esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions and Future Work  
In this paper, we proposed a constructive adaptive HDR data hiding method, where a stego HDR image is synthesized during the HDR format conversion. Secret messages are adaptively embedded based on the distribution of the E channel information, so more messages are conveyed in lower-luminance pixels and fewer in higher-luminance areas. Thanks to the optimal base mechanism we propose, our algorithm not only complies with a user's demand, but also generates a stego image with minimal mean squared error. To the best of our knowledge, our algorithm is the first providing prediction and satisfying the user's embedding capacity demand in the HDR image literature. To further protect the stego image from unauthorized user access as well as the hidden secret message, we adopted 2D Sine Logistic modulation map and the sequence produced passed 16 randomness tests in the NIST SP 800-22 test suite, confirming that it has better hyperchaotic behavior to cipher the stego HDR image. We introduced a random permutation technique able to fully shuffle the pixel contents, thus achieving the bit-level permutation image ciphering. We adopted six metrics to thoroughly and comprehensively evaluate the security of the stego ciphered HDR RGBE image. Our scheme offers 18% to 32% larger embedding rate than the current state-of-the-art schemes' results without degrading the quality of stego image. The security evaluation confirms that our scheme provides high security that is superior to the competitors.  
Our future work is to extend the current algorithm to provide the reversibility, able to restore the original HDR image after message extraction, and to improve our algorithm by taking into consideration human visual sensitivity for message embedding.  
Conceptualization, C.-F.L. and C.-M.W.; methodology, C.-F.L.; software, C.-F.L.; validation, C.-F.L.; writing--original draft preparation, C.-F.L. and C.-M.W.; writing--review and editing, C.-F.L. and C.-M.W.; project administration, C.-M.W. and W.L.; Supervision, W.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable. Data Availability StatementData are available in a publicly accessible repository.  
This work is supported in part by the Ministry of Science and Technology, Taiwan, under Grant MOST 107-2221-E-005-069, 108-2221-E-005-051, MOST 110-2221-E-005-062, and NSC-111-2221-E-005-076.  
The authors declare no conflict of interest.
# MuMIA: Multimodal Interactions to Better Understand Art Contexts
## 2 Related Work and Motivation
### Motivation  
From the aforementioned discussion, we argue that voice and gaze interaction channels (through sound/speech and gaze interfaces) can be combined to build an interactive multimodal system that aims to improve the visitor experience. The motivation underlying our work is the design of a multimodal interface, based on eye tracking (gaze interface) and voice (sound/speech interface), for exploring virtual cultural heritage exhibitions. Through the evaluation of this multimodal interface, we aim to investigate whether we can provide the visitors with a better understanding of art contexts and can improve their experience in a cultural heritage institution (e.g., virtual museum). Therefore, the research question that this paper aims to answer is:  
_\" Is the design of an interactive multimodal interface based on eye-tracking and voice communication within the cultural heritage domain feasible? \"_  
In case of a positive answer, we aim to answer the following question too:  
_\" What is its impact on the visitor experience? \"_  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Work** & **Sound/Speech Interface** & **Gaze Interface** \\ \hline [PERSON] et al. [44] & Not available & Eye-tracking was used to elicit visitors’ cognitive profiles and to adjust cultural heritage applications (virtual tour and game) during visit time. \\ [PERSON] et al. [45] & Passive audio guide & Gaze data were used to build visitors’ attention models to extract patterns and to provide art recommendations that would be interesting to the visitors during visit time. \\ [PERSON] et al. [46] & The visitors were delivered with verbal information about the exhibit they were looking at. Gesture identification was also employed. \\ [PERSON] et al. [47] & After identifying an exhibit, the corresponding audio file was played and verbal information was delivered to the visitors. \\ [PERSON] et al. [48] & Not available & Mobile eye tracking was used to identify areas of attention on exhibits and identify eye-movement patterns within exhibition spaces during visit time. \\ [PERSON] et al. [49] & Not available & Gaze interactions was used to enable visitors of an exhibition to select artworks, to perform image handling (e.g., scrolling and resizing), and to define areas of interest. \\ Our tool: _MuMIA_ & Visitors ask for information about the areas of interest they look at. They can combine areas of interest and ask for information about them, including areas that they had looked at before. The system provides visitors with verbal information. \\ \hline \end{tabular}
\end{table}
Table 1: Comparison between our proposed tool (_MuMIA_) and other tools in cultural heritage that are primarily based on active eye tracking.
# Performance Evaluation of a Novel Propulsion System for the Spherical Underwater Robot (SURIII)
## 6 Conclusions  
A novel spherical underwater robot which has more stable propulsion system and better hydrodynamic performance than a previous version was developed. Firstly, a novel propulsion system was proposed to improve the dynamic performance and stability of the SURIII. Although one more water-jet thruster increases the weight of the robot from 6.3 kg to 6.9 kg, the improvement of performance for the robot more than offsets the additional weight. In the up and forward motions, the direction of the propulsive force is aligned with the direction of motion, rather than merely having a component along it. Therefore, this kind of propulsion system can provide greater propulsive force for the underwater robot. Secondly, the hydrodynamic analysis of the SURIII was presented as two different motions: surge and heave. According to the influence of edges and gaps in the SURIII, two kinds of methods were given to analyze the drag coefficient. In surge motion, the drag coefficient is 0.4 which can be selected according to the Reynolds number. Thirdly, the hydrodynamic model for CFD simulation was established. Some relevant parameters and conditions were presupposed in the pre-processing. And the pressure contours, velocity vectors and velocity streamlines were obtained from the post-processing. The maximum pressure occurred in the top, bottom and near the edge in heave motion. The maximum resistance was obtained in down motion. The drag coefficient was calculated by hydrodynamic equation and it equals to 0.386. This indicates that edges and gaps effect  
Figure 19: The average propulsive force of different experimental cases. (**a**) Case I; (**b**) Case II; (**c**) Case III.  
little. The calculated drag coefficient in surge motion is 0.394, it has a 1.5% error compared with the chosen one, which indicates the robot can be similarly considered as a sphere. Finally, the experiment is conducted for measuring the propulsive force of multi-vectored water-jet thrusters. The experimental results indicate that the propulsive force is greater than that of the previous version. The changed amplitude of the propulsive force is within 6%.  
This research is partly supported by the National Natural Science Foundation of China (61375094), the National High Tech. Research and Development Program of China (No. 2015 AA043202) and SPS KAKENHI Grant Number 15K2120.  
[PERSON] and [PERSON] co-organized the work; [PERSON] and [PERSON] conceived and designed the simulation and experiment work; [PERSON] performed the simulation and experiment work; [PERSON] contributed analysis and experiment tools; [PERSON] wrote the paper; [PERSON] have made substantial contributions to guide and revise the manuscript.  
The authors declare no conflict of interest.
## 4 Simulation and Analysis
#### 4.1.1 Architecture  
The structure of the intention recognition network is shown in Figure 2, where the number of neurons in each fully connected layer of the stacked network was set to 128; the three LSTM layers were formed as 512, 256, and 128. The _tanh_ activation function was chosen for the state activation function of the intent recognition network. The weight matrix was orthogonally initialized to avoid gradient disappearance or gradient explosion at the beginning of the training equation. Then, we set the initial value of the bias to zero. The length of the sequence was set to 200.
# Heparin-Eluting Tissue-Engineered Bioabsorbable Vascular Grafts
## 3 Heparin Conjugation Methods
### Chemical Conjugation
#### 3.2.2 Electrostatic Interactions  
Heparin-loaded gelatin electrospun scaffolds have been used to exploit the drug delivery potential of heparin scaffolds as vascular grafts [32]. Heparin-containing scaffolds were developed by exploiting the electrostatic interaction between positively charged gelatin and negatively charged heparin. Sustained release of heparin was observed from the gelatin-heparin scaffold in vitro over a period of 14 days. Biocompatibility studies performed with human umbilical vein endothelial cells (HUVECs) in vitro showed that cell viability and proliferation were better on the gelatin-heparin scaffold when compared to the control. In a study by [PERSON] et al., electrospun grafts were prepared from polyurethane elastomer (PU) containing cell adhesion peptides and heparin as an anticoagulant [58]. The cell adhesion peptides enhance effective EC adhesion, which is essential for the biocompatibility of the scaffold. The bio-functionalization of the scaffold was confirmed in vitro by increased HUVEC adhesion and cell proliferation. A significant increase in patency of the surface-modified graft compared to the pristine polyurethane graft was also reported in a 60-day validation. The patency rate at nine weeks after grafting was significantly higher in the modified PU graft (71.4%) than in the control graft (46.2%). The non-treated PU grafts showed higher levels of \(\alpha\)-SMA expression compared to the modified grafts.  
Additionally, heparin conjugation is useful to prevent the thrombosis of otherwise positively charged materials due to its highly negative charge. As such, some groups have improved sustained heparin release by changing the surface charge. [PERSON]'s group selected mesoporous silica SBA-15 composed of silicon for the sustained release of heparin and optimized the surface conditions of their bioengineered scaffold. Their modified SBA-15 material promoted the sustained release of heparin and extended the release equilibrium time up to 60 days. Furthermore, the APTES-modified SBA-15 sample was able to capture three-fold more heparin than the parent SBA-15 due to the positive charge that attracted heparin through electrostatic interaction, increasing the release rate to 80% (38% for SBA-15) [59; 60]. These results suggest the feasibility of this approach.
# A Study on Analyzing Travel Characteristics of Micro Electric Vehicles by Using GPS Data
## 2 Literature Review
### Research on Travel Data Using Location-Based Information  
The collection of location-based data has been increasing recently with the integration of GPS data collection devices on vehicles, mobile phones, etc. Even for vehicles that do not come with this technology integrated by default, data collection happens through any mobile device connected to the vehicle. These technologies have made it easy for us to collect, analyze, and deduct results from location-based data. For example, we can now derive the places most visited this month by analyzing the number of devices choosing specific locations as their destinations. Furthermore, the collection of location-based data from vehicles helps us to determine areas of traffic congestion, collisions, etc. The information obtained in these cases is then analyzed by GPS technologies, and these routes are not suggested for a period until the traffic clears.  
There have been studies conducted where data on driving patterns, driving behaviors, and stopping behaviors of trucks were collected and analyzed using machine learning methodologies to classify truck stop locations into two categories, primary and secondary [12]. Additionally, GPS data collection from public transport vehicles can help us to analyze the quality of services a transportation system provides. Research has been conducted to analyze the same by monitoring the routes the transportation system covers, monitoring the number of cycles that a public transport vehicle achieves in a day, and monitoring whether a bus operates on its schedule. This activity helped determine the areas of improvement that a new bus service needs to establish, and analyze the public use of the system on weekdays as compared to weekends. Furthermore, it helped in deciding the number of additional buses to be added to existing routes to improve the quality of the service delivered [13].  
Interestingly, GPS data collection can help us accurately predict delivery times for goods in the logistics market. For example, information has been collected from transport trucks operating in Mexico to analyze the data and predict accurate delivery times and possible delays, and eliminate activities that cause potential delays in delivery operations. This can help industries to become more reliable and develop trust with customers, thereby improving export markets, along with providing a lean approach to industries [14].
## 4 Flight Experiments  
In hover flight, sweep-motions were manually conducted on Configuration D in longitudinal direction, lateral direction and yaw direction. Time duration was 10 s\(\sim\)15 s. The input control signals and output responses were recorded by the onboard computer. The output responses are angular velocities, linear accelerations, Euler angles, power and so forth.  
In high speed condition, the compound flights were difficult to conduct manually. Thus, Configuration D and Configuration WD were realized in automatic flights. The control algorithm written in the onboard computer made the helicopter fly at a constant height following a route. Figure 8  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Mode** & **IDM** & **NMM** \\ \hline Pitch & [0.4261, 21.6214] & [0.4812, 20.2831] \\ Roll & [0.3288, 26.9422] & [0.3695, 27.8265] \\ Yaw & [0.5045, 19.8832] & [0.5100, 23.1020] \\ Heave & (\(-\)1.7136) & (\(-\)1.7101) \\ \hline \hline \end{tabular}
\end{table}
Table 6: Hover eigenvalues in the updated NMM compared with IDM.  
shows the control logic in the tests. The helicopter performed an acceleration from hover to the target forward speed and maintained the target speed in straight and level status. In the allocation algorithm, from low speed to high speed, the ducted fan gradually replaced the action of the longitudinal cyclic pitch \(\delta_{lon}\) to control the forward speed. In general configuration, the helicopter needs to maintain a \(-10^{\text{o}}\) pitch angle at 25 m/s to provide necessary forward thrust. But after installing the ducted fan in Configuration D, it only needs a constant \(-2^{\text{o}}\) pitch angle at 25 m/s and the ducted fan dominated the forward-direction control. In the experiment of Configuration WD, \(\theta_{a}\) was set to zero and the lateral control still relied on the lateral cyclic pitch of the main rotor. The T-style vertical and horizontal stabilizer were not installed in these validation experiments. From the forward flight data, 5 s-10 s period of stable speed section at different target speeds were extracted. The criteria of selecting the stable speed sections were: error of forward speed \(|\Delta u|\leq\ 0.3\ \ \text{m/s}\), error in height \(|\Delta H|\leq\ 2\ \ \text{m}\), error in pitch angle \(|\Delta\theta|\leq 2^{\text{o}}\) and error in roll angle \(|\Delta\phi|\leq 2^{\text{o}}\). Trim results can be obtained by the mean values of these stable section data.
## 4 Discussion on the Results  
While applying the above described mathematical procedure, the technical powers were calculated and are listed for the measured parameters in Figure 14. Once the mechanical power on the shaft and the technical power of the compressor are known, then the Formula (1) can be used to determine the total thermal power of the compressor \(P_{\text{ts}}\) (Figure 15). During the gas compression, this power must be absorbed by the cooling water. The heat loss into the surrounding environment, which is caused by free convection and radiation, was identified by an approximate calculation of a maximum 2.4% of the total compressor input power and by considering the low level of, they were subsequently ignored.  
Figure 14: Calculated technical power (\(P_{\text{TW}}\)) in Stages 1 and 2 of the gas mixture compression.  
Figure 13: Values of the polytropic exponents \(n_{1}\) and \(n_{2}\).  
The minimum cooling water flow rate (Figure 16) is determined using the Formula (14):  
\[Q_{V\mathrm{wmin}}=\frac{P_{\mathrm{ls}}}{\rho_{\mathrm{w}}\cdot c_{\mathrm{w}} \cdot(t_{\mathrm{wmax}}-t_{\mathrm{wi}})}, \tag{14}\]  
where \(Q_{V\mathrm{w\,min}}\) is the minimum cooling water flow rate (m\({}^{3}\cdot\)s\({}^{-1}\)), \(\rho_{\mathrm{w}}\) is the water density at the mean temperature (kg\(\cdot\)m\({}^{-3}\)), \(c_{\mathrm{w}}\) is the specific heat capacity of the water at the mean temperature (J\(\cdot\)kg\({}^{-1}\cdot\)K\({}^{-1}\)), \(t_{\mathrm{w\,max}}\) is the maximum allowable temperature of the cooling water at the outlet from the compressor (\({}^{\circ}\)C), and \(t_{\mathrm{wi}}\) is the temperature of the cooling water at the inlet to the compressor (\({}^{\circ}\)C).  
The minimum flow rate also depends on the temperature of the feed water. At the maximum compressor thermal power of 10.8 kW and at the maximum allowable outlet water temperature (50 \({}^{\circ}\)C), a sensitivity analysis of the minimum flow rate to the change in the cooling water inlet temperature can be carried out (Figure 17).  
The compressor was also tested at an outlet temperature of cooling water above 50 \({}^{\circ}\)C. This state corresponded to an increase in the electric current from the nominal value of 41 A to 43 A. The current increase was induced by the increase in the gas overpressure at the inlet to Stage 1 of the compressor up to 25 kPa, which was representing an approximately 2.5-fold increase of the overpressure that was occurring in a regular operation at the inlet to Stage 1.  
Figure 16: Minimum cooling water flow rate required for cooling the compressor.  
Figure 15: Thermal power of the compressor.
## 3 Dataset  
Keelung Chang Gung Memorial Hospital in Taiwan collected a kidney ultrasound image dataset, which contained a total of 798 kidney ultrasound images from 205 patients. All subjects agreed to the ultrasound image collection, and the study was approved by the Institutional Review Board of Chang Gung Memorial Hospital (IRB No. CGMH-99-0029B). The acquired dataset was de-identified to protect the patient's privacy. Subjects with diabetes, acute renal failure, polycystic kidney disease, and hydronephrosis were excluded from this study, and the subjects were aged between 18 and 75 years. The ultrasound kidney images were obtained using a Toshiba PowerVision 7000 SSA-380A ultrasound scanner, equipped with 3.5 MHz and 5.0 MHz linear array or convex scanning probes, and the images were acquired under the same environmental settings. Among the 798 kidney ultrasound images, five images were obtained from the left kidney, right kidney, and different directions of the same patient at the same time. In addition to these five images, only the images of the left or right kidney of the patients were taken. After removing the marks, borders, length, and width information, and other additional marks in the images annotated by the doctors, the dataset contains 607 different images in total.  
All subjects underwent blood tests and renal ultrasound examinations simultaneously, and a collective diagnosis by two experienced nephrologists for CKD stage classification of each subject was performed based on both eGFR index and renal ultrasound images. The eGFR threshold settings were defined as 15, 30, 60, and 90 mL/min/1.73 m\({}^{2}\) for five different CKD stages. According to the settings, from the first to the fifth CKD stage, the remaining ultrasound images contained 231, 134, 91, 108, and 43 images, respectively [35]. However, the number of images in the fifth stage was relatively small; we combined the fourth and fifth stages into the fourth stage and represented it as a serious condition stage. Several examples of kidney images are shown in Figure 1. From the left to right columns, the images were diagnosed from the first to the fourth categories.  
Figure 1: Kidney ultrasound image data collection. The images of different CKD stages are displayed from left to right columns.
## 2 Materials and Methods
### Experimental Groups  
The teeth were removed, the cotton pellet was taken out, and the same irrigation process was performed. Afterward, the canals were dried with sterile paper points. The samples were randomly divided into 5 main groups according to the prevention of discoloration strategies:  
* Group 1: (No laser, no bonding application) The internal walls of the pulp chamber were not sealed with any method, and this group was used as the control group.
* Group 2: (Optibond FL, Kerr Corporation, Orange, CA, USA) After 15 s of acid application to the pulp chamber, the acid was washed away for 15 s. After gentle air drying, prime was applied by rubbing for 15 s. After air drying, adhesive was applied by rubbing for 15 s and polymerized for 20 s after air drying.
* Group 3: (Clearfill SE Bond, Kuraray Medical Inc., Tokyo, Japan) It was applied to the pulp chamber by rubbing primer for 20 s. After 5 s of gentle air drying, the bond was applied to the specimens. After air drying, it was polymerized for 10 s.
* Group 4: (Optibond Universal, Kerr Corporation, Orange, CA, USA) With a self-etch approach, it was applied to the pulp chamber by rubbing for 20 s. After 5 s of gentle air drying, it was polymerized for 10 s.
* Group 5: (Laser irradiation) The internal walls of the pulp chamber in this group were irradiated using an Nd:YAG laser (Fotona, Lightwalker, San Clemente, CA, USA). Lasers were used with 1 W power, at an energy level of 100 mJ per pulse, and a repetition rate of 10 Hz, for 10 s, firing interval: 250 msn. A 300 mm quartz fiber was used with pre-established movements in the occluso-apical and mesio-distal directions and vice versa.  
After applying sealing strategies, a volume of 0.2 cc of fresh human blood was obtained from one of the researchers (T.O). This blood was injected directly into the root canal using an insulin syringe, filling it up to approximately 4 mm below the CEJ. Subsequently, a blood clot was allowed to form over a 15 min period, and spongostan (Cutanplast, Milan, Italy) was placed on the clot. A 3 mm thickness of ProRoot MTA in the coronal third of the root canal was positioned 1 mm below the CEJ. The endodontic access cavity was sealed with temporary restorative material, and the thickness and depth of the MTA were verified by capturing a periapical radiograph. Throughout the entire experiment, the samples were maintained at 37 \({}^{\circ}\)C with 100% humidity (Figure 1).