esa-sceva/satcom-chunk-collection huggingface dataset:
# Design and Implementation of a Digital Twin System for Log Rotary Cutting Optimization
## 2 Materials and Methods  
### Five-Dimensional Model  
The process of rotary cutting of logs includes operations such as log centering, log debarking, and veneer peeling. The procedure involves locating the optimal clamping point through the log-centering process, removing outer waste materials through the log debarker, and ultimately processing them into veneers using the veneer peeling machine. The equipment involved in each step of the log rotary cutting process includes the log centering machine, log debarker, and veneer peeling machine. In response to the low level of intelligence and poor log utilization in log rotary cutting equipment, this paper proposesa digital twin system for log rotary cutting based on the five-dimensional model of digital twins (M\({}_{\text{DT}}\)) [14], as shown in (1). The system design is illustrated in Figure 1, consisting of five components: the physical entity (PE) of the log rotary cutting system, the virtual entity (VE) of the log rotary cutting system, the digital twin data (DD) generated by the integration of the physical entity and services, the service system (SS) that supports cutting analysis and simulation, and the connection of data (CN) and information between the components. The digital twin data includes the physical data of the log rotary cutting system during actual operation, data collected by sensors, virtual data generated by the log rotary cutting system model during simulation, and service data generated by the service system.  
\[\text{M}_{\text{DT}}=(\text{PE},\text{VE},\text{SS},\text{DD},\text{CN}) \tag{1}\]  
This paper aims to establish a digital twin system for log peeling optimization. By obtaining log point cloud information, it can independently confirm the optimal log peeling plan and conduct simulation verification of the log peeling plan in the twin space.
# Auto-Encoder Learning-Based UAV Communications for Livestock Management
## 2 System Model and Problem Formulation  
Reliable communication among UAVs monitoring livestock is critical for efficient and accurate data transmission for managing large herds. Figure 2 portrays a typical high-speed local architecture network constructed over long-distance WiFi access points to establish communication with UAVs and the ground control stations used for cattle and sheep rearing. The UAVs are equipped with onboard cameras and sensors used for taking images of herds and territorial surveillance. Information about the locations of animals is exchanged between the UAVs and the ground control station (GCS), which could be monitored manually or remotely by a human operator.  
Throughout this section, we assume a known perfect channel state information (CSI) between the UAVs and the GCS. The communication links between the UAVs and the GCS can be viewed as a simple communications system consisting of a transmitter, a channel and a receiver. Suppose the UAV wants to send one out of \(M\) possible messages \(s\in\mathbb{M}=\{1,2,\cdots,M\}\) to another UAV or GCS through a wireless fading channel. Then the received message is modelled as  
\[y=hx+n_{0} \tag{1}\]  
Figure 2: Communications network architecture of UAV-based livestock management system.  
where \(x,h\) and \(n\) are the message. The complex baseband message is converted to its equivalent real format using the transformation \(f:\mathbb{M}\rightarrow\mathbb{R}^{2n}\) to the message \(s\) to generate the transmitted signal \(x=f(s)\in\mathbb{R}^{2n}\). It should be noted that the UAV imposes some constraints on the \(x\) based on either average energy or average power of the transmitted message as follows [30]  
\[\|\mathbf{x}\|_{2}^{2}\leq 2n, \tag{2}\]  
\[\mathbb{E}[|x_{i}|^{2}]\leq 1. \tag{3}\]  
For simplicity, we use Quadrature phase shift keying (QPSK) and 8-phase shift keying (8 PSK) modulation schemes because of their abilities to transmit two bits and three per symbol, respectively. As an illustration, for QPSK, the transmitted symbols \(s\in\mathbb{M}=\{\frac{1}{\sqrt{2}}\pm j\frac{1}{\sqrt{2}},-\frac{1}{\sqrt{2}} \pm j\frac{1}{\sqrt{2}}\}\). Compared to ordinary phase shift keying (PSK), QPSK conveys twice as much information using the same bandwidth [31]. The rate at which the message is sent over a communications channel, known as the communication rate, is given by  
\[R=\frac{k}{n}\left[\text{bit/channel}\right], \tag{4}\]  
where \(k=\log_{2}{(M)}\) and \(M\) is the number of symbols or modulation index. Intuitively, (4) shows that the communication system transmits one out of \(M=2^{k}\) messages through \(n\) active channels or channel uses. This is usually presented by the notation \((n,k)\)[32].
# DPSIR Model Applied to the Remediation of Contaminated Sites. A Case Study: Mar Piccolo of Taranto
## 7 Impacts
### Eutrophication of Toxic Algae  
One of the main issues worldwide caused by anthropogenic inputs is eutrophication, especially in areas with limited water exchange [72], salt marshes, and lagoons [73].  
The comparison with a 20-year dataset revealed a drastic decrease in nutrient concentrations after the year 2000, validating the functionality of the treatment plants discharging into Mar Piccolo basin. The reduction in nutrient inputs (up to \(-90\%\) in the first inlet) changed the biogeochemical characteristics of Mar Piccolo from being relatively eutrophic to moderately oligotrophic [74].  
Phytoplankton dynamics were investigated by [PERSON] et al. [75] concerning environmental parameters, with particular reference to harmful algal blooms (HABs). They found that the relocation of the main urban sewage outfalls had positive effects on the environment, reducing sewage detritus and nutrient loadings by 25% and increasing the Mar Piccolo water transparency.  
A recovery of shallow water _phytoenthos_ occurred [76]. Seagrasses, for instance, are indicators of good environmental status. It was observed that the phytoplankton composition changed, with nano-sized species, indicators of oligotrophic conditions, becoming dominant over micro-sized species. However, even though phytoplankton dynamics were affected by the closure of the sewage outfalls, it did not preserve the Mar Piccolo from HABs and anoxia crises. They also detected about 25 harmful species throughout the years, such as the potentially domoic acid producers, _Pseudo-nitzschia_ cf. _galaxiae_, and _Pseudo-nitzschia_ cf. _multistriata_[77].
## 4 Formulating the Expression of the Total Number of Transmissions and Receptions  
Compared with the mainstream algorithms [15; 20; 21], the proposed scheme CS-DDSG reduces the number of transmissions and receptions rather than the number of fusions. In this section, we formulate the total number of transmissions \(\mathbf{N}_{\mathbf{T}\mathbf{t}\mathbf{t}}\) and receptions \(\mathbf{N}_{\mathbf{R}\mathbf{t}\mathbf{t}}\) based on the random geometric graph (RGG) mode [26] and the torus convention [27] to investigate the efficiency in reducing \(\mathbf{N}_{\mathbf{T}\mathbf{t}\mathbf{t}}\) and \(\mathbf{N}_{\mathbf{R}\mathbf{t}\mathbf{t}}\).  
According to Section 3, \(\mathbf{N}_{\mathbf{T}\mathbf{t}\mathbf{t}}\) and \(\mathbf{N}_{\mathbf{R}\mathbf{t}\mathbf{t}}\) can be expressed as follows:  
\[\begin{split}\mathbf{N}_{\mathbf{T}\mathbf{t}\mathbf{t}}&=\mathbf{N}_{ \mathbf{t}}^{P}+\mathbf{N}_{\mathbf{t}}=\mathbf{N}_{\mathbf{s}}+\sum_{q=1}^{\mathbf{N}_{\mathbf{t}}}\mathbf{N}_{ \mathbf{t}}^{q}\\ \mathbf{N}_{\mathbf{R}\mathbf{t}\mathbf{t}}&=\mathbf{N}_{\mathbf{r}}^{P}+\mathbf{N }_{\mathbf{r}}=\mathbf{N}_{\mathbf{r}}^{P}+\sum_{q=1}^{\\(N_{t}^{q}\) and \(N_{r}^{q}\) represent the number of transmitting and receiving nodes in the \(q\)th forwarding of Stage 3, respectively. \(N_{f}\) denotes the number of forwarding iterations. In Stage 2, \(N_{s}\) nodes are selected to broadcast, thus \(N_{t}^{P}=N_{s}\). Because the receiving nodes in Stage 3 forward their packet with the probability \(p_{2}\), \(N_{r}^{q-1}\) and \(N_{t}^{q}\) satisfy the following:  
\[N_{t}^{q}=N_{r}^{q-1}.p_{2}. \tag{22}\]  
When \(N_{t}^{q*}=N_{r}^{q*-1}.p_{2}\leq 0\), no node forwards packets and the forwarding process is completed. Thus, \(N_{f}=q^{*}-1\), \(N_{t}=\sum_{q=1}^{\overline{N_{f}}}N_{t}^{q},N_{r}=\sum_{q=1}^{N_{f}}N_{r}^{q}\). Additionally, \(N_{r}^{0}=N_{r}^{P}\) and \(N_{t}^{0}=N_{s}\). Next, we formulate the expression of \(N_{r}^{P}\), \(N_{t}^{q}\) and \(N_{r}^{q}\).
# River Discharge and Saltwater Intrusion Level Study of Yangtze River Estuary, China
## 3 Results
### Influences of the River Discharges on the Four Reservoirs in the YRE
It was found that when it was 18,112 m\({}^{3}\)/s, the river discharge started to exert influences on the water intake at the Dongfeng Xisha Reservoir resulting in the longest successive time that exceeded 0.45% and reached 196 h, with the total excess time correspondingly increasing to 614 h. It was also determined that when the discharge was 16,331 m\({}^{3}\)/s, the increasing longest successive time exceeded 0.45% at the Dongfeng Xisha Reservoir and reached 204 h, which was more than that at the Chenhang (175 h) and Baogang (203 h) Reservoirs. The impacts of the river discharges on the increasing time exceeding 0.45% at the Dongfeng Xisha Reservoir was greater than at the other reservoirs. The salinities at the four reservoir locations exceeded the drinking water standard for more than 23 days in the 14,832 m\({}^{3}\)/s river discharge scenario, and had major negative effects on the water intake in the YRE. Figure 12: The salinity changes of four freshwater reservoirs in different river discharge: (**1**) Dongfengxisha; (**2**) Baogang; (**3**) Chenhang; (**4**) Qingcaosha. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Discharge (m\({}^{3}\)/s)** & **Dongfengxisha** & **Baogang** & **Chenhang** & **Qingcaosha** \\ \hline
18,112 & 177.08\% & 61.42\% & 62.41\% & 58.91\% \\
16,331 & 216.50\% & 91.51\% & 92.33\% & 88.27\% \\
14,832 & 256.77\% & 123.99\% & 124.50\% & 121.36\% \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Monthly mean salinity increasing percentage in different river discharge.
## 2 Materials and Methods
### Data Analysis  
Diversity indices such as species richness (\(S\)), [PERSON]'s diversity index (\(H^{\prime}\)), and [PERSON]'s evenness (\(J^{\prime}\)) of the epibenthic communities were calculated from the beam trawl samples. The \(N_{90}\) index is based on the SIMPER analysis that quantifies the contribution of each species to the within-group similarity in a group of samples based on the Bray-Curtis similarity index [47; 48]. \(N_{90}\) represents the number of species that contributes up to 90% to within-group similarity in SIMPER analysis and has been calculated following the procedure described in [PERSON] et al. [49]. The samples were grouped according to the four sampled areas (Non-impacted, Low effort history, Medium effort history and High effort).  
For each area (level of fishing effort), we calculated the mean values, with their standard errors, of the standardized abundance and biomass of the whole epibenthic communities, their main taxonomic groups, and the diversity indices mentioned above.  
Based on the rhodoliths measures explained in Section 2.3, two morphological variables were calculated:  
* Size: longest axis of each rhodolith.
* Roundness (\(R\)): used as a proxy of the sphericity of rhodoliths. Results measured range from 0 (elongated shape) to 1 (circle shape). It was calculated as follows: \[R=4\times\frac{[area]}{\pi[longest\ axis]^{2}}.\] (1)  
The mean values of standardized biomass, size, and roundness, with their standard errors, of \(L\). _valens_, \(S\). _fruticulous_, and _P. calcareum_ were calculated in each of the four areas considered.  
A multivariate composed multidimensional scaling (MDS) analysis was applied to standardized abundances of species of beam trawl samples with PRIMER 7 [50]. This analysis allows for linking multivariate environmental patterns to the MDS based on species composition of samples. For multivariate analysis, data were square-root transformed and the similarity between samples was calculated using the Bray-Curtis index. The explanatory variables considered were, depth, slope, backscatter, and orientation of the seafloor, as well as horizontal and vertical components of velocity currents in the bottom and the velocity module. The characteristics of sediments have not been included in the model because sediment samples associated to each beam trawl sample were not available. The environmental variables represented on the MDS were selected to maximize the Spearman rank correlation between species composition and environmental patterns with the BEST routine in PRIMER 7 [50]. For environmental data, similarity between samples was calculated using the Euclidian distance.  
Student's \(t\)-test was applied to test for differences in abundances and biomass of main taxonomic groups and diversity indices of the epibenthic assemblages in these areas, as well as to compare biomass, size, and roundness of the three species of rhodoliths considered and their coverage. Prior to the use of the \(t\)-test, the Shapiro-Wilk test was applied to check for normality. When this assumption was not met, a Kruskal-Wallis non-parametric test was applied.
# MAC Protocols for mmWave Communication: A Comparative Survey +
## 1 Introduction
* In this survey, we investigated the current trends of different directional and non-directional MAC protocols, which have a strong potential for improving mmWave communication systems. * We compared the existing surveys chronologically according to their publishing dates, identifying the research focus areas over the years, which is presented in Section 2. * We classified all mmWave spectrum operating MAC protocols based on their methodologies into standard centralized and distributed protocols, which is illustrated in Figure 1.  
Figure 1: Structural classification of MAC protocols. * In this survey, we further investigated all the protocols and pointed out their scopes, limitations, and advantages. We summarize the centralized protocols and the distributed protocols in Sections 4 and 5, respectively. * We also identified the challenges regarding the design methodologies for the MAC protocols and pointed out the future research directions in the MAC layer domain of mmWave communication systems. * Although there are a few surveys in the field of mmWave MAC issues, none of them have organized all available protocols with detailed review and classified them into standard categories, stating their descriptive advantages and disadvantages. Moreover, we noted the probable implementations for respective protocols in the comparative analysis table.
## 2 Related Work
### Real-Time POI Recommendation  
Real-time POI recommendation is different from traditional POI recommendation in that it pays more attention to the user's possible real-time needs and preferences at a given time. The location recommendation model (LRT) [21] demonstrates its ability to improve the performance of the POI recommendation by learning the user behavior through the temporal patterns of check-in records and introduces four temporal aggregation strategies to integrate the user's check-in preferences for different time states. The real-time preference-mining (RTPM) model [22] uses the LSTM to mine the real-time preferences from the user's long-term and short-term preferences. For long-term preferences, the RTPM analyzes the cyclical trend of the user behavior between weeks. For short-term preferences, trainable time-shift vectors are introduced to model the user's publicly influenced preferences at the current time. The Timestamp Cross-Attention Network (TSCAN) model [23] uses a two-layer cross-attention network to predict the most relevant next POIs by focusing on the cross-over information between the timestamps through a timestamp cross-attention module; secondly, a cross-interval-aware module adjusts the POI sequences by using the time intervals to enhance the similarity of the neighboring POIs. The exploring user's preferences and real-time demand simultaneously (DSPR) model [24] utilizes various types of contextual information, including the absolute time, POI-POI transition time, and POI type, combined with user preferences, which are further modeled and automatically learned by an attention-based recurrent neural network model to support the final next-POI recommendation. However, these POI recommendation methods do not fully exploit the spatial correlation features and ignore the fact that users have different choices between different regions and different categories of POIs. Therefore, we propose a real-time POI recommendation model (AST-PG) that fully captures both the spatial and real-time information of the POIs, aiming to achieve better recommendation results.
## 2 Materials and Methods  
### Theory  
The AIEs can be described as a mass-damper-spring system. In Figure 1a this is described by the stiffness \(k\), the viscous damping \(c\) and the moving part of the element as mass \(m\). The equation of motion for this context is given by Equation (1). For vibration investigation, the motion in time domain \(x(t)\) is described by a sinus with phase shift \(\varphi_{0}\), shown with its derivatives \(\dot{x}(t)\) and \(\ddot{x}(t)\) in Equation (2). Vibration testing applies forced displacement controlled vibration and analyzes the response of the structure. Different excitation types can be chosen, among others, stepped-sinusoidal, slow sine sweep, periodic, random and transient excitation are common [26].  
\[F(t)=k\cdot x(t)+c\cdot\dot{x}(t)+m\cdot\ddot{x}(t) \tag{1}\]  
Figure 1: (**a**) mechanical model of a mass-damper-spring system; (**b**) mass separated into \(m_{sensor}\) and \(m_{testobj}\).  
\[x(t)=\hat{x}\cdot sin(\omega t+\varphi_{0});\] \[\dot{x}(t)=\hat{x}\omega\cdot cos(\omega t+\varphi_{0}); \tag{2}\] \[\ddot{x}(t)=-\hat{x}\omega^{2}\cdot sin(\omega t+\varphi_{0})\]  
According to [PERSON] [26], vibration testing can be separated into two types of vibration measurement: \"those in which just one parameter is measured (usually a response level), and those in which both input and response output are measured\" [26]. The frequency response function (FRF) is used to characterize the behavior of a dynamic system, it describes the input-output relationship in the frequency domain. From a mechanical point of view, the relationship between force \(F\) and displacement \(x\) is relevant, for static testing this relation describes the stiffness of the system. Furthermore, the FRFs of the derivatives of displacement velocity \(\dot{x}\) and acceleration \(\dot{x}\) are of technical relevance [26]. The measurement acceleration is most commonly used in vibration testing [2]. These FRFs are defined as apparent mass (AM), mechanical impedance (MI) and apparent stiffness (AS) and are the inverse values of accelerance (AC), mobility (MO) and receptance (RE) [27].  
\[AM(\omega)=F(\omega)/\ddot{x}(\omega); \tag{3}\] \[MI(\omega)=F(\omega)/\dot{x}(\omega);\] \[AS(\omega)=F(\omega)/\dot{x}(\omega)\]  
\[AM(\omega)=1/\textit{AC}(\omega);\] \[MI(\omega)=1/\textit{MO}(\omega); \tag{4}\] \[AS(\omega)=1/\textit{RE}(\omega)\]  
\[AM(\omega)=MI/i\omega;\] \[MI(\omega)=AS/i\omega \tag{5}\]  
Depending on the dominating mechanical properties, the respective FRFs have their advantages in representing and analyzing the behavior. The representation of the complex quantities in magnitude and phase is typical. Between the FRFs there is a phase shift of \(\pi/2\) between AM and MI and as well between MI and AS.
## 3 User Clustering and Power Allocation Co-Design  
In application, to achieve the overall energy efficiency maximization in the systems, the BS will schedule the subchannel assignment and power allocation to each user before the downlink NOMA transmission, i.e., solve the energy efficiency maximization problem formulated in (6). However, problem (6) is a mixed-integer nonlinear programming problem, which is NP-hard [43]. Though the optimal result can be found by an exhaustive search of all possible user clustering and power allocation, it is computationally complex and unacceptable in existing systems.  
The intractability justifies the development of suboptimal solutions. To break down the original optimal problem into several steps, we first investigate user clustering and put forward a pairing-assignment strategy to group users into clusters with a very low computational complexity. After user clustering, the target problem is formulated as a Lagrangian multiplier based dynamic programming model for obtaining the optimal allocation of the energy. Combining with the Lagrangian multiplier method, the dynamic programming techniques can generate the power allocation's optimal schedule.
## 5 Decentralization of VANETs  
### Threshold Encryption  
The utilization of threshold encryption has significantly altered the management of cryptographic keys. This is crucial in VANET. The idea behind this strategy is to divide a secret key into numerous pieces, each of which is in the possession of a different person. One important feature of this method is that, to reconstruct the original key, a threshold of shares must be met. For example, let's assume that each Participant \(i\) holds a public and private key share \((pk,sk_{i})\). Collectively, they yield a combined public and private key pair \((pk,sk)\) that is generated from each of their separate keys in a threshold version \((k,n)\) in which no single user is aware of the entire secret key \(sk\). In this method, at least two of \(k\) users are required to decrypt the ciphertext. The confidentiality of participant information can be preserved by doing data analysis under encryption thanks to homomorphic encryption techniques like ElGamal or Paillier encryption [57; 58; 59; 60]. Hence, the security is increased by breaking the key into several pieces because the compromise of one piece does not compromise the system as a whole. In distributed network setups such as VANETs, where trust and security are critical, this approach greatly enhances these features. The following papers (refer to Table 2) investigate several strategies and frameworks to improve security in VANETs through the utilization of threshold encryption, and distributed trust management systems.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Paper** & **Main Idea** \\ \hline \multirow{6}{*}{WDC2023 [61]} & Introduces a decentralized trust management framework for VANETs to mitigate the impact of malicious vehicles and compromised RSUs. The framework incorporates a process of beneficial oversight, encompassing trust assessment, decision-making, and a vehicle appeal system. The model’s efficacy in detecting malicious vehicles is confirmed through comprehensive simulations, even in situations when RSUs are not reliable. \\ \cline{1-1}  & \\ \cline{1-1}  & \\ \cline{1-1}  & \\ \hline \hline \end{tabular}
\end{table}
Table 2: A summary of threshold homomorphic encryption schemes for VANETs.