esa-sceva/satcom-chunk-collection huggingface dataset:
# Unsupervised Transformer-Based Anomaly Detection in ECG Signals
## 4 Results and Discussion
### ECG 5000 Dataset Results
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**No.** & **No.** & **Hidden** & **F1** & **Accuracy** & **Recall** & **Precision** \\
**Enceder** & **Heads** & **Size** & & & & & \\ \hline
1 & 16 & 32 & 96.7\% & 96.8\% & 97.7\% & 96.2\% \\
1 & 16 & 64 & 97.6\% & 97.6\% & 96.9\% & 98.4\% \\
1 & 16 & 128 & 98\% & 98\% & 96.9\% & 99.2\% \\
1 & 16 & 256 & 98.2\% & 98.2\% & 96.6\% & 100\% \\
1 & 32 & 32 & 98.4\% & 98.4\% & 96.9\% & 100\% \\
1 & 32 & 64 & 97\% & 97\% & 96.6\% & 97.7\% \\
1 & 32 & 128 & 98.4\% & 98.4\% & 97.7\% & 99.2\% \\
1 & 32 & 256 & 98.8\% & 98.8\% & 97.7\% & 100\% \\
2 & 16 & 32 & 98.2\% & 98.2\% & 97.3\% & 99.2\% \\
2 & 16 & 64 & 98.4\% & 98.4\% & 97.3\% & 96.6\% \\
2 & 16 & 128 & 98.6\% & 98.6\% & 97.3\% & 100\% \\
2 & 16 & 256 & 98.4\% & 98.4\% & 97.3\% & 99.6\% \\
2 & 32 & 32 & 98.2\% & 98.2\% & 96.9\% & 99.6\% \\
2 & 32 & 64 & 98.6\% & 98.6\% & 97.3\% & 100\% \\
2 & 32 & 128 & 99\% & 99\% & 98.1\% & 100\% \\
2 & 32 & 256 & 98.2\% & 98.2\% & 96.9\% & 99.6\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Transformer anomaly detection results for the ECG5000 test dataset. Figure 7: ROC curve of ECG 5000 testing set. our model outperforms these deep learning models in all evolution metrics, with an F1 score of 99%, an accuracy of 99%, a recall of 98.1%, and a precision of 100%. However, the comparison was considered unfair because we used different data-splitting methods. Therefore, we compared our results to those obtained recently by [43] and [44] because the data was split into 80% training 10% validation and 10% testing, exactly as we did here. The authors of [43] Concat Attention Autoencoder (CAT-AE), AE-without-Attention, and VAE claim state-of-the-art accuracy and precision in anomaly detection. On the other hand, the authors in [44] used an unsupervised LSTM AE. As shown in Table 4, our model outperforms these deep-learning models using the same data-splitting methods.
# Performance Evaluation of Track Curvature Sensor for
###### Abstract  
Active railway vehicles such as tilting trains and active steering bogies are being developed to improve the curve running performance of railway vehicles. In this case, a technology for sensing a curve and extracting curve information such as a curvature in real time is required. The existing railway curve detection technology has the disadvantage of requiring many calibration processes through test driving and being affected by running speed. In order to overcome these disadvantages, this paper proposes a very simple and efficient curvature estimation method. A curvature sensor prototype was manufactured and a test run was performed on the test track. As a test result compared with the track inspection data, the minimum deviation was 0.8%, the maximum deviation was 4.0% and the average deviation was 2.8%, showing good curvature measurement performance. It was also confirmed that the effect of the running speed was very small and the accuracy was high in the small curve with a large curvature. Therefore, the developed curvature measurement sensor is expected to be used very practically in the field of curvature detection and curvature extraction to control the vehicle in the curve section.  
curved track section; curvature sensor; kinematic motion; track inspection data; railway vehicle Article
# Digitalizing Industrialized Construction Projects: Status Quo and Future Development
## 4 Qualitative Analysis
### Design Phase
#### 4.1.3 Performance Assessment  
Performance assessment plays a crucial role in improving a project's performance and mitigating environmental impact over its entire life cycle. By analyzing various facets such as energy consumption and carbon emission, designers can refine building schemes early on. For instance, [PERSON] et al. [38] simulated the internal surface temperature and heat release of a wall throughout the year, thereby determining the optimal phase-change material and thickness for energy-efficient precast concrete walls. Similarly, [PERSON] et al. [39] compared the environmental performance of timber and concrete structures by using a multizonal energy simulation, which elucidated the superior energy efficiency and thermal comfort of timber structures. Furthermore, [PERSON] et al. [40] proposed a robotic fabrication-based material system that combined the sustainability properties of cork with the structural efficiency of concrete. The harmonious integration of these materials provides an environmentally friendly solution.  
Life cycle assessment (LCA) is a valuable tool for assessing a building's environmental impacts from raw material extraction to disposal. The integration of LCA into the building design process offers substantial potential for minimizing environmental impacts. For instance, [PERSON] et al. [41] introduced an automated process to merge comprehensive and detailed LCA data into BIM models, evaluating buildings' environmental performancesthrough systematic zoning, model setup, and impact estimation. [PERSON] et al. [42] also developed a BIM-based LCA methodology and used environmental impact data to assess, optimize, and compare various design alternatives. These methods streamline the data-intensive LCA process and increase designers' willingness to apply LCA in the design phase of industrialized construction. However, their effectiveness is limited by the paucity of accurate environmental impact data.  
In summary, the existing research on the design phase of industrialized construction highlights several key areas. First, parametric design enables the efficient exploration of complex geometries and forms by defining parameters such as size, material, and shape. Discrete design leverages generic components to explore the flexibility of component combinations, while maintaining a visually cohesive design. Second, DfMA aims to optimize designs to reduce costs and improve producibility by considering manufacturing and assembly constraints early in the process. Performance assessment evaluates energy use and emissions to refine the design and mitigate environmental impacts throughout the building lifecycle. Third, BIM bridges the gap between design and production by incorporating manufacturing details into the digital model. However, limitations persist in terms of data availability and support for prefabrication standards.
## 3 5G Technology Enablers for V2X Use Cases
### The Evolution of V2X Communications
#### 3.1.6 3 GPP Release 18  
Release 18 is marked as the start of 5G-Advanced. The evolution to 5G-Advanced with Release 18 was described as balanced, considering mobile broadband evolution, vertical domain expansion, market needs, and device/network evolution. Release 18 generated a list of topics for further discussion, including downlink MIMO evolution, uplink enhancements, mobility enhancements, additional topological improvements, XR enhancements, sidelink enhancements, RedCap evolution, NTN evolution, broadcast and multicast services evolution, positioning improvements, duplex operation evolution, AI/ML applications, network energy savings, and RAN enhancements.  
From the V2X perspective, Release 18 continues to focus on enhancing sidelink communication to support vehicular devices in V2X (vehicle-to-everything) services. The objective is to improve the sidelink data rate by introducing carrier aggregation (CA) in sidelink communication, extending sidelink operation to the unlicensed spectrum, and enhancing sidelink support in the frequency range 2 (FR2). Additionally, the 3 GPP is investigating mechanisms to enable LTE V2X and NR V2X devices to coexist in the same frequency channel, ensuring compatibility and an efficient utilization of resources. Furthermore, Release 18 aims to extend support for aerial vehicles, specifically unmanned aerial vehicles (UAVs), by introducing 5G NR capabilities. This is in continuation of the support provided for UAVs in 4G LTE, which included features such as enhanced measurement reports; the reporting of UAV height, location, and speed; flight path reporting; and signaling support for subscription-based aerial UE (user equipment) identification. These features will be incorporated into the 5G NR specifications as appropriate, enabling UAVs to leverage the benefits of 5G technology.  
Overall, the 3 GPP's efforts in Release 18 aim to enhance sidelink communication for V2X services, support the coexistence of LTE V2X and NR V2X devices, and extend 5G NR capabilities to UAVs, catering to the evolving needs of various industries and facilitating seamless communication between vehicles and aerial vehicles [80; 81; 82].
# Joint Uplink and Downlink Resource Allocation for D2D Communications System
## 2 System Model and Problem Formulation
### System Capacity  
The status parameter \(\rho_{mk}^{u}\) of the uplink is  
\[\rho_{mk}^{u}=\left\{\begin{array}{ll}1,&\text{if D2D}_{k}\text{reuses the uplink of CU}_{m}\\ 0,&\text{otherwise}\end{array}\right. \tag{2}\]  
where \(\rho_{mk}^{u}\) is a binary variable.  
The status parameter \(\rho_{mk}^{d}\) of the downlink is  
\[\rho_{mk}^{d}=\left\{\begin{array}{ll}1,&\text{if D2D}_{k}\text{reuses the downlink of CU}_{m}\\ 0,&\text{otherwise}\end{array}\right. \tag{3}\]  
where \(\rho_{mk}^{d}\) is a binary variable.
## 8 Conclusions
### Further Works  
In order to improve the application limit of the aerobot speech interface, alternative automatic speech recognisers with different learning models from the CMU Sphinx's hidden Markov model would be considered next. ASRs based on artificial neural network or deep learning are of particular interests, such as the IBM Watson speech to text cloud AI service [27]. A hardware upgrade to directional, noise canceling, and array microphones would be considered. Multi and single word speech command selection would be optimised in favour of the more resilient command variant as observed in this particular study.  
In order to improve the gesture performance, better alternative hardware (cameras and single board computers) capable of capturing high resolution images and performing complex graphic computation processing in real time would be used. In addition, instead of the appearance-based 2D-model algorithm used in this paper, a more advanced 3D-model based AI gesture algorithm would be developed for capturing and recognising hand, arm, and upper body gestures.  
The following are available online at [[http://www.mdpi.com/2076-3417/9/10/2066/s1](http://www.mdpi.com/2076-3417/9/10/2066/s1)]([http://www.mdpi.com/2076-3417/9/10/2066/s1](http://www.mdpi.com/2076-3417/9/10/2066/s1)), Table S1: Varying Noise Levels--Commands, Table S2: Varying Noise Levels--Word Frequency, Table S3: Varying Lighting Levels--Finger Gestures.  
Conceptualization, A.O.A., S.D.P., P.S., and S.D.R.; Methodology, A.O.A., S.D.P., P.S., and S.D.R.; Software, A.O.A.; Validation, A.O.A., S.D.P., P.S., and S.D.R.; Formal Analysis, A.O.A.; Investigation, A.O.A.; Resources, A.O.A., S.D.P., S.D.R., and P.S.; Data Curation, A.O.A.; Writing--Original Draft Preparation, A.O.A.; Writing--Review & Editing, A.O.A., S.D.P., and P.S.; Visualization, A.O.A.; Supervision, S.D.P., P.S., and S.D.R.; Project Administration, A.O.A., S.D.P., and S.D.R.; Funding Acquisition, A.O.A. and S.D.P.  
This research was funded by the Petroleum Technology Development Fund (PTDF) of the Federal Government of Nigeria, Grant Number: PTDF/16 PHD052/862.  
The authors wish to acknowledge [PERSON] for directional guidance given during the first half of this research work.  
The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.  
The following abbreviations are used in this manuscript:  
Aerobat Aerial Robot  
ASR Automatic Speech Recognition/Recognisers  
API Application Programming Interface  
CMU Carnegie Mellon University  
LS Lighting Stage  
mSVG Multimodal Speech and Visual Gesture  
nCA Navigational Control Autonomy  
NUI Natural User Interface  
OpenCV Open source Computer Vision  
SC Speech Command  
SW Speech Word  
UAV Unmanned Aerial Vehicle  
VLL Varying Lighting Level  
VNL-WF Varying Noise Level--Word Frequency  
VNLC Varying Noise Level--Command
## 2 Materials and Methods
### Models  
The Langmuir model in the general form and linear form according to the Langmuir, Lineweaver-Burk, Scatchard, and Eadie-Hoffsie linearization methods were used to model isotherms. These models are shown in Table 1. The models in linear form were used to calculate the characteristic coefficients of the process, while the model in general form was used for error analysis.  
The sorption capacity q in mg/g was calculated based on Equation (2), in which m denotes the adsorbent mass (in g); C\({}_{\mathrm{e}}\) denotes the equilibrium phosphate (mg/L); and V denotes the sample volume, given in L  
\[\mathrm{q}=\frac{\mathrm{C}_{\mathrm{e}}\cdot\mathrm{V}}{\mathrm{m}} \tag{2}\]  
The modeling of the process using Langmuir isotherms was conducted using linear forms, in which graphs with Ce/q = f(q) in the Langmuir linearization, 1/q = f(1/Ce) in the Lineweaver-Burke linearization, q/Ce = f(q) in the Scatchard linearization, and q = f(q/Ce) in the Eadie-Hofstee linearization [47,49] were made. The points on the graphs were approximated via a linear function accounting for the slope coefficients and the point of intersection with the vertical axis. This allowed for the calculation of the characteristicparameters, which are the Langmuir isotherm constant, K\({}_{\rm L}\), and the maximum sorption capacity, i.e., the mass that the analyzed adsorbent, qmax, can bind.  
To evaluate the degree of fit of the linear trend function, the coefficient of determination, R\({}^{2}\), was determined. The separation coefficient, also called the equilibrium parameter, R\({}_{\rm L}\), which is expressed in Formula (8), was also calculated:  
\[R_{L}=\frac{1}{1+K_{L}\,C_{0}} \tag{8}\]  
R\({}_{\rm L}\) is interpreted as follows: R\({}_{\rm L}\) < 1 indicates that adsorption is favorable; R\({}_{\rm L}\)\(\sim\) 0 indicates that adsorption is irreversible; R\({}_{\rm L}\) = 1 suggests that the adsorption isotherm is linear; and R\({}_{\rm L}\) > 1 indicates that adsorption is unfavorable [28]. A considerable number of publications inaccurately indicate that adsorption is irreversible when R\({}_{\rm L}\) = 0 [25; 26; 27; 47; 52; 53]. Such a situation cannot occur, as the denominator must reach infinity. For the high denominator values in Formula (8), the R\({}_{\rm L}\)-value will be very small--close to zero. Also highly doubtful is the situation wherein R\({}_{\rm L}\) > 1. This can occur only if the product C\({}_{0}\) \(\cdot\) K\({}_{\rm L}\) < 0 translates into a negative value of the constant K\({}_{\rm L}\) because C\({}_{0}\) cannot be harmful.
## 2 Materials and Methods
### Antibiotic Susceptibility Testing  
A total of 240 random colonies from the detected bioindicator isolates in mango peel (50 colonies) and remaining pulp (30 colonies) and wedges (160 colonies) were picked up and used for antibiotic susceptibility test using commercial discs such as: Amoxicillin (AMX: 25 \(\upmu\)g), Ampicillin (AM: 10 \(\upmu\)g) Gentamicin (CN: 10 \(\upmu\)g), Kanamycin (K: 30 \(\upmu\)g), Tetracycline (TE: 30 \(\upmu\)g), and Cefuroxime (CXM: 30 \(\upmu\)g). For the disk diffusion assay, we used the concentrations recommended by the Scientific Committee on Animal Nutrition (discs provided by Merck, USA). For quality control of the disks, _Escherichia coli_ ATCC2592 was used. The microbiological breakpoints reported by the FEEDAP standards were used to categorize the isolates as susceptible, intermediary, or resistant [29]. The % of resistance was determined as the number of total bacteria resistant/number of total isolates.  
Lactic Acid Bacterial Strains Growth Conditions, and Preparation of Cell-Free Supernatant (CFS) and Precipitated Peptides (PP)  
CFS and PP from _L. plantarum_ UTNCys5-4 (GenBank accession No. KY041686.1) and _L. lactis_ subsp. _lactis_ UTNG428 (GenBank accession No. MG675576.1) were obtained as described [21]. Briefly, the LAB strains grown in MRS (de Man Ragosa and Sharpe) broth at 37 \({}^{\circ}\)C for 24 h were used to extract CFS by centrifugation at 13,000\(\times\)\(g\) for 30 min (4 \({}^{\circ}\)C), followed by filtration using 0.22 \(\upmu\)m porosity syringe filter (#STF020025H, Chemlab Group, Washington, USA). To obtain partially purified peptides (PP), ammonium sulfate was added at 80% saturation to the CFS extract followed by overnight incubation with refrigeration without stirring and centrifuged at 8000\(\times\)\(g\) for 30 min and 4 \({}^{\circ}\)C. The PPs were recovered in 25 mM ammonium acetate (pH 6.5), desalted by using a midi dialysis kit (cat # PURD10005-1 KT, Sigma-Aldrich Co. LLC, Saint Louis, MO, USA), was pre-equilibratedwith phosphate buffer (pH 7.0), and stored at (-) 20 \({}^{\circ}\)C before use in antimicrobial assays. Titer, estimated as AU/mL (defined as the highest dilution that inhibited the growth of the indicator strain), was determined as described [21]. The CFS and PP with a determined concentration (ranged from 800 to 12,800 AU/mL) were added independently into broth tubes containing the indicator bacteria, incubated for 24 h at 37 \({}^{\circ}\)C followed by plate agar to determine the minimum concentration that inhibits 50% of the target bacteria. The titer was estimated at 6400 AU/mL for CFS and 9600 AU/mL for PP toward each indicator tested.
# Electrochemical Properties of NdCl3 and CeCl3 in Molten LiCl-KCl Eutectic Salt
## 4 Conclusions  
The present study collects the available thermochemical and electrochemical properties of CeCl\({}_{3}\) and NdCl\({}_{3}\) in the molten LiCl-KCl eutectic for pyroprocessing technology. The determination of the reaction mechanism was primarily investigated with cyclic voltammetry and was confirmed using Nernst plots. The results include the apparent standard potential, diffusion coefficient and the activity coefficient in the molten salt considered. The free Gibbs energies of formation, and the activity coefficients were derived from the electrochemical measurements. Apparent standard potential was determined through plotting the equilibrium potential, determined via cyclic voltammetry, of each concentration measurement against the natural logarithm of the concentration. The intercept of this Nernst plot was defined as the apparent standard potential. For apparent standard potential values of CeCl\({}_{3}\), a good agreement was obtained with the literature data, except above 773 K. The activity coefficient can then be calculate based on the experimentally determined apparent standard potential and standard-state Gibb's free energy.  
Conceptualization, S.K. and S.-h.L.; methodology, S.K.; software, S.-h.L.; validation, S.K.; investigation, S.K.; data curation, S.-h.L.; writing--original draft preparation, S.K.; writing--review and editing, S.K.; visualization, S.-h.L.; project administration, S.K. Both authors have read and agreed to the published version of the manuscript.  
This study is supported by MOTIE and KETEP (No. 2018170201770).  
Both authors declare no conflict of interest.
## 5 Precise Point Positioning (PPP)
### Static PPP Solutions
For the four solutions GB114, GB134, B134, and B114, it is noteworthy that when BeiDou-3e satellites were added, the performance for the horizontal components was improved to a limited extent. As shown in Figure 10, the horizontal and vertical precisions of BeiDou-only solutions are both lower than those of solutions GPS, GB114 and GB134. This may be caused by the
## 5 Discussion
### Injectivity and Productivity Decline  
A few months after the Mezobereny wells were completed and the production testing was carried out, the productivity of the injection well (well VS-1) had declined from \(\sim\)400 L/min to \(\sim\)40 L/min; as already noted, injectivity decline is common in Hungary. Our thin section analyses support previous studies that suggest scaling and erosion as common causes of these injection problems [19]. Our XRD analysis shows that much of the cement in the analyzed samples is calcite, which could easily dissolve if injection water chemistry were not carefully managed, potentially leading to reservoir erosion and fines migration. In addition, the dissolved calcite could be re-deposited elsewhere, clogging pore space. Another possible cause of the productivity decline is that hydraulic connectivity between both wells is poor [18]. If the sandstone bodies intersected by the wells do not form continuous flow paths between the wells, reinjected water cannot easily flow into and through the reservoir, which increases the pressure required to sustain flow rates [49]. Connectivity issues are common in sedimentary reservoirs, especially if the sandstone content is low as the GR logs of well VS-1 and T-1 indicate (Figure 2) [50; 51]. [PERSON] et al. [52] reported an example of the impact of poor reservoir connectivity on recovery efficiency in the Sirikit hydrocarbon field in Thailand, which may be an analogue of the Ujfalu Fm.  
Another injectivity-reducing factor was recently recognized in the Mezobereny wells; in 2017, biofilm was found in the reinjection well VS-1 following maintenance work. We consider it unlikely that this biofilm caused the early injectivity decline in this well, but we mention it here to give a full overview of injection issues in the Ujfalu Fm. Microbiology might both reduce injectivity as well as enhance scaling and reservoir erosion because it could influence pH and water chemistry. The microbial activity at Mezobereny might have been introduced by circulating insufficiently cleaned surface water during maintenance; alternatively, autochthonous microbes might have been activated by injecting water that was chemically different from the original formation water [53]. Indeed, [PERSON] et al. [54] have presented a detailed analysis of the biofilm-related issues that have affected the geothermal energy project at Hodmezovasarhely in SE Hungary (\(\sim\)25 km NE of Szeged; Figure 1).