esa-sceva/satcom-chunk-collection huggingface dataset:
# Space-Borne System-in-Package Based on High Reliability Microwave Interconnections
## 2 Analysis of Traditional Interconnections in Space-Borne Microwave Systems
### Gold-Ribbon Lap Bonding  
Gold-ribbon lap bonding is the use of a gold ribbon to form a \"Z\" shape along the transmission line, and the use of parallel gap-bonding equipment to complete the connection of pads at both ends [16; 18]. The \"Z\" shaped gold ribbon is usually used for the interconnection of a non-coplanar coaxial seal to plane, such as the connection between the coaxial inner core and the side of substrate, as shown in Figure 4.  
The \"Z\" shaped gold ribbon is used to connect the inner core of the coaxial structure to the microstrip line of the substrate for gold-ribbon lap bonding. The same method is used  
Figure 4: Gold-ribbon lap bonding structure.  
Figure 3: Wire winding soldering structure.  
to analyze the mechanical stress characteristics. The stress of the ribbon is about 41 Mpa. At the same time, because the length of the ribbon is shorter and the width is closer to the microstrip line, the microwave matching characteristics are better than in the core wire winding soldering. Through 3D electromagnetic simulation, its reflection loss is better than \(-12\) dB below 5 GHz, which can adapt to the transmission of microwave signals in the C-band and below.
## 3 Results and Discussion
### Smartphones for Evacuation  
Question 4 explored whether occupants would consider using their smartphone for information during evacuation. All interviewee responses were positive, as they all agreed that they would use it as a source of information. The first and most important reason was to gather information from neighbours or other family members within the building. It was clear that information gathered would allow occupants to evacuate the building much faster. This is by knowing which evacuation route to use and the less crowded area in the building. Interviewees believed that information would make them feel safer. Information such as the shortest route to take was very important to interviewees as they clearly stated that the purpose of gathering information is to make sure they are aware of the fire situation in the building and to aid them in finding the most suitable egress route based on their location. Other interviewees explained that other than making and receiving calls to either provide or gather information, there is a WhatsApp group that they have as building tenants, which is also used for communication. The use of the WhatsApp group chat to gather information was raised by eight interviewees, either for communications from occupants who have already evacuated or who are still in the building. Moreover, the word \"information\" occurred 48 times in all interviewee responses, which clearly highlights the importance of using smartphones to gather or send information. Other interviewees focused on information about the location of the fire and confirmation if the fire services had already been informed. Other information could be exchanged through the use of text messages. Interviewees believed that this might be quicker than voice calls as crowdedness and noise would make voice conversations difficult. All interviewees agreed that information gathered would allow them to avoid floors with high traffic, slow speed, and, more importantly, floors that have fire or smoke.  
In addition to what actions they need to take, four interviewees explained that they do not have the knowledge to deal with fire evacuation so they would use their smartphone to call fire services or building security. It is clear from the results that all interviewees would consider using their smartphone during evacuation either by making or receiving calls to/from relatives and neighbours, sending or receiving text messages, and communicating with others on WhatsApp chat. However, two interviewees explained that, although they would use their smartphones during evacuation, this use would be concentrated in the first minutes after detecting the fire. However, other interviewees believed that it could take a couple of minutes to gather information and that is why the use of smartphones would still result in a faster evacuation as they will have more information on the fire situation and what actions they need to take.
# Fingerprinting Acoustic Localization Indoor Based on Cluster Analysis and Iterative Interpolation
###### Abstract  
Fingerprinting acoustic localization usually requires tremendous time and effort for database construction in sampling phase and reference points (RPs) matching in positioning phase. To improve the efficiency of this acoustic localization process, an iterative interpolation method is proposed to reduce the initial RPs needed for the required positioning accuracy by generating virtual RPs in positioning phase. Meanwhile, a two-stage matching method based on cluster analysis is proposed for computation reduction of RPs matching. Results reported show that, on the premise of ensuring positioning accuracy, two-stage matching method based on feature clustering partition can reduce the average RPs matching amount to 30.14% of the global linear matching method taken. Meanwhile, the iterative interpolation method can guarantee the positioning accuracy with only 27.77% initial RPs of the traditional method needed.  
fingerprinting acoustic localization; iterative interpolation; K-Means clustering; Two-stage matching; Adjacent RPs +
Footnote †: journal: Applied Sciences
# Fog Computing: Enabling the Management and Orchestration of Smart City Applications in 5G Networks
## 4 Evaluation Use Case
### Data Analysis Operations
#### 4.3.2 Global Analysis: GPS Locations of Outliers  
The unusual measurements detected by FNs through outlier detection must be further analyzed by application experts in order to extract more information from them. As such, FNs will trigger  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Dataset Name** & **No. of Records** & **Description** \\ \hline \multirow{3}{*}{bpost 1} & \multirow{3}{*}{70636} & Particle matter indicators (PM1, PM2.5, PM10), Temperature, \\  & & Humidity and GPS locations from bpost car 1 between 9 May \\  & & 2017 and 29 June 2017 \\ \hline \multirow{3}{*}{bpost 2} & \multirow{3}{*}{70640} & Particle matter indicators (PM1, PM2.5, PM10), Temperature, \\  & & Humidity and GPS locations from bpost car 2 between 9 May \\  & & 2017 and 29 June 2017 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Evaluation datasets. bpost, Belgian postal services.  
Figure 10: Temperature and relative humidity values collected from two bpost cars. (**a**) bpost Car 1; (**b**) bpost Car 2.  
appropriate alarms and notifications, which will be forwarded through the network to the CN. Then, these unusual samples will be sent to the CN so that more complex and resource-consuming operations can be performed, e.g., for root cause analysis. In our evaluation, the outliers have been compared with the annotated GPS locations as a global analysis operation.
## 5 Experimental Results  
Our pricing model was implemented in Python, using MySQL as the underlying database to manage the data. We evaluated the pricing model in terms of two aspects: (a) the effectiveness, i.e., how well the approximation algorithm approximated the price, and (b) the efficiency, i.e., how quickly the approximation algorithm approximated the price.  
We performed our experimental evaluation on two real-world datasets, including the shuhuibao dataset from the Personal Data Bank [2] and the MovieLens 1M dataset [20]. First, the shuhuibao dataset is a real dataset from our project team. The shuhuibao dataset has 12 relations. Here, the query operation was mainly performed on the two relations of consume and message, in which the consume relation contains 326 source tuples, and the message relation contains 45,294 source tuples. Besides, the MovieLens dataset contains 1000,209 ratings of 3900 movies from 6040 anonymous users [21]. We performed multi-table multi-logical queries on the MovieLens dataset. Each source tuple was assigned a price between one and five according to its importance, and this can also reflect the value of the data themselves. That is, we set a price attribute for each source tuple, which reflected the importance of the source tuple. The larger the value, the more important the source tuple was.  
Firstly, the effectiveness of the algorithm was measured by the calculated price; the lower the price, the more effective the algorithm. Further, the effectiveness of the algorithm was also measured by calculating the ratio between the approximate price and the exact price, as shown below:  
\[\alpha=\frac{a\_p}{p} \tag{21}\]  
where \(a\_p\) and \(p\) denote the approximate price and the exact price, respectively. The optimization goal of the algorithm pursued a smaller \(\alpha\) value.  
WE evaluated the efficiency of different algorithms by the run time and memory consumption required to execute different queries on different datasets.  
All the experiments were run on a single machine running Windows 8.1, equipped with a 2.60-GHz processor and 8 GB RAM. We performed different query operations on two datasets to evaluate the memory consumption of different algorithms.
# AHC: Advanced Network-Hiding Access Control Framework
###### Abstract  
In the current context of rapid Internet of Things (IoT) and cloud computing technology development, the Single Packet Authorization (SPA) protocol faces increasing challenges, such as security threats from Distributed Denial of Service (DDoS) attacks. To address these issues, we propose the Advanced Network-Hiding Access Control (AHAC) framework, designed to enhance security by reducing network environment exposure and providing secure access methods. AHAC introduces an independent control surface as the access proxy service and combines it with a noise generation mechanism for encrypted access schemes, replacing the traditional RSA signature method used in SPA protocols. This framework significantly improves system security, reduces computational costs, and enhances key verification efficiency. The AHAC framework addresses several limitations inherent in SPA: users need to know the IP address of resources in advance, exposing the resource address to potential attacks; SPA's one-way authentication mechanism is insufficient for multi-level authentication in dynamic environments; deploying the knocking module and protected resources on the same host can lead to resource exhaustion and service unavailability under heavy loads; and SPA often uses high-overhead encryption algorithms like RSA2048. To counter these limitations, AHAC separates the Port Knocking module from the access control module, supports mutual authentication, and implements an extensible two-way communication mechanism. It also employs ECC and ECDH algorithms, enhancing security while reducing computational costs. We conducted extensive experiments to validate AHAC's performance, high availability, extensibility, and compatibility. The experiments compared AHAC with traditional SPA in terms of time cost and performance.  
access control; network security; zero trust; single packet authorization (SPA); port knocking; DDoS attacks +
Footnote †: journal: Applied Sciences
# Unsupervised Image Classification Based on Fully Fuzzy Voronoi Tessellation
## 5 Discussion
### Parameter Influence Analysis  
In the proposed FVT-FCM, there are six parameters that need to be initialized; they are the number of classes \(k\), the number of polygons \(m\), the regulatory factor \(q\) and \(R\), and the fuzzy factors \(\lambda_{1}\)_and_\(\lambda_{2}\). \(k\) is fixed based on the image. \(q\) and \(R\) are two regulatory parameters generated from \(\eta\). \(q\) is generally fixed at a smaller value of 0.1. Thus, \(R\) plays a major role. For the fuzzy factors, it is generally assumed that \(\lambda_{1}=\lambda_{2}=\lambda\) to simplify the algorithm. Therefore, the main parameters that need to be discussed are \(m\), \(R\), and \(\lambda\).  
Taking Figure 6(c1) as an example, the curve of classification accuracy with parameter variation is drawn in Figure 12. It can be seen that the impact of parameter \(m\) on OA is relatively small when it is greater than 60. For \(R\), OA will slightly decrease as it increases. The main reason is that the higher \(R\) will lead to strong local spatial constraints. When R is large enough, the role of Voronoi tessellation in the proposed algorithm is equivalent to that of the VT-HMRF-FCM algorithm. Therefore, the proposed algorithm can be regarded as a general form of the VT-HMRF-FCM algorithm. Normally, the range of values for \(R\) is 20-100. For general images, such as panchromatic and multispectral, \(R\approx 30\). For images with strong noise, such as SAR, \(R\approx 100\). For \(\lambda\), OA shows a trend of first increasing and then decreasing with its increase. It indicates that a higher fuzzy degree is not always better, but rather, it should be at a suitable value. A smaller \(\lambda\) is beneficial for distinguishing targets with similar spectra, while a larger \(\lambda\) is beneficial for improving noise resistance. Overall, the recommended range of \(\lambda\) is 1.5-2.5.  
Figure 11: Boundary accuracy curves of various algorithms; (**a**–**f**) images 1–6.
# Effects of the Extraction Technology on Pomegranate Juice Quality
## 2 Materials and Methods
### Chemical Analytical Determinations
#### 2.5.5 Radical-Scavenging Activity (RSA) of 1,1-diphenyl-2-picrylhydrazyl Radical (DPPH)  
The antioxidant activity of juice samples was measured in terms of their Radical-Scavenging Activity (RSA), by using the DPPH (1,1-diphenyl-2-picrylhydrazyl radical) method [19; 20]. Aliquots of the whole pomeranate juice were mixed with an ethanol solution of DPPH (3 mM), i.e., 2.37 mg of DPPH in 2 mL of ethanol. For the sample solution, 28 \(\upmu\)L of whole juice were mixed with 28 \(\upmu\)L of DPPH solution and 944 \(\upmu\)L of ethanol. After incubation in the dark at room temperature for 10 min, the spectrophotometric determination was assayed at 515 nm by means of a spectrophotometer (UV5, Mettler Toledo, Columbus, OH, USA). A freshly prepared DPPH blank solution (containing 972 \(\upmu\)L of ethanol and 28 \(\upmu\)L of DPPH solution) was used. The DPPH solution was stored in a flask covered with aluminium foil and kept in the dark at 4 \({}^{\circ}\)C from one measurement to another. The percentage decrease of absorbance was recorded for each sample and the percentage quenching of DPPH radical was calculated on the basis of the observed decrease of absorbance according to the following equation:  
\[\text{Antioxidant power inhibition (\%)}=[(\text{A0}-\text{A1})/\text{A0}]\times 100 \tag{3}\]  
where A0 is the absorbance value of the DPPH blank solution and A1 is the absorbance value of the sample solution.
# Performance Evaluation of Sequential Rule Mining Algorithms
## 3 Methods of Applying Comparative Algorithms
### The Operation of the Top-k Non-Redundant Sequential Rule (TNS)  
The TNS algorithm adopts TopSeqRules to mine the Top-k rules after eliminating redundancy of sequential rule. It depends on the same search procedure of the RuleGrowth algorithm. The TopSeqRules has two parameters: the number of rules that is determined by the user needs (K), and the minConf threshold that also satisfies the user requirements. It also utilizes three main variables; the first is minSup that is set to initial value = 0 and raises with regard to the number of rules generated. The second variable is L, which helps to perform Top-k rules by keeping each item that achieved the threshold value. The third variable is R having the rule with the maximum support values that helps in choosing the most candidate rules.  
The TNS Algorithm Implementation  
The TNS algorithm firstly scans the dataset only once to identify each item, as seen in Figure 2. It considers an integer parameter K, minConf value, and initializes a value of minSup with zero. Then it generates a rule recursively by growing the valid rule size \(1*1\). After that, it performes two procedures to extend the right and the left side of the rule to generate the Top-k sequential rules. It is followed by removing all redundant rules which means that if \(\mathrm{r_{a}}\) is equal to \(\mathrm{r_{b}}\) with the same support, we will absorb \(\mathrm{r_{a}}\). Then it verifies the result by setting parameter delta \(\Delta\) with a value higher than the all removed rules, so the Top-k non-redundant rules will be generated as shown in Algorithm A2 [24].  
Applying the TNS algorithm solves the trouble of generating either a large number of sequential rules or fewer numbers which may lose valuable information. It also addresses the challenge of generating redundant sequential rules. It has more advantages as:  
1. It saves more time by depending on another parameter to generate the wanted number of sequential rules. Therefore, it does not rely on minSup value that is difficult to be determined regarding database features.
2. Removes the redundant rules and verifies the result by the delta parameter that was set higher than the removed sequential rules.
## 4 Media Access Control
### Cooperative Sensing  
Due to the nature of wireless transmissions, signals are subject to various influences, such as fading and interference [49], and hence, the result of spectrum sensing may not accurately reflect the medium condition. Moreover, the spatial variation of wireless interference could lead to biased channel estimation. Consequently, individual nodes cannot make a reliable judgment of the spectrum utilization solely based on their own local sensing results [20].  
The answer to the problem is to form MAC layer cooperation among _IoT_ devices [20] by incorporating spatially distributed entities in a cycle of sensing, sharing, and decision-making procedures [35]. Thanks to the collective robustness introduced by the diversity of their physical  
\begin{table}
\begin{tabular}{|p{56.9 pt}|p{113.8 pt}|p{113.8 pt}|} \cline{2-3} \multicolumn{1}{c|}{} & \multicolumn{1}{c|}{Pros} & Cons \\ \hline Mode [23, 27, 39] & Reactive & Reduced sensing operation and related overhead & Limited knowledge of spectral condition \\  & & Higher transmission throughput & Delay if frequency adaptation is needed before transmission \\ \cline{2-3}  & Proactive & Updated knowledge of spectrum characteristics Quick in finding available channels & Higher energy cost Affected throughput \\ \hline Duration [26, 42, 44, 45, 46] & Long & More statistics leading to better accuracy & Higher energy cost Affected throughput \\ \cline{2-3}  & Short & Longer lifetime Less disruption to transmissions & Suboptimal sensing results \\ \hline \end{tabular}
\end{table}
Table 2: Tradeoffs for sensing configurations.  
surroundings and spectral conditions, the chance of getting defective or compromised sensing results is reduced, leading to improved reliability compared with non-cooperative schemes [50, 51].  
In the following, some primary aspects of cooperative spectrum sensing are visited. First, the topological organization of the cooperation is discussed. Then, mechanisms for temporal coordination of sensing activities are reviewed. Afterward, two types of method for adaptive decision formulation are described and compared. Finally, a summary of cooperative sensing is provided.
# Improvement of Aerodynamic Performance of Savonius Wind Rotor Using Straight-Arc Curtain
## 4 Results and Discussion
### Dynamic Performance  
To explore the effect of Curtain-c on the dynamic performance of the rotor, the same numerical method as that described in Section 4.1 is used to calculate the mean power coefficients of the wind rotor with and without Curtain-c. Then, the changes in the mean power with the \(TSR\) are used for their comparison. The numerical results are shown in Figure 18.  
Figure 17: Static torque coefficients for different parameters (\(\theta=165^{\circ}\)).  
Figure 18: \(Cont.\)  
Figure 18 shows that the wind rotor with Curtain-c exhibits great improvement in the power coefficients compared with the conventional Savonius wind rotor. The power coefficients increase with increasing \(TSR\) up to a certain maximum value, beyond which they decrease with further increase in the \(TSR\). In addition, the variation of the power coefficient is similar at different Reynolds numbers.  
The Figure also shows that the maximum mean power coefficient obtained with the wind rotor with Curtain-c is about 0.303 at \(TSR\) = 0.8 and without curtains it is about 0.20 at \(TSR\) = 0.78 when the wind velocity is 10 m/s. The maximum power coefficient of the rotor with Curtain-c is approximately 1.5 times higher than that of the rotor without curtain. The results prove that the straight-arc curtain can effectively improve the dynamic performance of the rotor and increase the power coefficients.
## 2 Methods  
### Impact of the Curved Surface  
All the formulas and protocols for measuring the performance of PV modules are based on the precondition that the PV modules are flat. For example, it is essential to determine the output power and other fundamental electrical parameters such as the short-circuit current (Isc), open-circuit voltage (Voc), and fill factor (FF). The aperture area of the curved PV device differs from the surface of the module. The vehicle roof is curved three-dimensionally. Its curvature can induce power loss through cosine and self-shading losses. The orientation of the VIPV varies with time without any correlation with the orientation of the sun. These factors have different effects on a curved shape. These interactions also need to be considered.  
The efficiency of curved modules is generally overestimated [68]. Solar simulators frequently underestimate the input energy. The aperture area of a standard flat PV device is equal to the active area of the module. However, this area is not on a curved surface because the aperture area is defined as the window of the flat plane.  
First, a curved PV module generally collects more light than an aperture window. As the solar simulator illuminates a larger area than the PV module, a curved module receives more unexpected light from the outer region to generate more unexpected power, because the aperture area and the area of the active area of curved PV devices are different (the active area is more substantial than the aperture area). However, they are the same for flat PV devices. Placing an aperture mask on a curved PV module is a highly effective alternative.  
The second reason is the aperture area. The area of the active zone of the curved PV device is not clearly defined.  
The third cause is the angular distribution difference between indoor and outdoor VIPV operations. Depending on the points on the surface, curved PV devices induce larger illumination losses at higher incident angles. Unlike flat PV modules, this approach cannot be applied to improve the efficiency of indoor modules in outdoor operations. It is essential to correct the curved shape.  
Also, this study covered a surface containing a flat zone in the curved surface or an entire flat plane. Based on differential geometry, the equations used in this study cover flat planes, which is the particular case for the curved surface. Note that the input is the X, Y, and Z coordinates, and we did not use equations that potentially lead to division by zero.