Miracle-dz/UniFAR-FTUs huggingface dataset:
Copositivity in Infinite Dimension

Many combinatorial optimization problems on finite graphs can be formulated as conic convex programs, e.g. the stable set problem, the maximum clique problem or the maximum cut problem. Especially NP-hard problems can be written as copositive programs. In this case the complexity is moved entirely into the copositivity constraint. Copositive programming is a quite new topic in optimization. It deals with optimization over the so-called copositive cone, a superset of the positive semidefinite cone, where the quadratic form x^T Ax has to be nonnegative for only the nonnegative vectors x. Its dual cone is the cone of completely positive matrices, which includes all matrices that can be decomposed as a sum of nonnegative symmetric vector-vector-products. The related optimization problems are linear programs with matrix variables and cone constraints. However, some optimization problems can be formulated as combinatorial problems on infinite graphs. For example, the kissing number problem can be formulated as a stable set problem on a circle. In this thesis we will discuss how the theory of copositive optimization can be lifted up to infinite dimension. For some special cases we will give applications in combinatorial optimization.
Data Reconciliation and Gross Error Detection for a Mineral Processing Plant

This paper discusses the implementation of data reconciliation and gross error detection in a mineral processing plant. The process is the heat interchange unit of the Alcoa Alumina Refinery, Kwinana. Simulation and modeling were done using Speedup together with the AspenPlus physical properties package. Two gross error detection methods were applied, measurement test (MT) and principal component analysis (PCA). PCA readily detected instrument errors which can be corrected to obtain more accurate and reliable process measurements.
Improving time travel experience by combining annotations

Since recorded audio material is played, navigating relevantly through it is a key expectation. This paper provides a formalism to introduce flexible navigation systems based on sets of annotations applying to the same audio object. It aims to build web interfaces to explore audio in time, robust for large data-sets and long files. Introducing the concept of weights applied to annotations, it specifies a parameterized version of the functionality next/previous and presents an effective implementation.
Design of testing data visualization from the robotic system for the YSoft SafeQ print management

Cieľom tejto prace je uprava testovacieho prostredia YSoft SafeQ tak, aby simulovalo produkcne prostredie. Ďalsim cieľom je navrh a implementacia vizualizacie výsledkov testovania z takto upraveneho testovacieho prostredia. Najskor su skumane aspekty pritomne pri realnom použivani YSoft SafeQ, ktore možu ovplyvňovať jeho výkon, ako aj nastroje, ktore umožňuju simulaciu týchto aspektov v testovacom prostredi. Zmeny v databaze, ktore su potrebne pre ukladanie dat z takehoto testovacieho prostredia su identifikovane a nasledne je navrhnuta a implementovana nova databazova schema. Posledna casť prace je venovana vizualizacii výsledkov testovania zo simulovaneho produkcneho prostredia s ohľadom na potreby spolocnosti Y Soft Corporation.
Three-Step Probabilistic Model for Korean Morphological Analysis

A morphological analyzer based on probabilistic model can learn easily various language phenomena and tagging principles used in morpheme-tagged corpus, so that it is very portable to various domains. In this paper, we propose a three-step probabilistic model for Korean morphological analysis which consists of original form restoring step, morpheme segmentation step and morpheme tagging step. The three-step method, which uses modular approach, reduces processing complexity compared with two-step probabilistic model. Processing in Jaso unit rather than syllable unit and using morpheme transition probahility for morpheme segmentation increase portahility for various tagging principles. Experiment on Sejong tagged corpus, both of written text corpus and spoken text corpus, was done to show the performance of the model and compare it with other methods.
Short-term Load Forecasting Model Based on Least Square Support Vector Machine

Support vector machine(SVM) is a novel machine learning method,which is powerful for solving the problems characterized by small samples,nonlinearity,high dimension,local minima,and other practical problems.The extension algorithm of the support vector machine-least squares support vector machine(LSSVM) is studied and applied to the time series forecasting of short-term load in power system.Compared with the predicting outcomings of the neural network model through some examples,the result shows that the forecast accuracy of LSSVM model is higher than that of neural network model,and verifies LSSVM model can apply effectively to short-term load forecasting.This provides a new resolution for short-term load forecasting.
Elements Of Data Compression

From the Publisher: Today's increased use of digital sound and video makes data compression crucial to computer technology because of its vast storage and transmission requirements. The question in many applications is now not whether to compress data, but what compression method should be applied. Most data compression books have been written for professionals and require a strong background in data compression techniques as well as an understanding of algorithms based on sophisticated mathematical models. This book is one of a handful of textbooks to present Data Compression for students in an academic environment. This is not a simple task since most of the widely used algorithms rely on sophisticated mathematical models. ELEMENTS OF DATA COMPRESSION addresses the needs of students who will use these techniques on a daily basis. The author accomplishes this through the use of elementary-level representative methods of text, audio, and video compression. Drozdek presents these methods with pseudocode, tables, diagrams, and many worked out examples, all the while employing commonly used techniques that build upon the mathematics students have been exposed to in earlier courses.
Shuffle Reduction Based Sparse Matrix-Vector Multiplication on Kepler GPU

GPU is the suitable equipment for accelerating computing-intensive applications in order to get the higher throughput for High Performance Computing (HPC). Sparse Matrix-Vector Multiplication (SpMV) is the core algorithm of HPC, so the SpMV’s throughput on GPU may affect the throughput on HPC platform. In the paper, we focus on the latency of reduction routine in SpMV included in CUSP, such as accessing shared memory and bank conflicting while multiple threads simultaneously accessing the same bank. We provide shuffle method to reduce the partial results instead of reducing in the shared memory in order to improve the throughput of SpMV on Kepler GPU. Experiments show that shuffle method can improve the throughput up to 9% of the original routine of SpMV in CUSP on average.
A new user interest shift modelling algorithm for websites with hierarchical classification structure

To identify Web users' interest shift on hierarchical structure websites,this paper present a new algorithm,which is used for adaptive website building and composed of two models based on exponential decay and Bayesian posterior probability respectively.Experiments based on a real Internet website show that the proposed algorithm can identify the user interests' shift promptly,as well as satisfying personalized information demands.The proposed algorithm can thus be widely implemented on various websites such as online News and virtual communities.
Uso de teléfonos inteligentes y aplicaciones para la autocapacitación y la telemedicina en médicos peruanos

Para determinar la frecuencia de uso de telefonos inteligentes y aplicaciones para la autocapacitacion y la telemedicina se realizo un estudio descriptivo, prospectivo y multicentrico, en el que preguntamos acerca del uso de la tecnologia de la informacion para la practica asistencial y la autocapacitacion en medicos peruanos. Se midio el uso de telefonos inteligentes, las aplicaciones y la telemedicina. Se encontro que, de los 1 013 medicos que manifestaron que usaban algun telefono inteligente, el 65 % (661) fueron hombres y la mediana de edad fue 35 anos (rango: 22-74 anos). El 48,5 % (460) usaban el telefono inteligente para la autocapacitacion. Medscape fue el mas usado para este fin (13 %); el 98 % usaba alguna aplicacion para su telefono inteligente; el 30 % de los que eran docentes usaba alguna aplicacion para esta actividad; las aplicaciones mas usadas fueron las que permitian el acceso a la web y/o busqueda de autocapacitacion (31 %) y al correo electronico (30 %). En cuanto al uso de la telemedicina, el 73 % habia enviado una imagen/video de un paciente a otro colega, el 29 % habia tenido una video-conferencia con otro medico para discutir algun caso de su paciente y el 30 % (269) habia usado su telefono inteligente para una comunicacion con algun paciente (sin contar las llamadas). Si bien la gran mayoria de medicos encuestados posee un telefono inteligente, no todos usan telemedicina o aplicaciones como parte habitual de su practica asistencial o para su autocapacitacion. Este puede ser un recurso importante a ser explotado para la mejora de la prestacion de la salud en Peru.
Content-Adaptive Non-Stationary Projector Resolution Enhancement

For any projection system, one goal will surely be to maximize the quality of projected imagery at a minimized hardware cost, which is considered a challenging engineering problem. Experience in applying different image filters and enhancements to projected video suggests quite clearly that the quality of a projected enhanced video is very much a function of the content of the video itself. That is, to first order, whether the video contains content which is moving as opposed to still plays an important role in the video quality, since the human visual system tolerates much more blur in moving imagery but at the same time is significantly sensitive to the flickering and aliasing caused by moving sharp textures. Furthermore, the spatial and statistical characteristics of text and non-text images are quite distinct. We would, therefore, assert that the text-like, moving and background pixels of a given video stream should be enhanced differently using class-dependent video enhancement filters to achieve maximum visual quality. In this thesis, we present a novel text-dependent content enhancement scheme, a novel motion-dependent content enhancement scheme and a novel content-adaptive resolution enhancement scheme based on a text-like / non-text-like classification and a pixel-wise moving / non-moving classification, with the actual enhancement obtained via class– dependent Wiener deconvolution filtering. Given an input image, the text and motion detection methods are used to generate binary masks to indicate the location of the text and moving regions in the video stream. Then enhanced images are obtained by applying a plurality of class-dependent enhancement filters, with text-like regions sharpened more than the background and moving regions sharpened less than the background. Later, one or more resulting enhanced images are combined into a composite output image based on the corresponding mask of different features. Finally, a higher resolution projected video stream is conducted by controlling one or more projectors to project the plurality of output frame streams in a rapid overlapping way. Experimental results on the test images and videos show that the proposed schemes all offer improved visual quality over projection without enhancement as well as compared to a recent state-of-the-art enhancement method. Particularly, the proposed content-adaptive resolution enhancement scheme increases the PSNR value by at least 18.2% and decreases MSE value by at least 25%.
On $L^p$-resolvent estimates and the density of eigenvalues for compact Riemannian manifolds

We address an interesting question raised by Dos Santos Ferreira, Kenig and Salo about regions ${\mathcal R}_g\subset {\mathbb C}$ for which there can be uniform $L^{\frac{2n}{n+2}}\to L^{\frac{2n}{n-2}}$ resolvent estimates for $\Delta_g+\zeta$, $\zeta \in {\mathcal R}_g$, where $\Delta_g$ is the Laplace-Beltrami operator with metric $g$ on a given compact boundaryless Riemannian manifold of dimension $n\ge3$. This is related to earlier work of Kenig, Ruiz and the third author for the Euclidean Laplacian, in which case the region is the entire complex plane minus any disc centered at the origin. Presently, we show that for the round metric on the sphere, $S^n$, the resolvent estimates in Ferreira et al, involving a much smaller region, are essentially optimal. We do this by establishing sharp bounds based on the distance from $\zeta$ to the spectrum of $\Delta_{S^n}$. In the other direction, we also show that the bounds in \cite{Kenig} can be sharpened logarithmically for manifolds with nonpositive curvature, and by powers in the case of the torus, ${\mathbb T}^n={\mathbb R}^n/{\mathbb Z}^n$, with the flat metric. The latter improves earlier bounds of Shen. Further improvements for the torus are obtained using recent techniques of the first author and his work with Guth based on the multilinear estimates of Bennett, Carbery and Tao. Our approach also allows us to give a natural necessary condition for favorable resolvent estimates that is based on a measurement of the density of the spectrum of $\sqrt{-\Delta_g}$, and, moreover, a necessary and sufficient condition based on natural improved spectral projection estimates for shrinking intervals.
Quantized Decentralized Adaptive Neural Network PI Tracking Control for Uncertain Interconnected Nonlinear Systems With Dynamic Uncertainties

In this paper, a decentralized adaptive neural network proportional–integral (PI) tracking control scheme is proposed for interconnected nonlinear systems with input quantization and dynamic uncertainties. This algorithm is underpinned by the use of the dynamic signal, graph theory, and function recombination to deal with the difficulties existing in the nontriangular form, unmodeled dynamics, and unknown interconnected terms. Recalling the backstepping method and neural network approximation technology, a new PI tracking controller characterized by simple structure and easy implementation is developed which ensures that all the closed-loop signals are uniformly ultimately bounded. The effectiveness of the obtained controller is exemplified via a numerical example and an application to an inverted pendulum.
High-NA lensless coherent imager as a building block for a synthetic aperture interferometry array

In digital holography, the field of view (FOV) and lateral resolution are limited by the pixel pitch and sensor dimensions, respectively. A large numerical aperture can be synthesized to increase the FOV and spatial resolution by coherently combining low resolution holograms obtained for different illumination and/or observation directions. This is known as Synthetic Aperture Interferometry (SAI) and in this work we describe the design, construction, calibration and testing of high numerical aperture compact coherent imagers (CI) which constitute the optical building block of a multi-sensor SAI array. The CIs consist of a photodetector array, a highly divergent reference beam close to it and an aperture that acts as a spatial filter to prevent aliasing of the digital holograms. We explore different optical designs to produce a highly divergent reference beam close to the sensor, including bulk optics, micro-optics, and ion beam milled optical fibres. An optimization approach is used to characterize the reference wavefront for accurate digital reconstructions of the scattered field first at the aperture plane and then at the object plane. The performance of a compact CI is demonstrated by reconstructing an object 76 mm wide at 80 mm from the sensor, which corresponds to a numerical aperture NA>0.5.
Effect of unitary transformation on Bayesian information criterion for source numbering in array processing

An approach based on unitary transformation for the problem of estimating the number of signals is proposed in this study. Among the information theoretic criteria, the authors focus on the conventional Bayesian information criterion (BIC) in the presence of a uniform linear array. The sample covariance matrix of this array is transformed into the real symmetric one by using a unitary transformation. This real symmetric matrix has real eigenvalues and eigenvectors. Therefore its eigenvalue decomposition needs only real computations. Since the eigenvalues of this real symmetric matrix are equal to the eigenvalues of the sample covariance matrix, by replacing them in BIC formula, the term log-likelihood of BIC does not change but it is obtained by fewer computations. Also by considering the resulting real eigenvectors instead of the complex eigenvectors as a part of free parameters in the parameter vector of the model, they have a reduction in the number of degrees of freedom in the penalty term of BIC. This reduction makes their proposed method outperform BIC. They refer to this approach as unitary BIC. A series of simulations are included to demonstrate the usefulness of this approach.
Review of the Modeling and Control of Swarm Behaviors

An introduction in the field of modeling and analysis of swarm behaviors is provided with a focus on the various methods that have been put forward by researchers.The work which has been done in the field is reviewed.The various methods are described and compared.Something that is missing in the current research and the factors that must be considered in designing an engineering swarm system are pointed out.At last,the directions of further research are proposed.
A Distributed Usage Control System Based on Trusted Computing

As the development of distributed environment such as internet,controlling usage of data after it has been released to a different control domain from its provider's becomes an important security issue.Recently proposed usage control concept and model are suitable for describing this issue but the area of usage control enforcement mechanism has not been fully explored yet.This paper proposes a novel distributed usage control system based on trusted computing technology,which could implement and support all three features of usage control model:abundant policy decision elements,control continuity and mutability of attributes.Experiments show the system enjoys good performance and can be used as an effective solution for usage control enforcement in distributed computing environments.
The pattern of growth in viable f(R) cosmologies

We study the evolution of linear perturbations in metric f(R) models of gravity and identify a potentially observable characteristic scale-dependent pattern in the behavior of cosmological struc- tures. While at the background level viable f(R) models must closely mimicCDM, the differences in their prediction for the growth of large scale structures can be sufficiently large to be seen with future weak lensing surveys. While working in the Jordan frame, we perform an analytical study of the growth of structures in the Einstein frame, demonstrating the equivalence of the dynamics in the two frames. We also provide a physical interpretation of the results in terms of the dynamics of an effective dark energy fluid with a non-zero shear. We find that the growth of structure in f(R) is enhanced, but that there are no small scale instabilities associated with the additional attractive "fifth force". We then briefly consider some recently proposed observational tests of modified gravity and their utility for detecting the f(R) pattern of structure growth.
A keypoint based copy-move forgery detection and localization in digital images / Somayeh Sadeghi

Due to the fast development of powerful image processing tools and the importance of image integrity, digital image forgery has become a very important topic for certain organizations. Copy-move forgery is one of the most commonly used types of digital image forgery, where one part of the image is copied and placed elsewhere in the same image. Because of the existence of various digital environments, a copy-move forgery detector should be robust against pre- and post-processing operations, such as scaling, rotation, JPEG compression and noise. A copy-move forgery detector should be able to detect forgery in a reasonable amount of time. In this research, an image authentication scheme with the capability of copy-move forgery localization is proposed, based on the scale invariant feature transform (SIFT). The importance of the proposed method is its ability to authenticate digital images and accurately locate copied and pasted areas. The proposed algorithm starts by extracting local image features, which are known as keypoints, using SIFT, followed by searching for similar keypoints by clustering extracted descriptors from the image. Finally, matched keypoints, which are duplicated regions in the image, are connected to each other to illustrate which part of the image has been tampered with. Several experiments are performed to validate the effectiveness and robustness of the proposed algorithm against different attacks, such as pre-processing attacks. The experimental results illustrate that the proposed algorithm is robust against several geometric changes, such as JPEG compression, rotation, noise and scaling. Furthermore, the detection rate of the algorithm is improved by utilizing the proposed clustering procedure. The true and false positive rates achieved by the proposed algorithm outperform several current detection algorithms.
Analysis on XEN Virtualization Machine

The great improvement of the hardware computing capability has stimulated people's enthusiasm to study virtual machine monitor again. XEN is an open-source virtualization machine monitor, whose future is widespread optimistic by the industry. It has a good system architecture and surprising performance. Companying With the application of the virtual machine, there are some new security challenges to be proposed. The hardware virtualization technology was interpreted based on Intel's VT-x technology and the essences of XEN from the prospects of processor, memory and device managements were analyzed. Based on the above analysis, the security of XEN was discussed and some solution schema against security flaws was proposed.