esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Proposed PMSM-SCS Based on DTC Strategy
### PMSM-SCS Based on Variable-Flux DTC Strategy
#### 2.2.1 SMC-Type Controller for PMSM-SCS Based on DTC Strategy Using Variable Flux  
Equations (1)-(4) are rewritten in the following form [41]:  
\[\begin{pmatrix}\dot{i}_{d}\\ \dot{i}_{q}\\ \dot{\omega}\end{pmatrix}=\begin{pmatrix}-\dfrac{R_{s}}{L}&n_{P}\omega&0\\ -n_{P}\omega&-\dfrac{R_{s}}{L}&-\dfrac{n_{P}\lambda_{0}}{L}\\ 0&\dfrac{K_{t}}{J}&-\dfrac{B}{J}\end{pmatrix}\begin{pmatrix}i_{d}\\ i_{q}\\ \omega\end{pmatrix}+\begin{pmatrix}\dfrac{u_{d}}{L}\\ \dfrac{u_{q}}{L}\\ -\dfrac{T_{L}}{J}\end{pmatrix} \tag{33}\]  
to synthesise an SMC-type controller for PMSM control, the state variables \(x_{1}\) and \(x_{2}\) are selected and described by the following equations:  
\[x_{1}=\omega_{ref}-\omega \tag{34}\]  
where \(x_{1}\)--speed tracking error.  
\[x_{2}=\dot{x}_{1}=\dfrac{\omega_{ref}-\omega}{dt}=-\dot{\omega} \tag{35}\]  
The sliding surface \(S\) of the zero error variation is defined in Equation (36), and by deriving this equation we can obtain Equation (37).  
\[S=cx_{1}+x_{2} \tag{36}\]  
\[\dot{S}=cx_{2}+\dot{x}_{2}=cx_{2}-D\dot{i}_{q} \tag{37}\]  
where the parameter \(c\) is positive and adjustable, and \(D=\frac{3n_{P}\lambda_{0}}{2J}\) is obtained from the Equations (1)-(3).  
Equation (38) shows the condition for the surface \(S\) time evolution; this condition ensures the control of the response time of the PMSM-SCS based on DTC strategy.  
\[\dot{S}=-\varepsilon\text{sgn}(S)-qS,\ \ \ \varepsilon,q>0 \tag{38}\]  
where the parameters \(\varepsilon\) and \(q\) are positive and the _signum_ function is noted with _sgn_().  
The above _sgn_ function is replaced by the _signoid_ function defined in Equation (29), and this is used in the synthesis of the SMC-type controller in order to reduce the chattering  
Figure 3: Schema of the proposed PMSM-SCS based on the DTC strategy using SMC and FOSMC controllers with variable flux.  
phenomenon characteristic of the structure of this type of controller. From the above equations, according to SMC specific methods, the next equation can be written as  
\[i_{qref}(t)=\frac{1}{D}\int\limits_{0}^{t}{[cx_{2}+\varepsilon H(S)+qS]dt} \tag{39}\]  
From Equations (9)-(11), the following custom equations can be obtained for the reference values of the electromagnetic torque, the reference current \(i_{qref}\) and the reference value of the stator flux in the usual case, where \(L_{d}=L_{q}\):  
\[i_{qref}=\frac{T_{ref}}{1.5n_{p}\lambda_{0}} \tag{40}\]  
\[\psi_{ref}=\lambda_{0}^{2}+\left(\frac{L_{q}T_{ref}}{1.5n_{p}\lambda_{0}} \right)^{2} \tag{41}\]  
The stability property of the PMSM-SCS based on DTC strategy using the control law expressed through Equation (39) is demonstrated by selecting a Lyapunov function of the following form:  
\[V=\frac{1}{2}S^{2} \tag{42}\]  
The following expression is obtained by calculating the derivative \(\dot{V}\):  
\[\dot{V}=S\dot{S}=S[-\varepsilon H(S)-qS]=-\varepsilon H(S)-qS^{2} \tag{43}\]  
The stability property of the system is given by the negativity of the derivative \(\dot{V}\).
## 4 Optimal Tuning of Damping Controllers
### Controller Structure  
The excitation current of the DFIG is AC, and the output decoupling of active power and reactive power can be realized by changing the magnitude and phase of the excitation current.  
The DFIG basically does not respond to the low-frequency oscillation of a power system. To involve the DFIG in suppressing the power system oscillation, the design of the additional damping controller should be based on the PSS of the synchronous generator. The specific additional damping control strategy using the conventional PSS control structure is shown in Figure 4. It consists of a stabilizer gain \(K\), a washout filter with time constant, and two-phase compensator blocks with time constants \(T_{1}\), \(T_{2}\), \(T_{3}\), and \(T_{4}\). The selection of these control parameters will directly affect the working effect of the PSS. The additional signal forms a closed loop with the feedback signal and the additional damping signal is adjusted according to the system power oscillation, so that the DFIG increases the damping torque component and thereby suppresses the power oscillation.
## 2 Materials and Methods  
### Dentine Sample Preparation  
In an in vitro study, 120 bovine dentine slabs were submitted to the erosive demineralization challenge twice a day for a total period of 15 days. The dentine samples were prepared from bovine incisors. Dental crowns were separated from the roots using a double-sided diamond disc in low-speed rotation. The vestibular dentine surfaces were ground flat with water-cooled abrasive discs (120, 400, 600--Buelher, Lake Bluff, IL, USA) and then placed in a metallographic cutter (LabCut--Extec Corp., Enfield, CT, USA) for obtaining the dentine slabs (4 \(\times\) 4 \(\times\) 2 mm). The samples were individually immersed for 20 min in a solution of 80 mL of citric acid (citric acid monohydrate--C\({}_{6}\)H\({}_{8}\)O\({}_{7}\).H\({}_{2}\)O; M: 210.14 g\(\cdot\)mol\({}^{-1}\); pH: 2.3; 0.05 M) and washed by distilled water for 15 s at the end of each cycling. After 10 days, visual lesions were observed on dentine specimens. Samples were randomly distributed into eight groups and submitted to treatments, as described in Table 1.  
Samples from groups F, FL1, FL2, and FL3 received topical application of sodium fluoride 2% (GEL Flutop Neutral--[PERSON], Rio de Janeiro, RJ, Brazil) for four minutes, followed by distilled water baths for 10 s, and then dried with absorbent paper. Samples from FL1, FL2, and FL3 were submitted to laser irradiation after fluoride application.  
Dentine specimens of laser-treated groups (L1, L2, L3, FL1, FL2, and FL3) were irradiated using a Nd:YAG laser device (Power Laser TM ST6, Lares Research(r), Chico, CA, USA) operating at wavelength of 1.064 um and temporal width of 120 us. The irradiation parameters of each laser  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Group** & **Treatment** & **Power (W)** & **Energy (mJ)** & **Energy Density (J-cm\({}^{-2}\))** \\ \hline C (n = 15) & Control & - & - & - \\ F (n = 15) & Fluoride & - & - & - \\ L1 (n = 15) & Laser irradiation & 1 & 100 & 79.5 \\ L2 (n = 15) & Laser irradiation & 0.7 & 70 & 55.7 \\ L3 (n = 15) & Laser irradiation & 0.5 & 50 & 39.7 \\ FL1 (n = 15) & Fluoride + Laser irradiation & 1 & 100 & 79.5 \\ FL2 (n = 15) & Fluoride + Laser irradiation & 0.7 & 70 & 55.7 \\ FL3 (n = 15) & Fluoride + Laser irradiation & 0.5 & 50 & 39.7 \\ \hline \end{tabular}
\end{table}
Table 1: Experimental groups.  
group are described in Table 1. The slabs were irradiated in contact mode, scanning the surfaces by hand using a fibre optic system with 400 \(\upmu\)m of spot size. The energy per pulse was calibrated using an energy/power meter prior each irradiation. After receiving treatment, the samples were re-submitted to erosive cycles for five days.
## 4 BIMcontracts Approach  
### Conditions and Requirements  
The BIMcontracts approach is proposed for automated payment and contract management through blockchain-based smart contracts (see Figure 1). The main emphasis is on the combination of BIM with smart contracts and the developed software architecture. In the first step, the focus is, on the one hand, exclusively on the contractual relationships between an owner and a general contractor and on a general contractor and its subcontractor on the other hand. Since all other relevant contractual relationships can be considered similar with respect to the payment process, our findings can be generalized for future applications.  
The use of a smart contract does not imply the complete digitalization of the contractual relationship between the parties. The parties still conclude a classic paper-based construction contract with digital contract elements. This holds true regardless of whether the parties opt for the application of German law (BGB, VOB/B) or make use of internationally recognized contractual standards (especially FIDIC contracts [55]). The legal issues at hand remain fundamentally the same so that no further differentiation is required for this purpose. Furthermore, the appropriate adjustment of other elements of the contract is an important consideration, but is outside the scope of this paper. To make the smart contract algorithm legally binding, its use must be specified in advance in the paper-based contract. The digital counterpart of the contract is signed via uniquely identifiable blockchain identities.  
A prerequisite for the conclusion of the contract is the provision of digital BIM-based tender documents by the client or by the contractor. These documents are agreed upon between the contracting parties during the tendering procedure. The data relevant to the contract should be provided as a digital building model (BIM model) linked with materials, works, and cost in the form of a detailed BoQ using detailed Quantity Take-Offs (QTOs). This information can be understood as a part of a 5D BIM model and can be delivered as an information container.  
Figure 1: BIMcontracts framework.  
As already pointed out, it is not efficient to store all of the project-related data on the blockchain. The concept assumes the usage of a CDE in the construction project and treats it as off-chain storage, where it is possible to store any structured (e.g., BIM models, BoQ files) or unstructured (e.g., documents, photos) information. For secure and resource-efficient storage of the information in a blockchain, only checksums in the form of cryptographic hash values of the files stored in the CDE are used. The hash value of a file is generated based on all of the data of the file and the timestamp of the generation time. Once the confirmed file data are modified, a new hash value will be generated that differs from the confirmed hash value. This procedure secures the immutability of the project data stored in the CDE.
## 1 Introduction  
Automatic text summarization is a crucial task in natural language processing (NLP) that aims to condense the core information of a given corpus into a brief summary. With the exponential growth of textual data, including documents, articles, and news, automatic summarization has become increasingly important.  
Text summarization methods can be classified into two categories: extractive and abstractive. Extractive summarization selects the most important sentences from the original corpus based on statistical or linguistic features, whereas abstractive summarization generates a summary by semantically understanding the text and expressing it in a new way [1]. Abstractive summarization is more challenging than extractive summarization, but it is also considered superior, as it avoids the issues of coherence and consistency in the summaries generated with extractive methods.  
Deep learning has achieved state-of-the-art results in NLP, and more researchers have shifted their focus to abstractive summarization. The sequence-to-sequence (seq2 seq) model [2] combined with an attention mechanism has become a benchmark in abstractive summarization [3; 4; 5]. However, these methods require well-constructed datasets, which can be difficult and costly to build.  
In this paper, we propose a semi-supervised learning method for text summarization that treats summarization as a style transfer task. Our approach uses a transfer text-to-text transformer (T5) model as the text generator and trains it with loss functions from the cycle-consistent adversarial network (CycleGAN) for semantic transfer.  
The remainder of this paper is structured as follows. In Section 2, we review previous research related to our work. Section 3 describes our method of text summarization in detail. Section 4 presents the experimental results of our proposed model. In Section 5, we perform an extensive ablation study to validate the effectiveness of our model. Finally, we summarize our work in Section 6.
# Enhanced Joint and Separable Reversible Data Hiding in Encrypted Images with High Payload
## 4 The Proposed Separable Data Hiding System
### An Example of the Proposed Separable Data Hiding System  
To illustrate our proposed separable data hiding system, a simple example is included. Let \(I\) be the original image of size \(4\times 6\), as shown in Figure 7a. First, by using the encryption key, \(I\) is encrypted and encrypted image \(I^{\prime}\) is obtained, as demonstrated in Figure 7b. Then, the information bits can be embedded into \(I^{\prime}\) and it is considered that the four bits to be embedded are 1001, and after permutation the permuted bits are \(A=0110\). Let \(Q\) selected pixels be [186,189,160,183] that are marked with green in Figure 7b. The most significant bits of the pixels are collected and replaced with \(A=0110\). Thus, the embedded encrypted image is obtained, as shown in Figure 7c. In the separable method, we can extract the data from the embedded encrypted image. To extract the hidden bits, we need to collect \(Q\) pixels [58,189,160,55] and fetch the \(t=8\) th bit by using (14). Then, the extracted bits are permuted to get the original information. For image restoration, first the embedded encrypted image is decrypted. The directly decrypted image (Figure 7d) is similar to original except some pixels. Then, we collect the pixels [136,15,18,133] from the directly decrypted image. By setting the \(t\) th bit as 0 and 1, two possible values of each pixel are achieved. Let us consider two possible cases of the pixel 136, which are \(t=0\), \(D_{0}=8\) and \(t=1\), \(D_{1}=136\). The fluctuation of \(D_{0}\) and \(D_{1}\) is calculated from (15) and (16), respectively. After calculation, we get\(f_{0}=16\) and \(f_{1}=508\). As\(f_{0}<f_{1}\), then \(D_{0}=8\) will be the original pixel. Therefore, we will restore the original pixels and collect them to restore the original image, as demonstrate in Figure 7e.  
Figure 7: Example of the proposed separable data hiding system. (**a**) Original image; (**b**) encrypted image; (**c**) encrypted image containing information bits; (**d**) decrypted image containing information bits; and (**e**) recovered image.
## 4 Test Experiments and Discussion of DMMAEO
### Comparative Analysis Between DMMAEO and Other Algorithms
To summarize, in accordance with the aforementioned experimental results acquired by the compared algorithms, the D MMAEO exhibits better optimization performance in terms of convergence ability, exploitation ability, exploration ability, and balance ability between exploitation and exploration. Figure 4: Convergence curves for D MMAEO and several recent promising algorithms across 9 test functions.
# A Review of Air Pollution Monitoring Technology for Ports
## 3 Air Pollutant Monitoring Systems for Ports
### Ship Exhaust Monitoring
In the spring and summer seasons, when a northerly wind prevails and when the wind blows from the ocean to the land, it is possible to effectively monitor the emission of ship exhaust from the port terminal by placing the telescope horizontally and collecting the signal of the light directly passing through the ship exhaust and using the measured spectrum in the direction of the sun's zenith angle as the reference spectrum, as shown in Figure 3.  
Additionally, in recent years, in the face of ship exhaust monitoring on the waterway, in addition to this fixed-point monitoring equipment, UAVs (Unmanned Aerial Vehicles) have been gradually applied to ship exhaust monitoring because of their high flexibility and maneuverability. These UAV monitoring systems mainly consist of rotary-wing drones, sniffing sensor modules, flight controllers, and rapid screening systems for ship emissions [52]. They monitor the content of air pollutants in ship exhaust gas through the exhaust gas plume entering the ship and can transmit data through 4G or 5G networks and monitor real-time data through cloud platforms. [PERSON] et al. [53] developed a new multi-UAV collaborative path planning model for ship air pollution detection in dynamic  
Figure 3: MAX-DOAS monitoring of ship emissions (Reproduced from [51] under the terms and conditions of a CC-BY copyright license agreement). environments. Aiming at the uncertainty brought by the ship's dynamic position, this model uses different UAVs to detect different numbers of ships and proposes a multi-UAV cooperative detection strategy with lower detection cost and higher detection efficiency. Through this method, it is possible to remotely monitor in real-time whether the ships entering the port comply with the emission standards, and it is possible to cooperate with the monitoring equipment at the terminal to achieve comprehensive online monitoring of the port.
# Study of the Impact of PV-Thermal and Nanofluids on the Desalination Process by Flashing
## 1 Introduction
Another objective of the reported developed mathematical model was to calculate the productivity of the system under different operating conditions. A mathematical model for a multi-stage flash (MSF) desalination system with brine recirculation (BR) configuration was developed and presented by the authors of [13]. They described the heat source chosen for the BR-MSF as a nanofluid-based direct absorption solar collector (DASC), for which the numerical model was developed. Both systems, BR-MSF and DASC were coupled via a countercurrent flow heat exchanger. The overall performance of the combined system was determined in terms of gained output ratio, referred to as GOR. The conceptual design for a photovoltaic thermal (PV/T) solar panel has been developed and analyzed to control the inherent temperature increase of PV cells in order to increase electrical efficiency [14; 15; 16; 17]. A hybrid solar panel was developed and presented by [PERSON] et al. [1] and [PERSON] [16; 17] to integrate photovoltaic (PV) cells onto a substrate through a functionally graded material (FGM) with water tubes cast inside, through which water serves as both heat sink and solar heat collector. In addition to the above literature review, it is evident that very limited research work has been published on the use of nanofluids in the desalination process, as well as the use of multi-stage flashing (MSF) chamber process modeling and simulation of sea water brine. Thermal and membrane desalination studies have been focused on evaporation processes using steam. The novel concept for the MSF presented in this paper implements PV-thermal solar panels using a hot heat transfer fluid with nanofluids in the MSF process. The main objective of this paper was to present a mathematical and numerical modeling on the use of nanofluids and a PV-thermal solar system to power the multi-stage flashing chamber thermal process. The model proposed was established after the mass and energy conservation equations of the flashing process were integrated with the thermal and thermophysical properties of the vapor and nanofluids at different volume fractions as well as solar radiation levels. The nanofluids studied were Ai2O3, CuO, Fe3O4, and SiO2 at different volume fractions. The process of multi-stage flashing using PV-thermal solar panels and nanofluids was analyzed under different conditions of sea water (brine) salt concentration, brine flows, and temperatures, as well as nanofluid concentrations and solar radiation levels.
# Ensuring the Long-Term Preservation of and Access to the Italian Federated Electronic Health Record
## 2 Background
### The FSE Infrastructure  
The need to create a national federated EHR infrastructure in Italy derives from the autonomy in healthcare matters that Italian regions have, which has allowed them, over time, to create their own EHR systems, which need to be maintained (considering the effort for their implementation and their consolidated use at a regional level) and to make them interoperable. The FSE architecture is based on a federated model, which focuses on the cooperation of local nodes. Specifically, it is based on a system of systems approach, where each regional system has to expose a set of specific services, which provide all the functionalities needed to manage, search, and consult data and documents regarding the patient and produced by different healthcare facilities. This national architectural model aims at enabling interoperability among different regional systems and allowing the exchange of clinical data and documents among them, thanks to the already mentioned INI (Figure 1). In this scenario, the first need is permitting users to locate clinical information that can be distributed on all national territory, i.e., patients' clinical documents and data can be archived in different information systems of different regions. This makes the retrieval task quite problematic. The simplest solution would have been to query all the regional registries, but it would lead to an all-time high in search, which could be fatal for the whole system. Therefore, the chosen approach for FSE lies in the identification, in each regional domain, of a node in charge of managing all the meta-information about a patient. Specifically, the region in which the patient resides (RDA) is liable to manage meta-information associated with his/her clinical documents, even if they are produced in another regional domain. Thus, in order to consult a document located outside a regional domain, it is first necessary to identify such a region and then to interrogate its regional system for locating the specific healthcare facility in which the document is stored.  
Figure 1: FSE architectural framework and interoperability services.  
This solution is peculiar to the Italian context so its success could be determined only if evaluated in that frame; nonetheless, it could be also considered in the light of the recent study by [PERSON] et al. (2013) which reviews EHR implementations across different healthcare contexts, by evidencing key factors which impact on their success.