esa-sceva/satcom-chunk-collection huggingface dataset:
# A New Integrated Multi-Criteria Decision-Making Model for Resilient Supplier Selection
## 7 Conclusions  
This study has integrated GRA-BWM-TOPSIS to propose a framework for resilient supplier selection. Generally, there has been a lack of attention on resilient supplier selection, particularly with the presence of uncertain and incomplete data. Among the existing MCDM models, the integration of GRA-BWM-TOPSIS is novel. To implement the proposed model, seven resilience criteria (Quality, Lead Time, Cost, Flexibility, Visibility, Responsiveness, and Financial Stability) were determined based on the literature review and SC requirements. Subsequently, the importance levels for all the criteria were determined, the resilience criteria weights were computed, the consistency test was carried out, the suppliers' performances were assessed and finally the supplier with the best performance was identified.  
There are several contributions of this study. Firstly, the application of the serial-integrated MCDM method which is GRA-BWM-TOPSIS in the area of resilient supplier selection is new and has not yet been investigated in the literature. Secondly, grey theory rather than fuzzy theory is used in this study to improve the reliability of the supplier assessment process with the consideration of uncertainties and incomplete data. In addition, this is the first time where the resilience criteria for supplier selection in the food manufacturing industry have been investigated. In addition, the proposed criteria are generic and can be applied to different types of economic, operational and natural risks or disruptions.  
Other than the contributions, there are also recommendations to be considered for future work. In this study, the proposed technique is a serial-integrated method. Further studies could be conducted with a different kind of integration of other methods [40] to select resilient suppliers. Next, the proposed technique has only been tested in the food manufacturing industry. In the future, the technique could be applied to select resilient suppliers in other industries. Furthermore, the proposed criteria set consists of only seven criteria and they may be varied depending on a company's policy. Future studies could explore more criteria for resilient supplier selection.  
W.Y.L.: Writing; methodology; data collection; reviewing; editing of manuscript. K.Y.W.: Writing; supervision; reviewing; editing of manuscript. W.P.W.: Reviewing; editing of manuscript. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors are grateful to Universiti Teknologi Malaysia (UTM) (Vote Number: 20H69).  
The authors declare no conflict of interest.
# Software Defined Networks in Wireless Sensor Architectures
## 5 Wireless Cellular Networks
### Wireless Cellular Networks Architecture  
Wireless Cellular Networks (WCN) are composed of phones and smart devices that are connected to the Internet through base stations that are installed on cellular towers. At the same time, base stations are classified as Serving Gateway and Packet data network Gateway. These gateways work as control plane and data plane entities. On one hand, the control plane includes mobile connection establishment, routing, mobility management, QoS [15] and Quality of Experience (QoE). On the other hand, the data plane is comprised of access control and traffic monitoring. Nevertheless, the close union of both planes opens resource management and scalability challenges in WCN.  
WCN architecture is comprised of several components; the main two components are RAN and Core Network (CN). RAN consists of close cellular towers that supply the access to user devices. Moreover, this technology offers functionality as resource allocation and essential management.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Reference** & **Proposal** & **OpenFlow** & **Data Aggregation** & **Management** & **Resource Allocation** \\ \hline
[13] & Sensor OpenFlow & & & & \\
[62] & Multitasking SDN & X & X & & \\
[65] & Explotation OpenFlow & & & & \\
[66] & SDNN & & X & & \\
[67] & SDN-WISE & & & & \\
[69] & Smart WSN & X & X & & \\ \hline \hline \end{tabular}
\end{table}
Table 2: Differences between Software Defined Sensor Networks (SDSNs).  
For its part, CN provides connectivity between different RANs and also services such as connection establishment and maintenance, among others.
# Antennas for Licensed Shared Access in 5G Communications with LTE Mid- and High-Band Coverage
## 2 A Planar Antenna for LSA Bands
### Antenna Configuration  
This printed antenna (Ant#1) is designed to operate in the 1452-1492 and 2300-2400 MHz LSA bands and its detailed geometry with top and bottom views is shown in Figure 1. The total area of the antenna is 40 mm \(\times\) 15 mm, or 0.18\(\lambda_{0}\)\(\times\) 0.07\(\lambda_{0}\), where \(\lambda_{0}\) is the free-space wavelength at 1.38 GHz. For the simulation, the antenna is assumed to be fed by an SMA connector at the bottom. To ensure isolation between the ground plane and the center pin of the SMA connector, a circular portion of copper with radius \(r\) is etched off from the ground plane, as shown in Figure 1b. The antenna is placed in the top-right corner of a mobile device substrate with dimensions of 120 mm \(\times\) 70 mm. A substrate commonly used in mobile devices is FR-4, with a relative permittivity (\(\epsilon_{r}\)) and loss tangent (\(\tan\delta\)) of 4.3 and 0.025, respectively. Its thickness is assumed to be 0.8 mm. The overall area of the ground plane is equal to the area of the substrate. A segment of copper with dimensions of 50 mm \(\times\) 11 mm is removed from the top-right corner of the ground plane, as shown in Figure 1b.  
The proposed antenna is composed of two elements: an L-shaped element to the left of the feed point (left element) to cover the 1.5 GHz LSA band and an L-shaped element to the right (right element) to cover the 2.3 GHz LSA band. CST Microwave Studio is used for the design and analyses of the antenna. The dimensions are optimized using a parameter analysis conducted in CST for good impedance matching.
## 2 Methods
### Glonass UPD Estimation Strategy  
The NL code and WL carrier phase observation can be defined as  
\[\begin{array}{l}P_{n,i}^{k}=\frac{f_{1}^{k}}{f_{1}^{k}+f_{2}^{k}}P_{1,i}^{k }+\frac{f_{2}^{k}}{f_{1}^{k}+f_{2}^{k}}P_{2,i}^{k}=\rho_{i}^{k}+\frac{\mu_{i}^ {k}}{f_{1}^{k}+f_{n,i}^{k}}+F_{n,i}^{k}+e_{w,i}^{k}\\ L_{w,i}^{k}=\frac{f_{1}^{k}}{f_{1}^{k}-f_{2}^{k}}L_{1,i}^{k}-\frac{f_{2}^{k}}{f _{1}^{k}-f_{2}^{k}}L_{2,i}^{k}  
\[\widetilde{N}_{w,i}^{k}=N_{w,i}^{k}+\phi_{w,i}-\widetilde{\phi}_{w}^{k}, \tag{7}\]  
where \(\widetilde{\phi}_{w}^{k}=\phi_{w}^{k}+H_{w}^{k}\). With this reformulation, we have eliminated the effect of the receiver WL IFCB, and GLONASS PPP ambiguity fixing can therefore be carried out in a straightforward manner. According to Equations (3) and (7), GLONASS un-differenced WL and NL UPDs can be generated with the strategy proposed in [7].
# A Subjective Study on User Perception Aspects in Virtual Reality
## 5 Conclusions  
In this paper, we first highlighted main QoE aspects, key factors affecting QoE of 360 video, and the related work. It is shown that currently studies on this area are still limited that motivates us carrying out this study. By means of subjective experiment and statistical analysis, we evaluated the impacts of multiple factors on four main QoE aspects of 360 video, namely, perceptual quality, presence, cybersickness, and acceptability. Experiment results showed that the perceptual quality aspect is significantly impacted by all the four considered factors of encoding parameters (i.e., QP and resolution), content motion, rendering device, and rendering mode. It is also found that there exist strong impacts of encoding parameters, content motion, and rendering device on the presence aspect. Regarding the cybersickness aspect, the impact of content motion is shown to be significant, while the impact of rendering device is trivial. With respect to the acceptability aspect, the encoding parameters and the rendering mode have considerable impacts, whereas the content motion and the rendering device do not. Also, the acceptability aspect is strongly impacted by the perceptual quality and presence aspects.  
For future work, we intend to build and evaluate QoE models of 360 video, which take into account the impacts of multiple factors, as well as QoE aspects. The findings in our study, as well as QoE models, in the future work are expected to be helpful to improve the QoE of video streaming services over Internet and VR applications for education and entertainment. In addition, we plan to study QoE aspects in a new context of VR gaming where QoE aspects such as presence is crucial for service providers.  
**Author Contributions:** Conceptualization, H.T.T.T. and T.C.T.; Data curation, N.P.N.; Formal analysis, H.T.T.T. and T.C.T.; Funding acquisition, T.C.T.; Investigation, N.P.N. and Y.J.J.; Methodology, H.T.T.T. and N.P.N.; Project administration, T.C.T.; Resources, N.P.N. and C.T.P.; Software, H.T.T.T. and C.T.P.; Supervision, Y.J.J. and T.C.T.; Validation, H.T.T.T., Y.J.J. and T.C.T.; Visualization, H.T.T.T.; Writing--original draft, H.T.T.T. and N.P.N.; Writing--review and editing, C.T.P., Y.J.J. and T.C.T.  
**Funding:** This work was supported in part by the Competitive Fund No. P-11 of the University of Aizu.  
**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
## 3 Results and Discussions
### Liver Biomarkers and Hepatocellular Injury Indicators
It has also been reported that powdered barley grass improved liver function and immunity, it has anti-inflammatory and anticancer inflammatory properties, it helps with weight loss, is hypolipidemic, and prevents cardiovascular disease. In addition, the authors of [67; 68] also stated that barley grass and sprouts have many health benefits, including hypoplipemic, hypoglycemic, anticancer, anti-inflammatory constipation prevention, antioxidant properties. [PERSON] et al. and [PERSON] et al. [69; 68] attributed the protective liver effect and the prevention of an inflammatory to saponarin, which occurs abundantly in barley sprouts. In Table 6, it is seen that the rats that were administrated tap water and mixed HMs recorded a significant increase in total bilirubin (TB), direct bilirubin (DB), and indirect bilirubin IDB levels. However, all of the treated rat groups (i.e., G3- 2 to G3-5) revealed a significant decline in the mean values of those parameters compared with the G2 and G3-1 groups. It was demonstrated that the wheatgrass extract exerted hepatoprotective mechanisms by improving insulin resistance and lipid metabolism, suggesting the probability of functional diets for improving liver health and overall metabolic syndrome [28]. [PERSON] et al. [70] indicated that a diet rich in phenolic contents could prevent oxidative stress by boosting antioxidant enzymes and reversing liver damage. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameters Groups** & **T.B (mg dL\({}^{-1}\))** & **D.B (mg dL\({}^{-1}\))** & **ID.B (mg dL\({}^{-1}\))** \\ \hline
**Control\({}^{-}\)** & 0.55 \(\pm\) 0.09 \({}^{\text{cd}}\) & 0.09 \(\pm\) 0.02 \({}^{\text{c}}\) & 0.46 \(\pm\) 0.08 \({}^{\text{bc}}\) \\
**Control\({}^{+}\)** & 0.85 \(\pm\) 0.10 \({}^{\text{ab}}\) & 0.18 \(\pm\) 0.02 \({}^{\text{b}}\) & 0.67 \(\pm\) 0.12 \({}^{\text{a}}\) \\
**G3-1** & 0.87 \(\pm\) 0.09 \({}^{\text{a}}\) & 0.22 \(\pm\) 0.02 \({}^{\text{a}}\) & 0.65 \(\pm\) 0.12 \({}^{\text{a}}\) \\
**G3-2** & 0.70 \(\pm\) 0.05 \({}^{\text{bc}}\) & 0.16 \(\pm\) 0.01 \({}^{\text{b}}\) & 0.53 \(\pm\) 0.04 \({}^{\text{ab}}\) \\
**G3-3** & 0.55 \(\pm\) 0.07 \({}^{\text{cd}}\) & 0.12 \(\pm\) 0.01 \({}^{\text{c}}\) & 0.43 \(\pm\) 0.06 \({}^{\text{bc}}\) \\
**G3-4** & 0.72 \(\pm\) 0.10 \({}^{\text{ab}}\) & 0.16 \(\pm\) 0.01 \({}^{\text{b}}\) & 0.56 \(\pm\) 0.10 \({}^{\text{ab}}\) \\
**G3-5** & 0.44 \(\pm\) 0.07 \({}^{\text{d}}\) & 0.11 \(\pm\) 0.02 \({}^{\text{c}}\) & 0.33 \(\pm\) 0.05 \({}^{\text{c}}\) \\ \hline \hline \end{tabular}  
* T.B—total bilirubin; D.B—direct bilirubin; ID.B—indirect bilirubin. The values with different letters in each column showed a significant difference.  
\end{table} 
Table 6: Effect of wheat and barley grass on changes in the total bilirubin, direct bilirubin, and indirect bilirubin of rats exposed to toxic metals (mean \(\pm\) SD).
# Research on Vibration Comfort of Non-Motorized Lane Riding Based on Three-Axis Acceleration
## 2 Analysis of Factors Affecting Riding Vibration Comfort
### Road Characteristics
#### 2.1.4 Influence of Road Surface on Ride Vibration Comfort  
The riding state on non-motorized roadways is primarily affected by the surface levelness. Potholes, manhole covers, and pavement-joint height differences can significantly alter longitudinal acceleration. Although urban road surfaces are generally level, manhole covers and joint differences have a substantial impact [29]. Consequently, this paper selects the number of manhole covers and pavement articulation protrusions as potential factors influencing riding vibration comfort.
# Dynamic Response Analysis of Soil around Curve Section Tunnel under Train Vibration Load
## 6 Conclusions  
In this paper, through the combination of field monitoring, numerical simulation and theoretical analysis, the dynamic response of the soil layer around the tunnel under the train vibration load is studied, and the conclusions are as follows:  
1. During the initial stage of train operation, the pore water pressure is relatively high. However, as time passes, the pore pressure gradually decreases. Overall, there is a seasonal trend, with the weather warming up in the second quarter, the temperature rising, and rainfall reducing, leading to a significant drop in water level and pore pressure. The rate of decrease in pore pressure and water level differs depending on the depth of burial, with deeper monitoring points showing smaller changes in rate, and shallower monitoring points showing larger changes in rate;
2. Under the action of train vibration load, the response of the soil surrounding the tunnel is closely related to the location, and the response becomes more sensitive the closer it is to the tunnel. After exceeding a certain depth range, the disturbance effect of train vibration on the soil gradually reduces and is more affected by changes in groundwater level and rainfall. The pore pressure in the soil is basically the same as the static water pressure at the same depth, and is proportional to the depth;
3. The trend of groundwater level change in the soil is basically consistent with the trend of pore pressure change, and the groundwater level is proportional to the depth;
4. Under the action of subway vibration load, the closer to the bottom of the tunnel the curves are, the greater the amplitude and rate of change of pore pressure, and the greater the vertical deformation. The vertical deformation response of the bottom soil of the small radius curve tunnel under the action of different train running speeds decreases with the increase in the distance from the tunnel and increases with the increase in the speed. The dynamic response of the soil at the bottom of the tunnel decreases with increasing depth and radius of curvature, and the main impact range of the dynamic response is 0-15 m below the bottom of the tunnel.  
The above research results can provide the basis for the safety evaluation of subway train operation in small radius curve sections.  
Conceptualization, L.S., J.Z. and X.W.; Methodology, L.S.; Software, W.Q.; Formal analysis, J.Z.; Resources, L.S.; Writing--original draft, W.Q., D.H. and X.W.; Supervision, J.Z. and X.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (No. 51309100), Science and Technology Project of Henan Province (No. 222102320135).  
Not applicable.  
The authors declare no conflict of interest.
## 2 Model and Formulations
### Band Structure of Infinite Systems
To more clearly figure out the changes, Figure 7 plots the change of the bandgaps for the various \(\gamma\). In the calculation, the parameter \(d\) remains unchanged, and the initial compression ratio \(\gamma\) is adjusted by changing the initial compression \(l_{c}\) of the spring \(k_{n}\). As can be seen in Figure 7, the effect of the parameter \(\gamma\) on the bandgaps is similar to that of the parameter \(\beta\). This phenomenon can be explained by Equation (5), which shows that parameters \(x\) and \(y\) have a similar effect on the equivalent stiffness of the QZS system. The reason for the disappearance of the first bandgap is the same as that revealed in Figure 5, which will not be repeated here. Figure 5: Effects of the stiffness ratio \(\beta\) on the bandgaps. The above parametric analysis shows that on the premise of ensuring that the static stiffness of the structure is not weakened and the mass load on the system is not increased, appropriately increasing the stiffness ratio \(\beta\) of the QZS system and the initial compression ratio \(\gamma\) of the negative stiffness spring are effective ways to obtain ultralow-frequency bandgaps.
# A Efficient and Accurate UAV Detection Method Based on YOLOv5s
This involves the adoption of efficient algorithms and techniques, such as model pruning [17], quantization [18], and knowledge distillation [19] to reduce model complexity and enhance computational efficiency. These methods enable effective deployment on low-power devices without sacrificing detection performance, ensuring the capability to detect and respond to aerial threats in real-time [12; 20]. Furthermore, optimized models are adaptable to various deployment environments, enhancing the overall reliability and efficiency of the system. As illustrated in Figure 1. To enhance the efficiency of drone detection and recognition, this paper has implemented a lightweight optimization design for the YOLOv5s. The model employs the ShuffleNetV2 network combined with a coordinate attention mechanism to maintain efficient feature extraction while reducing computational load. Furthermore, to improve the efficiency of feature fusion, the algorithm incorporates a bidirectional feature pyramid network to optimize the feature fusion path and assigns learnable weights to each input feature, achieving more balanced feature integration. Lastly, to enhance the precision of bounding box regression tasks, we introduce the EIoU bounding box loss function, which accelerates network convergence and improves the model's positioning accuracy. The main contribution of this work is summarized as follows. * The main backbone network of YOLOv5s was reconstructed using Shufflenetv2 and coordinate attention mechanism, simplifying the network structure and reducing the model parameter size. * The neck network of YOLOv5s was reconstructed using Bi-FPN and Ghost Convolution, extracting more accurate and rich features. * The introduction of the new loss function EIoU to replace CIoU accelerates the network convergence speed and enhances the model's localization ability.
## 1 Introduction
### Video Exploration
As elaborated in Section 2, current SOTA approaches only provide the ability to either jump to a particular section of a video (non-liner navigation) or there are approaches that provide a smaller video extracted from the source video (video summarization) to let the user quickly skim the video. However, they are inadequate as in a typical exploration task user needs keeps evolving [1; 19]. RAAVE takes a different approach and transforms a video into a multimedia document automatically so that the user can explore the content in different configurations and perform exploration related tasks (both navigation and synopsis) using RAAVE as per their evolving needs. The following are the main contributions of this paper:  
* an algorithm for our approach to the transformation of video content;
* a novel system based on the proposed architecture;
* a comparison-based user study to evaluate the effectiveness of the prototype system and the proposed approach in exploration tasks, including:
* finding a particular piece of information within video content, and
* evaluating the context of a video in a short time and writing a synopsis. * In addition, this study assessed user engagement, comparing RAAVE to a baseline approach. The rest of this paper is organized as follows. Section 2 described the state of the art. Section 3 described the design principal of RAAVE, while the details of the design of the proposed approach are described in Section 4. In Section 5 a prototype system based on the design is described. Section 6 describes the user study and the results of the user study which was conducted to evaluate the proposed approach in multiple exploration tasks are described in Section 8. Section 9 provides a discussion of the results of the user study and finally Section 10 concludes the paper.
## 5 Adaptive Dual-Mode Routing-Based Mobile Data Gathering Algorithm
### Routing Set-Up and Update  
The state of each node changes with time, and the network needs to update routing in a timely manner according to the distribution of charging cells in each round. The MCGV broadcasts the charging scheme and the relative state parameters of all nodes in the previous round at the beginning of the round. Each node determines its next hop according to the information. This process is outlined in Algorithm 1.  
```
Inputs: Sensor list \(V\), Anchor point set \(AS\), Outputs: Network Routing \(V.next\); for all\(v_{i}\in V\) \(FN(v_{i})=\big{\{}v_{j}\big{|}d_{i,a_{j}}>d_{j,a_{j}},d_{i,j}\leq R,\big{|}a_{ i},a_{j}\big{\}}\subseteq AS\big{\}}\) if\(d_{i,a_{i}}\leq d^{th}\) or \(FN(v_{i})\in\phi\)then\(v_{i}.next\gets a_{i}\); else\(v_{i}.next\leftarrow\arg\max_{v_{i}\in FN(v_{i})}\big{\{}EE_{v_{i}}\big{\}}\); endif endfor \(V.next=\{v_{i}.next|\forall v_{i}\in V\}\)
```  
**Algorithm 1**Adaptive dual-mode routing-based mobile data gathering algorithm.  
Each node collects sensor data and determines its next hop according to adaptive dual-mode routing, as shown in Algorithm 1, at the beginning of the round. The nodes which adopt the multi-hop mode send their data packets to their next hops until these data packets reach the nodes which adopt a direct upload mode. The MCGV broadcasts its location to the network when visiting each charging cell in \(CV\) in order to charge the nodes in these cells. Meanwhile, it gathers data packets from the direct upload nodes upon reaching the nearest charging cells. Compared with the single upload mode, adaptive dual-mode routing for mobile data gathering in this paper can optimize the energy balance effect.  
The operation principle of adaptive dual-mode routing is described in Figure 2. The average upload distance of nodes is relatively short in mobile data gathering, but some nodes still have a longer upload distance, and their energy consumption is higher than that of other nodes. According to adaptive dual-mode routing, the nodes near anchors still employ the direct upload mode. However, the nodes with a long upload distance can change to the multi-hop mode, which decreases their energy consumption and balances energy. Moreover, the network lifetime can be prolonged based on this routing strategy.  
Figure 2: Operation principle of adaptive dual-mode routing.