esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Tender Types
### General Tender  
This type is a contract that deals directly with a local or international contractor, and it is performed through a competitive bidding process [50]. The accomplishments of the GT's run have resulted in the distribution of contracts achieved via global tenders, benefiting both local contractors within Saudi Arabia and those from abroad. According to data gathered by the BGT, local contractors have accounted for an average of 80-84% of the total contracts awarded, encompassing various contract types, during the previous twenty years. The majority of these contracts pertain to relatively smaller- to medium-sized undertakings related to urban infrastructure. Only a minority, around 20-32%, constitute the scope of megaprojects within the public sector. These megaprojects are often related to large-scale transportation systems and major developments in the energy sector. Most of these contracts are small- and medium-scale projects involving city infrastructure. Only 20-32% of public works are megaprojects [34; 39; 40].  
Previously, the General Tender (GT) exclusively applied the FIDIC Conditions of Contract for Construction as its General Conditions. However, the Arab Contractors Club from the KSA requested the GT to issue contract forms that are applicable to the Saudi Arabian construction market. There were significant differences between the FIDIC's 1987 version and Saudi Arabian construction practices, as well as the local legal system. As a result, the \"NEW GT Contract\" was issued in 1999, specifically developed for the Kingdom of Saudi Arabia. The GT asks contracting parties to amend the prescribed contract forms, considering the parties' agreement as Special Conditions [51; 52; 53; 54]. The Saudi Council of Ministers has established a body to regulate the performance, auditing, and decreeing of tendering procedures for the allocation of Saudi public works contracts. This body is known as the Board of the General Tender (GT), and all public works contracts are tendered by the GT, an independent regulatory body. The BGT has published contract forms for this purpose. Although many clients want to use their own standard contract forms due to special contract conditions or penalties, the BGT usually rejects these requests. Difficulties with this type include the standardization of contract forms and ensuring fairness in the tendering process. The GT has implemented strict guidelines and evaluation criteria to address these challenges and promote transparency and equal opportunities for all bidders [5; 51].
# A Fault Section Location Method for Distribution Networks Based on Divide-and-Conquer
## 3 Recursive Structure of Fault Location for the Distribution Network
### Recursive Structure  
The core idea of DAC is to apply the recursive structure to solve the target problem in a reduced dimension. Specifically, DAC follows a divide-conquer-combine approach in each level of recursion: it breaks the problem into several subproblems that are similar to the original problem but smaller in size, solves the subproblems recursively (if the subproblem satisfies the \"bottoms out\" condition, the recursion is stopped and the solution is solved directly), and then combines these solutions to create a solution to the original problem.  
From this, we can deduce the prerequisites for applying DAC to solve the target problem; that is, the target problem should have the following recursive structure.  
* The original problem and the subproblem should have the same descriptive form.
* When the \"bottoms out\" condition is satisfied, it enters the \"base case\" and can be solved directly.
* If the condition of \"bottoms out\" is not satisfied, it enters the \"recursive case\", and the solution of the original problem can be created by combining the solutions of the subproblem.  
This section discusses the description of the subproblem, the base case, and the recursive case of the fault section location for the distribution network, and the construction of the recursive structure of the fault location problem is described.
# An Ensemble Approach for Speaker Identification from Audio Files in Noisy Environments
## 5 Conclusions  
In this article, we present a novel approach to speaker recognition in noisy environments utilizing voice activity detection (VAD), a multilayer perceptron (MLP) classifier, and a softmax activation function. We conducted a series of experiments to demonstrate the effectiveness of these techniques in addressing the challenges of speaker recognition under noise. The results of our study show that the proposed system, which combines MFCCs with VAD and softmax, significantly outperforms the two baseline systems. Furthermore, we observed that the MLP classifier delivers superior performance compared to Long Short-Term Memory (LSTM) and Bidirectional LSTM (BiLSTM) classifiers for the speaker recognition task. Our findings indicate that using VAD, an MLP, and softmax with MFCC features provides a robust solution for speaker recognition, especially in noisy environments. This suggests that the MLP classifier, when combined with these techniques, offers a more reliable and efficient approach for handling noise in speaker recognition tasks.  
Conceptualization, S.S.Z.; methodology, S.S.Z.; software, E.M.; validation, A.N., M.H.A. and S.K.u.Z.; formal analysis, M.H.A. and A.N.; investigation, S.S.Z.; resources, S.S.Z., M.H.A. and E.M.; data curation, S.S.Z. and S.K.u.Z.; writing--original draft preparation, S.S.Z.; writing--review and editing, E.M. and S.K.u.Z.; visualization, M.H.A. and A.N.; supervision, M.H.A.; project administration, A.N.; funding acquisition, S.S.Z. and A.N. All authors have read and agreed to the published version of the manuscript.  
The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, KSA for funding this research work through the project number \"NBU-FFR-2024-1180-02\".  
Not applicable.  
The data associated with this research will be made available from the corresponding authors upon reasonable request.  
The authors declare no conflicts of interest.  
The following abbreviations are used in this manuscript:  
VAD Voice Activity Detection  
MLP Multilayer Perceptron  
LSTM Long Short-Term Memory  
BiLSTM Bidirectional Long Short-Term Memory  
ASR Automatic Speech Recognition  
DNN Deep Neural Network  
RNN Recurrent Neural Network  
Figure 18: Validation MSE of the three models.
# Parametric Investigation of Die-Sinking EDM of Ti6 Al4V Using the Hybrid Taguchi-Rams-RATMI Method
## 2 Experimental Methodology
### Machining Setup  
The experiment was carried out using a copper tool and MET-L-COOL EDM 30 oil (submerged with flushing) as the electrolyte on a die-sinking NC EDM machine (ELECTRONICA EMS-5535, Electronica India Limited, Kolkata, India). The flushing pressure was set at 0.5 kg/cm\({}^{2}\) (7.1 psi). For each material, spark gaps of 50 \(\upmu\)m on either side are taken into account for the electrode diameter. For finishing activities, the aforementioned structure is typically taken into account. In order to achieve a larger material removal rate when the discharge energy increases, a transistor pulse (TP) power circuit method--which is the most versatile circuit according to previous research--is applied. The oscillation circuit that is chosen determines the current setting, voltage setting, duty cycle (the percentage of the on time compared with the overall cycle time), and the on time (during this period the voltage is applied across the wire electrode and job). Thousands of pulses are produced every second by a TP circuit, which also results in shorter pulse intervals. The work's surface hardness, material removal, and surface polish are largely determined by the interaction of these three variables. Given that the material Ti6 Al4V has a high hardness value, a maximum current of 50 Amps is specified. In order to obtain the appropriate surface smoothness and to avoid arcing or burning of the sparked surface, the spark gap, also known as the arc gap, must be maintained. The operation's speed is also determined  
Figure 2: Experimental setup (**a**) EDM machine, (**b**) Copper tool (**c**) Machining process and (**d**) Machined specimen.  
by the spark gap. Greater and coarser material removal and a rougher operation are associated with larger spark gaps. Where a finer finish is needed, a smaller spark gap is maintained, which takes more time. For every run, the same 5 min of machining time were used. Additionally, a 0.1 mm overcut was preserved. Leica M50 optical microscope (Leica, Wetzlar, Germany) equipped with depth measuring capabilities was used to quantify the depth of the incision, and MRR was computed by taking TWR, the beginning and final weight of the tool and workpiece after machining, the dimensions of the workpiece area to be machined, and the machined cavity after the EDM process; the surface roughness was assessed using a surface roughness tester (Mitutoyo SURFEST SJ-410, Mitutoyo, Kawasaki, Japan) (Figure 3). A total of twenty-seven experimental runs were planned utilizing the parameters in [PERSON]'s plan. SEM micrographs analysis was performed JEOL JSM-6480 LV (JEOL Ltd., Tokyo, Japan) scanning electron microscope (SEM).
## 2 Study Area
### Typical Years Selection and Water Demand Analysis  
The section flows of Hedongdian and Shengxiancun hydrological stations were considered the inflow of Shimen and Jiaoyan reservoirs, respectively. The designed runoffs of Shimen reservoir under 25%, 50%, and 75% inflow frequencies were \(1.36\times 10^{9}\) m\({}^{3}\), \(9.00\times 10^{8}\) m\({}^{3}\), \(6.65\times 10^{8}\) m\({}^{3}\), and \(4.41\times 10^{8}\) m\({}^{3}\), respectively. The designed runoff of Jiaoyan reservoir under 25%, 50%, and 75% inflow frequencies were \(1.21\times 10^{9}\) m\({}^{3}\), \(8.93\times 10^{8}\) m\({}^{3}\), \(7.00\times 10^{8}\) m\({}^{3}\), and \(4.94\times 10^{8}\) m\({}^{3}\), respectively. Figure 2 shows the inflow processes of the Shimen and Jiaoyan reservoirs.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Parameter Category**} & **Dead** & **Normal** & **Flood** & **Total** & **Utilizable** & **Installed** & **Maximum Flow** & **Minimum Flow** \\  & **Water** & **Water** & **Control** & **Storage** & **Capacity** & **Capacity** & **Through Water** & **through Water** \\  & **Level** & **Level** & **Level** & **108  
The water supply objective of the Jiaoyan-Shimen parallel reservoirs mainly included urban-rural water demand, irrigation, and ecology of the downstream river. Among them, the urban-rural water demand and ecology were the same under different inflow frequencies. The comprehensive water demand mainly included the urban-rural water demand and irrigation. The comprehensive water demand under 25%, 50%, and 75% inflow frequencies were 4.83 \(\times\) 10\({}^{8}\) m\({}^{3}\), 5.07 \(\times\) 10\({}^{8}\) m\({}^{3}\), and 6.73 \(\times\) 10\({}^{8}\) m\({}^{3}\), respectively. The comprehensive water demand under a 95% inflow frequency was the same as that under a 75% inflow frequency. The ecological and comprehensive water demand processes are shown in Figures 3 and 4.  
Figure 2: Inflow processes in different typical years: (**a**) Shimen reservoir; (**b**) Jiaoyan reservoir.
# Comparisons of Spatially Downscaling TMPA and IMERG over the Tibetan Plateau
## 2 Materials and Methods
### Materials
#### 2.2.2 TRMM Satellite Precipitation Dataset  
The TRMM was launched in November 1997 through cooperation between NASA and JAXA to monitor and investigate tropical and subtropical rainfall system. The TMPA employed inputs from two different types of satellite sensors. The primary data source was from precipitation-related microwave sensors, including the TMI, Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Sounding Unit (AMSU) and the Microwave Humidity Sounders  
Figure 1: Spatial distribution of gauge stations and the Digital Elevation Model (DEM) over the Tibetan Plateau (TP).  
(MHS). Additionally, the second major data source for the TMPA was the geo-infrared (IR) data. Precipitation information collected from these sensors were combined to generate precipitation estimates. The TMPA 3B43 Version 7 monthly precipitation products were published for free at a spatial resolution of 0.25\({}^{\circ}\) for latitudes from 50\({}^{\circ}\) N-50\({}^{\circ}\) S worldwide [12]. The TMPA 3B43 V7 spanning from January 2015 to December 2015 were employed in this study and it were obtained from the Precipitation Measurement Mission (PMM) website ([[http://pmm.nasa.gov/data-access/downloads/trmm](http://pmm.nasa.gov/data-access/downloads/trmm)]([http://pmm.nasa.gov/data-access/downloads/trmm](http://pmm.nasa.gov/data-access/downloads/trmm))). Annual precipitation was obtained by accumulating monthly TMPA precipitation in the year.
## 3 Topological Classification
### Hybrid FCS and Battery System  
The most prevalent topology for the FCHEV is the combination of FCS and battery, which is characterized by its established industry chain and low production costs [32; 33; 34]. This configuration has the fuel cell energy serving as the principal energy source, supplemented by the battery during peak demand or sudden load change, and recapturing energy during regenerative braking mode. This topology helps reduce the impact of high current required from the FCS during high-load conditions or a sudden load change, and also improves the overall efficiency [35; 36]. The connection between the FCS and the battery can be differentiated into four categories, including a direct parallel connection of both the FC and battery, direct parallel linking of only the FC, direct parallel linking of only the battery bank, and an indirect parallel linking of both the FC and battery. Each connection approach possesses its own distinctive features, which can impact the durability and the cost of the FCHEV. The further analysis of this hybridization will focus on these different connections.
## 2 Related Works
Virtual sensors combine data from diverse physical sensors to compute abstract measurements that are not directly observable, offering significant advantages such as increased flexibility, reduced costs, and enhanced reusability. The paper highlights the importance of virtual sensors in enabling more complex, domain-specific data aggregation and in-network processing in future sensor networks, emphasizing their potential to support adaptive, efficient, and scalable solutions for various applications. The authors also discuss the prototype implementation of the middleware that supports virtual sensors, allowing developers to specify high-level data requirements and dynamically reprogram sensor networks. In [23], the authors explore the concept of virtual sensors within the framework of the Missouri S&T sensor cloud, which connects various sensor networks spread across large geographical areas, enabling multiple users to access and interact with them on demand. Virtual sensors are essentially software representations of physical sensors that aggregate data from multiple physical sources to provide customized and efficient views for users, supporting applications like environmental monitoring or traffic flow analysis. These sensors are classified into several configurations such as one-to-many, many-to-one, and many-to-many, each designed to optimize data aggregation and ensure fault tolerance. Additionally, derived virtual sensors allow for more complex measurements by combining data from different sensor types. The paper details how these virtual sensors are managed through a multi-layered sensor cloud architecture, with distinct client-centric, middleware, and sensor-centric layers. The middleware layer plays a crucial role in provisioning, managing the lifecycle of virtual sensors, and facilitating communication between users and the physical sensors. While several approaches to virtual sensing techniques are available in the literature, there remains room for improvement in our prior forest fire prediction method [8], which combines virtual sensors with physical sensors. The primary objective of incorporating virtual sensors is to lower costs associated with monitoring while expanding the coverage area across the forest.
# Time-Varying Reliability Evaluation of Concrete Based on Carbonation Depth
## 2 Test Specimens and Experimental Result  
Most of structural concretes are exposed to environmental factors that cause corrosion. In order to guarantee structural safety, regular testing of structural components are conducted in every three years. In this paper, all data were obtained from these testing and all tested components were NAC, taken from several constructions in Yokohama, Japan, where the average temperature and humidity were 15.208 \({}^{\circ}\)C and 69%, respectively. In this experiment, the specimens were cast into cement mortar cylinders 80 mm in diameter and 100 mm in height to measure the material properties. To investigate the carbonation depths of the components, the cylinders were cut into two halves, and the fresh cuts were polished and cleaned. Then, 1% phenolphthalein solution was sprinkled on the cuts to observe the non-carbonated area, identified by pink color, which also reflected the boundaries of carbonated and non-carbonated zones. The carbonation depths of the specimens were obtained by measuring the carbonated area. Each specimen was tested repeatedly 10 times, and the resulting test data were averaged together to improve the measurement precision, which resulted in an accuracy of 0.1 mm.  
We obtained 13,198 tested data of carbonation depth from this experiment. Different from the investigations carried out in accelerated experiments, the specimens were taken from the natural environment. Therefore, the experimental results are more convincing, because the environmental factors were considered. In this paper, the data were divided into several groups according to different design values of concrete strength (\(f_{c}\)) and service ages, as shown in Figures 1 and 2.  
According to the experimental results, it was observed that a large number of specimens were uncarbonized. To investigate the initial carbonation rate, the data were divided into several groups according to \(f_{c}\) and to whether the concrete was carbonized. Then, the ratio of carbonized concrete to uncarbonized concrete at different service ages was determined, as shown in Figure 3.  
Figure 1: Statistics of carbonation depth (\(f_{c}\)\(=\) 18 N/mm\({}^{2}\)).  
Figure 2: Statistics of carbonation depth (\(f_{c}\)\(=\) 21 N/mm\({}^{2}\)).  
According to Figure 3, \(f_{c}\) had a negligible effect on the carbonation rate, and the carbonation ratio increased over time. The relationship between carbonation rate (CR) and time (\(t\)) is expressed as:  
\[CR(t)=0.0086t-0.147 \tag{1}\]  
where \(t\) is the service age in years.  
To carry out a further analysis of the effect of \(f_{c}\), the data of carbonation depth with respect to the service years varying from 42 to 46 years were used to plot the probability density distribution. As shown in Figure 4, the distributions of \(f_{c}=18\) N/mm\({}^{2}\) and \(f_{c}=21\) N/mm\({}^{2}\) were in good agreement, showing that the deterioration rates of these two groups were similar.
# 5G-IPAKA: An Improved Primary Authentication and Key Agreement Protocol for 5G Networks
## 3 Shortcomings of the 5G AKA Protocol
** In the latest version of the 5G AKA protocol, if \(K\) is leaked, then the penetrator can calculate \(K_{\textit{AUSF}}\) and \(K_{\textit{SEAF}}\) based on those messages transmitted in the past run of the protocol. As a result, the penetrator can decrypt those encrypted communication messages transmitted in the past run of the protocol. Therefore, the latest version of the 5G AKA protocol cannot provide perfect forward secrecy.
## 3 Results and Discussion
### RSM Modeling
shown in Figure 1a-e. From these graphics, it can be seen that the molasses' osmolality had a less significant effect on the microorganisms' viability than exposure time, which can be explained by the smaller tested experimental range of osmolality values (from 5500 to 7000 mmol/kg) compared with exposure times' experimental range (from 0 to 5 h). The minimal numbers of all the tested microorganisms, indicating maximal reduction, were obtained when exposed to molasses with maximal osmolality (7000 mmol/kg) at the longest exposure time (5 h). The highest minimal obtained number was for _Salmonella_ spp. (4.30 log\({}_{10}\)(cfu/g)), pointing to the highest resilience to the osmotic stress among tested microorganisms. The minimal obtained result for _E. coli_ was 3.19 log\({}_{10}\)(cfu/g), while the lowest minimal result was for _L. monocytogenes_ (1.00 log\({}_{10}\)(cfu/g)--below the level of detection), indicating on total reduction in this inoculated microorganism. The high levels of reduction in the present tested microorganisms in molasses, in addition to a high osmotic pressure environment, can be explained by the molasses' specific chemical composition. The obtained results are correlated with [PERSON] et al. [13], where the special antimicrobial activity of molasses' antioxidative compounds is demonstrated, especially the phenolic compounds on _L. monocytogenes_. [PERSON] et al. [46] also showed molasses' antioxidant capabilities and showed that they had high antibacterial activity toward the selected foodborne pathogens. RSM was chosen to develop the mathematical models of the selected microorganisms' viability exposed to the high-osmolality environment of molasses. Table 2 shows the results of the ANOVA of the RSM models. On the basis of experimental data, mathematical models were developed for the following microorganisms' numbers for molasses: _E. coli._, _L. monocytogenes_, _Salmonella_ spp., Enterobacteriaceaeae, and TPC. On the basis of these results, the statistically significant effects of independent variables (exposure time and molasses osmolality), together with their interactions on mathematical model responses, were analyzed. A second-order polynomial (SOP) in the form of Equation (1) for five responses (numbers of _E. coli._, _L. monocytogenes_, _Salmonella_ spp., _Enterobacteriaceae_, and TPC), in response surface methodology, is used. The results of Table 2 show that the values of the numbers for all the tested microorganisms (_E. coli_, _L. monocytogenes_, _Salmonella_ spp., _Enterobacteriaceae_, and TPC) were statistically significantly affected by both the independent variables, where the more influential variable was shown to be time. The SOP linear terms for exposure time and osmolality statistically significantly contributed to the formation of mathematical models for all tested microorganisms. The quadratic term for exposure time was statistically significant for all the analyzed microorganisms, except for _L. monocytogenes_. The cross products
## 3 Methodology and Data Sources
### Model Formulation  
Two-stage spatiotemporal multi-box (TSSTMB) modeling takes HTP as the calculation unit and treats the HWFGs and the receptor city as sub-boxes with a certain height, as shown in Figure 4. The plane size of the boxes is the area of the grids or city, and the height of the boxes is the PBLH when the air mass passes through the grids or city. The sub-boxes of the HWFGs are numbered as \(i\) (\(i\) = 1, 2,..., \(n\), in order, far from to near the receptor city), and the receptor city sub-box is numbered as \(rc\).  
The inflow concentration of SOB-caused PM\({}_{2.5}\), that is, the PM\({}_{2.5}\) concentration of the air mass carrying SOB-caused PM\({}_{2.5}\) before entering the receptor city after long-range transport, was estimated in the first stage. For simplicity, the SOB-caused inflow PM\({}_{2.5}\) concentration into the receptor city mentioned below is denoted as PM\({}_{2.5\text{-inflow}}\) concentration. In the second stage, the contribution of PM\({}_{2.5\text{-inflow}}\) concentration to the urban hourly average PM\({}_{2.5}\) concentration was estimated.