esa-sceva/satcom-chunk-collection huggingface dataset:
# Paraphrase Identification with Lexical, Syntactic and Sentential Encodings
###### Abstract  
Paraphrase identification has been one of the major topics in Natural Language Processing (NLP). However, how to interpret a diversity of contexts such as lexical and semantic information within a sentence as relevant features is still an open problem. This paper addresses the problem and presents an approach for leveraging contextual features with a neural-based learning model. Our Lexical, Syntactic, and Sentential Encodings (LSSE) learning model incorporates Relational Graph Convolutional Networks (R-GCNs) to make use of different features from local contexts, i.e., word encoding, position encoding, and full dependency structures. By utilizing the hidden states obtained by the R-GCNs as well as lexical and sentential encodings by Bidirectional Encoder Representations from Transformers (BERT), our model learns the contextual similarity between sentences effectively. The experimental results by using the two benchmark datasets, Microsoft Research Paraphrase Corpus (MRPC) and Quora Question Pairs (QQP) show that the improvement compared with the baseline, BERT sentential encodings model, was 1.7% F1-score on MRPC and 1.0% F1-score on QQP. Moreover, we verified that the combination of position encoding and syntactic features contributes to performance improvement.  
paraphrase identification; encodings, R-GCNs; BERT; contextual features +
Footnote †: journal: Medical Image Processing  
1
## 5 Results and Discussion
### Modified Shaft Resistance  
The mobilized shaft resistance was further calculated, Figure 9 presents the distribution of shaft resistance for shafts TS1 and TS2.  
It can be observed from Figure 9 that the shaft resistance at various depths after grouting is greater than that without grouting under the same load. For example, 1t silty clay at depths between 21.4 and 29.4 m, the maximum shaft resistance values for shafts TS1 and TS2 were 52 kPa and 82 kPa, respectively, when the load was determined to be 2 \(\times\) 9.0 MN.  
In addition, the shaft-soil relative displacement was calculated based on the axial force. It should be noted that the relative displacement of shaft and soil at a specific depth is considered to be equal to the displacement of shaft. Hence, Figure 10 presents the curves of shaft resistance and relative displacement for the shaft and soil at various depths. It can be seen from Figure 10 that the grouted shaft (TS2) can be mobilized with significantly higher shaft resistance than the control shaft (TS1) for the same relative displacement. Furthermore, Figure 10a, c shows that the shaft resistance at the specific soil and depth can be more fully developed due to its adjacent to the grouting pipe. For instance, the shaft resistance of the soil layer within the depth of 4.4-10.0 m of test shaft TS2 was more fully exerted than that in the depth of 0-4.4 m. Moreover, the shaft resistance at sections farther away from the grouting pipes was also enhanced, which indicates that the cement slurry was driven by pressure to migrate along the axis. For example, the shaft resistance of grouted shaft TS2 in the soil layer within the depth range of 0-4.4 m has an increase compared with ungrouted shaft TS1. It can also be seen in Figure 10b that the enhancement effect of the post-grouting craftwork on the resistance of the shaft is related to the type of soil along the shaft. For instance, the shaft resistance in the soil layer 3 Coarse sand is more significantly mobilized after grouting than that in the deeper layer 1t Silty clay. Additionally, Figure 10c shows that the soil layer close to the shaft tip of grouted shaft TS2 has a higher strength and stiffness than soil layers of the same type and different depths. Figure 10c shows that for 1t Silty clay, the soil at the tip of shaft TS2 has higher strength and stiffness than the other depths after grouting.  
Figure 9: Distributions of shaft resistance. (**a**) TS1. (**b**) TS2.  
As a conclusion, the soil surrounding the shaft can be stronger and stiffer through the post-grouting technique. The shaft resistance can further be mobilized at a smaller shaft-soil relative displacement. The effect of post grouting to improve the mechanical properties of the soil around the shaft is related to the type of soil, and the enhancement effect is more significant for cohesionless soil.
## 2 Literature Survey
To combat underwater interference, the Maximal Ratio Combining method is used for the receiving end, while the multi-layer perceptron (MLP) technique is utilized to mitigate nonlinear deficiencies. The deep neural network (DNN) outperforms the least mean square equalizer. A digital low-pass filter and a high-pass filter are then used to separate the received signal into two parallel streams. However, excessive nodes make the NN more complex, and the update process only partially mitigates distortion [23]. The significant nonlinear distortions of underwater PAM8 VLC channels may be effectively compensated for by a \"Gaussian kernel-aided deep neural network (GK-DNN) equalizer\" [24]. Incorporating categorical variables is challenging, as Gaussian mixture models need to be better suited to categorical data, assuming all features are typically distributed. The performance of deep learning (DL) methods for AMC in VLC systems is empirically examined [25]. Yet, the majority of active learning (AL) methods for VLC systems rely on AMC techniques that necessitate a substantial amount of labeled training information that is challenging to get in practical systems. Article [26] examined the effectiveness of the suggested ocean monitoring system, which links marine and terrestrial life. The communication system is supported by a satellite link for constant real-time monitoring and all-encompassing coverage. Underwater visible light communication (UVLC) is used to transfer sensor data from several sensor nodes (SN) positioned at various depths to underwater vehicles (UV). For a single chip silicon-substrate light-emitting diode (LED) based underwater visible light communication (UVLC), we build a real-time discrete multi-tone (DMT) transceiver based on FPGA chips [27].
## 2 Design of the Proposed DDL-TDC
### Architecture of DDL-TDC  
Figure 3 illustrates the architecture of the proposed DDL-TDC, in which two TDLs are incorporated in the calibration circuit and a real-time FSM is implemented upstream of the TDL-TDC output. The proposed FSM has two calibration mapping memories; these memories control the two delay lines to do calibration or run TDC conversion. For this reason, the DDL-TDC can run calibration and conversion based on the control signal from the proposed FSM. Figure 4 presents a flowchart for two FSMs that manage calibration and output. The calibration FSM(_FSM Cal_) has three states:  
* _Init_: As the TDL enters calibration mode, the FSM transitions to the _Init_ state. In this state, calibration memory will be reset to zero for all addresses, and the system begins to run code density counts. The calibration memories, _Cal_Mem A_ and _Cal_Mem B_, include 512 8-bit words; thus, 9-bit addresses must be reset.
* _Cal_Run_: Code density counts are run in this state to calibrate the time distribution corresponding to the delay line that will be calibrated. For this, \(2^{17}\) counts are run for the _Cal_Run_ state to obtain the time distribution based on the code density test scheme [33].  
* _Cal_Num_: After _Cal_Run_, the _Cal_Num_ sums the hit counts for each delay cell. Then, the time distribution can be converted to time delay. These items of time information are stored within the calibration memory ((_Cal_Mem A_ or (_Cal_Mem B_) appropriate for the relevant cell delay. Thus, the TDC output code can be calibrated from this calibration mapping memory.  
Figure 3: Architecture of DDL-TDC.  
Figure 2: Layout view of two delay chains in the proposed FPGA-based DDL-TDC.  
The conversion FSM (_FSM Output_) includes just one state (_Run_TDC_), in which the time delay is converted into digital code based on data in the calibration memory. According to _FSM Cal_ and _FSM Output_, the proposed TDC can always calibrate the delay cell. TDL-A runs DNL calibration and updates calibration mapping codes in the calibration memory _Cal_Mem A_, while TDL-B simultaneously performs conversions based on _Cal_Mem B_. Following the calibration of TDL-A, TDL-B calibrates the DNL and updates the mapping code in _Cal_Mem B_, while TDL-A simultaneously runs the conversion. The proposed DDL calibration circuit is able to perform calibrations in real time and shows excellent performance in terms of time linearity.
# A Hybrid IVFF-AHP and Deep Reinforcement Learning Framework for an ATM Location and Routing Problem
## 5 Discussion and Implications
Unlike the literature, they propose an innovative methodology that combines ATM location selection with IVFF-AHP and cash transportation route optimization with DDQN-RL. Unlike the heuristic method applications in the literature, the application of DRL in the routing of cash transportation vehicles provides the advantage of adapting to changes in ATM distribution networks without requiring retraining and flexibility and sustainability in cash transportation operations. Its sectoral contribution is aimed at banks and logistics service providers. With the proposed methodology, banks optimize ATM location selection and improve customer satisfaction and operational costs, while logistics companies optimize cash transportation routes, increasing security and efficiency.
## 4 Experimental Evaluation
### Experimental Scenarios and Settings  
This section evaluates communication performance by IEEE 802.11 ad in the following three scenarios:  
Scenario 1 (S1): antenna direction;  
Scenario 2 (S2): distance between STA and AP;  
Scenario 3 (S3): multiple STAs.  
S1 evaluates the impact of antenna direction on communication performance due to a highly directional link from IEEE 802.11 ad, and S2 examines the relationship between distance and communication performance. Finally, S3 evaluates communication performance affected by two STAs at different distances. Note that the experiments are based on the topology of (a) in Figure 1.  
As for the experimental settings, the stations (STAs) and access point (AP) use an Intel(r) NUC Kit NUC7i7 DNHE [38] attached with an SX-PCIAD [39], which implements IEEE 802.11 ad in the 60 GHz band. They use Ubuntu 16.04.6 LTS, and the hostapd software [37] is run to work as an AP.  
The three tools execute simultaneously during measurement. The tool _ipref3_ measures TCP and UDP communication performance, while for TCP measurement, the server and  
Figure 1: Measurement overview.  
client programs run on the AP and STA sides; in UDP measurement, the STA sends data to the AP at 2 Gb/s. In addition, _ping_ obtains the indicators, including the RTT and packet loss, every 100 msec, and then _iw_ works to get the wireless information every 500 msec. Note that a one-minute measurement is executed ten times.
## 4 Simulation Studies
### Throughput  
This metric shows the amount of data transmitted from a source to a destination per time unit over a communication link. It is measured in bits per second [28].  
\[Average\ Throughput=\frac{PDR}{ST-SPT} \tag{12}\]  
\(PDR\) stands for packet delivery ratio, and \(ST-SPT\) stands for start time and stop time.
## 2 Materials and Methods  
### Engineering-Driven Methodology  
In this study, a systematic and engineering-driven approach was implemented having the structural design as the central process, based on analytical assumptions and simplified numerical models. The deployment site and the MMFAR requirements and functions were also considered as problem variables. Subsequent numerical analysis (CFD and FSI) and experimental characterization for detailed characterization of innovative materials and structural systems were also acknowledged. This approach is represented in Figure 1, and in this research the focus is mostly on processes 1 to 5, directly related to the structural design, summarized as follows:  
1. **Concept and geometric design:** in this stage, with the MMFAR objectives established, the process selects the site location and collects environmental data on physical and biological aspects. The design of shapes and dimensions is undertaken with the objective of meeting functional requirements. Stakeholders, including experts and the local community, participate actively.
2. **Constructive approach:** the development of cross-sections and 3D models is initiated. It considers materials, structural systems, constructive processes, and durability specifications. These aspects must prevent marine pollution and establish a support that meets technical and functional requirements. Logistics and construction techniques are also considered.
3. **Site location and sea conditions:** the analysis of the site location results in the identification of specific actions affecting the structure, such as dead, live, environmental, and accidental. Environmental actions are among the most important. The actions and load combinations follow the recommendations from ISO, API, DNV, and NOR-SOK [2; 3; 4; 5]. Historical site data and prediction models are used to account for time and space variability.
4. **Structural model:** the effects of the loads are obtained from a simplified numerical simulation. For that, the numerical model is discretized in bar elements, and a linear-elastic quasi-static analysis is performed. The materials, section properties, and supports are defined, along with load cases and combinations. The results are the axial (N), shear (V), flexural (M), and torsional (T) stresses for safety verifications.
5. **Cross-section design:** determines the load capacity based on material strength and cross-section dimensions, checking limit states to assess performance and feasibility. A parametric study explores various structural combinations in order to identify the promising solutions. This approach optimizes the cross-section, eliminates less promising options, and encourages new structural systems.  
Figure 1: Design flowchart.
# Exploring the Evolution of Drought Characteristics in Balochistan, Pakistan
###### Abstract  
In the wake of a rapidly changing climate, droughts have intensified, in both duration and severity, across the globe. The Germanwatch long-term Climate Risk Index ranks Pakistan among the top 10 countries most affected by the adverse effects of climate change. Within Pakistan, the province of Balochistan is among the most vulnerable regions due to recurring prolonged droughts, erratic precipitation patterns, and dependence on agriculture and livestock for survival. This study aims to explore how the characteristics of droughts have evolved in the region from 1902-2015 using 3-month and 12-month timescales of a popular drought index, the Standardized Precipitation Evapotranspirationpid Index (SPEI). The region was divided into six zones using Spatial \"K\"luster Analysis using Tree Edge Removal (SKATER) method, and run theory was applied to characterize droughts in terms of duration, severity, intensity, and peak. The results of the non-parametric Mann-Kendall trend test applied to SPEI indicate prevailing significant negative trends (dryer conditions) in all the zones. Balochistan experienced its most severe droughts in the 1960s and around 2000. The effects of climate change are also evident in the fact that all the long duration droughts occurred after 1960. Moreover, the number of droughts identified by 3-month SPEI showed a significant increase after 1960 for all six zones. The same trend was found in the 12-month SPEI but for only three zones.  
climate change; drought events; drought characterization; SPEI; Balochistan Article
# A Review on the Performance of Concrete Containing Non-Potable Water
## 1 Introduction  
Depletion of fresh water resources has increased due to climate changes, urbanization and industrialization [1, 2]. Extraction of fresh water more than its natural supply has also increased concerns for sustainability. With the increasing demand for new infrastructure accompanying massive urbanization, the production of concrete and other building materials has increased enormously over the previous 50 years, with _per capita_ growth rates higher than that of the population [3, 4]. Due to the advantages of low cost and formability, concrete has experienced massive growth in its demand compared to other construction materials. Fresh water plays an important role in the different phases of concrete production and construction, i.e., aggregates cleaning, mixing, and curing of concrete, and cleaning of machinery and batching plants. [PERSON] et al. [1] reported that 9% industrial extraction of fresh water is used by concrete industry, which accounts for up to 1.7% of the total extraction of fresh water.  
The concrete industry can be considered one of the largest water-consuming sectors. As reported in [5], about 150 litres of water are needed per m\({}^{3}\) of concrete. This value can increase to 500 litres per m\({}^{3}\) of concrete by considering washing and losses during the production and transportation stages of concrete [6]. The wastewater (WW) generated by this activity can be considered a hazardous substance due to the presence of heavy metals and its high pH [7]. Furthermore, mandatory chemical boundaries, other limits,and general guidance on the type and amount of impurities of concrete mixing water are collected in [8].  
To overcome the above issue, some studies suggest that, apart from potable water, treated heavy industry [9], treated palm-oil mill [9], fertilizer factory [10], reverse osmosis filter [11], polished filter [12], sugar factory [10,11], stone slurry [13], tanning industry [13], polyvinyl acetate [14], textile factory [10] and service station [10] WW can be used as mixing water in concrete. Nevertheless, studies on this path are still very scarce. Additionally, there is not an extensive review study to show the effect of different types and various incorporation ratios of WW on the performance of concrete.  
Accordingly, this study focused on the mentioned gaps and collected all relevant studies on treated and untreated WW as mixing water in concrete. Furthermore, the focus of this study is mainly on the effect of WW as \"mixing water\" rather than its effect as curing water. In addition, some of the properties such as carbonation have not been considered because there were not many reliable sources.
# Student's t Kernel-Based Maximum Correntropy Criterion Extended Kalman Filter for GPS Navigation
## 4 Results and Discussion
### Environment 2: Impact of Outliers in a Time-Varying Noise Environment
With modern embedded hardware and optimization techniques, the STMCCEKF can be implemented in real-time navigation systems without significant performance bottlenecks.
## 3 Methodology
### Criteria Weight Determination Using AHP-MEREC Approach  
Selecting an appropriate criteria-weighting method for a specific multi-criteria decision-making problem is a challenging task. Various subjective, objective, and integrated approaches can be used for this purpose. [PERSON] et al. [54] conducted a comprehensive review of the criteria-weighting methods proposed in the last decade, including the FUCOM [55], SAPEVO-M [56] and MEREC [57] approaches. A significant increase in the number of publications related to MEREC (Method based on the Removal Effects of Criteria) was detected [58]. It is an objective criteria-weighting method, which analyses criteria removal effects to calculate objective weights. MEREC is also capable of minimising the influence of subjective preferences on the criteria weights. This is different from Entropy [59] which is another widely used criteria-weighting approach calculating criteria weights, based on the randomness of the analysed data.  
Integrated criteria-weighting approaches are often proposed to reduce potential biases and inconsistencies that may arise from using single methods [24]. The Analytic Hierarchy Process (AHP) [22] is a widely used subjective criteria-weighting method that retains its popularity due to its effectiveness in analysing complex decisions. AHP also allows for the consideration of both qualitative and quantitative information, making it suitable for the decision-making problem presented in this paper.  
The integration of the subjective AHP and objective MEREC approaches could be beneficial in providing a more holistic and comprehensive assessment of the criteria weights, taking into account both the preferences of decision-makers and the removal effects of criteria. However, to the best of our knowledge, there are no studies proposing AHP and MEREC integration. Thus in this paper, we present the novel AHP-MEREC integrated criteria-weighting approach, which aims to leverage the strengths of both methods, making it suitable for working with both objectively and subjectively gathered data.
## 5 Conclusions  
The InSAR technology progress and development trends introduced in this article mainly include repeat-pass interferometry and single-pass interferometry. In recent years, the number of SAR satellites launched has been increasing continuously, especially after commercial satellite companies joined the ranks of developing and launching SAR satellites. Moreover, due to the limitations of weather conditions, meaning that optical satellites cannot achieve all-weather earth observation, countries around the world need SAR satellites to fill the observation gaps of optical satellites.  
Repeat-pass interferometry includes D-InSAR technology, PS-InSAR technology, and SBAS-InSAR technology, and its main application field is surface deformation observation. Traditional repeat-pass interferometry has a long revisit period, which means it cannot meet the timeliness requirements of emergency disaster reduction. Earth-synchronous orbit SAR satellites have a short revisit period and are not affected by weather and night images, and can achieve high-precision feedback for surface deformation products and timely warning.  
Single-pass interferometry includes CT-InSAR and AT-InSAR technologies. CT-InSAR technology is mainly applied in DEM and DSM generation, as well as sea surface elevation measurement, while AT-InSAR technology is mainly applied in ocean surface current field measurement and moving target detection. Traditional single-baseline earth observation has a single dimension, and fixed baselines cannot adapt to different terrains and sea conditions. Development towards multi-satellite and multi-baseline capability is conducive to achieving multi-dimensional high-precision measurement.  
We are proud to demonstrate that China has made substantial progress in the development of SAR systems, establishing a spaceborne SAR constellation that spans multiple frequency bands, imaging modes, and orbital configurations. Satellites such as the GF-3 series and the Land Exploration series have been widely applied in surface monitoring,disaster response, and deep space exploration. The systematic advancement of China's SAR missions continues to enhance its influence and technological leadership in the global InSAR field.  
Conceptualization, Q.Z. and H.F.; methodology, Q.Z. and H.F.; formal analysis, Q.Z., Y.Z., and H.F.; investigation, H.F.; resources, Q.Z. and Y.Z.; data curation, Y.Q. and H.F.; writing--original draft preparation, Q.Z. and H.F.; writing--review and editing, H.F. and Y.Q.; visualization, Y.Z. and H.F.; supervision, Y.Q. and Y.Z.; project administration, Q.Z. and H.F.; funding acquisition, Q.Z. and Y.Z. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the National Science Fund under grants 62201573, 62031005 and 42104039. This work is supported in part by the National Key R&D Program of China #2023 YFB3904902, #2023 YFB3904900.  
The authors appreciate the anonymous referees for good suggestions in improving the paper's quality.  
The authors declare no conflicts of interest.