Miracle-dz/UniFAR-FTUs huggingface dataset:
Soliton resolution for the modified KdV equation

The soliton resolution for the focusing modified Korteweg-de vries (mKdV) equation is established for initial conditions in some weighted Sobolev spaces. Our approach is based on the nonlinear steepest descent method and its reformulation through $\bar{\partial}$-derivatives. From the view of stationary points, we give precise asymptotic formulas along trajectory $x=\textrm{v}t$ for any fixed $ \textrm{v} $. To extend the asymptotics to solutions with initial data in low regularity spaces, we apply a global approximation via PDE techniques. As byproducts of our long-time asymptotics, we also obtain the asymptotic stability of nonlinear structures involving solitons and breathers.
IDENTIFICATION OF IMAGE SPAM BY USING LOW LEVEL & METADATA FEATURES

Spammers are constantly evolving new spam technologies, the latest of which is image spam. Till now research in spam image identification has been addressed by considering properties like colour, size, compressibility, entropy, content etc. However, we feel the methods of identification so evolved have certain limitations due to embedded obfuscation like complex backgrounds, compression artifacts and wide variety of fonts and formats . To overcome these limitations, we have proposed 2 methodologies(however there can be more). Each methodology has 4 stages. Both the methodologies are almost similar except in the second stage where methodology I extracts low level features while the other extracts metadata features. Also a comparison between both the methodologies is shown. The method works on images with and without noise separately. Colour properties of the images are altered so that OCR (Optical Character Recognition) can easily read the text embedded in the image. The proposed methods are tested on a dataset of 1984 spam images and are found to be effective in identifying all types of spam images having (1) only text, (2) only images or (3) both text and images. The encouraging experimental results show that the methodology I achieves an accuracy of 92% while the other achieves an accuracy of 93.3%.
Death by Dark Matter

Macroscopic dark matter refers to a variety of dark matter candidates that would be expected to (elastically) scatter off of ordinary matter with a large geometric cross-section. A wide range of macro masses $M_X$ and cross-sections $\sigma_X$ remain unprobed. We show that over a wide region within the unexplored parameter space, collisions of a macro with a human body would result in serious injury or death. We use the absence of such unexplained impacts with a well-monitored subset of the human population to exclude a region bounded by $\sigma_X \geq 10^{-8} - 10^{-7}$ cm$^2$ and $M_X < 50$ kg. Our results open a new window on dark matter: the human body as a dark matter detector.
AVR theory, techniques and application

AVR (from actual reality to virtual reality) is a development of VR technique. In AVR, the objects in real world are virtualized directly from their shape information based on computer graphics and computer vision techniques, which provides the virtual environment with a higher level realism and preciseness. The basic theory and core techniques of AVR have been expounded in this paper. In order to achieve the integration of computer vision and computer graphics, superquadric-based model (SQ-based model) as the universal description of virtual objects is chosen and PAMVISION model providing a general framework for vision recognition and reconstruction in AVR modeling is developed. As the core techniques of AVR, two approaches for virtualizing the real objects from either 2D images or 3D data are implemented.
Golden mean renormalization for the almost Mathieu operator and related skew products

Considering SL(2,R) skew-product maps over circle rotations, we prove that a renormalization transformation associated with the golden mean alpha has a nontrivial periodic orbit of length 3. We also present some numerical results, including evidence this period 3 describes scaling properties of the Hofstadter butterfly near the top of the spectrum at alpha, and scaling properties of the generalized eigenfunction for this energy.
Stochastic Gradient Markov Chain Monte Carlo

Abstract Markov chain Monte Carlo (MCMC) algorithms are generally regarded as the gold standard technique for Bayesian inference. They are theoretically well-understood and conceptually simple to apply in practice. The drawback of MCMC is that performing exact inference generally requires all of the data to be processed at each iteration of the algorithm. For large datasets, the computational cost of MCMC can be prohibitive, which has led to recent developments in scalable Monte Carlo algorithms that have a significantly lower computational cost than standard MCMC. In this article, we focus on a particular class of scalable Monte Carlo algorithms, stochastic gradient Markov chain Monte Carlo (SGMCMC) which utilizes data subsampling techniques to reduce the per-iteration cost of MCMC. We provide an introduction to some popular SGMCMC algorithms and review the supporting theoretical results, as well as comparing the efficiency of SGMCMC algorithms against MCMC on benchmark examples. The supporting R code is available online at https://github.com/chris-nemeth/sgmcmc-review-paper.
Comparison between algebraic and matrix‐free geometric multigrid for a Stokes problem on adaptive meshes with variable viscosity

Problems arising in Earth's mantle convection involve finding the solution to Stokes systems with large viscosity contrasts. These systems contain localized features which, even with adaptive mesh refinement, result in linear systems that can be on the order of 109 or more unknowns. One common approach for preconditioning to the velocity block of these systems is to apply an Algebraic Multigrid (AMG) V‐cycle (as is done in the ASPECT software, for example), however, we find that AMG is lacking robustness with respect to problem size and number of parallel processes. Additionally, we see an increase in iteration counts with refinement when using AMG. In contrast, the Geometric Multigrid (GMG) method, by using information about the geometry of the problem, should offer a more robust option.Here we present a matrix‐free GMG V‐cycle which works on adaptively refined, distributed meshes, and we will compare it against the current AMG preconditioner (Trilinos ML) used in the ASPECT1 software. We will demonstrate the robustness of GMG with respect to problem size and show scaling up to 114,688 cores and 217 billion unknowns. All computations are run using the open‐source, finite element library deal.II. 2
Let's play 'puters: expressive language use at the computer center

The researchers investigated 25 preschool children's expressive language while they were engaged at a classroom computer center and during their free play at traditional early childhood learning centers. The participants were enrolled in an inclusive preschool setting and ranged in age from four years, three months to five years, two months, at the beginning of the study. Over a period of six months, trained pre-service educators collected multiple language samples from each child at the computer center and at a variety of other classroom centers such as blocks, housekeeping, library, and art. An analysis of each child's mean length of utterance (MLU) indicated that 21 of the children evidenced no significant difference in the amount of language spoken at the computer versus other learning centers. Of the remaining four children, one used more expressive language at the computer, while three children were more verbal at other centers. Results indicated that the use of computers, as a self-selected activity, in early childhood classrooms could be as enriching for children's language development as other traditional learning centers.
Crystal structure of N′-(4-nitrobenzylidene)-5-phenyl-1H-pyrazole-3-carbohydrazide, C17H13N5O3

Abstract C17H13N5O3, monoclinic, P21/c (no. 14), a = 20.1049(8) Å, b = 11.1534(4) Å, c = 6.8890(3) Å, β = 97.224(2)°, V = 1532.51(11) Å3, Z = 4, Rgt(F) = = 0.0451, wRref(F2) = 0.1153, T = 100 K.
Surface Based Virtual Mechanical Equipment Modification

We present a surface based system to manipulate virtual mechanical equipment. Our system can modify or deform the equipment as will. As we model the process of manipulation as a linear system which can be solved very fast by state-of-art numerical solver, our system is very efficient. We also provide an intuitive user interface for our system.
Parameter estimation in deformable models using Markov chain Monte Carlo

Deformable models have gained much popularity recently for many applications in medical imaging, such as image segmentation, image reconstruction, and image registration. Such models are very powerful because various kinds of information can be integrated together in an elegant statistical framework. Each such piece of information is typically associated with a user-defined parameter. The values of these parameters can have a significant effect on the results generated using these models. Despite the popularity of deformable models for various applications, not much attention has been paid to the estimation of these parameters. In this paper we describe systematic methods for the automatic estimation of these deformable model parameters. These methods are derived by posing the deformable models as a Bayesian inference problem. Our parameter estimation methods use Markov chain Monte Carlo methods for generating samples from highly complex probability distributions.
A conversation with Robert Langer: pioneering biomedical scientist and engineer. Interview by Paul S. Weiss.

PSW: You took a very unusual path for a chemical engineer and redefined what chemical engineers can do. When you started your career, how did you get advice and inspiration? Robert Langer: When I got done with my chemical engineering degree, most of my colleagues went into the petrochemical industry and I didn’t want to do that. I ended up getting a job in a surgery department with Judah Folkman. For me that was wonderful. It gave me an opportunity to learn a lot about medicine and gave me a lot of ideas. He was also a great person to give advice.
Extension of analog network coding in wireless information exchange

Ever since the concept of analog network coding(ANC) was put forward by S.Katti, much attention has been focused on how to utilize analog network coding to take advantage of wireless interference, which used to be considered generally harmful, to improve throughput performance. Previously, only the case of two nodes that need to exchange information has been fully discussed while the issue of extending analog network coding to more than three nodes remains undeveloped. In this paper, we propose a practical transmission scheme to extend analog network coding to more than two nodes that need to exchange information among themselves. We start with the case of three nodes that need to exchange information and demonstrate that through utilizing our algorithm, the throughput can achieve 33% and 20% increase compared with that of traditional transmission scheduling and digital network coding, respectively. Then, we generalize the algorithm so that it can fit for occasions with any number of nodes. We also discuss some technical issues and throughput analysis as well as the bit error rate.
A comprehensive software suite for optical trapping and manipulation

We present a comprehensive laser tweezers software package, comprising the software components for any laser tweezers system. This includes fast hologram generation software, implemented on a graphics card, thereby allowing 100 hundred independently moving traps at video frame rate. The software also includes comprehensive camera suite and image recognition software for multi-particle tracking and analysis. The software is freely available from the authors and online(http://www.physics.gla.ac.uk/Optics/).
Specifying Collective Adaptive Situations in Cross Cultural Game towards Validation of Agent-Based Social Simulation

This paper focuses on a collective adaptive situation as an complex phenomena in social dynamics and aims at specifying its situation towards a validation of agent-based social simulations. For this purpose, the fuzzy c-means clustering (FCM) method is applied into the experimental data of both the human subject experiments and the agent-based social simulations in the cross-cultural game, Barnga, and compare these results from the viewpoint of a collective adaptive situation. The analysis of these data has revealed the following implications: (1) the collective adaptive situation can be specified by the FCM method; and (2) the classified results of both of the experimental data are close to each other, indicating that agent-based social simulations can be validated from the viewpoint of a collective adaptive situation.
Energy Efficiency in Wireless Networks – a Composite Review

ABSTRACT Energy efficiency is one of the most distinguished area on which several research groups and organizations across the globe are progressively working. This paper focuses on various technologies for truncating energy consumption in wireless communication. This incorporates new network architecture, network resource management, and supreme physical layer methods. Network architecture embraces multi-hop mobile networks, distributed antennas, diverse networks, etc. Furthermore, network resource management schemes comprise cross-layer optimization, multiple radio access technologies, and the dynamic power saving. The supreme physical layer methods encompass cognitive radio, multiple-input multiple-output (MIMO), concerted communications, network coding, orthogonal frequency division multiplexing (OFDM), etc. We render an exhaustive survey of such techniques proposed by several organizations across the globe. We also discussed energy efficiency prospect in future wireless communication systems like 5G, mobile cloud computing, Internet of things (IoT), and big data. Finally, we confer the major challenges and open issues in these technologies.
A fast motion estimation algorithm for mobile communications

The limitation of processing power, battery life and memory capacity of portable terminals requires reducing encoding complexity in mobile communications. Motion estimation (ME) is the most computationally intensive module in a typical video codec, which determines not only the encoder’s performance but also the reconstructed video quality. In this paper, a fast ME algorithm for H.264/AVC baseline profile coding is proposed based on the analysis of motion vector field and error surface, and the statistical distributions of different type macroblocks (MBs). Simulation results showed that: in comparison with MVFAST, the proposed algorithm can decrease the computational load over 7.2% with no requirement of expanding memory capacity while maintaining the same video quality as MVFAST. Furthermore, its simplicity makes it easy to be implemented on hardware.
Innovation in Public and Academic North American Libraries:Examining White Literature and Website Applications / L'innovation dans les bibliothèques publiques et académiques en Amérique du Nord :examen de la littérature blanche (livres et périodiques) et des applications pour sites web

Though innovation is a popular theme of LIS literature, its specific meaning for libraries remains obscure. Clarifying the implicit definition of innovation in librarianship can facilitate a more meaningful use of the term. To do so, we employ a ground-up exploration of innovation through the white literature in conjunction with a detailed survey of website features, of 160 libraries across the United States and Canada.Bien que l'innovation soit un thème populaire dans la littérature en bibliothéconomie et sciences de l'information, le sens spécifique du terme dans le contexte d'une bibliothèque demeure obscur. Essayer de clarifier la définition implicite de l'innovation en bibliothéconomie peut permettre un usage plus prégnant du terme. Pour y parvenir, nous entreprenons une exploration à partir de la base de l'innovation dans la littérature blanche (livres et périodiques publiés), et nous y joignons une enquête détaillée des fonctionnalités de sites web dans 160 bibliothèques aux États-Unis et au Canada.
Real-time look-up table-based color correction for still image stabilization of digital cameras without using frame memory

Abstract. Digital cameras usually decrease exposure time to capture motion-blur-free images. However, this operation will generate an under-exposed image with a low-budget complementary metal-oxide semiconductor image sensor (CIS). Conventional color correction algorithms can efficiently correct under-exposed images; however, they are generally not performed in real time and need at least one frame memory if they are implemented by hardware. The authors propose a real-time look-up table-based color correction method that corrects under-exposed images with hardware without using frame memory. The method utilizes histogram matching of two preview images, which are exposed for a long and short time, respectively, to construct an improved look-up table (ILUT) and then corrects the captured under-exposed image in real time. Because the ILUT is calculated in real time before processing the captured image, this method does not require frame memory to buffer image data, and therefore can greatly save the cost of CIS. This method not only supports single image capture, but also bracketing to capture three images at a time. The proposed method was implemented by hardware description language and verified by a field-programmable gate array with a 5 M CIS. Simulations show that the system can perform in real time with a low cost and can correct the color of under-exposed images well.
Cost/survivability analysis of multi-layer restoration strategies in broadband transport networks

Service survivability, i.e., continued service provision amidst network facility failures is an important feature of broadband transport networks. Due to the multitechnology (e.g., IP, ATM, SONET, WDM) and multiservice (e.g., low delay, low loss, etc.) aspects of the present day broadband transport networks, multi-layer restoration strategies that take advantage of the particular networking technology and the restoration objectives of the particular service will be very useful. However, with the potential advantages of multi-layer restoration are a variety of tradeoffs. Thus, a systematic methodology that can help analyze the cost-survivability performance tradeoffs is essential to a good network engineering and design. We propose a methodology that can be used to analyze the cost/survivability performance tradeoffs of single- and multi-layer restoration strategies. We also use the proposed methodology to analyze the performance of a multi-layer restoration strategy for ATM-SONET networks, and compare the performance of the proposed multi-layer restoration strategy with single-layer strategies such as the single-layer SONET 1:1 APS, ATM switch-based restoration strategies and the popularly used self-healing bi-directional line switched rings (BLSRs).
A machine learning approach to recognizing acronyms and their expansion

The paper addresses the problem of automatically recognizing acronyms and their corresponding expansions in free format text. To deal with the problem, we propose a machine learning approach. First, all likely acronyms are identified from text. Second, candidate expansions against likely acronyms are generated from their surrounding text. Last, we employ support vector machines (SVM) to select the genuine expansions for acronyms. Experimental results show that our approach outperforms baseline method of using patterns. Experimental results also show that the trained SVM model is generic and performs well on different domains.
Classification of heart sounds using time-frequency method and artificial neural networks

Digitally recorded pathological and non-pathological phonocardiograms (PCGs) were characterised by a time-frequency (TF) method known as the trimmed mean spectrogram (TMS). Features were extracted from the TMS containing the distribution of the systolic and diastolic signatures in the TF domain. Together with the acoustic intensities in systole and diastole, these features were used as inputs to the probabilistic neural networks (PNNs) for classification. A total of 56 PCGs were employed to train the PNNs including 21 non-pathological and 35 pathological PCGs. The PNNs were then tested with a different group of 18 non-pathological and 37 pathological PCGs. The system provided a sensitivity of 97.3% (36/37) and a specificity of 94.4% (17/18) in detecting pathological systolic murmurs. The results show that the system offers a promising methodology for classifying murmurs.
A prototype multimedia application for breast self examination training

This paper discusses the development of a prototype multimedia application for training women to perform Breast Self Examination (BSE) correctly. The paper presents the main differences between the BSE multimedia application and the other, traditional training approaches currently in use by the UK National Health Service (NHS) at the moment. The benefits of using multimedia in biomedical training and education are discussed. An overview of the applications structure and design is presented along with the evaluation criteria for the applications effectiveness.
Searching in Dual Worlds

State space search has been the most fundamental concept in artificial intelligence (AI). In this paper, we explore the concept of co-state for problem-solving using state space search, and discuss the related issue of searching in dual worlds, which consists of a surface world and a shadow world. We first point out how the proposed concepts emerge from various studies of recent AI research. In particular, we discuss tow sample applications in some detail, namely, expert system explanation and detective story analysis, both making use of co-states and dual-world searching. Expanding the ideas presented in these two examples, we provide several additional remarks on the proposed concepts. As part of our ongoing and future work, some considerations related to implementation are also briefly discussed.
Business Simulation Games: Current Usage Levels—An Update

A major survey involving more than 1,500 mail questionnaires was administered just over 10 years ago to determine the extent of business simulation game usage in academia and in business training programs. This article updates the earlier study through a mailing of 1,583 questionnaires to business school deans, business faculty, and training and development managers in industry. The findings from this study show that business simulation game usage in academia and in industry has continued to grow over the past 10 years with expectations for further growth.
Quality Analyses of Fine Structures Transfer in the Photorealistic Images

This work presents method of the quality analyses of the photorealistic images. Developed method utilizes proposed criteria of image definition quality for fine details. Presented method has the following significant property: the quality estimation is provided without test images or patterns. Algorithm for search and recognition of fine structures in the photorealistic images using the predefined criterion is considered.
Superresolution video reconstruction

Superresolution techniques attempt to reconstruct a higher resolution image (or video) from a low resolution input video sequence. The motivation here is that camera and scene motion lead temporal frames in the source video sequence contain similar but not identical information. In this paper, we present a novel warping synthesis combined with an error correction scheme to reconstruct an SR video from an input video sequence as an alternative to the conventional `sliding window' approach. Simulation results demonstrate that the proposed scheme reduces dramatically the computational load with little or no loss of reconstruction quality.