esa-sceva/satcom-chunk-collection huggingface dataset:
# Analysis of Trends in Korean BIM Research and Technologies Using Text Mining
## 5 Conclusions  
In order to propose a strategic direction for the future of BIM-related research and technology in Korea, in this study, research papers related to BIM in Korea were collected and the change patterns and research trends of the BIM research periods were analyzed by dividing them it into the periods of introduction, development, and adaptation using text-mining methods and techniques, frequency analysis, and topic modeling methods. We first conducted a keyword search on the titles of theses to know the overall trend. As a result, we realized the distribution by keyword for about 5000 papers, and it was found that the number of papers increased gradually from 2013 to 2017. In addition, we classified them by the number of articles. 'Period A' is the phase of first publication in Korea about BIM. 'Period B' is represented by a rapid increase in the number of publications. Lastly, 'Period C' is the period of a regular rate of publications. In conclusion, the introduction period of BIM includes a comparison with traditional methods in relation to the introduction of BIM, a change in the working environment, and interoperability for exploring and utilizing the new BIM paradigm. In addition, the interest in 3D authoring tools for implementing BIM implementation increased. In the development period, as a result of the increasing interest in the quality and performance of buildings, the research on energy increased significantly; BIM was not seen as being limited to functioning as a modeling tool, and research on standards and guidelines for quantity calculation, cost analysis, practical application, and project management was actively conducted. In the application of BIM in practice, various practical problems have arisen, and researches were conducted to solve these problems. As the adaptation period progressed, a steady progress in research on various technologies that could be used in BIM was observed--such as the calculation of energy, quantity surveys, and cost analysis--instead of a study of the environmental problems for initial BIM adaptation. In addition, as the necessity and importance of the literature in terms of practical applications increased, the related research increased greatly. The words 'design', 'construction', 'process', 'data', and'system' were the most used terms in Periods A, B, and C. As time went on, we realized that words used in various fields, like civil engineering, information communication technology (ICT), among others, appeared rather than words limited to the field of architecture. The focus of attention on adaptation is a priority, and there are various efforts being made to apply BIM in areas other than construction, such as railways, tunnels, and harbors. In addition, it is being converged with advanced fields such as IoT and deep learning, which presents a potential future direction for BIM. As BIM evolves in the fourth industrial revolution, its convergence with technologies such as those associated with IoT and deep learning will result in an increase in automation, even in knowledge-based tasks.
## 3 Continuous-Time Spline Representation for Fast Motion Estimation
### Accuracy Evaluation of B-Spline Representation  
Using Equations (18)-(20), the continuous-time's position, velocity and acceleration of a moving object can be estimated. The sampling frequency of knots (i.e., the frame-rate of cameras) influences the accuracy of the estimated result. We use HFR cameras with a different frame-rate to capture the known motion of a moving object. Using cubic B-spline motion estimation, the distribution of the position error, velocity error and acceleration error in three axes of the world coordinate are shown in Figure 4.  
With the initial velocity at around 30 m/s, with a captured frame-rate of over 500 FPS, the velocity error of the B-splines estimation can be controlled under 16 cm/s. The percentage error of the position, velocity and acceleration are under 1%.  
Figure 4: Boxplot of position error, velocity error and acceleration error (cm/s\({}^{2}\)) in three axes of the world coordinate with a frame-rate from 180 to 1080 FPS.
# A Noncontact Method for Calibrating the Angle and Position of the Composite Module Array
## 3 Calibration Method
### Position Calibration Experiments  
The spindle of the CMM drove the angle sensor to move according to the predetermined path, and the laser interferometer was used to monitor the precise displacement between the measurement points. Figure 10 shows the results of five repeated calibration experiments. The standard deviation for the results of each composite module is shown in Table 15.  
\begin{table}
\begin{tabular}{c c c} \hline
**Composite Module** & **Standard Deviation of the Angle** & **Standard Deviation of the Angle** \\  & **around the X-axis /arcsec** & **around the Y-axis /arcsec** \\ \hline
1 & 0 & 0 \\
2 & 0.28 & 0.25 \\
3 & 0.32 & 0.13 \\
4 & 0.27 & 0.19 \\
5 & 0.28 & 0.14 \\
6 & 0.24 & 0.28 \\
7 & 0.21 & 0.15 \\
8 & 0.28 & 0.16 \\
9 & 0.15 & 0.25 \\ \hline \end{tabular}
\end{table}
Table 13: The standard deviation of the relative angle.  
Figure 10: Repeatability of the calibration experiment.  
\begin{table}
\begin{tabular}{c c c} \hline
**Composite Module** & **Angle around the X-axis /arcsec** & **Angle around the Y-axis /arcsec** \\ \hline
1 & 0 & 0 \\
2 & 35.53 & 5.28 \\
3 & 56.27 & \(-\)50.69 \\
4 & 45.66 & \(-\)22.78 \\
5 & 29.48 & \(-\)37.01 \\
6 & 58.17 & 6.40 \\
7 & 44.61 & \(-\)16.44 \\
8 & 43.01 & \(-\)27.25 \\
9 & 41.08 & \(-\)3.26 \\ \hline \end{tabular}
\end{table}
Table 14: Calibration results of the relative angle.  
The repeatability of the data in five tests was fine, and the maximum error was within 0.4 \(\upmu\)m in the X direction and within 0.7 \(\upmu\)m in the Y direction. In order to eliminate the influence of the error caused by the single measurement, the average of the five calibration values was used as the final result, as shown in Table 16.  
Since the rotating paraboloid is turned on the metal surface of the processed plane part, the plane of the composite module may have a surface shape error owing to the limitation of the processing technology. Based on the feature point calibration scheme, the separation of the rotating paraboloid from the plane can be considered in the future, which is of great significance for improving the measurement accuracy.
# High-Speed Tomography--A New Approach to Plasma Bulk Velocity Measurement
###### Abstract  
The plasma bulk velocity is one of the key parameters describing the behavior of a plasma jet and is relevant for applications such as plasma spraying or electric propulsion. Therefore, different measurement techniques to determine the velocity were developed in the past. This paper presents a novel, non-invasive method for spatially resolved velocity measurements. The method is based on tracking of characteristic features in tomographic reconstructions of the plasma plume. A high-speed image recording system combined with tomographic acquisition is therefore the backbone of this method. The proposed setup captures the object under study from six different directions at a frame rate up to one million frames per second, providing high spatial and temporal resolution. The tomographic reconstructions are then calculated using the ART algorithm to track features in the plasma fluctuations, from which the bulk velocity is determined. The setup was tested with a DC plasma torch operated at reduced pressures in the range of tens of millibars. For the analyzed parameters, the axial velocity reached a maximum of 1061 m/s at a distance of three centimeters from the plasma torch exit and decreased to 919 m/s further downstream at a distance of seven centimeters, which is in good accordance with previous work. Therefore, the proposed diagnostic method can serve as a non-invasive alternative to velocity measurements, providing additional information in the form of a 3D model of the plasma bulk.  
tomography; plasma velocity; plasma torch; high-speed imaging +
Footnote †: journal: Applied
## 3 Results and Discussion
### Transport Distance (TD)
WBSF measurement and sensory analysis were conducted for cooked meat samples. Taste, odor, and hardness were measured using a 1 to 100 scale, where 1 stands for “not perceptible” and 100 stands for “intense”. values. These values showed that the meat from animals that had undergone short TD tended to be yellowish with intense and vivid colors, when compared with the meat pieces of animals that underwent medium and long TD. No significant differences were found for meat hardness between different TDs, according to both sensory analysis and WBSF results. There were also no significant differences observed for odor and taste judgement between treatments. A similar study that compared various pre-slaughter transport times and the sensory characteristics of beef found that there were no discernible correlations between the meat's sensory traits, including hardness, flavor, or odor, when animal transport lasted less than 6 h [55].
## 6 Conclusions and Future Work  
Blockchain has great potential in the IoT field, but issues such as scalability, security and privacy, power and processing time and storage capacity are complex and mature due to the combination of these two giant technologies. The scalability problem could be solved by designing a proper consensus algorithm. In this study, a consensus algorithm \"CBICI\" is designed for blockchain-based IoT applications, working perfectly for IoT devices that are not delay-sensitive. Limited broadcast domain causes to increase its efficiency. It can be configured according to IoT requirements due to the flexibility present in the algorithm. In this algorithm, a delay (wait to collect maximum one time data from IoT devices) is required, so it will be a great choice to use it for other IoT scenarios where delay can be tolerated. This study is only based on a consensus algorithm, so parameters that affect its scalability and throughput are addressed adequately. Results show its reliability and make it proficient in TPS and verifications (<5 s) such as present-day voting-based algorithms in cryptocurrencies. The anonymity of master node selection and validating nodes by a master make it protective against attacks. Although it has not been tried to compromise this algorithm, this could be a topic for future work.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Characteristics** & **PoW** & **PoS** & **DPoS** & ** RAFT** & **SCP** & **CBIoT (Study)** \\ \hline Accessibility & Public & Public, Private & Public & Private & Public & Public \\ \hline Decentralization & High & high & High & Medium & High & High \\ \hline Throughput & Low & Low & High & High & High & High \\ \hline Scalibility & Strong & Strong & Strong & Weak & Strong & Strong \\ \hline verification Speed & \textgreater{}100 s & \textless{}100 s & \textless{}100 s & \textless{}5 s & \textless{}5 s & \textless{}5 s \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparisons between consensus algorithms [26; 47].  
**Author Contributions:** Conceptualization, M.U., M.M. and M.K.H.; methodology, M.U. and M.M.M.; validation, M.U.; writing--original draft preparation, I.T.J. and M.K.H.; writing--review and editing, B.A. and N.C.; visualization, I.T.J.; funding acquisition, N.C. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work is partly supported with the financial support of the Science Foundation Ireland grant 13/RC/2094_P2 and partly funded from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 754489.  
**Conflicts of Interest:** The authors declare no conflict of interest
## 3 Results
### Driving Performance Test
#### 3.1.3 Key Performance Indicators  
KPIs have been selected in the context of the PRYSTINE project [47], by conducting specific project workshops with experts in the field. Previous works in shared control studies [8] were also used as a reference to select the representative measurements of the main fields of evaluation.)  
Three types of indicators are used to quantitatively evaluate the performance of the tested driving modes:  
* Tracking errors: the ability to follow the expected trajectory is evaluated by the RMS and maximum (MAX) lateral and angular tracking errors.
* Safety indicators: the RMS and minimum (MIN) TLC indicate how close (in time) the vehicle is from departing the lane limits. It is estimated at any given time assuming the steering angular speed would remain unchanged. Additionally, the percentage of the time driven with the TLC below a threshold of 3.8 s (the minimum TLC when the automated system drives alone by the testing route, with the configuration of the nominal controller) provides a measure of the risk exposure.
* Driving efforts: the RMS and maximum torque exerted by the driver provide a measure of the effort applied, which relates to conflict and comfort. The RMS and maximum automation torque provide a measure of the work performed by the system and are related to its efficiency.  
Moreover, three types of indicators are used to evaluate the subjective perception of the different driving modes, in the particular test-driving conditions, by the participants:  
* Safety-related indicators: evaluate the driver's sense of being protected, being allowed to perform the secondary task, or being required to continuously monitor the environment.
* Comfort-related indicators: evaluate the driver's feeling of the system being harmonious or too intrusive in its interaction.
* Overall driver perception: evaluates the driver's assessment of the system, using its own criteria to ponder safety and comfort behavior.
## 6 Example Solution and Analysis  
### Numerical Experiment Settings  
The program was written in Matlab 2016a 9.0 and performed on a Windows 10 computer with an AMD Ryzen 7 4800H CPU @2.90 GHZ processor, 16 G RAM, and 64-bit OS. The simulation is based on the supply chain in December 2020 of a pharmaceutical plant in North China. There are 46 customer nodes in the supply chain, and it passes by nine provinces covering three temperature zones. The distribution of the customer nodes is demonstrated in a square area of 100 \(\times\) 100 under the conversion ratio of 1:10 km, as shown in Figure 8. The temperature data and customer nodes data are collected from the China Meteorological Center Yearbook and the China Cold Chain Logistics Development Report (2021) [36].  
In the simulation area, the coordinates of the pharmaceutical factory are (58.3, 69.4), and the logistics process is divided into two distribution modes: cold chain vehicle transportation and van-loaded reefer transportation. The diesel consumption of cold chain trucks is 0.12 L/km when empty and 0.43 L/km when fully loaded. The diesel consumption of vans is 0.11 L/km when empty and 0.18 L/km when fully loaded. The unit price of diesel is 7.18 RMB/liter; the carbon emissions are in accordance with the Greenhouse Gas Inventory Protocol fuel conversion factor: 2.676 kg/L; the carbon tax rate is 30 RMB/t; the fixed cost of a van is RMB 50, the fixed cost of a reefer truck is RMB 70; the depreciation cost of reefer box use is 1.5 RMB/use; the PDF thermometer unit price is 24.8 RMB/use, according to each customer's location in the temperature zone and simulation when in the season; and the single refrigerant storage use cost is RMB 2. The customer nodes and demand table is shown in Table 4.  
\begin{table}
\begin{tabular}{c} **Coordinate** \\ **Location** \\ \end{tabular} & **Demand/Piece** \\ \hline
1 & (91.5, 94.7) & 7 & 17 & (22.9, 66.4) & 6 & 33 & (66.3, 34.7) & 21 \\
2 & (85.9, 88.2) & 5 & 18 & (21.9, 72.3) & 5 & 34 & (46.9, 34.6) & 3 \\
3 & (85.9, 88.2) & 13 & 19 & (78.1, 84.7) & 8 & 35 & (43.3, 41.1) & 5 \\
4 & (832.8, 81) & 3 & 20 & (37.5, 52.3) & 6 & 36 & (49.5, 69.7) & 10 \\
5 & (88.2, 82.2) & 9 & 21 & (49.4, 55.1) & 8 & 37 & (67.7, 29.3) & 11 \\
6 & (81.4, 75.5) & 5 & 22 & (49.2, 52.3) & 12 & 38 & (65.2, 25.8) & 9 \\
7 & (77.3, 71.2) & 8 & 23 & (66.4, 45.6) & 6 & 39 & (57.6, 29.5) & 8 \\
8 & (68.7, 67.9) & 5 & 24 & (70.3, 47.1) & 3 & 40 & (46.4, 29.5) & 16 \\
9 & (66.3, 77.9) & 3 & 25 & (76.4, 47.7) & 14 & 41 & (38.7, 29.4) & 23 \\
10 & (49.6, 75.2) & 9 & 26 & (49.7, 44.4) & 8 & 42 & (43.9, 23.6) & 11 \\
11 & (60.4, 66.1) & 7 & 27 & (84.4, 44.8) & 15 & 43 & (29.7, 41.3) & 27 \\
12 & (64.4, 64) & 11 & 28 & (65.5, 42.4) & 13 & 44 & (50.7, 39.5) & 4 \\
13 & (58.5, 61.9) & 3 & 29 & (49.4, 40.5) & 9 & 45 & (53.1, 35.6) & 6 \\
14 & (54.3, 61.5) & 6 & 30 & (41.9, 41) & 13 & 46 & (40.76.5) & 8 \\
15 & (40.8, 69.8) & 7 & 31 & (62.8, 36.8) & 17 & & & \\
16 & (33.3, 73.9) & 11 & 32 & (73.8, 35.8) & 7 & & & \\ \hline \hline \end{tabular}
\end{table}
Table 4: Customer nodes and demand table.  
Figure 8: Temperature band diagram of the customer nodes.
# Evaluation of the Variability of Vibration Measurement Results in Rolling Bearing Quality Control
## 2 Rolling Bearing Quality Control  
Although the individual components of the bearing are measured repeatedly within tight tolerances during the manufacturing process, unavoidable manufacturing and mounting errors in the individual bearing components mean that the bearing's quality can only be fully assessed once the bearing has been assembled [5].  
In order to assess the quality of a rolling bearing, both production companies and independent laboratories must have precise measuring equipment that is adapted to trends in the bearing industry [6]. Various techniques are used in the bearing industry to assess the quality of a manufactured rolling bearing, the most important of which are listed below [7; 8; 9]:  
* Vibration measurement;
* Thrust torque measurement;
* Durability testing;
* Measurement of rotation accuracy (the amount of instantaneous deviation of the bearing from its operating position);
* Measurement of noise level;
* Cleanliness test;
* Testing of load-carrying capacity.  
It must be borne in mind that the process of evaluating the quality of a bearing is complex and is strongly dependent on the requirements of the customer. Some procedures, such as vibration measurement, are always performed, while others are carried out only if specifically requested by the customer. Some procedures apply to the entire population of manufactured bearings, while others apply only to a specific statistical sample. Some procedures are destructive; others are not.  
It should be noted at this point that the methods used in quality control procedures may differ from the techniques used in rolling bearing diagnostics [10]. This difference is not only due to the measuring equipment or methods used, but may also relate to the interpretation and analysis of the measurement result. In production measurements, a bearing straight from production is tested, which may only have discrete imperfections, which diagnostic models do not take into account. In production, electrodynamic sensors measuring vibration velocity are used and vibration is measured in a relative (indirect) manner. The bearing is left unbuilt and subjected to a relatively light axial load, with the RMS value of the vibration recorded in three frequency bands at a reference speed strictly in accordance with the standards.  
Diagnostic measurements, on the other hand, concern bearings at various stages of life, which are often damaged or worn out. In these methods, piezoelectric sensors measuring vibration acceleration are used and vibration measurement is carried out in an absolute manner. The bearing under test is built up and the load can be varied both axial and radial. A variety of analysis methods are used in diagnostics, with spectral analysis being the predominant technique and the speed depending on the specific application.  
Hence, the paragraph highlighted states that although the article deals with production aspects, the knowledge can also be useful in diagnostic topics.
# Development of an Electric Pulse Device for Coal Grinding
## 1 Introduction
However, preliminary weakening of the ore using low specific energy (~2 kWh/t) results in reduced material strength, leading to a 24% decrease in energy consumption in subsequent grinding processes. These results indicate that EDT can be an effective alternative to traditional grinding methods, providing better mineral liberation with equal or lower energy consumption. Experimental studies [4; 12; 13; 14; 27; 28; 29; 30] show that the application of electric pulse technology contributes to energy savings of 30-60% when processing hard-to-beneficiate and low-grade ores compared with traditional methods like ball mills and jaw crushers. Other studies [15; 18; 31] indicate that, with proper pulse parameter settings, it is possible to achieve more than a 40% reduction in process energy consumption while maintaining the same yield of commercial fractions. The study by [14] also confirms energy savings in the range of 30-50% when processing finely dispersed minerals. Additionally, study [12] reports a 40-50% reduction in specific energy consumption when grinding certain types of ones using electric pulses. The industrial practices described by a company in [16] demonstrate improved energy efficiency of up to 60% during primary ore crushing. According to study [27], high-voltage pulse fragmentation of phosphate ore reduced energy consumption by 30-55%, significantly improving mineral liberation quality. Moreover, electric pulse technology ensures a more selective destruction of material structures, reducing overgrinding and enhancing the extraction of valuable components, which is particularly relevant for the coal industry [4; 9; 10; 15; 17; 27; 29]. At the same time, there are several challenges associated with the introduction of electric pulses in industrial systems: the complex control of pulse parameters and ensuring the durability of electrodes and the working chambers. Therefore, research aimed at improving the design of electropulse systems and optimizing their operating modes remains highly relevant. In this article, we present the laboratory development and testing of an electric pulse device for coal grinding. The research focuses on the impact of pulse frequency and voltage on the efficiency of coal grinding.