esa-sceva/satcom-chunk-collection huggingface dataset:
There is also a constantly growing interest among researchers in the possibility of using NIRS in monitoring changes in muscle oxygenation and blood flow during physiological and pathological conditions, e.g., during submaximal and maximum exercise [13; 20; 21; 22], to identify peripheral vascular disease [23], in chronic obstructive pulmonary disease (COPD) [24], in cardiovascular diseases [25] and in sepsis [26]. It has been found that during work the degree of deoxidation of skeletal muscles varies depending on the type of muscle, type of exercise and blood flow specific to a given area and health status [27; 28]. Only a few authors refer to the use of NIRS in physiotherapy as a method for assessing the impact of physical or kinesotherapy treatment or entire rehabilitation programs in therapeutic rehabilitation [3; 29; 30]. However, the lack of standard measurement procedures and reference data for region of interest (ROI) assessment is the main limitation of this technique, which is often highlighted by researchers [12]. It has not yet been assessed whether different body areas are characterized by the same or different values of rSO\({}_{2}\) at rest. Also, there is no established measurement site, which can lead to different values for variables when different muscles are used. Significant regional variations in rSO\({}_{2}\) values seem very likely to be due to natural differences in the morphological characteristics of each individual tissue (thickness, structure and optical properties through which NIR radiation potentially must penetrate), as well as microcirculatory properties, functions and metabolic states. Understanding the differences in regional oxygen saturation in healthy young people under physiological conditions is crucial for the subsequent assessment of changes in saturation in different areas, both in detecting abnormal/pathological situations as well as in assessing the progress of treatment and rehabilitation in relation to a specific area of the body. Many therapeutic effects of rehabilitation are based on the stimulation of microcirculation and tissue metabolism, which means trophic effects in tissue regeneration. Currently, especially in physiotherapy practice, the assessment of this effect is often based on the patient's subjective assessment. It seems that NIRS will allow for an objective assessment of therapeutic effects in this aspect, but for these purposes it is necessary to know the specific physiological differences in regional saturation in healthy people. Therefore, the main goal of this pilot study was to determine reference values of regional oxygen saturation (rSO\({}_{2}\)) for 18 selected body areas under physiological conditions in healthy young people aged 18-30 and to determine possible variations in their values depending on the body area, gender and age (compared to elderly people over 60 years of age). Additionally, the symmetry of rSO\({}_{2}\) values in opposite areas of the body in individual subjects was also assessed.
# Response of NDVI and SIF to Meteorological Drought in the Yellow River Basin from 2001 to 2020
## 2 Materials and Methods
### Datasets  
#### 2.2.1 MODIS Dataset  
This study used the MOD13A2 NDVI dataset from the Terra satellite from 2001 to 2020 ([[https://earthdata.nasa.gov/](https://earthdata.nasa.gov/)]([https://earthdata.nasa.gov/](https://earthdata.nasa.gov/)), accessed on 10 June 2021). MOD13A2 is synthesized every 16 days, and the spatial resolution is 1 km. The remote sensing data are synthesized into monthly values by using the maximum value composite method (MVC). NDVI values range from \(-\)1 to 1, and negative values indicate that the ground is covered by clouds, water, snow, etc. Due to the influence of aerosols, field of view, clouds, solar altitude angle, and other conditions, MOD13A2 NDVI remote sensing image contains mutation points and noise, consequently Savitzky Golay (S-G) filtering method is used to reduce or eliminate this influence [34]. In order to be consistent with the resolution of GOSIF, the NDVI is resampled to 0.05\({}^{\circ}\) using the nearest neighbor method.
# Multi-Angle Fast Neural Tangent Kernel Classifier
## 4 Experimental Setup
### Multi-Kernel-NTK and Other Multi-Kernel Models  
We use the HMPSO algorithm to select various parameters in the multi-kernel-NTK model. The particle length in the HMPSO algorithm is set to 40, where the first 20 particles constitute the penalty parameter C of the support vector model, taking values in the range \(2^{-8}\leq C\leq 2^{10}\). The remaining particles are the kernel function selection particles, denoted as \([r_{1},r_{2},\cdots,r_{20}]\), where \(r_{i}\) takes values of 1 or 0, representing whether the corresponding kernel is selected or not, respectively.  
The features of Boolean type in the original dataset are extracted and trained using the Monotone Disjunctive Kernel. At the same time, the data are saved in binary to improve the computational efficiency further. The NTK kernel function is used to construct a four-dimensional GRAM matrix based on the remaining features, and the two are combined and brought into the SVM training.  
For the NTK-Boolean and POLY-Boolean models, we choose linear combinatorial synthetic multi-kernel models, while for the RBF-Boolean model, we choose 20 alternative basis kernels, which are constructed by a multiscale multi-kernel learning method, with the kernel parameters obtained by exponential growth, taking values. The range is \(\sigma_{i}=2^{i}\sigma,1=0,1,2,\cdots\)  
We compare our proposed model with well-known models such as RF and Adaboost and perform statistical hypothesis testing and present the results in the \"Discussion\" section (Section 6). In the support vector machine training using NTK, a two-dimensional symmetric matrix is reconstructed from a four-dimensional tensor using the index as a Gram matrix in a general sense and involved in the computation, and the computational flow of our proposed primary model: NTK-Boolean model is shown in Figure 1.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Kernel** & **Para.1** & **Range** & **Para.2** & **Range** & **Para.3** & **Range** \\ \hline Poly & C & 0.001,..., 1024 & Coef0 & 0.02,..., 2 & degree & 1, 2, 3 \\ Rbf & C & 0.001,..., 1024 & gamma & 0.1,..., 50 & & \\ MDK & C & 0.004,..., 1024 & d & 0.003,..., 32 & & \\ NTK & C & 0.004,..., 128 & dep & 1,..., 13 & fix & 0,..., 12 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Support vector model parameter settings.  
Relevant experiments were designed and completed to visualize the experimental results and discuss the accuracy ranking among the models and the acceleration achieved by our approach.
# A Reliable Routing Algorithm Based on Path Satisfaction in the Energy Internet
## 2 Related Work
### Routing Algorithms in the Communication Network
It was performed in the 60-node Routing Protocol for low power and lossy network (RPL). In particular, certain critical links may become congested when the working path switches to a pre-allocated alternate route in the case of failure occurrence. Authors in [21] provide a reliable multi-path route selection strategy based on the evidence theory, which computes a reliable score of the route incorporating trust parameters. The first preference route is selected according to the reliable score, and the second preference is given to the length of the route, which can be widely used in the Internet of Things Networks (IOTN). Authors in [22] proposed constrained routing algorithms considering end-to-end latency, cost, and balanced network risks in the smart grid communication network. However, these static routing algorithms focus on finding appropriate routing paths for services in terms of optimal objectives and current network conditions, which lack flexible adjustments in network resource utilization, especially in dynamic network situations. Due to different data exchange mechanisms and network modes between the IP layer and the transmission layer [23; 24], it is not easy to accomplish coordinative control and management operations for services in a distributed heterogeneous network.
###### Abstract  
An observation system integrating satellite images, in situ water parameters and hydrodynamic measurements was implemented in a tidal inlet of the Venice Lagoon (Northern Adriatic Sea, Italy). The experimental infrastructure was developed to autonomously investigate suspended sediment dynamics in the two channels of the Lido inlet in relation to the longshore currents in the littoral zone and the tidal circulation along the lagoon channel network. It provided time series of turbidity at the surface, water flow and acoustic backscatter, which was converted into turbidity along the vertical column during different tidal phases and meteo-marine conditions. Accurate turbidity maps were derived from Sentinel-2 (Copernicus) and Landsat 8 (NASA) satellites. Long-term in situ data from field surveys enabled the calibration and intercalibration of the instrumental setup and validation of satellite-derived products. Time series from the instrumental network were analyzed in order to evaluate the temporal variability of suspended sediment in relation to tidal phases and the different meteo-marine conditions. The integration of available datasets with satellite images also permitted the testing of the methodology for a 3-D reconstruction of the suspended sediment pattern in calm sea conditions, under the effect of the sole hydrodynamical forcing. Remotely sensed data provide a synoptic distribution of turbidity in the inlet area allowing the analysis of the surficial patterns of suspended sediment and the inferring of information on the transport processes at different spatial scales. In calm sea conditions, the results show that the transport is driven by tidal currents with a net seaward transport related to a larger export of materials from the northern basin of the Lagoon of Venice. During typical northeasterly storms, materials mobilized on the beaches and in the shortage are transported into the inlet and distributed into the lagoon channel network, following the flood tidal currents and determining net import of materials. The multitude of information provided by this system can support research on aquatic science (_i.e._, numerical simulations) and address end-user community practices. The ecosystem management will also benefit operational purposes, such as the monitoring of morphological transformations, erosion processes and planning of coastal defense in the future scenarios of sea level rise. The developed approach will also help to understand how the regulation of the inlet flow introduced by the operation of the flood barriers will affect the fluxes of particles and, in the long term, the lagoon morphodynamics.  
remote sensing; sediment transport; turbidity; tidal inlets +
Footnote †: journal: remote sensing
# Biologically-Inspired Learning and Adaptation of Self-Evolving Control for Networked Mobile Robots
## 3 Application to Self-Evolving Control of Networked Mobile Robots
### Leader-Follower Formation Control of Networked Mobile Robots  
The leader-follower model is the main trend of networked mobile robotics, where a leader robot and several follower robots are included in a multi-robot system [32]. For networked mobile robots, formation control is an important topic that the leader robot tracks the desired trajectory while the follower robots maintain the formation shape. Figure 8 depicts a leader-follower networked mobile robotic system to achieve triangular formation control with three robots.  
In this paper, all mobile robots are independently controlled by using Equation (17) to accomplish leader-follower formation control, and the control parameters are self-tuned via the GA-KF-RBFNN paradigm. Compared to traditional consensus multiple robot systems with directed graph topology, the proposed broadcast leader-follower networked mobile robot system circumvents the delay problem. The position and orientation of the robots are broadcasted via the network. To maintain the desired formation shape, the geometrical relationship of the leader robot and follower robots in Figure 7 is calculated. Since the data flow is broadcasted online to every robot, the communication delay issues that occur in the consensus multiple robot system are therefore avoided. The proposed GA-KF-RBFNN self-evolving formation control for networked mobile robots not only reduces the system noises, but also avoids the communication delay.  
Figure 7: Block diagram of the GA-KF-RBFNN redundant control scheme for mobile robot.
# IoT-Driven Intelligent Scheduling Solution for Industrial Sewing Based on Real-RCPSP Model
## 3 IoT in Industrial Garment Production and Real-Time Data Collection Methods
### Synchronize Data from the Cloud Server to the Enterprise's MIS System  
The IoT device and service provider's cloud server system can aggregate and generate reports to support the monitoring of device operations in the factory. However, these reports are often simple and statistical. As a result, managers often need help to grasp detailed production information in real time. To overcome this issue, enterprises often extract data stored on the cloud server and store it in the database of their enterprise MIS system. The MIS system is a system that enterprises have deployed separately to serve their management tasks, including detailed information on human resources, resources, costs, warehousing, contract management information, human resources management, and data on the performance of previous contracts. Therefore, integrating MIS data with data obtained from the cloud server enables enterprises to create comprehensive and in-depth reports that meet the specific needs of managers.  
To facilitate the transfer of data from the cloud server to the enterprise MIS, it is necessary to establish a robust data synchronization system and design appropriate data structures for efficient storage. This ensures that all accessed data can be fully and seamlessly integrated and utilized. Figure 2 illustrates the entire process, from data retrieval from the cloud server to data storage in the enterprise MIS.  
_The specific steps are as follows:_  
Step 1: From the enterprise's information management system, connect to the IoT device provider's cloud server system through application programming interfaces (API). This  
Figure 2: Synchronizing data from cloud server to the MIS.  
connection must be authenticated with a security account issued by the service provider to the business using the IoT device.  
Step 2: Retrieve data stored on the cloud server. API methods are used to query data from the cloud server according to the business's wishes and when the data are generated.  
Step 3: Store the collected data in the MIS system database (on the enterprise's server). Retrieved data can be classified, encrypted, or authorized to use data according to the specific wishes of the business.  
Step 4: The system will synthesize information and display reports according to business management requirements.  
To ensure continuity and uniformity of the synchronization process, the enterprise server has set up processes or automatically synchronizes data over time. This process must be performed carefully and under control to ensure the accuracy and reliability of data synchronization between the two servers.
# Augmented MIMO: Body-Mounted Antennas for Tiny Wearable Devices
## 6 Discussion
### On-Body Antenna Locations and Isolation from Body  
In the experiment, the FPC antennas were located at the shoulders. This antenna location is reasonable to avoid the shadowing effect by the user's body itself and other furniture, assuming the access point is to be installed at a high position, such as near the ceiling, in daily indoor use cases. From this point of view, it is preferable to place the antenna close to the head.  
On the other hand, for safety reasons, it is preferable to avoid RF radiation around the head [25]. In terms of the actual power radiated from the antennas, the antenna system implemented in clothing is completely passive and lossy; therefore, the power radiated from the shoulder antennas is less than that of the original watch antenna. However, safety, especially the user's sense of security, depends not only on the absolute power but also on the factor of how close the radiating element is to the head. With regard to this factor, the Augmented MIMO scheme has a degree of freedom to choose antenna locations preferred by the users.  
Thus, the appropriate antenna location on the clothing depends on the application and the user and is controversial; therefore, future research on this aspect is required; for example, psychophysical experiments with a large number of subjects.  
Even for antennas away from the head, the backward radiation to the human body, causing safety issues and the degradation of antenna efficiency, is a common problem for wearable antennas. Reducing these unwanted effects by metamaterials is a promising approach [26], and extensive future research is expected.
## 4 Comprehensive Review
### A Comprehensive Overview of Bioactive Compounds in Different Food Drying Systems
#### 4.1.5 Cold Plasma
[96] is the only study that presents energy consumption values for both the plasma reactor and the convective dryer, reporting ranges from 15 to 60 kJ for the reactor and from 934.29 to 565.02 kJ for the dryer. Other studies, such as [PERSON] et al. [101; 102], provide only the total energy consumption of the drying process with and without cold plasma pretreatments. [PERSON] et al. [101] reported an energy consumption ranging from 2.25 to 4.18 kWh for the tray dryer and from 2.48 to 9.87 kWh for the vacuum dryer. In turn, [PERSON] et al. [102] reported values between 0.063 and 0.105 kWh for microwave drying. Energy consumption is an important parameter for assessing the operational costs associated with the use of cold plasma reactors and, consequently, for determining the feasibility of their application. In addition to the scarcity of energy consumption data, there is a notable lack of technical information regarding plasma reactors. Often, only the operating conditions (power, frequency, and time) are described, without detailed structural or electrical specifications. Regarding the effects of cold plasma on foods, several studies mention physical and chemical modifications; however, only [PERSON] et al. [96] directly investigated chemical transformations. They reported an increase in crocin and picrocroccin contents in saffron (Crocus sativus) following treatments, which was attributed to plasma-induced reactions. Thus, cold plasma as a drying pretreatment emerges as a promising strategy for preserving or even enhancing the content of bioactive compounds in dehydrated foods. Nevertheless, further studies are needed to elucidate the underlying chemical mechanisms and to advance reactor design, aiming at the development of larger-scale equipment suitable for industrial adoption.
# Bridging User Perception and Stickiness in Business Microblog Contacts: A Moderated Mediation Model
## 1 Introduction
Accordingly, an interesting question arises: Does emotional connection mediate the relationship between user perceptions and customer stickiness? In addition, a firm's superior performance depends upon the appropriate alignment of its strategic actions with different situations [17]. Based on this logic, this study proposes the use of adaptivity (system), which enables corporations to adjust themselves for users through obtaining information and facilitating suitable modifications to the user interface [18]. Adaptivity allows firms with microblogs to effectively and efficiently customize messages that more precisely match products to customer needs, thereby resulting in customer satisfaction and stickiness [19]. Therefore, another interesting question arises: Does adaptivity affect the mediating effect of emotional connection within the microblogs? Put differently, is the relationship between user perceptions and stickiness through emotional connection contingent on adaptivity? This study views these enterprise microblogs as a type of virtual brand community in which corporations disseminate brief messages and offer platforms for individuals to communicate, share information and experiences, and interact with other members. This study extends the existing literature in two respects. First, whereas previous studies have typically examined either the moderating or the mediating effects in the microblog context [4; 6], this study empirically tests the relationships which incorporate both moderation and mediation into a single model. The current study illustrates how emotional connection mediates the relationship between user perception and customer stickiness, and how the mediating process varies as a result of the functionality of adaptivity. Second, this study contributes to the online human behavior theory by showing how emotional connection plays a crucial mediating role by creating a sense of belonging and mutual history, thus creating customer value in the virtual group of the microblog. The paper further discusses the use of adaptivity to generate different mediating processes, which emphasizes the requirement for customized messages to fit customer needs and deliver more valuable information for users. Here are brief highlights of our contribution:  
* This study proposes that emotional connection mediates the link between user perception and customer stickiness. * This study develops the moderated mediation model to argue that the mediating effect of emotional connection relies on the adaptively system. The remainder of this paper is organized as follows. Section 2 presents the literature review and develops the research hypotheses, as guided by the theoretical model. Section 3 addresses the research methods. Section 4 reports the results. Finally, Section 5 concludes the study.
## 4 Results and Discussion
### Evaluation
#### 4.2.4 Representation of Food Shipments and Storage  
Representing food shipments was one of the core features for demonstrating the food supply chain. As described in Section 3.4, the raw material system and product storage services represent the storage. Food shipments were simulated, and the representations of raw material and food product shipments were handled internally as JSON messages. The relevant information was included in the shipment messages. Listing 1 provides an example of the representations of the raw materials in the system. Each shipment has an ID number and metrics describing its properties relevant to the food supply chain use case.  
```
{ \"id\":\"283d61 bf-fafd-465a-a525-ca43b27c4 cbe\", \"amount\":359, \"batch4\":\"7552b60a-6413-4d2d-82b5-e3d2255 ae4b6\", \"metrics\": { \"temperature\":5, \"acidValue\":2.2132, \"somaticCells\":344558 }, \"type\":\"milk\" }
```  
Listing 1: JSON representation of raw material.