Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study on Oil Palm Remote Sensing at L-Band With Dense Medium Microwave Backscattering Model

Studies on the potential of using synthetic aperture radar (SAR) imaging data for remote sensing in oil palm growth needs to be done in depth. In this paper, we utilized a scattering model for oil palm to study and understand how L-band microwave interacts with the structure of the oil palm. The model is developed based on the radiative transfer theory and solved iteratively up to the second order. The knowledge obtained can likely be used to interpret the backscattering behavior of oil palm with respect to growth. The oil palm is modeled as a multilayer dense medium with leaflets as elliptical disk while the trunk and fronds as cylinders. The model takes into consideration of the close spacing effects of scattering in a dense medium with the use of phase correction theory. Furthermore, near-field interactions between closely spaced scatterers are also considered via the Fresnel phase and amplitude corrections. Ground truth data were measured from the oil palm fields and are used as input parameters in the model. Five different age groups of oil palm were chosen and their backscatter coefficient simulated at L-band frequency. L-band SAR data acquired were compared with the simulated results, and it was found that there was a good agreement between the simulated results and measured data. For further understanding, the model also simulated the breakdown of backscatter contribution by various components of oil palm which allows a better understanding of the interaction between microwave backscatter with specific components.
Evaluation of Moist Static Energy in a Simulated Tropical Cyclone

The characteristics of moist static energy (MSE) and its budget in a simulated tropical cyclone (TC) are examined in this study. Results demonstrate that MSE in a TC system is enhanced as the storm strengthens, primarily because of two mechanisms: upward transfer of surface heat fluxes and subsequent warming of the upper troposphere. An inspection of the interchangeable approximation between MSE and equivalent potential temperature (θe) suggests that although MSE is capable of capturing overall structures of θe, some important features will still be distorted, specifically the low-MSE pool outside the eyewall. In this low-MSE region, from the budget analysis, the discharge of MSE in the boundary layer may even surpass the recharge of MSE from the ocean. Unlike the volume-averaged MSE, the mass-weighted MSE in a fixed volume following the TC shows no apparent increase as the TC intensifies, because the atmosphere becomes continually thinner accompanying the warming of the storm. By calculating a mass-weighted volume MSE budget, the TC system is found to export MSE throughout its lifetime, since the radial outflow overwhelms the radial inflow. Moreover, the more intensified the TC is, the more export of MSE there tends to be. The input of MSE by surface heat fluxes is roughly balanced by the combined effects of radiation and lateral export, wherein a great majority of the imported MSE is reduced by radiation, while the export of MSE from the TC system to the environment accounts for only a small portion.
Unexpected Consequences of Transverse Isotropy

In a series of papers, Kawakatsu et al. (2015) and Kawakatsu (2016a, b, 2017) introduced and discussed a new parameter, ηκ, that characterizes the incidence angle dependence (relative to the symmetry axis) of seismic body wave velocities in a transverse isotropy (TI) system. With the properly defined new set of parameters, Kawakatsu (2016b) further demonstrated that sensitivities of those parameters to Rayleigh wave phase velocity made much more sense and thus they were useful for long-period seismology. More recently, Kawakatsu (2017) showed how the reflection and transmission coefficients behaved in terms of ηκ. During the course of these exercises, several nontrivial consequences of transverse isotropy are realized and summarized as follow: (1) a trade-off exists between ηκ and Vp/Vs-ratio if assumed for isotropy; (2) P-wave velocity (anisotropy) strongly influences the conversion efficiency of P-to-S and S-to-P, as much as S-wave velocity perturbation does; (3) Rayleigh wave phase velocity has substantially sensitivity to P-wave anisotropy near the surface. These findings, especially the last two, might deserve careful attention in interpretation of results of popular seismic analysis methods, such as receiver function analyses and ambient noise Rayleigh wave dispersion measurements. Especially, the strong influence of P-wave anisotropy to P-to-S and S-to-P conversion may be essential to the receiver function analysis, because, for isotropic media, we typically attribute the primary receiver function signals to S-wave velocity changes. Considering that the receiver function analysis has become a popular and powerful tool to investigate the crustal and upper mantle structures, it seems important to fully investigate to what extent and under what circumstances the effect might be significant.
Non-linear optimization applied to preliminary ship design

Ship preliminary design optimization has been widely studied in two areas, the models that allow the optimum characteristics calculation and the optimization algorithms to be used. In this work, special relevance is given to the nonlinear optimization algorithm, with focus in the evolutionary and direct-search methods. First, the results of a set of selected methods are compared using a simple bulk carrier ship model found in literature, next a new optimization process is proposed and is validated with the model mentioned. Finally, to test the proposed method in preliminary ship design dimensioning, a container ship model was developed, with an innovative method to estimate the total container capacity. In the traditional containers ship models, the capacities are calculated with statistical formulas derived from existent ships. The total number of containers in the hull is calculated by estimating the internal hull volume for each vertical row which is derived from sectional area curves.
Developing question answering (QA) systems using the patterns

This paper describes a way to use Natural Language Processing (NLP) techniques in order to gain faster access to information from a closed domain. Using traditional graphical user interfaces built as a tree structure, such as menus, determine users to browse irrelevant information. To avoid this, we use one of the major tasks in NLI, Question Answering (QA) and build with Visual FoxPro 9.0 a demonstrating application. We impose restrictions related to the domain of use that of tourist attractions in Romania, and restrictions related to natural language input method. We use tags to represent words or groups of words and patterns to symbolize questions. We use this representation in order to provide to user a non-traditional human-computer interaction. The QA system rely on a database where we store specific information on chosen domain and related data in order to accomplish the task of providing an answer. The answering mechanism uses a knowledge engineering with syntactic and semantic approach. At the end of this paper we discuss the QA System Evaluation.
Approche par neurolattice pour la prédiction des angles de talus naturel des matières divisées

La modelisation du comportement des materiaux granulaires est delicate par les approches classiques, car ceux-ci se comportent selon des caracteristiques hybrides entre les fluides et les solides. Cette complexite permet d’envisager une modelisation combinant des automates cellulaires et des reseaux de neurones profonds. Cette approche permet de preentrainer des reseaux de neurones avec des donnees artificielles plus facile et moins couteuses a obtenir que des donnees reelles, dans l’optique de pouvoir reduire le temps d’apprentissage et la quantite de donnees reelles necessaires a l’ajustement fin du modele. Nous avons evalue cette approche neurolattice sur la prediction des angles de talus naturels qui represente un probleme important dans les industries manipulant des solides pulverulents (geologie, agroalimentaire, pharmacie, cosmetique…). Un automate cellulaire implante dans une classe openAI GYM a servi de base d’apprentissage a un reseau de neurones LSTM (Long Short Term Memory) pour relier la distribution granulometrique a un angle de talus apres ecoulement. Le reseaux de neurones obtenu predit les angles de talus naturel avec une precision de plus de 98%.
Star formation histories of resolved galaxies – I. The method

We present a new method to determine the star formation and metal enrichment histories of any resolved stellar system. This method is based on the fact that any observed star in a colour-magnitude diagram will have a certain probability of being associated with an isochrone characterised by an age t and metallicity [Fe/H] (i.e. to have formed at the time and with the metallicity of that isochrone). We formulate this as a maximum likelihood problem that is then solved with a genetic algorithm. We test the method with synthetic simple and complex stellar populations. We also present tests using real data for open and globular clusters. We are able to determine parameters for the clusters (t, [Fe/H]) that agree well with results found in the literature. Our tests on complex stellar populations show that we can recover the star formation history and age-metallicity relation very accurately. Finally, we look at the history of the Carina dwarf galaxy using deep BVI data. Our results compare well with what we know about the history of Carina.
Decoupling method for parallel Delaunay 2D mesh generation

PAGE Meshes are central structures for numerical methods, such as the finite element method. These numerical methods require high quality refined meshes in order to achieve good approximations of the analytical model. Unstructured meshes are the most popular; their adaptive nature allows them to give boundary conforming meshes of good quality, with optimal size. The most widely studied 2D mesh generation method is the Delaunay method. Creating in parallel guaranteed quality large unstructured meshes is a challenging problem. The Delaunay refinement procedure is memory intensive with unpredictable computational behavior. Moreover, geometries may be quite complex, adding difficulty to parallelize the mesh generation. Parallel mesh generation procedures decompose the original mesh generation problem into smaller subproblems that can be solved in parallel. The subproblems can be treated as either completely or partially coupled, or they can be treated as completely decoupled. Parallel mesh generation procedures that are based on geometric domain decompositions require the permenant separators to be of good quality (in terms of their angles and length), in order to maintain the mesh quality. The Medial Axis domain decomposition, an innovative geometric domain decomposition procedure that addresses this problem, is introduced. The Medial Axis domain decomposition is of high quality in terms of the formed angles, and provides separators of small size, and also good work-load balance. It presents for the first time a decomposition method suitable for parallel meshing procedures that are based on geometric domain decompositions. The decoupling method for parallel Delaunay 2D mesh generation is a highly efficient and effective parallel procedure, able to generate billions of elements in a few hundred of seconds, on distributed memory machines. Our mathematical formulation introduces the notion of the decoupling path, which guarantees the decoupling property, and also the quality and conformity of the Delaunay submeshes. The subdomains are meshed independently, and as a result, the method eliminates the communication and the synchronization during the parallel meshing. A method for shielding small angles is introduced, so that the decoupled parallel Delaunay algorithm can be applied on domains with small angles. Moreover, we present the construction of a sizing function, that encompasses an existing sizing function and also geometric features and small angles. The decoupling procedure can be used for parallel graded Delaunay mesh generation, controlled by the sizing function. The decoupling approach allows 100% code re-use of existing, fine-tuned and well tested, sequential mesh generators, minimizing the effort of code parallelization. Our results indicate high scalability of the decoupling approach, and also show superlinear speedups, when compared to the sequential library.
Improved trajectory control for an interior permanent magnet synchronous motor drive with extended operating limit

This paper presents analysis of trajectory control for an interior permanent magnet (IPM) synchronous motor drive under PWM current control. An improved trajectory control with extended speed range has been introduced. The scheme allows the motor to be driven with maximum-torque-per-ampere characteristic (MTPA) below the base speed and it maintains the maximum voltage limit of the motor under wide flux-weakening and the motor current limit under all conditions of operation accurately. Following the analysis of the trajectory control, the results of extensive simulation and experiment are given.
Theory I: Deep networks and the curse of dimensionality

Deep Learning references start with Hinton’s backpropagation and with Lecun’s convolutional networks (see for a review [8]). Of course, multilayer convolutional networks have been around at least as far back as the optical processing era of the 1970s. The Neocognitron [9] was a convolutional neural network that was trained to recognize characters. The property of compositionality was a main motivation for hierarchical models of visual cortex such as HMAX which can be regarded as a pyramid of AND and OR layers [10], that is a sequence of conjunctions and disjunctions. Several papers in the 1980s focused on the approximation power and learning properties of one-hidden layer networks (called shallow networks here). Very little appeared on multilayer networks, (but see [11‒13]), mainly because one hidden layer nets performed empirically as well as deeper networks. On the theory side, a review by Pinkus in 1999 [14] concludes that “. there seems to be reason to conjecture that the two hidden layer model may be significantly more promising than the single hidden layer model. ”. A version of the questions about the importance of hierarchies was asked in [15] as follows: “A comparison with real brains offers another, and probably related, challenge to learning theory. The “learning algorithms” we have described in this paper correspond to onelayer architectures. Are hierarchical architectures with more layers justifiable in terms of learning theory? It seems that the learning theory of the type we have outlined does not offer any general argument in favor of hierarchical learning machines for regression or classification. This is somewhat of a puzzle since the organization of cortex – for instance visual cortex – is strongly hierarchical. At the same time, hierarchical learning systems show superior performance in several engineering applications. ” Because of the great empirical success of deep learning over the last three years, several papers addressing the question of why hierarchies have appeared. Sum-Product 1. A theory of deep learning
A High‐Index Ge2Sb2Te5‐Based Fabry–Perot Cavity and Its Application for Third‐Harmonic Generation

Third‐order harmonic generation (THG) plays a vital role in microscopy, optical communications, etc. Conventional methods of obtaining efficient THG in macroscopic crystals is already mature; however, they will finally limit the miniaturization and integration of on‐chip laser sources. To date, THG from either photonic crystals or metamaterials provides compact photonic platforms; however, selection of materials remains elusive. Herein, a giant enhancement of THG efficiency from an air/high index Ge2Sb2Te5 (GST)/gold multi‐layered Fabry–Perot cavity is experimentally demonstrated. At cavity resonant wavelength in near‐infrared regime, the efficiency of THG from a 50‐nm thick amorphous GST planar film is boosted 422 times compared to that of nonresonant conditions. Interestingly, the THG efficiency has a dramatic decrease of three orders when the structural state of GST is transformed from amorphous to crystalline. These findings have a potential for achieving an ultracompact nonlinear optical source with high efficiency and switchable functionality.
Network Inference and Community Detection, Based on Covariance Matrices, Correlations and Test Statistics from Arbitrary Distributions

In this paper we propose methodology for inference of binary-valued adjacency matrices from various measures of the strength of association between pairs of network nodes, or more generally pairs of variables. This strength of association can be quantified by sample covariance and correlation matrices, and more generally by test-statistics and hypothesis test p-values from arbitrary distributions. Community detection methods such as block modelling typically require binary-valued adjacency matrices as a starting point. Hence, a main motivation for the methodology we propose is to obtain binary-valued adjacency matrices from such pairwise measures of strength of association between variables. The proposed methodology is applicable to large high-dimensional data-sets and is based on computationally efficient algorithms. We illustrate its utility in a range of contexts and data-sets.
Simulations of Neocortical Columnar Oscillations

The intentionof this thesis is to examine the role of the neocortical local drcuit in supporting synchronisatLon and fast (gamma) oscUlation. The aim is to include stereotypical features of the local neocortex in model simulations of cortical activity. Modelling is hmitedby scale in number and detail. Model features include three neurontypes(RS, FS and IB) andsynapses with three time courses takenfrom reportedtri-phasic PSPs (fEPSP, flPSP andsIPSP). Cell types and synapses are distributedin a two layer model. The contribution of the layers to columnactivity is investigated. The upperlayer has a tendancy towardspredse synchronisation and can dominate the activity producing synchronisation and oscillation in the whole column. This is attributed to the stronger inhibitory circuit in the upperlayer. The lower layer achieves a less precise synchronisatiorv this is attributed to a lower level of inhibition and the intraburst duration of IB neurons. The significance of this difference in the temporal properties of the two layers is discussed in relation to existing theories andmodels of local cortical function. Following a further consideration of local cortical physiology a new model of cortical functioning is proposed. The key features of this model include: the generation of local oscillations in a vertical interlarninar reciprocal circuit; the apical dendrite providing a sharp coincidence detection functionbetweenthe layers; slow axonal lateral propagationprovidinga time delay network; apical dendrites of bursting cells (CH and IB) providing coincidence detectionbetweenmputs 6:0m distant areas (layer 1 inputs) and local activity; bursting cell innervationof intemeurons, linking the local oscillation cy de to coinddence detection. This moddis termed an'intrinsically osdllating time coding networld (lOTCN). Specific predictions are made concerning the functiorungof the local circuit m neocortex, and the connectivity of CH neurons.
New View of the Solar Chromosphere

The solar chromosphere forms a crucial, yet complex and until recently poorly understood, interface between the solar photosphere and the heliosphere. ▪ Advances in high-resolution instrumentation, adaptive optics, image reconstruction techniques, and space-based observatories allow unprecedented high-resolution views of the finely structured and highly dynamic chromosphere. ▪ Dramatic progress in numerical computations allows 3D radiative magnetohydrodynamic forward models to take the place of the previous generation of 1D semiempirical atmosphere models. These new models provide deep insight into complex nonlocal thermodynamic equilibrium chromospheric diagnostics and enable physics-based interpretations of observations. ▪ This combination of modeling and observations has led to new insights into the role of shock waves, transverse magnetic waves, magnetic reconnection and flux emergence in the chromospheric energy balance, the formation of spicules, the impact of ion-neutral interactions, and the connectivity between chromosphere and transition region. ▪ During the next few years, the advent of new instrumentation (integral-field-unit spectropolarimetry) and observatories (ALMA, DKIST), coupled with novel inversion codes and expansion of existing numerical models to deal with ever more complex physical processes (including multifluid approaches), is expected to lead to major new insights into the dominant heating processes in the chromosphere and beyond.
The New Product Development Process as a Communication Web Part I: Introduction, Concepts, and Spanish Context

This chapter contributes towards existing literature by analysing the innovation activities of Spanish companies and by proposing New Product Development (NPD) as a communication web. We propose a model, based on literature reviews, that relates the external communication of cross-functional teams to the performance of NPD programmes. The composition of NPD teams and the external communication activities thereof are a core competency for companies and can provide them with major competitive advantages. DOI: 10.4018/978-1-61350-165-8.ch028
KRNJENJE SLOVENSKIH BESEDIL S PODROČJA BIBLIOTEKARSTVA

Abstract The theme of the article is the preparation of a stemming algorithm for Slovenian library science texts. The procedure consisted of three phases: learning, testing and evaluation. The preparation of the optimal stemmer for Slovenian texts from the field of library science is presented, its testing and comparison with two other stemmers for the Slovenian language: the Popovic stemmer and the Generic stemmer. A corpus of 790.000 words from the field of library science was used for learning. Lists of stems, word endings and stop-words were built. In the testing phase, the component parts of the algorithm were tested on an additional corpus of 167.000 words. In the evaluation phase, a comparison of the three stemmers processing the same word corpus was made. The results of each stemmer were compared with an intellectually prepared control result of the stemming of the corpus. It consisted of groups of semantically connected words with no errors. Understemming was especially monitored – the number of stems for semantically connected words, produced by an algorithm. The results were statistically processed with the Kruskal-Wallis test. The Optimal stemmer produced the best results. It matched best with the reference results and also gave the smallest number of stems for one semantic meaning. The Popovic stemmer followed closely. The Generic stemmer proved to be the least accurate. The procedures described in the thesis can represent a platform for the development of the tools for automatic indexing and retrieval for library science texts in Slovenian language.