esa-sceva/satcom-chunk-collection huggingface dataset:
# A Systematic Review of Cybersecurity Risks in Higher Education
## 10 Limitations and Future Work
### Future Work within HE Risk Management  
The amount of empirical studies featuring information assets in higher education was quite limited. We identified one relevant academic resource [40], which was not written for risk assessment purposes and thus did not feature a holistic and adequate representation of the information assets featured in a HE institution or a ranking said assets. While multiple sources mentioned critical assets in their description, for example, Table 5 illustrates a vastly more complex picture than that listed in the reviewed risk literature. The level of value these information assets possess, can also be disputed. The reason for this might be the complexity of quantifying information assets in higher education. A call for more studies to examine the value of information assets in higher education would be beneficial, both for the HE security community and researchers. As modern HEI can be considered as enterprises, one can research comparisons with industry who have similar enterprise systems and expand the understanding.  
The literature search identified peer reviewed sources researching infosec vulnerabilities in HE. While there is room for more research, the most saturated area was _cybersecurity awareness_ in HE (Table 14). However, significant effort should be put into improving security awareness in HE, through both research and training. Raising awareness and discussing the issues highlighted in our research is a start. It is also likely that cybersecurity will become a competitional advantage in future research grant applications, especially within the STEM disciplines.  
One paper focused on comparative analysis of compliance to technical security mechanisms [4]. In this study, the six surveyed universities scored high on security maturity and were probably well ahead of the average HE institution within infosec and not representative. Nevertheless, this was an interesting study which yielded interesting results. A path for future work is to conduct similar maturity modeling studies of international universities to expand the knowledge and increase security compliance.  
Other topics regarding vulnerabilities in HEI were either absent or not specifically described in the academic papers, but documented in technical reports and white papers instead. This issue might be caused by the sensitivity level and possibility of reputational loss in HE by going public with this information. Only FireEye [5] and UNIT [6] attempted to provide a holistic overview of the vulnerabilities in HEI. Generally, academia should be more willing to publish vulnerability and incident data for researchers. More empirical studies of security vulnerabilities in HE would be beneficial. Cloud security in HEI was also an area with scarce information.  
We also researched threat agents in this study and proposed a generic threat model for HE. More research and understanding of the threat landscape will allow for better security decision-making when planning for research and administrative tasks.
# A Fault Analysis Method Based on Association Rule Mining for Distribution Terminal Unit
## 8 Conclusions and Future Work  
This paper proposed a fault analysis method based on an association rule mining algorithm for DTU so as to improve the efficiency of fault elimination. The selection of algorithm for this method was proven to be reasonable through simulation, and the practicality of this method was proven by a realistic DTU fault database. This method can form fault rule bases and diagnosis rule bases, which can be used for supporting planned maintenance and fault repairing. In this way, DTU fault incidence can be reduced and fault elimination ability can be enhanced. Comparative experiment in the application example demonstrated the effectiveness of this method.  
However, the performance of this method was not satisfying when not enough data were available. Moreover, since this method only relied on objective data, the results were not always reliable. A possible solution is to combine expertise to verify the generated rules as well as remove the redundant and invalid rules.  
It is recommended that, with the successful application of this fault analysis and diagnosis method, more research that combines this objective data-driven method with subjective expertise should be conducted to improve the reliability of fault analysis. Additionally, machine-learning techniques can be incorporated into this method to analyze fault and estimate the state of devices so as to improve the accuracy of fault diagnosis. With the integration of more DTU devices, lifecycle management of devices should be studied to facilitate the application of this method and enhance its positive impacts. Moreover, in order to reduce maintenance pressure, future work can be conducted on eliminating manual processes and realizing intelligent maintenance.  
Conceptualization, X.Z and Y.T.; methodology, X.Z.; investigation, G.L.; resources, J.C.; writing--original draft preparation, X.Z.; writing--review and editing, Y.T.; supervision, Q.L.; project administration, X.N.; funding acquisition, Q.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by State Grid Corporation of China. Program name: Research on automatic configuration and intelligent operation and maintenance technology of large-scale plug and play power distribution terminal. Grant number: SGJSNJ00 KHJS2000556.  
Not applicable.  
Data Availability StatementRestrictions apply to the availability of these data. Data was obtained from State Grid Corporation of China. Data is available on request from the corresponding author.  
The authors declare no conflict of interest.
## 2 Construction of Dimensional Feature Images
### Light Source Selection  
In the experiment, the selection and arrangement of the light source have a significant impact on image quality and the accuracy of subsequent algorithm processing. Based on the material of the workpiece and the detection requirements, a ring light source was chosen for this study. The ring light source, with its characteristics of uniform illumination and multi-angle lighting, not only effectively eliminates shadows and local brightness inconsistencies but also enhances the clarity of surface textures and details.  
For workpieces with high reflectivity or complex surfaces, the ring light source further improves image quality by reducing reflective interference. To optimize the experimental results, this study conducted a detailed analysis of the characteristics of two lighting arrangements: front lighting and side lighting using the ring light source. Based on the experimental findings, the optimal light source arrangement was determined. The lighting setup diagram is shown in Figure 4, and the experimental results are shown in Figure 5.  
Figure 3: Centroid correction process.  
* Frontal lighting involves positioning the light source between the camera and the workpiece, directing light from the camera towards the workpiece surface. This method uniformly illuminates the workpiece surface and is suitable for tasks that require capturing detailed texture features of the target. The advantages of frontal lighting include even illumination that effectively highlights the texture features of the workpiece surface.
* Side lighting places the light source at the side of the workpiece, with light striking the surface at an angle. This method enhances the contrast and clarity of the workpiece's edges. However, the drawback is that side illumination can cause uneven brightness, leading to overly dark or bright areas at the edges. It is not suitable for detection tasks that rely solely on surface texture features.  
In conclusion, this study opts for frontal lighting due to its advantages in providing uniform illumination that enhances the visibility of surface details.
# True Random Number Generator Based on Fibonacci-Galois Ring Oscillators for FPGA
## 2 All-Digital True Random Number Generators
### Digital TRNGs
#### 2.2.4 FiGaRO True Random Number Generator  
As suggested in [24], the randomness, as well as robustness, can be further increased by XOR-ing the outputs of a Fibonacci Ring Oscillator and a Galois Ring Oscillator. The structure formed by XORing FiRO and GaRO is named as a FiGaRO structure. Figure 7 shows an example of a FiGaRO structure as specified in [24] composed of four FiRO and four GaRO connected using a XOR tree. The lengths of the two oscillators minus one should preferably be mutually prime to maximize the period of the corresponding pseudorandom sequence and to reduce coupling effect. Besides, it is suggested that the lengths differ only by one, where the even length corresponds to the Fibonacci ring oscillator.  
Figure 5: Fibonacci Ring Oscillator with enable port.  
Figure 6: Galois ring oscillator with enable port.
## 4 Application: A Real Case  
### Geological and Engineering Background  
The Songmugou landslide is located in the middle of the mining area of the Jingu Coal Industry in Guvian County, Shanxi. It belongs to Songmugou Formation, Guyang Village, Guyang Town, Gu County, with coordinates: N: 112\({}^{\circ}\)01'04'', E: 36\({}^{\circ}\)23'24''. The main terrain is a middle-low mountainous area, with an elevation of 1050 m and a valley cutting depth of 100 m-200 m, and the south side of the point is mostly high mountains and steep slopes with great terrain changes, with an elevation of 1200 m and above, and the slope range of the mountain slope is \(50--60^{\circ}\), while the terrain on the north side is relatively flat, with an elevation of 1050 m and below, most of which are the residences of villagers, transportation and administrative centers. The geographic location of the Songmugou landslide is shown in Figure 8, and the geological section of the landslide is shown in Figure 9.  
The Songmugou landslide is located on the south side of Songmugou valley. The bottom of the valley has an elevation of 1050 m and a widened \"U\" shape. The top of the slope on the south side has an elevation of 1200 m, and the original slope is \(55^{\circ}\). The slope on the north side is relatively flat, with an elevation distribution of 1050 m-1100 m, of which there are four steep ridges distributed in steps, with a drop of 0.8 m-1.0 m, thus forming multiple loess platforms. The landslide is the unstable deformation of the southern slope, and the sliding body and the front edge of the landslide slide into the valley.  
Figure 7: The comparison of the proposed method and the displacement-based method.
## 5 Conclusions  
In this study, eco-friendly pervious concrete containing FA and BFS was prepared to investigate the mechanical and hydraulic behaviors. Rheological tests were first conducted to explore the effect of FA and BFS on the behaviors of the fresh pastes. Compressive strength and permeability coefficient were selected as the indicators in the analysis of the mechanical and hydraulic performance. Based on the laboratory tests, the following conclusions can be drawn.  
* FA increased the apparent viscosity, while BFS was not able to change the rheology performance significantly. Rheology performance of cementitious pastes containing FA and/or BFS belonged to the Bingham model.
* FA and BFS both decreased the compressive strength of pervious concrete at 28 d, while FA and/or BFS could slightly increase the compressive strength at 60 d. Compared to BFS, FA plays a more significant role in the compressive strength.
* The effective porosity and permeability coefficient both decreased with the incorporation of FA and/or BFS in the pervious concrete. As the content of FA or BFS increased, the reduction was larger. However, when the replacement rate was 30%, concretes with ternary blends presented larger porosity than binary blends.
* Permeability coefficient and compressive strength both decreased with the increase of effective porosity.
* The use of FA and BFS is a sustainable approach in pervious concrete that considers both the mechanical properties and hydraulic properties.  
For this paper, [PERSON] formulated research ideas and conducted lab test, result analysis and manuscript writing. [PERSON] and [PERSON] made some revisions to the manuscript.  
This research was funded by the Key Project of Hunan Department of Science and Technology (Grant No. 2013 FJ2002).  
The authors declare no conflict of interest.
# LightR: A Fault-Tolerant Wavelength-Routed Optical Networks-on-Chip Topology +
## 4 Experimental Results  
To evaluate the performance of the LightR, we compared it to three state-of-the-art WRONoC topologies, \(\lambda\)-router [17], GWOR [18], and Light [16], for two aspects: reliability and efficiency. We present the comparison in Section 4.1. Then, we compared the LightR with the RobustONoC [15], which inserts backup MRRs to deal with the MRR faults, and we discuss their performances in Section 4.2.
## 4 Calculation Results of the Three-Dimensional Chargeable Body Model
### The Influence of System Parameters on IP Response  
In the field measurements of GREATEM, due to the influence of airflow and environment, the flight height was not a constant. Therefore, it was necessary to analyze the influence of flight altitude on the IP effect. We take the 3D model (Figure 8) as an example. The air layer conductivity was set to \(\sigma_{\rm air}\)\(=10^{-6}\) S/m and the earth conductivity was set to 0.001 S/m, while the size of the chargeable body was \(400\times 400\times 300\) m. The model parameters of the chargeable body were as follows: chargeability \(\eta\)\(=0.5\), frequency dependence \(\rm c=0.5\), characteristic time constant \(\rm\tau\)\(=0.01\) s, conductivity at the infinite frequency \(\sigma_{\infty}\)\(=0.1\) S/m, offset distance \(\rm r=200\) m, and flight altitude \(\rm h=25\) m, \(\rm h=50\) m, \(\rm h=75\) m, and \(\rm h=100\) m. The induced polarization (IP) effect at different flight altitudes was calculated as depicted in Figure 12. In order to understand the influence of the parameters of GREATEM on the IP response, other parameters remained unchanged, while the flight height was set to \(\rm h=25\) m, and the emission source length was \(\rm L_{Tx}\)\(=50\) m, \(\rm L_{Tx}\)\(=100\) m, and \(\rm L_{Tx}\)\(=200\) m. The responses of different emission source lengths are shown in Figure 13. Taking \(\rm L_{Tx}\)\(=400\)  
From Figures 15 and 16, it can be seen that all the amplitudes decreased, while the depth of chargeable body increased. However, the time of the reversal sign did not change. In the early stage, as the distance between the emitter source and the chargeable body decreased, the amplitude of the induced field increased, the attenuation of the curve was delayed. In the later stage, the time of sign reversal appeared later when the distance between the emitter and the chargeable body decreased.  
Figure 14: The response curves under different offset distances.  
Figure 12: IP effects at different flight altitudes.  
Figure 13: The response curves under different emission source lengths.
# A Dynamic, Cost-Aware, Optimized Maintenance Policy for Interactive Exploration of Linked Data
## 2 Background
### Related Work  
The issues related to the exploitation and maintenance of local views have received considerable attention in the research community over recent years. Most of the maintenance algorithms proposed in the literature are based on _eager (or deferred)_ maintenance. Eager maintenance protocols update the view periodically whenever a change occurs in the cloud. [PERSON] et al. [25] proposed deferred view maintenance to reduce the view downtime and perform incremental maintenance to keep the local views up-to-date. However, all these algorithms divide the maintenance task into smaller steps, which is not as effective as combining the small maintenance task to improve the efficiency of the overall maintenance process. Data warehouses have also used a _lazy maintenance_[26] policy that delays maintenance until downtime rather than the peak query time. Also worth mentioning are the maintenance policies for stream monitoring that examine the problem to schedule multiple continuous queries. They are able to manage incoming data streams using on deferred maintenance for updating local data caches. However, their policies mainly focus on ETL (Extract, Transform and Load) operations and they have difficulties in managing latency and accuracy when a large-scale fusion of linked datasets is given.  
Semantic caching was originally proposed for Database Management System (DBMS) [27] to reduce the overhead when retrieving data over a network. The idea is to maintain has been extended to previously issued queries to facilitate the future requests. Nowadays, the semantic caching technique triplestores [28]. [PERSON] et al. [29] proposed a notion of semantic overlap and introduced a caching approach that utilized client-server systems. To extend this idea, [PERSON] et al. [27] proposed a semantic region-based caching and introduced a distance metric to update the cache where the far regions are discarded from the cache. However, these approaches can only handle _SELECT_ SPARQL queries. [PERSON] et al. [28] proposed an idea to apply cache on the SPARQL processor. The benefit of this work is to cache both the triple query result and the application result. However, this work does not consider identical and similar queries for cache replacement. To extend this work, [PERSON] et al. [30] proposed a content-aware approach that utilized _query containment_ to estimate whether the queries can be answered from the caches. The containment checking approach produces a lot of overhead, therefore this approach is not widely utilized by the Semantic Web community. [PERSON] et al. [31] proposed an approach to decompose the query into basic graph patterns and cache intermediate results but they do not consider cache replacement to maintain the freshness of the cache. In summary, only few works have been reported that deal with the problems related to view maintenance. Moreover, the existing solutions are unable to provide proactive maintenance policy therefore reducing query time.
# Performance Evaluation of Bedding Sand and Load Transfer Characteristic of Concrete Block Pavements
## 2 Materials and Experimental Methods
### Experimental Methods
#### 2.2.2 Load Transfer and Rotational Interlocking  
To evaluate the load transfer performance and rotational interlocking effect of the joint, a test pavement was fabricated, as shown in Figure 3. Its dimensions were 1450 mm \(\times\) 1450 mm, consisting of an 80 mm surface block, a 30 mm bedding sand layer, a 200 mm crushed aggregate base course, and a 300 mm subgrade layer. To measure the load and displacement, Tokyo Sokki's LFWD and displacement sensors were used. The experiment was conducted by arranging the LFWD and sensors as shown in Figure 4; a weight of 5 kg was dropped from a height of 500 mm and a load of 20 kN was applied. Concrete block shapes, lying patterns, and degree of joint filling were considered as parameters for the experiment. The degree of joint filling was divided into five stages: 0%, 25%, 50%, 75%, and 100%. The LTE was calculated by multiplying the correction factor with the ratio of the deflection measured in D\({}_{2}\) and D\({}_{1}\), as shown in Equation (1) presented by AASHTO. The rotational interlocking of the concrete block pavement was calculated by Equation (2) using the displacement that occurred at the position where the load was applied and at the opposite end. Data were collected by measuring each parameter 20 times and were averaged to produce the resulting value.  
\[LTE=\frac{\delta_{2}}{\delta_{1}}\times\frac{l_{2}}{l_{1}}\times 100\% \tag{1}\]  
\[\theta=sin^{-1}\bigg{(}\frac{\delta_{0}-\delta_{1}}{l_{1}}\bigg{)} \tag{2}\]  
where \(LTE\) is the load transfer efficiency (%); \(\theta\) is the rotation angle of the concrete block; \(\delta_{0}\) is the deflection (mm) measured at the position where the load is applied; \(\delta_{1}\) is that measured at D\({}_{1}\), \(\delta_{2}\) is that measured at D\({}_{2}\); \(l_{1}\) is the distance (mm) between D\({}_{1}\) and D\({}_{0}\); and \(l_{2}\) is that between D\({}_{2}\) and D\({}_{0}\).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{Block shapes} & Dimension & \multirow{2}{*}{\begin{tabular}{c} **Square** \\ (mm) \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Rectangular** \\ \end{tabular} } & \multirow{2}{*}{\
\begin{tabular}{c} **Uni block** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **Dasuri** \\ \end{tabular} } \\  & & & & \\ \cline{2-2} \cline{5-5} \cline
## 2 Background and Related Works
### DoS in WSNs  
As mentioned previously, the main objective of the DoS or DDoS attack is to affect the network's availability by disrupting services and network performance. Therefore, the effect of this type of attack varies depending on the network layer stack [5]. Since wireless sensor networks have stacks of five network layers, each layer is vulnerable to different types of attacks [10; 45]. The attached Table 1 shows each layer and type of DDoS attack that can be represented.  
Blackhole and grayhole DDoS attacks affect the routing protocol in layer three by declaring the attacker node itself as the cluster head, and we will discuss the cluster head functionality in detail in the clustering management subsection. By comparison, a flooding attack affects WSN availability by sending a large number of advertising messages to cluster heads. In scheduling attacks, the perception and MAC layers' activity is targeted by changing the broadcast channel schedule to a unicast channel schedule. This change leads to packet collision and later data loss [29].  
Several researchers have attempted to mitigate DDoS or DoS in WSNs. The Message Authentication System (MAS) algorithm was used by the authors in [7] to locate and delete DoS attacks. The proposal divides WSN nodes into different clusters, with each cluster head using the MAS method to separate legitimate traffic from phishing scams. The authors in [20; 46] improved the k-means clustering scheme for finding DDoS and misdirection attacks. To detect attacks in a home WSN, the authors of [47] used user-behaviors learning analysis. In [18], the authors used Restricted Boltzmann Machine-based Clustered IDS  
\begin{table}
\begin{tabular}{c c} \hline \hline
**WSN Layers** & **Description** \\ \hline Perception layer & Jamming \\  & Tempering \\  & Scheduling \\  & Collision \\ Perception MAC Layer & Exhaustion \\  & Blackhole \\ Network or Routing Layer & Grayhole \\  & Hello \\ Transport Layer & Flooding \\ Application Layer & Overwhelming nodes \\  & Path-Based DoS \\ \hline \hline \end{tabular}
\end{table}
Table 1: Taxonomy of WSN DDoS attacks.  
(RBC-IDS), a deep learning-based technique for tracking sensitive infrastructure utilizing three hidden layers for potential intruders. Authors in [48] used a genetic algorithm combined with a Multi-Layer Perceptron algorithm to improve detection methods. In [49], the authors presented a novel swarm optimization algorithm for clustering WSN nodes and then used a VSM classifier to detect DoS attacks in each cluster. However, rather than anti-attack initiatives, the focus of this study will be on analyzing DoS attack detection efficiency. In this work we will look at four types of DoS attacks, namely Blackhole, Grayhole, Flooding, and Scheduling.