ALBERT

Description: Information, Vol. 9, Pages 128: Key Concept Identification: A Comprehensive Analysis of Frequency and Topical Graph-Based Approaches Information doi: 10.3390/info9050128 Authors: Muhammad Aman Abas bin Md Said Said Jadid Abdul Kadir Israr Ullah Automatic key concept extraction from text is the main challenging task in information extraction, information retrieval and digital libraries, ontology learning, and text analysis. The statistical frequency and topical graph-based ranking are the two kinds of potentially powerful and leading unsupervised approaches in this area, devised to address the problem. To utilize the potential of these approaches and improve key concept identification, a comprehensive performance analysis of these approaches on datasets from different domains is needed. The objective of the study presented in this paper is to perform a comprehensive empirical analysis of selected frequency and topical graph-based algorithms for key concept extraction on three different datasets, to identify the major sources of error in these approaches. For experimental analysis, we have selected TF-IDF, KP-Miner and TopicRank. Three major sources of error, i.e., frequency errors, syntactical errors and semantical errors, and the factors that contribute to these errors are identified. Analysis of the results reveals that performance of the selected approaches is significantly degraded by these errors. These findings can help us develop an intelligent solution for key concept extraction in the future.

Description: The authors would like to add the following note in the Affiliation Section of their paper published in Energies [...]

Description: Exponential fertilization is well-known for improving the growth and nutritional status of seedlings during nursery culture. However, less is known about how genetic variability among seedling species influences the effects of fertilization regimes on the growth of seedlings and their nutritional status under varying fertilization levels. Here, we conducted a greenhouse experiment to compare the growth, as well as the nitrogen (N) and phosphorus (P) nutrient concentration responses, of 2- and 3-generation Chinese fir (Cunninghamia lanceolata (Lambert) Hooker) seedlings to the impacts of varying exponential and conventional constant-rate fertilization levels (50, 100, and 200 mg P seedling−1). Seedling size and shoot:root ratios were lower in exponential fertilization than in conventional fertilization. Exponentially fertilized seedlings had higher concentrations of N and P nutrients compared to conventionally fertilized seedlings during low-level fertilization. Conversely, an elevated P concentration was observed in seedlings subjected to conventional fertilization compared to those exposed to exponential fertilization during high-level fertilization. However, there were no significant differences in seedling N and P concentrations between the two fertilization regimes during medium-level fertilization. Furthermore, 2- and 3-generation Chinese fir seedlings differed greatly in their growth and nutritional status. Additionally, there were significant fertilization regime × seedling generation interaction effects on the seedling shoot:root ratio and N concentration. Our findings suggest that exponential fertilization can improve the nutritional status, survival, and growth of Chinese fir seedlings, especially on competitive sites, and that information on both intra-species genetic variability and appropriate fertilizer levels is necessary for the successful fertilization of Chinese fir seedlings, regardless of fertilization regimes.

Description: Drought in Australia has widespread impacts on agriculture and ecosystems. Satellite-based Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) has great potential to monitor and assess drought impacts on vegetation greenness and health. Various FAPAR products based on satellite observations have been generated and made available to the public. However, differences remain among these datasets due to different retrieval methodologies and assumptions. The Quality Assurance for Essential Climate Variables (QA4ECV) project recently developed a quality assurance framework to provide understandable and traceable quality information for Essential Climate Variables (ECVs). The QA4ECV FAPAR is one of these ECVs. The aim of this study is to investigate the capability of QA4ECV FAPAR for drought monitoring in Australia. Through spatial and temporal comparison and correlation analysis with widely used Moderate Resolution Imaging Spectroradiometer (MODIS), Satellite Pour l’Observation de la Terre (SPOT)/PROBA-V FAPAR generated by Copernicus Global Land Service (CGLS), and the Standardized Precipitation Evapotranspiration Index (SPEI) drought index, as well as the European Space Agency’s Climate Change Initiative (ESA CCI) soil moisture, the study shows that the QA4ECV FAPAR can support agricultural drought monitoring and assessment in Australia. The traceable and reliable uncertainties associated with the QA4ECV FAPAR provide valuable information for applications that use the QA4ECV FAPAR dataset in the future.

Description: Detecting the cognitive profiles of learners is an important step towards personalized and adaptive learning. Electroencephalograms (EEG) have been used to detect the subject’s emotional and cognitive states. In this paper, an approach for detecting two cognitive skills, focused attention and working memory, using EEG signals is proposed. The proposed approach consists of the following main steps: first, subjects undergo a scientifically-validated cognitive assessment test that stimulates and measures their full cognitive profile while putting on a 14-channel wearable EEG headset. Second, the scores of focused attention and working memory are extracted and encoded for a classification problem. Third, the collected EEG data are analyzed and a total of 280 time- and frequency-domain features are extracted. Fourth, several classifiers were trained to correctly classify and predict three levels (low, average, and high) of the two cognitive skills. The classification accuracies that were obtained on 86 subjects were 84% and 81% for the focused attention and working memory, respectively. In comparison with similar approaches, the obtained results indicate the generalizability and suitability of the proposed approach for the detection of these two skills. Thus, the presented approach can be used as a step towards adaptive learning where real-time adaptation is to be done according to the predicted levels of the measured cognitive skills.

Description: ZnO nanorods (NRs) with an average length and diameter of 186 and 20 nm, respectively, were prepared through a mild solvothermal route and used as photocatalysts either as dispersed powder or immobilized on glass slides. The ZnO NRs were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray diffraction (XRD). Dispersed ZnO NRs and, to a lesser extent, immobilized ZnO NRs were demonstrated to exhibit high photocatalytic activity under simulated sunlight of low intensity (5.5 mW/cm2) both for the degradation of the Orange II dye and for Escherichia coli bacterial decontamination (2.5-fold survival decrease after 180 min irradiation for immobilized NRs). SEM, atomic force microscopy (AFM), fluorescence spectroscopy, and epifluorescence microscopy demonstrate that cell surface damages are responsible of bacterial inactivation. The immobilized ZnO NRs could be reused up to five times for bacterial decontamination at comparable efficiency and therefore have great potential for real environmental applications.

Description: The Multi-angle Imaging SpectroRadiometer (MISR) sensor onboard the Terra satellite provides high accuracy albedo products. MISR deploys nine cameras each at different view angles, which allow a near-simultaneous angular sampling of the surface anisotropy. This is particularly important to measure the near-instantaneous albedo of dynamic surface features such as clouds or sea ice. However, MISR’s cloud mask over snow or sea ice is not yet sufficiently robust because MISR’s spectral bands are only located in the visible and the near infrared. To overcome this obstacle, we performed data fusion using a specially processed MISR sea ice albedo product (that was generated at Langley Research Center using Rayleigh correction) combining this with a cloud mask of a sea ice mask product, MOD29, which is derived from the MODerate Resolution Imaging Spectroradiometer (MODIS), which is also, like MISR, onboard the Terra satellite. The accuracy of the MOD29 cloud mask has been assessed as 〉90% due to the fact that MODIS has a much larger number of spectral bands and covers a much wider range of the solar spectrum. Four daily sea ice products have been created, each with a different averaging time window (24 h, 7 days, 15 days, 31 days). For each time window, the number of samples, mean and standard deviation of MISR cloud-free sea ice albedo is calculated. These products are publicly available on a predefined polar stereographic grid at three spatial resolutions (1 km, 5 km, 25 km). The time span of the generated sea ice albedo covers the months between March and September of each year from 2000 to 2016 inclusive. In addition to data production, an evaluation of the accuracy of sea ice albedo was performed through a comparison with a dataset generated from a tower based albedometer from NOAA/ESRL/GMD/GRAD. This comparison confirms the high accuracy and stability of MISR’s sea ice albedo since its launch in February 2000. We also performed an evaluation of the day-of-year trend of sea ice albedo between 2000 and 2016, which confirm the reduction of sea ice shortwave albedo with an order of 0.4–1%, depending on the day of year and the length of observed time window.

Description: Elderly Bedouin men in southern Israel are a unique traditional population living in remote unrecognized villages and experiencing rapid social transition, in addition to deep poverty and political tension. In this study, we aimed to explore stressful events, as self-defined by the participants, and the ways in which these men have coped with those stressful events. This study involved 12 men, aged 69–74, who participated in in-depth narrative interviews during which they were asked about transformative stressful events in their lives and how they had managed, understood, and utilized human capital, meaning-making, and other methods of coping. Analysis of the interviews revealed several themes: (a) the definition of stressful events within the cultural context, (b) the use of human capital to overcome those events, (c) the transformation of experience from hindsight into a didactic narrative that can be used to assign meaning to past events, which can then be passed on to the next generation, and (d) cultural transition as a catalyst for the creation of new understandings of events. This paper sheds new light on how elderly indigenous Bedouin men self-define stressful situations within a complex and unstable cultural context. This specific context, can help us to gain insight into how indigenous impoverished older men in similar contexts may self-define their stress and coping, based on the types of generalization accepted in qualitative research. The methodological contribution of this work lies in its use of narrative to culturally contextualize phenomenological meaning structures. Its theoretical contribution lies in its examination of the concept of stress within a specific cultural context.

Description: Stochastic optimisation in Riemannian manifolds, especially the Riemannian stochastic gradient method, has attracted much recent attention. The present work applies stochastic optimisation to the task of recursive estimation of a statistical parameter which belongs to a Riemannian manifold. Roughly, this task amounts to stochastic minimisation of a statistical divergence function. The following problem is considered: how to obtain fast, asymptotically efficient, recursive estimates, using a Riemannian stochastic optimisation algorithm with decreasing step sizes. In solving this problem, several original results are introduced. First, without any convexity assumptions on the divergence function, we proved that, with an adequate choice of step sizes, the algorithm computes recursive estimates which achieve a fast non-asymptotic rate of convergence. Second, the asymptotic normality of these recursive estimates is proved by employing a novel linearisation technique. Third, it is proved that, when the Fisher information metric is used to guide the algorithm, these recursive estimates achieve an optimal asymptotic rate of convergence, in the sense that they become asymptotically efficient. These results, while relatively familiar in the Euclidean context, are here formulated and proved for the first time in the Riemannian context. In addition, they are illustrated with a numerical application to the recursive estimation of elliptically contoured distributions.

Description: The purpose of this article is to obtain the exact and approximate numerical solutions of linear and nonlinear singular conformable pseudohyperbolic equations and conformable coupled pseudohyperbolic equations through the conformable double Laplace decomposition method. Further, the numerical examples were provided in order to demonstrate the efficiency, high accuracy, and the simplicity of present method.