esa-sceva/satcom-chunk-collection huggingface dataset:
# Fourier Singular Values-Based False Data Injection Attack Detection in AC Smart-Grids
## 3 FDIA Detection
### Fourier Singular Values
#### 3.1.2 SVD Theory  
To begin with, a vibration signal as a set of one dimensional data is considered as h(n), where n = 1, 2,..., M. Here, M gives the length of h(n). Based on the viewpoint of phase space reconstruction, the track matrix of h(n) which is noticed as Hankel matrix, is defined as Equation (9) [47]:  
\[\mathrm{H}=\left[\begin{array}{cccc}\mathrm{h(1)}&\mathrm{h(2)}&\dots& \mathrm{h(M-R+1)}\\ \mathrm{h(2)}&\mathrm{h(3)}&\dots&\mathrm{h(M-R+2)}\\ \vdots&\ddots&\vdots\\ \mathrm{h(R)}&\mathrm{h(R+1)}&\dots&\mathrm{h(M)}\end{array}\right] \tag{9}\]  
where, R represents the number of rows, and H defines a m\(\times\)n real matrix by rank of r and the SVD will be an approach to break down the matrix as three different matrices as follows; herein, SVD of H is formulated in Equation (10) [48].  
\[\mathrm{H}=\mathrm{U}\left(\begin{array}{cc}\mathrm{S}&\mathrm{O}\\ \mathrm{O}&\mathrm{O}\end{array}\right)\mathrm{V}^{\mathrm{T}} \tag{10}\]  
Here, U and V represent orthogonal matrices with m and n order, and T gives the function of conjugate transpose. The null matrix is presented by O, also, S defines a diagonal matrix with order of r which is given in Equation (11):  
\[\mathrm{S}=\left[\begin{array}{cccc}\rho_{1}&0&\dots&0\\ 0&\rho_{2}&&\\ &0&\ddots&&\\ \vdots&\vdots&&\rho_{i}&&\vdots\\ &&&\ddots&&\\ &&&\rho_{r-1}&0\\ 0&0&&\dots&0\rho_{r}\end{array}\right]\text{; }\mathrm{i}=1,\,2,\,\dots,\, \mathrm{r} \tag{11}\]  
\[\mathrm{H}=\mathrm{diag}(\sigma_{1},\sigma_{2},\dots,\sigma_{r}) \tag{12}\]  
Here, \(\rho_{i}\) indicates the non-zero singular values of H. With eliminating the zero singular value from Equation (9), it can be expressed that the simplified shape of the SVD of H is given in Equation (13):  
\[\mathrm{H}=\sum_{i=1}^{r}\rho_{i}\mathrm{u}_{i}\mathrm{v}_{i}^{\mathrm{T}} \tag{13}\]  
with \(\rho_{1}\geq\rho_{2}\geq\dots\geq\rho_{r-1}\geq\rho_{r}\geq 0\).  
In Equation (13), \(\mathrm{u}_{i}\) and \(\mathrm{v}_{i}\) indicate the i\({}^{th}\) column vectors of U and V. Therefore, the singular value ingredients will be taken from \(\rho_{i}\mathrm{u}_{i}\mathrm{v}_{i}^{\mathrm{H}}\).
# An Experimental Tuning Approach of Fractional Order Controllers in the Frequency Domain
## 2 Proposed Tuning Method
If the results obtained by the fractional-order PI/PD controller are not satisfactory, a more complex fractional-order PID may be required:  
\[C_{FO-PID}=k_{p}+k_{d}s^{\mu}+\frac{k_{i}}{s^{\lambda}}, \tag{13}\]where \(k_{p}\), \(k_{d}\), and \(k_{i}\) are the proportional, derivative, and integral gains, whereas \(\mu\in(0,1]\) denotes the order of the differentiation and \(\lambda\in[-1,0)\) expresses the order of the integration. The fractional PID requires a minimum number \(n=5\) of experimental tests in order to develop the system needed for the controller optimization. The focus of the method is mitigating vibration. The optimization approach is related to the frequency domain magnitude and phase. The method guarantees the computation of a viable fractional-order controller that efficiently suppresses vibration. It is important to emphasize that the efficiency of the obtained fractional-order controller lies in a stable, robust, closed-loop system that reduces the effect of the vibration on the process. The tuning methodology is focused on flattening the resonant peak that causes real-life vibration mitigation, without specific attention to the closed-loop system's performance such as settling time. As the method is an experimental one and does not require a mathematical model for the process, validating the method will be done on an experimental platform.
## 1 Introduction  
The challenge to digitalize cultural heritage data has long been a focus of interest. Digitalization has become an important step in the development of civilization as a whole, and this is also the case in the humanities. Over the last few years, this has become crucial due to the COVID-19 pandemic restrictions. Museums and cultural institutions advanced at a faster pace [1, 2] as compared to archaeological expeditions. However, the submission requirements for reports and documentation are also changing under the new circumstances. The preservation of information in digital form, including artifacts and field findings, has become vital to avoid them being lost, e.g., artifacts can be destroyed and reports can be damaged by fire. Regrettably, such incidents have occurred in history. Moreover, excavations themselves can cause damage to a site, leading to the information being saved but the heritage object being ruined. Therefore, it is essential to keep any information in a comprehensive visual form. The most convenient way of achieving this is by presenting materials in 3D format with a geographic reference to the terrain. The most favorable approaches are laser scanning and photogrammetry, with the latter becoming increasingly widespread due to its availability and low cost [3; 4; 5; 6; 7]. This article presents the work of the Institute of Archeology of the Russian Academy of Sciences' Markul Expedition, which conducted research in the Northwestern Colchis (the Greater Sochi Region of the Russian Federation and the Republic of Abkhazia) using a combination of digital technologies in order to recreate a holistic picture of the historical and cultural landscape of this territory in antiquity (Figure 1). In ancient times, Northwestern Colchis played an essential role in the interaction between the ancient world and the world of barbarian tribes. The history of the region is \"antique-centrist\" according to the available ancient written data; however, archaeologically, this territory has only been studied fragmentarily, without generalizations or attempts to evaluate the role of the local population. Therefore, the work of the Markul Expedition aimed at filling this gap in knowledge.  
Figure 1: Location of Northwestern Colchis: the territory of the Markul expedition and the location of the Markul settlement.  
The expedition had two main objectives: to create a complete geographic information system (GIS) of the archaeological sites in the region and to study the Markul settlement [7], which is a unique local population site that has been virtually untouched by anthropogenic activity, and thus reflects the history of the region from the 4 th century BC to the 14 th century A.D. This site is located in the Ochamchira region of the Republic of Abkhazia, 10 km inland from the coast.
## 4 Discussion
As reported in Table 4, the TLSE method reaches the highest accuracy on the Herlev datasets on the fine-grained classification task. On one hand, the snapshot ensemble phase in TLSE acquires an ensemble benefit by averaging the last two snapshot models' soft-max class posteriors. The ensemble result can be beneficial as it is a process of consulting several experts before taking a final decision. On the other hand, the transfer learning phase in TLSE provides better initialization weights rather than train from scratch, which provides the model with a good start point and makes the loss converge fast. In addition, the transfer learning plays a major role in reducing over-fitting, especially for small samples, as in the Herlev dataset case. Despite of the accuracy improvement from TLSE, the proposed approach demonstrates a few limitations. Firstly, the size of input samples varies, so the images need to be resized into a fixed \(128\times 128\) for data processing, and zero padding is adopted for cropping. However, the cropped region may not contain the whole cell, and a fixed scale may not be appropriate when the cell image scales vary. Our ongoing study shows that this may be solved by using the spatial pyramid-pooling layer, for input images of arbitrary scales. Secondly, the final accuracy of the seven-class cervical cells classification is still not satisfied. The big gap between the two-class accuracy and the seven-class accuracy, as to our knowledge, is mainly due to the small sample. For the two-class problem, the amount of the data with data augmentation is sufficient. However, for the seven-class problem, the traditional data augmentation method may not be enough. As for the rare data especially in the medical image application areas, data augmentation methods, such as mix-up, GAN can be taken into consideration for increasing the number of samples. Thirdly, our approach is not based on microscopy slide images but rather on database images; thus, an important task related to image acquisition from the microscope is missing. The detection of cervical cells on microscopy slide images is another challenge task in this area. We anticipate that an end-to-end, highly accurate, and real-time cervical cells detection and classification system of this type is promising for the development of automation-assisted reading systems for cervical screening.
## 4 A Case Study
### Test Cases in a Complex Scenario  
A more complex scenario involving three ships (OS, TS1, and TS2) was considered in this test case. It is a typical offshore water area, where the OS needs to avoid both islands and TSs. As shown in Figure 11a, the encounter scenario size was set to 4 km \(\times\) 4 km, where the center was taken as the origin \((0,\ 0)\) m. The initial position of OS was \((-1172.4,\ 0)\) m, and its destination was \((1172.4,\ 620.7)\) m. The velocity and the course of OS were 7.0 m/s and \(315^{\circ}\), respectively. Correspondingly, the positions, speeds, and courses of TS1 and TS2 were set to \((115.9,\ 1487)\) m, \((1763,-619.5)\) m, \(7.0\) m/s, \(5.0\) m/s, \(270^{\circ}\), and \(135^{\circ}\), respectively.  
In this test case, an assumption was made that the TSs are navigating in the fairways, and the OS tries to cross the fairways. According to COLREGs Rule 9 [29], the OS is required not to impede the TSs. In other words, the OS is a give-way vessel, and the TSs are stand-on vessels. Parameters \(r_{1}\), \(r_{2}\), \(r_{3}\), and \(r_{4}\) for dynamic obstacles were set to 4.0, 1.0, 1.0, and 1.0, respectively, and the corresponding safety distance thresholds \(d_{1}\), \(d_{2}\), \(d_{3}\), and \(d_{4}\) were 400 m, 100 m, 100 m, and 100 m. In addition, the safety distance threshold for static obstacles was 200 m in this scenario.  
Figure 10: The path planning results and the collision avoidance trajectories in Crossing-2. (**a**) The path planning results, (**b**) The collision avoidance trajectories.  
Figure 9: The path planning results and the collision avoidance trajectories in Crossing-1. (**a**) The path planning results, (**b**) The collision avoidance trajectories.  
A preliminary path indicated with a solid red line was generated only based on the static obstacle representation, as shown in Figure 11b. A reasonable path shown in Figure 11c was obtained through path optimization based on the preliminary path. Figure 11d shows the collision avoidance trajectories according to the trajectories' prediction, and a specific quantitative assessment is shown in Figure 12. It is evident that the OS plans to pass by the bow of the TS1. Usually, this is a kind of dangerous navigation behavior. However, a minimum relative distance of 191.65 m can always be maintained between the OS and the TS1 based on the collision avoidance trajectories. According to the above results, the proposed path planning scheme can provide a robust collision avoidance approach by considering spatial-temporal interaction effects.  
Figure 11: The path planning results and the collision avoidance trajectories in the complex scenario. (**a**) The encounter scenario, (**b**) The preliminary path, (**c**) The path planning results, (**d**) The collision avoidance trajectories.
# Effects of Biochar Production Methods and Biomass Types on Lead Removal from Aqueous Solution
## 3 Results and Discussion
### Lead Adsorption  
All biochar materials exhibited Pb\({}^{2+}\) removal greater than 90% (Figure 4). Note that % Pb\({}^{2+}\) removal in the current study was used as a relative index in comparing eight different biochars, and it does not indicate the absolute amount of Pb\({}^{2+}\) removal. Of the tube-furnace-produced biochars, avocado seed (AST) and grapefruit peel biochars (GPT) performed the best with 98-99% Pb\({}^{2+}\) removal. The high Pb\({}^{2+}\) removal from GPT agrees with a previous study that found 96% Pb\({}^{2+}\) removal when low temperature (300 \({}^{\circ}\)C) organic peel biochar was equilibrated with 10 mg Pb\({}^{2+}\) L\({}^{-1}\). Of the BioCharlie-produced biochars, brown seaweed and avocado seed biochars performed equally well (97%). It is notable that brown seaweed biochar from BioCharlie performed well as it is not a carbon-rich biomass.  
The biochars from the tube furnace showed slightly greater Pb\({}^{2+}\) removal than the BioCharlie counterparts except brown seaweed biochars. Avocado seed and grapefruit peel biochars from the tube furnace were particularly effective and their performance was comparable to commercial activated carbon (98%). From the FTIR data (Figure 3), land-based biochars (AST, APT, and GPT) showed oxygen-containing surface functional groups, while BST did not. This absence of oxygen-containing groups can explain the lower Pb\({}^{2+}\) adsorption of BST (tube furnace). The enhanced performance of BSB (BioCharlie) may be attributed to its high ash content (68%, Table 1). The positive role of biochar mineral fraction has been postulated to enhance heavy metal adsorption onto the biochar in a previous study, and both C and mineral (ash) fractions of biochar likely contributed to the effective Pb\({}^{2+}\) removal in the current study [38; 39]. It is important to note that the current study does not reveal the adsorption mechanism of Pb\({}^{2+}\) (e.g., physisorption or chemisorption) on the biochar materials. As the current study used relatively low-temperature biochars with no surface activation, chemisorption processes (e.g., precipitation, ion exchange, electrostatic  
Figure 3: Fourier transform infrared (FTIR) spectra of tube-furnace-produced biochars: (**a**) avocado seed biochar, (**b**) avocado peel biochar, (**c**) grapefruit peel biochar, and (**d**) brown seaweed biochar.  
attraction, and surface complexation) were likely to be dominant for Pb\({}^{2+}\) adsorption, but there was no mechanistic information to support this statement in the current study [20; 39].
## 3 FSM Motion System  
### Identification of FSM Motion System  
In the FSM motion system, the mechanical aspect was comprised of PZT actuators, while the electrical portion consisted of an actuator amplifier and a sensing signal processing unit. As shown in Figure 1, the PZT actuators were designed with a resistance strain gauge sensor attached to the PZT ceramic surface and were mounted below the mirror to enable tip-tilt motion within the required actuation ranges. Figure 5 shows the mirror-mounted FSM using the PZT actuators, encompassing all the mechanical and electrical components required for tip-tilt motion. Designing a feedback control system generally necessitates identifying the dynamic characteristics of the input and output signals of a real plant. The frequency response of the real plant (i.e., the FSM motion system) in this study was analyzed using a dynamic signal analyzer (35670A, KEYSIGHT, Colorado Springs, CO, USA). The identified dynamic specifications of the real plant are summarized in Table 2. Based on these specifications, the frequency responses of the real and modeled plants for the mirror-mounted FSM using PZT actuators are illustrated in Figure 6.  
Figure 5: Assembled view of the mirror-mounted FSM using PZT actuator for tip-tilt motion.  
Figure 6: Frequency responses of real and modeled plants for mirror\(-\)mounted FSM using PZT actuator.  
the 0 dB crossover frequency and loop gain were 102 Hz and over 30 dB, respectively. The stability gain of the PI controller was selected to achieve the required control performance. The disturbance-attenuation performance of the designed PI controller is presented in Figure 9.
## 2 Energy Piles  
Initial studies into EGSs were recorded for several cases in Austria, including both piles and walls [10]. In subsequent decades energy piles have been installed in many countries, including the UK [12; 13] and China [11]. As an example, [PERSON] (2006) reported that the total number of energy piles installed in Austria increased by almost an order of magnitude in the period from 1990 to 2004 [10]. In the UK, the first energy piles were installed at Keble College in Oxford in 2001 [14]. Since then, installation of energy foundations has increased rapidly. Just 150 energy piles were installed per year in the UK in 2004; by 2008 this had risen to nearly 1600 energy piles per year [15]. After 2010 the rate of increase has reduced in line with the economic situation [12], but there still remains significant interest in this relatively new technology. There are landmark GSHP coupled foundation schemes such as \"One New Change\" Project [16] with both energy piles and open loop GSHP wells. Moreover, several energy-pile projects have been built, operated, and published [12; 14; 17].  
Until recently, energy piles were mainly built as driven precast concrete piles with integrated heat exchange tubes. Since 2000, the technology has been extended to large-diameter bored piles, where the size of the pile allows for placing multiple U-shaped loops of pipes used to circulate the carrier fluid. In bored energy piles the pipes are typically made of high-density polyethylene, 20-25 mm in diameter and about 2 mm thick and are fixed to the reinforcement cage. Heat carrier fluid used in the primary circuit can be water, saline solutions or water-glycol mixtures, with the latter having been proven to be the most suitable option in most cases due to their good antifreeze properties and low environmental impact as a result of their low toxicity and high biodegradability. The fluid flow rates, and pipe diameters are selected to achieve turbulent flow conditions that enhance heat transfer and obtain the required amount of heat transfer [18].  
Determination of diameter, material, flow rates and pipe size, etc. requires careful design work. The design of energy piles is more complicated than for BHE since energy piles play double roles. They not only work as piles holding the mechanical load of the building, but also as underground heat exchangers which extract heat from or inject heat into the ground. Although a standard framework for energy pile design has been produced by the Ground Source Heat Pump Association (GSHPA) in the UK, further work is needed to help engineers make design decisions about thermal behaviors, and especially for energy piles. The next section will illustrate the background and methodology to analyze the data from the Lambeth College and Shell Centre projects, which could assist in the wider application of energy piles.
###### Abstract  
Olfactory self-assessments have been analyzed with often negative but also positive conclusions about their usefulness as a surrogate for sensory olfactory testing. Patients with nasal polyposis have been highlighted as a well-predisposed group for reliable self-assessment. In a prospective cohort of \(n=156\) nasal polyposis patients, olfactory threshold, odor discrimination, and odor identification were tested using the \"Sniffin' Sticks\" test battery, along with self-assessments of olfactory acuity on a numerical rating scale with seven named items or on a 10-point scale with only the extremes named. Apparent highly significant correlations in the complete cohort proved to reflect the group differences in olfactory diagnoses of anosmia (\(n=65\)), hyposmia (\(n=74\)), and normosmia (\(n=17\)), more than the true correlations of self-ratings with olfactory test results, which were mostly very weak. The olfactory self-ratings correlated with a quality of life score, however, only weakly. By contrast, olfactory self-ratings proved as informative in assigning the categorical olfactory diagnosis. Using an olfactory diagnostic instrument, which consists of a mapping rule of two numerical rating scales of one's olfactory function to the olfactory functional diagnosis based on the \"Sniffin' Sticks\" clinical test battery, the diagnoses of anosmia, hyposmia, or normosmia could be derived from the self-ratings at a satisfactorily balanced accuracy of about 80%. It remains to be seen whether this approach of translating self-assessments into olfactory diagnoses of anosmia, hyposmia, and normosmia can be generalized to other clinical cohorts in which olfaction plays a role. data science; olfaction; patients; human subjects; clinical research +
Footnote †: journal: Medical  
The assessment of olfactory self-ratings in terms of their correspondence to the tested olfactory function was mostly moderate rather than enthusiastic. For example, we recently published an analysis of a large cohort of \(n=6049\) subjects comparing self-assessments with the results of a 12-item odor identification test, with the conclusion that asking the patient about olfactory function can at best provide a rough diagnosis of anosmia versus normosmia that cannot be relied upon [20]. Similarly, an analysis of \(n=211\) subjects from the general population of Taiwan came to the result that most subjects did not rate their olfactory function well and measured olfactory function and self-ratings correlated only weakly [7]. This seems to be partly rooted in the fact that many individuals in the general population are not aware of their own olfactory status [23; 24]. High correlations have been reported twice and independently for patients with nasal polyposis [1; 21]. This raised the question of whether they constitute a special group that is particularly aware of their olfactory function. In the present study, a cohort of patients
# Research on Shear Behavior of Sand-Structure Interface Based on Monotonic and Cyclic Tests
## Materials and Experimental Process
### Experimental Programs  
The relative density, vertical confinement pressure and interface roughness of the sand samples for the interface shear test are listed in Table 2.  
Two series of tests were conducted in this study, one was the monotonic shear test of sand-steel interface, which considered the influence of factors such as normal stress, interface roughness, and relative density of sand on the test. In the shear test studies of sand conducted by [PERSON] [30], [PERSON] [31] and [PERSON] [32] and many other researchers, the shear rate was 0.2-1.2 mm/min. In order to ensure the stability and reliability of the test data, this test controlled the shear rate at 0.3 mm/min and stopped the test when the fixed shearing displacement had reached 10 mm. The other was the cyclic shear test of sand-steel interface considering the initial shear stress. This is to ensure the consistency and reliability of the comparison between results of static and dynamic tests. Therefore, the shear rate of the cyclic shear tests was also controlled at 0.3 mm/min. The initial shear stresses were set to 30%, 60%, and 90% of the peak shear stress, and then unloaded so that each set of tests were cycled 10 times.