esa-sceva/satcom-chunk-collection huggingface dataset:
# Bone Conduction Auditory Navigation Device for Blind People
## 3 Sound Localization Performance of Panned Binaural Sound
### Details of the Bone-Conduction Device  
As a reproduction method of the bone-conducted sound, there are two types of conduction scheme: the direct-bone-drive-type scheme and the over-skin-drive-type scheme. The former type has an implant device, such as a bone-anchored hearing aid (BAHA) [19; 20]. This type of bone conduction realizes sound transmission to the inner ear with high efficiency. However, due to the invasive nature of this method, it is difficult to adopt this manner of conduction from the viewpoint of casual usage of bone conduction in a navigation device. In contrast, the latter type of conduction scheme can provide a very-easy-to-wear bone-conduction device due to its non-invasivity, whereas the efficiency of sound transmission by this scheme is slightly decreased compared to the former type of conduction scheme, particularly in higher-frequency ranges. In the present study, to increase the usability of the device, the latter type of scheme was adopted so as to reproduce the bone-conducted sound by pressing the device against the human face.  
Figure 2a shows the exciter (COM-10917, Sparkfun Electronics [21]) of the bone-conduction device used in the present study. The device can be excited in the frequency range of from 500 Hz to 12 kHz. The actuator was forced to contact the human face using a hairband-type fixing device, as shown in Figure 2b. The contact position of the actuator was set to P1, as shown in Figure 2c, which was selected in our previous study [22] as the best position to efficiently reproduce the bone-conducted sound.  
In our former study, the excitation performance by the abovementioned actuator was measured by a simple acrylic model of the head, as shown in Figure 2d [22]. As the model of human skin, a thin gel sheet with a thickness of 1 mm was sandwiched between the actuator and the acrylic plate, as shown in Figure 2e. White noise was generated by the actuator fixed by each hairband-type device. The vibration acceleration transmitted to the acrylic plate was measured, as shown in Figure 2f. Since the measured result has generally flat characteristics from approximately 500 Hz up to 10 kHz, this actuator was adopted for the navigation system.
# Faults and Diagnosis Methods of Permanent Magnet Synchronous Motors: A Review
## 3 Fault Diagnosis Methods
### Signal Processing Methods
#### 3.2.2 Short-time Fourier Transform  
With the frequency domain methods, time information is lost, and sometimes it is difficult to accurately distinguish similar harmonics. Therefore, many time-frequency analysis techniques have been proposed, each of which have their own advantages and disadvantages.  
Short-time Fourier transform (STFT) is an improved method based on FFT. It realizes time-frequency analysis by dividing the signal into small time windows, whose types include rectangle, Hamming, Hanning, Gauss and so on. For an input signal \(x(n)\), the discrete expression of STFT is [66]:  
\[STFT(n,k)=\sum_{n=0}^{N-1}x(n)\omega(n-mH)e^{-j\frac{2n}{N}kn} \tag{9}\]  
where \(\omega(n)\) is the window function, \(k\) represents the frequency index, N represents the number of FFT points; \(m\) represents the position of window, and \(H\) represents the jump distance between two consecutive windows.  
This method is advantageous for dealing with nonlinear complex signal. However, the time and frequency resolution depend on the selected window, but as can be seen from the formula, the time window size \(H\) is fixed, so the resolution is fixed over the entire time and frequency range, and their resolution cannot be accurate at the same time. If great resolution is expected, STFT requires a high computational cost; thus, as a basic time-frequency analysis method, STFT is not the most suitable for transient analysis. According to the research of [PERSON] et al., STFT performs the worst in several time-frequency analysis techniques [67]. Therefore, [PERSON] et al. combined the STFT and Gabor spectra to analyze the PMSM current signal [68].
## 3 Simulation Study
### Simulation Results
Figure 4: Comparison results between the single ES, double ES, and the two-stage EWMA in (**a**) Pattern 2, (**b**) Pattern 3, (**c**) Pattern 4 and (**d**) Pattern 5. Figure 5 shows the comparative results from Pattern 6 to Pattern 9 that have a seasonality pattern. Please note that the initial seasonal factors in the triple ES model should be carefully estimated for more accurate forecasting. However, in our problem setting, the number of initial historical data is too small to accurately estimate the initial seasonal factors. Moreover, when the noises become large, the seasonal factors also tend to be inaccurately estimated. For these reasons, the triple ES model showed the worst forecasting performance in these scenarios, although this model is proposed for forecasting the seasonal time series. These results imply that the triple ES model is not effective for seasonality-patterned data when the initial time series is insufficiently prepared and the time series data contain large sized noises. Finally, when the periods of the seasonality are changing (Pattern 9), the triple ES model performs the worst because this model is based on the assumption that the period is constant. The double ES model also yielded unsatisfactory forecasting results because this model was designed for only considering the linear trend factors. In addition, as mentioned earlier, this model is quite sensitive to the noises, and hence, when large-sized noises are added to the time series, forecasting accuracies become worse. Conversely, the two-stage EMWA model tends to produce the best forecasting results among all EWMA models because the adjustment factor helps adjust the bias of the estimation results of the level factors for the patterns whose changing rates between successive time series observations is not constant. However, the two-stage EMWA model cannot accurately forecast when the forecasting windows become large in the seasonality-patterned data because this method is basically proposed for forecasting the monotonically changing patterns. Thus, these results confirmed that the two-stage EWMA can also be effectively applied to short-term forecasting for the seasonality time series data. Figure 5: _Cont._  
In addition, the experimental results in heteroscedastic settings are similar to those in homoscedastic settings. That is to say because the seasonal factors cannot be accurately estimated under  
Figure 5: Comparison results between the single ES, double ES, triple ES, and two-stage EWMA in (**a**) Pattern 6, (**b**) Pattern 7, (**c**) Pattern 8 and (**d**) Pattern 9.  
insufficient time series observations, the triple ES model cannot produce a satisfactory forecasting performance regardless of the varying patterns of noises. Besides, single ES and double ES models are proposed for the stationary and monotonically changing time series patterns, and thus, they cannot yield superior performance in seasonal time series patterns for both cases that the noises are homoscedastic and heteroscedastic.
# Advances in Fermentation Technology: A Focus on Health and Safety
## 2 Microbial Control of the Pathogens' Growth--Biocontrol Strategies
### Potential Health Hazards in Traditional Fermentation
#### 2.1.1 Pathogenic Contamination
Furthermore, fermented mixed vegetables showed an even higher contamination rate of coliform bacteria (50%) than single-type fermented vegetables (13%). These contamination issues have been attributed to inadequate hygiene practices [23]. Alcoholic beverages are generally considered as microbiology safe due to their intrinsic physical and chemicalproperties, including high carbon dioxide, high alcohol content, low oxygen, low pH, and antimicrobial agents [24]. Nonetheless, some foodborne pathogens can survive within these environments, with studies showing that bacteria like _Listeria_, _E. coli_, and _Salmonella_ can persist in low-pH products like apple cider and juice concentrates for several weeks [25]. Pathogens inoculated in betroot or watermelon juice were effectively controlled through combined treatments with organic acid or lemon (Citrus limon) extract and mild heat. Heating the juices to 55 \({}^{\circ}\)C for 5 min resulted in log reductions of less than 2.0 for _E. coli_ O157:H7, _Salmonella typhimurium_, and _L. monocytogenes_ populations. However, the addition of 1.0% organic acid or 20% lemon extract, along with mild heat, significantly enhanced the effectiveness of the treatment, achieving further log reductions of 2.2 to 5.0 logs for _E. coli_ O157:H7, 4.5 to 5.0 logs for _S. Typhimurium_, and 1.5 to 5.0 logs for _L. monocytogenes_[26]. The chemical compounds produced during the fermentation process of these beverages provide a partially favourable environment for microbial survival despite their inherent antibacterial properties. A comprehensive investigation into the survival of pathogenic bacteria and their spores in fermented alcoholic beverages, including beer and rice wine, is crucial for accurately assessing potential health risks associated with these products [25]. Therefore, a comparative analysis of contamination rates in different regions and types of fermented products is essential as it provides a comprehensive framework for understanding the global implications of microbial safety in fermentation practices.
## 3 The Study
### Scenarios Implementation  
#### 3.4.1 Network A: One-Tier Architecture  
In this scenario, the involved entities are \(S\) sensors in the water, \(E\) eNodeB cell towers of the LTE network, and the server. The sensors monitor the river water's \(pH\) and periodically sends the information to the server. In the alarm condition, when the server starts receiving data indicating pollution from a sensor \(s_{i}\), it notifies all the subsequent ones (\(s_{j}\), \(j=i+1,...,S\)) to begin transmitting more often for better tracking the pollutant.
## 3 Numerical Results
Figure 7: Near E-field behavior in the Cartesian coordinate planes \(xz\) and \(xy\) of a two stacked thin resistive disks resonator at three resonance frequencies (\(k_{0}a=9.662491,10.643395,11.998105\)), when a plane wave orthogonally impinges onto the structure with \(\underline{E}_{0}=E_{0}\beta\): (**a**) Near E-field in the \(xz\) plane, \(k_{0}a=9.662491\); (**b**) Near E-field in the \(xy\) plane, \(k_{0}a=9.662491\); (**c**) Near E-field in the \(xz\) plane, \(k_{0}a=10.643395\); (**d**) Near E-field in the \(xy\) plane, \(k_{0}a=10.643395\); (**e**) Near E-field in the \(xz\) plane, \(k_{0}a=11.998105\); (**f**) Near E-field in the \(xy\) plane, \(k_{0}a=11.998105\). Figure 2:0 Near E-field behavior in the Cartesian coordinate planes \(xz\) and \(xy\) of a two stacked thin resistive disks resonator at three resonance frequencies (\(k_{0}a=15.862148,16.503645,17.532887\)), when a plane wave orthogonally impinges onto the structure with \(\underline{E}_{0}=E_{0}\vartheta\): (**a**) Near E-field in the \(xz\) plane, \(k_{0}a=15.862148\); (**b**) Near E-field in the \(xy\) plane, \(k_{0}a=15.862148\); (**c**) Near E-field in the \(xz\) plane, \(k_{0}a=16.503645\); (**d**) Near E-field in the \(xy\) plane, \(k_{0}a=16.503645\); (**e**) Near E-field in the \(xz\) plane, \(k_{0}a=17.532887\); (**f**) Near E-field in the \(xy\) plane, \(k_{0}a=17.532887\).
# Repetition with Learning Approaches in Massive Machine Type Communications
## 5 Conclusions  
An insufficient number of repetitions prevents the successful deciphering of the data by the receivers, leading to a high bit error rate. Excessively high repetitions of UE pieces lead to the wastage of valuable wireless resources in 3 GPP mMTC. Therefore, in the present study, adaptive repetition approaches with machine learning were developed to substantially increase the network transmission efficacy for eMTC systems in mMTC. The simulation results show that the proposed RLA could effectively improve the transmission  
Figure 11: Average energy consumption.  
Figure 10: Resource utilization.  
probabilities, the resource utilization, the average number of repetitions, and the average energy consumption. The proposed RLA is more suitable than the common LUT for the eMTC system in mMTC. In future work, we will adopt online deep learning approach for 6G or open radio access network (O-RAN) AI architecture and specific use cases. We will enable the approach to learn effectively in special communication scenarios with difficult-to-obtain training samples and have more appropriate depth and accuracy of learning.  
Conceptualization, L.-S.C., C.-H.H., C.-C.C., Y.-S.L. and S.-Y.K.; Writing--original draft, L.-S.C. and C.-H.H.; Writing--review & editing, C.-C.C., Y.-S.L. and S.-Y.K. All authors have read and agreed to the published version of the manuscript.  
The original research work presented in this paper is partly related to BSMI under contract number 1D201101221-134 awarded by BSMI Taiwan and MOST under contract 111-2218-E-305-002-18 October 2022.  
The authors would like to thank the BSMI (Bureau of Standards, Metrology and Inspection, Taiwan) research group and MOST for their technical support.  
The authors declare no conflict of interest.
## 3 Experimental Setup
### Data Description
We avoided focusing on a single week, as it would introduce additional entropy due to the inherent nature of the dataset for this region. A single working day provides enough data for analyzing mobile traffic patterns while offering sufficient input for our analysis. To streamline data management and improve classifier performance, we performed two additional processing steps on the dataset. First, we aggregated all measurements into one-hour intervals. Then, we applied min-max scaling [35] to normalize all values to a range between 0 and 1. To serve as a way to classify the entire grid, we manually labeled two sets of cells as homes and workplaces. This was feasible because we had access to the Trento grid's GeoJSON file [36], containing the coordinates of the grid. Our sample set comprised cells within a 15 \(\times\) 15 subgrid that clearly covered an industrial area and the city center of Trento with high-density residential areas (Figure 2). Additionally, a smaller 4 \(\times\) 4 subgrid was also considered to include a forest area that was representative of the alpine area from the province of Trento that was not sufficiently considered in the smaller 15 \(\times\) 15 subgrid selection. This was important to represent all the diversity of the region while also trying to avoid overfitting. The cells in yellow represent work areas, the ones in blue represent home areas, and the ones in red indicate forest areas.
# Research on the Applicability of Transformer Model in Remote-Sensing Image Segmentation
## 2 Methods
### Accuracy Comparison of Models  
In order to verify which transformer model is more suitable for remote-sensing image segmentation, three aspects of the segmentation results, the segmentation accuracy, and  
Figure 8: TransUnet’s transformer layer structure.  
Figure 7: TransUnet structure.  
the training time of three transformer models in two data sets, namely the Vaihingen data set and Potsdam data set, were compared.
###### Abstract  
Environmental approaches in the asphalt industry have focused on utilizing waste materials as modifiers. Lignin is a high-potential bitumen modifier due to its characteristics; however, the blending process with bitumen is critical. This study investigates the chemo-thermal characteristics of lignin-modified bitumen under two different blending protocols, including a mechanical and high-shear mixer to evaluate its performance as a modifier. According to the protocols, 5, 10, and 20% of Kraft lignin was added to a PG 58S\(-\)28 bitumen. The samples were subjected to analysis using Brookfield Rotational Viscosity (BRV), Dynamic Shear Rheometer (DSR), Fourier-Transform Infrared Spectroscopy (FTIR), Environmental Scanning Electron Microscopy (ESEM), Thermogravimetric Analysis (TGA), and Differential Scanning Calorimetry (DSC) tests. The BRV and DSR test results indicate a remarkable alteration in the rheological properties of lignin-modified bitumen under blending conditions. The FTIR analysis indicated that Kraft lignin did not produce new functional groups. The fibril structures of the bitumens are affected by Kraft lignin content and blending conditions due to ESEM. The Kraft lignin and blending conditions influence the thermal behavior of bitumen. The findings highlight Kraft lignin's potential as a bitumen modifier, and the fact that its characteristics are influenced by the blending protocol and Kraft lignin content.  
kraft lignin; lignin-modified bitumen; mechanical mixer; high-shear mixer; chemo-thermal characteristics; sustainable asphalt materials 2023
# Force Analysis of Circular Diaphragm Wall Based on Circular Cylindrical Shell Theory
## 4 Circular Cylindrical Shell Theory Calculation Method (CCSTCM)
### Solving Steps  
For the engineering case in this study, the circular diaphragm wall of the north anchorage foundation pit is subjected to four normal loads: the horizontal supporting force \(q_{\mathrm{M}}\) of the cap beam, the horizontal supporting force \(q_{\mathrm{CI}}\) of the lining, the horizontal subgrade reaction \(e_{\mathrm{p}}(\alpha)\) on the pit-facing surface of the circular diaphragm wall, and the horizontal earth pressure strengths \(e_{\mathrm{an}}\) and \(e^{\prime}_{\mathrm{an}}\) on the pit-back surface of the circular diaphragm wall. According to the circular cylindrical shell theory above and the superposition principle in elasticity, the solving steps for deriving the results of the circular diaphragm wall under normal loads in every working condition in the engineering case can be concluded as follows.  
Firstly, all four normal loads in every working condition must be calculated, including \(q_{\mathrm{M}}\), \(q_{\mathrm{CI}}\), \(e_{\mathrm{p}}(\alpha)\), \(e_{\mathrm{an}}\) and \(e^{\prime}_{\mathrm{an}}\).  
Secondly, the internal forces and deformations \(A_{i}\), \(B_{i}\), \(C_{i}\), \(D_{i}\) of the circular diaphragm wall, caused by each normal load in any one working condition, should be calculated by Equation (29).  
\[\left.\begin{array}{l}A_{i}=f(q_{\mathrm{M}})\\ B_{i}=f(q_{\mathrm{CI}})\\ C_{i}=f\big{[}e_{\mathrm{p}}(\alpha)\big{]}\\ D_{i}=f\big{[}e_{\mathrm{an}},e^{\prime}_{\mathrm{an}}\big{]}\end{array}\right\} \tag{29}\]  
Finally, the total internal force and deformation \(F_{i}\) will be obtained in each working condition by Equation (30).  
\[F_{i}=A_{i}+B_{i}+C_{i}+D_{i} \tag{30}\]
# A Lightweight Crop Pest Detection Method Based on Convolutional Neural Networks
## 3 Results
### Comparison with Existing Major Object Detection Methods  
In order to evaluate the performance of our method, we compared our method with some existing regular-size and lightweight object detection methods. The comparison experiment was performed on the CP15 dataset. In this experiment, YOLOv3, YOLOv5m, CenterNet, and Faster R-CNN were selected to represent regular-size object detection methods, and YOLOv3-tiny, Nanodet-plus-m-1.5x, and YOLOv5s were selected to represent lightweight object detection methods.  
The results of the comparison experiment in Table 5 show that the detection accuracy of our method, YOLOLite-CSG, is 0.3% higher than that of YOLOv5m, the best-performing regular-size object detection method chosen for this study. Moreover, our method has an absolutely huge advantage in terms of the number of parameters and computations. Furthermore, our method outperforms all lightweight object detection methods in terms of detection accuracy with a maximum improvement of 10.6%, and has the lowest number of parameters and a comparable number of computations to lightweight object detection methods. These experimental results fully demonstrate that our method YOLOLite-CSG achieves state-of-the-art pest detection performance with high detection accuracy and an extremely low number of parameters and computations.
###### Abstract
Therefore, for the optimal collection of solar energy, it is better to use double-axis solar trackers with the ability to track the direction of the Sun's movement from the North to the South and from the East to the West throughout a day and a year [37]. Designs of two-axis systems with an automatic tracking mechanism oriented \"East-West\" and \"North-South\" are complex and expensive, as they contain motors, redundant sensors and other control systems [38]. Also, according to the research of different authors, the difference in the amount of energy generated by biaxial and uniaxial trackers range from 3% [39] to 20% [40; 41]. Further, although a two-axis tracker provides better solar energy collection, this additional collected energy may not be worth the cost of installing additional Sun-tracking mechanisms, sensors that also require additional power sources [4]. Based on the above, vertical stationary PV-modules with an \"East-West\"-oriented solar panel are a good alternative to expensive PV-modules with a two-axis tracker, especially for underdeveloped regions [42]. To increase the efficiency of such PV-modules, it is suggested to install double-sided solar panels with the physical adjustment of their optimal angles of inclination to the horizon depending on geographical latitude, season, and weather conditions [28; 43; 44]. Based on the analysis of scientific works [36; 37; 38; 39; 40; 41; 42; 43; 44], we note that the determination of the optimal design and the angles of inclination of solar PV-module panels to the horizon can significantly increase the installation efficiency of the modules. In view of the above, there is a need to research stationary PV-modules installed vertically, equipped with a double-sided solar panel with an \"East-West\" orientation to increase their installation efficiency. Thus, the purpose of the study is to determine the installation efficiency of the vertical fixed PV modules with a double-sided \"East-West\" orientation of the solar panel. By \"double-sided solar panel\", we mean two solar panels mechanically connected to each other, with the working surface of one panel oriented to the East, and the working surface of the second panel oriented to the West. Both panels are installed in a sealed aluminium frame for reliable fixation. The frame with the panels is attached to an iron profile assembled with a slim structure, which ensures the fixed vertical position of the module with an angle of inclination of the attached solar panel to the horizon equal to zero degrees. To achieve the goal, the following tasks were set:  
* Determine the characteristic angles of incidence of the Sun's rays on vertically fixed PV-modules with a double-sided solar panel at latitude of 50\({}^{\circ}\);To compare the installation efficiency of the vertical stationary PV-modules equipped with a double-sided solar panel with an \"East-West\" orientation and PV-modules installed at a latitude angle with a \"South\" orientation.
# A New Method of Time-Series Event Prediction Based on Sequence Labeling
## 3 Experiment  
This article applied the CX-LC model to the prediction of time-series events and aimed to explore and answer the following two questions:  
* Q1: Compared with other advanced classification event prediction methods, how does CX-LC perform on the same prediction task?
* Q2: Do the pattern recognition, feature selection, and smoothing refinement parts of the CX-LC framework really improve the prediction results?