esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Conclusions
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Ref.** & **Antenna (Freq.)** & \
\begin{tabular}{c} **Circuit** \\ **(Freq.)** \\ \end{tabular} &
\begin{tabular}{c} **Circuit Efficiency** \\ **(Input Power)** \\ \end{tabular} & **Sensor Testing** \\ \hline
[5] & \begin{tabular}{c} Array of Log. Spiral \\ (2–18 GHz) \\ \end{tabular} & \
\begin{tabular}{c} Half-Wave \\ Rectifier \\ (-) \\ \end{tabular} &
\begin{tabular}{c} 20\% \\ (4 dBm) \\ \end{tabular} & NO \\ \hline
[8] & Linear Tapered Slot Antenna (1.85/2.4 GHz) & Differential Rectifier & 13\% \\ \hline
[13] & \begin{tabular}{c} Concentric Square Patches \\ (2.4/5.5 GHz) \\ \end{tabular} & \
\begin{tabular}{c} Full-Wave \\ Rectifier \\ (2.4/5.5 GHz) \\ \end{tabular} &
\begin{tabular}{c} 36\% @2.4 GHz \\ 5\% @5.5 GHz \\ (0 dBm) \\ \end{tabular} & NO \\ \hline
[14] & \begin{tabular}{c} Slotted Patch Antenna \\ (2.45 GHz) \\ \end{tabular} & \
\begin{tabular}{c} Half-Wave \\ Cockcroft-Walton \\ (2.45 GHz) \\ \end{tabular} &
\begin{tabular}{c} 68\% \\ (5 dBm) \\ \end{tabular} & NO \\ \hline
[31] & \begin{tabular}{c} Meander Antenna \\ (434 MHz) \\ \end{tabular} & \
\begin{tabular}{c} Voltage Doubler \\ (434 MHz) \\ \end{tabular} &
\begin{tabular}{c} 20\% \\ (–30 dBm) \\ \end{tabular} & NO \\ \hline
**This Work** & \begin{tabular}{c} Arch. spiral \\ (0.3–16 GHz) \\ \end{tabular} & \
\begin{tabular}{c} Half-Wave \\ Cockcroft-Walton \\ (800/900 MHz) \\ \end{tabular} &
\begin{tabular}{c} 30\% \\ (0 dBm) \\ \end{tabular} & Temperature \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison among different RF energy harvesting systems.
_Algorithms_**2012**, \(5\), 304-317; doi:10.3390/a5020304  
_Algorithms_  
**ISSN 1999-4893**  
www.mdpi.com/journal/algorithms  
An Agent-Based Fuzzy Collaborative Intelligence Approach for Predicting the Price of a Dynamic Random Access Memory (DRAM) Product  
**[PERSON]**  
Department of Industrial Engineering and Systems Management, Feng Chia University,  
Taichung City, 407 Taiwan; E-Mail: [EMAIL_ADDRESS]; Tel.: 886-4-24527150;  
Fax: 886-4-24510240  
_Received: 9 April 2012; in revised form: 7 May 2012 / Accepted: 9 May 2012 / Published: 24 May 2012_  
**Abstract:** Predicting the price of a dynamic random access memory (DRAM) product is a critical task to the manufacturer. However, it is not easy to contend with the uncertainty of the price. In order to effectively predict the price of a DRAM product, an agent-based fuzzy collaborative intelligence approach is proposed in this study. In the agent-based fuzzy collaborative intelligence approach, each agent uses a fuzzy neural network to predict the DRAM price based on its view. The agent then communicates its view and forecasting results to other agents with the aid of an automatic collaboration mechanism. According to the experimental results, the overall performance was improved through the agents' collaboration.  
**Keywords:** fuzzy collaborative intelligence; dynamic random access memory; prediction; agent; price
## 7 Simulation Results and Analysis
### Service Request SR on Two Network Topologies
#### 7.2.3 Service Request SR of the RAWC Scheme under Different Scenarios  
In the service request model of this paper, there may be one or more services arriving at each moment. Multiple requests arriving at one moment may lead to wavelength conflicts. To test the ability of the RAWC algorithm to solve the wavelength conflict problem, we set up two scenarios: 1 Scenario 1: there are four moments with multiple service requests arriving at the same time; 2 Scenario 2: there are eight moments with multiple service requests arriving at the same time. As a comparison, both the benchmark algorithm and the RAWC algorithm were applied to these two scenarios, where the benchmark algorithm is RA and no competition for wavelength resources is considered. Figures 9 and 10 demonstrate the results of the two algorithms on the six-node network topology and the NSFNET topology, respectively. The vertical coordinates on the right side indicate the percentage improvement in the RAWC algorithm in SR compared with the benchmark scheme under  
Figure 7: SR of the three schemes. (**a**) Six-node network topology; (**b**) NSFNET topology.  
each scenario. As shown in Figure 9a,b, the RAWC algorithm (cyan line in Figure 9a and black line in Figure 9b) has a higher SR than the benchmark algorithm (yellow line in all Figures) under both scenario 1 and scenario 2. In addition, the RAWC algorithm under scenario 2 has a higher improvement over the benchmark algorithm for the same traffic load compared to scenario 1. Under scenario 1, the improvement rate is up to 6% at a traffic load of 140 Erlang; under scenario 2, the improvement rate is up to 13% at a traffic load of 100 Erlang. The reason is that there is a higher number of multiple services under scenario 2, and the RAWC algorithm can better avoid the path with more wavelength conflicts to meet the transmission requirements of more services than the benchmark algorithm. Figure 10a,b show the comparison results of the two schemes on NSFNET under scenario 1 and scenario 2, respectively. It should be noted that the simulation results on NSFNET topology are similar to the six-node network topology, except for some differences in performance improvement. On NSFNET topology, the maximum SR improvement in the RAWC scheme is no more than 10%, which is related to the network topology itself. To summarize, for the problem of multi-service request arrival, we can effectively improve the network performance by considering wavelength conflicts in the dynamic routing scheme.  
Figure 8: SR of the RAWC algorithm in different cases (case 1: \(\lambda_{ini}=20,K_{ini}=80\); case 2: \(\lambda_{ini}=30\), \(K_{ini}=90\); case 3: \(\lambda_{ini}=40,K_{ini}=100\)). (**a**) Six-node network topology; (**b**) NSFNET topology.  
Figure 9: SR of the RAWC algorithm under different scenarios on the six-node network topology. (**a**) Scenario 1; (**b**) Scenario 2.
# A Method for Generation of a Sizing System and Representative Models for a Facial Mask Design
## 2 Development of a Sizing System of a Pilot Oxygen Mask for KAF Pilots
### Development of an Oxygen Mask Sizing System for KAF Pilots  
The present study developed a new sizing system of oxygen masks for KAF pilots by the following approach. First, an initial sizing system was generated through a grid formation method proposed by [PERSON], [PERSON] and [PERSON] [19]. The initial sizing system consisted of six sizing categories generated based on predefined constraints: (1) a size interval of 10 mm for the key dimensions SSL and LW, (2) an accommodation percentage of 95%, and (3) a minimum presence percentage of 5% for a sizing category. The 10 mm sizing interval for SSL and LW (smaller than 13 mm for SSL and 15 mm for LW in the existing mask) was determined by considering the variations of SSL (range: 80.7 mm-114.1 mm) and LW (range: 38.5 mm-58.2 mm) of KAF pilots. Additionally, the interval of 10 mm was set as its ease-of-read and rememberability compared to the existing sizing system of the MBU-20/P. A sizing system having six sizing categories (Figure 3a) was formed automatically by the distributed representative human model generation and analysis system (DRHM-GAS) proposed by [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] [4]. The DRHM-GAS automatically formed the initial sizing system by inputting the sizing interval (10 mm in this case) and the number of sizing categories (6 categories in this case). The initial sizing system with 98% of accommodation percentage was generated with the sizing criteria of 82, 92, 102, and 112 mm in SSL and 39, 49, and 59 mm in LW. Then, the sizing criteria were adjusted to 80, 90, 100, and 110 mm in SSL and 40, 50, and 60 mm in LW, as shown in Figure 3b to provide an easy perception of size cut-off values. The adjusted sizing system showed 99% of the accommodation percentage.  
Figure 3: Generation of a revised oxygen mask sizing system for KAF pilots. (**a**) initial sizing system (accommodation percentage = 98%); (**b**) adjusted sizing system (accommodation percentage = 99%).
## 2 Model and Simulation Structure
### Simulation Model  
The simulation model consists of the main system and the optimization tool. By using the monitoring and the control system of the microgrid, the system parameters can be retrieved and new values of those parameters may be sent back to the original system. The research infrastructure's SCADA system monitors all analog data and converts them into digital signals by the measurement equipment. All the data managed by the SCADA (input data and set points) are stored in a REDIS database and can be accessed (as input or output) by Matlab applications using dedicated REDIS interface.  
The experiment(s) and the simulation(s) are performed by using a coordinated approach as given in Figure 1. From the figure, it is obvious that after an experiment is performed, several system parameters such as power flows, voltage magnitudes, phase angles can be transferred as parameters to the optimization tool. Harmony search based optimization tool then finds the optimal parameters to minimize the voltage deviations in the system and those parameters are then passed to the experimented system and the new parameter values are set.
# Reliability Modeling and Analysis of Multi-Degradation of Momentum Wheel Based on Copula Function
## 3 Establishing a Degenerate Model  
### Modeling Ideas  
Let \(X(t)\) denote the amount of degradation of the long-lived product. The growth law of product degradation can be represented by the average function \(E[X(t)]\) of the degradation amount. Due to changes in the environment and individual characteristics, the actual degradation process and growth law of the product is a random process. The process is well described by the Wiener process. If \(X(t)\) is satisfied:  
\[X(t)=\mu t+\sigma B(t) \tag{1}\]  
where \(\mu\) is the drift coefficient, \(\sigma\) is the diffusion coefficient, and \(B(t)\) is the Brownian motion, then the product degradation process obeys the linear drift Wiener process. At this point, \(X(t)\) satisfies the following properties:  
1. The incremental amount of degradation at any time obeys the normal distribution, that is \(\Delta X=X(t+\Delta t)-X(t)\sim N\big{(}\mu\Delta t,\sigma^{2}\Delta t\big{)}\)2. The increments in any two disjoint periods are independent of each other. The corresponding mathematical description is as follows: for any \(0<t_{1}<t_{2}<\ldots<t_{n}\), then \(X(t_{1})-X(t_{0}),X(t_{2})-X(t_{1}),\ldots,X(t_{n})-X(t_{n-1})\) are independent;
3. \(X(0)=0\), and \(X(0)\) is continuous at \(t=0\).
###### Abstract  
Membrane-assisted crystallization, aiming to induce supersaturation in a solution, has been successfully tested in the crystallization of ionic salts, low molecular organic acids, and proteins. Membrane crystallization is an emerging membrane process with the capability to simultaneously extract fresh water and valuable components from various streams. Successful application of crystallization for produced water treatment, seawater desalination, and salt recovery has been demonstrated. Recently, membrane crystallization has been developed to recover valuable minerals from highly concentrated solutions, since the recovery of high-quality minerals is expected to impact agriculture, pharmaceuticals, and household activities. In this work, molecular dynamics simulations were used to study the crystal nucleation and growth of sodium chloride in bulk and with hydrophobic polymer surfaces of polyvinylidene fluoride (PVDF) and polypropylene (PP) at a supersaturated concentration of salt. In parallel, membrane crystallization experiments were performed utilizing the same polymeric membranes in order to compare the experimental results with the computational ones. Moreover, the comparison in terms of nucleation time between the crystallization of sodium chloride (NaCl) using the traditional evaporation process and the membrane-assisted crystallization process was performed. Here, with an integrated experimental-computational approach, we demonstrate that the PVDF and PP membranes assist the crystal growth for NaCl, speeding up crystal nucleation in comparison to the bulk solution and leading to smaller and regularly structured face-centered cubic lattice NaCl crystals. This results in a mutual validation between theoretical data and experimental findings and provides the stimuli to investigate other mono and bivalent crystals with a new class of materials in advanced membrane separations.  
molecular simulation; computational chemistry; membrane-assisted crystallization; crystal growth; nucleation 2018 8 2145; doi:10.3390/app8112145
## 2 Materials and Methods
### Methods
#### 2.3.3 Land Productivity Assessment Based on Trends.Earth for SDG Indicator 15.3.1  
SDG indicator 15.3.1 uses information from three sub-indicators: land productivity, land cover, and soil organic carbon, according to the conceptual framework for monitoring LDN released by UNCCD. The Trends.Earth plugin ([[http://trends.earth](http://trends.earth)]([http://trends.earth](http://trends.earth)), accessed on 25 May 2021) can be used to calculate the above sub-indicators. Trends.Earth allows the user to calculate each sub-indicator in a spatially explicit manner, generating raster maps that are later integrated into the final SDG 15.3.1 indicator maps [60]. The output is a tabular report that shows potential areas for improvement and degradation. In Trends.Earth, land productivity is calculated using annual average NDVI from MODIS or AVHRR data. Three measures of change derived from NDVI timeseries data are used to estimate land productivity, including trajectory, state, and performance.  
1. Trajectory--measures the rate of change in land productivity over time. Trends.Earth uses pixel-level linear regressions to identify areas where land productivity has changed during the analysis period. Mann-Kendall non-parametric tests are then performed, considering only those significant changes with a \(p\)-value \(\leq\) 0.05. Positive significant trends in NDVI indicate potential improvement, while negative significant trends suggest potential degradation.
2. State--detects the most recent changes in land productivity compared with the baseline period. The baseline period is considered as the historical period, while the comparison period is defined as the most recent years. Then, the average NDVI is calculated for the baseline and comparison periods. The percentile class to which it belongs is determined, with possible values ranging from 1 (lowest class) to 10 (highest class). If the difference in class between the baseline period and the comparison period is less than 2, the pixel may be degraded; if the difference is greater than 2, the pixel may have a recent improvement in productivity; if there is only a small change, the pixel is considered stable.
3. Performance--measures local productivity compared with similar land cover types across the study area. If the observed average NDVI is less than 50% of the maximum productivity, this sub-indicator considers the pixel to be potentially degraded. The maximum productivity is at the 90 th percentile of the frequency distribution of NDVI.  
In addition, the three sub-indicators of land productivity are merged to determine the integrated degradation type of land productivity occurring in the area, according to the rules shown in the table below (Table 2). The result is a 5-level indication supporting the assessment of SDG 15.3.1.
# Occluded Pedestrian Detection Techniques by Deformable Attention-Guided Network (DAGN)
## 4 Experimental Results
### Caltech Pedestrian Dataset  
The Caltech pedestrian dataset is one of the most popular and large-scale datasets for the pedestrian detection task. It includes six train sets and five test sets in a sequence video format. In our experiment, we used the new annotations provided by [41] for training and testing. In total, 42,782 images are used for training and 4024 images for testing with the size of 480 \(\times\) 640 pixels.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Dataset** & **Case** & **Height of Pedestrian (pixels)** & **Occlusion Area** & **Visibility** \\ \hline \multirow{3}{*}{Caltech [8]} & Reasonable & \textgreater{}50 & \textless{}35\% & \textgreater{}0.65 \\ \cline{2-5}  & Heavy occlusion & \textgreater{}50 & 35–80\% & 0.2–0.65 \\ \cline{2-5}  & All & \textgreater{}20 & - & \textgreater{}0.2 \\ \hline \multirow{3}{*}{CityPersons [9]} & Reasonable & \textgreater{}50 & - & \textgreater{}0.65 \\ \cline{2-5}  & Heavy occlusion & \textgreater{}50 & - & \textgreater{}0.9 \\ \cline{2-5}  & Partial occlusion & \textgreater{}50 & - & 0.65–0.9 \\ \cline{2-5}  & Bare & \textgreater{}50 & - & \textless{}0.65 \\ \cline{2-5}  & Small & 50–75 & - & \textgreater{}0.65 \\ \cline{2-5}  & Medium & 75–100 & - & \textgreater{}0.65 \\ \cline{2-5}  & Large scale & \textgreater{}100 & - & \textgreater{}0.65 \\ \hline \multirow{3}{*}{EuroCity Persons [14]} & Reasonable & \textgreater{}40 & \textless{}40\% & - \\ \cline{2-5}  & Small & 30–60 & \textless{}40\% & - \\ \cline{1-1} \cline{2-5}  & Occluded & \textgreater{}40 & 40–80\% & - \\ \cline{1-1} \cline{2-5}  & All & \textgreater{}30 & - & - \\ \hline \hline \end{tabular}  
* The range of occlusion area and visibility is from 0 to 1.  
\end{table}
Table 1: Benchmark datasets used for pedestrian detection.
## 2 Materials and Methods
### MRR Improvement  
The equipment used in this study is obtained through the transformation of DK7720 fast wire EDM wire-cutting machine, mainly replacing the molybdenum wire used in the EDM wire-cutting machine with a diamond wire saw, and adding the discharge circuit and electrolyte supply device to the machine. The movement of the diamond wire is driven by a rotating roller, and the workpiece is fixed on a slider mounted on the guide rail. The slider is pulled by the counterweight and moves forward as the working material is removed. In this feed mode, the workpiece is only moved forward when the working material is removed. The feed rate of the workpiece is not a process parameter, but a result of the material removal of the workpiece [29].  
Experiments were conducted to analyze the MRR of Al2O3 ceramic by diamond wire sawing with and without the assistance of oil film-assisted ECDM. The characteristics of the Al2O3 ceramic are shown in Table 1. The guide rail oil with properties shown in Table 2 was used to online form an oil film on the diamond wire. The experimental conditions are shown in Table 3. An NaCl solution with a mass fraction of 20% was chosen as the electrolyte because of its non-corrosive and good electrical conductivity properties, and the velocity of spraying NaCl solution was 0.583 m/s. Figure 5 shows the experimental picture of cutting Al2O3 ceramic by diamond wire sawing combined with oil film-assisted ECDM. It can be seen that spark discharges were generated around the diamond wire (Figure 5a), and a cutting slit was produced (Figure 5b). Figure 6 shows that the diamond wire sawing combined with oil film-assisted ECDM increased MRR by 0.46 mm\({}^{3}\)/min or 36%. MRR is approximated by the formula: MRR = slit length \(\times\) slit width \(\times\) workpiece thickness/processing time, where slit length is measured by a microscope, and slit width is approximately the diameter of a wire saw.
## 4 Simulation Results
### Simulation Results
Unlike the 6-repetitions case, Scheme 2 with three repetitions shows apparently better performance than the packet train method over the entire nodes except at the abnormal 10 th node. Figure 13: Transmit power of each node when the node is on the transmission state. From Figure 14, it can be expected that if the abnormality caused by a heavy load cumulated at high-indexed nodes is removed, the superiority of Scheme 2 over the packet train method becomes clearer. Therefore, an attempt is made to reduce the network size, \(L\), _i.e._, the number of nodes except the sink, to determine how much power saving gain can be achieved in smaller networks. Figure 15 shows the average value of the time-averaged power obtained in Figure 14 over all nodes from the 1 st to the \(L\)th node. The power saving of Scheme 2 appears clear, particularly in the case of three repetitions. Figure 16 shows the signal to noise power ratio of Scheme 2 received at 100 m from the transmitter, comparing analysis and simulation results. Because the repetition is not modeled in the analysis, the equivalent data rate for the analysis is calculated. The equivalent \(Cw_{\  
Figure 14: Time-averaged transmit power of each node. Figure 15: Average transmit power over the network depending on the number of nodes or the network size. 0.015 (= (120 symbols) \(\times\) (2 bits/symbol)/(10 accumulations)/(6 repetitions)/_Tf/f\({}_{BW}\)\(\times\)_ 50%) and 0.03 for six and three repetitions, respectively. The disagreement by almost 10-fold between the simulation and analysis is because the simulation is performed under much severer conditions, such as real channels with a delay spread, the inclusion of all interference, the absence of channel coding, and the use of guard time. On the other hand, the shapes of the curves agree well enough to support that the mathematical analysis in this paper based on a simple network topology is still useful in more realistic scenarios with different parameters.
# In Vitro Antibacterialential Activity of Marine Microalgae Extract against _Vibrio harveyi_  
[PERSON]  
1 Borneo Marine Research Institute, Universit Malaysia Sabah, Kota Kinabalu 88400, Sabah, Malaysia; [EMAIL_ADDRESS](M.R.J.); [EMAIL_ADDRESS](S.R.M.S.); cf  
non-biodegradable, highly biomagnified, and antibiotic resistance has grown [7]. Antibiotic overuse can result in various environmental problems, including contamination of the culture environment, organism harm, and the development of bacterial resistance that can extend to the food chain [8]. Alternatively, numerous techniques for controlling pathogenic vivbiosis have been proposed, including phage therapy, short-chain fatty acid inhibition of bacterial growth, quorum-sensing disruption, probiotics, immunostimulants, vaccinations, and green water [9].  
Pathogen management in aquaculture, particularly disease prevention employing herbs and phytochemicals, has garnered a considerable amount of attention in the previous decade [10]. Furthermore, microalgae can produce a variety of bioactive compounds such as carotenoids, polysaccharides, vitamins, and lipids [11]. Recently, microalgae have been frequently utilised in aquaculture as nutritional supplements, immunostimulants to strengthen immune systems, and to increase disease resistance against harmful bacteria [2]. Furthermore, they contain antibacterial and antiviral properties that could be exploited for disease prevention and management in the aquaculture industry [11]. Thus, because the habitat is in a trapped and limited area, such as in fish-rearing tanks or cage culture, the transmission of numerous viral, fungal, parasitic, and bacterial diseases easily occurs among cultured fish, which can further cause co-infections and mortality in cultured fish [12; 13]. It has been found that adding microalgae to farmed fish reduces the bacterial load of larval rearing systems by reducing the number of opportunistic bacteria [14].  
Furthermore, the growing desire for more ecologically friendly disease control strategies has prompted academics to investigate alternate ways with little negative effects. Thus, the primary goal of this work was to investigate the antibacterial activity effects of several marine microalgae cultures, including _Nannochloropsis oceanica_, _Chaetoceros gracilis_, _Isochrysis_ sp. and _Thalassioira westisflogii_, against _V. harveyi_ at different cell viability levels.