Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Species of the Basal “Kangaroo” Balbaroo and a Re-Evaluation of Stem Macropodiform Interrelationships

Exceptionally well-preserved skulls and postcranial elements of a new species of the plesiomorphic stem macropodiform Balbaroo have been recovered from middle Miocene freshwater limestone deposits in the Riversleigh World Heritage Area of northwestern Queensland, Australia. This constitutes the richest intraspecific sample for any currently known basal “kangaroo”, and, along with additional material referred to Balbaroo fangaroo, provides new insights into structural variability within the most prolific archaic macropodiform clade – Balbaridae. Qualitative and metric evaluations of taxonomic boundaries demonstrate that the previously distinct species Nambaroo bullockensis is a junior synonym of B. camfieldensis. Furthermore, coupled Maximum Parsimony and Bayesian phylogenetic analyses reveal that our new Balbaroo remains represent the most derived member of the Balbaroo lineage, and are closely related to the middle Miocene B. camfieldensis, which like most named balbarid species is identifiable only from isolated jaws. The postcranial elements of Balbaroo concur with earlier finds of the stratigraphically oldest balbarid skeleton, Nambaroo gillespieae, and suggest that quadrupedal progression was a primary gait mode as opposed to bipedal saltation. All Balbaroo spp. have low-crowned bilophodont molars, which are typical for browsing herbivores inhabiting the densely forested environments envisaged for middle Miocene northeastern Australia.
Excess Winter Mortality and Cold Temperatures in a Subtropical City, Guangzhou, China

Background A significant increase in mortality was observed during cold winters in many temperate regions. However, there is a lack of evidence from tropical and subtropical regions, and the influence of ambient temperatures on seasonal variation of mortality was not well documented. Methods This study included 213,737 registered deaths from January 2003 to December 2011 in Guangzhou, a subtropical city in Southern China. Excess winter mortality was calculated by the excess percentage of monthly mortality in winters over that of non-winter months. A generalized linear model with a quasi-Poisson distribution was applied to analyze the association between monthly mean temperature and mortality, after controlling for other meteorological measures and air pollution. Results The mortality rate in the winter was 26% higher than the average rate in other seasons. On average, there were 1,848 excess winter deaths annually, with around half (52%) from cardiovascular diseases and a quarter (24%) from respiratory diseases. Excess winter mortality was higher in the elderly, females and those with low education level than the young, males and those with high education level, respectively. A much larger winter increase was observed in out-of-hospital mortality compared to in-hospital mortality (45% vs. 17%). We found a significant negative correlation of annual excess winter mortality with average winter temperature (rs=-0.738, P=0.037), but not with air pollution levels. A 1 °C decrease in monthly mean temperature was associated with an increase of 1.38% (95%CI:0.34%-2.40%) and 0.88% (95%CI:0.11%-1.64%) in monthly mortality at lags of 0-1 month, respectively. Conclusion Similar to temperate regions, a subtropical city Guangzhou showed a clear seasonal pattern in mortality, with a sharper spike in winter. Our results highlight the role of cold temperature on the winter mortality even in warm climate. Precautionary measures should be strengthened to mitigate cold-related mortality for people living in warm climate.
A robust blind image watermarking based on Double Haar Wavelet Transform (DHWT)

2MAM Group of Institutions, Siruganur, Tiruchirappalli 621 105, India Received 18 November 2011; revised 19 March 2012; accepted 21 March 2012 This study proposes a blind watermarking algorithm based on Double Haar Wavelet Transform (DHWT) for copyright protection of digital images. Watermark embedding is performed in wavelet transform domain. DHWT is applied to the original cover image and binary watermark. Singular value decomposition (SVD) is applied on selected subband of cover image and binary watermark. Eigen values of selected subband of cover image are replaced by Eigen values of selected subband of binary watermark, which are multiplied with an appropriate strength factor. Proposed algorithm achieved very high imperceptibility, evidenced by high PSNR value for gray scale images, and produced very high robustness against image processing attacks.
Digital optical signal processing for telecommunication applications

Optical packet switching has received considerable attention over the last few years. In this paper we discus how optical signal processing can play a role in photonic packet routing. Two examples are given. Firstly we discuss ultrafast wavelength switching at 160 Gbit/s in a single semiconductor optical amplifier. Secondly, an integrated photonic flip-flop is discussed. Finally a discussion is given about potential opportunities and limitations of optics in packet switched nodes.
Global Fixed Capital Investment by Multinational Firms

We develop and test a model of the simultaneous determination of global gross fixed capital investments by multinational firms. We integrate a model of multi‐product firms choosing optimal manufacturing locations with a model of dynamic investment optimization. Firms adjust capital stocks in each location in accordance with the expected marginal profitability of capital. Analysis of 1504 fixed capital investment decisions by Japanese multinational firms confirms the prediction that investment is determined not only by total factor productivity, effective demand, and wage levels in the host country, but also by wage levels in other countries in which the firm operates.
Automatic head pose estimation using randomly projected dense SIFT descriptors

In this paper, we propose an automatic method for determining the head pose from a given face image. The face image is divided into a regular grid and a representation of the image is obtained by extracting dense SIFT descriptors from its grid points. Random Projection (RP) is then applied to reduce the dimension of the concatenated SIFT descriptor vector. Classification and regression using Support Vector Machine (SVM) are combined in order to obtain an accurate estimate of the head pose. The advantage of the proposed approach is that it does not require facial feature points such as eye corners, mouth corners and the nose tip to be extracted from the input face image as in many other methods. Experimental results are presented to demonstrate the effectiveness of the approach.
Backdating and Directors Incentives : Greed or Reputation ?

This paper investigates how directors’incentives play a role in the occurrences of firms’backdating employee stock options. Particularly, we examine directors’option compensation, independence of the audit and compensation committees, board size and board independence. Stock options granted to directors are supposed to provide incentives to directors to guard the firm from engaging in shareholder value destroying activities. However, “greed”might drive directors with more wealth tied up in stock options to pursue activities that enhance their personal wealth. Backdating is one of the practices that was recently discovered to be used by many firms. We document a positive association between directors’option compensation and the likelihood that firms backdate their employee stock options.
Analyzing visual attention during whole body interaction with public displays

While whole body interaction can enrich user experience on public displays, it remains unclear how common visualizations of user representations impact users' ability to perceive content on the display. In this work we use a head-mounted eye tracker to record visual behavior of 25 users interacting with a public display game that uses a silhouette user representation, mirroring the users' movements. Results from visual attention analysis as well as post-hoc recall and recognition tasks on display contents reveal that visual attention is mostly on users' silhouette while peripheral screen elements remain largely unattended. In our experiment, content attached to the user representation attracted significantly more attention than other screen contents, while content placed at the top and bottom of the screen attracted significantly less. Screen contents attached to the user representation were also significantly better remembered than those at the top and bottom of the screen.
Mainstream university pedagogy in feminist perspective

ABSTRACT This article analyses university pedagogy by contrasting mainstream pedagogy and feminist pedagogical thought. The data consist of two textbooks, and we investigate what kinds of teaching, learning and knowledge the textbooks construct and what kinds of student and teacher positions they suggest. The inquiry shows that learning in the textbooks is seen as a strictly defined, hierarchical process and that ideal teaching stresses methods over content. The power of knowledge is not discussed, nor are gender, sexuality and other differences. Academics are seen as professional teachers who master teaching methods, and students are framed as customers. An assumed human sameness, marketisation of education, emphasis on vocational benefit and ‘pathos of the new’ were found to be themes guiding mainstream pedagogy. We suggest that feminist pedagogy can offer an alternative approach, one enabling a critical analysis of the power of knowledge and an awareness of differences among students.
Lexical Acquisition in the Presence of Noise and Homonymy

This paper conjectures a computational account of how children might learn the meanings of words in their native language. First, a simplified version of the lexical acquisition task faced by children is modeled by a precisely specified formal problem. Then, an implemented algorithm for solving this formal problem is presented. Key advances of this algorithm over previously proposed algorithms are its ability to learn homonymous word senses in the presence of noisy input and its ability to scale up to problems of the size faced by real children.
Tandem representations of spectral envelope and modulation frequency features for ASR

We present a feature extraction technique for automatic speech recognition that uses Tandem representation of short-term spectral envelope and modulation frequency features. These features, derived from sub-band temporal envelopes of speech estimated using frequency domain linear prediction, are combined at the phoneme posterior level. Tandem representations derived from these phoneme posteriors are used along with HMM based ASR systems for both small and large vocabulary continuous speech recognition (LVCSR) tasks. For a small vocabulary continuous digit task on the OGI Digits database, the proposed features reduce the word error rate (WER) by 13 % relative to other feature extraction techniques. We obtain a relative reduction of about 14 % in WER for an LVCSR task using the NIST RT05 evaluation data. For phoneme recognition tasks on the TIMIT database these features provide a relative improvement of 13% compared to other techniques.
A Framework for Individual Cognitive Performance Assessment in Real-time for Elderly Users

Changing cognitive performance in human elderly users requires a real-time assessment of current performance to provide appropriate, i.e. adaptive, assistance without bothering them. In the presented approach, the assessment of cognitive performance is done by simulating the user’s cognitive functions through a computational cognitive model that is highly individualized for the specific user. The behavior of this model is evaluated with respect to the current cognitive performance by employing computerized psychological tests that allow a realtime assessment of cognitive performance with respect to a range of cognitive functions. By doing this, a realtime assessment is possible without involving the user in explicit performance tests.
Systematization of methods and ways of personnel analysis and evaluation in an educational organization

This article considers and systematizes the existing methods, types, techniques and ways of personnel analysis and evaluation and presents recommendations on their application in the practice of personnel management in an educational organization. The information obtained through the evaluation procedures significantly expands and qualitatively enriches the personnel database and allows for the continuous monitoring of personnel's conditions, whose task is to provide managers with prompt access to information and to make reasonable managerial decisions. With a large variety of systems for personnel analysis and evaluation, when choosing an appropriate system or developing a unique internal organizational evaluation system in practice, one should pay special attention to its compliance with other systems of personnel management – motivation, compensation, career planning, vocational training, etc. Such compliance will allow the administration to achieve a synergistic effect as well as to avoid conflicts and contradictions. When determining the methods of personnel evaluation in an educational organization, one should proceed from the RESUMEN: Este artículo considera y sistematiza los métodos, tipos, técnicas y formas existentes de análisis y evaluación de personal y presenta recomendaciones sobre su aplicación en la práctica de la gestión del personal en una organización educativa. La información obtenida a través de los procedimientos de evaluación amplía y enriquece de forma cualitativa la base de datos de personal y permite el monitoreo continuo de las condiciones del personal, cuya tarea es brindar a los gerentes acceso rápido a la información y tomar decisiones gerenciales razonables. Con una gran variedad de sistemas de análisis y evaluación de personal, al elegir un sistema apropiado o desarrollar un sistema de evaluación organizacional interno único en la práctica, se debe prestar especial atención a su cumplimiento con otros sistemas de gestión de personal: motivación, Formación profesional, etc. Este cumplimiento permitirá a la administración lograr un efecto sinérgico así como evitar conflictos y contradicciones. Al determinar los métodos de evaluación del personal en una organización educativa, uno debe proceder de los objetivos de esta organización objectives of this organization and the immediate task of evaluation. The chosen evaluation system should also comply with the culture of an educational organization. The information and methodological base of an educational organization created on the basis of the proposed classification will make it possible to evaluate and analyze not only the professional and competence level of individual employees, structural subdivisions and personnel, but also to conduct a dynamic analysis of the development of the personnel management system in each organization.
A Theory of Lossy Compression for Individual Data

We develop rate-distortion theory for individual data with respect to general distortion measures, that is, a theory of lossy compression of individual data. This is applied to Euclidean distortion, Hamming distortion, Kolmogorov distortion, and Shannon-Fano distortion. We show that in all these cases for every function satisfying the obvious constraints there are data that have this function as their individual rate-distortion function. Shannon’s distortion-rate function over a random source is shown to be the pointswise asymptotic expectation of the individual distortion-rate functions we have defined. The great differences in the distortion-rate functions for individual non-random (that is, the aspects important to lossy compression) data we established were previously invisible and obliterated in the Shannon theory. The techniques are based on Kolmogorov complexity.
An algorithm for selecting Chinese features based on TF-NIDF weight

This article discusses the problem of selecting Chinese features based on TF-IDF weight in text categorization. TF-IDF weight is commonly used in text categorization for its simplexes. However, it can not express the relationship between a feature appearance frequency in one class and appearance frequency in other classes. To solve the problem, we designed TF-NIDF weighting method to express the relationship and computer feature weight. We also incorporated the weight into Naïve Bayesian classifier and tested it on Chinese text data. Experiments showed that Naïve Bayesian classifier with features selection based on TF-NIDF weight have a higher categorization precision than Naïve Bayesian classifier with features selection based on traditional TF-IDF weight.
The distance between the eigenvalues of Hermitian matrices

It is shown that the minmax principle of Ky Fan leads to a quick simple derivation of a recent inequality of V. S. Sunder giving a lower bound for the spectral distance between two Hermitian matrices. This brings out a striking parallel between this result and an earlier known upper bound for the spectral distance due to L. Mirsky.
The GLOSS system for transformations from plain text to XML

Mathematical texts are complicated, and XML representations of mathematics rightly insist on accuracy and attention-to-detail. This asks a lot of a mere mortal required to enter mathematical data. But the potential of the web and XML-based applications for mathematics cannot be realised until professional mathematicians in particular are persuaded of the advantages and presented with suitable tools to author their texts that are as straightforward as the ones they are used to.
Study of Learning Source Ontology Modeling in Remote Education

This paper , remote education learning resource for metadata standards that learning resources in the semantic status of the missing , to analyze learning resource metadata ,as well as learning resource metadata and ontology integration. combining meta-data ontology with domain ontology to form a learning resource ontology , instantiating the metadata ontology and domain ontology. using IEEE LOM metadata and ACM CSS field of computer science as a specific metadata ontologies ontology and domain ontology,combining the principles of ontology Modeling and using their formed a ACM CSS computer science classification system's learning resource ontology.
Towards a unified metamodel for i*

i* is a framework for goal-oriented requirements modeling. This framework contains an organizational modeling language defined by actors and dependencies among them. Although i* has been widely used, it is still hard to work with it due to its diversity of variants. In this paper, we propose a unified metamodel that presents elements of two well-known variants of i*. We show how OCL restrictions can be applied this metamodel in order to generate a specific variant. In doing so, we intend to unify the efforts of i* community. This metamodel can be useful when developing generic tools for i*, as well as to reason about i* language. Moreover, it makes it easier to extend the i* language. Thus, our proposal is an attempt towards the unification on i* variants by considering similarities and differences among them.
The Design and Experiments of A SID-Based Power-Aware Simulator for Embedded Multicore Systems

Embedded multicore systems are playing increasingly important roles in the design of consumer electronics. The objective of such systems is to optimize both performance and power characteristics of mobile devices. However, currently there are no power metrics supporting popular application design platforms (such as SID) that application developers use to develop their applications. This hinders the ability of application developers to optimize power consumption. In this article we present the design and experiments of a SID-based power-aware simulation framework for embedded multicore systems. The proposed power estimation flow includes two phases: IP-level power modeling and power-aware system simulation. The first phase employs PowerMixerIP to construct the power model for the processor IP and other major IPs, while the second phase involves a power abstract interpretation method for summarizing the simulation trace, then, with a CPE module, estimating the power consumption based on the summarized trace information and the input of IP power models. In addition, a Manager component is devised to map each digital signal processor (DSP) component to a host thread and maintain the access to shared resources. The aim is to maintain the simulation performance as the number of simulated DSP components increases. A power-profiling API is also supported that developers of embedded software can use to tune the granularity of power-profiling for a specific code section of the target application. We demonstrate via case studies and experiments how application developers can use our SID-based power simulator for optimizing the power consumption of their applications. We characterize the power consumption of DSP applications with the DSPstone benchmark and discuss how compiler optimization levels with SIMD intrinsics influence the performance and power consumption. A histogram application and an augmented-reality application based on human-face-based RMS (recognition, mining, and synthesis) application are deployed as running examples on multicore systems to demonstrate how our power simulator can be used by developers in the optimization process to illustrate different views of power dissipations of applications.
APPLICATION OF IMAGE PROCESSING AND IMAGE ANALYSIS METHODS FOR LARGE SCALE MAP REVISION

The aim of this study is to use different image analysis and processing methods in order to extract information content needed to update large scale maps. Recently available high resolution satellite imagery attracted mapping communities to shift their focus from aerial photographs to satellite imagery. Obviously, this new source of information requires different methods and algorithms to extract needed information for map revision. The purpose of this paper, therefore, is to examine reliability of image analysis methods to extract fine groups of classes required to update large scale maps. Data used include Ikonos and QuickBird images of the study area together with aerial photographs and digital maps of the same region.
Context-enhanced Text Recognition Using Semantic Vector Space Models

Contextual information is important to correctly recognize text. Several methods exist to use contextual information in text recognition systems, most notably statistical language models. However, these models have the disadvantage that they can not generalize over similar sequences of words, because they treat words as atomic units. Moreover has previous work failed to find a satisfiable solution to add semantic context information to text recognition systems. Several attempts have been made, however these often require a lot of manual work and do not scale to large vocabularies. In recent years, with the rise of deep learning techniques, substantial progress has been made to build semantic representations of words based on large text corpora with unsupervised methods. We propose a way to use these so called semantic vector space models to add semantic context information to text recognition systems. Two different neural network architectures are implemented and experiments show that they are able to make useful predictions about the meaning of unknown words based on the context in which these words occur. Experiments with a simulated text recognition system show that the proposed methods perform better than N-gram models when trained on the same data. The proposed methods can improve current text recognition systems, because they add semantic information, scale to large vocabularies and generalize over semantically similar words.