Miracle-dz/UniFAR-FTUs huggingface dataset:
Sliding-Window RLS Low-Cost Implementation of Proportionate Affine Projection Algorithms

This paper addresses adaptive filtering for sparse identification. Proportionate affine projection algorithms (PAPAs) are known to be efficient techniques for this purpose. We show that the PAPA performance may improve with an increase in the projection order M (for example, such as M = 512), which, however, also results in an increased complexity; the complexity is in general O(M2N) or at least O(MN) operations per sample, where N is the filter length. We show that PAPAs are equivalent to specific sliding-window recursive least squares (SRLS) adaptive algorithms with time-varying and tap-varying diagonal loading (SRLS-VDLs). We then propose an approximation to the SRLS-VDLs based on dichotomous coordinate descent (DCD) iterations with a complexity of O(NuN), which does not depend on M; it depends on the number of DCD iterations Nu, which as we show can be significantly smaller than M, thus allowing a low-complexity implementation of PAPA adaptive filters.
On Constructing Minimum Spanning Trees in k-Dimensional Spaces and Related Problems

The problem of finding a minimum spanning tree connecting n points in a k-dimensional space is discussed under three common distance metrics -- Euclidean, rectilinear, and $L_\infty$. By employing a subroutine that solves the post office problem, we show that, for fixed k $\geq$ 3, such a minimum spanning tree can be found in time O($n^{2-a(k)} {(log n)}^{1-a(k)}$), where a(k) = $2^{-(k+1)}$. The bound can be improved to O(${(n log n)}^{1.8}$) for points in the 3-dimensional Euclidean space. We also obtain o($n^2$) algorithms for finding a farthest pair in a set of n points and for other related problems.
The VVDS-VLA deep field. III. GMRT observations at 610 MHz and the radio spectral index properties o

Aims. We present the low frequency (610 MHz) radio source counts of the VVDS-VLA field and investigate the radio spectral index properties of the sub-mJy population. Methods. We use new deep (${\rm rms}\simeq 50~\mu$Jy/beam) observations of the VVDS-VLA field obtained at 610 MHz with the GMRT and matched in resolution (6 arcsec) with already available VLA data at 1.4 GHz on the same field. Results. We find evidence of a change of the dominant population of radio sources below 0.5 mJy (at 1.4 GHz): between 0.15 and 0.5 mJy the median spectral index is significantly flatter ($\alpha=-0.46\pm 0.03$) than that of brighter sources ($\alpha=-0.67\pm 0.05$). A relevant contribution below 0.5 mJy from a population of flat spectrum low luminosity compact AGNs and radio quiet QSOs could explain this effect. At even fainter flux density, between 0.10 and 0.15 mJy at 1.4 GHz, the median spectral index steepens again ($\alpha=-0.61\pm 0.04$) suggesting that the contribution of starburst galaxies becomes important below ∼ 0.2 mJy. Finally we present a sample of 58 candidate ultra-steep sources with radio flux density from one to two orders of magnitude lower than any other sample of such objects.
Lost in calculation: the clinical SYNTAX score goes logistic.

This editorial refers to ‘Combined anatomical and clinical factors for the long-term risk stratification of patients undergoing percutaneous coronary intervention: the Logistic Clinical SYNTAX score’, by V. Farooq et al., doi:10.1093/eurheartj/ehs295 Cardiothoracic surgery pioneered the use of risk models in the reporting of operative results of patients referred to myocardial revascularization. Recently, interventional cardiology has rekindled its interest in constructing specific scores for long-term risk prediction of percutaneous coronary intervention (PCI). One of them, dubbed the SYNTAX score, is a successful model with website dissemination and extensive validation, in which the final score is calculated after coronary angiography by summing the scorings assigned to each individual lesion.1 Inherent limitations of the SYNTAX score, such as the lack of clinical or ischaemia information, have lately prompted its integration into more sophisticated algorithms with increased prognostic accuracy.2 There are two ways in which a prognostic model may be useful in clinical decision-making. First, it may be collapsed by tertiles or arbitrary cut-offs to classify patients into risk categories. This knowledge assists in defining the threshold for a procedure and contributes to better resource allocation. Secondly, it can be used to estimate the prognosis of individual patients. These methods may be perceived as two ways to look at the same information, but they differ significantly. For instance, consider a category-based score (i.e. the SYNTAX score) which predicts that 19.2% of patients in the high-risk group will be deceased at 5 years from complex PCI. This model implies that among a large population of patients undergoing complex PCI, ∼19% of those categorized in the high-risk group will be dead after 5 years. Owing to the typical stochastic and time-dependent nature of prognostic models, classification into risk strata is frequently …
Utilization of the multidimensional well-being assessment to understand well-being in individuals with identified religious affiliations

This study examined multiple dimensions of well-being among adults with identified religious or spiritual affiliations utilizing the Multidimensional Well-Being Assessment (MWA). This study focused on transcendent well-being and its dimensions of religiosity/spirituality and meaning/purpose/flow. A non-random sample of 492 participants with identified religious or spiritual affiliations completed multiple measures of well-being as part of a larger psychometric investigation of the MWA. This study supports the MWA as a valid and reliable measure of transcendent well-being among adults with identified religious or spiritual affiliations. This study also found that those who view religiosity or spiritualty as very important to them and value its importance to their overall well-being had higher levels of transcendent well-being than those who did not. Furthermore, results of a series of MANOVAs found statistically significant differences between groups on various demographic and background variables (e.g., religious orientation, race/ethnicity, relationship status, and education level) who rate religion or spirituality in their top determinants of overall well-being. This study’s findings also indicated transcendent well-being is positively correlated with other dimensions of well-being. This study has implications for future research related to understanding well-being in individuals who identify as religious or spiritual.
Restructuring the College Classroom: A Critical Reflection on the Use of Collaborative Strategies to Target Student Engagement in Higher Education

Recent years have witnessed a surge in classroom-based pedagogies aimed at targeting student engagement. This paper seeks to report on the design, delivery and small-scale evaluation of a final year undergraduate module in developmental psychology. Adopting a range of innovative teaching/learning methodologies, the author sought to support student engagement across the module. Using a scaffolded approach to module delivery, four discrete teaching methodologies were employed: ‘lectorial’ design, the jigsaw method, in-class presentations and an online discussion forum. Such strategies were chosen due to their strong alignment with the six ‘engagement indices’, as put forward by the Irish Survey of Student Engagement (ISSE). Following module completion, student feedback was obtained using the Student Course Engagement Questionnaire (SCEQ) and additional Likert scale questions. Based on descriptive and inferential analysis of findings, student feedback is presented, with implications for practice outlined. Limitations of the small-scale evaluation are also noted, offering potential avenues for future research.
Diagram Recognition: Domain Knowledge Based Approach

Information has become a very important resource of any organization and a great demand exists for speedily inputting the colossal amount of printed and handwritten information present on documents into the computer, which requires a lot of manual labour. Over the past few decades, electronic document management systems have turned out to be "beneficial to" and "popular in" the society. Profound research and development has been done in this field. Automatic pattern analysis & recognition systems have been & are being developed to analyze the contents of the documents. An important stage in this procedure is the automatic recognition of diagrams from the document. Diagram recognition being one of the main areas in the field of document analysis & pattern recognition is still an open area for researchers. Diagram recognition is a trivial task for humans, but the development of its computer based solution is tremendously difficult. Various subject-specific methods have been developed. In this paper, we present a novel cognitive approach for the recognition of offline typeset/machine-drawn diagrams by the identification of its symbols. The focus here is to use minimal amount of data for the purpose of recognition and to provide a general system for recognition of various types of diagrams. This involves the development of a Recognition Domain Knowledge Kernel. The algorithm proposed is independent of the size of the symbol used in the diagram. Based on the type of symbols present in the diagram, a diagram classification is made.
D.A.C Draw and Calc - the intuitive calculator -

This paper is presenting a complete system to recognize on-line handwritten digits and other mathematical symbols integrated in an intuitive calculator application running on an Android OS based smart device. Among the multitude of such existing calculator applications available on the market, this software framework provides not only an intuitive user interface (UI), but a special user experience too, allowing the user to input the algebraic formula using handwriting instead of classical buttons. The system uses not only the off-line information but also the on-line information available during the drawing process, and the combination of these aspects allowed the possibility to build a competitive real-time application. The used neural networks beside providing an accurate recognition for the different digits, operators and other symbols, provide a straightforward way to adapt the tool to the specific handwriting of each particular user. The experimental results proved an efficiency (91.57%) of the system using a rather large on-line dataset collected from users.
Scan-based ATPG diagnostic and optical techniques combination: A new approach to improve accuracy of defect isolation in functional logic failure

Nowadays, with the increasing complexity of new VLSI circuits, laser stimulation or emission techniques and scan-based ATPG diagnostic reach their limits in functional logic failure. To overcome these limitations, a new methodology has been established. This methodology, presented in this paper, combines the advantages of both approaches in order to improve accuracy of fault isolation and defect localization.
Sequential images fusion of traffic accident scene based on pixel level

For the scene of the accident, firstly use the sequential images to cover the sequential image information and then apply the image fusion means to process the obtaining sequential panoramic image and eventually get to panoramic images information of the traffic accident scene. The key point study of this paper is to research the feasibility of sequential images fusion of traffic accident scene based on pixel level, set up a sequential improved model of weighted mean method, and then verify the availability of the proposed methods through the experiment.
Automated prediction of the apnea-hypopnea index using a wireless patch sensor

Polysomnography (PSG) is the gold standard that manually quantifies the apnea-hypopnea index (AHI) to assess the severity of sleep apnea syndrome (SAS). This study presents an algorithm that automatically estimates the AHI value using a disposable HealthPatchTM sensor. Volunteers (n=53, AHI: 0.1-85.8) participated in an overnight PSG study with patch sensors attached to their chest at three specified locations and data were wirelessly acquired. Features were computed for 150-second epochs of patch sensor data using analyses of heart rate variability, respiratory signals, posture and movements. Linear Support Vector Machine classifier was trained to detect the presence/absence of apnea/hypopnea events for each epoch. The number of epochs identified with events was subsequently mapped to AHI values using quadratic regression analysis. The classifier and regression models were optimized to minimize the mean-square error of AHI based on leave-one-out cross-validation. Comparison of predicted and reference AHI values resulted in linear correlation coefficients of 0.87, 0.88 and 0.92 for the three locations, respectively. The predicted AHI values were subsequently used to classify the control-to-mild apnea group (AHI<;15) and moderate-to-severe apnea (AHI≥15) with an accuracy (95% confidence intervals) of 89.4% (77.4-95.4%), 85.0% (70.9-92.9%), and 82.9% (67.3-91.9%) for the three locations, respectively. Overnight physiological monitoring using a wireless patch sensor provides an accurate estimate of AHI.
A framework for defining and learning fuzzy behaviors for autonomous mobile robots

In this paper we show our work on the use of fuzzy behaviors in the field of autonomous mobile robots. We address here how we use learning techniques to efficiently coordinate the conflicts between the different behaviors that compete with each other to take control of the robot. We use fuzzy rules to perform such fusion. These rules can be set using expert knowledge, but as this can be a complex task, we show how to automatically define them using genetic algorithms. We also describe the working environment, which includes a custom programming language (named BG) based on the multi‐agent paradigm. Finally, some results related to simple goods‐delivery tasks in an unknown environment are presented. © 2002 John Wiley & Sons, Inc.
Exploring group awareness in a mixed reality collaborative environment

Mixed reality collaborative environments connect physical and virtual worlds to present an integrated collaborative space for remote and co-located collaborators. We designed an immersive mixed reality environment using Unity 3D1 and an Oculus Rift2head-mounted display. We are using virtual arm embodiments to visualize the remote collaborator's arms on the physical tabletop [introduce the fact that people are collaborating around a tabletop first] while s/he is interacting with the virtual tabletop. We will conduct a study examining the impact of our immersive virtual collaborative environment on presence disparity and group awareness of collaborators in the virtually connected space.
Nanoseismic Monitoring : Method and First Applications

We introduce the concept of nanoseismic monitoring aimed at determining the sources of seismic energy radiation in (slant) distances of 10 m to 10 km, and magnitude ranges down to ML –3.0. Recording seismometers are arranged as tripartite array of 100 m layout around the three-comp center site, forming a six-channel Seismic Navigating System (SNS). The associated evaluation program, HypoLine, utilizes network and array processing tools, spectral and polarization analysis, and displays uncertainty ranges by jackknifing instead of residuals. Waveform parameters can be picked close to 0 dB SNR; initial ambiguities are resolved by constraints on slowness and azimuth. Event processing is highly interactive; it allows for determination of origin time, epicenter, depth, suited half space vp and vs, and ML by just one SNS.
Consistently GPU-Accelerated Graph Visualization

Graph visualization is essential for the analysis of networks and relational data sets. Often, most of the effort is expended on computing sophisticated layouts of the visual representation of the graph. Even though this is increasingly accelerated by use of graphics processing units (GPUs), the rendering is often considered as circumstantial. In this paper, we present a coherent approach to graph visualization that utilizes all features of modern GPUs. We describe specialized data structures and our GPU-centric pipeline for computing and rendering a layout, while enabling steering and interaction. We evaluate technical aspects of our approach as well as its applicability to huge real-world graphs.
On the Perils of Hyperfine Splitting: A Reanalysis of Mn and Sc Abundance Trends

We investigate the impact of hyperfine splitting on stellar abundance analyses of Mn and Sc and find that incorrect hyperfine splitting treatment can lead to spurious abundance trends with metallicity. We estimate corrections to a recent study by Nissen et al. and find (1) [Mn/Fe] is described by a bimodal distribution, with [Mn/Fe] ~ -0.3 for stars with [Fe/H] < -0.7 and [Mn/Fe] ~ -0.05 for stars at higher metallicity, suggestive of a transition between halo/thick-disk and thin-disk populations, and (2) the large majority of stars show nearly solar [Sc/Fe] ratios, although important deviations cannot be ruled out.
Competitive and Asymmetric Nature of Relationships between Expert Blog Sentiment and General Consumer Brand perception

Expert blogs have become an important source from which consumers obtain information about products and brands. Consumers heed information from such blogs because they are provided by fellow consumers who are regarded as experts and yet are not restrained to speak for a particular company. Thus, expert blogs are considered more credible, and it is likely that when expert bloggers choose to write favorably about a brand, consumer perception about the brand is enhanced. Furthermore, expert blogs may influence not only consumer perception of a focal brand, but also that of competing brand. By analyzing a novel, comprehensive dataset that combined expert blog sentiment of competing brands in the PC industry and consumer perception of the brands at a daily level, our study unveils three insights: 1) expert blog sentiment on a focal brand is positively related to consumer perception about the brand while negatively related to that of its competitors; 2) the focal brand’s blog sentiment has a reinforcing relationship with its future blog sentiments, while a cannibalistic relationship with that of its competitors; and 3) the extents of the positive and reinforcing relationships depend on the firms’ position (leading vs. non-leading). Implications for research and practice are discussed.
An analysis of local energy and phase congruency models in visual feature detection

Abstract A variety of approaches have been developed for the detection of features such as edges, lines, and corners in images. Many techniques presuppose the feature type, such as a step edge, and use the differential properties of the luminance function to detect the location of such features. The local energy model provides an alternative approach, detecting a variety of feature types in a single pass by analysing order in the phase components of the Fourier transform of the image. The local energy model is usually implemented by calculating the envelope of the analytic signal associated with the image function. Here we analyse the accuracy of such an implementation, and show that in certain cases the feature location is only approximately given by the local energy model. Orientation selectivity is another aspect of the local energy model, and we show that a feature is only correctly located at a peak of the local energy function when local energy has a zero gradient in two orthogonal directions at the peak point.
The Golod Shafarevich counter-example without Hilbert series

Let $F$ be an arbitrary field. The Golod-Shafarevich example of a finitely generated nil $F$-algebra which is infinite dimensional -- is revisited. Here we offer a rather elementary treatment of that example, in which induction replaces Hilbert series techniques. This note also contains a detailed exposition of the construction of that example.
Cooking the Enterprise-Scale Solutions: An Integrated Modeling Approach for Business Process and System Objectives

Business process modeling assists an enterprise to achieve strategic objectives by providing methodology and tools to develop integrated business process models, however there is little discussion on how to integrate the strategic objectives into the IT system and how process and functional objectives link to the PIM. One of the primary challenges to be addressed in developing enterprise-scale solutions is to connect the domain specific requirements expressed by business analysts with the technology-specific solutions designed by IT architecture. This paper, by discussing the definition of business process and system objectives and analyzing the relationship between different levels of objectives based on the proposal modeling methodology, presents a new modeling method about the business process based on the analysis of the notion-activity and the objectives used in enterprise. It is also addressed that how a neutral linkage model between process objectives and system objectives is defined to construct the PIM, and how business process and system modeling approaches interact with each other in order to provide an overall solution for enterprises. Finally, the enterprise-scale model integrated architecture is described.
CHARACTERISATION OF EPOXY MATERIALS USED IN THE DEVELOPMENT OF ULTRASONIC ARRAYS

: The increasing popularity of piezocomposite technology is largely due to the improvements in mechanical and electro-acoustical properties over for example monolithic piezoelectric elements. Polymer materials are extensively used in the manufacture of ultrasonic transducers. Epoxy resins exhibit a great range of properties (from soft to hard) which leads to a great versatility in application. This is mainly due to good adhesive properties, low expansion coefficients and low viscosity. A variety of epoxies may be used in order to suit a particular application e.g. isolation of piezo-electric rods within the matrix material. Furthermore loaded epoxy is often used as a backing material due to possibility of achieving high impedance in the order of 11 Mrayl and attenuation values of about 15 to 20 dB/cm. Investigations have been performed on epoxy materials to provide a basic knowledge of how such materials are influenced by such factors as temperature and pressure. It is expected that the piezo-ceramic will only be minimally influenced by changes in temperature up to 200 °C but within this range dramatic changes can occur in a polymer material leading to a reduction in often impedance and variations in attenuation. By employing customised sensors and equipment, experiments were performed in an oilbath at temperatures up to 180 °C. Measurement of mechanical moduli, linear expansion coefficients are also employed to understand variations in the physical properties of the pure material. The
A 94GHz SPST Switch in 65nm Bulk CMOS

A 3-bit lumped SPST switch that operates from DC to greater than 94 GHz has been realized in 65 nm CMOS. At 94 GHz, it provides an insertion loss of 1.6 dB and an isolation of over 30 dB. Power-handling measurements of the switch at 60 GHz show no sign of input compression up to an equipment-limited input power of +9 dBm. The circuit was demonstrated as a digitally controlled variable attenuator and as a transmit-receive switch in an array of three 94 GHz transceivers. In the latter case, the on-chip loop-back of PA signals into the LNA in each individual transceiver is possible, enabling the production testing of mm-wave transceiver functionality at IF without the requirement for high-speed signal sources or probes. Measurements of the transmit-receive switch show a return-loss better than -8 dB from 58 to 94 GHz.