esa-sceva/satcom-chunk-collection huggingface dataset:
## Preliminaries
### Bilinear Pairing  
Denote \(G_{1}\) and \(G_{2}\) as two multiplicative groups with the prime order \(q\). \(g\) is a generator of group \(G_{1}\). A function \(\mathrm{e}:G_{1}\times G_{1}\to G_{2}\) is called a bilinear pairing [12] if it has the following properties:  
* Bilinearity: For all \(u,v\in G_{1}\). and \(a,b\in Z_{q}\), \(e(u^{a},v^{b})=e(u,v)^{ab}\) holds.
* Non-Degeneracy: \(e(g,g)\
eq 1_{G_{2}}\), in which \(1_{G_{2}}\) is the identity of \(G_{2}\).
* Efficient Computation: \(e(u,v)\) can be computed efficiently for all. \(u,v\in G_{1}\).
# Semantic 3D Mapping from Deep Image Segmentation
## 1 Introduction
For example, a robot could use this information to self-locate in its environment, improving accuracy or resetting its position in the case of local (tracking) location algorithms. Or it could also be used to command the robot to move close to a previously detected object instead of a specific metric position. In summary, this paper has two main contributions:  
* Two novel algorithms to calculate the space occupied by elements detected from deep image segmentation. * Their application to the semantic mapping problem, which is used to validate its performance. The rest of the paper is organized as follows: In Section 2, we introduce relevant works related to our approach. Then, in Section 3, we describe our work in 3D segmentation, which is later used in Section 3.2 to map the environment with semantic information. We validate our approach in Section 4, and finally, after presenting some limitation in Section 5, we provide the conclusions in Section 6.
## 6 Results
### Discussion of the Results from Section 6.2  
The results for the traffic characterization are similar to those for the PDU. The generated traffic is again minimal, with no traffic at times when the UPS is not accessed. Everything discussed for the studied PDU also applies to the studied UPS.  
Here again it was found that the data exchange is not secure. All important information is transmitted in plain text, including the user information, the measured parameter values, and the UPS shutdown commands. The UPS can very easily be hacked, or to say much more \"culturally\", the UPS can be manipulated remotely by others to sabotage the operation of devices that are powered by it, or just for fun. This is also true for the PDU under study. The potential consequences of cyber-attacks over the studied UPS are the same, similar to the ones discussed in the above section (for the PDU).  
To secure the data exchange between the UPS and the control center, again it is proposed to use VPN technology as the easiest to implement. Again, the data is encrypted, and the UPS is hidden.
# Surface Plasmon Resonance-Based Fiber Optic Sensors Utilizing Molecular Imprinting
## 5 Molecular Imprinting
### Applications of Molecular Imprinting  
As discussed in the Introduction section, MIP has high specificity towards the template and it can be applied in harsh conditions like high pH, temperature, etc. Due to its interesting advantageous features, this technique is applied in number of applications such as solid phase extraction (SPE) [120; 121; 122], chiral discrimination [123], binding assays [124; 125; 126] and sensing [127; 128; 129]. Since the present review is based on MIP and fiber optic SPR sensors, here we shall discuss the sensing applications of this combined phenomenon and technology.  
MIT for Chemical/Biological Sensing  
The application of MIPs for the sensing element has been introduced by [PERSON] and co-workers for the detection of vitamin K\({}_{1}\) using a surface imprinted silicon substrate by means of optical detection. After this study, an era of sensing based on MIPs started due to the several beneficial factors like high selectivity and stability, simple and cheap fabrication process and the versatility in many areas such as environmental control, bio-medical diagnostics, drug screening and food analysis. Because of the complementary shape and size of the imprinted sites as that of the template to be detected, the MIPs show high specificity properties which are an essential parameter of a reliable sensing method. This is the reason why a number of sensing schemes based on electrochemical [130; 131; 132], fluorescence [133; 134; 135], chemiluminescence [136; 137; 138], colorimetric/UV-Vis spectroscopy [139; 140; 141], surface plasmon resonance (SPR) [142; 143; 144], surface enhanced Raman scattering (SERS) [145; 146; 147] have been published using molecular imprinting technique. Among these, SPR has been developed as a broadly used detection scheme due to its properties of speed, highly sensitive detection and label-free sensing abilities [32; 36; 39; 58]. The SPR sensing fiber optic configuration boosts sensing with factors of simple instrumentation, cost effectiveness, immunity to electromagnetic interference and the ability of performing online and remote sensing applications [1; 3; 29; 50]. Hence, in the next section the sensing mechanism and various sensors reported in the literature using fiber optic SPR and MIT are discussed.
## Waveguiding Light into Silicon Oxycarbide  
**[PERSON] 1,2,*, [PERSON] 1 and [PERSON] 1**  
1 Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, via [PERSON] 34/5, 20133 Milan, Italy; [EMAIL_ADDRESS] (F.M.); [EMAIL_ADDRESS] (A.M.)  
2 Department of Telecommunications Engineering, Mehran University of Engineering & Technology, Jamshoro 76062, Sindh, Pakistan  
*Correspondence: [EMAIL_ADDRESS] or [EMAIL_ADDRESS]; Tel.: +39-2-2399-8978  
Received: 1 May 2017; Accepted: 25 May 2017; Published: 30 May 2017  
**Featured Application: Silicon oxycarbide is demonstrated to be a potential photonic platform for integrated optics applications.**  
**Abstract:** In this work, we demonstrate the fabrication of single mode optical waveguides in silicon oxycarbide (SiOC) with a high refractive index n = 1.578 on silica (SiO\({}_{2}\)), exhibiting an index contrast of \(\Delta\)n = 8.2%. Silicon oxycarbide layers were deposited by reactive RF magnetron sputtering of a SiC target in a controlled process of argon and oxygen gases. The optical properties of SiOC film were measured with spectroscopic ellipsometry in the near-infrared range and the acquired refractive indices of the film exhibit anisotropy on the order of 10\({}^{-2}\). The structure of the SiOC films is investigated with atomic force microscopy (AFM) and scanning electron microscopy (SEM). The channel waveguides in SiOC are buried in SiO\({}_{2}\) (n = 1.444) and defined with UV photolithography and reactive ion etching techniques. Propagation losses of about 4 dB/cm for both TE and TM polarizations at telecommunication wavelength 1550 nm are estimated with cut-back technique. Results indicate the potential of silicon oxycarbide for guided wave applications.  
**Keywords:** silicon oxycarbide; optical waveguides; optical materials; guided waves; integrated optics
# Energy Storage Overflow-Aware Data Delivery Scheme for Energy Harvesting Wireless Sensor Networks
## 3 ESO-Aware Data Delivering Scheme  
In this section, we present the ESO-aware multiple paths (EAMP) data delivery scheme, which uses multiple disjointed paths. In the following, we use the terms \"path\" and \"route\" interchangeably.  
First, we present an example to show the main idea underlying the proposed EAMP.
## 2 Materials and Methods
### Measurements  
#### 2.4.1 Physiological Parameters  
Body mass was assessed using a calibrated weighing scale, with an accuracy of \(\pm\)0.1 kg, and height was measured using a stadiometer, with an accuracy of \(\pm\)0.5 cm. The waistand hip circumferences were assessed using a non-elastic flexible measuring tape, with an accuracy of \(\pm\)0.5 cm. All the measurements were conducted by a qualified dietitian. Based on the conducted measurements, BMI [40] and waist-to-hip ratio (WHR) [41] were obtained.  
Body composition was assessed using a bioelectrical impedance measurement conducted with a frequency of 50 kHz by a BIA 101/SC device (Akern SrI, Firenze, Italy). The measurement was conducted by a qualified dietitian using a commonly applied methodology and procedure--after a day characterized by a typical diet, without any alcohol, coffee or other caffeine beverages and moderate physical activity, in a fasting state [42].  
Diet was assessed using the method of a 3-day dietary record as recommended by the Food and Agriculture Organization of the United Nations (FAO) [43]. The serving sizes were allowed to be either weighted or recorded in household measures to provide accurate assessment of the intake. Based on the recorded intake, the energy value of the diet and nutrient intake were calculated using a Polish table of the nutritional value of foods [44] and Polish software--Energia 4.1 (1997/2006 by [PERSON], Warsaw, Poland). The daily intake was compared with the Polish recommendations on the estimated average requirement (EAR) or adequate intake (AI) level, depending on the nutrient [45].  
As an additional element of dietary assessment, the diet quality indices were calculated. The atherogenic index of Keys was calculated based on the intake of saturated fatty acids (SFA), polyunsaturated fatty acids (PUFA) and cholesterol, according to the following formula: the atherogenic index of Keys = 1.35 \(\times\) (2 \(\times\) %SFA \(-\) %PUFA) + 1.5 \(\times\) \(\surd\)(Cholesterol/1000 kcal), while: %SFA and %PUFA present % of energy value from indicated fatty acids, and cholesterol expressed in mg [46].  
Physical activity was monitored using a SenseWear Armband Pro3 (SenseWear, Body-Media, Pittsburgh, PA, USA), which is a monitor of energy expenditure, physical activity level and number of steps, as well as time spent while moving. The measurement was conducted for 3 consecutive days while the monitor was placed on the upper dominant arm.
## 2 Simulation Method of Three-Dimensional DFN Based on Monte-Carlo Technique
### Construction of Probability Models for Geological Parameters of Rock Fractures
#### 2.1.3 Model of Fracture Density  
Fracture density is an important index to measure the degree of development of a fracture, and is generally divided into three types, linear density, surface density and bulk density. [PERSON] [27] derived the relationship between bulk density and linear density using a fracture tensor under the assumption that the distribution of orientation of the disk fracture and its diameter are independent of each other. [PERSON] and [PERSON] [28] established a correlation between bulk density and surface density based on the relationship between traces within sample windows and the windows themselves. However, due to the complexity of the calculation process, this method is rarely used.  
[PERSON] et al. [29] found that the bulk density of a fracture is relatively constant in a relatively statistically homogeneous region, independent of its orientation, and is related to the linear density as follows:  
\[\lambda_{v}=\frac{\lambda_{d}}{2\pi\int_{0}^{\infty}R\int_{R}^{\infty}f(r)drdR} \tag{5}\]  
where \(\lambda_{v}\) is the bulk density of the fracture; \(\lambda_{d}\) is their linear density, and \(f(r)\) is the distribution function of the probability density of the radius of the disk.  
Substituting the probability density function of the radius of the disk that satisfies the negative exponential distribution and Equation (2) into Equation (5) yields the following:  
\[\lambda_{v}=\frac{\overline{\lambda_{d}}}{2\pi\lambda^{2}}=\frac{32\overline{ \lambda_{d}}}{\pi^{3}\overline{l}^{2}} \tag{6}\]  
In addition, we assume that the bulk density of the fracture is independent of its shape. Thus, rectangular fractures can be assumed to have approximately the same bulk density as disk fractures in a relatively statistically homogeneous region. Therefore, the number of rectangular fractures in a given study area can be expressed as follows:  
\[N=V\lambda_{v} \tag{7}\]  
where \(N\) is the number of rectangular fractures contained in the area, \(V\) is the volume of the rock mass in the study area, and \(\lambda_{v}\) is the bulk density of fractures.  
The number of fractures in each group in the study area can be calculated by repeating the above process several times.
# Naturally Occurring Flavonoids and Isoflavonoids and Their Microbial Transformation: A Review
## 2 Isoflavonoids and Flavonoids from Actinomycetes and Fungi
### Flavonoids
#### 2.2.3 Complex Flavonoids  
Two new lavandulylated flavonoids, 6-lavandulyl-7-methoxy-5,2',4'-trihydroxylflavanone (**75**) and 5'-lavandulyl-4'-methoxy-2,4,2',6'-tetrahydroxylchalcone (**76**) were isolated from the sponge-derived actinomycete _Streptomyces_ sp. G246. Compounds **75** and **76** showed a broad spectrum of antimicrobial activity. Compound **76** showed excellent inhibitory effects on _C. albicans_, _S. aureus_, _Bacillus cereus_, _Enterococcus faecalis_, _Salmonella enterica_, and _Pseudomonas aeruginosa_, but no inhibitory effect on _Escherichia coli_. [60].  
Three new lavandulylated flavonoids, (2S,2\"S)-6-lavandulyl-7,4'-dimethoxy-5,2'-dihydroxylflavanone (**77**), (2S,2\"S)-6-lavandulyl-5,7,2',4'-tetrahydroxylflavanone (**78**) and (2\"S)-5'-lavandulyl-2'-methoxy-2,4,4',6'-tetrahydroxylchalcone (**79**), together with two known compounds, (2S,2\"S)-6-lavandulyl-7-methoxy-5,2',4'-trihydroxyl-flavanone (**80**) and 6-phenyl-4'-methoxy-5,7-dihydroxylflavanone (**81**), were isolated from the fermentation broth of _Streptomyces_ sp. G248. Compounds **77-79** showed remarkable antimicrobial activity, and compounds **80** and **81** were found to inhibit _Mycobacterium tuberculosis_ H37 Rv with the MIC values of 6.0 and 11.1 ug/mL [61]. A strain of _Penicillium griseroseum_ was isolated from _Coffee arabica_ seeds, and its metabolites were studied in 5,7,3',4',5'-pentamethoxyflavanone supplemented medium to obtain bezylated flavanone (**82**) [62].
# Bricks Using Clay Mixed with Powder and Ashes from Lignocellulosic Biomass: A Review
## Composition of Lignocellulosic Biomass and Clays Properties  
### Structure and Texture of Lignocellulosic Biomass  
According to the European Directive 2003/30/EC, biomass is all types of biodegradable products/by-products from forestry residues, woody processing industries, agriculture (animal and plant residues) as well as municipal and industrial waste (food industries), allowed for energy use in accordance with environmental protection regulations [13]. Hence, biomass can be classified into four types: Forestry waste, Agricultural waste, Aquatic residues, and other origins. The waste of agricultural origin and forestry are classified as lignocellulosic biomasses. Lignocellulosic biomass is a fibrillar biological structure composed of cellulose, hemicellulose, and lignin as it is illustrated in Figure 1, in relatively small proportions of non-nitrogenous extractives, crude proteinaceous material, lipid, and mineral matter. Plant species, age, and organs determine the proportions of these constituents [14].  
The world's production of lignocellulosic biomass is estimated at more than 220 billion tons per year [15] In order to valorize this type of waste and preserve the environment, biomass can be used in animal feed, soil fertilization, as well as biofuel. Indeed, lignocellulosic biomass has a significant calorific value thanks to its chemical composition rich in organic matter and combustible carbon, which favors its energy valorization as biofuels [16]. Currently, biomass contributes between 8% and 15% of the world's energy supply in the form of heat and/or electricity and transport fuels. Therefore, around 476 million tons of biomass ash are generated worldwide each year through the biomass burned is estimated at 7 billion tons with an average ash yield of 6.8% on a dry basis [17]. These ashes are classified as hazardous materials because they contain high percentages of heavy metals. It has been proved that the addition of such by-products (olive waste, rice husk, palm waste, paper pulp residues, Typha Australis, sunflower seed cake, wheat, and sawdust straw...) constituted an innovative and effective way of generating more pores in the fired bricks [18-26]. It was shown that a small quantity of additives (usually less than 10% by weight), which burns during the firing process, leads to an increase in the porosity of the brick and thus to a decrease in thermal conductivity. However, it was also observed that this creation of pores generally led to a significant decrease in mechanical performance.  
Figure 1: The main structure of lignocellulosic biomass.
## 2 The Principle and Components of CPFTA  
### Principle of CPFTA  
Figure 1 illustrates the configuration of the CPFTA, which consists of linearly polarized feed antenna, reflectarray and transmitarray. The planar reflectarray and transmitarray are placed in parallel. The reflectarray can realize the cross-polarized reflection. For different linearly polarized incident waves, the transmitarray can realize dual different functions--co-polarized reflection and circularly polarized transmission.  
In Figure 1, folded electromagnetic wave path is presented to illustrate the principle of CPFTA.  
(1) Wave path A: the feed antenna radiates _y_-polarized waves at incident angle \(\beta_{1}\).  
(2) Wave path B: the _y_-polarized waves are reflected by the transmitarray at angle \(\beta_{2}\).  
(3) Wave path C: the _y_-polarized waves are converted into _x_-polarized waves by the reflectarray at angle \(\beta_{4}\).  
(4) Finally, the transmitarray compensates the phase of _x_-polarized spherical waves and radiates circularly polarized quasi-plane waves.  
Based on Fresnel reflection law, the incident angle equals to the reflection angle, i.e., \(\beta_{1}=\beta_{2}\) or \(\beta_{3}=\beta_{4}\). According to the geometrical relationship shown in Figure 1, we can  
Figure 1: The configuration of the CPFTA in side-view.  
further derive that \(\beta_{1}=\beta_{2}=\beta_{3}=\beta_{4}\). Therefore, the total path after two reflections is equivalent to the path from the focus (F) and the profile of FTA is reduced to F/3.
# Experiencing LoRa Network Establishment on a Smart Energy Campus Testbed
## 2 LPWAN and LoRa
### LoRa MAC  
LoRaWAN defines the LoRa MAC layer, which has low power, network capacity, quality of service, and security. Collisions can occur because multiple transmitters share the same radio channel. Scheduling or random-access methods can mitigate this problem. Since scheduling is complicated and difficult to control as the number of nodes increases, most wireless communication technologies use a random-access approach. Two popular indicators for evaluating LoRa MAC performance are the packet delivery ratio (PDR) and throughput.  
In general, when a node transmits little data, the collision rate decreases, which increases the PDR but decreases the throughput. Table 3 lists the parameters and shows their impacts on the two indicators when their values increase. The parameters are the number of channels, the number of nodes, packet length, or ToA, transmission period, and transmission scheme. Having more channels in the network decreases the opportunity for collision, thus increasing the value of both indicators. Given a fixed number of channels, however, a bigger packet (i.e., long length) indicates longer ToA and is likely to increase collisions and decrease the PDR. Please note that delivering the packet implies the transmission of more bits of data. The data period also influences LoRa MAC performance. If data are transmitted quite infrequently, the chance of collision decreases. LoRa has two options for transmission: confirmed and unconfirmed. Upon receiving a data packet from a node, with the confirmed message type, a gateway sends an additional packet back to the node to acknowledge the receipt of data. Unless the node receives the response, it retransmits the data, which places a considerable load on the network [10].
# Detection and Classification of Bearing Surface Defects Based on Machine Vision
## 3 Materials and Methods
### Defect Detection
#### 3.2.1 Region-of-Interest (ROI) Extraction  
The bearing is placed flat on the turntable, the linear array camera is parallel to the axis of the bearing, the turntable rotates at a constant speed, and the linear array camera scans the outer ring of the bearing synchronously. The acquired bearing image is divided into three areas: the bottom turntable area, the central bearing area, and the upper background area. As the three areas are distributed along the \(y\)-axis, they are well aligned in the \(x\)-axis, the gray level of the black background in the upper part is low, and the gray level of the turntable image in the bottom part is high, where the features are more pronounced and relatively stable, and it is easy to detect them by using the feature region localization algorithm. The design algorithm goes as follows:  
1. Perform a mean value filter on the image.
2. Convert the filtered image into a binary image.  
Figure 2: Comparison of side images before and after correction: (**a**) inner side image before correction; (**b**) inner side image after correction; (**c**) outer side image before correction; (**d**) outer side image after correction.  
* Based on local features of the binary image, select the dark background portion of the bearing image.
* Using the smallest circumscribed rectangle, determine the coordinate of the center of the dark background.
* Based on the size of the bearing image at the center, establish a rectangular model for the central bearing region.
* Using the position information of the dark background region and its relative position to the central bearing image, locate the rectangular model of the bearing and obtain the ROI region.  
Figure 3 shows the processing procedure on a ground waste sample according to the steps described above.
# Modeling and Spatial Diversity-Based Receiving Improvement of In-Flight UAV FSO Communication Links
###### Abstract  
An in-flight unmanned aerial vehicle (UAV) free-space optical (FSO) communication channel model is proposed by considering the beam deviation of the UAV under different motion states and the phase distortion caused by atmospheric turbulences. The influence of the different motion states and turbulences on the communication quality is evaluated through phase screen and Monte Carlo methods. When the average bit error rate (BER) is \(10^{-5}\), the signal-to-noise ratio (SNR) should be increased from 13 dB to 20 dB when the tilt angle of the UAV increases from 0 to 5 mrad. An SNR of up to 20 dB is required when the variance of the wind \(\sigma_{\mathrm{z}}^{2}\) is 2 mrad. The performance of the in-flight UAV FSO link can be effectively improved through spatial diversity receiving technology. The BER of lower than \(10^{-5}\) can be obtained just with an SNR of 13 dB if the spatial diversity array with four receivers is used.  
in-flight; unmanned aerial vehicles; free-space optical communication; tilt angle; wind resistance; spatial diversity +
Footnote †: journal: Applied Sciences  
article