esa-sceva/satcom-chunk-collection huggingface dataset:
# An FPGA Based Energy Efficient DS-SLAM Accelerator for Mobile Robots in Dynamic Environment
###### Abstract  
The Simultaneous Localization and Mapping (SLAM) algorithm is a hotspot in robot application research with the ability to help mobile robots solve the most fundamental problems of \"localization\" and \"mapping\". The visual semantic SLAM algorithm fused with semantic information enables robots to understand the surrounding environment better, thus dealing with complexity and variability of real application scenarios. DS-SLAM (Semantic SLAM towards Dynamic Environment), one of the representative works in visual semantic SLAM, enhances the robustness in the dynamic scene through semantic information. However, the introduction of deep learning increases the complexity of the system, which makes it a considerable challenge to achieve the real-time semantic SLAM system on the low-power embedded platform. In this paper, we realized the high energy-efficiency DS-SLAM algorithm on the Field Programmable Gate Array (FPGA) based heterogeneous platform through the optimization co-design of software and hardware with the help of OpenCL (Open Computing Language) development flow. Compared with Intel i7 CPU on the TUM dataset, our accelerator achieves up to \(13\times\) frame rate improvement, and up to \(18\times\) energy efficiency improvement, without significant loss in accuracy.  
visual semantic SLAM; semantic segmentation; FPGA; hardware acceleration; mobile robots +
Footnote †: journal: Applied Sciences
# Systematic Review of Discrete Event Simulation in Healthcare and Statistics Distributions
## 4 Discussion
### Application Areas  
In terms of application areas, our analysis revealed that a significant portion of the case studies, i.e., 90 (25.8%) publications, focused on the Emergency Department (ED). This was followed by generic models, with 35 (10%) publications, and the Oncology Department, with 31 (8.9%) articles. This distribution pattern builds upon previous research that has identified these areas as particularly challenging for healthcare management and improvement.  
The prominence of DES articles in the ED and oncology areas can be attributed to the high complexity and variability of these healthcare systems. Both areas face challenges such as high patient volumes, limited resources, and unpredictable patient arrivals, especially in the Emergency Department, making it difficult to optimize patient flow and resource utilization. DES serves as a valuable tool for modeling and analyzing these intricate systems, enabling researchers to identify bottlenecks, analyze processes, and ultimately enhance patient outcomes.  
The majority of articles concentrate on the ED, which is a critical area due to its association with prolonged wait times, increased morbidity and mortality rates, and reduced patient satisfaction. Reducing wait times in the Emergency Department is a challenging task [33]. The ED is a highly dynamic service that requires frequent reviews and updates to minimize patient waiting times (WT), which directly impact other patients and can prevent the need for patient transfers to other hospitals during periods of saturation.  
Previous studies have demonstrated that DES has proven effective in improving the ED by reducing WT and increasing service capacity [34; 35; 36]. However, our analysis reveals that some healthcare departments, such as gynecology, urology, and obstetrics, among others, have a smaller number of publications.  
Figure 4 shows all the application areas identified in the reviewed articles.  
Figure 4: Medical departments and number of publications.  
Our analysis highlights its successful application across various medical departments, each presenting unique challenges and opportunities for process improvement.
# A Low-Cost Soft Robotic Hand Exoskeleton for Use in Therapy of Limited Hand-Motor Function
## 2 Materials and Methods
### Actuation Method
As the actuator force is applied to the palmar tendon and the finger is flexed, the torque applied to the DIP joint and in turn the force applied tangential to the radius of the circle centered on the DIP joint that contains the anchor point for the tendon increases. Thus, our determination of proper actuator torque was taken when the finger was at full extension, i.e., the worst-case scenario. A linear actuation stroke, shown as \(\Delta\)L in Figure 2a, was achieved by using the rotational motion of the DC motor to wind the palmar tendon around a spool. Position feedback was implemented by coupling a rotary potentiometer to the shaft of the DC motor using spur gears with a 2:1 potentiometer-to-motor shaft gear ratio in order to increase the tracking resolution of the potentiometer, as shown in Figure 3. The brushed DC gearmotors are 6 V high-power carbon brush (HPCB) micro metal motors with a gear ratio of 298:1, weighing 9.5 g each, with dimensions of 10 \(\times\) 12 \(\times\) 26 mm and 3 mm shaft diameter, stall torque of 0.034 kg*m at 1.5 A stall current and output power of 0.65 W at maximum efficiency. The motors were driven by dual TB6612 FNG motor drivers, which can control two motors each at constant current of 1.2 A (3.2 A peak). The potentiometers are 10 k\(\Omega\) linear taper. The spur gear, the spool with the spur gear, the housing and enclosure for the custom actuator mechanism were 3D-printed. These custom actuators achieved the mechanical requirements needed for anthropomorphic actuation as well as being low-cost, non-proprietary and easy to assemble. Figure 2: (a) Joint control diagram. (b) Fingertip force vs. angle of distal phalange.
# Chinese Text Classification Model Based on Deep Learning
## 5 Results
### Overall Performance  
Both SST-1 and SST-2 datasets are employed to compare the performance of different methods. As shown in Table 1, our model is compared with some well-performed models from different areas, such as Support Vector Machine(SVM), Recursive Neural Network, Convolutional Neural Network,and Recurrent Neural Network. Specifically, for the Recursive Neural Network, what are chosen include MV-RNN: Semantic Compositionality through Recursive Matrix-Vector Spaces (Neural Network, 2016), RNTN: Recursive Deep Models for semantic compositionality over a sentiment treebank ([PERSON] et al., 2015), and DRNN: Deep Recursive Neural Networks for compositionality in language ([PERSON] et al., 2016). For CNN, what are chosen include DCNN: a CNN for modeling sentences ([PERSON] et al., 2016), CNN-nonstatic and CNN multichannel: Convolutional Neural Networks for sentence classification ([PERSON] et al., 2016), and Molding-CNN: Molding CNNs for text, including nonlinear and non-consecutive convolutions ([PERSON] et al., 2016). For Recurrent Neural Networks, what are chosen include RCNN: Recurrent Convolutional Neural Networks for Text Classification ([PERSON] et al., 2016), S-LSTM: Long Short-term Memory over recursive structures ([PERSON] et al., 2014), BLSTM and Tree-LSTM: improved semantic representations from tree-structured Long Short-term Memory networks ([PERSON] et al., 2014). For other baseline methods, we use a Support Vector Machine, n-gram bag of words and a Paragraph Vector. In addition, LSTM and B-LSTM were also implemented by us for further comparison of category classification on our Chinese news dataset.  
The table above shows that our BLSTM-C model achieves remarkable performance in two out of three tasks (numbers in bold represent the best results). In sentiment classification, our BLSTM-C model gets the best result in the SST-2 dataset while molding-CNN achieves the best performance in the SST-1 dataset. Although our model fails to beat the state-of-art ones, it still obtains an acceptable result which means that the model is feasible for various scenarios.  
As for the classification of text category, our model outperforms other well-performed models, achieving outstanding results. Through the comparison between our model and single-layer LSTM, B-LSTM and LSTM models, it is found that our model does combine the advantages of both LSTM and CNN. Apart from successfully learning long-term dependencies, it extracts features from text, leading to better results. Although almost no human-designed features are employed in our model, it beats the state-of-the-art SVM that highly requires engineered features.
# SARDIM: High-Speed Near-Memory Processing Architecture for Synthetic Aperture Radar Imaging
## 1 Introduction
In the FFT and IFFT algorithms, the operation is performed sequentially by dividing it into several stages, and data ordering for each stage is essential. SARDIM does not perform such ordering using the host processor but instead uses the NMP module. In addition, the NMP module effectively reduces the execution time by performing an FFT using two single butterfly operation modules in parallel. In this study, the performance of SARDIM was evaluated by experimenting with RDAs on images of various sizes. The evaluation results show that SARDIMM effectively accelerated the RDA operation. Compared with the baseline system, SARDIMM achieved a maximum speedup of 6.926\(\times\) and an energy saving of 48.2%. The remainder of this paper  
Figure 1: Roofline model of the 8192 \(\times\) 8192 2D-FFT. is structured as follows: Section 2 provides a background that explains the concepts of RDA and NMP. Section 3 describes the hardware architecture and execution flow of the proposed SARDIMM. Section 4 presents the acceleration performance evaluation results of the SARDIMM for RDA operations on various images, and Section 5 concludes the paper.
## 2 Results and Discussion  
### Biochar Yield and Ash Content at Various Pyrolysis Temperatures  
Table 1 summarises the yield and ash content of the rice-husk and cotton-straw biochar samples obtained at various pyrolysis temperatures. It can be seen that the yield of both materials decreased with increasing pyrolysis temperature, while the ash content increased. This shows that higher temperatures improved the degree of pyrolysis, as the volatile components gradually escaped from the raw material, and the level of residual components decreased. As a result, the biochar yield decreased while the ash content increased [13]. The yields of both materials showed slight differences. At 300-700 \({}^{\circ}\)C, the biochar yield from rice husk was 37.52-23.32%, while the biochar yield from cotton straw was 51.64-19.92%. In contrast, the ash content of the rice-husk biochar was 64.19-76.20%,far higher than that for the cotton-straw biochar (5.54-12.15%). During pyrolysis, the biochar yield was mainly affected by the removal of volatile substances, while the variations in ash content were mainly due to differences in the mineral content and proportion of carbon compounds [14]. Therefore, the content of volatile substances did not differ greatly between both materials, although large differences existed in the type and content of minerals. It is widely known that, in addition to K, P, Ca, Fe, etc., rice husk also contains large amounts of Si that are not lost during the pyrolysis process. In raw materials, the silicon content can be as high as 10%, and even higher in rice husk [15]. This is the direct cause of the high ash content in the biochar samples prepared from rice husk.
###### Abstract  
Trade-off between transient response and grid-side current quality is a well-known issue of single-phase mains-connected power converters. A dual-loop control structure (usually based on PI or type-II controllers) is typically employed in such systems to regulate the DC link voltage to a constant reference (in order to maintain power balance) while forcing the grid-side current to have a specific shape (in order to comply with power quality requirements). Introducing notch term/s (tuned to certain multiple/s of the mains base frequency) into one of the loops allows either for the improvement of the dynamic performance without worsening the total harmonic distortion of grid-side current or for the enhancement of the current quality without impairing the dynamic response. Since the maximum tolerable value of total harmonic distortion is typically imposed by a certain power quality standard, it is desirable to enhance the transient response of the power converter system as much as possible while keeping the total harmonic distortion at the maximum allowed value. However, universal off-grid operating power conversion systems must support both 50 Hz and 60 Hz mains; consequently, tuning the notch term/s to 50 Hz multiple/s would not be sufficient for a 60 Hz mains operation and vice-versa. Consequently, this work examines the possibility of introducing a dual-t notch term into the control loop in order to cover both above-mentioned base frequencies. It is demonstrated that under typical base frequency uncertainty values, the performances of dual-notch terms are nearly decoupled so that the term tuned to a 50 Hz frequency (and optionally to its multiples) has nearly no influence at a 60 Hz mains operation and vice-versa. Consequently, the methodology allows for the improvement of the dynamics of universal grid-connected power converters without total harmonic distortion (THD) deterioration. A stability analysis of the proposed control structure is carried out and quantitative design guidelines, allowing for the attainment of an optimized dynamic response for a given maximum tolerable total harmonic distortion, minimum allowed phase margin and a certain base frequency uncertainty, are established. It is shown that a DC link voltage loop bandwidth of 52 Hz may be attained while keeping the grid-side current THD below 5%. Simulations and experimental results support well the proposed design methodology.  
s 2023
_Applied_  
_sciences_  
_Article_  
**Chlorine Tolerance and Inactivation of _Escherichia coli_ recovered from Wastewater Treatment Plants in the Eastern Cape, South Africa**  
**[PERSON] 1,2,* (c)**, [PERSON] 3 and [PERSON] 1,2**  
SAMRC Microbial Water Quality Monitoring Centre, University of Fort Hare, Alice 5700, South Africa; [EMAIL_ADDRESS]  
Applied and Environmental Microbiology Research Group, Department of Biochemistry and Microbiology, University of Fort Hare, Alice 5700, South Africa  
Department of Microbiology, School of Life Sciences, University of Kwazulu-Natal, Private Bag X54001, Durban 4000, South Africa; [EMAIL_ADDRESS]  
Correspondence: [EMAIL_ADDRESS]; Tel.: +27-7193063911  
Received: 13 June 2017; Accepted: 1 August 2017; Published: 8 August 2017  
**Featured Application: This study examined the tolerance of _Escherichia coli_ isolates, a fecal indicator of water contamination, to chlorine as a common water disinfectant and the effectiveness of chlorine at different concentrations in eliminating _E. coli_ in wastewater effluent. Data obtained can be used as baseline monitoring data for future epidemiological surveillance that could further enhance the control of _E. coli_ and some bacteria species of public health concern in wastewater treatment plants and ensure protection of public and environmental health.**  
**Abstract: This study investigated the survival of _Escherichia coli_ (_E. coli_) recovered from secondary effluents of two wastewater treatment plants in the Eastern Cape Province, South Africa, in the presence of different chlorine concentrations. The bacterial survival, chlorine lethal dose and inactivation kinetics at lethal doses were examined. The bacterial isolates were identified by 165 rRNA gene sequencing. Comparison of the nucleotide sequences of 16S rRNA gene of bacteria with known taxa in the GenBank revealed the bacterial isolates to belong to _Escherichia coli_. At the recommended free chlorine of 0.5 mg/L, reduction of _E. coli_ isolates (\(n=20\)) initial bacterial concentration of 8.35-8.75 log was within a range of 3.88-6.0 log at chlorine residuals of 0.14-0.44 mg/L after 30 min. At higher doses, a marked reduction (\(p<0.05\)) in the viability of _E. coli_ isolates was achieved with a greater than 7.3 log inactivation of the bacterial population. Inactivation kinetics revealed a high rate of bacterial kill over time (\(R^{2}>0.9\)) at chlorine dose of 1.5 mg/L. This study indicates poor removal of bacteria at free chlorine at 0.5 mg/L and a greater efficacy of 1.5 mg/L in checking _E. coli_ tolerance.  
**Keywords:**_Escherichia coli_; chlorine tolerance; chlorine lethal dose; inactivation kinetics; wastewater treatment plants; public health
# Cotton Terry Textiles with Photo- and Bio-Activity in a Model Study and Real Conditions
## 5 Conclusions  
The results of the study suggest that textile fabrics modified with TiO2 and ZnO nanoparticles can be used as self-cleaning towels. The low and medium antimicrobial effectiveness of photocatalytically modified TiO2 and ZnO textile materials under model conditions was revealed, alongside with high effectiveness under real conditions. Significant biostatic activity was shown on the surface of the modified towels, where the number of microorganisms decreased by 1-5 log to a level of 0-5 CFU/cm2 for the following bacteria: _Enterobacteriaceae_, _Enterococcus_, coli group and _E. coli_, and _Pseudomonas_. Furthermore, a statistically significant decrease was found for the total number of fungi and bacteria.  
Moreover, fabrics in visible lighting conditions can support air cleaning by reducing the number of bacteria and fungi, and the concentration of gases and VOCs in the air. A statistically significant reduction in the total number of bacteria and fungi (by 1 log) and the concentration of gases (NO2, CO2, CO) in the air of bathrooms where modified towels were used, was determined. The removal of VOCs or a reduction in their concentration in the air above the modified towels was determined. Under real conditions, in the humidity range RH = 36-67% and light intensity between 81 and 167 lux, the type and time of lighting were observed to be more significant for the effectiveness of photocatalysis than air humidity. Greater photocatalytic effectiveness was revealed in natural light during 7 h/day than in artificial light during 1.5 h/day.  
Future studies should focus on determining the durability of the photocatalytic effects of modified textile fabrics after washing. Furthermore, studies should be continued to optimize microclimatic conditions and lighting with visible light in order to improve the photocatalytic effects.  
Conceptualization, B.G., J.S., E.M.-Z., P.K. and E.R.; methodology, B.G., J.S., E.M.-Z., P.K., K.P.-P., A.R., A.J. and E.R.; investigation, B.G., J.S., E.M.-Z., K.P.-P., A.R., A.J. and E.R.; formal analysis, B.G., E.M.-Z. and K.P.-P.; validation, K.P.P.; writing--original draft preparation, [PERSON], [PERSON]-Z. and P.K.; writing--review and editing, [PERSON], P.K., [PERSON] and J.S.; supervision, B.G., P.K. and E.R.; project administration, B.G., P.K. and E.R.; funding acquisition, E.R. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Zwoltex Sp. z o.o, Zdunska Wola, Poland.  
We would like to thank Zwoltex Sp. z o.o. for preparing textile materials and financing the study.  
The authors declare no conflict of interest.
# Fuzzy Logic in Selection of Maritime Search and Rescue Units
## 4 Case Study  
In order to demonstrate the application of fuzzy logic, a simulation of the planning of an SAR operation has been conducted. The simulation covers the evaluation of a vessel's suitability, based on selected criteria.  
Examination of ships' parameters in single-criterion and multi-criteria analyses will provide data to create a ranking of vessels, sorted by their suitability in a descending order (from the one which best meets the SAR coordinator's preferences to the least useful one).  
The ultimate goal is to provide the SAR coordinator with information on the vessel's potential and support him/her in the decision-making process.  
Two cases were considered during the simulation. In the first criteria evaluation, a combination of MCDA and fuzzy logic results were used. In the second criteria evaluation, the test result without the use of fuzzy logic was presented. The outcome was compared and discussed.
# Deep Compressed Sensing Generation Model for End-to-End Extreme Observation and Reconstruction
###### Abstract  
Data transmission and storage are inseparable from compression technology. Compressed sensing directly undersamples and reconstructs data at a much lower sampling frequency than Nyquist, which reduces redundant sampling. However, the requirement of data sparsity in compressed sensing limits its application. The combination of neural network-based generative models and compressed sensing breaks the limitation of data sparsity. Compressed sensing for extreme observations can reduce costs, but the reconstruction effect of the above methods in extreme observations is blurry. We addressed this problem by proposing an end-to-end observation and reconstruction method based on a deep compressed sensing generative model. Under RIP and S-REC, data can be observed and reconstructed from end to end. In MNIST extreme observation and reconstruction, end-to-end feasibility compared to random input is verified. End-to-end reconstruction accuracy improves by 5.20% over random input and SSIM by 0.2200. In the Fashion_MNIST extreme observation and reconstruction, it is verified that the reconstruction effect of the deconvolution generative model is better than that of the multi-layer perceptron. The end-to-end reconstruction accuracy of the deconvolution generative model is 2.49% higher than that of the multi-layer perceptron generative model, and the SSIM is 0.0532 higher.  
compressed sensing; deep learning; extreme observation; high precision reconstruction; end-to-end +
Footnote †: journal: Applied Sciences
# Analysis of Shield Tunnels Undercrossing an Existing Building and Tunnel Reinforcement Measures
## 7 Deep Hole Grouting Reinforcement Technology for Shield Tunnel  
From Section 5.3, the successive excavation of the double shield tunnels had an obvious nonlinear effect on the subsidence of the building and the lateral displacement of the pile  
Figure 28: Relation between the subsidence of building and grouting pressures.  
Figure 29: Relation between the lateral displacement of pile and grouting pressures.  
along the excavation direction, affecting the safety and durability of the building and piles. The grouting reinforcement technology was one of the effective measures to reduce this impact [33,34]. At present, the grouting reinforcement technology is divided into the ground grouting measures and the deep hole grouting reinforcement technology in the tunnel. The latter was gradually becoming one of the main auxiliary measures for shield tunneling through various buildings due to its good reinforcement effect, as it can be carried out inside the tunnel and is not impacted by the external environment. This section studied the impact of the technical parameters of deep hole grouting reinforcement on the building and piles caused by the successive excavation of double shield tunnels. The radius of radial reinforcement and the reinforcement range before and after the building were considered the main technical parameters. The effects of these two parameters on the maximum subsidence of the building and the maximum lateral displacement of the pile were analyzed. Table 3 shows the comparison of the parameters of soil after grouting and the parameters of undisturbed soil.