Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatio-Temporal Video Slice Edges Analysis for Shot Transition Detection and Classification

— In this work we will present a new approach for shot transition auto-detection. Our approach is based on the analysis of Spatio-Temporal Video Slice (STVS) edges extracted from videos. The proposed approach is capable to efficiently detect both abrupt shot transitions “cuts” and gradual ones such as fade-in, fade-out and dissolve. Compared to other techniques, our method is distinguished by its high level of precision and speed. Those performances are obtained due to minimizing the problem of the boundary shot detection to a simple 2D image partitioning problem.
Exploring Texture Ensembles by Efficient Markov Chain Monte Carlo

I E E E Trans on P A M ! , (accepted), 1999. Exploring Texture Ensembles by Efficient Markov Chain Monte Carlo - T o w a r d s a T r i e h r o m a e y T h e o r y of Texture Song C h u n Z h u , X i u Wen Liu, Ying Nian W u Abstract T h i s article presents a m a t h e m a t i c a l definition of texture - the Julesz ensemble 0(h), w h i c h is the set of a l l images (defined on Z ) that share identical statistics h. T h e n texture m o d e l i n g is posed as a n inverse problem: given a set of images sampled from a n u n k n o w n Julesz ensemble fi(h*), we search for the statistics h* w h i c h define the ensemble. A Julesz ensemble fi(h) has a n associated p r o b a b i l i t y d i s t r i b u t i o n g(I;h), w h i c h is uniform over the images i n the ensemble a n d has zero p r o b a b i l i t y outside. I n a c o m p a n i o n paper[32], q(I; h) is shown to be the limit distribution of the F R A M E ( F i l t e r , R a n d o m F i e l d , A n d M i n i m a x E n t r o p y ) model[35] as the image lattice A -~ 7r. T h i s conclusion establishes the intrinsic link between the scientific definition of texture o n Z models of texture o n finite lattices. a n d the m a t h e m a t i c a l It brings two advantages to computer vision. T h e engineering practice of synthesizing texture images by m a t c h i n g statistics has been put o n a m a t h e m a t i c a l foundation. 2). W e are released from the b u r d e n of learning the expensive F R A M E m o d e l i n feature pursuit, m o d e l selection a n d texture synthesis. In this paper, a n efficient M a r k o v chain M o n t e C a r l o a l g o r i t h m is proposed for s a m p l i n g Julesz ensembles. T h e a l g o r i t h m generates r a n d o m texture images by m o v i n g along the directions of filter coefficients a n d thus extends the t r a d i t i o n a l single site G i b b s sampler. T h i s paper also compares four p o p u l a r statistical measures i n the literature, namely, moments, rectified functions, m a r g i n a l histograms a n d joint histograms of linear filter responses i n terms of their descriptive abilities. O u r experiments suggest that a s m a l l number of bins i n m a r g i n a l histograms are sufficient for c a p t u r i n g a variety of texture patterns. W e illustrate our theory a n d a l g o r i t h m by successfully synthesizing a number of n a t u r a l textures. Keywords: G i b b s ensemble, Julesz ensemble, texture modeling, texture synthesis, M a r k o v chain M o n t e C a r l o . Song C h u n Z h u a n d X i u W e n L i u are w i t h the Department of C o m p u t e r a n d Informa- t i o n Sciences, T h e O h i o State University, C o l u m b u s , O H 43210. Y i n g N i a n W u is w i t h the Department of Statistics, U n i v e r s i t y of C a l i f o r n i a , Los Angeles, C A 90095.
The Dynamic Domain Reduction Procedure for Test Data Generation A. JEFFERSON OFFUTT

Test data generation is one of the most technically challenging steps of testing software, but most commercial systems currently incorporate very little automation for this step. This paper presents results from a project that is trying to nd ways to incorporate test data generation into practical test processes. The results include a new procedure for automatically generating test data that incorporates ideas from symbolic evaluation, constraint-based testing, and dynamic test data generation. It takes an initial set of values for each input, and dynamically \pushes" the values through the controlow graph of the program, modifying the sets of values as branches in the program are taken. The result is usually a set of values for each input parameter that has the property that any choice from the sets will cause the path to be traversed. This procedure uses new analysis techniques, o ers improvements over previous research results in constraint-based testing, and combines several steps into one coherent process. The dynamic nature of this procedure yields several bene ts. Moving through the control ow graph dynamically allows path constraints to be resolved immediately, which is more e cient both in space and time, and more often successful than constraint-based testing. This new procedure also incorporates an intelligent search technique based on bisection. The dynamic nature of this procedure also allows certain improvements to be made in the handling of arrays, loops, and expressions; language features that are traditionally di cult to handle in test data generation systems. The paper presents the test data generation procedure, examples to explain the working of the procedure, and results from a proof-of-concept implementation.
Personalizing Search Based on user Search Histories

In improving the quality of various search services on the Internet, Individualized web search (IWS) has demonstrated its effectiveness. User preferences are modelled as hierarchical user profiles in IWS applications. We propose an IWS framework called UPS that can adaptively generalize profiles by queries. Our runtime generalization evaluates the utility of personalization and the privacy risk of exposing the generalized profile. We present two greedy algorithms, namely GreedyDP and GreedyIL, for runtime generalization. For deciding whether personalizing a query is beneficial, we also provide an online prediction mechanism. The experimental results also reveal that GreedyIL significantly outperforms GreedyDP in terms of efficiency.
M : A flexible free-software package for electromagnetic simulations by the FDTD method

This paper describes Meep, a popular free implementation of the finite-di fference time-domain (FDTD) method for simulating electromagnetism. In particu lar, we focus on aspects of implementing a full-featured FDTD package that go beyond standar d textbook descriptions of the algorithm, or ways in which Meep di ffers from typical FDTD implementations. These include pervasive interpolation and accurate modeling of subpixel features, advanced signal processing, support for nonlinear materials via Padé approximants, an d flexible scripting capabilities. PACS: 02.70. Bf; 82.20. Wt; 03.50. De; 87.64. Aa.
Event studies in information systems research: past, present and future

Event studies, which gauge stock market reactions to specific events or happenings that may impact a business's operations, represent a relatively new but fast growing research approach in the information systems field. Building on four earlier literature reviews, in this paper we examine seventy-three event studies dealing with information technology. The purpose of this review is to assess the current state of information technology related event studies and to identify needs and opportunities for future research.
Computational investigations of three main drugs and their comparison with synthesized compounds as potent inhibitors of SARS-CoV-2 main protease (M pro ): DFT, QSAR, molecular docking, and in silico toxicity analysis of King Saud University – Science

In this study, we examined ﬁve previously synthesized compounds and checked their binding afﬁnity towards the SARS-CoV-2 main protease (M pro ) by molecular docking study, and compared the data with three FDA approved drugs, i.e., Remdesivir, Ivermectine and Hydroxychlorochine. In addition, we have investigated the docking study against the main protease of SARS-CoV-2 (M pro ) by using Autodock 4.2 software package. The results suggested that the investigated compounds have property to bind the active position of the protein as reported in approved drugs. Hence, further experimental studies are required. The formation of intermolecular interactions, negative values of scoring functions, free binding energy and the calculated binding constants conﬁrmed that the studied compounds have signiﬁcant afﬁnity for the speciﬁed biotarget. These studied compounds were passed the drug-likeness criteria as suggested by calculating ADME data by SwissADME server. Moreover, the ADMET properties suggested that the investigated compounds to be orally active compounds in human. Furthermore, density func- tional computations (DFT) were executed by applying GAUSSIAN 09 suit program. In addition, Quantitative Structure-Activity Relationship (QSAR) was studied by applying HyperChem Professional 8.0. 3 program. (cid:1) 2020 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an openaccess article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Score-Informed Source Separation of Choral Music

As a longtime choir singer and conductor, I have seen professional and amateur choirs alike spend much of their rehearsal time on part-learning. Most singers are not able to ‘sight sing’ perfectly from a score, and are helped by hearing a recording of their part. For this reason, conductors sometimes record practice tracks to help singers and save valuable rehearsal time. In this thesis, I propose to devise a method to produce practice tracks automatically by extracting them from mixed choral music recordings. This act of ‘de-mixing’ a recording into tracks is known as audio source separation. Source separation enables additional applications such as fine-grained editing and analysis. Choral music poses several challenges to source separation. The singing voice is hard to model due to its highly variable acoustic properties. Overlap between partials in the spectrum, which is ubiquitous in music, makes it difficult to differentiate between simultaneously sounding notes. Furthermore, an important goal in choral performance is achieving blend between singers, and separation must undo that blend. The large amount of reverberation that is often present in choir recordings acts as another obstacle. Finally, choirs are seldom recorded in a ‘one voice per track’ setting, and this lack of multi-track recordings makes it harder to design and validate source separation systems. This research will attempt to overcome these challenges by taking advantage of recent research breakthroughs that have shown promising results in singing voice source separation.
Tech United Eindhoven Team Description 2012

This paper provides an overview of the hardware and software of the AMIGO robot, which competes on behalf of Tech United Eindhoven in the RoboCup@Home competition. Special attention is given to the main research improvements of last year, in the fields of sharing knowledge between robots (RoboEarth), Robotic Open Platform (ROP), world modeling and perception.
"Zadar calm" during severe Bora

In this study, we investigate small-scale characteristics and spatial variability of severe Bora flow in the wider Zadar area with the objective of identifying reasons for the “ Zadar calm” . A detailed analysis of several severe Bora events that occurred in the winter-spring 2004/5 season is undertaken, during which a new sodar system was deployed at the Zadar-Zemunik airport, which provided continuous vertical soundings from 40 to 700 m MSL at the temporal resolution of 10 minutes. The Zadar sodar data reveals a significant variability in the wind speed and direction during the severe Bora events. The maximum Bora speeds were observed in the layer between 300 and 500 m MSL, while the low-level flow was characterized by weak winds. This observational analysis also includes surface data from Zadar and several automatic weather stations located inside the target area, as well as the Zadar - Zemunik radio-sounding data. Initial simulation results indicate that the Bora flow never fully penetrated to the surface near the coast in the Zadar area. The simulation results also suggest that the primary mountain wave could be responsible for low-level flow separation over the steep terrain, leading to weak surface winds over Zadar, downstream of Velebit.
Harmonic Variance : A Novel Measure for Infocus Segmentation

We introduce an efficient measure for estimating the degree of in-focus within an image region. This measure, harmonic mean of variances, is computed from the statistical properties of the image in its bandpass filtered versions. We incorporate the harmonic variance into a graph Laplacian spectrum based segmentation framework in order to accurately align the in-focus measure responses on the underlying image structure. Our results demonstrate the effectiveness of this novel measure for determining and segmenting in-focus regions in low depth-of-field images. British Machine Vision Conference (BMVC) This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c © Mitsubishi Electric Research Laboratories, Inc., 2013 201 Broadway, Cambridge, Massachusetts 02139 LI, PORIKLI: HARMONIC VARIANCE 1 Harmonic Variance: A Novel Measure for In-focus Segmentation Feng Li http://www.eecis. udel.edu/~feli/ Fatih Porikli http://www.porikli. com/ Mitsubishi Electric Research Labs Cambridge, MA 02139, USA
ICEMST 2014 : International Conference on Education in Mathematics , Science & Technology PREDICTING STUDENTS ’ ACADEMIC PERFORMANCE USING ARTIFICIAL NEURAL NETWORK : A CASE STUDY FROM FACULTY OF ORGANIZATIONAL SCIENCES

University students’ retention and performance in higher education are important issues for educational institutions, educators, and students. Educational data mining is focused on developing models and methods for exploring data collected from educational environments in order to better understand and improve educational process. Analyzing and determining patterns among indicators of academic success (study grade point average) and their correlation to students’ personal, high school, admission data can present be a good foundation in process to adapt and improve the curriculum of higher education institutions, according to the students’ characteristics. In this paper we use different artificial neural network algorithms in order to find the best suited model for prediction of students' success at the end of their studies. Additionally, we identified which factors had the crucial influence on overall students’ success. Data were collected from the graduated students of Faculty of Organizational Sciences, University of Belgrade.
International Journal of Soft Computing and Engineering

Image Segmentation has been an area for a long time which is providing opportunities for the intellectual communities to do research work. Image segmentation is a process of partitioning an image into meaningful regions. There exist many digital image segmentation techniques which are currently applied on different fields. These image segmentation techniques need comparative analysis for further development and modifications for continuous and consistent improvement. Hence, in this paper an overview of image segmentation and its present techniques is presented which demands a lot of research
2 Notations and Proposed Distance Measure for Graphs

Metric graphs are ubiquitous in science and engineering. For example, many data are drawn from hidden spaces that are graph-like, such as the cosmic web. A metric graph offers one of the simplest yet still meaningful ways to represent the non-linear structure hidden behind the data. In this paper, we propose a new distance between two finite metric graphs, called the persistence-distortion distance, which draws upon a topological idea. This topological perspective along with the metric space viewpoint provide a new angle to the graph matching problem. Our persistence-distortion distance has two properties not shared by previous methods: First, it is stable against the perturbations of the input graph metrics. Second, it is a continuous distance measure, in the sense that it is defined on an alignment of the underlying spaces of input graphs, instead of merely their nodes. This makes our persistence-distortion distance robust against, for example, different discretizations of the same underlying graph. Despite considering the input graphs as continuous spaces, that is, taking all points into account, we show that we can compute the persistence-distortion distance in polynomial time. The time complexity for the discrete case where only graph nodes are considered is much faster. We also provide some preliminary experimental results to demonstrate the use of the new distance measure.
Interactive Publication : The document as a research tool

The increasing prevalence of multimedia and research data generated by scientific work affords an opportunity to reformulate the idea of a scientific article from the traditional static document, or even one with links to supplemental material in remote databases, to a self-contained, multimedia-rich interactive publication. This paper describes our concept of such a document, and the design of tools for authoring (Forge) and visualization/analysis (Panorama). They are platform-independent applications written in Java, and developed in Eclipse 1 using its Rich Client Platform (RCP) framework. Both applications operate on PDF files with links to XML files that define the media type, location, and action to be performed. We also briefly cite the challenges posed by the potentially large size of interactive publications, the need for evaluating their value to improved comprehension and learning, and the need for their long-term preservation by the National Library of Medicine and other libraries.
Empirical Analysis of Data Breach Litigation

In recent years, many lawsuits have been filed by individuals seeking legal redress for harms caused by the loss or theft of their personal information. However, very little is known about the drivers, mechanics, and outcomes of those lawsuits, making it difficult to assess the effectiveness of litigation at balancing organizations' usage of personal data with individual privacy rights. Using a unique and manually collected database, we analyze court dockets for more than 230 federal data breach lawsuits from 2000 to 2010. We investigate two questions: Which data breaches are being litigated? and Which data breach lawsuits are settling? Our results suggest that the odds of a firm being sued are 3.5 times greater when individuals suffer financial harm, but 6 times lower when the firm provides free credit monitoring. Moreover, defendants settle 30 percent more often when plaintiffs allege financial loss, or when faced with a certified class action suit. By providing the first comprehensive empirical analysis of data breach litigation, our findings offer insight into the debate over privacy litigation versus privacy regulation.
Analysis of Gene‐Gene Interactions

The goal of this unit is to introduce gene‐gene interactions (epistasis) as a significant complicating factor in the search for disease susceptibility genes. This unit begins with an overview of gene‐gene interactions and why they are likely to be common. Then, it reviews several statistical and computational methods for detecting and characterizing genes with effects that are dependent on other genes. The focus of this unit is genetic association studies of discrete and quantitative traits because most of the methods for detecting gene‐gene interactions have been developed specifically for these study designs. Curr. Protoc. Hum. Genet. 59:1.14. 1‐1.14. 10. © 2008 by John Wiley & Sons, Inc.
Centralized radio access networks over wavelength-division multiplexing: a plug-and-play implementation

The evolution of centralized radio access networks is discussed from a pragmatic perspective, taking into account the network and radio requirements. The use of wavelength-division multiplexing technology to support this evolution is proposed, and the opportunities for network operators in terms of operational cost, energy efficiency, reuse of already deployed infrastructures, and network convergence are discussed.
Speech Enhancement from Additive Noise and Channel Distortion - a Corpus-Based Approach

This paper presents a new approach to single-channel speech enhancement involving both noise and channel distortion (i.e., convolutional noise). The approach is based on ﬁnding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise. Third, we present an iterative algorithm for improved speech estimates. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction signiﬁcantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement.
GrainAutLine: an Environment for Semi-Automatic Processing of Marble Thin Section Images

GrainAutLine is an interdisciplinary microscopy image analysis tool with domain specific smart functions to partially auto - mate the processing of marble thin section images. It allows the user to create a clean grain boundary image which is a starting point of several archaeometric and geologic analyses. The semi-automatic tools minimize the need for carefully draw - ing the grain boundaries manually, even in cases where twin crystals prohibit the use of classic edge detection based bound - ary detection. Due to the semi-automatic approach, the user has full control over the process and can modify the automatic results before finalizing a specific step. This approach guaran - tees high quality results both in cases where the process is easy to automate, and also if it needs more help from the user. This paper presents the basic operation of the system and details about the provided tools as a case study for an interdisciplin - ary, semi-automatic image processing application.
Block compressed sensing of images using directional transforms

Block-based random image sampling is coupled with a projection-driven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously with a smooth reconstructed image. Both contourlets as well as complex-valued dual-tree wavelets are considered for their highly directional representation, while bivariate shrinkage is adapted to their multiscale decomposition structure to provide the requisite sparsity constraint. Smoothing is achieved via a Wiener filter incorporated into iterative projected Landweber compressed-sensing recovery, yielding fast reconstruction. The proposed approach yields images with quality that matches or exceeds that produced by a popular, yet computationally expensive, technique which minimizes total variation. Additionally, reconstruction quality is substantially superior to that from several prominent pursuits-based algorithms that do not include any smoothing.