Miracle-dz/UniFAR-FTUs huggingface dataset:
RETRIEVAL OF SOIL MOISTURE FROM ENVISAT ASAR IMAGES: A COMPARISON OF INVERSION ALGORITHMS

ABSTRACT The aim of this paper was to verify the capability of ENVISAT/ASAR images in providing soil moisture maps of agricultural areas. SAR images were collected in two sites in Italy (Alessandria and Montespertoli) in 2003 and 2004, along with ground measurements of soil moisture and roughness. The performances of some inversion statistical algorithms (Regression, Bayes, Neural Network, Nelder-Mead) in retrieving several levels of soil moisture were tested and compared to each other. Up to six levels of soil moisture were correctly retrieved by using these techniques. 1. INTRODUCTION Soil moisture (SMC) plays a critical role in the surface energy balance at the soil-atmosphere interface and can be considered a key state variable that influences the redistribution of the radiant energy and the runoff generation and percolation of water in soil. We know that local SMC measurements are strongly affected by spatial variability, besides being time-consuming and expensive. Moreover, the use of hydrological models for extending the forecast of soil moisture over larger areas is not easy, and depends on the homogeneity of the selected areas and on the information available on them (soil properties, i.e. hydraulic characteristics, and permeability, together with meteorological and climatological data, etc.). The possibility of measuring soil moisture on a large scale from satellites, with complete and frequent coverage of the Earth’s surface, is, therefore, extremely attractive. The sensitivity to soil moisture of the backscattering coefficient measured at low microwave frequencies is a well-known phenomenon already investigated by many scientists [1,3]. Indeed, research activities carried out worldwide in the past have demonstrated that sensors operating in the low frequency portion of the microwave spectrum (P- to L-band) are able to measure the moisture of a soil layer, the depth of which depends on soil characteristics and moisture profile [3]. The most significant information was obtained by combining different frequencies, polarizations, and incidence angles [4]. Unfortunately, L-band is not available in current satellite sensors. Thus, research for the retrieval of soil moisture has been focused on the potential of existing sensor frequency, i.e. the C-band, which is operational on ERS-2, RADARSAT, and ENVISAT. C-band backscattering is still sensitive to SMC, but it is significantly influenced by vegetation and surface roughness too, so that the estimation of spatial variations of moisture with the accuracy requested in many applications is rather still problematic, and needs the use of correcting procedures. In this paper we present a comparison of algorithms for retrieving SMC from ENVISAT ASAR images collected on two agricultural areas in Italy: Alessandria, in the Northern part, and Montespertoli, in Central Italy. SAR images were collected in 2003 and 2004 (Table I), together with ground data of soil and vegetation parameters. Table I – List of ENVISAT images collected on the Italian agricultural areas
Banking Crises and 'Japanization': Origins and Implications

Japan’s “two lost decades” perhaps represent an extreme example of a weak recovery from a financial crisis, and are now referred to as “Japanization. ” More recently, widespread stagnation in advanced economies in the wake of the global financial crisis led to fears that Japanization might spread to other countries. This study examines the dimensions of Japanization—including low trend growth, debt deleveraging, deflation and massive increases in government debt—and analyzes their possible causes—including inadequate macroeconomic policy responses, delayed banking sector restructuring, inadequate corporate investment, loss of industrial competitiveness, a slowdown in total factor productivity (TFP) growth due to excessive regulation and economic rigidities, and an aging society.
Research Note—Is Social Work Education a Form of Social Work Practice?

ABSTRACT The inclusion of social work education as a form of practice has been missing from the debates on the need for a unified definition of social work practice. This Research Note reports the findings from interviews with 20 social work educators who were asked whether social work education is a form of social work practice and were encouraged to elaborate on their response. The qualitative data were analyzed using thematic analysis and revealed five themes. The findings contribute to the debate on the need for clarification among social work authorities in shaping the definition of social work practice and the need to provide a clear stance on the extent to which social work education is a form of social work practice.
How employee turnover impacts social capital and performance of companies

Recently, The Wall Street Journal proclaimed there is a "War for Internet Talent" among companies in the Information and Communication Technology (ICT) sector. At the same time, talented employees often become entrepreneurial and establish their own startups. Thus, my research is motivated by these guiding questions: Which turnover patterns/trends can be observed in the ICT industry from a macro perspective (i.e., where does social and human capital flow)? To what extent can startup performance in this industry be explained by the social capital aggregated from the turnover history of its founders - that is, from the ties to former employers? Which employees are key resources in terms of their individual contributions to the aggregate social capital of their current employers? Do brokerage opportunities create turnover incentives for employees? As a first step to answering these questions, I aim to provide evidence that startup performance is not based exclusively on access to talent in the sense of individual human capital but is also determined by a social capital aspect resulting from their founder's career history. I apply social network analysis (SNA) combined with logistical regression on a large dataset of companies and people in the ICT sector to explore this topic.
Novel expression of resistin in rat testis: functional role and regulation by nutritional status and hormonal factors

Resistin, a recently cloned adipose-secreted factor, is primarily involved in the modulation of insulin sensitivity and adipocyte differentiation. However, additional metabolic or endocrine functions of this molecule remain largely unexplored. In this study, a series of experiments were undertaken to explore the potential expression, regulation and functional role of this novel adipocytokine in rat testis. Resistin gene expression was demonstrated in rat testis throughout postnatal development, with maximum mRNA levels in adult specimens. At this age, resistin peptide was immunodetected in interstitial Leydig cells and Sertoli cells within seminiferous tubules. Testicular expression of resistin was under hormonal regulation of pituitary gonadotropins and showed stage-specificity, with peak expression values at stages II-VI of the seminiferous epithelial cycle. In addition, testicular resistin mRNA was down-regulated by the selective agonist of PPARγ, rosiglitazone, in vivo and in vitro. Similarly, fasting and central administration of the adipocyte-derived factor, leptin, evoked a significant reduction in testicular resistin mRNA levels, whereas they remained unaltered in a model of diet-induced obesity. From a functional standpoint, resistin, in a dose-dependent manner, significantly increased both basal and choriogonadotropin-stimulated testosterone secretion in vitro. Overall, our present results provide the first evidence for the expression, regulation and functional role of resistin in rat testis. These data underscore a reproductive facet of this recently cloned molecule, which may operate as a novel endocrine integrator linking energy homeostasis and reproduction.
Cognitive development and educational attainment across the life span

In this thesis I explore two strands of research: in the first half I explore the effects of language learning on brain structure and cognitive function. In the second half I study to what extent educational attainment alter the rate of cognitive decline in old age. These different strands of research are united through the concept of brain plasticity, which is the brain’s ability to change its structural configuration in response to new experiences. In Study I we charted the neural underpinning of foreign language learning in a sample of younger adults. A total of 56 younger adults were randomized to either a 10-week beginner’s course in Italian or a control condition. For those studying Italian we found that grey-matter change in the right hippocampus was associated with how much time they spent practicing, rather than with how good they became suggesting that effort, rather than achieved proficiency, is what drives neuroplastic change. Study II presents the largest (to date) randomized trial looking into the causal effects of language learning as cognitive engagement in older age, specifically foreign language learning. 160 people between ages 65 and 75 were randomized to either an 11-week beginner’s course in Italian, or an 11-week relaxation training course. While we predicted that language learning would improve cognitive function, specifically associative memory, we found no evidence to support this hypothesis. Study III and IV address the question of whether or not educational attainment affects the rate of cognitive decline in old age. While it is clear that educational attainment is associated with level of cognitive function, we find no evidence that it alters the rate of decline in old age. Study III address this question using a novel statistical approach while Study IV presents a meta-analysis on the subject, arriving at similar conclusions. LIST OF SCIENTIFIC PAPERS I. Bellander, M. , Berggren, R. , Mårtensson, J., Brehmer, Y. , Wenger, E. , Li, TQ. , Bodammer, NC. , Shing, YL. , Werkle-Bergner, M. , Lövdén, M. (2016). Behavioral correlates of changes in hippocampal gray matter structure during acquisition of foreign vocabulary. NeuroImage, 131(205-213) II. Berggren, R. , Nilsson, J., Brehmer, Y. , Schmiedek, F. , Lövdén, M. (Under review). Foreign language learning in older age does not improve memory or intelligence: Evidence from a randomized controlled study. III. Berggren, R. , Nilsson, J., Lövdén, M. (2018). Education does not affect cognitive decline in aging: A Bayesian assessment of the association between education and change in cognitive performance. Frontiers in Psychology, 9:1138. IV. Seblova, D. , Berggren, R. , Lövdén, M. (Manuscript). Education and agerelated decline in episodic memory performance: systematic review and meta-analysis of longitudinal studies.
Research on the Method of Nonlinear Dimensionality Reduction for the Text of Laws and Regulations of Construction

Research on existing vector representation method of the text data and it is advantages or disadvantages and applicability of linear and nonlinear dimensionality reduction methods, the paper analysis the feature of laws and regulations of construction data, establishes the vector space model of the text data. Based on Riemann Surface Theory and Topology Theory, adopting the globe pole mapping method of space analytic geometry, forming a homeomorphism with the linear analytic function from the high-dimensional vector to the low one, and then realizing a corresponding mapping, maintained the topological structure of data before and after dimensionality reduction, at last, the results solve the neighbor problem of nonlinear dimensionality reduction for text mining effectively. Appling the method in the text data of laws and regulations of construction, it has obtained the projection in any two-or-three dimensional orthogonal and univocal direction, caparisoning with other research methods shows the validity of this method.
Detection Decoding Joint Adaptive Iterative Technique for MIMO System With Impulse Noise Interference

Multiple input multiple output (MIMO) techniques can improve the spectrum efficiency of a communication system significantly. Decision outputs are feedbacked as reference signal in minimum mean square error (MMSE) adaptive detection. When channel conditions change abruptly, especially if there is impulse noise, continuously abrupt errors may occur. Even if the channel conditions change better thereafter, the output signal can not be detected correctly. Detection decoding joint detection method is efficient to improve coded communication system performance. Because decoded data have lower bits error rate, the decoded data are then re-interleaved and reused as the reference signal in MMSE detection. This iterative algorithm can reduce the continuously abrupt errors. Simulation results show the effectiveness of this iterative method
Zero-shot object prediction and context modeling using semantic scene knowledge

This work will focus on the semantic relations between scenes and objects for visual object recognition. Semantic knowledge can be a powerful source of information especially in scenarios with less or no annotated training samples. These scenarios are referred to as zero-shot recognition and often build on visual attributes. Here, instead of attributes a more direct way is pursued, relating scenes and objects. The contribution of this paper is two-fold: First, it will be shown that scene knowledge can be an important cue for predicting objects in an unsupervised manner. This is especially useful in cluttered scenes where visual recognition may be difficult. Second, it will be shown that this information can easily be integrated as a context model for object detection in a supervised setting.
A HIERARCHICAL BAYESIAN APPROACH FOR SPATIAL TIME SERIES MODELING

Abstract Despite the fact that the amount of datasets containing long economic time series with a spatial reference has significantly increased during the years, the presence of integrated techniques that aim to describe the temporal evolution of the series while accounting for the location of the measurements and their neighboring relations is very sparse in the econometric literature. This paper shows how the Hierarchical Bayesian Space Time model presented by Wikle, Berliner and Cressie (Environmental and Ecological Statistics, l998) for temperature modeling, can be tailored to model relationships between variables that have both a spatial and a temporal reference. The first stage of the hierarchical model includes a set of regression equations (each one corresponding to a different location) coupled with a dynamic space-time process that accounts for the unexplained variation. At the second stage, the regression parameters are endowed with priors that reflect the neighboring relations of the locations under study; moreover, the spatio-temporal dependencies in the dynamic process for the unexplained variation are being established. Putting hyperpriors on previous stages’ parameters completes the Bayesian formulation, which can be implemented in a Markov Chain Monte Carlo framework. The proposed modeling strategy is useful in quantifying the temporal evolution in relations between economic variables and this quantification may serve for excess forecasting accuracy.
Auditory masking threshold estimation for broadband noise sources with application to speech enhancement

This paper addresses issues encountered in the use of an Auditory Masking Threshold (AMT) for speech enhancement and proposes an algorithm to improve AMT estimation for broadband noise sources. We determined that while AMT estimation is fairly accurate, and hence an enhancement scheme based on AMT can suppress audible noise to a greater extent for low frequency colored noise sources, the algorithm fails to converge to the clean speech AMT for broadband communication channel noise. We propose a new AMT estimation scheme and incorporate the proposed algorithm into a previously developed enhancement framework [2]. We evaluate our algorithm on a set of sentences obtained from the standard TIMIT database for (cid:13)at communications channel noise (FLN), and automobile highway noise (HWY) at 5 dB and 0 dB SNR levels, respectively. Evaluations were performed for 8 kHz and 16 kHz sampled speech and performance is measured with both objective and subjective assessment methods. The results show that the new AMT codebook based enhancement method is more e(cid:11)ective than traditional AMT methods. Also, that traditional AMT methods may not be as e(cid:11)ective for reduced bandwidth speech (4 kHz), or broadband interference, but that alternative AMT estimation methods can help improve convergence properties.
A new look of doping technique in BICM-ID

Doping technique was employed to remove the high error floor in conventional bit-interleaved coded modulation with iterative demapping and decoding (BICM-ID). This paper proposes a new look of the doping technique-BICM-ID with serial concatenated convolutional code (SCCC-BICM-ID). Unlike conventional doping decoding scheme which deems the doping decoder and the demapper as a whole doped demapper, we combine the doping code and the outer convolutional code together to form an SCCC, so that iterative demapping and decoding is performed between the demapper and the SCCC decoder. Extrinsic information transfer (EXIT) chart is used to analyze these two decoding schemes and reveals that they both can achieve near-capacity performance with no penalty of error floor. According to the results of EXIT analysis and BER simulations, SCCC-BICM-ID system can achieve the same or even better performance compared to the doping BICM-ID system with lower decoding complexity.
Experiences running a Web anonymising service

The research project "AN.ON - Anonymity online" focuses on developing and providing a Web anonymising service. This service provides anonymity and unobservability against external observers, the user's ISP and the operators of the service themselves. AN.ON is being promoted by the German Federal Ministry of Economic Affairs for three years (2001-2003). Main criteria for the design of the Web anonymising service are security, trustworthiness, performance and usability. Of utmost importance is legal compliance, especially with respect to data protection law. In the submitted paper the project partners, Dresden University of Technology resp. Freie Universitat Berlin and Independent Centre for Privacy Protection Schleswig-Holstein, Germany, describe technical background, legal topics, economic issues, socio-political side effects and practical experiences in developing and operating this Web anonymising service.
Sealing OS Processes to Improve Dependability and Security

On most modern operating systems, a process is a hardware-protected abstraction for executing potentially mutable code and data. Common features of processes include: dynamic code loading, dynamic code generation, access to cross-process shared memory, and a universal API. This paper argues that many of the dependability and security weaknesses of modern systems are exacerbated by this open process architecture. Moreover, this architecture impairs the ability of tools to analyze code statically, to improve its performance or dependability. By contrast, a sealed process architecture prohibits dynamic code loading, prohibits self-modifying code, prohibits shared memory, and replaces a universal API with a process-limited API. This paper describes an implementation of a sealed process architecture in the Singularity operating system, discusses its merits, and evaluates its impact. Among the benefits are: improved static program analysis, strong security guarantees, elimination of OS redundancies found in language runtimes such as the JVM and CLR, and better software engineering.
Preliminary Analysis of Hepatitis Data by Beam-wise Graph-Based Induction

Graph-Based Induction (GBI) extracts typical patterns from graph data by stepwise pair expansion (pairwise chunking). It is very efficient because of its greedy search strategy but at the same time it suffers from the incompleteness of search. Improvement is made on its search capability without imposing much computational complexity by 1) incorporating a beam search, 2) using a different evaluation function to extract patterns that are more discriminatory than those simply occurring frequently, and 3) adopting canonical labeling to enumerate identical patterns accurately. This new algorithm, now called Beam-wise GBI, B-GBI for short, was tested against the promoter dataset from UCI repository and shown successful in extracting discriminatory substructures. Effect of beam width on the number of discovered attributes and predictive accuracy was evaluated. The best result obtained by this approach was better than the previously best known result. B-GBI was then applied to a real-world data, Hepatitis dataset provided by Chiba University. Our very preliminary results indicate that B-GBI can actually handle graphs with a few thousands nodes and extract discriminatory patterns.
A New Templates Presentation and Extraction Method for Handwritten Digit Recognition

It is a diicult task to distinguish legible digits from unsure patterns in connected handwritten digit recognition due to ambiguous character segmentation. In this paper, we rst present a new template presentation scheme based on a distance-to-boundary distribution for connected handwritten digit recognition. A neural network approach is then presented to extract templates based on this new presentation scheme, and a evolutionary algorithm based optimization algorithm is applied to nd the global optimized templates. In our approach, a template is presented by the distribution map of pixel distances to the boundary(s) between the foreground and the background, instead of the shape of a digit. A rational B-spline surface with a set of control knots is adopted to present each template. With 10,426 training samples from NIST Special Database 3 and 1,000 templates, this approach can successful reject 90.7% of unsure patterns while achieves 96:4% correct classiication on isolated digits.
Analysis of effects of rebounds and aerodynamics for trajectory of table tennis ball

In this paper, we firstly analyze the effects of the rebounds and aerodynamics for trajectory of a table tennis ball. We firstly analyze the effect of the aerodynamics with a criterion of evaluation, where the half area of the table is considered as 9 divided areas. Furthermore, the drag and lift coefficients are identified by assuming that the rotational velocity is invalid during the ball flying. With the identified coefficients, the modeling errors of the table and racket are secondly verified by the criterion mentioned previously. Some conclusions are finally shown.
Grouping Entities in a Fleet by Community Detection in Network of Regression Models

This paper deals with grouping of entities in a fleet based on their behavior. The behavior of each entity is characterized by its historical dataset, which comprises a dependent variable, typically a performance measure, and multiple independent variables, typically operating conditions. A regression model built using this dataset is used as a proxy for the behavior of an entity. The validation error of the model of one unit with respect to the dataset of another unit is used as a measure of the difference in behavior between two units. Grouping entities based on their behavior is posed as a graph clustering problem with nodes representing regression models and edge weights given by the validation errors. Specifically, we find communities in this graph, having dense edge connections within and sparse connections outside. A way to assess the goodness of grouping and finding the optimum number of divisions is proposed. The algorithm and measures proposed are illustrated with application to synthetic data.