dataesr/scientific-paragraphs-categorization huggingface dataset:
A heuristic semi-deterministic path loss model is also proposed for the 930 MHz narrowband channel. The following main propagation mechanisms affecting path loss are considered: (i) Free-space propagation and reflection from the track. (ii) Diffraction: This mechanism mainly occurs in the case of cutting. Finally, the Deygout model is chosen. The proposed model is validated by the measurements. Details of the semi-deterministic path loss model can be found in Guan et al. [GZAK13b]. Then, a heuristic deterministic model in railway cutting scenario is proposed. The deterministic model approach consists of a 3D ray-optical channel model using a vector database and a multi-edge diffraction model based on a raster database. The ray-optical approach takes into account reflections and diffuse scattering based on the image method.
There are several strategies to determine when a frequency is unoccupied: SS (also called detection) where devices monitor frequencies for any radio transmissions and if they do not detect any, assume that the channel is free and can be used; or geolocation database where devices determine their location and query a geolocation database which returns the frequencies they can use at their current location [Ofc09]. Although WSD based on SS presents many advantages as its low-cost infrastructure, its major drawback is that sensing to very low signal levels is costly and possibly not achievable, giving rise to a not accurate detection and causing interferences to DTT transmissions  [Ofc10]. In Barbiroli et al. [BCGP12] , authors propose three different approaches to determine whether a frequency is free, based on geolocation databases: based on a threshold approach applied to a coverage map; based on the location probability; and a combination of geolocation approach and field strength measurements (sensing approach).
Physical Modelling Techniques Radio channel physical modelling is based on the application of a sound physical theory to a proper representation of the environment. The model is statistical if the environment is simply described through few, general parameters; assuming the outdoor urban channel as a reference case, such parameters may be the mean buildings height, the mean street width, etc. On the contrary, if a somehow detailed and specific description of the environment is needed, the model is said deterministic or site-specific. Deterministic physical models are mainly addressed in the following. A deterministic description of the environment refers to both its geometrical and electromagnetic properties. The geometrical description concerns the shape, the dimension and the position of each object inside the environment; these data are often stored into a proper digital environment database in vectorial or raster form which feed the model as input file.
For a long time, environment databases had to be achieved by hand based on paper maps (e. g. , cadastral maps); this procedure was cheap but also rather time consuming and practically limited to restricted environment like the indoor one. The final accuracy was often quite poor due to the lack of details in the starting map. Some automatic procedures have been then established (e. g. , aerophotogrammetry), which allow a somehow detailed digitalisation of large areas but are also rather expensive. More recently, detailed digital description and representation of the environment are being more and more available on the web, and proper interface programs may be therefore able to extract the environment database from the on-line maps. The electromagnetic description requires to associate each object with proper values of the electromagnetic parameters (e.
g. , relative electrical permittivity ε R and conductivity σ) of the materials it is made of, so that its electromagnetic behaviour (e. g. , reflection and transmission coefficients, absorbing properties, etc. ) can be defined. Again, such information is often stored in a second input file somehow linked to the environment database. Unfortunately, permittivity and conductivity are little known in several cases, and compound materials are often accounted by means of rough effective electromagnetic parameters. Irrespective of the way they are achieved, both the environment and the electromagnetic databases are always affected by unavoidable imprecisions, which may impact on the model performance to an extent that must be evaluated case by case. In order to partly compensate for performance degradation due to inaccuracies in the environment description, empirical or statistical elements are often embedded into deterministic physical models.
If, for example, surface roughness or building details such as windows, balconies, rain pipes, etc. , are missing in the urban database, then an empirical/stochastic modelling of scattering generated by those details should be introduced in the deterministic model. Deterministic physical models may potentially produce a wide spectrum of results, ranging from narrowband to wideband prediction, up to a full multidimensional characterisation of the channel, i. e. , related to the polarimetric, space-time distribution of the received signal contributions in a multipath environment. This represents a valuable quality for the design and the deployment of next wideband, multi-gigabit radio systems. In fact, the effectiveness of multi-antenna technical solutions such as antenna diversity, spatial multiplexing, and beamforming, already included in the 802.
Rays trajectories are commonly tracked according to two, different techniques, namely images RT and ray launching method  [IY02]. Since a ray-based description of radio wave propagation somehow corresponds to mental, intuitive visualisation of the actual propagation phenomenon, RT models represent very helpful study and teaching tools. On the contrary, they have not still achieved widespread application to wireless systems design and deployment problems, mainly because of the heavy computational burden and the unavailability of detailed and reliable environment description databases. Moreover, radio system planning has traditionally aimed at pursuing a satisfactory coverage level, and simple, ready-to-use models such as the Hata model  [Hat80]  have commonly represented a satisfactory and fast solution to achieve the necessary narrowband, path loss predictions.
Physical Modelling Techniques 359 Several models have been then developed to take DS into account, like the effective roughness (ER) model, which has been recently proposed and can be easily embedded into RT conventional tools. According to the ER approach, each wall/object surface is subdivided into small tiles, and the power impinging on each tile is partly reflected specularly and partly scattered according to a proper scattering coefficient S and a specific scattering pattern [DEFV + 07]. Both the S value and the width of the scattering lobe should be tuned based on measurement data collected in some reference cases in order to empirically account for the overall scattering effect, since surface irregularities and volume inhomogeneities are usually not included in the input database and a strictly deterministic approach to DS is, therefore, often unpracticable.
The non-zero matrices entries are expressed according to the ER model assuming a Lambertian scattering pattern. It's worth noticing that the matrices to be computed are independent of the number of "bounces" of propagation among the scatterers, i. e. , the computation cost is not affected by the number of allowed scattering interactions. The model performance is assessed by comparing the simulated power delay profile (PDP) with RT predictions and real channel measurement data (Figure  9. 9). With respect to a previous work of Pedersen and Fleury  [PF07] , where the propagation graph is set up assuming a random distribution of the scatterers, the deterministic approach generates the PDPs with more realistic decaying slopes. Results are also in good agreement with a RT prediction, provided that the same lambertian model is implemented.
Fang et al. [FFK02] and Abdous et al. AGR05]) and rely on a parametric dependence model based on a copula construction, which is justified by the Sklar's theorem: Sklar's Theorem: Let X and Y be random variables with distribution functions F and G respectively and joint distribution function H. Then there exists a copula C such that for all (x,y) εR × R one has H(x, y) = C(F (x), G(y)). (8. 1) If F and G are continuous, then C is unique; otherwise, C is uniquely determined on Ran(F) × Ran(G), the cartesian product of the ranges of the marginal cumulative distributions. Conversely, if C is a copula and F and G are distribution functions, then the function H defined by Equation (8. 1) is a joint distribution function with margins F and G.
As the observational network is coarse and the terrain of the study region is complex, a detailed model validation is hardly possible. This study aims at evaluating the model performance using a small number of climate stations, and in addition, radio soundings performed during an experiment. We address the question whether the key parameters 2-m temperature and surface precipitation are spatially and temporally represented better in the COSMO simulations, than in the driving global reanalysis data set ERA-Interim. The capability of COSMO to represent the vertical structure of the atmosphere in this region in terms of temperature and humidity is evaluated using radio soundings conducted during a field campaign in July 2013. The outline of this paper is as follows. In Sect. 2, the model setup and an overview of the performed simulations are presented.
Two 5-year periods have been simulated with CCLM (Table  1 ): the first period  (1979) (1980) (1981) (1982) (1983)  covers the beginning of the ERA-Interim data set, while the second period ranges from 2008 to 2012. We have chosen the two most distant time periods to best grasp the rapid and consecutive warming in the region since 1997  (Dagvadorj et al. 2014). In this experimental design, which is of course not appropriate for evaluating a linear climate trend, we define trend in the following as the absolute difference between the second and first time periods. Regional weather forecast simulations were performed to evaluate the ability of COSMO to reproduce the vertical structure of the atmosphere. GME analyses were used as driving data for these simulations. GME was until recently the operational global circulation model of the German Meteorological Service (DWD) which features an icosahedral-hexagonal grid  (Majewski et al.
2002) , an equivalent grid spacing of approximately 20 km and 60 vertical layers. GME data are available every 3 h. Daily simulations were performed for July 2013, starting at 18 UTC (1 am local time). For both types of simulation, a two time-level Runge-Kutta time-split scheme was used for the numerical integration with a time step of 60 s for the climate runs and 40 s for the weather runs. The setup includes a Kessler-type  (Kessler 1969 ) microphysics scheme handling cloud water, rain, snow, and cloud ice, a multilayer soil model  (Schrodin and Heise 2002; Grasselt et al. 2008 ) with 9 and 7 layers, 40 and 60 atmospheric layers, a radiation scheme according to  Ritter and Geleyn (1992) , and the Tiedtke mass-flux convection scheme for moist convection  (Tiedtke 1989 ) in the climate and weather simulations, respectively.
Acknowledgements We would like to thank the  WATERCOPE  project for the funding of  Oyunmunkh Byambaa , the provision of their climate station data, and for setting up and financing the field experiment in 2013. WATERCOPE was funded by the  International Fund for Agricultural Development (IFAD)  under Grant  I-R-1284. We also thank the  Institute of Meteorology and Hydrology (IMH) of Mongolia  for providing us with the station measurements. Open Access This article is distributed under the terms of the Creative Commons Attribution 4. 0 International License (http://crea tivecommons. org/licenses/by/4. 0/),which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
The Numerical Human Body Model An analysis of WBANs and sensor network operating in the proximity of a human body is often carried out with the use of full-wave electromagnetic simulation software which also implements a numerical model of the human body. The Finite Difference Time Domain (FDTD) method is widely used for this type of studies  [10]. In our research we use the XFdtd ® FDTD implementation from REMCOM, Inc. (State College, PA, USA)  [11]. This package supports a scripting language which allows the user to execute customized functions, including real-time data exchange with external software. A number of numerical human body models have been developed for the purpose of calculating the amount of electromagnetic power absorbed by the human body  [12, 13]  (i. e. , Specific Absorption Rate) which can be also used for WBAN design.
In  [9]  a robust optimization model and a new algorithm for designing WBAN in terms of topology and routing, taking into account data generation uncertainty, is presented. Also nature-mimicking algorithms are successfully exploited in WBAN design: for instance,  [7]  presents a fast evolutionary algorithm inspired by an ant colony; the case study is the optimal design of the body sensor network defined in  [8]. As far as the implementation of the optimization procedure proposed in this paper is concerned, the following remarks can be put forward: The XFdtd package provides users with a scripting language based on ECMAScript, in which one can prepare an antenna geometry model, as well as meshing and simulation procedures. In contrast, EStra optimization algorithm was originally coded in Mathworks Matlab and for further work Octave  [37]  environment was applied because it is freeware and compatible with original Matlab scripts.
The Octave and XFdtd scripts are combined and operate in turns to generate a new antenna position and calculate the objective function. Synchronization and data exchange between XFdtd and Octave have been solved by file exchange (Figure  6 ). In fact, successful applications of EStra to the design of low-frequency electromagnetic setups can be found in  [26] , while its combination with a FDTD solver for body-worn wireless sensor network optimization is an original concept presented in this paper. The subject is an emerging one. In fact, in  [36]  a flow optimization model for designing WBAN is provided; attention is focused on network installation cost and energy consumption of antennas, which are both design criteria to minimize. In  [9]  a robust optimization model and a new algorithm for designing WBAN in terms of topology and routing, taking into account data generation uncertainty, is presented.
Also nature-mimicking algorithms are successfully exploited in WBAN design: for instance,  [7]  presents a fast evolutionary algorithm inspired by an ant colony; the case study is the optimal design of the body sensor network defined in  [8]. As far as the implementation of the optimization procedure proposed in this paper is concerned, the following remarks can be put forward: The XFdtd package provides users with a scripting language based on ECMAScript, in which one can prepare an antenna geometry model, as well as meshing and simulation procedures. In contrast, EStra optimization algorithm was originally coded in Mathworks Matlab and for further work Octave  [37]  environment was applied because it is freeware and compatible with original Matlab scripts. The Octave and XFdtd scripts are combined and operate in turns to generate a new antenna position and calculate the objective function.
Conclusions In this paper we present original results of our investigation of an evolutionary optimization of a simple body-worn wireless sensor network comprising three on-body nodes. This case was motivated by the practical need of improving performance of a WBAN designed to monitor firefighters' vital signs and environmental conditions. A number of design assumptions and constraints were imposed by our application, for example the fixed position of the head and arm nodes predetermined by the types of sensors they use. One degree of freedom available to us was the placement of the chest node in the front-left part of the jacket. In this paper we show that even with such strong design constraints it is possible to considerably decrease the path loss between nodes using an automated optimization procedure based on evolutionary computing (EStra) combined with a computational electromagnetics code (XFdtd) to evaluate the value of the objective function.
A specific tool, called Atelier B  [18] , designed to implement the B Method and provided with a theorem prover, helps users verify the validity of proof obligations, automatically or interactively. Improving the automated verification of proof obligations is a crucial task. The BWare research project  [10]  proposed to use external automated provers, like first-order Automated Theorem Provers (ATPs) and Satisfiability Modulo Theory (SMT) solvers, by building a common platform to run these tools. This platform, based on the software verification tool Why3  [3] , requires proof obligations to be encoded in its native language called WhyML. Mentré et al. [16]  proposed a translator program called bpo2why to address this issue. This tool focuses on the translation of B proof obligations output by Atelier B into the WhyML language.
This allows highly efficient observation of the rest-frame optical spectral features for objects at redshifts beyond one (e. g. 5  ) and absorption bands in the infrared continuum of cool, low-mass stars (e. g. 6  ). Recently, the Subaru Telescope observatory has started accepting a large program in the framework called "Subaru Strategic Program" (SSP) that can span up to ∼300 nights over ∼5 years. A cosmology survey program called "FastSound"  7  (PI: T. Totani), one of the few SSP programs, was successfully completed with PFS (8. 2m) for z~1. 5 slice 4m-class tel. Best datasets at z>1… before WFIRST (NASA: 2025-) Wide & deep survey of MW dwarf galaxies w. Subaru/PFS nominal boundary (r t ~ 76'), but more member stars actually exist inside/beyond this limit. Cumula=ve number of observable stars w.
Subaru/PFS Subaru/PFS enables us to measure a large number of stellar spectra over unprecedentedly wide outer areas, where DM largely dominates! Best for studying the nature of DM Top left: the product of the mean galaxy space density and the galaxy clustering amplitude is plotted as a function of redshift and the case for the PFS cosmology program is compared with WFIRST and DESI. 10, 11   op right: the cosmic star formation history  12  is illustrated with a wide range of redshifts that can be accessed in the PFS galaxy & AGN evolution survey exploiting the wide wavelength coverage. Bottom: a PFS pointing plan around the Sculptor dwarf galaxy  13, 14  as a part of the Galactic archaeology program is summarized, showing high efficiency thanks to the wide field and high multiplicity. FMOS to reveal a 3D map of ∼3000 galaxies around z ∼ 1.
4 and a significant detection of Redshift Space Distortions (RSD). 8 w new instrumentation projects are underway to upgrade the Subaru prime focus and push the cutting edge science further forward, taking the full advantage of the unique wide field of view. Hyper Suprime-Cam (HSC),  9  the successor of Suprime-Cam, is a very wide-field imager with a 1. 5-degree diameter field of view "paved" by 116 2K×4K CCDs. It has been in science operation since 2014 and a 5-year, 300-night SSP survey program is ongoing. PFS (Prime Focus Spectrograph), as described in this article, is a very wide-field, massively multiplexed, optical and near-infrared (NIR) spectrometer. The focal plane will be equipped with 2394 reconfigurable fibers distributed in the 1. 3-degree wide hexagonal field of view. The spectrograph has been designed to cover a wide range of wavelengths simultaneously from 380nm to 1260nm in one exposure.
This way, a PFS SSP program for follow-up spectroscopy can start in a timely manner subsequently after the HSC SSP survey. In what follows, the instrument basics are described in § 2, and an overview of the instrument and survey operation concept is given in § 3. Then updates of a few major aspects of the project are summarized in § 4, and this article is summarized and a timeline for the future developments is given in § 5. At the Subaru prime focus, HSC has already been in science operation with the wide field of view and the reasonably flat focal plane provided by the new Wide-Field Corrector lens system (WFC). The WFC will be used for PFS as well. Mechanically, the new prime focus housing unit "POpt2" is integrated with WFC and accommodates the HSC instrument inside. When PFS is in operation, the HSC instrument will be taken out and our Prime Focus Instrument (PFI) will be installed in POpt2.
OPERATION CONCEPT For the operation of the PFS instrument and the large survey program it will carry out, coordination not only between the hardware and software but also between different software packages is crucial. Four software components are under development for this, with different sets of functions packaged and therefore designed to * California Institute of Technology be only loosely coupled to each other. The detailed definitions of these four packages have been evolving as the instrument and survey operation concepts are being updated to maximally accommodate the distinct features of the planned survey for PFS SSP such as: (1) A much fainter limit than previous legacy surveys such as SDSS is pursued, exploiting the large light-gathering power of the Subaru Telescope, (2) given the wide variety of scientific goals, a wide variety of objects are targeted for observation and therefore a variety of definitions of success need to be encompassed, (3) PFS allows dynamic fiber reallocation even on an individual exposure basis, unlike the static integration in case of classical multi-slit and multi-fiber spectroscopy using machined plates.
Observation preparation The observation process starts with preparing an input target catalog which includes not only science targets but also stars for field acquisition, auto-guiding & focusing, and flux calibration. Then telescope pointings, position angles, and fiber allocations to science targets at each pointing are defined for a given time of observation. This planning task is performed by a software package called "ETS" (Exposure Targeting Software) being developed by MPA. This observation configuration is prepared by scientists at sites off the observatory, and the prepared configuration is then uploaded to a database system. At the actual time of observation, which may be different from the one in the plan, the details in the mapping between the science targets and allocated fibers are recalculated before the fiber configuration starts.
Instrument operation & data acquisition "ICS" (Instrument Control Software) is the software package that orchestrates the PFS subsystems and subcomponents for instrument operation in coordination with the telescope system. The key component for the integration and coordination is a messaging hub system (MHS). As has been demonstrated in the SDSS operations at Apache Point Observatory, it efficiently organizes distributed processes providing uniform communication interfaces between subcomponents. MHS is being used for the operation of the CHARIS instrument  26  (a high contrast integral field spectrograph for studying disks and extrasolar planets around stars) which is now in the commissioning phase at the Subaru Telescope, so we will take advantages of this experience in advance of the PFS commissioning process.