Miracle-dz/UniFAR-FTUs huggingface dataset:
A dynamic user adaptive combination strategy for hybrid movie recommendation

Movie recommendation is a very popular service in internet based movie related websites such as NetFlix, MovieLens. The performance of the recommendation plays the key role in the user experience. Existing works have shown that combining content based and collaborative filtering based algorithms is the best way for movie recommendation. Nevertheless, the performance of this hybrid algorithm is strongly depended on the strategy how to combine the basic pure algorithms. Existing works usually use a static combination strategy which may generate even worse performance for some users. To solve this problems, in this paper we propose a new item based hybrid algorithm that uses a dynamic user adaptive combination strategy. Besides, we also exploit the external open resources IMDB as the movie content data. Experiments on real datasets show that the dynamic user adaptive combination strategy can significantly enhance the performance of the recommendation and the external open resource IMDB is a very good information resource for recommendation.
Research of improved DV-Hop algorithm in coal mine monitoring application for WSNs

DV-Hop and its improved algorithms for WSNs are analyzed. It proposes IDV-Hop(Improved DV-Hop) based on the special circumstances of coal mine. In IDV-Hop, every beacon node only broadcasts information within the n-hop, which reduces high communication overhead for flooding in the whole network and improves system stability. The anchor nodes are all from the least number of m anchor nodes within the n-hop, which enhances positioning accuracy and meet highly the requirement of practical applications.
An Empirical Research on the Influence of Knowledge Customization Degree to Knowledge Transfer Performance

In this paper, the knowledge transfer between the organizations is analyzed from a new angle, namely knowledge customization, which not only expends the research area of the knowledge management study but also provides guide line for the managerial practice of the knowledge transfer. First, through analyzing, we conclude that it is necessary to introduce the conception of knowledge customization and also defined the meaning of this conception. Secondly, the empirical model is constructed on the basis of analyzing the relations among the study inclination of members, the demand of the work, the degree of the knowledge customization and the transfer performance of the final knowledge. Moreover, this empirical model is verified by the data collected from the survey. Based on the analyzing and the result of the model, the conclusion is made and the future direction of research is proposed.
Dimension Reduction on Hyperspectral Images

Although hyperspectral images contain much more information than regular RGB images, more than ninety percent of the variance can be explained by a small portion of the data. The goal of dimension reduction is to map high dimensional data into a lower dimension while preserving the main features of the original data. The dimension reduction codes are taken from Van Der Maaten’s matlab dimension reduction toolbox [1], except for FastICA which comes from [2]. The Urban and Indian Pines datasets we are working with can be obtained from the HyperCube [3] and MultiSpec [4] website, respectively.
Database Design of a PDM System for Research Institutions

On the background of developing the Product Data Management(PDM) system for vehicle powertrain integrated design, we found three problems to solve. The first is product and its technical parameters need to customize freely. It’s solved by defining code fields for product database table and parameter table. Second, the technical parameters of different levels overlap each other or the cause and effect relationship exists. The solution is storing one parameter in structured format and others in unstructured format. Third, design task needs to be dynamicly associated with its input parameters, output parameters, knowledge, tools, and the solution is introducing the Design Function as the carrier of data package. Base the database design, one PDM system was developed which provides a better tool for designing activity of the research institutions. In the paper, the relational database design scheme offer a new way of thinking for the database design of PDM system.
TWIN DEFICITS HYPOTHESIS AND HORIOKA-FELDSTEIN PUZZLE IN TRANSITION ECONOMIES

The article’s main objective is to investigate the empirical link between the fiscal balance and the current account (i.e. the twin deficits phenomenon). The article focuses on transition economies which are according to their different characteristics divided into three major groups, i.e. Central and Eastern Europe (CEE), Southern and Eastern Europe (SEE) and the Commonwealth of Independent States (CIS). In fact, the inconsistency between public sector instability and currency overvaluations which led to current account balance deterioration was denoted as one of the key determinants of the balance of payments (currency) crisis seen in transition economies like Czech Republic (1997) and Russia (1998). Moreover, the importance of the so- called Horioka-Feldstein puzzle in transition economies is examined in order to draw some conclusions about the regions’ integration with international capital markets. For this purpose, pooled cross-sectional and time-series techniques are used to characterize the properties of current account variations across selected groups of transition economies in the 1990-2003 period. The empirical results suggest that high budget deficits in transition countries have signaled relatively low level of substitutability between private and public savings, implying a relatively high correlation between fiscal and external imbalances. Accordingly, special emphasis should be paid to the fiscal policy shift in these economies. Indeed, the main element of the economic policy reversal in transition countries should involve a substantial reduction of fiscal deficits in the future in order to reduce the probability of a balance of payments (currency) crisis. Finally, the article provides some evidence of the existence of the Horioka-Feldstein puzzle in transition economies.
Migration Restrictions and Criminal Behavior: Evidence from a Natural Experiment

We estimate the causal effect of immigrants' legal status on criminal behavior exploiting exogenous variation in migration restrictions across nationalities driven by the last round of the European Union enlargement. Unique individual-level data on a collective clemency bill enacted in Italy five months before the enlargement allow us to compare the post-release criminal record of inmates from new EU member countries with a control group of pardoned inmates from candidate EU member countries. Difference-in-differences in the probability of re-arrest between the two groups before and after the enlargement show that obtaining legal status lowers the recidivism of economically motivated offenders, but only in areas that provide relatively better labor market opportunities to legal immigrants. We provide a search-theoretic model of criminal behavior that is consistent with these results.
An Empirical Bipolar Device Nonlinear Noise Modeling Approach for Large-Signal Microwave Circuit Analysis

An empirical bipolar transistor nonlinear noise model for the large-signal (LS) noise analysis of microwave circuits is described. The model is derived according to the charge-controlled nonlinear noise behavioral modeling approach, and includes nonlinearly controlled equivalent noise (EN) generators describing the low-frequency (LF) noise up-conversion encountered in LS RF operation. LS-modulated shot-noise sources and parametric LF noise in parasitic resistors are also taken into account for improved model accuracy. Details for the implementation of the proposed cyclostationary EN generators in the framework of a computer-aided design tool are presented. As an application example, a simplified version of the proposed nonlinear noise model for two GaInP-GaAs HBTs has been formulated and empirically characterized on the basis of both bias-dependent LF noise and phase-noise measurements. Measured and simulated noise performance of a monolithic voltage-controlled oscillator over a set of different operating conditions is shown for the validation of the proposed approach
Client-weighted medium-transparent MAC protocol for user-centric fairness in 60 GHz radio-over-fiber WLANs

We present a novel client-weighted mediumtransparent medium access control (CW-MT-MAC) protocol with enhanced fairness service delivery properties accompanied by a low-loss remote access unit (RAU) architecture for use in indoor, Gbps-capable, 60 GHz radio-over-fiber (RoF) wireless local area networks (WLANs). Our approach relies on incorporating a client-weighted algorithm (CWA) in the optical capacity allocation mechanism employed in the MT-MAC scheme, so as to distribute the available wavelengths to the different antenna units according to the total number of active users served by each individual antenna. The protocol's throughput and delay fairness characteristics are evaluated and validated through both simulations and analytic modeling for saturated network traffic operational conditions. In addition, extended simulation-based performance analysis for nonsaturated network conditions and for different end-user distributions, traffic loads, and available optical wavelengths at 1 Gbps data rates is presented. Our results confirm that complete throughput equalization can be achieved even for highly varying user population patterns when certain wavelength availability conditions are satisfied. At the same time, the presented scheme manages to equalize the average packet delays amongst packets generated by all RAUs while concurrently dropping the packet delay variation metric that is essential for quality of service delivery. Finally the proposed RAU design reduces insertion losses by almost 14 dB compared to RAU elements used in MT-MAC-compatible bus networks, extending in this way the number of supported RAUs by an order of magnitude and enabling the formation of extended-reach, high-speed RoF WLANs.
DEEP 1.4 GHz FOLLOW-UP OF THE STEEP SPECTRUM RADIO HALO IN A521

In a recent paper, we reported on the discovery of a radio halo with very steep spectrum in the merging galaxy cluster A521 through observations with the Giant Metrewave Radio Telescope. We showed that the steep spectrum of the halo is inconsistent with a secondary origin of the relativistic electrons and supports a turbulent acceleration scenario. At that time, due to the steep spectrum, the available observations at 1.4 GHz (archival NRAO–Very Large Array–VLA–CnB-configuration data) were not adequate to accurately determine the flux density associated with the radio halo. In this paper, we report the detection at 1.4 GHz of the radio halo in A521 using deep VLA observations in the D configuration. We use these new data to confirm the steep spectrum of the object. We consider A521 the prototype of a population of very steep spectrum halos. This population is predicted assuming that turbulence plays an important role in the acceleration of relativistic particles in galaxy clusters, and we expect it will be unveiled by future surveys at low frequencies with the LOFAR and LWA radio telescopes.
Full reuse maintenance process for reducing software degradation

It is known that during maintenance activities system quality tends to degrade. This work presents a field investigation carried out on two industrial projects with the aim of comparing the effectiveness of the "full reuse" maintenance process with an "iterative enhancement" one. The results of the work confirm the greater effectiveness of the first process in slowing down the degradation of software quality. Furthermore, through the analysis of both process and product metrics, we show that monitoring maintenance performances is a poor indicator of system quality degradation. In fact, when the reduction of maintenance performance becomes large, quality has degraded considerably and to a point that ordinary maintenance may no longer be considered.
Changes in molecular composition of rat medial prefrontal cortex synapses during adolescent development

Postnatal brain development continues throughout adolescence into young adulthood. In particular, synapse strengthening and elimination are prominent processes during adolescence. However, molecular data of this relatively late stage of synaptic development are sparse. In this study, we used iTRAQ (isobaric tag for relative and absolute quantification)‐based proteomics and electron microscopy to investigate the molecular composition of a synaptic membrane fraction from adolescent postnatal day (P)34 and P44 and adult (P78) rat medial prefrontal cortex. Differential expression of proteins was most prominent between early adolescence and young adulthood (35%, P34–P78), with an over‐representation of cell‐membrane proteins during adolescent development (between P34 and P44), and synaptic vesicle proteins between late adolescence and young adulthood (P44–P78). Indicative of the critical period of development, we found that, between P34 and P44, a substantial number of proteins was differentially expressed (14%), much more than during the period after adolescence, i.e. between P44 and P78 (5%). A striking observation was the developmental non‐stoichiometric regulation of distinct classes of proteins from the synaptic vesicle and the presynaptic release machinery. Electron microscopy demonstrated a small change in the number of docked vesicles between P34 and P44, but not in the total number of synaptic vesicles and in the size of the vesicle cluster. We conclude that the molecular composition of synapses, and more specifically the synaptic release machinery, of the medial prefrontal cortex changes drastically during adolescent development.
Current Account Dynamics and the Feldstein and Horioka Puzzle: the Case of Greece

In this paper we investigate the degree of integration of the Greek economy into international capital markets using the analytical framework proposed by Felstein-Horioka. We examine the time series properties of data on current account balance and national savings for the period 1960-2004. Structural breaks are explicitly taken into account on the basis of the historical evolution of the institutional framework that governs international transactions. The evidence suggests that the links of the Greek economy to international capital markets have significantly strengthened after its accession to the European Union. Furthermore, the empirical results add another piece of evidence - albeit small - to the literature on the Feldstein-Horioka puzzle, indicating that the Feldstein-Horioka puzzle does not hold for the Greek economy.
Kernel Dependent Functions in Nonparametric Regression with Fractional Time Series Errors kernel dependent function, bandwidth selection

This paper considers estimation of the regression function and its derivatives in nonparametric regression with fractional time series errors. We focus on investigating the properties of a kernel dependent function V (δ) in the asymptotic variance and finding closed form formula of it, where δ is the long-memory parameter. It is shown that V (δ) has a unified form for δ ∈ (−0.5, 0.5)\0 with V (0) := lim δ→0 V (δ) = R(K), the kernel constant for iid errors. General solution of V (δ) for polynomial kernels is given together with a few examples. It is also found, e.g. that the Uniform kernel is no longer the minimum variance one by strongly antipersistent errors and that, for a fourth order kernel, V (δ) at some δ > 0 is clearly smaller than R(K). The results are used to develop a general data-driven algorithm. Data examples illustrate the practical relevance of the approach and the performance of the algorithm.
Morphometry of in vivo human white matter association pathways with diffusion‐weighted magnetic resonance imaging

The precise characterization of cortical connectivity is important for the understanding of brain morphological and functional organization. Such connectivity is conveyed by specific pathways or tracts in the white matter. Diffusion‐weighted magnetic resonance imaging detects the diffusivity of water molecules in three dimensions. Diffusivity in anisotropic in oriented tissues such as fiber tracts. In the present study, we used this method to map (in terms of orientation, location, and size) the “stem” (compact portion) of the principal association, projection, and commissural white matter pathways of the human brain in vivo, in 3 normal subjects. In addition, its use in clinical neurology is illustrated in a patient with left inferior parietal lobule embolic infarction in whom a significant reduction in relative size of the stem of the left superior longitudinal fasciculus was observed. This represents an important method for the characterization of major association pathways in the living human that are not discernible by conventional magnetic resonance imaging. In the clinical domain, this method will have a potential impact on the understanding of the diseases that involve white matter such as stroke, multiple sclerosis, amyotrophic lateral sclerosis, head injury, and spinal cord injury.
GMM and OLS Estimation and Inference for New Keynesian Phillips Curve

This paper considers estimation situations where identification, endogeneity and non-spherical regression error problems are present. Instead of always using GMM despite weak instruments to solve the endogeneity, it is possible to first check whether endogeneity is serious enough to cause inconsistency in the particular problem at hand. We show how to use Maximum Entropy bootstrap (meboot) for nonstationary time series data and check `convergence in probability' and `almost sure convergence' by evaluating the proportion of sample paths straying outside error bounds as the sample size increases. The new Keynesian Phillips curve (NKPC) ordinary least squares (OLS) estimation for US data finds little endogeneity-induced inconsistency and that GMM seems to worsen it. The potential `lack of identification' problem is solved by replacing the traditional pivot which divides an estimate by its standard error by the Godambe pivot, as explained in Vinod (2008) and Vinod (2010), leading to superior confidence intervals for deep parameters of the NKPC model.
Long memory in the volatility of the Australian All Ordinaries Index and the Share Price Index futures

This paper tests for long memory in the volatility of the All Ordinaries Index and its Share Price Index (SPI) futures. This has important implications for those agents concerned with the long term volatility in these markets. We use daily data and a short span of high frequency data to estimate the fractional differencing parameter, examine the fit of the implied autocorrelation function, and calculate the modified R/S and KPSS test statistics. All procedures support the existence of long memory in volatility in both markets except the KPSS test on the index using daily data. We argue that this is due to the low power of the KPSS test.
Translating SNOMED CT Terminology into a Minor Language

This paper presents the first attempt to semi-automatically translate SNOMED CT (Systematized Nomenclature of Medicine ‐ Clinical Terms) terminology content to Basque, a less resourced language. Thus, it would be possible to build a new clinical healthcare terminology for Basque. We have designed the translation algorithm and the first two phases of the algorithm that feed the SNOMED CT’s Terminology content, have been implemented (it is composed of four phases). The goal of the translation is twofold: the enforcement of the use of Basque in the bio-sanitary area and the access to a rich multilingual resource in our language.
Contrast enhancement for images of raised characters on region of interest

Raised or indented characters are widely used for recording the product information in the industrial field. However, images of such characters are of poor contrast because the characters have the same color and material as the background. It is this problem that makes recognition of such characters is difficult than that of conventional optical characters. To address this issue, the aim of this work is to investigate a contrast enhancement method applicable for raised or indented characters by carrying out an independent study on the illumination factor. Firstly, the illumination model of raised character is analyzed. Then, four different algorithms are introduced and the experiment was carried out with images of the raised characters pressed on metal label. Experiment results prove that homomorphic filtering is the most suitable contrast enhancement algorithm for raised or indented characters.
Speaker normalization through constrained MLLR based transforms

In this paper, a novel speaker normalization method is presented and compared to a well known vocal tract length normalization method. With this method, acoustic observations of training and testing speakers are mapped into a normalized acoustic space through speaker-specific transformations with the aim of reducing inter-speaker acoustic variability. For each speaker, an affine transformation is estimated with the goal of reducing the mismatch between the acoustic data of the speaker and a set of target hidden Markov models. This transformation is estimated through constrained maximum likelihood linear regression and then applied to map the acoustic observations of the speaker into the normalized acoustic space. Recognition experiments made use of two corpora, the first one consisting of adults’ speech, the second one consisting of children’s speech. Performing training and recognition with normalized data resulted in a consistent reduction of the word error rate with respect to the baseline systems trained on unnormalized data. In addition, the novel method always performed better than the reference vocal tract length normalization method.
Firm-Specific Capital, Nominal Rigidities and the Business Cycle

This paper formulates and estimates a three-shock US business cycle model. The estimated model accounts for a substantial fraction of the cyclical variation in output and is consistent with the observed inertia in inflation. This is true even though firms in the model reoptimize prices on average once every 1.8 quarters. The key feature of our model underlying this result is that capital is firm-specific. If we adopt the standard assumption that capital is homogeneous and traded in economy-wide rental markets, we find that firms reoptimize their prices on average once every 9 quarters. We argue that the micro implications of the model strongly favor the firm-specific capital specification.