits_{n=0}^{N-1}\biggl{\{}\sum\limits_{n=0}^{\infty}h_{l}[m]e^{-j2 \pi im/N}\biggr{\}}X_{l}[i]\sum\limits_{n=0}^{\infty}e^{-j2\pi(k-l)n/N} \biggr{\}}e^{-j2\pi ktn/N}+Z_{l}[k]\\ \\ &=H_{l}[k]X_{l}[k]+Z_{l}[k]\end{array}  \tag{6}\]  
where \(X_{l}[k],Y_{l}[k],H_{l}[k],Z_{l}[k]\) are denoted as the transmitted symbols, the received symbols, the frequency response of the channel, and the noise in the frequency domain on the \(k\)-\(th\) subcarrier of the \(l\)-\(th\) symbol, respectively.
# Low-Latency Short-Packet Transmission over a Large Spatial Scale
## Appendix A Derivatives of Function \(\mathcal{G}\)  
The partial derivatives of \(\mathcal{G}(n,\gamma)\) are listed in this Appendix. Furthermore, we prove whether each of them is positive or negative.  
The partial derivative of \(\mathcal{G}\) w.r.t. \(n\) is:  
\[\begin{split}\mathcal{G}^{{}^{\prime}}_{n}&=\sqrt{ \frac{(\gamma+1)^{2}}{\gamma(\gamma+2)}}\bigg{(}\frac{k\ln 2}{2n^{\frac{3}{2}}}+ \frac{\ln(1+\gamma)}{2n^{\frac{1}{2}}}\bigg{)}\\ &>0,\end{split} \tag{18}\]  
and the partial derivative of \(\mathcal{G}\) w.r.t. \(\gamma\) is:  
\[\begin{split}\mathcal{G}^{{}^{\prime}}_{\gamma}&= \sqrt{n}\big{[}\gamma(\gamma+2)\big{]}^{-\frac{3}{2}}\bigg{[}\gamma(\gamma+2) -\bigg{(}\ln(1+\gamma)-\frac{k\ln 2}{n}\bigg{)}\bigg{]}\\ &>0.\end{split} \tag{19}\]  
This is because \(\gamma(\gamma+2)-\Big{(}\ln(1+\gamma)-\frac{k\ln 2}{n}\Big{)}>\gamma-\ln(1+ \gamma)>0\).  
The second-order partial derivative of \(\mathcal{G}\) w.r.t. \(\gamma\) is given by:  
\[\begin{split}\mathcal{G}^{{}^{\prime\prime}}_{n}&= -\sqrt{\frac{(\gamma+1)^{2}}{\gamma(\gamma+2)}}\bigg{(}\frac{3k\ln 2}{4n^{ \frac{5}{2}}}+\frac{\ln(1+\gamma)}{4n^{\frac{3}{2}}}\bigg{)}\\ &<0.\end{split} \tag{20}\]  
The second-order partial derivative of \(\mathcal{G}\) w.r.t. \(\gamma\) is given by:  
\[\begin{split}\mathcal{G}^{{}^{\prime\prime}}_{\gamma}=& -\sqrt{n}\big{[}\gamma(\gamma+2)\big{]}^{-\frac{3}{2}}\bigg{[} \gamma+1+\frac{1}{\gamma+1}-\frac{3\big{(}\ln(1+\gamma)-\frac{k\ln 2}{n} \big{)}(\gamma+1)}{\gamma(\gamma+2)}\bigg{]}\\ <&-\sqrt{n}\big{[}\gamma(\gamma+2)\big{]}^{-\frac{3} {2}}\bigg{[}\gamma+1-\frac{3\gamma(\gamma+1)}{\gamma(\gamma+2)}\bigg{]}\\ <& 0.\end{split} \tag{21}\]  
The first inequation holds because:  
\[\begin{split}\gamma+1+\frac{1}{\gamma+1}&-\frac{3 \Big{(}\ln(1+\gamma)-\frac{k\ln 2}{n}\Big{)}(\gamma+1)}{\gamma(\gamma+2)}\\ &>\gamma+1+\frac{1}{\gamma+1}-\frac{3\ln(1+\gamma)(\gamma+1)}{ \gamma(\gamma+2)}\\ &>\gamma+1+\frac{1}{\gamma+1}-\frac{3\gamma+1}{\gamma+2}\\ &>\gamma+2+\frac{4}{\gamma+2}-4\\ &>0,\end{split} \tag{22}\]  
which applies the inequality of the arithmetic and geometric means (AM-GM inequality) in the last step.  
Last but not least, we have:  
\[\begin{split}\mathcal{G}^{{}^{\prime\prime}}_{n\gamma}& =[n\gamma(\gamma+2)]^{-\frac{3}{2}}\bigg{[}\frac{n\gamma(\gamma+2)}{2}+k-\frac{ n\ln(1+\gamma)-k\ln 2}{2}\bigg{]}\\ &>[n\gamma(\gamma+2)]^{-\frac{3}{2}}\bigg{[}\frac{n\gamma(\gamma+ 2)}{2}-\frac{n\ln(1+\gamma)}{2}\bigg{]}\\ &>[n\gamma(\gamma+2)]^{-\frac{3}{2}}\bigg{[}\frac{n\gamma(\gamma +2)}{2}-\frac{n\gamma}{2}\bigg{]}\\ &>0.\end{split} \tag{10}\]  
In conclusion, we have the expressions of the derivatives of \(\mathcal{G}\) and proved whether each of the derivatives is positive or negative.
# A Modified Bio-Ecological Process for Rural Wastewater Treatment
## 3 Results and Discussion
### Overall Reactor Performance
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Parameters**} & \multicolumn{4}{c}{**Influent**} & \multicolumn{4}{c}{**Effluent**} & \multicolumn{4}{c}{**Efficiency**} \\ \cline{2-10}  & **Min** & **Max** & **Mean \(\pm\) SD ** & **Min** & **Max** & **Mean \(\pm\) SD ** & **Min** & **Max** & **Mean** \\ \hline  & & & & **mg/L\({}^{-1}\) & & & & **\%** & \\ \hline
**COD** & 185.3 & 321.2 & 268.2 \(\pm\) 30.75 & 10.4 & 28.7 & 19.6 \(\pm\) 4.6 & 0.87 & 0.95 & 0.91 \\
**TN** & 22.4 & 42.1 & 36.01 \(\pm\) 4.59 & 3.6 & 11.5 & 7.96 \(\pm\) 1.84 & 0.75 & 0.85 & 0.78 \\
**NH\({}_{4}\)-N** & 17 & 36 & 29.9 \(\pm\) 4.42 & 0.5 & 4.6 & 2.35 \(\pm\) 0.99 & 0.81 & 0.94 & 0.85 \\
**TP** & 3.2 & 5.7 & 4.7 \(\pm\) 0.59 & 0.2 & 0.58 & 0.36 \(\pm\) 0.10 & 0.87 & 0.95 & 0.92 \\ \hline \hline \end{tabular} Here, COD = chemical oxygen demand; TN = total nitrogen; NH\({}_{4}\)-N = ammonium; TP = total phosphorus.  
** is the probability value >0.001.  
\end{table} 
Table 4: Removal efficiencies were achieved by A2O-wetland system. Figure 7: Removal efficiencies of COD, TN, NH\({}_{4}\)+-N, and TP in different units of A2O–wetland system. The bio-ecological system showed a highly significant effect (\(p<0.001\)) for COD, TN, ammonium, and TP. According to [53], aeration, pumping, and material flow are the most important units in WWTPs (wastewater treatment plants) regarding energy consumption, and aeration consumes more than a half of the total energy consumption in WWTPs. In the bio-ecological system, there was no other energy consumption equipment other than a water pump. Thus, the average cost of wastewater could be kept to a minimum. An important approach for bio-ecological processes is the treatment and reuse of domestic wastewater in a decentralized manner, especially in rural areas [54]. Ecological wastewater treatment often leads to decentralized treatment, and considers the wastewater as a resource for irrigation and fertilizer [24].