esa-sceva/satcom-chunk-collection huggingface dataset:
# Adaptive Energy Balanced Routing Strategy for Wireless Reschargeable Sensor Networks
###### Abstract  
The network lifetime of wireless rechargeable sensor network (WRSN) is commonly extended through routing strategy or wireless charging technology. In this paper, we propose an optimization algorithm from the aspects of both charging and routing process. To balance the network energy in charging part, node's charging efficiency is balanced by dynamically planning charging point positions and the charging time is allocated according to the energy consumption rate of nodes. Moreover, the routing method is adapted to the node's charging efficiency. The adaptive routing strategy assigns more forwarding tasks to nodes that can get more energy during the charging phase, and makes the data packets transmit farther away, thus reducing the average hops and energy consumption of the network. Finally, the simulation results reveal that the proposed algorithm has certain advantages in prolonging the network lifetime, reducing the average hop counts and balancing the energy of each node.  
wireless rechargeable sensor networks; energy balance; charging strategy; adaptive routing strategy +
Footnote †: journal: Applied
# The Impact of Information Systems Implementation in the Greek Manufacturing Enterprises
## 4 Results and Discussion
### General Characteristics
#### 4.1.1 Information Systems (ISs) and Future Investment  
Although 83 companies stated that they use at least one IS, one company did not specify which system/systems she uses. The responses of those 82 companies regarding the IS they have implemented are presented in Figure 2. It is noted that the percentages in this figure sum up to much more than 100 percent because most companies use more than one system. A great majority (85.4%) of the companies use the ERP system and the percentages for CRM, OMS, and WMS range between 35.4% and 39%. One third of the companies (32.9%) use only one system, of whom 88.9% use ERP. In addition, 68.3% of the respondents use a combination of not more than three systems combined. It is worth mentioning that only a small number of companies use SCM (13.4%) in order to conduct their business. As the competition shifts from individual firms to supply chains one could expect that SCM would be more in use in order to help manufacturers to successfully manage their supply chain.  
As it was also referenced in the research conducted by the authors in [34], there are similarities and differences in regards of IS adoption with the research that was conducted by authors in [30]. The percentage of the companies they use IS in the current study is almost 75% higher than the one in [30]. On the other hand, fewer companies use WMS, MRP, SCM, SRM and APS in the current research compared to those they use them in [30].  
Figure 1: Profile of the companies: Industry sector.  
Figure 2: Information systems that have been implemented.  
Although the great majority of the companies (90.4%) have invested in an IS in the last decade [34], 62.7% of them have declared that are eager to invest in a new IS in the prompt future. According to the authors in [20], research in Korean manufacturing firms that have already implemented a form of ERP most of the firms were in the process of implementing, planning, or considering to implement various extensions to their ERP system. Among them were CRM--greater percentage--SCM, APS as well as modules that would make easier to tie up their customers or suppliers to their ERP systems. That means that just because they already have a system they don't stop investing in additions that they will improve the way they conduct their business.
# No-Reference Quality Assessment of Transmitted Stereoscopic Videos Based on Human Visual System
## 3 Materials and Methods
### Proposed Method  
The assessment of the quality of a distorted 3D video is an important part of building and organizing advanced immersible media delivery platforms. As shown in Figure 3, our proposed QA method is implemented by extracting the binocular and perceptual features of a stereoscopic video, which are combined afterward to generate a QA Objective Metric (QAOM). At first, perceptual attributes were taken into account to estimate the binocular features that influence the quality of a stereoscopic video. A new video quality index based on two image/video features has been devised to evaluate the perceived quality of transmitted stereoscopic videos, with the extracted features accumulated according to the tube suppression theory. The disparity index was developed by taking into account similar aspects of stereoscopic film, as well as edge detection, which was used to assess binocular vision impairment and distortions due to packet loss in the network.
# On the Use of Structured Prior Models for Bayesian Compressive Sensing of Modulated Signals
## 2 Proposed Method
### Group Sparse Model for Modulated Signals  
#### 2.3.1 Related Works  
One way to build a structured model is by jointly estimating the elements that are assumed to share the same inherent structure. In particular, this is achieved in Block Sparse Bayesian learning framework by modeling elements sharing the same group with a multivariate Gaussian distribution [34]. The correlation within each block was also encouraged in [49]. This model has been successfully applied to CS reconstruction of bearing vibration signals [39]. The constructed model in the latter work takes advantage of bearing signals spectrum structure, where non-zero coefficients tend to appear in small groups, rather than isolated peaks.
## 3 Meta-Modeling Techniques for Surrogating NARX Model Coefficients
### PCE Meta-Model  
PCE is a weighted linear combination of orthogonal polynomial basis functions of input random variables [31] and has been widely used in many fields due to its solid mathematical foundation and good performance. For the \(d\)-dimensional input random variables \(\mathbf{\xi}=\left[\xi_{1},\xi_{2},\ldots,\xi_{d}\right]^{T}\in\mathbb{R}^{d}\), the single system output \(y\) can be expanded through polynomial chaos expansion as:  
\[y(\mathbf{\xi})=\sum_{i=0}^{D-1}\mathbf{C}_{i}\Phi^{(i)}(\mathbf{\xi})+\varepsilon \tag{21}\]  
where \(\Phi^{(i)}(\mathbf{\xi})\) is the \(i\)th orthogonal multivariate basis function composed of Winer-Askey polynomials; the terms number \(D=(d+r)!/(d!r!)\) with the PCE order \(r\); and \(\varepsilon\) is the truncation error. The coefficients \(\mathbf{c}=\left[\mathbf{c}_{0},\ c_{1},\ldots,\mathbf{c}_{D-1}\right]^{T}\) can be determined through least square regression as:  
\[\mathbf{c}=\big{(}\mathbf{A}^{\mathrm{T}}\mathbf{A}\big{)}^{-1}\mathbf{A}^{\mathrm{T}}\mathbf{Y} \tag{22}\]  
\[\mathbf{A}=\begin{bmatrix}\[PERSON]^{(0)}(\mathbf{\xi}_{1})&\[PERSON]^{(1)}(\mathbf{\xi}_{1})&\cdots &\[PERSON]^{(D-1)}(\mathbf{\xi}_{1})\\ \[PERSON]^{(0)}(\mathbf{\xi}_{2})&\[PERSON]^{(1)}(\mathbf{\xi}_{2})&\cdots&\[PERSON]^{(D-1)}(\mathbf{\xi} _{2})\\ \vdots&\vdots&\ddots&\vdots\\ \[PERSON]^{(0)}(\mathbf{\xi}_{N})&\[PERSON]^{(1)}(\mathbf{\xi}_{N})&\cdots&\[PERSON]^{(D-1)}(\mathbf{\xi} _{N})\end{bmatrix},\mathbf{Y}=\begin{bmatrix}Y(\mathbf{\xi}_{1})\\ Y(\mathbf{\xi}_{2})\\ \vdots\\ Y(\mathbf{\xi}_{N})\end{bmatrix} \tag{23}\]  
where \(\mathbf{A}\) is the matrix of orthonormal multivariate polynomials; \(\mathbf{Y}\) is the real value vector of the sample output; and \(N\) is the number of samples, which is suggested to be no less than twice the number of expansion terms \(D\). In this study, the MATLAB-based UQLab toolbox [32] is utilized to construct the PCE model for the NARX model coefficients obtained from the least square method. The orthogonal polynomials are chosen based on the distribution of input variables. When the system has multiple outputs under uncertain inputs, one PCE surrogate model needs to be constructed for each system output.
# Effect of Ultrasonic Treatment on Taste and Flavor Quality of Japonic Rice
## 3 Results
### Pasting Characteristics  
The results showed that ultrasound treatment reduced various viscosities of cooked rice samples during the pasting process (Table 1). As ultrasound time increased, the peak viscosity, trough viscosity, and final viscosity of the sample gradually decreased, reaching a minimum after 30 min treatment. Ultrasound treatment breaks branched starch and releases more linear starch. When the content of branched starch in the sample is higher, it is easier to form a paste, whereas when the content of linear starch is higher, it is more difficult to form a paste, so the viscosity decreases. The viscosity reduction in different varieties after ultrasound treatment varies. This phenomenon may be due to the different varieties of the ratio of amylose and amylopectin. The higher the content of branched starch, the more affected by ultrasound treatment, the more linear starch formed after ultrasound treatment [4]. At the same time, the regeneration value also decreased.  
This observation indicated that ultrasound treatment enhanced branched-chain starch decomposition and facilitated straight-chain starch depolymerization. The depolymerized straight-chain starch formed complexes with lipids, indicating that lipids were incorporated into the starch helices to form resistant starch. This complexation reduced the likelihood of lipid leaching from the helices, preventing the penetration of water into the starch grains. This finding showed that ultrasound treatment increased the resistant starch content in cooked rice and inhibited its pasty expansion and starch regeneration.
## 2 Materials and Methods
### Optical Glass Fibers  
Since FCSs are designed for reinforced concrete structures, the optical fibers inside FCSs have to withstand the highly alkaline concrete environment and still be fully capable of expected operations in terms of sensing and light guidance. Usually a fiber coating is applied in order to protect the optical silica glass fiber against impacts and thus to avoid mechanical degradation. However, when, for instance, the fiber is subjected to harsh environments, such as highly alkaline concrete environments, the fiber coating might be destroyed and thus the optical glass fiber might lose its mechanical stability. Therefore, commercially available optical fibers with different fiber coatings have been investigated in terms of their suitability to be applied for FCS applications. For the investigation, the Corning CC with acrylate coating (ClearCurve ZBL), the OFS Fitel Clearlite with polyimide (PI) (F21976) coating as well as the OFS GEOSIL with carbon/polyimide (C/PI) (BF06159) coating were chosen.
## 4 Analysis of Experimental Results  
### Simulation Experiment  
#### 4.1.1 Experimental Settings and Test Functions  
The experimental operating environment was made up of the Windows 10 64-bit operating system, an Intel(R) Core (TM) i5-7200U processor, 2.5 GHz main frequency, and 4.00 GB of RAM. The algorithm was created using MATLAB 2021a as a basis.  
Experiments were conducted on 12 benchmark functions in order to confirm the usefulness of the IGEO in solving diverse optimization challenges. Two continuous unimodal benchmark functions (F1 and F2) were used to assess the algorithm's speed and accuracy of convergence. To assess the algorithm's ability to perform a global search and the likelihood of leaving the local optimum, six complex multimodal benchmark functions (F3-F8) were utilized. The comprehensiveness of the approach was assessed using four fixed low-dimensional benchmark functions (F9-F12). Table 2 displays the specifications of the benchmarking functions.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Fun No.** & **Name** & **Equation** & **Features** & **D** & **Bounds** & **f*** \\ \hline F1 & Sphere & \(F_{1}(x)=\sum\limits_{i=1}^{n}x_{i}^{2}\) & Unimodal & 30 & \([-100,100]^{\text{D}}\) & 0 \\ F2 & Schwefel 2.22 & \(F_{2}(x)=\sum\limits_{i=1}^{n}x_{i}^{2}+\pi|x_{i}|\) & Unimodal & 30 & \([-10,10]^{\text{D}}\) & 0 \\ F3 & Griewank & \(F_{3}(x)=1+\sum\limits_{i=1}^{n-\frac{x_{i}^{2}}{4000}}-\sum\limits_{i=1}^{n} cos\left(\frac{x_{i}}{\sqrt{l}}\right)\) & Multimodal & 30 & \([-600,600]^{\text{D}}\) & 0 \\ F4 & Ackley1 & \(F_{4}(x)=-20e^{(-0.2\sqrt{\frac{1}{\kappa}\sum\limits_{i=1}^{n}x_{i}^{2}})}-e ^{(\sqrt{\frac{1}{\kappa}\sum\limits_{i=1}^{n}\cos(2\pi x_{i})})}+20+e\) & Multimodal & 30 & \([-32,32]^{\text{D}}\) & 0 \\ F5 & Periodic & \(F_{5}(x)=1+\sum\limits_{i=1}^{n}sin^{2}(x_{i})-0.1e^{(\sum\limits_{i=1}^{n}x_{ i}^{2})}\) & Multimodal & 30 & \([-50,50]^{\text{D}}\) & 0.9 \\ F6 & Rastrigin & \(F_{6}(x)=10n+\sum\limits_{i=1}^{n}(x_{i}^{2}-10\cos(2\pi x_{i}))\) & Multimodal & 30 & \([-5.12,5.12]^{\text{D}}\) & 0 \\ F7 & Salomon & \(F_{7}(x)=1-cos\left(2\pi\sqrt{\sum\limits_{i=1}^{n}x_{i}^{2}}\right)+0.1\sqrt{ \sum\limits_{i=1}^{n}x_{i}^{2}}\) & Multimodal & 30 & \([-100,100]^{\text{D}}\) & 0 \\ F8 & Yang 4 & \(F_{8}(x)=\left(\sum\limits_{i=1}^{n}sin^{2}(x_{i})\right)e^{(-\sum\limits_{i=1 }^{n}sin^{2}\sqrt{|x_{i}|}
## 2 Materials and Methods  
### Plant Material and Experimental Design  
Seeds of _C. balansae_ (cba) and _C. striatus_ (cst) were hand harvested in the summer of 2014 from natural populations in central-west Spain. The strains cba and cst had been previously obtained from nodules of _C. balansae_ and _C. striatus_ plants in monospecific natural populations [29]. Strains were identified as _Bradyrhizobium_ isolates with the accession numbers AF461191 and AF461194 for cba and cst, respectively. The strains were maintained on yeast extract mannitol (YEM) agar [31] at 4 \({}^{\circ}\)C. For inoculation of seedlings, cultures were grown for 6 days in YEM broth at 26 \({}^{\circ}\)C in an orbital shaker at 100 rpm before dilution to the required concentration of cells.  
Seeds were hand scarified using an emery board. This treatment was followed by surface-sterilization in 70% ethanol for 5 min and 1% sodium hypochlorite for 3 min and then washed six times in sterile distilled water. Twenty-five seedlings per species were transplanted to 10-cm diameter pots containing sterile sand-river and were given the appropriate treatment (all seedlings were supplied with 25% Hoagland's solution--pH 5.8) [32], modified with either high P (500 \(\upmu\)M) or low P (5 \(\upmu\)M) as NaH\({}_{2}\)PO\({}_{4}\) 2H\({}_{2}\)O). Plants were maintained in a glasshouse at the University Pablo de Olavide (Seville, Spain) under natural light and temperature, with a 12-h photoperiod (24 \({}^{\circ}\)C day and 18 \({}^{\circ}\)C right) and a photon flux density at the top of the plants of approximately 700 \(\upmu\)mol \(\cdot\) m\({}^{-2}\cdot\) s\({}^{-1}\) for 22 weeks (February until July 2015). Pots with different treatments were randomly distributed on benches in the glass house, 1 m apart from any other treatment, to prevent cross contamination; a total of 25 replicates per combination of species and treatments were maintained.  
The control treatment consisted of un-inoculated Hoagland's solution from which nitrogenous compounds had been removed (\(-\)N\(-\)R). One of the treatments consisted of nitrogen-free Hoagland's solution and rhizobial inoculation (\(-\)N+R). A second treatment consisted of the application of 500 \(\upmu\)M NH\({}_{4}\)NO\({}_{3}\) as an N source with no rhizobial inoculation (\(+\)N\(-\)R). In the last experiment, plants received the same amount of NH\({}_{4}\)NO\({}_{3}\) as before and were simultaneously inoculated (\(+\)N+R). All treatments were subjected to both high and low P levels.  
Inoculation treatments consisted of growth phase broth-cultured inoculant at 1 \(\times\) 10\({}^{8}\) cells mL\({}^{-1}\). Each plant species was inoculated with 100 mL of its own rhizobia, _i.e._, cba (AF461191) and cst (AF461194). The surface of the pots was covered with sterile polyurethane beds and watering was conducted weekly through a watering pipe.
# Methods and Applications of Space Understanding in Indoor Environment--A Decade Survey
## 2 Review Methodology and Conduction
### Search Query and Data Sources  
The construction of a proper search query, used during the survey, was one of its most essential tasks. Overly vague phrases would overflow us with irrelevant publications, while too precise ones would result in an excessive restriction of the search results. For this survey, we proposed to use two groups of examples to build the search query: _'room [activity]'_ and _'floor plan [activity]'_. For the room group, there was a set of seven activities chosen: _'segmentation'_, _'classification'_, _'clustering'_, _'structure'_, _'detection'_, _'recognition'_ and _'labeling'_. For the floor plan group, the set contained only three activities: _'segmentation'_, _'clustering'_, and _'analysis'_. This way, we expected the returned results to provide a wide range of possible differentiated input data types (because of the room examples group) but with an additional focus on processing 2D images (because of the floor plan examples group). Adjusted search phrases were used within the advanced search engines of the selected databases as a single merged query. We searched six different databases of publications. They all collect numerous publications, are fully digital, and are available via web browsers. In many cases, they are also accessible to academic researchers free of charge via their institutions.  
The selected databases were as follows:  
* Association for Computing Machinery Digital Library (ACM DL),
* Institute of Electrical and Electronics Engineers Xplore (IEEE Explore),
* Digital Bibliography & Library Project (dblp),
* Scopus,
* Elsevier Science Direct (SD),
* Springer Link (SL).
## 2 Materials and Methods
### Spectra Collection  
Spectra were obtained in situ with a Micro-NIR OnSiteW (VIAVI, Santa Rosa, CA, USA), a portable device which collects diffuse reflectance spectra in the spectral range between 950-1650 nm, with a spectral resolution of 6.2 nm and equipped with an InGaAs photodiode array detector, equipped with a sapphire window of 18 mm with an aluminium enclosure for use in the field. Spectra were collected with 10 ms as the integration time and 100 as the scan count. Prior to spectra acquisition and to verify the spectrometer performance, a series of tests were undertaken. A white reference was built using Spectralon to register the total reflectance value and a dark reference (total absorbance) was recorded leaving the tungsten lamps on, with the empty support, also known as dark current scan.  
From each area of 0.1 m\({}^{2}\) five spectra were collected. Using the instrument software (MicroNIR\({}^{\text{TM}}\) Pro software, Version 3.1), the mean spectrum was calculated and exported as Log (1/R). During the development of the CP and NDF models, the important spectral regions were selected according to the weighted regression coefficients plot and the spectral range was limited to these wavelengths.
# Reliability-Based Optimization of Impeller Structure Using Exponential Function Approximation
## 4 Reliability-Based Optimization of an Impeller Structure
### Reliability-Based Optimization of the Impeller Structure
Notably, the failure probabilities obtained by all three optimization methods were less than \(10^{-4}\), satisfying the reliability constraint conditions; the LS method exhibited the smallest failure probability, indicating its superior ability to ensure structural reliability. The coefficients of variation for the IS, SS, and LS methods were 0.0292, 0.0965, and 0.0709, respectively, indicating that the computational accuracy of each method was within the acceptable range. In terms of computational efficiency, the IS, SS, and LS methods, respectively, required 4.7 \(\times\) 10\({}^{5}\), 2.0 \(\times\) 10\({}^{6}\), and 2.4 \(\times\) 10\({}^{4}\) iterations. Clearly, the proposed method exhibited significantly improved computational efficiency, requiring an order of magnitude fewer iterations than the conventional double-loop methods. The proposed method yields a failure probability lower than the target, which may suggest conservatism in the final design. This occurs because the first-order exponential approximation ensures strict satisfaction of the reliability constraint within each local optimization interval during the sequential optimization process. However, the objective function value of the proposed method, \(-\)2.1978, is only 1.4% higher, i.e., less optimal than the double-loop IS result, \(-\)2.2291, while achieving a 95% reduction in computational cost. Such a minor sacrifice in optimality is acceptable in engineering practice, given the drastic efficiency improvement.
# A Multicast Routing Scheme for the Internet: Simulation and Experimentation in Large-Scale Networks
## 3 The Greedy Compact Multicast Routing (GCMR) Scheme
### Examples
At the same time, node 2 sends type-R messages towards the upstream nodes, in such a way that upstream nodes can also start sending type-A messages to reconnect the MDT. In the example in Figure 4b, node 2 sends a type-R message only to the source which in turn sends type-A messages to its neighbours. In Figure 4c, the three disconnected leaf nodes \(D_{1}\), \(D_{2}\) and \(D_{3}\) are reached and they can join the new least cost branching path to node 2 and eventually releases the now unused edges previously part of the MDT. In the example, \(D_{3}\) receives three messages and compares the cost of the branching paths towards node 2: two paths have the same cost and the preference goes to the path that was received first (the oldest one), i.e., \(D_{3}\) keeps the path to node 5 which was already part of the MDT. On the contrary, node \(D_{1}\) needs to explicitly change the direction of the edge to node 7. Finally, node \(D_{2}\) keeps the same path. Figure 3: Creation of a branching path between a joining node and the MDT using global search: (**a**) local search fails to find a node of the MDT in \(B(J)\); (**b**) joining node \(J\) searching messages outside \(B(J)\); (**c**) nodes’ answers to the joining node; (**d**) node joins the MDT through the least cost branching path.
# Evaluation of 8-Channel Radiative Antenna Arrays for Human Head Imaging at 10.5 Tesla
## 4 Discussion
The SAR efficiency of the phantom/human model was 0.91/0.8 (13.8% drop) with the dipole antenna array, 1.2/0.83 (44.6% drop) with the monopole antenna array, and 1.18/1.05 (12.4% drop) with the sleeve antenna array. Due to the nonuniform distance from the antenna to the human subject, SAR efficiency can differ between a human model and a phantom. The field-generating'monopole' antenna parts of both the monopole and the sleeve antennas are expected to perform similarly; however, the classical monopole antenna is using a pronounced 'RF ground plane' as an electrical current mirror antenna element. This results in clear differences in E- and B-fields between the monopole and sleeve antenna arrays. The low peak 10 g SAR leads to the highest SAR efficiency of the sleeve antenna array (Figure 5f) over the ROI compared to the dipole (Figure 5d) and the monopole (Figure 5e) antenna arrays. The highest SAR efficiency in the human model is a particularly important advantage of the asymmetric sleeve antenna array concept compared to both dipole and monopole antenna arrays. The sleeve antenna array has an asymmetric structure that is configured with monopole antennas (i.e., 15 cm) and sleeves (i.e., 5 cm). E-fields of a sleeve antenna change depending on the size of the sleeve. For the sleeve antenna concept, we have the freedom to modify both the geometry of the sleeve parts and the monopole antenna parts. As shown in Supplementary Table S1 and Figure S1, without any decoupling circuitry, each 8-channel array produced acceptable decoupling values and noise covariance values to proceed with the imaging experiment. However, the coupling and noise covariance of the 8-channel sleeve antenna array (Supplementary Figure S1d) showed the lowest overall values compared to the 8-channel dipole (Supplementary Figure S1a,b) and monopole (Supplementary Figure S1c) antenna arrays. It is an additional advantage of the sleeve antenna concept.