esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Summary and Consideration for Implementation of Optical Backbone  
The MSSI-based DM link proposed in this study can be used as optical backbone link. In this section, we summarize the simulation results and mention the points to be considered when implementing the results of this study into an optical fiber backbone network.  
The random distribution of RDPSs in the former half link and the reverse distribution to those of the former half in the latter half link is the most suitable configuration capable of compensating for the distorted WDM signal. This result means that the midway OPC significantly affects the compensation performance compared to the dispersion management. Although the RDPS random distribution of fiber spans can increase the flexibility of link design compared to the conventional DM system, the system performance is deteriorated due to the irregularly shaped dispersion-power profile. However, the random-inverse distribution can make the dispersion-power profile almost symmetrical with respect to the midway OPC; thus, it is possible to satisfy the conditions necessary for compensation of the signal distortion due to not only the chromatic dispersion but also the nonlinear Kerr effect, especially SPM.  
In the design stage, by applying MSSI-based DM to the ultra-long haul backbone link, it is common to allocate RDPS for all fiber spans uniformly, but the practical process is not easy because of the various field conditions. That is, in practice, it may be more convenient to allocate the different RDPS to each fiber span. As a result, the random distribution of RDPS is realistic in backbone link design. It is expected that the compensation deterioration derived from the field circumstance can be reduced by making the random distribution of RDPS before and after OPC symmetry.  
The all-random distribution is more advantageous than the random-inverse distribution in terms of the practical convenience of RDPS allocation. Although the MSSI-based DM link configured with the all-random distribution cannot good compensate for the distorted WDM signal, it is improved over the random-follow distribution. We confirm that the allowable launch power and effective NRD range can be maintained as much as in the conventional scheme by applying the special random distribution pattern that can approximately symmetrize the dispersion-power profile, even when the WDM signal is transmitted through the MSSI-based DM link in which the RDPSs in both halves are randomly distributed.  
The compensation effect of the distorted WDM signal through the link proposed in this study may not be comparable to that of the MSSI-based DM link configured with the artificial distribution of RDPS. This is because all RDPSs are intentionally distributed to set up the symmetric dispersion-power profile with respect to the OPC. However, even with the excellent DM configuration for the compensation, it requires effort to find the optimal dispersion map and not the RDPS combination pattern in the artificial distribution.
## 2 Materials and Methods
### Data Acquisition and Calibration  
Multimode HSI systems are used to acquire continuous spectral images of the grain flours. In this present study, all imaging systems adopted the line-scan mode and the moving sample stage. The HSI data contain the spectral and spatial information of the target material. In addition, the acquired data are prone to noise from the environment and facility, and thus data classification was performed using dark and white references.  
To calibrate reflectance images for robustness of image processing, the acquired original image (RO) must be corrected using dark and white references. The dark image (RD) with block reflectance was acquired with its opaque cap, whereas a Teflon plate (SRT-151, Labsphere, NH, USA) was used to acquire the white reference (RW) images. The calibrated image (RC) can be calculated as follows:  
\[R_{C}=\frac{R_{O}-R_{D}}{R_{W}-R_{D}} \tag{1}\]  
Figure 1: Hyperspectral imaging system (**a**) visible and near-infrared (VNIR) and (**b**) short-wavelength infrared (SWIR) range. Camera system is stationary and sample holders move.
# Spatiotemporal Analysis of Web News Archives for Crime Prediction
## 4 Spatial Crime Analysis
### Analysis Using Average Nearest Neighbor  
According to the Routine Activity Theory, the behavior patterns of people and their environment has a significant impact on criminal activities. Therefore, to identify and explain the relationship between neighborhood and crime characteristics is a key aspect [12]. It is necessary to know how the crime data is spatially distributed, i.e., either clustered, random, or dispersed. We have used the average nearest neighbor, a statistical tool in ArcGIS, to measure the autocorrelation between crime features in our spatial crime dataset. Average nearest neighbor is the tool that measures the distance from the center of each point to the centers of its neighbors. Further, it calculates the average of all the calculated nearest distances. The average distance is compared with the average of the hypothetically which gives a random distribution using the formula given in Equation (1). The average nearest neighbor is calculated as the ratio between the observed distances of each feature to the expected distance.  
\[\textit{average nearest neighbor}=DO/DE \tag{1}\]  
In average nearest neighbor, if the value of the nearest neighbor ratio is less than one, it indicates that the patterns are clustered as shown in Figure 4. Figure 4 is obtained and built using the average nearest neighbor tool in ArcMap. In the case that the value is greater than one, it shows that the patterns are dispersed in the relationship. Hence, Figure 4 shows that in our data, the spatial correlation of feature points is clustered.
## 2 Materials and Methods
### Image Analysis  
Patients with both CT and MRI images acquired within a month were included after being retrieved from the computer database for assessment. A total of 500 examinations, consisting of 250 CT images and 250 MRI images, were analyzed by using OnDemand3D software (version 1.0.9.3223, CyberMed Inc., Seul, Republic of Korea). Two dentomaxillofacial radiologists, with more than 15 years of experience, selected and analyzed the images based on a consensus on bone changes, namely erosion and flattening.  
Initially, they considered including cases among those in the sample related to other alterations, such as the presence of osteophytes and subchondral cysts. However, the decision was made to focus exclusively on cases with flattening and erosion of the condylar cortex. This selection was based on the rationale that flattening represents an initial stage of degenerative changes, whereas erosion indicates a more advanced and severe stage. Additionally, the number of cases with other alterations in our sample was small, which could potentially have introduced a bias in the results and reduced the statistical power of our analysis. By concentrating on these two specific alterations, we aimed to capture the progression of TMJ degeneration more clearly to provide a comprehensive understanding of the early and late manifestations of the condition. This approach allowed for a more precise evaluation of the efficacy of TA in identifying varying degrees of degenerative changes, thus enhancing the clinical relevance of our findings. Therefore, the final sample consisted of 47 patients of both genders, which was divided into groups of TMJs with flattening and erosion. TMJs without any alteration constituted the control group.  
The inclusion criteria were patients from both genders older than 16 years who presented with bilaterally visible TMJs, whereas exclusion criteria were patients with images showing severe artifacts or a history of systemic diseases, maxillofacial trauma, recent jaw surgery, or congenital bone/cartilage disease.  
After applying the inclusion and exclusion criteria, 47 patients aged between 16 and 72 years old were included in the study.
###### Abstract
The loads of the categorized SBSs (environmental changes are also considered) are effectively adjusted through the use of appropriate modes. * GPS positioning and received signal strength (RSS) support: Using GPS positioning, the SBSs in a large area that are suited for a handover can be identified, such that an OIS is able to determine the best SBS in advance and we are able to identify the actual location of the OIS. After the most suitable SBS has been determined, RSS can then be utilized to enable the timely handover of the connection signal by the OIS. * Ability of the OIS to facilitate a handover by evaluating and selecting the most suitable SBS in its path based on the current situation: SBSs that are suitable for a handover are individually evaluated. Weighted scoring is performed using three indicators, namely the hold time of the connection between the OIS and an SBS, the RSS of the OIS, and the load capacity of an SBS, with the purpose of identifying the SBS in the OIS's path that is most suitable for a handover. * Simulation of fading in different channel environments: Simulations based on different symmetric fading channel environments were performed in this study, with the aim of developing practical SBS selection and handover methods that can be applied to mobile terminal equipment in a realistic context. The subsequent contents of this article are divided into the four sections as follows: Section 2 is a literature review in which relevant studies are discussed; Section 3 introduces the design of the proposed model and toss-and-catch algorithm by first establishing and defining the model's relevant parameters and then describing the steps involved in the  
Figure 1: Toss-and-catch algorithm concept (as illustrated by the ����1 -> ��2 -> �3 sequence of conversations). At T\({}_{0}\), the “outdoor unit (ODU) + indoor unit (IDU) + small cell” (OIS) is communicating with Cell B and uses the toss-and-catch algorithm (detailed description in Section 3) to determine that it will enter the coverage of Cell E at T\({}_{1}\); the OIS then informs Cell B to transfer the returning transmission data to Cell E, with the result that the OIS can receive returning transmission data from Cell E at T\({}_{1}\). algorithm process; Section 4 presents and discusses the detailed simulation results to highlight the superior attributes of the proposed method; and Section 5 provides a conclusion for the study in addition to discussing future expectations.
## 2 Related Works
### Algorithms to reduce routing overhead  
Compared to the proactive approach, the reactive approach is high-powered at a lower network overhead and has less data transmission delay and no periodical routing update. The LAR protocol has been presented as an On-Demand protocol based on source routing. The protocol utilizes location information to limit the area when seeking to discover a new route to a smaller \"request zone\". As a consequence, the number of route request messages is reduced.  
The Greedy Perimeter Stateless Routing (GPSR) protocol [18], another Geo-routing protocol, holds only neighbor location information for delivering data packets. This approach is appropriate for dense wireless networks due to its small number of per-node routing states and low routing message complexity.  
The Fisheye technique, another algorithm to reduce routing message overhead, is used for Fisheye State Routing (FSR) [19] and AODV-DFR. First, FSR exchanges all of the link state information with closer neighbors instead of flooding the information over the network. Regarding link state table management, FSR uses an up-to-date technique. Secondly, in FSR, the link state information is swapped periodically instead of being event-triggered as a method to prevent frequent link state updates which cause link breaks and unreliable wireless links. Moreover, periodic broadcasts of thelink state information are operated using different frequencies on different entries that depend on their hop distances to the current node.  
Finally, protocols similar to the improved original AODV routing protocol were presented in other studies [20,21]. In these two protocols, the originating node can estimate the distance to the destination node and set the initial value of the TTL field in the RREQ message based on that estimated value. This is done using a simple modification of TTL field technique, which may result in an unnecessarily large number of control packets traveling through the network.
# Shellfish Chitosan Potential in Wine Clarification
## 3 Results and Discussion  
### Chitosan Deacetylation  
The degree of deacetylation (DDA) is a useful tool for identifying chitosan structural rigidity and its polymer conformation; in addition, it is directly connected to the chitosan (CTS) number of positive charges [23] and thus to its cross-linking attitude [25]. The high number of charged amino groups arranged on the chitosan surface facilitates its dissolution in acid solutions and guarantees a general greater functionality, i.e., the control of microorganisms, the binding of lipids, the improving of immune response, and the cytotoxic activity [26]. Nevertheless, the DDA is strongly affected by the CTS production method in light of the variation in the extraction protocols [3] that acquired even more importance when chitosan derived from different original materials are considered, as is the case of the samples studied here. Nevertheless, the identification of the original raw material cannot be sufficient to describe chitosan deacetylation and therefore, at first, the selected chitosan underwent a preliminary test that defined their deacetylation degrees.  
Overall, the samples evidenced a degree of deacetylation varying between 70 and 95%, the common interval expected for commercial chitosan. CTSs could be categorized into three groups, i.e., \"low\" degree of deacetylation when DDA is ranging between 55 and 70%, \"medium\" when comprised between 70 and 85% and \"high\" when achieved 85-95% of DDA [26]. To date, the \"ultrahigh\" degree of deacetylation--DDA above 95%--is difficult to reach through an industrial process. Figure 2 shows that A9 and A10 achieved the \"high\" value of DDA, with 86.3% and 87.7%, respectively, while A6 evidenced the lowest level of deacetylation with 70% of DDA. The other samples were ascribed to the \"medium\" group. The comparison among samples highlighted a statistically significant difference between A6 and A9 and A10, with the latter grouped together (F\({}_{\theta,19}\)) = 2.668, \(p\) = 0.034). It shouldbe noted that A6 was not completely dissolved in the buffer solution before the test, and that certainly influenced the result.
## 3 Results and Discussion  
### Absorption of Curcumin into BC  
Due to the unique properties of BC, studying the absorption and release of curcumin from BC revealed interesting information about the characteristics of the material. Our results suggest that BC has potential as a carrier for the controlled release and transdermal delivery of drugs or active components. Immersion in curcumin solution was carried out for 24 h because absorption occurs rapidly in the first 12 h, then gradually increases, reaching a plateau within 24 h. The actual amount of curcumin absorbed into BCC0.25, BCC0.5, and BCC1.0 films was found to be 0.19 \(\pm\) 0.03, 0.36 \(\pm\) 0.03, and 0.47 \(\pm\) 0.03 mg/cm\({}^{2}\) of film (with a thickness of \(\approx\)20 \(\upmu\)m), respectively. During immersion, the curcumin solution enters the loose matrix of the never-dried BC film. Entrapment of curcumin is a result of the interaction between BC microfibrils and curcumin that occurs during air drying [33]. As the concentration of curcumin solution increased, more curcumin molecules were observed to diffuse and absorb into the BC matrix.
# Coal Seam Thickness Prediction Based on Transition Probability of Structural Elements
## 5 Conclusions  
A STTP-GPR coal seam prediction algorithm with the cutting data being interpolated by the RBF-Kriging is proposed. The RBF-Kriging interpolation algorithm ensures the data integrity of the structural elements at the edge of the marching direction. It uses the transition probabilities between the structural elements to represent the spatial distribution structure. By taking into account the spatial distribution of coal seams, the proposed method makes up for the deficiencies only using the marching direction to predict the coal seam without considering the influence in other directions, thus improving prediction performance. The proposed method is verified using the simulated and real coal seam data.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Algorithm** & **MAE(m)** \\ \hline SVR & 0.061 \\ BPNNs & 0.043 \\ GPR & 0.036 \\ STTP-GPR & 0.025 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Mean absolute error.  
Figure 13: 3D visualization of the coal seam surface obtained from the real experiment: (**a**) Real surface and (**b**) prediction surface.  
The experimental results show that the prediction accuracy of the proposed STTP-GPR algorithm is superior in comparison to the popular BP neural network, SVR algorithm, and GPR algorithm.  
In practical application, due to the precise prediction of coal-rock interface and coal seam thickness of next cutting, the proposed method enables the shearer to automatically track the coal-rock interface in mining and adjust the coal cutting height to improve the production efficiency and coal quality. The proposed method can be used both for manually operated shearers and for computer controlled shearers.  
Conceptualization, W.K. and A.Q.; Methodology, W.K.; Software, W.K.; Validation, A.Q., W.K. and H.L.; Formal Analysis, W.K.; Investigation, H.L.; Resources, A.Q.; Data Curation, A.Q. and W.K.; Writing-Original Draft Preparation, W.K.; Writing-Review & Editing, G.Z.; Visualization, W.K.; Supervision, A.Q.; Project Administration, W.K.; Funding Acquisition, A.Q.  
This research was funded by National Natural Science Foundation of China (No. 61674121).  
The authors declare no conflict of interest.
# Towards a New Digital Era: Observing Local E-Government Services Adoption in a Chinese Municipality
## 1 Introduction  
The development of Information and Communication Technologies (ICT) has impacted every aspect of our society, including the way governments interact with citizens. The advent of electronic government (e-government) has lifted a worldwide management reform movement in governance area to this day, evolving from delivering to citizens efficient, transparent and effective services to promoting open data, e-democracy, and so forth [1; 2; 3]. Academia has responded to this transformation with massive interdisciplinary research on e-government issues in which e-government adoption remains a fundamental topic, simply because e-government projects would become meaningless without citizens' usage.  
Several theories have achieved prominence in predicting user adoption rates and identifying their determinants. For instance, the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology are the most frequently used models for analyzing e-services adoption [4; 5]. Nevertheless, in e-government terms, e-services extend not only to the introduction of new technologies to public life, they constitute a must-do mission due to the differing development strategies in various countries, and a must-use tool to differentiate themselves with emerging technologies chosen by users' interests (such as e-commerce).  
While traditional e-government applications have been infused into people's daily lives, governmental departments have started to utilize social networking services (SNS) to reach wideraudiences and expand the depth of services. In the case of this trend, e-commercial platforms in China have recently been participating in the delivery of local e-services to citizens. An unprecedented collaboration between private Internet corporations and governments is underway that far beyond the current discussion regarding social media and e-government services. With the aid of advanced e-commercial skills, local governments in China promptly reform the delivery of local public services in the wave of digital era governance [6]. To understand e-government adoption in the context of modern digital society, this research conducted a case study in a Chinese municipality premised upon survey data (N = 605) collected in Chongqing, China in 2016. The paper begins with a literature review sorting out e-government applications and important factors predicting adoption via the TAM and UTAUT models mentioned above; the e-government situation in China is also described to provide background to the survey. Next, the data collection and research methods are described, followed by analysis and findings. Discussion and conclusion are presented as the last sections.
## 3 A Trimmed-Clustering Based \(I_{1}\)-PCA Model
### Synthetic Analysis  
We demonstrate the robustness of the proposed TC-PCA to the data with outliers. Figure 4 shows the first projection vectors estimated by the \(l_{1}\)-PCA and the proposed TC-PCA in a noisy environment. The dataset with outliers is obtained by adding 50 2-dimensional Gaussian noise into the dataset used in Figure 3. With 4.8% (50/(1000 + 50)) outliers in the dataset, the projection vector obtained by the \(l_{1}\)-PCA is influenced by outliers (see Figure 4a), whereas the projection vector estimated by the TC-PCA is not affected by outliers (see Figure 4b). This is mainly due to the fact that the TC-PCA adopts the trimming set which retains only \(p\%\) of samples that are close to the cluster centers for the estimation of projection vector while the remaining \(1-p\%\) of the data that include outliers will be discarded. It is important to note that the percentage of data discarded by the trimming set should be greater than the percentage of outliers in the dataset so that an accurate projection vector can be obtained (see Theorem 1).