Miracle-dz/UniFAR-FTUs huggingface dataset:
Intelligent systems for mixing multichannel audio

Multichannel signal processing techniques are usually concerned with extracting information about sources from several received signals. In this paper, we describe an emerging field of multichannel audio signal processing where the inter-channel relationships are exploited in order to manipulate the multichannel content. Applications to real-time, automatic audio production are described and the necessary technologies and the architecture of such systems are presented. The current state of the art is reviewed, and directions of future research are also discussed.
Experiment study of energy transmission by acoustic wave in a metal plate

In this paper, a 2D axisymmetric model was built to observe the acoustic field and electric potential distributions during the energy transmission process from a piezoelectric layer to a metal plate. The effect of dimension of the piezoelectric transducer on the energy transmission is compared and analyzed by using the COMSOL multiphysics. Then, an experimental platform is instituted to verify the feasibility of the method of energy transmission by acoustic wave through a metal plate. Based on the finite element simulation and experimental test, it is found that the power conversion efficiency is related to the size of the transducer, the thickness of the metal plate, and other parameters. It is shown by experimental measurement that the conversion efficiency could be reached about 30%.
Variable density spatial data clustering

This paper presents an effective clustering method which can detect embedded and nested clusters over variable density space. The proposed method, VDSC uses a density based approach for detecting clusters of arbitrary shapes, sizes and densities. VDSC was compared with several other comparable algorithms and the experimental results show that our method could detect all clusters effectively.
M i POS-the Mote Indoor Positioning System ∗

In the past few years, there have been huge research efforts into ubiquitous and context aware platforms that offer a user a custom level of service based on some known local parameters. The utility of such systems is greatly enhanced if a physical locational area can be determined. Recently, hybrid devices have been developed combining low power microcontrollers with short range FM radio transceivers. Some location identification work has been carried out with these systems such as the Matrix Pencil approximation technique[8], however most of these all provide information for an ideal square area with no RF obstructions. Here we present MiPOS, a scalable locationing system based on the MICA mote[11] family of devices. The design goal of MiPOS is to provide a low-power, scalable, distributed locationing system suited to an indoor (office) environment. During the presentation of this paper we will highlight solutions in the areas of security, radio and network management and power awareness for a hybrid context aware wearable locationing device.
Efficient Online Algorithms for the Polygonal Approximation of Trajectory Data

The paper deals with the problem of how most efficiently to represent trajectory data with a piecewise -- constant velocity model of the object movement. Firstly, we experimented with fast and efficient offline algorithms based on heuristic and optimal algorithms for the approximation of planar and spatial curves for a given constraint on the maximum of the approximation error. Secondly, we developed efficient online algorithm for the approximation of trajectories adaptive to the size of buffer. The online algorithm can be successfully used to reduce spatiotemporal data and multidimensional signals.
Expectations, Communication and Monetary Policy in Turkey

This study analyzes the behavioral aspects of inflation expectations in Turkey by utilizing data from a panel of survey respondents, and draws implications for the formulation of monetary policy and communication strategy. Our results lend support to the view that the survey respondents take the inflation targets and the official forecasts of the Central Bank of Turkey into account in forming their expectations. We show that inflation expectations during the rapid disinflation episode of 2002-2005 were firmly anchored by the announced targets. Yet, the weight attached to past inflation and the sensitivity of inflation expectations to variables such as exchange rates and the risk premia seem to have increased in recent years. We also show that there is significant heterogeneity in the expectation formation process. Real sector attaches a greater weight to past inflation than the financial sector, suggesting that more effort should be devoted to communicating quantitative policy objectives to the real sector. Moreover, the financial sector appears to be relatively more sensitive to variations in volatile variables such as exchange rates, risk premium and short-term inflation surprises, implying that communication to financial markets should keep emphasizing the medium-term policy perspective of the monetary policy.
Overexpression of WsSGTL1 Gene of Withania somnifera Enhances Salt Tolerance, Heat Tolerance and Cold Acclimation Ability in Transgenic Arabidopsis Plants

Background Sterol glycosyltrnasferases (SGT) are enzymes that glycosylate sterols which play important role in plant adaptation to stress and are medicinally important in plants like Withania somnifera. The present study aims to find the role of WsSGTL1 which is a sterol glycosyltransferase from W. somnifera, in plant’s adaptation to abiotic stress. Methodology The WsSGTL1 gene was transformed in Arabidopsis thaliana through Agrobacterium mediated transformation, using the binary vector pBI121, by floral dip method. The phenotypic and physiological parameters like germination, root length, shoot weight, relative electrolyte conductivity, MDA content, SOD levels, relative electrolyte leakage and chlorophyll measurements were compared between transgenic and wild type Arabidopsis plants under different abiotic stresses - salt, heat and cold. Biochemical analysis was done by HPLC-TLC and radiolabelled enzyme assay. The promoter of the WsSGTL1 gene was cloned by using Genome Walker kit (Clontech, USA) and the 3D structures were predicted by using Discovery Studio Ver. 2.5. Results The WsSGTL1 transgenic plants were confirmed to be single copy by Southern and homozygous by segregation analysis. As compared to WT, the transgenic plants showed better germination, salt tolerance, heat and cold tolerance. The level of the transgene WsSGTL1 was elevated in heat, cold and salt stress along with other marker genes such as HSP70, HSP90, RD29, SOS3 and LEA4-5. Biochemical analysis showed the formation of sterol glycosides and increase in enzyme activity. When the promoter of WsSGTL1 gene was cloned from W. somnifera and sequenced, it contained stress responsive elements. Bioinformatics analysis of the 3D structure of the WsSGTL1 protein showed functional similarity with sterol glycosyltransferase AtSGT of A. thaliana. Conclusions Transformation of WsSGTL1 gene in A. thaliana conferred abiotic stress tolerance. The promoter of the gene in W.somnifera was found to have stress responsive elements. The 3D structure showed functional similarity with sterol glycosyltransferases.
The challenge of attracting graduates - a strategic process in people resourcing: To explore, identify and understand the issues associated with graduate attraction facing the graduate employers in Ireland, in the current economic situation.

Purpose – Attracting the best from the ever-expanding pool of talent is an intense and demanding process (Branine 2008). A poor recruitment experience is not only an expensive financial damage (Cennamo and Gardner 2008) but also a barrier to the organization’s performance and future. The aim of this study is to congregate and provide the essential information needed by organizations to attract graduates. The research extends on the past study and identifies the attributes necessary to become an attractive employer in a wide choice of labour market context by examining the outlooks and attitudes of employers towards graduates. It intends to provide an insight into the differences in the organizational attributes of two generations, Gen Y and Gen Z. Gender comparison in the orientations and perceptions of the graduates on the labour market will help to break the conventional views of employers around traditional career management. Design/methodology – The study undertakes a mixed method approach involving two phases. In phase one, interviews with talent management specialists who directly recruit and supervise graduates from two different organizations, as well as focus group with the existing graduate employees were carried out. A shortlist of organizational attributes and graduate expectations was built into a survey of undergraduates, in phase two. Findings – The findings indicated that there was a level of mismatch in the perceptions of employers and graduate employees or students. Organizations struggle to attract talent due to sector preferences of graduates. Lack of competency, cultural compatibility and leadership skills, in undergraduates are the biggest challenges to talent managers. Although gender differences in the attractiveness of the attributes of the organizations seem to be diminishing, generational differences exist, which needs in-depth exploration by the employers before designing the attraction strategy. Implications of the study - It is believed that this research will provide a means of helping organizations and HR specialists to understand and adjust to changing career prospects and work patterns of graduates, especially the technology generation Gen Z, in the contemporary labour market.
Extracting Generalized Semantic Roles from Corpus

One of the oldest constructs of linguistic theory is semantic role. Automatic extraction of semantic roles in a sentence is a movement towards semantic processing of texts which has been the focus of attention in recent years. Extraction of semantic roles from a text contains some essential parts. Recognition of verb(s) of the sentence, recognition of noun phrases and their heads, and labeling the role of each phrase in the sentence as a semantic argument of verb are general parts of a system that does this task. There is a wide variety of definitions for semantic roles from verb specific roles to some general roles known as thematic roles, This paper focuses on a generalization of thematic roles called proto-roles or generalized semantic roles which includes two roles; actor and undergoer. In this paper we extract proto-roles in a Persian sentence exploiting POS tags. We use Peykareh as our input corpus and apply a rule based approach to extract actor and undergoer of verb(s).
Evolution of the Low-Energy Photon Spectra in Gamma-Ray Bursts

We report evidence that the asymptotic low-energy power-law slope α (below the spectral break) of BATSE gamma-ray burst (GRB) photon spectra evolves with time rather than remaining constant. We find that a high degree of positive correlation exists between the time-resolved spectral break energy Epk and α. In samples of 18 “hard-to-soft” and 12 “tracking” pulses, evolution of α was found to correlate with that of the spectral break energy Epk at the 99.7% and 98% confidence levels, respectively. We also find that in the flux rise phase of hard-to-soft pulses, the mean value of α is often positive, and in some bursts the maximum value of α is consistent with a value > +1. BATSE burst 3B 910927, for example, has an αmax equal to 1.6 ± 0.3. These findings challenge GRB spectral models in which α must be negative or remain constant.
Covariance Structure Maximum-Likelihood Estimates in Compound Gaussian Noise: Existence and Algorithm Analysis

Recently, a new adaptive scheme [Conte (1995), Gini (1997)] has been introduced for covariance structure matrix estimation in the context of adaptive radar detection under non-Gaussian noise. This latter has been modeled by compound-Gaussian noise, which is the product c of the square root of a positive unknown variable tau (deterministic or random) and an independent Gaussian vector x, c=radictaux. Because of the implicit algebraic structure of the equation to solve, we called the corresponding solution, the fixed point (FP) estimate. When tau is assumed deterministic and unknown, the FP is the exact maximum-likelihood (ML) estimate of the noise covariance structure, while when tau is a positive random variable, the FP is an approximate maximum likelihood (AML). This estimate has been already used for its excellent statistical properties without proofs of its existence and uniqueness. The major contribution of this paper is to fill these gaps. Our derivation is based on some likelihood functions general properties like homogeneity and can be easily adapted to other recursive contexts. Moreover, the corresponding iterative algorithm used for the FP estimate practical determination is also analyzed and we show the convergence of this recursive scheme, ensured whatever the initialization.
Saliency detection based on proto-objects and topic model

This paper proposes a novel computational framework for saliency detection, which integrates the saliency map computation and proto-objects detection. The proto-objects are detected based on the saliency map using latent topic model. The detected proto-objects are then utilized to improve the saliency map computation. Extensive experiments are performed on two publicly available datasets. The experimental results show that the proposed framework outperforms the state-of-art methods.
Automatic Evaluation of Organized Basketball Activity using Bayesian Networks

In this article the trajectory-based evaluation of multi-player basketball activity is addressed. The organized basketball activity consists of a set of key elements and their temporal relations. The activity evaluation is performed by analyzing individually each of them and the ﬁnal reasoning about the activity is achieved using the Bayesian network. The network structure is obtained automatically from the activity template which is a standard tool used by the basket-ball experts. The experimental results suggest that our approach can successfully evaluate the quality of the observed activity.
Gait Recognition Considering Directions of Walking

Studies on gait recognition are mostly based on the assumption that walking direction is parallel to the camera, and the person's side view is extracted. Walking direction has becoming one of the gait recognition challenge problems. In this paper we explore gait recognition considering any directions of walking which is not definitely parallel to the camera. We propose a novel approach to computing the walking direction and extracting features by employing a human model. Furthermore, a support vector machine (SVM) is performed allowing us to investigate and evaluate the recognition power of any walking directions. We applied our method to the real human walking video data, and achieved high recognition rate. Our approach finds out how changes in walking direction affect gait parameters in terms of recognition performance. As it is entirely based on human gait, our approach is robust to different type of clothes and different walking directions
On the first $n$ strongly compact cardinals

Using techniques of Kimchi and Magidor, we generalize an earlier result and show that it is relatively consistent for the first n strongly compact cardinals to be somewhat supercompact yet not fully supercompact. The class of strongly compact cardinals is, without a doubt, one of the most peculiar in the entire theory of large cardinals. As is well known, the class of strongly compact cardinals suffers from a severe identity crisis. Magidor's fundamental result of [Ma] shows that it is consistent for the least strongly compact cardinal to coincide with either the least measurable or the least supercompact cardinal. The result of [Al] shows that it is consistent for the least strongly compact cardinal to be somewhat supercompact although not fully supercompact. The result of Kimchi and Magidor [KM] shows that it is consistent for the class of strongly compact cardinals to coincide with the class of supercompact cardinals (except at limit points where Menas' result [Me] shows that such a coincidence may not occur) or for the first n for n £ œ strongly compact cardinals to coincide with the first n measurable cardinals. The purpose of this paper is to show that matters can be muddled still further. Specifically, we generalize the result of [Al] using the methods of [KM] and prove the following Theorem. Let V \= "K = {kx , . , k„} with kx < k2 < ■■■ < k„ the first n supercompact cardinals". For each k g K, let <pK be a formula in the language of set theory which defines an increasing ~L2 function from the ordinals to the ordinals which, in addition, has the following properties: (a) <pK is preserved at and above k when forcing with a cardinal preserving partial ordering of size k, i.e., for P £ V a cardinal preserving partial ordering, \P\ = K, a>K, Vt "0 = <pK(a) "iff Vp \= "Ô = tpK(a) ". (b) If for any model M of ZFC, M \= "a < ß and ß is q>K(ß) supercompact", then <pK(ot) < ß ■ (c) If for any model M of ZFC, M \= "ô is <pKi(S) supercompact, ô is (pKj(ô) supercompact, and i < j ", then g>Ki(S) > <pKj(S). There is then a partial ordering P so that for each k £ K, Vp 1= " k is Received by the editors March 14, 1991 and, in revised form, November 29, 1993. 1991 Mathematics Subject Classification. Primary 03E35, 03E55. The research for this paper was partially supported by PSC-CUNY Grants 661371 and 662341 and by a salary grant from Tel Aviv University. ©1995 American Mathematical Society
BRIDEMAID: An Hybrid Tool for Accurate Detection of Android Malware

This paper presents BRIDEMAID, a framework which exploits an approach static and dynamic for accurate detection of Android malware. The static analysis is based on n-grams matching, whilst the dynamic analysis is based on multi-level monitoring of device, app and user behavior. The framework has been tested against 2794 malicious apps reporting a detection accuracy of 99,7% and a negligible false positive rate, tested on a set of 10k genuine apps.
Design considerations for view interpolation in a 3D video coding framework

A 3D video stream typically consists of a set of views capturing simultaneously the same scene. For an efficient transmission of the 3D video, a compression technique is required. In this paper, we describe a coding architecture and appropriate algorithms that enable the compression and reconstruction of views at the decoder. We explore the concept of predicting views in order to reduce transmission bandwidth, and add a correction to maintain sufficient accuracy. The correction contains occlusion data to cover complicated situations in 3D scenes. Additionally, we present experimental results for occlusion handling, performing a more accurate synthesis of views for the rendering on a multi view display.
Topological Structure of Urban Street Networks from the Perspective of Degree Correlations

Many complex networks demonstrate a phenomenon of striking degree correlations: that is, a node tends to link to other nodes with similar (or dissimilar) degrees. From the perspective of degree correlations, in this paper we attempt to characterize topological structures of urban street networks. We adopted six urban street networks (three European and three North American), and converted them into network topologies in which nodes and edges represent individual streets and street intersections, respectively, and compared the network topologies with three reference network topologies (biological, technological, and social). The urban street network topologies (with the exception of Manhattan) showed a consistent pattern that distinctly differs from the three reference networks. The topologies of urban street networks lack striking degree correlations in general. Through reshuffling the network topologies towards, for example, maximum or minimum degree correlations while retaining the initial degree distributions, we found that all the surrogate topologies of the urban street networks, as well as the reference ones, tended to deviate from small-world properties. This implies that the initial degree correlations do not have any positive or negative effect on the networks' performance or functions.
Efficient Shadow Removal Using Subregion Matching Illumination Transfer

This paper proposes a new shadow removal approach for input single natural image by using subregion matching illumination transfer We first propose an effective and automatic shadow detection algorithm incorporating global successive thresholding scheme and local boundary refinement. Then we present a novel shadow removal algorithm by performing illumination transfer on the matched subregion pairs between the shadow regions and non‐shadow regions, and this method can process complex images with different kinds of shadowed texture regions and illumination conditions. In addition, we develop an efficient shadow boundary processing method by using alpha matte interpolation, which produces seamless transition between the shadow and non‐shadow regions. Experimental results demonstrate the capabilities of our algorithm in both the shadow removal quality and performance.
ZYX-A Multimedia Document Model for Reuse and Adaptation of Multimedia Content

Advanced multimedia applications require adequate support for the modeling of multimedia content by multimedia document models. More and more this support calls for not only the adequate modeling of the temporal and spatial course of a multimedia presentation and its interactions, but also for the partial reuse of multimedia documents and adaptation to a given user context. However, our thorough investigation of existing standards for multimedia document models such as HTML, MHEG, SMIL, and HyTime leads to us the conclusion that these standard models do not provide sufficient modeling support for reuse and adaptation. Therefore, we propose a new approach for the modeling of adaptable and reusable multimedia content, the Z/sub Y/X model. The model offers primitives that provide-beyond the more or less common primitives for temporal, spatial, and interaction modeling-a variform support for reuse of structure and layout of document fragments and for the adaptation of the content and its presentation to the user context. We present the model in detail and illustrate the application and effectiveness of these concepts by samples taken from our Cardio-OP application in the domain of cardiac surgery. With the Z/sub Y/X model, we developed a comprehensive means for advanced multimedia content creation: support for template-driven authoring of multimedia content and support for flexible, dynamic composition of multimedia documents customized to the user's local context and needs. The approach significantly impacts and supports the authoring process in terms of methodology and economic aspects.