esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Analysis of Oil Displacement Performance Evaluation
#### 3.3.2 Core Displacement Experiment Evaluation  
Figure 11 shows the oil recovery, water cut and pressure difference of different polymer injection PVs.  
Table 7 shows the results of the oil displacement experiments. As shown in Figure 11, at the beginning, the injection pressure dropped rapidly and, when the oil displacement begun, the injection pressure slightly increased until it became steady. After the recovery was gradually increased to a certain value, it started to increase more slowly and, finally, remained unchanged. This was mainly because the water flooding involved a smooth migration of the oil in the formation, and the recovery levels in the water flooding stage reached 39.5%, 40.55% and 39.7%, respectively. Following the injection of the polymer, it can be seen that, when the amounts of the polymer injection were 0.2 PV, 0.3 PV and 0.5 PV, the ultimate oil recovery reached 52.26%, 57.72% and 60.35%; the lowest water cut reached 77.14%, 68.75% and 65.52%; and the EOR values were 12.76%, 17.17% and 20.65%. The pressure difference increased, and it can be seen that the polymer QJ75-39 could block the high-permeability pores and increase the sweep volume. The polymer oil recovery was higher than the water flooding, and this was due to both the improvement in the washing efficiency and the increase in the volume of the sweep.  
We can see that the polymer QJ75-39 could effectively enhance oil recovery, and with the increase in the injection PVs, the recovery increased and the lowest water cut decreased.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Injection (PV)** & **Porosity (\%)** & **K\({}_{w}\) (mD)** & **So (\%)** & **R\({}_{w}\) (\%)** & **Ultimate Recovery (\%)** & **EOR (\%)** \\ \hline
0.2 & 15.98 & 206 & 65.85 & 39.5 & 52.26 & 12.76 \\
0.3 & 15.77 & 201.7 & 65.36 & 40.55 & 57.72 & 17.17 \\
0.5 & 15.48 & 197.5 & 66.43 & 39.7 & 60.35 & 20.65 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Summary of oil displacement experiment results.  
Figure 11: Oil displacement effect curves for different polymer injection PVs.
# Robust Image Embedded Watermarking Using DCT and Listless SPIHT
###### Abstract  
This paper presents a DCT-based (DCT: discrete cosine transform) listless set partitioning in hierarchical trees (SPIHT) digital watermarking technique that is robust against several common attacks such as cropping, filtering, sharpening, noise, inversion, contrast manipulation, and compression. The proposed technique is made further robust by the incorporation of the Chinese remainder theorem (CRT) encryption technique. Our scheme is compared with the recently proposed CRT-based DCT technique, CRT-based spatial domain watermarking, and DCT-based inter block correlation techniques. Extensive simulation experiments show better robustness in common image manipulations and, at the same time, the proposed technique successfully makes the watermark perceptually invisible. A better Tamper Assessment Function (TAF) value of 2-15% and a better Normalized Correlation (NC) is achieved compared to some of the above techniques. In particular, the proposed technique shows better robustness on compression attacks at moderate to higher compression ratios. It is possible to maintain the imperceptibility and low TAF for various values by doubling the capacity of the watermark.  
discrete cosine transform; watermarking; cryptography; random number generation; normalized correlation +
Footnote †: journal:  
_Future Internet_**2017**, 9, 33; doi:10.3390/f69030033
## 4 Results and Discussion
### Discussion  
In general, it can be observed that the pressure plots appear qualitatively similar across all cases. Thus, while the reduction of the blood vessel lumen does not affect the shape of these plots, it does influence their maximum values. The smallest changes in the maximum pressures, \(p_{max}\), in the left ventricle and aorta occur between case 0 (no reduction in blood vessel lumen) and case 1 (first stage of reduction). These pressures increase in case 2 (second stage of reduction). Increasing the operating frequency, on the other hand, increases the balloon pressure for all vessel lumen reduction values.  
Figure 7: Power \(P\) consumed by the servo drive \(P_{2}\) (a system with the servo amplifier and servo motor) and power consumed by two systems \(P_{1}+P_{2}\): servo drive \(P_{2}\) plus the control system \(P_{1}\) (system with 12 V DC to 24 V DC converter and a sensor for determining the position of the compressor system base point and 12 V DC to 5 V DC converter and ODROID computer); 0—no reduction-, 1—first-, 2—second stage of the reduction of the blood vessel lumen.  
Decreasing the vessel lumen results in consecutive increases in aortic and left ventricular pressures, while there is no effect on their frequency-dependent values. The effect of frequency is evident between frequencies of 60 and 100 cyc/min. Above 100 cyc/min, the operating frequency has little effect on pressure values.  
The results obtained in terms of pressure measurements mean that the innovative implantable LVAD proposed here can operate over a wide frequency range, i.e., from 60 to 160 cyc/min, extending the applicability of the device at much higher operating frequencies than in [35].  
Increasing the operating frequency of the device results in a linear increase in energy consumption. Significantly, the effect of reducing the lumen of the vessel has a negligible effect on energy consumption. Another finding is that the part of the power, which was labeled \(P_{1}\), is constant, regardless of the operating conditions of the device.  
The innovative implantable LVAD is able to increase the mass flow rate by approximately 50% in the absence of the reduction of the blood vessel lumen with an increase in operating frequency, from 60 to 160 cyc/min. One of the reasons the device works effectively is that, in addition to supporting the left ventricle, the valve balloon occludes the mitral valve. This is a unique solution, which is unknown in the literature--the essence of which is to simultaneously block the flow through the mitral valve during systole, as well as the ejection of blood from the left ventricle into the aorta at the same time. The solutions known in the literature only support the ventricles without simultaneous valve occlusion, e.g., [16; 17; 32; 36; 37; 38; 39; 40; 41].  
Another advantage of the proposed LVAD is the minimally invasive method of implantation, which is important for patients with end-stage heart failure. This also means that it complements support in patients previously ineligible or qualified with bad results, i.e., pulmonary hypertension.
## 3 Results and Discussion
### Comparison with Other Studies  
A comparison of the proposed methodology with other studies is presented in Table 8.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Element** & **CS-1** & **CS-2** & **CS-3** & **CS-4** & **CS-5** & **CS-6** & **LS-1** & **LS-2** \\ \hline Bi & & & & & & & & \\ (mg kg\({}^{-1}\)) & 3.15 \(\pm\) 0.21 & 1.91 \(\pm\) 0.12 & 3.06 \(\pm\) 0.04 & 2.68 \(\pm\) 0.43 & \textless{}LOD & 1.38 \(\pm\) 0.02 & \textless{}LOD & 4.03 \(\pm\) 0.19 \\ Ca & & & & & & & & \\ (mg kg\({}^{-1}\)) & 10.5 \(\pm\) 0.7 & 14.6 \(\pm\) 1.0 & 7.55 \(\pm\) 0.81 & 5.93 \(\pm\) 0.10 & 26.3 \(\pm\) 1.8 & 9.76 \(\pm\) 0.34 & 2.64 \(\pm\) 0.19 & 5.10 \(\pm\) 0.14 \\ Cr & & & & & & & & \\ (mg kg\({}^{-1}\)) & 0.29 \(\pm\) 0.02 & 0.31 \(\pm\) 0.03 & 0.36 \(\pm\) 0.01 & 0.15 \(\pm\) 0.01 & 0.33 \(\pm\) 0.03 & 0.32 \(\pm\) 0.02 & 0.29 \(\pm\) 0.01 & 0.19 \(\pm\) 0.07 \\ Fe & & & & & & & & \\ (mg kg\({}^{-1}\)) & 3.15 \(\pm\) 0.21 & 1.91 \(\pm\) 0.12 & 3.06 \(\pm\) 0.04 & 2.68 \(\pm\) 0.43 & \textless{}LOD & 1.38 \(\pm\) 0.02 & \textless{}LOD & 4.03 \(\pm\) 0.19 \\ Mg & & & & & & & & \\ (mg kg\({}^{-1}\)) & 3.32 \(\pm\) 0.22 & 7.46 \(\pm\) 0.65 & 3.23 \(\pm\) 0.07 & 2.00 \(\pm\) 0.44 & 3.73 \(\pm\) 0.9 & 1.93 \(\pm\) 0.08 & 0.71 \(\pm\) 0.01 & 2.37 \(\pm\) 0.25 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Elemental composition of the hard candy and lollipop samples.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Analytes** & **Samples** & **Instrumental Technique1** & **Digestion** & **Digestion** & **Relative** & **Precision** & **LODs** & **Ref.** \\ \hline \multicolumn{6}{c}{Candy packages} & \\  & and candies & & & & & \\ Cd, Cr, Co, Cu, Mn, Pb, & (lollipops, & & & & \\ Ch, Mn, Pb, & & & & & & \\ Zn & & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 8: Comparison of the herein developed procedure with other studies.  
As can be observed, in this study the number of the examined analytes was significantly higher, and the simultaneous multi-elemental determination of both toxic and nutrient metals was possible. Moreover, the proposed methodology exhibited adequate accuracy and precision. Regarding the experimentally found concentration ranges of the proposed elements, lower LOD values were reported in other methodologies [4; 21]. This can be considered as a limitation of the proposed methodology, which can be overcome by coupling the herein mentioned experimental procedure (i.e., open-vessel wet digestion) with more advanced instrumentation, such as ICP-MS instruments, that are able to provide better sensitivity. It is important to mention that the proposed methodology could efficiently reduce the required sample preparation time and the consumption of chemicals compared to other studies [4; 21; 22], since only 3 mL of conc. HNO\({}_{3}\) was needed, while complete sample decomposition was achieved within 10 min.
## 2 Materials and Methods
### A\(\beta\) Fibril Formation and Its Observation  
A\(\beta\) was dissolved in a 0.02% ammonia solution at a concentration of 200 uM at 4 \({}^{\circ}\)C. This solution was occasionally centrifuged at 10,000 rpm, at 4 \({}^{\circ}\)C for 20 min, to separate the aggregates, because such aggregates can act as nuclei for fibrillation. The A\(\beta\) solution was maintained at 4 \({}^{\circ}\)C to avoid fibril formation. Next, A\(\beta\) fibrils were prepared using the fibril extension method, as previously described [23, 24]. Briefly, a stock solution of A\(\beta\) was diluted in Tris buffer (50 mM) at 37 \({}^{\circ}\)C to a final concentration of 10 uM, which triggered fibril formation. This sample was incubated on a variety of planar membranes  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Polymer** & **Molecular Weight, _Mw_** & \
\begin{tabular}{c} **Entanglement** \\ **Molecular Weight, _M\({}_{\text{e}}\)** \\ \end{tabular} &
\begin{tabular}{c} **Possible** \\ **Entanglement, _Mw_/\({}_{\text{e}}\)** \\ \end{tabular} \\ \hline PVP & 1,200,000 & 12,000 * & 100 \\ iso-PMMA & 500,000 & 14,600 * & 34.2 \\ syn-PMMA & 400,000 & 9200 * & 43.5 \\ PSf & 75,000 & 2250 \% & 33.3 \\  & 5000 & & 0.56 \\ PLLA & 10,000 & & 1.1 \\
20,000 & 9000 * & 2.2 \\  & 50,000 & & 5.6 \\ \hline \hline \end{tabular}  
\end{table}
Table 1: Summary of polymers.  
at 37 \({}^{\circ}\)C for the desired time (up to 120 h). As for TIRFM, the fluorescence microscopic system used to observe individual amyloid fibrils was developed based on an inverted microscope (IX70; Olympus, Tokyo, Japan), as described previously [24]. The ThT molecule was excited using an argon laser (model 185F02-ADM; Spectra Physics, Mountain View, CA, USA). The sample solution was mixed with ThT (5 \(\upmu\)M) and observed using TIRFM.  
To estimate fibrillogenesis, fibrils stained by ThT were counted in the field of view in TIRFM. ThT fluorescence intensity was estimated using ImageJ (version 1.32) imaging software. In short, the image was subtracted by the background within the same image, i.e., the place where there was no fibril. Subsequently, the fluorescence intensity originating from ThT bound to amyloid fibrils was extracted and integrated within the image. Afterwards, the integrated fluorescence intensity was averaged using more than ten images.
## 4 Numerical Example and Verification
### Effect of Tooth Longitudinal Modifications  
Using the same example cycloid gear pair with NNM, four cases were considered to demonstrate the effects of TLM on the contact stress, LTE, and GR. One is the NNM gear tooth without TLM. The other three cases are FCM, PCM, and LCM, the TLM parameters of which are listed in Table 4.  
Figure 11 shows the contact stress distributions of the NNM cycloid gear pair with different types of TLM at a random crankshaft angle, illustrated in 3D representations. From the results, it can be clearly observed that without TLM, the maximum stress is 1229 MPa concentrated at the two edges of the face-width of the cycloid gear tooth at a 120\({}^{\circ}\) crankshaft angle, while on other mesh phases, it could  
Figure 10: Comparison of loaded transmission error and gear ratio in a mesh circle obtained by the current model and the proposed model for the cases of standard, NNM, and PPM profiles.  
get even bigger, such as 1236 MPa at a 300\({}^{\circ}\) crankshaft angle. Contact stresses decrease significantly with axial distance from this edge, as shown in Figure 9a. The minimum value is about 982 MPa, occurring at the middle of the contact region. Hence, the contact pattern looks like a saddle shape, as expected.  
As shown in Figure 11, in the presence of TLM, a dramatic reduction in concentrated stress was observed, which demonstrates the significant effects of the TLM. The maximum stresses decreased to 1045 MPa, 1075 MPa, and 1030 MPa, corresponding to the three types of TLM. Among them, the case of LCM seems to show the best contact stress distribution wherein the contact pattern presents a drum shape where the contact stress is distributed more uniformly and the concentrated stress disappears; this demonstrates the effectiveness of TLM in improving the contact stress distributions of cycloid drives. Note that the TLM parameters were arbitrarily selected for the case studies in this paper; the optimization of parameters for the three types of TLM remains as a future task.  
Figure 12 shows the effects of TLM on the LTE and GR of the NNM cycloid gear pairs in a mesh circle. It was observed that the LTE for the four cases varied periodically as the crankshaft rotated with almost the same period, shape, and peak-to-peak value of 3.04 arcseconds, while their mean absolute values were slightly different due to the different types of TLM resulting in different deflection angles. The GR for the four cases showed good agreement in terms of the period, shape, and peak-to-peak value of 0.29, meaning that TLM has a rather negligible influence on the GR of cycloid drives.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Without TLM** & **FCM** & **PCM** & **LCM** \\ \hline - & \(R_{f}=3000\) mm & \(R_{p}=4500\) mm, \(L_{0}=13.6\) mm & \(f=0.005\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Tooth longitudinal modification (TLM) parameters of four cases for the example cycloid gear pair with NNM.  
Figure 11: Contact stress of the NNM cycloid gear pair without TLM and with FCM, PCM, and LCM at a 120\({}^{\circ}\) crankshaft angle, illustrated in 3D representations.
## 3 Sinusoidal Models in Simulation Studies
### Constant Amplitude with Trend  
The constant amplitude model represents a fundamental form of sinusoidal time series, characterized by regular oscillations of a fixed amplitude around a central level:  
\[y_{t}=A\sin(\omega t+f)+C+\beta t+\varepsilon_{t}, \tag{9}\]  
where \(A\) is the amplitude, \(\omega\) is the angular frequency, \(f\) is the phase shift, \(C\) is the central level, \(\beta t\) introduces a linear trend, and \(\varepsilon_{t}\) is a random error component. The inclusion of \(\beta t\) allows the model to capture long-term directional movements, making it applicable to phenomena exhibiting both cyclic behavior and overall growth or decline trends.
# Generating Activity-Based Mobility Plans from Trip-Based Models and Mobility Surveys
## 4 Results and Validation
### General Mobility Behavior
This phenomenon is based on the fact that our model is restricted to the boundaries of the city of Munich, effectively reducing the maximum possible trip distances to approximately 40 km. Nevertheless, the existing deviations remained, on average, below 5 km per car and day. Hence, in addition to realistic activities, the model also delivered reliable traffic benchmarks. Because of their apparent impact on the daily distances and the successful validation of these, our parameter choices for \(v_{\text{avg,Munich}}\) and \(a_{\text{dist}}\) were implicitly validated. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & \multicolumn{2}{c}{**MID**} & \multicolumn{3}{c}{**Simulation**} \\ \hline
**StartEnd** & **Home** & **Elsewhere** & **StartEnd** & **Home** & **Elsewhere** \\ \hline Home & 0.801 & 0.079 & Home & 0.811 & 0.089 \\ Elsewhere & 0.089 & 0.031 & Elsewhere & 0.072 & 0.028 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Share of cars returning to and starting from home at the end of a day when comparing MID and the simulation. Figure 10: Share of partial activity chains. Comparison of simulation and MID. Activity types are abbreviated by their first letters (home = H, work = W, shopping = S, recreational = R, work-related = WR, private business—P, accompanying others = A, education = E, and other = O). Figure 12 serves to elaborate on another aspect of the traffic indicators. It depicts the share of traveled distances per activity type. It is striking that the share of the travel distances associated with work activities within our mobility model was smaller than expected, although the share of working activities was found to be slightly larger than that in the reference survey. This may be due to the fact that the study area was restricted to the city of Munich, resulting in the implicit omission of any commuting for work or work-related activities. As a consequence, the share of the trip distances for all other activity types was marginally overestimated by our model.
# An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications
## 1 Introduction
#### Methods to Measure Glucose  
The main concern of a person with diabetes is to control the blood glucose parameter in order to avoid abnormalities in glucose boundaries. Methods for monitoring these levels are classified into three categories, invasive, minimally invasive, and noninvasive [4] described as follows:  
* The invasive category includes techniques that are mostly used, because it offers the greatest precision of results due to direct contact with the patient's blood. The traditional procedure is to pick a finger, which is painful for the patient. The measurements must be carried out under a rigorous cleaning regimen, since infections can occur [4; 5].
* The minimally invasive category includes one of the techniques under investigation. This technique makes use of micropores, which are small holes on the skin caused by laser radiation. When the pores are open, a device applies a continuous vacuum pressure that extracts a small amount of transdermal body fluid. With the obtained sample, an enzyme-based electrode processes and measures glucose levels.
* The noninvasive category includes noninvasive glucometers in which the objective is to replace the blood variable with another to which access is obtained by external means. Its operation consists of placing a sensor on a specific region of the body to obtain a reading of the glucose. The reliability of the values is almost 100%, because experts have been assured that the amount of glucose in the blood is equal to the amount found on the skin of a patient [4; 5]. Biofluids such as saliva, urine, sweat, or tears have been studied as noninvasive glucose tests, but with these, it is not possible to continuously track the glucose levels.  
It has been proven that continuous glucose monitoring improves metabolic control of the patient and provides a better profile of the glucose variations throughout the entire day. We can avoid critical values with the help of prediction, for example, analyzing the tendency of the levels with intelligent algorithms. Recently, approaches for monitoring patients' glucose parameter have been developed. The proposals make use of noninvasive methods, as well as transmission technology and data processing that provides timely readings. There are areas of opportunity concerning the use of more efficient algorithms for generating appraisals and more effective communication architectures [6; 7; 8].
## 4 Design Consideration and Simulation
### CLC Using PIAP Control Method  
1. At a \(V_{in}\) of 9 V, the HPLD operated the in the boost mode, and a slight current spike with a peak value of 1.25 A was observed. The settling time was 65 ms (simulation was 40 ms), as shown in Figure 16a.
2. At a \(V_{in}\) of 15 V, the HPLD operated in the buck-boost mode, a slight current spike was observed, with a peak of 1.3 A, which was lower than the HPLD maximum operating current of 1.5 A. The settling time was 100 ms, as shown in Figure 16b.
3. At a \(V_{in}\) of 16 V, the HPLD operated in the buck mode, and a slight current spike with a peak of 1.3 A was observed. This peak value was also lower than 1.5 A. The settling time was 80 ms (simulation was 80 ms), as shown in Figure 16c.  
Therefore, the start-up current spike could be mitigated, and the current settling time could be obviously reduced, when the CLC used the PIAP control technology.  
Figure 16: _Cont._A photograph of the HPLDDC system is presented in Figure 17, including three HPLDs' heat sinks, three heat-sink struts, a lead-acid battery, and a print circuit board assembly of the HPLDDC. The lead-acid battery could supply to the HPLDDC to drive HPLDs, and then laser blue beams were produced.
## 2 System Model  
Consider a system composed of a WLAN Access Point (AP) and a finite number of Mobile Stations (MSs), as depicted in Figure 1. Data packets arrive at the AP and need to be transmitted to their designated MS. The AP has multiple antennas, whereas each MS has a single antenna (multi-user MIMO). This problem is a variant of the well-known broadcast channel problem. The AP needs to transmit the packets to the MS. The arriving packets have both priority and deadlines. The system is defined to be a hard real-time system; i.e., packets that miss their deadline do not earn their priority as rewards. The goal is to maximize the sum of the rewards over the complete system.  
Figure 1: System.
## 2 Experimental Investigation of Column
### Axial Compression Test Results and Discussions
#### 2.4.3 Load-Displacement Curves  
The typical load-displacement curves of all samples are shown in Figure 9. The vertical axis denotes the axial force (\(P\)) and the horizontal axis denotes the vertical displacement (\(\Delta_{\rm v}\)). The ultimate bearing capacity (\(P_{\rm u}\)) under compression is presented in Table 1. As shown in Figures 7a and 9c, it can be concluded that with the increasing \(D\), both the \(P_{\rm u}\) and the vertical displacement corresponding to \(P_{\rm u}\) increase, whereas the influence of \(H\) on the \(P\)-\(\Delta_{\rm v}\) curves decreases significantly. Similar results may be obtained, as shown in Figure 9b,d. It may be observed that the capacity to resist impact is improved by a large \(D\), and thus, the residual bearing capacity after transverse impact cannot be significantly influenced by the drop hammer height.  
Comparing Figure 9a,b, it can be noted that with the increasing \(t\), both the \(P_{\rm u}\) and the initial slope of the \(P\)-\(\Delta_{\rm v}\) curve increase, while the vertical displacement corresponding to \(P_{\rm u}\) decreases. Similar results may be obtained, as shown in Figure 9c,d. It may be due to the fact that the capacity to resist deformation of CFCSTC can be improved by increasing the \(t\). However the difference resulting from the \(t\) is not more evident than that of the \(D\), which may be due to the fact that the effect of \(t\) on the behavior of CFCSTC is less than that of \(D\).